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Sample records for understood sanyal classification

  1. Category:Sanyal Temperature Classification | Open Energy Information

    Open Energy Info (EERE)

    Sanyal Temperature Classification Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Category:Sanyal Temperature Classification Geothermalpower.jpg Looking for the Sanyal...

  2. Sanyal Temperature Classification | Open Energy Information

    Open Energy Info (EERE)

    and (e) unusual operational problems that impact power cost (such as scaling, corrosion, high content of non-condensable gases, etc.). Table 1. A Possible Classification...

  3. Geothermal Literature Review At General Us Region (Sanyal, Et...

    Open Energy Info (EERE)

    navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermal Literature Review At General Us Region (Sanyal, Et Al., 2004) Exploration Activity Details...

  4. Hot Pot Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    of Replacement Wells: Average Temperature of Geofluid: Sanyal Classification (Wellhead): Reservoir Temp (Geothermometry): Reservoir Temp (Measured): Sanyal Classification...

  5. Tungsten Mountain Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    of Replacement Wells: Average Temperature of Geofluid: Sanyal Classification (Wellhead): Reservoir Temp (Geothermometry): Reservoir Temp (Measured): Sanyal Classification...

  6. McGuinness Hills Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    of Replacement Wells: Average Temperature of Geofluid: Sanyal Classification (Wellhead): Reservoir Temp (Geothermometry): Reservoir Temp (Measured): Sanyal Classification...

  7. Dixie Meadows Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    of Geofluid: Sanyal Classification (Wellhead): Reservoir Temp (Geothermometry): Reservoir Temp (Measured): Sanyal Classification (Reservoir): Depth to Top of Reservoir:...

  8. Jersey Valley Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    of Replacement Wells: Average Temperature of Geofluid: Sanyal Classification (Wellhead): Reservoir Temp (Geothermometry): Reservoir Temp (Measured): Sanyal Classification...

  9. Drum Mountain Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    of Geofluid: Sanyal Classification (Wellhead): Reservoir Temp (Geothermometry): Reservoir Temp (Measured): Sanyal Classification (Reservoir): Depth to Top of Reservoir:...

  10. Extremely Low Temperature | Open Energy Information

    Open Energy Info (EERE)

    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...

  11. Classification of Geothermal Systems: A Possible Scheme | Open...

    Open Energy Info (EERE)

    of Geothermal Systems: A Possible Scheme Abstract Abstract unavailable. Author Subir K. Sanyal Conference Thirtieth Workshop on Geothermal Reservoir Engineering; Stanford,...

  12. Understanding Classification

    Energy Savers [EERE]

    CONFIDENTIAL SECRET TOP SECRET 2 (3) Submit any formal challenges to the classification of ... classification uses three levels (Confidential, Secret, Top Secret) to define the ...

  13. Gabbs Valley Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    Reservoir Temp (Measured): Sanyal Classification (Reservoir): Depth to Top of Reservoir: Depth to Bottom of Reservoir: Average Depth to Reservoir: Use the "Edit with...

  14. Coyote Canyon Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    Sanyal Classification (Reservoir): Depth to Top of Reservoir: Depth to Bottom of Reservoir: Average Depth to Reservoir: Use the "Edit with Form" button at the top of the...

  15. Carson Lake Corral Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    Sanyal Classification (Reservoir): Depth to Top of Reservoir: Depth to Bottom of Reservoir: Average Depth to Reservoir: Use the "Edit with Form" button at the top of the...

  16. Reese River Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    Reservoir Temp (Geothermometry): Reservoir Temp (Measured): Sanyal Classification (Reservoir): Depth to Top of Reservoir: Depth to Bottom of Reservoir: Average Depth to...

  17. Gabbs Valley Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    Sanyal Classification (Reservoir): Depth to Top of Reservoir: Depth to Bottom of Reservoir: Average Depth to Reservoir: Use the "Edit with Form" button at the top of the...

  18. McCoy Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    Sanyal Classification (Reservoir): Depth to Top of Reservoir: Depth to Bottom of Reservoir: Average Depth to Reservoir: Use the "Edit with Form" button at the top of the...

  19. Silver Peak Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    Sanyal Classification (Reservoir): Depth to Top of Reservoir: Depth to Bottom of Reservoir: Average Depth to Reservoir: Use the "Edit with Form" button at the top of the...

  20. Steam Field | Open Energy Information

    Open Energy Info (EERE)

    Steam Field Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Print PDF Sanyal Temperature Classification: Steam Field Dictionary.png Steam Field: No definition has been...

  1. Ultra High Temperature | Open Energy Information

    Open Energy Info (EERE)

    Ultra High Temperature Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Print PDF Sanyal Temperature Classification: Ultra High Temperature Dictionary.png Ultra High...

  2. Property:SanyalTempWellhead | Open Energy Information

    Open Energy Info (EERE)

    Area + Moderate Temperature + Blue Mountain Geothermal Area + Moderate Temperature + Brady Hot Springs Geothermal Area + Low Temperature + C Chena Geothermal Area + Extremely...

  3. Property:SanyalTempReservoir | Open Energy Information

    Open Energy Info (EERE)

    Area + High Temperature + C Chena Geothermal Area + Very Low Temperature + D Desert Peak Geothermal Area + Moderate Temperature + F Fenton Hill HDR Geothermal Area + High...

  4. Classification Training Institute Catalog | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Classification Training Institute Catalog Classification Training Institute Catalog Classification Training Institute (CTI) Catalog

  5. Classification Documents and Publications

    Broader source: Energy.gov [DOE]

    Certain documents and publications created or issued by the Office of Classification are available from this page.

  6. Security classification of information

    SciTech Connect (OSTI)

    Quist, A.S.

    1993-04-01

    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.

  7. Security classification of information

    SciTech Connect (OSTI)

    Quist, A.S.

    1989-09-01

    Certain governmental information must be classified for national security reasons. However, the national security benefits from classifying information are usually accompanied by significant costs -- those due to a citizenry not fully informed on governmental activities, the extra costs of operating classified programs and procuring classified materials (e.g., weapons), the losses to our nation when advances made in classified programs cannot be utilized in unclassified programs. The goal of a classification system should be to clearly identify that information which must be protected for national security reasons and to ensure that information not needing such protection is not classified. This document was prepared to help attain that goal. This document is the first of a planned four-volume work that comprehensively discusses the security classification of information. Volume 1 broadly describes the need for classification, the basis for classification, and the history of classification in the United States from colonial times until World War 2. Classification of information since World War 2, under Executive Orders and the Atomic Energy Acts of 1946 and 1954, is discussed in more detail, with particular emphasis on the classification of atomic energy information. Adverse impacts of classification are also described. Subsequent volumes will discuss classification principles, classification management, and the control of certain unclassified scientific and technical information. 340 refs., 6 tabs.

  8. Standard Subject Classification System

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1979-08-14

    The order establishes the DOE Standard Subject Classification System for classifying documents and records by subject, including correspondence, directives, and forms.Cancels DOE O 0000.1.

  9. Engineering rock mass classifications

    SciTech Connect (OSTI)

    Bieniawski, Z.T.

    1989-01-01

    This book is a reference on rock mass classification, consolidating into one handy source information widely scattered through the literature. Includes new, unpublished material and case histories. Presents the fundamental concepts of classification schemes and critically appraises their practical application in industrial projects such as tunneling and mining.

  10. 2-Stage Classification Modeling

    Energy Science and Technology Software Center (OSTI)

    1994-11-01

    CIRCUIT2.4 is used to design optimum two-stage classification configurations and operating conditions for energy conservation. It permits simulation of five basic grinding-classification circuits, including one single-stage and four two-stage classification arrangements. Hydrocyclones, spiral classifiers, and sieve band screens can be simulated, and the user may choose the combination of devices for the flowsheet simulation. In addition, the user may select from four classification modeling methods to achieve the goals of a simulation project using themore » most familiar concepts. Circuit performance is modeled based on classification parameters or equipment operating conditions. A modular approach was taken in designing the program, which allows future addition of other models with relatively minor changes.« less

  11. Standard Subject Classification System

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1978-07-19

    The order establishes the Department of Energy (DOE) Standard Subject Classification System for classifying documents and records by subject, including correspondence, directives, and forms. Canceled by DOE O 0000.1A.

  12. Classification | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Classification Classification PREVENTING THE PROLIFERATION OF NUCLEAR WEAPONS Since the advent of the nuclear age, the United States has been dedicated to preventing the proliferation of nuclear weapons. In order to stop the spread of nuclear weapons-related technology, Congress gave the Atomic Energy Commission (now the Department of Energy [DOE]), authority to control nuclear weapons-related information. This task has gained even greater importance in recent years with an increasing number of

  13. Position Management and Classification - DOE Directives, Delegations...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    O 325.2, Position Management and Classification by Bruce Murray Functional areas: Position Classification, Federal Wage System Standards, Position Management and Classification The...

  14. Position Management and Classification

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    2015-04-01

    The order establishes departmental requirements and responsibilities for classifying positions using general schedule (GS) and federal wage system (FWS) standards and for developing and administering a sound position management and classification program within the Department. Cancels Chapter VII of DOE O 320.1. Canceled by DOE O 325.2 Chg 1 (Admin Chg), 9-1-15.

  15. Position Management and Classification

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    2015-04-01

    The order establishes departmental requirements and responsibilities for classifying positions using the general schedule (GS) and federal wage system (FWS) standards and to develop and administer a sound position management and classification program. Supersedes DOE O 325.2, dated 4-1-15.

  16. Classification of Information Manual

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1985-05-08

    To specify responsibilities, authorities, policy, and procedures for the management of the Department of Energy (DOE) classification system. Cancels DOE O 5650.2, dated 12-12-1978. Canceled by DOE O 5650.2B, dated 12-31-1991.

  17. Materials Classification & Accelerated Property Predictions using...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Materials Classification & Accelerated Property Predictions using Machine Learning Citation Details In-Document Search Title: Materials Classification & ...

  18. Brochure, Understanding Classification - June 2012 | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Brochure, Understanding Classification - June 2012 Brochure, Understanding Classification - June 2012 June 2012 This booklet highlights your responsibilities identified in DOE...

  19. Catalog, Classification Training Institute | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Catalog, Classification Training Institute Catalog, Classification Training Institute 2016 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.

  20. Automated Defect Classification (ADC)

    Energy Science and Technology Software Center (OSTI)

    1998-01-01

    The ADC Software System is designed to provide semiconductor defect feature analysis and defect classification capabilities. Defect classification is an important software method used by semiconductor wafer manufacturers to automate the analysis of defect data collected by a wide range of microscopy techniques in semiconductor wafer manufacturing today. These microscopies (e.g., optical bright and dark field, scanning electron microscopy, atomic force microscopy, etc.) generate images of anomalies that are induced or otherwise appear on wafermore » surfaces as a result of errant manufacturing processes or simple atmospheric contamination (e.g., airborne particles). This software provides methods for analyzing these images, extracting statistical features from the anomalous regions, and applying supervised classifiers to label the anomalies into user-defined categories.« less

  1. Classification of Information

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1978-12-12

    To provide specific responsibilities, standards, and procedures for the management of the Department of Energy (DOE) classification system. Cancels DOE O 5650.1, dated 7-18-78; DOE N 5650.1, dated 8-7-78; DOE N 5650.2, dated 8-7-78; DOE N 5650.3, dated 8-7-78. Canceled by DOE O 5650.2A, dated 5-8-95

  2. Office of Classification

    Office of Energy Efficiency and Renewable Energy (EERE)

    The Office of Classification develops and interprets Government-wide and Department-wide policies, procedures and guidance, performs document reviews, and conducts training to ensure the accurate identification of information and documents that must be classified or controlled under statute or Executive order to protect the National Security, and controlled unclassified information (Official Use Only) to protect commercial and private interests and to provide for the effective operation of the Government.

  3. Automatic Fault Classification

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Automatic Fault Classification of Photovoltaic Strings Based on an In Situ IV Characterization System and a Gaussian Process Algorithm. C. Birk Jones ∗ , Manel Mart´ ınez-Ram´ on ‡ , § Ryan Smith † , Craig K. Carmignani ∗ , Olga Lavrova ∗ , Charles Robinson ∗ , and Joshua S. Stein ∗ ∗ Sandia National Laboratories Solar PV & Grid Integration, Albuquerque, NM, USA. ‡ Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA, §

  4. Seismic event classification system

    DOE Patents [OSTI]

    Dowla, Farid U.; Jarpe, Stephen P.; Maurer, William

    1994-01-01

    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.

  5. Seismic event classification system

    DOE Patents [OSTI]

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

    1994-12-13

    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.

  6. Position Classification | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Position Classification Position Classification Documents Available for Download June 5, 2014 POLICY GUIDANCE MEMORANDUM #03 Addressing Missclassified Positions This memorandum provides policy guidance on how to consistently address misclassified positions within the Department and is effective immediately. There are several different circumstances that affect how a misclassified position will be addressed. April 27, 2010 POLICY GUIDANCE MEMORANDUM #08 DOE Fair Labor Standards Act (FLSA)

  7. Benefits Summary - Temporary Job Classification | Argonne National...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Temporary Job Classification Download a summary of benefits offered to employees in the temporary job classification (at least 6 months term and 20 hoursweek). PDF icon 2015 Long...

  8. EPA - UIC Well Classifications | Open Energy Information

    Open Energy Info (EERE)

    Well Classifications Jump to: navigation, search OpenEI Reference LibraryAdd to library Web Site: EPA - UIC Well Classifications Author Environmental Protection Agency Published...

  9. Universal Membrane Classification Scheme: Maximizing the Return...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Universal Membrane Classification Scheme: Maximizing the Return on High Temperature PEM Membrane Research Universal Membrane Classification Scheme: Maximizing the Return on High ...

  10. Position Management and Classification - DOE Directives, Delegations...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    CURRENT DOE O 325.2 Chg 1 (AdminChg), Position Management and Classification by Bruce Murray Functional areas: Administrative Change, Position Classification, Federal Wage System...

  11. HIV classification using coalescent theory

    SciTech Connect (OSTI)

    Zhang, Ming; Letiner, Thomas K; Korber, Bette T

    2008-01-01

    Algorithms for subtype classification and breakpoint detection of HIV-I sequences are based on a classification system of HIV-l. Hence, their quality highly depend on this system. Due to the history of creation of the current HIV-I nomenclature, the current one contains inconsistencies like: The phylogenetic distance between the subtype B and D is remarkably small compared with other pairs of subtypes. In fact, it is more like the distance of a pair of subsubtypes Robertson et al. (2000); Subtypes E and I do not exist any more since they were discovered to be composed of recombinants Robertson et al. (2000); It is currently discussed whether -- instead of CRF02 being a recombinant of subtype A and G -- subtype G should be designated as a circulating recombination form (CRF) nd CRF02 as a subtype Abecasis et al. (2007); There are 8 complete and over 400 partial HIV genomes in the LANL-database which belong neither to a subtype nor to a CRF (denoted by U). Moreover, the current classification system is somehow arbitrary like all complex classification systems that were created manually. To this end, it is desirable to deduce the classification system of HIV systematically by an algorithm. Of course, this problem is not restricted to HIV, but applies to all fast mutating and recombining viruses. Our work addresses the simpler subproblem to score classifications of given input sequences of some virus species (classification denotes a partition of the input sequences in several subtypes and CRFs). To this end, we reconstruct ancestral recombination graphs (ARG) of the input sequences under restrictions determined by the given classification. These restritions are imposed in order to ensure that the reconstructed ARGs do not contradict the classification under consideration. Then, we find the ARG with maximal probability by means of Markov Chain Monte Carlo methods. The probability of the most probable ARG is interpreted as a score for the classification. To our

  12. ADP computer security classification program

    SciTech Connect (OSTI)

    Augustson, S.J.

    1984-01-01

    CG-ADP-1, the Automatic Data Processing Security Classification Guide, provides for classification guidance (for security information) concerning the protection of Department of Energy (DOE) and DOE contractor Automatic Data Processing (ADP) systems which handle classified information. Within the DOE, ADP facilities that process classified information provide potentially lucrative targets for compromise. In conjunction with the security measures required by DOE regulations, necessary precautions must be taken to protect details of those ADP security measures which could aid in their own subversion. Accordingly, the basic principle underlying ADP security classification policy is to protect information which could be of significant assistance in gaining unauthorized access to classified information being processed at an ADP facility. Given this policy, classification topics and guidelines are approved for implementation. The basic program guide, CG-ADP-1 is broad in scope and based upon it, more detailed local guides are sometimes developed and approved for specific sites. Classification topics are provided for system features, system and security management, and passwords. Site-specific topics can be addressed in local guides if needed.

  13. Hazard classification process at LLNL

    SciTech Connect (OSTI)

    Hildum, J. S., LLNL

    1998-05-01

    An essential part of Integrated Safety Management is the identification of hazards in the workplace and the assessment of possible consequences of accidents involving those hazards. The process of hazard classification suggested by the DOE orders on Safety Analysis is the formalization of this identification and assessment for hazards that might cause harm to the public or workers external to the operation. Possible injury to workers in the facility who are exposed to the hazard is not considered in the designation of the hazard classification for facilities at LLNL, although worker safety is discussed in facility Safety Basis documentation.

  14. Brochure, Classification Overview of RD and FRD - September 2010...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Brochure, Classification Overview of RD and FRD - September 2010 Brochure, Classification Overview of RD and FRD - September 2010 September 2010 A Classification Overview of ...

  15. Updating the Classification of Geothermal Resources

    Broader source: Energy.gov [DOE]

    USGS is working with DOE, the geothermal industry, and academic partners to develop a new geothermal resource classification system.

  16. Statutes, Regulations, and Directives for Classification Program |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy 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

  17. Updating the Classification of Geothermal Resources- Presentation

    Office of Energy Efficiency and Renewable Energy (EERE)

    USGS is working with DOE, the geothermal industry, and academic partners to develop a new geothermal resource classification system.

  18. Vapor Retarder Classification - Building America Top Innovation |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy Vapor Retarder Classification - Building America Top Innovation Vapor Retarder Classification - Building America Top Innovation Photo of a vapor retarder classification. Air-tight and well-insulated homes have little or no tolerance for drying if they get wet; moisture control is critical. This Top Innovation profile describes Building America research that established vapor retarder classifications and appropriate applications that has been instrumental in the market

  19. Geothermal Resource Classification | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Resource Classification Geothermal Resource Classification Geothermal Resource Classification.PDF (869.18 KB) More Documents & Publications Water Use in the Development and Operations of Geothermal Power Plants Water Use in the Development and Operations of Geothermal Power Plants Water Use in the Development and Operation of Geothermal Power Plants

  20. Cloud classification using whole-sky imager data

    SciTech Connect (OSTI)

    Buch, K.A. Jr.; Sun, C.H.; Thorne, L.R.

    1996-04-01

    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 based on measured data from real cloud scenes. These renderings will provide 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 uses binary decision trees to distinguish the different cloud types based on cloud features vectors.

  1. Identification of Export Control Classification Number - ITER

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    of Export Control Classification Number - ITER (April 2012) As the "Shipper of Record" ... be shipped from the United States to the ITER International Organization in Cadarache, ...

  2. Discriminant forest classification method and system

    DOE Patents [OSTI]

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

    2012-11-06

    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.

  3. National Geothermal Resource Assessment and Classification |...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    National Geothermal Resource Assessment and Classification track 2: hydrothermal | geothermal 2015 peer review National Geothermal Data System Architecture Design, Testing and ...

  4. National Security Information Classification Guidance Fundamental...

    Broader source: Energy.gov (indexed) [DOE]

    ... Isotopes Separation by the Atomic Vapor Laser Isotope Separation Process (CG-UAV-2) . ... classification is based on an assessment of the damage done by releasing this information. ...

  5. Classification CommuniQué - Year: 2015 | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    5 Classification CommuniQué - Year: 2015 Classification newsletters for the year 2015, consisting of the following issues: CommuniQue 2015-1 - Spring 2015 (784.22 KB) More Documents & Publications Classification CommuniQué - Year: 2014 Classification CommuniQué - Year: 2012 Classification CommuniQué - Year: 2013

  6. Microsoft Word - Data Classification Security Framework V5.doc

    Broader source: Energy.gov (indexed) [DOE]

    2007 Security Framework for Control System Data Classification and Protection Bryan T. ... Security Framework for Control System Data Classification and Protection 2 Issued by ...

  7. A complete electrical hazard classification system and its application

    SciTech Connect (OSTI)

    Gordon, Lloyd B; Cartelli, Laura

    2009-01-01

    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

  8. IDENTIFYING ROOF FALL PREDICTORS USING FUZZY CLASSIFICATION

    SciTech Connect (OSTI)

    Bertoncini, C. A.; Hinders, M. K.

    2010-02-22

    Microseismic monitoring involves placing geophones on the rock surfaces of a mine to record seismic activity. Classification of microseismic mine data can be used to predict seismic events in a mine to mitigate mining hazards, such as roof falls, where properly bolting and bracing the roof is often an insufficient method of preventing weak roofs from destabilizing. In this study, six months of recorded acoustic waveforms from microseismic monitoring in a Pennsylvania limestone mine were analyzed using classification techniques to predict roof falls. Fuzzy classification using features selected for computational ease was applied on the mine data. Both large roof fall events could be predicted using a Roof Fall Index (RFI) metric calculated from the results of the fuzzy classification. RFI was successfully used to resolve the two significant roof fall events and predicted both events by at least 15 hours before visual signs of the roof falls were evident.

  9. National Geothermal Resource Assessment and Classification

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    National Geothermal Resource Assessment and Classification Colin F. Williams US Geological Survey Data Systems and Analysis (Resource Assessment) April 24, 2013 This presentation does not contain any proprietary confidential, or otherwise restricted information. 2 | US DOE Geothermal Office eere.energy.gov Relevance/Impact of Research * Overall Summary - Major Project Goals * Develop new Geothermal Resource Classification standards * Expand Resource Assessment scope across all 50 states

  10. Identification of Export Control Classification Number - ITER

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    of Export Control Classification Number - ITER (April 2012) As the "Shipper of Record" please provide the appropriate Export Control Classification Number (ECCN) for the products (equipment, components and/or materials) and if applicable the nonproprietary associated installation/maintenance documentation that will be shipped from the United States to the ITER International Organization in Cadarache, France or to ITER Members worldwide on behalf of the Company. In rare instances an

  11. Laser-guidance systems, security classification. Instruction

    SciTech Connect (OSTI)

    Flickinger, A.

    1982-12-03

    The Instruction reissues Department of Defense (DoD) Instruction 5210.62, April 25, 1980, and prescribes policies, standards, and criteria governing the security classification of information pertaining to any laser-guidance system that is developed in whole or in part with information or knowledge obtained from or developed for the Department of Defense; and provides guidance to DoD Components responsible for issuing security classification guides for individual systems and equipment under their control.

  12. Brochure, Understanding Classification - June 2012 | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Brochure, Understanding Classification - June 2012 Brochure, Understanding Classification - June 2012 June 2012 This booklet highlights your responsibilities identified in DOE Order 475.2A, Identifying Classified Information. Classification is how certain information is identified that needs to be protected in the interest of national security. DOE has a formal process for classifying and declassifying information, documents, and materials. Brochure, Understanding Classification - June 2012

  13. Light-water reactor accident classification

    SciTech Connect (OSTI)

    Washburn, B.W.

    1980-02-01

    The evolution of existing classifications and definitions of light-water reactor accidents is considered. Licensing practice and licensing trends are examined with respect to terms of art such as Class 8 and Class 9 accidents. Interim definitions, consistent with current licensing practice and the regulations, are proposed for these terms of art.

  14. Common occupational classification system - revision 3

    SciTech Connect (OSTI)

    Stahlman, E.J.; Lewis, R.E.

    1996-05-01

    Workforce planning has become an increasing concern within the DOE community as the Office of Environmental Restoration and Waste Management (ER/WM or EM) seeks to consolidate and refocus its activities and the Office of Defense Programs (DP) closes production sites. Attempts to manage the growth and skills mix of the EM workforce while retaining the critical skills of the DP workforce have been difficult due to the lack of a consistent set of occupational titles and definitions across the complex. Two reasons for this difficulty may be cited. First, classification systems commonly used in industry often fail to cover in sufficient depth the unique demands of DOE`s nuclear energy and research community. Second, the government practice of contracting the operation of government facilities to the private sector has introduced numerous contractor-specific classification schemes to the DOE complex. As a result, sites/contractors report their workforce needs using unique classification systems. It becomes difficult, therefore, to roll these data up to the national level necessary to support strategic planning and analysis. The Common Occupational Classification System (COCS) is designed to overcome these workforce planning barriers. The COCS is based on earlier workforce planning activities and the input of technical, workforce planning, and human resource managers from across the DOE complex. It provides a set of mutually-exclusive occupation titles and definitions that cover the broad range of activities present in the DOE complex. The COCS is not a required record-keeping or data management guide. Neither is it intended to replace contractor/DOE-specific classification systems. Instead, the system provides a consistent, high- level, functional structure of occupations to which contractors can crosswalk (map) their job titles.

  15. National Geothermal Resource Assessment and Classification | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Energy Resource Assessment and Classification National Geothermal Resource Assessment and Classification National Geothermal Resource Assessment and Classification presentation at the April 2013 peer review meeting held in Denver, Colorado. gs_resource_assessment_peer2013.pdf (2.37 MB) More Documents & Publications National Geothermal Resource Assessment and Classification track 2: hydrothermal | geothermal 2015 peer review National Geothermal Data System Architecture Design, Testing and

  16. Security Framework for Control System Data Classification and Protection |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy Framework for Control System Data Classification and Protection Security Framework for Control System Data Classification and Protection This document presents a data classification process that gives utility administrators, control engineers, and IT personnel a cohesive approach to deploying efficient and effective process control security. Security Framework for Control System Data Classification and Protection (230.98 KB) More Documents & Publications Essential

  17. Classification CommuniQué - Year: 2013 | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    3 Classification CommuniQué - Year: 2013 Classification newsletters for the year 2013, consisting of the following issues: CommuniQué 2013-1 - Spring 2013 (910.28 KB) CommuniQué 2013-2 - Fall 2013 (724.57 KB) More Documents & Publications Briefing, Transclassified Foreign Nuclear Information - June 2014 Classification CommuniQué - Year: 2012

  18. Microsoft Word - Global Harmonization Classifications.docx

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Harmonization Classifications: The following is prepared for your understanding of the new Global Harmonization System Physical hazards  H200: Unstable explosive  H201: Explosive; mass explosion hazard  H202: Explosive; severe projection hazard  H203: Explosive; fire, blast or projection hazard  H204: Fire or projection hazard  H205: May mass explode in fire  H220: Extremely flammable gas  H221: Flammable gas  H222: Extremely flammable aerosol  H223: Flammable

  19. A classification scheme for risk assessment methods.

    SciTech Connect (OSTI)

    Stamp, Jason Edwin; Campbell, Philip LaRoche

    2004-08-01

    This report presents a classification scheme for risk assessment methods. This scheme, like all classification schemes, provides meaning by imposing a structure that identifies relationships. Our scheme is based on two orthogonal aspects--level of detail, and approach. The resulting structure is shown in Table 1 and is explained in the body of the report. Each cell in the Table represent a different arrangement of strengths and weaknesses. Those arrangements shift gradually as one moves through the table, each cell optimal for a particular situation. The intention of this report is to enable informed use of the methods so that a method chosen is optimal for a situation given. This report imposes structure on the set of risk assessment methods in order to reveal their relationships and thus optimize their usage.We present a two-dimensional structure in the form of a matrix, using three abstraction levels for the rows and three approaches for the columns. For each of the nine cells in the matrix we identify the method type by name and example. The matrix helps the user understand: (1) what to expect from a given method, (2) how it relates to other methods, and (3) how best to use it. Each cell in the matrix represent a different arrangement of strengths and weaknesses. Those arrangements shift gradually as one moves through the table, each cell optimal for a particular situation. The intention of this report is to enable informed use of the methods so that a method chosen is optimal for a situation given. The matrix, with type names in the cells, is introduced in Table 2 on page 13 below. Unless otherwise stated we use the word 'method' in this report to refer to a 'risk assessment method', though often times we use the full phrase. The use of the terms 'risk assessment' and 'risk management' are close enough that we do not attempt to distinguish them in this report. The remainder of this report is organized as follows. In Section 2 we provide context for this report

  20. Cross-ontological analytics for alignment of different classification schemes

    DOE Patents [OSTI]

    Posse, Christian; Sanfilippo, Antonio P; Gopalan, Banu; Riensche, Roderick M; Baddeley, Robert L

    2010-09-28

    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.

  1. Classification CommuniQué - Year: 2014 | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    4 Classification CommuniQué - Year: 2014 Classification newsletters for the year 2014, consisting of the following issues: CommuniQue Spring 2014 (967.62 KB) CommuniQue Fall 2014 (1.04 MB) More Documents & Publications Briefing, DOE Order 475.2B, Identifying Classified Information, What Derivative Classifiers Should Know Brochure, Understanding Classification - June 2012 Declassification Instruction Guide, March 2014

  2. Classification/Declassification of Government Documents | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Energy Services » Classification » Classification/Declassification of Government Documents Classification/Declassification of Government Documents BALANCING NATIONAL SECURITY WITH OPENESS DOE promotes the release of information assets to the maximum extent possible consistent at all times with our paramount concern for the security of our nation. Programs are established to review historical records scheduled for declassification, documents requested under statute or Executive Order,

  3. North American Industry Classification System (NAICS) Search Tool

    Broader source: Energy.gov [DOE]

    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...

  4. Hawaii Land Study Bureau's Land Classification Finder | Open...

    Open Energy Info (EERE)

    Not Provided DOI Not Provided Check for DOI availability: http:crossref.org Online Internet link for Hawaii Land Study Bureau's Land Classification Finder Citation Hawaii State...

  5. Briefing, Classification Bulletin GEN-16 - October 2014 | Department...

    Broader source: Energy.gov (indexed) [DOE]

    No Comment Policy on Classified Information in the Open Literature This briefing provides information on Classification Bulletin GEN-16, No Comment Policy on Classified Information ...

  6. Special nuclear material information, security classification guidance. Instruction

    SciTech Connect (OSTI)

    Flickinger, A.

    1982-12-03

    The Instruction reissues DoD Instruction 5210.67, July 5, 1979, and provides security classification guidance for information concerning significant quantities of special nuclear material, other than that contained in nuclear weapons and that used in the production of energy in the reactor plant of nuclear-powered ships. Security classification guidance for these data in the latter two applications is contained in Joint DoE/DoD Nuclear Weapons Classification Guide and Joint DoE/DoD Classification Guide for the Naval Nuclear Propulsion Program.

  7. A Brief Classification of Geothermal Systems | Open Energy Information

    Open Energy Info (EERE)

    LibraryAdd to library General: A Brief Classification of Geothermal Systems Author Paul Brophy Published GRC Annual Meeting, 2007 DOI Not Provided Check for DOI availability:...

  8. Classification CommuniQué - Year: 2012 | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    2 Classification CommuniQué - Year: 2012 Classification newsletters for the year 2012 consisting of the following issues: CommuniQué 2012-1 - March/April 2012 (626.89 KB) CommuniQué 2012-2 - September/October 2012 (716.99 KB) CommuniQué 2012-2 - September/October 2012, Crossword Puzzle Solution (36.28 KB) More Documents & Publications Classification CommuniQué - Year: 2013 Classification CommuniQué - Year: 2014

  9. Classification Policy, Guidance & Reports | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Classification Policy, Guidance & Reports Classification Policy, Guidance & Reports Statutes, Regulations, Executive Orders, DOE Directives and Bulletins Atomic Energy Act of 1954 - Establishes Government-wide policies for classifying, safeguarding, and declassifying Restricted Data information. 10 CFR Part 1045 - establishes responsiblities and requirements for classifying and declassifying RD and FRD. Executive Order 13526, Classified National Security Information - Prescribes the

  10. Multivariate classification of infrared spectra of cell and tissue samples

    DOE Patents [OSTI]

    Haaland, David M.; Jones, Howland D. T.; Thomas, Edward V.

    1997-01-01

    Multivariate classification techniques are applied to spectra from cell and tissue samples irradiated with infrared radiation to determine if the samples are normal or abnormal (cancerous). Mid and near infrared radiation can be used for in vivo and in vitro classifications using at least different wavelengths.

  11. WNClASSIflfO CLASSIFICATION CANCELLED

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    WNClASSIflfO ^ CLASSIFICATION CANCELLED DATE FEB 1 6 1957 For The Atomic Cnargy Commission *74/^ Cl<JlMAJUL Chief, Declftuifloatlon Branch ^VAA ARGOfraS NATION f V L j..ABORATOKy C o n t r a c t Mo. W°31»109-Sng-3S Wc Ho Z.irm, D i r e c t o r ; ( t ^ * * 3 j ! * ) ) ! 4 ^ RADIOCARBON .FROM P I L S GRAPHIfB^ CHEMICAL LiETiiODii FOR ITS GOKCKNTRATION JAMES R« ARNOLD AND Wc Fo LIBB3f Photostat P r i c e ' T " - - ^ ^ J y O Microfilm Price $_ Available from the Office of Technical

  12. Hazard classification assessment for the High Voltage Initiator

    SciTech Connect (OSTI)

    Cogan, J.D.

    1994-04-19

    An investigation was conducted to determine whether the High Voltage Initiator (Sandia p number 395710; Navy NAVSEA No. 6237177) could be assigned a Department of Transportation (DOT) hazard classification of ``IGNITERS, 1.4G, UN0325`` under Code of Federal Regulations, 49 CFR 173.101, when packaged per Mound drawing NXB911442. A hazard classification test was performed, and the test data led to a recommended hazard classification of ``IGNITERS, 1.4G, UN0325,`` based on guidance outlined in DOE Order 1540.2 and 49 CFR 173.56.

  13. NEW- DOE O 325.2, Position Management and Classification

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    The order establishes departmental requirements and responsibilities for classifying positions using general schedule (GS) and federal wage system (FWS) standards and for developing and administering a sound position management and classification program within the Department.

  14. National Geothermal Resource Assessment and Classification | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Energy Resource Assessment and Classification National Geothermal Resource Assessment and Classification This work will enable lower risk/cost deployment of conventional and EGS geothermal power. USGS is also supporting GTP input to DOE National Energy Modeling by providing resource assessment data by geothermal region as input to GTP supply curves. analysis_williams_resource_assessment.pdf (661.92 KB) More Documents & Publications National Geothermal Resource Assessment and

  15. Universal Membrane Classification Scheme: Maximizing the Return on High

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Temperature PEM Membrane Research | Department of Energy Universal Membrane Classification Scheme: Maximizing the Return on High Temperature PEM Membrane Research Universal Membrane Classification Scheme: Maximizing the Return on High Temperature PEM Membrane Research This presentation on maximizing the return of high temperature PEM membrane research was given at the High Temperature Membrane Working Group Meeting in May 2007. htmwg_kopasz.pdf (1010.95 KB) More Documents & Publications

  16. Classification Bulletin GEN-16 Revision 2 | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Bulletin GEN-16 Revision 2 Classification Bulletin GEN-16 Revision 2 Provides guidance to DOE Federal and contractor employees with access to classified information on appropriate actions when classified information (i.e., Restricted Data (RD), Formerly Restricted Data (FRD), Transclassified Foreign Nuclear Information (IFNI), National Security Information (NSI)) appears in the open literature and to clarify the circumstances that constitute comment. Classification Bulletin GEN-16 Revision 2

  17. Evaluating multimedia chemical persistence: Classification and regression tree analysis

    SciTech Connect (OSTI)

    Bennett, D.H.; McKone, T.E.; Kastenberg, W.E.

