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1

Sanyal Temperature Classification | Open Energy Information  

Open Energy Info (EERE)

Sanyal Temperature Classification Sanyal Temperature Classification Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Print PDF Sanyal Temperature Classification The information for this page was taken directly from Subir Sanyal's paper, Classification of Geothermal Systems: A Possible Scheme (Stanford, February 2, 2005) At the request of the United States Department of Energy, the author was asked by the Geothermal Energy Association (Washington, D.C.) to prepare a white paper on the subject (in connection with a new national assessment of geothermal resources). This paper offers a possible scheme in which geothermal resources are classified into seven categories based on temperature. This scheme is based not only on temperature but also according to a set of additional attributes important for practical utilization of geothermal

2

Category:Sanyal Temperature Classification | Open Energy Information  

Open Energy Info (EERE)

source source History View New Pages Recent Changes All Special Pages Semantic Search/Querying Get Involved Help Apps Datasets Community Login | Sign Up Search Category Edit History Facebook icon Twitter icon » Category:Sanyal Temperature Classification Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Category:Sanyal Temperature Classification Geothermalpower.jpg Looking for the Sanyal Temperature Classification page? For detailed information on Sanyal Temperature Classification, click here. Pages in category "Sanyal Temperature Classification" The following 7 pages are in this category, out of 7 total. E Extremely Low Temperature H High Temperature L Low Temperature M Moderate Temperature S Steam Field U Ultra High Temperature V Very Low Temperature Retrieved from

3

Property:SanyalTempWellhead | Open Energy Information  

Open Energy Info (EERE)

SanyalTempWellhead SanyalTempWellhead Jump to: navigation, search Property Name SanyalTempWellhead Property Type Page Description see Sanyal_Temperature_Classification Allows Values Extremely Low Temperature;Very Low Temperature;Low Temperature;Moderate Temperature;High Temperature;Ultra High Temperature;Steam Field Pages using the property "SanyalTempWellhead" Showing 25 pages using this property. A Amedee Geothermal Area + Extremely Low Temperature + B Beowawe Hot Springs Geothermal Area + Moderate Temperature + Blue Mountain Geothermal Area + Moderate Temperature + Brady Hot Springs Geothermal Area + Low Temperature + C Chena Geothermal Area + Extremely Low Temperature + Coso Geothermal Area + High Temperature + D Desert Peak Geothermal Area + Moderate Temperature +

4

Property:SanyalTempReservoir | Open Energy Information  

Open Energy Info (EERE)

SanyalTempReservoir SanyalTempReservoir Jump to: navigation, search Property Name SanyalTempReservoir Property Type Page Description see Sanyal_Temperature_Classification Allows Values Extremely Low Temperature;Very Low Temperature;Low Temperature;Moderate Temperature;High Temperature;Ultra High Temperature;Steam Field Pages using the property "SanyalTempReservoir" Showing 16 pages using this property. A Amedee Geothermal Area + Very Low Temperature + B Beowawe Hot Springs Geothermal Area + Moderate Temperature + Blue Mountain Geothermal Area + High Temperature + C Chena Geothermal Area + Very Low Temperature + D Desert Peak Geothermal Area + Moderate Temperature + K Kilauea East Rift Geothermal Area + High Temperature + L Lightning Dock Geothermal Area + High Temperature +

5

Gas Geothermometry | Open Energy Information  

Open Energy Info (EERE)

Gas Geothermometry Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Technique: Gas Geothermometry Details Activities (0) Areas (0) Regions (0) NEPA(0)...

6

Geothermometry At Socorro Mountain Area (Armstrong, Et Al., 1995) | Open  

Open Energy Info (EERE)

Geothermometry At Socorro Mountain Area (Armstrong, Et Al., 1995) Geothermometry At Socorro Mountain Area (Armstrong, Et Al., 1995) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Socorro Mountain Area (Armstrong, Et Al., 1995) Exploration Activity Details Location Socorro Mountain Area Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown Notes Corresponding Socorro caldera Carboniferous rocks were studied in the field in 1988-1992-Renault later completed geochemistry and silica-crystallite geothermometry, Armstrong petrographic analysis and cathodoluminescence, Oscarson SEM studies, and John Repetski (USGS, Reston, Virgina) conodont stratigraphy and color and textural alteration as guides to the carbonate rocks' thermal history. The carbonate-rock classification used in this

7

Geothermometry | Open Energy Information  

Open Energy Info (EERE)

Geothermometry Geothermometry Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Technique: Geothermometry Details Activities (65) Areas (48) Regions (5) NEPA(0) Exploration Technique Information Exploration Group: Geochemical Techniques Exploration Sub Group: Geochemical Data Analysis Parent Exploration Technique: Geochemical Data Analysis Information Provided by Technique Lithology: Stratigraphic/Structural: Hydrological: Thermal: used to estimate reservoir temperatures Cost Information Low-End Estimate (USD): 30.003,000 centUSD 0.03 kUSD 3.0e-5 MUSD 3.0e-8 TUSD / sample Median Estimate (USD): 30.003,000 centUSD 0.03 kUSD 3.0e-5 MUSD 3.0e-8 TUSD / sample High-End Estimate (USD): 30.003,000 centUSD 0.03 kUSD 3.0e-5 MUSD 3.0e-8 TUSD / sample Dictionary.png Geothermometry:

8

Geothermometry At Fort Bliss Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

Geothermometry At Fort Bliss Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Fort Bliss Area (DOE GTP)...

9

Geothermometry At The Needles Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

Geothermometry At The Needles Area (DOE GTP) Exploration Activity Details Location The Needles Area Exploration Technique Geothermometry Activity Date Usefulness not indicated...

10

Geothermometry At New River Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

Geothermometry At New River Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At New River Area (DOE GTP) Exploration...

11

Category:Geothermometry | Open Energy Information  

Open Energy Info (EERE)

Category Edit History Facebook icon Twitter icon Category:Geothermometry Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Geothermalpower.jpg Looking for the...

12

Definition: Geothermometry | Open Energy Information  

Open Energy Info (EERE)

Definition Definition Edit with form History Facebook icon Twitter icon » Definition: Geothermometry Jump to: navigation, search Dictionary.png Geothermometry Chemical geothermometers are used to estimate reservoir temperatures for most of the systems. The geothermometers are based on temperature- dependent, water-rock reactions which control the chemical and isotopic composition of the thermal water. This method is applicable only to hot-water systems because the common chemical constituents of thermal water (SiO2, Na, K, Ca, Mg, Cl, HCO3, and CO3) are soluble in liquid water but lack significant solubility in steam.[1] View on Wikipedia Wikipedia Definition Geothermobarometry is the science of measuring the previous pressure and temperature history of a metamorphic or intrusive igneous rocks.

13

Geothermometry At Akutan Fumaroles Area (Kolker, Et Al., 2010) | Open  

Open Energy Info (EERE)

Akutan Fumaroles Area (Kolker, Et Al., 2010) Akutan Fumaroles Area (Kolker, Et Al., 2010) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Akutan Fumaroles Area (Kolker, Et Al., 2010) Exploration Activity Details Location Akutan Fumaroles Area Exploration Technique Geothermometry Activity Date Usefulness useful DOE-funding Unknown Notes The chemistry of the hot springs strongly suggests the existence of a neutral chloride reservoir with economically developable temperature. The fluid geothermometry tells a consistent story, with cation geothermometry detecting a >210degrees C reservoir temperature, probably near the fumarole, and silica geothermometry and presence of sinter suggesting that 160 to 180degrees C exists close to hot spring B. References

14

Geothermometry At Honokowai Area (Thomas, 1986) | Open Energy Information  

Open Energy Info (EERE)

Geothermometry At Honokowai Area (Thomas, 1986) Geothermometry At Honokowai Area (Thomas, 1986) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Honokowai Area (Thomas, 1986) Exploration Activity Details Location Honokowai Area Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown Notes Temperature and groundwater chemistry analyses were performed on three wells along the alluvial fan above Honokowai. Water temperatures were approximately 20degrees C and normal basal aquifer water chemistry was observed (Table 4). References Donald M. Thomas (1 January 1986) Geothermal Resources Assessment In Hawaii Retrieved from "http://en.openei.org/w/index.php?title=Geothermometry_At_Honokowai_Area_(Thomas,_1986)&oldid=387033"

15

Geothermometry At Salt Wells Area (Shevenell, Et Al., 2008) ...  

Open Energy Info (EERE)

search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Salt Wells Area (Shevenell, Et Al., 2008) Exploration Activity Details Location Salt Wells Area...

16

Geothermometry At Rhodes Marsh Area (Coolbaugh, Et Al., 2006...  

Open Energy Info (EERE)

At Rhodes Marsh Area (Coolbaugh, Et Al., 2006) Exploration Activity Details Location Rhodes Marsh Area Exploration Technique Geothermometry Activity Date Usefulness useful...

17

Geothermometry At Coso Geothermal Area (1978) | Open Energy Information  

Open Energy Info (EERE)

Geothermometry At Coso Geothermal Area (1978) Geothermometry At Coso Geothermal Area (1978) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Coso Geothermal Area (1978) Exploration Activity Details Location Coso Geothermal Area Exploration Technique Geothermometry Activity Date 1978 Usefulness useful DOE-funding Unknown Exploration Basis Determine fluid origin in two exploratory wells Notes Collected water from original coso hot springs well (1967) and CGEH No. 1. and completed chemical analysis to determine fluid origin. The surface expression of fumarole and acid sulfate pools and shallow steam wells gives a false indication of an extensive vapor dominated system because upward convecting, boiling alkaline-chloride waters do not reach the surface.

18

Geothermometry At Haleakala Volcano Area (Thomas, 1986) | Open Energy  

Open Energy Info (EERE)

Geothermometry At Haleakala Volcano Area (Thomas, 1986) Geothermometry At Haleakala Volcano Area (Thomas, 1986) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Haleakala Volcano Area (Thomas, 1986) Exploration Activity Details Location Haleakala Volcano Area Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown Notes The field survey program on the northwest rift zone consisted of soil mercury and radon emanometry surveys, groundwater temperature and chemistry studies, Schlumberger resistivity soundings and self-potential profiles. Geophysical and geochemical surveys along this rift (southwest) were limited by difficult field conditions and access limitations. The geophysical program consisted of one Schlumberger sounding, one

19

Geothermometry At Nevada Test And Training Range Area (Sabin...  

Open Energy Info (EERE)

Nevada Test And Training Range Area (Sabin, Et Al., 2004) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Nevada Test And...

20

Geothermometry At Fish Lake Valley Area (DOE GTP) | Open Energy...  

Open Energy Info (EERE)

Fish Lake Valley Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Fish Lake Valley Area (DOE GTP) Exploration...

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Geothermometry At Alum Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

Alum Geothermal Area (DOE GTP) Exploration Activity Details Location Alum Geothermal Area Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding...

22

Geothermometry At Silver Peak Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Silver Peak Area (DOE GTP) Exploration Activity Details Location...

23

Geochemistry And Geothermometry Of Spring Water From The Blackfoot...  

Open Energy Info (EERE)

And Geothermometry Of Spring Water From The Blackfoot Reservoir Region, Southeastern Idaho Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Journal Article:...

24

Geothermometry At Central Nevada Seismic Zone Region (Shevenell & De  

Open Energy Info (EERE)

Region (Shevenell & De Region (Shevenell & De Rocher, 2005) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Central Nevada Seismic Zone Region (Shevenell & De Rocher, 2005) Exploration Activity Details Location Central Nevada Seismic Zone Geothermal Region Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown References Lisa Shevenell, Ted De Rocher (2005) Evaluation Of Chemical Geothermometers For Calculating Reservoir Temperatures At Nevada Geothermal Power Plants Retrieved from "http://en.openei.org/w/index.php?title=Geothermometry_At_Central_Nevada_Seismic_Zone_Region_(Shevenell_%26_De_Rocher,_2005)&oldid=401374" Category: Exploration Activities What links here

25

Geothermometry At Lualualei Valley Area (Thomas, 1986) | Open Energy  

Open Energy Info (EERE)

Geothermometry At Lualualei Valley Area (Thomas, 1986) Geothermometry At Lualualei Valley Area (Thomas, 1986) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Lualualei Valley Area (Thomas, 1986) Exploration Activity Details Location Lualualei Valley Area Exploration Technique Geothermometry Activity Date Usefulness useful DOE-funding Unknown Notes Yhe extensive set of groundwater chemical data compiled for the wells in the valley (Table 1) showed that two of the primary indicators that have been commonly used in Hawaii for identifying geothermal potential (i.e. silica concentration and chloride to magnesium ion ratios) were anomalous in the groundwater of this survey area (Cox and Thomas, 1979). Several wells located on the caldera boundaries were found to have both

26

Geothermometry At Kawaihae Area (Thomas, 1986) | Open Energy Information  

Open Energy Info (EERE)

Geothermometry At Kawaihae Area (Thomas, 1986) Geothermometry At Kawaihae Area (Thomas, 1986) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Kawaihae Area (Thomas, 1986) Exploration Activity Details Location Kawaihae Area Exploration Technique Geothermometry Activity Date Usefulness useful DOE-funding Unknown Notes Groundwater chemical data are limited due to the small number of wells near Kawaihae; however, the data that are available strongly substantiate the presence of a thermal resource. A measured water temperature of 31 degrees C in one well is clearly above normal ambient temperatures, and the chloride/magnesium ion ratio in the same well is elevated substantially above the normal range (Table 8). Both of these data provide strong evidence that at least a low-level thermal anomaly is present in the area.

27

Geothermometry At Lassen Volcanic National Park Area (Janik & Mclaren,  

Open Energy Info (EERE)

Geothermometry At Lassen Volcanic National Park Area (Janik & Mclaren, Geothermometry At Lassen Volcanic National Park Area (Janik & Mclaren, 2010) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Lassen Volcanic National Park Area (Janik & Mclaren, 2010) Exploration Activity Details Location Lassen Volcanic National Park Area Exploration Technique Geothermometry Activity Date Usefulness useful DOE-funding Unknown Notes Analyses of eight well samples taken consecutively during the flow test showed an inverse correlation between NH3 and Cl_ concentrations. The last sample taken had a pH of 8.35 and contained 2100 ppm Cl_ and 0.55 ppm NH3. Ratios of Na+/K+ and Na+/Cl_ remained nearly constant throughout the flow test. Cation geothermometers (with inherent uncertainties of at least

28

Geothermometry At Mauna Loa Northeast Rift Area (Thomas, 1986) | Open  

Open Energy Info (EERE)

Geothermometry At Mauna Loa Northeast Rift Area (Thomas, 1986) Geothermometry At Mauna Loa Northeast Rift Area (Thomas, 1986) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Mauna Loa Northeast Rift Area (Thomas, 1986) Exploration Activity Details Location Mauna Loa Northeast Rift Area Exploration Technique Geothermometry Activity Date Usefulness useful DOE-funding Unknown Notes A reexamination of all groundwater sources in the Keaau area was undertaken in an effort to confirm the chemical and temperature anomalies that formed the primary basis on which the Keaau area was identified during the preliminary assessment survey. The data generated by this survey (Table 9) determined that all of the anomalous data present in the earlier data base were spurious and that the groundwater chemistry and temperatures in this

29

Geothermometry At Coso Geothermal Area (1980) | Open Energy Information  

Open Energy Info (EERE)

Geothermometry At Coso Geothermal Area (1980) Geothermometry At Coso Geothermal Area (1980) Exploration Activity Details Location Coso Geothermal Area Exploration Technique Geothermometry Activity Date 1980 Usefulness useful DOE-funding Unknown Exploration Basis Fluid temperature of feed water Notes Cation and sulfate isotope geothermometers indicate that the reservoir feeding water to the Coso Hot Spring well has a temperature of about 240 -250 C, and the reservoir feeding the CGEH well has a temperature of about 205 C. The variation in the chemical composition of water from the two wells suggests a model in which water-rock chemical equilibrium is maintained as a convecting solution cools from about 245-205 C by conductive heat loss. References Fournier, R.O.; Thompson, J.M.; Austin, C.F. (10 May 1980)

30

Geochemistry And Geothermometry Of Spring Water From The Blackfoot  

Open Energy Info (EERE)

Geothermometry Of Spring Water From The Blackfoot Geothermometry Of Spring Water From The Blackfoot Reservoir Region, Southeastern Idaho Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Journal Article: Geochemistry And Geothermometry Of Spring Water From The Blackfoot Reservoir Region, Southeastern Idaho Details Activities (3) Areas (1) Regions (0) Abstract: The Blackfoot Reservoir region in southeastern Idaho is recognized as a potential geothermal area because of the presence of several young rhyolite domes (50,000 years old), Quaternary basalt flows, and warm springs. North- to northwest-trending high-angle normal faults of Tertiary to Holocene age appear to be the dominant structural control of spring activity. Surface spring-water temperatures average 14°C except for a group of springs west of the Reservoir Mountains which average 33°C.

31

Geothermometry At Raft River Geothermal Area (1980) | Open Energy  

Open Energy Info (EERE)

Geothermometry At Raft River Geothermal Area (1980) Geothermometry At Raft River Geothermal Area (1980) Exploration Activity Details Location Raft River Geothermal Area Exploration Technique Geothermometry Activity Date 1980 Usefulness not indicated DOE-funding Unknown Notes Geothermometer temperatures of shallow samples suggest significant re-equilibration at temperatures below those found in the deep wells. Silica geothermometer temperatures of water samples from the deep wells are in reasonable agreement with measured temperatures, whereas Na-K-Ca temperatures are significantly higher than measured temperatures. The chemical characteristics of the water, as indicated by chloride concentration, are extremely variable in shallow and deep samples. Chloride concentrations of the deep samples range from 580 to 2200 mg/kg.

32

Geothermometry At Lahaina-Kaanapali Area (Thomas, 1986) | Open Energy  

Open Energy Info (EERE)

Lahaina-Kaanapali Area (Thomas, 1986) Lahaina-Kaanapali Area (Thomas, 1986) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Lahaina-Kaanapali Area (Thomas, 1986) Exploration Activity Details Location Lahaina-Kaanapali Area Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown Notes Groundwater temperature and chemistry surveys were similarly unable to identify any detectable thermal influence on the basal groundwaters. Silica concentrations and water temperatures (Table 4) were within the normal range expected for basal groundwaters receiving a limited amount of irrigation return water; chloride/magnesium ratios ranged downward from normal seawater values. References Donald M. Thomas (1 January 1986) Geothermal Resources Assessment In

33

Sodium-Lithium Ratio In Water Applied To Geothermometry Of Geothermal...  

Open Energy Info (EERE)

Sign Up Search Page Edit with form History Facebook icon Twitter icon Sodium-Lithium Ratio In Water Applied To Geothermometry Of Geothermal Reservoirs Jump to: navigation,...

34

Geothermometry At Buffalo Valley Hot Springs Area (Laney, 2005) | Open  

Open Energy Info (EERE)

Buffalo Valley Hot Springs Area (Laney, 2005) Buffalo Valley Hot Springs Area (Laney, 2005) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Buffalo Valley Hot Springs Area (Laney, 2005) Exploration Activity Details Location Buffalo Valley Hot Springs Area Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown Notes Geochemical Sampling of Thermal and Non-thermal Waters in Nevada, Shevenell and Garside. The objective of this project is to obtain geochemical data from springs (and some wells) for which data are not publicly available, or for which the analyses are incomplete, poor, or nonexistent. With these data, geothermometers are being calculated and a preliminary assessment of the geothermal potential and ranking of the sampled areas is being

35

Geothermometry At Hot Springs Ranch Area (Szybinski, 2006) | Open Energy  

Open Energy Info (EERE)

Hot Springs Ranch Area (Szybinski, 2006) Hot Springs Ranch Area (Szybinski, 2006) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Hot Springs Ranch Area (Szybinski, 2006) Exploration Activity Details Location Hot Springs Ranch Area Exploration Technique Geothermometry Activity Date Usefulness useful DOE-funding Unknown Notes The brine from the drill holes, hot springs, seepages, and irrigation wells was sampled, as well as water from two nearby creeks, (total of 13 samples) and sent for analysis to Thermochem Inc. For sample locations refer to Figure 35; the geochemical data are presented in Appendix C. Geochemical results indicate the presence of two distinct waters in this group of samples (Tom Powell of Thermochem Inc., personal communication, 2005).

36

Geothermometry At Socorro Mountain Area (Owens, Et Al., 2005) | Open Energy  

Open Energy Info (EERE)

Geothermometry At Socorro Mountain Area (Owens, Et Al., 2005) Geothermometry At Socorro Mountain Area (Owens, Et Al., 2005) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Socorro Mountain Area (Owens, Et Al., 2005) Exploration Activity Details Location Socorro Mountain Area Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown Notes Pre-existing evidence includes heat gradients of upwards of 490mW/m2 from thermal-gradient wells, tepid spring waters (32oC) and silica geochemistry indicating thermal waters with a minimum of 82oC at depth References Lara Owens, Richard Baars, David Norman, Harold Tobin (2005) New Methods In Exploration At The Socorro Peak Kgra- A Gred Iii Project Retrieved from "http://en.openei.org/w/index.php?title=Geothermometry_At_Socorro_Mountain_Area_(Owens,_Et_Al.,_2005)&oldid=389518

37

Geothermometry At Columbus Salt Marsh Area (Shevenell, Et Al., 2008) | Open  

Open Energy Info (EERE)

Geothermometry At Columbus Salt Marsh Area (Shevenell, Et Al., 2008) Geothermometry At Columbus Salt Marsh Area (Shevenell, Et Al., 2008) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Columbus Salt Marsh Area (Shevenell, Et Al., 2008) Exploration Activity Details Location Columbus Salt Marsh Area Exploration Technique Geothermometry Activity Date Usefulness useful DOE-funding Unknown Notes Borate crusts that were partially mined during the 1800s were identified and mapped at Rhodes, Teels, and Columbus Marshes (playas), all in western Nevada (Figure 1). Subsequent field verification and chemical analyses of well, spring and groundwater samples indicated the presence of hidden subsurface geothermal reservoirs. Cation and quartz geothermometry indicate subsurface reservoir temperatures between 118°C and 162°C at all three

38

Geothermometry At Walker-Lane Transitional Zone Region (Shevenell & De  

Open Energy Info (EERE)

Shevenell & De Shevenell & De Rocher, 2005) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Walker-Lane Transitional Zone Region (Shevenell & De Rocher, 2005) Exploration Activity Details Location Walker-Lane Transition Zone Geothermal Region Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown References Lisa Shevenell, Ted De Rocher (2005) Evaluation Of Chemical Geothermometers For Calculating Reservoir Temperatures At Nevada Geothermal Power Plants Retrieved from "http://en.openei.org/w/index.php?title=Geothermometry_At_Walker-Lane_Transitional_Zone_Region_(Shevenell_%26_De_Rocher,_2005)&oldid=399607" Category: Exploration Activities What links here Related changes

39

Geothermometry At Rhodes Marsh Area (Shevenell, Et Al., 2008) | Open Energy  

Open Energy Info (EERE)

Geothermometry At Rhodes Marsh Area (Shevenell, Et Geothermometry At Rhodes Marsh Area (Shevenell, Et Al., 2008) Exploration Activity Details Location Rhodes Marsh Area Exploration Technique Geothermometry Activity Date Usefulness useful DOE-funding Unknown Notes Borate crusts that were partially mined during the 1800s were identified and mapped at Rhodes, Teels, and Columbus Marshes (playas), all in western Nevada (Figure 1). Subsequent field verification and chemical analyses of well, spring and groundwater samples indicated the presence of hidden subsurface geothermal reservoirs. Cation and quartz geothermometry indicate subsurface reservoir temperatures between 118°C and 162°C at all three areas based on results from waters sampled proximal to borate crusts. References Lisa Shevenell, Mark Coolbaugh, Chris Sladek, Rick Zehner, Chris

40

Geothermometry At Reese River Area (Henkle & Ronne, 2008) | Open Energy  

Open Energy Info (EERE)

Geothermometry At Reese River Area (Henkle & Ronne, 2008) Geothermometry At Reese River Area (Henkle & Ronne, 2008) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Reese River Area (Henkle & Ronne, 2008) Exploration Activity Details Location Reese River Area Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown Notes Four formation water samples were collected from well 56-4, during an airlift test which took place between November 11 and November 14, 2007. One sample was taken from the Steiner Well which was the source for drilling water for the drilling of 56-4 and for the short injection test. The samples were analyzed by Thermochem for chemical constituents and by Rafter Lab at GNS for isotope analysis. References

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Geothermometry At Fish Lake Valley Area (Deymonaz, Et Al., 2008) | Open  

Open Energy Info (EERE)

Geothermometry At Fish Lake Valley Area (Deymonaz, Et Al., 2008) Geothermometry At Fish Lake Valley Area (Deymonaz, Et Al., 2008) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Fish Lake Valley Area (Deymonaz, Et Al., 2008) Exploration Activity Details Location Fish Lake Valley Area Exploration Technique Geothermometry Activity Date Usefulness useful DOE-funding Unknown Notes There are no thermal springs within the Emigrant prospect area, but unambiguously indigenous hotwater samples were collected from boreholes 211 (see above) and 112 (Fig. 3). These samples were analyzed for major and selected minor chemical components (Table 1; Pilkington, 1984). Hot water at 96degrees C from borehole 211 was collected by airlifting from a depth of 123 m (water level) at a rate of 240 liters per minute. The

42

Geothermometry At Salt Wells Area (Henkle, Et Al., 2005) | Open Energy  

Open Energy Info (EERE)

Geothermometry At Salt Wells Area (Henkle, Et Al., 2005) Geothermometry At Salt Wells Area (Henkle, Et Al., 2005) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Salt Wells Area (Henkle, Et Al., 2005) Exploration Activity Details Location Salt Wells Geothermal Area Exploration Technique Geothermometry Activity Date 2004 - 2005 Usefulness useful DOE-funding Unknown Exploration Basis Adsorbed mercury soil geochemical surveys and radiometric geophysical surveys were carried out in conjunction with geologic mapping to test the application of these ground-based techniques to geothermal exploration at three prospects in Nevada by Henkle Jr. et al. in 2005. Mercury soil vapor surveys were not widely used in geothermal exploration in the western US at the time, although the association of mercury vapors with geothermal

43

Geothermometry At Upper Hot Creek Ranch Area (Benoit & Blackwell, 2006) |  

Open Energy Info (EERE)

Geothermometry At Upper Hot Creek Ranch Area (Benoit & Blackwell, 2006) Geothermometry At Upper Hot Creek Ranch Area (Benoit & Blackwell, 2006) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Upper Hot Creek Ranch Area (Benoit & Blackwell, 2006) Exploration Activity Details Location Upper Hot Creek Ranch Area Exploration Technique Geothermometry Activity Date Usefulness useful DOE-funding Unknown Notes Ten water samples were collected for chemical analysis and interpretation. Analyses of three samples of the UHCR thermal give predicted subsurface temperatures ranging from 317 to 334 oF from the Na-K-Ca, silica (quartz), and Na-Li geothermometers. The fact that all three thermometers closely agree gives the predictions added credibility. References Dick Benoit, David Blackwell (2006) Exploration Of The Upper Hot

44

Geothermometry At Northern Basin & Range Region (Laney, 2005) | Open Energy  

Open Energy Info (EERE)

Geothermometry At Northern Basin & Range Region (Laney, 2005) Geothermometry At Northern Basin & Range Region (Laney, 2005) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Northern Basin & Range Region (Laney, 2005) Exploration Activity Details Location Northern Basin and Range Geothermal Region Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown Notes Geochemical Sampling of Thermal and Non-thermal Waters in Nevada, Shevenell and Garside. The objective of this project is to obtain geochemical data from springs (and some wells) for which data are not publicly available, or for which the analyses are incomplete, poor, or nonexistent. With these data, geothermometers are being calculated and a preliminary assessment of

45

Geothermometry At U.S. Midwest Region (Vugrinovich, 1987) | Open Energy  

Open Energy Info (EERE)

Geothermometry At U.S. Midwest Region (Vugrinovich, 1987) Geothermometry At U.S. Midwest Region (Vugrinovich, 1987) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At U.S. Midwest Region (Vugrinovich, 1987) Exploration Activity Details Location U.S. Midwest Region Exploration Technique Geothermometry Activity Date Usefulness useful DOE-funding Unknown Notes Michigan "The silica heat flow estimator does provide estimates of surface heat flow which appear to be in good agreement with conventional estimates, but which are not entirely free from disturbances caused by groundwater movements. The technique should be more widely applied to areas where conventional heat flow measurements are lacking." References Raymond Vugrinovich (1987) Regional Heat Flow Variations In The

46

Geothermometry At Central Nevada Seismic Zone Region (Laney, 2005) | Open  

Open Energy Info (EERE)

Region Region (Laney, 2005) Exploration Activity Details Location Central Nevada Seismic Zone Geothermal Region Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown Notes Geochemical Sampling of Thermal and Non-thermal Waters in Nevada, Shevenell and Garside. The objective of this project is to obtain geochemical data from springs (and some wells) for which data are not publicly available, or for which the analyses are incomplete, poor, or nonexistent. With these data, geothermometers are being calculated and a preliminary assessment of the geothermal potential and ranking of the sampled areas is being conducted using the new geochemical data. Objectives changed slightly in 2004. Samples are now being collected at sites identified by other

47

Geothermometry At Teels Marsh Area (Shevenell, Et Al., 2008) | Open Energy  

Open Energy Info (EERE)

Shevenell, Et Al., 2008) Shevenell, Et Al., 2008) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Teels Marsh Area (Shevenell, Et Al., 2008) Exploration Activity Details Location Teels Marsh Area Exploration Technique Geothermometry Activity Date Usefulness useful DOE-funding Unknown Notes Borate crusts that were partially mined during the 1800s were identified and mapped at Rhodes, Teels, and Columbus Marshes (playas), all in western Nevada (Figure 1). Subsequent field verification and chemical analyses of well, spring and groundwater samples indicated the presence of hidden subsurface geothermal reservoirs. Cation and quartz geothermometry indicate subsurface reservoir temperatures between 118°C and 162°C at all three areas based on results from waters sampled proximal to borate crusts.

48

Geothermometry At Salt Wells Area (Edmiston & Benoit, 1984) | Open Energy  

Open Energy Info (EERE)

Geothermometry At Salt Wells Area (Edmiston & Benoit, Geothermometry At Salt Wells Area (Edmiston & Benoit, 1984) Exploration Activity Details Location Salt Wells Geothermal Area Exploration Technique Geothermometry Activity Date 1980 - 1984 Usefulness useful DOE-funding Unknown Exploration Basis The blind Salt Wells geothermal system was first identified when Anadarko Petroleum Corporation drilled slim hole and geothermal exploration wells at the site in 1980. Two reports detail the results of this drilling activity. This paper seeks to (1) describe several moderate-temperature (150-200°C) geothermal systems discovered and drilled during the early 1980's that had not been documented previously in the literature, (2) summarize and compare chemical and temperature data from known moderate- to high-temperature (>200°C) in the region, and (3) to comment on the

49

Geothermometry At Salt Wells Area (Coolbaugh, Et Al., 2006) | Open Energy  

Open Energy Info (EERE)

source source History View New Pages Recent Changes All Special Pages Semantic Search/Querying Get Involved Help Apps Datasets Community Login | Sign Up Search Page Edit History Facebook icon Twitter icon » Geothermometry At Salt Wells Area (Coolbaugh, Et Al., 2006) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Salt Wells Area (Coolbaugh, Et Al., 2006) Exploration Activity Details Location Salt Wells Geothermal Area Exploration Technique Geothermometry Activity Date 2005 - 2005 Usefulness useful DOE-funding Unknown Exploration Basis Geochemical water sampling, mineral distribution mapping, and shallow (30 cm) temperature probe measurements were conducted to expand on a previous field mapping study of surface geothermal features at Salt Wells, in order

50

Geothermometry At Nw Basin & Range Region (Laney, 2005) | Open Energy  

Open Energy Info (EERE)

Geothermometry At Nw Basin & Range Region (Laney, Geothermometry At Nw Basin & Range Region (Laney, 2005) Exploration Activity Details Location Northwest Basin and Range Geothermal Region Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown Notes Geochemical Sampling of Thermal and Non-thermal Waters in Nevada, Shevenell and Garside. The objective of this project is to obtain geochemical data from springs (and some wells) for which data are not publicly available, or for which the analyses are incomplete, poor, or nonexistent. With these data, geothermometers are being calculated and a preliminary assessment of the geothermal potential and ranking of the sampled areas is being conducted using the new geochemical data. Objectives changed slightly in 2004. Samples are now being collected at sites identified by other

51

Geothermometry At Nevada Test And Training Range Area (Sabin, Et Al., 2004)  

Open Energy Info (EERE)

2004) 2004) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Nevada Test And Training Range Area (Sabin, Et Al., 2004) Exploration Activity Details Location Nevada Test And Training Range Area Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown Notes Groundwater data are limited to a portion of NAFR; data are more plentiful beyond the range boundaries. Geothermometry yields calculated groundwater temperatures generally ranging from 30 to 105degrees C, with a rough correlation between the SiO2-chalcedony and the Na-K-Na (Mg-corrected) geothermometers. References A. E. Sabin, J. D. Walker, J. Unruh, F. C. Monastero (2004) Toward The Development Of Occurrence Models For Geothermal Resources In The

52

Classification  

NLE Websites -- All DOE Office Websites (Extended Search)

Classification Classification Name: mike Status: N/A Age: N/A Location: N/A Country: N/A Date: Around 1993 Question: What is the most accurate way to classify animals in taxonomy? Replies: If by "most accurate", you mean the way that best approximates classifying animals according to their genetic relatedness, and historical ties, then the best way is called "cladistics." Cladistics is a method that is used to split a group of animals (or any living thing) into two groups. The process is completed until there are only two animals left, and they are split. The criteria they use to split groups is based on "synapomorphies" a 50-cent word which means a SHARED and DERIVED CHARACTER. A CHARACTER is a measure of an organism, like its color, or structure, or size. A DERIVED character is one that is newly evolved. For instance, if you had a group of 5 fish, and 2 monkeys, you would guess (based on previous work) that the two monkeys belong in one group, and the 5 fish in the other (and you would be right). This is because the 2 monkeys SHARE many DERIVED CHARACTERS that the fish do not share with the monkeys. One such derived character is the presence of legs. Fossil evidence shows that vertebrate legs are newly evolved with respect to fish. Fish came first, the vertebrate legs. You have now created a simple cladogram. One branch is for fish, the other for monkeys. By the by, taxonomy is the process of naming organisms, and is neither accurate nor inaccurate. Phyletics is the science of determining the beasts genetic relationships, and that can be inaccurate if one is not careful

53

Geothermometry At Desert Queen Area (Garchar & Arehart, 2008) | Open Energy  

Open Energy Info (EERE)

Queen Area (Garchar & Arehart, 2008) Queen Area (Garchar & Arehart, 2008) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Desert Queen Area (Garchar & Arehart, 2008) Exploration Activity Details Location Desert Queen Area Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown Notes Temperatures of the reservoir at depth are estimated to be between 92-141 degrees C and were calculated using the δ18O(SO4-H2O) geothermometer. It is unclear whether these temperatures reflect waters from the outflow zone of the Desert Peak geothermal system, or waters from a different reservoir at Desert Queen. Quartz, chalcedony, amorphous silica, Na-K-Ca, and δ18O(SO4-H2O) geothermometer calculations were performed.

54

Geothermometry At Walker-Lane Transitional Zone Region (Laney, 2005) | Open  

Open Energy Info (EERE)

Laney, 2005) Laney, 2005) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Walker-Lane Transitional Zone Region (Laney, 2005) Exploration Activity Details Location Walker-Lane Transition Zone Geothermal Region Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown Notes Geochemical Sampling of Thermal and Non-thermal Waters in Nevada, Shevenell and Garside. The objective of this project is to obtain geochemical data from springs (and some wells) for which data are not publicly available, or for which the analyses are incomplete, poor, or nonexistent. With these data, geothermometers are being calculated and a preliminary assessment of the geothermal potential and ranking of the sampled areas is being

55

Geothermometry At Northern Basin & Range Region (Cole, 1983) | Open Energy  

Open Energy Info (EERE)

Northern Basin & Range Region Northern Basin & Range Region (Cole, 1983) Exploration Activity Details Location Northern Basin and Range Geothermal Region Exploration Technique Geothermometry Activity Date Usefulness not indicated DOE-funding Unknown Notes Wstern Utah hot springs: Antelope, Fish (Deadman), Fish (Wilson), Twin Peak, Cudahy, Laverkin, Grantsville, Crystal Prison, Arrowhead, Red Hill, Monroe, Joseph, Castilla, Saratoga, Thermo, Crater, Wasatch, Beck, Deseret, Big Spring, Blue Warm, Crystal Madsen, Udy, Cutler, Garland, Utah, Ogden, Hooper, Newcastle Area References David R. Cole (1983) Chemical And Isotopic Investigation Of Warm Springs Associated With Normal Faults In Utah Retrieved from "http://en.openei.org/w/index.php?title=Geothermometry_At_Northern_Basin_%26_Range_Region_(Cole,_1983)&oldid=4014

56

Geothermometry At Clear Lake Area (Thompson, Et Al., 1992) | Open Energy  

Open Energy Info (EERE)

Clear Lake Area (Thompson, Et Al., 1992) Clear Lake Area (Thompson, Et Al., 1992) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Clear Lake Area (Thompson, Et Al., 1992) Exploration Activity Details Location Clear Lake Area Exploration Technique Geothermometry Activity Date Usefulness useful DOE-funding Unknown Notes Based on the above discussion, we favor a model in which thermal water rises somewhere between Howard and Seigler Springs. At Howard Springs we see evidence for the most representative deep thermal water because the C1 is elevated (highest measured C1 concentrations occur at Howard Springs). Moreover, the Na-Li, Na-K and Na-K-Ca geothermometers suggest temperatures greater than 240 degrees C. References J. M. Thompson, R. H. Mariner, L. D. White, T. S. Presser, W. C.

57

Geothermometry At Long Valley Caldera Area (Sorey, Et Al., 1991) | Open  

Open Energy Info (EERE)

Long Valley Caldera Area (Sorey, Et Long Valley Caldera Area (Sorey, Et Al., 1991) Exploration Activity Details Location Long Valley Caldera Area Exploration Technique Geothermometry Activity Date Usefulness could be useful with more improvements DOE-funding Unknown Notes Silica-geothermometer temperature estimates for the Casa Diablo and RDO-8 well samples ( 196-202 degrees C) are lower than the corresponding cation-geothermometer temperature estimates, indicating loss of silica with declining reservoir temperature or dilution with low-silica waters. At shallow depths in the caldera References Michael L. Sorey, Gene A. Suemnicht, Neil C. Sturchio, Gregg A. Nordquist (1991) New Evidence On The Hydrothermal System In Long Valley Caldera, California, From Wells, Fluid Sampling, Electrical Geophysics, And

58

Lubricant Classification  

Science Conference Proceedings (OSTI)

Table 9   Engine tests for API classification...wear ASTM sequence VI (1982 Buick V-6 engine): Fuel economy Diesel engines CRC L-38: Bearing corrosion, oxidation, shear stability Caterpillar 1K: Piston deposits Detroit diesel 6V-92TA (two-stroke engine): Piston

59

Classification Training Institute Catalog | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Classification Training Institute Catalog Classification Training Institute Catalog Enforcement Guidance Oversight Reporting Classification Classification Training Institute...

60

Geology, hydrothermal petrology, stable isotope geochemistry, and fluid inclusion geothermometry of LASL geothermal test well C/T-1 (Mesa 31-1), East Mesa, Imperial Valley, California, USA  

DOE Green Energy (OSTI)

Borehole Mesa 31-1 (LASL C/T-1) is an 1899-m (6231-ft) deep well located in the northwestern part of the East Mesa Geothermal Field. Mesa 31-1 is the first Calibration/Test Well (C/T-1) in the Los Alamos Scientific Laboratory (LASL), Geothermal Log Interpretation Program. The purpose of this study is to provide a compilation of drillhole data, drill cuttings, well lithology, and formation petrology that will serve to support the use of well LASL C/T-1 as a calibration/test well for geothermal logging. In addition, reviews of fluid chemistry, stable isotope studies, isotopic and fluid inclusion geothermometry, and the temperature log data are presented. This study provides the basic data on the geology and hydrothermal alteration of the rocks in LASL C/T-1 as background for the interpretation of wireline logs.

Miller, K.R.; Elders, W.A.

