National Library of Energy BETA

Sample records for year rank mining

  1. Research at Mines Fiscal Year

    E-Print Network [OSTI]

    Matlock, De Moor, Speer #12;New Initiatives · Unconventional Oil & gas, Fracking (Santi) · Mines NREL

  2. B.S. in Mining Engineering Four-Year Plan

    E-Print Network [OSTI]

    Wong, Pak Kin

    courses (See advisor for requirements) 5TH SEMESTER MNE 427 Geomechanics 4 CE 214; CE 215 MNE 412 Mine MNE 427 Geomechanics 4 CE 214; CE 215 MNE 412 Mine Surveying 2 Corequisite MNE 297A CE 218 Mechanics

  3. International Conference on Ground Control in Mining During the last 25 years, technological advancement and

    E-Print Network [OSTI]

    plan, coal structure characteristics, rate of mining, overburden lithology, and the type of surface environmental considerations in the permitting, planning, and monitoring of coal mining operations. Surface

  4. Data Mining Group VNG Corporation

    E-Print Network [OSTI]

    Shahabi, Cyrus

    Data Mining Group VNG Corporation Data Mining Group_VNG Corporation 1 #12;Data Mining Group_VNG Corporation 2 1 ·Introduction 2 ·Edge Rank 3 ·Parameter Estimate 4 ·Conclusion #12;Data Mining Group_VNG Corporation 3 #12;Data Mining Group_VNG Corporation 4 #12; User's self activity Update status Write blogs

  5. Palimpsest : derelict mines and architecture of archeology one hundred years from now

    E-Print Network [OSTI]

    Gora, Tsitsi Isabel

    2009-01-01

    The realities of the built past and the palimpsest-ic nature of activities on the African mining landscape is under critique. On a site where nature gives way to the man-made activity of platinum ore excavation and mineral ...

  6. Rank Project Name Directorate,

    E-Print Network [OSTI]

    ,000 0.5 400 lbs industrial waste, eliminates potential for oil contaminated run-off 3 RetrofitRank Project Name Directorate, Dept/Div and POC Cost Savings Payback (Years) Waste Reduction 1 Minimization of Silver Waste from Silver-Staining Electrophoretic Mini-Gels Life Sciences, Biology (B

  7. Rank Journal title Eigenfactor

    E-Print Network [OSTI]

    Rank Journal title 2014 Total Cites 2014 Impact Factor 5-Year Impact Factor Immediacy Index 2013 Articles Cited Half-life Eigenfactor® Score Article Influence® Score 1 JOURNAL OF ECONOMIC LITERATURE 5861 ACADEMY OF MANAGEMENT JOURNAL 22351 6.448 9.812 0.653 72 >10.0 0.02813 5.738 5 QUARTERLY JOURNAL

  8. Rank Journal title Eigenfactor

    E-Print Network [OSTI]

    Rank Journal title 2013 Total Cites 2013 Impact Factor 5-Year Impact Factor Immediacy Index 2013 Articles Cited Half-life Eigenfactor® Score Article Influence® Score 1 JOURNAL OF ECONOMIC LITERATURE 5479 JOURNAL OF ECONOMICS 16827 5.966 9.126 0.775 40 >10.0 0.05316 14.78 5 ACADEMY OF MANAGEMENT JOURNAL 19426

  9. The Geology Department at Oregon State got its start in 1914 (then OAC), one year after the Oregon Legislature approved the establishment of the School of Mines, which

    E-Print Network [OSTI]

    Kurapov, Alexander

    The Geology Department at Oregon State got its start in 1914 (then OAC), one year after the Oregon Legislature approved the establishment of the School of Mines, which had four departments, including geology. But geology courses were o ered through various programs for scores of years before that. Alice E. Biddle

  10. Mining | 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 RankADVANCED MANUFACTURING OFFICESpecialAPPENDIX F Wetlands Assessment JulyDepartmentColoradoMining Mining

  11. Data Mining and Business Analytics

    E-Print Network [OSTI]

    Data Mining and Business Analytics CertifiCate Programs spears school of business oklahoma state university #12;e ach year, students enrolled in the OSU Graduate Certificate in Business Data Mining program compete in a national data mining shootout competition at the annual analytics (data mining) conference

  12. Low rank matrix completion

    E-Print Network [OSTI]

    Nan, Feng, S.M. Massachusetts Institute of Technology

    2009-01-01

    We consider the problem of recovering a low rank matrix given a sampling of its entries. Such problems are of considerable interest in a diverse set of fields including control, system identification, statistics and signal ...

  13. YEAR

    National Nuclear Security Administration (NNSA)

    4 YEAR 2012 Males 65 Females 29 YEAR 2012 SES 3 EJEK 5 EN 04 3 NN (Engineering) 21 NQ (ProfTechAdmin) 61 NU (TechAdmin Support) 1 YEAR 2012 American Indian Male 0 American...

  14. YEAR

    National Nuclear Security Administration (NNSA)

    4 YEAR 2011 Males 21 Females 23 YEAR 2011 SES 3 EJEK 1 EN 03 1 NN (Engineering) 3 NQ (ProfTechAdmin) 31 NU (TechAdmin Support) 5 YEAR 2011 American Indian Male 0 American...

  15. YEAR

    National Nuclear Security Administration (NNSA)

    92 YEAR 2012 Males 52 Females 40 YEAR 2012 SES 1 EJEK 7 EN 04 13 EN 03 1 NN (Engineering) 27 NQ (ProfTechAdmin) 38 NU (TechAdmin Support) 5 YEAR 2012 American Indian Male 0...

  16. YEAR

    National Nuclear Security Administration (NNSA)

    558 YEAR 2013 Males 512 Females 46 YEAR 2013 SES 2 EJEK 2 EN 04 1 NN (Engineering) 11 NQ (ProfTechAdmin) 220 NU (TechAdmin Support) 1 NV (Nuc Mat Courier) 321 YEAR 2013...

  17. YEAR

    National Nuclear Security Administration (NNSA)

    11 YEAR 2012 Males 78 Females 33 YEAR 2012 SES 2 EJEK 9 EN 05 1 EN 04 33 NN (Engineering) 32 NQ (ProfTechAdmin) 31 NU (TechAdmin Support) 3 YEAR 2012 American Indian Male 2...

  18. YEAR

    National Nuclear Security Administration (NNSA)

    300 YEAR 2011 Males 109 Females 191 YEAR 2011 SES 9 EJEK 1 NN (Engineering) 2 NQ (ProfTechAdmin) 203 NU (TechAdmin Support) 38 NF (Future Ldrs) 47 YEAR 2011 American Indian...

  19. YEAR

    National Nuclear Security Administration (NNSA)

    02 YEAR 2011 Males 48 Females 54 YEAR 2011 SES 5 EJEK 1 NN (Engineering) 13 NQ (ProfTechAdmin) 80 NU (TechAdmin Support) 3 YEAR 2011 American Indian Male 0 American Indian...

  20. YEAR

    National Nuclear Security Administration (NNSA)

    8 YEAR 2013 Males 27 Females 11 YEAR 2013 SES 1 EN 05 1 EN 04 11 NN (Engineering) 8 NQ (ProfTechAdmin) 15 NU (TechAdmin Support) 2 YEAR 2013 American Indian Alaska Native Male...

  1. YEAR

    National Nuclear Security Administration (NNSA)

    31 YEAR 2013 Males 20 Females 11 YEAR 2013 SES 2 EN 04 4 NN (Engineering) 12 NQ (ProfTechAdmin) 12 NU (TechAdmin Support) 1 YEAR 2013 American Indian Alaska Native Male (AIAN,...

  2. YEAR

    National Nuclear Security Administration (NNSA)

    16 YEAR 2012 Males 84 Females 32 YEAR 2012 SES 26 EJEK 2 EN 05 9 NN (Engineering) 39 NQ (ProfTechAdmin) 30 NU (TechAdmin Support) 10 YEAR 2012 American Indian Male 0 American...

  3. YEAR

    National Nuclear Security Administration (NNSA)

    34 YEAR 2012 Males 66 Females 68 YEAR 2012 SES 6 NN (Engineering) 15 NQ (ProfTechAdmin) 110 NU (TechAdmin Support) 3 YEAR 2012 American Indian Male 1 American Indian Female 2...

  4. YEAR

    National Nuclear Security Administration (NNSA)

    86 YEAR 2012 Males 103 Females 183 YEAR 2012 SES 7 EJEK 1 NN (Engineering) 1 NQ (ProfTechAdmin) 202 NU (TechAdmin Support) 30 NF (Future Ldrs) 45 YEAR 2012 American Indian Male...

  5. YEAR

    National Nuclear Security Administration (NNSA)

    80 YEAR 2012 Males 51 Females 29 YEAR 2012 SES 1 EJEK 22 EN 04 21 NN (Engineering) 14 NQ (ProfTechAdmin) 21 NU (TechAdmin Support) 1 YEAR 2012 American Indian Male 0 American...

  6. YEAR

    National Nuclear Security Administration (NNSA)

    1 YEAR 2012 Males 30 Females 11 YEAR 2012 SES 1 EN 05 1 EN 04 11 NN (Engineering) 9 NQ (ProfTechAdmin) 17 NU (TechAdmin Support) 2 YEAR 2012 American Indian Male 0 American...

  7. YEAR

    National Nuclear Security Administration (NNSA)

    96 YEAR 2013 Males 69 Females 27 YEAR 2013 SES 1 EJEK 9 EN 04 27 NN (Engineering) 26 NQ (ProfTechAdmin) 30 NU (TechAdmin Support) 3 YEAR 2013 American Indian Alaska Native Male...

  8. YEAR

    National Nuclear Security Administration (NNSA)

    31 YEAR 2012 Males 19 Females 12 YEAR 2012 SES 2 EN 04 4 NN (Engineering) 12 NQ (ProfTechAdmin) 12 NU (TechAdmin Support) 1 YEAR 2012 American Indian Male 0 American Indian...

  9. YEAR

    National Nuclear Security Administration (NNSA)

    0 YEAR 2013 Males 48 Females 32 YEAR 2013 SES 2 EJEK 7 EN 04 11 EN 03 1 NN (Engineering) 23 NQ (ProfTechAdmin) 33 NU (TechAdmin Support) 3 YEAR 2013 American Indian Alaska...

  10. YEAR

    National Nuclear Security Administration (NNSA)

    40 YEAR 2011 Males 68 Females 72 YEAR 2011 SES 5 EJEK 1 NN (Engineering) 16 NQ (ProfTechAdmin) 115 NU (TechAdmin Support) 3 YEAR 2011 American Indian Male 1 American Indian...

  11. YEAR

    National Nuclear Security Administration (NNSA)

    00 YEAR 2012 Males 48 Females 52 YEAR 2012 SES 5 EJEK 1 NN (Engineering) 11 NQ (ProfTechAdmin) 80 NU (TechAdmin Support) 3 YEAR 2012 American Indian Male 0 American Indian...

  12. YEAR

    National Nuclear Security Administration (NNSA)

    137 YEAR 2013 Males 90 Females 47 YEAR 2013 SES 2 SL 1 EJEK 30 EN 04 30 EN 03 2 NN (Engineering) 23 NQ (ProfTechAdmin) 45 NU (TechAdmin Support) 4 YEAR 2013 American Indian...

  13. YEAR

    National Nuclear Security Administration (NNSA)

    of Employees 14 GENDER YEAR 2012 Males 9 Females 5 YEAR 2012 SES 2 EJEK 2 NN (Engineering) 4 NQ (ProfTechAdmin) 6 YEAR 2012 American Indian Male 0 American Indian Female 0...

  14. YEAR

    National Nuclear Security Administration (NNSA)

    3 YEAR 2012 Males 21 Females 22 YEAR 2012 SES 3 EJEK 1 EN 03 1 NN (Engineering) 3 NQ (ProfTechAdmin) 30 NU (TechAdmin Support) 5 YEAR 2012 American Indian Male 0 American...

  15. YEAR

    National Nuclear Security Administration (NNSA)

    YEAR 2014 Males 48 Females 33 PAY PLAN YEAR 2014 SES 1 EJEK 8 EN 04 10 EN 03 1 NN (Engineering) 27 NQ (ProfTechAdmin) 29 NU (TechAdmin Support) 5 YEAR 2014 American Indian...

  16. YEAR

    National Nuclear Security Administration (NNSA)

    8 YEAR 2014 Males 18 Females 10 PAY PLAN YEAR 2014 SES 1 EN 05 1 EN 04 4 NN (Engineering) 12 NQ (ProfTechAdmin) 9 NU (TechAdmin Support) 1 YEAR 2014 American Indian Alaska...

  17. YEAR

    National Nuclear Security Administration (NNSA)

    5 YEAR 2014 Males 61 Females 24 PAY PLAN YEAR 2014 SES 1 EJEK 8 EN 04 22 NN (Engineering) 23 NQ (ProfTechAdmin) 28 NU (TechAdmin Support) 3 YEAR 2014 American Indian Alaska...

  18. YEAR

    National Nuclear Security Administration (NNSA)

    69 YEAR 2014 Males 34 Females 35 YEAR 2014 SES 5 EJEK 1 EN 05 8 EN 04 5 NN (Engineering) 27 NQ (ProfTechAdmin) 22 NU (TechAdmin Support) 1 YEAR 2014 American Indian Alaska...

  19. YEAR

    National Nuclear Security Administration (NNSA)

    42 YEAR 2014 Males 36 Females 6 PAY PLAN YEAR 2014 SES 2 EJEK 5 EN 05 7 EN 04 6 EN 03 1 NN (Engineering) 15 NQ (ProfTechAdmin) 6 YEAR 2014 American Indian Alaska Native Male...

  20. AS A MINING ENGINEER Mining provides the raw materials and energy resources needed to sustain modern civilization. Mining Engineers

    E-Print Network [OSTI]

    Capecchi, Mario R.

    AS A MINING ENGINEER Mining provides the raw materials and energy resources needed to sustain modern civilization. Mining Engineers are trained to determine the safest most sustainable way to remove, metals, and fuels each year, making mining an indispensable part of our daily life and world economy

  1. Nuclear Engineering Program Ranking

    E-Print Network [OSTI]

    Evans, Paul G.

    Nuclear Engineering Program Ranking 2 Enrollment Approximately 200 undergraduate students and 120 in Nuclear Engineering (BS) · Bachelor of Science in Engineering Physics (BS) · Master of Science in Nuclear Engineering and Engineering Physics (MS) · Doctor of Philosophy in Nuclear Engineering and Engineering Physics

  2. YEAR

    National Nuclear Security Administration (NNSA)

    Males 139 Females 88 YEAR 2012 SES 13 EX 1 EJEK 8 EN 05 23 EN 04 20 EN 03 2 NN (Engineering) 91 NQ (ProfTechAdmin) 62 NU (TechAdmin Support) 7 YEAR 2012 American Indian...

  3. YEAR

    National Nuclear Security Administration (NNSA)

    25 Females 10 YEAR 2014 SES 1 EN 04 11 NN (Engineering) 8 NQ (ProfTechAdmin) 13 NU (TechAdmin Support) 2 YEAR 2014 American Indian Alaska Native Male (AIAN M) 0 American Indian...