    2000-04-01

    For the thousands of chemicals continuously released into the environment, it is desirable to make prospective assessments of those likely to be persistent. Widely distributed persistent chemicals are impossible to remove from the environment and remediation by natural processes may take decades, which is problematic if adverse health or ecological effects are discovered after prolonged release into the environment. A tiered approach using a classification scheme and a multimedia model for determining persistence is presented. Using specific criteria for persistence, a classification tree is developed to classify a chemical as persistent or nonpersistent based on the chemical properties. In this approach, the classification is derived from the results of a standardized unit world multimedia model. Thus, the classifications are more robust for multimedia pollutants than classifications using a single medium half-life. The method can be readily implemented and provides insight without requiring extensive and often unavailable data. This method can be used to classify chemicals when only a few properties are known and can be used to direct further data collection. Case studies are presented to demonstrate the advantages of the approach.

  18. Automatic classification of time-variable X-ray sources

    SciTech Connect (OSTI)

    Lo, Kitty K.; Farrell, Sean; Murphy, Tara; Gaensler, B. M.

    2014-05-01

    To maximize the discovery potential of future synoptic surveys, especially in the field of transient science, it will be necessary to use automatic classification to identify some of the astronomical sources. The data mining technique of supervised classification is suitable for this problem. Here, we present a supervised learning method to automatically classify variable X-ray sources in the Second XMM-Newton Serendipitous Source Catalog (2XMMi-DR2). Random Forest is our classifier of choice since it is one of the most accurate learning algorithms available. Our training set consists of 873 variable sources and their features are derived from time series, spectra, and other multi-wavelength contextual information. The 10 fold cross validation accuracy of the training data is ∼97% on a 7 class data set. We applied the trained classification model to 411 unknown variable 2XMM sources to produce a probabilistically classified catalog. Using the classification margin and the Random Forest derived outlier measure, we identified 12 anomalous sources, of which 2XMM J180658.7–500250 appears to be the most unusual source in the sample. Its X-ray spectra is suggestive of a ultraluminous X-ray source but its variability makes it highly unusual. Machine-learned classification and anomaly detection will facilitate scientific discoveries in the era of all-sky surveys.

  19. AUTOMATIC CLASSIFICATION OF VARIABLE STARS IN CATALOGS WITH MISSING DATA

    SciTech Connect (OSTI)

    Pichara, Karim; Protopapas, Pavlos

    2013-11-10

    We present an automatic classification method for astronomical catalogs with missing data. We use Bayesian networks and a probabilistic graphical model that allows us to perform inference to predict missing values given observed data and dependency relationships between variables. To learn a Bayesian network from incomplete data, we use an iterative algorithm that utilizes sampling methods and expectation maximization to estimate the distributions and probabilistic dependencies of variables from data with missing values. To test our model, we use three catalogs with missing data (SAGE, Two Micron All Sky Survey, and UBVI) and one complete catalog (MACHO). We examine how classification accuracy changes when information from missing data catalogs is included, how our method compares to traditional missing data approaches, and at what computational cost. Integrating these catalogs with missing data, we find that classification of variable objects improves by a few percent and by 15% for quasar detection while keeping the computational cost the same.

  20. Classification of US hydropower dams by their modes of operation

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    McManamay, Ryan A.; Oigbokie, II, Clement O.; Kao, Shih -Chieh; Bevelhimer, Mark S.

    2016-02-19

    A key challenge to understanding ecohydrologic responses to dam regulation is the absence of a universally transferable classification framework for how dams operate. In the present paper, we develop a classification system to organize the modes of operation (MOPs) for U.S. hydropower dams and powerplants. To determine the full diversity of MOPs, we mined federal documents, open-access data repositories, and internet sources. W then used CART classification trees to predict MOPs based on physical characteristics, regulation, and project generation. Finally, we evaluated how much variation MOPs explained in sub-daily discharge patterns for stream gages downstream of hydropower dams. After reviewingmore » information for 721 dams and 597 power plants, we developed a 2-tier hierarchical classification based on 1) the storage and control of flows to powerplants, and 2) the presence of a diversion around the natural stream bed. This resulted in nine tier-1 MOPs representing a continuum of operations from strictly peaking, to reregulating, to run-of-river, and two tier-2 MOPs, representing diversion and integral dam-powerhouse configurations. Although MOPs differed in physical characteristics and energy production, classification trees had low accuracies (<62%), which suggested accurate evaluations of MOPs may require individual attention. MOPs and dam storage explained 20% of the variation in downstream subdaily flow characteristics and showed consistent alterations in subdaily flow patterns from reference streams. Lastly, this standardized classification scheme is important for future research including estimating reservoir operations for large-scale hydrologic models and evaluating project economics, environmental impacts, and mitigation.« less

  1. A Hybrid Classification Scheme for Mining Multisource Geospatial Data

    SciTech Connect (OSTI)

    Vatsavai, Raju; Bhaduri, Budhendra L

    2007-01-01

    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 are often overlapping. The spectral response distributions of thematic classes are dependent on many factors including elevation, soil types, and atmospheric conditions present at the time of data acquisition. A second problem with statistical classifiers is the requirement of large number of accurate training samples, which are often costly and time consuming to acquire over large geographic regions. With the increasing availability of geospatial databases, it is possible to exploit the knowledge derived from these ancillary datasets to improve classification accuracies even when the class distributions are highly overlapping. Likewise newer semi-supervised techniques can be adopted to improve the parameter estimates of statistical model by utilizing a large number of easily available unlabeled training samples. Unfortunately there is no convenient multivariate statistical model that can be employed for mulitsource geospatial databases. In this paper we present a hybrid semi-supervised learning algorithm that effectively exploits freely available unlabeled training samples from multispectral remote sensing images and also incorporates ancillary geospatial databases. We have conducted several experiments on real datasets, and our new hybrid approach shows over 15% improvement in classification accuracy over conventional classification schemes.

  2. Classification of Birds and Bats Using Flight Tracks

    SciTech Connect (OSTI)

    Cullinan, Valerie I.; Matzner, Shari; Duberstein, Corey A.

    2015-05-01

    Classification of birds and bats that use areas targeted for offshore wind farm development and the inference of their behavior is essential to evaluating the potential effects of development. The current approach to assessing the number and distribution of birds at sea involves transect surveys using trained individuals in boats or airplanes or using high-resolution imagery. These approaches are costly and have safety concerns. Based on a limited annotated library extracted from a single-camera thermal video, we provide a framework for building models that classify birds and bats and their associated behaviors. As an example, we developed a discriminant model for theoretical flight paths and applied it to data (N = 64 tracks) extracted from 5-min video clips. The agreement between model- and observer-classified path types was initially only 41%, but it increased to 73% when small-scale jitter was censored and path types were combined. Classification of 46 tracks of bats, swallows, gulls, and terns on average was 82% accurate, based on a jackknife cross-validation. Model classification of bats and terns (N = 4 and 2, respectively) was 94% and 91% correct, respectively; however, the variance associated with the tracks from these targets is poorly estimated. Model classification of gulls and swallows (N ≥ 18) was on average 73% and 85% correct, respectively. The models developed here should be considered preliminary because they are based on a small data set both in terms of the numbers of species and the identified flight tracks. Future classification models would be greatly improved by including a measure of distance between the camera and the target.

  3. Department of Energy versus Department of Defense: security, classification markings, procedures, and clearance requirements

    SciTech Connect (OSTI)

    Not Available

    1985-01-01

    The differences between the Department of Energy's and the Department of Defense's system of classification and security are clarified.

  4. A Multi-Dimensional Classification Model for Scientific Workflow Characteristics

    SciTech Connect (OSTI)

    Ramakrishnan, Lavanya; Plale, Beth

    2010-04-05

    Workflows have been used to model repeatable tasks or operations in manufacturing, business process, and software. In recent years, workflows are increasingly used for orchestration of science discovery tasks that use distributed resources and web services environments through resource models such as grid and cloud computing. Workflows have disparate re uirements and constraints that affects how they might be managed in distributed environments. In this paper, we present a multi-dimensional classification model illustrated by workflow examples obtained through a survey of scientists from different domains including bioinformatics and biomedical, weather and ocean modeling, astronomy detailing their data and computational requirements. The survey results and classification model contribute to the high level understandingof scientific workflows.

  5. CLASSIFICATION OF THE MGR NON-FUEL COMPONENTS DISPOSAL CONTAINER

    SciTech Connect (OSTI)

    J.A. Ziegler

    1999-08-31

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) non-fuel components disposal container 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).

  6. Microsoft Word - Data Classification Security Framework V5.doc

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    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;

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

    Office of Energy Efficiency and Renewable Energy (EERE) 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

  8. Security classification of information concerning high-energy lasers. Instruction

    SciTech Connect (OSTI)

    MacCallum, J.

    1981-09-18

    The Instruction reissues Department of Defense (DoD) Instruction 5210.61, April 7, 1977, to update policy and guidance, and establishes uniform criteria for the security classification of information concerning DoD programs and projects involving the research, development, test and evaluation (RDT E), application, production, and operational use of high-energy lasers (HEL), and their application for military purposes, whether as weapons or in other military systems.

  9. CLASSIFICATION OF THE MGR SAFEGUARDS AND SECURITY SYSTEM

    SciTech Connect (OSTI)

    J.A. Ziegler

    1999-08-31

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) safeguards and security 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).

  10. 3.0 UNIT IDENTIFICATION, CLASSIFICATION, AND PRIORITIZATION

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    3-1 3.0 UNIT IDENTIFICATION, CLASSIFICATION, AND PRIORITIZATION 3.1 INTRODUCTION This section describes what constitutes a waste management unit at the Hanford Site. In addition, it describes how waste management units are classified, prioritized, and grouped for common investigation and response or corrective action. A waste management unit represents any location within the boundary of the Hanford Site that may require action to mitigate a potential environmental impact. This would include all

  11. Deep Learning in Label-free Cell Classification

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

    2016-03-15

    Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

  12. UAS Detection Classification and Neutralization: Market Survey 2015

    SciTech Connect (OSTI)

    Birch, Gabriel Carisle; Griffin, John Clark; Erdman, Matthew Kelly

    2015-07-01

    The purpose of this document is to briefly frame the challenges of detecting low, slow, and small (LSS) unmanned aerial systems (UAS). The conclusion drawn from internal discussions and external reports is the following; detection of LSS UAS is a challenging problem that can- not be achieved with a single detection modality for all potential targets. Classification of LSS UAS, especially classification in the presence of background clutter (e.g., urban environment) or other non-threating targets (e.g., birds), is under-explored. Though information of avail- able technologies is sparse, many of the existing options for UAS detection appear to be in their infancy (when compared to more established ground-based air defense systems for larger and/or faster threats). Companies currently providing or developing technologies to combat the UAS safety and security problem are certainly worth investigating, however, no company has provided the statistical evidence necessary to support robust detection, identification, and/or neutralization of LSS UAS targets. The results of a market survey are included that highlights potential commercial entities that could contribute some technology that assists in the detection, classification, and neutral- ization of a LSS UAS. This survey found no clear and obvious commercial solution, though recommendations are given for further investigation of several potential systems.

  13. Unsupervised Feature Learning for High-Resolution Satellite Image Classification

    SciTech Connect (OSTI)

    Cheriyadat, Anil M

    2013-01-01

    The rich data provided by high-resolution satellite imagery allow us to directly model geospatial neighborhoods by understanding their spatial and structural patterns. In this paper we explore an unsupervised feature learning approach to model geospatial neighborhoods for classification purposes. While pixel and object based classification approaches are widely used for satellite image analysis, often these approaches exploit the high-fidelity image data in a limited way. In this paper we extract low-level features to characterize the local neighborhood patterns. We exploit the unlabeled feature measurements in a novel way to learn a set of basis functions to derive new features. The derived sparse feature representation obtained by encoding the measured features in terms of the learned basis function set yields superior classification performance. We applied our technique on two challenging image datasets: ORNL dataset representing one-meter spatial resolution satellite imagery representing five land-use categories and, UCMERCED dataset consisting of 21 different categories representing sub-meter resolution overhead imagery. Our results are highly promising and, in the case of UCMERCED dataset we outperform the best results obtained for this dataset. We show that our feature extraction and learning methods are highly effective in developing a detection system that can be used to automatically scan large-scale high-resolution satellite imagery for detecting large-facility.

  14. A Biochar Classification System and Associated Test Methods

    SciTech Connect (OSTI)

    Camps-Arbestain, Marta; Amonette, James E.; Singh, Balwant; Wang, Tao; Schmidt, Hans-Peter

    2015-02-18

    In this chapter, a biochar classification system related to its use as soil amendment is proposed. This document builds upon previous work and constrains its scope to materials with properties that satisfy the criteria for biochar as defined by either the International Biochar Initiative (IBI) Biochar Standards or the European Biochar Community (EBC) Standards, and it is intended to minimise the need for testing in addition to those required according to the above-mentioned standards. The classification system envisions enabling stakeholders and commercial entities to (i) identify the most suitable biochar to fulfil the requirements for a particular soil and/or land-use, and (ii) distinguish the application of biochar for specific niches (e.g., soilless agriculture). It is based on the best current knowledge and the intention is to periodically review and update the document based on new data and knowledge that become available in the scientific literature. The main thrust of this classification system is based on the direct or indirect beneficial effects that biochar provides from its application to soil. We have classified the potential beneficial effects of biochar application to soils into five categories with their corresponding classes, where applicable: (i) carbon (C) storage value, (ii) fertiliser value, (iii) liming value, (iv) particle-size, and (v) use in soil-less agriculture. A summary of recommended test methods is provided at the end of the chapter.

  15. Various forms of indexing HDMR for modelling multivariate classification problems

    SciTech Connect (OSTI)

    Aksu, a?r?; Tunga, M. Alper

    2014-12-10

    The Indexing HDMR method was recently developed for modelling multivariate interpolation problems. The method uses the Plain HDMR philosophy in partitioning the given multivariate data set into less variate data sets and then constructing an analytical structure through these partitioned data sets to represent the given multidimensional problem. Indexing HDMR makes HDMR be applicable to classification problems having real world data. Mostly, we do not know all possible class values in the domain of the given problem, that is, we have a non-orthogonal data structure. However, Plain HDMR needs an orthogonal data structure in the given problem to be modelled. In this sense, the main idea of this work is to offer various forms of Indexing HDMR to successfully model these real life classification problems. To test these different forms, several well-known multivariate classification problems given in UCI Machine Learning Repository were used and it was observed that the accuracy results lie between 80% and 95% which are very satisfactory.

  16. THE PHOTOMETRIC CLASSIFICATION SERVER FOR Pan-STARRS1

    SciTech Connect (OSTI)

    Saglia, R. P.; Bender, R.; Seitz, S.; Senger, R.; Snigula, J.; Phleps, S.; Wilman, D.; Tonry, J. L.; Burgett, W. S.; Chambers, K. C.; Heasley, J. N.; Kaiser, N.; Magnier, E. A.; Morgan, J. S.; Greisel, N.; Bailer-Jones, C. A. L.; Klement, R. J.; Rix, H.-W.; Smith, K.; Green, P. J.; and others

    2012-02-20

    The Pan-STARRS1 survey is obtaining multi-epoch imaging in five bands (g{sub P1} r{sub P1} i{sub P1} z{sub P1} y{sub P1}) over the entire sky north of declination -30 deg. We describe here the implementation of the Photometric Classification Server (PCS) for Pan-STARRS1. PCS will allow the automatic classification of objects into star/galaxy/quasar classes based on colors and the measurement of photometric redshifts for extragalactic objects, and will constrain stellar parameters for stellar objects, working at the catalog level. We present tests of the system based on high signal-to-noise photometry derived from the Medium-Deep Fields of Pan-STARRS1, using available spectroscopic surveys as training and/or verification sets. We show that the Pan-STARRS1 photometry delivers classifications and photometric redshifts as good as the Sloan Digital Sky Survey (SDSS) photometry to the same magnitude limits. In particular, our preliminary results, based on this relatively limited data set down to the SDSS spectroscopic limits, and therefore potentially improvable, show that stars are correctly classified as such in 85% of cases, galaxies in 97%, and QSOs in 84%. False positives are less than 1% for galaxies, Almost-Equal-To 19% for stars, and Almost-Equal-To 28% for QSOs. Moreover, photometric redshifts for 1000 luminous red galaxies up to redshift 0.5 are determined to 2.4% precision (defined as 1.48 Multiplication-Sign Median|z{sub phot} - z{sub spec}|/(1 + z)) with just 0.4% catastrophic outliers and small (-0.5%) residual bias. For bluer galaxies up to the same redshift, the residual bias (on average -0.5%) trend, percentage of catastrophic failures (1.2%), and precision (4.2%) are higher, but still interestingly small for many science applications. Good photometric redshifts (to 5%) can be obtained for at most 60% of the QSOs of the sample. PCS will create a value-added catalog with classifications and photometric redshifts for eventually many millions of sources.

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

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (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 ...

  18. Machine Learning Approaches for High-resolution Urban Land Cover Classification: A Comparative Study

    SciTech Connect (OSTI)

    Vatsavai, Raju; Chandola, Varun; Cheriyadat, Anil M; Bright, Eddie A; Bhaduri, Budhendra L; Graesser, Jordan B

    2011-01-01

    The proliferation of several machine learning approaches makes it difficult to identify a suitable classification technique for analyzing high-resolution remote sensing images. In this study, ten classification techniques were compared from five broad machine learning categories. Surprisingly, the performance of simple statistical classification schemes like maximum likelihood and Logistic regression over complex and recent techniques is very close. Given that these two classifiers require little input from the user, they should still be considered for most classification tasks. Multiple classifier systems is a good choice if the resources permit.

  19. DOE Publishes Petition of CSA Group for Classification as a Nationally...

    Broader source: Energy.gov (indexed) [DOE]

    notice of petition and request for public comments regarding CSA Group for classification as a nationally recognized certification program for small electric motors. 78 FR...

  20. NEW- DOE O 325.2, Position Management and Classification - DOE...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    NEW- DOE O 325.2, Position Management and Classification by Website Administrator The order establishes departmental requirements and responsibilities for classifying positions...

  1. How to Find More Supernovae with Less Work: Object ClassificationTechn...

    Office of Scientific and Technical Information (OSTI)

    Language: English Subject: 99; ASTEROIDS; CLASSIFICATION; DETECTION; EFFICIENCY; FORESTS; ... Word Cloud More Like This Full Text preview image File size NAView Full Text View Full ...

  2. Support Vector Machine algorithm for regression and classification

    Energy Science and Technology Software Center (OSTI)

    2001-08-01

    The software is an implementation of the Support Vector Machine (SVM) algorithm that was invented and developed by Vladimir Vapnik and his co-workers at AT&T Bell Laboratories. The specific implementation reported here is an Active Set method for solving a quadratic optimization problem that forms the major part of any SVM program. The implementation is tuned to specific constraints generated in the SVM learning. Thus, it is more efficient than general-purpose quadratic optimization programs. Amore » decomposition method has been implemented in the software that enables processing large data sets. The size of the learning data is virtually unlimited by the capacity of the computer physical memory. The software is flexible and extensible. Two upper bounds are implemented to regulate the SVM learning for classification, which allow users to adjust the false positive and false negative rates. The software can be used either as a standalone, general-purpose SVM regression or classification program, or be embedded into a larger software system.« less

  3. Hazard categorization and classification for the sodium storage facility

    SciTech Connect (OSTI)

    Van Keuren, J.C.

    1994-08-30

    The Sodium Storage Facility is planned to be constructed in the 400 area for long term storage of sodium from the Fast Flux Test Facility (FFTF). It will contain four large sodium storage tanks. Three of the tanks have a capacity of 80,000 gallons of sodium each, and the fourth will hold 52,500 gallons. The tanks will be connected by piping with each other and to the FFTF. Sodium from the FFTF primary and secondary Heat Transport Systems (HTS), Interim Decay Storage (IDS), and the Fuel Storage Facility (FSF) will be transferred to the facility, and stored there in a frozen state pending final disposition. A Hazard Classification has been performed in order to evaluate the potential toxic consequences of a sodium fire according to the provisions of DOE Order 5481.1B. The conclusion of these evaluations is that the Sodium Storage Facility meets the requirements of the lowest Hazard Category, i.e., radiological facility, and the Hazard Classification is recommended to be moderate.

  4. Towards catchment classification in data-scarce regions

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Auerbach, Daniel A.; Buchanan, Brian P.; Alexiades, Alex V.; Anderson, Elizabeth P.; Encalada, Andrea C.; Larson, Erin I.; McManamay, Ryan A.; Poe, Gregory L.; Walter, M. Todd; Flecker, Alexander S.

    2016-01-29

    Assessing spatial variation in hydrologic processes can help to inform freshwater management and advance ecological understanding, yet many areas lack sufficient flow records on which to base classifications. Seeking to address this challenge, we apply concepts developed in data-rich settings to public, global data in order to demonstrate a broadly replicable approach to characterizing hydrologic variation. The proposed approach groups the basins associated with reaches in a river network according to key environmental drivers of hydrologic conditions. This initial study examines Colorado (USA), where long-term streamflow records permit comparison to previously distinguished flow regime types, and the Republic of Ecuador,more » where data limitations preclude such analysis. The flow regime types assigned to gages in Colorado corresponded reasonably well to the classes distinguished from environmental features. The divisions in Ecuador reflected major known biophysical gradients while also providing a higher resolution supplement to an existing depiction of freshwater ecoregions. Although freshwater policy and management decisions occur amidst uncertainty and imperfect knowledge, this classification framework offers a rigorous and transferrable means to distinguish catchments in data-scarce regions. The maps and attributes of the resulting ecohydrologic classes offer a departure point for additional study and data collection programs such as the placement of stations in under-monitored classes, and the divisions may serve as a preliminary template with which to structure conservation efforts such as environmental flow assessments.« less

  5. Pattern classification and associative recall by neural networks

    SciTech Connect (OSTI)

    Chiueh, Tzi-Dar.

    1989-01-01

    The first part of this dissertation discusses a new classifier based on a multilayer feed-forward network architecture. The main idea is to map irregularly-distributed prototypes in a classification problem to codewords that are organized in some way. Then the pattern classification problem is transformed into a threshold decoding problem, which is easily solved using simple hard-limiter neurons. At first the author proposes the new model and introduce two families of good internal representation codes. Then some analyses and software simulation concerning the storage capacity of this new model are done. The results show that the new classifier is much better than the classifier based on the Hopfield model in terms of both the storage capacity and the ability to classify correlated prototypes. A general model for neural network associative memories with a feedback structure is proposed. Many existing neural network associative memories can be expressed as special cases of this general model. Among these models, there is a class of associative memories, called correlation associative memories, that are capable of storing a large number of memory patterns. If the function used in the evolution equation is monotonically nondecreasing, then a correlation associative memory can be proved to be asymptotically stable in both the synchronous and asynchronous updating modes. Of these correlation associative memories, one stands out because of its VLSI implementation feasibility and large storage capacity. This memory uses the exponentiation function in its evolution equation; hence it is called exponential correlation associative memory (ECAM).

  6. Automatic Fault Characterization via Abnormality-Enhanced Classification

    SciTech Connect (OSTI)

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

    2010-12-20

    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.

  7. EPA`s program for risk assessment guidelines: Cancer classification issues

    SciTech Connect (OSTI)

    Wiltse, J.

    1990-12-31

    Issues presented are related to classification of weight of evidence in cancer risk assessments. The focus in this paper is on lines of evidence used in constructing a conclusion about potential human carcinogenicity. The paper also discusses issues that are mistakenly addressed as classification issues but are really part of the risk assessment process. 2 figs.

  8. Associations among hydrologic classifications and fish traits to support environmental flow standards

    SciTech Connect (OSTI)

    McManamay, Ryan A; Bevelhimer, Mark S; Frimpong, Dr. Emmanuel A,

    2014-01-01

    Classification systems are valuable to ecological management in that they organize information into consolidated units thereby providing efficient means to achieve conservation objectives. Of the many ways classifications benefit management, hypothesis generation has been discussed as the most important. However, in order to provide templates for developing and testing ecologically relevant hypotheses, classifications created using environmental variables must be linked to ecological patterns. Herein, we develop associations between a recent US hydrologic classification and fish traits in order to form a template for generating flow ecology hypotheses and supporting environmental flow standard development. Tradeoffs in adaptive strategies for fish were observed across a spectrum of stable, perennial flow to unstable intermittent flow. In accordance with theory, periodic strategists were associated with stable, predictable flow, whereas opportunistic strategists were more affiliated with intermittent, variable flows. We developed linkages between the uniqueness of hydrologic character and ecological distinction among classes, which may translate into predictions between losses in hydrologic uniqueness and ecological community response. Comparisons of classification strength between hydrologic classifications and other frameworks suggested that spatially contiguous classifications with higher regionalization will tend to explain more variation in ecological patterns. Despite explaining less ecological variation than other frameworks, we contend that hydrologic classifications are still useful because they provide a conceptual linkage between hydrologic variation and ecological communities to support flow ecology relationships. Mechanistic associations among fish traits and hydrologic classes support the presumption that environmental flow standards should be developed uniquely for stream classes and ecological communities, therein.

  9. A Visual Analytics Approach for Correlation, Classification, and Regression Analysis

    SciTech Connect (OSTI)

    Steed, Chad A; SwanII, J. Edward; Fitzpatrick, Patrick J.; Jankun-Kelly, T.J.

    2012-02-01

    New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today's increasing complex, multivariate data sets. In this paper, a novel visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today's data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. The current work provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.

  10. Development of characterization protocol for mixed liquid radioactive waste classification

    SciTech Connect (OSTI)

    Zakaria, Norasalwa; Wafa, Syed Asraf; Wo, Yii Mei; Mahat, Sarimah

    2015-04-29

    Mixed liquid organic waste generated from health-care and research activities containing tritium, carbon-14, and other radionuclides posed specific challenges in its management. Often, these wastes become legacy waste in many nuclear facilities and being considered as problematic waste. One of the most important recommendations made by IAEA is to perform multistage processes aiming at declassification of the waste. At this moment, approximately 3000 bottles of mixed liquid waste, with estimated volume of 6000 litres are currently stored at the National Radioactive Waste Management Centre, Malaysia and some have been stored for more than 25 years. The aim of this study is to develop a characterization protocol towards reclassification of these wastes. The characterization protocol entails waste identification, waste screening and segregation, and analytical radionuclides profiling using various analytical procedures including gross alpha/ gross beta, gamma spectrometry, and LSC method. The results obtained from the characterization protocol are used to establish criteria for speedy classification of the waste.

  11. Classification of groundwater at the Nevada Test Site

    SciTech Connect (OSTI)

    Chapman, J.B.

    1994-08-01

    Groundwater occurring at the Nevada Test Site (NTS) has been classified according to the ``Guidelines for Ground-Water Classification Under the US Environmental Protection Agency (EPA) Ground-Water Protection Strategy`` (June 1988). All of the groundwater units at the NTS are Class II, groundwater currently (IIA) or potentially (IIB) a source of drinking water. The Classification Review Area (CRA) for the NTS is defined as the standard two-mile distance from the facility boundary recommended by EPA. The possibility of expanding the CRA was evaluated, but the two-mile distance encompasses the area expected to be impacted by contaminant transport during a 10-year period (EPA,s suggested limit), should a release occur. The CRA is very large as a consequence of the large size of the NTS and the decision to classify the entire site, not individual areas of activity. Because most activities are located many miles hydraulically upgradient of the NTS boundary, the CRA generally provides much more than the usual two-mile buffer required by EPA. The CRA is considered sufficiently large to allow confident determination of the use and value of groundwater and identification of potentially affected users. The size and complex hydrogeology of the NTS are inconsistent with the EPA guideline assumption of a high degree of hydrologic interconnection throughout the review area. To more realistically depict the site hydrogeology, the CRA is subdivided into eight groundwater units. Two main aquifer systems are recognized: the lower carbonate aquifer system and the Cenozoic aquifer system (consisting of aquifers in Quaternary valley fill and Tertiary volcanics). These aquifer systems are further divided geographically based on the location of low permeability boundaries.

  12. Classification of Malaysia aromatic rice using multivariate statistical analysis

    SciTech Connect (OSTI)

    Abdullah, A. H.; Adom, A. H.; Shakaff, A. Y. Md; Masnan, M. J.; Zakaria, A.; Rahim, N. A.; Omar, O.

    2015-05-15

    Aromatic rice (Oryza sativa L.) is considered as the best quality premium rice. The varieties are preferred by consumers because of its preference criteria such as shape, colour, distinctive aroma and flavour. The price of aromatic rice is higher than ordinary rice due to its special needed growth condition for instance specific climate and soil. Presently, the aromatic rice quality is identified by using its key elements and isotopic variables. The rice can also be classified via Gas Chromatography Mass Spectrometry (GC-MS) or human sensory panels. However, the uses of human sensory panels have significant drawbacks such as lengthy training time, and prone to fatigue as the number of sample increased and inconsistent. The GC–MS analysis techniques on the other hand, require detailed procedures, lengthy analysis and quite costly. This paper presents the application of in-house developed Electronic Nose (e-nose) to classify new aromatic rice varieties. The e-nose is used to classify the variety of aromatic rice based on the samples odour. The samples were taken from the variety of rice. The instrument utilizes multivariate statistical data analysis, including Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and K-Nearest Neighbours (KNN) to classify the unknown rice samples. The Leave-One-Out (LOO) validation approach is applied to evaluate the ability of KNN to perform recognition and classification of the unspecified samples. The visual observation of the PCA and LDA plots of the rice proves that the instrument was able to separate the samples into different clusters accordingly. The results of LDA and KNN with low misclassification error support the above findings and we may conclude that the e-nose is successfully applied to the classification of the aromatic rice varieties.

  13. Classification Bulletin GEN-16, Revision 2, No Comment Poly on Classified Information in the Open Literature

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    3, 2014 MEMORANDUM FORDISTRl ~N fJJ!}/, 'ViJ ~ FROM: A~~s?oVokdKES DIRECTOR OFFICE OF CLASSIFICATION OFFICE OF ENVIRONMENT, HEALTH, SAFETY AND SECURITY SUBJECT: Classification Bulletin GEN-16, REVISION 2, "No Comment" Policy on Classified Information in the Open Literature Classification Bulletin GEN-16, Revision 1, '"NO COMMENT' POLICY ON CLASSIFIED INFORMATION IN THE PUBLIC DOMAIN," has been updated to address concerns regarding documents marked as classified in the open

  14. Fact #623: May 17, 2010 Classification Changes in the CAFE Standards |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy 3: May 17, 2010 Classification Changes in the CAFE Standards Fact #623: May 17, 2010 Classification Changes in the CAFE Standards Beginning with model year (MY) 2011, the classification of cars or light trucks has changed for the purposes of the Corporate Average Fuel Economy (CAFE) Standards. Two-wheel-drive (2wd) sport utility vehicles of 6,000 pounds or less gross vehicle weight rating (GVWR) will no longer be classified as light trucks, though the 4wd models of these

  15. Classification of generalized quantum statistics associated with the exceptional Lie (super)algebras

    SciTech Connect (OSTI)

    Stoilova, N. I.; Jeugt, J. van der

    2007-04-15

    Generalized quantum statistics (GQS) associated with a Lie algebra or Lie superalgebra extends the notion of para-Bose or para-Fermi statistics. Such GQS have been classified for all classical simple Lie algebras and basic classical Lie superalgebras. In the current paper we finalize this classification for all exceptional Lie algebras and superalgebras. Since the definition of GQS is closely related to a certain Z grading of the Lie (super)algebra G, our classification reproduces some known Z gradings of exceptional Lie algebras. For exceptional Lie superalgebras such a classification of Z gradings has not been given before.

  16. Historical literature review on waste classification and categorization

    SciTech Connect (OSTI)

    Croff, A.G.; Richmond, A.A.; Williams, J.P.

    1995-03-01

    The Staff of the Waste Management Document Library (WMDL), in cooperation with Allen Croff have been requested to provide information support for a historical search concerning waste categorization/classification. This bibliography has been compiled under the sponsorship of Oak Ridge National Laboratory`s Chemical Technology Division to help in Allen`s ongoing committee work with the NRC/NRCP. After examining the search, Allen Croff saw the value of the search being published. Permission was sought from the database providers to allow limited publication (i.e. 20--50 copies) of the search for internal distribution at the Oak Ridge National Laboratory and for Allen Croff`s associated committee. Citations from the database providers who did not grant legal permission for their material to be published have been omitted from the literature review. Some of the longer citations have been included in an abbreviated form in the search to allow the format of the published document to be shortened from approximately 1,400 pages. The bibliography contains 372 citations.

  17. Classification methodology for tritiated waste requiring interim storage

    SciTech Connect (OSTI)

    Cana, D.; Dall'ava, D.

    2015-03-15

    Fusion machines like the ITER experimental research facility will use tritium as fuel. Therefore, most of the solid radioactive waste will result not only from activation by 14 MeV neutrons, but also from contamination by tritium. As a consequence, optimizing the treatment process for waste containing tritium (tritiated waste) is a major challenge. This paper summarizes the studies conducted in France within the framework of the French national plan for the management of radioactive materials and waste. The paper recommends a reference program for managing this waste based on its sorting, treatment and packaging by the producer. It also recommends setting up a 50-year temporary storage facility to allow for tritium decay and designing future disposal facilities using tritiated radwaste characteristics as input data. This paper first describes this waste program and then details an optimized classification methodology which takes into account tritium decay over a 50-year storage period. The paper also describes a specific application for purely tritiated waste and discusses the set-up expected to be implemented for ITER decommissioning waste (current assumption). Comparison between this optimized approach and other viable detritiation techniques will be drawn. (authors)

  18. Developmental defects in zebrafish for classification of EGF pathway inhibitors

    SciTech Connect (OSTI)

    Pruvot, Benoist; Cur, Yoann; Djiotsa, Joachim; Voncken, Audrey; Muller, Marc

    2014-01-15

    One of the major challenges when testing drug candidates targeted at a specific pathway in whole animals is the discrimination between specific effects and unwanted, off-target effects. Here we used the zebrafish to define several developmental defects caused by impairment of Egf signaling, a major pathway of interest in tumor biology. We inactivated Egf signaling by genetically blocking Egf expression or using specific inhibitors of the Egf receptor function. We show that the combined occurrence of defects in cartilage formation, disturbance of blood flow in the trunk and a decrease of myelin basic protein expression represent good indicators for impairment of Egf signaling. Finally, we present a classification of known tyrosine kinase inhibitors according to their specificity for the Egf pathway. In conclusion, we show that developmental indicators can help to discriminate between specific effects on the target pathway from off-target effects in molecularly targeted drug screening experiments in whole animal systems. - Highlights: We analyze the functions of Egf signaling on zebrafish development. Genetic blocking of Egf expression causes cartilage, myelin and circulatory defects. Chemical inhibition of Egf receptor function causes similar defects. Developmental defects can reveal the specificity of Egf pathway inhibitors.

  19. Classification of heart valve condition using acoustic measurements

    SciTech Connect (OSTI)

    Clark, G.

    1994-11-15

    Prosthetic heart valves and the many great strides in valve design have been responsible for extending the life spans of many people with serious heart conditions. Even though the prosthetic valves are extremely reliable, they are eventually susceptible to long-term fatigue and structural failure effects expected from mechanical devices operating over long periods of time. The purpose of our work is to classify the condition of in vivo Bjork-Shiley Convexo-Concave (BSCC) heart valves by processing acoustic measurements of heart valve sounds. The structural failures of interest for Bscc valves is called single leg separation (SLS). SLS can occur if the outlet strut cracks and separates from the main structure of the valve. We measure acoustic opening and closing sounds (waveforms) using high sensitivity contact microphones on the patient`s thorax. For our analysis, we focus our processing and classification efforts on the opening sounds because they yield direct information about outlet strut condition with minimal distortion caused by energy radiated from the valve disc.