1980-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Understanding Classification  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

n n n d d e e r r s s t t a a n n d d i i n n g g C C l l a a s s s s i i f f i i c c a a t t i i o o n n O O f f f f i i c c e e o o f f C C l l a a s s s s i i f f i i c c a a t t i i o o n n O O f f f f i i c c e e o o f f H H e e a a l l t t h h , , S S a a f f e e t t y y a a n n d d S S e e c c u u r r i i t t y y U U . . S S . . D D e e p p a a r r t t m m e e n n t t o o f f E E n n e e r r g g y y J J u u n n e e 2 2 0 0 1 1 2 2 1 Now that you have your clearance, you are likely to be working with classified information. As a result - * You may originate a document that must be reviewed for classification. * You may have a classified document that you want to have reviewed for declassification. * You may be reading a newspaper or magazine article and find information in it that appears to be classified. * You may encounter classified information you believe should NOT be classified. This booklet highlights your responsibilities identified in DOE Order

62

Ultra High Temperature | Open Energy Information  

Open Energy Info (EERE)

Ultra High Temperature Ultra High Temperature Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Print PDF Sanyal Temperature Classification: Ultra High Temperature Dictionary.png Ultra High Temperature: No definition has been provided for this term. Add a Definition Sanyal Temp Classification This temperature scheme was developed by Sanyal in 2005 at the request of DOE and GEA, as reported in Classification of Geothermal Systems: A Possible Scheme. Extremely Low Temperature Very Low Temperature Low Temperature Moderate Temperature High Temperature Ultra High Temperature Steam Field Reservoir fluid greater than 300°C is considered by Sanyal to be "ultra high temperature". "Such reservoirs are characterized by rapid development of steam saturation in the reservoir and steam fraction in the mobile fluid phase upon

63

Extremely Low Temperature | Open Energy Information  

Open Energy Info (EERE)

Extremely Low Temperature Extremely Low Temperature Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Print PDF Sanyal Temperature Classification: Extremely Low Temperature Dictionary.png Extremely Low Temperature: No definition has been provided for this term. Add a Definition Sanyal Temp Classification This temperature scheme was developed by Sanyal in 2005 at the request of DOE and GEA, as reported in Classification of Geothermal Systems: A Possible Scheme. Extremely Low Temperature Very Low Temperature Low Temperature Moderate Temperature High Temperature Ultra High Temperature Steam Field Reservoir fluid less than 100°C is considered to to be "extremely low temperature." Note: Sanyal classified fluids of these temperatures to be "non-electrical grade" in 2005, but electricity has since been generated from these

64

Moderate Temperature | Open Energy Information  

Open Energy Info (EERE)

Moderate Temperature Moderate Temperature Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Print PDF Sanyal Temperature Classification: Moderate Temperature Dictionary.png Moderate Temperature: No definition has been provided for this term. Add a Definition Sanyal Temp Classification This temperature scheme was developed by Sanyal in 2005 at the request of DOE and GEA, as reported in Classification of Geothermal Systems: A Possible Scheme. Extremely Low Temperature Very Low Temperature Low Temperature Moderate Temperature High Temperature Ultra High Temperature Steam Field Reservoir fluid between 190°C and 230°C is considered by Sanyal to be "moderate temperature." "The next higher resource temperature limit is chosen as 230°C, which is lower than the minimum initial resource temperature encountered in

65

Low Temperature | Open Energy Information  

Open Energy Info (EERE)

Temperature Temperature Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Print PDF Sanyal Temperature Classification: Low Temperature Dictionary.png Low Temperature: No definition has been provided for this term. Add a Definition Sanyal Temp Classification This temperature scheme was developed by Sanyal in 2005 at the request of DOE and GEA, as reported in Classification of Geothermal Systems: A Possible Scheme. Extremely Low Temperature Very Low Temperature Low Temperature Moderate Temperature High Temperature Ultra High Temperature Steam Field Reservoir fluid between 150°C and 190°C is considered by Sanyal to be "low temperature." "The mobile fluid phase in these reservoirs is liquid water. A number of commercial power projects have been operated over the last two decades

66

Very Low Temperature | Open Energy Information  

Open Energy Info (EERE)

Very Low Temperature Very Low Temperature Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Print PDF Sanyal Temperature Classification: Very Low Temperature Dictionary.png Very Low Temperature: No definition has been provided for this term. Add a Definition Sanyal Temp Classification This temperature scheme was developed by Sanyal in 2005 at the request of DOE and GEA, as reported in Classification of Geothermal Systems: A Possible Scheme. Extremely Low Temperature Very Low Temperature Low Temperature Moderate Temperature High Temperature Ultra High Temperature Steam Field Reservoir fluid between 100°C and 150°C is considered by Sanyal to be "very low temperature." "The mobile fluid phase in these reservoirs is liquid water. Very few power projects have been developed in the U.S. based on geothermal resources in

67

High Temperature | Open Energy Information  

Open Energy Info (EERE)

Temperature Temperature Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Print PDF Sanyal Temperature Classification: High Temperature Dictionary.png High Temperature: No definition has been provided for this term. Add a Definition Sanyal Temp Classification This temperature scheme was developed by Sanyal in 2005 at the request of DOE and GEA, as reported in Classification of Geothermal Systems: A Possible Scheme. Extremely Low Temperature Very Low Temperature Low Temperature Moderate Temperature High Temperature Ultra High Temperature Steam Field Reservoir fluid between 230°C and 300°C is considered by Sanyal to be "high temperature." "Above a temperature level of 230°C, the reservoir would be expected to become two-phase at some point during exploitation. The next higher

68

Security classification of information  

Science Conference Proceedings (OSTI)

This document is the second of a planned four-volume work that comprehensively discusses the security classification of information. The main focus of Volume 2 is on the principles for classification of information. Included herein are descriptions of the two major types of information that governments classify for national security reasons (subjective and objective information), guidance to use when determining whether information under consideration for classification is controlled by the government (a necessary requirement for classification to be effective), information disclosure risks and benefits (the benefits and costs of classification), standards to use when balancing information disclosure risks and benefits, guidance for assigning classification levels (Top Secret, Secret, or Confidential) to classified information, guidance for determining how long information should be classified (classification duration), classification of associations of information, classification of compilations of information, and principles for declassifying and downgrading information. Rules or principles of certain areas of our legal system (e.g., trade secret law) are sometimes mentioned to .provide added support to some of those classification principles.

Quist, A.S.

1993-04-01T23:59:59.000Z

69

Classification Training Institute, 2013 Course Catelog  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Classification Classification Classification Training Institute 2013 Course Catalog 1 TABLE OF CONTENTS Introduction ................................................................................................................................... 2 Classification Level ....................................................................................................................... 2 Registration ................................................................................................................................... 2 Additional Information ................................................................................................................... 2 2013 Course Schedule and Locations .......................................................................................... 3

70

Multidimensional data classification  

Science Conference Proceedings (OSTI)

This paper deals with the classification of objects into the limited number of classes. Objects are characterised by n-features, e.g. n-dimensional vectors describe them. The paper focuses on the Bayes classifier based on the probability principle, with ... Keywords: Bayes classifier, classification, decision rule, feature, fixed number of features, loss function, multispectral data

Dana Klimeov; Eva Ocelkov

2009-03-01T23:59:59.000Z

71

DOE LLW classification rationale  

Science Conference Proceedings (OSTI)

This report was about the rationale which the US Department of Energy had with low-level radioactive waste (LLW) classification. It is based on the Nuclear Regulatory Commission's classification system. DOE site operators met to review the qualifications and characteristics of the classification systems. They evaluated performance objectives, developed waste classification tables, and compiled dose limits on the waste. A goal of the LLW classification system was to allow each disposal site the freedom to develop limits to radionuclide inventories and concentrations according to its own site-specific characteristics. This goal was achieved with the adoption of a performance objectives system based on a performance assessment, with site-specific environmental conditions and engineered disposal systems.

Flores, A.Y.

1991-09-16T23:59:59.000Z

72

DOE LLW classification rationale  

Science Conference Proceedings (OSTI)

This report was about the rationale which the US Department of Energy had with low-level radioactive waste (LLW) classification. It is based on the Nuclear Regulatory Commission`s classification system. DOE site operators met to review the qualifications and characteristics of the classification systems. They evaluated performance objectives, developed waste classification tables, and compiled dose limits on the waste. A goal of the LLW classification system was to allow each disposal site the freedom to develop limits to radionuclide inventories and concentrations according to its own site-specific characteristics. This goal was achieved with the adoption of a performance objectives system based on a performance assessment, with site-specific environmental conditions and engineered disposal systems.

Flores, A.Y.

1991-09-16T23:59:59.000Z

73

Introduction to Classification  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

3 3 This briefing provides an introduction to classified information. 2 Introduction to Classified Information April 2013 3 What is classification?  Classification is how we identify certain information that needs to be protected in the interest of national security.  DOE has a formal process for classifying and declassifying information, documents, and materials. 4 Restricted Data (RD) Formerly Restricted Data (FRD) What information is classified? Atomic Energy Act Implemented by 10 CFR part 1045 Executive Order 13526 Implemented by 32 CFR part 2001 National Security Information (NSI) 5 Transclassified Foreign Nuclear Information (TFNI) Authority Classified Information Category 6 Restricted Data  The Atomic Energy Act defines "Restricted

74

Algorithms for pseudoknot classification  

Science Conference Proceedings (OSTI)

The structures of non-coding RNAs are found to be critical in many biological functions. In particular, pseudoknotted structures play an important role in some of these functions. Different pseudoknotted structures may have different functionalities. ... Keywords: non-coding RNA, pseudoknot classification

Thomas K. F. Wong; Hui-Ting Yu; Bay-Yuan Hsu; Tak-Wah Lam; Wing-Kai Hon; Siu-Ming Yiu

2011-08-01T23:59:59.000Z

75

Data envelopment analysis classification machine  

Science Conference Proceedings (OSTI)

This paper establishes the equivalent relationship between the data classification machine and the data envelopment analysis (DEA) model, and thus build up a DEA based classification machine. A data is characterized by a set of values. Without loss of ... Keywords: Classification machine, Data envelopment analysis, Preference cone

Hong Yan; Quanling Wei

2011-11-01T23:59:59.000Z

76

Soil Classification Using GATree  

E-Print Network (OSTI)

This paper details the application of a genetic programming framework for classification of decision tree of Soil data to classify soil texture. The database contains measurements of soil profile data. We have applied GATree for generating classification decision tree. GATree is a decision tree builder that is based on Genetic Algorithms (GAs). The idea behind it is rather simple but powerful. Instead of using statistic metrics that are biased towards specific trees we use a more flexible, global metric of tree quality that try to optimize accuracy and size. GATree offers some unique features not to be found in any other tree inducers while at the same time it can produce better results for many difficult problems. Experimental results are presented which illustrate the performance of generating best decision tree for classifying soil texture for soil data set.

Bhargavi, P

2010-01-01T23:59:59.000Z

77

Seismic event classification system  

DOE Patents (OSTI)

In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. Self-organizing neural networks (SONNs) can be used for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs are useful for this purpose. Given the detection of a seismic event and the corresponding signal, computation is made of: the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This pre-processed input is fed into the SONNs. These neural networks are able to group events that look similar. The ART SONN has an advantage in classifying the event because the types of cluster groups do not need to be pre-defined. The results from the SONNs together with an expert seismologist's classification are then used to derive event classification probabilities. 21 figures.

Dowla, F.U.; Jarpe, S.P.; Maurer, W.

1994-12-13T23:59:59.000Z

78

Seismic event classification system  

DOE Patents (OSTI)

In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. Self-organizing neural networks (SONNs) can be used for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs are useful for this purpose. Given the detection of a seismic event and the corresponding signal, computation is made of: the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This pre-processed input is fed into the SONNs. These neural networks are able to group events that look similar. The ART SONN has an advantage in classifying the event because the types of cluster groups do not need to be pre-defined. The results from the SONNs together with an expert seismologist's classification are then used to derive event classification probabilities.

Dowla, Farid U. (Castro Valley, CA); Jarpe, Stephen P. (Brentwood, CA); Maurer, William (Livermore, CA)

1994-01-01T23:59:59.000Z

79

Classification Training Institute Catalog | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Services » Classification » Classification Training Institute » Services » Classification » Classification Training Institute » Classification Training Institute Catalog Classification Training Institute Catalog Classification Training Institute (CTI) Catalog Training & Reference Materials Online Classified or Controlled Information Mini-Lessons Classified Information Training Unclassified Controlled Nuclear Information Training Official Use Only Training OpenNet Training Training For Other Agency Personnel Classification Training Institute Catalog Enforcement Guidance Oversight Reporting Security Classification Classification Training Institute Official Use Only Information Unclassified Controlled Nuclear Information (UCNI) Statutes, Regulations, & Directives Nuclear Safety Assistance Training Outreach & Collaboration

80

Steam Field | Open Energy Information  

Open Energy Info (EERE)

Field Field Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Print PDF Sanyal Temperature Classification: Steam Field Dictionary.png Steam Field: No definition has been provided for this term. Add a Definition Sanyal Temp Classification This temperature scheme was developed by Sanyal in 2005 at the request of DOE and GEA, as reported in Classification of Geothermal Systems: A Possible Scheme. Extremely Low Temperature Very Low Temperature Low Temperature Moderate Temperature High Temperature Ultra High Temperature Steam Field Steam field reservoirs are special cases where the fluid is predominantly found in a gas phase between 230°C to 240°C. "This special class of resource needs to be recognized, its uniqueness being the remarkably consistent initial temperature and pressure

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

Geothermometry (Fouillac & Michard, 1981) | Open Energy Information  

Open Energy Info (EERE)

for geochemical surveys. An interesting point is the remarkable constancy of the NaLi ratio from aquifer to surface manifestations. References C. Fouillac, G. Michard (1981)...

82

On Classification with Incomplete Data  

Science Conference Proceedings (OSTI)

We address the incomplete-data problem in which feature vectors to be classified are missing data (features). A (supervised) logistic regression algorithm for the classification of incomplete data is developed. Single or multiple imputation for the missing ... Keywords: Classification, incomplete data, missing data, supervised learning, semisupervised learning, imperfect labeling.

David Williams; Xuejun Liao; Ya Xue; Lawrence Carin; Balaji Krishnapuram

2007-03-01T23:59:59.000Z

83

Supercomputer Assisted Generation of Machine Learning Agents Jibonananda Sanyal, Joshua New, and Richard Edwards  

E-Print Network (OSTI)

of Building Energy Models {sanyalj, newjr}@ornl.gov, redwar15@utk.edu The Autotune methodology Supercomputing lifetimes of the known universe on Titan! o 14 parameter full combinatorial subset of most important ones o

Wang, Xiaorui "Ray"

84

Taking advantage of models for legal classification  

Science Conference Proceedings (OSTI)

Legal reasoning is often couched in terms of legal classification. We examine how three models of classification Classical, Probabilistic and Exemplar are used to perform legal classification. We argue that all three models of ...

D. B. Skalak

1989-05-01T23:59:59.000Z

85

Catalog, Classification Training Institute | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Catalog, Classification Training Institute Catalog, Classification Training Institute Catalog, Classification Training Institute December 2012 2013 Classification Training Course Catalog. To ensure that all classification and declassification decisions are based on these principles, the Office of Classification has undertaken the establishment and maintenance of a comprehensive classification and declassification education program. The training and education program is perpetually evolving with new courses and special briefings as events dictate. Basic courses that are in constant demand are described in this course catalog. Other more specialized courses and briefings have been developed and are available on an "as needed" basis. Classification Training Institute (CTI) 2013 Catalog can be viewed below:

86

Catalog, Classification Training Institute | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Catalog, Classification Training Institute Catalog, Classification Training Institute Catalog, Classification Training Institute December 2012 2013 Classification Training Course Catalog. To ensure that all classification and declassification decisions are based on these principles, the Office of Classification has undertaken the establishment and maintenance of a comprehensive classification and declassification education program. The training and education program is perpetually evolving with new courses and special briefings as events dictate. Basic courses that are in constant demand are described in this course catalog. Other more specialized courses and briefings have been developed and are available on an "as needed" basis. Classification Training Institute (CTI) 2013 Catalog can be viewed below:

87

Text structure-aware classification  

E-Print Network (OSTI)

Bag-of-words representations are used in many NLP applications, such as text classification and sentiment analysis. These representations ignore relations across different sentences in a text and disregard the underlying ...

Dzunic, Zoran, S.M. Massachusetts Institute of Technology

2009-01-01T23:59:59.000Z

88

Cloud Classification Before Luke Howard  

Science Conference Proceedings (OSTI)

A brief outline of the history of cloud painting prior to the first cloud classification schemes of Luke Howard and Lamarck is presented. It is shown that European painters had accurately represented most of the different cloud forms between ...

Stanely David Gedzelman

1989-04-01T23:59:59.000Z

89

Protein structure classification by structural transformatio  

Science Conference Proceedings (OSTI)

Protein structure classification plays an important role in understanding the relationships among structure and sequence. Recently, as the number of known protein structure are increasing steeply, automatic classification is highly required. This paper ... Keywords: Brookhaven Protein Data Bank, automatic classification, molecular biophysics, primitive operations, protein folds, protein structure classification, secondary structural elements, sequence, structural transformation

T. Ohkawa; D. Namihira; N. Komoda; A. Kidera; H. Nakamura

1996-11-01T23:59:59.000Z

90

Statutes, Regulations, and Directives for Classification Program |  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Classification » Statutes, Regulations, and Directives Classification » Statutes, Regulations, and Directives for Classification Program Statutes, Regulations, and Directives for Classification Program Classification Atomic Energy Act of 1954 - Establishes Government-wide policies for classifying, safeguarding, and declassifying Restricted Data information. 10 CFR Part 1045, Nuclear Classification and Declassification - Establishes the Government-wide policies and procedures for implementing sections 141 and 142 of the Atomic Energy Act of 1954 for classifying and declassifying RD and FRD and implements those requirements of Executive Order 12958 concerning NSI that affect the public. Executive Order 13526, Classified National Security Information - Prescribes the Government-wide system for classifying, safeguarding, and

91

Brochure, Classification Bulletin GEN-16 - February 2012 | Department...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Brochure, Classification Bulletin GEN-16 - February 2012 Brochure, Classification Bulletin GEN-16 - February 2012 This brochure provides information on Classification Bulletin...

92

Automated classification of congressional legislation  

Science Conference Proceedings (OSTI)

For social science researchers, content analysis and classification of United States Congressional legislative activities have been time consuming and costly. The Library of Congress THOMAS system provides detailed information about bills and laws, but ... Keywords: SVMs, U.S. congress, institutions, legislative activities, support vector machines, text analysis

Stephen Purpura; Dustin Hillard

2006-05-01T23:59:59.000Z

93

Classification of 7-dimensional Einstein nilradicals II  

E-Print Network (OSTI)

This paper contains all computations supporting the classification of 7-dimensional Einstein nilradicals given in the article "Classification of 7-dimensional Einstein nilradicals" (arXiv). Each algebra is analyzed in detail here.

Culma, Edison Alberto Fernndez

2011-01-01T23:59:59.000Z

94

A property based specification formalism classification  

Science Conference Proceedings (OSTI)

Specification formalisms may be classified through some common properties. Specification formalism classification may be used as a basis for the evaluation of the adequacy of formal specification languages within specific application domains. System ... Keywords: Classification, Specification formalism, Specification properties

Amir A. Khwaja; Joseph E. Urban

2010-11-01T23:59:59.000Z

95

Interferometric SAR coherence classification utility assessment  

SciTech Connect

The classification utility of a dual-antenna interferometric synthetic aperture radar (IFSAR) is explored by comparison of maximum likelihood classification results for synthetic aperture radar (SAR) intensity images and IPSAR intensity and coherence images. The addition of IFSAR coherence improves the overall classification accuracy for classes of trees, water, and fields. A threshold intensity-coherence classifier is also compared to the intensity-only classification results.

Yocky, D.A.

1998-03-01T23:59:59.000Z

96

UK Radioactive Waste: Classification, Sources and Management ...  

Science Conference Proceedings (OSTI)

Paper contents outlook: Introduction; Radioactive waste classification; Sources of waste (Nuclear power plant operation/decommissioning, Reprocessing and...

97

Remote Sensing Ayman F. Habib Image Classification  

E-Print Network (OSTI)

1 Remote Sensing Ayman F. Habib 1 Chapter 6 Image Classification Remote Sensing Ayman F. Habib 2. ­ Unsupervised classification. · Accuracy assessment. #12;2 Remote Sensing Ayman F. Habib 3 Image Classification of image pixels is based on their digital numbers/grey values in one or more spectral bands. Remote Sensing

Habib, Ayman

98

Scalable Active Learning for Multiclass Image Classification  

Science Conference Proceedings (OSTI)

Machine learning techniques for computer vision applications like object recognition, scene classification, etc., require a large number of training samples for satisfactory performance. Especially when classification is to be performed over many categories, ... Keywords: Training,Support vector machines,Training data,Noise,Accuracy,Learning systems,Couplings,object recognition,Active learning,scalable machine learning,multiclass classification

Ajay J. Joshi; Fatih Porikli; Nikos Papanikolopoulos

2012-11-01T23:59:59.000Z

99

Non-smoothness in classification problems  

Science Conference Proceedings (OSTI)

We review the role played by non-smooth optimization techniques in many recent applications in classification area. Starting from the classical concept of linear separability in binary classification, we recall the more general concepts of polyhedral, ... Keywords: classification, non-smooth optimization, separation of sets

A. Astorino; A. Fuduli; E. Gorgone

2008-10-01T23:59:59.000Z

100

Classification Training Institute | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Classification Training Institute Classification Training Institute Classification Training Institute Welcome to the Classification Training Institute (CTI) Webpage. This page provides information for Department of Energy (DOE) and non-DOE personnel concerning courses offered by the CTI, the current course schedule, and provides training and resources (reference materials and links to web pages with additional information) concerning information classified and controlled information within the DOE. This page also contains short animated lessons. If you need a quick refresher on an aspect of classified or controlled information, refer to the section "Online Mini-Lessons" below. Additional lessons are being developed. The training materials provided on this page are for information only. If

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

Proposed Uniformat II Classification of Bridge Elements  

Science Conference Proceedings (OSTI)

... Because sub-elements can be tied into a work breakdown structure, they significantly enhance the usefulness of an elemental classification across ...

2011-06-24T23:59:59.000Z

102

Discriminant Random Forest (DRF) Classification Methodology  

Jupiter Laser Facility. ... State-of-the-art methodologies that perform this type of classification include Support Vector Machines, Neural Networks, and Random Forest.

103

Independent Oversight Inspection of Classification and Information...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

PNNL. Procedures PNSO administers its CIC programs in accordance with DOE orders and manuals on classification, UCNI, and OUO and does not issue local procedures. PNNL has a...

104

Discriminant forest classification method and system  

DOE Patents (OSTI)

A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

2012-11-06T23:59:59.000Z

105

Microarray gene expression classification with few genes: Criteria to combine attribute selection and classification methods  

Science Conference Proceedings (OSTI)

Microarray data classification is a task involving high dimensionality and small samples sizes. A common criterion to decide on the number of selected genes is maximizing the accuracy, which risks overfitting and usually selects more genes than actually ... Keywords: Efficient classification with few genes, Feature selection, Machine learning, Microarray data classification

Carlos J. Alonso-Gonzlez; Q. Isaac Moro-Sancho; Arancha Simon-Hurtado; Ricardo Varela-Arrabal

2012-06-01T23:59:59.000Z

106

An extensive study on automated Dewey Decimal Classification  

Science Conference Proceedings (OSTI)

In this paper, we present a theoretical analysis and extensive experiments on the automated assignment of Dewey Decimal Classification (DDC) classes to bibliographic data with a supervised machine-learning approach. Library classification systems, such ... Keywords: Dewey Decimal Classification, automatic classification, hierarchical classification, hierarchical models, tree structures

Jun Wang

2009-11-01T23:59:59.000Z

107

Free biholomorphic classification of noncommutative domains  

E-Print Network (OSTI)

In this paper we develop a theory of free holomorphic functions on noncommutative Reinhardt domains generated by positive regular free holomorphic functions in n noncommuting variables. We show that the free biholomorphic classification of these domains is the same as the classification, up to unital completely isometric isomorphisms, of the corresponding noncommutative domain algebras.

Popescu, Gelu

2010-01-01T23:59:59.000Z

108

Ethnicity classification based on a hierarchical fusion  

Science Conference Proceedings (OSTI)

In this paper, we propose a cascaded multimodal biometrics system involving a fusion of frontal face and lateral gait, for the specific problem of ethnicity classification. This system performs human ethnicity classification first from the cues of gait ... Keywords: ethnicity, face, fusion, gait

De Zhang; Yunhong Wang; Zhaoxiang Zhang

2012-12-01T23:59:59.000Z

109

Classification of Supertransitive 2-Webs on Surfaces  

Science Conference Proceedings (OSTI)

We obtain a complete classification of supertransitive 2-webs on a closed oriented surface of genus p ? 1 in terms of asymptotic directions of leaves on the universal covering surface and represent all topological classes of 2-webs by means ... Keywords: Anosov and pseudo-Anosov diffeomorphisms, geodesic laminations, supertransitive webs, topological classification

S. Kh. Aranson; V. Z. Grines; V. A. Kaimanovich

2003-10-01T23:59:59.000Z

110

Classification with dynamic reducts and belief functions  

Science Conference Proceedings (OSTI)

In this paper, we propose two approaches of classification namely, Dynamic Belief Rough Set Classifier (D-BRSC) and Dynamic Belief Rough Set Classifier based on Generalization Distribution Table (D-BRSC-GDT). Both the classifiers are induced from uncertain ... Keywords: belief function theory, classification, dynamic reduct, generalization distribution table, rough sets, uncertainty

Salsabil Trabelsi; Zied Elouedi; Pawan Lingras

2011-01-01T23:59:59.000Z

111

Environmental Noise Source Classification Using Neural Networks  

Science Conference Proceedings (OSTI)

Neural networks have been applied to many interesting problems in different areas including noise identification/recognition. With this study, we studied noise classification using artificial neural networks (ANN). Three commonly encountered non-stationary ... Keywords: ACF-based feature parameter, environmental noise classification, Neural Networks (ANN)

Buket D. Barkana; Inci Saricicek

2010-04-01T23:59:59.000Z

112

A multiresolution spectral angle-based hyperspectral classification method  

Science Conference Proceedings (OSTI)

Due to the lack of training samples, hyperspectral classification often adopts the minimum distance classification method based on spectral metrics. This paper proposes a novel multiresolution spectral-angle-based hyperspectral classification method, ...

Jin Chen; Runsheng Wang; Cheng Wang

2008-06-01T23:59:59.000Z

113

Fuzzy one-class classification model using contamination neighborhoods  

Science Conference Proceedings (OSTI)

A fuzzy classification model is studied in the paper. It is based on the contaminated (robust) model which produces fuzzy expected risk measures characterizing classification errors. Optimal classification parameters of the models are derived by minimizing ...

Lev V. Utkin

2012-01-01T23:59:59.000Z

114

Classification Bulletin GEN-16 Revision | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Classification Bulletin GEN-16 Revision Classification Bulletin GEN-16 Revision Provides guidance to DOE Federal and contractor employees with access to classified information on...

115

Brochure, Classification Bulletin GEN-16 - February 2012 | Department...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Bulletin GEN-16 - February 2012 Brochure, Classification Bulletin GEN-16 - February 2012 This brochure provides information on Classification Bulletin GEN-16, No Comment Policy on...

116

Security Framework for Control System Data Classification and...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Framework for Control System Data Classification and Protection Security Framework for Control System Data Classification and Protection This document presents a data...

117

Mutation testing strategies using mutant classification  

Science Conference Proceedings (OSTI)

Mutation testing has a widespread reputation of being a rather powerful testing technique. However, its practical application requires the detection of equivalent mutants. Detecting equivalent mutants is cumbersome since it requires manual analysis, ... Keywords: mutant classification, mutants' impact, mutation testing

Mike Papadakis; Yves Le Traon

2013-03-01T23:59:59.000Z

118

A Classification Scheme for Satellite Temperature Retrievals  

Science Conference Proceedings (OSTI)

A new approach is presented to the problem of specifying constraints on retrieval estimators used to calculate vertical temperature profiles from satellite measurements of upwelling radiance. An unsupervised classification scheme determines the ...

M. J. Uddstrom; D. Q. Wark

1985-01-01T23:59:59.000Z

119

Evaluation for Uncertain Image Classification and Segmentation  

E-Print Network (OSTI)

Each year, numerous segmentation and classification algorithms are invented or reused to solve problems where machine vision is needed. Generally, the efficiency of these algorithms is compared against the results given by one or many human experts. However, in many situations, the location of the real boundaries of the objects as well as their classes are not known with certainty by the human experts. Furthermore, only one aspect of the segmentation and classification problem is generally evaluated. In this paper we present a new evaluation method for classification and segmentation of image, where we take into account both the classification and segmentation results as well as the level of certainty given by the experts. As a concrete example of our method, we evaluate an automatic seabed characterization algorithm based on sonar images.

Martin, Arnaud; Arnold-Bos, Andreas

2008-01-01T23:59:59.000Z

120

Classification of Unseen Examples under Uncertainty  

Science Conference Proceedings (OSTI)

Very frequently machine learning from real-life data is affected by uncertainty. There are three main reasons for imperfection in data: incompleteness, imprecision (also called vagueness), and errors. In this paper the main emphasis is on classification ...

Jerzy W. Grzymala-Busse

1997-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

Improved VSM for Incremental Text Classification  

Science Conference Proceedings (OSTI)

As a simple classification method VSM has been widely applied in text information processing field. There are some problems for traditional VSM to select a refined vector model representation

Zhen Yang; Jianjun Lei; Jian Wang; Xing Zhang; Jim Guo

2008-01-01T23:59:59.000Z

122

Automatic recommendation of classification algorithms based on data set characteristics  

Science Conference Proceedings (OSTI)

Choosing appropriate classification algorithms for a given data set is very important and useful in practice but also is full of challenges. In this paper, a method of recommending classification algorithms is proposed. Firstly the feature vectors of ... Keywords: Algorithm performance, Classification, Classification algorithm automatic recommendation, Data set characteristics extraction, k-Nearest Neighbors

Qinbao Song; Guangtao Wang; Chao Wang

2012-07-01T23:59:59.000Z

123

A Study of Hierarchical and Flat Classification of Proteins  

Science Conference Proceedings (OSTI)

Automatic classification of proteins using machine learning is an important problem that has received significant attention in the literature. One feature of this problem is that expert-defined hierarchies of protein classes exist and can potentially ... Keywords: Protein classification, hierarchical classification, multiclass classification.

Arthur Zimek; Fabian Buchwald; Eibe Frank; Stefan Kramer

2010-07-01T23:59:59.000Z

124

Geothermometry At Central Nevada Seismic Zone Region (Shevenell...  

Open Energy Info (EERE)

DOE-funding Unknown References Lisa Shevenell, Ted De Rocher (2005) Evaluation Of Chemical Geothermometers For Calculating Reservoir Temperatures At Nevada Geothermal Power...

125

Geothermometry At Walker-Lane Transitional Zone Region (Shevenell...  

Open Energy Info (EERE)

DOE-funding Unknown References Lisa Shevenell, Ted De Rocher (2005) Evaluation Of Chemical Geothermometers For Calculating Reservoir Temperatures At Nevada Geothermal Power...

126

Geothermometry At Olowalu-Ukumehame Canyon Area (Thomas, 1986...  

Open Energy Info (EERE)

of the water produced by this aquifer indicates that the chloridemagnesium ion ratio has been significantly altered by thermal processes. References Donald M. Thomas (1...

127

Fuzzy set classifier for waste classification tracking  

SciTech Connect

We have developed an expert system based on fuzzy logic theory to fuse the data from multiple sensors and make classification decisions for objects in a waste reprocessing stream. Fuzzy set theory has been applied in decision and control applications with some success, particularly by the Japanese. We have found that the fuzzy logic system is rather easy to design and train, a feature that can cut development costs considerably. With proper training, the classification accuracy is quite high. We performed several tests sorting radioactive test samples using a gamma spectrometer to compare fuzzy logic to more conventional sorting schemes.

Gavel, D.T.

1992-11-04T23:59:59.000Z

128

On exploiting classification taxonomies in recommender systems  

Science Conference Proceedings (OSTI)

Massive taxonomies for product classification are currently gaining popularity among e-commerce systems for diverse domains. For instance, Amazon.com maintains an entire plethora of hand-crafted taxonomies classifying books, movies, apparel and various ... Keywords: Collaborative filtering, metrics, taxonomies, topic diversification

Cai-Nicolas Ziegler; Georg Lausen; Joseph A. Konstan

2008-04-01T23:59:59.000Z

129

Aerial image classification using structural texture similarity  

Science Conference Proceedings (OSTI)

There is an increasing need for algorithms for automatic analysis of remote sensing images and in this paper we address the problem of semantic classification of aerial images. For the task at hand we propose and evaluate local structural texture descriptor ...

Vladimir Risojevic; Zdenka Babic

2011-12-01T23:59:59.000Z

130

The imbalanced problem in morphological galaxy classification  

Science Conference Proceedings (OSTI)

In this paper we present an experimental study of the performance of six machine learning algorithms applied to morphological galaxy classification. We also address the learning approach from imbalanced data sets, inherent to many real-world applications, ... Keywords: galaxies, imbalanced data sets, machine learning

Jorge De la Calleja; Gladis Huerta; Olac Fuentes; Antonio Benitez; Eduardo Lpez Domnguez; Ma. Auxilio Medina

2010-11-01T23:59:59.000Z

131

Biometric Fusion Using Enhanced SVM Classification  

Science Conference Proceedings (OSTI)

Support Vector Machines or SVM is one of the most successful and powerful statistical learning classification techniques. It has been also implemented in the biometric field. In this paper we propose the use of SVM as a fusion tool. We propose a system ... Keywords: SVM, Biometric Fusion, Multimodal Biometrics, Fingerprint, Iris

Menrit S. Fahmy; Amir F. Atyia; Raafat S. Elfouly

2008-08-01T23:59:59.000Z

132

A Bayesian feature selection paradigm for text classification  

Science Conference Proceedings (OSTI)

The automated classification of texts into predefined categories has witnessed a booming interest, due to the increased availability of documents in digital form and the ensuing need to organize them. An important problem for text classification is feature ... Keywords: Bayesian feature selection, Metropolis search, Mixture model, Text classification

Guozhong Feng; Jianhua Guo; Bing-Yi Jing; Lizhu Hao

2012-03-01T23:59:59.000Z

133

Automatic fish classification for underwater species behavior understanding  

Science Conference Proceedings (OSTI)

The aim of this work is to propose an automatic fish classification system that operates in the natural underwater environment to assist marine biologists in understanding subehavior. Fish classification is performed by combining two types of features: ... Keywords: fish species description and classification

Concetto Spampinato; Daniela Giordano; Roberto Di Salvo; Yun-Heh Jessica Chen-Burger; Robert Bob Fisher; Gayathri Nadarajan

2010-10-01T23:59:59.000Z

134

Learning valued preference structures for solving classification problems  

Science Conference Proceedings (OSTI)

This paper introduces a new approach to classification which combines pairwise decomposition techniques with ideas and tools from fuzzy preference modeling. More specifically, our approach first decomposes a polychotomous classification problem involving ... Keywords: Classification, Decision analysis, Fuzzy preference relations, Machine learning

Eyke Hllermeier; Klaus Brinker

2008-09-01T23:59:59.000Z

135

A ternary unification framework for optimizing TCAM-based packet classification systems  

Science Conference Proceedings (OSTI)

Packet classification is the key mechanism for enabling many networking and security services. Ternary Content Addressable Memory (TCAM) has been the industrial standard for implementing high-speed packet classification because of its constant classification ... Keywords: packet classification, tcam

Eric Norige, Alex X. Liu, Eric Torng

2013-10-01T23:59:59.000Z

136

Soft Classification of Diffractive Interactions at the LHC  

SciTech Connect

Multivariate machine learning techniques provide an alternative to the rapidity gap method for event-by-event identification and classification of diffraction in hadron-hadron collisions. Traditionally, such methods assign each event exclusively to a single class producing classification errors in overlap regions of data space. As an alternative to this so called hard classification approach, we propose estimating posterior probabilities of each diffractive class and using these estimates to weigh event contributions to physical observables. It is shown with a Monte Carlo study that such a soft classification scheme is able to reproduce observables such as multiplicity distributions and relative event rates with a much higher accuracy than hard classification.

Kuusela, Mikael; Malmi, Eric [Division of Elementary Particle Physics, Department of Physics, PO Box 64, FI-00014 University of Helsinki (Finland); Department of Information and Computer Science, Aalto University School of Science and Technology, PO Box 15400, FI-00076 Aalto (Finland); Orava, Risto [Helsinki Institute of Physics, PO Box 64, FI-00014 University of Helsinki (Finland); Division of Elementary Particle Physics, Department of Physics, PO Box 64, FI-00014 University of Helsinki (Finland); Vatanen, Tommi [Helsinki Institute of Physics, PO Box 64, FI-00014 University of Helsinki (Finland); Department of Information and Computer Science, Aalto University School of Science and Technology, PO Box 15400, FI-00076 Aalto (Finland)

2011-07-15T23:59:59.000Z

137

A Fuzzy Classification Model for Online Customers  

E-Print Network (OSTI)

Building and maintaining customer loyalty are important issues in electronic business. By providing customer services, sharing cost benefits with online customers, and rewarding the most valued customers, customer loyalty and customer equity can be improved. With conventional marketing programs, groups or segments of customers are typically constituted according to a small number of attributes. Although corresponding data values may be similar for two customers, they may fall into different classes and be treated differently. With the proposed fuzzy classification model, however, customers with similar behavior and qualifying attributes have similar membership functions and therefore similar customer values. The paper illustrates how webshops can be extended by a fuzzy classification model. This allows webshop administrators to improve customer equity, launch loyalty programs, automate mass customization and personalization issues, and refine marketing campaigns to maximize the real value of the customers. Povzetek: Razvit je model za dolo?anje lojalnosti internetnih kupcev. 1

Andreas Meier; Nicolas Werro

2007-01-01T23:59:59.000Z

138

Classification of Bidens in wheat farms  

Science Conference Proceedings (OSTI)

Bidens pilosa L. (commonly known as cobbler's peg) is an annual broad leaf weed widely distributed in tropical and subtropical regions of the world and is reported to be a weed of 31 crops, including wheat. Automatic detection of Bidens in ... Keywords: Bidens pilosa L, automatic detection, classification, cobbler', colour-based segmentation, precision agriculture, s peg, sensing, shape-based validation, weed detection, wheat farms

Zhengzhi Zhang; Sarath Kodagoda; David Ruiz; Jayantha Katupitiya; Gamini Dissanayake

2010-08-01T23:59:59.000Z

139

Distance Based Algorithms for Small Biomolecule Classification  

E-Print Network (OSTI)

Structural similarity search among small molecules is a standard tool used in molecular classification and insilico drug discovery. The effectiveness of this general approach depends on how well the following problems are addressed. The notion of similarity should be chosen for providing the highest level of discrimination of compounds wrt the bioactivity of interest. The data structure for performing search should be very efficient as the molecular databases of interest include several millions of compounds.

And Structural Similarity; Emre Karakoc; Artem Cherkasov; S. Cenk Sahinalp

2006-01-01T23:59:59.000Z

140

Classification of Images Using Support Vector Machines  

E-Print Network (OSTI)

Support Vector Machines (SVMs) are a relatively new supervised classification technique to the land cover mapping community. They have their roots in Statistical Learning Theory and have gained prominence because they are robust, accurate and are effective even when using a small training sample. By their nature SVMs are essentially binary classifiers, however, they can be adopted to handle the multiple classification tasks common in remote sensing studies. The two approaches commonly used are the One-Against-One (1A1) and One-Against-All (1AA) techniques. In this paper, these approaches are evaluated in as far as their impact and implication for land cover mapping. The main finding from this research is that whereas the 1AA technique is more predisposed to yielding unclassified and mixed pixels, the resulting classification accuracy is not significantly different from 1A1 approach. It is the authors conclusions that ultimately the choice of technique adopted boils down to personal preference and the uniquene...

Anthony, Gidudu; Tshilidzi, Marwala

2007-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

Cross-ontological analytics for alignment of different classification schemes  

Science Conference Proceedings (OSTI)

Quantification of the similarity between nodes in multiple electronic classification schemes is provided by automatically identifying relationships and similarities between nodes within and across the electronic classification schemes. Quantifying the similarity between a first node in a first electronic classification scheme and a second node in a second electronic classification scheme involves finding a third node in the first electronic classification scheme, wherein a first product value of an inter-scheme similarity value between the second and third nodes and an intra-scheme similarity value between the first and third nodes is a maximum. A fourth node in the second electronic classification scheme can be found, wherein a second product value of an inter-scheme similarity value between the first and fourth nodes and an intra-scheme similarity value between the second and fourth nodes is a maximum. The maximum between the first and second product values represents a measure of similarity between the first and second nodes.

Posse, Christian (Seattle, WA); Sanfilippo, Antonio P (Richland, WA); Gopalan, Banu (Cleveland, OH); Riensche, Roderick M (Richland, WA); Baddeley, Robert L (Richland, WA)

2010-09-28T23:59:59.000Z

142

CLASSIFICATION OF THE MGR HEALTH SAFETY SYSTEM  

SciTech Connect

The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) health safety system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998).

J.A. Ziegler

1999-08-31T23:59:59.000Z

143

Classification of 7-dimensional Einstein nilradicals  

E-Print Network (OSTI)

The problem of classifying Einstein solvmanifolds, or equivalently, Ricci soliton nilmanifolds, is known to be equivalent to a question on the variety of n-dimensional complex nilpotent Lie algebra laws. Namely, one has to determine which GL(n)-orbits in this variety have a critical point of the squared norm of the moment map. In dimension 7, there are 148 complex nilpotent Lie algebras and 6 curves of pairwise non-isomorphic nilpotent Lie algebras, and we give in this paper a complete classification of the aforementioned distinguished orbits.

