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


1

A Dataset Search Engine for the Research Document Corpus  

E-Print Network [OSTI]

A Dataset Search Engine for the Research Document Corpus Meiyu Lu # , Srinivas Bangalore , Graham no useful tools for researchers to understand which datasets have been used for what purpose, or in what prior work. Instead, they have to manually browse through papers to find suitable datasets

Fisher, Kathleen

2

Grazing and Browsing: How Plants are Affected  

E-Print Network [OSTI]

Grazing and browsing can have a neutral, positive or negative effect on rangeland plants. This publication explains the effects of grazing and browsing on plants, details the indicators of overuse of the range, and lists grazing management practices...

Lyons, Robert K.; Hanselka, C. Wayne

2001-12-13T23:59:59.000Z

3

Optimization Online - Search or Browse Submissions  

E-Print Network [OSTI]

Search or Browse Optimization Online Submissions. Advanced Search using Our Search Engine. Enter your search terms: name of author(s), title, keywords,...

4

Optimization Online - Search or Browse Submissions  

E-Print Network [OSTI]

Search or Browse Optimization Online Submissions. Google Search. Enter your search terms: name of author(s), title, keywords, journal, etc. The Web

5

A Learning Apprentice For Browsing Robert C. Holte Chris Drummond  

E-Print Network [OSTI]

A Learning Apprentice For Browsing Robert C. Holte Chris Drummond Computer Science Department of browsing. The agent is a learning apprentice: it monitors the user's normal browsing actions and learns task for learning apprentice research. 1 THE BROWSING TASK "Browsing" is the searching of a computer

Holte, Robert

6

Green Button App Ideas | Department of Energy  

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

App Ideas Green Button App Ideas March 4, 2012 - 10:16pm Addthis Green Button App Ideas Matthew Loveless Matthew Loveless Data Integration Specialist, Office of Public Affairs...

7

Fluxnet Synthesis Dataset Collaboration Infrastructure  

SciTech Connect (OSTI)

The Fluxnet synthesis dataset originally compiled for the La Thuile workshop contained approximately 600 site years. Since the workshop, several additional site years have been added and the dataset now contains over 920 site years from over 240 sites. A data refresh update is expected to increase those numbers in the next few months. The ancillary data describing the sites continues to evolve as well. There are on the order of 120 site contacts and 60proposals have been approved to use thedata. These proposals involve around 120 researchers. The size and complexity of the dataset and collaboration has led to a new approach to providing access to the data and collaboration support and the support team attended the workshop and worked closely with the attendees and the Fluxnet project office to define the requirements for the support infrastructure. As a result of this effort, a new website (http://www.fluxdata.org) has been created to provide access to the Fluxnet synthesis dataset. This new web site is based on a scientific data server which enables browsing of the data on-line, data download, and version tracking. We leverage database and data analysis tools such as OLAP data cubes and web reports to enable browser and Excel pivot table access to the data.

Agarwal, Deborah A.; Humphrey, Marty; van Ingen, Catharine; Beekwilder, Norm; Goode, Monte; Jackson, Keith; Rodriguez, Matt; Weber, Robin

2008-02-06T23:59:59.000Z

8

Data Mining for Selective Visualization of Large Spatial Datasets Shashi Shekhar  

E-Print Network [OSTI]

Data Mining for Selective Visualization of Large Spatial Datasets Shashi Shekhar £ , Chang-Tien Lu exploring data for pattern and trend analysis, and it is a common method of browsing spatial datasets the summarization of spatial patterns and temporal trends. We also present data mining algorithms for filtering out

Shekhar, Shashi

9

myPublications: Searching and browsing v4 myPublications: Searching and browsing  

E-Print Network [OSTI]

to conduct either a simple search or an advanced search. You can enter keywords and dates, and restrict searches You can save the terms used for a search of the database so that they can be used again without1 myPublications: Searching and browsing v4 myPublications: Searching and browsing Within my

Oakley, Jeremy

10

NERSC Releases Mobile Apps to Users  

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

Releases Mobile Apps to Users NERSC Releases Mobile Apps to Users Job Status, MOTD and Pilot of VASP Submission Available with More to Come April 23, 2012 In an effort to make...

11

ICE Pulse Oximeter Smart Alarm App Requirements  

E-Print Network [OSTI]

ICE Pulse Oximeter Smart Alarm App Requirements 6 March 2012 Revision 0 for an Integrated Clinical Environment (ICE) pulse oximetry monitoring app that provides.2 References [Purpose: List all ICE standards, and other standards and references

Huth, Michael

12

Models Datasets  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: VegetationEquipment SurfacesResource Program PreliminaryA3,0StatementsMixingAssessing8 MayModels-Datasets

13

Speed-dependent Automatic Zooming for Browsing Large Documents  

E-Print Network [OSTI]

@microsoft.com ABSTRACT We propose a navigation technique for browsing large documents that integrates rate. With typical scrolling interfaces, it is difficult to browse a large document efficiently. UsingSpeed-dependent Automatic Zooming for Browsing Large Documents Takeo Igarashi Computer Science

Igarashi, Takeo

14

Energy Efficiency Wins Top Prize at EPA App Contest | Department...  

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

Energy Efficiency Wins Top Prize at EPA App Contest Energy Efficiency Wins Top Prize at EPA App Contest November 23, 2011 - 11:11am Addthis The winner of best overall app at the...

15

ORISE: CDC Travelers' Health Mobile App, Designed by ORISE, Gains...  

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

Can I Eat This? Mobile App Helps International Travelers Make Safe Dining Choices CDC Travelers' Health app, designed by ORISE, gains attention on multiple websites How ORISE is...

16

Browse Success Stories - Energy Innovation Portal  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone6 M.ExtracellularBradburyBrianforRequirementsBrowse

17

Fluxnet Synthesis Dataset Collaboration Infrastructure  

E-Print Network [OSTI]

Fluxnet Synthesis Dataset Collaboration Infrastructure DebUCB) The Fluxnet synthesis dataset originally compiled forhave been added and the dataset now contains over 920 site

Agarwal, Deborah A.

2009-01-01T23:59:59.000Z

18

Concrete Browsing Of A Graphical Toolkit Library Denys Duchier  

E-Print Network [OSTI]

Concrete Browsing Of A Graphical Toolkit Library Denys Duchier Department of Computer Science and promote reuse. This paper introduces Concrete Browsing as an improved method of consult- ing a graphical library, and Spreading Computation as novel paradigm for search and retrieval. A concrete browser allows

Duchier, Denys

19

Concrete Browsing Of A Graphical Toolkit Library Denys Duchier  

E-Print Network [OSTI]

Concrete Browsing Of A Graphical Toolkit Library Denys Duchier Department of Computer Science and promote reuse. This paper introduces Concrete Browsing as an improved method of consult­ ing a graphical library, and Spreading Computation as novel paradigm for search and retrieval. A concrete browser allows

Duchier, Denys

20

Apps for Energy FAQ | Department of Energy  

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

available at http:energy.govdeveloper. You may also use sample Green Button data from utilities, utility customers, or other sources. If you would like to demonstrate your app...

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


21

MDCF Tutorial Device Interface and App Development  

E-Print Network [OSTI]

-generated Device Interface (ICE Device Model) Vision: IDE for Driver Development & Validation Vision: IntegratedMDCF Tutorial Device Interface and App Development Acknowledgements: Funding provided by US National Science Foundation awards 0734204, 0930647 Clinical documentation and hardware provided by CIMIT

Huth, Michael

22

Data Mining for Selective Visualization of Large Spatial Datasets Shashi Shekhar , ChangTien Lu y , Pusheng Zhang, Rulin Liu  

E-Print Network [OSTI]

Data Mining for Selective Visualization of Large Spatial Datasets Shashi Shekhar #3; , Chang of visually exploring data for pattern and trend analysis, and it is a common method of browsing spatial for observing the summarization of spatial patterns and temporal trends. We also present data mining algorithms

Shekhar, Shashi

23

An immersive system for browsing and visualizing surveillance video  

E-Print Network [OSTI]

HouseFly is an interactive data browsing and visualization system that synthesizes audio-visual recordings from multiple sensors, as well as the meta-data derived from those recordings, into a unified viewing experience. ...

DeCamp, Philip James

24

Introduction Real datasets with known classes  

E-Print Network [OSTI]

Introduction Real datasets with known classes Simulated datasets Real datasets without known 8, 2011 Christian Hennig Some thoughts on cluster benchmarking #12;Introduction Real datasets with known classes Simulated datasets Real datasets without known classes Benchmarking should not be ranking

Hennig, Christian

25

American Energy Data Challenge Hackathons - "Apps For Energy...  

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

Designers hard at work turning energy data into useful apps in Washington D.C. January 25 Designers hard at work turning energy data into useful apps in Washington D.C. January 25...

26

Ultrasound images in the new `iPA Phonetics' App  

E-Print Network [OSTI]

Ultrasound images in the new `iPA Phonetics' App Christopher Coey1 , John H. Esling1 , Scott R in an App iPA Phonetics is an application that illustrates the sounds and articulations of an expanded version of the IPA chart. The App gives users of Apple iOS mobile electronic devices the ability to access

Edinburgh, University of

27

Apps for Vehicles: Can I develop a vehicle data app using commercial...  

Open Energy Info (EERE)

develop a vehicle data app using commercial software and hardware or do I have to use the open-source versions? Home > Groups > Developer This question relates to energy hackathons...

28

Form ElectApp11 ELECTRICAL APPLIANCES  

E-Print Network [OSTI]

Form ElectApp11 ELECTRICAL APPLIANCES In accordance with Residence Regulation 14.2 (see Section Two. Permission to bring personal electrical items will not be unreasonably withheld, but will not be granted amplifiers electrical heaters cooking equipment such as deep fat fryers. (Please note that permitted cooking

Applebaum, David

29

Form ElectApp13 ELECTRICAL APPLIANCES  

E-Print Network [OSTI]

Form ElectApp13 ELECTRICAL APPLIANCES In accordance with the Agreement Terms and Conditions clause to the Residence. Permission to bring personal electrical items will not be unreasonably withheld systems amplifiers electrical heaters cooking equipment such as deep fat fryers. (Please note

Applebaum, David

30

Form ElectApp12 ELECTRICAL APPLIANCES  

E-Print Network [OSTI]

Form ElectApp12 ELECTRICAL APPLIANCES In accordance with Residence Regulation 15.2 (see Section Two. Permission to bring personal electrical items will not be unreasonably withheld, but will not be granted · amplifiers · electrical heaters · cooking equipment such as deep fat fryers. (Please note that permitted

Applebaum, David

31

White-tailed Deer Browse Preferences for South Texas and the Edwards Plateau  

E-Print Network [OSTI]

Used plants usually are protected from browsing by physical or chemical deterrents. For example, cedar has volatile oils (terpenes) that dis- courage browsing. Agarito has a physical defense; young leaves are tender and readily eaten, but mature agarito... on your property and their relative abundance. ? Monitor deer and livestock use of the dif- ferent categories of browse on your prop- erty. ? Manage for herbivore densities that prevent severe hedging or the disappearance of highly preferred browse species...

Wright, Byron D.; Lyons, Robert K.; Cooper, Susan; Cathey, James

2003-01-06T23:59:59.000Z

32

Sextant: Browsing and Mapping the Ocean of Linked Geospatial Data  

E-Print Network [OSTI]

Sextant: Browsing and Mapping the Ocean of Linked Geospatial Data Charalampos Nikolaou, Kallirroi {charnik,kallirroi,kkyzir,koubarak}@di.uoa.gr Abstract. Linked geospatial data has recently received available on the Web. With the rapid population of the Web of data with geospatial information, applications

Koubarakis, Manolis

33

DBDOC: Querying and Browsing Databases and Interrelated Documents  

E-Print Network [OSTI]

]: Database Administra- tion--Data warehouse and repository General Terms Management, Documentation, Design 1 to describe this structured data. Managing semi- structured sources, such as documents, text files, web pagesDBDOC: Querying and Browsing Databases and Interrelated Documents Carlos Garcia-Alvarado University

Ordonez, Carlos

34

ScentTrails: Integrating Browsing and Searching on the Web  

E-Print Network [OSTI]

. Searching is the process of entering a search query (usually a list of keywords) into a search engine, which are more appropriately termed by Jul and Furnas [1997] as "search by navigation" and "search by query," respectively, but we will use the more common terms "browsing" and "searching.") Authors' addresses: Chris

Chi, Ed Huai-hsin

35

Fast Browsing of Archived Web Contents Sangchul Song  

E-Print Network [OSTI]

and deep contents, web contents involve a wide variety of objects such as html pages, documents, multimediaFast Browsing of Archived Web Contents Sangchul Song Department of Electrical and Computer The web is becoming the preferred medium for communicating and storing information pertaining to almost

JaJa, Joseph F.

36

Launching Apps for Energy! Developers, Are You Ready?  

Broader source: Energy.gov [DOE]

We're challenging the American developer community to build apps that help consumers get the most out of their electricity usage data.

37

Apps for Energy Public Voting Starts Today! | Department of Energy  

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

Back in April, we launched Apps for Energy -- challenging developers to build mobile and web applications that bring Green Button electricity data to life. You answered...

38

Alternative Fueling Station Locator App Provides Info at Your...  

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

Fueling Station Locator website. It provides information on more than 15,000 public and private alternative fueling stations throughout the United States. The app lists where...

39

New app takes Lab's volunteer efforts mobile  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the Contributions andDataNational Libraryornl.gov RonStaffReturningNew ZoneNew app

40

APP LGE JV | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 NoPublic Utilities Address: 160 East 300 SouthWater Rights,InformationWind Energy Jump to:WindenergieAPP LGE JV

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


41

AppsBoston2014_final.pptx  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAbout theOFFICEAmesApplication AccelerationCycle7:45 am, May 27,APPS on HPX

42

AppsWG_whitepaper_Feb2011  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAbout theOFFICEAmesApplication AccelerationCycle7:45 am, May 27,APPS on

43

Rediscovering old datasets Paul Withers  

E-Print Network [OSTI]

Rediscovering old datasets Paul Withers Center for Space Physics, Boston University (withers if these data are accessible and useable #12;PVO · http://nssdc.gsfc.nasa.gov/nmc/datasetDisplay.d o://nssdc.gsfc.nasa.gov/nmc/datasetDisplay.do?id=PSPA-00141 · Tables of ionospheric profiles and other

Withers, Paul

44

car_app1.doc STAFF PARKING PERMIT APPLICATION  

E-Print Network [OSTI]

and drop off points Frequency of lifts (days per week) 6. Car Sharing You can share a group permit with upcar_app1.doc STAFF PARKING PERMIT APPLICATION The information supplied on this form will allow (whichever is quicker) from campus to home? (Departing campus at 1700 hours) #12;car_app1.doc 4. Staff

Haase, Markus

45

File:App Commercial Leases and Easements or Amendment or Residential...  

Open Energy Info (EERE)

App Commercial Leases and Easements or Amendment or Residential Coastal Easements HOA.pdf Jump to: navigation, search File File history File usage Metadata File:App Commercial...

46

The Lifecycles of Apps in a Social Ecosystem  

E-Print Network [OSTI]

Apps are emerging as an important form of on-line content, and they combine aspects of Web usage in interesting ways --- they exhibit a rich temporal structure of user adoption and long-term engagement, and they exist in a broader social ecosystem that helps drive these patterns of adoption and engagement. It has been difficult, however, to study apps in their natural setting since this requires a simultaneous analysis of a large set of popular apps and the underlying social network they inhabit. In this work we address this challenge through an analysis of the collection of apps on Facebook Login, developing a novel framework for analyzing both temporal and social properties. At the temporal level, we develop a retention model that represents a user's tendency to return to an app using a very small parameter set. At the social level, we organize the space of apps along two fundamental axes --- popularity and sociality --- and we show how a user's probability of adopting an app depends both on properties of t...

Kloumann, Isabel; Kleinberg, Jon; Wu, Shaomei

2015-01-01T23:59:59.000Z

47

APPE forms task force to look at pipelines  

SciTech Connect (OSTI)

The Association of Petrochemicals Producers in Europe (APPE; Brussels) is embarking on an initiative to help with restructuring. Speaking at the recent meeting of the European Chemical Industry Council in Cernobbio, Italy, Jukka Viinanen, president of APPE, said that although the initial ethylene restructuring plan collapsed, {open_quotes}it was not a complete failure.{close_quotes} The association Viinanen says, is continuing to find ways and means to improve the situation. {open_quotes}One of the things that APPE is now doing is to study carefully the [ethylene] pipeline system.{close_quotes}

NONE

1994-06-29T23:59:59.000Z

48

ITCS 4121/5121 Contest Assignment 1 Datasets: Select one dataset I provided for HW 1 as your target dataset.  

E-Print Network [OSTI]

ITCS 4121/5121 Contest Assignment 1 Datasets: Select one dataset I provided for HW 1 as your target dataset. Visualization: The four datasets are closely related to our daily life. What to you want to do with your target dataset? Try to find one or more tasks. For example, you may want to find the best cereal

Yang, Jing

49

Home | Login | Logout | Access Information | Ale Top 100 Documents BROWSE SEARCH IEEE XPLORE GUIDE  

E-Print Network [OSTI]

Home | Login | Logout | Access Information | Ale Top 100 Documents BROWSE SEARCH IEEE XPLORE GUIDE Information 1. Subtly different facial expression recognition and expressionintensity estimation Lien, J

Yang, Liuqing

50

E-Print Network 3.0 - analysis browsing server Sample Search...  

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

>> 1 UBB Mining: Finding Unexpected Browsing Behaviour in Clickstream Data to Improve a Web Site's Design Summary: algorithm can discover the relationship between different user's...

51

Browse by region (RaphaelSVGMap) | OpenEI Community  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpenWendeGuo FengBoulder, CO) JumpNREL BiofuelsBrowse by region

52

Browse Draft Directives - DOE Directives, Delegations, and Requirements  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone6 M.ExtracellularBradburyBrianforRequirementsBrowse Draft

53

Trust based app marketing : design, implementation and evaluation  

E-Print Network [OSTI]

A trust-based marketing application is a web or mobile app which provides a utility to the consumer that is not directly linked to purchasing products or services from the company. In this thesis, I explore the efficacy ...

Hon, Keone D. (Keone David)

2011-01-01T23:59:59.000Z

54

A new bed elevation dataset for Greenland  

E-Print Network [OSTI]

A new bed elevation dataset for Greenland J. L. Bamber 1 ,al. : A new bed elevation dataset for Greenland Howat, I. M.al. : A new bed elevation dataset for Greenland Fig. 3. (a)

2013-01-01T23:59:59.000Z

55

Scaling Properties of Common Statistical Operators for Gridded Datasets  

E-Print Network [OSTI]

model that accounts for dataset size and structure can helpclimate model-origin. For these dataset geometries our modelfor simple analysis (e.g. dataset differencing). Dataset

Zender, C. S; Mangalam, H.

2007-01-01T23:59:59.000Z

56

Effective Browsing and Serendipitous Discovery with an Experience-Infused Browser  

E-Print Network [OSTI]

Effective Browsing and Serendipitous Discovery with an Experience-Infused Browser Sudheendra Hangal explore how this recall can be leveraged during web browsing. We have built a system called the Experience-Infused, an experience-infused browser can enhance the effect of a user noticing personally relevant terms on a page

Pratt, Vaughan

57

Repellents to prevent cattle browsing of pine seedlings  

E-Print Network [OSTI]

is little other green forage available. There have be n numerous theory co cnd. Opinions advas ed ac to why c"tule browse pinon?erhal. s the mst comon being that xhc cattle c 'o asm~lug gre. n feed end. there ls little other green vegetation availablo... jjv 0(x-, . oocrpv Gqx Jox (9TT+J~w 3UT. 'OJq-vov eqx Uaqn 9uepr(co GT 0 jtU, 'Gpujipao- etp. Co 90agga GGJG((pt( xo -6=:&p ei os jsq XTguapjrta GgUGTTG~TJ TTG '(Ig(I go UoyqcTaorca eqx tjtg[", 'sagJoguarcUZ 63smt(p atjt UT Jatj(63' pa(InoJ3 GJc9x E...

Duncan, Don Arlen

1959-01-01T23:59:59.000Z

58

Fast Clustering of Web Users Based on Browsing Patterns Yongjian Fu Kanwalpreet Sandhu Ming-Yi Shih  

E-Print Network [OSTI]

Fast Clustering of Web Users Based on Browsing Patterns Yongjian Fu Kanwalpreet Sandhu Ming-Yi Shih propose the clustering of the Web users based on patterns of their browsing activities on the Web. The browsing pattern of a Web user consists of the pages the user visited and the times spent on them

Fu, Yongjian

59

Building Blocks for Mobile Games : A multiplayer framework for App Inventor for Android  

E-Print Network [OSTI]

Building Blocks for Mobile Games is a client-server multiplayer game-building-framework for the App Inventor for Android platform. The Building Blocks for Mobile Games multiplayer framework includes an App Inventor component ...

Magnuson, Bill

2010-01-01T23:59:59.000Z

60

A Role-Based Access Control (RBAC) Schema for REAP Web App  

SciTech Connect (OSTI)

This document describes a Role-Based Access Control (RBAC) Schema for Reactor Embrittlement Archive Project Web App.

Klasky, Hilda B [ORNL; Tadinada, Sashi [ORNL; Williams, Paul T [ORNL; Bass, Bennett Richard [ORNL

2013-09-01T23:59:59.000Z

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


61

Email Clients as Decentralized Social Apps in Mr. Privacy  

E-Print Network [OSTI]

Email Clients as Decentralized Social Apps in Mr. Privacy Michael H. Fischer T. J. Purtell Monica S,tpurtell,lam}@cs.stanford.edu Abstract. This paper proposes Mr. Privacy, a social application frame- work built on top of email, that encourages open competition and pro- vides privacy for users. Applications built on Mr. Privacy are "social

Pratt, Vaughan

62

Differential Turbo Coded Modulation with APP Channel Estimation  

E-Print Network [OSTI]

Differential Turbo Coded Modulation with APP Channel Estimation Sheryl L. Howard and Christian, iterative decoding. I. INTRODUCTION With the advent of turbo codes [1], [2] and iterative de- coding in very high noise/low signal- to-noise ratio (SNR) environments. Turbo trellis coded modulation (TTCM

Howard, Sheryl

63

Software Verification in the Google App-Engine Cloud  

E-Print Network [OSTI]

resources. In the last years, cloud services emerged as an inexpensive, flexible, and energy for verification. We chose the platform-as-a-service offer Google App Engine and ported the open are available on demand. This enables a verification process that is less expensive (only actual usage is paid

Beyer, Dirk

64

BOX: Browsing Objects in XML Christian Nentwich, Wolfgang Emmerich, Anthony Finkelstein and Andrea Zisman  

E-Print Network [OSTI]

BOX: Browsing Objects in XML Christian Nentwich, Wolfgang Emmerich, Anthony Finkelstein and Andrea|W.Emmerich|A.Finkelstein|A.Zismang@cs.ucl.ac.uk Abstract The latest Internet markup languages

Finkelstein, Anthony

65

The UTIAS multi-robot cooperative localization and mapping dataset  

E-Print Network [OSTI]

The UTIAS multi-robot cooperative localization and mapping dataset The International Journal and mapping dataset collection for research and educational purposes. The dataset consists of nine sub-datasets in each sub-dataset is also provided. The dataset is available for download at http://asrl.utias.utoronto.ca/datasets

66

Distribution-sensitive learning for imbalanced datasets  

E-Print Network [OSTI]

Many real-world face and gesture datasets are by nature imbalanced across classes. Conventional statistical learning models (e.g., SVM, HMM, CRY), however, are sensitive to imbalanced datasets. In this paper we show how ...

Song, Yale

67

1 Calibration against independent human travel datasets  

E-Print Network [OSTI]

1 Calibration against independent human travel datasets 1.1 Calibration against United States at www.bts.gov. Although the BTS dataset is large, the movements were histogrammed 1 #12;with a low

Shull, Kenneth R.