  4. YEAR

    National Nuclear Security Administration (NNSA)

    2014 Males 81 Females 45 PAY PLAN YEAR 2014 SES 1 SL 1 EJEK 25 EN 04 26 EN 03 2 NN (Engineering) 23 NQ (ProfTechAdmin) 44 NU (TechAdmin Support) 4 YEAR 2014 American Indian...

  5. YEAR

    National Nuclear Security Administration (NNSA)

    563 YEAR 2012 Males 518 Females 45 YEAR 2012 SES 1 EJEK 2 EN 04 1 EN 03 1 NN (Engineering) 12 NQ (ProfTechAdmin) 209 NU (TechAdmin Support) 2 NV (Nuc Mat Courier) 335 YEAR 2012...

  6. YEAR

    National Nuclear Security Administration (NNSA)

    7 YEAR 2012 Males 64 Females 33 YEAR 2012 SES 2 EJEK 3 EN 05 1 EN 04 30 EN 03 1 NN (Engineering) 26 NQ (ProfTechAdmin) 32 NU (TechAdmin Support) 2 YEAR 2012 American Indian...

  7. YEAR

    National Nuclear Security Administration (NNSA)

    4 YEAR 2012 Males 37 Females 7 YEAR 2012 SES 1 EJEK 6 EN 05 5 EN 04 7 EN 03 1 NN (Engineering) 17 NQ (ProfTechAdmin) 6 NU (TechAdmin Support) 1 YEAR 2012 American Indian Male 2...

  8. YEAR

    National Nuclear Security Administration (NNSA)

    7 YEAR 2011 Males 38 Females 9 YEAR 2011 SES 1 EJEK 6 EN 05 5 EN 04 7 EN 03 1 NN (Engineering) 19 NQ (ProfTechAdmin) 7 NU (TechAdmin Support) 1 YEAR 2011 American Indian Male 2...

  9. YEAR

    National Nuclear Security Administration (NNSA)

    8 YEAR 2013 Males 62 Females 26 YEAR 2013 SES 1 EJEK 3 EN 05 1 EN 04 28 EN 03 1 NN (Engineering) 25 NQ (ProfTechAdmin) 27 NU (TechAdmin Support) 2 YEAR 2013 American Indian...

  10. YEAR

    National Nuclear Security Administration (NNSA)

    6 YEAR 2012 Males 64 Females 32 YEAR 2012 SES 1 EJEK 5 EN 05 3 EN 04 23 EN 03 9 NN (Engineering) 18 NQ (ProfTechAdmin) 33 NU (TechAdmin Support) 4 YEAR 2012 American Indian...

  11. YEAR

    National Nuclear Security Administration (NNSA)

    5 YEAR 2013 Males 58 Females 27 YEAR 2013 SES 1 EJEK 4 EN 05 3 EN 04 21 EN 03 8 NN (Engineering) 16 NQ (ProfTechAdmin) 28 NU (TechAdmin Support) 4 YEAR 2013 American Indian...

  12. YEAR

    National Nuclear Security Administration (NNSA)

    78 YEAR 2012 Males 57 Females 21 YEAR 2012 SES 2 SL 1 EJEK 12 EN 04 21 EN 03 2 NN (Engineering) 12 NQ (ProfTechAdmin) 24 NU (TechAdmin Support) 4 YEAR 2012 American Indian Male...

  13. PRB mines mature

    SciTech Connect (OSTI)

    Buchsbaum, L.

    2007-08-15

    Already seeing the results of reclamation efforts, America's largest surface mines advance as engineers prepare for the future. 30 years after the signing of the Surface Mining Control and Reclamation Act by Jimmy Carter, western strip mines in the USA, especially in the Powder River Basin, are producing more coal than ever. The article describes the construction and installation of a $38.5 million near-pit crusher and overland belt conveyor system at Foundation Coal West's (FCW) Belle Ayr surface mine in Wyoming, one of the earliest PRB mines. It goes on to describe the development by Rio Tinto of an elk conservatory, the Rochelle Hill Conservation Easement, on reclaimed land at Jacobs Ranch, adjacent to the Rochelle Hills. 4 photos.

  14. YEAR

    National Nuclear Security Administration (NNSA)

    2012 Males 149 Females 115 YEAR 2012 SES 17 EX 1 EJEK 7 EN 05 2 EN 04 9 EN 03 2 NN (Engineering) 56 NQ (ProfTechAdmin) 165 NU (TechAdmin Support) 4 GS 13 1 YEAR 2012 American...

  15. YEAR

    National Nuclear Security Administration (NNSA)

    9 Females 24 PAY PLAN YEAR 2014 SES 1 EJEK 4 EN 05 3 EN 04 22 EN 03 8 NN (Engineering) 15 NQ (ProfTechAdmin) 27 NU (TechAdmin Support) 3 YEAR 2014 American Indian Alaska Native...

  16. YEAR

    National Nuclear Security Administration (NNSA)

    8 Females 25 PAY PLAN YEAR 2014 SES 1 EJEK 3 EN 05 1 EN 04 25 EN 03 1 NN (Engineering) 25 NQ (ProfTechAdmin) 25 NU (TechAdmin Support) 2 YEAR 2014 American Indian Alaska Native...

  17. Guide to journal rankings 1. What are journal rankings?

    E-Print Network [OSTI]

    McCusker, Guy

    Opus Guide to journal rankings 1. What are journal rankings? Journal rankings are metrics that provide information on how a journal performs in comparison with other journals in the same discipline. Articles in high impact journals are more likely to be cited. Good citation counts are often considered

  18. Department of MINING ENGINEERING

    E-Print Network [OSTI]

    Capecchi, Mario R.

    AS A MINING ENGINEER IMAGINE IMAGINE Department of MINING ENGINEERING THE UNIVERSITY OF UTAH www.mining

  19. Rank Equilibration and Political Behavior 

    E-Print Network [OSTI]

    Anderson, Bo; Zelditch, Morris Jr

    2015-07-14

    /plain; charset=UTF-8 RANK EQUILIBRATION AND POLITICAL BEHAVIOR by Bo Anderson and Morris Zelditch, Jr0 TR #9 Rank Equilibration end Political Behavior* 1« Introduction The terra ,,status politics" refers to a way of conceptualizing some aspects o...

  20. YEAR

    National Nuclear Security Administration (NNSA)

    -9.09% YEAR 2012 2013 SES 1 1 0.00% EN 05 1 1 0.00% EN 04 11 11 0.00% NN (Engineering) 8 8 0.00% NQ (ProfTechAdmin) 17 14 -17.65% NU (TechAdmin Support) 2 2...

  1. YEAR

    National Nuclear Security Administration (NNSA)

    Females 863 YEAR 2013 SES 102 EX 3 SL 1 EJEK 89 EN 05 41 EN 04 170 EN 03 18 NN (Engineering) 448 NQ (ProfTechAdmin) 1249 NU (TechAdmin Support) 76 NV (Nuc Mat Courier) 321...

  2. YEAR

    National Nuclear Security Administration (NNSA)

    Females 942 YEAR 2012 SES 108 EX 4 SL 1 EJEK 96 EN 05 45 EN 04 196 EN 03 20 NN (Engineering) 452 NQ (ProfTechAdmin) 1291 NU (TechAdmin Support) 106 NV (Nuc Mat Courier) 335...

  3. YEAR

    National Nuclear Security Administration (NNSA)

    YEAR 2012 2013 SES 2 1 -50.00% EN 05 0 1 100.00% EN 04 4 4 0.00% NN (Engineering) 13 12 -7.69% NQ (ProfTechAdmin) 13 9 -30.77% NU (TechAdmin Support) 1 1...

  4. Data Mining 4.6. " "

    E-Print Network [OSTI]

    Borissova, Daniela

    1 . . Data Mining "" 4.6. " " ( 01.01.12. "") . . .. 2012. .- - - , , .". . ", .2. : : Data Mining #12;3 (Data Mining) - 20-25 . , , , , , . , (Data Mining) , , , , . Data Mining . Data Mining

  5. Data Mining Students' Ordinary Handwritten Coursework

    E-Print Network [OSTI]

    Herold, James

    2013-01-01

    Data Mining . . . . . . . . . . . . . . . . . . . . . . .Mining . . . . . . . . . . . . . . . . . . . . . . . . .Sequence Mining 6.1 Introduction . . . . . . . . .

  6. Rank Project Name Directorate, Dept/Div

    E-Print Network [OSTI]

    gallons industrial waste 7 Oil-free Vacuum Pumps and new Catalyst EENS, Environmental Sciences Dept. (L. Nunnermacker) $6,000 $3,516 1.7 50 pounds of hazardous waste 8 Bulk Motor Oil F&A, Staff Services (H. HauptmanRank Project Name Directorate, Dept/Div and POC Cost Savings Payback (Years) Waste Reduction 1

  7. Rank Project Name Directorate, Dept/Div

    E-Print Network [OSTI]

    Electronic Recycling Procurement & Property Management (John Collins) $3,500 TBD N/A 10 tons of e-waste 7 Oil,000 $830.00 7.23 6 liters of industrial waste 8 Disposal of #6 Fuel Oil * EENS (Yousif Celebi $500 $4Rank Project Name Directorate, Dept/Div and POC Cost Savings Payback (Years) Waste Reduction 1

  8. YEAR

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia4)9 Federal RegisterStorm1 3 6370-Rev.National26 YEAR

  9. YEAR

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia4)9 Federal RegisterStorm1 3 6370-Rev.National26 YEAR93

  10. YEAR

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia4)9 Federal RegisterStorm1 3 6370-Rev.National26 YEAR93

  11. YEAR

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia4)9 Federal RegisterStorm1 3 6370-Rev.National26 YEAR9374

  12. YEAR

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia4)9 Federal RegisterStorm1 3 6370-Rev.National268 YEAR

  13. YEAR

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia4)9 Federal RegisterStorm1 3 6370-Rev.National268 YEAR17

  14. YEAR

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia4)9 Federal RegisterStorm1 3 6370-Rev.National268255 YEAR

  15. YEAR

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia4)9 Federal RegisterStorm1 3446 YEAR 2014 Males 1626

  16. YEAR

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia4)9 Federal RegisterStorm1 3446 YEAR 2014 Males 16268

  17. YEAR

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia4)9 Federal RegisterStorm1 3446 YEAR 2014 Males 16268563

  18. YEAR

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia4)9 Federal RegisterStorm1 3446 YEAR 2014 Males 162685638

  19. YEAR

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal GasAdministration Medal01 Sandia4)9 Federal RegisterStorm1 3446 YEAR 2014 Males

  20. The Department of Industrial and Systems Engineering is accepting applications for open rank non-tenure track faculty positions for academic year 2014-2015. All positions require teaching undergraduate and/or

    E-Print Network [OSTI]

    The Department of Industrial and Systems Engineering is accepting applications for open rank non/or graduate courses related to Industrial and Systems Engineering, and service to the department. A successful of Industrial and Systems Engineering provides competitive compensation packages and benefits. To apply, please

  1. Ranking nodes in growing networks: When PageRank fails

    E-Print Network [OSTI]

    Mariani, Manuel Sebastian; Zhang, Yi-Cheng

    2015-01-01

    PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm's efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank's performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

  2. ITP Mining: Exploration and Mining Technology Roadmap

    Broader source: Energy.gov [DOE]

    This document describes the Mining Industry of the Future's development of technology roadmaps to guide collaborative research activities for mining.

  3. Low-rank coal research

    SciTech Connect (OSTI)

    Weber, G. F.; Laudal, D. L.

    1989-01-01

    This work is a compilation of reports on ongoing research at the University of North Dakota. Topics include: Control Technology and Coal Preparation Research (SO{sub x}/NO{sub x} control, waste management), Advanced Research and Technology Development (turbine combustion phenomena, combustion inorganic transformation, coal/char reactivity, liquefaction reactivity of low-rank coals, gasification ash and slag characterization, fine particulate emissions), Combustion Research (fluidized bed combustion, beneficiation of low-rank coals, combustion characterization of low-rank coal fuels, diesel utilization of low-rank coals), Liquefaction Research (low-rank coal direct liquefaction), and Gasification Research (hydrogen production from low-rank coals, advanced wastewater treatment, mild gasification, color and residual COD removal from Synfuel wastewaters, Great Plains Gasification Plant, gasifier optimization).

  4. Mining Sequential Patterns from Temporal Streaming Data

    E-Print Network [OSTI]

    Malerba, Donato

    Mining Sequential Patterns from Temporal Streaming Data A. Marascu and F. Masseglia INRIA Sophia.Marascu,Florent.Masseglia}@sophia.inria.fr Abstract. In recent years, emerging applications introduced new con- straints for data mining methods of our knowledge, no method has been proposed for mining sequential patterns in data streams. We argue

  5. African mining

    SciTech Connect (OSTI)

    Not Available

    1987-01-01

    This book contains papers presented at a conference addressing the development of the minerals industry in Africa. Topics covered include: A review - past, present and future - of Zimbabwe's mining industry; Geomorphological processes and related mineralization in Tanzania; and Rock mechanics investigations at Mufulira mine, Zambia.

  6. Quarrying and Mining (Stone)

    E-Print Network [OSTI]

    Bloxam, Elizabeth

    2010-01-01

    the author.   Quarrying and Mining (Stone), Bloxam, UEE 2010archaeology and anthropology of mining. In Social approachesand anthropology of mining, ed. Bernard Knapp, Vincent

  7. August 2011 Bachelor of Civil Engineering/Bachelor of Mining Engineering 3146

    E-Print Network [OSTI]

    New South Wales, University of

    August 2011 Bachelor of Civil Engineering/Bachelor of Mining Engineering 3146 Year 1 Year 2 Year 3 Year 4 Year 5 Semester 1 ENGG1000 Engineering Design and Innovation CVEN2301 Mechanics for Solids CVEN3201 Applied Geotechnics and Engineering Geology MINE3220 Resource Estimation and Evaluation MINE4250

  8. Toward mining of spatiotemporal maximal frequent patterns

    E-Print Network [OSTI]

    Malerba, Donato

    show that propositional spatiotemporal logic PSTL is a powerful tool for mining in various and temporal features and show that the spa- tiotemporal logic ST0 is powerful enough for mining interesting in future), windstorms data where K is a unique identifier for a strong wind, and the frequent pattern year

  9. LEARNING OUTCOMES EVALUATION Mining Engineering

    E-Print Network [OSTI]

    Missouri-Rolla, University of

    geomechanics, geometrics and computer-aided mine design, and optimization of flow processes for designing mine

  10. ANU MLSS 2010: Data Mining

    E-Print Network [OSTI]

    McCreath, Eric Charles

    ANU MLSS 2010: Data Mining Part 1: Introduction, data mining challenges, and data issues for data mining Data Mining module outline Part 1: Very short introduction to data mining Data mining process Challenges in data mining Data cleaning, integration and pre-processing Part 2: Association rule mining Part

  11. Toward Knowledge-Rich Data Mining Pedro Domingos

    E-Print Network [OSTI]

    Domingos, Pedro

    Toward Knowledge-Rich Data Mining Pedro Domingos Department of Computer Science and Engineering University of Washington Seattle, WA 98195 pedrod@cs.washington.edu 1 The Knowledge Gap Data mining has made tremendous progress in the last ten years. However, a large gap remains between the results a data mining

  12. Data Mining Students' Ordinary Handwritten Coursework

    E-Print Network [OSTI]

    Herold, James

    2013-01-01

    Data Mining . . . . . . . . . . . . . . . . . . . . . . .Data Mining . . . . . . . . . . . . . . . . . . . . . . . . .In this work we apply data mining and machine learning

  13. POLYTOPES OF MINIMUM POSITIVE SEMIDEFINITE RANK 1 ...

    E-Print Network [OSTI]

    2012-05-23

    M ? rank M. In Exam- ple 2.3 we saw that the first inequality may be strict. We now ..... Let Si denote the ith row of SP . Since rank SP = n+ 1, we have ? n+2.