Culma, Edison Alberto Fernndez

2011-01-01T23:59:59.000Z

144

Combining Supervised and Unsupervised Learning for GIS Classification  

E-Print Network (OSTI)

This paper presents a new hybrid learning algorithm for unsupervised classification tasks. We combined Fuzzy c-means learning algorithm and a supervised version of Minimerror to develop a hybrid incremental strategy allowing unsupervised classifications. We applied this new approach to a real-world database in order to know if the information contained in unlabeled features of a Geographic Information System (GIS), allows to well classify it. Finally, we compared our results to a classical supervised classification obtained by a multilayer perceptron.

Torres-Moreno, Juan-Manuel; Alexandre, Frdric

2009-01-01T23:59:59.000Z

145

Briefing, Classification Bulletin GEN-16 - April 2012 | Department...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Bulletin GEN-16 - April 2012 Briefing, Classification Bulletin GEN-16 - April 2012 April 2012 No Comment Policy on Classified Information in the Public Domain This briefing...

146

Updating the Classification of Geothermal Resources | Open Energy  

Open Energy Info (EERE)

Updating the Classification of Geothermal Resources Updating the Classification of Geothermal Resources Jump to: navigation, search OpenEI Reference LibraryAdd to library Conference Paper: Updating the Classification of Geothermal Resources Abstract Resource classification is a key element in the characterization, assessment and development of energy resources, including geothermal energy. Stakeholders at all levels of government, within the geothermal industry, and among the general public need to be able to use and understand consistent terminology when addressing geothermal resource issues such as location, quality, feasibility of development, and potential impacts. This terminology must encompass both the fundamentally geological nature of geothermal resources and the practical technological and economic

147

A Note on Multistage Methods for Freight Train Classification  

E-Print Network (OSTI)

Nov 21, 2012 ... Abstract: The paper Multistage Methods for Freight Train Classification by Jacob et al. ([2]) provides a great insight to the theory and practice...

148

A Note on Multistage Methods for Freight Train Classification  

E-Print Network (OSTI)

The paper Multistage Methods for Freight Train Classification by Jacob et al. ... In [2] many relevant shunting situations (e.g. single or multiple inbound trains,...

149

Vehicle Detection and Classification from a LIDAR equipped probe vehicle.  

E-Print Network (OSTI)

??Vehicle detection and classification is important in traffic analysis and management. Various sensing techniques can be used in this field, while most preceding work relies (more)

Yang, Rong

2009-01-01T23:59:59.000Z

150

A classification scheme for LWR fuel assemblies  

Science Conference Proceedings (OSTI)

With over 100 light water nuclear reactors operating nationwide, representing designs by four primary vendors, and with reload fuel manufactured by these vendors and additional suppliers, a wide variety of fuel assembly types are in existence. At Oak Ridge National Laboratory, both the Systems Integration Program and the Characteristics Data Base project required a classification scheme for these fuels. This scheme can be applied to other areas and is expected to be of value to many Office of Civilian Radioactive Waste Management programs. To develop the classification scheme, extensive information on the fuel assemblies that have been and are being manufactured by the various nuclear fuel vendors was compiled, reviewed, and evaluated. It was determined that it is possible to characterize assemblies in a systematic manner, using a combination of physical factors. A two-stage scheme was developed consisting of 79 assembly types, which are grouped into 22 assembly classes. The assembly classes are determined by the general design of the reactor cores in which the assemblies are, or were, used. The general BWR and PWR classes are divided differently but both are based on reactor core configuration. 2 refs., 15 tabs.

Moore, R.S.; Williamson, D.A.; Notz, K.J.

1988-11-01T23:59:59.000Z

151

SED: supervised experimental design and its application to text classification  

Science Conference Proceedings (OSTI)

In recent years, active learning methods based on experimental design achieve state-of-the-art performance in text classification applications. Although these methods can exploit the distribution of unlabeled data and support batch selection, they cannot ... Keywords: active learning, convex optimization, supervised experimental design, text classification

Yi Zhen; Dit-Yan Yeung

2010-07-01T23:59:59.000Z

152

CIM: A Reliable Metric for Evaluating Program Phase Classifications  

E-Print Network (OSTI)

CIM: A Reliable Metric for Evaluating Program Phase Classifications Sreekumar V. Kodakara, Jinpyo Interval of estimated Mean (CIM), a metric based on statistical sampling theory, to evaluate the quality of estimated Mean (CIM) correctly estimates the quality of phase classification with a meaningful statistical

Minnesota, University of

153

Post-processing of associative classification rules using closed sets  

Science Conference Proceedings (OSTI)

For a classifier, besides classification capability, its size is another vital aspect. In pursuit of high performance, many classifiers do not take into consideration their sizes and contain numerous both essential and insignificant rules. This, however, ... Keywords: Classification, Closed set, Data mining, Post-processing, Rule pruning

Huawen Liu; Jigui Sun; Huijie Zhang

2009-04-01T23:59:59.000Z

154

Vibration-based terrain classification for electric powered wheelchairs  

Science Conference Proceedings (OSTI)

Automated terrain classification for electric powered wheelchairs (EPWs) has two primary motivations. First, certain terrains (e.g., sand and gravel) make wheelchair mobility more difficult. To alleviate this problem the wheelchair control system can ... Keywords: advanced wheelchair systems, electric powered wheelchairs, terrain classification, vibrations

Eric Coyle; Emmanuel G. Collins, Jr.; Edmond DuPont; Dan Ding; Hongwu Wang; Rory A. Cooper; Garrett Grindle

2008-04-01T23:59:59.000Z

155

Comparison of metrics for feature selection in imbalanced text classification  

Science Conference Proceedings (OSTI)

Abstract: Class imbalance problems are often encountered in real applications of automatic text classifications especially at the so-called ''one-against-all'' settings and thus handling the problem with satisfactory performance is substantially important. ... Keywords: Combination framework, Feature selection, Imbalanced data, Poisson distribution, Text classification, k-NN classifier

Hiroshi Ogura; Hiromi Amano; Masato Kondo

2011-05-01T23:59:59.000Z

156

Multi-view gender classification using hierarchical classifiers structure  

Science Conference Proceedings (OSTI)

In this paper, we propose a hierarchical classifier structure for gender classification based on facial images by reducing the complexity of the original problem. In the proposed framework, we first train a classifier, which will properly divide the ... Keywords: gender classification, hierarchical classifiers, multi-view facial images

Tian-Xiang Wu; Bao-Liang Lu

2010-11-01T23:59:59.000Z

157

A fuzzy binary neural network for interpretable classifications  

Science Conference Proceedings (OSTI)

Classification is probably the most frequently encountered problem in machine learning (ML). The most successful ML techniques like multi-layer perceptrons or support vector machines constitute very complex systems and the underlying reasoning processes ... Keywords: Fuzzy reasoning, Machine learning, Neural networks, Supervised classification

Robert Meyer, Simon O'keefe

2013-12-01T23:59:59.000Z

158

Context-aware systems: A literature review and classification  

Science Conference Proceedings (OSTI)

Nowadays, numerous journals and conferences have published articles related to context-aware systems, indicating many researchers' interest. Therefore, the goal of this paper is to review the works that were published in journals, suggest a new classification ... Keywords: Classification framework, Context-aware systems, Literature reviews

Jong-yi Hong; Eui-ho Suh; Sung-Jin Kim

2009-05-01T23:59:59.000Z

159

Spatio-temporal optical flow statistics (STOFS) for activity classification  

Science Conference Proceedings (OSTI)

This paper presents a novel descriptor for activity classification. The intuition behind the descriptor is "learning" statistics of optical flow histograms (as opposed to learning "raw" histograms). Towards this end, an activity descriptor capturing ... Keywords: action classification, flow statistics, motion descriptor

Vignesh Jagadeesh; S. Karthikeyan; B. S. Manjunath

2010-12-01T23:59:59.000Z

160

Document classification utilising ontologies and relations between documents  

Science Conference Proceedings (OSTI)

Two major types of relational information can be utilized in automatic document classification as background information: relations between terms, such as ontologies, and relations between documents, such as web links or citations in articles. We introduce ... Keywords: document classification, ontologies, relational models

Katariina Nyberg; Tapani Raiko; Teemu Tiinanen; Eero Hyvnen

2010-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

An one-class classification approach to detecting porn image  

Science Conference Proceedings (OSTI)

Porn image detection has been treated as a binary classification task in previous learning based studies. In binary classification methods, the training samples cannot be collected broadly enough, which will limit the generalization ability of the classifiers. ... Keywords: BoW model, one-class SVM, porn image detection, random forest

Yi Liu; Chuangbai Xiao; Zhe Wang; Chunxiao Bian

2012-11-01T23:59:59.000Z

162

MC3196 Detonator Shipping Package Hazard Classification Assessment  

SciTech Connect

An investigation was made to determine whether the MC3196 detonator should be assigned a DOT hazard classification of Detonating Fuze, Class C Explosives per 49 CFR 173.113. This study covers the Propagation Test and the External Heat Test as approved by DOE Albuquerque Operations Office. Test data led to the recommeded hazard classification of detonating fuze, Class C explosives.

Jones; Robert B.

1979-05-31T23:59:59.000Z

163

A new parallel tool for classification of remotely sensed imagery  

Science Conference Proceedings (OSTI)

In this paper, we describe a new tool for classification of remotely sensed images. Our processing chain is based on three main parts: (1) pre-processing, performed using morphological profiles which model both the spatial (high resolution) and the spectral ... Keywords: Google maps' engine, Graphics processing units (GPUs), Information extraction, Parallel processing, Satellite image classification

Sergio Bernab; Antonio Plaza; Prashanth Reddy Marpu; Jon Atli Benediktsson

2012-09-01T23:59:59.000Z

164

Evolutionary-based selection of generalized instances for imbalanced classification  

Science Conference Proceedings (OSTI)

In supervised classification, we often encounter many real world problems in which the data do not have an equitable distribution among the different classes of the problem. In such cases, we are dealing with the so-called imbalanced data sets. One of ... Keywords: Evolutionary algorithms, Imbalanced classification, Instance selection, Nested generalized exemplar learning, Rule induction

Salvador Garc?a; Joaqu?n Derrac; Isaac Triguero; Cristbal J. Carmona; Francisco Herrera

2012-02-01T23:59:59.000Z

165

Large margin mixture of AR models for time series classification  

Science Conference Proceedings (OSTI)

In this paper, we propose the large margin autoregressive (LMAR) model for classification of time series patterns. The parameters of the generative AR models for different classes are estimated using the margin of the boundaries of AR models as the optimization ... Keywords: Generative and discriminative hybrid models, Large margin autoregressive model, Large margin mixture autoregressive model, Outlier detection, Rejection option, Time series classification

B. Venkataramana Kini; C. Chandra Sekhar

2013-01-01T23:59:59.000Z

166

An Evolutionary Artificial Neural Network for Medical Pattern Classification  

Science Conference Proceedings (OSTI)

In this paper, a novel evolutionary artificial neural network based on the integration between Fuzzy ARTMAP (FAM) and a Hybrid Genetic Algorithm (HGA) is proposed for tackling medical pattern classification tasks. To assess the effectiveness of the proposed ... Keywords: Fuzzy ARTMAP, Hybrid Genetic Algorithms, Medical Decision Support, Pattern Classification

Shing Chiang Tan; Chee Peng Lim; Kay Sin Tan; Jose C. Navarro

2009-12-01T23:59:59.000Z

167

Information---Theoretic Multiclass Classification Based on Binary Classifiers  

Science Conference Proceedings (OSTI)

In this paper, we consider the multiclass classification problem based on sets of independent binary classifiers. Each binary classifier represents the output of a quantized projection of training data onto a randomly generated orthonormal basis vector ... Keywords: Classification, Coding matrix design, Complexity, Maximum number of classes, Reliability

Sviatoslav Voloshynovskiy; Oleksiy Koval; Fokko Beekhof; Taras Holotyak

2011-12-01T23:59:59.000Z

168

RapidRadio: Signal Classification and Radio Deployment Framework  

Science Conference Proceedings (OSTI)

In this article, the RapidRadio framework for signal classification and receiver deployment is discussed. The framework is a productivity-enhancing tool that reduces the required knowledge base for implementing a receiver on an FPGA-based SDR platform. ... Keywords: FPGA, signal classification, system synthesis

Jorge A. Surs; Adolfo Recio; Peter Athanas

2012-08-01T23:59:59.000Z

169

An incremental structured part model for image classification  

Science Conference Proceedings (OSTI)

The state-of-the-art image classification methods usually require many training samples to achieve good performance. To tackle this problem, we present a novel incremental method in this paper, which learns a part model to classify objects using only ... Keywords: image classification, incremental learning, semantic parts, structural relationship

Huigang Zhang; Xiao Bai; Jian Cheng; Jun Zhou; Huijie Zhao

2012-11-01T23:59:59.000Z

170

A co-evolving decision tree classification method  

Science Conference Proceedings (OSTI)

Decision tree classification provides a rapid and effective method of categorising datasets. Many algorithmic methods exist for optimising decision tree structure, although these can be vulnerable to changes in the training dataset. An evolutionary method ... Keywords: Classification, Data mining, Decision tree, Evolutionary computation, Simulated annealing

M. J. Aitkenhead

2008-01-01T23:59:59.000Z

171

Statement map: reducing web information credibility noise through opinion classification  

Science Conference Proceedings (OSTI)

On the Internet, users often encounter noise in the form of spelling errors or unknown words, however, dishonest, unreliable, or biased information also acts as noise that makes it difficult to find credible sources of information. As people come to ... Keywords: STATEMENT MAP, credibility analysis, discourse processing, opinion classification, semantic relation classification, structural alignment

Koji Murakami; Eric Nichols; Junta Mizuno; Yotaro Watanabe; Shouko Masuda; Hayato Goto; Megumi Ohki; Chitose Sao; Suguru Matsuyoshi; Kentaro Inui; Yuji Matsumoto

2010-10-01T23:59:59.000Z

172

Hierarchical distributed data classification in wireless sensor networks  

Science Conference Proceedings (OSTI)

Wireless sensor networks promise an unprecedented opportunity to monitor physical environments via inexpensive wireless embedded devices. Given the sheer amount of sensed data, efficient classification of them becomes a critical task in many sensor network ... Keywords: C4.5, Classification, Decision tree, Wireless sensor network

Xu Cheng; Ji Xu; Jian Pei; Jiangchuan Liu

2010-07-01T23:59:59.000Z

173

North American Industry Classification System (NAICS) Search Tool |  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

North American Industry Classification System (NAICS) Search Tool North American Industry Classification System (NAICS) Search Tool North American Industry Classification System (NAICS) Search Tool The North American Industry Classification System (NAICS) is the standard used by Federal statistical agencies in classifying business establishments for the purpose of collecting, analyzing, and publishing statistical data related to the U.S. business economy. NAICS was developed under the auspices of the Office of Management and Budget, and adopted in 1997 to replace the Standard Industrial Classification system. Through our website, you can search for procurement opportunities using your company's NAICS code, and you can learn more about the history of purchasing for your NAICS code at the Department. Visit our Industry Information page to learn more about our procurements by

174

Increasing soft classification accuracy through the use of an ensemble of classifiers  

Science Conference Proceedings (OSTI)

Although soft classification analyses can reduce problems such as those associated with mixed pixels that impact negatively on conventional hard classifications their accuracy is often low. One approach to increasing the accuracy of soft classifications ...

H. T. X. Doan; G. M. Foody

2007-10-01T23:59:59.000Z

175

National Security Information Classification Guidance Fundamental Review, June 2012  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Security Security Information Fundamental Classification Guidance Review Report to the Information Security Oversight Office June 2012 United States Department of Energy Washington, DC 20585 Department of Energy | June 2012 National Security Information Fundamental Classification Guidance Review | Page iii Executive Summary Section 1.9 of Executive Order (E.O.) 13526, Classified National Security Information, dated December 29, 2009, directs agency heads to complete a comprehensive review of agency classification guides to ensure they reflect current circumstances and to identify classified information that no longer requires protection and can be declassified. To meet this requirement, the Department of Energy (DOE), under the direction of the Senior Agency Official, devoted

176

Fusion for Evaluation of Image Classification in Uncertain Environments  

E-Print Network (OSTI)

We present in this article a new evaluation method for classification and segmentation of textured images in uncertain environments. In uncertain environments, real classes and boundaries are known with only a partial certainty given by the experts. Most of the time, in many presented papers, only classification or only segmentation are considered and evaluated. Here, we propose to take into account both the classification and segmentation results according to the certainty given by the experts. We present the results of this method on a fusion of classifiers of sonar images for a seabed characterization.

Martin, Arnaud

2008-01-01T23:59:59.000Z

177

Investigating isomorphs with the topological cluster classification  

E-Print Network (OSTI)

Isomorphs are lines in the density-temperature plane of certain "strongly-correlating" or "Roskilde simple" liquids where two-point structure and dynamics have been shown to be close to identical up to a scale transformation. Here we consider such a liquid, a Lennard-Jones glassformer, and investigate the behavior along isomorphs of higher-order structural and dynamical correlations. We then consider an inverse power law reference system mapped to the Lennard-Jones system [Pedersen et al., Phys. Rev. Lett. 105, 157801 (2010)]. Using the topological cluster classification to identify higher-order structures, in both systems we find bicapped square anti-prisms, which are known to be a locally favored structure in the Lennard-Jones glassformer. The population of these locally favored structures is up to 80% higher in the Lennard-Jones system than the equivalent inverse power law system. The structural relaxation time of the two systems, on the other hand, is almost identical, and the four-point dynamical susceptibility is marginally higher in the inverse power law system. Upon cooling the lifetime of the locally favored structures in the Lennard-Jones system are up to 40% higher relative to the reference system.

Alex Malins; Jens Eggers; C. Patrick Royall

2013-07-21T23:59:59.000Z

178

WNClASSIflfO CLASSIFICATION CANCELLED  

NLE Websites -- All DOE Office Websites (Extended Search)

WNClASSIflfO WNClASSIflfO ^ CLASSIFICATION CANCELLED DATE FEB 1 6 1957 For The Atomic Cnargy Commission *74/^ Cl

179

Classification of breast computed tomography data  

Science Conference Proceedings (OSTI)

Differences in breast tissue composition are important determinants in assessing risk, identifying disease in images and following changes over time. This paper presents an algorithm for tissue classification that separates breast tissue into its three primary constituents of skin, fat and glandular tissue. We have designed and built a dedicated breast CT scanner. Fifty-five normal volunteers and patients with mammographically identified breast lesions were scanned. Breast CT voxel data were filtered using a 5 pt median filter and the image histogram was computed. A two compartment Gaussian fit of histogram data was used to provide an initial estimate of tissue compartments. After histogram analysis, data were input to region-growing algorithms and classified as to belonging to skin, fat or gland based on their value and architectural features. Once tissues were classified, a more detailed analysis of glandular tissue patterns and a more quantitative analysis of breast composition was made. Algorithm performance assessment demonstrated very good or excellent agreement between algorithm and radiologist observers in 97.7% of the segmented data. We observed that even in dense breasts the fraction of glandular tissue seldom exceeded 50%. For most individuals the composition is better characterized as being a 70% (fat)-30% (gland) composition than a 50% (fat)-50% (gland) composition.

Nelson, Thomas R.; Cervino, Laura I.; Boone, John M.; Lindfors, Karen K. [Department of Radiology, University of California, San Diego, La Jolla, California 92037-0610 (United States); University of California Davis Medical Center, 4860 Y Street, Ambulatory Care Center Suite 3100, Sacramento, California 95817 (United States)

2008-03-15T23:59:59.000Z

180

A hybrid classification scheme for mining multisource geospatial data  

Science Conference Proceedings (OSTI)

Supervised learning methods such as Maximum Likelihood (ML) are often used in land cover (thematic) classification of remote sensing imagery. ML classifier relies exclusively on spectral characteristics of thematic classes whose statistical distributions ... Keywords: EM, MLC, Semi-supervised learning

Ranga Raju Vatsavai; Budhendra Bhaduri

2011-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

Office of Classification CommuniQu- Year: 2008  

Energy.gov (U.S. Department of Energy (DOE))

Office of Classification newsletters for the year 2008, consisting of the following issues: CommuniQu 2008-1 - March 2008 CommuniQu 2008-2 - September 2008

182

A Hybrid System for Learning Sunspot Recognition and Classification  

Science Conference Proceedings (OSTI)

Sunspots observation and classification are important tasks for solar astronomers. The activity of sunspots can give clues to the timing of solar flares and the solar weather in general. This paper describes a hybrid system for automatic sunspot recognition ...

Trung Thanh Nguyen; Claire P. Willis; Derek J. Paddon; Hung Son Nguyen

2006-11-01T23:59:59.000Z

183

Seabed Classification Through Multifractal Analysis of Sidescan Sonar Imagery  

E-Print Network (OSTI)

This paper presents a technique for the classification and analysis of seabed sediments from sidescan sonar image, the origins of which lie in the body of fractal theory. Six seabed types were analysed, namely clay, mud, sand, gravel, stones and rock. These data sets have previously been analysed by several authors who have used techniques based on the power spectrum. The method proposed in this paper allows frequency information to be obtained but without the use of large windows which are generally required for frequency domain measurements. Results are presented for the classification of individual ground-truthed sediments and the segmentation of composite images containing these sediments. Correct classification rates of greater then 99% have been obtained and good segmentation accuracy achieved. Keywords:- swathe seabed classification, sidescan sonar, fractals. Defence Research Agency, Newton's Road, Weymoth, Dorset y Department of Computing and Electrical Engineering, Heriot...

D.R. Carmichael; L.M. Linnett; S.J. Clarke; B.R. Calder

1996-01-01T23:59:59.000Z

184

Classification of linearly compact simple Jordan and generalized Poisson superalgebras  

E-Print Network (OSTI)

We classify all linearly compact simple Jordan superalgebras over an algebraically closed field of characteristic zero. As a corollary, we deduce the classification of all linearly compact unital simple generalized Poisson superalgebras.

Nicoletta Cantarini; Victor G. Kac; To Ernest; Borisovich Vinberg

2006-01-01T23:59:59.000Z

185

Optimization of an Instance-Based GOES Cloud Classification Algorithm  

Science Conference Proceedings (OSTI)

An instance-based nearest-neighbor algorithm was developed for a Geostationary Operational Environmental Satellite (GOES) cloud classifier. Expert-labeled samples serve as the training sets for the various GOES image classification scenes. The ...

Richard L. Bankert; Robert H. Wade

2007-01-01T23:59:59.000Z

186

The Classification of Ambiguous Ice Particle Shadowgraphs by Consensus  

Science Conference Proceedings (OSTI)

A major impediment to the development of computer algorithms for the automatic classification of ice particle types found in the atmosphere as measured by a Particle Measuring System two-dimensional probe is the difficulty of obtaining training ...

Rosemary M. Dyer; Morton Glass; Herbert E. Hunter

1985-12-01T23:59:59.000Z

187

Office of Classification CommuniQu- Year: 2005  

Energy.gov (U.S. Department of Energy (DOE))

Office of Classification newsletters for the year 2005, consisting of the following issues: February 2005 - 2005-1 May 2005 - 2005-2 August 2005 - 2005-3 November 2005 - 2005-4

188

Simple Fully Automated Group Classification on Brain fMRI  

SciTech Connect

We propose a simple, well grounded classification technique which is suited for group classification on brain fMRI data sets that have high dimensionality, small number of subjects, high noise level, high subject variability, imperfect registration and capture subtle cognitive effects. We propose threshold-split region as a new feature selection method and majority voteas the classification technique. Our method does not require a predefined set of regions of interest. We use average acros ssessions, only one feature perexperimental condition, feature independence assumption, and simple classifiers. The seeming counter-intuitive approach of using a simple design is supported by signal processing and statistical theory. Experimental results in two block design data sets that capture brain function under distinct monetary rewards for cocaine addicted and control subjects, show that our method exhibits increased generalization accuracy compared to commonly used feature selection and classification techniques.

Honorio, J.; Goldstein, R.; Honorio, J.; Samaras, D.; Tomasi, D.; Goldstein, R.Z.

2010-04-14T23:59:59.000Z

189

Contemporary and historical classification of crop types in Arizona  

Science Conference Proceedings (OSTI)

This research compares three different classification algorithms for mapping crops in Pinal County, Arizona, using both present and historical image data. The study area lacked past crop maps, and farmers were dealing with the risk of evolution of resistance ...

KyleA. Hartfield, StuartE. Marsh, ChristaD. Kirk, Yves Carrire

2013-09-01T23:59:59.000Z

190

A mood-based music classification and exploration system  

E-Print Network (OSTI)

Mood classification of music is an emerging domain of music information retrieval. In the approach presented here features extracted from an audio file are used in combination with the affective value of song lyrics to map ...

Meyers, Owen Craigie

2007-01-01T23:59:59.000Z

191

An indexing approach for speeding-up image classification  

Science Conference Proceedings (OSTI)

One of the most common computer vision tasks is that of recognizing the category of objects present in a given image. Previous work has mostly focused on building accurate classifiers based on carefully selected features. Classification is often carried ...

Rahul Jain; Praveen M. Sudha; Sankar K. Pramod; C. V. Jawahar

2010-12-01T23:59:59.000Z

192

Object-Centric spatial pooling for image classification  

Science Conference Proceedings (OSTI)

Spatial pyramid matching (SPM) based pooling has been the dominant choice for state-of-art image classification systems. In contrast, we propose a novel object-centric spatial pooling (OCP) approach, following the intuition that knowing the location ...

Olga Russakovsky; Yuanqing Lin; Kai Yu; Li Fei-Fei

2012-10-01T23:59:59.000Z

193

Bayesian Classification of Astronomical Objects -- and what is behind it  

E-Print Network (OSTI)

We present a Bayesian method for the identification and classification of objects from sets of astronomical catalogs, given a predefined classification scheme. Identification refers here to the association of entries in different catalogs to a single object, and classification refers to the matching of the associated data set to a model selected from a set of parametrized models of different complexity. By the virtue of Bayes' theorem, we can combine both tasks in an efficient way, which allows a largely automated and still reliable way to generate classified astronomical catalogs. A problem to the Bayesian approach is hereby the handling of exceptions, for which no likelihoods can be specified. We present and discuss a simple and practical solution to this problem, emphasizing the role of the "evidence" term in Bayes' theorem for the identification of exceptions. Comparing the practice and logic of Bayesian classification to Bayesian inference, we finally note some interesting links to concepts of the philos...

Rachen, Jrg P

2013-01-01T23:59:59.000Z

194

Cloud Ice Crystal Classification Using a 95-GHz Polarimetric Radar  

Science Conference Proceedings (OSTI)

Two algorithms are presented for ice crystal classification using 95-GHz polarimetric radar observables and air temperature (T). Both are based on a fuzzy logic scheme. Ice crystals are classified as columnar crystals (CC), planar crystals (PC), ...

K. Aydin; J. Singh

2004-11-01T23:59:59.000Z

195

The CALIPSO Automated Aerosol Classification and Lidar Ratio Selection Algorithm  

Science Conference Proceedings (OSTI)

Descriptions are provided of the aerosol classification algorithms and the extinction-to-backscatter ratio (lidar ratio) selection schemes for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) aerosol products. One ...

Ali H. Omar; David M. Winker; Mark A. Vaughan; Yongxiang Hu; Charles R. Trepte; Richard A. Ferrare; Kam-Pui Lee; Chris A. Hostetler; Chieko Kittaka; Raymond R. Rogers; Ralph E. Kuehn; Zhaoyan Liu

2009-10-01T23:59:59.000Z

196

The class imbalance problem in TLC image classification  

Science Conference Proceedings (OSTI)

The paper presents the methodology developed to solve the class imbalanced problem that occurs in the classification of Thin-Layer Chromatography (TLC) images. The proposed methodology is based on re-sampling, and consists in the undersampling of the ...

Antnio V. Sousa; Ana Maria Mendona; Aurlio Campilho

2006-09-01T23:59:59.000Z

197

Classification of high dimensional and imbalanced hyperspectral imagery data  

Science Conference Proceedings (OSTI)

The present paper addresses the problem of the classification of hyperspectral images with multiple imbalanced classes and very high dimensionality. Class imbalance is handled by resampling the data set, whereas PCA is applied to reduce the number of ...

Vicente Garca; J. Salvador Snchez; Ramn A. Mollineda

2011-06-01T23:59:59.000Z

198

Group classification for the nonlinear heat conductivity equation  

E-Print Network (OSTI)

Symmetry properties of the nonlinear heat conductivity equations of the general form $u_t=[E(x,u)u_x]_x + H(x,u)$ is studied. The point symmetry analysis of these equations is considered as well as an equivalence classification which admits an extension by one dimension of the principal Lie algebra of the equation. The invariant solutions of equivalence transformations and classification of the nonlinear heat conductivity equations among with additional operators are also given.

Mahdipour-Shirayeh, Ali

2009-01-01T23:59:59.000Z

199

An Optimization-Based Classification Approach with the Non-additive Measure  

Science Conference Proceedings (OSTI)

Optimization-based classification approaches have well been used for decision making problems, such as classification in data mining. It considers that the contributions from all the attributes for the classification model equals to the joint individual ... Keywords: Classification, Data Mining, Non-additive Measure, Optimization

Nian Yan; Zhengxin Chen; Rong Liu; Yong Shi

2008-06-01T23:59:59.000Z

200

Safety classification of systems 300 area N reactor fuel supply facilities  

Science Conference Proceedings (OSTI)

Classification of the Fuel Supply Shutdown (FSS) safety systems, equipment, and components is presented.

Benecke, M.W., Westinghouse Hanford, Richland, WA

1997-10-10T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets q  

E-Print Network (OSTI)

of classification such as fraud detection [16], detection of oil spills from satellite images [31], prediction

Granada, Universidad de

202

A method for identification and classification of medicinal plant images based on level set segmentation and SVM classification  

Science Conference Proceedings (OSTI)

This paper presents a methodology for identification and classification of images of the medicinal plants based on level set segmentation. The medicinal plants are identified using structural features, namely, height, shape, size of leafy part, flowers, ...

Suvarna S. Nandyal; Basavaraj S. Anami; A. Govardhan; P. S. Hiremath

2012-04-01T23:59:59.000Z

203

REGIONAL-SCALE WIND FIELD CLASSIFICATION EMPLOYING CLUSTER ANALYSIS  

DOE Green Energy (OSTI)

The classification of time-varying multivariate regional-scale wind fields at a specific location can assist event planning as well as consequence and risk analysis. Further, wind field classification involves data transformation and inference techniques that effectively characterize stochastic wind field variation. Such a classification scheme is potentially useful for addressing overall atmospheric transport uncertainty and meteorological parameter sensitivity issues. Different methods to classify wind fields over a location include the principal component analysis of wind data (e.g., Hardy and Walton, 1978) and the use of cluster analysis for wind data (e.g., Green et al., 1992; Kaufmann and Weber, 1996). The goal of this study is to use a clustering method to classify the winds of a gridded data set, i.e, from meteorological simulations generated by a forecast model.

Glascoe, L G; Glaser, R E; Chin, H S; Loosmore, G A

2004-06-17T23:59:59.000Z

204

Groundwater Classification and Standards (North Carolina) | Department of  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Classification and Standards (North Carolina) Classification and Standards (North Carolina) Groundwater Classification and Standards (North Carolina) < Back Eligibility Commercial Industrial Construction Transportation Savings Category Alternative Fuel Vehicles Hydrogen & Fuel Cells Buying & Making Electricity Water Home Weatherization Solar Wind Program Info State North Carolina Program Type Environmental Regulations Siting and Permitting Provider Department of Environment and Natural Resources The rules established in this Subchapter 2L of North Carolina Administrative Code Title 15A are intended to maintain and preserve the quality of the groundwaters, prevent and abate pollution and contamination of the waters of the state, protect public health, and permit management of the groundwaters for their best usage by the citizens of North Carolina. It

205

Topological classification of crystalline insulators with space group symmetry  

Science Conference Proceedings (OSTI)

We show that in crystalline insulators, space group symmetry alone gives rise to a topological classification based on the discretization of electric polarization. Using C3 rotational symmetry as an example, we first prove that the polarization is discretized into three distinct classes, i.e., it can only take three inequivalent values. We then prove that these classes are topologically distinct. Therefore, a Z3 topological classification exists, with polarization as a topological class index. A concrete tight-binding model is derived to demonstrate the Z3 topological phase transition. Using first-principles calculations, we identify graphene on a BN substrate as a possible candidate to realize these Z3 topological states. To complete our analysis, we extend the classification of band structures to all 17 two-dimensional space groups. This work will contribute to a complete theory of symmetry-conserved topological phases and also elucidate topological properties of graphenelike systems.

Jadaun, Priyamvada [University of Texas at Austin; Xiao, Di [Carnegie Mellon University (CMU); Niu, Q. [University of Texas at Austin; Banerjee, Sanjay K. [University of Texas at Austin

2013-01-01T23:59:59.000Z

206

Industrial Steam Power Cycles Final End-Use Classification  

E-Print Network (OSTI)

Final end uses of steam include two major classifications: those uses that condense the steam against heat transfer surfaces to provide heat to an item of process or service equipment; and those that require a mass flow of steam for stripping, dilution, a reaction ingredient, etc. These classifications are termed 'Btu' loads or 'Pound' loads. Some final end uses of steam are actually a combination of the two. The classification of steam loads is extremely important to the overall economics of the industrial plant steam system. These economic effects are explained in detail as they impact on both the thermal efficiency and the heat power cycle efficiency of an industrial system. The use of a powerful steam system mass and energy modeling program called MESA (Modular Energy System Analyzer, The MESA Company) in identifying and accurately evaluating these effects is described.

Waterland, A. F.

1983-01-01T23:59:59.000Z

207

A Brief Summary of Dictionary Learning Based Approach for Classification  

E-Print Network (OSTI)

This note presents some representative methods which are based on dictionary learning (DL) for classification. We do not review the sophisticated methods or frameworks that involve DL for classification, such as online DL and spatial pyramid matching (SPM), but rather, we concentrate on the direct DL-based classification methods. Here, the "so-called direct DL-based method" is the approach directly deals with DL framework by adding some meaningful penalty terms. By listing some representative methods, we can roughly divide them into two categories, i.e. (1) directly making the dictionary discriminative and (2) forcing the sparse coefficients discriminative to push the discrimination power of the dictionary. From this taxonomy, we can expect some extensions of them as future researches.

Shu, Kong

2012-01-01T23:59:59.000Z

208

OFFICE OF CLASSIFICATION OFFICE OF HEALTH, SAFETY AND SECURITY  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

CLASSIFICATION CLASSIFICATION OFFICE OF HEALTH, SAFETY AND SECURITY UNDERSTANDING U U O O SE NLY U.S. DEPARTMENT OF ENERGY O O FFICIAL EXEMPTION 3 - Statutory Exemption Examples: Cooperative Research and Development Agreement Information Export Controlled Information EXEMPTION 4 - Commercial/Proprietary Examples: Trade secrets Scientific and manufacturing processes Bids, contracts, or proposals Agency credit card or bank account numbers Security measures for commercial entities performing Government work EXEMPTION 5 - Privileged Information Examples: Recommendations Evaluations Appraisal results Drafts of new policies Attorney-Client exchanges EXEMPTION 6 - Personal Privacy Examples: Social security numbers Date of birth associated with an individual

209

Expanded bag of words representation for object classification  

Science Conference Proceedings (OSTI)

Currently, the bag of visual words (BOW) representation has received wide applications in object categorization. However, the BOW representation ignores the dependency relationship among visual words, which could provide informative knowledge to understand ... Keywords: bag of words, object classification, query expansion, spatial correlation

Tinglin Liu; Jing Liu; Qinshan Liu; Hanqing Lu

2009-11-01T23:59:59.000Z

210

SIC (MUltiple SIgnal Classification) CSP (Cross-power Spectrum Phase)  

E-Print Network (OSTI)

2ch CSP ( ) 1 MU- SIC (MUltiple SIgnal Classification) CSP (Cross- power Spectrum Phase) [1, 2, 3, 4] [5, 6] [7, 8, 9, 10] [7] CSP CSP [8] [9] CSP [10] Estimation of talker's head orientation based (Kobe univ.) [11] 2ch CSP CSP CSP CSP 2 CSP GCC-PHAT (Generalized Cross- Correlation PHAse Transform

Takiguchi, Tetsuya

211

When Van Gogh meets Mandelbrot: Multifractal classification of painting's texture  

Science Conference Proceedings (OSTI)

Recently, a growing interest has emerged for examining the potential of Image Processing tools to assist Art Investigation. Simultaneously, several research works showed the interest of using multifractal analysis for the description of homogeneous textures ... Keywords: Forgery detection, Image processing, Multifractal analysis, Paintings, Period dating, Regularity, Texture classification, Van Gogh, Wavelet leaders

P. Abry; H. Wendt; S. Jaffard

2013-03-01T23:59:59.000Z

212

Editorial: Occupation inference through detection and classification of biographical activities  

Science Conference Proceedings (OSTI)

Dealing with biographical information (e.g., biography generation, answering biography-related questions, etc.) requires the identification of important activities in the life of the individual in question. While there are activities that can be used ... Keywords: Biography information, Occupation classification

Elena Filatova; John Prager

2012-06-01T23:59:59.000Z

213

Estimating Fractional Snow Cover in Mountain Environments with Fuzzy Classification  

Science Conference Proceedings (OSTI)

The disproportionate amount of water runoff from mountains to surrounding arid and semiarid lands has generated much research in snow water equivalent (SWE) modeling. A primary input in SWE models is snow covered area (SCA) which is generally obtained ... Keywords: Fuzzy Classification, GIS, Landsat ETM+, Mountain Environments, Recursive Partitioning, Remote Sensing, Snow Covered Area, Snow Water Equivalent

Clayton J. Whitesides; Matthew H. Connolly

2012-07-01T23:59:59.000Z

214

Sentence-level event classification in unstructured texts  

Science Conference Proceedings (OSTI)

The ability to correctly classify sentences that describe events is an important task for many natural language applications such as Question Answering (QA) and Text Summarisation. In this paper, we treat event detection as a sentence level text classification ... Keywords: Event detection, Information extraction, Language modeling, Machine learning

M. Naughton; N. Stokes; J. Carthy

2010-04-01T23:59:59.000Z

215

On the role of classification in patent invalidity searches  

Science Conference Proceedings (OSTI)

Searches on patents to determine prior art violations are often cumbersome and require extensive manpower to accomplish successfully. When time is constrained, an automatically generated list of candidate patents may decrease search costs and improve ... Keywords: hierarchical classification, invalidity patent search, wordnet

Christopher G. Harris; Steven Foster; Robert Arens; Padmini Srinivasan

2009-11-01T23:59:59.000Z

216

Classification of multi class dataset using wavelet power spectrum  

Science Conference Proceedings (OSTI)

Data mining techniques are widely used in many fields. One of the applications of data mining in the field of the Bioinformatics is classification of tissue samples. In the present work, a wavelet power spectrum based approach has been presented for ... Keywords: Feature selection, Multi class, RPV, Wavelet power spectrum

S. Prabakaran; Rajendra Sahu; Sekher Verma

2007-12-01T23:59:59.000Z

217

Bioclimate weather classification of Doboj for helth spa tourism  

Science Conference Proceedings (OSTI)

The goal of this paper is to show possibilities of multidisciplinary approach to the bioclimatic research in tourism, particularly in the spa tourism. In addition to the treatment of various diseases with thermal and mineral water, mud, gas and healing ... Keywords: bioclimate, biothermal weather classification, spa tourism

Milovan Pecelj; Milica Pecelj; Milisav Cutovic; Mila Pavlovic; Dragica Zivkovic; Ljiljana Zivkovic; Snezana Vujadinovic; Jelena Pecelj; Mirjana Gajic; Danimir Mandic

2011-02-01T23:59:59.000Z

218

Wind speed PDF classification using Dirichlet mixtures Rudy CALIF1  

E-Print Network (OSTI)

Wind speed PDF classification using Dirichlet mixtures Rudy CALIF1 , Richard EMILION2 , Ted'Orléans), UMR CNRS 6628 Université d'Orléans, France. Abstract: Wind energy production is very sensitive to instantaneous wind speed fluctuations. Thus rapid variation of wind speed due to changes in the local

Paris-Sud XI, Université de

219

A probabilistic approach for semi-supervised nearest neighbor classification  

Science Conference Proceedings (OSTI)

In supervised classification, we learn from a training set of labeled observations to form a decision rule for classifying all unlabeled test cases. But if the training sample is small, one may fail to extract sufficient information from that sample ... Keywords: Bayesian model averaging, Cross-validation, Likelihood function, Markov Chain Monte Carlo, Misclassification rate, Transductive learning

Anil K. Ghosh

2012-07-01T23:59:59.000Z

220

Subglacial water presence classification from polar radar data  

Science Conference Proceedings (OSTI)

Ground and airborne radar depth-sounding of the Greenland and Antarctic ice sheets have been used for many years to remotely determine characteristics such as ice thickness, subglacial topography, and mass balance of large bodies of ice. Ice coring efforts ... Keywords: Ensemble classification, Machine learning, Pattern recognition, Radar remote sensing, Subglacial water

Christopher M. Gifford; Arvin Agah

2012-06-01T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

PADMA: PArallel Data Mining Agents for scalable text classification  

Science Conference Proceedings (OSTI)

This paper introduces PADMA (PArallel Data Mining Agents), a parallel agent based system for scalable text classification. PADMA contains modules for (1) parallel data accessing operations, (2) parallel hierarchical clustering, and (3) web-based data visualization. This paper introduces the general architecture of PADMA and presents a detailed description of its different modules.