68

European Climate Assessment & Dataset Report 2008  

E-Print Network [OSTI]

European Climate Assessment & Dataset Report 2008 ECA&D · · · · European Climate Assessment & Dataset (ECA&D) Report 2008 "Towards an operational system for assessing observed changes in climate & Dataset Report 2008 ECA&D · · · · Aryan van Engelen, Albert Klein Tank, Gerard van de Schrier and Lisette

Stoffelen, Ad

69

Integrated Datasets (IDs) Wood/Bretherton proposal  

E-Print Network [OSTI]

Integrated Datasets (IDs) Wood/Bretherton proposal ID Rationale Space/Time scale; Location; Platforms Parameters Combined Drizzle Dataset (CD ID) Collocated precipitation, aerosol and cloud micro, precip. rate, cloud Cross- Section Dataset (XS-ID) Data on E-W cross- section along 20°S from coast

Wood, Robert

70

Unbiased Look at Dataset Bias Antonio Torralba  

E-Print Network [OSTI]

Unbiased Look at Dataset Bias Antonio Torralba Massachusetts Institute of Technology torralba@csail.mit.edu Alexei A. Efros Carnegie Mellon University efros@cs.cmu.edu Abstract Datasets are an integral part and comparing performance of competing algo- rithms. At the same time, datasets have often been blamed

Guestrin, Carlos

71

Observational Datasets We use two different satellite soil moisture datasets, one derived from the Advanced Microwave  

E-Print Network [OSTI]

Observational Datasets We use two different satellite soil moisture datasets, one derived from of the datasets. Whilst the AMSRE soil moisture product is gridded at 0.25°, the footprint of the sensor different precipitation datasets which use a combination of satellite data and, in some cases, surface

Guichard, Francoise

72

Clean Cities Launches iPhone App for Alternative Fueling Station...  

Office of Environmental Management (EM)

free app that locates fueling stations offering alternative fuels, including electricity, natural gas, biodiesel, E85, propane, and hydrogen. The National Renewable Energy...

73

T-589: Citrix XenApp and Citrix Presentation Server Bug  

Broader source: Energy.gov [DOE]

A vulnerability was reported in Citrix XenApp (Presentation Server). A remote user can execute arbitrary code on the target system.

74

Celebrating Our Apps for Energy Developers | Department of Energy  

Energy Savers [EERE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious RankCombustion |Energy UsageAUDITVehiclesTankless orA BRIEFAprilBudgetAbout5Carmichael RobertsOur Apps for

75

Apps for Vehicles Challenge Finalists Announced | Department of Energy  

Energy Savers [EERE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious RankCombustion |Energyon ArmedWaste andAccess to OUO Access toEnergy 5 BTOof Energy ApprovalApps for

76

Fall 2012 focal follow FAD GPS dataset  

E-Print Network [OSTI]

Dataset includes 23 GPS files that describe fishing trips made by Dominican fishers to fish aggregating devices. Files are in RData file format....

Alvard, Michael

2014-06-11T23:59:59.000Z

77

Improving the web browsing environment for dyslexics by elaborating the viewing and reading functionalities  

E-Print Network [OSTI]

functionalities by R. Nagatsuma, S. Iizuka, M. Takizawa, T. Ohko, T. Wada, and T. Saito, IBM Abstract Dyslexia of people who experience dyslexia may be around 6-10% of the population. It varies from language to language for people with dyslexia when they are browsing the Web. In this paper, we investigate effective support

78

RESHAPING REMINISCENCE, WEB BROWSING AND WEB SEARCH USING PERSONAL DIGITAL ARCHIVES  

E-Print Network [OSTI]

RESHAPING REMINISCENCE, WEB BROWSING AND WEB SEARCH USING PERSONAL DIGITAL ARCHIVES A DISSERTATION important examples of such applications. The first is an experience- infused web browser that annotates web studies find that this tech- nique is useful to personalize crowded web pages and to serendipitously s

Straight, Aaron

79

Browse > Journals> Smart Grid, IEEE Transactions ...> Top Accessed Articles 1. Smart Transmission Grid: Vision and Framework  

E-Print Network [OSTI]

Browse > Journals> Smart Grid, IEEE Transactions ...> Top Accessed Articles 1. Smart Transmission.2080328 3. A Reliability Perspective of the Smart Grid Moslehi, K. Kumar, R. Page(s): 57 - 64 Digital Object Consumption Scheduling for the Future Smart Grid Mohsenian-Rad, A. Wong, V.W.S. Jatskevich, J. Schober, R

Tennessee, University of

80

Development and Deployment of a Large-Scale Flower Recognition Mobile App  

E-Print Network [OSTI]

engine and re- lies on computer vision recognition technology. The mobile phone app is available freeDevelopment and Deployment of a Large-Scale Flower Recognition Mobile App Anelia Angelova NEC Labs- eration of user generated content, especially from mobile de- vices, there is a need to develop

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


81

HOW-TO / USER GUIDEfor Android Devices App Version 3.1.2.1  

E-Print Network [OSTI]

app. Select "Accept" for App Permissions. Select Search then type & select Emergensee Launch GETTING STARTED Select "Sign In" or "Create Account" options. Accept "Terms of Use" and "User License · First Name · Last Name · Email Address · Mobile Phone Number · Create an Account Password · Re-Enter

Napier, Terrence

82

Berkeley Center for Green Chemistry Newsletter First mobile app for green chemistry fosters sustainable manufacturing of  

E-Print Network [OSTI]

Berkeley Center for Green Chemistry Newsletter First mobile app for green chemistry fosters sustainable manufacturing of medicines Mention mobile applications, or mobile apps, and people think of games of the environmentally friendly and sustainable principles of green chemistry -- is the topic of a report in the American

Silver, Whendee

83

Deutsche Telekom drives open approach to apps and content stores Feb 16, 2010  

E-Print Network [OSTI]

Deutsche Telekom drives open approach to apps and content stores Feb 16, 2010 · Deutsche Telekom, allowing Deutsche Telekom customers to charge apps and other content onto their mobile phone bill key stores is planned for 2010 Deutsche Telekom today announces plans to further integrate with mobile

Deutschmann, Rainer

84

Synthetic Datasets Rong Huang, Rada Chirkova, Yahya Fathi  

E-Print Network [OSTI]

Synthetic Datasets Rong Huang, Rada Chirkova, Yahya Fathi 1 Introduction Datasets may be generated will define symmetric synthetic dataset and two types of non-symmetric synthetic datasets that has some introduce symmetric synthetic dataset, its structure and the properties of the associated views. In Section

Young, R. Michael

85

KDD 99 intrusion detection datasets, which are based on DARPA 98 dataset, provides labeled data for researchers  

E-Print Network [OSTI]

Abstract KDD 99 intrusion detection datasets, which are based on DARPA 98 dataset, provides labeled data for researchers working in the field of intrusion detection and is the only labeled dataset publicly available. Numerous researchers employed the datasets in KDD 99 intrusion detection datasets

Zincir-Heywood, Nur

86

ITCS 4121/5121 Contest Assignment 1 Datasets: Four multiple datasets have been uploaded into the course Blackboard.  

E-Print Network [OSTI]

ITCS 4121/5121 Contest Assignment 1 Datasets: Four multiple datasets have been uploaded into the course Blackboard. Download the datasets and select one from them to be your target dataset. Visualization: The four datasets are closely related to our daily life. What to you want to do with your target

Yang, Jing

87

Correspondence Clustering: An Approach to Cluster Multiple Related Spatial Datasets  

E-Print Network [OSTI]

Correspondence Clustering: An Approach to Cluster Multiple Related Spatial Datasets Vadeerat spatial datasets. This capability is important for change analysis and contrast mining. In this paper spatial datasets by maximizing cluster interestingness and correspondence between clusters derived from

Eick, Christoph F.

88

To users of the Western Wind Dataset: We have run into some issues on the wind dataset. For many uses of the dataset  

E-Print Network [OSTI]

To users of the Western Wind Dataset: We have run into some issues on the wind dataset. For many uses of the dataset (general capacity factor comparisons, diurnal or seasonal profile comparisons, etc), these issues may not affect you. However, if you are using the dataset for an extensive wind integration study

89

LESSONS LEARNED Biosurveillance Mobile App Development Intern Competition (Summer 2013)  

SciTech Connect (OSTI)

The purpose of the lessons learned document for the BEOWulf Biosurveillance Mobile App Development Intern Competition is to capture the projects lessons learned in a formal document for use by other project managers on similar future projects. This document may be used as part of new project planning for similar projects in order to determine what problems occurred and how those problems were handled and may be avoided in the future. Additionally, this document details what went well with the project and why, so that other project managers may capitalize on these actions. Project managers may also use this document to determine who the project team members were in order to solicit feedback for planning their projects in the future. This document will be formally communicated with the organization and will become a part of the organizational assets and archives.

Noonan, Christine F.; Henry, Michael J.; Corley, Courtney D.

2014-01-14T23:59:59.000Z

90

A new bed elevation dataset for Greenland  

E-Print Network [OSTI]

and bed data set for the Greenland ice sheet 1. Measure-bed elevation dataset for Greenland J. L. Bamber 1 , J. A.face mass balance of the Greenland ice sheet revealed by

2013-01-01T23:59:59.000Z

91

Comparison of Recent SnIa datasets  

E-Print Network [OSTI]

We rank the six latest Type Ia supernova (SnIa) datasets (Constitution (C), Union (U), ESSENCE (Davis) (E), Gold06 (G), SNLS 1yr (S) and SDSS-II (D)) in the context of the Chevalier-Polarski-Linder (CPL) parametrization $w(a)=w_0+w_1 (1-a)$, according to their Figure of Merit (FoM), their consistency with the cosmological constant ($\\Lambda$CDM), their consistency with standard rulers (Cosmic Microwave Background (CMB) and Baryon Acoustic Oscillations (BAO)) and their mutual consistency. We find a significant improvement of the FoM (defined as the inverse area of the 95.4% parameter contour) with the number of SnIa of these datasets ((C) highest FoM, (U), (G), (D), (E), (S) lowest FoM). Standard rulers (CMB+BAO) have a better FoM by about a factor of 3, compared to the highest FoM SnIa dataset (C). We also find that the ranking sequence based on consistency with $\\Lambda$CDM is identical with the corresponding ranking based on consistency with standard rulers ((S) most consistent, (D), (C), (E), (U), (G) least consistent). The ranking sequence of the datasets however changes when we consider the consistency with an expansion history corresponding to evolving dark energy $(w_0,w_1)=(-1.4,2)$ crossing the phantom divide line $w=-1$ (it is practically reversed to (G), (U), (E), (S), (D), (C)). The SALT2 and MLCS2k2 fitters are also compared and some peculiar features of the SDSS-II dataset when standardized with the MLCS2k2 fitter are pointed out. Finally, we construct a statistic to estimate the internal consistency of a collection of SnIa datasets. We find that even though there is good consistency among most samples taken from the above datasets, this consistency decreases significantly when the Gold06 (G) dataset is included in the sample.

J. C. Bueno Sanchez; S. Nesseris; L. Perivolaropoulos

2009-10-01T23:59:59.000Z

92

INITIATIVE MOBILE APPS DEVELOPMENT Description and details about the program or initiative that is being proposed  

E-Print Network [OSTI]

INITIATIVE ­ MOBILE APPS DEVELOPMENT Description and details about the program or initiative using mobile technologies. Adoption of these technologies will allow UWM to communicate with students university vision? What guiding values are applied? Access: Mobile technologies provide more options

Saldin, Dilano

93

Maximum Entropy in Support of Semantically Annotated Datasets  

E-Print Network [OSTI]

Maximum Entropy in Support of Semantically Annotated Datasets Paulo Pinheiro da Silva, Vladik whether two datasets describe the same quantity. The existing solution to this problem is to use these datasets' ontologies to deduce that these datasets indeed represent the same quantity. However, even when

Kreinovich, Vladik

94

Covariance Tapering for Likelihood Based Estimation in Large Spatial Datasets  

E-Print Network [OSTI]

Covariance Tapering for Likelihood Based Estimation in Large Spatial Datasets Cari Kaufman, Mark the likelihood can be computationally infeasible for large datasets, requiring O(n3) calculations for a dataset and Marshall, 1984). However, evaluating the likelihood requires order n3 operations for a dataset of size n

95

Collaborative Facial Landmark Localization for Transferring Annotations Across Datasets  

E-Print Network [OSTI]

Collaborative Facial Landmark Localization for Transferring Annotations Across Datasets Brandon M landmark datasets with different landmark definitions into a super dataset, with a union of all landmark known landmarks in the target dataset to constrain the localization. Our novel pipeline is built upon

Zhang, Li

96

A Dataset availability The ``public domain'' datasets are listed below with an anonymous ftp address. If you do  

E-Print Network [OSTI]

APPENDICES A Dataset availability The ``public domain'' datasets are listed below with an anonymous ftp address. If you do not have access to these, then you can obtain the datasets on diskette from Dr Porto, Potugal. The main source of datasets is ics.uci.edu (128.195.1.1) ­ the UCI Repository of Machine

Taylor, Charles C.

97

Governance of the NHD and WBD By design, and in practice, the National Hydrography Dataset and Watershed Boundary Dataset are  

E-Print Network [OSTI]

Dataset and Watershed Boundary Dataset are governed in a collaborative process consisting Agency jointly designed a hydrography feature dataset for nationwide use by all agencies in an effort number of stakeholders to ensure a "best fit" dataset that would meet as many needs as possible

Torgersen, Christian

98

END USER LICENCE AGREEMENT iTUNES STORE, APPLE APP STORE AND iBOOKSTORE ("APPLE iSTORE") DOWNLOADS OF THE JAMES COOK UNIVERSITY MOBILE APP  

E-Print Network [OSTI]

1 END USER LICENCE AGREEMENT ­ iTUNES STORE, APPLE APP STORE AND iBOOKSTORE ("APPLE i and JCU only. Apple Inc. is not a party to this Agreement. JCU, and not Apple Inc., is solely responsible or control that runs the iOS operating system software provided by Apple Inc. ("Device"); (b) for Your own

99

135 Cal. App. 4th 263, *; 37 Cal. Rptr. 3d 434, **; 2005 Cal. App. LEXIS 1979, ***; 2005 Cal. Daily Op. Service 10923  

E-Print Network [OSTI]

, 2007 PROGRESSIVE WEST INSURANCE COMPANY, Petitioner, v. THE SUPERIOR COURT OF YOLO COUNTY, Respondent by Pro- gressive West Insurance Company v. Superior Court of Yolo County & Preciado, 2006 Cal. App. LEXIS.S. Dist. LEXIS 72208 (E.D. Cal., Oct. 2, 2006) PRIOR HISTORY: [***1] Superior Court of Yolo County, No. CV

Kammen, Daniel M.

100

U-007: IBM Rational AppScan Import/Load Function Flaws Let Remote Users Execute Arbitrary Code  

Broader source: Energy.gov [DOE]

Two vulnerabilities were reported in IBM Rational AppScan. A remote user can cause arbitrary code to be executed on the target user's system.

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


101

Migrating attributes tied to the EPA river reache file to the national hydrography dataset  

E-Print Network [OSTI]

The National Hydrography Dataset. Veisze, P. , K. Beardsley,the National Hydrography Dataset In cooperation with severalto California's hydrography dataset (a modified form of the

Moore, Cynthia L.; Mullins, James C.; Willett, Karen Beardsley; Quinn, James F.

1999-01-01T23:59:59.000Z

102

Bulk Data Movement for Climate Dataset: Efficient Data Transfer Management with Dynamic Transfer Adjustment  

E-Print Network [OSTI]

Data Movement for Climate Dataset: Efficient Data Transferbeen managing the massive dataset transfers efficiently withdistribution in climate dataset in Intergovernmental Panel

Sim, Alexander

2010-01-01T23:59:59.000Z

103

Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets  

E-Print Network [OSTI]

targets within our RNAi dataset that may be components ofgenes within our FG dataset that are novel components ofa functional genomics dataset In this study, we examine the

Ho, Hsiang; Milenkovic, Tijana; Memisevic, Vesna; Aruri, Jayavani; Przulj, Natasa; Ganesan, Anand K

2010-01-01T23:59:59.000Z

104

Sensitivity of Steel Casting Simulation Results to Alloy Property Datasets  

E-Print Network [OSTI]

1 Sensitivity of Steel Casting Simulation Results to Alloy Property Datasets Kent D. Carlson dataset; Ni-based alloys N3M, CW6MC and CW12MW can be represented by the benchmark CW12MW dataset; and Ni-based alloys M30C and M35-1 can be represented by the benchmark M35-1 dataset. While these alloy groupings

Beckermann, Christoph

105

Covariance Tapering for Interpolation of Large Spatial Datasets  

E-Print Network [OSTI]

Covariance Tapering for Interpolation of Large Spatial Datasets Reinhard FURRER, Marc G. GENTON results. An application to a large climatological precipitation dataset is presented as a concrete-based methods make it possible to analyze and fit large spatial datasets in a high level Reinhard Furrer

Genton, Marc G.

106

Columbia Photographic Images and Photorealistic Computer Graphics Dataset  

E-Print Network [OSTI]

Columbia Photographic Images and Photorealistic Computer Graphics Dataset Tian-Tsong Ng, Shih Abstract Passive-blind image authentication is a new area of research. A suitable dataset. In response to the need for a new dataset, the Columbia Photographic Images and Photorealistic Computer

Chang, Shih-Fu

107

RENOIR -A Benchmark Dataset for Real Noise Reduction Evaluation  

E-Print Network [OSTI]

1 RENOIR - A Benchmark Dataset for Real Noise Reduction Evaluation Josue Anaya, Adrian Barbu Abstract--In this paper we introduce a dataset of uncom- pressed color images taken with three digital and in intensity. The dataset contains over 100 scenes and more than 400 images, including both RAW formatted

Barbu, Adrian

108

Estimating Dataset Size Requirements for Classifying DNA Microarray Data  

E-Print Network [OSTI]

Estimating Dataset Size Requirements for Classifying DNA Microarray Data S. Mukherjee*+#1 , P methodology for estimating dataset size requirements for classifying microarray data using learning curves is introduced. The goal is to use existing classification results to estimate dataset size requirements

Poggio, Tomaso

109

Datasets for the Evaluation of Substitution-Tolerant Subgraph Isomorphism  

E-Print Network [OSTI]

Datasets for the Evaluation of Substitution-Tolerant Subgraph Isomorphism Pierre H´eroux LITIS EA datasets allowing to evaluate the performance of subgraph iso- morphism approaches in presence of noisy data. In this paper, we present three datasets that can be used to evaluate the performance

Paris-Sud XI, Université de

110

A Dataset Search Engine for the Research Document Corpus  

E-Print Network [OSTI]

A Dataset Search Engine for the Research Document Corpus Meiyu Lu # , Srinivas Bangalore , Graham a proposed idea or system is to evaluate over a suitable dataset. However, to this date there have been no useful tools for researchers to understand which datasets have been used for what purpose, or in what

Cormode, Graham

111

Dataset Issues in Object Recognition J. Ponce1,2  

E-Print Network [OSTI]

Dataset Issues in Object Recognition J. Ponce1,2 , T.L. Berg3 , M. Everingham4 , D.A. Forsyth1 , M of Edinburgh, Edinburgh, UK Abstract. Appropriate datasets are required at all stages of object recognition datasets are lacking in several respects, and this paper discusses some of the lessons learned from

Everingham, Mark

112

Updating the Tyrol tree-ring dataset , U. Bntgen1  

E-Print Network [OSTI]

Updating the Tyrol tree-ring dataset J. Esper1 , U. Büntgen1 , D. Frank1 , T. Pichler2 , K in palaeoclimatology The Tyrol dataset is a collection of 71 Picea abies ring width measurement series from the study area in Tyrol in the central Alps. We here describe efforts of updating this relevant dataset

Nicolussi, Kurt

113

Overcoming Dataset Bias: An Unsupervised Domain Adaptation Approach  

E-Print Network [OSTI]

Overcoming Dataset Bias: An Unsupervised Domain Adaptation Approach Boqing Gong Dept. of Computer that recognition datasets are biased. Paying no heed to those biases, learning algorithms often result in classifiers with poor cross- dataset generalization. We are developing domain adaptation techniques to over

Grauman, Kristen

114

How Sensitive is Processor Customization to the Workload's Input Datasets?  

E-Print Network [OSTI]

How Sensitive is Processor Customization to the Workload's Input Datasets? Maximilien Breughe Zheng though is to what extent processor customiza- tion is sensitive to the training workload's input datasets. Current practice is to consider a single or only a few input datasets per workload during the processor

Eeckhout, Lieven

115

Probing Metagenomics by Rapid Cluster Analysis of Very Large Datasets  

E-Print Network [OSTI]

Probing Metagenomics by Rapid Cluster Analysis of Very Large Datasets Weizhong Li1 , John C. Wooley PLoS Biol 5, e16). Such datasets, not only by their sheer size, but also by many other features, defy datasets by advanced clustering strategies using the newly modified CD-HIT algorithm. We performed

Weitz, Joshua S.

116

In situ thermal performance of APP modified bitumen roof membranes coated with reflective coatings  

SciTech Connect (OSTI)

A multi-faceted field research program regarding seven atactic polypropylene (APP) modified bitumen membrane roof systems and four reflective coatings began in 1991. This long-term project is evaluating the performance of various APP modified bitumen membranes (both coated and uncoated), the comparative performance of coating application soon after membrane installation versus preweathering, coating performance, and aspects of recoating. This paper is a progress report on the in situ thermal performance of the various types of coatings compared to the thermal performance of the exposed membrane. The thermal performance of an adjacent ballasted ethylene propylene diene terpolymer (EPDM) roofing system is also described.

Carlson, J.D.; Smith, T.L. (National Roofing Contractors Association, Rosemont, IL (United States)); Christian, J.E. (Oak Ridge National Lab., TN (United States))

1992-01-01T23:59:59.000Z

117

In situ thermal performance of APP modified bitumen roof membranes coated with reflective coatings  

SciTech Connect (OSTI)

A multi-faceted field research program regarding seven atactic polypropylene (APP) modified bitumen membrane roof systems and four reflective coatings began in 1991. This long-term project is evaluating the performance of various APP modified bitumen membranes (both coated and uncoated), the comparative performance of coating application soon after membrane installation versus preweathering, coating performance, and aspects of recoating. This paper is a progress report on the in situ thermal performance of the various types of coatings compared to the thermal performance of the exposed membrane. The thermal performance of an adjacent ballasted ethylene propylene diene terpolymer (EPDM) roofing system is also described.

Carlson, J.D.; Smith, T.L. [National Roofing Contractors Association, Rosemont, IL (United States); Christian, J.E. [Oak Ridge National Lab., TN (United States)

1992-10-01T23:59:59.000Z

118

OFFICIAL POLICY 10.17 / 3.2 Mobile Websites and Mobile Applications ("Apps") 08/01/12  

E-Print Network [OSTI]

OFFICIAL POLICY 10.17 / 3.2 Mobile Websites and Mobile Applications ("Apps") 08/01/12 Policy Statement All existing or proposed College of Charleston mobile website and mobile application ("apps/or the Android store), must be reviewed and approved by both Information Technology and the Division of Marketing

Kasman, Alex

119

Cholesterol accumulation in Niemann Pick type C (NPC) model cells causes a shift in APP localization to lipid rafts  

SciTech Connect (OSTI)

It has been suggested that cholesterol may modulate amyloid-{beta} (A{beta}) formation, a causative factor of Alzheimer's disease (AD), by regulating distribution of the three key proteins in the pathogenesis of AD ({beta}-amyloid precursor protein (APP), {beta}-secretase (BACE1) and/or presenilin 1 (PS1)) within lipid rafts. In this work we tested whether cholesterol accumulation upon NPC1 dysfunction, which causes Niemann Pick type C disease (NPC), causes increased partitioning of APP into lipid rafts leading to increased CTF/A{beta} formation in these cholesterol-rich membrane microdomains. To test this we used CHO NPC1{sup -/-} cells (NPC cells) and parental CHOwt cells. By sucrose density gradient centrifugation we observed a shift in fl-APP/CTF compartmentalization into lipid raft fractions upon cholesterol accumulation in NPC vs. wt cells. Furthermore, {gamma}-secretase inhibitor treatment significantly increased fl-APP/CTF distribution in raft fractions in NPC vs. wt cells, suggesting that upon cholesterol accumulation in NPC1-null cells increased formation of APP-CTF and its increased processing towards A{beta} occurs in lipid rafts. Our results support that cholesterol overload, such as in NPC disease, leads to increased partitioning of APP/CTF into lipid rafts resulting in increased amyloidogenic processing of APP in these cholesterol-rich membranes. This work adds to the mechanism of the cholesterol-effect on APP processing and the pathogenesis of Alzheimer's disease and supports the role of lipid rafts in these processes.