  14. of Mining & Engineering

    E-Print Network [OSTI]

    Wong, Pak Kin

    & Illness in Mining (3 units) MNE 527 Geomechanics (4 units) MNE 547 Underground Construction Geomechanics

  15. Low rank approximations of matrices and tensors

    E-Print Network [OSTI]

    Friedland, Shmuel

    Low rank approximations of matrices and tensors S. Friedland, V. Mehrmann, A. Miedlar and M, 2008 S. Friedland, V. Mehrmann, A. Miedlar and M. Nkengla Low rank approximations of matrices and tensors #12;Overview S. Friedland, V. Mehrmann, A. Miedlar and M. Nkengla Low rank approximations

  16. ITP Mining: Mining Industry Roadmap for Crosscutting Technologies...

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

    Roadmap for Crosscutting Technologies ITP Mining: Mining Industry Roadmap for Crosscutting Technologies ccroadmap.pdf More Documents & Publications ITP Mining: Exploration and...

  17. Mine roof geology information system

    SciTech Connect (OSTI)

    Peng, S.S.; Sasaoka, T.; Tang, D.X.; Wilson, Y.; Wilson, G.

    2005-05-01

    A project sponsored by the US Department of Energy under the Industry of Future (Mining) program was initiated five years ago. In this project a patented drill control unit (DCU) installed DIN. the J.H. Flecher & Co.'s roof bolter was used to record the drilling parameter for experiments conducted in the mines and laboratory. Today, the drilling parameters have been recorded for more than 1,000 roof bolt holes. This article summarizes the results to date including the methods for determining quantitatively the location of voids/fractures and estimation of roof rock strength from the recorded roof bolter drilling parameters. 8 figs., 2 tabs.

  18. Graph Mining Meets the Semantic Web

    SciTech Connect (OSTI)

    Lee, Sangkeun (Matt) [ORNL; Sukumar, Sreenivas R [ORNL; Lim, Seung-Hwan [ORNL

    2015-01-01

    The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today, data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. We address that need through implementation of three popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, and PageRank). We implement these algorithms as SPARQL queries, wrapped within Python scripts. We evaluate the performance of our implementation on 6 real world data sets and show graph mining algorithms (that have a linear-algebra formulation) can indeed be unleashed on data represented as RDF graphs using the SPARQL query interface.

  19. Transportation costs for new fuel forms produced from low rank US coals

    SciTech Connect (OSTI)

    Newcombe, R.J.; McKelvey, D.G. ); Ruether, J.A. )

    1990-09-01

    Transportation costs are examined for four types of new fuel forms (solid, syncrude, methanol, and slurry) produced from low rank coals found in the lower 48 states of the USA. Nine low rank coal deposits are considered as possible feedstocks for mine mouth processing plants. Transportation modes analyzed include ship/barge, pipelines, rail, and truck. The largest potential market for the new fuel forms is coal-fired utility boilers without emission controls. Lowest cost routes from each of the nine source regions to supply this market are determined. 12 figs.

  20. On the Balance of a Set of Ranks 

    E-Print Network [OSTI]

    Zelditch, Morris Jr; Anderson, Bo

    2015-07-13

    the balance o f a s e t o f ranks. A theory o f rank balance i s concerned w ith s itu a t io n s in which a c to r s , s ta tu s e s , or c o l le c t iv e s are ranked in se v e r a l d if fe r e n t ways which can be regarded as in c o n... s is t e n t ? Some examples are: the Negro p r o fe s s io n a l, the w ealthy Jew, the im poverished Boston Brahmin, the $5,000 a year Harvard Ph»D. I t i s w id ely supposed th at d iscrep a n c ies o f th is kind are a source o f s t r a...

  1. On Boolean matrices with full factor rank

    SciTech Connect (OSTI)

    Shitov, Ya

    2013-11-30

    It is demonstrated that every (0,1)-matrix of size n×m having Boolean rank n contains a column with at least ?n/2?1 zero entries. This bound is shown to be asymptotically optimal. As a corollary, it is established that the size of a full-rank Boolean matrix is bounded from above by a function of its tropical and determinantal ranks. Bibliography: 16 titles.

  2. Personalized PageRank Solution Paths

    E-Print Network [OSTI]

    2015-04-13

    gorithms to estimate the solution path as a function of the sparsity and propose .... see shortly, we actually are describing degree normalized. PageRank values.

  3. Imaging Ahead of Mining

    Office of Energy Efficiency and Renewable Energy (EERE)

    Coal mining is becoming more difficult as machines must extract the coal from deeper, thinner, and more geologically complex coal beds. This type of mining also includes the need to reduce risk and...

  4. of Mining & Engineering

    E-Print Network [OSTI]

    Wong, Pak Kin

    .621.8330 Engr-mining@email.arizona.edu ONLINE GRADUATE CERTIFICATE PROGRAM 15 UNITS YOUR CAREER GEOMECHANICS #12;GEOMECHANICS Department of Mining & Geological Engineering www.mge.arizona.edu Contact the MGE Department for more information: ENGR-mining@email.arizona.edu REQUIRED COURSES (12 units) MNE 527 Geomechanics (3

  5. Data Warehousing and Data Mining Conference, January 25, 1999, Singapore Data Mining:Data Mining

    E-Print Network [OSTI]

    Wu, Xindong

    Data Warehousing and Data Mining Conference, January 25, 1999, Singapore 1 Welcome Data Mining:Data Mining: Updates in TechnologiesUpdates in Technologies Xindong Wu Dept of Math and Computer Science Colorado School of Mines Golden, Colorado 80401, USA Email: xwu@ mines.edu Home Page: http://kais.mines

  6. The generating rank of the symplectic grassmannians

    E-Print Network [OSTI]

    Blok, Rieuwert J.

    The generating rank of the symplectic grassmannians: hyperbolic and isotropic geometry Rieuwert J.S.A. blokr@member.ams.org Accepted: March 7 2006 Key Words: symplectic geometry, grassmannian, generating to the symplectic group Sp2n(F) has generating rank 2n k - 2n k-2 when Char(F) = 2. #12;1 Introduction Generating

  7. The MultiRank Bootstrap Algorithm: Semi-Supervised Political Blog Classification and Ranking Using Semi-

    E-Print Network [OSTI]

    Cohen, William W.

    The MultiRank Bootstrap Algorithm: Semi-Supervised Political Blog Classification and Ranking Using: Semi-Supervised Political Blog Classification and Ranking Using Semi-Supervised Link Classification present a new, intuitive semi-supervised learning algo- rithm for classifying political blogs in a blog

  8. Post-Mining 2005, November 16-17, Nancy, France 1 LARGE SCALE APPLICATIONS OF COVERS WITH CAPILLARY BARRIER EFFECTS

    E-Print Network [OSTI]

    Aubertin, Michel

    BARRIER EFFECTS TO CONTROL THE PRODUCTION OF ACID MINE DRAINAGE DAGENAIS Anne-Marie1 , AUBERTIN Michel2 used in recent years as part of the closure plan for mines having an acid mine drainage (AMD) problem migration in the case of more humid climatic conditions. KEYWORDS: Covers, Acid mine drainage, Monitoring

  9. Rank Quantization Mountain View, CA, USA

    E-Print Network [OSTI]

    Singh, Jaswinder Pal

    Rank Quantization Ravi Kumar Google Mountain View, CA, USA ravi.k53@gmail.com Ronny Lempel Yahoo and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post

  10. Low-rank coal oil agglomeration

    DOE Patents [OSTI]

    Knudson, Curtis L. (Grand Forks, ND); Timpe, Ronald C. (Grand Forks, ND)

    1991-01-01

    A low-rank coal oil agglomeration process. High mineral content, a high ash content subbituminous coals are effectively agglomerated with a bridging oil which is partially water soluble and capable of entering the pore structure, and usually coal derived.

  11. Data Mining and Knowledge Discovery

    E-Print Network [OSTI]

    Novak, Petra Kralj

    Data Mining and Knowledge Discovery Part of Jozef Stefan IPS Programme - ICT3 and UL Programme. Introduction Data Mining in a Nutshell Predictive and descriptive DM techniques Data Mining and KDD process Technologies I. Introduction: First generation data mining Data Mining in a nutshell Predictive

  12. Top for economics Rank Business School

    E-Print Network [OSTI]

    Lin, Xiaodong

    Top for economics Rank Business School 1 University of Chicago: Booth Rutgers Business School of Strathclyde Business School University of Pretoria, Gibs IMD 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Top/WHU Beisheim Tsinghua University/Insead Top for international business Rank Business School 1 2 3 4 5 6 7 8 9

  13. Presidential Rank Awards Announced | 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 RankADVANCED MANUFACTURINGEnergy Bills andOrderNATIONAL CHAIRSEnergyPresidential Rank Awards Announced

  14. ITP Mining: Education Roadmap for Mining Professionals (December 2002)

    Broader source: Energy.gov [DOE]

    A profitable and stable mining industry is vital to U.S. economic and national security. This roadmap serves to educate those professionals in the mining industry.

  15. ITP Mining: Mining Industry of the Future Mineral Processing...

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

    of the Future Mineral Processing Technology Roadmap ITP Mining: Mining Industry of the Future Mineral Processing Technology Roadmap mptroadmap.pdf More Documents & Publications ITP...

  16. Data Mining Tools Irfan Altas

    E-Print Network [OSTI]

    Turlach, Berwin A.

    Data Mining Tools Irfan Altas School of Information Studies, Charles Sturt University Wagga Wagga discuss several scalable and parallel discovery and predictive data mining tools. They successfully Data mining tools, thin plate splines, BMARS, revolver, regression, smoothing, addi­ tive models

  17. Groundwater contaminant plume ranking. [UMTRA Project

    SciTech Connect (OSTI)

    Not Available

    1988-08-01

    Containment plumes at Uranium Mill Tailings Remedial Action (UMTRA) Project sites were ranked to assist in Subpart B (i.e., restoration requirements of 40 CFR Part 192) compliance strategies for each site, to prioritize aquifer restoration, and to budget future requests and allocations. The rankings roughly estimate hazards to the environment and human health, and thus assist in determining for which sites cleanup, if appropriate, will provide the greatest benefits for funds available. The rankings are based on the scores that were obtained using the US Department of Energy's (DOE) Modified Hazard Ranking System (MHRS). The MHRS and HRS consider and score three hazard modes for a site: migration, fire and explosion, and direct contact. The migration hazard mode score reflects the potential for harm to humans or the environment from migration of a hazardous substance off a site by groundwater, surface water, and air; it is a composite of separate scores for each of these routes. For ranking the containment plumes at UMTRA Project sites, it was assumed that each site had been remediated in compliance with the EPA standards and that relict contaminant plumes were present. Therefore, only the groundwater route was scored, and the surface water and air routes were not considered. Section 2.0 of this document describes the assumptions and procedures used to score the groundwater route, and Section 3.0 provides the resulting scores for each site. 40 tabs.

  18. Particulate control for low rank coals

    SciTech Connect (OSTI)

    Touzel, R.McD.

    1993-12-31

    The power generating system in Victoria currently comprises a total capacity of 6650 MW. Eighty percent of this capacity consists of base load stations in the Latrobe Valley using brown coal. The Latrobe Valley brown coals have unique characteristics with high moisture content ranging from 58 percent to 70 percent and an ash content which is relatively low but very variable in nature. These and other factors associated with the coal have caused special problems in handling and combustion of the coal and the de-dusting of the boiler flue gases. In recent years, this has been the basis for the design parameters adopted for all the plants in the system. With respect to flue gas de-dusting, the SECV has carried out extensive laboratory studies to characterize the different ashes obtained from the Latrobe Valley brown coals, including precipitability and aerodynamic tests. It also carried out full-scale tests on operating plants and pilot tests have been conducted on inertial collectors, precipitators and bag filters. The Environmental Protection Authority of Victoria has established a particulate emission level of 0.150 grams/m{sup 3} n.t.p. dry for recent Latrobe Valley boilers. However, the mandated emission level takes into account wide variations in operating conditions, and the plants normally achieve much lower emission levels. The Latrobe Valley plants presently in operation include Yallourn W (2x350 MW + 2x375 MW), Morwell (170 MW total and briquette factory), Hazelwood (8x200 MW) and Loy Yang (4x500 MW). The Yalloum W boilers are supplied with coal from the Yalloum Open Cut, the Morwell and Hazelwood boilers from the Morwell Open Cut and Loy Yang boilers from the Loy Yang Open Cut. All boilers are pulverized coal fired (PCF) and incorporate special firing equipment to enable the as-mined wet coal to be fired directly into the furnaces. All boilers are fitted with electrostatic precipitators. The locations of the stations and open cuts are shown.

  19. Low-Rank Regularization for Learning Gene Expression Programs

    E-Print Network [OSTI]

    Ye, Guibo; Tang, Mengfan; Cai, Jian-Feng; Nie, Qing; Xie, Xiaohui; Muldoon, Mark R

    2013-01-01

    8 | Issue 12 | e82146 Low-Rank for Learning Gene ExpressionWe will call (3) the linear low-rank model in the following.so is its square root K 2 . Low-rank regularized nonlinear

  20. Rank-finiteness for modular categories

    E-Print Network [OSTI]

    Paul Bruillard; Siu-Hung Ng; Eric C. Rowell; Zhenghan Wang

    2015-05-27

    We prove a rank-finiteness conjecture for modular categories: up to equivalence, there are only finitely many modular categories of any fixed rank. Our technical advance is a generalization of the Cauchy theorem in group theory to the context of spherical fusion categories. For a modular category $\\mathcal{C}$ with $N=ord(T)$, the order of the modular $T$-matrix, the Cauchy theorem says that the set of primes dividing the global quantum dimension $D^2$ in the Dedekind domain $\\mathbb{Z}[e^{\\frac{2\\pi i}{N}}]$ is identical to that of $N$.