Kargupta, H.; Hamzaoglu, I.; Stafford, B. [and others

1997-03-01T23:59:59.000Z

222

Classification of co-expressed genes from DNA regulatory regions  

Science Conference Proceedings (OSTI)

The analysis of non-coding DNA regulatory regions is one of the most challenging open problems in computational biology. In this paper we investigate whether we can predict functional information about genes by using information extracted from their ... Keywords: Combinatorial and machine learning methods integration, Gene classification, Gene expression and bio-sequence data integration, Motif extraction and selection

Giulio Pavesi; Giorgio Valentini

2009-07-01T23:59:59.000Z

223

A Chinese Text Classification Approach Based on Semantic Web  

Science Conference Proceedings (OSTI)

This paper discusses a approach of Chinese text classification on semantic Web. It is given one classified technology based on the semantic concept established on the "How-net" . It extracts keywords from text, analyses the full text using the keywords ...

Shiqun Yin; Yuhui Qiu; Jike Ge; Fang Wang

2008-12-01T23:59:59.000Z

224

Office of Classification CommuniQu- Year: 2012  

Energy.gov (U.S. Department of Energy (DOE))

Office of Classification newsletters for the year 2012 consisting of the following issues: CommuniQu 2012-1 - March/April 2012 CommuniQu 2012-2 - September/October 2012 CommuniQu 2012-2 - September/October 2012 - Crossword Puzzle Solution

225

A Novel Rule Ordering Approach in Classification Association Rule Mining  

E-Print Network (OSTI)

Abstract. A Classification Association Rule (CAR), a common type of mined knowledge in Data Mining, describes an implicative co-occurring relationship between a set of binary-valued data-attributes (items) and a pre-defined class, expressed in the form of an antecedent ? consequent-class rule. Classification Association Rule Mining (CARM) is a recent Classification Rule Mining (CRM) approach that builds an Association Rule Mining (ARM) based classifier using CARs. Regardless of which particular methodology is used to build it, a classifier is usually presented as an ordered CAR list, based on an applied rule ordering strategy. Five existing rule ordering mechanisms can be identified: (1) Confidence-Support-size_of_Antecedent (CSA), (2) size_of_Antecedent-Confidence-Support (ACS), (3) Weighted Relative Accuracy (WRA), (4) Laplace Accuracy, and (5) ? 2 Testing. In this paper, we divide the above mechanisms into two groups: (i) pure support-confidence framework like, and (ii) additive score assigning like. We consequently propose a hybrid rule ordering approach by combining one approach taken from (i) and another approach taken from (ii). The experimental results show that the proposed rule ordering approach performs well with respect to the accuracy of classification.

Yanbo J. Wang; Qin Xin; Frans Coenen

2007-01-01T23:59:59.000Z

226

Multimodal Person Tracking and Attention Classification Marek P. Michalowski  

E-Print Network (OSTI)

The problems of human detection, tracking, and attention recognition can be solved more effectively tracking of humans by a laser scanner with de- tected and tracked faces from a vision system. 2. SYSTEMMultimodal Person Tracking and Attention Classification Marek P. Michalowski Carnegie Mellon

Simmons, Reid

227

SAR-based land cover classification of Kuwait  

Science Conference Proceedings (OSTI)

Orbital synthetic aperture radar (SAR) C-band data acquired by ERS-1/2 in vv-polarization and Radarsat in hh-polarization during the period from 1996 to 1999 were used to evaluate their combined information potential for classification of land cover ...

A. Y. Kwarteng; M. C. Dobson; J. Kellndorfer; R. Williams

2008-12-01T23:59:59.000Z

228

Four-Qubit Entanglement Classification from String Theory  

Science Conference Proceedings (OSTI)

We invoke the black-hole-qubit correspondence to derive the classification of four-qubit entanglement. The U-duality orbits resulting from timelike reduction of string theory from D=4 to D=3 yield 31 entanglement families, which reduce to nine up to permutation of the four qubits.

Borsten, L.; Dahanayake, D.; Duff, M. J.; Rubens, W. [Theoretical Physics, Blackett Laboratory, Imperial College London, London SW7 2AZ (United Kingdom); Marrani, A. [Stanford Institute for Theoretical Physics, Stanford University, Stanford, California 94305-4060 (United States)

2010-09-03T23:59:59.000Z

229

Classification of functional voice disorders based on phonovibrograms  

Science Conference Proceedings (OSTI)

Objective: This work presents a computer-aided method for automatically and objectively classifying individuals with healthy and dysfunctional vocal fold vibration patterns as depicted in clinical high-speed (HS) videos of the larynx. Methods: By employing ... Keywords: Diagnosis support system, Feature extraction, Laryngeal high-speed video, Machine learning, PVG, Pattern recognition, Phonovibrogram, Voice pathology classification

Daniel Voigt; Michael Dllinger; Thomas Braunschweig; Anxiong Yang; Ulrich Eysholdt; Jrg Lohscheller

2010-05-01T23:59:59.000Z

230

Classification of raster maps for automatic feature extraction  

Science Conference Proceedings (OSTI)

Raster maps are widely available and contain useful geographic features such as labels and road lines. To extract the geographic features, most research work relies on a manual step to first extract the foreground pixels from the maps using the distinctive ... Keywords: color histogram, color moments, color-coherence vectors, content-based image retrieval, image similarity, luminance-boundary histogram, raster map classification

Yao-Yi Chiang; Craig A. Knoblock

2009-11-01T23:59:59.000Z

231

Survey on speech emotion recognition: Features, classification schemes, and databases  

Science Conference Proceedings (OSTI)

Recently, increasing attention has been directed to the study of the emotional content of speech signals, and hence, many systems have been proposed to identify the emotional content of a spoken utterance. This paper is a survey of speech emotion classification ... Keywords: Archetypal emotions, Dimensionality reduction techniques, Emotional speech databases, Speech emotion recognition, Statistical classifiers

Moataz El Ayadi; Mohamed S. Kamel; Fakhri Karray

2011-03-01T23:59:59.000Z

232

Classification of Commodity Price Forecast With Random Forests and Bayesian  

E-Print Network (OSTI)

Classification of Commodity Price Forecast Sentiment With Random Forests and Bayesian Optimization, Morgan Stanley or Merrill Lynch produce24 price forecasting and reports to predict the direction on the sentiment of price39 forecasts and reports for commodities such as gold, natural gas or most commonly oil

de Freitas, Nando

233

Classification and forecasting of load curves Nolwen Huet  

E-Print Network (OSTI)

on up to stabilisation of the clusters. Finally, the load profiles are predicted by covariance analysis of electricity customer uses. This load curve is only available for customers with automated meter readingClassification and forecasting of load curves Nolwen Huet Abstract The load curve, which gives

Cuesta, Juan Antonio

234

Automatic texture feature selection for image pixel classification  

Science Conference Proceedings (OSTI)

Pixel-based texture classifiers and segmenters are typically based on the combination of texture feature extraction methods that belong to a single family (e.g., Gabor filters). However, combining texture methods from different families has proven to ... Keywords: Multiple evaluation windows, Multiple texture methods, Supervised texture classification, Texture feature selection

Domenec Puig; Miguel Angel Garcia

2006-11-01T23:59:59.000Z

235

Sensor network based vehicle classification and license plate identification system  

Science Conference Proceedings (OSTI)

Typically, for energy efficiency and scalability purposes, sensor networks have been used in the context of environmental and traffic monitoring applications in which operations at the sensor level are not computationally intensive. But increasingly, ... Keywords: acoustic vehicle classification, license plate detection, seismic, wireless sensor networks

Jan Frigo; Vinod Kulathumani; Sean Brennan; Ed Rosten; Eric Raby

2009-06-01T23:59:59.000Z

236

Design and comparison of different evolution strategies for feature selection and consolidation in music classification  

Science Conference Proceedings (OSTI)

Music classification is a complex problem which has gained high relevance for organizing large music collections. Different parameters concerning feature extraction, selection, processing and classification have a strong impact on the categorization ...

I. Vatolkin; W. Theimer; G. Rudolph

2009-05-01T23:59:59.000Z

237

Classification of Precipitation Types during Transitional Winter Weather Using the RUC Model and Polarimetric Radar Retrievals  

Science Conference Proceedings (OSTI)

A new hydrometeor classification algorithm that combines thermodynamic output from the Rapid Update Cycle (RUC) model with polarimetric radar observations is introduced. The algorithm improves upon existing classification techniques that rely ...

Terry J. Schuur; Hyang-Suk Park; Alexander V. Ryzhkov; Heather D. Reeves

2012-04-01T23:59:59.000Z

238

On improving dissimilarity-based classifications using a statistical similarity measure  

Science Conference Proceedings (OSTI)

The aim of this paper is to present a dissimilarity measure strategy by which a new philosophy for pattern classification pertaining to dissimilarity-based classifications (DBCs) can be efficiently implemented. In DBCs, classifiers are not based on the ...

Sang-Woon Kim; Robert P. W. Duin

2010-11-01T23:59:59.000Z

239

On the Classification of Low-Rank Braided Fusion Categories  

E-Print Network (OSTI)

A physical system is said to be in topological phase if at low energies and long wavelengths the observable quantities are invariant under diffeomorphisms. Such physical systems are of great interest in condensed matter physics and computer science where they can be applied to form topological insulators and faulttolerant quantum computers. Physical systems in topological phase may be rigorously studied through their algebraic manifestations, (pre)modular categories. A complete classification of these categories would lead to a taxonomy of the topological phases of matter. Beyond their ties to physical systems, premodular categories are of general mathematical interest as they govern the representation theories of quasiHopf algebras, lead to manifold and link invariants, and provide insights into the braid group. In the course of this work, we study the classification problem for (pre)modular categories with particular attention paid to their arithmetic properties. Central to our analysis is the question of rank finiteness for modular categories, also known as Wangs Conjecture. In this work, we lay this problem to rest by exploiting certain arithmetic properties of modular categories. While the rank finiteness problem for premodular categories is still open, we provide new methods for approaching this problem. The arithmetic techniques suggested by the rank finiteness analysis are particularly pronounced in the (weakly) integral setting. There, we use Diophantine techniques to classify all weakly integral modular categories through rank 6 up to Grothendieck equivalence. In the case that the category is not only weakly integral, but actually integral, the analysis is further extended to produce a classification of integral modular categories up to Grothendieck equivalence through rank 7. It is observed that such classification can be extended provided some mild assumptions are made. For instance, if we further assume that the category is also odddimensional, then the classification up to Grothendieck equivalence is completed through rank 11. Moving beyond modular categories has historically been difficult. We suggest new methods for doing this inspired by our work on (weakly) integral modular categories and related problems in algebraic number theory. The allows us to produce a Grothendieck classification of rank 4 premodular categories thereby extending the previously known rank 3 classification.

Bruillard, Paul Joseph

2013-08-01T23:59:59.000Z

240

Towards automatic lithological classification from remote sensing data using support vector machines  

Science Conference Proceedings (OSTI)

Remote sensing data can be effectively used as a means to build geological knowledge for poorly mapped terrains. In this study, the support vector machine (SVM) algorithm is applied to an automated lithological classification of a study area in northwestern ... Keywords: ASTER, Aeromagnetic, DEM, Lithological classification, Supervised classification, Support vector machine (SVM)

Le Yu; Alok Porwal; Eun-Jung Holden; Michael C. Dentith

2012-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Effective temporal data classification by integrating sequential pattern mining and probabilistic induction  

Science Conference Proceedings (OSTI)

Data classification is an important topic in the field of data mining due to its wide applications. A number of related methods have been proposed based on the well-known learning models such as decision tree or neural network. Although data classification ... Keywords: Classification, Data mining, Scoring method, Sequential pattern, Temporal data

Vincent S. Tseng; Chao-Hui Lee

2009-07-01T23:59:59.000Z

242

An evolutionary Michigan recurrent fuzzy system for nuclei classification in cytological images using nuclear chromatin distribution  

Science Conference Proceedings (OSTI)

Objective: The objective of this research is to carry out the classification of cellular nuclei in cytological pleural fluid images. The article focuses on the feature extraction and classification processes. The extracted feature is a spatial measurement ... Keywords: Cytological images, Genetic algorithm, Nuclei chromatin distribution, Nuclei classification, Pattern recognition, ROC analysis, Recurrent fuzzy system

S. Alayn; J. I. Estvez; J. Sigut; J. L. Snchez; P. Toledo

2006-12-01T23:59:59.000Z

243

A color-action perceptual approach to the classification of animated movies  

Science Conference Proceedings (OSTI)

We address a particular case of video genre classification, namely the classification of animated movies. This task is achieved using two categories of content descriptors, temporal and color based, which are adapted to this particular content. Temporal ... Keywords: action content, animated genre classification, color properties, video indexing

Bogdan Ionescu; Constantin Vertan; Patrick Lambert; Alexandre Benoit

2011-04-01T23:59:59.000Z

244

A systematic fuzzy rule based approach for fault classification in transmission lines  

Science Conference Proceedings (OSTI)

The paper presents a new approach for fault classification in transmission line using a systematic fuzzy rule based approach. Fault classification is one of the important requirements in distance relaying for identifying the accurate phases involved ... Keywords: DT-fuzzy rule base, Decision Tree, Distance relaying, Fault classification, Heuristic fuzzy system, S-transform, Wavelet transform

S. R. Samantaray

2013-02-01T23:59:59.000Z

245

Microsoft Word - Data Classification Security Framework V5.doc  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

888P 888P Unlimited Release Printed July 2007 Security Framework for Control System Data Classification and Protection Bryan T. Richardson and John Michalski Prepared by Sandia National Laboratories Albuquerque, New Mexico 87185 and Livermore, California 94550 Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under Contract DE-AC04-94AL85000. Approved for public release; further dissemination unlimited. Security Framework for Control System Data Classification and Protection 2 Issued by Sandia National Laboratories, operated for the United States Department of Energy by Sandia Corporation. NOTICE: This report was prepared as an account of work sponsored by an agency of

246

Bidirectional Pipelining for Scalable IP Lookup and Packet Classification  

E-Print Network (OSTI)

Both IP lookup and packet classification in IP routers can be implemented by some form of tree traversal. SRAM-based Pipelining can improve the throughput dramatically. However, previous pipelining schemes result in unbalanced memory allocation over the pipeline stages. This has been identified as a major challenge for scalable pipelined solutions. This paper proposes a flexible bidirectional linear pipeline architecture based on widely-used dual-port SRAMs. A search tree is partitioned, and then mapped onto pipeline stages by a bidirectional fine-grained mapping scheme. We introduce the notion of inversion factor and several heuristics to invert subtrees for memory balancing. Due to its linear structure, the architecture maintains packet input order, and supports non-blocking route updates. Our experiments show that, the architecture can achieve a perfectly balanced memory distribution over the pipeline stages, for both trie-based IP lookup and tree-based multi-dimensional packet classification. For IP looku...

Jiang, Weirong; Prasanna, Viktor K

2011-01-01T23:59:59.000Z

247

High-resolution Urban Image Classification Using Extended Features  

SciTech Connect

High-resolution image classification poses several challenges because the typical object size is much larger than the pixel resolution. Any given pixel (spectral features at that location) by itself is not a good indicator of the object it belongs to without looking at the broader spatial footprint. Therefore most modern machine learning approaches that are based on per-pixel spectral features are not very effective in high- resolution urban image classification. One way to overcome this problem is to extract features that exploit spatial contextual information. In this study, we evaluated several features in- cluding edge density, texture, and morphology. Several machine learning schemes were tested on the features extracted from a very high-resolution remote sensing image and results were presented.

Vatsavai, Raju [ORNL

2011-01-01T23:59:59.000Z

248

CLASSIFICATION OF THE MGR CARRIER/CASK TRANSPORT SYSTEM  

SciTech Connect

The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) carrier/cask transport system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998).

S.E. Salzman

1999-08-30T23:59:59.000Z

249

CLASSIFICATION OF THE MGR SITE COMPRESSED AIR SYSTEM  

SciTech Connect

The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) site compressed air system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998).

J.A. Ziegler

1999-08-31T23:59:59.000Z

250

CLASSIFICATION OF THE MGR SUBSURFACE ELECTRICAL DISTRIBUTION SYSTEM  

SciTech Connect

The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) subsurface electrical distribution system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333PY ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998).

R.J. Garrett

1999-08-31T23:59:59.000Z

251

CLASSIFICATION OF THE MGR WASTE HANDLING BUILDING ELECTRICAL SYSTEM  

SciTech Connect

The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) waste handling building electrical system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998).

S.E. Salzman

1999-08-31T23:59:59.000Z

252

Supervised Parametric Classification of Aerial LiDAR Data  

E-Print Network (OSTI)

In this work, we classify 3D aerial LiDAR height data into roads, grass, buildings, and trees using a supervised parametric classification algorithm. Since the terrain is highly undulating, we subtract the terrain elevations using digital elevation models (DEMs, easily available from the United States Geological Survey (USGS)) to obtain the height of objects from a flat level. In addition to this height information, we use height texture (variation in height), intensity (amplitude of lidar response), and multiple (two) returns from lidar to classify the data. Furthermore, we have used luminance (measured in the visible spectrum) from aerial imagery as the fifth feature for classification. We have used mixture of Gaussian models for modeling the training data. Model parameters and the posterior probabilities are estimated using Expectation-Maximization (EM) algorithm. We have experimented with different number of components per model and found that four components per model yield satisfactory results. We have tested the results using leaveone -out as well as random test. Classification results are in the range of 66% -- 84% depending upon the combination of features used that compares very favorably with. trainall -test-all results of 85%. Further improvement is achieved using spatial coherence.

Amin P. Charaniya; Roberto Manduchi; Roberto M; Suresh K. Lodha

2004-01-01T23:59:59.000Z

253

Problems of trace-element ratios and geothermometry in a gravel geothermal-aquifer system  

DOE Green Energy (OSTI)

The system studied is a Tertiary-age, block-faulted basin in which a Pleistocene gravel bed acts as a confined aquifer and permits the lateral dispersion of the geothermal fluids. Vertical movement of the hot water is currently believed to be controlled by faults on the east side of the valley. An aerial magnetic anomaly and a Bouguer gravity anomaly appear to correspond with thoese eastern faults. Basic data on the geology and trace element halos has been presented previously. Evaluation of the mixing phenomena in this system was attempted using a dissolved silica-enthalpy graph. A chalcedony curve is also plotted. An enthalpy versus chloride plot, suggests that either conductive cooling occurs before mixing or that higher chloride content background waters are available for mixing. (MHR)

Sonderegger, J.L.; Donovan, J.J.

1982-01-01T23:59:59.000Z

254

1. INSERT ABOVE, CLASSIFICATION LEVEL, UNCLASSIFIED, OR OFFICIAL USE ONLY  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

(03-98) (Exception to SF 14, Approved by NARS, June 1978) 1. INSERT ABOVE, CLASSIFICATION LEVEL, UNCLASSIFIED, OR OFFICIAL USE ONLY 4. PRECEDENCE DESIGNATION ("X" appropriate box): 6. FROM 9. TO COMMUNICATION CENTER ROUTING U.S. DEPARTMENT OF ENERGY TELECOMMUNICATION MESSAGE (See reverse side for Instructions) 5. TYPE OF MESSAGE FOR COMMUNICATION CENTER USE MESSAGE IDENTIFICATION NR: DTG: Z YES 2. MESSAGE CONTAINS WEAPON DATA? ("X" appropriate box. Message Center will not transmit message unless one box is marked.) 3. THIS DOCUMENT CONSIST OF PAGES NO ("X" appropriate box) Single Address Multiple Address Title Address Book Message 7. OFFICIAL BUSINESS (TIME) A.M. P.M. (Signature of authorizing official)

255

CLASSIFICATION OF THE MGR SITE ELECTRICAL POWER SYSTEM  

SciTech Connect

The purpose of this analysis is to document the Quality As.surance (QA) classification of the Monitored Geologic Repository (MGR) site fire protection system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P7 ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998b).

J.A. Ziegler

1999-08-31T23:59:59.000Z

256

Efficient and robust classification method using combined feature vector for lane detection  

Science Conference Proceedings (OSTI)

The aim of this paper is to develop a method for low-cost and accurate classification of highways and rural ways image pixels for lane detection. The method uses three main components: adaptive/predefined image splitting, subimage level classification ... Keywords: Adaptive/predefined image splitting, Breshenham line drawing, Kalman filter, combination K-mean, forward and backward method, homogeneity checking conditions, subimage level classification, texture feature vector

Pangyu Jeong; S. Nedevschi

2005-04-01T23:59:59.000Z

257

Classification of the Entangled states L\\times N\\times N  

E-Print Network (OSTI)

We presented a general classification scheme for the tripartite $L\\times N\\times N$ entangled system under stochastic local operation and classical communication. The whole classification procedure consists of two correlated parts: the simultaneous similarity transformation of a commuting matrix pair into a canonical form and the study of internal symmetry of parameters in the canonical form. Based on this scheme, a concrete example of entanglement classification for a $3\\times N\\times N$ system is given.

Jun-Li Li; Shi-Yuan Li; Cong-Feng Qiao

2011-08-29T23:59:59.000Z

258

New models for region of interest reader classification analysis in chest radiographs  

Science Conference Proceedings (OSTI)

In several computer-aided diagnosis (CAD) applications of image processing, there is no sufficiently sensitive and specific method for determining what constitutes a normal versus an abnormal classification of a chest radiograph. In the case of lung ... Keywords: 10.-v, 75.Pq, 87.85.Tu, Binary classification, Chest radiographs, Logic, set theory, and algebra, Mathematical procedures and computer techniques, Modeling biomedical systems, Pneumoconiosis, ROC analysis, Region of interest classification

M. S. Pattichis; T. Cacoullos; Peter Soliz

2009-06-01T23:59:59.000Z

259

Improve the Classification System in Hydro Alunorte Lines 4/5  

Science Conference Proceedings (OSTI)

Presentation Title, Improve the Classification System in Hydro Alunorte Lines 4/5. Author(s), Cleto Maus de Azevedo Junior, Emerson Moraes, Joaquim Ribeiro...

260

Net-Zero Energy Buildings: A Classification System Based on Renewable...  

NLE Websites -- All DOE Office Websites (Extended Search)

Net-Zero Energy Buildings: A Classification System Based on Renewable Energy Supply Options Shanti Pless and Paul Torcellini Technical Report NRELTP-550-44586 June 2010 Technical...

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

KEPLER INPUT CATALOG: PHOTOMETRIC CALIBRATION AND STELLAR CLASSIFICATION  

Science Conference Proceedings (OSTI)

We describe the photometric calibration and stellar classification methods used by the Stellar Classification Project to produce the Kepler Input Catalog (KIC). The KIC is a catalog containing photometric and physical data for sources in the Kepler mission field of view; it is used by the mission to select optimal targets. Four of the visible-light (g, r, i, z) magnitudes used in the KIC are tied to Sloan Digital Sky Survey magnitudes; the fifth (D51) is an AB magnitude calibrated to be consistent with Castelli and Kurucz (CK) model atmosphere fluxes. We derived atmospheric extinction corrections from hourly observations of secondary standard fields within the Kepler field of view. For these filters and extinction estimates, repeatability of absolute photometry for stars brighter than magnitude 15 is typically 2%. We estimated stellar parameters {l_brace}T{sub eff}, log (g), log (Z), E{sub B-V}{r_brace} using Bayesian posterior probability maximization to match observed colors to CK stellar atmosphere models. We applied Bayesian priors describing the distribution of solar-neighborhood stars in the color-magnitude diagram, in log (Z), and in height above the galactic plane. Several comparisons with samples of stars classified by other means indicate that for 4500 K {data archive.

Brown, Timothy M. [Las Cumbres Observatory Global Telescope, Goleta, CA 93117 (United States); Latham, David W.; Esquerdo, Gilbert A. [Harvard-Smithsonian Center for Astrophysics, Cambridge, MA 02138 (United States); Everett, Mark E., E-mail: tbrown@lcogt.net, E-mail: latham@cfa.harvard.edu, E-mail: gesquerd@cfa.harvard.edu, E-mail: everett@noao.edu [National Optical Astronomy Observatories, Tucson, AZ 85721 (United States)

2011-10-15T23:59:59.000Z

262

STAR-GALAXY CLASSIFICATION IN MULTI-BAND OPTICAL IMAGING  

Science Conference Proceedings (OSTI)

Ground-based optical surveys such as PanSTARRS, DES, and LSST will produce large catalogs to limiting magnitudes of r {approx}> 24. Star-galaxy separation poses a major challenge to such surveys because galaxies-even very compact galaxies-outnumber halo stars at these depths. We investigate photometric classification techniques on stars and galaxies with intrinsic FWHM scenario (SVM{sub best}) where the training data are (unrealistically) a random sampling of the data in both signal-to-noise and demographics and (2) a more realistic scenario where training is done on higher signal-to-noise data (SVM{sub real}) at brighter apparent magnitudes. Testing with COSMOS ugriz data, we find that HB outperforms ML, delivering {approx}80% completeness, with purity of {approx}60%-90% for both stars and galaxies. We find that no algorithm delivers perfect performance and that studies of metal-poor main-sequence turnoff stars may be challenged by poor star-galaxy separation. Using the Receiver Operating Characteristic curve, we find a best-to-worst ranking of SVM{sub best}, HB, ML, and SVM{sub real}. We conclude, therefore, that a well-trained SVM will outperform template-fitting methods. However, a normally trained SVM performs worse. Thus, HB template fitting may prove to be the optimal classification method in future surveys.

Fadely, Ross; Willman, Beth [Haverford College, Department of Physics and Astronomy, 370 Lancaster Ave., Haverford, PA 19041 (United States); Hogg, David W. [Center for Cosmology and Particle Physics, Department of Physics, New York University, 4 Washington Place, New York, NY 10003 (United States)

2012-11-20T23:59:59.000Z

263

Cloud classification using whole-sky imager data  

SciTech Connect

Clouds are one of the most important moderators of the earth radiation budget and one of the least understood. The effect that clouds have on the reflection and absorption of solar and terrestrial radiation is strongly influenced by their shape, size, and composition. Physically accurate parameterization of clouds is necessary for any general circulation model (GCM) to yield meaningful results. The work presented here is part of a larger project that is aimed at producing realistic three-dimensional (3D) volume renderings of cloud scenes, thereby providing the important shape information for parameterizing GCMs. The specific goal of the current study is to develop an algorithm that automatically classifies (by cloud type) the clouds observed in the scene. This information will assist the volume rendering program in determining the shape of the cloud. Much work has been done on cloud classification using multispectral satellite images. Most of these references use some kind of texture measure to distinguish the different cloud types and some also use topological features (such as cloud/sky connectivity or total number of clouds). A wide variety of classification methods has been used, including neural networks, various types of clustering, and thresholding. The work presented here utilizes binary decision trees to distinguish the different cloud types based on cloud feature vectors.

Buch, K.A. Jr.; Sun, Chen-Hui

1995-02-01T23:59:59.000Z

264

Automatic Fault Characterization via Abnormality-Enhanced Classification  

Science Conference Proceedings (OSTI)

Enterprise and high-performance computing systems are growing extremely large and complex, employing hundreds to hundreds of thousands of processors and software/hardware stacks built by many people across many organizations. As the growing scale of these machines increases the frequency of faults, system complexity makes these faults difficult to detect and to diagnose. Current system management techniques, which focus primarily on efficient data access and query mechanisms, require system administrators to examine the behavior of various system services manually. Growing system complexity is making this manual process unmanageable: administrators require more effective management tools that can detect faults and help to identify their root causes. System administrators need timely notification when a fault is manifested that includes the type of fault, the time period in which it occurred and the processor on which it originated. Statistical modeling approaches can accurately characterize system behavior. However, the complex effects of system faults make these tools difficult to apply effectively. This paper investigates the application of classification and clustering algorithms to fault detection and characterization. We show experimentally that naively applying these methods achieves poor accuracy. Further, we design novel techniques that combine classification algorithms with information on the abnormality of application behavior to improve detection and characterization accuracy. Our experiments demonstrate that these techniques can detect and characterize faults with 65% accuracy, compared to just 5% accuracy for naive approaches.

Bronevetsky, G; Laguna, I; de Supinski, B R

2010-12-20T23:59:59.000Z

265

A CLASSIFICATION SCHEME FOR TURBULENT ACCELERATION PROCESSES IN SOLAR FLARES  

SciTech Connect

We establish a classification scheme for stochastic acceleration models involving low-frequency plasma turbulence in a strongly magnetized plasma. This classification takes into account both the properties of the accelerating electromagnetic field, and the nature of the transport of charged particles in the acceleration region. We group the acceleration processes as either resonant, non-resonant, or resonant-broadened, depending on whether the particle motion is free-streaming along the magnetic field, diffusive, or a combination of the two. Stochastic acceleration by moving magnetic mirrors and adiabatic compressions are addressed as illustrative examples. We obtain expressions for the momentum-dependent diffusion coefficient D(p), both for general forms of the accelerating force and for the situation when the electromagnetic force is wave-like, with a specified dispersion relation {omega} = {omega}(k). Finally, for models considered, we calculate the energy-dependent acceleration time, a quantity that can be directly compared with observations of the time profile of the radiation field produced by the accelerated particles, such as those occuring during solar flares.

Bian, Nicolas; Kontar, Eduard P. [School of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Emslie, A. Gordon, E-mail: n.bian@physics.gla.ac.uk, E-mail: eduard@astro.gla.ac.uk, E-mail: emslieg@wku.edu [Department of Physics and Astronomy, Western Kentucky University, Bowling Green, KY 42101 (United States)

2012-08-01T23:59:59.000Z

266

A complete electrical hazard classification system and its application  

Science Conference Proceedings (OSTI)

The Standard for Electrical Safety in the Workplace, NFPA 70E, and relevant OSHA electrical safety standards evolved to address the hazards of 60-Hz power that are faced primarily by electricians, linemen, and others performing facility and utility work. This leaves a substantial gap in the management of electrical hazards in Research and Development (R&D) and specialized high voltage and high power equipment. Examples include lasers, accelerators, capacitor banks, electroplating systems, induction and dielectric heating systems, etc. Although all such systems are fed by 50/60 Hz alternating current (ac) power, we find substantial use of direct current (dc) electrical energy, and the use of capacitors, inductors, batteries, and radiofrequency (RF) power. The electrical hazards of these forms of electricity and their systems are different than for 50160 Hz power. Over the past 10 years there has been an effort to develop a method of classifying all of the electrical hazards found in all types of R&D and utilization equipment. Examples of the variation of these hazards from NFPA 70E include (a) high voltage can be harmless, if the available current is sufficiently low, (b) low voltage can be harmful if the available current/power is high, (c) high voltage capacitor hazards are unique and include severe reflex action, affects on the heart, and tissue damage, and (d) arc flash hazard analysis for dc and capacitor systems are not provided in existing standards. This work has led to a comprehensive electrical hazard classification system that is based on various research conducted over the past 100 years, on analysis of such systems in R&D, and on decades of experience. Initially, national electrical safety codes required the qualified worker only to know the source voltage to determine the shock hazard. Later, as arc flash hazards were understood, the fault current and clearing time were needed. These items are still insufficient to fully characterize all types of electrical hazards. The new comprehensive electrical hazard classification system uses a combination of voltage, shock current available, fault current available, power, energy, and waveform to classify all forms of electrical hazards. Based on this electrical hazard classification system, many new tools have been developed, including (a) work controls for these hazards, (b) better selection of PPE for R&D work, (c) improved training, and (d) a new Severity Ranking Tool that is used to rank electrical accidents and incidents with various forms of electrical energy.

Gordon, Lloyd B [Los Alamos National Laboratory; Cartelli, Laura [Los Alamos National Laboratory

2009-01-01T23:59:59.000Z

267

A Bio-inspired Connectionist Architecture for Visual Classification of Moving Objects  

Science Conference Proceedings (OSTI)

In this paper we propose a bio-inspired connectionist architecture for visual classification of moving objects in articulated and non-articulated ones. It is based on a previous model called CONEPVIM, which uses the behaviour of simples cells in the ... Keywords: Bio-inspired connectionist architecture, articulated/non-articulated moving objects, visual classification

Pedro L. Snchez Orellana; Claudio Castellanos Snchez

2008-09-01T23:59:59.000Z

268

Fully complex-valued radial basis function networks: Orthogonal least squares regression and classification  

Science Conference Proceedings (OSTI)

We consider a fully complex-valued radial basis function (RBF) network for regression and classification applications. For regression problems, the locally regularised orthogonal least squares (LROLS) algorithm aided with the D-optimality experimental ... Keywords: Classification, Complex-valued radial basis function network, D-optimality experimental design, Fisher ratio of class separability measure, Orthogonal least squares algorithm, Regression

S. Chen; X. Hong; C. J. Harris; L. Hanzo

2008-10-01T23:59:59.000Z

269

Differential evolution for optimizing the positioning of prototypes in nearest neighbor classification  

Science Conference Proceedings (OSTI)

Nearest neighbor classification is one of the most used and well known methods in data mining. Its simplest version has several drawbacks, such as low efficiency, high storage requirements and sensitivity to noise. Data reduction techniques have been ... Keywords: Classification, Differential evolution, Evolutionary algorithms, Prototype generation, Prototype selection

Isaac Triguero; Salvador Garca; Francisco Herrera

2011-04-01T23:59:59.000Z

270

Hybrid clustering for validation and improvement of subject-classification schemes  

Science Conference Proceedings (OSTI)

A hybrid text/citation-based method is used to cluster journals covered by the Web of Science database in the period 2002-2006. The objective is to use this clustering to validate and, if possible, to improve existing journal-based subject-classification ... Keywords: Hybrid clustering, Journal cross-citation, Mapping of science, Subject classification

Frizo Janssens; Lin Zhang; Bart De Moor; Wolfgang Glnzel

2009-11-01T23:59:59.000Z

271

Wavelet-based feature extraction using probabilistic finite state automata for pattern classification  

Science Conference Proceedings (OSTI)

Real-time data-driven pattern classification requires extraction of relevant features from the observed time series as low-dimensional and yet information-rich representations of the underlying dynamics. These low-dimensional features facilitate in situ ... Keywords: Feature extraction, Pattern classification, Probabilistic finite state automata, Symbolic dynamics, Time series analysis

Xin Jin; Shalabh Gupta; Kushal Mukherjee; Asok Ray

2011-07-01T23:59:59.000Z

272

SMASH: a distributed sensing and processing garment for the classification of upper body postures  

Science Conference Proceedings (OSTI)

This paper introduces a smart textile for posture classification. A distributed sensing and processing architecture is implemented into a loose fitting long sleeve shirt. Standardized interfaces to remote periphery support the variable placement of different ... Keywords: SMASH, Smart Shirt, posture classification, smart textiles

Holger Harms; Oliver Amft; Gerhard Trster; Daniel Roggen

2008-03-01T23:59:59.000Z

273

Classification of coal images by a multi-scale segmentation techniques  

Science Conference Proceedings (OSTI)

This paper describes development of an automated and efficient technique for classifying different major maceral groups within polished coal blocks. Coal utilisation processes can be significantly affected by the distribution of macerals in the feed ... Keywords: coal images classification, computational complexity, image classification, image segmentation, maceral groups, multi-scale segmentation techniques, pixel values, polished coal blocks, probability, statistical model, transition distribution

1995-11-01T23:59:59.000Z

274

REMOTE SENSING TECHNIQUES FOR LAND USE CLASSIFICATION OF RIO JAUCA WATERSHED USING IKONOS IMAGES  

E-Print Network (OSTI)

REMOTE SENSING TECHNIQUES FOR LAND USE CLASSIFICATION OF RIO JAUCA WATERSHED USING IKONOS IMAGES-Mayagüez E-mail: edwinmm80@yahoo.com Key words: GIS, remote sensing, land use, supervised classification resource and supplies water to the metropolitan area. Remote sensing techniques can be used to assess

Gilbes, Fernando

275

Fuzzy theory applied in quality management of distributed manufacturing system: A literature review and classification  

Science Conference Proceedings (OSTI)

Fuzzy theory has been regarded as a very important technique for quality management (QM) of distributed manufacturing system and attracts the attentions of academic and industry; however, there is a lack of a comprehensive literature review and a classification ... Keywords: Classification, Clustering analysis, Distributed manufacturing network, Fuzzy theory, Quality management

Lv Yaqiong; Lee Ka Man; Wu Zhang

2011-03-01T23:59:59.000Z

276

Classification of Multispectral High-Resolution Satellite Imagery Using LIDAR Elevation Data  

Science Conference Proceedings (OSTI)

This paper studies the influence of airborne LIDAR elevation data on the classification of multispectral SPOT5 imagery over a semi-urban area; to do this, multispectral and LIDAR elevation data are integrated in a single imagery file composed of independent ... Keywords: Classification, LIDAR, Satellite Imagery, Support Vector Machine

Mara C. Alonso; Jos A. Malpica

2008-12-01T23:59:59.000Z

277

Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive Bayesian classification  

Science Conference Proceedings (OSTI)

Averaged n-Dependence Estimators (AnDE) is an approach to probabilistic classification learning that learns by extrapolation from marginal to full-multivariate probability distributions. It utilizes a single parameter that transforms ... Keywords: Averaged one-dependence estimators, Bayesian learning, Classification learning, Ensemble learning, Feating, Learning without model selection, Naive Bayes, Probabilistic learning, Semi-naive Bayesian learning

Geoffrey I. Webb; Janice R. Boughton; Fei Zheng; Kai Ming Ting; Houssam Salem

2012-02-01T23:59:59.000Z

278

Class-specific feature polynomial classifier for pattern classification and its application to handwritten numeral recognition  

Science Conference Proceedings (OSTI)

The polynomial classifier (PC) that takes the binomial terms of reduced subspace features as inputs has shown superior performance to multilayer neural networks in pattern classification. In this paper, we propose a class-specific feature polynomial ... Keywords: Class-specific feature polynomial classifier, Handwritten digit recognition, Neural classifiers, Numeral string recognition, Pattern classification

Cheng-Lin Liu; Hiroshi Sako

2006-04-01T23:59:59.000Z

279

Dissimilarity based feature selection for text classification: a cluster based approach  

Science Conference Proceedings (OSTI)

In this paper, a simple and efficient symbolic text classification is presented. We propose a new method of representing documents based on clustering of term frequency vectors. For each class of documents we propose to create multiple clusters to preserve ... Keywords: dissimilarity measure, fuzzy C means, symbolic representation, text classification, text document

S. Manjunath; B. S. Harish; D. S. Guru

2011-02-01T23:59:59.000Z

280

CSMC: A combination strategy for multi-class classification based on multiple association rules  

Science Conference Proceedings (OSTI)

Constructing accurate classifier based on association rules is an important and challenging task in data mining and knowledge discovery. In this paper, a novel combination strategy for multi-class classification (CSMC) based on multiple rules is proposed. ... Keywords: Associative classification, Basic probability assignment, Combination strategy, Evidence theory, Evidence weight

Ye-Zheng Liu; Yuan-Chun Jiang; Xiao Liu; Shan-Lin Yang

2008-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

A New System to Perform Unsupervised and Supervised Classification of Satellite Images from Google Maps  

E-Print Network (OSTI)

A New System to Perform Unsupervised and Supervised Classification of Satellite Images from Google of satellite images from Google Maps. The system has been developed using the SwingX-WS library Systems ENVI package. Keywords: Satellite image classification, Google Maps. 1. INTRODUCTION The wealth

Plaza, Antonio J.