Kosicek, Marko, E-mail: marko.kosicek@irb.hr [Division of Molecular Medicine, Ruder Boskovic Institute, Bijenicka 54, 10000 Zagreb (Croatia)] [Division of Molecular Medicine, Ruder Boskovic Institute, Bijenicka 54, 10000 Zagreb (Croatia); Malnar, Martina, E-mail: martina.malnar@irb.hr [Division of Molecular Medicine, Ruder Boskovic Institute, Bijenicka 54, 10000 Zagreb (Croatia)] [Division of Molecular Medicine, Ruder Boskovic Institute, Bijenicka 54, 10000 Zagreb (Croatia); Goate, Alison, E-mail: goate@icarus.wustl.edu [Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO 63110 (United States)] [Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO 63110 (United States); Hecimovic, Silva, E-mail: silva.hecimovic@irb.hr [Division of Molecular Medicine, Ruder Boskovic Institute, Bijenicka 54, 10000 Zagreb (Croatia)] [Division of Molecular Medicine, Ruder Boskovic Institute, Bijenicka 54, 10000 Zagreb (Croatia)

2010-03-12T23:59:59.000Z

120

RUTGERS MOBILE APP Stay connected with the Rutgers mobile application, available for the iPhone, iPad, iPod, as well  

E-Print Network [OSTI]

- 1 - RUTGERS MOBILE APP Stay connected with the Rutgers mobile application, available for the i Rutgers mobile web sites that work great whether you're on cellular or RUWireless. News: Up, and more. How to request this service: The Rutgers Mobile App can be downloaded at the App

Hanson, Stephen José

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


121

Evaluation of DysWebxia: A Reading App Designed for People with Dyslexia  

E-Print Network [OSTI]

Evaluation of DysWebxia: A Reading App Designed for People with Dyslexia Luz Rello Web Research for people with dyslexia. DysWebxia integrates previous results about the best way to present text for people with dyslexia to gether with a unique feature, the ability to show synonyms on demand for complex words

122

8-6-12 CRC online App1 UNIVERSITY OF ROCHESTER  

E-Print Network [OSTI]

policies, programs and activities. Questions on compliance should be directed to the particular school8-6-12 CRC online App1 UNIVERSITY OF ROCHESTER SCHOOL OF NURSING Clinical Research Coordinator Thank you for your interest in the University of Rochester School of Nursing Leadership in Health Care

Goldman, Steven A.

123

4-29-13 1 PMC Online App UNIVERSITY OF ROCHESTER  

E-Print Network [OSTI]

4-29-13 1 PMC Online App UNIVERSITY OF ROCHESTER SCHOOL OF NURSING Post Masters Certificate Program School of Nursing Post Masters Certificate Program. Semester to Begin Program Application Deadline School of Nursing and enclose the fee with your application. Copy of RN registration Current copy

Goldman, Steven A.

124

8-7-12 1 DNP Online APP UNIVERSITY OF ROCHESTER  

E-Print Network [OSTI]

policies, programs and activities. Questions on compliance should be directed to the particular school8-7-12 1 DNP Online APP UNIVERSITY OF ROCHESTER SCHOOL OF NURSING Instructions for Applicants of Rochester School of Nursing DNP Program. This program has rolling admission. A completed application

Goldman, Steven A.

125

4-29-13 HCML Online App1 UNIVERSITY OF ROCHESTER  

E-Print Network [OSTI]

, 601 Elmwood Ave Box SON, Rochester NY 14642 Questions may be directed to the School of Nursing Office4-29-13 HCML Online App1 UNIVERSITY OF ROCHESTER SCHOOL OF NURSING Health Care Organization Management and Leadership Program Thank you for your interest in the University of Rochester School

Goldman, Steven A.

126

8-19-13 1 PhD Online APP UNIVERSITY OF ROCHESTER  

E-Print Network [OSTI]

.urmc.rochester.edu/son) for information on current opportunities and sources of support. If you have any questions, please call the School8-19-13 1 PhD Online APP UNIVERSITY OF ROCHESTER SCHOOL OF NURSING Instructions for Applicants to the PhD Program Web page address: www.son.rochester.edu The University of Rochester School of Nursing

Goldman, Steven A.

127

8-2-12 1 Post B DNP Online APP UNIVERSITY OF ROCHESTER  

E-Print Network [OSTI]

, 601 Elmwood Avenue, Box SON, Rochester NY 14642 If you have any questions, please call the School, programs and activities. Questions on compliance should be directed to the particular school or department8-2-12 1 Post B DNP Online APP UNIVERSITY OF ROCHESTER SCHOOL OF NURSING Instructions

Goldman, Steven A.

128

8-1-12 1 MS Online App UNIVERSITY OF ROCHESTER  

E-Print Network [OSTI]

of Student Affairs, 601 Elmwood Avenue Box SON, Rochester NY 14642 Questions may be directed to the School, programs and activities. Questions on compliance should be directed to the particular school or department8-1-12 1 MS Online App UNIVERSITY OF ROCHESTER SCHOOL OF NURSING Nurse Practitioner Masters Program

Goldman, Steven A.

129

8-1-12 RNBSMS Online APP1 UNIVERSITY OF ROCHESTER  

E-Print Network [OSTI]

School of Nursing, Office of Student Affairs, 601 Elmwood Avenue Box SON, Rochester NY 14642 Questions8-1-12 RNBSMS Online APP1 UNIVERSITY OF ROCHESTER SCHOOL OF NURSING RN to BS to MS Program Web Page Address: www.son.rochester.edu Thank you for your interest in the University of Rochester School

Goldman, Steven A.

130

Form:Dataset | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision has beenFfe2fb55-352f-473b-a2dd-50ae8b27f0a6Theoretical vsFlintFluxInput your dataset name below to add

131

Template:DatasetValue | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:Seadov Pty LtdSteen,Ltd Jump to:Taos County,TeesAtlasTabs JumpDatabusNav JumpDatasetValue

132

DSM Electricity Savings Potential in the Buildings Sector in APP Countries  

SciTech Connect (OSTI)

The global economy has grown rapidly over the past decade with a commensurate growth in the demand for electricity services that has increased a country's vulnerability to energy supply disruptions. Increasing need of reliable and affordable electricity supply is a challenge which is before every Asia Pacific Partnership (APP) country. Collaboration between APP members has been extremely fruitful in identifying potential efficiency upgrades and implementing clean technology in the supply side of the power sector as well established the beginnings of collaboration. However, significantly more effort needs to be focused on demand side potential in each country. Demand side management or DSM in this case is a policy measure that promotes energy efficiency as an alternative to increasing electricity supply. It uses financial or other incentives to slow demand growth on condition that the incremental cost needed is less than the cost of increasing supply. Such DSM measures provide an alternative to building power supply capacity The type of financial incentives comprise of rebates (subsidies), tax exemptions, reduced interest loans, etc. Other approaches include the utilization of a cap and trade scheme to foster energy efficiency projects by creating a market where savings are valued. Under this scheme, greenhouse gas (GHG) emissions associated with the production of electricity are capped and electricity retailers are required to meet the target partially or entirely through energy efficiency activities. Implementation of DSM projects is very much in the early stages in several of the APP countries or localized to a regional part of the country. The purpose of this project is to review the different types of DSM programs experienced by APP countries and to estimate the overall future potential for cost-effective demand-side efficiency improvements in buildings sectors in the 7 APP countries through the year 2030. Overall, the savings potential is estimated to be 1.7 thousand TWh or 21percent of the 2030 projected base case electricity demand. Electricity savings potential ranges from a high of 38percent in India to a low of 9percent in Korea for the two sectors. Lighting, fans, and TV sets and lighting and refrigeration are the largest contributors to residential and commercial electricity savings respectively. This work presents a first estimates of the savings potential of DSM programs in APP countries. While the resulting estimates are based on detailed end-use data, it is worth keeping in mind that more work is needed to overcome limitation in data at this time of the project.

McNeil, MIchael; Letschert, Virginie; Shen, Bo; Sathaye, Jayant; de la Ru du Can, Stephane

2011-01-12T23:59:59.000Z

133

Framework for Interactive Parallel Dataset Analysis on the Grid  

SciTech Connect (OSTI)

We present a framework for use at a typical Grid site to facilitate custom interactive parallel dataset analysis targeting terabyte-scale datasets of the type typically produced by large multi-institutional science experiments. We summarize the needs for interactive analysis and show a prototype solution that satisfies those needs. The solution consists of desktop client tool and a set of Web Services that allow scientists to sign onto a Grid site, compose analysis script code to carry out physics analysis on datasets, distribute the code and datasets to worker nodes, collect the results back to the client, and to construct professional-quality visualizations of the results.

Alexander, David A.; Ananthan, Balamurali; /Tech-X Corp.; Johnson, Tony; Serbo, Victor; /SLAC

2007-01-10T23:59:59.000Z

134

Visualization of Cosmological Particle-Based Datasets  

E-Print Network [OSTI]

We describe our visualization process for a particle-based simulation of the formation of the first stars and their impact on cosmic history. The dataset consists of several hundred time-steps of point simulation data, with each time-step containing approximately two million point particles. For each time-step, we interpolate the point data onto a regular grid using a method taken from the radiance estimate of photon mapping. We import the resulting regular grid representation into ParaView, with which we extract isosurfaces across multiple variables. Our images provide insights into the evolution of the early universe, tracing the cosmic transition from an initially homogeneous state to one of increasing complexity. Specifically, our visualizations capture the build-up of regions of ionized gas around the first stars, their evolution, and their complex interactions with the surrounding matter. These observations will guide the upcoming James Webb Space Telescope, the key astronomy mission of the next decade.

Paul Arthur Navrtil; Jarrett L. Johnson; Volker Bromm

2007-08-07T23:59:59.000Z

135

HOW-TO / USER GUIDEfor iOS Devices App Version 3.1.2.1  

E-Print Network [OSTI]

Install Select Search then type & select Emergensee Launch Emergensee App 1 4 2 5 3 6 STEP STEP STEP STEP Account options. Read & Accept Terms of Use. 1 2 STEP STEP #12;5 Sign-in to an Existing Account if you · Create an Account Password · Re-Enter Password · EmergenSee Pro · EmergenSee U · EmergenSee #12;7 How

Napier, Terrence

136

Creating a Global Humidity DatasetCreating a Global Humidity Dataset Progress with the Marine ComponentProgress with the Marine Component  

E-Print Network [OSTI]

Creating a Global Humidity DatasetCreating a Global Humidity Dataset ­­ Progress with the Marine PROJECT SUMMARY CLIMATOLOGIES Create a global gridded monthly mean dataset of surface vapour pressure, Exeter, UK ­ CASE sponsors ICOADS, NCDC ­ for providing the marine dataset Philip Brohan, Hadley Centre

Feigon, Brooke

137

Multivariate Protein Signatures of Pre-Clinical Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative (ADNI) Plasma Proteome Dataset  

E-Print Network [OSTI]

these samples. Following dataset pruning, 17 analytes passedwere incorporated back into the dataset for assessment ofADNI) Plasma Proteome Dataset Daniel Johnstone 1,2 ,

Johnstone, Daniel; Milward, Elizabeth A.; Berretta, Regina; Moscato, Pablo

2012-01-01T23:59:59.000Z

138

Development and evaluation of a thermodynamic dataset for phases of interest in CO2 mineral sequestration in basaltic rocks  

E-Print Network [OSTI]

evaluation of a thermodynamic dataset for phases of interestKeywords: Thermodynamic dataset CO2water basaltABSTRACT A thermodynamic dataset describing 36 mineral

Aradottir, E.S.P.

2013-01-01T23:59:59.000Z

139

Reconstructing thawing quintessence with multiple datasets  

E-Print Network [OSTI]

In this work we model the quintessence potential in a Taylor series expansion, up to second order, around the present-day value of the scalar field. The field is evolved in a thawing regime assuming zero initial velocity. We use the latest data from the Planck satellite, baryonic acoustic oscillations observations from the Sloan Digital Sky Survey, and Supernovae luminosity distance information from Union$2.1$ to constrain our models parameters, and also include perturbation growth data from WiggleZ. We show explicitly that the growth data does not perform as well as the other datasets in constraining the dark energy parameters we introduce. We also show that the constraints we obtain for our model parameters, when compared to previous works of nearly a decade ago, have not improved significantly. This is indicative of how little dark energy constraints, overall, have improved in the last decade, even when we add new growth of structure data to previous existent types of data.

Lima, Nelson A; Sahln, Martin; Parkinson, David

2015-01-01T23:59:59.000Z

140

A Comparison of State-of-the-Art Technologies for Irreversible Compression of Large Medical Datasets  

E-Print Network [OSTI]

Datasets Alberto Signoroni, Mario Pezzoni, Claudia Tonoli and Riccardo Leonardi University of Brescia datasets, also keep- ing into account relevant features related to modern appli- cation requirements and infrastructures (PACS, teleradiology) involving large datasets. Reproducibility and possible extension

Signoroni, Alberto

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


141

Multiresolution Approaches to Representation and Visualization of Large Influenza Virus Sequence Datasets  

E-Print Network [OSTI]

Datasets Leonid Zaslavsky National Center for Biotechnology Information National Library of Medicine dataset is characterized by low estimated values of the Kolmogorov (box) dimension. Multi- scale methodologies allow interactive visual representation of the dataset and accelerate computations by importance

Levin, Judith G.

142

Tension in the Recent Type Ia Supernovae Datasets  

E-Print Network [OSTI]

In the present work, we investigate the tension in the recent Type Ia supernovae (SNIa) datasets Constitution and Union. We show that they are in tension not only with the observations of the cosmic microwave background (CMB) anisotropy and the baryon acoustic oscillations (BAO), but also with other SNIa datasets such as Davis and SNLS. Then, we find the main sources responsible for the tension. Further, we make this more robust by employing the method of random truncation. Based on the results of this work, we suggest two truncated versions of the Union and Constitution datasets, namely the UnionT and ConstitutionT SNIa samples, whose behaviors are more regular.

Hao Wei

2010-04-07T23:59:59.000Z

143

E-Print Network 3.0 - association dataset methodological Sample...  

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

dataset methodological Search Powered by Explorit Topic List Advanced Search Sample search results for: association dataset methodological Page: << < 1 2 3 4 5 > >> 1 IOWA STATE...

144

Green Button App of the Week Part 2: Melon | Department of Energy  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:YearRound-UpHeatMulti-Dimensional Subject: GuidanceNotGrand Coulee-CrestonAmericanApp of the Week

145

Green Button App of the Week Part 1: Leafully | Department of Energy  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation ProposedUsingFun with Big Sky LearningGetGraphene's 3D Counterpart Print1, 2009Button App

146

Archiving a Complex Dataset:: IST-3 - A case study  

E-Print Network [OSTI]

would include (but not be limited to) drug regulatory agencies, research governance organisations, lawyers and scientists wishing to analyse the data under appropriate data sharing licences. The trial datasets therefore had to be understood as a whole so...

Drever, Jonathan

2014-08-26T23:59:59.000Z

147

Development of Regional Wind Resource and Wind Plant Output Datasets...  

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

50-47676 March 2010 Development of Regional Wind Resource and Wind Plant Output Datasets Final Subcontract Report 15 October 2007 - 15 March 2009 3TIER Seattle, Washington National...

148

A survey of results on mobile phone datasets analysis  

E-Print Network [OSTI]

In this paper, we review some advances made recently in the study of mobile phone datasets. This area of research has emerged a decade ago, with the increasing availability of large-scale anonymized datasets, and has grown into a stand-alone topic. We will survey the contributions made so far on the social networks that can be constructed with such data, the study of personal mobility, geographical partitioning, urban planning, and help towards development as well as security and privacy issues.

Blondel, Vincent D; Krings, Gautier

2015-01-01T23:59:59.000Z

149

Determining Mountaintop Mining Locations in West Virginia Using Elevation Datasets  

E-Print Network [OSTI]

Determining Mountaintop Mining Locations in West Virginia Using Elevation Datasets Danny Rowland Haskell Indian Nations University Image from: http://www.colorado.edu/geography/cartpro/cartography2/spring2006/syphers.../projects/westvirginia/whatis.htm Image from: http://washingtonindependent.com/49008/congress-takes-on-mountaintop-mining Mountaintop Mining Operation 2 Elevation datasets: NED & SRTM West Virginia NED SRTM Elevation Change Over ~30 Year Period 20021970s SRTM Subtracted from...

Rowland, Danny

2009-11-18T23:59:59.000Z

150

App. I  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAbout theOFFICEAmes LaboratoryAntonya Sanders-Promoting nanoscienceAparna,D

151

App. I  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAbout theOFFICEAmes LaboratoryAntonya Sanders-Promoting

152

App. I  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone by E-mailRadioimmunotherapy of Cancers. |Contract No.:

153

The Blackboard Mobile Learn app for Android devices allows you to access your Blackboard courses in the palm of your hands.  

E-Print Network [OSTI]

The Blackboard Mobile Learn app for Android devices allows you to access your Blackboard courses. To download and install the app, go to the Play Store and search for Blackboard Mobile Learn 2. Once you have in to CUNY Portal. Blackboard Mobile Learn for Android 3 4 Revised: 3.27.2014 Bb9: Blackboard Mobile

Qiu, Weigang

154

'g55wld0098.dat', Version 1.0, March 1999 1. The Dataset  

E-Print Network [OSTI]

1 'g55wld0098.dat', Version 1.0, March 1999 1. The Dataset: An historic monthly precipitation dataset for global land areas from 1900 to 1998, gridded at 5deg resolution (a 2.5 by 3.75deg resolution. Letts., 25, 3379-3382. The station dataset from which this gridded dataset has been constructed

Feigon, Brooke

155

RED: a Rich Epinions Dataset for Recommender Systems Simon Meyffret1,2  

E-Print Network [OSTI]

RED: a Rich Epinions Dataset for Recommender Systems Simon Meyffret1,2 , Emmanuel Guillot1}@liris.cnrs.fr ABSTRACT Recommender Systems require specific datasets to evaluate their approach. They do not require is not gathered in today datasets. In this paper, we provide a dataset containing reviews from users on items

Paris-Sud XI, Université de

156

A Comparison of Phylogenetic Reconstruction Methods on an IE Dataset Luay Nakhleh Tandy Warnow  

E-Print Network [OSTI]

A Comparison of Phylogenetic Reconstruction Methods on an IE Dataset Luay Nakhleh Tandy Warnow Dept the dataset, we study the consequences for phylogenetic reconstruction of restricting the data to lexical datasets that use only lexical characters being probably less accurate than analyses based upon datasets

Evans, Steven N.

157

The 30-year TAMSAT African Rainfall Climatology1 And Time-series (TARCAT) Dataset  

E-Print Network [OSTI]

Page 1 The 30-year TAMSAT African Rainfall Climatology1 And Time-series (TARCAT) Dataset 2 Authors 2 Key points1 Development of a satellite based 30 year rainfall dataset for Africa2 The dataset has been designed to be temporally consistency3 The dataset skilfully captures interannual

Allan, Richard P.

158

Exploring Constraints to Eciently Mine Emerging Patterns from Large High-dimensional Datasets  

E-Print Network [OSTI]

Exploring Constraints to E?ciently Mine Emerging Patterns from Large High-dimensional Datasets proposed recently to capture changes or di#11;erences between datasets: an EP is a multi- variate feature whose support increases sharply from a back- ground dataset to a target dataset, and the support ratio

Dong, Guozhu

159

To appear in Proc. KDD-97 A dataset decomposition approach to  

E-Print Network [OSTI]

To appear in Proc. KDD-97 A dataset decomposition approach to data mining and machine discovery to analyze a given dataset, the method decomposes it to a hierar- chy of smaller and less complex datasets allocation dataset, showing that the decom- position can (1) discover meaningful intermedi- ate concepts, (2

Bohanec, Marko

160

An air itinerary choice model based on a mixed RP/SP dataset  

E-Print Network [OSTI]

An air itinerary choice model based on a mixed RP/SP dataset Bilge Atasoy Michel Bierlaire April/SP dataset. The aim of the combination of the two datasets is to exploit the variability of the SP data is modeled as a latent class. In this study we develop an itinerary choice model based on a real dataset

Bierlaire, Michel

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


161

Processing Steps For Creating Standardized 5-Minute-by-Lane Datasets  

E-Print Network [OSTI]

1 Processing Steps For Creating Standardized 5-Minute-by-Lane Datasets (program code in "city measures. · Dataset DS1: Import original source data into SAS using INFILE statement. In SAS, we give this first dataset a "DS1" label (DataSet1). Most, if not all, original source data is submitted as ASCII

162

'gu23wld0098.dat', Version 1.0, March 1999 1. The Dataset  

E-Print Network [OSTI]

'gu23wld0098.dat', Version 1.0, March 1999 1. The Dataset An historical monthly precipitation dataset for global land areas from 1900 to 1998, gridded at 2.5° latitude by 3.75° longitude resolution (a. Letts., 25, 3379-3382. The station dataset from which this gridded dataset has been constructed

Feigon, Brooke

163

On the Use of Perceptual Cues and Data Mining for Effective Visualization of Scientific Datasets  

E-Print Network [OSTI]

On the Use of Perceptual Cues and Data Mining for Effective Visualization of Scientific Datasets datasets are often difficult to analyse or visualize, due to their large size and high dimensionality. We areas of interest within the dataset. This allows us to reducea dataset's size and dimensionality

Healey, Christopher G.

164

Effects of the Training Dataset Characteristics on the Performance of Nine Species Distribution Models  

E-Print Network [OSTI]

Effects of the Training Dataset Characteristics on the Performance of Nine Species Distribution species need to be fitted to a training dataset before practical use. The training dataset of this paper is to study the effect of the training dataset characteristics on model performance and to compare

Kratochvíl, Lukas

165

The LIRIS Human activities dataset and the ICPR 2012 human activities recognition and localization competition  

E-Print Network [OSTI]

The LIRIS Human activities dataset and the ICPR 2012 human activities recognition and localization-69621, France March 28, 2012 Abstract We describe the LIRIS human activities dataset, the dataset used competitions and existing datasets, the tasks focus on complex human behavior involving several people

Wolf, Christian

166

This page shows how to use the My Pitt Video (Panopto) iOS application on an iPad. To log into the My Pitt Video (Panopto) iOS App, tap "Sign In" in the top left corner.  

E-Print Network [OSTI]

iPad App iPad App This page shows how to use the My Pitt Video (Panopto) iOS application on an iPad. Login To log into the My Pitt Video (Panopto) iOS App, tap "Sign In" in the top left corner. In the Sign name and tap "Record a new video" to begin recording. Page 9 of 17 #12;iPad App Once you are finished

Benos, Panayiotis "Takis"

167

Pacific Northwest Region MAPS dataset retrospective analysis Project Title: USFS Region Six MAPS Dataset Re-analysis for the Development of Management  

E-Print Network [OSTI]

Pacific Northwest Region MAPS dataset ­ retrospective analysis Project Title: USFS Region Six MAPS Dataset Re-analysis for the Development of Management and Climate Change Support Tools for Landbird) demographic dataset may reveal how predicted patterns of climate-related forest fragmentation, pest outbreak

DeSante, David F.

168

Figure 1. The dataset for the running example is excerpted at left, arranged in the typical manner for MVPA. The boxes at right introduce the dataset  

E-Print Network [OSTI]

Figure 1. The dataset for the running example is excerpted at left, arranged in the typical manner for MVPA. The boxes at right introduce the dataset representation used in later figures. In these boxes the "dataset-wise" scheme, the examples are relabeled prior to conducting the cross- validation, while

169

How energy-efficient is your cloud app? Energy measurements in virtualized environments with PowerAPI  

E-Print Network [OSTI]

How energy-efficient is your cloud app? Energy measurements in virtualized environments with PowerAPI Context Energy-efficiency major concern in data centers Existing approaches work for physical servers consumption in virtualized environments Measurements are first step towards energy-efficient data centers Host

Boyer, Edmond

170

PDX\\APP L_STATE FED INVENTORY.DOC 1 Inventory of State and Federal Fish and Wildlife  

E-Print Network [OSTI]

PDX\\APP L_STATE FED INVENTORY.DOC 1 APPENDIX L Inventory of State and Federal Fish and Wildlife Plans and Programs This inventory was conducted in the spring of 2003 by the Oregon Department of Fish and Wildlife under contract to WRI. The following pages are printed from the spreadsheet used in the inventory

171

Get the app on your phone or visit creditaction.org.uk/students Get smart about money  

E-Print Network [OSTI]

2013 Get the app on your phone or visit creditaction.org.uk/students Get smart about money the essential Independent, in-depth advice Everything student money Moneymanual Get it. Keep it. Make it go further. Money matters you need to know about #12;04 01 At Santander we understand the importance

Birmingham, University of

172

Bayesian evidence as a tool for comparing datasets  

E-Print Network [OSTI]

We introduce a new conservative test for quantifying the consistency of two or more datasets. The test is based on the Bayesian answer to the question, ``How much more probable is it that all my data were generated from the same model system than if each dataset were generated from an independent set of model parameters?''. We make explicit the connection between evidence ratios and the differences in peak chi-squared values, the latter of which are more widely used and more cheaply calculated. Calculating evidence ratios for three cosmological datasets (recent CMB data (WMAP, ACBAR, CBI, VSA), SDSS and the most recent SNe Type 1A data) we find that concordance is favoured and the tightening of constraints on cosmological parameters is indeed justified.