  1. Mining Views: Database Views for Data Mining Hendrik Blockeel #1

    E-Print Network [OSTI]

    Antwerpen, Universiteit

    Mining Views: Database Views for Data Mining Hendrik Blockeel #1 , Toon Calders 2 , Elisa Fromont adriana.prado}@ua.ac.be Abstract-- We present a system towards the integration of data mining mining views. We show that several types of patterns and models over the data, such as itemsets

  2. Frequent Set Meta Mining: Towards Multi-Agent Data Mining

    E-Print Network [OSTI]

    Coenen, Frans

    Frequent Set Meta Mining: Towards Multi-Agent Data Mining Kamal Ali Albashiri, Frans Coenen, Rob. The typical scenario where this is desirable is in multi-agent data mining where individual agents wish to preserve the security and privacy of their raw data but are prepared to share data mining results. Four

  3. Efficient Mining of Indirect Associations Using HI-Mine

    E-Print Network [OSTI]

    An, Aijun

    Efficient Mining of Indirect Associations Using HI-Mine Qian Wan and Aijun An Department. Discovering association rules is one of the important tasks in data mining. While most of the existing algorithms are developed for efficient mining of frequent patterns, it has been noted recently that some

  4. Mining Views: Database Views for Data Mining Hendrik Blockeel1

    E-Print Network [OSTI]

    Antwerpen, Universiteit

    Mining Views: Database Views for Data Mining Hendrik Blockeel1 , Toon Calders2 , Elisa Fromont1 model towards the inte- gration of data mining into relational database systems, based on the so called virtual mining views. We show that several types of patterns and models over the data, such as itemsets

  5. GROUND TRUTH WITH MINE COOPERATION Minnesota Taconite Mines

    E-Print Network [OSTI]

    Stump, Brian W.

    arrangement has been developed with a large taconite mine in the Mesabi Iron Range of Minnesota. Explosives are used to fracture relatively hard rock formations in order to facilitate the recovery of iron. The mine on understanding regional signals from hard rock mining practices. Mining operations in the Mesabi Iron Range

  6. Ranking websites through prioritized web accessibility barriers

    E-Print Network [OSTI]

    Brajnik, Giorgio

    of these comments apply as well to the current WCAG 2.0 draft, to Section 508 and to the Italian official technical criteria in WCAG 2.0), or when they do it (like priority levels in WCAG 1.0) they do not depend on specificRanking websites through prioritized web accessibility barriers Giorgio Brajnik Dip. di Matematica

  7. Low-rank coal oil agglomeration

    DOE Patents [OSTI]

    Knudson, C.L.; Timpe, R.C.

    1991-07-16

    A low-rank coal oil agglomeration process is described. High mineral content, a high ash content subbituminous coals are effectively agglomerated with a bridging oil which is partially water soluble and capable of entering the pore structure, and is usually coal-derived.

  8. Atomic Representations of Rank 2 Graph Algebras

    E-Print Network [OSTI]

    Davidson, Ken

    Atomic Representations of Rank 2 Graph Algebras Kenneth R. Davidson a , Stephen C. Power b , Dilian University, Lancaster LA1 4YF, U.K. Abstract We provide a detailed analysis of atomic -representations- posed into a direct sum or direct integral of irreducible atomic representations. The building blocks

  9. Link Analysis Ranking Algorithms, Theory, and Experiments #

    E-Print Network [OSTI]

    Rosenthal, Jeffrey S.

    and the widespread accessibility of the Web has led to surge of research activity in the area of information retrieval on the World Wide Web. The seminal papers of Kleinberg [31], and Brin and Page [9] introduced Link Analysis Ranking, where hyperlink structures are used to determine the relative authority of a Web page

  10. Carbon Sequestration on Surface Mine Lands

    SciTech Connect (OSTI)

    Donald Graves; Christopher Barton; Richard Sweigard; Richard Warner; Carmen Agouridis

    2006-03-31

    Since the implementation of the federal Surface Mining Control and Reclamation Act of 1977 (SMCRA) in May of 1978, many opportunities have been lost for the reforestation of surface mines in the eastern United States. Research has shown that excessive compaction of spoil material in the backfilling and grading process is the biggest impediment to the establishment of productive forests as a post-mining land use (Ashby, 1998, Burger et al., 1994, Graves et al., 2000). Stability of mine sites was a prominent concern among regulators and mine operators in the years immediately following the implementation of SMCRA. These concerns resulted in the highly compacted, flatly graded, and consequently unproductive spoils of the early post-SMCRA era. However, there is nothing in the regulations that requires mine sites to be overly compacted as long as stability is achieved. It has been cultural barriers and not regulatory barriers that have contributed to the failure of reforestation efforts under the federal law over the past 27 years. Efforts to change the perception that the federal law and regulations impede effective reforestation techniques and interfere with bond release must be implemented. Demonstration of techniques that lead to the successful reforestation of surface mines is one such method that can be used to change perceptions and protect the forest ecosystems that were indigenous to these areas prior to mining. The University of Kentucky initiated a large-scale reforestation effort to address regulatory and cultural impediments to forest reclamation in 2003. During the three years of this project 383,000 trees were planted on over 556 acres in different physiographic areas of Kentucky (Table 1, Figure 1). Species used for the project were similar to those that existed on the sites before mining was initiated (Table 2). A monitoring program was undertaken to evaluate growth and survival of the planted species as a function of spoil characteristics and reclamation practice. In addition, experiments were integrated within the reforestation effort to address specific questions pertaining to sequestration of carbon (C) on these sites.

  11. Solar for Mining Hugh Rudnick

    E-Print Network [OSTI]

    Catholic University of Chile (Universidad Católica de Chile)

    Solar for Mining Hugh Rudnick Professor Pontificia Universidad Católica de Chile #12;Solar Energy in Mining · Solar energy is becoming affordable · Attractive potential use for mining purposes · Must solve the storage requirement to increase its participation worldwide #12;Solar Energy in Mining · Electrical Energy

  12. Indonesian coal mining

    SciTech Connect (OSTI)

    NONE

    2008-11-15

    The article examines the opportunities and challenges facing the Indonesian coal mining industry and how the coal producers, government and wider Indonesian society are working to overcome them. 2 figs., 1 tab.

  13. Algorithms for data mining

    E-Print Network [OSTI]

    Wang, Grant J. (Grant Jenhorn), 1979-

    2006-01-01

    Data of massive size are now available in a wide variety of fields and come with great promise. In theory, these massive data sets allow data mining and exploration on a scale previously unimaginable. However, in practice, ...

  14. Efficient Algorithms for High Dimensional Data Mining

    E-Print Network [OSTI]

    Rakthanmanon, Thanawin

    2012-01-01

    demonstration. Data Mining and Knowledge. Discovery 7, 4,Demonstration,” Data Mining and Knowledge Discovery, vol. 7,and S. Burschka. 2011. Data mining for hackers – encrypted

  15. Data Mining Historical Manuscripts and Culture Artifacts

    E-Print Network [OSTI]

    Zhu, Qiang

    2011-01-01

    information retrieval and data mining have had large impactsinformation retrieval and data mining. In the meanwhile, dueinformation retrieval and data mining have had a large

  16. Mining Test Cases To Improve Software Maintenance

    E-Print Network [OSTI]

    Ziftci, Celal

    Chapter 6 Automatically Mining Requirements Relationships6.4 R EQ R EL E X : Mining Requirements Relationships fromTest Cases . . . . 6.4.1 Mining Requirements

  17. Internet Usage Mining Using Random Forests

    E-Print Network [OSTI]

    Liu, Xuening

    2013-01-01

    Los Angeles Internet Usage Mining Using Random Forests Aof the Thesis Internet Usage Mining Using Random Forests bydata emerges, data mining is finally in the spotlight. This

  18. DTC DATA MINING CONSORTIUM MEMBERSHIP BENEFITS

    E-Print Network [OSTI]

    Minnesota, University of

    DTC DATA MINING CONSORTIUM MEMBERSHIP BENEFITS I Collaboration with leading companies I Creation Analysis Optimization Scalable Database Mining Auto-Mining Agents CUTTING-EDGE CAPABILITIES

  19. Higher rank stable pairs and virtual localization

    E-Print Network [OSTI]

    Artan Sheshmani

    2015-02-08

    We introduce a higher rank analog of the Pandharipande-Thomas theory of stable pairs on a Calabi-Yau threefold $X$. More precisely, we develop a moduli theory for frozen triples given by the data $O^r(-n)\\rightarrow F$ where $F$ is a sheaf of pure dimension 1. The moduli space of such objects does not naturally determine an enumerative theory: that is, it does not naturally possess a perfect symmetric obstruction theory. Instead, we build a zero-dimensional virtual fundamental class by hand, by truncating a deformation-obstruction theory coming from the moduli of objects in the derived category of $X$. This yields the first deformation-theoretic construction of a higher-rank enumerative theory for Calabi-Yau threefolds. We calculate this enumerative theory for local $\\mathbb{P}^1$ using the Graber-Pandharipande virtual localization technique.

  20. Rankbox: An Adaptive Ranking System for Mining Complex Semantic Relationships Using User Feedback

    E-Print Network [OSTI]

    Hwang, Kai

    project, Cen- ter for Interactive Smart Oilfield Technologies (CiSoft), at the University of Southern

  1. Mines and Quarries: The Coal Mines (Firedamp Drainage) Regulations, 1960 

    E-Print Network [OSTI]

    Wood, Richard

    1960-01-01

    These regulations, which are made by the Minister of Power under section 141 of the Mines and Quarries Act, 1954, apply to the collecting of firedamp in coal mines before it has been diluted by any ventilation therein and ...

  2. US uranium mining industry: background information on economics and emissions

    SciTech Connect (OSTI)

    Bruno, G.A.; Dirks, J.A.; Jackson, P.O.; Young, J.K.

    1984-03-01

    A review of the US uranium mining industry has revealed a generally depressed industry situation. The 1982 U/sub 3/O/sub 8/ production from both open-pit and underground mines declined to 3800 and 6300 tons respectively with the underground portion representing 46% of total production. US exploration and development has continued downward in 1982. Employment in the mining and milling sectors has dropped 31% and 17% respectively in 1982. Representative forecasts were developed for reactor fuel demand and U/sub 3/O/sub 8/ production for the years 1983 and 1990. Reactor fuel demand is estimated to increase from 15,900 tons to 21,300 tons U/sub 3/O/sub 8/ respectively. U/sub 3/O/sub 8/ production, however, is estimated to decrease from 10,600 tons to 9600 tons respectively. A field examination was conducted of 29 selected underground uranium mines that represent 84% of the 1982 underground production. Data was gathered regarding population, land ownership and private property valuation. An analysis of the increased cost to production resulting from the installation of 20-meter high exhaust borehole vent stacks was conducted. An assessment was made of the current and future /sup 222/Rn emission levels for a group of 27 uranium mines. It is shown that /sup 222/Rn emission rates are increasing from 10 individual operating mines through 1990 by 1.2 to 3.8 times. But for the group of 27 mines as a whole, a reduction of total /sup 222/Rn emissions is predicted due to 17 of the mines being shutdown and sealed. The estimated total /sup 222/Rn emission rate for this group of mines will be 105 Ci/yr by year end 1983 or 70% of the 1978-79 measured rate and 124 Ci/yr by year end 1990 or 83% of the 1978-79 measured rate.

  3. Generic Pattern Mining via Data Mining Template Library

    E-Print Network [OSTI]

    Zaki, Mohammed Javeed

    - rithms for classification, and Weka [20], which is a general purpose Java library of different dataGeneric Pattern Mining via Data Mining Template Library Mohammed J. Zaki, Nilanjana De, Feng Gao. In this paper we propose the Data Mining Template Library, a collec- tion of generic containers and algorithms

  4. National Mining Association Experimental Determination

    E-Print Network [OSTI]

    National Mining Association Experimental Determination of Radon Fluxes over Water #12;Introduction research funded by the National Mining Association (NMA) regarding radon fluxes from water surfaces surfaces at uranium recovery operations are insignificant and approximate background soil fluxes for most

  5. Abstract--Data mining aims at extraction of previously unidentified information from large databases. It can be

    E-Print Network [OSTI]

    Fong, Chi Chiu "Simon"

    1 Abstract-- Data mining aims at extraction of previously unidentified information from large the last few years. Several works in the past emphasized the integration of OLAP and data mining. More recently, data mining techniques along with OLAP have been applied in decision support applications

  6. 0018-9162/99/$10.00 1999 IEEE2 Computer lthough there have been many data-mining

    E-Print Network [OSTI]

    Han, Jiawei

    0018-9162/99/$10.00 © 1999 IEEE2 Computer A lthough there have been many data-mining methodologies and systems developed in recent years, we contend that by and large, present mining models lack human involve- ment, particularly in the form of guidance and user control. We believe that data mining is most

  7. Minerals and mine drainage

    SciTech Connect (OSTI)

    Liang, H.C.; Thomson, B.M. [Tetra Technical Inc, Denver, CO (United States)

    2009-09-15

    A review of literature published in 2008 and early 2009 on research related to the production of acid mine drainage and/or in the dissolution of minerals as a result of mining, with special emphasis on the effects of these phenomena on the water quality in the surrounding environment, is presented. This review is divided into six sections: 1) Site Characterization and Assessment, 2) Protection, Prevention, and Restoration, 3) Toxicity Assessment, 4) Environmental Fate and Transport, 5) Biological Characterization, and 6) Treatment Technologies. Because there is much overlap in research areas associated with minerals and mine drainage, many papers presented in this review can be classified into more than one category, and the six sections should not be regarded as being mutually-exclusive, nor should they be thought of as being all-inclusive.

  8. Do PageRank-based author rankings outperform simple citation counts?

    E-Print Network [OSTI]

    Fiala, Dalibor; Žitnik, Slavko; Bajec, Marko

    2015-01-01

    The basic indicators of a researcher's productivity and impact are still the number of publications and their citation counts. These metrics are clear, straightforward, and easy to obtain. When a ranking of scholars is needed, for instance in grant, award, or promotion procedures, their use is the fastest and cheapest way of prioritizing some scientists over others. However, due to their nature, there is a danger of oversimplifying scientific achievements. Therefore, many other indicators have been proposed including the usage of the PageRank algorithm known for the ranking of webpages and its modifications suited to citation networks. Nevertheless, this recursive method is computationally expensive and even if it has the advantage of favouring prestige over popularity, its application should be well justified, particularly when compared to the standard citation counts. In this study, we analyze three large datasets of computer science papers in the categories of artificial intelligence, software engineering,...

  9. School of Mines Undergraduate Bulletin

    E-Print Network [OSTI]

    is for your use as a source of continuing reference. Please save it. Published by Colorado School of Mines

  10. School of Mines Graduate Bulletin

    E-Print Network [OSTI]

    is for your use as a source of continuing reference. Please save it. Published by Colorado School of Mines

  11. Probabilistic Workflow Mining Ricardo Silva

    E-Print Network [OSTI]

    Silva, Ricardo

    Probabilistic Workflow Mining Ricardo Silva School of Computer Science - CALD Carnegie Mellon a workflow representation of such activ- ities. In either case, machine learning tools that can mine workflow interest. Such a problem has been called process mining (van der Aalst and We- jters, 2004; Greco et al

  12. Logical Itemset Mining Shailesh Kumar

    E-Print Network [OSTI]

    Cortes, Corinna

    Logical Itemset Mining Shailesh Kumar Google Inc. Hyderabad, India Email: shkumar: {chandrasekhar.v@students, jawahar}@iiit.ac.in Abstract--Frequent Itemset Mining (FISM) attempts to find large baskets (projection property). We propose a simple and robust framework called LOGICAL ITEMSET MINING

  13. CALCULATING RANKS, NULL SPACES AND PSEUDOINVERSE SOLUTIONS FOR

    E-Print Network [OSTI]

    Foster, Leslie

    CONFERENCE 2009, OCT. 26-31, 2009, M #12;ALGORITM SPQR_NULL SPQR_NULL: returns accurate numerical rank

  14. Random Walker Ranking for NCAA Division I-A Football

    E-Print Network [OSTI]

    Porter, Mason A.