  20. Classification and storage of wastewater from floor finish removal operations

    SciTech Connect (OSTI)

    Hunt, C.E.

    1996-05-01

    This study evaluates the wastewater generated from hard surface floor finish removal operations at Lawrence Livermore Laboratory in order to determine if this wastewater is a hazardous waste, either by statistical evaluation, or other measurable regulatory guidelines established in California Regulations. This research also comparatively evaluates the 55 gallon drum and other portable tanks, all less than 1,000 gallons in size in order to determine which is most effective for the management of this waste stream at Lawrence Livermore Laboratory. The statistical methods in SW-846 were found to be scientifically questionable in their application to hazardous waste determination. In this statistical evaluation, the different data transformations discussed in the regulatory guidance document were applied along with the log transformation to the population of 18 samples from 55 gallon drums. Although this statistical evaluation proved awkward in its application, once the data is collected and organized on a spreadsheet this statistical analysis can be an effective tool which can aid the environmental manager in the hazardous waste classification process.

  1. System diagnostics using qualitative analysis and component functional classification

    DOE Patents [OSTI]

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

    1993-11-23

    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.

  2. System diagnostics using qualitative analysis and component functional classification

    DOE Patents [OSTI]

    Reifman, Jaques; Wei, Thomas Y. C.

    1993-01-01

    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.

  3. Deep Spatiotemporal Feature Learning with Application to Image Classification

    SciTech Connect (OSTI)

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

    2010-01-01

    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.

  4. Classification of subsurface objects using singular values derived from signal frames

    DOE Patents [OSTI]

    Chambers, David H; Paglieroni, David W

    2014-05-06

    The classification system represents a detected object with a feature vector derived from the return signals acquired by an array of N transceivers operating in multistatic mode. The classification system generates the feature vector by transforming the real-valued return signals into complex-valued spectra, using, for example, a Fast Fourier Transform. The classification system then generates a feature vector of singular values for each user-designated spectral sub-band by applying a singular value decomposition (SVD) to the N.times.N square complex-valued matrix formed from sub-band samples associated with all possible transmitter-receiver pairs. The resulting feature vector of singular values may be transformed into a feature vector of singular value likelihoods and then subjected to a multi-category linear or neural network classifier for object classification.

  5. Early F-type stars - refined classification, confrontation with Stromgren photometry, and the effects of rotation

    SciTech Connect (OSTI)

    Gray, R.O.; Garrison, R.F.

    1989-02-01

    The classification for early F-type stars in the MK spectral classification system presented by Gray and Garrison (1987) is refined. The effect of rotation on spectral classification and ubvy-beta photometry of early F-type stars is examined. It is found that the classical luminosity criterion, the 4417 A/4481 A ratio gives inconsistent results. It is shown that most of the stars in the Delta Delphini class of metallic-line stars are either normal or are indistinguishable from proto-Am stars. It is suggested that the designation Delta Delphini should be dropped. The classifications are compared with Stromgren photometry. The effects of rotation on the delta-c sub 1 index in the early-F field dwarfs is demonstrated. 55 references.

  6. Classification of Lattice Defects in the Kesterite Cu2ZnSnS4...

    Office of Scientific and Technical Information (OSTI)

    Journal Article: Classification of Lattice Defects in the Kesterite Cu2ZnSnS4 and Cu2ZnSnSe4 Earth-Abundant Solar Cell Absorbers Citation Details In-Document Search Title: ...

  7. Stream Classification Tool User Manual: For Use in Applications in Hydropower-Related Evironmental Mitigation

    SciTech Connect (OSTI)

    McManamay, Ryan A.; Troia, Matthew J.; DeRolph, Christopher R.; Samu, Nicole M.

    2016-01-01

    Stream classifications are an inventory of different types of streams. Classifications help us explore similarities and differences among different types of streams, make inferences regarding stream ecosystem behavior, and communicate the complexities of ecosystems. We developed a nested, layered, and spatially contiguous stream classification to characterize the biophysical settings of stream reaches within the Eastern United States (~ 900,000 reaches). The classification is composed of five natural characteristics (hydrology, temperature, size, confinement, and substrate) along with several disturbance regime layers, and each was selected because of their relevance to hydropower mitigation. We developed the classification at the stream reach level using the National Hydrography Dataset Plus Version 1 (1:100k scale). The stream classification is useful to environmental mitigation for hydropower dams in multiple ways. First, it creates efficiency in the regulatory process by creating an objective and data-rich means to address meaningful mitigation actions. Secondly, the SCT addresses data gaps as it quickly provides an inventory of hydrology, temperature, morphology, and ecological communities for the immediate project area, but also surrounding streams. This includes identifying potential reference streams as those that are proximate to the hydropower facility and fall within the same class. These streams can potentially be used to identify ideal environmental conditions or identify desired ecological communities. In doing so, the stream provides some context for how streams may function, respond to dam regulation, and an overview of specific mitigation needs. Herein, we describe the methodology in developing each stream classification layer and provide a tutorial to guide applications of the classification (and associated data) in regulatory settings, such as hydropower (re)licensing.

  8. Updating the US hydrologic classification: an approach to clustering and stratifying ecohydrologic data

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Updating the US hydrologic classification: an approach to clustering and stratifying ecohydrologic data Ryan A. McManamay, * Mark S. Bevelhimer and Shih-Chieh Kao Environmental Sciences Division, Oak Ridge National Lab, Oak Ridge, TN 37831, USA ABSTRACT Hydrologic classifications unveil the structure of relationships among groups of streams with differing streamflows and provide a foundation for drawing inferences about the principles that govern those relationships. Hydrologic classes provide a

  9. Classification of poison inhalation hazard materials into severity groups

    SciTech Connect (OSTI)

    Griego, N.R.; Weiner, R.F.

    1996-02-01

    Approximately 1.5 billion tons of hazardous materials (hazmat) are transported in the US annually, and most reach their destinations safely. However, there are infrequent transportation accidents in which hazmat is released from its packaging. These accidental releases can potentially affect the health of the exposed population and damage the surrounding environment. Although these events are rare, they cause genuine public concern. Therefore, the US Department of Transportation Research & Special Programs Administration (DOT- RSPA) has sponsored a project to evaluate the protection provided by the current bulk (defined as larger than 118 gallons) packagings used to transport materials that have been classified as Poison Inhalation Hazards (PIH) and recommend performance standards for these PIH packagings. This project was limited to evaluating bulk packagings larger than 2000 gallons. This project involved classifying the PIH into severity categories so that only one set of packaging performance criteria would be needed for each severity category rather than a separate set of performance criteria for each individual PIH. By grouping the PIH into Hazard Zones, Packaging Groups and performance standards for these Hazard Zones can be defined. Each Hazard Zone can correspond to a Packaging Group or, as in 49CFR173 for non-bulk packagings, one Packaging Group may cover more than one Hazard Zone. If the packaging groups are chosen to correspond to the classification categories presented in this report, then the maximum allowable leak rates used to define these categories could be used as the maximum allowable leak rates for the performance oriented packaging standards. The results discussed in this report are intended to provide quantitative guidance for the appropriate authorities to use in making these decisions.

  10. Authorization Basis Safety Classification of Transfer Bay Bridge Crane at the 105-K Basins

    SciTech Connect (OSTI)

    CHAFFEE, G.A.

    2000-04-06

    This supporting document provides the bases for the safety classification for the K Basin transfer bay bridge crane and the bases for the Structures, Systems, and Components (SSC) safety classification. A table is presented that delineates the safety significant components. This safety classification is based on a review of the Authorization Basis (AB). This Authorization Basis review was performed regarding AB and design baseline issues. The primary issues are: (1) What is the AB for the safety classification of the transfer bay bridge crane? (2) What does the SSC safety classification ''Safety Significant'' or ''Safety Significant for Design Only'' mean for design requirements and quality requirements for procurement, installation and maintenance (including replacement of parts) activities for the crane during its expected life time? The AB information on the crane was identified based on review of Department of Energy--Richland Office (RL) and Spent Nuclear Fuel (SNF) Project correspondence, K Basin Safety Analysis Report (SAR) and RL Safety Evaluation Reports (SERs) of SNF Project SAR submittals. The relevant correspondence, actions and activities taken and substantive directions or conclusions of these documents are provided in Appendix A.

  11. A modified version of the geomechanics classification for entry design in underground coal mines

    SciTech Connect (OSTI)

    Newman, D.A.; Bieniawski, Z.T.

    1985-01-01

    The Geomechanics Classification was modified for entry and roof support design in underground room-and-pillar coal mines. Adjustment multipliers were introduced to incorporate the influence of strata weatherability, high horizontal stresses, and the roof support reinforcement factor into the existing classification system. Sixty-two case histories of both standing and fallen mine roof were collected from two mines in the northern Appalachian coalfield. Twenty-seven engineering and geologic parameters were recorded for each case. A partial correlation analysis was carried out on the cases to establish which parameters have a significant impact upon the supported stand-up time of coal mine roof. Survival analysis, a statistical technique used in medical research to assess the effect of a drug or treatment on a patient's life expectancy, was conducted together with stepwise multiple regression to derive values for the adjustment multipliers. A practical example is included to illustrate the application of the modified Geomechanics Classification to underground coal mine design.

  12. Classification of octet AB-type binary compounds using dynamical charges: A materials informatics perspective

    SciTech Connect (OSTI)

    Pilania, G.; Gubernatis, J. E.; Lookman, T.

    2015-12-03

    The role of dynamical (or Born effective) charges in classification of octet AB-type binary compounds between four-fold (zincblende/wurtzite crystal structures) and six-fold (rocksalt crystal structure) coordinated systems is discussed. We show that the difference in the dynamical charges of the fourfold and sixfold coordinated structures, in combination with Harrison’s polarity, serves as an excellent feature to classify the coordination of 82 sp–bonded binary octet compounds. We use a support vector machine classifier to estimate the average classification accuracy and the associated variance in our model where a decision boundary is learned in a supervised manner. Lastly, we compare the out-of-sample classification accuracy achieved by our feature pair with those reported previously.

  13. Classification of octet AB-type binary compounds using dynamical charges: A materials informatics perspective

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Pilania, G.; Gubernatis, J. E.; Lookman, T.

    2015-12-03

    The role of dynamical (or Born effective) charges in classification of octet AB-type binary compounds between four-fold (zincblende/wurtzite crystal structures) and six-fold (rocksalt crystal structure) coordinated systems is discussed. We show that the difference in the dynamical charges of the fourfold and sixfold coordinated structures, in combination with Harrison’s polarity, serves as an excellent feature to classify the coordination of 82 sp–bonded binary octet compounds. We use a support vector machine classifier to estimate the average classification accuracy and the associated variance in our model where a decision boundary is learned in a supervised manner. Lastly, we compare the out-of-samplemore » classification accuracy achieved by our feature pair with those reported previously.« less

  14. Multi-contingency preprocessing for security assessment using physical concepts and CQR with classifications

    SciTech Connect (OSTI)

    Chen, R.H.; Malik, O.P.; Hope, G.S. ); Jingde Gao; Shiying Wang; Niande Xiang )

    1993-08-01

    A new method for preprocessing the outage lists for an Expert System for Security Assessment of power systems is presented in this paper. This method uses disturbing capability, structure and location classifications and CQR with Classifications (CQRC). Because this method avoids the traditional enumerative methods such as Automatic Contingency Selection, the number of contingencies can be reduced very sharply with heuristic common sense and rules of CQRC before numerical computing. So the double contingency problem or extremely heavy cost of computing can be tackled successfully. The proposed method along with an Automatic Contingency Analysis and Classification technique can assess the classified contingencies with basic physical concepts and without network simplification, minimize the number of missing harmful contingencies efficiently and give a clear accurate output.

  15. AFREET: HUMAN-INSPIRED SPATIO-SPECTRAL FEATURE CONSTRUCTION FOR IMAGE CLASSIFICATION WITH SUPPORT VECTOR MACHINES

    SciTech Connect (OSTI)

    S. PERKINS; N. HARVEY

    2001-02-01

    The authors examine the task of pixel-by-pixel classification of the multispectral and grayscale images typically found in remote-sensing and medical applications. Simple machine learning techniques have long been applied to remote-sensed image classification, but almost always using purely spectral information about each pixel. Humans can often outperform these systems, and make extensive use of spatial context to make classification decisions. They present AFREET: an SVM-based learning system which attempts to automatically construct and refine spatio-spectral features in a somewhat human-inspired fashion. Comparisons with traditionally used machine learning techniques show that AFREET achieves significantly higher performance. The use of spatial context is particularly useful for medical imagery, where multispectral images are still rare.

  16. A minimum spanning forest based classification method for dedicated breast CT images

    SciTech Connect (OSTI)

    Pike, Robert; Sechopoulos, Ioannis; Fei, Baowei

    2015-11-15

    Purpose: To develop and test an automated algorithm to classify different types of tissue in dedicated breast CT images. Methods: Images of a single breast of five different patients were acquired with a dedicated breast CT clinical prototype. The breast CT images were processed by a multiscale bilateral filter to reduce noise while keeping edge information and were corrected to overcome cupping artifacts. As skin and glandular tissue have similar CT values on breast CT images, morphologic processing is used to identify the skin based on its position information. A support vector machine (SVM) is trained and the resulting model used to create a pixelwise classification map of fat and glandular tissue. By combining the results of the skin mask with the SVM results, the breast tissue is classified as skin, fat, and glandular tissue. This map is then used to identify markers for a minimum spanning forest that is grown to segment the image using spatial and intensity information. To evaluate the authors’ classification method, they use DICE overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on five patient images. Results: Comparison between the automatic and the manual segmentation shows that the minimum spanning forest based classification method was able to successfully classify dedicated breast CT image with average DICE ratios of 96.9%, 89.8%, and 89.5% for fat, glandular, and skin tissue, respectively. Conclusions: A 2D minimum spanning forest based classification method was proposed and evaluated for classifying the fat, skin, and glandular tissue in dedicated breast CT images. The classification method can be used for dense breast tissue quantification, radiation dose assessment, and other applications in breast imaging.

  17. Real-time detection and classification of anomalous events in streaming data

    DOE Patents [OSTI]

    Ferragut, Erik M.; Goodall, John R.; Iannacone, Michael D.; Laska, Jason A.; Harrison, Lane T.

    2016-04-19

    A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The events can be displayed to a user in user-defined groupings in an animated fashion. The system can include a plurality of anomaly detectors that together implement an algorithm to identify low probability events and detect atypical traffic patterns. The atypical traffic patterns can then be classified as being of interest or not. In one particular example, in a network environment, the classification can be whether the network traffic is malicious or not.

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

    SciTech Connect (OSTI)

    Pete Jordan

    2010-09-01

    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.

  19. NEW - DOE O 325.2 Chg 1 (Admin Chg), Position Management and Classification

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    The order establishes departmental requirements and responsibilities for classifying positions using the general schedule (GS) and federal wage system (FWS) standards and to develop and administer a sound position management and classification program. Cancels DOE O 325.2, dated 4-1-15.

  20. The Council of Industrial Boiler Owners special project on non-utility fossil fuel ash classification

    SciTech Connect (OSTI)

    Svendsen, R.L.

    1996-12-31

    Information is outlined on the Council of Industrial Boiler Owners (CIBO) special project on non-utility fossil fuel ash classification. Data are presented on; current (1996) regulatory status of fossil-fuel combustion wastes; FBC technology identified for further study; CIBO special project methods; Bevill amendment study factors; data collection; and CIBO special project status.

  1. A Hybrid Semi-supervised Classification Scheme for Mining Multisource Geospatial Data

    SciTech Connect (OSTI)

    Vatsavai, Raju; Bhaduri, Budhendra L

    2011-01-01

    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 (class conditional probability densities) are often overlapping. The spectral response distributions of thematic classes are dependent on many factors including elevation, soil types, and ecological zones. A second problem with statistical classifiers is the requirement of large number of accurate training samples (10 to 30 |dimensions|), which are often costly and time consuming to acquire over large geographic regions. With the increasing availability of geospatial databases, it is possible to exploit the knowledge derived from these ancillary datasets to improve classification accuracies even when the class distributions are highly overlapping. Likewise newer semi-supervised techniques can be adopted to improve the parameter estimates of statistical model by utilizing a large number of easily available unlabeled training samples. Unfortunately there is no convenient multivariate statistical model that can be employed for mulitsource geospatial databases. In this paper we present a hybrid semi-supervised learning algorithm that effectively exploits freely available unlabeled training samples from multispectral remote sensing images and also incorporates ancillary geospatial databases. We have conducted several experiments on real datasets, and our new hybrid approach shows over 25 to 35% improvement in overall classification accuracy over conventional classification schemes.

  2. Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; Altmann, Garrett L.

    2014-12-09

    We present results from an ongoing effort to extend neuromimetic machine vision algorithms to multispectral data using adaptive signal processing combined with compressive sensing and machine learning techniques. Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and topographic/geomorphic characteristics. We use a Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labelsmore » are automatically generated using unsupervised clustering of sparse approximations (CoSA). We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska. We explore learning from both raw multispectral imagery and normalized band difference indices. We explore a quantitative metric to evaluate the spectral properties of the clusters in order to potentially aid in assigning land cover categories to the cluster labels. In this study, our results suggest CoSA is a promising approach to unsupervised land cover classification in high-resolution satellite imagery.« less

  3. Using Process Knowledge to Manage Disposal Classification of Ion-Exchange Resin - 13566

    SciTech Connect (OSTI)

    Bohnsack, Jonathan N.; James, David W.

    2013-07-01

    It has been previously shown by EPRI [1] that Class B and C resins represent a small portion by volume of the overall generation of radioactively contaminated resins. In fact, if all of the resins were taken together the overall classification would meet Class A disposal requirements. Lowering the classification of the ion exchange resins as they are presented for disposal provides a path for minimizing the amount of waste stored. Currently there are commercial options for blending wastes from various generators for Class A disposal in development. The NRC may have by this time introduced changes and clarifications to the Branch Technical Position (BTP) on Concentration Averaging and Encapsulation [2] that may ultimately add more flexibility to what can be done at the plant level. The BTP has always maintained that mixtures of resins that are combined for ALARA purposes or operational efficiency can be classified on the basis of the mixture. This is a point often misinterpreted and misapplied. This paper will address options that can be exercised by the generator that can limit B and C waste generation by more rigorous tracking of generation and taking advantage of the normal mix of wastes. This can be achieved through the monitoring of reactor coolant chemistry data and coupled with our knowledge of radionuclide production mechanisms. This knowledge can be used to determine the overall accumulation of activity in ion-exchange resins and provides a 'real-time' waste classification determination of the resin and thereby provide a mechanism to reduce the production of waste that exceeds class A limits. It should be noted that this alternative approach, although rarely used in a nuclear power plant setting, is acknowledged in the original BTP on classification [3] as a viable option for determining radionuclide inventories for classification of waste. Also included is a discussion of an examination performed at the Byron plant to estimate radionuclide content in the

  4. Classification of heart valve single leg separations from acoustic clinical measurements

    SciTech Connect (OSTI)

    Clark, G.A.; Bowman, B.C.; Boruta, N.; Thomas, G.H.; Jones, H.E.; Buhl, M.R.

    1994-05-01

    Our system classifies the condition (intact or single leg separated) of in vivo Bjork-Shiley Convexo-Concave (BSCC) heart valves by processing acoustic measurements of clinical heart valve opening sounds. We use spectral features as inputs to a two-stage classifier, which first classifies individual heart beats, then classifies valves. Performance is measured by probability of detection and probability of false alarm, and by confidence intervals on the probability of correct classification. The novelty of the work lies in the application of advanced techniques to real heart valve data, and extensions of published algorithms that enhance their applicability. We show that even when given a very small number of training samples, the classifier can achieve a probability of correct classification of 100%.

  5. A probablistic neural network classification system for signal and image processing

    SciTech Connect (OSTI)

    Bowman, B.

    1994-11-15

    The Acoustical Heart Valve Analysis Package is a system for signal and image processing and classification. It is being developed in both Matlab and C, to provide an interactive, interpreted environment, and has been optimized for large scale matrix operations. It has been used successfully to classify acoustic signals from implanted prosthetic heart valves in human patients, and will be integrated into a commercial Heart Valve Screening Center. The system uses several standard signal processing algorithms, as well as supervised learning techniques using the probabilistic neural network (PNN). Although currently used for the acoustic heart valve application, the algorithms and modular design allow it to be used for other applications, as well. We will describe the signal classification system, and show results from a set of test valves.

  6. Communications and control for electric power systems: Power flow classification for static security assessment

    SciTech Connect (OSTI)

    Niebur, D.; Germond, A.

    1993-02-01

    This report investigates the classification of power system states using an artificial neural network model, Kohonen's self-organizing feature map. The ultimate goal of this classification is to assess power system static security in real-time. Kohonen's self-organizing feature map is an unsupervised neural network which maps N-dimensional input vectors to an array of M neurons. After learning, the synaptic weight vectors exhibit a topological organization which represents the relationship between the vectors of the training set. This learning is unsupervised, which means that the number and size of the classes are not specified beforehand. In the application developed in the paper, the input vectors used as the training set are generated by off-line load-flow simulations. The learning algorithm and the results of the organization are discussed.

  7. Communications and control for electric power systems: Power flow classification for static security assessment

    SciTech Connect (OSTI)

    Niebur, D.; Germond, A.

    1993-02-01

    This report investigates the classification of power system states using an artificial neural network model, Kohonen`s self-organizing feature map. The ultimate goal of this classification is to assess power system static security in real-time. Kohonen`s self-organizing feature map is an unsupervised neural network which maps N-dimensional input vectors to an array of M neurons. After learning, the synaptic weight vectors exhibit a topological organization which represents the relationship between the vectors of the training set. This learning is unsupervised, which means that the number and size of the classes are not specified beforehand. In the application developed in the paper, the input vectors used as the training set are generated by off-line load-flow simulations. The learning algorithm and the results of the organization are discussed.

  8. Momotombo Geothermal Area | Open Energy Information

    Open Energy Info (EERE)

    World Geothermal Power Generation 2001-2005. Proceedings of World Geothermal Congress; Turkey: World Geothermal Congress. Tom Harding-Newman, James Morrow, Subir Sanyal,...

  9. Vegetation classification in southern pine mixed hardwood forests using airborne scanning laser point data.

    SciTech Connect (OSTI)

    McGaughey, Robert J.; Reutebuch, Stephen E.

    2012-09-01

    Forests of the southeastern United States are dominated by a relatively small number of conifer species. However, many of these forests also have a hardwood component composed of a wide variety of species that are found in all canopy positions. The presence or absence of hardwood species and their position in the canopy often dictates management activities such as thinning or prescribed burning. In addition, the characteristics of the under- and mid-story layers, often dominated by hardwood species, are key factors when assessing suitable habitat for threatened and endangered species such as the Red Cockaded Woodpecker (Picoides borealis) (RCW), making information describing the hardwood component important to forest managers. General classification of cover types using LIDAR data has been reported (Song et al. 2002, Brennan and Webster 2006) but most efforts focusing on the identification of individual species or species groups rely on some type of imagery to provide more complete spectral information for the study area. Brandtberg (2007) found that use of intensity data significantly improved LIDAR detection and classification of three leaf-off deciduous eastern species: oaks (Quercus spp.), red maple (Acer rubrum L.), and yellow poplar (Liriodendron tulipifera L.). Our primary objective was to determine the proportion of hardwood species present in the canopy using only the LIDAR point data and derived products. However, the presence of several hardwood species that retain their foliage through the winter months complicated our analyses. We present two classification approaches. The first identifies areas containing hardwood and softwood (conifer) species (H/S) and the second identifies vegetation with foliage absent or present (FA/FP) at the time of the LIDAR data acquisition. The classification results were used to develop predictor variables for forest inventory models. The ability to incorporate the proportion of hardwood and softwood was important to the

  10. An Improved Cloud Classification Algorithm Based on the SGP CART Site Observations

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Improved Cloud Classification Algorithm Based on the SGP CART Site Observations Z. Wang Goddard Earth Sciences and Technology Center University of Maryland Greenbelt, Maryland K. Sassen University of Alaska Fairbanks, Alaska Introduction Different types of clouds are usually governed by different cloud dynamics processes and have different microphysical properties, which results in different cloud radiative forcings (Hartmann et al. 1992; Chen et al. 2000). Climate changes can result in changing

  11. On the construction of a new stellar classification template library for the LAMOST spectral analysis pipeline

    SciTech Connect (OSTI)

    Wei, Peng; Luo, Ali; Li, Yinbi; Tu, Liangping; Wang, Fengfei; Zhang, Jiannan; Chen, Xiaoyan; Hou, Wen; Kong, Xiao; Wu, Yue; Zuo, Fang; Yi, Zhenping; Zhao, Yongheng; Chen, Jianjun; Du, Bing; Guo, Yanxin; Ren, Juanjuan; Pan, Jingchang; Jiang, Bin; Liu, Jie E-mail: weipeng@nao.cas.cn; and others

    2014-05-01

    The LAMOST spectral analysis pipeline, called the 1D pipeline, aims to classify and measure the spectra observed in the LAMOST survey. Through this pipeline, the observed stellar spectra are classified into different subclasses by matching with template spectra. Consequently, the performance of the stellar classification greatly depends on the quality of the template spectra. In this paper, we construct a new LAMOST stellar spectral classification template library, which is supposed to improve the precision and credibility of the present LAMOST stellar classification. About one million spectra are selected from LAMOST Data Release One to construct the new stellar templates, and they are gathered in 233 groups by two criteria: (1) pseudo g r colors obtained by convolving the LAMOST spectra with the Sloan Digital Sky Survey ugriz filter response curve, and (2) the stellar subclass given by the LAMOST pipeline. In each group, the template spectra are constructed using three steps. (1) Outliers are excluded using the Local Outlier Probabilities algorithm, and then the principal component analysis method is applied to the remaining spectra of each group. About 5% of the one million spectra are ruled out as outliers. (2) All remaining spectra are reconstructed using the first principal components of each group. (3) The weighted average spectrum is used as the template spectrum in each group. Using the previous 3 steps, we initially obtain 216 stellar template spectra. We visually inspect all template spectra, and 29 spectra are abandoned due to low spectral quality. Furthermore, the MK classification for the remaining 187 template spectra is manually determined by comparing with 3 template libraries. Meanwhile, 10 template spectra whose subclass is difficult to determine are abandoned. Finally, we obtain a new template library containing 183 LAMOST template spectra with 61 different MK classes by combining it with the current library.

  12. Groenewold-Moyal product, ?*-cohomology, and classification of translation-invariant non-commutative structures

    SciTech Connect (OSTI)

    Varshovi, Amir Abbass

    2013-07-15

    The theory of ?*-cohomology is studied thoroughly and it is shown that in each cohomology class there exists a unique 2-cocycle, the harmonic form, which generates a particular Groenewold-Moyal star product. This leads to an algebraic classification of translation-invariant non-commutative structures and shows that any general translation-invariant non-commutative quantum field theory is physically equivalent to a Groenewold-Moyal non-commutative quantum field theory.

  13. Classification of Distributed Data Using Topic Modeling and Maximum Variation Sampling

    SciTech Connect (OSTI)

    Patton, Robert M; Beaver, Justin M; Potok, Thomas E

    2011-01-01

    From a management perspective, understanding the information that exists on a network and how it is distributed provides a critical advantage. This work explores the use of topic modeling as an approach to automatically determine the classes of information that exist on an organization's network, and then use the resultant topics as centroid vectors for the classification of individual documents in order to understand the distribution of information topics across the enterprise network. The approach is tested using the 20 Newsgroups dataset.

  14. Performance analysis of distributed applications using automatic classification of communication inefficiencies

    DOE Patents [OSTI]

    Vetter, Jeffrey S.

    2005-02-01

    The method and system described herein presents a technique for performance analysis that helps users understand the communication behavior of their message passing applications. The method and system described herein may automatically classifies individual communication operations and reveal the cause of communication inefficiencies in the application. This classification allows the developer to quickly focus on the culprits of truly inefficient behavior, rather than manually foraging through massive amounts of performance data. Specifically, the method and system described herein trace the message operations of Message Passing Interface (MPI) applications and then classify each individual communication event using a supervised learning technique: decision tree classification. The decision tree may be trained using microbenchmarks that demonstrate both efficient and inefficient communication. Since the method and system described herein adapt to the target system's configuration through these microbenchmarks, they simultaneously automate the performance analysis process and improve classification accuracy. The method and system described herein may improve the accuracy of performance analysis and dramatically reduce the amount of data that users must encounter.

  15. YOUNG PLANETARY NEBULAE: HUBBLE SPACE TELESCOPE IMAGING AND A NEW MORPHOLOGICAL CLASSIFICATION SYSTEM

    SciTech Connect (OSTI)

    Sahai, Raghvendra; Villar, Gregory G.; Morris, Mark R.

    2011-04-15

    Using Hubble Space Telescope images of 119 young planetary nebulae (PNs), most of which have not previously been published, we have devised a comprehensive morphological classification system for these objects. This system generalizes a recently devised system for pre-planetary nebulae, which are the immediate progenitors of PNs. Unlike previous classification studies, we have focused primarily on young PNs rather than all PNs, because the former best show the influences or symmetries imposed on them by the dominant physical processes operating at the first and primary stage of the shaping process. Older PNs develop instabilities, interact with the ambient interstellar medium, and are subject to the passage of photoionization fronts, all of which obscure the underlying symmetries and geometries imposed early on. Our classification system is designed to suffer minimal prejudice regarding the underlying physical causes of the different shapes and structures seen in our PN sample, however, in many cases, physical causes are readily suggested by the geometry, along with the kinematics that have been measured in some systems. Secondary characteristics in our system, such as ansae, indicate the impact of a jet upon a slower-moving, prior wind; a waist is the signature of a strong equatorial concentration of matter, whether it be outflowing or in a bound Keplerian disk, and point symmetry indicates a secular trend, presumably precession, in the orientation of the central driver of a rapid, collimated outflow.

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

    SciTech Connect (OSTI)

    Matijevic, Gal; Prsa, Andrej; Orosz, Jerome A.; Welsh, William F.; Bloemen, Steven; Barclay, Thomas E-mail: andrej.prsa@villanova.edu

    2012-05-15

    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.

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

    SciTech Connect (OSTI)

    Nomura, Motoo; Department of Clinical Oncology, Aichi Cancer Center Hospital, Nagoya; Department of Radiation Oncology, Aichi Cancer Center Hospital, Nagoya ; Shitara, Kohei; Kodaira, Takeshi; Kondoh, Chihiro; Takahari, Daisuke; Ura, Takashi; Kojima, Hiroyuki; Kamata, Minoru; Muro, Kei; Sawada, Satoshi

    2012-11-01

    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.

  18. Resolving Radiological Classification and Release Issues for Many DOE Solid Wastes and Salvageable Materials

    SciTech Connect (OSTI)

    Hochel, R.C.

    1999-06-14

    The cost effective radiological classification and disposal of solid materials with potential volume contamination, in accordance with applicable U.S. Department of Energy (DOE) Orders, suffers from an inability to unambiguously distinguish among transuranic waste, low-level waste, and unconditional-release materials. Depending on the classification, disposal costs can vary by a hundred-fold. But in many cases, the issues can be easily resolved by a combination of process information, some simple measurements, and calculational predictions from a computer model for radiation shielding.The proper classification and disposal of many solid wastes requires a measurement regime that is able to show compliance with a variety of institutional and regulatory contamination limits. Although this is not possible for all solid wastes, there are many that do lend themselves to such measures. Several examples are discussed which demonstrate the possibilities, including one which was successfully applied to bulk contamination.The only barriers to such broader uses are the slow-to-change institutional perceptions and procedures. For many issues and materials, the measurement tools are available; they need only be applied.

  19. Context-based automated defect classification system using multiple morphological masks

    DOE Patents [OSTI]

    Gleason, Shaun S.; Hunt, Martin A.; Sari-Sarraf, Hamed

    2002-01-01

    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.

  20. DOE Publishes Petition of CSA Group for Classification as a Nationally Recognized Certification Program for Small Electric Motors

    Broader source: Energy.gov [DOE]

    The Department of Energy has published a Federal Register notice of petition and request for public comments regarding CSA Group for classification as a nationally recognized certification program for small electric motors.

  1. Object Classification

    Office of Scientific and Technical Information (OSTI)

    ... For this analysis we used a soft- boundary SVM method called C-SVM, which handles noisy ... provide as much sig- nalbackground separation power as the decision tree based methods. ...

  2. Understanding Classification

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    U U 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

  3. Classification of heart valve sounds from experiments in an anechoic water tank

    SciTech Connect (OSTI)

    Axelrod, M C; Clark, G A; Scott, D

    1999-06-01

    In vivo studies in both sheep and humans were plagued by a number of problems including movement artifacts, biological noise, low signal-to-noise ratio (SNR), chest-wall reverberation, and limited bandwidth recordings as discussed by [1]. To overcome these problems it was decided to record heart valve sounds under controlled conditions deep in an anechoic water tank, free from reverberation noise, including surface reflections. Experiments were conducted in a deep water tank at the Transdec facility in San Diego, which satisfies these requirements. The Transdec measurements are free of reverberations, but not totally free of acoustic and electrical noise. We used a high quality hydrophone together with a wide-band data acquisition system [2]. We recorded sounds from 100 repetitions of the opening-closing cycles on each of 50 different heart valves, including 21 SLS valves and 29 intact valves. The power spectrum of the opening and closing phases of each cycle were calculated and outlier spectra removed as described by Candy [2]. In this report, we discuss the results of our classification of the heart valve sound measurements. The goal of this classification task was to apply the fundamental classification algorithms developed for the clinical data in 1994 and 1996 to the measurements from the anechoic water tank. From the beginning of this project, LLNL's responsibility has been to process and classify the heart valve opening sounds. For this experiment, however, we processed both the opening sounds and closing sounds for comparison purposes. The results of this experiment show that the classifier did not perform well. We believe this is because of low signal-to-noise ratio and excessive variability in signal power from beat-to-beat for a given valve.

  4. Classification of heart valve sounds from experiments in an anechoic water tank

    SciTech Connect (OSTI)

    Axelrod, M C; Clark, G A; Scott, D

    1999-06-01

    In vivo studies in both sheep and humans were plagued by a number of problems including movement artifacts, biological noise, low signal-to-noise ratio (SNR), chest-wall reverberation, and limited bandwidth recordings as discussed by [1]. To overcome these problems it was decided to record heart valve sounds under controlled conditions deep in an anechoic water tank, free from reverberation noise. The main goal of this experiment was to obtain measurements of ''pure'' heart valve sounds free of the scattering effects of the body. Experiments were conducted at the Transdec facility in San Diego [2]. We used a high quality hydrophone together with a wide-band data acquisition system [2]. We recorded sounds from 100 repetitions of the opening-closing cycles on each of 50 different heart valves, including 21 SLS valves and 29 intact valves. The power spectrum of the opening and closing phases of each cycle were calculated and outlier spectra removed as described by Candy [2]. In this report, we discuss the results of our classification of the heart valve sound measurements. The goal of this classification task was to apply the fundamental classification algorithms developed for the clinical data in 1994 and 1996 to the measurements from the anechoic water tank. From the beginning of this project, LLNL's responsibility has been to process and classify the heart valve sounds. For this experiment, however, we processed both the opening sounds and closing sounds for comparison purposes. The results of this experiment show that the classifier did not perform well because of low signal-to-noise ratio and excessive variability in signal power from beat-to-beat for a given valve.

  5. Removal of introduced inorganic content from chipped forest residues via air classification

    SciTech Connect (OSTI)

    Lacey, Jeffrey A.; Aston, John E.; Westover, Tyler L.; Cherry, Robert S.; Thompson, David N.