Phil Marshall; Nutan Rajguru; Anze Slosar

2007-10-30T23:59:59.000Z

173

The Wind Integration National Dataset (WIND) toolkit (Presentation)  

SciTech Connect (OSTI)

Regional wind integration studies require detailed wind power output data at many locations to perform simulations of how the power system will operate under high penetration scenarios. The wind datasets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as being time synchronized with available load profiles.As described in this presentation, the WIND Toolkit fulfills these requirements by providing a state-of-the-art national (US) wind resource, power production and forecast dataset.

Caroline Draxl: NREL

2014-01-01T23:59:59.000Z

174

Using Large Datasets to Forecast Sectoral Employment Rangan Gupta*  

E-Print Network [OSTI]

Using Large Datasets to Forecast Sectoral Employment Rangan Gupta* Department of Economics Bayesian and classical methods to forecast employment for eight sectors of the US economy. In addition-sample period and January 1990 to March 2009 as the out-of- sample horizon, we compare the forecast performance

Ahmad, Sajjad

175

A Polygon-based Methodology for Mining Related Spatial Datasets  

E-Print Network [OSTI]

, such as countries, and in that they can be used for the modeling of spatial events, such as air pollution. MoreoverA Polygon-based Methodology for Mining Related Spatial Datasets Sujing Wang, Chun-Sheng Chen clusters. This paper claims that polygon analysis is particularly useful for mining related, spatial

Eick, Christoph F.

176

Global Sediment Thickness Dataset updated for the Australian-Antarctic  

E-Print Network [OSTI]

Global Sediment Thickness Dataset updated for the Australian-Antarctic Southern Ocean Joanne author: jo.whittaker@utas.edu.au Key Points - Global minimum sediment thickness compilation updated for Australia Antarctica - Sediment thicknesses computed from seismic reflection and refraction data - Sediment

Müller, Dietmar

177

Capturing Datasets ... is only the half of it!  

E-Print Network [OSTI]

that the project is merely a stepping stone in providing the ability to deliver their science. In the majority of cases the research continues from one grant to the next and therefore the datasets at any given time are merely snap shots of a lifelong commitment...

Simpson, Colin

2014-08-26T23:59:59.000Z

178

DECOMPOSITION OF MULTIVARIATE DATASETS WITH STRUCTURE/ORDERING  

E-Print Network [OSTI]

analysis. However, contrary to Fourier decomposition these new variables are located in frequency as well as location (space, time, wavelength etc). 1 Introduction The maximum autocorrelation factor (MAF) analysisDECOMPOSITION OF MULTIVARIATE DATASETS WITH STRUCTURE/ORDERING OF OBSERVATIONS OR VARIABLES USING

179

Eastern Renewable Generation Integration Study Solar Dataset (Presentation)  

SciTech Connect (OSTI)

The National Renewable Energy Laboratory produced solar power production data for the Eastern Renewable Generation Integration Study (ERGIS) including "real time" 5-minute interval data, "four hour ahead forecast" 60-minute interval data, and "day-ahead forecast" 60-minute interval data for the year 2006. This presentation provides a brief overview of the three solar power datasets.

Hummon, M.

2014-04-01T23:59:59.000Z

180

OctOber 2011 | ArgOnne nAtiOnAl lAbOrAtOry NG Workshop summary report appeNDIX F  

E-Print Network [OSTI]

OctOber 2011 | ArgOnne nAtiOnAl lAbOrAtOry NG Workshop summary report ­ appeNDIX F presentation;OctOber 2011 | ArgOnne nAtiOnAl lAbOrAtOry NG Workshop summary report ­ appeNDIX F 2 #12;OctOber 2011 | ArgOnne nAtiOnAl lAbOrAtOry NG Workshop summary report ­ appeNDIX F 3 #12;OctOber 2011 | ArgOnne n

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


181

OctOber 2011 | ArgOnne nAtiOnAl lAbOrAtOry NG Workshop summary report appeNDIX G  

E-Print Network [OSTI]

OctOber 2011 | ArgOnne nAtiOnAl lAbOrAtOry NG Workshop summary report ­ appeNDIX G presentation & Associates, LLC 1 #12;OctOber 2011 | ArgOnne nAtiOnAl lAbOrAtOry NG Workshop summary report ­ appeNDIX G 2 #12;OctOber 2011 | ArgOnne nAtiOnAl lAbOrAtOry NG Workshop summary report ­ appeNDIX G 3 #12;Oct

182

Organic aerosol components observed in Northern Hemispheric datasets from Aerosol Mass Spectrometry  

E-Print Network [OSTI]

In this study we compile and present results from the factor analysis of 43 Aerosol Mass Spectrometer (AMS) datasets (27 of the datasets are reanalyzed in this work). The components from all sites, when taken together, ...

Kroll, Jesse

183

An equal opportunity educator and employer NonUofM-ScholarshipApp_13.indd Web 10/13 First name Last name  

E-Print Network [OSTI]

An equal opportunity educator and employer NonUofM-ScholarshipApp_13.indd · Web · 10/13 First name-managed scholarship in print, web, video, social media, and/or other publications. Yes No Application Instructions

Amin, S. Massoud

184

Musculoskeletal simulation model generation from MRI datasets and motion capture data  

E-Print Network [OSTI]

Musculoskeletal simulation model generation from MRI datasets and motion capture data Jérôme Schmid

Paris-Sud XI, Université de

185

Genetic variation in the odorant receptors family 13 and the MHC loci influence mate selection in a Multiple Sclerosis dataset  

E-Print Network [OSTI]

S2. Validation on MHC results with the IMAGEN dataset.In the screening IMSGC dataset, the MHC region (663 SNPs)in a multiple sclerosis dataset. BMC Genomics 2010 11:626.

2010-01-01T23:59:59.000Z

186

Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets  

E-Print Network [OSTI]

for individual genes in the dataset of Wang, et al. usingfor individual genes in the dataset of Sorlie, et al. usingfor individual genes in the dataset of Wang, et al. using

Martin, Katherine J.

2008-01-01T23:59:59.000Z

187

Indoor carbon dioxide concentrations and sick building syndrome symptoms in the BASE study revisited: Analyses of the 100 building dataset  

E-Print Network [OSTI]

OF THE 100 BUILDING DATASET CA Erdmann 1 , KC Steiner 1 ,and Evaluation (BASE) dataset, higher workday time-averaged100-building 1994-1998 BASE dataset. Multivariate logistic

Erdmann, Christine A.; Steiner, Kate C.; Apte, Michael G.

2002-01-01T23:59:59.000Z

188

Attribute Preserving Dataset Simplification Jason D. Walter and Christopher G. Healey  

E-Print Network [OSTI]

Attribute Preserving Dataset Simplification Jason D. Walter and Christopher G. Healey Department of feature preserving mesh simplification to the problem of managing large, multidimensional datasets during scientific visualization. To allow this, we view a sci- entific dataset as a triangulated mesh of data

Healey, Christopher G.

189

THE MILLION SONG DATASET Thierry Bertin-Mahieux, Daniel P.W. Ellis  

E-Print Network [OSTI]

THE MILLION SONG DATASET Thierry Bertin-Mahieux, Daniel P.W. Ellis Columbia University LabROSA, EE {brian, paul}@echonest.com ABSTRACT We introduce the Million Song Dataset, a freely-available collection research dataset in our field. As an illustra- tion, we present year prediction as an example application

Ellis, Dan

190

CVS-Vintage: A Dataset of 14 CVS Repositories of Java Software  

E-Print Network [OSTI]

CVS-Vintage: A Dataset of 14 CVS Repositories of Java Software Martin Monperrus and Matias Martinez INRIA Technical Report, 2012. Abstract This paper presents a dataset of 14 CVS repositories of Java applications. This dataset aims at supporting the replication of early papers in the field of software

Paris-Sud XI, Université de

191

LCAV-31: A Dataset for Light Field Object Recognition Alireza Ghasemi , Nelly Afonso and Martin Vetterli  

E-Print Network [OSTI]

LCAV-31: A Dataset for Light Field Object Recognition Alireza Ghasemi , Nelly Afonso and Martin present LCAV-31, a multi-view object recognition dataset designed specifically for benchmarking light field image analysis tasks. The principal distinctive factor of LCAV-31 compared to similar datasets

Vetterli, Martin

192

A tail strength measure for assessing the overall significance in a dataset  

E-Print Network [OSTI]

A tail strength measure for assessing the overall significance in a dataset Jonathan Taylor Robert, and illustrate its use on a number of real datasets. 1 Introduction Dave et al. (2004) published a study we would expect to see by chance. Perhaps this is why the Golub dataset has become the most common

Tibshirani, Robeert

193

COMP-598: Applied Machine Learning Mini-project #1: Building a new ML dataset  

E-Print Network [OSTI]

COMP-598: Applied Machine Learning Mini-project #1: Building a new ML dataset Due on September 23, 11:59pm. Background: The goal of this project is to collect a new machine learning dataset, and identify an interesting prediction question that can be tackled using this dataset (regression

Pineau, Joelle

194

EVITA: A Prototype System for Efficient Visualization and Interrogation of Terascale Datasets  

E-Print Network [OSTI]

EVITA: A Prototype System for Efficient Visualization and Interrogation of Terascale Datasets Raghu and visualization techniques has not kept pace with the growth in size and complexity of such datasets. To address datasets. The cornerstone of the EVITA system is a representational scheme that allows ranked access

Fowler, James E.

195

OBIT DEVELOPMENT MEMO SERIES NO. 21 1 Efficacy of Obit Threading on an EVLA Dataset  

E-Print Network [OSTI]

OBIT DEVELOPMENT MEMO SERIES NO. 21 1 Efficacy of Obit Threading on an EVLA Dataset W. D. Cotton, R of the Obit wide bandwidth imager MFImage in realistic tests on an EVLA dataset including multiple iterations://www.cv.nrao.edu/bcotton/Obit.html) to do wide- band imaging of a recent EVLA dataset. This test uses multiple iterations of self

Groppi, Christopher

196

AHIS Dataset Search Engine: An intelligent approach to EML Data Management  

E-Print Network [OSTI]

AHIS Dataset Search Engine: An intelligent approach to EML Data Management Hung V. Nguyen, Corinna Language ­ EML format. Efficient dataset retrieval system needs to understand the important keywords with text mining techniques for ecological datasets to bridge this gap Technique: · Data extraction: Extract

Hall, Sharon J.

197

VIVDR -Vortex-induced vibration data repository An overview of available riser datasets  

E-Print Network [OSTI]

VIVDR - Vortex-induced vibration data repository An overview of available riser datasets http://oe.mit.edu/VIV H. Mukundan and M. Triantafyllou 20 April 2008 #12;NDP 38m long riser model datasets #12;33 q Rig q Tension applied through spring-supported clump weights NDP 38m long riser model datasets

198

ComSIS Vol. 1, No. 1, February 2004 75 Network Models of Massive Datasets  

E-Print Network [OSTI]

ComSIS Vol. 1, No. 1, February 2004 75 Network Models of Massive Datasets Vladimir Boginski 1 overview of the methodology of modeling massive datasets arising in various applications as networks. This approach is often useful for extracting non-trivial information from the datasets by applying standard

Butenko, Sergiy

199

iVIBRATE: Interactive Visualization Based Framework for Clustering Large Datasets (Version 3)  

E-Print Network [OSTI]

iVIBRATE: Interactive Visualization Based Framework for Clustering Large Datasets (Version 3) Keke and high-quality clustering of large datasets continues to be one of the most important problems in large- scale data analysis. A commonly used methodology for cluster analysis on large datasets is the three

Liu, Ling

200

Bootstrapping for Significance of Compact Clusters in Multi-dimensional Datasets  

E-Print Network [OSTI]

Bootstrapping for Significance of Compact Clusters in Multi-dimensional Datasets Ranjan Maitra in the clustering of multi-dimensional datasets. The developed procedure compares two models and declares the more of the procedure is illustrated on two well-known classification datasets and comprehensively evaluated in terms

Maitra, Ranjan

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


201

Selecting the Number of Imputed Datasets When Using Multiple Imputation for Missing Data and Disclosure Limitation  

E-Print Network [OSTI]

Selecting the Number of Imputed Datasets When Using Multiple Imputation for Missing Data and disclosure limitation simultaneously. First, fill in the missing data to generate m completed datasets, then replace confidential values in each completed dataset with r imputations. I investigate how to select m

Reiter, Jerome P.

202

A tail strength measure for assessing the overall significance in a dataset  

E-Print Network [OSTI]

A tail strength measure for assessing the overall significance in a dataset Jonathan Taylor, and illustrate its use on a number of real datasets. 1 Introduction Dave et al. (2004) published a study than we would expect to see by chance. Perhaps this is why the Golub dataset has become the most common

Tibshirani, Robeert

203

Mining Image Datasets Using Perceptual Association Rules Jelena Tesic, Shawn Newsam and B. S. Manjunath  

E-Print Network [OSTI]

Mining Image Datasets Using Perceptual Association Rules Jelena Tesi´c, Shawn Newsam and B. S for applying traditional data mining techniques to the non-traditional domain of image datasets for the purpose association rules, are used to distill the frequent perceptual events in large image datasets in order to dis

California at Santa Barbara, University of

204

GeoLens: Enabling Interactive Visual Analytics over Large-scale, Multidimensional Geospatial Datasets  

E-Print Network [OSTI]

Datasets Jared Koontz, Matthew Malensek, and Sangmi Lee Pallickara Department of Computer Science, Colorado for scientists are needed. This is critical when scientists are manipulating voluminous datasets and especially when they need to explore datasets interactively to develop their hypotheses. In this paper, we present

Pallickara, Sangmi

205

DataHub: Collaborative Data Science & Dataset Version Management at Scale  

E-Print Network [OSTI]

DataHub: Collaborative Data Science & Dataset Version Management at Scale Anant Bhardwaj1 , Souvik teams collaboratively curate and analyze large datasets. In- spired by software version control systems like git, we propose (a) a dataset version control system, giving users the ability to create, branch

206

1/28/2014 CFCAM Workshop 2014 1 How to generate ^ PAW Atomic Datasets*  

E-Print Network [OSTI]

1/28/2014 CFCAM Workshop 2014 1 Good How to generate ^ PAW Atomic Datasets* N. A. W. Holzwarth 2014 2 Good How to generate ^ PAW Atomic Datasets Challenges Tricks Opportunities for collaboration Importance of having several independent codes (both for atomic dataset generation and for materials

Holzwarth, Natalie

207

A New Global Rayleigh and Love Wave Group Velocity Dataset For Constraining Lithosphere Properties  

E-Print Network [OSTI]

A New Global Rayleigh and Love Wave Group Velocity Dataset For Constraining Lithosphere Properties features and fit our data very well. This dataset will be used to constrain lithospheric structure globally the global datasets used in Ritzwoller et al. (2002) already consist of more than 100,000 paths, the nature

Laske, Gabi

208

iVIBRATE: Interactive Visualization Based Framework for Clustering Large Datasets  

E-Print Network [OSTI]

iVIBRATE: Interactive Visualization Based Framework for Clustering Large Datasets Keke Chen Ling of large datasets continues to be one of the most important problems in large- scale data analysis. A commonly used methodology for cluster analysis on large datasets is the three-phase framework of "sampling

209

Error estimation of bathymetric grid models derived from historic and contemporary datasets  

E-Print Network [OSTI]

1 Error estimation of bathymetric grid models derived from historic and contemporary datasets and rapidly collecting dense bathymetric datasets. Sextants were replaced by radio navigation, then transit, to digitized contours; the test dataset shows examples of all of these types. From this database, we assign

New Hampshire, University of

210

A Comprehensive Comparison of Ligand-Based Virtual Screening Tools Against the DUD Dataset  

E-Print Network [OSTI]

A Comprehensive Comparison of Ligand-Based Virtual Screening Tools Against the DUD Dataset Reveals) dataset comprising over 100,000 compounds distributed across 40 protein targets. The DUD was developed and the composition of the DUD dataset itself. We propose that in order to To whom correspondence should be addressed

Paris-Sud XI, Université de

211

Statistical Characteristics of Daily Precipitation: Comparisons of Gridded and Point Datasets  

E-Print Network [OSTI]

Statistical Characteristics of Daily Precipitation: Comparisons of Gridded and Point Datasets Gauge Dataset (URD) and those of its nearest (rain gauge) station. To further examine differences between the two datasets, return periods of daily precipitation were calculated over a region encompassing

Roy Chowdhury, Rinku

212

A classical dataset from Williams, and its role in the study of supersaturated designs.  

E-Print Network [OSTI]

A classical dataset from Williams, and its role in the study of supersaturated designs. Rolf Sundberg April 29, 2008 Abstract A Plackett­Burman type dataset from a paper by Williams (1968), with 28 observations and 24 two-level factors, has become a standard dataset for illustrating construction (by halving

Sundberg, Rolf

213

Using metadata to improve spatial dataset quality during updates Christelle Pierkot  

E-Print Network [OSTI]

1 Using metadata to improve spatial dataset quality during updates Christelle Pierkot LIRMM, D and degrade the dataset's quality. Within this broad issue, we limit our scope to the updating of geographic their integration into different datasets. In this context, our objective is to propose solutions to allow coherent

Paris-Sud XI, Université de

214

Robust Machine Learning Applied to Terascale Astronomical Datasets  

E-Print Network [OSTI]

We present recent results from the Laboratory for Cosmological Data Mining (http://lcdm.astro.uiuc.edu) at the National Center for Supercomputing Applications (NCSA) to provide robust classifications and photometric redshifts for objects in the terascale-class Sloan Digital Sky Survey (SDSS). Through a combination of machine learning in the form of decision trees, k-nearest neighbor, and genetic algorithms, the use of supercomputing resources at NCSA, and the cyberenvironment Data-to-Knowledge, we are able to provide improved classifications for over 100 million objects in the SDSS, improved photometric redshifts, and a full exploitation of the powerful k-nearest neighbor algorithm. This work is the first to apply the full power of these algorithms to contemporary terascale astronomical datasets, and the improvement over existing results is demonstrable. We discuss issues that we have encountered in dealing with data on the terascale, and possible solutions that can be implemented to deal with upcoming petascale datasets.

Nicholas M. Ball; Robert J. Brunner; Adam D. Myers

2007-10-24T23:59:59.000Z

215

Wind Integration Datasets from the National Renewable Energy Laboratory (NREL)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The Wind Integration Datasets provide time-series wind data for 2004, 2005, and 2006. They are intended to be used by energy professionals such as transmission planners, utility planners, project developers, and university researchers, helping them to perform comparisons of sites and estimate power production from hypothetical wind plants. NREL cautions that the information from modeled data may not match wind resource information shown on NREL;s state wind maps as they were created for different purposes and using different methodologies.

216

Parton distributions based on a maximally consistent dataset  

E-Print Network [OSTI]

The choice of data that enters a global QCD analysis can have a substantial impact on the resulting parton distributions and their predictions for collider observables. One of the main reasons for this has to do with the possible presence of inconsistencies, either internal within an experiment or external between different experiments. In order to assess the robustness of the global fit, different definitions of a conservative PDF set, that is, a PDF set based on a maximally consistent dataset, have been introduced. However, these approaches are typically affected by theory biases in the selection of the dataset. In this contribution, after a brief overview of recent NNPDF developments, we propose a new, fully objective, definition of a conservative PDF set, based on the Bayesian reweighting approach. Using the new NNPDF3.0 framework, we produce various conservative sets, which turn out to be mutually in agreement within the respective PDF uncertainties, as well as with the global fit. We explore some of their implications for LHC phenomenology, finding also good consistency with the global fit result. These results provide a non-trivial validation test of the new NNPDF3.0 fitting methodology, and indicate that possible inconsistencies in the fitted dataset do not affect substantially the global fit PDFs.

Juan Rojo

2014-09-10T23:59:59.000Z

217

Filtergraph: An Interactive Web Application for Visualization of Astronomy Datasets  

E-Print Network [OSTI]

Filtergraph is a web application being developed and maintained by the Vanderbilt Initiative in Data-intensive Astrophysics (VIDA) to flexibly and rapidly visualize a large variety of astronomy datasets of various formats and sizes. The user loads a flat-file dataset into Filtergraph which automatically generates an interactive data portal that can be easily shared with others. From this portal, the user can immediately generate scatter plots of up to 5 dimensions as well as histograms and tables based on the dataset. Key features of the portal include intuitive controls with auto-completed variable names, the ability to filter the data in real time through user-specified criteria, the ability to select data by dragging on the screen, and the ability to perform arithmetic operations on the data in real time. To enable seamless data visualization and exploration, changes are quickly rendered on screen and visualizations can be exported as high quality graphics files. The application is optimized for speed in t...

Burger, Dan; Pepper, Joshua; Siverd, Robert J; Paegert, Martin; De Lee, Nathan M

2013-01-01T23:59:59.000Z

218

Comparison of the Legacy and Gold SnIa Dataset Constraints on Dark Energy Models  

E-Print Network [OSTI]

We have performed a comparative analysis of three recent and reliable SnIa datasets available in the literature: the Full Gold (FG) dataset (157 data points $0dataset (140 data points $0dataset (115 data points $0datasets are consistent with each other at the 95% confidence level, the latest (SNLS) dataset shows distinct trends which are not shared by the Gold datasets. We find that the best fit dynamical $w(z)$ obtained from the SNLS dataset does not cross the PDL $w=-1$ and remains above and close to the $w=-1$ line for the whole redshift range $0datasets (FG and TG) clearly crosses the PDL and departs significantly from the PDL $w=-1$ line while the LCDM parameter values are about $2\\sigma$ away from the best fit $w(z)$. In addition, the $(\\Omega_{0m},\\Omega_\\Lambda)$ parameters in a LCDM parametrization without a flat prior, fit by the SNLS dataset, favor the minimal flat LCDM concordance model. The corresponding fit with the Gold datasets mildly favors a closed universe and the flat LCDM parameter values are $1\\sigma - 2\\sigma$ away from the best fit $(\\Omega_{0m},\\Omega_\\Lambda)$.

S. Nesseris; L. Perivolaropoulos

2005-12-02T23:59:59.000Z

219

The Group Evolution Multiwavelength Study (GEMS): the Sample and Datasets  

E-Print Network [OSTI]

Galaxy groups have been under-studied relative to their richer counterparts -- clusters. The Group Evolution Multiwavelength Study (GEMS) aims to redress some the balance. Here we describe the GEMS sample selection and resulting sample of 60 nearby (distance dataset of X-ray, optical and HI imaging. ROSAT X-ray images of each group are presented. GEMS also utilizes near-infrared imaging from the 2MASS survey and optical spectra from the 6dFGS. These observational data are complemented by mock group catalogues generated from the latest LCDM simulations with gas physics included. Existing GEMS publications are briefly highlighted as are future publication plans.

Duncan A. Forbes; Trevor Ponman; Frazer Pearce; John Osmond; Virginia Kilborn; Sarah Brough; Somak Raychaudhury; Carole Mundell; Trevor Miles; Katie Kern

2006-02-09T23:59:59.000Z

220

Constructing Collaborative Desktop Storage Caches for Large Scientific Datasets  

SciTech Connect (OSTI)

High-end computing is suffering a data deluge from experiments, simulations, and apparatus that creates overwhelming application dataset sizes. This has led to the proliferation of high-end mass storage systems, storage area clusters, and data centers. These storage facilities offer a large range of choices in terms of capacity and access rate, as well as strong data availability and consistency support. However, for most end-users, the "last mile" in their analysis pipeline often requires data processing and visualization at local computers, typically local desktop workstations. End-user workstations-despite having more processing power than ever before-are ill-equipped to cope with such data demands due to insufficient secondary storage space and I/O rates. Meanwhile, a large portion of desktop storage is unused. We propose the FreeLoader framework, which aggregates unused desktop storage space and I/O bandwidth into a shared cache/scratch space, for hosting large, immutable datasets and exploiting data access locality. This article presents the FreeLoader architecture, component design, and performance results based on our proof-of-concept prototype. Its architecture comprises contributing benefactor nodes, steered by a management layer, providing services such as data integrity, high performance, load balancing, and impact control. Our experiments show that FreeLoader is an appealing low-cost solution to storing massive datasets by delivering higher data access ratesthan traditional storage facilities, namely, local or remote shared file systems, storage systems, and Internet data repositories. In particular, we present novel data striping techniques that allow FreeLoader to efficiently aggregate a workstation's network communication bandwidth and local I/O bandwidth. In addition, the performance impact on the native workload of donor machines is small and can be effectively controlled. Further, we show that security features such as data encryptions and integrity checks can be easily added as filters for interested clients. Finally, we demonstrate how legacy applications can use the FreeLoader API to store and retrieve datasets.