282

Real-time classification via sparse representation in acoustic sensor networks  

Science Conference Proceedings (OSTI)

Acoustic Sensor Networks (ASNs) have a wide range of applications in natural and urban environment monitoring, as well as indoor activity monitoring. In-network classification is critically important in ASNs because wireless transmission costs several ... Keywords: ℓ1 minimization, acoustic sensor networks (ASNs), audio classification, sparse approximation

Bo Wei, Mingrui Yang, Yiran Shen, Rajib Rana, Chun Tung Chou, Wen Hu

2013-11-01T23:59:59.000Z

283

How to reuse a faceted classification and put it on the semantic web  

Science Conference Proceedings (OSTI)

There are ontology domain concepts that can be represented according to multiple alternative classification criteria. Current ontology modeling guidelines do not explicitly consider this aspect in the representation of such concepts. To assist with this ... Keywords: facet analysis, faceted classification, normalisation, ontology design pattern, ontology modeling

Bene Rodriguez-Castro; Hugh Glaser; Leslie Carr

2010-11-01T23:59:59.000Z

284

Design of an automatic wood types classification system by using fluorescence spectra  

Science Conference Proceedings (OSTI)

The classification of wood types is needed in many industrial sectors, since it can provide relevant information concerning the features and characteristics of the final product (appearance, cost,mechanical properties, etc.). This analysis is typical ... Keywords: automatic spectra analysis, automatic wood classification, computational intelligence

Vincenzo Piuri; Fabio Scotti

2010-05-01T23:59:59.000Z

285

A hypergraph reduction algorithm for joint segmentation and classification of satellite image content  

Science Conference Proceedings (OSTI)

In this paper, we introduce a novel hypergraph reduction algorithm, and we evaluate it in an innovative method for joint segmentation and classification of satellite image content. It operates in 3 steps. First, we compute an Image Neighborhood Hypergraph ... Keywords: hypergraph, hypergraph reduction, satellite image, superpixel, supervised classification

Alain Bretto; Aurlien Ducournau; Soufiane Rital

2010-11-01T23:59:59.000Z

286

Discovery of Mineralization Predication Classification Rules by Using Gene Expression Programming Based on PCA  

Science Conference Proceedings (OSTI)

Classification is one of the fundamental tasks in geology field. In this paper, we propose an evolutionary approach for discovering classification rules of mineralization predication from distinct combinations of geochemistry elements by using gene expression ... Keywords: GEP, Principal Component Analysis, mineralization predication

Dongmei Zhang; Yue Huang; Jing Zhi

2009-08-01T23:59:59.000Z

287

Conditional random fields for urban scene classification with full waveform LiDAR data  

Science Conference Proceedings (OSTI)

We propose a context-based classification method for point clouds acquired by full waveform airborne laser scanners. As these devices provide a higher point density and additional information like echo width or type of return, an accurate distinction ... Keywords: 3D point cloud, classification, conditional random fields, full waveform LiDAR, urban

Joachim Niemeyer; Jan Dirk Wegner; Clment Mallet; Franz Rottensteiner; Uwe Soergel

2011-10-01T23:59:59.000Z

288

Bayesian classification and survival analysis with curve predictors  

E-Print Network (OSTI)

We propose classification models for binary and multicategory data where the predictor is a random function. The functional predictor could be irregularly and sparsely sampled or characterized by high dimension and sharp localized changes. In the former case, we employ Bayesian modeling utilizing flexible spline basis which is widely used for functional regression. In the latter case, we use Bayesian modeling with wavelet basis functions which have nice approximation properties over a large class of functional spaces and can accommodate varieties of functional forms observed in real life applications. We develop an unified hierarchical model which accommodates both the adaptive spline or wavelet based function estimation model as well as the logistic classification model. These two models are coupled together to borrow strengths from each other in this unified hierarchical framework. The use of Gibbs sampling with conjugate priors for posterior inference makes the method computationally feasible. We compare the performance of the proposed models with the naive models as well as existing alternatives by analyzing simulated as well as real data. We also propose a Bayesian unified hierarchical model based on a proportional hazards model and generalized linear model for survival analysis with irregular longitudinal covariates. This relatively simple joint model has two advantages. One is that using spline basis simplifies the parameterizations while a flexible non-linear pattern of the function is captured. The other is that joint modeling framework allows sharing of the information between the regression of functional predictors and proportional hazards modeling of survival data to improve the efficiency of estimation. The novel method can be used not only for one functional predictor case, but also for multiple functional predictors case. Our methods are applied to analyze real data sets and compared with a parameterized regression method.

Wang, Xiaohui

2006-12-01T23:59:59.000Z

289

An incremental learning algorithm based on the K-associated graph for non-stationary data classification  

Science Conference Proceedings (OSTI)

Non-stationary classification problems concern the changes on data distribution over a classifier lifetime. To face this problem, learning algorithms must conciliate essential, but difficult to gather, attributes like good classification performance, ... Keywords: Concept drift, Graph-based learning, Incremental learning, K-associated graph, Non-stationary classification, Purity measure

JoO Roberto Bertini, Jr, Liang Zhao, Alneu A. Lopes

2013-10-01T23:59:59.000Z

290

A hybrid text classification approach with low dependency on parameter by integrating K-nearest neighbor and support vector machine  

Science Conference Proceedings (OSTI)

This work implements a new text document classifier by integrating the K-nearest neighbor (KNN) classification approach with the support vector machine (SVM) training algorithm. The proposed Nearest Neighbor-Support Vector Machine hybrid classification ... Keywords: Euclidean distance function, K-nearest neighbor, Support vector machine, Text document classification

Chin Heng Wan; Lam Hong Lee; Rajprasad Rajkumar; Dino Isa

2012-11-01T23:59:59.000Z

291

Assessment of classification and indexing of an agricultural journal based on metadata in AGRIS and CAB Abstracts databases  

Science Conference Proceedings (OSTI)

Agricultural thesauri and classification schemes are being increasingly upgraded as ontologies, prompting end-user awareness of the concept of structured taxonomies and metadata. Related agricultural databases, such as Agris and CAB Abstracts, exhibit ... Keywords: agricultural classification, agricultural journals, agricultural thesauri, agriculture, databases, descriptors, information retrieval, journal classification, journal indexing, metadata, ontology, scientific papers, semantics, subject categories, subject headings, terminology

Tomaz Bartol

2009-05-01T23:59:59.000Z

292

Neural net application to transmission line fault detection and classification  

E-Print Network (OSTI)

Today, in electric power systems, a large amount of data is made readily available at the occurrence of a fault due to the use of advanced communication systems, digital relays and fault recorders. Such systems are intended to obtain data from contacts of the relays and circuit breakers under operation. In addition, corresponding voltages and currents are recorded during prefault, fault and postfault periods. Restoration of power Systems after a fault occurred requires quick judgment. Hence, fault analysis, as the first step of restoration is very important. However, since faults in power systems are various and relaying systems may be complex, fault analysis is difficult to automate. Common practice in power utility companies, today, is to perform fault analysis by expert operators using their knowledge about the power systems and experience with past faults. Because of the time required to deal with complex fault situations, detailed fault analysis can not be performed by human operators in a short time. Therefore, on-line automated fault analysis system is strongly desired. Traditional approaches to the problem of analysis is to construct a heuristic, rule-based system which embodies a portion of the compiled experience of a human expert. These systems perform fault analysis by mapping fault indications to fault hypotheses. 'These hypotheses are used as inputs for next level of rules. After completion of inferencing process, conclusions are given. The knowledge acquisition process is exhaustive and time consuming. Also, data processing is usually too slow to be effectively applied in a real-time environment. Neural computing is one of the rapidly expanding areas of current research. Neural nets have some obvious advantages over expert systems. They are computationally more effective because of their parallel processing capabilities. Also, there is no need for detailed knowledge acquisition part, because neural nets learn by example. This thesis presents results of a study on using the new neural net system that can perform both on-line and off-line fault detection and classification. Fault analysis is conceptualized as a pattern classification problem which involves the association of input patterns representing the power system state to one or more fault conditions.

Rikalo, Igor

1994-01-01T23:59:59.000Z

293

System diagnostics using qualitative analysis and component functional classification  

DOE Patents (OSTI)

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system.

Reifman, Jaques (Lisle, IL); Wei, Thomas Y. C. (Downers Grove, IL)

1993-01-01T23:59:59.000Z

294

System diagnostics using qualitative analysis and component functional classification  

DOE Patents (OSTI)

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system. 5 figures.

Reifman, J.; Wei, T.Y.C.

1993-11-23T23:59:59.000Z

295

Toward the classification of the realistic free fermionic models  

SciTech Connect

The realistic free fermionic models have had remarkable success in providing plausible explanations for various properties of the Standard Model which include the natural appearance of three generations, the explanation of the heavy top quark mass and the qualitative structure of the fermion mass spectrum in general, the stability of the proton and more. These intriguing achievements makes evident the need to understand the general space of these models. While the number of possibilities is large, general patterns can be extracted. In this paper the author presents a detailed discussion on the construction of the realistic free fermionic models with the aim of providing some insight into the basic structures and building blocks that enter the construction. The role of free phases in the determination of the phenomenology of the models is discussed in detail. The author discusses the connection between the free phases and mirror symmetry in (2,2) models and the corresponding symmetries in the case of (2,0) models. The importance of the free phases in determining the effective low energy phenomenology is illustrated in several examples. The classification of the models in terms of boundary condition selection rules, real world-sheet fermion pairings, exotic matter states and the hidden sector is discussed.

Faraggi, A.E.

1997-08-01T23:59:59.000Z

296

Deep Spatiotemporal Feature Learning with Application to Image Classification  

SciTech Connect

Deep machine learning is an emerging framework for dealing with complex high-dimensionality data in a hierarchical fashion which draws some inspiration from biological sources. Despite the notable progress made in the field, there remains a need for an architecture that can represent temporal information with the same ease that spatial information is discovered. In this work, we present new results using a recently introduced deep learning architecture called Deep Spatio-Temporal Inference Network (DeSTIN). DeSTIN is a discriminative deep learning architecture that combines concepts from unsupervised learning for dynamic pattern representation together with Bayesian inference. In DeSTIN the spatiotemporal dependencies that exist within the observations are modeled inherently in an unguided manner. Each node models the inputs by means of clustering and simple dynamics modeling while it constructs a belief state over the distribution of sequences using Bayesian inference. We demonstrate that information from the different layers of this hierarchical system can be extracted and utilized for the purpose of pattern classification. Earlier simulation results indicated that the framework is highly promising, consequently in this work we expand DeSTIN to a popular problem, the MNIST data set of handwritten digits. The system as a preprocessor to a neural network achieves a recognition accuracy of 97.98% on this data set. We further show related experimental results pertaining to automatic cluster adaptation and termination.

Karnowski, Thomas Paul [ORNL; Arel, Itamar [ORNL; Rose, Derek C [ORNL

2010-01-01T23:59:59.000Z

297

Advanced Rain/No-Rain Classification Methods for Microwave Radiometer Observations over Land  

Science Conference Proceedings (OSTI)

Seto et al. developed rain/no-rain classification (RNC) methods over land for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). In this study, the methods are modified for application to other microwave radiometers. The ...

Shinta Seto; Takuji Kubota; Nobuhiro Takahashi; Toshio Iguchi; Taikan Oki

2008-11-01T23:59:59.000Z

298

The Aleutian Low and Winter Climatic Conditions in the Bering Sea. Part I: Classification  

Science Conference Proceedings (OSTI)

The Aleutian low is examined as a primary determinant of surface air temperature (SAT) variability in the Bering Sea during the winter [DecemberJanuaryFebruaryMarch (DJFM)] months. The Classification and Regression Tree (CART) method is used ...

S. N. Rodionov; J. E. Overland; N. A. Bond

2005-01-01T23:59:59.000Z

299

Using multiple sources to construct a sentiment sensitive thesaurus for cross-domain sentiment classification  

Science Conference Proceedings (OSTI)

We describe a sentiment classification method that is applicable when we do not have any labeled data for a target domain but have some labeled data for multiple other domains, designated as the source domains. We automatically create a ...

Danushka Bollegala; David Weir; John Carroll

2011-06-01T23:59:59.000Z

300

From top-level to domain ontologies: ecosystem classifications as a case study  

Science Conference Proceedings (OSTI)

This paper shows how to use a top-level ontology to create robust and logically coherent domain ontology in a way that facilitates computational implementation and interoperability. It uses a domain ontology of ecosystem classification and delineation ...

Thomas Bittner

2007-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Regression-Guided Clustering: A Semisupervised Method for Circulation-to-Environment Synoptic Classification  

Science Conference Proceedings (OSTI)

Regression-guided clustering is introduced as a means of constructing circulation-to-environment synoptic climatological classifications. Rather than applying an unsupervised clustering algorithm to synoptic-scale atmospheric circulation data, one ...

Alex J. Cannon

2012-02-01T23:59:59.000Z

302

An Automated Classification Scheme Designed to Better Elucidate the Dependence of Ozone on Meteorology  

Science Conference Proceedings (OSTI)

This paper utilizes a two-stage (average linkage then convergent k means) clustering approach as part of an automated meteorological classification scheme designed to better elucidate the dependence of ozone on meteorology. When applied to 10 ...

Brian K. Eder; Jerry M. Davis; Peter Bloomfield

1994-10-01T23:59:59.000Z

303

Assessment of a modified version of the EM algorithm for remote sensing data classification  

Science Conference Proceedings (OSTI)

This work aims to present an assessment of a modified version of the standard EM clustering algorithm for remote sensing data classification. As observing clusters with very similar mean vectors but differing only on the covariance structure is not natural ...

Thales Sehn Korting; Luciano Vieira Dutra; Guaraci Jos Erthal; Leila Maria Garcia Fonseca

2010-11-01T23:59:59.000Z

304

Phenomenological Description of Tropical Clouds Using CloudSat Cloud Classification  

Science Conference Proceedings (OSTI)

Two years of tropical oceanic cloud observations are analyzed using the operational CloudSat cloud classification product and CloudAerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar. Relationships are examined between ...

Ali Behrangi; Terry Kubar; Bjorn Lambrigtsen

2012-10-01T23:59:59.000Z

305

An investigation into the application of ensemble learning for entailment classification  

Science Conference Proceedings (OSTI)

Textual entailment is a task for which the application of supervised learning mechanisms has received considerable attention as driven by successive Recognizing Data Entailment data challenges. We developed a linguistic analysis framework in which a ... Keywords: Classification, Ensemble learning, Entailment

Niall Rooney, Hui Wang, Philip S. Taylor

2014-01-01T23:59:59.000Z

306

A global typology of cities : classification tree analysis of urban resource consumption  

E-Print Network (OSTI)

A study was carried out to develop a typology of urban metabolic (or resource consumption) profiles for 155 globally representative cities. Classification tree analysis was used to develop a model for determining how certain ...

Saldivar-Sali, Artessa Niccola D., 1980-

2010-01-01T23:59:59.000Z

307

Comparison of GOES Cloud Classification Algorithms Employing Explicit and Implicit Physics  

Science Conference Proceedings (OSTI)

Cloud-type classification based on multispectral satellite imagery data has been widely researched and demonstrated to be useful for distinguishing a variety of classes using a wide range of methods. The research described here is a comparison of ...

Richard L. Bankert; Cristian Mitrescu; Steven D. Miller; Robert H. Wade

2009-07-01T23:59:59.000Z

308

Weather pattern classification to represent the urban heat island in present and future climate  

Science Conference Proceedings (OSTI)

A classification of weather patterns (WP) is derived that is tailored to best represent situations relevant for the urban heat island (UHI). Three different types of k-means-based cluster methods are conducted. The explained cluster variance is ...

Peter Hoffmann; K. Heinke Schlnzen

309

On the Performance of Informative Wavelets for Classification and Diagnosis of Machine Faults  

Science Conference Proceedings (OSTI)

This paper deals with an application of wavelets for feature extraction and classification of machine faults in a real-world machine data analysis environment. We have utilized informative wavelet algorithm to generate wavelets and subsequent coefficients ...

H. Ahmadi; R. Tafreshi; F. Sassani; G. Dumont

2001-12-01T23:59:59.000Z

310

Detection, classification and localization of seabed objects with a virtual time reversal mirror  

E-Print Network (OSTI)

The work presented in this thesis addresses the problem of the detection, classification and localization of seabed objects in shallow water environments using a time reversal approach in a bistatic configuration. The ...

Dumortier, Alexis Jean Louis

2009-01-01T23:59:59.000Z

311

Classification of Tropical Precipitating Systems Using Wind Profiler Spectral Moments. Part I: Algorithm Description and Validation  

Science Conference Proceedings (OSTI)

The lower atmospheric wind profiler (LAWP) measurements made at Gadanki, India, have been used to develop an objective algorithm to classify the tropical precipitating systems. A detailed investigation on the existing classification scheme ...

T. Narayana Rao; N. V. P. Kirankumar; B. Radhakrishna; D. Narayana Rao; K. Nakamura

2008-06-01T23:59:59.000Z

312

Composite Kernels for Support Vector Classification of Hyper-Spectral Data  

Science Conference Proceedings (OSTI)

The incorporation of prior knowledge into the Support Vector Machine (SVM) architecture is a problem which if solved can lead to much more accurate classifiers in the near future. This result could be particularly effective in the classification of remote ...

Mojtaba Kohram; Mahd. Noor Sap

2008-10-01T23:59:59.000Z

313

Solar wind and geomagnetism: toward a standard classification of geomagnetic activity from 1868 to 2009  

E-Print Network (OSTI)

We examined solar activity with a large series of geomagnetic data from 1868 to 2009. We have revisited the geomagnetic activity classification scheme of Legrand and Simon (1989) and improve their scheme by lowering the ...

Zerbo, J. L.

314

APPLYING DATA MINING TECHNIQUES FOR CANCER CLASSIFICATION ON GENE EXPRESSION DATA  

Science Conference Proceedings (OSTI)

Cancer classification through gene expression data analysis has recently emerged as an active area of research. This paper applies Genetic Algorithms (GA) for selecting a group of relevant genes from cancer microarray data. Then, the popular classifiers, ...

Jinn-Yi Yeh

2008-08-01T23:59:59.000Z

315

The NSSL Hydrometeor Classification Algorithm in Winter Surface Precipitation: Evaluation and Future Development  

Science Conference Proceedings (OSTI)

The National Severe Storms Laboratory (NSSL) has developed a hydrometeor classification algorithm (HCA) for use with the polarimetric upgrade of the current Weather Surveillance Radar-1988 Doppler (WSR-88D) network. The algorithm was developed ...

Kimberly L. Elmore

2011-10-01T23:59:59.000Z

316

The Hydrometeor Classification Algorithm for the Polarimetric WSR-88D: Description and Application to an MCS  

Science Conference Proceedings (OSTI)

This paper contains a description of the most recent version of the hydrometeor classification algorithm for polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D). This version contains several modifications and refinements of the ...

Hyang Suk Park; A. V. Ryzhkov; D. S. Zrni?; Kyung-Eak Kim

2009-06-01T23:59:59.000Z

317

Modeling Seasonal Tropical Cyclone Activity in the Fiji Region as a Binary Classification Problem  

Science Conference Proceedings (OSTI)

This study presents a binary classification model for the prediction of tropical cyclone (TC) activity in the Fiji, Samoa, and Tonga regions (the FST region) using the accumulated cyclone energy (ACE) as a proxy of TC activity. A probit regression ...

Savin S. Chand; Kevin J. E. Walsh

2012-07-01T23:59:59.000Z

318

A Seasonal Snow Cover Classification System for Local to Global Applications  

Science Conference Proceedings (OSTI)

A new classification system for seasonal snow covers is proposed. It has six classes (tundra, taiga, alpine, maritime, prairie, and ephemeral, each class defined by a unique ensemble of textural and stratigraphic characteristics including the ...

Matthew Sturm; Jon Holmgren; Glen E. Liston

1995-05-01T23:59:59.000Z

319

Evaluation of an AVHRR Cloud Detection and Classification Method over the Central Arctic Ocean  

Science Conference Proceedings (OSTI)

A cloud classification method that uses both multispectral and textural features with a maximum likelihood discriminator is applied to full-resolution AVHRR (Advanced Very High Resolution Radiometer) data from 100 NOAA polar-orbiter overpasses ...

Dan Lubin; Esther Morrow

1998-02-01T23:59:59.000Z

320

Remote sensing classification of grass seed cropping practices in western Oregon  

Science Conference Proceedings (OSTI)

Our primary objective was extending knowledge of major crop rotations and stand establishment conditions present in 4800 grass seed fields surveyed over three years in western Oregon to the entire Willamette Valley through classification of multiband ...

George W. Mueller-Warrant; Gerald W. Whittaker; Stephen M. Griffith; Gary M. Banowetz; Bruce D. Dugger; Tiffany S. Garcia; Guillermo Giannico; Kathryn L. Boyer; Brenda C. McComb

2011-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

High-Spatial-Resolution Surface and Cloud-Type Classification from MODIS Multispectral Band Measurements  

Science Conference Proceedings (OSTI)

A method for automated classification of surface and cloud types using Moderate Resolution Imaging Spectroradiometer (MODIS) radiance measurements has been developed. The MODIS cloud mask is used to define the training sets. Surface and cloud-...

Jun Li; W. Paul Menzel; Zhongdong Yang; Richard A. Frey; Steven A. Ackerman

2003-02-01T23:59:59.000Z

322

Distinguishing Aerosols from Clouds in Global, Multispectral Satellite Data with Automated Cloud Classification Algorithms  

Science Conference Proceedings (OSTI)

A new approach is presented to distinguish between clouds and heavy aerosols with automated cloud classification algorithms developed for the National Polar-orbiting Operational Environmental Satellite System (NPOESS) program. These new ...

Keith D. Hutchison; Barbara D. Iisager; Thomas J. Kopp; John M. Jackson

2008-04-01T23:59:59.000Z

323

Analysis of full waveform LIDAR data for the classification of deciduous and coniferous trees  

Science Conference Proceedings (OSTI)

The paper describes a methodology for tree species classification using features that are derived from small-footprint full waveform Light Detection and Ranging (LIDAR) data. First, 3-dimensional coordinates of the laser beam reflections, the intensity, ...

J. Reitberger; P. Krzystek; U. Stilla

2008-03-01T23:59:59.000Z

324

Improved Accuracy of Radar WPMM Estimated Rainfall upon Application of Objective Classification Criteria  

Science Conference Proceedings (OSTI)

Application of the window probability matching method to radar and rain gauge data that have been objectivelyclassified into different rain types resulted in distinctly different Ze-R relationships for the various classifications.The ...

Daniel Rosenfeld; Eyal Amitai; David B. Wolff

1995-01-01T23:59:59.000Z

325

Sources, classification, and disposal of radioactive wastes: History and legal and regulatory requirements  

Science Conference Proceedings (OSTI)

This report discusses the following topics: (1) early definitions of different types (classes) of radioactive waste developed prior to definitions in laws and regulations; (2) sources of different classes of radioactive waste; (3) current laws and regulations addressing classification of radioactive wastes; and requirements for disposal of different waste classes. Relationship between waste classification and requirements for permanent disposal is emphasized; (4) federal and state responsibilities for radioactive wastes; and (5) distinctions between radioactive wastes produced in civilian and defense sectors.

Kocher, D.C.

1991-01-01T23:59:59.000Z

326

Parametrization and Classification of 20 Billion LSST Objects: Lessons from SDSS  

Science Conference Proceedings (OSTI)

The Large Synoptic Survey Telescope (LSST) will be a large, wide-field ground-based system designed to obtain, starting in 2015, multiple images of the sky that is visible from Cerro Pachon in Northern Chile. About 90% of the observing time will be devoted to a deep-wide-fast survey mode which will observe a 20,000 deg{sup 2} region about 1000 times during the anticipated 10 years of operations (distributed over six bands, ugrizy). Each 30-second long visit will deliver 5{sigma} depth for point sources of r {approx} 24.5 on average. The co-added map will be about 3 magnitudes deeper, and will include 10 billion galaxies and a similar number of stars. We discuss various measurements that will be automatically performed for these 20 billion sources, and how they can be used for classification and determination of source physical and other properties. We provide a few classification examples based on SDSS data, such as color classification of stars, color-spatial proximity search for wide-angle binary stars, orbital-color classification of asteroid families, and the recognition of main Galaxy components based on the distribution of stars in the position-metallicity-kinematics space. Guided by these examples, we anticipate that two grand classification challenges for LSST will be (1) rapid and robust classification of sources detected in difference images, and (2) simultaneous treatment of diverse astrometric and photometric time series measurements for an unprecedentedly large number of objects.

Ivezic, Z.; /Washington U., Seattle, Astron. Dept.; Axelrod, T.; /Large Binocular Telescope, Tucson; Becker, A.C.; /Washington U., Seattle, Astron. Dept.; Becla, J.; /SLAC; Borne, K.; /George Mason U.; Burke, David L.; /SLAC; Claver, C.F.; /NOAO, Tucson; Cook, K.H.; /LLNL, Livermore; Connolly, A.; /Washington U., Seattle, Astron. Dept.; Gilmore, D.K.; /SLAC; Jones, R.L.; /Washington U., Seattle, Astron. Dept.; Juric, M.; /Princeton, Inst. Advanced Study; Kahn, Steven M.; /SLAC; Lim, K-T.; /SLAC; Lupton, R.H.; /Princeton U.; Monet, D.G.; /Naval Observ., Flagstaff; Pinto, P.A.; /Arizona U.; Sesar, B.; /Washington U., Seattle, Astron. Dept.; Stubbs, Christopher W.; /Harvard U.; Tyson, J.Anthony; /UC, Davis

2011-11-10T23:59:59.000Z

327

Parametrization and Classification of 20 Billion LSST Objects: Lessons from SDSS  

E-Print Network (OSTI)

The Large Synoptic Survey Telescope (LSST) will be a large, wide-field ground-based system designed to obtain, starting in 2015, multiple images of the sky that is visible from Cerro Pachon in Northern Chile. About 90% of the observing time will be devoted to a deep-wide-fast survey mode which will observe a 20,000 deg$^2$ region about 1000 times during the anticipated 10 years of operations (distributed over six bands, $ugrizy$). Each 30-second long visit will deliver 5$\\sigma$ depth for point sources of $r\\sim24.5$ on average. The co-added map will be about 3 magnitudes deeper, and will include 10 billion galaxies and a similar number of stars. We discuss various measurements that will be automatically performed for these 20 billion sources, and how they can be used for classification and determination of source physical and other properties. We provide a few classification examples based on SDSS data, such as color classification of stars, color-spatial proximity search for wide-angle binary stars, orbital-color classification of asteroid families, and the recognition of main Galaxy components based on the distribution of stars in the position-metallicity-kinematics space. Guided by these examples, we anticipate that two grand classification challenges for LSST will be 1) rapid and robust classification of sources detected in difference images, and 2) {\\it simultaneous} treatment of diverse astrometric and photometric time series measurements for an unprecedentedly large number of objects.

Z. Ivezic; T. Axelrod; A. C. Becker

2008-10-28T23:59:59.000Z

328

Data driven process monitoring based on neural networks and classification trees  

E-Print Network (OSTI)

Process monitoring in the chemical and other process industries has been of great practical importance. Early detection of faults is critical in avoiding product quality deterioration, equipment damage, and personal injury. The goal of this dissertation is to develop process monitoring schemes that can be applied to complex process systems. Neural networks have been a popular tool for modeling and pattern classification for monitoring of process systems. However, due to the prohibitive computational cost caused by high dimensionality and frequently changing operating conditions in batch processes, their applications have been difficult. The first part of this work tackles this problem by employing a polynomial-based data preprocessing step that greatly reduces the dimensionality of the neural network process model. The process measurements and manipulated variables go through a polynomial regression step and the polynomial coefficients, which are usually of far lower dimensionality than the original data, are used to build a neural network model to produce residuals for fault classification. Case studies show a significant reduction in neural model construction time and sometimes better classification results as well. The second part of this research investigates classification trees as a promising approach to fault detection and classification. It is found that the underlying principles of classification trees often result in complicated trees even for rather simple problems, and construction time can excessive for high dimensional problems. Fisher Discriminant Analysis (FDA), which features an optimal linear discrimination between different faults and projects original data on to perpendicular scores, is used as a dimensionality reduction tool. Classification trees use the scores to separate observations into different fault classes. A procedure identifies the order of FDA scores that results in a minimum tree cost as the optimal order. Comparisons to other popular multivariate statistical analysis based methods indicate that the new scheme exhibits better performance on a benchmarking problem.

Zhou, Yifeng

2004-08-01T23:59:59.000Z

329

Classification of Nuclear Weapons-Related Information (Restricted Data and Formerly Restricted Data)  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

CLASSIFICATION OF CLASSIFICATION OF NUCLEAR WEAPONS-RELATED INFORMATION Restricted Data and Formerly Restricted Data (RD and FRD) June 2012 2 3 Purpose To familiarize individuals from agencies outside of DOE who may come in contact with RD and FRD with the procedures for identifying, classifying, marking, handling, and declassifying documents containing that information as required by  The Atomic Energy Act and  10 Code of Federal Regulation (CFR) Part 1045, Nuclear Classification and Declassification §1045.35 4 Not the Purpose This briefing does not authorize you to classify or declassify documents containing RD or FRD. Additional training is required to classify documents containing RD or FRD or identify RD or FRD within a document for redaction. Only authorized DOE

330

A Proposed New Classification Of The Granites Of Egypt | Open Energy  

Open Energy Info (EERE)

source source History View New Pages Recent Changes All Special Pages Semantic Search/Querying Get Involved Help Apps Datasets Community Login | Sign Up Search Page Edit History Facebook icon Twitter icon » A Proposed New Classification Of The Granites Of Egypt Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Journal Article: A Proposed New Classification Of The Granites Of Egypt Details Activities (0) Areas (0) Regions (0) Abstract: Granites and granitoids constitute an important rock group that covers vast areas of the Arabian-Nubian Shield in Egypt. They range in composition from quartz diorite and tonalite, through granodiorite and quartz monzonite to true granites and alkaline-peralkaline granites. Several workers tried the identification and classification of these

331

A Brief Summary of Dictionary Learning Based Approach for Classification (revised)  

E-Print Network (OSTI)

This note presents some representative methods which are based on dictionary learning (DL) for classification. We do not review the sophisticated methods or frameworks that involve DL for classification, such as online DL and spatial pyramid matching (SPM), but rather, we concentrate on the direct DL-based classification methods. Here, the "so-called direct DL-based method" is the approach directly deals with DL framework by adding some meaningful penalty terms. By listing some representative methods, we can roughly divide them into two categories, i.e. (1) directly making the dictionary discriminative and (2) forcing the sparse coefficients discriminative to push the discrimination power of the dictionary. From this taxonomy, we can expect some extensions of them as future researches.

Kong, Shu

2012-01-01T23:59:59.000Z

332

Biological named entity recognition using n-grams and classification methods  

E-Print Network (OSTI)

We propose a biological named entity recognition system which uses classification methods and a n-gram model to annotate terms in text. A novel method is presented to express lexical features in a pattern notation. Prefix and suffix characters are used instead of lists of potential terms or other external resources. Creating classification exemplars is conducted from text by using a word n-gram model. We evaluate our system based on the GE-NIA version 3.02 corpus which contains 2,000 paper abstracts. The system obtains an 0.705 F-score on exact match term performance. Biological concept markers are also assigned to each located term indicating its meaning. Our system retains simplicity and generalizability. Key words: Biological named entity recognition, information extraction, word n-gram, and classification algorithms 1

Sittichai Jiampojamarn; Nick Cercone

2005-01-01T23:59:59.000Z

333

Experts Fusion and Multilayer Perceptron Based on Belief Learning for Sonar Image Classification  

E-Print Network (OSTI)

The sonar images provide a rapid view of the seabed in order to characterize it. However, in such as uncertain environment, real seabed is unknown and the only information we can obtain, is the interpretation of different human experts, sometimes in conflict. In this paper, we propose to manage this conflict in order to provide a robust reality for the learning step of classification algorithms. The classification is conducted by a multilayer perceptron, taking into account the uncertainty of the reality in the learning stage. The results of this seabed characterization are presented on real sonar images.

Martin, Arnaud

2008-01-01T23:59:59.000Z

334

Classification of emotion in spoken Finnish using vowel-length segments: Increasing reliability with a fusion technique  

Science Conference Proceedings (OSTI)

Classification of emotional content of short Finnish emotional [a:] vowel speech samples is performed using vocal source parameter and traditional intonation contour parameter derived prosodic features. A multiple kNN classifier based decision level ... Keywords: Automatic classification of emotion, Classifier fusion, Prosodic features, Spoken Finnish, Vocal source features, Vowel segments

Eero Vyrynen; Juhani Toivanen; Tapio Seppnen

2011-03-01T23:59:59.000Z

335

Automatic Classification of Biological Particles fromElectron-microscopy Images Using Conventional and Genetic-algorithm Optimized Learning Vector Quantization  

Science Conference Proceedings (OSTI)

Automatic classification of transmission electron-microscopy images is an important step in the complex task of determining the structure of biologial macromolecules. The process of 3D reconstruction from a set of such images implies their previous ... Keywords: genetic algorithms, image classification, image reconstruction, neural network optimization, neural networks

J. J. Merelo; A. Prieto; F. Morn; R. Marabini; J. M. Carazo

1998-08-01T23:59:59.000Z

336

Classification of Markov processes of M/G/1 type with a tree structure and its applications to queueing models  

Science Conference Proceedings (OSTI)

This paper studies the classification problem of Markov processes of M/G/1 type with a tree structure. It is shown that the classification of positive recurrence, null recurrence, and transience of the Markov processes of interest is determined completely ... Keywords: Lyapunov function, Markov process, Mean drift method, Null recurrence, Positive recurrence, Queueing theory, Transience, Tree structure

Qi-Ming He

2000-03-01T23:59:59.000Z

337

FCM_FS: A Simultaneous Clustering and Feature Selection Model for Classification  

Science Conference Proceedings (OSTI)

Fuzzy relational classifier (FRC) is the recently proposed two-step nonlinear classifiers, which effectively integrates the formed clusters and the given classes. However, FRC can not copy with the influence of those irrelevant or redundant features. ... Keywords: FCM, Classification, Feature Selection, Enhanced Fuzzy Relational Classifier (EFRC)

Ming Yang; Jing Song; Gen-lin Ji

2009-03-01T23:59:59.000Z

338

Degasification system selection for US longwall mines using an expert classification system  

Science Conference Proceedings (OSTI)

Methane emissions from the active face areas and from the fractured formations overlying the mined coalbed can affect safety and productivity in longwall mines. Since ventilation alone may not be sufficient to control the methane levels on a longwall ... Keywords: Artificial neural networks, Classification, Coal seam degasification, Longwall mining, Principal component analysis, Ventilation

C. zgen Karacan

2009-03-01T23:59:59.000Z

339

Fuzzy Hopfield neural network clustering for single-trial motor imagery EEG classification  

Science Conference Proceedings (OSTI)

An electroencephalogram (EEG) analysis system for single-trial classification of motor imagery (MI) data is proposed in this study. Unsupervised fuzzy Hopfield neural network (FHNN) clustering, together with active segment selection and multiresolution ... Keywords: Brain-computer interface (BCI), Electroencephalogram (EEG), Fractal dimension (FD), Fuzzy Hopfield neural network (FHNN), Motor imagery (MI), Wavelet transform

Wei-Yen Hsu

2012-01-01T23:59:59.000Z

340

Extremal Horizons with Reduced Symmetry: Hyperscaling Violation, Stripes, and a Classification for the Homogeneous Case  

E-Print Network (OSTI)

Classifying the zero-temperature ground states of quantum field theories with finite charge density is a very interesting problem. Via holography, this problem is mapped to the classification of extremal charged black brane geometries with anti-de Sitter asymptotics. In a recent paper [1], we proposed a Bianchi classification of the extremal near-horizon geometries in five dimensions, in the case where they are homogeneous but, in general, anisotropic. Here, we extend our study in two directions: we show that Bianchi attractors can lead to new phases, and generalize the classification of homogeneous phases in a way suggested by holography. In the first direction, we show that hyperscaling violation can naturally be incorporated into the Bianchi horizons. We also find analytical examples of "striped" horizons. In the second direction, we propose a more complete classification of homogeneous horizon geometries where the natural mathematics involves real four-algebras with three dimensional sub-algebras. This gives rise to a richer set of possible near-horizon geometries, where the holographic radial direction is non-trivially intertwined with field theory spatial coordinates. We find examples of several of the new types in systems consisting of reasonably simple matter sectors coupled to gravity, while arguing that others are forbidden by the Null Energy Condition. Extremal horizons in four dimensions governed by three-algebras or four-algebras are also discussed.

Norihiro Iizuka; Shamit Kachru; Nilay Kundu; Prithvi Narayan; Nilanjan Sircar; Sandip P. Trivedi; Huajia Wang

2012-12-10T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Next Generation Nuclear Plant Structures, Systems, and Components Safety Classification White Paper  

SciTech Connect

This white paper outlines the relevant regulatory policy and guidance for a risk-informed approach for establishing the safety classification of Structures, Systems, and Components (SSCs) for the Next Generation Nuclear Plant and sets forth certain facts for review and discussion in order facilitate an effective submittal leading to an NGNP Combined Operating License application under 10 CFR 52.

Pete Jordan

2010-09-01T23:59:59.000Z

342

An autonomous GP-based system for regression and classification problems  

Science Conference Proceedings (OSTI)

The aim of this research is to develop an autonomous system for solving data analysis problems. The system, called Genetic Programming-Autonomous Solver (GP-AS) contains most of the features required by an autonomous software: it decides if it knows ... Keywords: 01.30. -y, Adaptive strategies, Autonomous systems, Classification, Genetic Programming, Symbolic regression

Mihai Oltean; Laura Dio?an

2009-01-01T23:59:59.000Z

343

Classification of public lands valuable for geothermal steam and associated geothermal resources  

DOE Green Energy (OSTI)

The Organic Act of 1879 (43 USC 31) that established the US Geological Survey provided, among other things, for the classification of the public lands and for the examination of the geological structure, mineral resources, and products of the national domain. In order to provide uniform executive action in classifying public lands, standards for determining which lands are valuable for mineral resources, for example, leasable mineral lands, or for other products are prepared by the US Geological Survey. This report presents the classification standards for determining which Federal lands are classifiable as geothermal steam and associated geothermal resources lands under the Geothermal Steam Act of 1970 (84 Stat. 1566). The concept of a geothermal resouces province is established for classification of lands for the purpose of retention in Federal ownership of rights to geothermal resources upon disposal of Federal lands. A geothermal resources province is defined as an area in which higher than normal temperatures are likely to occur with depth and in which there is a resonable possiblity of finding reservoir rocks that will yield steam or heated fluids to wells. The determination of a known geothermal resources area is made after careful evaluation of the available geologic, geochemical, and geophysical data and any evidence derived from nearby discoveries, competitive interests, and other indicia. The initial classification required by the Geothermal Steam Act of 1970 is presented.

Goodwin, L.H.; Haigler, L.B.; Rioux, R.L.; White, D.E.; Muffler, L.J.P.; Wayland, R.G.

1973-01-01T23:59:59.000Z

344

Information-theoretic approaches to SVM feature selection for metagenome read classification  

Science Conference Proceedings (OSTI)

Abstract: Analysis of DNA sequences isolated directly from the environment, known as metagenomics, produces a large quantity of genome fragments that need to be classified into specific taxa. Most composition-based classification methods use all features ... Keywords: Information theory, Metagenomics, Support vector machines

Elaine Garbarine; Joseph DePasquale; Vinay Gadia; Robi Polikar; Gail Rosen

2011-06-01T23:59:59.000Z

345

Document classification on relevance: a study on eye gaze patterns for reading  

Science Conference Proceedings (OSTI)

This paper presents a study that investigates the connection between the way that people read and the way that they understand content. The experiment consisted of having participants read some information on selected documents while an eye-tracking ... Keywords: artificial neural networks, document classification, gaze pattern, reading behavior, relevance, statistical analysis

Daniel Fahey; Tom Gedeon; Dingyun Zhu

2011-11-01T23:59:59.000Z

346

Efficient semantic kernel-based text classification using matching pursuit KFDA  

Science Conference Proceedings (OSTI)

A number of powerful kernel-based learning machines, such as support vector machines (SVMs), kernel Fisher discriminant analysis (KFDA), have been proposed with competitive performance. However, directly applying existing attractive kernel approaches ... Keywords: efficient text classification, kernel method, matching pursuit KFDA, semantic kernel

Qing Zhang; Jianwu Li; Zhiping Zhang

2011-11-01T23:59:59.000Z

347

Automatic design of artificial neural networks and associative memories for pattern classification and pattern restoration  

Science Conference Proceedings (OSTI)

In this note we present our most recent advances in the automatic design of artificial neural networks (ANNs) and associative memories (AMs) for pattern classification and pattern recall. Particle Swarm Optimization (PSO), Differential Evolution (DE), ... Keywords: artificial neural networks, associative memories, evolutionary programming

Humberto Sossa; Beatriz A. Garro; Juan Villegas; Carlos Avils; Gustavo Olague

2012-06-01T23:59:59.000Z

348

Network-based classification of recurrent endometrial cancers using high-throughput DNA methylation data  

Science Conference Proceedings (OSTI)

DNA methylation, a well-studied mechanism of epigenetic regulation, plays important roles in cancer. Increased levels of global DNA methylation is observed in primary solid tumors including endometrial carcinomas and is generally associated with silencing ... Keywords: DNA methylation, Steiner tree, cancer recurrence, classification, protein-protein interaction network, random walk

Jianhua Ruan; Md. Jamiul Jahid; Fei Gu; Chengwei Lei; Yi-Wen Huang; Ya-Ting Hsu; David G. Mutch; Chun-Liang Chen; Nameer B. Kirma; Tim H. Huang

2012-10-01T23:59:59.000Z

349

The Classification of Land Cover Derived from High Resolution Remote Sensing Imagery  

Science Conference Proceedings (OSTI)

Remote sensing imagery is an attractive source of land cover information. High resolution sensing imagery provides more land cover detail than low resolution sensing imagery. Due to more complex and noisier spectral signatures for the former, new algorithms ... Keywords: Remote Sensing Imagery, Spectral Information, Spatial Information, Classification

Xia Jun; Liu Jinmei; Wang Guoyu; Li Jizhong

2011-03-01T23:59:59.000Z

350

Automated Cloud Classification of Global AVHRR Data Using a Fuzzy Logic Approach  

Science Conference Proceedings (OSTI)

A fuzzy logic classification (FLC) methodology is proposed to achieve the two goals of this paper: 1) to discriminate between clear sky and clouds in a 32 32 pixel array, or sample, of 1.1-km Advanced Very High Resolution Radiometer (AVHRR) ...