    2015-08-04

    Inorganic content in biomass decreases the efficiency of conversion processes, especially thermochemical conversions. The combined concentrations of specific ash forming elements are the primary attributes that cause pine residues to be considered a degraded energy conversion feedstock, as compared to clean pine. Air classification is a potentially effective and economical tool to isolate high inorganic content biomass fractions away from primary feedstock sources to reduce their ash content. In this work, loblolly pine forest residues were air classified into 10 fractions whose ash content and composition were measured. Ash concentrations were highest in the lightest fractions (5.8–8.5 wt%), and in a heavy fraction of the fines (8.9–15.1 wt%). The removal of fractions with high inorganic content resulted in a substantial reduction in the ash content of the remaining biomass in forest thinnings (1.69–1.07 wt%) and logging residues (1.09–0.68 wt%). These high inorganic content fractions from both forest residue types represented less than 7.0 wt% of the total biomass, yet they contained greater than 40% of the ash content by mass. Elemental analysis of the air classified fractions revealed the lightest fractions were comprised of high concentrations of soil elements (silicon, aluminum, iron, sodium, and titanium). However, the elements of biological origin including calcium, potassium, magnesium, sulfur, manganese, and phosphorous were evenly distributed throughout all air classified fractions, making them more difficult to isolate into fractions with high mineral concentrations. Under the conditions reported in this study, an economic analysis revealed air classification could be used for ash removal for as little as $2.23 per ton of product biomass. As a result, this study suggests air classification is a potentially attractive technology for the removal of introduced soil minerals from pine forest residues.

  6. Application of air classification and formulation to manage feedstock cost, quality and availability for bioenergy

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Thompson, Vicki S.; Lacey, Jeffrey A.; Hartley, Damon; Jindra, Michael A.; Aston, John E.; Thompson, David N.

    2016-04-22

    Biomass such as agricultural residues, energy crops and yard waste has significant potential to be used as renewable feedstocks for production of fuels, chemicals and energy. However, in a given location, biomass availability, cost and quality can vary markedly. Strategies to manage these traits must be identified and implemented so that consistent low-cost and high-quality feedstocks can be delivered to biorefineries year round. In this study, we examine air classification as a method to mitigate high ash concentrations in corn stover, switchgrass, and grass clippings. Formulation techniques were then used to produce blends that met ash quality and biomass quantitymore » specifications at the lowest possible cost for biopower and biochemical conversion applications. It was found that air classification can separate the biomass into light fractions which contain concentrated amounts of elemental ash components introduced through soil contamination such as sodium, alumina, silica, iron and titania; and heavy fractions that are depleted in these components and have relatively lower total ash content. Light fractions of corn stover and grass clippings were found to be suitable for combustion applications since they had less propensity to slag than the whole biomass material. The remaining heavy fractions of corn stover or grass clippings could then be blended with switchgrass to produce blends that met the 5% total ash specifications suggested for biochemical conversions. However, ternary blends of the three feedstocks were not possible due to the high ash content of grass clippings. Lastly, it was determined that air classification by itself was not suitable to prepare these feedstocks for pyrolysis due to high ash content.« less

  7. Gradient Analysis and Classification of Carolina Bay Vegetation: A Framework for Bay Wetlands Conservation and Restoration

    SciTech Connect (OSTI)

    Diane De Steven,Ph.D.; Maureen Tone,PhD.

    1997-10-01

    This report address four project objectives: (1) Gradient model of Carolina bay vegetation on the SRS--The authors use ordination analyses to identify environmental and landscape factors that are correlated with vegetation composition. Significant factors can provide a framework for site-based conservation of existing diversity, and they may also be useful site predictors for potential vegetation in bay restorations. (2) Regional analysis of Carolina bay vegetation diversity--They expand the ordination analyses to assess the degree to which SRS bays encompass the range of vegetation diversity found in the regional landscape of South Carolina's western Upper Coastal Plain. Such comparisons can indicate floristic status relative to regional potentials and identify missing species or community elements that might be re-introduced or restored. (3) Classification of vegetation communities in Upper Coastal Plain bays--They use cluster analysis to identify plant community-types at the regional scale, and explore how this classification may be functional with respect to significant environmental and landscape factors. An environmentally-based classification at the whole-bay level can provide a system of templates for managing bays as individual units and for restoring bays to desired plant communities. (4) Qualitative model for bay vegetation dynamics--They analyze present-day vegetation in relation to historic land uses and disturbances. The distinctive history of SRS bays provides the possibility of assessing pathways of post-disturbance succession. They attempt to develop a coarse-scale model of vegetation shifts in response to changing site factors; such qualitative models can provide a basis for suggesting management interventions that may be needed to maintain desired vegetation in protected or restored bays.

  8. Removal of introduced inorganic content from chipped forest residues via air classification

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Lacey, Jeffrey A.; Aston, John E.; Westover, Tyler L.; Cherry, Robert S.; Thompson, David N.

    2015-08-04

    Inorganic content in biomass decreases the efficiency of conversion processes, especially thermochemical conversions. The combined concentrations of specific ash forming elements are the primary attributes that cause pine residues to be considered a degraded energy conversion feedstock, as compared to clean pine. Air classification is a potentially effective and economical tool to isolate high inorganic content biomass fractions away from primary feedstock sources to reduce their ash content. In this work, loblolly pine forest residues were air classified into 10 fractions whose ash content and composition were measured. Ash concentrations were highest in the lightest fractions (5.8–8.5 wt%), and inmore » a heavy fraction of the fines (8.9–15.1 wt%). The removal of fractions with high inorganic content resulted in a substantial reduction in the ash content of the remaining biomass in forest thinnings (1.69–1.07 wt%) and logging residues (1.09–0.68 wt%). These high inorganic content fractions from both forest residue types represented less than 7.0 wt% of the total biomass, yet they contained greater than 40% of the ash content by mass. Elemental analysis of the air classified fractions revealed the lightest fractions were comprised of high concentrations of soil elements (silicon, aluminum, iron, sodium, and titanium). However, the elements of biological origin including calcium, potassium, magnesium, sulfur, manganese, and phosphorous were evenly distributed throughout all air classified fractions, making them more difficult to isolate into fractions with high mineral concentrations. Under the conditions reported in this study, an economic analysis revealed air classification could be used for ash removal for as little as $2.23 per ton of product biomass. As a result, this study suggests air classification is a potentially attractive technology for the removal of introduced soil minerals from pine forest residues.« less

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

    SciTech Connect (OSTI)

    Lamata, L.; Leon, J.; Salgado, D.; Solano, E.

    2007-02-15

    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.

  10. Department of energy defense programs perspectives on safeguards, security, and classification

    SciTech Connect (OSTI)

    Eyck, E.Q.T. )

    1989-07-01

    This paper discusses why national and international safeguards and the protection of sensitive information are important to the United States and to other nations. It demonstrates that while the opposite consequence appears logical these functions will probably become even more important if the major powers agree on further arms reductions. Some of the steps taken by the U.S. Department of Energy to improve the effectiveness of its safeguards, security, and classification programs are reviewed. The valuable contributions in these areas since 1968 and 1976, respectively by the Technical Support Organization and the International Safeguards Project Offoce at Brookhaven are noted.

  11. OPTICAL CLASSIFICATION OF GAMMA-RAY BURSTS IN THE SWIFT ERA

    SciTech Connect (OSTI)

    Van der Horst, A. J.; Kouveliotou, C.; Gehrels, N.; Cannizzo, J. K.; Rol, E.; Wijers, R. A. M. J.; Racusin, J.; Burrows, D. N.

    2009-07-10

    We propose a new method for the classification of optically dark gamma-ray bursts (GRBs), based on the X-ray and optical-to-X-ray spectral indices of GRB afterglows, and utilizing the spectral capabilities of Swift. This method depends less on model assumptions than previous methods, and can be used as a quick diagnostic tool to identify optically sub-luminous bursts. With this method we can also find GRBs that are extremely bright at optical wavelengths. We show that the previously suggested correlation between the optical darkness and the X-ray/gamma-ray brightness is merely an observational selection effect.

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

    SciTech Connect (OSTI)

    Pless, S.; Torcellini, P.

    2010-06-01

    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.

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

    SciTech Connect (OSTI)

    Boyd D. Christensen

    2012-05-01

    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.

  14. Adaptive Classification of Landscape Process and Function: An Integration of Geoinformatics and Self-Organizing Maps

    SciTech Connect (OSTI)

    Coleman, Andre M.

    2009-07-17

    The advanced geospatial information extraction and analysis capabilities of a Geographic Information System (GISs) and Artificial Neural Networks (ANNs), particularly Self-Organizing Maps (SOMs), provide a topology-preserving means for reducing and understanding complex data relationships in the landscape. The Adaptive Landscape Classification Procedure (ALCP) is presented as an adaptive and evolutionary capability where varying types of data can be assimilated to address different management needs such as hydrologic response, erosion potential, habitat structure, instrumentation placement, and various forecast or what-if scenarios. This paper defines how the 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. Establishing relationships among high-dimensional datasets through neurocomputing based pattern recognition methods can help 1) resolve large volumes of data into a structured and meaningful form; 2) provide an approach for inferring landscape processes in areas that have limited data available but exhibit similar landscape characteristics; and 3) discover the value of individual variables or groups of variables that contribute to specific processes in the landscape. Classification of hydrologic patterns in the landscape is demonstrated.

  15. The Constitution, waste facility performance standards, and radioactive waste classification: Is equal protection possible?

    SciTech Connect (OSTI)

    Eye, R.V.

    1993-03-01

    The process for disposal of so-called low-level radioactive waste is deadlocked at present. Supporters of the proposed near-surface facilities assert that their designs will meet minimum legal and regulatory standards currently in effect. Among opponents there is an overarching concern that the proposed waste management facilities will not isolate radiation from the biosphere for an adequate length of time. This clash between legal acceptability and a perceived need to protect the environment and public health by requiring more than the law demand sis one of the underlying reasons why the process is deadlocked. Perhaps the most exhaustive public hearing yet conducted on low-level radioactive waste management has recently concluded in Illinois. The Illinois Low-Level Radioactive Waste Disposal Facility Sitting Commission conducted 71 days of fact-finding hearings on the safety and suitability of a site near Martinsville, Illinois, to serve as a location for disposition of low-level radioactive waste. Ultimately, the siting commission rejected the proposed facility site for several reasons. However, almost all the reasons were related, to the prospect that, as currently conceived, the concrete barrier/shallow-land burial method will not isolate radioactive waste from the biosphere. This paper reviews the relevant legal framework of the radioactive waste classification system and will argue that it is inadequate for long-lived radionuclides. Next, the paper will present a case for altering the classification system based on high-level waste regulatory considerations.

  16. An expert computer program for classifying stars on the MK spectral classification system

    SciTech Connect (OSTI)

    Gray, R. O.; Corbally, C. J.

    2014-04-01

    This paper describes an expert computer program (MKCLASS) designed to classify stellar spectra on the MK Spectral Classification system in a way similar to humans—by direct comparison with the MK classification standards. Like an expert human classifier, the program first comes up with a rough spectral type, and then refines that spectral type by direct comparison with MK standards drawn from a standards library. A number of spectral peculiarities, including barium stars, Ap and Am stars, λ Bootis stars, carbon-rich giants, etc., can be detected and classified by the program. The program also evaluates the quality of the delivered spectral type. The program currently is capable of classifying spectra in the violet-green region in either the rectified or flux-calibrated format, although the accuracy of the flux calibration is not important. We report on tests of MKCLASS on spectra classified by human classifiers; those tests suggest that over the entire HR diagram, MKCLASS will classify in the temperature dimension with a precision of 0.6 spectral subclass, and in the luminosity dimension with a precision of about one half of a luminosity class. These results compare well with human classifiers.

  17. High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Musah, Rabi A.; Espinoza, Edgard O.; Cody, Robert B.; Lesiak, Ashton D.; Christensen, Earl D.; Moore, Hannah E.; Maleknia, Simin; Drijhout, Falko P.

    2015-07-09

    A high throughput method for species identification and classification through chemometric processing of direct analysis in real time (DART) mass spectrometry-derived fingerprint signatures has been developed. The method entails introduction of samples to the open air space between the DART ion source and the mass spectrometer inlet, with the entire observed mass spectral fingerprint subjected to unsupervised hierarchical clustering processing. Moreover, a range of both polar and non-polar chemotypes are instantaneously detected. The result is identification and species level classification based on the entire DART-MS spectrum. In this paper, we illustrate how the method can be used to: (1) distinguishmore » between endangered woods regulated by the Convention for the International Trade of Endangered Flora and Fauna (CITES) treaty; (2) assess the origin and by extension the properties of biodiesel feedstocks; (3) determine insect species from analysis of puparial casings; (4) distinguish between psychoactive plants products; and (5) differentiate between Eucalyptus species. An advantage of the hierarchical clustering approach to processing of the DART-MS derived fingerprint is that it shows both similarities and differences between species based on their chemotypes. Furthermore, full knowledge of the identities of the constituents contained within the small molecule profile of analyzed samples is not required.« less

  18. High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures

    SciTech Connect (OSTI)

    Musah, Rabi A.; Espinoza, Edgard O.; Cody, Robert B.; Lesiak, Ashton D.; Christensen, Earl D.; Moore, Hannah E.; Maleknia, Simin; Drijhout, Falko P.

    2015-07-09

    A high throughput method for species identification and classification through chemometric processing of direct analysis in real time (DART) mass spectrometry-derived fingerprint signatures has been developed. The method entails introduction of samples to the open air space between the DART ion source and the mass spectrometer inlet, with the entire observed mass spectral fingerprint subjected to unsupervised hierarchical clustering processing. Moreover, a range of both polar and non-polar chemotypes are instantaneously detected. The result is identification and species level classification based on the entire DART-MS spectrum. In this paper, we illustrate how the method can be used to: (1) distinguish between endangered woods regulated by the Convention for the International Trade of Endangered Flora and Fauna (CITES) treaty; (2) assess the origin and by extension the properties of biodiesel feedstocks; (3) determine insect species from analysis of puparial casings; (4) distinguish between psychoactive plants products; and (5) differentiate between Eucalyptus species. An advantage of the hierarchical clustering approach to processing of the DART-MS derived fingerprint is that it shows both similarities and differences between species based on their chemotypes. Furthermore, full knowledge of the identities of the constituents contained within the small molecule profile of analyzed samples is not required.

  19. Threshold selection for classification of MR brain images by clustering method

    SciTech Connect (OSTI)

    Moldovanu, Simona; Obreja, Cristian; Moraru, Luminita

    2015-12-07

    Given a grey-intensity image, our method detects the optimal threshold for a suitable binarization of MR brain images. In MR brain image processing, the grey levels of pixels belonging to the object are not substantially different from the grey levels belonging to the background. Threshold optimization is an effective tool to separate objects from the background and further, in classification applications. This paper gives a detailed investigation on the selection of thresholds. Our method does not use the well-known method for binarization. Instead, we perform a simple threshold optimization which, in turn, will allow the best classification of the analyzed images into healthy and multiple sclerosis disease. The dissimilarity (or the distance between classes) has been established using the clustering method based on dendrograms. We tested our method using two classes of images: the first consists of 20 T2-weighted and 20 proton density PD-weighted scans from two healthy subjects and from two patients with multiple sclerosis. For each image and for each threshold, the number of the white pixels (or the area of white objects in binary image) has been determined. These pixel numbers represent the objects in clustering operation. The following optimum threshold values are obtained, T = 80 for PD images and T = 30 for T2w images. Each mentioned threshold separate clearly the clusters that belonging of the studied groups, healthy patient and multiple sclerosis disease.

  20. GIS Framework for Large River Geomorphic Classification to Aid in the Evaluation of Flow-Ecology Relationships

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    2296 Prepared for the U.S. Department of Energy under Contract DE-AC05-76RL01830 GIS Framework for Large River Geomorphic Classification to Aid in the Evaluation of Flow-Ecology Relationships CR Vernon EV Arntzen MC Richmond RA McManamay 1 TP Hanrahan CL Rakowski February 2013 PNNL-22296 GIS Framework for Large River Geomorphic Classification to Aid in the Evaluation of Flow-Ecology Relationships CR Vernon EV Arntzen MC Richmond RA McManamay 1 TP Hanrahan CL Rakwoski February 2013 Prepared for

  1. Inductive classification of multipartite entanglement under stochastic local operations and classical communication

    SciTech Connect (OSTI)

    Lamata, L.; Leon, J.; Solano, E.

    2006-11-15

    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.

  2. ISOLATING CONTENT AND METADATA FROM WEBLOGS USING CLASSIFICATION AND RULE-BASED APPROACHES

    SciTech Connect (OSTI)

    Marshall, Eric J.; Bell, Eric B.

    2011-09-04

    The emergence and increasing prevalence of social media, such as internet forums, weblogs (blogs), wikis, etc., has created a new opportunity to measure public opinion, attitude, and social structures. A major challenge in leveraging this information is isolating the content and metadata in weblogs, as there is no standard, universally supported, machine-readable format for presenting this information. We present two algorithms for isolating this information. The first uses web block classification, where each node in the Document Object Model (DOM) for a page is classified according to one of several pre-defined attributes from a common blog schema. The second uses a set of heuristics to select web blocks. These algorithms perform at a level suitable for initial use, validating this approach for isolating content and metadata from blogs. The resultant data serves as a starting point for analytical work on the content and substance of collections of weblog pages.

  3. Brownian motors in the low-energy approximation: Classification and properties

    SciTech Connect (OSTI)

    Rozenbaum, V. M.

    2010-04-15

    We classify Brownian motors based on the expansion of their velocity in terms of the reciprocal friction coefficient. The two main classes of motors (with dichotomic fluctuations in homogeneous force and periodic potential energy) are characterized by different analytical dependences of their mean velocity on the spatial and temporal asymmetry coefficients and by different adiabatic limits. The competition between the spatial and temporal asymmetries gives rise to stopping points. The transition through these points can be achieved by varying the asymmetry coefficients, temperature, and other motor parameters, which can be used, for example, for nanoparticle segregation. The proposed classification separates out a new type of motors based on synchronous fluctuations in symmetric potential and applied homogeneous force. As an example of this type of motors, we consider a near-surface motor whose two-dimensional motion (parallel and perpendicular to the substrate plane) results from fluctuations in external force inclined to the surface.

  4. Language Classification using N-grams Accelerated by FPGA-based Bloom Filters

    SciTech Connect (OSTI)

    Jacob, A; Gokhale, M

    2007-09-13

    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.

  5. Bayesian Models for Life Prediction and Fault-Mode Classification in Solid State Lamps

    SciTech Connect (OSTI)

    Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

    2015-04-19

    A new method has been developed for assessment of the onset of degradation in solid state luminaires to classifY failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identifY luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. It is expected that, the new test technique will allow the development of failure distributions without testing till L 70 life for the manifestation of failure.

  6. Video compression of coronary angiograms based on discrete wavelet transform with block classification

    SciTech Connect (OSTI)

    Ho, B.K.T.; Tsai, M.J.; Wei, J.; Ma, M.; Saipetch, P.

    1996-12-01

    A new method of video compression for angiographic images has been developed to achieve high compression ratio ({approximately}20:1) while eliminating block artifacts which leads to loss of diagnostic accuracy. This method adopts motion picture experts group`s (MPEG`s) motion compensated prediction to take advantage of frame to frame correlation. However, in contrast to MPEG, the error images arising from mismatches in the motion estimation are encoded by discrete wavelet transform (DWT) rather than block discrete cosine transform (DCT). Furthermore, the authors developed a classification scheme which label each block in an image as intra, error, or background type and encode it accordingly. This hybrid coding can significantly improve the compression efficiency in certain cases. This method can be generalized for any dynamic image sequences applications sensitive to block artifacts.

  7. Mechanism-based classification of PAH mixtures to predict carcinogenic potential

    SciTech Connect (OSTI)

    Tilton, Susan C.; Siddens, Lisbeth K.; Krueger, Sharon K.; Larkin, Andrew J.; Löhr, Christiane V.; Williams, David E.; Baird, William M.; Waters, Katrina M.

    2015-04-22

    We have previously shown that relative potency factors and DNA adduct measurements are inadequate for predicting carcinogenicity of certain polycyclic aromatic hydrocarbons (PAHs) and PAH mixtures, particularly those that function through alternate pathways or exhibit greater promotional activity compared to benzo[a]pyrene (BaP). Therefore, we developed a pathway based approach for classification of tumor outcome after dermal exposure to PAH/mixtures. FVB/N mice were exposed to dibenzo[def,p]chrysene (DBC), BaP or environmental PAH mixtures (Mix 1-3) following a two-stage initiation/promotion skin tumor protocol. Resulting tumor incidence could be categorized by carcinogenic potency as DBC>>BaP=Mix2=Mix3>Mix1=Control, based on statistical significance. Gene expression profiles measured in skin of mice collected 12 h post-initiation were compared to tumor outcome for identification of short-term bioactivity profiles. A Bayesian integration model was utilized to identify biological pathways predictive of PAH carcinogenic potential during initiation. Integration of probability matrices from four enriched pathways (p<0.05) for DNA damage, apoptosis, response to chemical stimulus and interferon gamma signaling resulted in the highest classification accuracy with leave-one-out cross validation. This pathway-driven approach was successfully utilized to distinguish early regulatory events during initiation prognostic for tumor outcome and provides proof-of-concept for using short-term initiation studies to classify carcinogenic potential of environmental PAH mixtures. As a result, these data further provide a ‘source-to outcome’ model that could be used to predict PAH interactions during tumorigenesis and provide an example of how mode-of-action based risk assessment could be employed for environmental PAH mixtures.

  8. Solid waste bin detection and classification using Dynamic Time Warping and MLP classifier

    SciTech Connect (OSTI)

    Islam, Md. Shafiqul; Hannan, M.A.; Basri, Hassan; Hussain, Aini; Arebey, Maher

    2014-02-15

    Highlights: • Solid waste bin level detection using Dynamic Time Warping (DTW). • Gabor wavelet filter is used to extract the solid waste image features. • Multi-Layer Perceptron classifier network is used for bin image classification. • The classification performance evaluated by ROC curve analysis. - Abstract: The increasing requirement for Solid Waste Management (SWM) has become a significant challenge for municipal authorities. A number of integrated systems and methods have introduced to overcome this challenge. Many researchers have aimed to develop an ideal SWM system, including approaches involving software-based routing, Geographic Information Systems (GIS), Radio-frequency Identification (RFID), or sensor intelligent bins. Image processing solutions for the Solid Waste (SW) collection have also been developed; however, during capturing the bin image, it is challenging to position the camera for getting a bin area centralized image. As yet, there is no ideal system which can correctly estimate the amount of SW. This paper briefly discusses an efficient image processing solution to overcome these problems. Dynamic Time Warping (DTW) was used for detecting and cropping the bin area and Gabor wavelet (GW) was introduced for feature extraction of the waste bin image. Image features were used to train the classifier. A Multi-Layer Perceptron (MLP) classifier was used to classify the waste bin level and estimate the amount of waste inside the bin. The area under the Receiver Operating Characteristic (ROC) curves was used to statistically evaluate classifier performance. The results of this developed system are comparable to previous image processing based system. The system demonstration using DTW with GW for feature extraction and an MLP classifier led to promising results with respect to the accuracy of waste level estimation (98.50%). The application can be used to optimize the routing of waste collection based on the estimated bin level.

  9. Validation and Simplification of the Radiation Therapy Oncology Group Recursive Partitioning Analysis Classification for Glioblastoma

    SciTech Connect (OSTI)

    Li Jing; Wang Meihua; Won, Minhee; Shaw, Edward G.; Coughlin, Christopher; Curran, Walter J.; Mehta, Minesh P.

    2011-11-01

    Purpose: Previous recursive partitioning analysis (RPA) of patients with malignant glioma (glioblastoma multiforme [GBM] and anaplastic astrocytoma [AA]) produced six prognostic groups (I-VI) classified by six factors. We sought here to determine whether the classification for GBM could be improved by using an updated Radiation Therapy Oncology Group (RTOG) GBM database excluding AA and by considering additional baseline variables. Methods and Materials: The new analysis considered 42 baseline variables and 1,672 GBM patients from the expanded RTOG glioma database. Patients receiving radiation only were excluded such that all patients received radiation+carmustine. 'Radiation dose received' was replaced with 'radiation dose assigned.' The new RPA models were compared with the original model by applying them to a test dataset comprising 488 patients from six other RTOG trials. Fitness of the original and new models was evaluated using explained variation. Results: The original RPA model explained more variations in survival in the test dataset than did the new models (20% vs. 15%) and was therefore chosen for further analysis. It was reduced by combining Classes V and VI to produce three prognostic classes (Classes III, IV, and V+VI), as Classes V and VI had indistinguishable survival in the test dataset. The simplified model did not further improve performance (explained variation 18% vs. 20%) but is easier to apply because it involves only four variables: age, performance status, extent of resection, and neurologic function. Applying this simplified model to the updated GBM database resulted in three distinct classes with median survival times of 17.1, 11.2, and 7.5 months for Classes III, IV, and V+VI, respectively. Conclusions: The final model, the simplified original RPA model combining Classes V and VI, resulted in three distinct prognostic groups defined by age, performance status, extent of resection, and neurologic function. This classification will be used

  10. Mechanism-based classification of PAH mixtures to predict carcinogenic potential

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Tilton, Susan C.; Siddens, Lisbeth K.; Krueger, Sharon K.; Larkin, Andrew J.; Löhr, Christiane V.; Williams, David E.; Baird, William M.; Waters, Katrina M.

    2015-04-22

    We have previously shown that relative potency factors and DNA adduct measurements are inadequate for predicting carcinogenicity of certain polycyclic aromatic hydrocarbons (PAHs) and PAH mixtures, particularly those that function through alternate pathways or exhibit greater promotional activity compared to benzo[a]pyrene (BaP). Therefore, we developed a pathway based approach for classification of tumor outcome after dermal exposure to PAH/mixtures. FVB/N mice were exposed to dibenzo[def,p]chrysene (DBC), BaP or environmental PAH mixtures (Mix 1-3) following a two-stage initiation/promotion skin tumor protocol. Resulting tumor incidence could be categorized by carcinogenic potency as DBC>>BaP=Mix2=Mix3>Mix1=Control, based on statistical significance. Gene expression profiles measured inmore » skin of mice collected 12 h post-initiation were compared to tumor outcome for identification of short-term bioactivity profiles. A Bayesian integration model was utilized to identify biological pathways predictive of PAH carcinogenic potential during initiation. Integration of probability matrices from four enriched pathways (p<0.05) for DNA damage, apoptosis, response to chemical stimulus and interferon gamma signaling resulted in the highest classification accuracy with leave-one-out cross validation. This pathway-driven approach was successfully utilized to distinguish early regulatory events during initiation prognostic for tumor outcome and provides proof-of-concept for using short-term initiation studies to classify carcinogenic potential of environmental PAH mixtures. As a result, these data further provide a ‘source-to outcome’ model that could be used to predict PAH interactions during tumorigenesis and provide an example of how mode-of-action based risk assessment could be employed for environmental PAH mixtures.« less

  11. Mechanism-based classification of PAH mixtures to predict carcinogenic potential

    SciTech Connect (OSTI)

    Tilton, Susan C.; Siddens, Lisbeth K.; Krueger, Sharon K.; Larkin, Andrew J.; Lhr, Christiane V.; Williams, David E.; Baird, William M.; Waters, Katrina M.

    2015-04-22

    We have previously shown that relative potency factors and DNA adduct measurements are inadequate for predicting carcinogenicity of certain polycyclic aromatic hydrocarbons (PAHs) and PAH mixtures, particularly those that function through alternate pathways or exhibit greater promotional activity compared to benzo[a]pyrene (BaP). Therefore, we developed a pathway based approach for classification of tumor outcome after dermal exposure to PAH/mixtures. FVB/N mice were exposed to dibenzo[def,p]chrysene (DBC), BaP or environmental PAH mixtures (Mix 1-3) following a two-stage initiation/promotion skin tumor protocol. Resulting tumor incidence could be categorized by carcinogenic potency as DBC>>BaP=Mix2=Mix3>Mix1=Control, based on statistical significance. Gene expression profiles measured in skin of mice collected 12 h post-initiation were compared to tumor outcome for identification of short-term bioactivity profiles. A Bayesian integration model was utilized to identify biological pathways predictive of PAH carcinogenic potential during initiation. Integration of probability matrices from four enriched pathways (p<0.05) for DNA damage, apoptosis, response to chemical stimulus and interferon gamma signaling resulted in the highest classification accuracy with leave-one-out cross validation. This pathway-driven approach was successfully utilized to distinguish early regulatory events during initiation prognostic for tumor outcome and provides proof-of-concept for using short-term initiation studies to classify carcinogenic potential of environmental PAH mixtures. As a result, these data further provide a source-to outcome model that could be used to predict PAH interactions during tumorigenesis and provide an example of how mode-of-action based risk assessment could be employed for environmental PAH mixtures.

  12. Pelvic Arterial Anatomy Relevant to Prostatic Artery Embolisation and Proposal for Angiographic Classification

    SciTech Connect (OSTI)

    Assis, André Moreira de Moreira, Airton Mota Paula Rodrigues, Vanessa Cristina de; Harward, Sardis Honoria; Antunes, Alberto Azoubel Srougi, Miguel; Carnevale, Francisco Cesar

    2015-08-15

    PurposeTo describe and categorize the angiographic findings regarding prostatic vascularization, propose an anatomic classification, and discuss its implications for the PAE procedure.MethodsAngiographic findings from 143 PAE procedures were reviewed retrospectively, and the origin of the inferior vesical artery (IVA) was classified into five subtypes as follows: type I: IVA originating from the anterior division of the internal iliac artery (IIA), from a common trunk with the superior vesical artery (SVA); type II: IVA originating from the anterior division of the IIA, inferior to the SVA origin; type III: IVA originating from the obturator artery; type IV: IVA originating from the internal pudendal artery; and type V: less common origins of the IVA. Incidences were calculated by percentage.ResultsTwo hundred eighty-six pelvic sides (n = 286) were analyzed, and 267 (93.3 %) were classified into I–IV types. Among them, the most common origin was type IV (n = 89, 31.1 %), followed by type I (n = 82, 28.7 %), type III (n = 54, 18.9 %), and type II (n = 42, 14.7 %). Type V anatomy was seen in 16 cases (5.6 %). Double vascularization, defined as two independent prostatic branches in one pelvic side, was seen in 23 cases (8.0 %).ConclusionsDespite the large number of possible anatomical variations of male pelvis, four main patterns corresponded to almost 95 % of the cases. Evaluation of anatomy in a systematic fashion, following a standard classification, will make PAE a faster, safer, and more effective procedure.

  13. SPECTRAL CLASSIFICATION OF THE BRIGHTEST OBJECTS IN THE GALACTIC STAR-FORMING REGION W40

    SciTech Connect (OSTI)

    Shuping, R. Y.; Vacca, William D.; Kassis, Marc; Yu, Ka Chun

    2012-10-01

    We present high signal-to-noise, moderate resolution (R Almost-Equal-To 2000) near-infrared spectra, as well as 10 {mu}m imaging, for the brightest members of the central stellar cluster in the W40 H II region, obtained using the SpeX and MIRSI instruments at NASA's Infrared Telescope Facility. Using these observations combined with archival Spitzer Space Telescope data, we have determined the spectral classifications, extinction, distances, and spectral energy distributions (SEDs) for the brightest members of the cluster. Of the eight objects observed, we identify four main-sequence (MS) OB stars (one late-O, three early-B), two Herbig Ae/Be stars, and two low-mass young stellar objects (Class II). Strong He I absorption at 1.083 {mu}m in the MS star spectra strongly suggests that at least some of these sources are in fact close binaries. Two out of the four MS stars also show significant infrared excesses typical of circumstellar disks. Extinctions and distances were determined for each MS star by fitting model stellar atmospheres to the SEDs. We estimate a distance to the cluster of between 455 and 535 pc, which agrees well with earlier (but far less precise) distance estimates. We conclude that the late-O star we identify is the dominant source of Lyman continuum luminosity needed to power the W40 H II region and is the likely source of the stellar wind that has blown a large ( Almost-Equal-To 4 pc) pinched-waist bubble observed in wide-field mid-IR images. We also suggest that 3.6 cm radio emission observed from some of the sources in the cluster is likely not due to emission from ultracompact H II regions, as suggested in other work, due to size constraints based on our derived distance to the cluster. Finally, we also present a discussion of the curious source IRS 3A, which has a very strong mid-IR excess (despite its B3 MS classification) and appears to be embedded in a dusty envelope roughly 2700 AU in size.

  14. The evaluation of an analytical protocol for the determination of substances in waste for hazard classification

    SciTech Connect (OSTI)

    Hennebert, Pierre; Papin, Arnaud; Padox, Jean-Marie; Hasebrouck, Benoît

    2013-07-15

    Highlights: • Knowledge of wastes in substances will be necessary to assess HP1–HP15 hazard properties. • A new analytical protocol is proposed for this and tested by two service laboratories on 32 samples. • Sixty-three percentage of the samples have a satisfactory analytical balance between 90% and 110%. • Eighty-four percentage of the samples were classified identically (Seveso Directive) for their hazardousness by the two laboratories. • The method, in progress, is being normalized in France and is be proposed to CEN. - Abstract: The classification of waste as hazardous could soon be assessed in Europe using largely the hazard properties of its constituents, according to the the Classification, Labelling and Packaging (CLP) regulation. Comprehensive knowledge of the component constituents of a given waste will therefore be necessary. An analytical protocol for determining waste composition is proposed, which includes using inductively coupled plasma (ICP) screening methods to identify major elements and gas chromatography/mass spectrometry (GC–MS) screening techniques to measure organic compounds. The method includes a gross or indicator measure of ‘pools’ of higher molecular weight organic substances that are taken to be less bioactive and less hazardous, and of unresolved ‘mass’ during the chromatography of volatile and semi-volatile compounds. The concentration of some elements and specific compounds that are linked to specific hazard properties and are subject to specific regulation (examples include: heavy metals, chromium(VI), cyanides, organo-halogens, and PCBs) are determined by classical quantitative analysis. To check the consistency of the analysis, the sum of the concentrations (including unresolved ‘pools’) should give a mass balance between 90% and 110%. Thirty-two laboratory samples comprising different industrial wastes (liquids and solids) were tested by two routine service laboratories, to give circa 7000 parameter

  15. EXPLORING THE VARIABLE SKY WITH LINEAR. III. CLASSIFICATION OF PERIODIC LIGHT CURVES

    SciTech Connect (OSTI)

    Palaversa, Lovro; Eyer, Laurent; Rimoldini, Lorenzo; Ivezi?, eljko; Loebman, Sarah; Hunt-Walker, Nicholas; VanderPlas, Jacob; Westman, David; Becker, Andrew C.; Rudjak, Domagoj; Sudar, Davor; Boi?, Hrvoje; Galin, Mario; Kroflin, Andrea; Mesari?, Martina; Munk, Petra; Vrbanec, Dijana; Sesar, Branimir; Stuart, J. Scott; Srdo?, Gregor; and others

    2013-10-01

    We describe the construction of a highly reliable sample of ?7000 optically faint periodic variable stars with light curves obtained by the asteroid survey LINEAR across 10,000 deg{sup 2} of the northern sky. The majority of these variables have not been cataloged yet. The sample flux limit is several magnitudes fainter than most other wide-angle surveys; the photometric errors range from ?0.03 mag at r = 15 to ?0.20 mag at r = 18. Light curves include on average 250 data points, collected over about a decade. Using Sloan Digital Sky Survey (SDSS) based photometric recalibration of the LINEAR data for about 25 million objects, we selected ?200,000 most probable candidate variables with r < 17 and visually confirmed and classified ?7000 periodic variables using phased light curves. The reliability and uniformity of visual classification across eight human classifiers was calibrated and tested using a catalog of variable stars from the SDSS Stripe 82 region and verified using an unsupervised machine learning approach. The resulting sample of periodic LINEAR variables is dominated by 3900 RR Lyrae stars and 2700 eclipsing binary stars of all subtypes and includes small fractions of relatively rare populations such as asymptotic giant branch stars and SX Phoenicis stars. We discuss the distribution of these mostly uncataloged variables in various diagrams constructed with optical-to-infrared SDSS, Two Micron All Sky Survey, and Wide-field Infrared Survey Explorer photometry, and with LINEAR light-curve features. We find that the combination of light-curve features and colors enables classification schemes much more powerful than when colors or light curves are each used separately. An interesting side result is a robust and precise quantitative description of a strong correlation between the light-curve period and color/spectral type for close and contact eclipsing binary stars (? Lyrae and W UMa): as the color-based spectral type varies from K4 to F5, the median

  16. THE GALEX TIME DOMAIN SURVEY. I. SELECTION AND CLASSIFICATION OF OVER A THOUSAND ULTRAVIOLET VARIABLE SOURCES

    SciTech Connect (OSTI)

    Gezari, S.; Martin, D. C.; Forster, K.; Neill, J. D.; Morrissey, P.; Wyder, T. K.; Huber, M.; Burgett, W. S.; Chambers, K. C.; Kaiser, N.; Magnier, E. A.; Tonry, J. L.; Heckman, T.; Bianchi, L.; Neff, S. G.; Seibert, M.; Schiminovich, D.; Price, P. A.