Vazhkudai, Sudharshan S [ORNL; Ma, Xiaosong [ORNL; Freeh, Vincent W [ORNL; Strickland, Jonathan W [ORNL; Tammineedi, Nandan [ORNL; Simon, Tyler A [ORNL; Scott, Stephen L [ORNL

2006-08-01T23:59:59.000Z

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


221

Swedish Energy Agency - Organizations - OpenEI Datasets  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:Seadov Pty LtdSteen,Ltd Jump to: navigation, search Name:STS3OID, m28 CountyStartDatasets

222

Fact #858 February 2, 2015 Retail Gasoline Prices in 2014 Experienced the Largest Decline since 2008 Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Retail Gasoline Prices in 2014 Experienced the Largest Decline since 2008

223

Supplemental Figures: Figure S1. Analysis of endo-siRNA targets in different microarray datasets. The  

E-Print Network [OSTI]

Supplemental Figures: Figure S1. Analysis of endo-siRNA targets in different microarray datasets. The percentage of each array dataset that were predicted endo-siRNA targets according to the Ambros dataset (Lee et al. 2006) was plotted [(number of endo-siRNA targets in microarray dataset / total genes

Bass, Brenda L.

224

Biofuel Enduse Datasets from the Bioenergy Knowledge Discovery Framework (KDF)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. [copied from https://www.bioenergykdf.net/content/about]

Holdings include datasets, models, and maps. This is a very new resource, but the collections will grow due to both DOE contributions and individuals data uploads. Currently the Biofuel Enduse collection includes 133 items. Most of these are categorized as literature, but 36 are listed as datasets and ten as models.

225

Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets  

E-Print Network [OSTI]

components within functional genomics datasets BMC SystemssiRNA-based functional genomics of pigmentation identifiesrelated functional genomics data. J R Soc Interface Motulsky

Ho, Hsiang; Milenkovic, Tijana; Memisevic, Vesna; Aruri, Jayavani; Przulj, Natasa; Ganesan, Anand K

2010-01-01T23:59:59.000Z

226

OctOber 2011 | ArgOnne nAtiOnAl lAbOrAtOry NG Workshop summary report appeNDIX e  

E-Print Network [OSTI]

OctOber 2011 | ArgOnne nAtiOnAl lAbOrAtOry NG Workshop summary report ­ appeNDIX e presentation slides: u.s. Natural Gas markets and perspectives Bill Liss, GTI 1 #12;OctOber 2011 | ArgOnne nAtiOnAl lAbOrAtOry NG Workshop summary report ­ appeNDIX e 2 #12;OctOber 2011 | ArgOnne nAtiOnAl lAbOrAtOry NG Workshop

227

1/28/09 3:40 PMBloomberg Printer-Friendly Page Page 1 of 2http://www.bloomberg.com/apps/news?pid=20670001&refer=science&sid=atoTqDydLoWA  

E-Print Network [OSTI]

1/28/09 3:40 PMBloomberg Printer-Friendly Page Page 1 of 2http://www.bloomberg.com/apps/news?pidhttp://www.bloomberg.com/apps/news?pid=20670001&refer=science&sid=atoTqDydLoWA list of genes that may

228

Probing cosmic acceleration by using the SNLS3 SNIa dataset  

SciTech Connect (OSTI)

We probe the cosmic acceleration by using the recently released SNLS3 sample of 472 type Ia supernovae. Combining this type Ia supernovae dataset with the cosmic microwave background anisotropy data from the Wilkinson Microwave Anisotropy Probe 7-yr observations, the baryon acoustic oscillation results from the Sloan Digital Sky Survey data release 7, and the Hubble constant measurement from the Wide Field Camera 3 on the Hubble Space Telescope, we measure the dark energy equation of state w and the deceleration parameter q as functions of redshift by using the Chevallier-Polarski-Linder parametrization. Our result is consistent with a cosmological constant at 1? confidence level, without evidence for the recent slowing down of the cosmic acceleration. Furthermore, we consider three binned parametrizations (w is piecewise constant in redshift z) based on different binning methods. The similar results are obtained, i.e., the ?CDM model is still nicely compatible with current observations.

Li, Xiao-Dong; Wang, Shuang; Zhang, Wen-Shuai [Department of Modern Physics, University of Science and Technology of China, Hefei 230026 (China); Li, Song; Huang, Qing-Guo; Li, Miao, E-mail: renzhe@mail.ustc.edu.cn, E-mail: sli@itp.ac.cn, E-mail: swang@mail.ustc.edu.cn, E-mail: wszhang@mail.ustc.edu.cn, E-mail: huangqg@itp.ac.cn, E-mail: mli@itp.ac.cn [Institute of Theoretical Physics, Chinese Academy of Science, Beijing 100080 (China)

2011-07-01T23:59:59.000Z

229

Non-local gravity and comparison with observational datasets  

E-Print Network [OSTI]

We study the cosmological predictions of two recently proposed non-local modifications of General Relativity. Both models have the same number of parameters as $\\Lambda$CDM, with a mass parameter $m$ replacing the cosmological constant. We implement the cosmological perturbations of the non-local models into a modification of the CLASS Boltzmann code, and we make a full comparison to CMB, BAO and supernova data. We find that the non-local models fit these datasets as well as $\\Lambda$CDM. For both non-local models parameter estimation using Planck+JLA+BAO data gives a value of $H_0$ higher than in $\\Lambda$CDM, and in better agreement with the values obtained from local measurements.

Yves Dirian; Stefano Foffa; Martin Kunz; Michele Maggiore; Valeria Pettorino

2014-11-27T23:59:59.000Z

230

MATCH: Metadata Access Tool for Climate and Health Datasets  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

MATCH is a searchable clearinghouse of publicly available Federal metadata (i.e. data about data) and links to datasets. Most metadata on MATCH pertain to geospatial data sets ranging from local to global scales. The goals of MATCH are to: 1) Provide an easily accessible clearinghouse of relevant Federal metadata on climate and health that will increase efficiency in solving research problems; 2) Promote application of research and information to understand, mitigate, and adapt to the health effects of climate change; 3) Facilitate multidirectional communication among interested stakeholders to inform and shape Federal research directions; 4) Encourage collaboration among traditional and non-traditional partners in development of new initiatives to address emerging climate and health issues. [copied from http://match.globalchange.gov/geoportal/catalog/content/about.page

231

Biofuel Distribution Datasets from the Bioenergy Knowledge Discovery Framework  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. [copied from https://www.bioenergykdf.net/content/about] Holdings include datasets, models, and maps and the collections are growing due to both DOE contributions and individuals' data uploads.

232

Biofuel Production Datasets from DOE's Bioenergy Knowledge Discovery Framework (KDF)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. [copied from https://www.bioenergykdf.net/content/about]

Holdings include datasets, models, and maps and the collections arel growing due to both DOE contributions and data uploads from individuals.

233

Feedstock Production Datasets from the Bioenergy Knowledge Discovery Framework  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. [copied from https://www.bioenergykdf.net/content/about] Holdings include datasets, models, and maps and the collections are growing due to both DOE contributions and data uploads from individuals.

234

Feedstock Logistics Datasets from DOE's Bioenergy Knowledge Discovery Framework (KDF)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. Holdings include datasets, models, and maps. [from https://www.bioenergykdf.net/content/about

235

SmartApps: Middle-ware for Adaptive Applications on Reconfigurable Platforms  

SciTech Connect (OSTI)

There are several reasons why the performance of current distributed and heterogeneous systems is often disappointing. For example, the characteristics of the application may be input sensitive and evolve during execution causing dramatic changes in memory reference patterns, resource requirements, or degree of concurrency between different phases of the computation. Or, the system may change dynamically with nodes failing or appearing, some network links severed and other links established with different latencies and bandwidths. Another important reason for poor performance is the fairly compartmentalized approach to optimization: applications, compilers, operating systems and hardware configurations are designed and optimized in isolation and without the knowledge of instance specific information and needs of a running application. There is too little information flow across these boundaries and no global optimization is even attempted. For example, most operating systems services like paging, virtual-to-physical page mapping, I/O, or data layout in disks, provide little or no application customization. Similarly, the off-the-shelf hardware used by most commercial systems is optimized to give best average-case performance. To address this problem, we have proposed application-centric computing, or Smart Applications (SAS). In the SAS executable, the compiler embeds most run-time system services, and a performance-optimizing feedback loop that monitors the application's performance and adaptively reconfigures the application and the OS/system platform. At run-time, after incorporating the code's input and determining the system's resources and state, the SAS performs an *instance* specific optimization, which is more tractable than a global generic optimization between application, OS and system. The overriding philosophy of SAS is ``measure, compare, and adapt if beneficial.'' That is, the application will continually monitor its performance and the available resources to determine if, and by how much, performance could be improved if the application was restructured. Then, if the potential performance benefit outweighs the projected overhead costs, the application will restructure itself and the underlying system accordingly. The SAS framework includes performance monitoring and modeling components and mechanisms for performing the actual restructuring at various levels including: (i) algorithmic adaptation, (ii) run-time software optimization (e.g., input sensitivity analysis, etc.), (iii) tuning reconfigurable OS services (scheduling policy, page size, etc), and (iv) system configuration (e.g., selecting which, and how many, computational resources to use). SmartApps is being developed in the STAPL infrastructure. STAPL (the Standard Template Adaptive Parallel Library) is a framework for developing highly-optimizable, adaptable, and portable parallel and distributed applications. It consists of a relatively new and still evolving collection of generic parallel algorithms and distributed containers and a run-time system (RTS) through which the application and compiler interact with the OS and hardware.

Lawrence Rauchwerger

2009-08-09T23:59:59.000Z

236

This page shows how to use the My Pitt Video (Panopto) iOS application on an iPhone. To log in to the iOS app, swipe the screen to the right or click the menu button in the top left corner,  

E-Print Network [OSTI]

iPhone app iPhone app This page shows how to use the My Pitt Video (Panopto) iOS applicationPhone app View Panopto Sessions To view sessions on the My Pitt Video (Panopto) server, tap the menu button you would like the session to be stored. Enter a session name, and tap "Record a new video" and begin

Benos, Panayiotis "Takis"

237

Operational Model forOperational Model forOperational Model forOperational Model for C3 Feedstock Optimization on aC3 Feedstock Optimization on app  

E-Print Network [OSTI]

Optimization on aC3 Feedstock Optimization on app Polypropylene Production FacilityPolypropylene Production for Advanced Process Decision-making Enterprise-Wide Optimization (EWO) Meeting ­ March 13-14, 2012 #12;Project ~95% propylene Refinery PolypropylenePropylene (91%) Grade (RG) Reactor effluent Distillation ~79

Grossmann, Ignacio E.

238

A Method For Eclipsing Component Identification In Large Photometric Datasets  

E-Print Network [OSTI]

We describe an automated method for assigning the most likely physical parameters to the components of an eclipsing binary (EB), using only its photometric light curve and combined color. In traditional methods (e.g. WD and EBOP) one attempts to optimize a multi-parameter model over many iterations, so as to minimize the chi-squared value. We suggest an alternative method, where one selects pairs of coeval stars from a set of theoretical stellar models, and compares their simulated light curves and combined colors with the observations. This approach greatly reduces the EB parameter-space over which one needs to search, and allows one to determine the components' masses, radii and absolute magnitudes, without spectroscopic data. We have implemented this method in an automated program using published theoretical isochrones and limb-darkening coefficients. Since it is easy to automate, this method lends itself to systematic analyses of datasets consisting of photometric time series of large numbers of stars, such as those produced by OGLE, MACHO, TrES, HAT, and many others surveys.

Jonathan Devor; David Charbonneau

2005-10-04T23:59:59.000Z

239

Fact #845: November 3, 2014 From 1970 to 2013 the Share of Older Vehicles in Operation has Increased Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Fact #845:From 1970 to 2013 the Share of Older Vehicles in Operation has Increased

240

Content of Submission The content of the RAE08 submission was comprised of the following nine datasets,  

E-Print Network [OSTI]

datasets, known as forms. Form Content of data set RA0 Overall staff summary to include: - The FTE number

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


241

Fact #857 January 26, 2015 Number of Partner Workplaces Offering Electric Vehicle Charging More Than Tripled Since 2011 Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Number of Partner Workplaces Offering Electric Vehicle Charging More Than Tripled Since 2011

242

Fact #844: October 27, 2014 Electricity Generated from Coal has Declined while Generation from Natural Gas has Grown Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Fact #844:Electricity Generated from Coal has Declined while Generation from Natural Gas has Grown

243

Fact #834: August 18, 2014 About Two-Thirds of Transportation Energy Use is Gasoline for Light Vehicles Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Fact #834: About Two-Thirds of Transportation Energy Use is Gasoline for Light Vehicles

244

Fact #837: September 8, 2014 Gap between Net Imports and Total Imports of Petroleum is Widening Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Fact #837: Gap between Net Imports and Total Imports of Petroleum is Widening

245

Texas Transportation Poll (TTP) Data Documentation The dataset and code book has been provided, so that researchers interested in conducting their own  

E-Print Network [OSTI]

Texas Transportation Poll (TTP) Data Documentation The dataset and code book) contains basic information about all the variables in the dataset. The second part been cleaned. The expanded weight has also been included in the dataset

246

Gathering Datasets for Activity Identification Lorcan Coyle, Juan Ye, Susan McKeever, Stephen Knox, Matthew Stabeler,  

E-Print Network [OSTI]

Gathering Datasets for Activity Identification Lorcan Coyle, Juan Ye, Susan McKeever, Stephen Knox is proceedings well, without publicly available datasets on which to compare results it is difficult to consolidate the disparate work being done. This prob- lem exists because realistic datasets describing human

Hammerton, James

247

Dataset Lifecycle Policy Development & Implementation at the PO.DAAC AGU Paper Number: IN53C-1579  

E-Print Network [OSTI]

Dataset Lifecycle Policy Development & Implementation at the PO.DAAC AGU Paper Number: IN53C-1579 Dataset Lifecycle Policy Development & Implementation at the PO.DAAC National Aeronautics and Space Aeronautics and Space Administration Jet Propulsion Laboratory/California Institute of Technology II. Dataset

Wright, Dawn Jeannine

248

978-1-4799-1270-4/13/$31.00 c 2013 IEEE Let's ChronoSync: Decentralized Dataset State  

E-Print Network [OSTI]

978-1-4799-1270-4/13/$31.00 c 2013 IEEE Let's ChronoSync: Decentralized Dataset State of knowledge about the dataset such as text messages, changes to the shared folder, or document edits. We to efficiently synchronize the state of a dataset among a distributed group of users. Using appropriate naming

California at Los Angeles, University of

249

Page 1 TXCRDC Notes on Datasets Available in CRDCs Texas A&M University Census Research Data Center  

E-Print Network [OSTI]

Page 1 ­ TXCRDC ­ Notes on Datasets Available in CRDCs Texas A&M University Census Research Data Center Datasets Available in Census Research Data Centers Overview This document brings together short. They include: 1. Links to Detailed Information about Available Datasets 2. Quick Summary Listings of Available

Bermúdez, José Luis

250

Using Representative-Based Clustering for Nearest Neighbor Dataset Editing Christoph F. Eick , Nidal Zeidat, and Ricardo Vilalta  

E-Print Network [OSTI]

Using Representative-Based Clustering for Nearest Neighbor Dataset Editing Christoph F. Eick, vilalta}@cs.uh.edu Abstract The goal of dataset editing in instance-based learning is to remove objects-based clustering algorithms for nearest neighbor dataset editing. We term this approach supervised clustering

Vilalta, Ricardo

251

AMM1 and MAMM Mosaics Three versions of the AMM1 and MAMM Ascending dataset are available, a  

E-Print Network [OSTI]

AMM1 and MAMM Mosaics Three versions of the AMM1 and MAMM Ascending dataset are available converted to a ° mosaic and a log-scaled 8-bit version. Dataset Rad. Smoothed Log-scaled 8-bit ° AMM1 Final The following equations were used to compute amplitude for the different datasets following inversion

Howat, Ian M.

252

License Terms This dataset is made freely available to academic and non-academic entities for non-commercial  

E-Print Network [OSTI]

License Terms This dataset is made freely available to academic and non-academic entities for non publication in any published work that makes use of the dataset. 3. That if you have altered the content of the dataset or created derivative work, prominent notice is made so that any recipients know

Hefei Institute of Intelligent Machines

253

BroadPeak: a novel algorithm for identifying broad peaks in dif-fuse ChIP-seq datasets  

E-Print Network [OSTI]

1 BroadPeak: a novel algorithm for identifying broad peaks in dif- fuse ChIP-seq datasets JianrongIP-seq datasets. We show that BroadPeak is a linear time algorithm that requires only two parame- ters, and we validate its performance on real and simulated histone modification ChIP-seq datasets. BroadPeak calls

Jordan, King

254

A Public Toolkit and ITS Dataset for EEG Yueran Yuan, Kai-min Chang, Yanbo Xu, Jack Mostow  

E-Print Network [OSTI]

A Public Toolkit and ITS Dataset for EEG Yueran Yuan, Kai-min Chang, Yanbo Xu, Jack Mostow Language a classifier to estimate a student's amount of prior exposure to a given word. We make this dataset and toolkit setting. In this paper, we present a dataset from 3 years of school usage of Project LISTEN's Reading

255

Evaluation of Model based Tracking with TrakMark Dataset Antoine Petit Guillaume Caron Hideaki Uchiyama Eric Marchand  

E-Print Network [OSTI]

Evaluation of Model based Tracking with TrakMark Dataset Antoine Petit Guillaume Caron Hideaki in the INRIA La- gadic team with a TrakMark dataset. Since these methods are based on a 3D model based approach, we selected a dataset named "Con- ference Venue Package 01" that includes a 3D textured model

Paris-Sud XI, Université de

256

CLIMATE MODELING BEST ESTIMATE DATASET (CMBE) -NEW ADDITIONS Renata McCoy, Shaocheng Xie, Stephen Klein, Lawrence Livermore National Laboratory  

E-Print Network [OSTI]

CLIMATE MODELING BEST ESTIMATE DATASET (CMBE) - NEW ADDITIONS Renata McCoy, Shaocheng Xie, Stephen ARM product, the Climate Modeling Best Estimate (CMBE) dataset, is being augmented with the additional observational and model data. The CMBE dataset was created to serve the needs of climate model developers

257

Equilibrium Response and Transient Dynamics Datasets from VEMAP: Vegetation/Ecosystem Modeling and Analysis Project  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

Users of the VEMAP Portal can access input files of numerical data that include monthly and daily files of geographic data, soil and site files, scenario files, etc. Model results from Phase I, the Equilibrium Response datasets, are available through the NCAR anonymous FTP site at http://www.cgd.ucar.edu/vemap/vresults.html. Phase II, Transient Dynamics, include climate datasets, models results, and analysis tools. Many supplemental files are also available from the main data page at http://www.cgd.ucar.edu/vemap/datasets.html.

258

Exudate-based diabetic macular edema detection in fundus images using publicly available datasets  

SciTech Connect (OSTI)

Diabetic macular edema (DME) is a common vision threatening complication of diabetic retinopathy. In a large scale screening environment DME can be assessed by detecting exudates (a type of bright lesions) in fundus images. In this work, we introduce a new methodology for diagnosis of DME using a novel set of features based on colour, wavelet decomposition and automatic lesion segmentation. These features are employed to train a classifier able to automatically diagnose DME through the presence of exudation. We present a new publicly available dataset with ground-truth data containing 169 patients from various ethnic groups and levels of DME. This and other two publicly available datasets are employed to evaluate our algorithm. We are able to achieve diagnosis performance comparable to retina experts on the MESSIDOR (an independently labelled dataset with 1200 images) with cross-dataset testing (e.g., the classifier was trained on an independent dataset and tested on MESSIDOR). Our algorithm obtained an AUC between 0.88 and 0.94 depending on the dataset/features used. Additionally, it does not need ground truth at lesion level to reject false positives and is computationally efficient, as it generates a diagnosis on an average of 4.4 s (9.3 s, considering the optic nerve localization) per image on an 2.6 GHz platform with an unoptimized Matlab implementation.

Giancardo, Luca [ORNL; Meriaudeau, Fabrice [ORNL; Karnowski, Thomas Paul [ORNL; Li, Yaquin [University of Tennessee, Knoxville (UTK); Garg, Seema [University of North Carolina; Tobin Jr, Kenneth William [ORNL; Chaum, Edward [University of Tennessee, Knoxville (UTK)

2011-01-01T23:59:59.000Z

259

What is ICA&D? The International Climate Assessment & Dataset (ICA&D) climate services concept combines the work of WMO's Expert  

E-Print Network [OSTI]

What is ICA&D? The International Climate Assessment & Dataset (ICA&D) climate services concept on the software developed for the European Climate Assessment & Dataset (ECA&D) and is already applied in four & Dataset (SACA&D) for WMO Region V and the Latin American Climate Assessment & Dataset (LACA&D) for WMO

Haak, Hein

260

A Category-Level 3-D Object Dataset: Putting the Kinect to Work Allison Janoch, Sergey Karayev, Yangqing Jia, Jonathan T. Barron, Mario Fritz, Kate Saenko, Trevor Darrell  

E-Print Network [OSTI]

A Category-Level 3-D Object Dataset: Putting the Kinect to Work Allison Janoch, Sergey Karayev for a chal- lenging category-level 3D object detection dataset to the fore. We review current 3D datasets our dataset of color and depth image pairs, gathered in real domestic and office environ- ments

O'Brien, James F.

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


261

Fact #846: November 10, 2014 Trucks Move 70% of all Freight by Weight and 74% of Freight by Value Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Fact #846:Trucks Move 70% of all Freight by Weight and 74% of Freight by Value

262

Fact #851: December 15, 2014 The Average Number of Gears used in Transmissions Continues to Rise Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Fact #851: December 15, 2014 The Average Number of Gears used in Transmissions Continues to Rise

263

Fact #853 December 29, 2014 Stop/Start Technology is in nearly 5% of All New Light Vehicles Produced- Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Fact #853: December 29, 2014 Stop/Start Technology is in nearly 5% of All New Light Vehicles Produced

264

Fact #839: September 22, 2014 World Petroleum Consumption Continues to Rise despite Declines from the United States and Europe- Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Fact #839: World Petroleum Consumption Continues to Rise despite Declines from the United States and Europe

265

Fact #838: September 15, 2014 Net Imports of Petroleum were Only 33% of U.S. Consumption in 2013- Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Fact #838: Net Imports of Petroleum were Only 33% of U.S. Consumption in 2013

266

Tension and Systematics in the Gold06 SnIa Dataset  

E-Print Network [OSTI]

The Gold06 SnIa dataset recently released in astro-ph/0611572 consists of five distinct subsets defined by the group or instrument that discovered and analyzed the corresponding data. These subsets are: the SNLS subset (47 SnIa), the HST subset (30 SnIa), the HZSST subset (41 SnIa), the SCP subset (26 SnIa) and the Low Redshift (LR) subset (38 SnIa). These subsets sum up to the 182 SnIa of the Gold06 dataset. We use Monte-Carlo simulations to study the statistical consistency of each one of the above subsets with the full Gold06 dataset. In particular, we compare the best fit $w(z)$ parameters (w_0,w_1) obtained by subtracting each one of the above subsets from the Gold06 dataset (subset truncation), with the corresponding best fit parameters (w^r_0,w^r_1) obtained by subtracting the same number of randomly selected SnIa from the same redshift range of the Gold06 dataset (random truncation). We find that the probability for (w^r_0,w^r_1)=(w_0,w_1) is large for the Gold06 minus SCP (Gold06-SCP) truncation but is less than 5% for the Gold06-SNLS, Gold06-HZSST and Gold06-HST truncations. This result implies that the Gold06 dataset is not statistically homogeneous. By comparing the values of the best fit (w_0,w_1) for each subset truncation we find that the tension among subsets is such that the SNLS and HST subsets are statistically consistent with each other and `pull' towards LCDM (w_0=-1,w_1=0) while the HZSST subset is statistically distinct and strongly `pulls' towards a varying w(z) crossing the line $w=-1$ from below (w_00). We also isolate six SnIa that are mostly responsible for this behavior of the HZSST subset.

S. Nesseris; L. Perivolaropoulos

2007-01-09T23:59:59.000Z

267

OpenEI: Datasets in the OpenEnergyInfo Data Repository  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The Open Energy Information initiative (OpenEI) is a platform to connect the world's energy data. It is a linked open data platform bringing together energy information to provide improved analyses, unique visualizations, and real-time access to data. OpenEI follows guidelines set by the White House Open Government Initiative , which is focused on transparency, collaboration, and participation. OpenEI strives to provide open access to this energy information, with the ultimate goal of spurring creativity and driving innovation in the energy sector.[Copied from the OpenEI Wiki main page]. It features a wiki, a blog, a list of information gateways, and a browsing list of deposited data sets.