    Random Walker Ranking for NCAA Division I-A Football Thomas Callaghan, Peter J. Mucha, and Mason A the top two NCAA Division I-A college football teams in a National Championship game at the end of each in accurately ranking or even agreeing on a ranking methodology for college football lies in two factors

  15. Generalized Multivariate Rank Type Test Statistics via Spatial U-Quantiles

    E-Print Network [OSTI]

    Serfling, Robert

    Generalized Multivariate Rank Type Test Statistics via Spatial U-Quantiles Weihua Zhou1 University for location have been extended over the years to the multivariate setting, including recent robust rotation invariant "spatial" versions. Here we introduce a broad class of rotation invariant multivariate spatial

  16. The MultiRank Bootstrap Algorithm: Semi-Supervised Political Blog Classification and Ranking Using Semi-Supervised Link Classification

    E-Print Network [OSTI]

    Murphy, Robert F.

    The MultiRank Bootstrap Algorithm: Semi-Supervised Political Blog Classification and Ranking Using-supervised learning algorithm for classifying political blogs in a blog network and ranking them within predicted.6% using only 2 seed blogs. Introduction We propose a novel algorithm that both classifies political blogs

  17. Characterization of seven United States coal regions. The development of optimal terrace pit coal mining systems

    SciTech Connect (OSTI)

    Wimer, R.L.; Adams, M.A.; Jurich, D.M.

    1981-02-01

    This report characterizes seven United State coal regions in the Northern Great Plains, Rocky Mountain, Interior, and Gulf Coast coal provinces. Descriptions include those of the Fort Union, Powder River, Green River, Four Corners, Lower Missouri, Illinois Basin, and Texas Gulf coal resource regions. The resource characterizations describe geologic, geographic, hydrologic, environmental and climatological conditions of each region, coal ranks and qualities, extent of reserves, reclamation requirements, and current mining activities. The report was compiled as a basis for the development of hypothetical coal mining situations for comparison of conventional and terrace pit surface mining methods, under contract to the Department of Energy, Contract No. DE-AC01-79ET10023, entitled The Development of Optimal Terrace Pit Coal Mining Systems.

  18. Germany knows mining

    SciTech Connect (OSTI)

    2006-11-15

    Whether it is the nuance of precision or robust rock breaking strength, German suppliers have the expertise. Germany has about 120 companies in the mining equipment industry, employing some 16,000 people. The article describes some recent developments of the following companies: DBT, Liebherr, Atlas Copco, BASF, Boart Longyear, Eickhoff, IBS, Maschinenfabrik Glueckauf, Komatsu, TAKRA, Terex O & R, Thyssen Krupp Foerdertechnik and Wirtgen. 7 photos.

  19. Distributed Data Mining: An Overview Yongjian Fu

    E-Print Network [OSTI]

    Fu, Yongjian

    Distributed Data Mining: An Overview Yongjian Fu Department of Computer Science University mining. We explain what distri­ bution data mining is and why distributed data mining is interesting. Problems and progress in distributed data mining are also discussed. 1 Introduction Facing a rapidly

  20. Data Mining ICPSR Summer Program, 2008

    E-Print Network [OSTI]

    Stine, Robert A.

    Data Mining ICPSR Summer Program, 2008 Robert Stine Statistics Department Wharton School-stat.wharton.upenn.edu/~stine These lectures introduce data mining. Once a nasty thing to be accused of, data mining has become respectable, useful, and even necessary. What is data mining? Basically, data mining refers to statistical algorithms

  1. Ranking Outlier Nodes in Subspaces of Attributed Graphs

    E-Print Network [OSTI]

    Antwerpen, Universiteit

    .mueller, patricia.iglesias, klemens.boehm}@kit.edu yvonne.muelle@student.kit.edu University of Antwerp, Belgium emmanuel.mueller@ua.ac.be Abstract-- Outlier analysis is an important data mining task that aims to detect mining task for fraud detection, network intrusion analysis, anomaly detection in e- commerce, and many

  2. Ground control for highwall mining

    SciTech Connect (OSTI)

    Zipf, R.K.; Mark, C.

    2007-09-15

    Perhaps the greatest risk to both equipment and personnel associated with highwall mining is from ground control. The two most significant ground control hazards are rock falls from highwall and equipment entrapment underground. In the central Appalachians, where the majority of highwall mining occurs in the USA, hillseams (or mountain cracks) are the most prominent structure that affects highwall stability. The article discusses measures to minimise the risk of failure associated with hillstreams. A 'stuck' or trapped highwall miner, and the ensuring retrieval or recovery operation, can be extremely disruptive to the highwall mining process. Most entrapment, are due to roof falls in the hole. The options for recovery are surface retrieval, surface excavation or underground recovery. Proper pillar design is essential to maintain highwall stability and prevent entrapments. NIOSH has developed the Analysis of Retreat Mining Pillar stability-Highwall Mining (ARMPS-HWM) computer program to help mine planners with this process. 10 figs.

  3. Random Walker Ranking for NCAA Division I-A Football

    E-Print Network [OSTI]

    Callaghan, T; Mucha, P J; Callaghan, Thomas; Porter, Mason A.; Mucha, Peter J.

    2003-01-01

    We develop a one-parameter family of ranking systems for NCAA Division I-A football teams based on a collection of voters, each with a single vote, executing independent random walks on a network defined by the teams (vertices) and the games played (edges). The virtue of this class of ranking systems lies in the simplicity of its explanation. We discuss the statistical properties of the randomly walking voters and relate them to the community structure of the underlying network. We compare the results of these rankings for recent seasons with Bowl Championship Series standings and component rankings. To better understand this ranking system, we also examine the asymptotic behaviors of the aggregate of walkers. Finally, we consider possible generalizations to this ranking algorithm.

  4. Coal Mining on Pitching Seams

    E-Print Network [OSTI]

    Brown, George MacMillan

    1915-01-01

    compressed air post punchers are used. Where the coal is undercut permissible explosives are used. On all solid shooting black powder is used. It might be said right here that black powder has caused more fires, explosions and deaths than any other one... thing in Oklahoma mines, with the exception probably of falls of rock. However, under ruling of the United States Bureau of Mines black powder will probably eventually be excluded from all mines on Indian lands. On the lower entries, owing...

  5. HPGMG 1.0: A Benchmark for Ranking High Performance Computing Systems

    E-Print Network [OSTI]

    Adams, Mark

    2014-01-01

    for Ranking High Performance Computing Systems Mark F. Adamsmetric for ranking high performance computing systems. HPLmetric for ranking high performance computing systems. When

  6. Lowest-rank Solutions of Continuous and Discrete Lyapunov ...

    E-Print Network [OSTI]

    Ziyan Luo

    2012-10-09

    Oct 9, 2012 ... Abstract: The low-rank solutions of continuous and discrete Lyapunov equations are of great importance but generally difficult to achieve in ...

  7. Proceedings of the sixteenth biennial low-rank fuels symposium

    SciTech Connect (OSTI)

    Not Available

    1991-01-01

    Low-rank coals represent a major energy resource for the world. The Low-Rank Fuels Symposium, building on the traditions established by the Lignite Symposium, focuses on the key opportunities for this resource. This conference offers a forum for leaders from industry, government, and academia to gather to share current information on the opportunities represented by low-rank coals. In the United States and throughout the world, the utility industry is the primary user of low-rank coals. As such, current experiences and future opportunities for new technologies in this industry were the primary focuses of the symposium.

  8. Exact Primitives for Time Series Data Mining

    E-Print Network [OSTI]

    Mueen, Abdullah Al

    2012-01-01

    on Knowledge discovery and data mining, KDD, pages 947–956,on Knowledge discovery and data mining, KDD ’11, pages [15]on Knowledge discovery and data mining, KDD ’03, pages 493–

  9. Data Mining Within a Regression Framework

    E-Print Network [OSTI]

    Richard A. Berk

    2011-01-01

    2003) Exploratory Data Mining and Data Cleaning. New York:I.H. and E. Frank. (2000). Data Mining. New York: Morgan and2001) Principle of Data Mining. Cambridge, Massachusetts:

  10. Data Mining Within a Regression Framework

    E-Print Network [OSTI]

    Richard A. Berk

    2011-01-01

    I.H. and E. Frank. (2000). Data Mining. New York: Morgan and2003) Exploratory Data Mining and Data Cleaning. New York:2001) Principle of Data Mining. Cambridge, Massachusetts:

  11. Exact Primitives for Time Series Data Mining

    E-Print Network [OSTI]

    Mueen, Abdullah Al

    2012-01-01

    G. Silva, and Rui M. M. Brito. Mining approximate motifs intime series. In Data Mining, 2001. ICDM 2001, Proceedingson Knowledge discovery and data mining, KDD, pages 947–956,

  12. Data Mining Historical Manuscripts and Culture Artifacts

    E-Print Network [OSTI]

    Zhu, Qiang

    2011-01-01

    Workshop on Temporal Data Mining. [62] Liu, Y. , Zhang, D. ,Faloutsos, C. 2006. Automatic mining of fruit fly embryo2011. The Mouse that Roared: Mining Massive Archives of Mice

  13. Efficient Algorithms for High Dimensional Data Mining

    E-Print Network [OSTI]

    Rakthanmanon, Thanawin

    2012-01-01

    E. J. Keogh. 2008. Querying and mining of time series data:Dupasquier and S. Burschka. 2011. Data mining for hackers –encrypted traffic mining. The 28 th Chaos Comm’ Congress. Y.

  14. Hydraulic mining method

    DOE Patents [OSTI]

    Huffman, Lester H. (Kent, WA); Knoke, Gerald S. (Kent, WA)

    1985-08-20

    A method of hydraulically mining an underground pitched mineral vein comprising drilling a vertical borehole through the earth's lithosphere into the vein and drilling a slant borehole along the footwall of the vein to intersect the vertical borehole. Material is removed from the mineral vein by directing a high pressure water jet thereagainst. The resulting slurry of mineral fragments and water flows along the slant borehole into the lower end of the vertical borehole from where it is pumped upwardly through the vertical borehole to the surface.

  15. Proceedings, 26th international conference on ground control in mining

    SciTech Connect (OSTI)

    Peng, S.S.; Mark, C.; Finfinger, G. (and others) (eds.)

    2007-07-01

    Papers are presented under the following topic headings: multiple-seam mining, surface subsidence, coal pillar, bunker and roadway/entry supports, mine design and highwall mining, longwall, roof bolting, stone and hardrock mining, rock mechanics and mine seal.

  16. FREQUENT SET MINING Bart Goethals

    E-Print Network [OSTI]

    Antwerpen, Universiteit

    Chapter 17 FREQUENT SET MINING Bart Goethals Departement of Mathemati1cs and Computer Science, University of Antwerp, Belgium bart.goethals@ua.ac.be Abstract Frequent sets lie at the basis of many Data Mining algorithms. As a result, hun- dreds of algorithms have been proposed in order to solve

  17. Web Mining for Hyperlinked Communities

    E-Print Network [OSTI]

    Hu, Wen-Chen

    Web Mining for Hyperlinked Communities Gary William Flake flake@research.nj.nec.com NEC Research Institute #12;Motivation for Web Mining More than 1B web pages and 20TB of raw data. Even more content will always be disorganized (or at best self-organized). In the future, everything will be on the web

  18. Characterization of Logics Over Ranked Tree Thomas Place

    E-Print Network [OSTI]

    Doyen, Laurent

    Characterization of Logics Over Ranked Tree Languages Thomas Place LSV, ENS-Cachan, CNRS, INRIA combinations of 1 over ranked trees. In particular, we provide effective characterizations of those three logics using algebraic identities. Characterizations had already been obtained for those logics over

  19. Distribution of ranks of ?-decay half-lives

    E-Print Network [OSTI]

    Juan Miguel Campanario

    2010-11-21

    I studied the distribution of ranks of values of 2949 {\\beta}-decay half-lives according to an empirical beta law with two exponents. {\\beta}-decay half-life ranks showed good fit to a beta function with two exponents.

  20. Chemical comminution and deashing of low-rank coals

    DOE Patents [OSTI]

    Quigley, David R. (Idaho Falls, ID)

    1992-01-01

    A method of chemically comminuting a low-rank coal while at the same time increasing the heating value of the coal. A strong alkali solution is added to a low-rank coal to solubilize the carbonaceous portion of the coal, leaving behind the noncarbonaceous mineral matter portion. The solubilized coal is precipitated from solution by a multivalent cation, preferably calcium.

  1. Chemical comminution and deashing of low-rank coals

    DOE Patents [OSTI]

    Quigley, David R.

    1992-12-01

    A method of chemically comminuting a low-rank coal while at the same time increasing the heating value of the coal. A strong alkali solution is added to a low-rank coal to solubilize the carbonaceous portion of the coal, leaving behind the noncarbonaceous mineral matter portion. The solubilized coal is precipitated from solution by a multivalent cation, preferably calcium.

  2. Finding True Beliefs: Applying Rank-Dependent Expected Utility Theory

    E-Print Network [OSTI]

    Chen, Yiling

    -making that incorporates probability weighting and non-linear utility functions, to the analysis of the quadratic scoringFinding True Beliefs: Applying Rank-Dependent Expected Utility Theory to Proper Scoring Rules-value maximizers. Thus, we apply rank-dependent expected utility theory, a more general model of decision

  3. Computable structures of Scott rank # CK familiar classes

    E-Print Network [OSTI]

    Calvert, Wesley

    Computable structures of Scott rank # CK 1 in familiar classes W. Calvert, S. S. Goncharov, and J. F. Knight # July 6, 2005 Abstract There are familiar examples of computable structures having various computable Scott ranks. There are also familiar structures, such as the Harrison ordering

  4. Rankings of Academic Journals and Institutions in Economics

    E-Print Network [OSTI]

    Rankings of Academic Journals and Institutions in Economics Pantelis Kalaitzidakis University European Economic Association is gratefully acknowledged. #12;1 Introduction There has been a lot of recent research literature on rankings of economics departments throughout the world. They serve as signals tools

  5. MATH 51 LECTURE NOTES: HOW GOOGLE RANKS WEB PAGES

    E-Print Network [OSTI]

    Easton, Robert W.

    MATH 51 LECTURE NOTES: HOW GOOGLE RANKS WEB PAGES BRIAN WHITE During a typical use of a search engine, (1) the user types a word, (2) the engine finds all web pages that contain the given word, and (3 of doing step 3, that is, a better way of ranking web pages. Google's method is called the Page

  6. Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination

    E-Print Network [OSTI]

    Zhang, Liqing

    IEEEProof Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination Qibin--CANDECOMP/PARAFAC (CP) tensor factorization of incomplete data is a powerful technique for tensor completion through explicitly capturing the multilinear latent factors. The existing CP algorithms require the tensor rank

  7. Measuring mine roof bolt strains

    DOE Patents [OSTI]

    Steblay, Bernard J. (Lakewood, CO)

    1986-01-01

    A mine roof bolt and a method of measuring the strain in mine roof bolts of this type are disclosed. According to the method, a flat portion on the head of the mine roof bolt is first machined. Next, a hole is drilled radially through the bolt at a predetermined distance from the bolt head. After installation of the mine roof bolt and loading, the strain of the mine roof bolt is measured by generating an ultrasonic pulse at the flat portion. The time of travel of the ultrasonic pulse reflected from the hole is measured. This time of travel is a function of the distance from the flat portion to the hole and increases as the bolt is loaded. Consequently, the time measurement is correlated to the strain in the bolt. Compensation for various factors affecting the travel time are also provided.