    2013-03-20

    We present the selection and classification of over a thousand ultraviolet (UV) variable sources discovered in {approx}40 deg{sup 2} of GALEX Time Domain Survey (TDS) NUV images observed with a cadence of 2 days and a baseline of observations of {approx}3 years. The GALEX TDS fields were designed to be in spatial and temporal coordination with the Pan-STARRS1 Medium Deep Survey, which provides deep optical imaging and simultaneous optical transient detections via image differencing. We characterize the GALEX photometric errors empirically as a function of mean magnitude, and select sources that vary at the 5{sigma} level in at least one epoch. We measure the statistical properties of the UV variability, including the structure function on timescales of days and years. We report classifications for the GALEX TDS sample using a combination of optical host colors and morphology, UV light curve characteristics, and matches to archival X-ray, and spectroscopy catalogs. We classify 62% of the sources as active galaxies (358 quasars and 305 active galactic nuclei), and 10% as variable stars (including 37 RR Lyrae, 53 M dwarf flare stars, and 2 cataclysmic variables). We detect a large-amplitude tail in the UV variability distribution for M-dwarf flare stars and RR Lyrae, reaching up to |{Delta}m| = 4.6 mag and 2.9 mag, respectively. The mean amplitude of the structure function for quasars on year timescales is five times larger than observed at optical wavelengths. The remaining unclassified sources include UV-bright extragalactic transients, two of which have been spectroscopically confirmed to be a young core-collapse supernova and a flare from the tidal disruption of a star by dormant supermassive black hole. We calculate a surface density for variable sources in the UV with NUV < 23 mag and |{Delta}m| > 0.2 mag of {approx}8.0, 7.7, and 1.8 deg{sup -2} for quasars, active galactic nuclei, and RR Lyrae stars, respectively. We also calculate a surface density rate in the

  17. THE CHOICE OF OPTIMAL STRUCTURE OF ARTIFICIAL NEURAL NETWORK CLASSIFIER INTENDED FOR CLASSIFICATION OF WELDING FLAWS

    SciTech Connect (OSTI)

    Sikora, R.; Chady, T.; Baniukiewicz, P.; Caryk, M.; Piekarczyk, B.

    2010-02-22

    Nondestructive testing and evaluation are under continuous development. Currently researches are concentrated on three main topics: advancement of existing methods, introduction of novel methods and development of artificial intelligent systems for automatic defect recognition (ADR). Automatic defect classification algorithm comprises of two main tasks: creating a defect database and preparing a defect classifier. Here, the database was built using defect features that describe all geometrical and texture properties of the defect. Almost twenty carefully selected features calculated for flaws extracted from real radiograms were used. The radiograms were obtained from shipbuilding industry and they were verified by qualified operator. Two weld defect's classifiers based on artificial neural networks were proposed and compared. First model consisted of one neural network model, where each output neuron corresponded to different defect group. The second model contained five neural networks. Each neural network had one neuron on output and was responsible for detection of defects from one group. In order to evaluate the effectiveness of the neural networks classifiers, the mean square errors were calculated for test radiograms and compared.

  18. Event Classification and Identification Based on the Characteristic Ellipsoid of Phasor Measurement

    SciTech Connect (OSTI)

    Ma, Jian; Diao, Ruisheng; Makarov, Yuri V.; Etingov, Pavel V.; Dagle, Jeffery E.

    2011-09-23

    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.

  19. Twisted injectivity in projected entangled pair states and the classification of quantum phases

    SciTech Connect (OSTI)

    Buerschaper, Oliver

    2014-12-15

    We introduce a class of projected entangled pair states (PEPS) which is based on a group symmetry twisted by a 3-cocycle of the group. This twisted symmetry is expressed as a matrix product operator (MPO) with bond dimension greater than 1 and acts on the virtual boundary of a PEPS tensor. We show that it gives rise to a new standard form for PEPS from which we construct a family of local Hamiltonians which are gapped, frustration-free and include fixed points of the renormalization group flow. Based on this insight, we advance the classification of 2D gapped quantum spin systems by showing how this new standard form for PEPS determines the emergent topological order of these local Hamiltonians. Specifically, we identify their universality class as DIJKGRAAF–WITTEN topological quantum field theory (TQFT). - Highlights: • We introduce a new standard form for projected entangled pair states via a twisted group symmetry which is given by nontrivial matrix product operators. • We construct a large family of gapped, frustration-free Hamiltonians in two dimensions from this new standard form. • We rigorously show how this new standard form for low energy states determines the emergent topological order.

  20. Classification of Superdeformed Bands in the Mass A{approx}60 Region

    SciTech Connect (OSTI)

    Andersson, L.-L.; Rudolph, D.; Fahlander, C.; Johansson, E. K.; Carlsson, B. G.; Ragnarsson, I.; Torres, D. A.

    2008-11-11

    The experimental knowledge of the {sub 29}{sup 61}Cu{sub 32} and {sub 30}{sup 61}Zn{sub 31} nuclei has been largely extended via the joint results from three experiments. The fusion-evaporation reaction used a {sup 36}Ar beam and a {sup 28}Si target foil to produce the two nuclei via the evaporation of either three protons ({sup 61}Cu) or two protons and a neutron ({sup 61}Zn). The experimental set-ups comprised the Ge-array GAMMASPHERE as well as neutron and charged-particle detectors placed around the target position.The resulting level schemes include around ten rotational superdeformed structures in each isotope. Most of them are linked to normally deformed states and in many cases spins and parities of the low-lying states in each structure have been determined.The collective structures are compared with results from configuration dependent Cranked Nilsson-Strutinsky calculations. The different structures are in general well understood from the calculation but the results do also suggest modifications of the standard Nilsson parameters in the mass A{approx}60 region.

  1. Standard for Communicating Waste Characterization and DOT Hazard Classification Requirements for Low Specific Activity Materials and Surface Contaminated Objects

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    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

  2. Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification

    SciTech Connect (OSTI)

    Drukker, Karen Giger, Maryellen L.; Li, Hui; Duewer, Fred; Malkov, Serghei; Joe, Bonnie; Kerlikowske, Karla; Shepherd, John A.; Flowers, Chris I.; Drukteinis, Jennifer S.

    2014-03-15

    Purpose: To investigate whether biologic image composition of mammographic lesions can improve upon existing mammographic quantitative image analysis (QIA) in estimating the probability of malignancy. Methods: The study population consisted of 45 breast lesions imaged with dual-energy mammography prior to breast biopsy with final diagnosis resulting in 10 invasive ductal carcinomas, 5 ductal carcinomain situ, 11 fibroadenomas, and 19 other benign diagnoses. Analysis was threefold: (1) The raw low-energy mammographic images were analyzed with an established in-house QIA method, QIA alone, (2) the three-compartment breast (3CB) composition measurederived from the dual-energy mammographyof water, lipid, and protein thickness were assessed, 3CB alone, and (3) information from QIA and 3CB was combined, QIA + 3CB. Analysis was initiated from radiologist-indicated lesion centers and was otherwise fully automated. Steps of the QIA and 3CB methods were lesion segmentation, characterization, and subsequent classification for malignancy in leave-one-case-out cross-validation. Performance assessment included box plots, BlandAltman plots, and Receiver Operating Characteristic (ROC) analysis. Results: The area under the ROC curve (AUC) for distinguishing between benign and malignant lesions (invasive and DCIS) was 0.81 (standard error 0.07) for the QIA alone method, 0.72 (0.07) for 3CB alone method, and 0.86 (0.04) for QIA+3CB combined. The difference in AUC was 0.043 between QIA + 3CB and QIA alone but failed to reach statistical significance (95% confidence interval [0.17 to + 0.26]). Conclusions: In this pilot study analyzing the new 3CB imaging modality, knowledge of the composition of breast lesions and their periphery appeared additive in combination with existing mammographic QIA methods for the distinction between different benign and malignant lesion types.

  3. ACTIVE LEARNING TO OVERCOME SAMPLE SELECTION BIAS: APPLICATION TO PHOTOMETRIC VARIABLE STAR CLASSIFICATION

    SciTech Connect (OSTI)

    Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J.; Brink, Henrik; Long, James P.; Rice, John

    2012-01-10

    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.

  4. ROBUSTNESS OF DECISION INSIGHTS UNDER ALTERNATIVE ALEATORY/EPISTEMIC UNCERTAINTY CLASSIFICATIONS

    SciTech Connect (OSTI)

    Unwin, Stephen D.; Eslinger, Paul W.; Johnson, Kenneth I.

    2013-09-22

    The Risk-Informed Safety Margin Characterization (RISMC) pathway is a set of activities defined under the U.S. Department of Energy Light Water Reactor Sustainability Program. The overarching objective of RISMC is to support plant life-extension decision-making by providing a state-of-knowledge characterization of safety margins in key systems, structures, and components (SSCs). A key technical challenge is to establish the conceptual and technical feasibility of analyzing safety margin in a risk-informed way, which, unlike conventionally defined deterministic margin analysis, would be founded on probabilistic characterizations of SSC performance. Evaluation of probabilistic safety margins will in general entail the uncertainty characterization both of the prospective challenge to the performance of an SSC ("load") and of its "capacity" to withstand that challenge. The RISMC framework contrasts sharply with the traditional probabilistic risk assessment (PRA) structure in that the underlying models are not inherently aleatory. Rather, they are largely deterministic physical/engineering models with ambiguities about the appropriate uncertainty classification of many model parameters. The current analysis demonstrates that if the distinction between epistemic and aleatory uncertainties is to be preserved in a RISMC-like modeling environment, then it is unlikely that analysis insights supporting decision-making will in general be robust under recategorization of input uncertainties. If it is believed there is a true conceptual distinction between epistemic and aleatory uncertainty (as opposed to the distinction being primarily a legacy of the PRA paradigm) then a consistent and defensible basis must be established by which to categorize input uncertainties.

  5. Eligibility for Renal Denervation: Anatomical Classification and Results in Essential Resistant Hypertension

    SciTech Connect (OSTI)

    Okada, Takuya Pellerin, Olivier; Savard, Sébastien; Curis, Emmanuel; Monge, Matthieu; Frank, Michael; Bobrie, Guillaume; Yamaguchi, Masato; Sugimoto, Koji; Plouin, Pierre-François; Azizi, Michel; Sapoval, Marc

    2015-02-15

    PurposeTo classify the renal artery (RA) anatomy based on specific requirements for endovascular renal artery denervation (RDN) in patients with drug-resistant hypertension (RH).Materials and MethodsThe RA anatomy of 122 consecutive RH patients was evaluated by computed tomography angiography and classified as two types: A (main RA ≥20 mm in length and ≥4.0 mm in diameter) or B (main RA <20 mm in length or main RA <4.0 mm in diameter). The A type included three subtypes: A1 (without accessory RAs), A2 (with accessory RAs <3.0 mm in diameter), and A3 (with accessory RAs ≥3.0 mm in diameter]. A1 and A2 types were eligible for RDN with the Simplicity Flex catheter. Type B included twi subtypes based on the main RA length and diameter. Patients were accordingly classified into three eligibility categories: complete (CE; both RAs were eligible), partial (PE; one eligible RA), and noneligibility (NE; no eligible RA).ResultsBilateral A1 type was the most prevalent and was observed in 48.4 % of the patients followed by the A1/A2 type (18 %). CE, PE, and NE were observed in 69.7, 22.9, and 7.4 % of patients, respectively. The prevalence of accessory RAs was 41 %.ConclusionsOf RH patients, 30.3 % were not eligible for bilateral RDN with the current Simplicity Flex catheter. This classification provides the basis for standardized reporting to allow for pooling of results of larger patient cohorts in the future.

  6. Impact of Passive Safety on FHR Instrumentation Systems Design and Classification

    SciTech Connect (OSTI)

    Holcomb, David Eugene

    2015-01-01

    Fluoride salt-cooled high-temperature reactors (FHRs) will rely more extensively on passive safety than earlier reactor classes. 10CFR50 Appendix A, General Design Criteria for Nuclear Power Plants, establishes minimum design requirements to provide reasonable assurance of adequate safety. 10CFR50.69, Risk-Informed Categorization and Treatment of Structures, Systems and Components for Nuclear Power Reactors, provides guidance on how the safety significance of systems, structures, and components (SSCs) should be reflected in their regulatory treatment. The Nuclear Energy Institute (NEI) has provided 10 CFR 50.69 SSC Categorization Guideline (NEI-00-04) that factors in probabilistic risk assessment (PRA) model insights, as well as deterministic insights, through an integrated decision-making panel. Employing the PRA to inform deterministic requirements enables an appropriately balanced, technically sound categorization to be established. No FHR currently has an adequate PRA or set of design basis accidents to enable establishing the safety classification of its SSCs. While all SSCs used to comply with the general design criteria (GDCs) will be safety related, the intent is to limit the instrumentation risk significance through effective design and reliance on inherent passive safety characteristics. For example, FHRs have no safety-significant temperature threshold phenomena, thus, enabling the primary and reserve reactivity control systems required by GDC 26 to be passively, thermally triggered at temperatures well below those for which core or primary coolant boundary damage would occur. Moreover, the passive thermal triggering of the primary and reserve shutdown systems may relegate the control rod drive motors to the control system, substantially decreasing the amount of safety-significant wiring needed. Similarly, FHR decay heat removal systems are intended to be running continuously to minimize the amount of safety-significant instrumentation needed to initiate

  7. An Adaptive Landscape Classification Procedure using Geoinformatics and Artificial Neural Networks

    SciTech Connect (OSTI)

    Coleman, Andre M.

    2008-08-01

    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

  8. Impact of Passive Safety on FHR Instrumentation Systems Design and Classification

    SciTech Connect (OSTI)

    Holcomb, David Eugene

    2015-01-01

    Fluoride salt-cooled high-temperature reactors (FHRs) will rely more extensively on passive safety than earlier reactor classes. 10CFR50 Appendix A, General Design Criteria for Nuclear Power Plants, establishes minimum design requirements to provide reasonable assurance of adequate safety. 10CFR50.69, Risk-Informed Categorization and Treatment of Structures, Systems and Components for Nuclear Power Reactors, provides guidance on how the safety significance of systems, structures, and components (SSCs) should be reflected in their regulatory treatment. The Nuclear Energy Institute (NEI) has provided 10 CFR 50.69 SSC Categorization Guideline (NEI-00-04) that factors in probabilistic risk assessment (PRA) model insights, as well as deterministic insights, through an integrated decision-making panel. Employing the PRA to inform deterministic requirements enables an appropriately balanced, technically sound categorization to be established. No FHR currently has an adequate PRA or set of design basis accidents to enable establishing the safety classification of its SSCs. While all SSCs used to comply with the general design criteria (GDCs) will be safety related, the intent is to limit the instrumentation risk significance through effective design and reliance on inherent passive safety characteristics. For example, FHRs have no safety-significant temperature threshold phenomena, thus enabling the primary and reserve reactivity control systems required by GDC 26 to be passively, thermally triggered at temperatures well below those for which core or primary coolant boundary damage would occur. Moreover, the passive thermal triggering of the primary and reserve shutdown systems may relegate the control rod drive motors to the control system, substantially decreasing the amount of safety-significant wiring needed. Similarly, FHR decay heat removal systems are intended to be running continuously to minimize the amount of safety-significant instrumentation needed to initiate

  9. GIS Framework for Large River Geomorphic Classification to Aid in the Evaluation of Flow-Ecology Relationships

    SciTech Connect (OSTI)

    Vernon, Christopher R.; Arntzen, Evan V.; Richmond, Marshall C.; McManamay, R. A.; Hanrahan, Timothy P.; Rakowski, Cynthia L.

    2013-02-01

    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.

  10. A support vector machine classifier reduces interscanner variation in the HRCT classification of regional disease pattern in diffuse lung disease: Comparison to a Bayesian classifier

    SciTech Connect (OSTI)

    Chang, Yongjun; Lim, Jonghyuck; Kim, Namkug; Seo, Joon Beom; Lynch, David A.

    2013-05-15

    Purpose: To investigate the effect of using different computed tomography (CT) scanners on the accuracy of high-resolution CT (HRCT) images in classifying regional disease patterns in patients with diffuse lung disease, support vector machine (SVM) and Bayesian classifiers were applied to multicenter data. Methods: Two experienced radiologists marked sets of 600 rectangular 20 Multiplication-Sign 20 pixel regions of interest (ROIs) on HRCT images obtained from two scanners (GE and Siemens), including 100 ROIs for each of local patterns of lungs-normal lung and five of regional pulmonary disease patterns (ground-glass opacity, reticular opacity, honeycombing, emphysema, and consolidation). Each ROI was assessed using 22 quantitative features belonging to one of the following descriptors: histogram, gradient, run-length, gray level co-occurrence matrix, low-attenuation area cluster, and top-hat transform. For automatic classification, a Bayesian classifier and a SVM classifier were compared under three different conditions. First, classification accuracies were estimated using data from each scanner. Next, data from the GE and Siemens scanners were used for training and testing, respectively, and vice versa. Finally, all ROI data were integrated regardless of the scanner type and were then trained and tested together. All experiments were performed based on forward feature selection and fivefold cross-validation with 20 repetitions. Results: For each scanner, better classification accuracies were achieved with the SVM classifier than the Bayesian classifier (92% and 82%, respectively, for the GE scanner; and 92% and 86%, respectively, for the Siemens scanner). The classification accuracies were 82%/72% for training with GE data and testing with Siemens data, and 79%/72% for the reverse. The use of training and test data obtained from the HRCT images of different scanners lowered the classification accuracy compared to the use of HRCT images from the same scanner. For

  11. A method for EIA scoping of wave energy converters-based on classification of the used technology

    SciTech Connect (OSTI)

    Margheritini, Lucia; Hansen, Anne Merrild; Frigaard, Peter

    2012-01-15

    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.

  12. Prognostic Value of Subclassification Using MRI in the T4 Classification Nasopharyngeal Carcinoma Intensity-Modulated Radiotherapy Treatment

    SciTech Connect (OSTI)

    Chen Lei; Liu Lizhi; Chen Mo; Li Wenfei; Yin Wenjing; Lin Aihua; Sun Ying; Li Li; Ma Jun

    2012-09-01

    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.

  13. SALTSTONE VAULT CLASSIFICATION SAMPLES MODULAR CAUSTIC SIDE SOLVENT EXTRACTION UNIT/ACTINIDE REMOVAL PROCESS WASTE STREAM APRIL 2011

    SciTech Connect (OSTI)

    Eibling, R.

    2011-09-28

    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

  14. GUIDANCE FOR THE PROPER CHARACTERIZATION AND CLASSIFICATION OF LOW SPECIFIC ACTIVITY MATERIALS AND SURFACE CONTAMINATED OBJECTS FOR DISPOSAL

    SciTech Connect (OSTI)

    PORTSMOUTH JH; BLACKFORD LT

    2012-02-13

    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

  15. Classification System for Identifying Women at Risk for Altered Partial Breast Irradiation Recommendations After Breast Magnetic Resonance Imaging

    SciTech Connect (OSTI)

    Kowalchik, Kristin V.; Vallow, Laura A.; McDonough, Michelle; Thomas, Colleen S.; Heckman, Michael G.; Peterson, Jennifer L.; Adkisson, Cameron D.; Serago, Christopher; McLaughlin, Sarah A.

    2013-09-01

    Purpose: To study the utility of preoperative breast MRI for partial breast irradiation (PBI) patient selection, using multivariable analysis of significant risk factors to create a classification rule. Methods and Materials: Between 2002 and 2009, 712 women with newly diagnosed breast cancer underwent preoperative bilateral breast MRI at Mayo Clinic Florida. Of this cohort, 566 were retrospectively deemed eligible for PBI according to the National Surgical Adjuvant Breast and Bowel Project Protocol B-39 inclusion criteria using physical examination, mammogram, and/or ultrasound. Magnetic resonance images were then reviewed to determine their impact on patient eligibility. The patient and tumor characteristics were evaluated to determine risk factors for altered PBI eligibility after MRI and to create a classification rule. Results: Of the 566 patients initially eligible for PBI, 141 (25%) were found ineligible because of pathologically proven MRI findings. Magnetic resonance imaging detected additional ipsilateral breast cancer in 118 (21%). Of these, 62 (11%) had more extensive disease than originally noted before MRI, and 64 (11%) had multicentric disease. Contralateral breast cancer was detected in 28 (5%). Four characteristics were found to be significantly associated with PBI ineligibility after MRI on multivariable analysis: premenopausal status (P=.021), detection by palpation (P<.001), first-degree relative with a history of breast cancer (P=.033), and lobular histology (P=.002). Risk factors were assigned a score of 0-2. The risk of altered PBI eligibility from MRI based on number of risk factors was 0:18%; 1:22%; 2:42%; 3:65%. Conclusions: Preoperative bilateral breast MRI altered the PBI recommendations for 25% of women. Women who may undergo PBI should be considered for breast MRI, especially those with lobular histology or with 2 or more of the following risk factors: premenopausal, detection by palpation, and first-degree relative with a history of

  16. The need for a characteristics-based approach to radioactive waste classification as informed by advanced nuclear fuel cycles using the fuel-cycle integration and tradeoffs (FIT) model

    SciTech Connect (OSTI)

    Djokic, D. [Department of Nuclear Engineering, University of California, Berkeley, 3115B Etcheverry Hall, Berkeley, CA 94720-1730 (United States); Piet, S.; Pincock, L.; Soelberg, N. [Idaho National Laboratory - INL, 2525 North Fremont Avenue, Idaho Falls, ID 83415 (United States)

    2013-07-01

    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. Because heat generation is generally the most important factor limiting geological repository areal loading, 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. Waste streams generated in different fuel cycles and their possible classification based on the current U.S. framework and international standards are discussed. It is shown that the effects of separating waste streams are neglected under a source-based radioactive waste classification system. (authors)

  17. Waste Classification based on Waste Form Heat Generation in Advanced Nuclear Fuel Cycles Using the Fuel-Cycle Integration and Tradeoffs (FIT) Model

    SciTech Connect (OSTI)

    Denia Djokic; Steven J. Piet; Layne F. Pincock; Nick R. Soelberg

    2013-02-01

    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.

  18. Navigation and vessel inspection circular No. 12-92. Guidelines for the classification and inspection of oil spill removal organizations (osros). Final report

    SciTech Connect (OSTI)

    1992-12-04

    The purpose of the circular is to facilitate the preparation and review of vessel and facility response plans by providing guidance on the classification of oil spill removal organizations. The guidelines propose a method of estimating the capacity of oil spill removal organizations to contain and remove oil from the water and shorelines.

  19. Waste Classification based on Waste Form Heat Generation in Advanced Nuclear Fuel Cycles Using the Fuel-Cycle Integration and Tradeoffs (FIT) Model - 13413

    SciTech Connect (OSTI)

    Djokic, Denia [Department of Nuclear Engineering, University of California - Berkeley, 4149 Etcheverry Hall, Berkeley, CA 94720-1730 (United States)] [Department of Nuclear Engineering, University of California - Berkeley, 4149 Etcheverry Hall, Berkeley, CA 94720-1730 (United States); Piet, Steven J.; Pincock, Layne F.; Soelberg, Nick R. [Idaho National Laboratory - INL, 2525 North Fremont Avenue, Idaho Falls, ID 83415 (United States)] [Idaho National Laboratory - INL, 2525 North Fremont Avenue, Idaho Falls, ID 83415 (United States)

    2013-07-01

    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. (authors)

  20. Assessment of Exploitable Geothermal Resources Using Magmatic...

    Open Energy Info (EERE)

    parameter in the magmatic transfer method. The method of magmatic heat transfer (Smith and Shaw, 1975; Sanyal et al., 2002) was applied in the main volcanic complexes of the...

  1. Assessing the Rye Patch Geothermal Field, a Classic Basin-and...

    Open Energy Info (EERE)

    the Rye Patch Geothermal Field, a Classic Basin-and-Range Resource Authors S.K Sanyal, J.R McNitt, S. J. Butler, C. W. Klein and and R.E. Elliss Published Journal GRC...

  2. Assessing the Rye Patch geothermal field, a classic Basin-and...

    Open Energy Info (EERE)

    if one or two additional wells are drilled for injection. Authors Sanyal, S.K., McNitt, J.R., Butler, S.J., Klein, C.W., and Ellis and R.K. Conference GRC Annual Meeting;...

  3. Position Management and Classification

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    2014-10-30

    The Order establishes Departmental requirements and responsibilities for classifying positions using the General Schedule (GS) and the Federal Wage System (FWS) standards.

  4. Methods for data classification

    DOE Patents [OSTI]

    Garrity, George; Lilburn, Timothy G.

    2011-10-11

    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.

  5. SU-E-J-125: Classification of CBCT Noises in Terms of Their Contribution to Proton Range Uncertainty

    SciTech Connect (OSTI)

    Brousmiche, S; Orban de Xivry, J; Macq, B; Seco, J

    2014-06-01

    Purpose: This study assesses the potential use of CBCT images in adaptive protontherapy by estimating the contribution of the main sources of noise and calibration errors to the proton range uncertainty. Methods: Measurements intended to highlight each particular source have been achieved by adapting either the testbench configuration, e.g. use of filtration, fan-beam collimation, beam stop arrays, phantoms and detector reset light, or the sequence of correction algorithms including water precorrection. Additional Monte-Carlo simulations have been performed to complement these measurements, especially for the beam hardening and the scatter cases. Simulations of proton beams penetration through the resulting images have then been carried out to quantify the range change due to these effects. The particular case of a brain irradiation is considered mainly because of the multiple effects that the skull bones have on the internal soft tissues. Results: On top of the range error sources is the undercorrection of scatter. Its influence has been analyzed from a comparison of fan-beam and full axial FOV acquisitions. In this case, large range errors of about 12 mm can be reached if the assumption is made that the scatter has only a constant contribution over the projection images. Even the detector lag, which a priori induces a much smaller effect, has been shown to contribute for up to 2 mm to the overall error if its correction only aims at reducing the skin artefact. This last result can partially be understood by the larger interface between tissues and bones inside the skull. Conclusion: This study has set the basis of a more systematical analysis of the effect CBCT noise on range uncertainties based on a combination of measurements, simulations and theoretical results. With our method, even more subtle effects such as the cone-beam artifact or the detector lag can be assessed. SBR and JOR are financed by iMagX, a public-private partnership between the region Wallone

  6. Integrating Epidermal Growth Factor Receptor Assay With Clinical Parameters Improves Risk Classification for Relapse and Survival in Head-and-Neck Squamous Cell Carcinoma

    SciTech Connect (OSTI)

    Chung, Christine H.; Hammond, Elizabeth M.; Trotti, Andy M.; Wang Huijun; Spencer, Sharon; Zhang Huazhong; Cooper, Jay; Jordan, Richard; Rotman, Marvin H.; Ang, K. Kian

    2011-10-01

    Purpose: Epidermal growth factor receptor (EGFR) overexpression has been consistently found to be an independent predictor of local-regional relapse (LRR) after radiotherapy. We assessed the extent by which it can refine risk classification for overall survival (OS) and LRR in patients with head-and-neck squamous cell carcinoma (HNSCC). Methods and Materials: EGFR expression in locally advanced HNSCC was measured by immunohistochemistry in a series of patients randomized to receive accelerated or conventional radiation regimens in a Phase III trial. Subsequently, data of the two series were pooled (N = 533) for conducting a recursive partitioning analysis that incorporated clinical parameters (e.g., performance status, primary site, T and N categories) and four molecular markers (EGFR, p53, Ki-67, and microvessel density). Results: This study confirmed that patients with higher than median levels of tumor EGFR expression had a lower OS (relative risk [RR]: 1.90, p = 0.0010) and a higher LRR (RR: 1.91, p = 0.0163). Of the four markers analyzed, only EGFR was found to contribute to refining classification of patients into three risk classes with distinct OS and LRR outcomes. The addition of EGFR to three clinical parameters could identify patients having up to a fivefold difference in the risk of LRR. Conclusions: Adding pretreatment EGFR expression data to known robust clinical prognostic variables improved the estimation of the probability for OS and LRR after radiotherapy. Its use for stratifying or selecting patients with defined tumor feature and pattern of relapse for enrollment into clinical trials testing specific therapeutic strategy warrants further investigation.

  7. The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classifications

    SciTech Connect (OSTI)

    Thomas, Alex D.; Stamatis, Dimitri; Bertsch, Jon; Isbandi, Michelle; Jansson, Jakob; Mallajosyula, Jyothi; Pagani, Ioanna; Lobos, Elizabeth A.; Kyrpides, Nikos C.; Reddy, Tatiparthi

    2014-10-29

    The Genomes OnLine Database (GOLD, http://www.genomesonline.org) is a comprehensive online resource to catalogue and monitor genetic studies worldwide. GOLD provides up-to-date status on complete and ongoing sequencing projects along with a broad array of curated metadata. Here we report version 5 (v.5) of the database. The newly designed database schema and web user interface supports several new features including the implementation of a four level (meta)genome project classification system and a simplified intuitive web interface to access reports and launch search tools. The database currently hosts information for about 19,200 studies, 56,000 Biosamples, 56,000 sequencing projects, and 39,400 analysis projects. More than just a catalogue of worldwide genome projects, GOLD is a manually curated, quality controlled metadata warehouse. The problems encountered in integrating disparate and varying quality data into GOLD are briefly highlighted. GOLD fully supports and follows the Genomic Standards Consortium (GSC) Minimum Information standards.

  8. MULTI-WAVELENGTH OBSERVATIONS OF SUPERNOVA 2011ei: TIME-DEPENDENT CLASSIFICATION OF TYPE IIb AND Ib SUPERNOVAE AND IMPLICATIONS FOR THEIR PROGENITORS

    SciTech Connect (OSTI)

    Milisavljevic, Dan; Margutti, Raffaella; Soderberg, Alicia M.; Chomiuk, Laura; Sanders, Nathan E.; Pignata, Giuliano; Bufano, Filomena; Fesen, Robert A.; Parrent, Jerod T.; Parker, Stuart; Mazzali, Paolo; Pian, Elena; Pickering, Timothy; Buckley, David A. H.; Crawford, Steven M.; Gulbis, Amanda A. S.; Hettlage, Christian; Hooper, Eric; Nordsieck, Kenneth H.; O'Donoghue, Darragh; and others

    2013-04-10

    We present X-ray, UV/optical, and radio observations of the stripped-envelope, core-collapse supernova (SN) 2011ei, one of the least luminous SNe IIb or Ib observed to date. Our observations begin with a discovery within {approx}1 day of explosion and span several months afterward. Early optical spectra exhibit broad, Type II-like hydrogen Balmer profiles that subside rapidly and are replaced by Type Ib-like He-rich features on a timescale of one week. High-cadence monitoring of this transition suggests absorption attributable to a high-velocity ({approx}> 12, 000 km s{sup -1}) H-rich shell, which is likely present in many Type Ib events. Radio observations imply a shock velocity of v Almost-Equal-To 0.13 c and a progenitor star average mass-loss rate of M-dot {approx}1.4 Multiplication-Sign 10{sup -5} M{sub sun} yr{sup -1} (assuming wind velocity v{sub w} = 10{sup 3} km s{sup -1}). This is consistent with independent constraints from deep X-ray observations with Swift-XRT and Chandra. Overall, the multi-wavelength properties of SN 2011ei are consistent with the explosion of a lower-mass (3-4 M{sub Sun }), compact (R{sub *} {approx}< 1 Multiplication-Sign 10{sup 11} cm), He-core star. The star retained a thin hydrogen envelope at the time of explosion, and was embedded in an inhomogeneous circumstellar wind suggestive of modest episodic mass loss. We conclude that SN 2011ei's rapid spectral metamorphosis is indicative of time-dependent classifications that bias estimates of the relative explosion rates for Type IIb and Ib objects, and that important information about a progenitor star's evolutionary state and mass loss immediately prior to SN explosion can be inferred from timely multi-wavelength observations.

  9. FUZZY SUPERNOVA TEMPLATES. I. CLASSIFICATION

    SciTech Connect (OSTI)

    Rodney, Steven A.; Tonry, John L. E-mail: jt@ifa.hawaii.ed

    2009-12-20

    Modern supernova (SN) surveys are now uncovering stellar explosions at rates that far surpass what the world's spectroscopic resources can handle. In order to make full use of these SN data sets, it is necessary to use analysis methods that depend only on the survey photometry. This paper presents two methods for utilizing a set of SN light-curve templates to classify SN objects. In the first case, we present an updated version of the Bayesian Adaptive Template Matching program (BATM). To address some shortcomings of that strictly Bayesian approach, we introduce a method for Supernova Ontology with Fuzzy Templates (SOFT), which utilizes fuzzy set theory for the definition and combination of SN light-curve models. For well-sampled light curves with a modest signal-to-noise ratio (S/N >10), the SOFT method can correctly separate thermonuclear (Type Ia) SNe from core collapse SNe with >=98% accuracy. In addition, the SOFT method has the potential to classify SNe into sub-types, providing photometric identification of very rare or peculiar explosions. The accuracy and precision of the SOFT method are verified using Monte Carlo simulations as well as real SN light curves from the Sloan Digital Sky Survey and the SuperNova Legacy Survey. In a subsequent paper, the SOFT method is extended to address the problem of parameter estimation, providing estimates of redshift, distance, and host galaxy extinction without any spectroscopy.

  10. Nonderivative modified gravity: a classification

    SciTech Connect (OSTI)

    Comelli, D.; Nesti, F.; Pilo, L. E-mail: fabrizio.nesti@irb.hr

    2014-11-01

    We analyze the theories of gravity modified by a generic nonderivative potential built from the metric, under the minimal requirement of unbroken spatial rotations. Using the canonical analysis, we classify the potentials V according to the number of degrees of freedom (DoF) that propagate at the nonperturbative level. We then compare the nonperturbative results with the perturbative DoF propagating around Minkowski and FRW backgrounds. A generic V implies 6 propagating DoF at the non-perturbative level, with a ghost on Minkowski background. There exist potentials which propagate 5 DoF, as already studied in previous works. Here, no V with unbroken rotational invariance admitting 4 DoF is found. Theories with 3 DoF turn out to be strongly coupled on Minkowski background. Finally, potentials with only the 2 DoF of a massive graviton exist. Their effect on cosmology is simply equivalent to a cosmological constant. Potentials with 2 or 5 DoF and explicit time dependence appear to be a further viable possibility.