268

Automatic Diabetic Macular Edema Detection in Fundus Images Using Publicly Available Datasets  

SciTech Connect (OSTI)

Diabetic macular edema (DME) is a common vision threatening complication of diabetic retinopathy. In a large scale screening environment DME can be assessed by detecting exudates (a type of bright lesions) in fundus images. In this work, we introduce a new methodology for diagnosis of DME using a novel set of features based on colour, wavelet decomposition and automatic lesion segmentation. These features are employed to train a classifier able to automatically diagnose DME. We present a new publicly available dataset with ground-truth data containing 169 patients from various ethnic groups and levels of DME. This and other two publicly available datasets are employed to evaluate our algorithm. We are able to achieve diagnosis performance comparable to retina experts on the MESSIDOR (an independently labelled dataset with 1200 images) with cross-dataset testing. Our algorithm is robust to segmentation uncertainties, does not need ground truth at lesion level, and is very fast, generating a diagnosis on an average of 4.4 seconds per image on an 2.6 GHz platform with an unoptimised Matlab implementation.

Giancardo, Luca [ORNL; Meriaudeau, Fabrice [ORNL; Karnowski, Thomas Paul [ORNL; Li, Yaquin [University of Tennessee, Knoxville (UTK); Garg, Seema [University of North Carolina; Tobin Jr, Kenneth William [ORNL; Chaum, Edward [University of Tennessee, Knoxville (UTK)

2011-01-01T23:59:59.000Z

269

SOIL MOISTURE CHARACTERIZATION USING MULTI-ANGULAR POLARIMETRIC RADARSAT-2 DATASETS  

E-Print Network [OSTI]

SOIL MOISTURE CHARACTERIZATION USING MULTI-ANGULAR POLARIMETRIC RADARSAT-2 DATASETS Hongquan Wang to be a solution to improve the effectiveness of bare soil char- acterization. However, the potential single and multiple incidence angle acquisitions is investigated against in situ soil moisture

Boyer, Edmond

270

Exploring the Latest Union2 SNIa Dataset by Using Model-Independent Parametrization Methods  

E-Print Network [OSTI]

We explore the cosmological consequences of the recently released Union2 sample of 557 Type Ia supernovae (SNIa). Combining this latest SNIa dataset with the Cosmic microwave background (CMB) anisotropy data from the Wilkinson Microwave Anisotropy Probe 7 year (WMAP7) observations and the baryon acoustic oscillation (BAO) results from the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7), we measure the dark energy density function $f(z)\\equiv \\rho_{de}(z)/\\rho_{de}(0)$ as a free function of redshift. Two model-independent parametrization methods (the binned parametrization and the polynomial interpolation parametrization) are used in this paper. By using the $\\chi^2$ statistic and the Bayesian information criterion, we find that the current observational data are still too limited to distinguish which parametrization method is better, and a simple model has advantage in fitting observational data than a complicated model. Moreover, it is found that all these parametrizations demonstrate that the Union2 dataset is still consistent with a cosmological constant at 1$\\sigma$ confidence level. Therefore, the Union2 dataset is different from the Constitution SNIa dataset, which more favors a dynamical dark energy.

Shuang Wang; Xiao-Dong Li; Miao Li

2011-01-04T23:59:59.000Z

271

Partition dataset according to amino acid type improves the prediction of deleterious non-synonymous SNPs  

SciTech Connect (OSTI)

Highlights: Black-Right-Pointing-Pointer Proper dataset partition can improve the prediction of deleterious nsSNPs. Black-Right-Pointing-Pointer Partition according to original residue type at nsSNP is a good criterion. Black-Right-Pointing-Pointer Similar strategy is supposed promising in other machine learning problems. -- Abstract: Many non-synonymous SNPs (nsSNPs) are associated with diseases, and numerous machine learning methods have been applied to train classifiers for sorting disease-associated nsSNPs from neutral ones. The continuously accumulated nsSNP data allows us to further explore better prediction approaches. In this work, we partitioned the training data into 20 subsets according to either original or substituted amino acid type at the nsSNP site. Using support vector machine (SVM), training classification models on each subset resulted in an overall accuracy of 76.3% or 74.9% depending on the two different partition criteria, while training on the whole dataset obtained an accuracy of only 72.6%. Moreover, the dataset was also randomly divided into 20 subsets, but the corresponding accuracy was only 73.2%. Our results demonstrated that partitioning the whole training dataset into subsets properly, i.e., according to the residue type at the nsSNP site, will improve the performance of the trained classifiers significantly, which should be valuable in developing better tools for predicting the disease-association of nsSNPs.

Yang, Jing; Li, Yuan-Yuan [School of Biotechnology, East China University of Science and Technology, Shanghai 200237 (China) [School of Biotechnology, East China University of Science and Technology, Shanghai 200237 (China); Shanghai Center for Bioinformation Technology, Shanghai 200235 (China); Li, Yi-Xue, E-mail: yxli@sibs.ac.cn [School of Biotechnology, East China University of Science and Technology, Shanghai 200237 (China) [School of Biotechnology, East China University of Science and Technology, Shanghai 200237 (China); Shanghai Center for Bioinformation Technology, Shanghai 200235 (China); Ye, Zhi-Qiang, E-mail: yezq@pkusz.edu.cn [Laboratory of Chemical Genomics, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen 518055 (China) [Laboratory of Chemical Genomics, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen 518055 (China); Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031 (China)

2012-03-02T23:59:59.000Z

272

arXiv:astro-ph/0106481v126Jun2001 MASSIVE DATASETS IN ASTRONOMY  

E-Print Network [OSTI]

arXiv:astro-ph/0106481v126Jun2001 Chapter 1 MASSIVE DATASETS IN ASTRONOMY Robert J. Brunner, S 21218 USA szalay@pha.jhu.edu Abstract Astronomy has a long history of acquiring, systematizing archives and services representing a new in- formation infrastructure for astronomy of the 21st century

Prince, Thomas A.

273

Discovery of Geospatial Discriminating Patterns from Remote Sensing Datasets Tomasz Stepinski  

E-Print Network [OSTI]

Discovery of Geospatial Discriminating Patterns from Remote Sensing Datasets Wei Ding Tomasz. Several geospatial feature vari- ables are fused together, and the vector of their values at each spatial cell is considered as a transaction to be used in association analysis. The concept of emerging

Ding, Wei

274

Analyzing Massive Astrophysical Datasets: Can Pig/Hadoop or a Relational DBMS Help?  

E-Print Network [OSTI]

Analyzing Massive Astrophysical Datasets: Can Pig/Hadoop or a Relational DBMS Help? Sarah Loebman1 distributed DBMS and in the Pig/Hadoop system. We compare the performance of the tools to each other of subatomic particles to the evolution of the universe. These simulations produce an ever more massive amount

Anderson, Richard

275

Stumbl: Using Facebook to Collect Rich Datasets for Opportunistic Networking Research  

E-Print Network [OSTI]

Stumbl: Using Facebook to Collect Rich Datasets for Opportunistic Networking Research Theus, mobility and communication ties. Stumbl is a Facebook application that provides participating users with a user-friendly interface to report their daily face-to-face meetings with other Facebook friends

Gesbert, David

276

5D-ODETLAP: A NOVEL FIVE-DIMENSIONAL COMPRESSION METHOD ON TIME-VARYING MULTIVARIABLE GEOSPATIAL DATASET  

E-Print Network [OSTI]

5D-ODETLAP: A NOVEL FIVE-DIMENSIONAL COMPRESSION METHOD ON TIME-VARYING MULTIVARIABLE GEOSPATIAL dimensional (5D) geospatial dataset consists of several multivariable 4D datasets, which are sequences of time technique for 5D geospatial data as a whole, instead of applying 3D compression method on each 3D slice

Franklin, W. Randolph

277

Z:\\gis553s12\\lab5\\demo\\grid2poly.py Wednesday, January 18, 2012 4:49 PM # Create a square quadrat (polygon) dataset based on the input feature class.  

E-Print Network [OSTI]

(polygon) dataset based on the input feature class. # The output polygon dataset cover all of the input where your point dataset is stored." print "2. The NAME of your point dataset." print "3. The SIZE, one_input("Enter the name of your point dataset (include .shp if a shapefile): ") quadrat = raw_input("Enter the size

Hung, I-Kuai

278

Z:\\gis553_lab\\lab5\\grid2poly.py Tuesday, February 18, 2014 8:30 PM # Create a square quadrat (polygon) dataset based on the input feature class.  

E-Print Network [OSTI]

(polygon) dataset based on the input feature class. # The output polygon dataset covers all of the input where your point dataset is stored. " print "2. The NAME of your point dataset." print "3. The SIZE, one = raw_input("Enter the name of your point dataset (include .shp if a shapefile):") quadrat = raw

Hung, I-Kuai

279

app_a  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality atangiemcgapm |A

280

app_b  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality atangiemcgapm |AB

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


281

app_c1  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality atangiemcgapm |AB

282

app_c10  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality atangiemcgapm

283

app_c2  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality atangiemcgapm2

284

app_c3  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality atangiemcgapm23

285

app_c4  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality atangiemcgapm234

286

app_c5  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality atangiemcgapm2345

287

app_c6  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality

288

app_c7  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7 Description of

289

app_c8  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7 Description of8

290

app_c9  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7 Description of89

291

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7 Description of89

292

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7 Description

293

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7 Description0

294

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7 Description0

295

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7 Description0

296

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7 Description023

297

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7 Description02326

298

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7

299

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality77 DOE/EIS-0287

300

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality77 DOE/EIS-028741

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


301

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality77

302

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7756 Document 36,

303

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7756 Document 36,2

304

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7756 Document

305

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7756 Document76

306

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7756

307

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality775686 Appendix D

308

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality775686 Appendix

309

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality775686

310

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality77568609

311

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7756860917

312

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality77568609173

313

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality775686091737

314

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7756860917372

315

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality77568609173726

316

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality775686091737268

317

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality7756860917372686

318

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data Quality775686091737268653

319

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data

320

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data8 Appendix D - New

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


321

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data8 Appendix D - New72

322

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data8 Appendix D - New720

323

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data8 Appendix D - New7208

324

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data8 Appendix D - New720894

325

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data8 Appendix D -

326

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data8 Appendix D -203

327

app_d  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, partReview of SIRS Data8 Appendix D -203D Comment

328

MobileMatch App  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas Conchas recovery challenge fundProject8Mistakes to Avoid Mistakes to AvoidMoMobileMatch

329

Associations of indoor carbon dioxide concentrations, VOCS, environmental susceptibilities with mucous membrane and lower respiratory sick building syndrome symptoms in the BASE study: Analyses of the 100 building dataset  

E-Print Network [OSTI]

ANALYSES OF THE 100 BUILDING DATASET MG Apte and CA ErdmannEvaluation (BASE) Study dataset, we performed multivariatewheeze). We explore, in a dataset collected in 100 US office

Apte, M.G.; Erdmann, C.A.

2002-01-01T23:59:59.000Z

330

Going into depth: Evaluating 2D and 3D cues for object classification on a new, large-scale object dataset  

E-Print Network [OSTI]

dataset Bj¨orn Browatzki MPI for Biological Cybernetics T¨ubingen, Germany bjoern part of this paper, we introduce a novel, large dataset containing 18 categories of objects found in typ- ical household and office environments--we envision this dataset to be useful in many

331

IEEE SENSORS JOURNAL, VOL. 10, NO. 12, DECEMBER 2010 1891 A Dataset for the Design of Smart Ion-Selective Electrode Arrays for  

E-Print Network [OSTI]

IEEE SENSORS JOURNAL, VOL. 10, NO. 12, DECEMBER 2010 1891 A Dataset for the Design of Smart Ion (ISEs). The development of the core of a SSA, the signal processing algorithm, often requires a dataset with arrays of ISEs. The acquired dataset is publicly available in a web page where published results

Paris-Sud XI, Université de

332

Describing the Cloud of Linked Datasets While there is a growing number of published and offered as openly available Linked Open Data  

E-Print Network [OSTI]

Describing the Cloud of Linked Datasets While there is a growing number of published and offered as openly available Linked Open Data datasets1 ; many challenges remain to be tackled on making such data what the data is all about? with most datasets having poor and superficial metadata describing content

Nejdl, Wolfgang

333

Enhancing mobile browsing and reading  

E-Print Network [OSTI]

Although the web browser has become a standard interface for information access on the Web, the mobile web browser on the smartphone does not hold the same interest to mobile users. A survey with 11 mobile users shows that ...

Yu, Chen-Hsiang

334

Browse the archive Show summaries  

E-Print Network [OSTI]

- China, the European Union (EU), Japan, Russia, South Korea and the US - at a ministerial meeting to be a safe and sustainable source of energy that does not produce any greenhouse-gas emissions or long-lived nuclear waste. A fusion reactor would need just 100 grams of deuterium and 3 tons of natural lithium

335

Does the Danube exist? Versions of reality given by various regional climate models and climatological datasets  

E-Print Network [OSTI]

We present an intercomparison and verification analysis of several regional climate models (RCMs) nested into the same run of the same Atmospheric Global Circulation Model (AGCM) regarding their representation of the statistical properties of the hydrological balance of the Danube river basin for 1961-1990. We also consider the datasets produced by the driving AGCM, from the ECMWF and NCEP-NCAR reanalyses. The hydrological balance is computed by integrating the precipitation and evaporation fields over the area of interest. Large discrepancies exist among RCMs for the monthly climatology as well as for the mean and variability of the annual balances, and only few datasets are consistent with the observed discharge values of the Danube at its Delta, even if the driving AGCM provides itself an excellent estimate. Since the considered approach relies on the mass conservation principle and bypasses the details of the air-land interface modeling, we propose that the atmospheric components of RCMs still face diffic...

Lucarini, V; Kriegerova, I; Speranza, A; Danihlik, Robert; Kriegerova, Ida; Lucarini, Valerio; Speranza, Antonio

2006-01-01T23:59:59.000Z

336

Advancements in Wind Integration Study Data Modeling: The Wind Integration National Dataset (WIND) Toolkit; Preprint  

SciTech Connect (OSTI)

Regional wind integration studies in the United States require detailed wind power output data at many locations to perform simulations of how the power system will operate under high-penetration scenarios. The wind data sets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as be time synchronized with available load profiles. The Wind Integration National Dataset (WIND) Toolkit described in this paper fulfills these requirements. A wind resource dataset, wind power production time series, and simulated forecasts from a numerical weather prediction model run on a nationwide 2-km grid at 5-min resolution will be made publicly available for more than 110,000 onshore and offshore wind power production sites.

Draxl, C.; Hodge, B. M.; Orwig, K.; Jones, W.; Searight, K.; Getman, D.; Harrold, S.; McCaa, J.; Cline, J.; Clark, C.

2013-10-01T23:59:59.000Z

337

Production of BaBar Skimmed Analysis Datasets Using the Grid  

SciTech Connect (OSTI)

The BABAR Collaboration, based at Stanford Linear Accelerator Center (SLAC), Stanford, US, has been performing physics reconstruction, simulation studies and data analysis for 8 years using a number of compute farms around the world. Recent developments in Grid technologies could provide a way to manage the distributed resources in a single coherent structure. We describe enhancements to the BABAR experiment's distributed skimmed dataset production system to make use of European Grid resources and present the results with regard to BABAR's latest cycle of skimmed dataset production. We compare the benefits of a local and Grid-based systems, the ease with which the system is managed and the challenges of integrating the Grid with legacy software. We compare job success rates and manageability issues between Grid and non-Grid production.

Brew, C.A.J.; /Rutherford; Wilson, F.F.; /Rutherford; Castelli, G.; /Rutherford; Adye, T.; /Rutherford; Roethel, W.; /Rutherford; Luppi, E.; /INFN, Ferrara; Andreotti, D.; /INFN, Ferrara; Smith, D.; /SLAC; Khan, A.; /Brunel U.; Barrett, M.; /Brunel U.; Barlow, R.; /Manchester U.; Bailey, D.; /Manchester U.

2011-11-10T23:59:59.000Z

338

Integrative analysis of transcriptomic and proteomic data of Shewanella oneidensis: missing value imputation using temporal datasets  

SciTech Connect (OSTI)

Despite significant improvements in recent years, proteomic datasets currently available still suffer large number of missing values. Integrative analyses based upon incomplete proteomic and transcriptomic da-tasets could seriously bias the biological interpretation. In this study, we applied a non-linear data-driven stochastic gradient boosted trees (GBT) model to impute missing proteomic values for proteins experi-mentally undetected, using a temporal transcriptomic and proteomic dataset of Shewanella oneidensis. In this dataset, genes expression was measured after the cells were exposed to 1 mM potassium chromate for 5-, 30-, 60-, and 90-min, while protein abundance was measured only for 45- and 90-min samples. With the goal of elucidating the relationship between temporal gene expression and protein abundance data, and then using it to impute missing proteomic values for samples of 45-min (which does not have cognate transcriptomic data) and 90-min, we initially used nonlinear Smoothing Splines Curve Fitting (SSCF) to identify temporal relationships among transcriptomic data at different time points and then imputed missing gene expression measurements for the sample at 45-min. After the imputation was validated by biological constrains (i.e. operons), we used a data-driven Gradient Boosted Trees (GBT) model to uncover possible non-linear relationships between temporal transcriptomic and proteomic data, and to impute protein abundance for the proteins experimentally undetected in the 45- and 90-min sam-ples, based on relevant predictors such as temporal mRNA gene expression data, cellular roles, molecular weight, sequence length, protein length, guanine-cytosine (GC) content and triple codon counts. The imputed protein values were validated using biological constraints such as operon, regulon and pathway information. Finally, we demonstrated that such missing value imputation improved characterization of the temporal response of S. oneidensis to chromate.

Torres-Garca, Wandaliz [Arizona State University; Brown, Steven D [ORNL; Johnson, Roger [Arizona State University; Zhang, Weiwen [Arizona State University; Runger, George [Arizona State University; Meldrum, Deirdre [Arizona State University

2011-01-01T23:59:59.000Z

339

Bulk Data Movement for Climate Dataset: Efficient Data Transfer Management with Dynamic Transfer Adjustment  

SciTech Connect (OSTI)

Many scientific applications and experiments, such as high energy and nuclear physics, astrophysics, climate observation and modeling, combustion, nano-scale material sciences, and computational biology, generate extreme volumes of data with a large number of files. These data sources are distributed among national and international data repositories, and are shared by large numbers of geographically distributed scientists. A large portion of data is frequently accessed, and a large volume of data is moved from one place to another for analysis and storage. One challenging issue in such efforts is the limited network capacity for moving large datasets to explore and manage. The Bulk Data Mover (BDM), a data transfer management tool in the Earth System Grid (ESG) community, has been managing the massive dataset transfers efficiently with the pre-configured transfer properties in the environment where the network bandwidth is limited. Dynamic transfer adjustment was studied to enhance the BDM to handle significant end-to-end performance changes in the dynamic network environment as well as to control the data transfers for the desired transfer performance. We describe the results from the BDM transfer management for the climate datasets. We also describe the transfer estimation model and results from the dynamic transfer adjustment.

Sim, Alexander; Balman, Mehmet; Williams, Dean; Shoshani, Arie; Natarajan, Vijaya

2010-07-16T23:59:59.000Z

340

Geochemical Fingerprinting of Coltan Ores by Machine Learning on Uneven Datasets  

SciTech Connect (OSTI)

Two modern machine learning techniques, Linear Programming Boosting (LPBoost) and Support Vector Machines (SVMs), are introduced and applied to a geochemical dataset of niobium-tantalum ('coltan') ores from Central Africa to demonstrate how such information may be used to distinguish ore provenance, i.e., place of origin. The compositional data used include uni- and multivariate outliers and elemental distributions are not described by parametric frequency distribution functions. The 'soft margin' techniques of LPBoost and SVMs can be applied to such data. Optimization of their learning parameters results in an average accuracy of up to c. 92%, if spot measurements are assessed to estimate the provenance of ore samples originating from two geographically defined source areas. A parameterized performance measure, together with common methods for its optimization, was evaluated to account for the presence of uneven datasets. Optimization of the classification function threshold improves the performance, as class importance is shifted towards one of those classes. For this dataset, the average performance of the SVMs is significantly better compared to that of LPBoost.

Savu-Krohn, Christian, E-mail: christian.savu-krohn@unileoben.ac.at; Rantitsch, Gerd, E-mail: gerd.rantitsch@unileoben.ac.at [Montanuniversitaet Leoben, Department of Applied Geosciences and Geophysics (Austria); Auer, Peter, E-mail: auer@unileoben.ac.at [Chair for Information Technology, Montanuniversitaet Leoben (Austria); Melcher, Frank, E-mail: frank.melcher@bgr.de; Graupner, Torsten, E-mail: torsten.graupner@bgr.de [Federal Institute for Geosciences and Natural Resources (Germany)

2011-09-15T23:59:59.000Z

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


341

IBM recently unveiled MobileFirst, a major initiative to develop mobile-related technologies and products that include security, analytics, mobile app development, and cloud-based backend services. MobileFirst  

E-Print Network [OSTI]

IBM recently unveiled MobileFirst, a major initiative to develop mobile-related technologies and products that include security, analytics, mobile app development, and cloud-based backend services. Mobile lab has been asked to lead key portions of IBM's mobile research agenda. IBM Research-Austin has

Plotkin, Joshua B.

342

FY13 Summary Report on the Augmentation of the Spent Fuel Composition Dataset for Nuclear Forensics: SFCOMPO/NF  

SciTech Connect (OSTI)

This report documents the FY13 efforts to enhance a dataset of spent nuclear fuel isotopic composition data for use in developing intrinsic signatures for nuclear forensics. A review and collection of data from the open literature was performed in FY10. In FY11, the Spent Fuel COMPOsition (SFCOMPO) excel-based dataset for nuclear forensics (NF), SFCOMPO/NF was established and measured data for graphite production reactors, Boiling Water Reactors (BWRs) and Pressurized Water Reactors (PWRs) were added to the dataset and expanded to include a consistent set of data simulated by calculations. A test was performed to determine whether the SFCOMPO/NF dataset will be useful for the analysis and identification of reactor types from isotopic ratios observed in interdicted samples.

Brady Raap, Michaele C.; Lyons, Jennifer A.; Collins, Brian A.; Livingston, James V.

2014-03-31T23:59:59.000Z

343

Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected In-the-Wild  

E-Print Network [OSTI]

Computer classification of facial expressions requires large amounts of data and this data needs to reflect the diversity of conditions seen in real applications. Public datasets help accelerate the progress of research ...

McDuff, Daniel Jonathan

344

Datasets - OpenEI Datasets  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision has beenFfe2fb55-352f-473b-a2dd-50ae8b27f0a6 No revision has been approved for thisDatabus - Q

345

Constraining the Mass Profiles of Stellar Systems: Schwarzschild Modeling of Discrete Velocity Datasets  

E-Print Network [OSTI]

(ABRIDGED) We present a new Schwarzschild orbit-superposition code designed to model discrete datasets composed of velocities of individual kinematic tracers in a dynamical system. This constitutes an extension of previous implementations that can only address continuous data in the form of (the moments of) velocity distributions, thus avoiding potentially important losses of information due to data binning. Furthermore, the code can handle any combination of available velocity components, i.e., only line-of-sight velocities, only proper motions, or a combination of both. It can also handle a combination of discrete and continuous data. The code finds the distribution function (DF, a function of the three integrals of motion E, Lz, and I3) that best reproduces the available kinematic and photometric observations in a given axisymmetric gravitational potential. The fully numerical approach ensures considerable freedom on the form of the DF f(E,Lz,I3). This allows a very general modeling of the orbital structure, thus avoiding restrictive assumptions about the degree of (an)isotropy of the orbits. We describe the implementation of the discrete code and present a series of tests of its performance based on the modeling of simulated datasets generated from a known DF. We find that the discrete Schwarzschild code recovers the original orbital structure, M/L ratios, and inclination of the input datasets to satisfactory accuracy, as quantified by various statistics. The code will be valuable, e.g., for modeling stellar motions in Galactic globular clusters, and those of individual stars, planetary nebulae, or globular clusters in nearby galaxies. This can shed new light on the total mass distributions of these systems, with central black holes and dark matter halos being of particular interest.

Julio Chanam; Jan Kleyna; Roeland van der Marel

2008-04-21T23:59:59.000Z

346

Development of a high-resolution bathymetry dataset for the Columbia River through the Hanford Reach  

SciTech Connect (OSTI)

A bathymetric and topographic data collection and processing effort involving existing and newly collected data has been performed for the Columbia River through the Hanford Reach in central Washington State, extending 60-miles from the tailrace of Priest Rapids Dam (river mile 397) to near the vicinity of the Interstate 182 bridge just upstream of the Yakima River confluence (river mile 337). The contents of this report provide a description of the data collections, data inputs, processing methodology, and final data quality assessment used to develop a comprehensive and continuous merged 1m resolution bathymetric and topographic surface dataset for the Columbia River through the Hanford Reach.