  8. Evaluation and Ranking of Geothermal Resources for Electrical Generation or Electrical Offset in Idaho, Montana, Oregon and Washington. Volume I.

    SciTech Connect (OSTI)

    Bloomquist, R. Gordon

    1985-06-01

    The objective was to consolidate and evaluate all geologic, environmental, and legal and institutional information in existing records and files, and to apply a uniform methodology to the evaluation and ranking of sites to allow the making of creditable forecasts of the supply of geothermal energy which could be available in the region over a 20 year planning horizon. A total of 1265 potential geothermal resource sites were identified from existing literature. Site selection was based upon the presence of thermal and mineral springs or wells and/or areas of recent volcanic activity and high heat flow. 250 sites were selected for detailed analysis. A methodology to rank the sites by energy potential, degree of developability, and cost of energy was developed. Resource developability was ranked by a method based on a weighted variable evaluation of resource favorability. Sites were ranked using an integration of values determined through the cost and developability analysis. 75 figs., 63 tabs.

  9. NEW MEXICO SCHOOL OF MINES STATE BUREAU OF MINES AND MINERAL RESOURCES

    E-Print Network [OSTI]

    Lee, Cin-Ty Aeolus

    NEW MEXICO SCHOOL OF MINES STATE BUREAU OF MINES AND MINERAL RESOURCES BULLETIN 13 FRONTISPIECE PIT AT HARDING MINE (To left of dump) DUMP AT HARDING MINE (To right of pit) #12;NEW MEXICO SCHOOL OF MINES STATE and Economic Features of the Pegmatites of Taos and Rio Arriba Counties, New Mexico By EVAN JUST SOCORRO, N. M

  10. Department of Geophysics Colorado School of Mines

    E-Print Network [OSTI]

    Department of Geophysics Colorado School of Mines Golden, CO 80401 http://www.geophysics Colorado School of Mines CGEM Alisa Marie Green #12;Department of Geophysics Colorado School of Mines Golden, CO 80401 http://www.geophysics.mines.edu/cgem Defended: November 06, 2003 Advisor: Dr. Yaoguo Li

  11. Department of Geophysics Colorado School of Mines

    E-Print Network [OSTI]

    Department of Geophysics Colorado School of Mines Golden, CO 80401 http://www.geophysics Colorado School of Mines CGEM Dongjie Cheng #12;#12;Department of Geophysics Colorado School of Mines Golden, CO 80401 http://www.geophysics.mines.edu/cgem Defended: December 2003 Advisor: Dr. Yaoguo Li (GP

  12. Social Media Mining: Fundamental Issues and Challenges

    E-Print Network [OSTI]

    Liu, Huan

    Social Media Mining: Fundamental Issues and Challenges Mohammad Ali Abbasi, Huan Liu, and Reza Zafarani Data Mining and Machine Learning Lab Arizona State University http://icdm2013.zafarani.net December 10, 2013 #12;2Social Media Mining Measures and Metrics 2Social Media Mining ICDM 2013 Tutorial

  13. AREA OVERVIEW----Agent & Data Mining Interaction

    E-Print Network [OSTI]

    Cao, Longbing

    AREA OVERVIEW---- Agent & Data Mining Interaction (ADMI) Longbing Cao Faculty of Information in a Multiple Agent Environment", EWSL91, 1991 Agent-based data mining & knowledge discovery by Davies, W., 1994 Research topics Agent driven data mining Data mining driven agents & multi- agent systems Mutual issues

  14. ANALYSIS OF MINING EXPLOSION PERFORMANCE WITH MULTIPLE

    E-Print Network [OSTI]

    Stump, Brian W.

    ANALYSIS OF MINING EXPLOSION PERFORMANCE WITH MULTIPLE SENSOR DATA AND PHYSICAL MODELS Brian W Martin Thunder Basin Coal Company Wright, Wyoming #12;Analysis of Mining Explosion Performance 2 1 to Different Types of Mining Explosions · Single Shot · Cast Blast · Coal Fragmentation #12;Analysis of Mining

  15. Mining Weighted Association Rules without Preassigned Weights

    E-Print Network [OSTI]

    Bai, Fengshan

    Mining Weighted Association Rules without Preassigned Weights Ke Sun and Fengshan Bai Abstract--Association rule mining is a key issue in data mining. However, the classical models ignore the difference between the transactions, and the weighted association rule mining does not work on databases with only binary attributes

  16. Identifying Relevant Databases for Multidatabase Mining

    E-Print Network [OSTI]

    Liu, Huan

    Identifying Relevant Databases for Multidatabase Mining Huan Liu, Hongjun Lu, Jun Yao Department,luhj,yaojung@iscs.nus.edu.sg Abstract. Various tools and systems for knowledge discovery and data mining are developed and available is where we should start mining. In this paper, breaking away from the conventional data mining assumption

  17. A Mass Balance Mercury Budget for a Mine-Dominated Lake: Clear Lake, California

    E-Print Network [OSTI]

    Richerson, Peter J.

    . 150­300 years. Keywords Acid mine drainage . Budget . Clear Lake . Mercury. Mass balance . Mercury) municipal and agricultural water diversions, (3) losses from out-flowing drainage of Cache Creek that feeds

  18. Expansion of the commercial output of Estonian oil shale mining and processing

    SciTech Connect (OSTI)

    Fraiman, J.; Kuzmiv, I. [Estonian Oil Shale State Co., Jyhvi (Estonia). Scientific Research Center

    1996-09-01

    Economic and ecological preconditions are considered for the transition from monoproduct oil shale mining to polyproduct Estonian oil shale deposits. Underground water, limestone, and underground heat found in oil shale mines with small reserves can be operated for a long time using chambers left after oil shale extraction. The adjacent fields of the closed mines can be connected to the operations of the mines that are still working. Complex usage of natural resources of Estonian oil shale deposits is made possible owing to the unique features of its geology and technology. Oil shale seam development is carried out at shallow depths (40--70 m) in stable limestones and does not require expensive maintenance. Such natural resources as underground water, carbonate rocks, heat of rock mass, and underground chambers are opened by mining and are ready for utilization. Room-and-pillar mining does not disturb the surface, and worked oil shale and greenery waste heaps do not breach its ecology. Technical decisions and economic evaluation are presented for the complex utilization of natural resources in the boundaries of mine take of the ``Tammiku`` underground mine and the adjacent closed mine N2. Ten countries have already experienced industrial utilization of oil shale in small volumes for many years. Usually oil shale deposits are not notable for complex geology of the strata and are not deeply bedded. Thus complex utilization of quite extensive natural resources of Estonian oil shale deposits is of both scientific and practical interest.

  19. The Economic Impact of Coal Mining in New Mexico

    SciTech Connect (OSTI)

    Peach, James; Starbuck, C.

    2009-06-01

    The economic impact of coal mining in New Mexico is examined in this report. The analysis is based on economic multipliers derived from an input-output model of the New Mexico economy. The direct, indirect, and induced impacts of coal mining in New Mexico are presented in terms of output, value added, employment, and labor income for calendar year 2007. Tax, rental, and royalty income to the State of New Mexico are also presented. Historical coal production, reserves, and price data are also presented and discussed. The impacts of coal-fired electricity generation will be examined in a separate report.

  20. Physics high-ranking Journals (category 2) Advances in Physics

    E-Print Network [OSTI]

    Bataillon, Thomas

    Physics high-ranking Journals (category 2) Advances in Physics Annual Review of Astronomy and Astrophysics Annual Review of Nuclear and Particle Science Applied Physics Letters Astronomy & Astrophysics Astronomy and Astrophysics Review Astrophysical Journal European Physical Journal D. Atomic, Molecular

  1. Appendix 14 CSKT Sensitive Species and Heritage Program Ranks for

    E-Print Network [OSTI]

    lemming Wolverine Gray wolf Fisher Grizzly bear River Otter Lynx Montana Natural Heritage Program Ranks Botrychium lineare Linearleaf Moonwort G1 S1 C Botrychium montanum Mountain Moonwort G3 S3 SENSITIVE

  2. Introduction Florida ranks second among the states in fresh market

    E-Print Network [OSTI]

    Ma, Lena

    corn, tomatoes and watermelons. Florida ranks second in fresh market value of strawberry, sweet pepper.5 % of the state's total value. Other major crops with a lesser proportion of the 2009 crop value were strawberry

  3. Linear rank inequalities on five or more variables

    E-Print Network [OSTI]

    Dougherty, Randall; Zeger, Kenneth

    2009-01-01

    Ranks of subspaces of vector spaces satisfy all linear inequalities satisfied by entropies (including the standard Shannon inequalities) and an additional inequality due to Ingleton. It is known that the Shannon and Ingleton inequalities generate all such linear rank inequalities on up to four variables, but it has been an open question whether additional inequalities hold for the case of five or more variables. Here we give a list of 24 inequalities which, together with the Shannon and Ingleton inequalities, generate all linear rank inequalities on five variables. We also give a partial list of linear rank inequalities on six variables and general results which produce such inequalities on an arbitrary number of variables; we prove that there are essentially new inequalities at each number of variables beyond four (a result also proved recently by Kinser).

  4. NETL's New Supercomputer Ranks Among the World's Top 100 | Department...

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

    Computer for Energy and the Environment (HPCEE) is not only on the TOP500 list as one of the top 100 supercomputers in the world--currently ranked at 55--but it is...

  5. Nuclear norm penalized LAD estimator for low rank matrix recovery

    E-Print Network [OSTI]

    Wei, Wenzhe

    2015-01-01

    In the thesis we propose a novel method for low rank matrix recovery. We study the framework using absolute deviation loss function and nuclear penalty. While nuclear norm penalty is widely utilized heuristic method for ...

  6. Privacy-preserving data mining 

    E-Print Network [OSTI]

    Zhang, Nan

    2009-05-15

    In the research of privacy-preserving data mining, we address issues related to extracting knowledge from large amounts of data without violating the privacy of the data owners. In this study, we first introduce an integrated baseline architecture...

  7. School of Mines Graduate Bulletin

    E-Print Network [OSTI]

    is for your use as a source of continuing reference. Please save it. Published by Colorado School of Mines & Divisions. . . . . . . . . . . . . . . . 5 General Information . . . . . . . . . . . . . . . . . . . . . 6 Mission and Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Institutional Values

  8. School of Mines Graduate Bulletin

    E-Print Network [OSTI]

    is for your use as a source of continuing reference. Please save it. Published by Colorado School of Mines . . . . . . . . . . . . . . . . . 5 Academic Departments & Divisions . . . . . . . . . . . . 5 General Information 6 Mission and Goals . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Institutional Values and Principles

  9. School of Mines Graduate Bulletin

    E-Print Network [OSTI]

    is for your use as a source of continuing reference. Please save it. Published by Colorado School of Mines General Information . . . . . . . . . . . . . . . . . . . . . 6 Mission and Goals . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Institutional Values and Principles . . . . . . . . . . . . . . 6 History of CSM

  10. Evaluating ranking methods on heterogeneous digital library collections

    E-Print Network [OSTI]

    Canévet, Olivier; Marian, Ludmila; Chonavel, Thierry

    In the frame of research in particle physics, CERN has been developing its own web-based software /Invenio/ to run the digital library of all the documents related to CERN and fundamental physics. The documents (articles, photos, news, thesis, ...) can be retrieved through a search engine. The results matching the query of the user can be displayed in several ways: sorted by latest first, author, title and also ranked by word similarity. The purpose of this project is to study and implement a new ranking method in Invenio: distributed-ranking (D-Rank). This method aims at aggregating several ranking scores coming from different ranking methods into a new score. In addition to query-related scores such as word similarity, the goal of the work is to take into account non-query-related scores such as citations, journal impact factor and in particular scores related to the document access frequency in the database. The idea is that for two equally query-relevant documents, if one has been more downloaded for inst...

  11. MODELING OF STATIC MINING SUBSIDENCE IN A NONLINEAR MEDIUM

    E-Print Network [OSTI]

    Ratigan, J.L.

    2013-01-01

    Static Evaluation of Mining Subsidence," Rep. No. LBL-11356,MODELING OF STATIC MINING SUBSIDENCE IN A NONLINEAR MEDIUMMODELING OF STATIC MINING SUBSIDENCE IN A NONLINEAR ~lliDIUM

  12. Data Mining Applied to Acoustic Bird Species Recognition

    E-Print Network [OSTI]

    Vilches, Erika; Escobar, Ivan A.; Vallejo, E E; Taylor, C E

    2006-01-01

    11] Witten, I. ; Frank, E. ; Data Mining: Practical MachineData Mining Applied to Acoustic Bird Species Recognitionthe application of data mining techniques to the problem of

  13. Abiotic Oxidation Rate of Chalcopyrite: Implications for Seafloor Mining

    E-Print Network [OSTI]

    Bilenker, Laura Danielle

    2011-01-01

    in Seawater: Implications for Mining Seafloor Hot Spring.American Institute of Mining, Metallurgical, and PetroleumImplications for Seafloor Mining A Thesis submitted in

  14. Data Mining Applied to Acoustic Bird Species Recognition

    E-Print Network [OSTI]

    Vilches, Erika; Escobar, Ivan A.; Vallejo, E E; Taylor, C E

    2006-01-01

    I. ; Frank, E. ; Data Mining: Practical Machine LearningData Mining Applied to Acoustic Bird Species Recognitionthe application of data mining techniques to the problem of

  15. Mining Time Series Data: Flying Insect Classification and Detection

    E-Print Network [OSTI]

    Chen, Yanping

    2015-01-01

    Application of Data Mining. ” KDD'11: 761-764, 2011. G.Wang, E. J. Keogh. “Querying and mining of time series data.Mining

  16. Metabolically active eukaryotic communities in extremely acidic mine drainage

    E-Print Network [OSTI]

    Baker, Brett J; Lutz, M A; Dawson, S C; Bond, P L; Banfield, J F

    2004-01-01

    Microbial communities in acid mine drainage. FEMS Microbiol.Biogeochem- istry of acid mine drainage at Iron Mountain,in an extreme acid mine drainage environment. Appl. Environ.

  17. Abiotic Oxidation Rate of Chalcopyrite: Implications for Seafloor Mining

    E-Print Network [OSTI]

    Bilenker, Laura Danielle

    2011-01-01

    the formation of acid mine drainage: Colonization of pyritegroundwaters yields acid mine drainage. Pulverization of SMSand groundwaters can yield acid mine drainage via overall

  18. ITP Mining: Energy and Environmental Profile of the U.S. Mining Industry (December 2002)

    Broader source: Energy.gov [DOE]

    The U.S. Department of Energy and the National Mining Association are working in partnership to implement the Mining Industry of the Future strategy.

  19. ITP Mining: The Future Begins with Mining- A Vision of the Mining Industry of the Future

    Broader source: Energy.gov [DOE]

    This vision document details long-term goals and objectives for the mining industry. Stemming from this vision document, targeted technology roadmaps were developed that describe pathways of research to achieve the vision goals.

  20. Dear Rector Simos E. Simopoulos, We are pleased to inform you that your university is ranked excellently in the 2013 Performance Ranking of Scientific Papers for World Universities.