  11. Rapid classification of biological components

    DOE Patents [OSTI]

    Thompson, Vicki S.; Barrett, Karen B.; Key, Diane E.

    2010-03-23

    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 to a 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.

  12. Rapid classification of biological components

    DOE Patents [OSTI]

    Thompson, Vicki S.; Barrett, Karen B.; Key, Diane E.

    2013-10-15

    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 to a 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.

  13. Rapid classification of biological components

    DOE Patents [OSTI]

    Thompson, Vicki S.; Barrett, Karen B.; Key, Diane E.

    2010-03-23

    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.

  14. Rapid classification of biological components

    DOE Patents [OSTI]

    Thompson, Vicki S.; Barrett, Karen B.; Key, Diane E.

    2006-01-24

    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, methamphetamine, methyltestosterone, or mesterolone. The method involves attaching antigens to 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 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 the subject's identity.

  15. Materials prediction via classification learning

    SciTech Connect (OSTI)

    Balachandran, Prasanna V.; Theiler, James; Rondinelli, James M.; Lookman, Turab

    2015-08-25

    In the paradigm of materials informatics for accelerated materials discovery, the choice of feature set (i.e. attributes that capture aspects of structure, chemistry and/or bonding) is critical. Ideally, the feature sets should provide a simple physical basis for extracting major structural and chemical trends and furthermore, enable rapid predictions of new material chemistries. Orbital radii calculated from model pseudopotential fits to spectroscopic data are potential candidates to satisfy these conditions. Although these radii (and their linear combinations) have been utilized in the past, their functional forms are largely justified with heuristic arguments. Here we show that machine learning methods naturally uncover the functional forms that mimic most frequently used features in the literature, thereby providing a mathematical basis for feature set construction without a priori assumptions. We apply these principles to study two broad materials classes: (i) wide band gap AB compounds and (ii) rare earth-main group RM intermetallics. The AB compounds serve as a prototypical example to demonstrate our approach, whereas the RM intermetallics show how these concepts can be used to rapidly design new ductile materials. In conclusion, our predictive models indicate that ScCo, ScIr, and YCd should be ductile, whereas each was previously proposed to be brittle.

  16. Materials prediction via classification learning

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Balachandran, Prasanna V.; Theiler, James; Rondinelli, James M.; Lookman, Turab

    2015-08-25

    In the paradigm of materials informatics for accelerated materials discovery, the choice of feature set (i.e. attributes that capture aspects of structure, chemistry and/or bonding) is critical. Ideally, the feature sets should provide a simple physical basis for extracting major structural and chemical trends and furthermore, enable rapid predictions of new material chemistries. Orbital radii calculated from model pseudopotential fits to spectroscopic data are potential candidates to satisfy these conditions. Although these radii (and their linear combinations) have been utilized in the past, their functional forms are largely justified with heuristic arguments. Here we show that machine learning methods naturallymore » uncover the functional forms that mimic most frequently used features in the literature, thereby providing a mathematical basis for feature set construction without a priori assumptions. We apply these principles to study two broad materials classes: (i) wide band gap AB compounds and (ii) rare earth-main group RM intermetallics. The AB compounds serve as a prototypical example to demonstrate our approach, whereas the RM intermetallics show how these concepts can be used to rapidly design new ductile materials. In conclusion, our predictive models indicate that ScCo, ScIr, and YCd should be ductile, whereas each was previously proposed to be brittle.« less

  17. Video occupant detection and classification

    DOE Patents [OSTI]

    Krumm, John C.

    1999-01-01

    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.

  18. A classification scheme for young stellar objects using the wide-field infrared survey explorer AllWISE catalog: revealing low-density star formation in the outer galaxy

    SciTech Connect (OSTI)

    Koenig, X. P.; Leisawitz, D. T.

    2014-08-20

    We present an assessment of the performance of WISE and the AllWISE data release for a section of the Galactic Plane. We lay out an approach to increasing the reliability of point-source photometry extracted from the AllWISE catalog in Galactic Plane regions using parameters provided in the catalog. We use the resulting catalog to construct a new, revised young star detection and classification scheme combining WISE and 2MASS near- and mid-infrared colors and magnitudes and test it in a section of the outer Milky Way. The clustering properties of the candidate Class I and II stars using a nearest neighbor density calculation and the two-point correlation function suggest that the majority of stars do form in massive star-forming regions, and any isolated mode of star formation is at most a small fraction of the total star forming output of the Galaxy. We also show that the isolated component may be very small and could represent the tail end of a single mechanism of star formation in line with models of molecular cloud collapse with supersonic turbulence and not a separate mode all to itself.

  19. Robustness of RISMC Insights under Alternative Aleatory/Epistemic Uncertainty Classifications: Draft Report under the Risk-Informed Safety Margin Characterization (RISMC) Pathway of the DOE Light Water Reactor Sustainability Program

    SciTech Connect (OSTI)

    Unwin, Stephen D.; Eslinger, Paul W.; Johnson, Kenneth I.

    2012-09-20

    The Risk-Informed Safety Margin Characterization (RISMC) pathway is a set of activities defined under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability Program. The overarching objective of RISMC is to support plant life-extension decision-making by providing a state-of-knowledge characterization of safety margins in key systems, structures, and components (SSCs). A technical challenge at the core of this effort is to establish the conceptual and technical feasibility of analyzing safety margin in a risk-informed way, which, unlike conventionally defined deterministic margin analysis, would be founded on probabilistic characterizations of uncertainty in SSC performance. In the context of probabilistic risk assessment (PRA) technology, there has arisen a general consensus about the distinctive roles of two types of uncertainty: aleatory and epistemic, where the former represents irreducible, random variability inherent in a system, whereas the latter represents a state of knowledge uncertainty on the part of the analyst about the system which is, in principle, reducible through further research. While there is often some ambiguity about how any one contributing uncertainty in an analysis should be classified, there has nevertheless emerged a broad consensus on the meanings of these uncertainty types in the PRA setting. However, while RISMC methodology shares some features with conventional PRA, it will nevertheless be a distinctive methodology set. Therefore, the paradigms for classification of uncertainty in the PRA setting may not fully port to the RISMC environment. Yet the notion of risk-informed margin is based on the characterization of uncertainty, and it is therefore critical to establish a common understanding of uncertainty in the RISMC setting.

  20. National Geothermal Resource Assessment and Classification

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    of the National Geothermal Data System. The results of this work will enable lower riskcost deployment of conventional and EGS geothermal power. USGS is also supporting GTP...

  1. Vapor Retarder Classification - Building America Top Innovation...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    - Building America Top Innovation Building America Webinar: High-Performance Enclosure Strategies, Part I: Unvented Roof Systems and Innovative Advanced Framing Strategies

  2. ARM - Evaluation Product - Cloud Classification VAP

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    properties includes cloud boundaries, thickness, phase, type, and precipitation information, and hence provides a useful tool for evaluation of model simulations and...

  3. Statistical fingerprinting for malware detection and classification

    SciTech Connect (OSTI)

    Prowell, Stacy J.; Rathgeb, Christopher T.

    2015-09-15

    A system detects malware in a computing architecture with an unknown pedigree. The system includes a first computing device having a known pedigree and operating free of malware. The first computing device executes a series of instrumented functions that, when executed, provide a statistical baseline that is representative of the time it takes the software application to run on a computing device having a known pedigree. A second computing device executes a second series of instrumented functions that, when executed, provides an actual time that is representative of the time the known software application runs on the second computing device. The system detects malware when there is a difference in execution times between the first and the second computing devices.

  4. Fly ash chemical classification based on lime

    SciTech Connect (OSTI)

    Fox, J.

    2007-07-01

    Typically, total lime content (CaO) of fly ash is shown in fly ash reports, but its significance is not addressed in US specifications. For certain applications a low lime ash is preferred. When a class C fly ash must be cementitious, lime content above 20% is required. A ternary S-A-C phase diagram pilot is given showing the location of fly ash compositions by coal rank and source in North America. Fly ashes from subbituminous coal from the Powder River Basin usually contain sufficient lime to be cementitious but blending with other coals may result in calcium being present in phases other than tricalcium aluminate. 9 refs., 1 fig.

  5. To' File CLASSIFICATION CANCF,LLED

    Office of Legacy Management (LM)

    diamtar by .lW deep on each end' of the slag. .Ibio will amble aocurnte cz&zing of .+.hc slu;E in th6. die, but,, LiftAr cnstdng, the pieoa v-ill ho-m expeod tubloy at encb ad. ...

  6. Influential input classification in probabilistic multimedia models

    SciTech Connect (OSTI)

    Maddalena, Randy L.; McKone, Thomas E.; Hsieh, Dennis P.H.; Geng, Shu

    1999-05-01

    Monte Carlo analysis is a statistical simulation method that is often used to assess and quantify the outcome variance in complex environmental fate and effects models. Total outcome variance of these models is a function of (1) the uncertainty and/or variability associated with each model input and (2) the sensitivity of the model outcome to changes in the inputs. To propagate variance through a model using Monte Carlo techniques, each variable must be assigned a probability distribution. The validity of these distributions directly influences the accuracy and reliability of the model outcome. To efficiently allocate resources for constructing distributions one should first identify the most influential set of variables in the model. Although existing sensitivity and uncertainty analysis methods can provide a relative ranking of the importance of model inputs, they fail to identify the minimum set of stochastic inputs necessary to sufficiently characterize the outcome variance. In this paper, we describe and demonstrate a novel sensitivity/uncertainty analysis method for assessing the importance of each variable in a multimedia environmental fate model. Our analyses show that for a given scenario, a relatively small number of input variables influence the central tendency of the model and an even smaller set determines the shape of the outcome distribution. For each input, the level of influence depends on the scenario under consideration. This information is useful for developing site specific models and improving our understanding of the processes that have the greatest influence on the variance in outcomes from multimedia models.

  7. Updating the Classification of Geothermal Resources - Presentation...

    Open Energy Info (EERE)

    - Presentation Abstract Abstract unavailable. Authors Colin F. Williams and Marshall J. Reed and Arlene F. Anderson Conference Thirty-Sixth Workshop on Geothermal Reservoir...

  8. Integrating multiple data sources for malware classification

    DOE Patents [OSTI]

    Anderson, Blake Harrell; Storlie, Curtis B; Lane, Terran

    2015-04-28

    Disclosed herein are representative embodiments of tools and techniques for classifying programs. According to one exemplary technique, at least one graph representation of at least one dynamic data source of at least one program is generated. Also, at least one graph representation of at least one static data source of the at least one program is generated. Additionally, at least using the at least one graph representation of the at least one dynamic data source and the at least one graph representation of the at least one static data source, the at least one program is classified.

  9. Waste Classification FAQ DRAFT.docx

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    classified, the more informed they will be when weighing in about Hanford cleanup. Here are some frequently asked questions about different waste forms and how they are classified...

  10. National Geothermal Resource Assessment and Classification |...

    Broader source: Energy.gov (indexed) [DOE]

    will enable lower riskcost deployment of conventional and EGS geothermal power. USGS is also supporting GTP input to DOE National Energy Modeling by providing resource assessment...

  11. Biological cell classification by multiangle light scattering

    DOE Patents [OSTI]

    Salzman, G.C.; Crowell, J.M.; Mullaney, P.F.

    1975-06-03

    The specification is directed to an apparatus and method for detecting light scattering from a biological cell. Light, preferably from a coherent source of radiation, intercepts an individual biological cell in a stream of cells passing through the beam. Light scattered from the cell is detected at a selected number of angles between 0 and 90/sup 0/ to the longitudinal axis of the beam with a circular array of light responsive elements which produce signals representative of the intensity of light incident thereon. Signals from the elements are processed to determine the light-scattering pattern of the cell and therefrom its identity.

  12. Classification Training Institute | Department of Energy

    Office of Environmental Management (EM)

    and links to web pages with additional information) concerning information classified and controlled information within the DOE. This page also contains short animated lessons. ...

  13. ORNL Researchers Develop 'Autotune' Software to Make it Quicker,

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Easier, and Cheaper to Model Energy Use of Buildings | Department of Energy ORNL Researchers Develop 'Autotune' Software to Make it Quicker, Easier, and Cheaper to Model Energy Use of Buildings ORNL Researchers Develop 'Autotune' Software to Make it Quicker, Easier, and Cheaper to Model Energy Use of Buildings October 15, 2014 - 12:34pm Addthis ORNL buildings researchers Jibonananda Sanyal, left, and Joshua New are developing software that will automatically calibrate models for simulating

  14. Unified HVAC and Refrigeration Control Systems for Small Footprint Supermarkets

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Unified HVAC and Refrigeration Control Systems for Small Footprint Supermarkets Teja Kuruganti, David Fugate, James Nutaro, Jibonananda Sanyal, Brian Fricke Oak Ridge National Laboratory John Wallace Emerson Climate Technologies Presented at: Technical Meeting on Software Framework for Transactive Energy: VOLTTRON 23 rd - 24 th July, 2015 2 Presentation_name Motivation and Objective * Supermarket Energy Consumption - 37,000 supermarkets in the US * 2,000,000 kWh per year per store * 1,000,000

  15. Automated Diagnosis and Classification of Steam Generator Tube Defects

    SciTech Connect (OSTI)

    Dr. Gabe V. Garcia

    2004-10-01

    A major cause of failure in nuclear steam generators is tube degradation. Tube defects are divided into seven categories, one of which is intergranular attack/stress corrosion cracking (IGA/SCC). Defects of this type usually begin on the outer surface of the tubes and propagate both inward and laterally. In many cases these defects occur at or near the tube support plates. Several different methods exist for the nondestructive evaluation of nuclear steam generator tubes for defect characterization.

  16. Rules governing the classification of coal slurries for filtering centrifuges

    SciTech Connect (OSTI)

    G.Y. Gol'berg; Y.B. Rubinshtein; S.A. Osadchii

    2008-07-01

    The feasibility of using filtering centrifuges for the cleaning of a coking-coal slurry is confirmed in principle, and regime operating parameters which ensure the production of a concentrate of conditioned quality are determined on the basis of results of experimental-industrial tests of a new procedure for this operation at the Neryungrinskaya Concentrating Mill. An equation is proposed for determination of solid carry-off in the centrifuge effluent, which completely satisfactorily (with a correlation coefficient of 0.7-0.8) describes the dependence of the parameter in question on the solid content in the centrifuge feed, and on its content of -0.2-mm material. It is noted that special investigations to determine the effect of the speed of the rotor and shape of the particles on the amount of solid carry-off in the centrifuge effluent are required for construction of a model describing the size reduction of solid-phase particles in the effluent during centrifuge filtration.

  17. Bianchi Attractors: A Classification of Extremal Black Brane...

    Office of Scientific and Technical Information (OSTI)

    Research Org: SLAC National Accelerator Laboratory (SLAC) Sponsoring Org: US DOE Office of Science (DOE SC) Country of Publication: United States Language: English Subject: ...

  18. Library Event Matching event classification algorithm for electron...

    Office of Scientific and Technical Information (OSTI)

    Type: Publisher's Accepted Manuscript Journal Name: Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment ...

  19. NFPA hazardous classifications and compliance regarding the electromagnetic induction probe

    SciTech Connect (OSTI)

    Vargo, G.F.; Stokes, T.I., Westinghouse Hanford

    1996-08-13

    This document discusses how the Electromagnetic Induction probe complies with the hazardous locations discussed for the Surface Moisture Measurement System (SMMS). The EMI probe head was designed to interchange with the neutron probe of the SMMS.

  20. Briefing, Classification of Nuclear Weapons-Related Information

    Broader source: Energy.gov [DOE]

    This brief will 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 Nuclear Weapons-Related Information.

  1. Binary classification of items of interest in a repeatable process

    SciTech Connect (OSTI)

    Abell, Jeffrey A.; Spicer, John Patrick; Wincek, Michael Anthony; Wang, Hui; Chakraborty, Debejyo

    2014-06-24

    A system includes host and learning machines in electrical communication with sensors positioned with respect to an item of interest, e.g., a weld, and memory. The host executes instructions from memory to predict a binary quality status of the item. The learning machine receives signals from the sensor(s), identifies candidate features, and extracts features from the candidates that are more predictive of the binary quality status relative to other candidate features. The learning machine maps the extracted features to a dimensional space that includes most of the items from a passing binary class and excludes all or most of the items from a failing binary class. The host also compares the received signals for a subsequent item of interest to the dimensional space to thereby predict, in real time, the binary quality status of the subsequent item of interest.

  2. Bianchi Attractors: A Classification of Extremal Black Brane...

    Office of Scientific and Technical Information (OSTI)

    Information Service, Springfield, VA at www.ntis.gov. Authors: Iizuka, Norihiro ; CERN ; Kachru, Shamit ; Stanford U., ITP SLAC ; Kundu, Nilay ; Narayan, Prithvi ; Sircar,...

  3. Accurate phylogenetic classification of DNA fragments based onsequence composition

    SciTech Connect (OSTI)

    McHardy, Alice C.; Garcia Martin, Hector; Tsirigos, Aristotelis; Hugenholtz, Philip; Rigoutsos, Isidore

    2006-05-01

    Metagenome studies have retrieved vast amounts of sequenceout of a variety of environments, leading to novel discoveries and greatinsights into the uncultured microbial world. Except for very simplecommunities, diversity makes sequence assembly and analysis a verychallenging problem. To understand the structure a 5 nd function ofmicrobial communities, a taxonomic characterization of the obtainedsequence fragments is highly desirable, yet currently limited mostly tothose sequences that contain phylogenetic marker genes. We show that forclades at the rank of domain down to genus, sequence composition allowsthe very accurate phylogenetic 10 characterization of genomic sequence.We developed a composition-based classifier, PhyloPythia, for de novophylogenetic sequence characterization and have trained it on adata setof 340 genomes. By extensive evaluation experiments we show that themethodis accurate across all taxonomic ranks considered, even forsequences that originate fromnovel organisms and are as short as 1kb.Application to two metagenome datasets 15 obtained from samples ofphosphorus-removing sludge showed that the method allows the accurateclassification at genus level of most sequence fragments from thedominant populations, while at the same time correctly characterizingeven larger parts of the samples at higher taxonomic levels.

  4. A Proposed New Classification Of The Granites Of Egypt | Open...

    Open Energy Info (EERE)

    classified according to relative age (old and younger granites), dominant colour (grey, red and pink granites), type localities (Shaitian, Gattarian and Gharib granites) or their...

  5. Final Hazard Classification for the FFTF Solid Waste Cask

    SciTech Connect (OSTI)

    HIMES, D.A.

    2002-07-03

    The Solid Waste Cask (SWC) (a major component of the Fast Flux Test Facility (FFTF) spent fuel offload system) is a shielded, bottom-loading cask containing an internal hoist system used to transfer irradiated fuel or non-fuel components from the Interim Examination and Maintenance Cell (IEM Cell) to the Cask Loading Station (CLS). The SWC is assumed to be loaded with 7 irradiated fuel assemblies in a Core Component Container (CCC) having maximum average burn-ups of 150,000 MWd/MTHM. Results show that the fuel handling activities with the SWC loaded with 7 irradiated fuel assemblies in a CCC should be classified as a Category 3 hazard. This conclusion is consistent with the relative simplicity of the system and passive nature of the barriers for purposes of determining the graded approach specified in DOE-STD-1027-92 (DOE 1992).

  6. THE CLASSIFICATION OF KEPLER B-STAR VARIABLES

    SciTech Connect (OSTI)

    McNamara, Bernard J.; Jackiewicz, Jason; McKeever, Jean E-mail: jasonj@nmsu.edu

    2012-04-15

    The light curves of 252 B-star candidates in the Kepler database are analyzed in a similar fashion to that done by Balona et al. to further characterize B-star variability, increase the sample of variable B stars for future study, and to identify stars whose power spectra include particularly interesting features such as frequency groupings. Stars are classified as either constant light emitters, {beta} Cep stars, slowly pulsating B stars (SPBs), hybrid pulsators, binaries or stars whose light curves are dominated by rotation (Bin/Rot), hot subdwarfs, or white dwarfs. One-hundred stars in our sample were found to be either light constants or to be variable at a level of less than 0.02 mmag. We increase the number of candidate B-star variables found in the Kepler database by Balona et al. in the following fashion: {beta} Cep stars from 0 to 10, SPBs from eight to 54, hybrid pulsators from seven to 21, and Bin/Rot stars from 23 to 82. For comparison purposes, approximately 51 SPBs and six hybrids had been known prior to 2007. The number of {beta} Cep stars known prior to 2004 was 93. A secondary result of this study is the identification of an additional 11 pulsating white dwarf candidates, four of which possess frequency groupings.

  7. Sensor network based vehicle classification and license plate identification system

    SciTech Connect (OSTI)

    Frigo, Janette Rose; Brennan, Sean M; Rosten, Edward J; Raby, Eric Y; Kulathumani, Vinod K

    2009-01-01

    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, sensor network applications require data and compute intensive sensors such video cameras and microphones. In this paper, we describe the design and implementation of two such systems: a vehicle classifier based on acoustic signals and a license plate identification system using a camera. The systems are implemented in an energy-efficient manner to the extent possible using commercially available hardware, the Mica motes and the Stargate platform. Our experience in designing these systems leads us to consider an alternate more flexible, modular, low-power mote architecture that uses a combination of FPGAs, specialized embedded processing units and sensor data acquisition systems.

  8. Initial VHTR accident scenario classification: models and data.

    SciTech Connect (OSTI)

    Vilim, R. B.; Feldman, E. E.; Pointer, W. D.; Wei, T. Y. C.; Nuclear Engineering Division

    2005-09-30

    Nuclear systems codes are being prepared for use as computational tools for conducting performance/safety analyses of the Very High Temperature Reactor. The thermal-hydraulic codes are RELAP5/ATHENA for one-dimensional systems modeling and FLUENT and/or Star-CD for three-dimensional modeling. We describe a formal qualification framework, the development of Phenomena Identification and Ranking Tables (PIRTs), the initial filtering of the experiment databases, and a preliminary screening of these codes for use in the performance/safety analyses. In the second year of this project we focused on development of PIRTS. Two events that result in maximum fuel and vessel temperatures, the Pressurized Conduction Cooldown (PCC) event and the Depressurized Conduction Cooldown (DCC) event, were selected for PIRT generation. A third event that may result in significant thermal stresses, the Load Change event, is also selected for PIRT generation. Gas reactor design experience and engineering judgment were used to identify the important phenomena in the primary system for these events. Sensitivity calculations performed with the RELAP5 code were used as an aid to rank the phenomena in order of importance with respect to the approach of plant response to safety limits. The overall code qualification methodology was illustrated by focusing on the Reactor Cavity Cooling System (RCCS). The mixed convection mode of heat transfer and pressure drop is identified as an important phenomenon for Reactor Cavity Cooling System (RCCS) operation. Scaling studies showed that the mixed convection mode is likely to occur in the RCCS air duct during normal operation and during conduction cooldown events. The RELAP5/ATHENA code was found to not adequately treat the mixed convection regime. Readying the code will require adding models for the turbulent mixed convection regime while possibly performing new experiments for the laminar mixed convection regime. Candidate correlations for the turbulent mixed convection regime for circular channel geometry were identified in the literature. We describe the use of computational experiments to obtain correction factors for applying these circular channel results to the specialized channel geometry of the RCCS. The intent is to reduce the number of laboratory experiments required. The FLUENT and Star-CD codes contain models that in principle can handle mixed convection but no data were found to indicate that their empirical models for turbulence have been benchmarked for mixed convection conditions. Separate effects experiments were proposed for gathering the needed data. In future work we will use the PIRTs to guide review of other components and phenomena in a similar manner as was done for the mixed convection mode in the RCCS. This is consistent with the project objective of identifying weaknesses or gaps in the code models for representing thermal-hydraulic phenomena expected to occur in the VHTR both during normal operation and upsets, identifying the models that need to be developed, and identifying the experiments that must be performed to support model development.

  9. Building America Top Innovations 2012: Vapor Retarder Classification

    SciTech Connect (OSTI)

    none,

    2013-01-01

    This Building America Top Innovations profile describes research in vapor retarders. Since 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.

  10. Representations and image classification methods for Cherenkov telescopes

    SciTech Connect (OSTI)

    Malagon, C.; Parcerisa, D. S.; Barrio, J. A.; Nieto, D.

    2008-05-29

    The problem of identifying gamma ray events out of charged cosmic ray background (so called hadrons) in Cherenkov telescopes is one of the key problems in VHE gamma ray astronomy. In this contribution, we present a novel approach to this problem by implementing different classifiers relying on the information of each pixel of the camera of a Cherenkov telescope.

  11. Reassessing the extent of the Q classification for containment paint

    SciTech Connect (OSTI)

    Spires, G.

    1995-12-31

    A mounting number of site-specific paint debris transport and screen clogging analyses submitted to justify substandard containment paint work have been deemed persuasive by virtue of favorable U.S. Nuclear Regulatory Commission safety evaluation report (SER) findings. These lay a strong foundation for a standardized approach to redefining the extent to which paint in containment needs to be considered {open_quotes}Q.{close_quotes} This information justifies an initiative by licensees to roll back paint work quality commitments made at the design phase. This paper questions the validity of the basic premise that all primary containment paint can significantly compromise core and containment cooling [emergency core cooling system/engineered safeguard feature (ECCS/ESF)]. It is posited that the physical extent of painted containment surfaces for which extant material qualification and quality control (QC) structures need apply can be limited to zones relatively proximate to ECCS/ESF suction points. For other painted containment surfaces, simplified criteria should be allowed.

  12. The classification of magnetohydrodynamic regimes of thermonuclear combustion

    SciTech Connect (OSTI)

    Remming, Ian S. [Department of Astronomy and Astrophysics, The University of Chicago, Chicago, IL 60637 (United States); Khokhlov, Alexei M. [Department of Astronomy and Astrophysics, the Enrico Fermi Institute, and the Computational Institute, The University of Chicago, Chicago, IL 60637 (United States)

    2014-10-10

    Physical properties of magnetohydrodynamic (MHD) reaction fronts are studied as functions of the thermodynamic conditions, and the strength and orientation of the magnetic field in the unburned matter through which the fronts propagate. We determine the conditions for the existence of the various types of MHD reaction fronts and the character of the changes in physical quantities across these reaction fronts. The analysis is carried out in general for a perfect gas equation of state and a constant energy release, and then extended to thermonuclear reaction fronts in degenerate carbon-oxygen mixtures and degenerate helium in conditions typical of Type Ia supernova explosions. We find that as unburned matter enters perpendicular to a reaction front, the release of energy through burning generates shear velocity in the reacting gas that, depending on the type of reaction front, strengthens or weakens the magnetic field. In addition, we find that the steady-state propagation of a reaction front is impossible for certain ranges of magnetic field direction. Our results provide insight into the phenomena of MHD thermonuclear combustion that is relevant to the interpretation of future simulations of SN Ia explosions that have magnetic fields systematically incorporated.

  13. Classification of collective modes in a charge density wave by...

    Office of Scientific and Technical Information (OSTI)

    Authors: Leuenberger, D. ; Sobota, J. A. ; Yang, S.-L. ; Kemper, A. F. ; Giraldo-Gallo, P. ; Moore, R. G. ; Fisher, I. R. ; Kirchmann, P. S. ; Devereaux, T. P. ; Shen, Z.-X. ...

  14. Detection and Classification of Buried Metallic Objects UX-1225

    SciTech Connect (OSTI)

    Morrison, Frank; Smith, Torquil; Becker, Alex; Gasperikova, Erika

    2005-03-31

    In summary the technical objectives of this project were: (1) To develop and demonstrate a methodology for the quantitative evaluation of existing active electromagnetic (AEM) systems and for the design of new systems. (2) To implement a new methodology for optimizing an AEM system for detecting and classifying UXO of a given class in a specified geologic setting and in a given noise environment. (3) To design and build a prototype of an active EM system for detecting and characterizing a metallic object in the ground.

  15. B-Cell waste classification sampling and analysis plan

    SciTech Connect (OSTI)

    HOBART, R.L.

    1999-09-22

    This report documents the methods used to collect and analyze samples to obtain data necessary to verify and/or determine the radionuclide content of the 324 Facility B-Cell decontamination and decommissioning waste stream.

  16. OpenNet recently redesigned for Office of Classification | OSTI...

    Office of Scientific and Technical Information (OSTI)

    OpenNet is now easier to navigate and includes more full-text content that can be searched electronically. The Web portal, developed by OSTI in support of the Department of ...

  17. Multitemporal spectral analysis for cheatgrass (Bromus tectorum) classification.

    SciTech Connect (OSTI)

    Singh, Nagendra; Glenn, Nancy F

    2009-07-01

    Operational satellite remote sensing data can provide the temporal repeatability necessary to capture phenological differences among species. This study develops a multitemporal stacking method coupled with spectral analysis for extracting information from Landsat imagery to provide species-level information. Temporal stacking can, in an approximate mathematical sense, effectively increase the 'spectral' resolution of the system by adding spectral bands of several multitemporal images. As a demonstration, multitemporal linear spectral unmixing is used to successfully delineate cheatgrass (Bromus tectorum) from soil and surrounding vegetation (77% overall accuracy). This invasive plant is an ideal target for exploring multitemporal methods because of its phenological differences with other vegetation in early spring and, to a lesser degree, in late summer. The techniques developed in this work are directly applicable for other targets with temporally unique spectral differences.

  18. Terrain detection and classification using single polarization SAR

    DOE Patents [OSTI]

    Chow, James G.; Koch, Mark W.

    2016-01-19

    The various technologies presented herein relate to identifying manmade and/or natural features in a radar image. Two radar images (e.g., single polarization SAR images) can be captured for a common scene. The first image is captured at a first instance and the second image is captured at a second instance, whereby the duration between the captures are of sufficient time such that temporal decorrelation occurs for natural surfaces in the scene, and only manmade surfaces, e.g., a road, produce correlated pixels. A LCCD image comprising the correlated and decorrelated pixels can be generated from the two radar images. A median image can be generated from a plurality of radar images, whereby any features in the median image can be identified. A superpixel operation can be performed on the LCCD image and the median image, thereby enabling a feature(s) in the LCCD image to be classified.

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

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    on Classified Information in the open literature. Provides guidance as to what use or discussion is allowed concerning sources in the open literature that contain classified ...

  20. USING CLOUD CLASSIFICATION TO MODEL SOLAR VARIABILITY Matthew...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Hourly cloud classified satellite images are compared to multiple years of ground measured ... type of cloud or weather pattern, as classified by NOAA. Instinctively, the type of ...

  1. A3-4 Table A3-1. Classification

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Slopes range from 2-15%. Ailey soils are classified as loamy, siliceous, thermic Arenic ... Slopes range from 0-6%. Albany soils are classified as loamy, siliceous, thermic ...

  2. Marginal erg facies: A trial approach toward a descriptive classification

    SciTech Connect (OSTI)

    Caputo, M.V. ); Langford, R.P. )

    1991-03-01

    During the late 1970s and early 1980s, sedimentologists began recognizing the margins of eolian sand seas as separate, components which differed from interior sand seas in geometry, extent, and facies. Stratigraphers have now observed these differences in eolian rocks. Erg margins may be grouped in five ways: (1) by associations with extradunal environments-coastal plain, lacustrine, periglacial, marine (tidal flat, coastal sabkha, beach, and lagoon), and arid alluvial (alluvial fan, fluvial, playa, inland sabkha); (2) by allocyclic controls-eustasy, plate tectonism, and climate; (3) by autocyclic controls-local tectonism, topography, vegetation, hydrology, structure, sediment source and supply, and wind regime; (4) by geographic position-upwind, downwind, and along-wind margins; and (5) by sedimentary facies-texture and architecture. In contrast with erg interiors, erg margins are characterized by smaller, less complex dune-forms related to thinner sand accumulation; elementary dune architecture; more vegetation and bioturbation; high occurrence of sand sheet, zibar, and serir facies; expansive, low-relief interdunes with widely distributed dunes; and a greater proportion of interbedded extradunal deposits. Some of the published studies on ancient eolian systems have identified erg margin facies that have been influences by marine and arid alluvial processes. Few reports have described lacustrine-eolian and periglacial-eolian interactions. This study is an attempt to organize known features of modern and ancient erg margins into a scheme based on erg margin controls.

  3. Materials Classification & Accelerated Property Predictions using Machine Learning

    SciTech Connect (OSTI)

    Pilania, Ghanshyam; Gubernatis, James E.; Lookman, Turab; Ramprasad, Rampi

    2015-06-10

    Examine reliability of ML methods for “small” data sets and potenial for new insights – role of excess effective born charge as a feature.

  4. Binary classification of items of interest in a repeatable process

    DOE Patents [OSTI]

    Abell, Jeffrey A; Spicer, John Patrick; Wincek, Michael Anthony; Wang, Hui; Chakraborty, Debejyo

    2015-01-06

    A system includes host and learning machines. Each machine has a processor in electrical communication with at least one sensor. Instructions for predicting a binary quality status of an item of interest during a repeatable process are recorded in memory. The binary quality status includes passing and failing binary classes. The learning machine receives signals from the at least one sensor and identifies candidate features. Features are extracted from the candidate features, each more predictive of the binary quality status. The extracted features are mapped to a dimensional space having a number of dimensions proportional to the number of extracted features. The dimensional space includes most of the passing class and excludes at least 90 percent of the failing class. Received signals are compared to the boundaries of the recorded dimensional space to predict, in real time, the binary quality status of a subsequent item of interest.

  5. SMART BRIDGE: A tool for estimating the military load classification...

    Office of Scientific and Technical Information (OSTI)

    Subject: 45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEFENSE; 99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; BRIDGES; STATIC LOADS; EXPERT ...

  6. THE CLASSIFICATION OF KEPLER B-STAR VARIABLES (Journal Article...

    Office of Scientific and Technical Information (OSTI)

    E-mail: jasonj@nmsu.edu 1 + Show Author Affiliations Department of Astronomy, New Mexico State University, P.O. Box 30001, MSC 4500, Las Cruces, NM 88003-8001 (United States) ...

  7. Object Classification at the Nearby Supernova Factory (Journal...

    Office of Scientific and Technical Information (OSTI)

    Nearby Supernova Factory Citation Details In-Document ... Report Number(s): LBNL-696E TRN: US200815%%72 DOE Contract Number: DE-AC02-05CH11231 Resource Type: Journal Article ...

  8. Modeling Personalized Email Prioritization: Classification-based and Regression-based Approaches

    SciTech Connect (OSTI)

    Yoo S.; Yang, Y.; Carbonell, J.

    2011-10-24

    Email overload, even after spam filtering, presents a serious productivity challenge for busy professionals and executives. One solution is automated prioritization of incoming emails to ensure the most important are read and processed quickly, while others are processed later as/if time permits in declining priority levels. This paper presents a study of machine learning approaches to email prioritization into discrete levels, comparing ordinal regression versus classier cascades. Given the ordinal nature of discrete email priority levels, SVM ordinal regression would be expected to perform well, but surprisingly a cascade of SVM classifiers significantly outperforms ordinal regression for email prioritization. In contrast, SVM regression performs well -- better than classifiers -- on selected UCI data sets. This unexpected performance inversion is analyzed and results are presented, providing core functionality for email prioritization systems.

  9. Bayesian probabilistic model for life prediction and fault mode classification of solid state luminaires

    SciTech Connect (OSTI)

    Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

    2014-06-22

    A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. Failure modes of the test population of the lamps have been studied to understand the failure mechanisms in 85°C/85%RH accelerated test. Results indicate that the dominant failure mechanism is the discoloration of the LED encapsulant inside the lamps which is the likely cause for the luminous flux degradation and the color shift. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. The α-λ plots have been used to evaluate the robustness of the proposed methodology. Results show that the predicted degradation for the lamps tracks the true degradation observed during 85°C/85%RH during accelerated life test fairly closely within the ±20% confidence bounds. Correlation of model prediction with experimental results indicates that the presented methodology allows the early identification of the onset of failure much prior to development of complete failure distributions and can be used for assessing the damage state of SSLs in fairly large deployments. It is expected that, the new prediction technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.