Coleman, Andre M.; Ward, Duane L.; Larson, Kyle B.; Lettrick, Joseph W.

2010-10-08T23:59:59.000Z

347

Reconstruction of Hessence Dark Energy and the Latest Type Ia Supernovae Gold Dataset  

E-Print Network [OSTI]

Recently, many efforts have been made to build dark energy models whose equation-of-state parameter can cross the so-called phantom divide $w_{de}=-1$. One of them is the so-called hessence dark energy model in which the role of dark energy is played by a non-canonical complex scalar field. In this work, we develop a simple method based on Hubble parameter $H(z)$ to reconstruct the hessence dark energy. As examples, we use two familiar parameterizations for $H(z)$ and fit them to the latest 182 type Ia supernovae Gold dataset. In the reconstruction, measurement errors are fully considered.

Hao Wei; Ningning Tang; Shuang Nan Zhang

2007-02-28T23:59:59.000Z

348

Reconstruction of a Deceleration Parameter from the Latest Type Ia Supernovae Gold Dataset  

E-Print Network [OSTI]

In this paper, a parameterized deceleration parameter $q(z)= 1/2 - a/(1 + z)^b$ is reconstructed from the latest type Ia supernovae gold dataset. It is found out that the transition redshift from decelerated expansion to accelerated expansion is at $z_T=0.35^{+0.14}_{-0.07}$ with $1\\sigma$ confidence level in this parameterized deceleration parameter. And, the best fit values of parameters in $1\\sigma$ errors are $a=1.56^{+0.99}_{-0.55}$ and $b=3.82^{+3.70}_{-2.27}$.

Lixin Xu; Chengwu Zhang; Baorong Chang; Hongya Liu

2007-01-17T23:59:59.000Z

349

International H2O Project (IHOP) 2002: Datasets Related to Atmospheric Moisture and Rainfall Prediction  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

IHOP 2002 was a field experiment that took place over the Southern Great Plains of the United States from 13 May to 25 June 2002. The chief aim of IHOP_2002 was improved characterization of the four-dimensional (4-D) distribution of water vapor and its application to improving the understanding and prediction of convection. The region was an optimal location due to existing experimental and operational facilities, strong variability in moisture, and active convection [copied from http://www.eol.ucar.edu/projects/ihop/]. The project's master list of data identifies 146 publicly accessible datasets.

Schanot, Allen [IHOP 2002 PI; Friesen, Dick [IHOP 2002 PI

350

Evaluating socio-economic state of a country analyzing airtime credit and mobile phone datasets  

E-Print Network [OSTI]

Reliable statistical information is important to make political decisions on a sound basis and to help measure the impact of policies. Unfortunately, statistics offices in developing countries have scarce resources and statistical censuses are therefore conducted sporadically. Based on mobile phone communications and history of airtime credit purchases, we estimate the relative income of individuals, the diversity and inequality of income, and an indicator for socioeconomic segregation for fine-grained regions of an African country. Our study shows how to use mobile phone datasets as a starting point to understand the socio-economic state of a country, which can be especially useful in countries with few resources to conduct large surveys.

Gutierrez, Thoralf; Blondel, Vincent D

2013-01-01T23:59:59.000Z

351

A 20-Year Dataset of Downwelling Longwave Flux at the Arctic Surface from TOVS Satellite Data  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered‰PNGExperience hands-onASTROPHYSICSHe β- DecayBenew20-Year Dataset of

352

A 22-Year Dataset of Surface Longwave Fluxes in the Arctic  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered‰PNGExperience hands-onASTROPHYSICSHe β- DecayBenew20-Year Dataset of22-Year

353

World Net Nuclear Electric Power Generation, 1980-2007 - Datasets - OpenEI  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperative JumpWilliamsonWoodson County,Worden, Montana: Energy|Datasets U.S.

354

Slow Roll Reconstruction: Constraints on Inflation from the 3 Year WMAP Dataset  

E-Print Network [OSTI]

We study the constraints on the inflationary parameter space derived from the 3 year WMAP dataset using ``slow roll reconstruction'', using the SDSS galaxy power spectrum to gain further leverage where appropriate. This approach inserts the inflationary slow roll parameters directly into a Monte Carlo Markov chain estimate of the cosmological parameters, and uses the inflationary flow hierarchy to compute the parameters' scale-dependence. We work with the first three parameters (epsilon, eta and xi) and pay close attention to the possibility that the 3 year WMAP dataset contains evidence for a ``running'' spectral index, which is dominated by the xi term. Mirroring the WMAP team's analysis we find that the permitted distribution of xi is broad, and centered away from zero. However, when we require that inflationary parameters yield at least 30 additional e-folds of inflation after the largest observable scales leave the horizon, the bounds on xi tighten dramatically. We make use of the absence of an explicit pivot scale in the slow roll reconstruction formalism to determine the dependence of the computed parameter distributions on the pivot. We show that the choice of pivot has a significant effect on the inferred constraints on the inflationary variables, and the spectral index and running derived from them. Finally, we argue that the next round of cosmological data can be expected to place very stringent constraints on the region of parameter space open to single field models of slow roll inflation.

Hiranya Peiris; Richard Easther

2006-10-12T23:59:59.000Z

355

Evaluation of Global Monsoon Precipitation Changes based on Five Reanalysis Datasets  

SciTech Connect (OSTI)

With the motivation to identify whether or not a reasonably simulated atmospheric circulation would necessarily lead to a successful reproduction of monsoon precipitation, the performances of five sets of reanalysis data (NCEP2, ERA40, JRA25, ERA-Interim and MERRA) in reproducing the climatology, interannual variation and long-term trend of global monsoon (GM) precipitation are comprehensively evaluated. In order to better understand the variability and long-term trend of GM precipitation, we also examined the major components of water budget, including evaporation, water vapor convergence and the change in local water vapor storage, based on five reanalysis datasets. The results show that all five reanalysis data reasonably reproduce the climatology of GM precipitation. The ERA-Interim (NCEP2) shows the highest (lowest) skill among the five datasets. The observed GM precipitation shows an increasing tendency during 1979-2001 along with a strong interannual variability, which is reasonably reproduced by the five sets of reanalysis data. The observed increasing trend of GM precipitation is dominated by the contribution from the North African, North American and Australian monsoons. All five data fail in reproducing the increasing tendency of North African monsoon precipitation. The wind convergence term in water budget equation dominate the GM precipitation variation, indicating a consistency between the GM precipitation and the seasonal change of prevailing wind.

Lin, Renping; Zhou, Tianjun; Qian, Yun

2014-02-01T23:59:59.000Z

356

Fact #852 December 22, 2014 Turbocharged Engines Account for 64.7% of all Four-Cylinder Gasoline Car Engines in 2014- Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Fact #852 December 22, 2014 Turbocharged Engines Account for 64.7% of all Four-Cylinder Gasoline Car Engines in 2014

357

Fact #863 March 9, 2015 Crude Oil Accounts for the Majority of Primary Energy Imports while Exports are Mostly Petroleum Products Dataset  

Broader source: Energy.gov [DOE]

Excel file and dataset for Crude Oil Accounts for the Majority of Primary Energy Imports while Exports are Mostly Petroleum Products

358

Fact #849: December 1, 2014 Midsize Hybrid Cars Averaged 51% Better Fuel Economy than Midsize Non-Hybrid Cars in 2014- Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Fact #849: December 1, 2014 Midsize Hybrid Cars Averaged 51% Better Fuel Economy than Midsize Non-Hybrid Cars in 2014

359

Fact #832: August 4, 2014 Over Half of the Refueling Stations in the U.S. and Canada Sell Diesel Fuel- Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Fact #832: Over Half of the Refueling Stations in the U.S. and Canada Sell Diesel Fuel

360

Fact #848: November 24, 2014 Nearly Three-Fourths of New Cars have Fuel Economy above 25 Miles per Gallon- Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Fact #848: November 24, 2014 Nearly Three-Fourths of New Cars have Fuel Economy above 25 Miles per Gallon

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


361

Exploring the Properties of Dark Energy Using Type Ia Supernovae and Other Datasets  

E-Print Network [OSTI]

We reconstruct dark energy properties from two complementary supernova datasets -- the newly released Gold+HST sample and SNLS. The results obtained are consistent with standard $\\Lambda$CDM model within $2\\sigma$ error bars although the Gold+HST data favour evolving dark energy slightly more than SNLS. Using complementary data from baryon acoustic oscillations and the cosmic microwave background to constrain dark energy, we find that our results in this case are strongly dependent on the present value of the matter density $\\Omega_m$. Consequently, no firm conclusions regarding constancy or variability of dark energy density can be drawn from these data alone unless the value of $\\Omega_m$ is known to an accuracy of a few percent. However, possible variability is significantly restricted if this data is used in conjunction with supernova data.

Ujjaini Alam; Varun Sahni; Alexei A. Starobinsky

2006-12-14T23:59:59.000Z

362

Exploring Cosmological Expansion Parametrizations with the Gold SnIa Dataset  

E-Print Network [OSTI]

We use the SnIa Gold dataset to compare LCDM with 10 representative parametrizations of the recent Hubble expansion history $H(z)$. For the comparison we use two statistical tests; the usual $\\chi_{min}^2$ which is insensitive to the parametrization number of parameters, and a statistic we call the p-test which depends on both the value of $\\chi_{min}^2$ and the number $n$ of the parametrization parameters. The p-test measures the confidence level to which the parameter values corresponding to LCDM are excluded from the viewpoint of the parametrization tested. For example, for a linear equation of state parametrization $w(z)=w_0 + w_1 z$ the LCDM parameter values ($w_0=-1$, $w_1=0$) are excluded at 75% confidence level. We use a flat prior and $\\Omega_{0m}=0.3$. All parametrizations tested are consistent with the Gold dataset at their best fit. According to both statistical tests, the worst fits among the 10 parametrizations, correspond to the Chaplygin gas, the brane world and the Cardassian parametrizations. The best fit is achieved by oscillating parametrizations which can exclude the parameter values corresponding to LCDM at 85% confidence level. Even though this level of significance does not provide a statistically significant exclusion of LCDM (it is less than $2\\sigma$) and does not by itself constitute conclusive evidence for oscillations in the cosmological expansion, when combined with similar independent recent evidence for oscillations coming from the CMB and matter power spectra it becomes an issue worth of further investigation.

R. Lazkoz; S. Nesseris; L. Perivolaropoulos

2005-11-10T23:59:59.000Z

363

Using Graphs for Fast Error Term Approximation of Time-varying Datasets  

SciTech Connect (OSTI)

We present a method for the efficient computation and storage of approximations of error tables used for error estimation of a region between different time steps in time-varying datasets. The error between two time steps is defined as the distance between the data of these time steps. Error tables are used to look up the error between different time steps of a time-varying dataset, especially when run time error computation is expensive. However, even the generation of error tables itself can be expensive. For n time steps, the exact error look-up table (which stores the error values for all pairs of time steps in a matrix) has a memory complexity and pre-processing time complexity of O(n2), and O(1) for error retrieval. Our approximate error look-up table approach uses trees, where the leaf nodes represent original time steps, and interior nodes contain an average (or best-representative) of the children nodes. The error computed on an edge of a tree describes the distance between the two nodes on that edge. Evaluating the error between two different time steps requires traversing a path between the two leaf nodes, and accumulating the errors on the traversed edges. For n time steps, this scheme has a memory complexity and pre-processing time complexity of O(nlog(n)), a significant improvement over the exact scheme; the error retrieval complexity is O(log(n)). As we do not need to calculate all possible n2 error terms, our approach is a fast way to generate the approximation.

Nuber, C; LaMar, E C; Pascucci, V; Hamann, B; Joy, K I

2003-02-27T23:59:59.000Z

364

Volume rendering at interactive frame rates remains a chal-lenge, especially with today's increasingly large datasets. We pro-  

E-Print Network [OSTI]

Abstract Volume rendering at interactive frame rates remains a chal- lenge, especially with today's increasingly large datasets. We pro- pose a framework, using concepts from Image-Based Rendering (IBR), that decreases the required framerate for the volume ren- derer significantly. All the volume renderer needs

Crawfis, Roger

365

Volume rendering at interactive frame rates remains a chal-lenge, especially with today's increasingly large datasets. We pro-  

E-Print Network [OSTI]

1 Abstract Volume rendering at interactive frame rates remains a chal- lenge, especially with today's increasingly large datasets. We pro- pose a framework, using concepts from Image-Based Rendering (IBR), that decreases the required framerate for the volume ren- derer significantly. All the volume renderer needs

Mueller, Klaus

366

Extended data analysis strategies for high resolution imaging MS: New methods to deal with extremely large image hyperspectral datasets  

E-Print Network [OSTI]

The large size of the hyperspectral datasets that are produced with modern mass spectrometric imaging techniques makes it difficult to analyze the results. Unsupervised statistical techniques are needed to extract relevant information from these datasets and reduce the data into a surveyable overview. Multivariate statistics are commonly used for this purpose. Computational power and computer memory limit the resolution at which the datasets can be analyzed with these techniques. We introduce the use of a data format capable of efficiently storing sparse datasets for multivariate analysis. This format is more memory-efficient and therefore it increases the possible resolution together with a decrease of computation time. Three multivariate techniques are compared for both sparse-type data and non-sparse data acquired in two different imaging ToF-SIMS experiments and one LDI-ToF imaging experiment. There is no significant qualitative difference in the use of different data formats for the same multivariate algorithms. All evaluated multivariate techniques could be applied on both SIMS and the LDI imaging datasets. Principal component analysis is shown to be the fastest choice; however a small increase of computation time using a VARIMAX optimization increases the decomposition quality significantly. PARAFAC analysis is shown to be very effective in separating different chemical components but the calculations take a significant amount of time, limiting its use as a routine technique. An effective visualization of the results of the multivariate analysis is as important for the analyst as the computational issues. For this reason, a new technique for visualization is presented, combining both spectral loadings and spatial

Leendert A. Klerk A; Er Broersen B; Ian W. Fletcher C

2006-01-01T23:59:59.000Z

367

An accurate determination of the Hubble constant from Baryon Acoustic Oscillation datasets  

E-Print Network [OSTI]

Even though the Hubble constant cannot be significantly determined by the low-redshift Baryon Acoustic Oscillation (BAO) data alone, it can be tightly constrained once the high-redshift BAO data are combined. Combining BAO data from 6dFGS, BOSS DR11 clustering of galaxies, WiggleZ and $z=2.34$ from BOSS DR11 quasar Lyman-$\\alpha$ forest lines, we get $H_0=68.17^{+1.55}_{-1.56}$ km s$^{-1}$ Mpc$^{-1}$. In addition, adopting the the simultaneous measurements of $H(z)$ and $D_A(z)$ from the two-dimensional two-point correlation function from BOSS DR9 CMASS sample and two-dimensional matter power spectrum from SDSS DR7 sample, we obtain $H_0=68.11\\pm1.69$ km s$^{-1}$ Mpc$^{-1}$. Finally, combining all of the BAO datasets, we conclude $H_0=68.11\\pm 0.86$ km s$^{-1}$ Mpc$^{-1}$, a 1.3% determination.

Cheng Cheng; Qing-Guo Huang

2014-09-22T23:59:59.000Z

368

Use of datasets derived from time-series AVHRR imagery as surrogates for land cover maps in predicting species' distributions  

E-Print Network [OSTI]

to be the case, it may be possible to use AVHRR, MODIS, or similar imagery, either in raw form or as easily and cheaply derived datasets, as direct inputs to models that predict species distributions. II. METHODS In this pilot analysis, we selected... for Advanced Computational Infrastructure, Earth System Science (NPACI/ESS) Thrust. E.M-M. was supported by a graduate fellowship from the Direccion General de Asuntos del Personal Academico of the National University of Mexico (UNAM...

Egbert, Stephen L.; Martí nez-Meyer, Enrique; Ortega-Huerta, Miguel; Peterson, A. Townsend

2002-06-01T23:59:59.000Z

369

Indoor carbon dioxide concentrations and sick building syndrome symptoms in the BASE study revisited: Analyses of the 100 building dataset  

SciTech Connect (OSTI)

In previously published analyses of the 41-building 1994-1996 USEPA Building Assessment Survey and Evaluation (BASE) dataset, higher workday time-averaged indoor minus outdoor CO{sub 2} concentrations (dCO{sub 2}) were associated with increased prevalence of certain mucous membrane and lower respiratory sick building syndrome (SBS) symptoms, even at peak dCO{sub 2} concentrations below 1,000 ppm. For this paper, similar analyses were performed using the larger 100-building 1994-1998 BASE dataset. Multivariate logistic regression analyses quantified the associations between dCO{sub 2} and the SBS symptoms, adjusting for age, sex, smoking status, presence of carpet in workspace, thermal exposure, relative humidity, and a marker for entrained automobile exhaust. Adjusted dCO{sub 2} prevalence odds ratios for sore throat and wheeze were 1.17 and 1.20 per 100-ppm increase in dCO{sub 2} (p <0.05), respectively. These new analyses generally support our prior findings. Regional differences in climate, building design, and operation may account for some of the differences observed in analyses of the two datasets.

Erdmann, Christine A.; Steiner, Kate C.; Apte, Michael G.

2002-02-01T23:59:59.000Z

370

AppStat14.xlsx  

Energy Savers [EERE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious RankCombustion |Energy UsageAUDITVehiclesTankless orA BRIEF HISTORYAgencyLocal|Annual Uncosted. 42,000 42,257

371

Apps | OpenEI Community  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpenWendeGuo Feng Bio Energy Co Ltd JumpJump to:OpenEIavailabledone6

372

App_B_Correspondence_Agencies  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "ofEarly Career Scientists' ResearchThe OfficeUtility Fed.9-0s)Excel workbook (version 5.2) isof EnergyC

373

Field App. 6.5  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation ProposedUsing ZirconiaPolicyFeasibility ofSmall15.000TechnologyTuneFewerDrilling &

374

Field App. 6.5  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation ProposedUsing ZirconiaPolicyFeasibility ofSmall15.000TechnologyTuneFewerDrilling &Cambria

375

Field App. 6.5  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation ProposedUsing ZirconiaPolicyFeasibility ofSmall15.000TechnologyTuneFewerDrilling

376

Field App. 6.5  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation ProposedUsing ZirconiaPolicyFeasibility ofSmall15.000TechnologyTuneFewerDrillingTHE PROBLEM

377

PAC_5Oct01_App  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 - September 2006 The 2002Optics GroupPlanningP-GlycoproteinAmmonia R ¯ Q ¯May 3,

378

PAC_5Oct01_App  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 - September 2006 The 2002Optics GroupPlanningP-GlycoproteinAmmonia R ¯ Q ¯May

379

OpenEI Community - Apps  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth'sOklahoma/Geothermal < Oklahoma Jumpcommunity 2013 Civic Hacking Day Ideas

380

Accurate Analysis of Large Datasets of Protein-Ligand Binding Geometries Using a Linear Clustering Method Based on MapReduce  

E-Print Network [OSTI]

are traditionally scored based on energy values. A protein-ligand complex selected because Accurate Analysis of Large Datasets of Protein-Ligand Binding Geometries for classifying protein-ligand binding geometries in molecular docking. We analyze results

Maccabe, Barney

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


381

SFI++ II: A New I-band Tully-Fisher Catalog, Derivation of Peculiar Velocities and Dataset Properties  

E-Print Network [OSTI]

We present the SFI++ dataset, a homogeneously derived catalog of photometric and rotational properties and the Tully-Fisher distances and peculiar velocities derived from them. We make use of digital optical images, optical long-slit spectra, and global HI line profiles to extract parameters of relevance to disk scaling relations, incorporating several previously published datasets as well as a new photometric sample of some 2000 objects. According to the completeness of available redshift samples over the sky area, we exploit both a modified percolation algorithm and the Voronoi-Delaunay method to assign individual galaxies to groups as well as clusters, thereby reducing scatter introduced by local orbital motions. We also provide corrections to the peculiar velocities for both homogeneous and inhomogeneous Malmquist bias, making use of the 2MASS Redshift Survey density field to approximate large scale structure. We summarize the sample selection criteria, corrections made to raw observational parameters, the grouping techniques, and our procedure for deriving peculiar velocities. The final SFI++ peculiar velocity catalog of 4861 field and cluster galaxies is large enough to permit the study not just of the global statistics of large scale flows but also of the {\\it details} of the local velocity field.

Christopher M. Springob; Karen L. Masters; Martha P. Haynes; Riccardo Giovanelli; Christian Marinoni

2007-05-04T23:59:59.000Z

382

Browse By Region | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpenWendeGuo FengBoulder, CO) JumpNREL Biofuels

383

DOE Research and Development Accomplishments Database Browse  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to UserProduct: Crude OilPublicDNALostPlasma PhysicsDOE

384

Browse Archived Directives - DOE Directives, Delegations, and  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone6 M.ExtracellularBradburyBrianforRequirements Accessibility

385

Browse Designations - DOE Directives, Delegations, and Requirements  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone6 M.ExtracellularBradburyBrianforRequirements

386

Browse Archived Directives - DOE Directives, Delegations, and  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformation InInformationCenterResearch HighlightsToolsBESEnergyArchaeology onEnergy InnovationBook

387

Browse Designations - DOE Directives, Delegations, and Requirements  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareers ApplyResistant:NOAA-EPA UVBrown carbon formation from

388

Robust Machine Learning Applied to Astronomical Datasets II: Quantifying Photometric Redshifts for Quasars Using Instance-Based Learning  

E-Print Network [OSTI]

We apply instance-based machine learning in the form of a k-nearest neighbor algorithm to the task of estimating photometric redshifts for 55,746 objects spectroscopically classified as quasars in the Fifth Data Release of the Sloan Digital Sky Survey. We compare the results obtained to those from an empirical color-redshift relation (CZR). In contrast to previously published results using CZRs, we find that the instance-based photometric redshifts are assigned with no regions of catastrophic failure. Remaining outliers are simply scattered about the ideal relation, in a similar manner to the pattern seen in the optical for normal galaxies at redshifts z < ~1. The instance-based algorithm is trained on a representative sample of the data and pseudo-blind-tested on the remaining unseen data. The variance between the photometric and spectroscopic redshifts is sigma^2 = 0.123 +/- 0.002 (compared to sigma^2 = 0.265 +/- 0.006 for the CZR), and 54.9 +/- 0.7%, 73.3 +/- 0.6%, and 80.7 +/- 0.3% of the objects are within delta z < 0.1, 0.2, and 0.3 respectively. We also match our sample to the Second Data Release of the Galaxy Evolution Explorer legacy data and the resulting 7,642 objects show a further improvement, giving a variance of sigma^2 = 0.054 +/- 0.005, and 70.8 +/- 1.2%, 85.8 +/- 1.0%, and 90.8 +/- 0.7% of objects within delta z < 0.1, 0.2, and 0.3. We show that the improvement is indeed due to the extra information provided by GALEX, by training on the same dataset using purely SDSS photometry, which has a variance of sigma^2 = 0.090 +/- 0.007. Each set of results represents a realistic standard for application to further datasets for which the spectra are representative.

Nicholas M. Ball; Robert J. Brunner; Adam D. Myers; Natalie E. Strand; Stacey L. Alberts; David Tcheng; Xavier Llor

2006-12-17T23:59:59.000Z

389

Oscillations in the inflaton potential: Complete numerical treatment and comparison with the recent and forthcoming CMB datasets  

E-Print Network [OSTI]

Amongst the multitude of inflationary models currently available, models that lead to features in the primordial scalar spectrum are drawing increasing attention, since certain features have been found to provide a better fit to the CMB data than the conventional, nearly scale invariant, primordial spectrum. In this work, we carry out a complete numerical analysis of two models that lead to oscillations over all scales in the scalar power spectrum. We consider the model described by a quadratic potential which is superposed by a sinusoidal modulation and the recently popular axion monodromy model. Since the oscillations continue even on to arc minute scales, in addition to the WMAP data, we also compare the models with the small scale data from ACT. Though, both the models, broadly, result in oscillations in the spectrum, interestingly, we find that, while the monodromy model leads to a considerably better fit to the data in comparison to the standard power law spectrum, the quadratic potential superposed with a sinusoidal modulation does not improve the fit to a similar extent. We also carry out forecasting of the parameters using simulated Planck data for both the models. We show that the Planck mock data performs better in constraining the model parameters as compared to the presently available CMB datasets.