Bryan A. Baum; Vasanth Tovinkere; Jay Titlow; Ronald M. Welch

1997-11-01T23:59:59.000Z

351

A Windows program for calculation and classification of tourmaline-supergroup (IMA-2011)  

Science Conference Proceedings (OSTI)

A Microsoft Visual Basic program, WinTcac, has been developed to calculate structural formulae of tourmaline analyses based on the Subcommittee on Tourmaline Nomenclature (STN) of the International Mineralogical Association's Commission on New Minerals, ... Keywords: Classification, International Mineralogical Association (IMA), Normalization, Software, Tourmaline

Fuat Yavuz, Necati Karakaya, Demet K. Y?ld?r?m, Muazzez . Karakaya, Mustafa Kumral

2014-02-01T23:59:59.000Z

352

Bag-of-Visual-Words Models for Adult Image Classification and Filtering Thomas Deselaers1  

E-Print Network (OSTI)

types of images are allowed. In the literature, different porn image filtering tech- niques were features for porn image classification are pre- sented and used in a retrieval/nearest neighbour clas model to discriminate between different classes of content-type. 2 Porn Image Identification For porn

Deselaers, Thomas

353

Classification of total load demand profiles for war-ships based on pattern recognition methods  

Science Conference Proceedings (OSTI)

The classification of total load demand profiles for every type of war-ships is crucial information, because it is the necessary base for a series of studies and operations, such as load estimation, load shedding and power management systems. In this ... Keywords: adequacy measures, clustering algorithms, load profiles, pattern recognition, warship

G. J. Tsekouras; I. S. Karanasiou; F. D. Kanellos

2011-07-01T23:59:59.000Z

354

Improving the industrial classification of cork stoppers by using image processing and Neuro-Fuzzy computing  

Science Conference Proceedings (OSTI)

This paper presents a solution to a problem existing in the cork industry: cork stopper/disk classification according to their quality using a visual inspection system. Cork is a natural and heterogeneous (remarkable variability among different samples, ... Keywords: Automated visual inspection system, Cork industry, Image processing, Neuro-Fuzzy classifier, Stopper quality

Beatriz Paniagua; Miguel A. Vega-Rodrguez; Juan A. Gomez-Pulido; Juan M. Sanchez-Perez

2010-12-01T23:59:59.000Z

355

The generation of faceted classification schemes for use in the organisation of engineering design documents  

Science Conference Proceedings (OSTI)

Vast quantities of electronic information are generated and stored such that engineers may later retrieve, assimilate and ultimately utilise such information during their daily activities. Where term-based querying relies upon suitable query formulation, ... Keywords: Faceted classification, Information management, Knowledge management

M. D. Giess; P. J. Wild; C. A. Mcmahon

2008-10-01T23:59:59.000Z

356

PartialVolume Bayesian Classification of Material Mixtures in MR Volume Data using Voxel Histograms  

E-Print Network (OSTI)

geometric models and renderings from volume data. It also has the potential to make more­accurate volume.g., both muscle and fat; we compute the relative proportion of each material in the voxels. Second, we Collection Classification Model Building Volume Rendering/ Visualization Analysis ?? ?? @ @ @ R @ @ @ R

357

Classification of telemetric signals and their spectral density estimation with the help of wavelets  

Science Conference Proceedings (OSTI)

The present paper is concerned with a new technique intended for the spectral density estimation of telemetric signals with the help of the wavelet transform. We briefly revise basic information on classical spectral estimates based on the calculation ... Keywords: classification, spectral density estimation, telemetric signals, wavelets

V. V. Geppener; D. M. Klionsky; N. I. Oreshko

2012-10-01T23:59:59.000Z

358

A new classification pattern recognition methodology for power system typical load profiles  

Science Conference Proceedings (OSTI)

In this paper a new pattern recognition methodology is described for the classification of the daily chronological load curves of power systems, in order to estimate their respective representative daily load profiles, which can be mainly used for load ... Keywords: adaptive vector quantization, adequacy measures, clustering algorithms, fuzzy k-means, hierarchical clustering, k-means, load profiles, pattern recognition, self-organized maps

G. J. Tsekouras; F. D. Kanellos; V. T. Kontargyri; I. S. Karanasiou; A. D. Salis; N. E. Mastorakis

2008-12-01T23:59:59.000Z

359

Automated crime report analysis and classification for e-government and decision support  

Science Conference Proceedings (OSTI)

With an increasing number of anonymous crime tips and reports being filed and digitized, it is generally difficult for crime analysts to process and analyze crime reports efficiently. We are developing a decision support system (DSS), combining Natural ... Keywords: classification, natural language processing, similarity measures

Chih-Hao Ku; Gondy Leroy

2013-06-01T23:59:59.000Z

360

Automated sub-cellular phenotype classification: an introduction and recent results  

Science Conference Proceedings (OSTI)

The genomic sequencing revolution has led to rapid growth in sequencing of genes and proteins, and attention is now turning to the function of the encoded proteins. In this respect, microscope imaging of a protein's subcellular location is proving invaluable. ... Keywords: image classification, image statistics, machine learning, subcellular localisation, subcellular phenotype

N. Hamilton; R. Pantelic; K. Hanson; J. L. Fink; S. Karunaratne; R. D. Teasdale

2006-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Heritage Debris Classification Based on 3D Texture Feature and SVM  

Science Conference Proceedings (OSTI)

A heritage debris classification based on 3D texture feature and SVM is proposed in this paper. We compute the bidirectional histogram and correlation function of Lambertian, isotropic, randomly rough surfaces which are common in real-world scenes firstly, ... Keywords: heritage debris, 3D texture, SVM

Meng Li; Canjie Huang; Ping Fu; Suyan Yue

2008-08-01T23:59:59.000Z

362

Collaborative multi-agent rock facies classification from wireline well log data  

Science Conference Proceedings (OSTI)

Gas and oil reservoirs have been the focus of modeling efforts for decades as an attempt to locate zones with high volumes. Certain subsurface layers and layer sequences, such as those containing shale, are known to be impermeable to gas and/or liquid. ... Keywords: Applied artificial intelligence, Collaborative learning, Multi-agent systems, Rock classification, Well logs

Christopher M. Gifford; Arvin Agah

2010-10-01T23:59:59.000Z

363

Where's @wally?: a classification approach to geolocating users based on their social ties  

Science Conference Proceedings (OSTI)

This paper presents an approach to geolocating users of online social networks, based solely on their 'friendship' connections. We observe that users interact more regularly with those closer to themselves and hypothesise that, in many cases, a person's ... Keywords: Twitter, classification, geolocation, social networks, support vector machines

Dominic Rout; Kalina Bontcheva; Daniel Preo?iuc-Pietro; Trevor Cohn

2013-05-01T23:59:59.000Z

364

One class classification for anomaly detection: support vector data description revisited  

Science Conference Proceedings (OSTI)

The Support Vector Data Description (SVDD) has been introduced to address the problem of anomaly (or outlier) detection. It essentially fits the smallest possible sphere around the given data points, allowing some points to be excluded as outliers. Whether ... Keywords: anomaly detection, minimal sphere fitting, one class classification, outlier detection, support vector data description

Eric J. Pauwels; Onkar Ambekar

2011-08-01T23:59:59.000Z

365

Some new results on non-rigid correspondence and classification of curves  

Science Conference Proceedings (OSTI)

We present two new algorithms for correspondence and classification of planar curves in a non-rigid sense. In the first algorithm we define deforming energy based on aligning curves using certain of their properties, namely Multi-Step-Size Local Similarity ... Keywords: correspondence, curve alignment, dynamic programming, recognition

Xiqiang Zheng; Yunmei Chen; David Groisser; David Wilson

2005-11-01T23:59:59.000Z

366

Classification of Cabo Frio (Brazil) three-dimensional ocean features using single-slice acoustic observations  

E-Print Network (OSTI)

Classification of Cabo Frio (Brazil) three-dimensional ocean features using single-slice acoustic-000 Arraial do Cabo, RJ, Brazil, {lcalado, ana.claudia}@ieapm.mar.mil.br Acoustic tomography is now a well for an instantaneous sound speed field constructed from dynamical predictions for Cabo Frio, Brazil. The results show

Jesus, Sérgio M.

367

Online linear and quadratic discriminant analysis with adaptive forgetting for streaming classification  

Science Conference Proceedings (OSTI)

Advances in data technology have enabled streaming acquisition of real-time information in a wide range of settings, including consumer credit, electricity consumption, and internet user behavior. Streaming data consist of transiently observed, temporally ... Keywords: forgetting factor, linear discriminant analysis, online, streaming data, time-varying classification

Christoforos Anagnostopoulos; Dimitris K. Tasoulis; Niall M. Adams; Nicos G. Pavlidis; David J. Hand

2012-04-01T23:59:59.000Z

368

Bag of spatio-visual words for context inference in scene classification  

Science Conference Proceedings (OSTI)

In the ''bag of visual words (BoVW)'' representation each image is represented by an unordered set of visual words. In this paper, a novel approach to encode ordered spatial configurations of visual words in order to add context in the representation ... Keywords: Bag of spatio-visual words, Contextual descriptors, Ensembles' learning, High dimensional features' clustering, Scene classification, Spatial co-occurrence

A. Bolovinou; I. Pratikakis; S. Perantonis

2013-03-01T23:59:59.000Z

369

A comparative study for content-based dynamic spam classification using four machine learning algorithms  

Science Conference Proceedings (OSTI)

The growth of email users has resulted in the dramatic increasing of the spam emails during the past few years. In this paper, four machine learning algorithms, which are Naive Bayesian (NB), neural network (NN), support vector machine (SVM) and relevance ... Keywords: Nave Bayesian, Neural network, Relevance vector machine, Spam classification, Support vector machine

Bo Yu; Zong-ben Xu

2008-05-01T23:59:59.000Z

370

Automatic representation of semantic abstraction of geographical data by means of classification  

Science Conference Proceedings (OSTI)

Providing Geographical Information Systems (GIS) with the mechanisms for processing geographical data based on their semantic abstraction is a task that at present is carried out in a number of research given their scope of applications. Tackling this ... Keywords: classification, geographical data, ontology, semantic

Rainer Larin Fonseca; Eduardo Garea Llano

2010-11-01T23:59:59.000Z

371

Oceanic Rainfall Detection and Classification in Tropical and Subtropical Mesoscale Convective Systems Using Underwater Acoustic Methods  

Science Conference Proceedings (OSTI)

Measurements of the underwater sound produced by rain were made at three U.S. coastal sites in a study to determine the feasibility and limitations of the acoustic detection and classification of rainfall over water. In the analysis of the rain ...

Peter G. Black; John R. Proni; John C. Wilkerson; Christopher E. Samsury

1997-09-01T23:59:59.000Z

372

Against Classification Attacks: A Decision Tree Pruning Approach to Privacy Protection in Data Mining  

Science Conference Proceedings (OSTI)

Data-mining techniques can be used not only to study collective behavior about customers, but also to discover private information about individuals. In this study, we demonstrate that decision trees, a popular classification technique for data mining, ... Keywords: computers, data mining, databases/artificial intelligence, decision trees, entropy, privacy, probability, pruning, public sector, relative entropy, society

Xiao-Bai Li; Sumit Sarkar

2009-11-01T23:59:59.000Z

373

Objective measures, sensors and computational techniques for stress recognition and classification: A survey  

Science Conference Proceedings (OSTI)

Stress is a major growing concern in our day and age adversely impacting both individuals and society. Stress research has a wide range of benefits from improving personal operations, learning, and increasing work productivity to benefiting society - ... Keywords: Computational stress model, Pattern recognition, Stress classification, Stress computational techniques, Stress prediction, Stress sensors

Nandita Sharma; Tom Gedeon

2012-12-01T23:59:59.000Z

374

An Alert Classification System for Monitoring and Assessing the ENSO Cycle  

Science Conference Proceedings (OSTI)

An alert classification system for the ENSO cycle is introduced. The system includes watches, advisories, and a five-class intensity scale for warm and cold phases of the ENSO cycle. A watch is issued when conditions are favorable for the ...

V. E. Kousky; R. W. Higgins

2007-04-01T23:59:59.000Z

375

Sediment facies classification of a sandy shoreline by means of airborne imaging spectroscopy  

Science Conference Proceedings (OSTI)

Airborne imaging spectroscopy data (AISA Eagle and HyMap) were applied to classify the sediments of a sandy beach in seven sand type classes. On the AISA-Eagle data, several classification strategies were tried out and compared with each other. The best ...

B. Deronde; P. Kempeneers; R. Houhuys; J. -P. Henriet; V. Van Lancker

2008-08-01T23:59:59.000Z

376

An experimental comparison of classification algorithms for imbalanced credit scoring data sets  

Science Conference Proceedings (OSTI)

In this paper, we set out to compare several techniques that can be used in the analysis of imbalanced credit scoring data sets. In a credit scoring context, imbalanced data sets frequently occur as the number of defaulting loans in a portfolio is usually ... Keywords: Benchmarking, Classification, Credit scoring, Imbalanced datasets

Iain Brown; Christophe Mues

2012-02-01T23:59:59.000Z

377

Power quality disturbances classification based on S-transform and probabilistic neural network  

Science Conference Proceedings (OSTI)

Classifying power quality (PQ) disturbances is one of the most important issues for power quality control. A novel high-performance classification system based on the S-transform and a probabilistic neural network (PNN) is proposed. The original power ... Keywords: Power quality, Power quality disturbances, Probabilistic neural network, S-transform

Nantian Huang; Dianguo Xu; Xiaosheng Liu; Lin Lin

2012-12-01T23:59:59.000Z

378

Cost-Sensitive Classification Methods for the Detection of Smuggled Nuclear Material in Cargo Containers  

E-Print Network (OSTI)

Classification problems arise in so many different parts of life from sorting machine parts to diagnosing a disease. Humans make these classifications utilizing vast amounts of data, filtering observations for useful information, and then making a decision based on a subjective level of cost/risk of classifying objects incorrectly. This study investigates the translation of the human decision process into a mathematical problem in the context of a border security problem: How does one find special nuclear material being smuggled inside large cargo crates while balancing the cost of invasively searching suspect containers against the risk of al lowing radioactive material to escape detection? This may be phrased as a classification problem in which one classifies cargo containers into two categories those containing a smuggled source and those containing only innocuous cargo. This task presents numerous challenges, e.g., the stochastic nature of radiation and the low signal-to-noise ratio caused by background radiation and cargo shielding. In the course of this work, we will break the analysis of this problem into three major sections the development of an optimal decision rule, the choice of most useful measurements or features, and the sensitivity of developed algorithms to physical variations. This will include an examination of how accounting for the cost/risk of a decision affects the formulation of our classification problem. Ultimately, a support vector machine (SVM) framework with F -score feature selection will be developed to provide nearly optimal classification given a constraint on the reliability of detection provided by our algorithm. In particular, this can decrease the fraction of false positives by an order of magnitude over current methods. The proposed method also takes into account the relationship between measurements, whereas current methods deal with detectors independently of one another.

Webster, Jennifer B

2013-08-01T23:59:59.000Z

379

Classification of oil reserves and resources in the former Soviet Union  

SciTech Connect

The terminology and principles of classification of oil reserves and resources that are presently used in Russia and other countries of the former Soviet Union (FSU) differ from those in the Western countries. This difference stems from the specificity of the Soviet practice in exploration, assessment, and keeping a record of resources that were controlled by the centralized government. In the FSU, the fundamental approach to the assessment of hydrocarbon resources is traditionally based on the extent to which the resources are explored. Such important factors as thickness of separate reservoir beds, their quality, physical characteristics of oil, the recovery factor, and the economic efficiency are not considered. Owing to this approach, the resource base appeared to be strongly exaggerated due to inclusion of reserves and resources that are neither reliable nor technologically and economically viable. A critical analysis of the long-term dynamics of reserves in the leading oil-producing regions of Russia, including west Siberia, shows a negative effect of the obsolete classification and errors in resource assessment on the development and production of oil fields. The classification of hydrocarbon resources presently used in Russia should be changed so that the principles of the new classification would be similar to those commonly accepted in the oil business. A proposed new classification scheme will make the assessment of resource base for oil production in Russia more reliable. This scheme uses the principles of differentiation and assessment of hydrocarbon resources that are conventional in the world. Because no method of resource assessment is precise, the results of assessment should be presented in a probabilistic form or, at least, as an interval, but not as a single number assessment that is a common practice at present.

Khalimov, E.M. (Institute of Geology and Exploration of Combustible Fuels, Moscow (Russian Federation))

1993-09-01T23:59:59.000Z

380

Rangely Oilfield Geothermal Area | Open Energy Information  

Open Energy Info (EERE)

Well Field Information Development Area: Number of Production Wells: Number of Injection Wells: Number of Replacement Wells: Average Temperature of Geofluid: Sanyal...

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Haleakala Volcano Geothermal Area | Open Energy Information  

Open Energy Info (EERE)

Well Field Information Development Area: Number of Production Wells: Number of Injection Wells: Number of Replacement Wells: Average Temperature of Geofluid: Sanyal...

382

Mauna Loa Southwest Rift Geothermal Area | Open Energy Information  

Open Energy Info (EERE)

Well Field Information Development Area: Number of Production Wells: Number of Injection Wells: Number of Replacement Wells: Average Temperature of Geofluid: Sanyal...

383

Fast communication: Joint design of Gaussianized spectrum-based features and least-square linear classifier for automatic acoustic environment classification in hearing aids  

Science Conference Proceedings (OSTI)

In this paper we propose a method to generate a novel set of features in order to improve sound classification in digital hearing aids. The approach is based on the fact that those classification algorithms whose design consists in minimizing the mean ... Keywords: Audio signals, Digital hearing aids, Feature extraction, Sound classification, Spectrum Gaussianization

Lucas Cuadra; Roberto Gil-Pita; Enrique Alexandre; Manuel Rosa-Zurera

2010-08-01T23:59:59.000Z

384

CONSTRUCTION OF A CALIBRATED PROBABILISTIC CLASSIFICATION CATALOG: APPLICATION TO 50k VARIABLE SOURCES IN THE ALL-SKY AUTOMATED SURVEY  

SciTech Connect

With growing data volumes from synoptic surveys, astronomers necessarily must become more abstracted from the discovery and introspection processes. Given the scarcity of follow-up resources, there is a particularly sharp onus on the frameworks that replace these human roles to provide accurate and well-calibrated probabilistic classification catalogs. Such catalogs inform the subsequent follow-up, allowing consumers to optimize the selection of specific sources for further study and permitting rigorous treatment of classification purities and efficiencies for population studies. Here, we describe a process to produce a probabilistic classification catalog of variability with machine learning from a multi-epoch photometric survey. In addition to producing accurate classifications, we show how to estimate calibrated class probabilities and motivate the importance of probability calibration. We also introduce a methodology for feature-based anomaly detection, which allows discovery of objects in the survey that do not fit within the predefined class taxonomy. Finally, we apply these methods to sources observed by the All-Sky Automated Survey (ASAS), and release the Machine-learned ASAS Classification Catalog (MACC), a 28 class probabilistic classification catalog of 50,124 ASAS sources in the ASAS Catalog of Variable Stars. We estimate that MACC achieves a sub-20% classification error rate and demonstrate that the class posterior probabilities are reasonably calibrated. MACC classifications compare favorably to the classifications of several previous domain-specific ASAS papers and to the ASAS Catalog of Variable Stars, which had classified only 24% of those sources into one of 12 science classes.

Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Brink, Henrik; Crellin-Quick, Arien [Astronomy Department, University of California, Berkeley, CA 94720-3411 (United States); Butler, Nathaniel R., E-mail: jwrichar@stat.berkeley.edu [School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287 (United States)

2012-12-15T23:59:59.000Z

385

Screening tests for hazard classification of complex waste materials - Selection of methods  

Science Conference Proceedings (OSTI)

In this study we describe the development of an alternative methodology for hazard characterization of waste materials. Such an alternative methodology for hazard assessment of complex waste materials is urgently needed, because the lack of a validated instrument leads to arbitrary hazard classification of such complex waste materials. False classification can lead to human and environmental health risks and also has important financial consequences for the waste owner. The Hazardous Waste Directive (HWD) describes the methodology for hazard classification of waste materials. For mirror entries the HWD classification is based upon the hazardous properties (H1-15) of the waste which can be assessed from the hazardous properties of individual identified waste compounds or - if not all compounds are identified - from test results of hazard assessment tests performed on the waste material itself. For the latter the HWD recommends toxicity tests that were initially designed for risk assessment of chemicals in consumer products (pharmaceuticals, cosmetics, biocides, food, etc.). These tests (often using mammals) are not designed nor suitable for the hazard characterization of waste materials. With the present study we want to contribute to the development of an alternative and transparent test strategy for hazard assessment of complex wastes that is in line with the HWD principles for waste classification. It is necessary to cope with this important shortcoming in hazardous waste classification and to demonstrate that alternative methods are available that can be used for hazard assessment of waste materials. Next, by describing the pros and cons of the available methods, and by identifying the needs for additional or further development of test methods, we hope to stimulate research efforts and development in this direction. In this paper we describe promising techniques and argument on the test selection for the pilot study that we have performed on different types of waste materials. Test results are presented in a second paper. As the application of many of the proposed test methods is new in the field of waste management, the principles of the tests are described. The selected tests tackle important hazardous properties but refinement of the test battery is needed to fulfil the a priori conditions.

Weltens, R., E-mail: reinhilde.weltens@vito.be [VITO Flemish Institute for Technological Research, Boeretang 200, B 2400 Mol (Belgium); Vanermen, G.; Tirez, K. [VITO Flemish Institute for Technological Research, Boeretang 200, B 2400 Mol (Belgium); Robbens, J. [University of Antwerp - Laboratory for Ecophysiology, Biochemistry and Toxicology, Groenenborgerlaan 171, B2020 Antwerp (Belgium); Deprez, K.; Michiels, L. [University of Hasselt - Biomedical Research Institute, University Hasselt, Campus Diepenbeek, Agoralaan A, B3590 Diepenbeek (Belgium)

2012-12-15T23:59:59.000Z

386

Online Discriminative Dictionary Learning for Image Classification Based on Block-Coordinate Descent Method  

E-Print Network (OSTI)

Previous researches have demonstrated that the framework of dictionary learning with sparse coding, in which signals are decomposed as linear combinations of a few atoms of a learned dictionary, is well adept to reconstruction issues. This framework has also been used for discrimination tasks such as image classification. To achieve better performances of classification, experts develop several methods to learn a discriminative dictionary in a supervised manner. However, another issue is that when the data become extremely large in scale, these methods will be no longer effective as they are all batch-oriented approaches. For this reason, we propose a novel online algorithm for discriminative dictionary learning, dubbed \\textbf{ODDL} in this paper. First, we introduce a linear classifier into the conventional dictionary learning formulation and derive a discriminative dictionary learning problem. Then, we exploit an online algorithm to solve the derived problem. Unlike the most existing approaches which updat...

Kong, Shu

2012-01-01T23:59:59.000Z

387

LED-Induced Fluorescence System for Tea Classification and Quality Assessment  

E-Print Network (OSTI)

A fluorescence system is developed by using several light emitting diodes (LEDs) with different wavelengths as excitation light sources. The fluorescence detection head consists of multi LED light sources and a multimode fiber for fluorescence collection, where the LEDs and the corresponding filters can be easily chosen to get appropriate excitation wavelengths for different applications. By analyzing fluorescence spectra with the principal component analysis method, the system is utilized in the classification of four types of green tea beverages and two types of black tea beverages. Qualities of the Xihu Longjing tea leaves of different grades, as well as the corresponding liquid tea samples, are studied to further investigate the ability and application of the system in the evaluation of classification/quality of tea and other foods.

Dong, Yongjiang; Mei, Liang; Feng, Chao; Yan, Chunsheng; He, Sailing

2013-01-01T23:59:59.000Z

388

GMM based SPECT image classification for the diagnosis of Alzheimer's disease  

Science Conference Proceedings (OSTI)

We present a novel classification method of SPECT images based on Gaussian mixture models (GMM) for the diagnosis of Alzheimer's disease. The aims of the model-based approach for density estimation is to automatically select regions of interest (ROIs) ... Keywords: 87.19.xr, 87.57.R-, 87.57.nm, 87.57.uh, Alzheimer's disease, EM algorithm, Gaussian mixture model, SPECT, Support vector machines (SVMs)

J. M. Grriz; F. Segovia; J. Ramrez; A. Lassl; D. Salas-Gonzalez

2011-03-01T23:59:59.000Z

389

Risk haplotype pattern discovery for gene mapping by recursive partitioning method based on weighted classification trees  

Science Conference Proceedings (OSTI)

In this paper, we present a combinatorial approach based on recursive weighted longest prefix trees (RWLPT) for mining a massive genetic marker data. Given a case and a control chromosome dataset, we develop a fast recursive permutation algorithm ... Keywords: combinatorial optimisation, disease susceptibility genes, gene mapping, genetic markers, haplotype clusters, haplotype-disease association, multilocus SNP analysis, non-numerical algorithms, recursive partitioning, risk haplotype pattern discovery, weighted classification trees

Tran Trang; Hoang Ngoc Minh

2010-02-01T23:59:59.000Z

390

Context-based automated defect classification system using multiple morphological masks  

DOE Patents (OSTI)

Automatic detection of defects during the fabrication of semiconductor wafers is largely automated, but the classification of those defects is still performed manually by technicians. This invention includes novel digital image analysis techniques that generate unique feature vector descriptions of semiconductor defects as well as classifiers that use these descriptions to automatically categorize the defects into one of a set of pre-defined classes. Feature extraction techniques based on multiple-focus images, multiple-defect mask images, and segmented semiconductor wafer images are used to create unique feature-based descriptions of the semiconductor defects. These feature-based defect descriptions are subsequently classified by a defect classifier into categories that depend on defect characteristics and defect contextual information, that is, the semiconductor process layer(s) with which the defect comes in contact. At the heart of the system is a knowledge database that stores and distributes historical semiconductor wafer and defect data to guide the feature extraction and classification processes. In summary, this invention takes as its input a set of images containing semiconductor defect information, and generates as its output a classification for the defect that describes not only the defect itself, but also the location of that defect with respect to the semiconductor process layers.

Gleason, Shaun S. (Knoxville, TN); Hunt, Martin A. (Knoxville, TN); Sari-Sarraf, Hamed (Lubbock, TX)

2002-01-01T23:59:59.000Z

391

Recursive Partitioning Analysis for New Classification of Patients With Esophageal Cancer Treated by Chemoradiotherapy  

SciTech Connect

Background: The 7th edition of the American Joint Committee on Cancer staging system does not include lymph node size in the guidelines for staging patients with esophageal cancer. The objectives of this study were to determine the prognostic impact of the maximum metastatic lymph node diameter (ND) on survival and to develop and validate a new staging system for patients with esophageal squamous cell cancer who were treated with definitive chemoradiotherapy (CRT). Methods: Information on 402 patients with esophageal cancer undergoing CRT at two institutions was reviewed. Univariate and multivariate analyses of data from one institution were used to assess the impact of clinical factors on survival, and recursive partitioning analysis was performed to develop the new staging classification. To assess its clinical utility, the new classification was validated using data from the second institution. Results: By multivariate analysis, gender, T, N, and ND stages were independently and significantly associated with survival (p < 0.05). The resulting new staging classification was based on the T and ND. The four new stages led to good separation of survival curves in both the developmental and validation datasets (p < 0.05). Conclusions: Our results showed that lymph node size is a strong independent prognostic factor and that the new staging system, which incorporated lymph node size, provided good prognostic power, and discriminated effectively for patients with esophageal cancer undergoing CRT.

Nomura, Motoo, E-mail: excell@hkg.odn.ne.jp [Department of Radiology, Kansai Medical University, Hirakata (Japan) [Department of Radiology, Kansai Medical University, Hirakata (Japan); Department of Clinical Oncology, Aichi Cancer Center Hospital, Nagoya (Japan); Department of Radiation Oncology, Aichi Cancer Center Hospital, Nagoya (Japan); Shitara, Kohei [Department of Clinical Oncology, Aichi Cancer Center Hospital, Nagoya (Japan)] [Department of Clinical Oncology, Aichi Cancer Center Hospital, Nagoya (Japan); Kodaira, Takeshi [Department of Radiation Oncology, Aichi Cancer Center Hospital, Nagoya (Japan)] [Department of Radiation Oncology, Aichi Cancer Center Hospital, Nagoya (Japan); Kondoh, Chihiro; Takahari, Daisuke; Ura, Takashi [Department of Clinical Oncology, Aichi Cancer Center Hospital, Nagoya (Japan)] [Department of Clinical Oncology, Aichi Cancer Center Hospital, Nagoya (Japan); Kojima, Hiroyuki; Kamata, Minoru [Department of Radiology, Kansai Medical University, Hirakata (Japan)] [Department of Radiology, Kansai Medical University, Hirakata (Japan); Muro, Kei [Department of Clinical Oncology, Aichi Cancer Center Hospital, Nagoya (Japan)] [Department of Clinical Oncology, Aichi Cancer Center Hospital, Nagoya (Japan); Sawada, Satoshi [Department of Radiology, Kansai Medical University, Hirakata (Japan)] [Department of Radiology, Kansai Medical University, Hirakata (Japan)

2012-11-01T23:59:59.000Z

392

Automated supervised classification of variable stars II. Application to the OGLE database  

E-Print Network (OSTI)

We aim to extend and test the classifiers presented in a previous work against an independent dataset. We complement the assessment of the validity of the classifiers by applying them to the set of OGLE light curves treated as variable objects of unknown class. The results are compared to published classification results based on the so-called extractor methods.Two complementary analyses are carried out in parallel. In both cases, the original time series of OGLE observations of the Galactic bulge and Magellanic Clouds are processed in order to identify and characterize the frequency components. In the first approach, the classifiers are applied to the data and the results analyzed in terms of systematic errors and differences between the definition samples in the training set and in the extractor rules. In the second approach, the original classifiers are extended with colour information and, again, applied to OGLE light curves. We have constructed a classification system that can process huge amounts of time series in negligible time and provide reliable samples of the main variability classes. We have evaluated its strengths and weaknesses and provide potential users of the classifier with a detailed description of its characteristics to aid in the interpretation of classification results. Finally, we apply the classifiers to obtain object samples of classes not previously studied in the OGLE database and analyse the results. We pay specific attention to the B-stars in the samples, as their pulsations are strongly dependent on metallicity.

L. M. Sarro; J. Debosscher; M. Lopez; C. Aerts

2008-06-20T23:59:59.000Z

393

KEPLER ECLIPSING BINARY STARS. III. CLASSIFICATION OF KEPLER ECLIPSING BINARY LIGHT CURVES WITH LOCALLY LINEAR EMBEDDING  

Science Conference Proceedings (OSTI)

We present an automated classification of 2165 Kepler eclipsing binary (EB) light curves that accompanied the second Kepler data release. The light curves are classified using locally linear embedding, a general nonlinear dimensionality reduction tool, into morphology types (detached, semi-detached, overcontact, ellipsoidal). The method, related to a more widely used principal component analysis, produces a lower-dimensional representation of the input data while preserving local geometry and, consequently, the similarity between neighboring data points. We use this property to reduce the dimensionality in a series of steps to a one-dimensional manifold and classify light curves with a single parameter that is a measure of 'detachedness' of the system. This fully automated classification correlates well with the manual determination of morphology from the data release, and also efficiently highlights any misclassified objects. Once a lower-dimensional projection space is defined, the classification of additional light curves runs in a negligible time and the method can therefore be used as a fully automated classifier in pipeline structures. The classifier forms a tier of the Kepler EB pipeline that pre-processes light curves for the artificial intelligence based parameter estimator.

Matijevic, Gal [Faculty of Mathematics and Physics, University of Ljubljana, Jadranska 19, 1000 Ljubljana (Slovenia); Prsa, Andrej [Department of Astronomy and Astrophysics, Villanova University, 800 E Lancaster Ave, Villanova, PA 19085 (United States); Orosz, Jerome A.; Welsh, William F. [Department of Astronomy, San Diego State University, 5500 Campanile Dr., San Diego, CA 92182 (United States); Bloemen, Steven [Instituut voor Sterrenkunde, KU Leuven, Celestijnenlaan 200 D, B-3001 Leuven (Belgium); Barclay, Thomas, E-mail: gal.matijevic@fmf.uni-lj.si, E-mail: andrej.prsa@villanova.edu [NASA Ames Research Center/BAER Institute, Moffett Field, CA 94035 (United States)

2012-05-15T23:59:59.000Z

394

Image Classification Using SVMs: One-against-One Vs One-against-All  

E-Print Network (OSTI)

Support Vector Machines (SVMs) are a relatively new supervised classification technique to the land cover mapping community. They have their roots in Statistical Learning Theory and have gained prominence because they are robust, accurate and are effective even when using a small training sample. By their nature SVMs are essentially binary classifiers, however, they can be adopted to handle the multiple classification tasks common in remote sensing studies. The two approaches commonly used are the One-Against-One (1A1) and One-Against-All (1AA) techniques. In this paper, these approaches are evaluated in as far as their impact and implication for land cover mapping. The main finding from this research is that whereas the 1AA technique is more predisposed to yielding unclassified and mixed pixels, the resulting classification accuracy is not significantly different from 1A1 approach. It is the authors conclusion therefore that ultimately the choice of technique adopted boils down to personal preference and the...

Anthony, Gidudu; Tshilidzi, Marwala

2007-01-01T23:59:59.000Z

395

Ward-Rainey N. Proposal for a new hierarchic classification system, Actinobacteria classis nov  

E-Print Network (OSTI)

A new hierarchic classification structure for the taxa between the taxonomic levels of genus and class is proposed for the actinomycete line of descent as defined by analysis of small subunit (16s) rRNA and genes coding for this molecule (rDNA). While the traditional circumscription of a genus of the actinomycete subphylum is by and large in accord with the 16s rRNA/rDNA-based phylogenetic clustering of these organisms, most of the higher taxa proposed in the past do not take into account the phylogenetic clustering of genera. The rich chemical, morphological and physiological diversity of phylogenetically closely related genera makes the description of families and higher taxa so broad that they become meaningless for the description of the enclosed taxa. Here we present a classification system in which phylogenetically neighboring taxa at the genus level are clustered into families, suborders, orders, subclasses, and a class irrespective of those phenotypic characteristics on which the delineation of taxa has been based in the past. Rather than being based on a listing of a wide array of chemotaxonomic, morphological, and physiological properties, the delineation is based solely on 16s rDNA/rRNA sequence-based phylogenetic clustering and the presence of taxon-specific 16s rDNA/RNA signature nucleotides. In their publication On the nature of global classification, Wheelis et al. (177) based the definition of higher taxa on the

Erko Stackebrandt; Fred A. Rainey; Naomi; L. Ward-rainey

1997-01-01T23:59:59.000Z

396

Parametrization and Classification of 20 Billion LSST Objects: Lessons from SDSS  

E-Print Network (OSTI)

The Large Synoptic Survey Telescope (LSST) will be a large, wide-field ground-based system designed to obtain, starting in 2015, multiple images of the sky that is visible from Cerro Pachon in Northern Chile. About 90% of the observing time will be devoted to a deep-wide-fast survey mode which will observe a 20,000 deg$^2$ region about 1000 times during the anticipated 10 years of operations (distributed over six bands, $ugrizy$). Each 30-second long visit will deliver 5$\\sigma$ depth for point sources of $r\\sim24.5$ on average. The co-added map will be about 3 magnitudes deeper, and will include 10 billion galaxies and a similar number of stars. We discuss various measurements that will be automatically performed for these 20 billion sources, and how they can be used for classification and determination of source physical and other properties. We provide a few classification examples based on SDSS data, such as color classification of stars, color-spatial proximity search for wide-angle binary stars, orbital...

Ivezic, Z; Becker, A C

2008-01-01T23:59:59.000Z

397

Prototyping a Generic, Unified Land Surface Classification and Screening Methodology for GPM-Era Microwave Land Precipitation Retrieval Algorithms  

Science Conference Proceedings (OSTI)

A prototype generic, unified land surface classification and screening methodology for Global Precipitation Measurement (GPM)-era microwave land precipitation retrieval algorithms by using ancillary datasets is developed. As an alternative to the ...

Arief Sudradjat; Nai-Yu Wang; Kaushik Gopalan; Ralph R. Ferraro

2011-06-01T23:59:59.000Z

398

Context inclusive function evaluation: a case study with EM-based multi-scale multi-granular image classification  

Science Conference Proceedings (OSTI)

Many statistical queries such as maximum likelihood estimation involve finding the best candidate model given a set of candidate models and a quality estimation function. This problem is common in important applications like land-use classification at ...

Vijay Gandhi; James M. Kang; Shashi Shekhar; Junchang Ju; Eric D. Kolaczyk; Sucharita Gopal

2009-10-01T23:59:59.000Z

399

Precipitation Classification and Quantification Using X-band Dual-Polarization Weather Radar: Application in the Hydrometeorology Testbed  

Science Conference Proceedings (OSTI)

This paper presents new methods for rainfall estimation from X-band dual-polarization radar observations along with advanced techniques for quality control, hydrometeor classification, and estimation of specific differential phase. Data collected ...

S. Lim; R. Cifelli; V. Chandrasekar; S. Y. Matrosov

400

2011 Special Issue: A just-in-time adaptive classification system based on the intersection of confidence intervals rule  

Science Conference Proceedings (OSTI)

Classification systems meant to operate in nonstationary environments are requested to adapt when the process generating the observed data changes. A straightforward form of adaptation implementing the instance selection approach suggests releasing the ... Keywords: Adaptive classifiers, Change-detection tests

Cesare Alippi; Giacomo Boracchi; Manuel Roveri

2011-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

A new fuzzy logic hydrometeor classification scheme applied to the French X, C and S-band polarimetric radars  

Science Conference Proceedings (OSTI)

A new fuzzy logic hydrometeor classification algorithm is proposed that takes into account data-based membership functions, measurement conditions and three-dimensional temperature information provided by a high-resolution non-hydrostatic ...

Hassan Al-Sakka; Abdel-Amin Boumahmoud; Batrice Fradon; Stephen J. Frasier; Pierre Tabary

402

A Continental-Scale Classification of Rainfall Seasonality Regimes in Africa Based on Gridded Precipitation and Land Surface Temperature Products  

Science Conference Proceedings (OSTI)

A classification of rainfall seasonality regimes in Africa was derived from gridded rainfall and land surface temperature products. By adapting a method that goes back to Walter and Lieths approach of presenting climatic diagrams, relationships ...

Stefanie M. Herrmann; Karen I. Mohr

2011-12-01T23:59:59.000Z

403

Scrap Classification  

Science Conference Proceedings (OSTI)

...replaced over the years by a number of semired brass alloys, and thus current red brass scrap might have a typical content of 80 to 83% Cu, 3 to 5% Sn, 3 to 6% Pb, and 5 to 8% Zn....

404

Product Classification  

Science Conference Proceedings (OSTI)

Table 1   Major types and uses of pipe...Uses Standard Industrial or residential water steam, oil, or gas

405

Product Classification  

Science Conference Proceedings (OSTI)

Table 1 Major types and uses of pipe...or residential water steam, oil, or gas transmission; distribution or service lines; structural uses Special Conduit, piling, pipe for nipples, and other Line Oil- or gas-transmission pipe, water-main pipe Oil country tubular goods Drill pipe, casing, tubing Water well Drive pipe, driven-well pipe,...

406

Understanding Classification  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

nuclear weapons program, the production of special nuclear material, naval nuclear propulsion, and space power systems. Examples of RD include the designs of nuclear weapons, the...

407

Rouge Classification  

Science Conference Proceedings (OSTI)

Table 8   Effect of type 316L stainless steel surface finish on iron release...water in 24 h Specimen surface finish Iron, ng/cm 2 360 grit (0.254 μm, or 10 μin., R a ) MP only (a) 1190 180 grit (0.635 μm, or 25 μin., R a ) MP only 1090 180 grit (0.635 μm, or 25 μin., R a ) MP+full electroplish 990 2B strip finish (~0.254 μm, or ~10 μin., R a )+HNO 3 passivation, 49 °C...

408

Neural Network-Based Classification of Single-Phase Distribution Transformer Fault Data  

E-Print Network (OSTI)

The ultimate goal of this research is to develop an online, non-destructive, incipient fault detection system that is able to detect incipient faults in transformers and other electric equipment before the faults become catastrophic. With the condition assessment capability of the detection system, operators are equipped with better information during their decision-making process. Corrective actions are taken prior to transformer and equipment failures to prevent down-time and reduce operating and maintenance costs. Diagnosis of data associated with incipient failures is essential to develop an efficient, non-destructive, and online system. Field testing data were collected from controlled experiment and simulation data from mathematical models are studied. This thesis presents a data-mining approach to analyze field recorded and simulation data to characterize incipient fault data and study its properties. A supervised classifier using neural network (NN) toolbox in Matlab provides an efficient and accurate classification method to separate monitoring signal data into clusters base on their properties. However, raw data collected from the field and simulations will create too many dimensions and inputs to the neural network and make it a complex and over-generalized classification. Therefore, features are extracted from the data set, and these features are formed into feature clusters in order to identify patterns in signals as they are related to various physical behaviors of the system. The similarity between recognized patterns and patterns shown in future monitoring signals will trigger the warning of initializing or developing faults in transformers or equipment. This thesis demonstrates how different features were extracted from the raw data using various analysis techniques in both time domain and time-frequency domain, and the design and implementation of a neural network-based classification method. The classifier outputs are classes of data being separated into groups based on their characteristics and behaviors. Meaning of different classes is also explained in this thesis.