  10. Technical basis for classification of low-activity waste fraction from Hanford site tanks

    SciTech Connect (OSTI)

    Petersen, C.A.

    1996-09-20

    The overall objective of this report is to provide a technical basis to support a U.S. Nuclear Regulatory Commission determination to classify the low-activity waste from the Hanford Site single-shell and double-shell tanks as `incidental` wastes after removal of additional radionuclides and immobilization.The proposed processing method, in addition to the previous radionuclide removal efforts, will remove the largest practical amount of total site radioactivity, attributable to high-level waste, for disposal is a deep geologic repository. The remainder of the waste would be considered `incidental` waste and could be disposed onsite.

  11. The role of trace impurities in classification of in-core reactor components. Final report

    SciTech Connect (OSTI)

    Luksic, A.T.; Pauley, K.A.; Reid, B.d.

    1993-08-01

    Low-level radioactive waste is classified into three distinct categories under Title 10 of the Code of Federal Regulations Part 61 (10CFR61). These categories, Class A, B, and C, are determined by the concentrations of specified radionuclides, with Class C being the most restrictive. Waste which is determined to exceed the Class C limits is referred to as Greater Than Class C (GTCC) and is generally deemed to be unacceptable for disposal in a shallow land burial site. Under the Low-Level Waste Policy Act Amendments of 1985 (Public Law 99-240), the responsibility for disposal of waste classified as GTCC rests with the US government. To provide a better understanding of the elemental constituents that are present in nuclear fuel related materials, 41 samples of unirradiated materials used in the manufacture of fuel assembly hardware and nonfuel assembly components were obtained and analyzed. Particular emphasis was placed on evaluating the concentration of niobium in Zircaloy. The results of this work indicate that insignificant amounts of niobium are found in the current generation of Zircaloy. However, the reason for the inconsistency between the trace amounts of elemental niobium (<10 ppM) observed in the current analysis and the significant amounts (>100 ppM) that were observed in the previous analysis has not been identified.

  12. Protein-Folding Landscapes in Multi-Chain Systems Major Classification...

    Office of Scientific and Technical Information (OSTI)

    ... Average radius of gyration (per chain): single-chain (blue), two-chain (red), and four chain systems (green) as functions of temperature (lower right). Figure 3. Free-energy ...

  13. Technical basis for classification of low-activity waste fraction from Hanford site tanks

    SciTech Connect (OSTI)

    Petersen, C.A., Westinghouse Hanford

    1996-07-17

    The overall objective of this report is to provide a technical basis to support a U.S. Nuclear Regulatory Commission determination to classify the low-activity waste from the Hanford Site single-shell and double-shell tanks as `incidental` wastes after removal of additional radionuclides and immobilization.The proposed processing method, in addition to the previous radionuclide removal efforts, will remove the largest practical amount of total site radioactivity, attributable to high-level wastes, for disposal in a deep geologic repository. The remainder of the waste would be considered `incidental` waste and could be disposed onsite.

  14. Radioactive and mixed waste - risk as a basis for waste classification. Symposium proceedings No. 2

    SciTech Connect (OSTI)

    1995-06-21

    The management of risks from radioactive and chemical materials has been a major environmental concern in the United states for the past two or three decades. Risk management of these materials encompasses the remediation of past disposal practices as well as development of appropriate strategies and controls for current and future operations. This symposium is concerned primarily with low-level radioactive wastes and mixed wastes. Individual reports were processed separately for the Department of Energy databases.

  15. Automated Thermal Image Processing for Detection and Classification of Birds and Bats - FY2012 Annual Report

    SciTech Connect (OSTI)

    Duberstein, Corey A.; Matzner, Shari; Cullinan, Valerie I.; Virden, Daniel J.; Myers, Joshua R.; Maxwell, Adam R.

    2012-09-01

    Surveying wildlife at risk from offshore wind energy development is difficult and expensive. Infrared video can be used to record birds and bats that pass through the camera view, but it is also time consuming and expensive to review video and determine what was recorded. We proposed to conduct algorithm and software development to identify and to differentiate thermally detected targets of interest that would allow automated processing of thermal image data to enumerate birds, bats, and insects. During FY2012 we developed computer code within MATLAB to identify objects recorded in video and extract attribute information that describes the objects recorded. We tested the efficiency of track identification using observer-based counts of tracks within segments of sample video. We examined object attributes, modeled the effects of random variability on attributes, and produced data smoothing techniques to limit random variation within attribute data. We also began drafting and testing methodology to identify objects recorded on video. We also recorded approximately 10 hours of infrared video of various marine birds, passerine birds, and bats near the Pacific Northwest National Laboratory (PNNL) Marine Sciences Laboratory (MSL) at Sequim, Washington. A total of 6 hours of bird video was captured overlooking Sequim Bay over a series of weeks. An additional 2 hours of video of birds was also captured during two weeks overlooking Dungeness Bay within the Strait of Juan de Fuca. Bats and passerine birds (swallows) were also recorded at dusk on the MSL campus during nine evenings. An observer noted the identity of objects viewed through the camera concurrently with recording. These video files will provide the information necessary to produce and test software developed during FY2013. The annotation will also form the basis for creation of a method to reliably identify recorded objects.

  16. Classification of AB O 3 perovskite solids: a machine learning study

    SciTech Connect (OSTI)

    Pilania, G.; Balachandran, P. V.; Gubernatis, J. E.; Lookman, T.

    2015-07-23

    Here we explored the use of machine learning methods for classifying whether a particularABO3chemistry forms a perovskite or non-perovskite structured solid. Starting with three sets of feature pairs (the tolerance and octahedral factors, theAandBionic radii relative to the radius of O, and the bond valence distances between theAandBions from the O atoms), we used machine learning to create a hyper-dimensional partial dependency structure plot using all three feature pairs or any two of them. Doing so increased the accuracy of our predictions by 2–3 percentage points over using any one pair. We also included the Mendeleev numbers of theAandBatoms to this set of feature pairs. Moreover, doing this and using the capabilities of our machine learning algorithm, the gradient tree boosting classifier, enabled us to generate a new type of structure plot that has the simplicity of one based on using just the Mendeleev numbers, but with the added advantages of having a higher accuracy and providing a measure of likelihood of the predicted structure.

  17. Microsoft PowerPoint - Marchand_ARM_STM_2008_Poster_Classification...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    removes the need for most of the cloud parameterizations used in traditional GCMs. This new approach is frequently called a Multiscale Modeling Framework (MMF). Here we present a...

  18. Gas Chromatography Data Classification Based on Complex Coefficients of an Autoregressive Model

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Zhao, Weixiang; Morgan, Joshua T.; Davis, Cristina E.

    2008-01-01

    This paper introduces autoregressive (AR) modeling as a novel method to classify outputs from gas chromatography (GC). The inverse Fourier transformation was applied to the original sensor data, and then an AR model was applied to transform data to generate AR model complex coefficients. This series of coefficients effectively contains a compressed version of all of the information in the original GC signal output. We applied this method to chromatograms resulting from proliferating bacteria species grown in culture. Three types of neural networks were used to classify the AR coefficients: backward propagating neural network (BPNN), radial basis function-principal component analysismore » (RBF-PCA) approach, and radial basis function-partial least squares regression (RBF-PLSR) approach. This exploratory study demonstrates the feasibility of using complex root coefficient patterns to distinguish various classes of experimental data, such as those from the different bacteria species. This cognition approach also proved to be robust and potentially useful for freeing us from time alignment of GC signals.« less

  19. ASTEROSEISMIC CLASSIFICATION OF STELLAR POPULATIONS AMONG 13,000 RED GIANTS OBSERVED BY KEPLER

    SciTech Connect (OSTI)

    Stello, Dennis; Bedding, Timothy R.; Benomar, Othman; White, Timothy R.; Huber, Daniel; Bildsten, Lars; Paxton, Bill; Elsworth, Yvonne P.; Gilliland, Ronald L.; Mosser, Benoit

    2013-03-10

    Of the more than 150,000 targets followed by the Kepler Mission, about 10% were selected as red giants. Due to their high scientific value, in particular for Galaxy population studies and stellar structure and evolution, their Kepler light curves were made public in late 2011. More than 13,000 (over 85%) of these stars show intrinsic flux variability caused by solar-like oscillations making them ideal for large-scale asteroseismic investigations. We automatically extracted individual frequencies and measured the period spacings of the dipole modes in nearly every red giant. These measurements naturally classify the stars into various populations, such as the red giant branch, the low-mass (M/M{sub Sun} {approx}< 1.8) helium-core-burning red clump, and the higher-mass (M/M{sub Sun} {approx}> 1.8) secondary clump. The period spacings also reveal that a large fraction of the stars show rotationally induced frequency splittings. This sample of stars will undoubtedly provide an extremely valuable source for studying the stellar population in the direction of the Kepler field, in particular when combined with complementary spectroscopic surveys.

  20. Failure Mode Classification for Life Prediction Modeling of Solid-State Lighting

    SciTech Connect (OSTI)

    Sakalaukus, Peter Joseph

    2015-08-01

    Since the passing of the Energy Independence and Security Act of 2007, the U.S. government has mandated greater energy independence which has acted as a catalyst for accelerating and facilitating research efforts toward the development and deployment of market-driven solutions for energy-saving homes, buildings and manufacturing, as well as sustainable transportation and renewable electricity generation. As part of this effort, an emphasis toward advancing solid-state lighting technology through research, development, demonstration, and commercial applications is assisting in the phase out of the common incandescent light bulb, as well as developing a more economical lighting source that is less toxic than compact fluorescent lighting. This has led lighting manufacturers to pursue SSL technologies for a wide range of consumer lighting applications. An SSL luminaire’s lifetime can be characterized in terms of lumen maintenance life. Lumen maintenance or lumen depreciation is the percentage decrease in the relative luminous flux from that of the original, pristine luminous flux value. Lumen maintenance life is the estimated operating time, in hours, when the desired failure threshold is projected to be reached at normal operating conditions. One accepted failure threshold of SSL luminaires is lumen maintenance of 70% -- a 30% reduction in the light output of the luminaire. Currently, the only approved lighting standard that puts forth a recommendation for long-term luminous flux maintenance projections towards a specified failure threshold of an SSL luminaire is the IES TM-28-14 (TM28) standard. iii TM28 was derived as a means to compare luminaires that have been tested at different facilities, research labs or companies. TM28 recommends the use of the Arrhenius equation to determine SSL device specific reaction rates from thermally driven failure mechanisms used to characterize a single failure mode – the relative change in the luminous flux output or “light power” of the SSL luminaire. The use of the Arrhenius equation necessitates two different temperature conditions, 25°C and 45°C are suggested by TM28, to determine the SSL lamp specific activation energy. One principal issue with TM28 is the lack of additional stresses or parameters needed to characterize non-temperature dependent failure mechanisms. Another principal issue with TM28 is the assumption that lumen maintenance or lumen depreciation gives an adequate comparison between SSL luminaires. Additionally, TM28 has no process for the determination of acceleration factors or lifetime estimations. Currently, a literature gap exists for established accelerated test methods for SSL devices to assess quality, reliability and durability before being introduced into the marketplace. Furthermore, there is a need for Physics-of-Failure based approaches to understand the processes and mechanisms that induce failure for the assessment of SSL reliability in order to develop generalized acceleration factors that better represent SSL product lifetime. This and the deficiencies in TM28 validate the need behind the development of acceleration techniques to quantify SSL reliability under a variety of environmental conditions. The ability to assess damage accrual and investigate reliability of SSL components and systems is essential to understanding the life time of the SSL device itself. The methodologies developed in this work increases the understanding of SSL devices iv through the investigation of component and device reliability under a variety of accelerated test conditions. The approaches for suitable lifetime predictions through the development of novel generalized acceleration factors, as well as a prognostics and health management framework, will greatly reduce the time and effort needed to produce SSL acceleration factors for the development of lifetime predictions.

  1. DRAFT-DOE O 325.2, Position Management and Classification

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    The Order establishes Departmental requirements and responsibilities for classifying positions using the General Schedule (GS) and the Federal Wage System (FWS) standards.

  2. SO/sub 2/ dose-response sensitivity classification data for crops and natural vegetation species

    SciTech Connect (OSTI)

    Irving, P.M.; Ballou, S.W.

    1980-09-01

    Over the past several years studies have been made on the interaction of sulfur dioxide (SO/sub 2/) and vegetation by performing field research and by developing analytical procedures for applying field observation data to energy impact assessments. As a result of this work, numerous reports have been prepared on crop-pollutant interactions, such as dose-response data; on the applications of such data to screening approaches for identifying crops at risk; and on models that predict crop yield reductions from point source emissions of SO/sub 2/. Data that were used for these studies, such as the crop-at-risk screening procedure, are presented in this report. Maps are also presented that show the national distribution of SO/sub 2/-sensitive crops and natural vegetation.

  3. NEC Hazardous classification and compliance regarding the surface moisture monitor measurement system

    SciTech Connect (OSTI)

    Bussell, J.H., WHC

    1996-06-12

    The National Electrical Code, NFPA 70, and National Fire Protection Association requirements for use of Surface Moisture Monitor Systems in classified locations are discussed. The design and configuration of the surface moisture monitor are analyzed with respect to how they comply with requirements of the National Electrical Code requirements, articles 500-504.

  4. On exact statistics and classification of ergodic systems of integer dimension

    SciTech Connect (OSTI)

    Guralnik, Zachary Guralnik, Gerald; Pehlevan, Cengiz

    2014-06-01

    We describe classes of ergodic dynamical systems for which some statistical properties are known exactly. These systems have integer dimension, are not globally dissipative, and are defined by a probability density and a two-form. This definition generalizes the construction of Hamiltonian systems by a Hamiltonian and a symplectic form. Some low dimensional examples are given, as well as a discretized field theory with a large number of degrees of freedom and a local nearest neighbor interaction. We also evaluate unequal-time correlations of these systems without direct numerical simulation, by Pad approximants of a short-time expansion. We briefly speculate on the possibility of constructing chaotic dynamical systems with non-integer dimension and exactly known statistics. In this case there is no probability density, suggesting an alternative construction in terms of a Hopf characteristic function and a two-form.

  5. Protein-Folding Landscapes in Multi-Chain Systems Major Classification...

    Office of Scientific and Technical Information (OSTI)

    ... The twelve beads listed in Table I, and shown within the context of the native state in ... A decrease in the entropy gain is indeed observed in our model upon increasing the number ...

  6. Classification of AB O 3 perovskite solids: a machine learning study

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Pilania, G.; Balachandran, P. V.; Gubernatis, J. E.; Lookman, T.

    2015-07-23

    Here we explored the use of machine learning methods for classifying whether a particularABO3chemistry forms a perovskite or non-perovskite structured solid. Starting with three sets of feature pairs (the tolerance and octahedral factors, theAandBionic radii relative to the radius of O, and the bond valence distances between theAandBions from the O atoms), we used machine learning to create a hyper-dimensional partial dependency structure plot using all three feature pairs or any two of them. Doing so increased the accuracy of our predictions by 2–3 percentage points over using any one pair. We also included the Mendeleev numbers of theAandBatoms tomore » this set of feature pairs. Moreover, doing this and using the capabilities of our machine learning algorithm, the gradient tree boosting classifier, enabled us to generate a new type of structure plot that has the simplicity of one based on using just the Mendeleev numbers, but with the added advantages of having a higher accuracy and providing a measure of likelihood of the predicted structure.« less

  7. Reconstruction of chaotic saddles by classification of unstable periodic orbits: Kuramoto-Sivashinsky equation

    SciTech Connect (OSTI)

    Saiki, Yoshitaka; Yamada, Michio; Chian, Abraham C.-L.; Miranda, Rodrigo A.; Rempel, Erico L.

    2015-10-15

    The unstable periodic orbits (UPOs) embedded in a chaotic attractor after an attractor merging crisis (MC) are classified into three subsets, and employed to reconstruct chaotic saddles in the Kuramoto-Sivashinsky equation. It is shown that in the post-MC regime, the two chaotic saddles evolved from the two coexisting chaotic attractors before crisis can be reconstructed from the UPOs embedded in the pre-MC chaotic attractors. The reconstruction also involves the detection of the mediating UPO responsible for the crisis, and the UPOs created after crisis that fill the gap regions of the chaotic saddles. We show that the gap UPOs originate from saddle-node, period-doubling, and pitchfork bifurcations inside the periodic windows in the post-MC chaotic region of the bifurcation diagram. The chaotic attractor in the post-MC regime is found to be the closure of gap UPOs.

  8. Life Prediction and Classification of Failure Modes in Solid State Luminaires Using Bayesian Probabilistic Models

    SciTech Connect (OSTI)

    Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

    2014-05-27

    A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. It is expected that, the new test technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.

  9. Switchgrass (Panicum virgatum L.) Intraspecific Variation and Thermotolerance Classification Using in Vitro Seed Germination Assay

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Seepaul, Ramdeo; Macoon, Bisoondat; Reddy, K. Raja; Baldwin, Brian

    2011-06-01

    Cardinal temperatures for plant processes have been used for thermotolerance screening of genotypes, geoclimatic adaptability determination and phenological prediction. Current simulation models for switchgrass (Panicum virgatum L.) utilize single cardinal temperatures across genotypes for both vegetative and reproductive processes although in-tra-specific variation exists among genotypes. An experiment was conducted to estimate the cardinal temperatures for seed germination of 14 diverse switchgrass genotypes and to classify genotypes for temperature tolerance. Stratified seeds of each genotype were germinated at eight constant temperatures from 10 °C to 45 °C under a constant light intensity of 35 μmol m-2s-1 for 12 hd-1. Germination wasmore » recorded at 6-h intervals in all treatments. Maximum seed germination (MSG) and germination rate (GR), estimated by fitting Sigmoidal function to germination-time series data, varied among genotypes. Quadratic and bilinear models best described the MSG and GR responses to temperature, respectively. The mean cardinal temperatures, Tmin, Topt, and Tmax, were 8.1, 26.6, and 45.1 °C for MSG and 11.1, 33.1, and 46.0 °C for GR, respectively. Cardinal temperatures for MSG and GR; however, varied significantly among genotypes. Genotypes were classified as sensitive (Cave-in-Rock, Dacotah, Expresso, Forestburg˜, Kanlow, ˜Sunburst, Trailblazer, and ˜Tusca™), intermediate (˜Alamo, Blackwell, Carthage, ˜Shawnee™, and Shelter™) and tolerant (˜Summer) to high temperature based on cumulative temperature response index (CTRI) estimated by summing individual response indices estimated from the MSG and GR cardinal temperatures. Similarly, genotypes were also classified as sensitive (Alamo, Blackwell, Carthage, Dacotah, Shawnee, Shelter and Summer), moderately sensitive (Cave-in-rock, Forestburg, Kanlow, Sunburst, and Tusca), moderately tolerant (Trailblazer), and tolerant (Expresso) to low temperatures. The cardinal temperature estimates would be useful to improve switchgrass models for field applications. Additionally, the identified cold- and heat-tolerant genotypes can be selected for niche environments and in switchgrass breeding programs to develop new genotypes for low and high temperature environments.« less

  10. Automatic Generation of Data Types for Classification of Deep Web Sources

    SciTech Connect (OSTI)

    Ngu, A H; Buttler, D J; Critchlow, T J

    2005-02-14

    A Service Class Description (SCD) is an effective meta-data based approach for discovering Deep Web sources whose data exhibit some regular patterns. However, it is tedious and error prone to create an SCD description manually. Moreover, a manually created SCD is not adaptive to the frequent changes of Web sources. It requires its creator to identify all the possible input and output types of a service a priori. In many domains, it is impossible to exhaustively list all the possible input and output data types of a source in advance. In this paper, we describe machine learning approaches for automatic generation of the data types of an SCD. We propose two different approaches for learning data types of a class of Web sources. The Brute-Force Learner is able to generate data types that can achieve high recall, but with low precision. The Clustering-based Learner generates data types that have a high precision rate, but with a lower recall rate. We demonstrate the feasibility of these two learning-based solutions for automatic generation of data types for citation Web sources and presented a quantitative evaluation of these two solutions.

  11. What happens to Petrov classification, on horizons of axisymmetric dirty black holes

    SciTech Connect (OSTI)

    Tanatarov, I. V.; Zaslavskii, O. B.

    2014-02-15

    We consider axisymmetric stationary dirty black holes with regular non-extremal or extremal horizons, and compute their on-horizon Petrov types. The Petrov type (PT) in the frame of the observer crossing the horizon can be different from that formally obtained in the usual (but singular in the horizon limit) frame of an observer on a circular orbit. We call this entity the boosted Petrov type (BPT), as the corresponding frame is obtained by a singular boost from the regular one. The PT off-horizon can be more general than PT on-horizon and that can be more general than the BPT on horizon. This is valid for all regular metrics, irrespective of the extremality of the horizon. We analyze and classify the possible relations between the three characteristics and discuss the nature and features of the underlying singular boost. The three Petrov types can be the same only for space-times of PT D and O off-horizon. The mutual alignment of principal null directions and the generator in the vicinity of the horizon is studied in detail. As an example, we also analyze a special class of metrics with utra-extremal horizons (for which the regularity conditions look different from the general case) and compare their off-horizon and on-horizon algebraic structure in both frames.

  12. A review on biomass classification and composition, cofiring issues and pretreatment methods

    SciTech Connect (OSTI)

    Jaya Shankar Tumuluru; Shahab Sokhansanj; Christopher T. Wright; Richard D. Boardman

    2011-08-01

    Presently around the globe there is a significant interest in using biomass for power generation as power generation from coal continues to raise environmental concerns. Biomass alone can be used for generation of power which can bring lot of environmental benefits. However the constraints of using biomass alone can include high investments costs for biomass feed systems and also uncertainty in the security of the feedstock supply due to seasonal variations and in most of the countries biomass is dispersed and the infrastructure for biomass supply is not well established. Alternatively cofiring biomass along with coal offer advantages like (a) reducing the issues related to biomass quality and buffers the system when there is insufficient feedstock quantity and (b) costs of adapting the existing coal power plants will be lower than building new systems dedicated only to biomass. However with the above said advantages there exists some technical constrains including low heating and energy density values, low bulk density, lower grindability index, higher moisture and ash content to successfully cofire biomass with coal. In order to successfully cofire biomass with coal, biomass feedstock specifications need to be established to direct pretreatment options that may include increasing the energy density, bulk density, stability during storage and grindability. Impacts on particle transport systems, flame stability, pollutant formation and boiler tube fouling/corrosion must also be minimized by setting feedstock specifications including composition and blend ratios if necessary. Some of these limitations can be overcome by using pretreatment methods. This paper discusses the impact of feedstock pretreatment methods like sizing, baling, pelletizing, briquetting, washing/leaching, torrefaction, torrefaction and pelletization and steam explosion in attainment of optimum feedstock characteristics to successfully cofire biomass with coal.

  13. Geochemistry of Bolivian salars, Lipez, southern Altiplano: Origin of solutes and brine evolution

    SciTech Connect (OSTI)

    Risacher, F. ); Fritz, B. )

    1991-03-01

    This paper focuses on poorly understood processes related to saline lakes, or salars, of the southern Bolivian Altiplano. A morphologic classification system is described, and the origin of solutes in the inflow waters is discussed. Next, the actual chemical evolution of these inflow waters is compared with their theoretical evolution based on thermodynamic equilibria. The water chemistry of a specific sequence of evaporating waters is then scrutinized to determine which processes are responsible for a significant discrepancy which is apparent between the measured and the calculated evolution.

  14. SPECTRAL CLASSIFICATION OF GALAXIES AT 0.5 {<=} z {<=} 1 IN THE CDFS: THE ARTIFICIAL NEURAL NETWORK APPROACH

    SciTech Connect (OSTI)

    Teimoorinia, H.

    2012-12-01

    The aim of this work is to combine spectral energy distribution (SED) fitting with artificial neural network techniques to assign spectral characteristics to a sample of galaxies at 0.5 < z < 1. The sample is selected from the spectroscopic campaign of the ESO/GOODS-South field, with 142 sources having photometric data from the GOODS-MUSIC catalog covering bands between {approx}0.4 and 24 {mu}m in 10-13 filters. We use the CIGALE code to fit photometric data to Maraston's synthesis spectra to derive mass, specific star formation rate, and age, as well as the best SED of the galaxies. We use the spectral models presented by Kinney et al. as targets in the wavelength interval {approx}1200-7500 A. Then a series of neural networks are trained, with average performance {approx}90%, to classify the best SED in a supervised manner. We consider the effects of the prominent features of the best SED on the performance of the trained networks and also test networks on the galaxy spectra of Coleman et al., which have a lower resolution than the target models. In this way, we conclude that the trained networks take into account all the features of the spectra simultaneously. Using the method, 105 out of 142 galaxies of the sample are classified with high significance. The locus of the classified galaxies in the three graphs of the physical parameters of mass, age, and specific star formation rate appears consistent with the morphological characteristics of the galaxies.

  15. SHORT VERSUS LONG AND COLLAPSARS VERSUS NON-COLLAPSARS: A QUANTITATIVE CLASSIFICATION OF GAMMA-RAY BURSTS

    SciTech Connect (OSTI)

    Bromberg, Omer; Piran, Tsvi; Sari, Re'em [Racah Institute of Physics, The Hebrew University, 91904 Jerusalem (Israel)] [Racah Institute of Physics, The Hebrew University, 91904 Jerusalem (Israel); Nakar, Ehud [The Raymond and Berverly Sackler School of Physics and Astronomy, Tel Aviv University, 69978 Tel Aviv (Israel)] [The Raymond and Berverly Sackler School of Physics and Astronomy, Tel Aviv University, 69978 Tel Aviv (Israel)

    2013-02-20

    Gamma-ray bursts (GRBs) are traditionally divided into long and short according to their durations (lg2 s). It was generally believed that this reflects a different physical origin: collapsars (long) and non-collapsars (short). We have recently shown that the duration distribution of collapsars is flat, namely, independent of the duration, at short durations. Using this model for the distribution of Collapsars we determine the duration distribution of non-Collapsars and estimate the probability that a burst with a given duration (and hardness) is a Collapsar or not. We find that this probability depends strongly on the spectral window of the observing detector. While the commonly used limit of 2 s is conservative and suitable for BATSE bursts, 40% of Swift's bursts shorter than 2 s are Collapsars and the division lg0.8 s is more suitable for Swift. We find that the duration overlap of the two populations is very large. On the one hand there is a non-negligible fraction of non-Collapsars longer than 10 s, while on the other hand even bursts shorter than 0.5 s in the Swift sample have a non-negligible probability to be Collapsars. Our results enable the construction of non-Collapsar samples while controlling the Collapsar contamination. They also highlight that no firm conclusions can be drawn based on a single burst and they have numerous implications concerning previous studies of non-Collapsar properties that were based on the current significantly contaminated Swift samples of localized short GRBs. Specifically (1) all known short bursts with z > 1 are most likely Collapsars; (2) the only short burst with a clear jet break is most likely a Collapsar, indicating our lack of knowledge concerning non-Collapsar beaming; and (3) the existence of non-Collapsars with durations up to 10 s imposes new challenges to non-Collapsar models.

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

    Gasoline and Diesel Fuel Update (EIA)

    1 Fuel Consumption, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: Energy Sources; Unit: Physical Units or Btu. Coke Net Residual Distillate Natural Gas(d) LPG and Coal and Breeze NAICS Total Electricity(b) Fuel Oil Fuel Oil(c) (billion NGL(e) (million (million Other(f) Code(a) Subsector and Industry (trillion Btu) (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) short tons) (trillion Btu) Total United States 311 Food 1,158 75,407 2 4 563 1 8 * 99

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

    Gasoline and Diesel Fuel Update (EIA)

    Imported Refiner Acquisition Cost of Crude Oil, Projected vs. Actual Projected Price in Constant Dollars (constant dollars per barrel in "dollar year" specific to each AEO) AEO $ Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 1992 16.69 16.43 16.99 17.66 18.28 19.06 19.89 20.72 21.65 22.61 23.51 24.29 24.90 25.60 26.30 27.00 27.64 28.16 AEO 1995 1993 14.90 16.41 16.90 17.45 18.00 18.53 19.13 19.65 20.16 20.63 21.08

  18. A NEW DISCRIMINATOR FOR GAMMA-RAY BURST CLASSIFICATION: THE E{sub peak}-FLUENCE ENERGY RATIO

    SciTech Connect (OSTI)

    Goldstein, Adam; Preece, Robert D.; Briggs, Michael S.

    2010-10-01

    Using the derived gamma-ray burst (GRB) E{sub peak} and fluences from the complete BATSE 5B Spectral Catalog, we study the ensemble characteristics of the E{sub peak}-fluence relation for GRBs. This relation appears to be a physically meaningful and insightful fundamental discriminator between long and short bursts. We discuss the results of the lower limit test of the E{sub peak}-E{sub iso} relations in the E{sub peak}-fluence plane for Burst And Transient Source Experiment bursts with no observed redshift. Our results confirm the presence of two GRB classes as well as heavily suggesting two different GRB progenitor types.

  19. Rapid quantification and taxonomic classification of environmentalDNA from both prokaryotic and eukaryotic origins using a microarray

    SciTech Connect (OSTI)

    DeSantis, Todd Z.; Stone, Carol E.; Murray, Sonya R.; Moberg,Jordan P.; Andersen, Gary L.

    2005-02-22

    A microarray has been designed using 62,358 probes matched to both prokaryotic and eukaryotic small-subunit ribosomal RNA genes. The array categorized environmental DNA to specific phylogenetic clusters in under 9 h. To a background of DNA generated from natural outdoor aerosols, known quantities of rRNA gene copies from distinct organisms were added producing corresponding hybridization intensity scores that correlated well with their concentrations (r=0.917). Reproducible differences in microbial community composition were observed by altering the genomic DNA extraction method. Notably, gentle extractions produced peak intensities for Mycoplasmatales and Burkholderiales, whereas a vigorous disruption produced peak intensities for Vibrionales,Clostridiales, and Bacillales.

  20. Classification of Multiple Types of Organic Carbon Composition in Atmospheric Particles by Scanning Transmission X-Ray Microscopy Analysis

    SciTech Connect (OSTI)

    Kilcoyne, Arthur L; Takahama, S.; Gilardoni, S.; Russell, L.M.; Kilcoyne, A.L.D.

    2007-05-16

    A scanning transmission X-ray microscope at the Lawrence Berkeley National Laboratory is used to measure organic functional group abundance and morphology of atmospheric aerosols. We present a summary of spectra, sizes, and shapes observed in 595 particles that were collected and analyzed between 2000 and 2006. These particles ranged between 0.1 and 12 mm and represent aerosols found in a large range of geographical areas, altitudes, and times. They include samples from seven different field campaigns: PELTI, ACE-ASIA, DYCOMS II, Princeton, MILAGRO (urban), MILAGRO (C-130), and INTEX-B. At least 14 different classes of organic particles show different types of spectroscopic signatures. Different particle types are found within the same region while the same particle types are also found in different geographical domains. Particles chemically resembling black carbon, humic-like aerosols, pine ultisol, and secondary or processed aerosol have been identified from functional group abundance and comparison of spectra with those published in the literature.

  1. Low-level radioactive waste from nuclear power generating stations: Characterization, classification and assessment of activated metals and waste streams

    SciTech Connect (OSTI)

    Thomas, V.W.; Robertson, D.E.; Thomas, C.W.

    1993-02-01

    Since the enactment of 10 CFR Part 61, additional difficult-to-measure long-lived radionuclides, not specified in Tables 1 2 of Part 61, have been identified (e.g., {sup 108m}Ag, {sup 93}Mo, {sup 36}Cl, {sup 10}Be, {sup 113m}Cd, {sup 121m}Sn, {sup 126}Sn, {sup 93m}Nb) that may be of concern in certain types of waste. These nuclides are primarily associated with activated metal and perhaps other nuclear power low-level waste (LLW) being sent to disposal facilities. The concentration of a radionuclide in waste materials is normally determined by direct measurement or by indirect calculational methods, such as using a scaling factor to relate inferred concentration of a difficult-to-measure radionuclide to another that is easily measured. The total disposal site inventory of certain difficult-to-measure radionuclides (e.g., {sup 14}C, {sup 129}I, and {sup 99}Tc) often control the total quantities of radioactive waste permitted in LLW burial facilities. Overly conservative scaling factors based on lower limits of detection (LLD), often used in the nuclear power industry to estimate these controlling nuclides, could lead to premature closure of a disposal facility. Samples of LLW (Class B and C activated metals [AM] and other waste streams) are being collected from operating nuclear power stations and analyzed for radionuclides covered in 10 CFR Part 61 and the additional difficult-to-measure radionuclides. This analysis will enhance the NRC`s understanding of the distribution and projected quantities of radionuclides within AM and LLW streams from commercial nuclear power stations. This research will also provide radiological characterization of AM specimens for others to use in leach-rate and lysimeter experiments to determine nuclide releases and subsequent movement in natural soil environments.

  2. Low-level radioactive waste from nuclear power generating stations: Characterization, classification and assessment of activated metals and waste streams

    SciTech Connect (OSTI)

    Thomas, V.W.; Robertson, D.E.; Thomas, C.W.

    1993-02-01

    Since the enactment of 10 CFR Part 61, additional difficult-to-measure long-lived radionuclides, not specified in Tables 1 2 of Part 61, have been identified (e.g., [sup 108m]Ag, [sup 93]Mo, [sup 36]Cl, [sup 10]Be, [sup 113m]Cd, [sup 121m]Sn, [sup 126]Sn, [sup 93m]Nb) that may be of concern in certain types of waste. These nuclides are primarily associated with activated metal and perhaps other nuclear power low-level waste (LLW) being sent to disposal facilities. The concentration of a radionuclide in waste materials is normally determined by direct measurement or by indirect calculational methods, such as using a scaling factor to relate inferred concentration of a difficult-to-measure radionuclide to another that is easily measured. The total disposal site inventory of certain difficult-to-measure radionuclides (e.g., [sup 14]C, [sup 129]I, and [sup 99]Tc) often control the total quantities of radioactive waste permitted in LLW burial facilities. Overly conservative scaling factors based on lower limits of detection (LLD), often used in the nuclear power industry to estimate these controlling nuclides, could lead to premature closure of a disposal facility. Samples of LLW (Class B and C activated metals [AM] and other waste streams) are being collected from operating nuclear power stations and analyzed for radionuclides covered in 10 CFR Part 61 and the additional difficult-to-measure radionuclides. This analysis will enhance the NRC's understanding of the distribution and projected quantities of radionuclides within AM and LLW streams from commercial nuclear power stations. This research will also provide radiological characterization of AM specimens for others to use in leach-rate and lysimeter experiments to determine nuclide releases and subsequent movement in natural soil environments.