Moumita Aich; Dhiraj Kumar Hazra; L. Sriramkumar; Tarun Souradeep

2012-10-22T23:59:59.000Z

390

DEVELOPING AND EXPLOITING A UNIQUE DATASET FROM SOUTH AFRICAN GOLD MINES FOR SOURCE CHARACTERIZATION AND WAVE PROPAGATION  

SciTech Connect (OSTI)

In this project, we are developing and exploiting a unique seismic dataset to address the characteristics of small seismic events and the associated seismic signals observed at local (< 200 km) and regional (< 2000 km) distances. The dataset is being developed using mining-induced events from three deep gold mines in South Africa recorded on in-mine networks (< 1 km) composed of tens of high-frequency sensors, a network of four broadband stations installed as part of this project at the surface around the mines (1-10 km), and a network of existing broadband seismic stations at local/regional distances (50-1000 km) from the mines. Data acquisition has now been completed and includes: (1) {approx}2 years (2007 and 2008) of continuous recording by the surface broadband array, and (2) tens of thousands of mine tremors in the -3.4 < ML < 4.4 local magnitude range. Events with positive magnitudes are generally well recorded by the surface-mine stations, while magnitudes of 3.0 and larger are seen at regional distances (up to {approx} 600 km) in high-pass filtered recordings. We have now completed the quality control of the in-mine data gathered at the three gold mines included in this project. The quality control consisted of: (1) identification and analysis of outliers among the P- and S-wave travel-time picks reported by the in-mine network operator and (2) verification of sensor orientations. The outliers have been identified through a 'Wadati filter' that searches for the largest subset of P- and S-wave travel-time picks consistent with a medium of uniform wave-speed. They have observed that outliers are generally picked at a few select stations. They have also detected that trigger times were mistakenly reported as origin times by the in-mine network operator, and corrections have been obtained from the intercept times in the Wadati diagrams. Sensor orientations have been verified through rotations into the local ray-coordinate system and, when possible, corrected by correlating waveforms obtained from theoretical and empirical rotation angles. Full moment tensor solutions have been obtained for selected events within the Savuka network volume, with moment magnitudes in the 0.5 < M{sub W} < 2.6 range. The solutions were obtained by inverting P-, SV-, and SH-spectral amplitudes measured on the theoretically rotated waveforms with visually assigned polarities. Most of the solutions have a non-zero implosive contribution (47 out of 76), while a small percentage is purely deviatoric (10 out of 76). The deviatoric moment tensors range from pure double couple to pure non-double couple mechanisms. We have also calibrated the regional stations for seismic coda-derived source spectra and moment magnitude using the envelope methodology of Mayeda et al. (2003). they tie the coda M{sub w} to independent values from waveform modeling. The resulting coda-based source spectra of shallow mining-related events show significant spectral peaking that is not seen in deeper tectonic earthquakes. This coda peaking may be an independent method of identifying shallow events and is similar to coda peaking with previously observed for Nevada explosions, where the frequency of the observed spectral peak correlates with the depth of burial (Murphy et al., 2009).

Julia, J; Nyblade, A; Gok, R; Walter, W; Linzer, L; Durrheim, R

2009-07-06T23:59:59.000Z

391

Experimental Datasets - Optimization Online  

E-Print Network [OSTI]

Mar 29, 2005 ... Preprint in Russian, see also the next paper in English, data and code in kcl, also ... Preprint in Russian, data and code in varcomp and in tdlib.

2005-03-29T23:59:59.000Z

392

Stalking the Wild Dataset  

E-Print Network [OSTI]

data, now migrated to the Web without the need to downloaddatabase, click on DataInsight-Web on left menu. Time-seriesthe years that follow." - Web site. Making ConnectionsNOTE:

Tsang, Daniel C

2015-01-01T23:59:59.000Z

393

Models and Datasets  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: VegetationEquipment SurfacesResource Program PreliminaryA3,0StatementsMixingAssessing8

394

Fact #843: October 20, 2014 Cumulative Plug-in Electric Vehicle Sales are Two and a Half Times Higher than Hybrid Electric Vehicle Sales in the First 45 Months since Market Introduction Dataset  

Broader source: Energy.gov [DOE]

Excel file with dataset for Fact #843: Cumulative Plug-in Electric Vehicle Sales are Two and a Half Times Higher than Hybrid Electric Vehicle Sales in the First 45 Months since Market Introduction

395

ARM - VAP Process - armbe2dgrid  

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

ARM Data Discovery Browse Data Comments? We would love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send VAP : ARMBE 2D gridded surface dataset (ARMBE2DGRID...

396

Treatment Planning Constraints to Avoid Xerostomia in Head-and-Neck Radiotherapy: An Independent Test of QUANTEC Criteria Using a Prospectively Collected Dataset  

SciTech Connect (OSTI)

Purpose: The severe reduction of salivary function (xerostomia) is a common complication after radiation therapy for head-and-neck cancer. Consequently, guidelines to ensure adequate function based on parotid gland tolerance dose-volume parameters have been suggested by the QUANTEC group and by Ortholan et al. We perform a validation test of these guidelines against a prospectively collected dataset and compared with a previously published dataset. Methods and Materials: Whole-mouth stimulated salivary flow data from 66 head-and-neck cancer patients treated with radiotherapy at the British Columbia Cancer Agency (BCCA) were measured, and treatment planning data were abstracted. Flow measurements were collected from 50 patients at 3 months, and 60 patients at 12-month follow-up. Previously published data from a second institution, Washington University in St. Louis (WUSTL), were used for comparison. A logistic model was used to describe the incidence of Grade 4 xerostomia as a function of the mean dose of the spared parotid gland. The rate of correctly predicting the lack of xerostomia (negative predictive value [NPV]) was computed for both the QUANTEC constraints and Ortholan et al. recommendation to constrain the total volume of both glands receiving more than 40 Gy to less than 33%. Results: Both datasets showed a rate of xerostomia of less than 20% when the mean dose to the least-irradiated parotid gland is kept to less than 20 Gy. Logistic model parameters for the incidence of xerostomia at 12 months after therapy, based on the least-irradiated gland, were D{sub 50} = 32.4 Gy and and {gamma} = 0.97. NPVs for QUANTEC guideline were 94% (BCCA data), and 90% (WUSTL data). For Ortholan et al. guideline NPVs were 85% (BCCA) and 86% (WUSTL). Conclusion: These data confirm that the QUANTEC guideline effectively avoids xerostomia, and this is somewhat more effective than constraints on the volume receiving more than 40 Gy.

Moiseenko, Vitali, E-mail: vmoiseenko@bccancer.bc.ca [Department of Medical Physics, Vancouver Cancer Centre, British Columbia Cancer Agency, Vancouver, BC (Canada); Wu, Jonn [Department of Radiation Oncology, Vancouver Cancer Centre, British Columbia Cancer Agency, Vancouver, BC (Canada); Hovan, Allan [Department of Oral Oncology, Vancouver Cancer Centre, British Columbia Cancer Agency, Vancouver, BC (Canada); Saleh, Ziad; Apte, Aditya; Deasy, Joseph O. [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY (United States); Harrow, Stephen [Department of Radiation Oncology, Vancouver Cancer Centre, British Columbia Cancer Agency, Vancouver, BC (Canada); Rabuka, Carman; Muggli, Adam [Department of Oral Oncology, Vancouver Cancer Centre, British Columbia Cancer Agency, Vancouver, BC (Canada); Thompson, Anna [Department of Radiation Oncology, Vancouver Cancer Centre, British Columbia Cancer Agency, Vancouver, BC (Canada)

2012-03-01T23:59:59.000Z

397

Microsoft Word - ^App Slipsheets.docx  

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

into a quickly available tanker for delivery to a U.S. GOM port. The restarting of offshore production in 2005 was made difficult by delays pertaining to the offloading issue...

398

Microsoft Word - App E Update Oct 2010  

National Nuclear Security Administration (NNSA)

TPWC 64 Texas Parks and Wildlife Code: Birds TPWC 66 Texas Parks and Wildlife Code: Fish TPWC 67 Texas Parks and Wildlife Code: Non Game Species TPWC 68 Texas Parks and...

399

Opower Thermostat App | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia: Energy ResourcesLoading map...(UtilityCounty, Michigan: EnergyOpenBarter Jump

400

NERSC Releases Mobile Apps to Users  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas Conchas recovery challengeMultiscaleLogos NERSC Logos NERSC logos arePlayed Key RoleReleases

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


401

Advanced Plasma Power APP | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpenWende NewSowitecAWS Ocean EnergyAdirondackBioenergy LLCPlasma

402

The Booming App Economy | Department of Energy  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious RankCombustion |Energy Usage »of Energy StrainClientDesignOfficeThe 21st CenturyThe2TheCreatingThe

403

Microsoft Word - App E Update Oct 2010  

National Nuclear Security Administration (NNSA)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "ofEarlyEnergyDepartmentNationalRestart of the Review of the Yucca MountainSourceUsers6 SPONSORED BY .

404

DOE APP 11-09.qxd  

Office of Environmental Management (EM)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergy Cooperation |South42.2Consolidated Edison5 by ISA -ofDATA REPORTI Office ofDNS asT A * S H

405

vol2app.chp:Corel VENTURA  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) " ,"ClickPipelinesProvedDecember 2005 (Thousand Barrels, Except Where Noted)December 2005 (ThousandEnergy

406

Apps for Energy Challenge | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergyCT Biomass Facility JumpvolcanicPhase 1ProcessesAppro-TecinAbout

407

HPC_AppPerf_2011.pptx  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation ProposedUsingFun with Big Sky9, 2010 The meeting wasEngineering and Debugging HPC Applications

408

Geothermal Prospector Web App | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia: Energy Resources Jump to: navigation, searchGeauga County,Information(EC-LEDS)Et1957) |(Ward,|

409

Sandia National Laboratories: The Killer App  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -theErikGroundbreakingStandardsTCES Sandia ResearchersDevelopmentClimateThe

410

Green Button Apps | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating Solar Power BasicsGermany: Energy Resources JumpEnergyGoltryOhio:Applications

411

Energy Apps Catalog | OpenEI  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORT Americium/Curium Vitrification Project At TheEXTERNAL INDEPENDENTApps

412

SU-E-I-87: Automated Liver Segmentation Method for CBCT Dataset by Combining Sparse Shape Composition and Probabilistic Atlas Construction  

SciTech Connect (OSTI)

Purpose: The aiming of this study was to extract liver structures for daily Cone beam CT (CBCT) images automatically. Methods: Datasets were collected from 50 intravenous contrast planning CT images, which were regarded as training dataset for probabilistic atlas and shape prior model construction. Firstly, probabilistic atlas and shape prior model based on sparse shape composition (SSC) were constructed by iterative deformable registration. Secondly, the artifacts and noise were removed from the daily CBCT image by an edge-preserving filtering using total variation with L1 norm (TV-L1). Furthermore, the initial liver region was obtained by registering the incoming CBCT image with the atlas utilizing edge-preserving deformable registration with multi-scale strategy, and then the initial liver region was converted to surface meshing which was registered with the shape model where the major variation of specific patient was modeled by sparse vectors. At the last stage, the shape and intensity information were incorporated into joint probabilistic model, and finally the liver structure was extracted by maximum a posteriori segmentation.Regarding the construction process, firstly the manually segmented contours were converted into meshes, and then arbitrary patient data was chosen as reference image to register with the rest of training datasets by deformable registration algorithm for constructing probabilistic atlas and prior shape model. To improve the efficiency of proposed method, the initial probabilistic atlas was used as reference image to register with other patient data for iterative construction for removing bias caused by arbitrary selection. Results: The experiment validated the accuracy of the segmentation results quantitatively by comparing with the manually ones. The volumetric overlap percentage between the automatically generated liver contours and the ground truth were on an average 88%95% for CBCT images. Conclusion: The experiment demonstrated that liver structures of CBCT with artifacts can be extracted accurately for following adaptive radiation therapy. This work is supported by National Natural Science Foundation of China (No. 61201441), Research Fund for Excellent Young and Middle-aged Scientists of Shandong Province (No. BS2012DX038), Project of Shandong Province Higher Educational Science and Technology Program (No. J12LN23), Jinan youth science and technology star (No.20120109)

Li, Dengwang [Shandong Normal University, Jinan, Shandong Province (China); Liu, Li [Shandong Normal University, Jinan, Shandong (China); Chen, Jinhu; Li, Hongsheng [Shandong Cancer Hospital and Institute, Jinan, Shandong (China)

2014-06-01T23:59:59.000Z

413

World Climate Research Programme (WCRP) Coupled Model Intercomparison Project phase 3 (CMIP3): Multi-Model Dataset Archive at PCMDI (Program for Climate Model Diagnosis and Intercomparison)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

In response to a proposed activity of the WCRP's Working Group on Coupled Modelling (WGCM),PCMDI volunteered to collect model output contributed by leading modeling centers around the world. Climate model output from simulations of the past, present and future climate was collected by PCMDI mostly during the years 2005 and 2006, and this archived data constitutes phase 3 of the Coupled Model Intercomparison Project (CMIP3). In part, the WGCM organized this activity to enable those outside the major modeling centers to perform research of relevance to climate scientists preparing the Fourth Asssessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The IPCC was established by the World Meteorological Organization and the United Nations Environmental Program to assess scientific information on climate change. The IPCC publishes reports that summarize the state of the science. This unprecedented collection of recent model output is officially known as the WCRP CMIP3 multi-model dataset. It is meant to serve IPCC's Working Group 1, which focuses on the physical climate system - atmosphere, land surface, ocean and sea ice - and the choice of variables archived at the PCMDI reflects this focus. A more comprehensive set of output for a given model may be available from the modeling center that produced it. As of November 2007, over 35 terabytes of data were in the archive and over 303 terabytes of data had been downloaded among the more than 1200 registered users. Over 250 journal articles, based at least in part on the dataset, have been published or have been accepted for peer-reviewed publication. Countries from which models have been gathered include Australia, Canada, China, France, Germany and Korea, Italy, Japan, Norway, Russia, Great Britain and the United States. Models, variables, and documentation are collected and stored. Check http://www-pcmdi.llnl.gov/ipcc/data_status_tables.htm to see at a glance the output that is available. (Description taken from http://www-pcmdi.llnl.gov/ipcc/about_ipcc.php)

414

International Journal of Mass Spectrometry 260 (2007) 222236 Extended data analysis strategies for high resolution imaging MS: New methods to deal with extremely large image hyperspectral datasets  

E-Print Network [OSTI]

The large size of the hyperspectral datasets that are produced with modern mass spectrometric imaging techniques makes it difficult to analyze the results. Unsupervised statistical techniques are needed to extract relevant information from these datasets and reduce the data into a surveyable overview. Multivariate statistics are commonly used for this purpose. Computational power and computer memory limit the resolution at which the datasets can be analyzed with these techniques. We introduce the use of a data format capable of efficiently storing sparse datasets for multivariate analysis. This format is more memory-efficient and therefore it increases the possible resolution together with a decrease of computation time. Three multivariate techniques are compared for both sparse-type data and non-sparse data acquired in two different imaging ToF-SIMS experiments and one LDI-ToF imaging experiment. There is no significant qualitative difference in the use of different data formats for the same multivariate algorithms. All evaluated multivariate techniques could be applied on both SIMS and the LDI imaging datasets. Principal component analysis is shown to be the fastest choice; however a small increase of computation time using a VARIMAX optimization increases the decomposition quality significantly. PARAFAC analysis is shown to be very effective in separating different chemical components but the calculations take a significant amount of time, limiting its use as a routine technique. An effective visualization of the results of the multivariate analysis is as important for the analyst as the computational issues. For this reason, a new technique for visualization is presented, combining both spectral loadings and spatial

Leendert A. Klerk A; Er Broersen B; Ian W. Fletcher C

2006-01-01T23:59:59.000Z

415

App D_Terrestrial Tech App.doc 1 Protection, Restoration, and Management of  

E-Print Network [OSTI]

1.4 Analytical Approaches 7 1.5 Building Upon Previous Efforts 11 1.6 How to Apply this Report: Indicators of Oak Woodland Ecological Condition and Sustainability 54 2.3 Focal Habitat: Upland Prairie.3.9 Synthesis: Indicators of Ecological Condition and Sustainability for Upland Prairie- Savanna 78 2.4 Focal

416

Apps for Vehicles: Can I develop a vehicle data app using commercial  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpenWendeGuo Feng Bio Energy Co Ltd JumpJump to:

417

Day Labour Mobile Electronic Data Capture and Browsing System  

E-Print Network [OSTI]

South Africa Tel +27 21 650 2663 chepken@gmail.com Edwin Blake Edwin Blake Department of Computer Science University of Cape Town Private Bag X3 Rondebosch 7701 South Africa edwin@cs.uct.ac.za Gary Marsden Gary Marsden ICT4D HPI Research Centre, Department of Computer Science University of Cape Town

Blake, Edwin

418

Breaking the Browsing Barrier for Historic Searching of Newspaper Texts.  

E-Print Network [OSTI]

government sources, from religious factions, and from indigenous sectors. Approximately 70% of the newspapers

Keegan, Te Taka

419

Dynamically exploiting available metadata for browsing and information retrieval  

E-Print Network [OSTI]

Systems trying to help users deal with information overload need to be able to support the user in an information-centric manner, and need to support portions of the information which are structured -like creation dates ...

Sinha, Vineet, 1978-

2004-01-01T23:59:59.000Z

420

JPEG2000-based Viewer Guidance for Mobile Image Browsing  

E-Print Network [OSTI]

is needed - the new image must only be decoded. The same principle is applied for image transmission, where properties of the new and flexible image coding standard JPEG2000 for creation and transmission- quires less bandwidth during image transmission. Regard- ing the main limitations of mobile devices

Rosenbaum, Rene

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


421

A Framework for Browsing, Manipulating and Maintaining Interoperable Learner Profiles  

E-Print Network [OSTI]

an extensible API to process heterogeneous profiles. The rest of the paper is structured as follows: Section 2. An API is designed and implemented to create/export and manipulate such learner profiles. The API is implemented for two cases, as a Java API and as web services with synchronized model exchange between multiple

Dolog, Peter

422

Dynamics of Tilt-based Browsing on Mobile Devices  

E-Print Network [OSTI]

Cho,S.J. Murray-Smith,R. Choi,C. Sung,Y. Lee,K. Kim,Y.B. CHI '07 extended abstracts on Human factors in computing systems, http://doi.acm.org/10.1145/1240866.1240930 pp 1947 - 1952 ACM Press

Cho, S.J.; Murray-Smith, R.

423

Dynamics of Tilt-based Browsing on Mobile Devices  

E-Print Network [OSTI]

with a button- based browser and an iPod wheel. We discuss the usability performance and contrast this with subjective experience from the users. The iPod wheel has significantly poorer performance than button pushing-handed use. An alternative is Apple's iPod click wheel [5] which enables users to scroll the list by rotating

Williamson, John

424

Browse by Discipline -- E-print Network Subject Pathways: -- Energy,  

Office of Scientific and Technical Information (OSTI)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinan antagonist Journal Article: Crystal structureComposite JC-118794ArgonneAnalysing thescience, and

425

Browse by Discipline -- E-print Network Subject Pathways: Biotechnology --  

Office of Scientific and Technical Information (OSTI)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinan antagonist Journal Article: Crystal structureComposite JC-118794ArgonneAnalysing thescience,

426

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

Office of Scientific and Technical Information (OSTI)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinan antagonist Journal Article: Crystal structureComposite JC-118794ArgonneAnalysing thescience,Energy,

427

Browse by Discipline -- E-print Network Subject Pathways: Computer  

Office of Scientific and Technical Information (OSTI)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinan antagonist Journal Article: Crystal structureComposite JC-118794ArgonneAnalysing

428

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

Office of Scientific and Technical Information (OSTI)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinan antagonist Journal Article: Crystal structureComposite JC-118794ArgonneAnalysingConversion andEnergy,

429

Browse by Discipline -- E-print Network Subject Pathways: Environmental  

Office of Scientific and Technical Information (OSTI)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinan antagonist Journal Article: Crystal structureComposite JC-118794ArgonneAnalysingConversion

430

Browse by Discipline -- E-print Network Subject Pathways: Environmental  

Office of Scientific and Technical Information (OSTI)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinan antagonist Journal Article: Crystal structureComposite JC-118794ArgonneAnalysingConversionSciences and

431

Browse by Discipline -- E-print Network Subject Pathways: Geosciences --  

Office of Scientific and Technical Information (OSTI)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinan antagonist Journal Article: Crystal structureComposite

432

Browse by Discipline -- E-print Network Subject Pathways: Mathematics --  

Office of Scientific and Technical Information (OSTI)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinan antagonist Journal Article: Crystal structureComposite-- Energy, science, and technology for the

433

Browse by Discipline -- E-print Network Subject Pathways: Physics --  

Office of Scientific and Technical Information (OSTI)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinan antagonist Journal Article: Crystal structureComposite-- Energy, science, and technology for theEnergy,

434

Browse by Discipline -- E-print Network Subject Pathways: Power  

Office of Scientific and Technical Information (OSTI)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinan antagonist Journal Article: Crystal structureComposite-- Energy, science, and technology forTransmission,

435

Browse by Discipline -- E-print Network Subject Pathways: Computer  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone6

436

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone6Energy, science, and technology for the research community --

437

Browse Draft Directives - DOE Directives, Delegations, and Requirements  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareers ApplyResistant:NOAA-EPA UVBrown carbon formation

438

Browse by Discipline -- E-print Network Subject Pathways: -- Energy,  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareers ApplyResistant:NOAA-EPA UVBrownOther --science, and

439

Browse by Discipline -- E-print Network Subject Pathways: Biotechnology --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareers ApplyResistant:NOAA-EPAMedicine

440

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

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


441

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareers ApplyResistant:NOAA-EPAMedicineEnergy, science,

442

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareers ApplyResistant:NOAA-EPAMedicineEnergy, science,Energy,

443

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareers ApplyResistant:NOAA-EPAMedicineEnergy,

444

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareers ApplyResistant:NOAA-EPAMedicineEnergy,Energy, science,

445

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareers ApplyResistant:NOAA-EPAMedicineEnergy,Energy,

446

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareers ApplyResistant:NOAA-EPAMedicineEnergy,Energy,Energy,

447

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

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448

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and technology for the research

449

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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450

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and technology for the

451

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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452

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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453

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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454

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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455

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and technology forEnergy, science, and

456

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and technology forEnergy, science,

457

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and technology forEnergy,

458

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and technology forEnergy,Energy,

459

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and technology forEnergy,Energy,Energy,

460

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and technology

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


461

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and technologyEnergy, science, and

462

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and technologyEnergy, science,

463

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and technologyEnergy, science,Energy,

464

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and technologyEnergy,

465

Browse by Discipline -- E-print Network Subject Pathways: Chemistry --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and technologyEnergy,Energy, science,

466

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and technologyEnergy,Energy,Energy,

467

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, and

468

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy, science, and technology for

469

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy, science, and technology

470

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy, science, and

471

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy, science, andEnergy, science,

472

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy, science, andEnergy,

473

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy, science, andEnergy,Energy,

474

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy, science,

475

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy, science,Energy, science, and

476

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy, science,Energy, science,

477

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy, science,Energy,

478

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy, science,Energy,Energy,

479

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy,

480

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy,Energy, science, and

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


481

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy,Energy, science, andEnergy,

482

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy,Energy, science,

483

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy,Energy, science,Energy,

484

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy,Energy,

485

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy,Energy,Energy, science, and

486

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy,Energy,Energy, science,

487

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy,Energy,Energy,

488

Browse by Discipline -- E-print Network Subject Pathways: Engineering --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science, andEnergy,Energy,Energy,Energy,

489

Browse by Discipline -- E-print Network Subject Pathways: Environmental  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science,

490

Browse by Discipline -- E-print Network Subject Pathways: Environmental  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science,Sciences and Ecology -- Energy, science,

491

Browse by Discipline -- E-print Network Subject Pathways: Geosciences --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science,Sciences and Ecology -- Energy,Energy,

492

Browse by Discipline -- E-print Network Subject Pathways: Mathematics --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science,Sciences and Ecology-- Energy,--Energy,

493

Browse by Discipline -- E-print Network Subject Pathways: Multidisciplinary  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science,Sciences and Ecology--

494

Browse by Discipline -- E-print Network Subject Pathways: Physics --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science,Sciences and Ecology--Energy, science,

495

Browse by Discipline -- E-print Network Subject Pathways: Physics --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science,Sciences and Ecology--Energy,

496

Browse by Discipline -- E-print Network Subject Pathways: Physics --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science,Sciences and Ecology--Energy,Energy,

497

Browse by Discipline -- E-print Network Subject Pathways: Physics --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science,Sciences and

498

Browse by Discipline -- E-print Network Subject Pathways: Physics --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science,Sciences andEnergy, science, and

499

Browse by Discipline -- E-print Network Subject Pathways: Physics --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science,Sciences andEnergy, science, andEnergy,

500

Browse by Discipline -- E-print Network Subject Pathways: Physics --  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)ProductssondeadjustsondeadjustAboutScienceCareersEnergy, science,Sciences andEnergy, science,