Zhang, Xujia

2006-08-16T23:59:59.000Z

409

Inductive entanglement classification of four qubits under stochastic local operations and classical communication  

Science Conference Proceedings (OSTI)

Using an inductive approach to classify multipartite entangled states under stochastic local operations and classical communication introduced recently by the authors [Phys. Rev. A 74, 052336 (2006)], we give the complete classification of four-qubit entangled pure states. Apart from the expected degenerate classes, we show that there exist eight inequivalent ways to entangle four qubits. In this respect, permutation symmetry is taken into account and states with a structure differing only by parameters inside a continuous set are considered to belong to the same class.

Lamata, L.; Leon, J. [Instituto de Matematicas y Fisica Fundamental, CSIC, Serrano 113-bis, 28006 Madrid (Spain); Salgado, D. [Dpto. Fisica Teorica, Universidad Autonoma de Madrid, 28049 Cantoblanco, Madrid (Spain); Solano, E. [Physics Department, ASC, and CeNS, Ludwig-Maximilians-Universitaet, Theresienstrasse 37, 80333 Munich (Germany); Seccion Fisica, Departamento de Ciencias, Pontificia Universidad Catolica del Peru, Apartado Postal 1761, Lima (Peru)

2007-02-15T23:59:59.000Z

410

Stochastic local operations and classical communication equations and classification of even $n$ qubits  

E-Print Network (OSTI)

For any even $n$ qubits we establish four SLOCC equations and construct four SLOCC polynomials (not complete) of degree $2^{n/2}$, which can be exploited for SLOCC classification (not complete) of any even $n$ qubits. In light of the SLOCC equations, we propose several different genuine entangled states of even $n$ qubits and show that they are inequivalent to the $|GHZ>$, $|W>$, or $|l,n>$ (the symmetric Dicke states with $l$ excitations) under SLOCC via the vanishing or not of the polynomials. The absolute values of the polynomials can be considered as entanglement measures.

X. Li; D. Li

2009-10-22T23:59:59.000Z

411

Improved prognostic classification of breast cancer defined by antagonistic activation patterns of immune response pathway modules  

E-Print Network (OSTI)

RESEARCH ARTICLE Open Access Improved prognostic classification of breast cancer defined by antagonistic activation patterns of immune response pathway modules Andrew E Teschendorff1,8*, Sergio Gomez2, Alex Arenas2,3,4, Dorraya El-Ashry5, Marcus... that consistency and trends in mRNA expres- sion levels of interacting proteins may be used to infer pathway activity [6-8]. In this work we refer to both the perturbation signatures and molecular interaction mod- els as model signatures. These same studies...

Teschendorff, Andrew E; Gomez, Sergio; Arenas, Alex; El-Ashry, Dorraya; Schmidt, Marcus; Gehrmann, Mathias; Caldas, Carlos

2010-11-04T23:59:59.000Z

412

An Evaluation of Alternative Classification Methods for Routine Low Level Waste from the Nuclear Power Industry  

Science Conference Proceedings (OSTI)

This report investigates the feasibility of classifying all routine nuclear power plant low level waste, including Class B and Class C waste, as Class A low level waste within the framework of NRC regulatory requirements. A change in classification could expand disposal venues and reduce the uncertainty of future disposal. The report shows that all of the waste, when managed as a composite stream, will meet the requirements for Class A disposal without leaving a portion of the stream orphaned to on-site ...

2007-11-19T23:59:59.000Z

413

Net-Zero Energy Buildings: A Classification System Based on Renewable Energy Supply Options  

SciTech Connect

A net-zero energy building (NZEB) is a residential or commercial building with greatly reduced energy needs. In such a building, efficiency gains have been made such that the balance of energy needs can be supplied with renewable energy technologies. Past work has developed a common NZEB definition system, consisting of four well-documented definitions, to improve the understanding of what net-zero energy means. For this paper, we created a classification system for NZEBs based on the renewable sources a building uses.

Pless, S.; Torcellini, P.

2010-06-01T23:59:59.000Z

414

Automated supervised classification of variable stars II. Application to the OGLE database  

E-Print Network (OSTI)

We aim to extend and test the classifiers presented in a previous work against an independent dataset. We complement the assessment of the validity of the classifiers by applying them to the set of OGLE light curves treated as variable objects of unknown class. The results are compared to published classification results based on the so-called extractor methods.Two complementary analyses are carried out in parallel. In both cases, the original time series of OGLE observations of the Galactic bulge and Magellanic Clouds are processed in order to identify and characterize the frequency components. In the first approach, the classifiers are applied to the data and the results analyzed in terms of systematic errors and differences between the definition samples in the training set and in the extractor rules. In the second approach, the original classifiers are extended with colour information and, again, applied to OGLE light curves. We have constructed a classification system that can process huge amounts of tim...

Sarro, L M; Lpez, M; Aerts, C

2008-01-01T23:59:59.000Z

415

Hazard Classification of the Remote Handled Low-Level Waste Disposal Facility  

Science Conference Proceedings (OSTI)

The Battelle Energy Alliance (BEA) at the Idaho National Laboratory (INL) is constructing a new facility to replace remote-handled low-level radioactive waste disposal capability for INL and Naval Reactors Facility operations. Current disposal capability at the Radioactive Waste Management Complex (RWMC) will continue until the facility is full or closed for remediation (estimated at approximately fiscal year 2015). Development of a new onsite disposal facility is the highest ranked alternative and will provide RH-LLW disposal capability and will ensure continuity of operations that generate RH-LLW for the foreseeable future. As a part of establishing a safety basis for facility operations, the facility will be categorized according to DOE-STD-1027-92. This classification is important in determining the scope of analyses performed in the safety basis and will also dictate operational requirements of the completed facility. This paper discusses the issues affecting hazard classification in this nuclear facility and impacts of the final hazard categorization.

Boyd D. Christensen

2012-05-01T23:59:59.000Z

416

Non-fuel assembly components: 10 CFR 61.55 classification for waste disposal  

SciTech Connect

This document reports the results of laboratory radionuclide measurements on a representative group of non-fuel assembly (NFA) components for the purposes of waste classification. This document also provides a methodology to estimate the radionuclide inventory of NFA components, including those located outside the fueled region of a nuclear reactor. These radionuclide estimates can then be used to determine the waste classification of NFA components for which there are no physical measurements. Previously, few radionuclide inventory measurements had been performed on NFA components. For this project, recommended scaling factors were selected for the ORIGEN2 computer code that result in conservative estimates of radionuclide concentrations in NFA components. These scaling factors were based upon experimental data obtained from the following NFA components: (1) a pressurized water reactor (PWR) burnable poison rod assembly, (2) a PVM rod cluster control assembly, and (3) a boiling water reactor cruciform control rod blade. As a whole, these components were found to be within Class C limits. Laboratory radionuclide measurements for these components are provided in detail.

Migliore, R.J.; Reid, B.D.; Fadeff, S.K.; Pauley, K.A.; Jenquin, U.P.

1994-09-01T23:59:59.000Z

417

Classification concepts from object oriented software design applied to engineering design  

E-Print Network (OSTI)

The objectives of this research were to study and explore Object Oriented Design, as applied in software design, and identify those principles and concepts that could be applied in engineering design to make it more efficient. An examination of the object oriented software design philosophy, methodology and programming approach was therefore carried out. The Object Oriented Design features of Functions, Properties and Inheritance were identified as having potential value in reformatting engineering classification charts, so as to make them more useful to both neophyte and experienced engineering designers. Engineering components have evolved from their basic forms into families of components and sub-components. Classification charts are often used to represent these families. In most charts, only the names of the components are provided. The design engineer, when faced with the need to choose the best form or variant of an item on the list, has to go to disparate sources to find even the most basic information to guide design decisions. In this thesis, the feature of Inheritance is proposed as a way to organize the information in these charts. Supplementary details are provided in the form of functions and properties to enable easier access of information on the operating concepts and functional characteristics of the devices within a given family. The goal is to select the member of a given family that best meets a particular need.

Krishnamurthy, Ritesh

2002-01-01T23:59:59.000Z

418

A COMPRESSED SENSING METHOD WITH ANALYTICAL RESULTS FOR LIDAR FEATURE CLASSIFICATION  

Science Conference Proceedings (OSTI)

We present an innovative way to autonomously classify LiDAR points into bare earth, building, vegetation, and other categories. One desirable product of LiDAR data is the automatic classification of the points in the scene. Our algorithm automatically classifies scene points using Compressed Sensing Methods via Orthogonal Matching Pursuit algorithms utilizing a generalized K-Means clustering algorithm to extract buildings and foliage from a Digital Surface Models (DSM). This technology reduces manual editing while being cost effective for large scale automated global scene modeling. Quantitative analyses are provided using Receiver Operating Characteristics (ROC) curves to show Probability of Detection and False Alarm of buildings vs. vegetation classification. Histograms are shown with sample size metrics. Our inpainting algorithms then fill the voids where buildings and vegetation were removed, utilizing Computational Fluid Dynamics (CFD) techniques and Partial Differential Equations (PDE) to create an accurate Digital Terrain Model (DTM) [6]. Inpainting preserves building height contour consistency and edge sharpness of identified inpainted regions. Qualitative results illustrate other benefits such as Terrain Inpainting s unique ability to minimize or eliminate undesirable terrain data artifacts. Keywords: Compressed Sensing, Sparsity, Data Dictionary, LiDAR, ROC, K-Means, Clustering, K-SVD, Orthogonal Matching Pursuit

Allen, Josef D [ORNL

2011-01-01T23:59:59.000Z

419

Table 40. U.S. Coal Stocks at Manufacturing Plants by North American Industry Classification System (NAICS) Code  

U.S. Energy Information Administration (EIA) Indexed Site

0. U.S. Coal Stocks at Manufacturing Plants by North American Industry Classification System (NAICS) Code 0. U.S. Coal Stocks at Manufacturing Plants by North American Industry Classification System (NAICS) Code (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 40. U.S. Coal Stocks at Manufacturing Plants by North American Industry Classification System (NAICS) Code (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 NAICS Code June 30, 2013 March 31, 2013 June 30, 2012 Percent Change (June 30) 2013 versus 2012 311 Food Manufacturing 875 926 1,015 -13.9 312 Beverage and Tobacco Product Mfg. 26 17 19 35.8 313 Textile Mills 22 22 25 -13.9 315 Apparel Manufacturing w w w w 321 Wood Product Manufacturing w w w w 322 Paper Manufacturing 570 583

420

Table 35. U.S. Coal Consumption at Manufacturing Plants by North American Industry Classification System (NAICS) Code  

U.S. Energy Information Administration (EIA) Indexed Site

U.S. Coal Consumption at Manufacturing Plants by North American Industry Classification System (NAICS) Code U.S. Coal Consumption at Manufacturing Plants by North American Industry Classification System (NAICS) Code (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 35. U.S. Coal Consumption at Manufacturing Plants by North American Industry Classification System (NAICS) Code (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Year to Date NAICS Code April - June 2013 January - March 2013 April - June 2012 2013 2012 Percent Change 311 Food Manufacturing 2,256 2,561 1,864 4,817 4,343 10.9 312 Beverage and Tobacco Product Mfg. 38 50 48 88 95 -7.7 313 Textile Mills 31 29 21 60 59 2.2 315 Apparel Manufacturing w w w w w w 321 Wood Product Manufacturing w w w

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Domains of competence of fuzzy rule based classification systems with data complexity measures: A case of study using a fuzzy hybrid genetic based machine learning method  

Science Conference Proceedings (OSTI)

The analysis of data complexity is a proper framework to characterize the tackled classification problem and to identify domains of competence of classifiers. As a practical outcome of this framework, the proposed data complexity measures may facilitate ... Keywords: Classification, Data complexity, Fuzzy rule based systems, Genetic fuzzy systems

Julin Luengo; Francisco Herrera

2010-01-01T23:59:59.000Z

422

Hierarchical Disaster Image Classification for Situation Report Enhancement Yimin Yang, Hsin-Yu Ha, Fausto Fleites, Shu-Ching Chen, Steven Luis  

E-Print Network (OSTI)

response situations. The HDIC framework classifies images into different disaster categories and subHierarchical Disaster Image Classification for Situation Report Enhancement Yimin Yang, Hsin-Yu Ha In this paper, a hierarchical disaster image classification (HDIC) framework based on multi-source data fusion

Chen, Shu-Ching

423

A comparison of automated land cover/use classification methods for a Texas bottomland hardwood system using lidar, spot-5, and ancillary data  

E-Print Network (OSTI)

Bottomland hardwood forests are highly productive ecosystems which perform many important ecological services. Unfortunately, many bottomland hardwood forests have been degraded or lost. Accurate land cover mapping is crucial for management decisions affecting these disappearing systems. SPOT-5 imagery from 2005 was combined with Light Detection and Ranging (LiDAR) data from 2006 and several ancillary datasets to map a portion of the bottomland hardwood system found in the Sulphur River Basin of Northeast Texas. Pixel-based classification techniques, rulebased classification techniques, and object-based classification techniques were used to distinguish nine land cover types in the area. The rule-based classification (84.41% overall accuracy) outperformed the other classification methods because it more effectively incorporated the LiDAR and ancillary datasets when needed. This output was compared to previous classifications from 1974, 1984, 1991, and 1997 to determine abundance trends in the areas bottomland hardwood forests. The classifications from 1974-1991 were conducted using identical class definitions and input imagery (Landsat MSS 60m), and the direct comparison demonstrates an overall declining trend in bottomland hardwood abundance. The trend levels off in 1997 when medium resolution imagery was first utilized (Landsat TM 30m) and the 2005 classification also shows an increase in bottomland hardwood from 1997 to 2005, when SPOT-5 10m imagery was used. However, when the classifications are re-sampled to the same resolution (60m), the percent area of bottomland hardwood consistently decreases from 1974-2005. Additional investigation of object-oriented classification proved useful. A major shortcoming of object-based classification is limited justification regarding the selection of segmentation parameters. Often, segmentation parameters are arbitrarily defined using general guidelines or are determined through a large number of parameter combinations. This research justifies the selection of segmentation parameters through a process that utilizes landscape metrics and statistical techniques to determine ideal segmentation parameters. The classification resulting from these parameters outperforms the classification resulting from arbitrary parameters by approximately three to six percent in terms of overall accuracy, demonstrating that landscape metrics can be successfully linked to segmentation parameters in order to create image objects that more closely resemble real-world objects and result in a more accurate final classification.

Vernon, Zachary Isaac

2008-05-01T23:59:59.000Z

424

Building America Top Innovations Hall of Fame Profile … Vapor Retarder Classification  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

2006 the IRC has permitted Class III 2006 the IRC has permitted Class III vapor retarders like latex paint (see list above) in all climate zones under certain conditions thanks to research by Building America teams. Air-tight and well-insulated homes have little or no tolerance for drying if they get wet; moisture control is critical. That's why Building America research establishing vapor retarder classifications and their appropriate applications has been instrumental in the market transformation to high-performance homes. As buildings have gotten tighter over the past several decades, questions about vapor retarders and vapor barriers have confounded builders and code developers. Vapor barriers have traditionally been installed on the warm in winter side of the wall assembly in an attempt to keep interior moisture from entering the wall cavity

425

ANUDISflM-37 SMART BRIDGE: A TOOL FOR ESTIMATING THE MILITARY LOAD CLASSIFICATION OF BRIDGES  

Office of Scientific and Technical Information (OSTI)

ANUDISflM-37 ANUDISflM-37 SMART BRIDGE: A TOOL FOR ESTIMATING THE MILITARY LOAD CLASSIFICATION OF BRIDGES USING VARYING LEVELS OF INFORMATION Decision and Information Sciences Division Argonne National Laboratory Operated by The University of Chicago, under Contract W-31-109-Eng-38, for the United States Department of Energy Argonne National Laboratory Argonne National Laboratory, with facilities in the states of Illinois and Idaho, is owned by the United States Government, and operated by the University of Chicago under the provisions of a contract with the Department of Energy. This technical memo is a product of Argonne's Decision and Information Sciences (DE) Division. For information on the division's scientific and engineering activities, contact: Director, Decision and Information

426

Language Classification using N-grams Accelerated by FPGA-based Bloom Filters  

SciTech Connect

N-Gram (n-character sequences in text documents) counting is a well-established technique used in classifying the language of text in a document. In this paper, n-gram processing is accelerated through the use of reconfigurable hardware on the XtremeData XD1000 system. Our design employs parallelism at multiple levels, with parallel Bloom Filters accessing on-chip RAM, parallel language classifiers, and parallel document processing. In contrast to another hardware implementation (HAIL algorithm) that uses off-chip SRAM for lookup, our highly scalable implementation uses only on-chip memory blocks. Our implementation of end-to-end language classification runs at 85x comparable software and 1.45x the competing hardware design.

Jacob, A; Gokhale, M

2007-09-13T23:59:59.000Z

427

Thermally-induced ventilation in atria: an atrium classification scheme and promising test sites  

DOE Green Energy (OSTI)

In establishing the atrium classification scheme, specific attention was given to: climate (hot-arid, warm-humid, and temperate), atrium configuration (open, closed, and adjustable tops), and thermal mechanism (natural convection, radiative cooling, shading, and others). Application of the resulting three-dimensional (three-coordinate) matrix was considered and tested. Although the testing was for purposes of checking scheme application, the procedure indicated that most of the atria examined were of the adjustable-top configuration with daylighting the principal functional mode. However, it was noted that thermally-induced air flow was present in many of the atria classified. In the identification of promising test sites it was noted that there appears to be a shortage of buildings which meet the atrium definition. Consequently, prospective test sites were categorized as follows based upon anticipated value to the study: commercial atria already constructed, commercial atria planned or under construction, and residential atria already constructed.

Not Available

1981-06-01T23:59:59.000Z

428

Inductive classification of multipartite entanglement under stochastic local operations and classical communication  

SciTech Connect

We propose an inductive procedure to classify N-partite entanglement under stochastic local operations and classical communication provided such a classification is known for N-1 qubits. The method is based upon the analysis of the coefficient matrix of the state in an arbitrary product basis. We illustrate this approach in detail with the well-known bipartite and tripartite systems, obtaining as a by-product a systematic criterion to establish the entanglement class of a given pure state without resourcing to any entanglement measure. The general case is proved by induction, allowing us to find an upper bound for the number of N-partite entanglement classes in terms of the number of entanglement classes for N-1 qubits.

Lamata, L.; Leon, J. [Instituto de Matematicas y Fisica Fundamental, CSIC, c/ Serrano, 113-bis, 28006 Madrid (Spain); Salgado, D. [Dpto. Fisica Teorica, Universidad Autonoma de Madrid, Ciudad Universitaria de Cantoblanco, 28049 Cantoblanco, Madrid (Spain); Solano, E. [Max-Planck-Institut fuer Quantenoptik, Hans-Kopfermann-Strasse 1, 85748 Garching (Germany); Depto. Ciencias, Seccion Fisica, Pontificia Universidad Catolica del Peru, 1761 Lima (Peru)

2006-11-15T23:59:59.000Z

429

On the phenomenological classification of continuum radio spectra variability patterns of Fermi blazars  

E-Print Network (OSTI)

The F-GAMMA program is a coordinated effort to investigate the physics of Active Galactic Nuclei (AGNs) via multi-frequency monitoring of {\\em Fermi} blazars. The current study is concerned with the broad-band radio spectra composed of measurement at ten frequencies between 2.64 and 142 GHz. It is shown that any of the 78 sources studied can be classified in terms of their variability characteristics in merely 5 types of variability. The first four types are dominated by spectral evolution and can be reproduced by a simple two-component system made of the quiescent spectrum of a large scale jet populated with a flaring event evolving according to Marscher & Gear (1985). The last type is characterized by an achromatic change of the broad-band spectrum which must be attributed to a completely different mechanism. Here are presented, the classification, the assumed physical system and the results of simulations that have been conducted.

Angelakis, E; Nestoras, I; Fromm, C M; Schmidt, R; Zensus, J A; Marchili, N; Krichbaum, T P; Perucho-Pla, M; Ungerechts, H; Sievers, A; Riquelme, D

2011-01-01T23:59:59.000Z

430

Classification of surficial sediments: North-Central and Eastern Gulf of Mexico  

E-Print Network (OSTI)

The surface sediments in the North-Central and Eastern Gulf of Mexico can be appropriately characterized by physical property analysis, especially by comparison of wet-bulk density. Two hundred and eighty, 1-5 meter cores have been collected on positive sea floor features in three physiographic regions in the Gulf of Mexico: the Intraslope Basin, Sigsbee Escarpment, and Mississippi Fan regions. Analysis found that using three independent calculations or approximations of wet-bulk density proved to reasonably identify distinct, surficial sediment characteristics for each of these three regions. After initial segregation into three density regimes, the cores were characterized based on analysis of p-wave velocity, porosity, impedance, void ratio, water content, shear strength and various observed physical properties such as grain-size, sediment structure, and color. The methods of characterization lead to the unique classification of surficial sediments in these physiographic regions.

Cain, William

2003-01-01T23:59:59.000Z

431

A 3D Automated Classification Scheme for the TAUVEX data pipeline  

E-Print Network (OSTI)

In order to develop a pipeline for automated classification of stars to be observed by the TAUVEX ultraviolet space Telescope, we employ an artificial neural network (ANN) technique for classifying stars by using synthetic spectra in the UV region from 1250\\AA to 3220\\AA as the training set and International Ultraviolet Explorer (IUE) low resolution spectra as the test set. Both the data sets have been pre-processed to mimic the observations of the TAUVEX ultraviolet imager. We have successfully classified 229 stars from the IUE low resolution catalog to within 3-4 spectral sub-class using two different simulated training spectra, the TAUVEX spectra of 286 spectral types and UVBLUE spectra of 277 spectral types. Further, we have also been able to obtain the colour excess (i.e. E(B-V) in magnitude units) or the interstellar reddening for those IUE spectra which have known reddening to an accuracy of better than 0.1 magnitudes. It has been shown that even with the limitation of data from just photometric bands, ANNs have not only classified the stars, but also provided satisfactory estimates for interstellar extinction. The ANN based classification scheme has been successfully tested on the simulated TAUVEX data pipeline. It is expected that the same technique can be employed for data validation in the ultraviolet from the virtual observatories. Finally, the interstellar extinction estimated by applying the ANNs on the TAUVEX data base would provide an extensive extinction map for our galaxy and which could in turn be modeled for the dust distribution in the galaxy.

Archana Bora; Ranjan Gupta; Harinder P. Singh; Jayant Murthy; Rekhesh Mohan; Kalpana Duorah

2007-11-27T23:59:59.000Z

432

A Hierarchical Concept-matrix Patterned Multi-Agent Based Automated Text Classification Method for Digital Libraries  

Science Conference Proceedings (OSTI)

In this work a new hierarchical concept-matrix patterned multi-agent based automated classification method is designed and developed in a distributed server environment. Phrase oriented approach is used instead of word based approach. Latent Semantic ... Keywords: Concept-Matrix, Latent Semantic Analysis, Multi-Agent System

R. Ponnusamy; T. V. Gopal; S. Vaidyanathan

2006-05-01T23:59:59.000Z

433

Using genetic algorithm to select the presentation order of training patterns that improves simplified fuzzy ARTMAP classification performance  

Science Conference Proceedings (OSTI)

The presentation order of training patterns to a simplified fuzzy ARTMAP (SFAM) neural network affects the classification performance. The common method to solve this problem is to use several simulations with training patterns presented in random order, ... Keywords: Fuzzy ARTMAP, Genetic algorithm, Individual identification, Min-max ordering, Visual evoked potential, Voting strategy

Ramaswamy Palaniappan; Chikkanan Eswaran

2009-01-01T23:59:59.000Z

434

An exploratory study on the impact of temporal features on the classification and clustering of future-related web documents  

Science Conference Proceedings (OSTI)

In the last few years, a huge amount of temporal written information has become widely available on the Internet with the advent of forums, blogs and social networks. This gave rise to a new challenging problem called future retrieval, which consists ... Keywords: prospective search, temporal classification, temporal clustering, temporal information retrieval, temporal web mining

Ricardo Campos; Gal Dias; Alpio Jorge

2011-10-01T23:59:59.000Z

435

A Classification Scheme for Winter Storms in the Eastern and Central United States with an emphasis on Nor'easters  

Science Conference Proceedings (OSTI)

A classification scheme for nor'easters and other winter storms (November-April) in the eastern and central United States provides real-time information on the potential impact of these storms. This scheme also may be applied to winterstorms over ...

Gregory A. Zielinski

2002-01-01T23:59:59.000Z

436

Making 3D work: a classification of visual depth cues, 3D display technologies and their applications  

Science Conference Proceedings (OSTI)

3D display technologies improve perception and interaction with 3D scenes, and hence can make applications more effective and efficient. This is achieved by simulating depth cues used by the human visual system for 3D perception. The type of employed ... Keywords: 3D display technologies, applications of 3D display technologies, classification, depth cues, stereo perception

Mostafa Mehrabi, Edward M. Peek, Burkhard C. Wuensche, Christof Lutteroth

2013-01-01T23:59:59.000Z

437

A Spatial Structural and Statistical Approach to Building Classification of Residential Function for City-Scale Impact Assessment Studies  

Science Conference Proceedings (OSTI)

In order to implement robust climate change adaption and mitigation strategies in cities fine spatial scale information on building stock is required. However, for many cities such information is rarely available. In response, we present a methodology ... Keywords: City Spatial Planning and Impact Assessment, Morphological and Spatial Metrics, Multinomial Logistic Regression, Residential Building Classification

Dimitrios P. Triantakonstantis; Stuart L. Barr

2009-07-01T23:59:59.000Z

438

Application of Support Vector Machine (SVM) and Proximal Support Vector Machine (PSVM) for fault classification of monoblock centrifugal pump  

Science Conference Proceedings (OSTI)

Monoblock centrifugal pumps are widely used in a variety of applications. Defects and malfunctions (faults) of these pumps result in significant economic loss. Therefore, the pumps must be under constant monitoring. When a possible fault is detected, ... Keywords: CAV, PSVM, bearing faults, cavitation, decision trees, fault classification, fault diagnosis, impeller faults, monoblock centrifugal pumps, proximal SVM, seal faults, support vector machines, vibration signals

N. R. Sakthivel; V. Sugumaran; Binoy B. Nair

2010-12-01T23:59:59.000Z

439

Generation of synthetic multifractal realistic surfaces based on natural model and lognormal cascade: application to MRI classification  

Science Conference Proceedings (OSTI)

This paper presents a method of generating realistic synthetic multi-fractals surfaces, constructed with multiplicative cascades, that follow lognormal probability density function.The conservation of the natural image gradient direction, and the variance ... Keywords: Bayesian classification, Monte-Carlo sampling, discrete wavelet transform, iterative conditional modes (ICM), lognormal cascade, markov random fields (MRF), multifractal analysis, probabilistic model, wavelet leader

Mohamed Khider; Abdelmalik Taleb-Ahmed; Boualem Haddad

2010-11-01T23:59:59.000Z

440

Hybrid segmentation, characterization and classification of basal cell nuclei from histopathological images of normal oral mucosa and oral submucous fibrosis  

Science Conference Proceedings (OSTI)

This work presents a quantitative microscopic approach for discriminating oral submucous fibrosis (OSF) from normal oral mucosa (NOM) in respect to morphological and textural properties of the basal cell nuclei. Practically, basal cells constitute the ... Keywords: Color deconvolution, Fuzzy divergence, Gradient vector flow, Oral submucous fibrosis, Parabola fitting, Pattern classification, Unsupervised feature selection, Zernike moments

M. Muthu Rama Krishnan; Chandan Chakraborty; Ranjan Rashmi Paul; Ajoy K. Ray

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Rock Sampling At Socorro Mountain Area (Armstrong, Et Al., 1995) | Open  

Open Energy Info (EERE)

Armstrong, Et Al., 1995) Armstrong, Et Al., 1995) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Rock Sampling At Socorro Mountain Area (Armstrong, Et Al., 1995) Exploration Activity Details Location Socorro Mountain Area Exploration Technique Rock Sampling Activity Date Usefulness not indicated DOE-funding Unknown Notes Corresponding Socorro caldera Carboniferous rocks were studied in the field in 1988-1992-Renault later completed geochemistry and silica-crystallite geothermometry, Armstrong petrographic analysis and cathodoluminescence, Oscarson SEM studies, and John Repetski (USGS, Reston, Virgina) conodont stratigraphy and color and textural alteration as guides to the carbonate rocks' thermal history. The carbonate-rock classification used in this

442

Machine Learning Based Classification of Textual Stimuli to Promote Ideation in Bioinspired Design  

E-Print Network (OSTI)

Bioinspired design uses biological systems to inspire engineering designs. One of bioinspired designs challenges is identifying relevant information sources in biology for an engineering design task. Currently information can be retrieved by searching biology texts or journals using biology-focused keywords that map to engineering functions. However, this search technique can overwhelm designers with unusable results. This work explores the use of text classification tools to identify relevant biology passages for design. Further, this research examines the effects of using biology passages as stimuli during idea generation. Four human-subjects studies are examined in this work. Two surveys are performed in which participants evaluate sentences from a biology corpus and indicate whether each sentence prompts an idea for solving a specific design problem. The surveys are used to develop and evaluate text classification tools. Two idea generation studies are performed in which participants generate and record solutions for designing a corn shucker using either different sets of biology passages as design stimuli, or no stimuli. Based 286 sentences from the surveys, a k Nearest Neighbor classifier is developed that is able to identify helpful sentences relating to the function separate with a precision of 0.62 and recall of 0.48. This classifier could potentially double the number of helpful results found using a keyword search. The developed classifier is specific to the function separate and performs poorly when used for another function. Classifiers developed using all sentences and participant responses from the surveys are not able to reliably identify helpful sentences. From the idea generation studies, we determine that using any biology passages as design stimuli increases the quantity and variety of participant solutions. Solution quantity and variety are also significantly increased when biology passages are presented one at a time instead of all at once. Quality and variety are not significantly affected by the presence of design stimuli. Biological stimuli are also found to lead designers to types of solution that are not typically produced otherwise. This work develops a means for designers to find more useful information when searching biology and demonstrates several ways that biology passages can improve ideation.

Glier, Michael W

2013-08-01T23:59:59.000Z

443

Development of an auditable safety analysis in support of a radiological facility classification  

SciTech Connect

In recent years, U.S. Department of Energy (DOE) facilities commonly have been classified as reactor, non-reactor nuclear, or nuclear facilities. Safety analysis documentation was prepared for these facilities, with few exceptions, using the requirements in either DOE Order 5481.1B, Safety Analysis and Review System; or DOE Order 5480.23, Nuclear Safety Analysis Reports. Traditionally, this has been accomplished by development of an extensive Safety Analysis Report (SAR), which identifies hazards, assesses risks of facility operation, describes and analyzes adequacy of measures taken to control hazards, and evaluates potential accidents and their associated risks. This process is complicated by analysis of secondary hazards and adequacy of backup (redundant) systems. The traditional SAR process is advantageous for DOE facilities with appreciable hazards or operational risks. SAR preparation for a low-risk facility or process can be cost-prohibitive and quite challenging because conventional safety analysis protocols may not readily be applied to a low-risk facility. The DOE Office of Environmental Restoration and Waste Management recognized this potential disadvantage and issued an EM limited technical standard, No. 5502-94, Hazard Baseline Documentation. This standard can be used for developing documentation for a facility classified as radiological, including preparation of an auditable (defensible) safety analysis. In support of the radiological facility classification process, the Uranium Mill Tailings Remedial Action (UMTRA) Project has developed an auditable safety analysis document based upon the postulation criteria and hazards analysis techniques defined in DOE Order 5480.23.

Kinney, M.D. [Roy F. Weston, Inc., Rockville, MD (United States); Young, B. [Dept. of Energy, Albuquerque, NM (United States)

1995-03-01T23:59:59.000Z

444

Event Classification and Identification Based on the Characteristic Ellipsoid of Phasor Measurement  

Science Conference Proceedings (OSTI)

In this paper, a method to classify and identify power system events based on the characteristic ellipsoid of phasor measurement is presented. The decision tree technique is used to perform the event classification and identification. Event types, event locations and clearance times are identified by decision trees based on the indices of the characteristic ellipsoid. A sufficiently large number of transient events were simulated on the New England 10-machine 39-bus system based on different system configurations. Transient simulations taking into account different event types, clearance times and various locations are conducted to simulate phasor measurement. Bus voltage magnitudes and recorded reactive and active power flows are used to build the characteristic ellipsoid. The volume, eccentricity, center and projection of the longest axis in the parameter space coordinates of the characteristic ellipsoids are used to classify and identify events. Results demonstrate that the characteristic ellipsoid and the decision tree are capable to detect the event type, location, and clearance time with very high accuracy.

Ma, Jian; Diao, Ruisheng; Makarov, Yuri V.; Etingov, Pavel V.; Dagle, Jeffery E.

2011-09-23T23:59:59.000Z

445

Bayesian Estimator for Angle Recovery: Event Classification and Reconstruction in Positron Emission Tomography  

SciTech Connect

PET at the highest level is an inverse problem: reconstruct the location of the emission (which localize biological function) from detected photons. Ideally, one would like to directly measure an annihilation photon's incident direction on the detector. In the developed algorithm, Bayesian Estimation for Angle Recovery (BEAR), we utilized the increased information gathered from localizing photon interactions in the detector and developed a Bayesian estimator for a photon's incident direction. Probability distribution functions (PDFs) were filled using an interaction energy weighted mean or center of mass (COM) reference space, which had the following computational advantages: (1) a significant reduction in the size of the data in measurement space, making further manipulation and searches faster (2) the construction of COM space does not depend on measurement location, it takes advantage of measurement symmetries, and data can be added to the training set without knowledge and recalculation of prior training data, (3) calculation of posterior probability map is fully parallelizable, it can scale to any number of processors. These PDFs were used to estimate the point spread function (PSF) in incident angle space for (i) algorithm assessment and (ii) to provide probability selection criteria for classification. The algorithm calculates both the incident {theta} and {phi} angle, with {approx}16 degrees RMS in both angles, limiting the incoming direction to a narrow cone. Feature size did not improve using the BEAR algorithm as an angle filter, but the contrast ratio improved 40% on average.

Foudray, Angela M K [Stanford University Molecular Imaging Program at Stanford Department of Radiology Palo Alto, CA (United States); University of California, San Diego Department of Physics La Jolla, CA (United States); Levin, Craig S [Stanford University Molecular Imaging Program at Stanford Department of Radiology Palo Alto, CA (United States)

2007-11-13T23:59:59.000Z

446

Identifying patients in target customer segments using a two-stage clustering-classification approach: A hospital-based assessment  

Science Conference Proceedings (OSTI)

Identifying patients in a Target Customer Segment (TCS) is important to determine the demand for, and to appropriately allocate resources for, health care services. The purpose of this study is to propose a two-stage clustering-classification model through ... Keywords: Customer relationship management (CRM), K-means clustering algorithm, Recency-Frequency-Monetary (RFM) analysis model, Rough set theory (RST), Target customer segment (TCS)

You-Shyang Chen; Ching-Hsue Cheng; Chien-Jung Lai; Cheng-Yi Hsu; Han-Jhou Syu

2012-02-01T23:59:59.000Z

447

Table 28. U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code  

U.S. Energy Information Administration (EIA) Indexed Site

U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 28. U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Year to Date NAICS Code April - June 2013 January - March 2013 April - June 2012 2013 2012 Percent Change 311 Food Manufacturing 2,214 2,356 1,994 4,570 4,353 5.0 312 Beverage and Tobacco Product Mfg. 48 37 53 85 90 -5.6 313 Textile Mills 31 29 22 59 63 -6.1 315 Apparel Manufacturing w w w w w w 321 Wood Product Manufacturing w w w w w w 322 Paper Manufacturing

448

Galaxy Zoo 2: detailed morphological classifications for 304,122 galaxies from the Sloan Digital Sky Survey  

E-Print Network (OSTI)

We present the data release for Galaxy Zoo 2 (GZ2), a citizen science project with more than 16 million morphological classifications of 304,122 galaxies drawn from the Sloan Digital Sky Survey. Morphology is a powerful probe for quantifying a galaxy's dynamical history; however, automatic classifications of morphology (either by computer analysis of images or by using other physical parameters as proxies) still have drawbacks when compared to visual inspection. The large number of images available in current surveys makes visual inspection of each galaxy impractical for individual astronomers. GZ2 uses classifications from volunteer citizen scientists to measure morphologies for all galaxies in the DR7 Legacy survey with m_r>17, in addition to deeper images from SDSS Stripe 82. While the original Galaxy Zoo project identified galaxies as early-types, late-types, or mergers, GZ2 measures finer morphological features. These include bars, bulges, and the shapes of edge-on disks, as well as quantifying the relat...

Willett, Kyle W; Bamford, Steven P; Masters, Karen L; Simmons, Brooke D; Casteels, Kevin R V; Edmondson, Edward M; Fortson, Lucy F; Kaviraj, Sugata; Keel, William C; Melvin, Thomas; Nichol, Robert C; Raddick, M Jordan; Schawinski, Kevin; Simpson, Robert J; Skibba, Ramin A; Smith, Arfon M; Thomas, Daniel

2013-01-01T23:59:59.000Z

449

A Land and Ocean Microwave Cloud Classification Algorithm Derived from AMSU-A and -B, Trained Using MSG-SEVIRI Infrared and Visible Observations  

Science Conference Proceedings (OSTI)

A statistical cloud classification and cloud mask algorithm is developed based on Advanced Microwave Sounding Unit (AMSU-A and -B) microwave (MW) observations. The visible and infrared data from the Meteosat Third Generation-Spinning Enhanced ...

Filipe Aires; Francis Marquisseau; Catherine Prigent; Genevive Sze

2011-08-01T23:59:59.000Z

450

Seismic interpretation and classification of mud volcanoes of the South Caspian Basin, offshore Azerbaijan.  

E-Print Network (OSTI)

Understanding the nature of mud volcanism, mechanisms of formation, types of eruptions and their relationship to the hydrocarbon systems provides important information about subsurface conditions and geological processes within the South Caspian Basin. A 2D seismic grid in southeastern offshore Azerbaijan is used to define the areal distribution of mud volcanoes and to make a classification of the mud volcanoes based on characteristic seismic features. As a result detailed database for each determined mud volcano is constructed. Analysis of different parameters from this database shows that there is a high concentration of mud volcanoes at the southern part of the study area. It is coincides with the distribution of the subsurface structures within the basin. Mud volcanoes with low relief (several tens of meters) are mainly concentrated in the northeast. Conversely, mud volcanoes with large vertical relief (greater than 200 m) are clustered in the southwest part of the basin. Mud volcano development in the South Caspian Basin is generally linked to faults, which in some instances are detached at the basement level. By using interpreted seismic surfaces it is possible to determine relative time of mud flows from the mud volcanoes. Timing of mud flows reveals to the actual activity of the mud volcanoes and it gives valuable information about possible mechanism of mud volcanism within the South Caspian Basin. Previous studies of the onshore mud volcanoes in Azerbaijan and the results from current work conclude that mud volcano formation within the South Caspian Basin is mainly controlled by tectonic forces and overpressured sediments. Mud volcano activity is not always related to the Maykop organic reach shale succession. It can occur at shallow depths by pressure breakthrough from any stratigraphic zone.

Yusifov, Mehdi Zahid

2004-08-01T23:59:59.000Z

451

Intruder scenarios for site-specific low-level radioactive waste classification  

Science Conference Proceedings (OSTI)

The US Department of Energy (DOE) has revised its low-level radioactive waste (LLW) management requirements and guidelines for waste generated at its facilities supporting defense missions. Specifically, draft DOE Order 5820.2A, Chapter 3 describes the purpose, policy, and requirements necessary for the management of defense LLW. The draft DOE policy calls for LLW operations to be managed to protect the health and safety of the public, preserve the environment, and ensure that no remedial action will be necessary after termination of operations. The basic approach used by DOE is to establish overall performance objectives, in terms of groundwater protection and public radiation dose limits, and to require site-specific performance assessments to determine compliance. As a result of these performance assessments, each site will develop waste acceptance criteria that define the allowable quantities and concentrations of specific radioisotopes. Additional limitations on waste disposal design, waste form, and waste treatment will also be developed on a site-specific basis. As a key step in the site-specific performance assessments, an evaluation must be conducted of potential radiation doses to intruders who may inadvertently move onto a closed DOE LLW disposal site after loss of institutional controls. This report (1) describes the types of intruder scenarios that should be considered when performing this step of the site-specific performance assessment, (2) provides the results of generic calculations performed using unit concentrations of various radionuclides as a comparison of the magnitude of importance of the various intruder scenarios, and (3) shows the relationship between the generic doses and waste classification limits for defense wastes.

Kennedy, W.E. Jr.; Peloquin, R.A.