  3. Twentieth workshop on geothermal reservoir engineering: Proceedings

    SciTech Connect (OSTI)

    1995-01-26

    PREFACE The Twentieth Workshop on Geothermal Reservoir Engineering, dedicated to the memory of Professor Hank Ramey, was held at Stanford University on January 24-26, 1995. There were ninety-five registered participants. Participants came from six foreign countries: Japan, Mexico, England, Italy, New Zealand and Iceland. The performance of many geothermal reservoirs outside the United States was described in several of the papers. Professor Roland N. Horne opened the meeting and welcomed visitors to the campus. The key note speaker was Marshall Reed, who gave a brief overview of the Department of Energy's current plan. Thirty-two papers were presented in the technical sessions of the workshop. Technical papers were organized into eleven sessions concerning: field development, modeling, well tesubore, injection, geoscience, geochemistry and field operations. Session chairmen were major contributors to the workshop, and we thank: Ben Barker, Bob Fournier, Mark Walters, John Counsil, Marcelo Lippmann, Keshav Goyal, Joel Renner and Mike Shook. In addition to the technical sessions, a panel discussion was held on ''What have we learned in 20 years?'' Panel speakers included Patrick Muffler, George Frye, Alfred Truesdell and John Pritchett. The subject was further discussed by Subir Sanyal, who gave the post-dinner speech at the banquet. The Workshop was organized by the Stanford Geothermal Program faculty, staff, and graduate students. We wish to thank our students who operated the audiovisual equipment. Shaun D. Fitzgerald Program Manager

  4. Status report: A hydrologic framework for the Oak Ridge Reservation

    SciTech Connect (OSTI)

    Solomon, D.K.; Toran, L.E.; Dreier, R.B.; Moore, G.K.; McMaster, W.M.

    1992-05-01

    This first status report on the Hydrologic Studies Task of the Oak Ridge Reservation Hydrology and Geology Study (ORRHAGS) revises earlier concepts of subsurface hydrology and hydrogeochemistry of the ORR. A new classification of hydrogeologic units is given, as well as new interpretations of the gydrogeologic properties and processes that influence contaminant migration. The conceptual hydrologic framework introduced in this report is based primarily on reinterpretations of data acquired during earlier hydrologic investigations of waste areas at and near the three US Department of Energy Oak Ridge (DOE-OR) plant facilities. In addition to describing and interpreting the properties and processes of the groundwater systems as they are presently understood, this report describes surface water-subsurface water relations, influences on contaminant migration,and implications to environmental restoration, environmental monitoring, and waste management.

  5. Characterizing the DNA damage response by cell tracking algorithms and cell features classification using high-content time-lapse analysis

    SciTech Connect (OSTI)

    Georgescu, Walter; Osseiran, Alma; Rojec, Maria; Liu, Yueyong; Bombrun, Maxime; Tang, Jonathan; Costes, Sylvain V.; Huen, Michael Shing-Yan

    2015-06-24

    Traditionally, the kinetics of DNA repair have been estimated using immunocytochemistry by labeling proteins involved in the DNA damage response (DDR) with fluorescent markers in a fixed cell assay. However, detailed knowledge of DDR dynamics across multiple cell generations cannot be obtained using a limited number of fixed cell time-points. Here we report on the dynamics of 53BP1 radiation induced foci (RIF) across multiple cell generations using live cell imaging of non-malignant human mammary epithelial cells (MCF10A) expressing histone H2B-GFP and the DNA repair protein 53BP1-mCherry. Using automatic extraction of RIF imaging features and linear programming techniques, we were able to characterize detailed RIF kinetics for 24 hours before and 24 hours after exposure to low and high doses of ionizing radiation. High-content-analysis at the single cell level over hundreds of cells allows us to quantify precisely the dose dependence of 53BP1 protein production, RIF nuclear localization and RIF movement after exposure to X-ray. Using elastic registration techniques based on the nuclear pattern of individual cells, we could describe the motion of individual RIF precisely within the nucleus. We show that DNA repair occurs in a limited number of large domains, within which multiple small RIFs form, merge and/or resolve with random motion following normal diffusion law. Large foci formation is shown to be mainly happening through the merging of smaller RIF rather than through growth of an individual focus. We estimate repair domain sizes of 7.5 to 11 µm2 with a maximum number of ~15 domains per MCF10A cell. This work also highlights DDR which are specific to doses larger than 1 Gy such as rapid 53BP1 protein increase in the nucleus and foci diffusion rates that are significantly faster than for spontaneous foci movement. We hypothesize that RIF merging reflects a "stressed" DNA repair process that has been taken outside physiological conditions when too many DSB occur at once. High doses of ionizing radiation lead to RIF merging into repair domains which in turn increases DSB proximity and misrepair. Furthermore, such finding may therefore be critical to explain the supralinear dose dependence for chromosomal rearrangement and cell death measured after exposure to ionizing radiation.

  6. e/a classification of Hume–Rothery Rhombic Triacontahedron-type approximants based on all-electron density functional theory calculations

    SciTech Connect (OSTI)

    Mizutani, U; Inukai, M; Sato, H; Zijlstra, E S; Lin, Q

    2014-05-16

    There are three key electronic parameters in elucidating the physics behind the Hume–Rothery electron concentration rule: the square of the Fermi diameter (2kF)2, the square of the critical reciprocal lattice vector and the electron concentration parameter or the number of itinerant electrons per atom e/a. We have reliably determined these three parameters for 10 Rhombic Triacontahedron-type 2/1–2/1–2/1 (N = 680) and 1/1–1/1–1/1 (N = 160–162) approximants by making full use of the full-potential linearized augmented plane wave-Fourier band calculations based on all-electron density-functional theory. We revealed that the 2/1–2/1–2/1 approximants Al13Mg27Zn45 and Na27Au27Ga31 belong to two different sub-groups classified in terms of equal to 126 and 109 and could explain why they take different e/a values of 2.13 and 1.76, respectively. Among eight 1/1–1/1–1/1 approximants Al3Mg4Zn3, Al9Mg8Ag3, Al21Li13Cu6, Ga21Li13Cu6, Na26Au24Ga30, Na26Au37Ge18, Na26Au37Sn18 and Na26Cd40Pb6, the first two, the second two and the last four compounds were classified into three sub-groups with = 50, 46 and 42; and were claimed to obey the e/a = 2.30, 2.10–2.15 and 1.70–1.80 rules, respectively.

  7. Characterizing the DNA damage response by cell tracking algorithms and cell features classification using high-content time-lapse analysis

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Georgescu, Walter; Osseiran, Alma; Rojec, Maria; Liu, Yueyong; Bombrun, Maxime; Tang, Jonathan; Costes, Sylvain V.; Huen, Michael Shing-Yan

    2015-06-24

    Traditionally, the kinetics of DNA repair have been estimated using immunocytochemistry by labeling proteins involved in the DNA damage response (DDR) with fluorescent markers in a fixed cell assay. However, detailed knowledge of DDR dynamics across multiple cell generations cannot be obtained using a limited number of fixed cell time-points. Here we report on the dynamics of 53BP1 radiation induced foci (RIF) across multiple cell generations using live cell imaging of non-malignant human mammary epithelial cells (MCF10A) expressing histone H2B-GFP and the DNA repair protein 53BP1-mCherry. Using automatic extraction of RIF imaging features and linear programming techniques, we were ablemore » to characterize detailed RIF kinetics for 24 hours before and 24 hours after exposure to low and high doses of ionizing radiation. High-content-analysis at the single cell level over hundreds of cells allows us to quantify precisely the dose dependence of 53BP1 protein production, RIF nuclear localization and RIF movement after exposure to X-ray. Using elastic registration techniques based on the nuclear pattern of individual cells, we could describe the motion of individual RIF precisely within the nucleus. We show that DNA repair occurs in a limited number of large domains, within which multiple small RIFs form, merge and/or resolve with random motion following normal diffusion law. Large foci formation is shown to be mainly happening through the merging of smaller RIF rather than through growth of an individual focus. We estimate repair domain sizes of 7.5 to 11 µm2 with a maximum number of ~15 domains per MCF10A cell. This work also highlights DDR which are specific to doses larger than 1 Gy such as rapid 53BP1 protein increase in the nucleus and foci diffusion rates that are significantly faster than for spontaneous foci movement. We hypothesize that RIF merging reflects a "stressed" DNA repair process that has been taken outside physiological conditions when too many DSB occur at once. High doses of ionizing radiation lead to RIF merging into repair domains which in turn increases DSB proximity and misrepair. Furthermore, such finding may therefore be critical to explain the supralinear dose dependence for chromosomal rearrangement and cell death measured after exposure to ionizing radiation.« less

  8. Twenty-first workshop on geothermal reservoir engineering: Proceedings

    SciTech Connect (OSTI)

    1996-01-26

    PREFACE The Twenty-First Workshop on Geothermal Reservoir Engineering was held at the Holiday Inn, Palo Alto on January 22-24, 1996. There were one-hundred fifty-five registered participants. Participants came from twenty foreign countries: Argentina, Austria, Canada, Costa Rica, El Salvador, France, Iceland, Indonesia, Italy, Japan, Mexico, The Netherlands, New Zealand, Nicaragua, the Philippines, Romania, Russia, Switzerland, Turkey and the UK. The performance of many geothermal reservoirs outside the United States was described in several of the papers. Professor Roland N. Horne opened the meeting and welcomed visitors. The key note speaker was Marshall Reed, who gave a brief overview of the Department of Energy's current plan. Sixty-six papers were presented in the technical sessions of the workshop. Technical papers were organized into twenty sessions concerning: reservoir assessment, modeling, geology/geochemistry, fracture modeling hot dry rock, geoscience, low enthalpy, injection, well testing, drilling, adsorption and stimulation. Session chairmen were major contributors to the workshop, and we thank: Ben Barker, Bobbie Bishop-Gollan, Tom Box, Jim Combs, John Counsil, Sabodh Garg, Malcolm Grant, Marcel0 Lippmann, Jim Lovekin, John Pritchett, Marshall Reed, Joel Renner, Subir Sanyal, Mike Shook, Alfred Truesdell and Ken Williamson. Jim Lovekin gave the post-dinner speech at the banquet and highlighted the exciting developments in the geothermal field which are taking place worldwide. The Workshop was organized by the Stanford Geothermal Program faculty, staff, and graduate students. We wish to thank our students who operated the audiovisual equipment. Shaun D. Fitzgerald Program Manager.

  9. September 2015 Most Viewed Documents for National Defense | OSTI...

    Office of Scientific and Technical Information (OSTI)

    SMART BRIDGE: A tool for estimating the military load classification of bridges using ... Smart bridge: a tool for estimating the military load classification of bridges Van ...

  10. Search for: All records | SciTech Connect

    Office of Scientific and Technical Information (OSTI)

    to use automatic classification to identify some of the astronomical sources. The data mining technique of supervised classification is suitable for this problem. Here, we present...

  11. file://C:\\Documents and Settings\\bh5\\My Documents\\Energy Effici

    Gasoline and Diesel Fuel Update (EIA)

    Classification System (NAICS) has replaced the Standard Industrial Classification (SIC) system. NAICS 331111 includes steel works, blast furnaces (including coke ovens), and...

  12. WHO Statistical Information System (WHOSIS) | Open Energy Information

    Open Energy Info (EERE)

    Classification of Diseases (ICD-10), International Classification of Impairments, Disabilities and Handicaps (ICIDH) Links to other sources of health-related statistical...

  13. Search for: All records | SciTech Connect

    Office of Scientific and Technical Information (OSTI)

    TN (United States) DOE HSS Office of Classification, Office of Document Reviews DOE ... CO (United States) HSS Office of Classification Hanford Site (HNF), Richland, WA ...

  14. Evolutionary conservation of sequence and secondary structures...

    Office of Scientific and Technical Information (OSTI)

    We also show that the repeat-based classification corresponds to, and expands upon, a previously reported CAS gene-based classification including specific relationships between ...

  15. Integration of hyperspectral imagery and biosensors for biological...

    Office of Scientific and Technical Information (OSTI)

    facility classification Citation Details In-Document Search Title: Integration of hyperspectral imagery and biosensors for biological and chemical facility classification Authors: ...

  16. Integration of hyperspectral imagery and biosensors for biological...

    Office of Scientific and Technical Information (OSTI)

    facility classification Citation Details In-Document Search Title: Integration of hyperspectral imagery and biosensors for biological and chemical facility classification You ...

  17. Integration of Hyperspectral Imagery and Biosensors for Biological...

    Office of Scientific and Technical Information (OSTI)

    Facility Classification Citation Details In-Document Search Title: Integration of Hyperspectral Imagery and Biosensors for Biological and Chemical Facility Classification You ...

  18. Student Spotlight

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Project Name: Image Analysis Classification algorithm to automatically classify NIF optics damage sites Project Description: Develop a classification system of potential damage...

  19. Ninth workshop on geothermal reservoir engineering: Proceedings

    SciTech Connect (OSTI)

    Ramey, H.J. Jr.; Kruger, P.; Miller, F.G.; Horne, R.N.; Brigham, W.E.; Gudmundsson, J.S.

    1983-12-15

    (Reservoir Chemistry), Greg Raasch (Production), Manny Nathenson (Injection), Susan Petty (Injection), Subir Sanyal (Simulation), Marty Molloy (Petrothermal), and Allen Moench (Reservoir Physics). The Workshop was organized by the Stanford Geothermal Program faculty, staff and students. We would like to thank Jean Cook, Joanne Hartford, Terri Ramey, Amy Osugi, and Marilyn King for their valued help with the Workshop arrangements and the Proceedings. We also owe thanks to the program students who arranged and operated the audio-visual equipment. The Ninth Workshop was supported by the Geothermal and Hydropower Technologies Division of the U . S . Department of Energy through contract DE-AT03-80SF11459. We deeply appreciate this continued support. H. J. Ramey, Jr., R. N. Horne, P. Kruger, W. E. Brigham, F. G. Miller, J. S . Gudmundsson -vii

  20. Thirteenth workshop on geothermal reservoir engineering: Proceedings

    SciTech Connect (OSTI)

    Ramey, H.J. Jr.; Kruger, P.; Horne, R.N.; Brigham, W.E.; Miller, F.G.; Cook, J.W.

    1988-01-21

    PREFACE The Thirteenth Workshop on Geothermal Reservoir Engineering was held at Stanford University on January 19-21, 1988. Although 1987 continued to be difficult for the domestic geothermal industry, world-wide activities continued to expand. Two invited presentations on mature geothermal systems were a keynote of the meeting. Malcolm Grant presented a detailed review of Wairakei, New Zealand and highlighted plans for new development. G. Neri summarized experience on flow rate decline and well test analysis in Larderello, Italy. Attendance continued to be high with 128 registered participants. Eight foreign countries were represented: England, France, Iceland, Italy, New Zealand, Japan, Mexico and The Philippines. A discussion of future workshops produced a strong recommendation that the Stanford Workshop program continue for the future. There were forty-one technical presentations at the Workshop. All of these are published as papers in this Proceedings volume. Four technical papers not presented at the Workshop are also published. In addition to these forty five technical presentations or papers, the introductory address was given by Henry J. Ramey, Jr. from the Stanford Geothermal Program. The Workshop Banquet speaker was Gustavo Calderon from the Inter-American Development Bank. We thank him for sharing with the Workshop participants a description of the Bank???s operations in Costa Rica developing alternative energy resources, specifically Geothermal, to improve the country???s economic basis. His talk appears as a paper in the back of this volume. The chairmen of the technical sessions made an important contribution to the workshop. Other than Stanford faculty members they included: J. Combs, G. T. Cole, J. Counsil, A. Drenick, H. Dykstra, K. Goyal, P. Muffler, K. Pruess, and S. K. Sanyal. The Workshop was organized by the Stanford Geothermal Program faculty, staff and students. We would like to thank Marilyn King, Pat Oto, Terri Ramey, Bronwyn Jones

  1. Jefferson Lab Human Resources

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    Compensation Online Forms Salary Ranges Intern Rates Classification Matrices Annual Promotion Process TRC Membership Promotion Forms...

  2. Pilfer

    Energy Science and Technology Software Center (OSTI)

    2005-06-06

    Extracts statistically regular temporal patterns from time-series data without human intervention for classification purposes.

  3. Table_of_Contents

    Broader source: Energy.gov (indexed) [DOE]

    ......... 304-1 305. Security Clearance Reinvestigations and ......... 501-1 502. Classification ......

  4. OpenEI:Projects/Improvements Oil and Gas | Open Energy Information

    Open Energy Info (EERE)

    2 Oil | General Classification 3 Oil | Uses 3.1 Fuels 3.2 Derivatives 3.3 Agriculture 4 Natural Gas | Energy Basics 5 Natural Gas | General Classification 5.1 Biogas 6 Natural...

  5. Slide 1

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Business 5 6 Classification Funding Small Business 322M SDB 8(a) 5M 8(a) 31M Native American 2-4.3M SDVOB 9M HUBSDV 5M FORECAST OF OPPORTUNITIES 7 Classification Funding ...

  6. The Department of Energy's National Security Information Fundamental

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Classification Guidance Review | Department of Energy The Department of Energy's National Security Information Fundamental Classification Guidance Review The Department of Energy's National Security Information Fundamental Classification Guidance Review The goals of this review process was to evaluate the guidance content, determine if the guidance conforms to current operational and technical circumstances, determine if the guidance meets the standards for classification under section 1.4

  7. Catalysis Working Group Meeting: July 2016 | Department of Energy

    Broader source: Energy.gov (indexed) [DOE]

    2016 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

  8. Manufacturing Energy and Carbon Footprints Scope

    Broader source: Energy.gov [DOE]

    List of manufacturing sectors selected for analysis along with North American Industry Classification System (NAICS) code descriptions

  9. Microsoft PowerPoint - Camper, ORNL-TN CAB-04-2010-final, via...

    Office of Environmental Management (EM)

    ...Assumptions * Difficult to Limit to Waste Classification * Spectrum of Possibilities * Spectrum of Possibilities * Significant Stakeholder Interest 5 Blending of LLW * ...

  10. PowerPoint Presentation

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... controls against existing PDSA controls to identify differences in functional classifications, safety functions, functional requirements, performance criteria, etc. * Defines ...

  11. Changing scene highlights III. [Iowa State University] (Technical...

    Office of Scientific and Technical Information (OSTI)

    radiography, grain dust explosions, biomass conversion, etc). (LTC) Authors: Fassel, ... SEPARATION; HYDROGEN STORAGE; HYDRIDES; BIOMASS; CATALYSTS; CLASSIFICATION; COAL; COAL ...

  12. A Lesson Learned on Determination of Radionuclides on Metal Surface Fixed Contamination

    SciTech Connect (OSTI)

    MEZNARICH, H.K.

    2000-02-01

    A Measurement of fixed surface contamination required to determine classification as low-level or as transuranic waste.

  13. Department of Energy (DOE) OpenNet documents

    Office of Scientific and Technical Information (OSTI)

    Report of the Fundamental Classification Policy Review Group Report of the Fundamental Classification Policy Review Group January 15, 1997 Dr. Albert Narath, Chair Unclassified Version (Classified Material Has been Removed) Issued by the Department of Energy October 1997 CONTENTS Part I Chapter 1 – Introduction The DOE Openness Initiative The Review Task The Approach Stakeholder Concerns Protectability of Information Chapter 2 – Principles for Governing the Classification System Classification

  14. RONALD T. BARTHOLOMEW

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    and programs in the areas of physical, information, internal, and personnel security; classification and declassification; computer security; technical surveillance ...

  15. U. S. Department of Energy Savannah River Operations Office ...

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    and programs in the areas of physical, information, internal, and personnel security; classification and declassification; computer security; technical surveillance ...

  16. Geochemical Evidence of the Seasonality, Affinity and Pigmenation of Solenopora jurassica

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Barden, Holly E.; Behnsen, Julia; Bergmann, Uwe; Leng, Melanie J.; Manning, Phillip L.; Withers, Philip J.; Wogelius, Roy A.; van Dongen, Bart E.; Silva, Lucas C. R.

    2015-09-14

    Solenopora jurassica is a fossil calcareous alga that functioned as an important reef-building organism during the Palaeozoic. It is of significant palaeobiological interest due to its distinctive but poorly understood pink and white banding. Though widely accepted as an alga there is still debate over its taxonomic affinity, with recent work arguing that it should be reclassified as a chaetetid sponge. The banding is thought to be seasonal, but there is no conclusive evidence for this. Other recent work has, however demonstrated the presence of a unique organic boron-containing pink/red pigment in the pink bands of S. jurassica. We presentmore » new geochemical evidence concerning the seasonality and pigmentation of S. jurassica. Seasonal growth cycles are demonstrated by X-ray radiography, which shows differences in calcite density, and by varying δ13C composition of the bands. Temperature variation in the bands is difficult to constrain accurately due to conflicting patterns arising from Mg/Ca molar ratios and δ18O data. Fluctuating chlorine levels indicate increased salinity in the white bands, when combined with the isotope data this suggests more suggestive of marine conditions during formation of the white band and a greater freshwater component (lower chlorinity) during pink band precipitation (δ18O). Increased photosynthesis is inferred within the pink bands in comparison to the white, based on δ13C. Pyrolysis Gas Chromatography Mass Spectrometry (Py-GCMS) and Fourier Transform Infrared Spectroscopy (FTIR) show the presence of tetramethyl pyrrole, protein moieties and carboxylic acid groups, suggestive of the presence of the red algal pigment phycoerythrin. This is consistent with the pink colour of S. jurassica. As phycoerythrin is only known to occur in algae and cyanobacteria, and no biomarker evidence of bacteria or sponges was detected we conclude S. jurassica is most likely an alga. Pigment analysis may be a reliable classification method for

  17. Geochemical Evidence of the Seasonality, Affinity and Pigmenation of Solenopora jurassica

    SciTech Connect (OSTI)

    Barden, Holly E.; Behnsen, Julia; Bergmann, Uwe; Leng, Melanie J.; Manning, Phillip L.; Withers, Philip J.; Wogelius, Roy A.; van Dongen, Bart E.; Silva, Lucas C. R.

    2015-09-14

    Solenopora jurassica is a fossil calcareous alga that functioned as an important reef-building organism during the Palaeozoic. It is of significant palaeobiological interest due to its distinctive but poorly understood pink and white banding. Though widely accepted as an alga there is still debate over its taxonomic affinity, with recent work arguing that it should be reclassified as a chaetetid sponge. The banding is thought to be seasonal, but there is no conclusive evidence for this. Other recent work has, however demonstrated the presence of a unique organic boron-containing pink/red pigment in the pink bands of S. jurassica. We present new geochemical evidence concerning the seasonality and pigmentation of S. jurassica. Seasonal growth cycles are demonstrated by X-ray radiography, which shows differences in calcite density, and by varying δ13C composition of the bands. Temperature variation in the bands is difficult to constrain accurately due to conflicting patterns arising from Mg/Ca molar ratios and δ18O data. Fluctuating chlorine levels indicate increased salinity in the white bands, when combined with the isotope data this suggests more suggestive of marine conditions during formation of the white band and a greater freshwater component (lower chlorinity) during pink band precipitation (δ18O). Increased photosynthesis is inferred within the pink bands in comparison to the white, based on δ13C. Pyrolysis Gas Chromatography Mass Spectrometry (Py-GCMS) and Fourier Transform Infrared Spectroscopy (FTIR) show the presence of tetramethyl pyrrole, protein moieties and carboxylic acid groups, suggestive of the presence of the red algal pigment phycoerythrin. This is consistent with the pink colour of S. jurassica. As phycoerythrin is only known to occur in algae and cyanobacteria, and no biomarker evidence of bacteria or sponges was detected we conclude S. jurassica is most likely an alga. Pigment analysis may be a

  18. Spontaneous Potential (book section) | Open Energy Information

    Open Energy Info (EERE)

    Reference LibraryAdd to library Book Section: Spontaneous Potential (book section) Author NA Published NA, The date "NA" was not understood.The date "NA" was not understood....

  19. New Species of Cyanobacteria Forms Intracellular Carbonates

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    understood. Scientists agree that calcification in cyanobacteria is an extracellular process: Photosynthesizing cells commonly export the photosynthesis byproduct CO32-...

  20. Semiotic indexing of digital resources

    DOE Patents [OSTI]

    Parker, Charles T; Garrity, George M

    2014-12-02

    A method of classifying a plurality of documents. The method includes steps of providing a first set of classification terms and a second set of classification terms, the second set of classification terms being different from the first set of classification terms; generating a first frequency array of a number of occurrences of each term from the first set of classification terms in each document; generating a second frequency array of a number of occurrences of each term from the second set of classification terms in each document; generating a first similarity matrix from the first frequency array; generating a second similarity matrix from the second frequency array; determining an entrywise combination of the first similarity matrix and the second similarity matrix; and clustering the plurality of documents based on the result of the entrywise combination.

  1. Microsoft Word - NOPR versus SNOPR Factsheet_Final

    National Nuclear Security Administration (NNSA)

    NOPR versus SNOPR: Proposed Changes to Key Provisions Destination classification NOPR: The NOPR proposed to change the classification of 3 countries with growing nuclear trade to generally authorized from requiring specific authorization. It was also proposed that 77 countries with limited nuclear trade, with the exception of Mexico, switch from generally authorized to requiring specific authorization. The proposed change did not affect the classification of 117 country destinations. SNOPR: The

  2. Andrew Weston-Dawkes | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Weston-Dawkes About Us Andrew Weston-Dawkes - Director, Office of Classification Andrew Weston-Dawkes Dr. Andrew Weston-Dawkes is the Director for the Office of Classification within the Office of Environment, Health, Safety and Security. The Office of Classification manages the Government-wide program to classify and declassify nuclear weapons-related technology as authorized under the Atomic Energy Act of 1954 and implements the requirements of Executive Order 13526 regarding the

  3. Department of Energy (DOE) OpenNet documents

    Office of Scientific and Technical Information (OSTI)

    Policy The following are documents relating to the Department of Energy's policy on Openness. General U. S. Department of Energy Open Government Plan 3.0 (June 2014) U. S. Department of Energy Open Government Plan 2.0 (April 2012) U. S. Department of Energy Open Government Plan 1.2 (June 2010) Orders Pertaining to Openness History of Classification and Declassification Department of Energy Fundamental Classification Policy Review Department of Energy Fundamental Classification Guidance Review

  4. Steam Turbines (DOE CHP Technology Fact Sheet Series) - Fact Sheet, 2016

    Office of Environmental Management (EM)

    Status Status Status (1.06 MB) More Documents & Publications DOE O 206.2 Identity, Credential, and Access Management (ICAM) ICAM Workshop Audit Report: IG-0860 Department of Energy

    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,

  5. Inspection Report: DOE/IG-0904 | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    For instance, our inspection determined that a classification marking tool embedded in the classified email system at an NNSA site automatically marked emails as SecretRestricted ...

  6. Search for: All records | SciTech Connect

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    States) DOE HSS Office of Classification, Office of Document Reviews DOE Office of Science Atmospheric Radiation Measurement (ARM) Program (United States) DOEEI USDOE Energy...

  7. Microsoft Word - M-2 WTP Contract Section H - Conformed Thru...

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    (or subcontracts thereunder) administered by the DOE, which are subject to the Davis-Bacon Act, in the classifications set forth in the Hanford Site Stabilization Agreement...

  8. The Department of Energy's National Security Information Fundamental...

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    The Department of Energy's National Security Information Fundamental Classification Guidance Review The goals of this review process was to evaluate the guidance content, determine ...

  9. Geographic Information System At Cove Fort Area - Vapor (Nash...

    Open Energy Info (EERE)

    Unknown Notes An example, shown in Figure 1, shows results from the classification of big sagebrush (Artimesia tridentata) spectra, acquired over the Cove Fort-Sulphurdale,...

  10. Geographic Information System At Cove Fort Area (Nash, Et Al...

    Open Energy Info (EERE)

    Unknown Notes An example, shown in Figure 1, shows results from the classification of big sagebrush (Artimesia tridentata) spectra, acquired over the Cove Fort-Sulphurdale,...

  11. UNIVERSITY OF CALIFORNIA, SAN DIEGO Automated Feature Design...

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    sample Index reserved for time series Fitness Classification error Quadratic loss Fitness component weighting factor Number of instances in training data Number of instances in...

  12. Building America Technology Solutions for New and Existing Homes...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    High-Performance Enclosure Strategies, Part I: Unvented Roof Systems and Innovative Advanced Framing Strategies Vapor Retarder Classification - Building America Top Innovation

  13. Posting Date: 12/18/15 Posting Close Date: 1/4/16

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    815 Posting Close Date: 1416 North American Industry Classification System (NAICS) code for the request: 336211 Estimated SubcontractPO Value: TBD Estimated Period of...

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    July 16, 2015 Posting Close Date: TBD North American Industry Classification System (NAICS) code for the request: 812332 Estimated SubcontractPO Value TBD Estimated Period of...

  15. Posting Date: 12/17/15 Posting Close Date: 12/24/15

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    715 Posting Close Date: 122415 North American Industry Classification System (NAICS) code for the request: 236220 Estimated SubcontractPO Value: TBD Estimated Period of...

  16. RAPID/Roadmap/3-TX-a | Open Energy Information

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    Act Lands' are defined in the Texas Administrative Code as "any public free school or asylum lands, whether surveyed or unsurveyed, sold with a mineral classification or...

  17. Staff

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    Feature Design for Time Series Classification by Genetic Programming (pdf) Dustin Harvey, Ph.D. Dissertation, 2014 Structural Eng., Univ. of California, San Diego...

  18. Interdisciplinary: General Engineer/Physical Scientist

    Broader source: Energy.gov [DOE]

    This position is located in the Office of Technical Guidance within the Office Classification. The Office of Technical Guidance develops, promulgates, and interprets National level policies,...

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    FR Staffing Process See Appendix C in DOE-STD-1063-2011, Facility Representatives ... Nuclear Safety Facility Safety Security Classification Databases Dashboards DOE Technical ...

  20. A Holistic Framework for Environmental Flows Determination in...

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    ... means to apply a multi-regional hydrologic classification to entire fish assemblages. ... to changes in flow may be highly dependent upon channel morphology and underlying geology. ...

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    of Classification, Office of Document Reviews DOE Office of Science Atmospheric ... S ; Zeng, Zhixiong ; Collins, Kathleen ; et al December 2015 , Nature Publishing Group

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    of Classification, Office of Document Reviews DOE Office of Science Atmospheric ... ; Myszka, David G. ; Wu, Hao ; Weill-Med) ; Utah) October 2015 , Nature Publishing Group

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    The Electric Power Sector comprises electricity-only and combined heat and power (CHP) plants within the North American Industrial Classification System 22 category whose...

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    Examining and Placement Records OPMGOVT-7: Applicant Race, Sex, National Origin, and Disability Status Records OPMGOVT-9: File on Position Classification Appeals, Job Grading...

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    ... Bianchi Attractors: A Classification of Extremal Black Brane Geometries Iizuka, Norihiro ; CERN ; Kachru, Shamit ; Stanford U., ITP SLAC ; Kundu, Nilay ; Narayan, Prithvi ; ...

  6. June 2015 Most Viewed Documents for National Defense | OSTI,...

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    SMART BRIDGE: A tool for estimating the military load classification of bridges using ... of components for high reliability military and space applications Hanlon, J.T. ...

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    Comments on TNT Equivalence Cooper, P.W. (1994) 64 SMART BRIDGE: A tool for estimating the military load classification of bridges using varying levels of information Van ...

  9. SMART BRIDGE: A Tool for Estimating the Military Load

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    D. SMART BRIDGE: A Tool for Estimating the Military Load Classification of Bridges Charles ... consideration in planning and executing military deployments is determining the routes ...

  10. Slide 1

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    regulatory guidance Change nature of interaction between operators and the system Affect ... classification and definition of interaction modalities Industry gap analysis of ...

  11. Wild and Scenic Rivers Act | Open Energy Information

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    as wild, scenic, or recreational. These classifications necessitate differing levels of environmental protection under the Act. Published NA Year Signed or Took Effect 1968...

  12. May 5, 2016, FTCP Face to Face Meeting Presentation - HR Service...

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    Officer Kurt Stephens Classification Branch Lori Carter M&P HQ HRAO Jason Nelson Recruitment & Staffing Branch Cathy Little Benefits Branch Robin Campbell HR Processing & Info. ...

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    definition of a manufacturing establishment is the definition stated in the Office of Management and Budget's Standard Industrial Classification (SIC) Manual: 16 Manufacturing...

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  20. U.S. DEPARTMENT OF ENERGY HEADQUARTERS RECORDS HOLDING AREA

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    INDIVIDUAL REQUESTING OFFICE MAIL STATION RECORDS CENTER JOB NO. HIGHEST CLASSIFICATION FORWARDED (Date) RETURNED (Date) DESCRIPTION OF RECORDS LOCATION RECEIPT I have...

  1. NEW - DOE O 325.2 Chg 1 (Admin Chg), Position Management and...

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    O 325.2 Chg 1 (Admin Chg), Position Management and Classification by Patricia Greeson The order establishes departmental requirements and responsibilities for classifying positions...

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    interconnection requests. A project must meet all of the requirements of a given classification in order to be eligible for that level of... Eligibility: Commercial, Industrial,...

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    2008, 2009, and 2010. You have asked for data that reflects positiontitle, name, classification, salary, all awards identified by type and any other cash recognition by fiscal...

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    contract for security support services at the Nevada National Security Site (NNSS). ... Security Assessments, support the Nevada Site Office classification program and ...

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    Classification, Office of Document Reviews DOE Office of Science Atmospheric ... and electrochemical impedance spectroscopy (EIS) were applied to investigate the structure, ...

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    ... The classification accuracy was evaluated using the area under the receiver operating characteristic curve. The authors' primary data set consisted of 427 biopsy-proven masses (200 ...

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  9. Microsoft Word - Final Quadrennial Energy Review Comments, Providence...

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  13. Classifying forest productivity at different scales

    SciTech Connect (OSTI)

    Graham, R.L.

    1991-01-01

    Spatial scale is an important consideration when evaluating, using, or constructing forest productivity classifications. First, the factors which dominate spatial variability in forest productivity are scale dependent. For example, within a stand, spatial variability in productivity is dominated by microsite differences; within a national forest such as the Cherokee National Forest, spatial variability is dominated by topography and land-use history (e.g., years since harvest); within a large region such as the southeast, spatial variability is dominated by climatic patterns. Second, classifications developed at different spatial scales are often used for different purposes. For example, stand-level classifications are often keys or rules used in the field to judge the quality or potential of a site. National-forest classifications are often presented as maps or tables and may be used in forest land planning. Regional classifications may be maps or tables and may be used to quantify or predict resource availability. These scale-related differences in controlling factors and purposes will affect both the methods and the data used to develop classifications. In this paper, I will illustrate these points by describing and comparing three forest productivity classifications, each developed for a specific purpose at a specific scale. My objective is not to argue for or against any of these particular classifications but rather to heighten awareness of the critical role that spatial scale plays in the use and development of forest productivity classifications. 8 refs., 2 figs., 1 tab.

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    Ia SNe, at redshifts from 0.10 to 0.78, identified through an impartial, effective methodology for spectroscopic classification and redshift determination. We present the...

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  12. Energy Intensity Indicators: Manufacturing Energy Intensity

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  15. Annual Energy Outlook 2015 - Appendix A

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    and user's guide Basore, P.A. (1991) 70 SMART BRIDGE: A tool for estimating the military load classification of bridges using varying levels of information Van Groningen, ...

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  10. Type D: Sedimentary-hosted, Volcanic-related Resource | Open...

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    F 1,035.27 R References Colin F. Williams, Marshall J. Reed and Arlene F. Anderson. 2011. Updating the Classification of Geothermal Resources - Presentation. In:...

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  13. Conductive Plays - Basement | Open Energy Information

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    Plays - Basement Author Graeme Beardsmore Conference IGA Workshop on Developing Best Practice for Geothermal Exploration and ResourceReserve Classification; Essen,...

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    in the Paris Basin Author Miklos Antics Conference IGA Workshop on Developing Best Practice for Geothermal Exploration and ResourceReserve Classification; Essen,...

  15. Towards a Characterization of Arctic Mixed-Phase Clouds

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    manual classification of cloud phase. Using collocated cloud radar and depolarization lidar observations, it is shown that mixed-phase conditions have a high correlation with a...

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    ... CO (United States) HSS Office of Classification Hanford Site (HNF), Richland, WA ... electron microscopy (SEM) and an optical microscopy connected to an image analyzer. ...

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