    E-Print Network [OSTI]

    Psarrakos, Panayiotis

    excellently in the 2013 Performance Ranking of Scientific Papers for World Universities. http Performance Ranking of Scientific Papers for World Universities. 72 for Civil Engineering 88 for Chemical Ranking of Scientific Papers for World Universitie is released by the National Taiwan University Ranking

  1. Westinghouse Earns Mine Safety Award for 16th Consecutive Year

    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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking WithTelecentricNCubic Feet)Completes its AP1000® Test StandEarns

  2. Forest Products Marketing on the Internet "When history is written, the creation of the Internet may be ranked

    E-Print Network [OSTI]

    Forest Products Marketing on the Internet Bob Smith "When history is written, the creation of the Internet may be ranked alongside Johann Gutenberg's printing press and Marconi's radio as among the major attention in the past year than the Internet. Every major newspaper, magazine, and television station have

  3. Survey of nine surface mines in North America. [Nine different mines in USA and Canada

    SciTech Connect (OSTI)

    Hayes, L.G.; Brackett, R.D.; Floyd, F.D.

    1981-01-01

    This report presents the information gathered by three mining engineers in a 1980 survey of nine surface mines in the United States and Canada. The mines visited included seven coal mines, one copper mine, and one tar sands mine selected as representative of present state of the art in open pit, strip, and terrace pit mining. The purpose of the survey was to investigate mining methods, equipment requirements, operating costs, reclamation procedures and costs, and other aspects of current surface mining practices in order to acquire basic data for a study comparing conventional and terrace pit mining methods, particularly in deeper overburdens. The survey was conducted as part of a project under DOE Contract No. DE-AC01-79ET10023 titled The Development of Optimal Terrace Pit Coal Mining Systems.

  4. COST AND SCHEDULE FOR DRILLING AND MINING UNDERGROUND TEST FACILITIES

    E-Print Network [OSTI]

    Lamb, D.W.

    2013-01-01

    SHAFT SINKING IN-MINE DRILLiNG NEW MINE - 1500 M SURFACEORILUNG SHAFT SINKiNG FACIUTY DEVELOPMENT IN-MINE DRILLINGSURFACE DRILLING FACIUTY DEVELOPMENT IN-MINE DRILLING ~~NGM!

  5. Design procedures for coal mine tunnels. Open file report 1 Oct 79-31 Dec 82 (final)

    SciTech Connect (OSTI)

    Bieniawski, Z.T.

    1983-03-31

    Although coal mine tunnels such as the main haulageways or roadways are the lifelines of coal mines, little attention has been paid to them in the United States in terms of preconstruction planning and design. This report summarizes the results of a 3-year research project aimed at improving the design procedures for coal mine tunnels. A new design approach was developed for this purpose and roof-support design charts were prepared for mine tunnels and their intersections. Analytical studies, 'base friction' model experiments, and in situ rock stress measurements were performed during this research.

  6. A network-based ranking system for American college football

    E-Print Network [OSTI]

    Park, J; Park, Juyong

    2005-01-01

    American college football faces a conflict created by the desire to stage national championship games between the best teams of a season when there is no conventional playoff system to decide which those teams are. Instead, ranking of teams is based on their record of wins and losses during the season, but each team plays only a small fraction of eligible opponents, making the system underdetermined or contradictory or both. It is an interesting challenge to create a ranking system that at once is mathematically well-founded, gives results in general accord with received wisdom concerning the relative strengths of the teams, and is based upon intuitive principles, allowing it to be accepted readily by fans and experts alike. Here we introduce a one-parameter ranking method that satisfies all of these requirements and is based on a network representation of college football schedules.

  7. Phenomena Identification and Ranking Technique (PIRT) Panel Meeting Summary Report

    SciTech Connect (OSTI)

    Mark Holbrook

    2007-07-01

    Phenomena Identification and Ranking Technique (PIRT) is a systematic way of gathering information from experts on a specific subject and ranking the importance of the information. NRC, in collaboration with DOE and the working group, conducted the PIRT exercises to identify safety-relevant phenomena for NGNP, and to assess and rank the importance and knowledge base for each phenomenon. The overall objective was to provide NRC with an expert assessment of the safety-relevant NGNP phenomena, and an overall assessment of R and D needs for NGNP licensing. The PIRT process was applied to five major topical areas relevant to NGNP safety and licensing: (1) thermofluids and accident analysis (including neutronics), (2) fission product transport, (3) high temperature materials, (4) graphite, and (5) process heat for hydrogen cogeneration.

  8. Using Lotkaian Informetrics for Ranking in Digital Libraries

    E-Print Network [OSTI]

    Schaer, Philipp

    2011-01-01

    The purpose of this paper is to propose the use of models, theories and laws in bibliometrics and scientometrics to enhance information retrieval processes, especially ranking. A common pattern in many man-made data sets is Lotka's Law which follows the well-known power-law distributions. These informetric distributions can be used to give an alternative order to large and scattered result sets and can be applied as a new ranking mechanism. The polyrepresentation of information in Digital Library systems is used to enhance the retrieval quality, to overcome the drawbacks of the typical term-based ranking approaches and to enable users to explore retrieved document sets from a different perspective.

  9. The Coal and Other Mines (Mechanics and Electricians) Regulations 1965 

    E-Print Network [OSTI]

    Lee, Fred

    1965-01-01

    STATUTORY INSTRUMENTS 1965 No. 1559 MINES AND QUARRIES The Coal and Other Mines (Mechanics and Electricians) Regulations 1965

  10. ORS 517 - Mining and Mining Claims | 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 QA:QAsource History ViewMayo, Maryland:NPI VenturesNewSt. Louis, Minnesota:Nulato,Nyack, - Mining and Mining Claims

  11. Rank-ordered Multifractal Spectrum for Intermittent Fluctuations

    E-Print Network [OSTI]

    Tom Chang; Cheng-chin Wu

    2007-12-27

    We describe a new method that is both physically explicable and quantitatively accurate in describing the multifractal characteristics of intermittent events based on groupings of rank-ordered fluctuations. The generic nature of such rank-ordered spectrum leads it to a natural connection with the concept of one-parameter scaling for monofractals. We demonstrate this technique using results obtained from a 2D MHD simulation. The calculated spectrum suggests a crossover from the near Gaussian characteristics of small amplitude fluctuations to the extreme intermittent state of large rare events.

  12. Enhancing Invenio Digital Library With An External Relevance Ranking Engine

    E-Print Network [OSTI]

    Glauner, Patrick Oliver

    Invenio is a comprehensive web-based free digital library software suite originally developed at CERN. In order to improve its information retrieval and word similarity ranking capabilities, the goal of this thesis is to enhance Invenio by bridging it with modern external information retrieval systems. In the first part a comparison of various information retrieval systems such as Solr and Xapian is made. In the second part a system-independent bridge for word similarity ranking is designed and implemented. Subsequently, Solr and Xapian are integrated in Invenio via adapters to the bridge. In the third part scalability tests are performed. Finally, a future outlook is briefly discussed.

  13. WIPP Takes Second in Mine Rescue Competition

    Broader source: Energy.gov [DOE]

    CARLSBAD, N.M. – EM’s Waste Isolation Pilot Plant (WIPP) mine rescue team placed second in the Southwestern Regional Mine Rescue Competition this past spring in Carlsbad, and it took home more than a trophy.

  14. Incident Data Analysis Using Data Mining Techniques 

    E-Print Network [OSTI]

    Veltman, Lisa M.

    2010-01-16

    of data mining and text mining to analyze the Hazardous Substances Emergency Events Surveillance (HSEES) system data by identifying relationships among variables, predicting the occurrence of injuries, and assessing the value added by the text data...

  15. Data Mining and Knowledge Discovery: Practice Notes

    E-Print Network [OSTI]

    Novak, Petra Kralj

    1 Data Mining and Knowledge Discovery: Practice Notes Petra Kralj Novak Petra.Kralj.Novak@ijs.si and exam · 2013/1/15: Written exam, seminar proposal discussion · 2013/2/12: Data mining seminar

  16. Data Mining and Knowledge Discovery: Practice Notes

    E-Print Network [OSTI]

    Novak, Petra Kralj

    1 Data Mining and Knowledge Discovery: Practice Notes Petra Kralj Novak Petra.Kralj.Novak@ijs.si on Weka 3: Descriptive data mining ­ Discussion about seminars and exam · 2013/12/16: Written exam

  17. LLM Oil, Gas and Mining Law Module Information: Oil, Gas & Mining Environmental Law I and

    E-Print Network [OSTI]

    Evans, Paul

    LLM Oil, Gas and Mining Law Module Information: Oil, Gas & Mining Environmental Law I and Oil, Gas of the area of Oil, Gas &, Mining Environmental Law; 2. communicate complex legal concepts that apply within the area of Oil, Gas & Mining & Environmental Law to a high level of competence; and 3. deploy a highly

  18. MINING ENGINEERING AT McGILL Bachelor of Engineering in Mining Engineering

    E-Print Network [OSTI]

    Barthelat, Francois

    mining engineering program in Canada and the second oldest in North America. The program offers students work term placements have included coal mining in New Mexico, zinc mining in the Arctic, gold mining Canada on work terms -- Val d'Or, Quebec; Fraser Lake, British Columbia; Ottawa and Sudbury, Ontario

  19. Spatial Data Mining, Michael May, Fraunhofer AIS 1 Spatial Data Mining for Customer

    E-Print Network [OSTI]

    Morik, Katharina

    Spatial Data Mining, Michael May, Fraunhofer AIS 1 Spatial Data Mining for Customer Segmentation Data Mining in Practice Seminar, Dortmund, 2003 Dr. Michael May Fraunhofer Institut Autonome Intelligente Systeme #12;Spatial Data Mining, Michael May, Fraunhofer AIS 2 Introduction: a classic example

  20. 08/22/2004 MRDM 2004 Workshop 1 Link MiningLink Mining

    E-Print Network [OSTI]

    Dzeroski, Saso

    08/22/2004 MRDM 2004 Workshop 1 Link MiningLink Mining Lise Getoor University of Maryland, College Park joint work with Indrajit Bhattacharya, Qing Lu and Prithviraj Sen #12;08/22/2004 MRDM 2004 detection · Group Detection · Conclusion #12;08/22/2004 MRDM 2004 Workshop 3 Link MiningLink Mining

  1. Data Mining Research: Opportunities and Challenges Data Mining Research: Opportunities and Challenges

    E-Print Network [OSTI]

    Grossman, Robert

    Data Mining Research: Opportunities and Challenges 1 Data Mining Research: Opportunities and Challenges A Report of three NSF Workshops on Mining Large, Massive, and Distributed Data* Robert Grossman, 1997 and February, 1998 to discuss the current state of the art of data mining and data intensive

  2. ECML TextMining Workshop, Chemnitz, 1998 Evaluation of four clustering methods used in text mining

    E-Print Network [OSTI]

    Turenne, Nicolas

    ECML TextMining Workshop, Chemnitz, 1998 Evaluation of four clustering methods used in text mining according the real-world. Keywords: conceptual clustering ; data mining ; knowledge structuration an acute need in concept extraction and text mining. The paper presents an evaluation of four clustering

  3. Generic Pattern Mining via Data Mining Template Library Nilanjana De, Feng Gao, Paolo Palmerini

    E-Print Network [OSTI]

    Bystroff, Chris

    Generic Pattern Mining via Data Mining Template Library Nilanjana De, Feng Gao, Paolo Palmerini Department, Rensselaer Polytechnic Institute, Troy NY 12180 Abstract Frequent Pattern Mining (FPM) is a very powerful paradigm for mining informative and use- ful patterns in massive, complex datasets. In this paper

  4. WindMine: Fast and Effective Mining of Web-click Sequences Yasushi Sakurai

    E-Print Network [OSTI]

    WindMine: Fast and Effective Mining of Web-click Sequences Yasushi Sakurai NTT Communication, patterns and anomalies? We have developed a novel method, WindMine, and its fine-tuning sibling, Wind of sequences (WindMine-part), with little loss of accuracy. We examine the effectiveness and scalability by per

  5. Coal mine methane global review

    SciTech Connect (OSTI)

    2008-07-01

    This is the second edition of the Coal Mine Methane Global Overview, updated in the summer of 2008. This document contains individual, comprehensive profiles that characterize the coal and coal mine methane sectors of 33 countries - 22 methane to market partners and an additional 11 coal-producing nations. The executive summary provides summary tables that include statistics on coal reserves, coal production, methane emissions, and CMM projects activity. An International Coal Mine Methane Projects Database accompanies this overview. It contains more detailed and comprehensive information on over two hundred CMM recovery and utilization projects around the world. Project information in the database is updated regularly. This document will be updated annually. Suggestions for updates and revisions can be submitted to the Administrative Support Group and will be incorporate into the document as appropriate.

  6. DOE SBIR Phase II Final Report: Distributed Relevance Ranking in Heterogeneous Document Collections

    SciTech Connect (OSTI)

    Abe Lederman

    2007-01-08

    This report contains the comprehensive summary of the work performed on the SBIR Phase II project (“Distributed Relevance Ranking in Heterogeneous Document Collections”) at Deep Web Technologies (http://www.deepwebtech.com). We have successfully completed all of the tasks defined in our SBIR Proposal work plan (See Table 1 - Phase II Tasks Status). The project was completed on schedule and we have successfully deployed an initial production release of the software architecture at DOE-OSTI for the Science.gov Alliance's search portal (http://www.science.gov). We have implemented a set of grid services that supports the extraction, filtering, aggregation, and presentation of search results from numerous heterogeneous document collections. Illustration 3 depicts the services required to perform QuickRank™ filtering of content as defined in our architecture documentation. Functionality that has been implemented is indicated by the services highlighted in green. We have successfully tested our implementation in a multi-node grid deployment both within the Deep Web Technologies offices, and in a heterogeneous geographically distributed grid environment. We have performed a series of load tests in which we successfully simulated 100 concurrent users submitting search requests to the system. This testing was performed on deployments of one, two, and three node grids with services distributed in a number of different configurations. The preliminary results from these tests indicate that our architecture will scale well across multi-node grid deployments, but more work will be needed, beyond the scope of this project, to perform testing and experimentation to determine scalability and resiliency requirements. We are pleased to report that a production quality version (1.4) of the science.gov Alliance's search portal based on our grid architecture was released in June of 2006. This demonstration portal is currently available at http://science.gov/search30 . The portal allows the user to select from a number of collections grouped by category and enter a query expression (See Illustration 1 - Science.gov 3.0 Search Page). After the user clicks “search” a results page is displayed that provides a list of results from the selected collections ordered by relevance based on the query expression the user provided. Our grid based solution to deep web search and document ranking has already gained attention within DOE, other Government Agencies and a fortune 50 company. We are committed to the continued development of grid based solutions to large scale data access, filtering, and presentation problems within the domain of Information Retrieval and the more general categories of content management, data mining and data analysis.

  7. UK mining invests, suppliers profit

    SciTech Connect (OSTI)

    2009-04-15

    In the midst of a major economic crisis in the United Kingdom, equipment suppliers have been reporting a number of considerable purchases by British coal mining companies. In December 2008, Liebherr-Great Britain delivered the first two of four Rq350 Litronic hydraulic excavators for use at the Broken Cross opencast coal site in Lanarkshire, Scotland. Ten Terex TR100 rigid haulers were delivered to the site in late 2008. Hatfield Colliery at Stainforth, South Yorkshire, has been reopened by PowerFuel. The main equipment for two longwall faces was supplied by Joy Mining Machinery UK Ltd. 2 photos.