1988-09-01T23:59:59.000Z

452

Classification of Invariant Differential Operators for Non-Compact Lie Algebras via Parabolic Relations  

E-Print Network (OSTI)

In the present paper we review the progress of the project of classification and construction of invariant differential operators for non-compact semisimple Lie groups. Our starting points is the class of algebras, which we called earlier 'conformal Lie algebras' (CLA), which have very similar properties to the conformal algebras of Minkowski space-time, though our aim is to go beyond this class in a natural way. For this we introduced recently the new notion of {\\it parabolic relation} between two non-compact semisimple Lie algebras $\\cal G$ and $\\cal G'$ that have the same complexification and possess maximal parabolic subalgebras with the same complexification. Thus, we consider the exceptional algebra $E_{7(7)}$ which is parabolically related to the CLA $E_{7(-25)}$. Other interesting examples are the orthogonal algebras $so(p,q)$ all of which are parabolically related to the conformal algebra $so(n,2)$ with $p+q=n+2$, the parabolic subalgebras including the Lorentz subalgebra $so(n-1,1)$ and its analogs $so(p-1,q-1)$. Further we consider the algebras $sl(2n,R)$ and for $n=2k$ the algebras $su^*(4k)$ which are parabolically related to the CLA $su(n,n)$. Further we consider the algebras $sp(r,r)$ which are parabolically related to the CLA $sp(2r,R)$. We consider also $E_{6(6)}$ and $E_{6(2)}$ which are parabolically related to the hermitian symmetric case $E_{6(-14)}$.

V. K. Dobrev

2013-11-29T23:59:59.000Z

453

ACTIVE LEARNING TO OVERCOME SAMPLE SELECTION BIAS: APPLICATION TO PHOTOMETRIC VARIABLE STAR CLASSIFICATION  

SciTech Connect

Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL-where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up-is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.

Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J. [Astronomy Department, University of California, Berkeley, CA 94720-7450 (United States); Brink, Henrik [Dark Cosmology Centre, Juliane Maries Vej 30, 2100 Copenhagen O (Denmark); Long, James P.; Rice, John, E-mail: jwrichar@stat.berkeley.edu [Statistics Department, University of California, Berkeley, CA 94720-7450 (United States)

2012-01-10T23:59:59.000Z

454

A RECOMMENDED PASQUILL-GIFFORD STABILITY CLASSIFICATION METHOD FOR SAFETY BASIS ATMOSPHERIC DISPERSION MODELING AT SRS  

SciTech Connect

Several of the most common methods for estimating Pasquill-Gifford (PG) stability (turbulence) class were evaluated for use in modeling the radiological consequences of SRS accidental releases using the MELCOR Accident Consequence Code System, Ver. 2 (MACCS2). Evaluation criteria included: (1) the ability of the method to represent diffusion characteristics above a predominantly forested landscape at SRS, (2) suitability of the method to provide data consistent with the formulation of the MACCS2 model, and (3) the availability of onsite meteorological data to support implementation of the method The evaluation resulted in a recommendation that PG stability classification for regulatory applications at SRS should be based on measurements of the standard deviation of the vertical component of wind direction fluctuations, {sigma}{sub e}, collected from the 61-m level of the SRS meteorological towers, and processed in full accordance with EPA-454/R-99-005 (EPA, 2000). This approach provides a direct measurement that is fundamental to diffusion and captures explicitly the turbulence generated by both mechanical and buoyant forces over the characteristic surface (forested) of SRS. Furthermore, due to the potentially significant enhancement of horizontal fluctuations in wind direction from the occurrence of meander at night, the use of {sigma}{sub e} will ensure a reasonably conservative estimate of PG stability class for use in dispersion models that base diffusion calculations on a single value of PG stability class. Furthermore, meteorological data bases used as input for MACCS2 calculations should contain hourly data for five consecutive annual periods from the most recent 10 years.

Hunter, C.

2012-03-28T23:59:59.000Z

455

Fuzzy neural network pattern recognition algorithm for classification of the events in power system networks  

E-Print Network (OSTI)

This dissertation introduces advanced artificial intelligence based algorithm for detecting and classifying faults on the power system transmission line. The proposed algorithm is aimed at substituting classical relays susceptible to possible performance deterioration during variable power system operating and fault conditions. The new concept relies on a principle of pattern recognition and detects the existence of the fault, identifies fault type, and estimates the transmission line faulted section. The approach utilizes self-organized, Adaptive Resonance Theory (ART) neural network, combined with fuzzy decision rule for interpretation of neural network outputs. Neural network learns the mapping between inputs and desired outputs through processing a set of example cases. Training of the neural network is based on the combined use of unsupervised and supervised learning methods. During training, a set of input events is transformed into a set of prototypes of typical input events. During application, real events are classified based on the interpretation of their matching to the prototypes through fuzzy decision rule. This study introduces several enhancements to the original version of the ART algorithm: suitable preprocessing of neural network inputs, improvement in the concept of supervised learning, fuzzyfication of neural network outputs, and utilization of on-line learning. A selected model of an actual power network is used to simulate extensive sets of scenarios covering a variety of power system operating conditions as well as fault and disturbance events. Simulation results show improved recognition capabilities compared to a previous version of ART neural network algorithm, Multilayer Perceptron (MLP) neural network algorithm, and impedance based distance relay. Simulation results also show exceptional robustness of the novel ART algorithm for all operating conditions and events studied, as well as superior classification capabilities compared to the other solutions. Consequently, it is demonstrated that the proposed ART solution may be used for accurate, high-speed distinction among faulted and unfaulted events, and estimation of fault type and fault section.

Vasilic, Slavko

2006-05-01T23:59:59.000Z

456

An Adaptive Landscape Classification Procedure using Geoinformatics and Artificial Neural Networks  

Science Conference Proceedings (OSTI)

The Adaptive Landscape Classification Procedure (ALCP), which links the advanced geospatial analysis capabilities of Geographic Information Systems (GISs) and Artificial Neural Networks (ANNs) and particularly Self-Organizing Maps (SOMs), is proposed as a method for establishing and reducing complex data relationships. Its adaptive and evolutionary capability is evaluated for situations where varying types of data can be combined to address different prediction and/or management needs such as hydrologic response, water quality, aquatic habitat, groundwater recharge, land use, instrumentation placement, and forecast scenarios. The research presented here documents and presents favorable results of a procedure that aims to be a powerful and flexible spatial data classifier that fuses the strengths of geoinformatics and the intelligence of SOMs to provide data patterns and spatial information for environmental managers and researchers. This research shows how evaluation and analysis of spatial and/or temporal patterns in the landscape can provide insight into complex ecological, hydrological, climatic, and other natural and anthropogenic-influenced processes. Certainly, environmental management and research within heterogeneous watersheds provide challenges for consistent evaluation and understanding of system functions. For instance, watersheds over a range of scales are likely to exhibit varying levels of diversity in their characteristics of climate, hydrology, physiography, ecology, and anthropogenic influence. Furthermore, it has become evident that understanding and analyzing these diverse systems can be difficult not only because of varying natural characteristics, but also because of the availability, quality, and variability of spatial and temporal data. Developments in geospatial technologies, however, are providing a wide range of relevant data, and in many cases, at a high temporal and spatial resolution. Such data resources can take the form of high-dimensional data arrays, which can difficult to fully use. Establishing relationships among high-dimensional datasets through neurocomputing based patterning methods can help 1) resolve large volumes of data into a meaningful form; 2) provide an approach for inferring landscape processes in areas that have limited data available but that exhibit similar landscape characteristics; and 3) discover the value of individual variables or groups of variables that contribute to specific processes in the landscape.

Coleman, Andre M.

2008-08-01T23:59:59.000Z

457

GIS Framework for Large River Geomorphic Classification to Aid in the Evaluation of Flow-Ecology Relationships  

SciTech Connect

Assessing the environmental benefits of proposed flow modification to large rivers provides invaluable insight into future hydropower project operations and relicensing activities. Providing a means to quantitatively define flow-ecology relationships is integral in establishing flow regimes that are mutually beneficial to power production and ecological needs. To compliment this effort an opportunity to create versatile tools that can be applied to broad geographic areas has been presented. In particular, integration with efforts standardized within the ecological limits of hydrologic alteration (ELOHA) is highly advantageous (Poff et al. 2010). This paper presents a geographic information system (GIS) framework for large river classification that houses a base geomorphic classification that is both flexible and accurate, allowing for full integration with other hydrologic models focused on addressing ELOHA efforts. A case study is also provided that integrates publically available National Hydrography Dataset Plus Version 2 (NHDPlusV2) data, Modular Aquatic Simulation System two-dimensional (MASS2) hydraulic data, and field collected data into the framework to produce a suite of flow-ecology related outputs. The case study objective was to establish areas of optimal juvenile salmonid rearing habitat under varying flow regimes throughout an impounded portion of the lower Snake River, USA (Figure 1) as an indicator to determine sites where the potential exists to create additional shallow water habitat. Additionally, an alternative hydrologic classification useable throughout the contiguous United States which can be coupled with the geomorphic aspect of this framework is also presented. This framework provides the user with the ability to integrate hydrologic and ecologic data into the base geomorphic aspect of this framework within a geographic information system (GIS) to output spatiotemporally variable flow-ecology relationship scenarios.

Vernon, Christopher R.; Arntzen, Evan V.; Richmond, Marshall C.; McManamay, R. A.; Hanrahan, Timothy P.; Rakowski, Cynthia L.

2013-02-01T23:59:59.000Z

458

REVISITING THE LONG/SOFT-SHORT/HARD CLASSIFICATION OF GAMMA-RAY BURSTS IN THE FERMI ERA  

SciTech Connect

We perform a statistical analysis of the temporal and spectral properties of the latest Fermi gamma-ray bursts (GRBs) to revisit the classification of GRBs. We find that the bimodalities of duration and the energy ratio (E{sub peak}/Fluence) and the anti-correlation between spectral hardness (hardness ratio (HR), peak energy, and spectral index) and duration (T{sub 90}) support the long/soft-short/hard classification scheme for Fermi GRBs. The HR-T{sub 90} anti-correlation strongly depends on the spectral shape of GRBs and energy bands, and the bursts with the curved spectra in the typical BATSE energy bands show a tighter anti-correlation than those with the power-law spectra in the typical BAT energy bands. This might explain why the HR-T{sub 90} correlation is not evident for those GRB samples detected by instruments like Swift with a narrower/softer energy bandpass. We also analyze the intrinsic energy correlation for the GRBs with measured redshifts and well-defined peak energies. The current sample suggests E{sub p,rest} = 2455 Multiplication-Sign (E{sub iso}/10{sup 52}){sup 0.59} for short GRBs, significantly different from that for long GRBs. However, both the long and short GRBs comply with the same E{sub p,rest}-L{sub iso} correlation.

Zhang Fuwen; Yan Jingzhi; Wei Daming [Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210008 (China); Shao Lang, E-mail: fwzhang@pmo.ac.cn [Department of Physics, Hebei Normal University, Shijiazhuang 050016 (China)

2012-05-10T23:59:59.000Z

459

A method for EIA scoping of wave energy converters-based on classification of the used technology  

SciTech Connect

During the first decade of the 21st Century the World faces spread concern for global warming caused by rise of green house gasses produced mainly by combustion of fossil fuels. Under this latest spin all renewable energies run parallel in order to achieve sustainable development. Among them wave energy has an unequivocal potential and technology is ready to enter the market and contribute to the renewable energy sector. Yet, frameworks and regulations for wave energy development are not fully ready, experiencing a setback caused by lack of understanding of the interaction of the technologies and marine environment, lack of coordination from the competent Authorities regulating device deployment and conflicts of maritime areas utilization. The EIA within the consent process is central in the realization of full scale devices and often is the meeting point for technology, politics and public. This paper presents the development of a classification of wave energy converters that is based on the different impact the technologies are expected to have on the environment. This innovative classification can be used in order to simplify the scoping process for developers and authorities.

Margheritini, Lucia, E-mail: lm@civil.aau.dk [Aalborg University, Department of Civil Engineering, Sohngardsholmsvej 57, DK - 9000, Aalborg (Denmark); Hansen, Anne Merrild, E-mail: merrild@plan.aau.dk [Aalborg University, Department of Planning and Development, Fibigerstraede 13, DK - 9220, Aalborg (Denmark); Frigaard, Peter, E-mail: pf@civil.aau.dk [Aalborg University, Department of Civil Engineering, Sohngardsholmsvej 57, DK - 9000, Aalborg (Denmark)

2012-01-15T23:59:59.000Z

460

Prognostic Value of Subclassification Using MRI in the T4 Classification Nasopharyngeal Carcinoma Intensity-Modulated Radiotherapy Treatment  

SciTech Connect

Purpose: To subclassify patients with the T4 classification nasopharyngeal carcinoma (NPC), according to the seventh edition of the American Joint Committee on Cancer staging system, using magnetic resonance imaging (MRI), and to evaluate the prognostic value of subclassification after intensity-modulated radiotherapy (IMRT). Methods and Materials: A total of 140 patients who underwent MRI and were subsequently histologically diagnosed with nondisseminated classification T4 NPC received IMRT as their primary treatment and were included in this retrospective study. T4 patients were subclassified into two grades: T4a was defined as a primary nasopharyngeal tumor with involvement of the masticator space only; and T4b was defined as involvement of the intracranial region, cranial nerves, and/or orbit. Results: The 5-year overall survival (OS) rate and distant metastasis-free survival (DMFS) rate for T4a patients (82.5% and 87.0%, respectively), were significantly higher than for T4b patients (62.6% and 66.8%; p = 0.033 and p = 0.036, respectively). The T4a/b subclassification was an independent prognostic factor for OS (hazard ratio = 2.331, p = 0.032) and DMFS (hazard ratio = 2.602, p = 0.034), and had no significant effect on local relapse-free survival. Conclusions: Subclassification of T4 patients, as T4a or T4b, using MRI according to the site of invasion, has prognostic value for the outcomes of IMRT treatment in NPC.

Chen Lei [State Key Laboratory of Oncology in South China, Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou (China)] [State Key Laboratory of Oncology in South China, Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou (China); Liu Lizhi [State Key Laboratory of Oncology in South China, Imaging Diagnosis and Interventional Center, Sun Yat-sen University Cancer Center, Guangzhou (China)] [State Key Laboratory of Oncology in South China, Imaging Diagnosis and Interventional Center, Sun Yat-sen University Cancer Center, Guangzhou (China); Chen Mo; Li Wenfei; Yin Wenjing [State Key Laboratory of Oncology in South China, Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou (China)] [State Key Laboratory of Oncology in South China, Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou (China); Lin Aihua [Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou (China)] [Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou (China); Sun Ying [State Key Laboratory of Oncology in South China, Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou (China)] [State Key Laboratory of Oncology in South China, Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou (China); Li Li [State Key Laboratory of Oncology in South China, Imaging Diagnosis and Interventional Center, Sun Yat-sen University Cancer Center, Guangzhou (China)] [State Key Laboratory of Oncology in South China, Imaging Diagnosis and Interventional Center, Sun Yat-sen University Cancer Center, Guangzhou (China); Ma Jun, E-mail: majun2@mail.sysu.edu.cn [State Key Laboratory of Oncology in South China, Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou (China)

2012-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
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461

SALTSTONE VAULT CLASSIFICATION SAMPLES MODULAR CAUSTIC SIDE SOLVENT EXTRACTION UNIT/ACTINIDE REMOVAL PROCESS WASTE STREAM APRIL 2011  

Science Conference Proceedings (OSTI)

Savannah River National Laboratory (SRNL) was asked to prepare saltstone from samples of Tank 50H obtained by SRNL on April 5, 2011 (Tank 50H sampling occurred on April 4, 2011) during 2QCY11 to determine the non-hazardous nature of the grout and for additional vault classification analyses. The samples were cured and shipped to Babcock & Wilcox Technical Services Group-Radioisotope and Analytical Chemistry Laboratory (B&W TSG-RACL) to perform the Toxic Characteristic Leaching Procedure (TCLP) and subsequent extract analysis on saltstone samples for the analytes required for the quarterly analysis saltstone sample. In addition to the eight toxic metals - arsenic, barium, cadmium, chromium, mercury, lead, selenium and silver - analytes included the underlying hazardous constituents (UHC) antimony, beryllium, nickel, and thallium which could not be eliminated from analysis by process knowledge. Additional inorganic species determined by B&W TSG-RACL include aluminum, boron, chloride, cobalt, copper, fluoride, iron, lithium, manganese, molybdenum, nitrate/nitrite as Nitrogen, strontium, sulfate, uranium, and zinc and the following radionuclides: gross alpha, gross beta/gamma, 3H, 60Co, 90Sr, 99Tc, 106Ru, 106Rh, 125Sb, 137Cs, 137mBa, 154Eu, 238Pu, 239/240Pu, 241Pu, 241Am, 242Cm, and 243/244Cm. B&W TSG-RACL provided subsamples to GEL Laboratories, LLC for analysis for the VOCs benzene, toluene, and 1-butanol. GEL also determines phenol (total) and the following radionuclides: 147Pm, 226Ra and 228Ra. Preparation of the 2QCY11 saltstone samples for the quarterly analysis and for vault classification purposes and the subsequent TCLP analyses of these samples showed that: (1) The saltstone waste form disposed of in the Saltstone Disposal Facility in 2QCY11 was not characteristically hazardous for toxicity. (2) The concentrations of the eight RCRA metals and UHCs identified as possible in the saltstone waste form were present at levels below the UTS. (3) Most of the inorganic species measured in the leachate do not exceed the MCL, SMCL or TW limits. (4) The inorganic waste species that exceeded the MCL by more than a factor of 10 were nitrate, nitrite and the sum of nitrate and nitrite. (5) Analyses met all quality assurance specifications of US EPA SW-846. (6) The organic species (benzene, toluene, 1-butanol, phenol) were either not detected or were less than reportable for the vault classification samples. (7) The gross alpha and radium isotopes could not be determined to the MCL because of the elevated background which raised the detection limits. (8) Most of the beta/gamma activity was from 137Cs and its daughter 137mBa. (9) The concentration of 137Cs and 90Sr were present in the leachate at concentrations 1/40th and 1/8th respectively than in the 2003 vault classification samples. The saltstone waste form placed in the Saltstone Disposal Facility in 2QCY11 met the SCHWMR R.61-79.261.24(b) RCRA metals requirements for a nonhazardous waste form. The TCLP leachate concentrations for nitrate, nitrite and the sum of nitrate and nitrite were greater than 10x the MCLs in SCDHEC Regulations R.61-107.19, Part I A, which confirms the Saltstone Disposal Facility classification as a Class 3 Landfill. The saltstone waste form placed in the Saltstone Disposal Facility in 2QCY11 met the R.61-79.268.48(a) non wastewater treatment standards.

Eibling, R.

2011-09-28T23:59:59.000Z

462

PROCEEDINGS, Thirty-Fourth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 9-11, 2009  

E-Print Network (OSTI)

, although there are two phases, steam and water (a very small amount of non-condensate gas such as CO2 Council Transactions, 29, 467-474. Sanyal, S. K. (2007), "Ensuring Resource Adequacy for a Commercial

Stanford University

463

GUIDANCE FOR THE PROPER CHARACTERIZATION AND CLASSIFICATION OF LOW SPECIFIC ACTIVITY MATERIALS AND SURFACE CONTAMINATED OBJECTS FOR DISPOSAL  

SciTech Connect

Regulatory concerns over the proper characterization of certain waste streams led CH2M HILL Plateau Remediation Company (CHPRC) to develop written guidance for personnel involved in Decontamination & Decommissioning (D&D) activities, facility management and Waste Management Representatives (WMRs) involved in the designation of wastes for disposal on and off the Hanford Site. It is essential that these waste streams regularly encountered in D&D operations are properly designated, characterized and classified prior to shipment to a Treatment, Storage or Disposal Facility (TSDF). Shipments of waste determined by the classification process as Low Specific Activity (LSA) or Surface Contaminated Objects (SCO) must also be compliant with all applicable U.S. Department of Transportation (DOE) regulations as well as Department of Energy (DOE) orders. The compliant shipment of these waste commodities is critical to the Hanford Central Plateau cleanup mission. Due to previous problems and concerns from DOE assessments, CHPRC internal critiques as well as DOT, a management decision was made to develop written guidance and procedures to assist CHPRC shippers and facility personnel in the proper classification of D&D waste materials as either LSA or SCO. The guidance provides a uniform methodology for the collection and documentation required to effectively characterize, classify and identify candidate materials for shipping operations. A primary focus is to ensure that waste materials generated from D&D and facility operations are compliant with the DOT regulations when packaged for shipment. At times this can be difficult as the current DOT regulations relative to the shipment of LSA and SCO materials are often not clear to waste generators. Guidance is often sought from NUREG 1608/RAMREG-003 [3]: a guidance document that was jointly developed by the DOT and the Nuclear Regulatory Commission (NRC) and published in 1998. However, NUREG 1608 [3] is now thirteen years old and requires updating to comply with the newer DOT regulations. Similar challenges present themselves throughout the nuclear industry in both commercial and government operations and therefore, this is not only a Hanford Site problem. Shipping radioactive wastes as either LSA or SCO rather than repacking it is significantly cheaper than other DOT radioactive materials shipping classifications particularly when the cost of packages is included. Additionally, the need to 'repackage' materials for transport can often increase worker exposure, necessitated by 'repackaging' waste materials into DOT 7 A Type A containers.

PORTSMOUTH JH; BLACKFORD LT

2012-02-13T23:59:59.000Z

464

The ARAUCARIA Project: VLT-FORS spectroscopy of blue supergiants in NGC 3109 - Classifications, first abundances and kinematics  

E-Print Network (OSTI)

We have obtained multi-object spectroscopy of luminous blue supergiants in NGC 3109, a galaxy at the periphery of the Local Group at ~1.3 Mpc. We present a detailed catalog including finding charts, V and I magnitudes, spectral classifications, and stellar radial velocities. The radial velocities are seen to trace the rotation curves obtained from studies of the HI gas. From quantitative analysis of eight B-type supergiants we find a mean oxygen abundance of 12+log(O/H) = 7.76 +/-0.07 (1-sigma systematic uncertainty), with a median result of 7.8. Given its distance, we highlight NGC 3109 as the ideal example of a low metallicity, dark-matter dominated, dwarf galaxy for observations with the next generation of ground-based extremely large telescopes (ELTs).

Evans, C J; Urbaneja, M A; Pietrzynski, G; Gieren, W; Kudritzki, R P

2006-01-01T23:59:59.000Z

465

Standard for Communicating Waste Characterization and DOT Hazard Classification Requirements for Low Specific Activity Materials and Surface Contaminated Objects  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

STD-5507-2013 STD-5507-2013 February 2013 DOE STANDARD Standard for Communicating Waste Characterization and DOT Hazard Classification Requirements for Low Specific Activity Materials and Surface Contaminated Objects [This Standard describes acceptable, but not mandatory means for complying with requirements. Standards are not requirements documents and are not to be construed as requirements in any audit or appraisal for compliance with associated rule or directives.] U.S. Department of Energy SAFT Washington, D.C. 20585 Distribution Statement: A. Approved for public release; distribution is unlimited This document has been reproduced directly from the best available copy. Available to DOE and DOE contractors from ES&H Technical Information Services,

466

Classification Tree Methods for Analysis of Mesoscale Distribution of Ixodes ricinus (Acari: Ixodidae) in Trentino, Italian Alps  

E-Print Network (OSTI)

Cases of Lyme disease and tick borne encephalitis were recently recognized in the province of Trento, Italian Alps. Assessment of areas of potential risk for these tick-borne diseases is carried out by a model based on CART (Classification and Regression Trees), using both discrete and continuous variables. Data on Ixodes ricinus (L.) occurrence resulted from samplings carried out by standard methods in 99 sites over an area of 2; 700 km 2 in the Province of Trento. A series of environmental parameters were recorded from each site and population densities of roe deer, Capreolus capreolus (L.), were considered. The CART model discriminates two variables which appear to have the greatest effect on the mesoscale occurrence of ticks: altitude and geological substratum with drastic decrease of tick frequency above 1; 100 m a:s:l: or on volcanic substrata. The model is effective in identifying the mesoscale areas at greater potential risk, with a relatively low sampling effort. KEY WOR...

Ixodes Ricinus; Stefano Merler; Cesare Furlanello; Claudio Chemini; Gianni Nicolini

1996-01-01T23:59:59.000Z

467

Empowering the access to public procurement opportunities by means of linking controlled vocabularies. A case study of Product Scheme Classifications in the European e-Procurement sector  

Science Conference Proceedings (OSTI)

The present paper introduces a method to promote existing controlled vocabularies to the Linked Data initiative. A common data model and an enclosed conversion method for knowledge organization systems based on semantic web technologies and vocabularies ... Keywords: Expert systems, Linked open data, Product Scheme Classifications, Semantic web, e-Procurement

Jose Mara Alvarez-Rodrguez, Jos Emilio Labra-Gayo, Alejandro Rodrguez-Gonzlez, Patricia Ordoez De Pablos

2014-01-01T23:59:59.000Z

468

Classification of Steam Generator Tube Defects for Real-Time Applications Using Eddy Current Test Data and Self-Organizing Maps  

Science Conference Proceedings (OSTI)

A new classification method, for isolating steam generator tube defects in nuclear power plants using Eddy Current Test (ECT) signals, has been developed. The method uses Self-Organizing maps (SOM) with different data signatures to identify and classify ... Keywords: eddy current, nuclear plant, self-organizing map, tube defects

Roberto N. De Mesquita; Daniel K. S. Ting; Eduardo L. L. Cabral; Belle R. Upadhyaya

2004-05-01T23:59:59.000Z

469

On the neural network classification of medical data and an endeavour to balance non-uniform data sets with artificial data extension  

Science Conference Proceedings (OSTI)

We studied the efficiency of multilayer perceptron networks to classify eight different medical data sets with typical problems connected to their strongly non-uniform distributions between output classes and relatively small sizes of training sets. ... Keywords: Artificial data extension, Artificial neural networks, Classification, Medical decision-making

Lassi Autio; Martti Juhola; Jorma Laurikkala

2007-03-01T23:59:59.000Z

470

Waste Classification based on Waste Form Heat Generation in Advanced Nuclear Fuel Cycles Using the Fuel-Cycle Integration and Tradeoffs (FIT) Model  

SciTech Connect

This study explores the impact of wastes generated from potential future fuel cycles and the issues presented by classifying these under current classification criteria, and discusses the possibility of a comprehensive and consistent characteristics-based classification framework based on new waste streams created from advanced fuel cycles. A static mass flow model, Fuel-Cycle Integration and Tradeoffs (FIT), was used to calculate the composition of waste streams resulting from different nuclear fuel cycle choices. This analysis focuses on the impact of waste form heat load on waste classification practices, although classifying by metrics of radiotoxicity, mass, and volume is also possible. The value of separation of heat-generating fission products and actinides in different fuel cycles is discussed. It was shown that the benefits of reducing the short-term fission-product heat load of waste destined for geologic disposal are neglected under the current source-based radioactive waste classification system , and that it is useful to classify waste streams based on how favorable the impact of interim storage is in increasing repository capacity.

Denia Djokic; Steven J. Piet; Layne F. Pincock; Nick R. Soelberg

2013-02-01T23:59:59.000Z

471

Induced Radioactivity and Waste Classification of Reactor Zone Components of the Chernobyl Nuclear Power Plant Unit 1 After Final Shutdown  

SciTech Connect

The dismantlement of the reactor core materials and surrounding structural components is a major technical concern for those planning closure and decontamination and decommissioning of the Chernobyl Nuclear Power Plant (NPP). Specific issues include when and how dismantlement should be accomplished and what the radwaste classification of the dismantled system would be at the time it is disassembled. Whereas radiation levels and residual radiological characteristics of the majority of the plant systems are directly measured using standard radiation survey and radiochemical analysis techniques, actual measurements of reactor zone materials are not practical due to high radiation levels and inaccessibility. For these reasons, neutron transport analysis was used to estimate induced radioactivity and radiation levels in the Chernobyl NPP Unit 1 reactor core materials and structures.Analysis results suggest that the optimum period of safe storage is 90 to 100 yr for the Unit 1 reactor. For all of the reactor components except the fuel channel pipes (or pressure tubes), this will provide sufficient decay time to allow unlimited worker access during dismantlement, minimize the need for expensive remote dismantlement, and allow for the dismantled reactor components to be classified as low- or medium-level radioactive waste. The fuel channel pipes will remain classified as high-activity waste requiring remote dismantlement for hundreds of years due to the high concentration of induced {sup 63}Ni in the Zircaloy pipes.

Bylkin, Boris K. [Russian Research Center 'Kurchatov Institute' (Russian Federation); Davydova, Galina B. [Russian Research Center 'Kurchatov Institute' (Russian Federation); Zverkov, Yuri A. [Russian Research Center 'Kurchatov Institute' (Russian Federation); Krayushkin, Alexander V. [Russian Research Center 'Kurchatov Institute' (Russian Federation); Neretin, Yuri A. [Chernobyl Nuclear Power Plant (Ukraine); Nosovsky, Anatoly V. [Slavutych Division of the International Chernobyl Center (Ukraine); Seyda, Valery A. [Chernobyl Nuclear Power Plant (Ukraine); Short, Steven M. [Pacific Northwest National Laboratory (United States)

2001-10-15T23:59:59.000Z

472

Table 29. Average Price of U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code  

U.S. Energy Information Administration (EIA) Indexed Site

Price of U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code Price of U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 29. Average Price of U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code (dollars per short ton) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Year to Date NAICS Code April - June 2013 January - March 2013 April - June 2012 2013 2012 Percent Change 311 Food Manufacturing 51.17 49.59 50.96 50.35 50.94 -1.2 312 Beverage and Tobacco Product Mfg. 111.56 115.95 113.47 113.49 117.55 -3.5 313 Textile Mills 115.95 118.96 127.41 117.40 128.07 -8.3 315 Apparel Manufacturing

473

On ancient coin classification  

Science Conference Proceedings (OSTI)

Illegal trade and theft of coins appears to be a major part of the illegal antiques market. Image based recognition of coins could substantially contribute to fight against it. Central component in the permanent identification and traceability of coins ...

M. Zaharieva; R. Huber-Moerk; M. Noelle; M. Kampel

2007-11-01T23:59:59.000Z

474

Classification of Wear  

Science Conference Proceedings (OSTI)

...such as turbines Combustion gases, such as gas turbines Water, such as pump impellers Cavitations, as in turbulent, high-velocity flowing liquids...

475

Office of Classification  

NLE Websites -- All DOE Office Websites (Extended Search)

for proper protection. This activity is vital to national security and U.S. non-proliferation efforts because information assets cannot be protected until they are identified...

476

Classification of Adhesive Materials  

Science Conference Proceedings (OSTI)

Table 1   Benefits and limitations of various adhesive types...very good moisture resistance on plastics. (d) Motor oil, toluene, gasoline, automatic transmission fluid. (e) Uncured liquid adhesives may

477

DUTY STATEMENT Classification  

E-Print Network (OSTI)

activities to develop electricity demand implications of environmental regulations on the natural gas associated with the electricity and natural gas systems. This position requires a high level of knowledge, skill and ability at the journey level. The incumbent will analyze results of the natural gas demand

478

Fox "Seabed habitat classification  

E-Print Network (OSTI)

Introduction. As the exploitation of marine biological resources increases, effective marine environmental management becomes important for a sustainable environment. Base maps of biological as well as physical and geological resources are required for effective marine environmental management. The practice of resource mapping making use of satellite remote sensing and

Justy Siwabessy; John Penrose; Rudy Kloser; David Fox

1996-01-01T23:59:59.000Z

479

Methods for data classification  

DOE Patents (OSTI)

The present invention provides methods for classifying data and uncovering and correcting annotation errors. In particular, the present invention provides a self-organizing, self-correcting algorithm for use in classifying data. Additionally, the present invention provides a method for classifying biological taxa.

Garrity, George (Okemos, MI); Lilburn, Timothy G. (Front Royal, VA)

2011-10-11T23:59:59.000Z

480

Classification of Wear  

Science Conference Proceedings (OSTI)

...vapor impingement on metals Wet steam, such as turbines Combustion gases, such as gas turbines Water, such as pump impellers Cavitations, as in turbulent, high-velocity flowing liquids...

Note: This page contains sample records for the topic "geothermometry sanyal classification" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

Introduction to Classification  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

for classifying and declassifying information, documents, and materials. 4 Restricted Data (RD) Formerly Restricted Data (FRD) What information is classified? Atomic Energy Act...

482

Matched-pair classification  

Science Conference Proceedings (OSTI)

Following an analogous distinction in statistical hypothesis testing, we investigate variants of machine learning where the training set comes in matched pairs. We demonstrate that even conventional classifiers can exhibit improved performance when the input data has a matched-pair structure. Online algorithms, in particular, converge quicker when the data is presented in pairs. In some scenarios (such as the weak signal detection problem), matched pairs can be generated from independent samples, with the effect not only doubling the nominal size of the training set, but of providing the structure that leads to better learning. A family of 'dipole' algorithms is introduced that explicitly takes advantage of matched-pair structure in the input data and leads to further performance gains. Finally, we illustrate the application of matched-pair learning to chemical plume detection in hyperspectral imagery.

Theiler, James P [Los Alamos National Laboratory

2009-01-01T23:59:59.000Z

483

Classification | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Safety and Security manages the Government-wide program to classify and declassify nuclear weapons-related technology, implements the requirements of Executive Order 13526...

484

DUTY STATEMENT CLASSIFICATION  

E-Print Network (OSTI)

15, 2012 OFFICE: Environmental KEY: (E) IS AN ESSENTIAL AND (M) IS A MARGINAL FUNCTION POSITION for power plant facilities. Review and analyze amendments and project changes to previously approved power production and transmission facilities, alternative energy technologies, energy research and development

485

DUTY STATEMENT Classification  

E-Print Network (OSTI)

Office of Chief Counsel Date Prepared August 30, 2013 Division KEY: (E) IS ESSENTIAL, (M) IS MARGINAL indoors in an office setting and occasionally in facilities near proposed power plant sites or with other AM ABLE TO PERFORM, WITH OR WITHOUT THE ASSISTANCE OF A REASONABLE ACCACCOMMODATION, THE ESSENTIAL

486

DUTY STATEMENT CLASSIFICATION  

E-Print Network (OSTI)

, 2012 OFFICE/UNIT: Environmental/Biology KEY: (E) IS AN ESSENTIAL AND (M) IS A MARGINAL FUNCTION biological resource issues related to electrical energy production and transmission facilities, alternative and policies pertinent to biological resource aspects of proposed energy facilities and Commission programs. (M

487

DUTY STATEMENT CLASSIFICATION  

E-Print Network (OSTI)

, 2012 OFFICE/UNIT: Environmental/Biology KEY: (E) IS AN ESSENTIAL AND (M) IS A MARGINAL FUNCTION of certification related to biological resource technical areas for power plant facilities. Review and analyze biological issues related to electrical energy production and transmission facilities, alternative energy

488

DUTY STATEMENT CLASSIFICATION  

E-Print Network (OSTI)

, 2012 OFFICE/UNIT: Environmental/Biology KEY: (E) IS AN ESSENTIAL AND (M) IS A MARGINAL FUNCTION to electrical energy production and transmission facilities, alternative energy technologies, energy research to biological resource aspects of proposed energy facilities and Commission programs. (M) 5% Performs other

489

DUTY STATEMENT Classification  

E-Print Network (OSTI)

; and calculating and estimating energy savings, project economics and environmental benefits (e.g., greenhouse gas and administers electricity- and natural gas-based energy research, development and demonstration (RD&D) efforts related to residential and commercial buildings with the goal of advancing science and technologies

490

Complex System Classification  

E-Print Network (OSTI)

The use of terms such as Engineering Systems, System of systems and others have been coming into greater use over the past decade to denote systems of importance but with implied higher complexity than for the term ...

Magee, Christopher

2004-07-24T23:59:59.000Z

491

Galilean Classification of Curves  

E-Print Network (OSTI)

In this paper, we classify space-time curves up to Galilean group of transformations with Cartan's method of equivalence. As an aim, we elicit invariats from action of special Galilean group on space-time curves, that are, in fact, conservation laws in physics. We also state a necessary and sufficient condition for equivalent Galilean motions.

Mehdi Nadjafikhah; Ali Mahdipour Shirayeh

2007-11-13T23:59:59.000Z

492

Geochemical Techniques | Open Energy Information  

Open Energy Info (EERE)

Geochemical Techniques Geochemical Techniques Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Technique: Geochemical Techniques Details Activities (0) Areas (0) Regions (0) NEPA(1) Exploration Technique Information Exploration Group: Geochemical Techniques Exploration Sub Group: None Parent Exploration Technique: Exploration Techniques Information Provided by Technique Lithology: Stratigraphic/Structural: Hydrological: Thermal: Dictionary.png Geochemical Techniques: No definition has been provided for this term. Add a Definition Related Techniques Geochemical Techniques Geochemical Data Analysis Geothermometry Gas Geothermometry Isotope Geothermometry Liquid Geothermometry Cation Geothermometers Multicomponent Geothermometers Silica Geothermometers Thermal Ion Dispersion

493

Microsoft Word - Cooper Stanford_Modeling_Paper__final__1_.docx  

NLE Websites -- All DOE Office Websites (Extended Search)

Equilibrium Models for Testing Geothermometry Approaches 38 th Workshop on Geothermal Reservoir Engineering D. Craig Cooper Carl D. Palmer Robert W. Smith Travis L....

494

Qrtzgeotherm: An ActiveX component for the quartz solubility geothermometer  

Science Conference Proceedings (OSTI)

An ActiveX component, QrtzGeotherm, to calculate temperature and vapor fraction in a geothermal reservoir using quartz solubility geothermometry was written in Visual Basic 6.0. Four quartz solubility equations along the liquid-vapor saturation curve: ... Keywords: ActiveX component, Computer program, QrtzGeotherm, QrtzGeothrm, Quartz geothermometry, Solubility equations, Visual Basic 6.0

Mahendra P. Verma

2008-12-01T23:59:59.000Z

495

PROCEEDINGS, Thirty-Fifth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 1-3, 2010  

E-Print Network (OSTI)

a heat mining operation rather than tapping an instantly renewable energy source, such as, solar, wind production rate of the water (Sanyal and Butler, 2009). A type of geothermal energy resource of very energy is considered a renewable resource. Therefore, we examine next this apparent contradiction. Figure

Stanford University

496

Harnessing Folksonomies for Resource Classification  

E-Print Network (OSTI)

In our daily lives, organizing resources into a set of categories is a common task. Categorization becomes more useful as the collection of resources increases. Large collections of books, movies, and web pages, for instance, are cataloged in libraries, organized in databases and classified in directories, respectively. However, the usual largeness of these collections requires a vast endeavor and an outrageous expense to organize manually. Recent research is moving towards developing automated classifiers that reduce the increasing costs and effort of the task. Little work has been done analyzing the appropriateness of and exploring how to harness the annotations provided by users on social tagging systems as a data source. Users on these systems save resources as bookmarks in a social environment by attaching annotations in the form of tags. It has been shown that these tags facilitate retrieval of resources not only for the annotators themselves but also for the whole community. Likewise, these tags provid...

Zubiaga, Arkaitz

2012-01-01T23:59:59.000Z

497

Rapid classification of biological components  

SciTech Connect

A method is disclosed for analyzing a biological sample by antibody profiling for identifying forensic samples or for detecting the presence of an analyte. In an illustrative embodiment of the invention, the analyte is a drug, such as marijuana, Cocaine (crystalline tropane alkaloid), methamphetamine, methyltestosterone, or mesterolone. The method involves attaching antigens of the surface of a solid support in a preselected pattern to form an array wherein the locations of the antigens are known; contacting the array with the biological sample such that a portion of antibodies in the sample reacts with and binds to antigens in the array, thereby forming immune complexes; washing away antibodies that do not form immune complexes; and detecting the immune complexes, thereby forming an antibody profile. Forensic samples are identified by comparing a sample from an unknown source with a sample from a known source. Further, an assay, such as a test for illegal drug use, can be coupled to a test for identity such that the results of the assay can be positively correlated to a subject's identity.

Thompson, Vicki S. (Idaho Falls, ID); Barrett, Karen B. (Meridian, ID); Key, Diane E. (Idaho Falls, ID)

2010-03-23T23:59:59.000Z

498

MICHIGAN TECHNOLOGICAL UNIVERSITY CLASSIFICATION DESCRIPTION  

E-Print Network (OSTI)

: Programming in one or more of: Java, Perl, PHP, Python, TCL/TK, ASP Computer system administration

499

Video occupant detection and classification  

DOE Patents (OSTI)

A system for determining when it is not safe to arm a vehicle airbag by storing representations of known situations as observed by a camera at a passenger seat; and comparing a representation of a camera output of the current situation to the stored representations to determine the known situation most closely represented by the current situation. In the preferred embodiment, the stored representations include the presence or absence of a person or infant seat in the front passenger seat of an automobile.

Krumm, John C. (Albuquerque, NM)

1999-01-01T23:59:59.000Z

500

An Agent Based Classification Model  

E-Print Network (OSTI)

The major function of this model is to access the UCI Wisconsin Breast Can- cer data-set[1] and classify the data items into two categories, which are normal and anomalous. This kind of classifi cation can be referred as anomaly detection, which discriminates anomalous behaviour from normal behaviour in computer systems. One popular solution for anomaly detection is Artifi cial Immune Sys- tems (AIS). AIS are adaptive systems inspired by theoretical immunology and observed immune functions, principles and models which are applied to prob- lem solving. The Dendritic Cell Algorithm (DCA)[2] is an AIS algorithm that is developed specifi cally for anomaly detection. It has been successfully applied to intrusion detection in computer security. It is believed that agent-based mod- elling is an ideal approach for implementing AIS, as intelligent agents could be the perfect representations of immune entities in AIS. This model evaluates the feasibility of re-implementing the DCA in an agent-based simulation environ- ...

Gu, Feng; Greensmith, Julie

2009-01-01T23:59:59.000Z