  8. Program of mining research, 1998--1999

    SciTech Connect (OSTI)

    1998-12-31

    The paper contains: Reflections on 1998; Project summaries; Noise; Injury prevention, ergonomics, and human factors; Surface, sand and gravel, and stone mines; Hazard detection and warning devices; Ground control -- metal/nonmetal mines; Ground control -- coal mines; Explosion and fire detection and suppression; Methane detection; Electrical hazards; Emerging technologies; Surveillance; Construction; Training and education; and Communication activity.

  9. Department of Geophysics Colorado School of Mines

    E-Print Network [OSTI]

    Department of Geophysics Colorado School of Mines Golden, CO 80401 http://www.geophysics of Geophysics Colorado School of Mines Golden, CO 80401 http://www.geophysics.mines.edu/cgem Defended: May 11 (Geophysics) On Original Copies Dr. Terence K. Young Professor and Head Department of Geophysics Approved

  10. Department of Geophysics Colorado School of Mines

    E-Print Network [OSTI]

    Department of Geophysics Colorado School of Mines Golden, CO 80401 http://www.geophysics of Geophysics Colorado School of Mines Golden, CO 80401 http://www.geophysics.mines.edu/cgem Defended: May 10 (Geophysics). Golden, Colorado Date May 15, 2006 Signed: on original copy Jeongmin Lee Signed: on original

  11. Department of Geophysics Colorado School of Mines

    E-Print Network [OSTI]

    Department of Geophysics Colorado School of Mines Golden, CO 80401 http://www.geophysics of Geophysics Colorado School of Mines Golden, CO 80401 http://www.geophysics.mines.edu/cgem Defended: September fulfillment of the requirements for the degree of Master of Science (Geophysics). Golden, Colorado Date

  12. Short Papers___________________________________________________________________________________________________ Mining Multiple-Level Association

    E-Print Network [OSTI]

    Wu, Xindong

    ___________________________________________________________________________________________________ Mining Multiple-Level Association Rules in Large Databases Jiawei Han, Member, IEEE Computer Society for efficient mining of multiple-level association rules from large transaction databases based on the Apriori. Index TermsÐData mining, knowledge discovery in databases, association rules, multiple-level association

  13. Data Mining: Foundation, Techniques and Applications

    E-Print Network [OSTI]

    Tung, Anthony Kum Hoe

    Data Mining: Foundation, Techniques and Applications Anthony Tung() School of Computing National #12;11/30/2007 Data Mining: Foundation, Techniques and Applications 2 Main objectives of this course: · Data mining is a diverse field which draw its foundation from many research areas like databases

  14. WhartonDepartment of Statistics Data Mining

    E-Print Network [OSTI]

    Stine, Robert A.

    WhartonDepartment of Statistics Data Mining Introduction Bob Stine Dept of Statistics What is data mining? · An insult? · Predictive modeling · Large, wide data sets, often unstructuredDepartment of Statistics Plan · Week 1 · Data mining with regression, logistic regression · Illustrate key ideas

  15. Efficiently Mining Maximal Frequent Itemsets Karam Gouda

    E-Print Network [OSTI]

    Fiat, Amos

    Efficiently Mining Maximal Frequent Itemsets Karam Gouda and Mohammed J. Zaki ¡ ComputerMax, a backtrack search based algorithm for mining maximal frequent itemsets. GenMax uses a num- ber based on dataset characteristics. We found GenMax to be a highly efficient method to mine the exact set

  16. Proof Mining in Practice Philipp Gerhardy

    E-Print Network [OSTI]

    Gerhardy, Philipp

    Proof Mining in Practice Philipp Gerhardy April 14, 2008 Abstract In this paper, we present some aspects of a recent application of proof mining by J.Avigad, H.Towsner and the author. In this case study for the ergodic averages. Proof mining generally falls into two main categories: Establishing general metatheorems

  17. ICPSR Summer Program, 2014 Data Mining

    E-Print Network [OSTI]

    Stine, Robert A.

    ICPSR Summer Program, 2014 Data Mining Tools for Exploring Big Data Robert Stine Department of Statistics Wharton School, University of Pennsylvania www-stat.wharton.upenn.edu/~stine Modern data mining a contribution. Rather than build a model that relates one or two experimental results to a response, data mining

  18. MINING TEMPORAL SEQUENCES TO DISCOVER INTERESTING PATTERNS

    E-Print Network [OSTI]

    Holder, Lawrence B.

    MINING TEMPORAL SEQUENCES TO DISCOVER INTERESTING PATTERNS Edwin O. Heierman, III, G. Michael, Texas 76019-0015 {heierman, youngbld, cook@cse.uta.edu ABSTRACT When mining temporal sequences sequences. In this paper, we present a novel data mining technique based on the Minimum Description Length

  19. DATA MINING IN TELECOMMUNICATIONS Gary M. Weiss

    E-Print Network [OSTI]

    Weiss, Gary

    DATA MINING IN TELECOMMUNICATIONS Gary M. Weiss Department of Computer and Information Science data, which describes the telecommunication customers. This chapter describes how data mining can be used to uncover useful information buried within these data sets. Several data mining applications

  20. Statistical data mining Finn Arup Nielsen

    E-Print Network [OSTI]

    Nielsen, Finn Årup

    Statistical data mining Finn °Arup Nielsen Informatics and Mathematical Modelling Technical University of Denmark February 3, 2004 #12;Introduction · "Statistical data mining". · The goal is "knowledge databases (PubMed, MeSH, fMRIDC, SenseLab) Finn °Arup Nielsen 2 February 3, 2004 #12;Mining for novelty

  1. Du Data Mining l'Apprentissage Statistique

    E-Print Network [OSTI]

    Besse, Philippe

    Du Data Mining à l'Apprentissage Statistique Philippe Besse Contenu : 1. Introduction 2. Risque et graphiques des scénarios Formation L'Oréal : 28 / 03 / 2014 #12;Introduction au data mining Apprentissage Mining Introduction Philippe Besse & B´eatrice Laurent INSA de Toulouse Institut de Math´ematiques INSA

  2. Dawdon Mine Water Heat Pump Trial

    E-Print Network [OSTI]

    Oak Ridge National Laboratory

    14-Dec-12 Dawdon Mine Water Heat Pump Trial #12;14 December 2012 2 Potential for Mine Water sourced heating Dawdon heat pump trial A demonstration project Contents #12;Friday, 14 December 2012 3 The UK salinity High Iron (removed by lime treatment) Offices , 8 rooms #12;Dawdon heat pump Warm mine water

  3. Frontiers of biomedical text mining: current progress

    E-Print Network [OSTI]

    Yu, Hong

    Frontiers of biomedical text mining: current progress Pierre Zweigenbaum, Dina Demner-Fushman, Hong of biomedical text mining continue to present interesting challenges and opportunities for great improvements and interesting research. In this article we review the current state of the art in biomedical text mining or `Bio

  4. Institut Mines-Tlcom EPOC : Energy Proportional

    E-Print Network [OSTI]

    Lefèvre, Laurent

    ? ? Renewable energy #12;Institut Mines-Télécom29/11/13 Green@Days Lille 28-29 Novembre 2013 Problem 5 time Workload Renewable energy ? ? regular electric #12;Institut Mines-Télécom29/11/13 Green@Days Lille 28Institut Mines-Télécom EPOC : Energy Proportional and Opportunistic Computing system 1 Labex Comin

  5. COLORADO SCHOOL OF MINES CONTROLLER'S OFFICE

    E-Print Network [OSTI]

    COLORADO SCHOOL OF MINES CONTROLLER'S OFFICE PROCUREMENT CARD HANDBOOK Revised November 2014 #12 ........................................................................................................9 #12;3 Introduction Procurement is a daily occurrence at Colorado School of Mines. The CSM VI.B.1.a]. There are many benefits to using the P-Card over any other methods of purchasing at Mines

  6. CAS CS 565, Data Mining Course logistics

    E-Print Network [OSTI]

    Terzi, Evimaria

    CAS CS 565, Data Mining #12;Course logistics · Course webpage: ­ www.cs.bu.edu/~evimaria/teaching.html · Schedule: Mon ­ Wed, 4-5:30 · Instructor: Evimaria Terzi, evimaria@cs.bu.edu · Office hours: Mon 2:30-4pm (tentative) · Introduction to data mining and prototype problems · Frequent pattern mining ­ Frequent

  7. Analysis of Some Methods for Reduced Rank Gaussian Process Regression

    E-Print Network [OSTI]

    Analysis of Some Methods for Reduced Rank Gaussian Process Regression Joaquin Qui~nonero-Candela1 there is strong motivation for using Gaussian Pro- cesses (GPs) due to their excellent performance in regression-effective ap- proximations to GPs, both for classification and for regression. In this paper we analyze one

  8. Alexandria Digital Library Project Spatial Search, Ranking, and

    E-Print Network [OSTI]

    Janée, Greg

    #12;Alexandria Digital Library Project 11 Proposed solution Geodetic box Defined by N/S/E/W edgesAlexandria Digital Library Project Spatial Search, Ranking, and Interoperability Greg Janée and James Frew University of California, Santa Barbara #12;Alexandria Digital Library Project 2 Background

  9. Stabilized thermally beneficiated low rank coal and method of manufacture

    DOE Patents [OSTI]

    Viall, Arthur J. (Colstrip, MT); Richards, Jeff M. (Colstrip, MT)

    2000-01-01

    A process for reducing the spontaneous combustion tendencies of thermally beneficiated low rank coals employing heat, air or an oxygen containing gas followed by an optional moisture addition. Specific reaction conditions are supplied along with knowledge of equipment types that may be employed on a commercial scale to complete the process.

  10. Rank Aggregation via Nuclear Norm Minimization David F. Gleich

    E-Print Network [OSTI]

    Lim, Lek-Heng

    ] for Supported by the Natural Sciences and Engineering Research Council of Canada and the Dept. of Energy's John@uchicago.edu ABSTRACT The process of rank aggregation is intimately intertwined with the structure of skew. Categories and Subject Descriptors H.3.5 [Information Storage and Retrieval]: On-line in- formation Services

  11. Scalable K-Means by Ranked Retrieval Andrei Broder

    E-Print Network [OSTI]

    Cortes, Corinna

    Scalable K-Means by Ranked Retrieval Andrei Broder Google 1600 Amphitheater Parkway Mountain View, CA 94043 broder @google.com Lluis Garcia-Pueyo Google 1600 Amphitheater Parkway Mountain View, CA 94043 lgpueyo@google.com Vanja Josifovski Google 1600 Amphitheater Parkway Mountain View, CA 94043

  12. Low-Rank Regularization for Learning Gene Expression Programs

    E-Print Network [OSTI]

    Ye, Guibo; Tang, Mengfan; Cai, Jian-Feng; Nie, Qing; Xie, Xiaohui; Muldoon, Mark R

    2013-01-01

    67–103. 11. Christley S, Nie Q, Xie X (2009) Incorporating1 , Jian-Feng Cai 3 , Qing Nie 2,4 , Xiaohui Xie 1,4 * 1Ye G, Tang M, Cai J-F, Nie Q, Xie X (2013) Low-Rank

  13. Stabilized thermally beneficiated low rank coal and method of manufacture

    DOE Patents [OSTI]

    Viall, A.J.; Richards, J.M.

    1999-01-26

    A process is described for reducing the spontaneous combustion tendencies of thermally beneficiated low rank coals employing heat, air or an oxygen containing gas followed by an optional moisture addition. Specific reaction conditions are supplied along with knowledge of equipment types that may be employed on a commercial scale to complete the process. 3 figs.

  14. Stabilized thermally beneficiated low rank coal and method of manufacture

    DOE Patents [OSTI]

    Viall, Arthur J. (Colstrip, MT); Richards, Jeff M. (Colstrip, MT)

    1999-01-01

    A process for reducing the spontaneous combustion tendencies of thermally beneficiated low rank coals employing heat, air or an oxygen containing gas followed by an optional moisture addition. Specific reaction conditions are supplied along with knowledge of equipment types that may be employed on a commercial scale to complete the process.

  15. Modeled atmospheric radon concentrations from uranium mines

    SciTech Connect (OSTI)

    Droppo, J.G.

    1985-04-01

    Uranium mining and milling operations result in the release of radon from numerous sources of various types and strengths. The US Environmental Protection Agency (EPA) under the Clean Air Act, is assessing the health impact of air emissions of radon from underground uranium mines. In this case, the radon emissions may impact workers and residents in the mine vicinity. To aid in this assessment, the EPA needs to know how mine releases can affect the radon concentrations at populated locations. To obtain this type of information, Pacific Northwest Laboratory used the radon emissions, release characteristics and local meterological conditions for a number of mines to model incremental radon concentrations. Long-term, average, incremental radon concentrations were computed based on the best available information on release rates, plume rise parameters, number and locations of vents, and local dispersion climatology. Calculations are made for a model mine, individual mines, and multiple mines. Our approach was to start with a general case and then consider specific cases for comparison. A model underground uranium mine was used to provide definition of the order of magnitude of typical impacts. Then computations were made for specific mines using the best mine-specific information available for each mine. These case study results are expressed as predicted incremental radon concentration contours plotted on maps with local population data from a previous study. Finally, the effect of possible overlap of radon releases from nearby mines was studied by calculating cumulative radon concentrations for multiple mines in a region with many mines. The dispersion model, modeling assumptions, data sources, computational procedures, and results are documented in this report. 7 refs., 27 figs., 18 tabs.

  16. Robot to the Mine Rescue

    Broader source: Energy.gov [DOE]

    To increase the speed of rescue efforts, scientists and engineers at the Energy Department’s Sandia National Laboratories recently developed a new robot, called the Gemini-Scout Mine Rescue Robot, that quickly finds dangers and provides relief to trapped miners.

  17. Corner-cutting mining assembly

    DOE Patents [OSTI]

    Bradley, John A. (San Antonio, TX)

    1983-01-01

    A mining assembly includes a primary rotary cutter mounted on one end of a support shaft and four secondary rotary cutters carried on the same support shaft and positioned behind the primary cutters for cutting corners in the hole cut by the latter.

  18. Corner-cutting mining assembly

    DOE Patents [OSTI]

    Bradley, J.A.

    1981-07-01

    This invention resulted from a contract with the United States Department of Energy and relates to a mining tool. More particularly, the invention relates to an assembly capable of drilling a hole having a square cross-sectional shape with radiused corners. In mining operations in which conventional auger-type drills are used to form a series of parallel, cylindrical holes in a coal seam, a large amount of coal remains in place in the seam because the shape of the holes leaves thick webs between the holes. A higher percentage of coal can be mined from a seam by a means capable of drilling holes having a substantially square cross section. It is an object of this invention to provide an improved mining apparatus by means of which the amount of coal recovered from a seam deposit can be increased. Another object of the invention is to provide a drilling assembly which cuts corners in a hole having a circular cross section. These objects and other advantages are attained by a preferred embodiment of the invention.

  19. Dragon Year

    E-Print Network [OSTI]

    Hacker, Randi

    2012-01-11

    Broadcast Transcript: Can you believe it? It's New Year again. It seems like only yesterday we were celebrating the advent of the year of the Rabbit and now, here it is, the year of the Dragon. January 22nd is New Year's Eve according to the Lunar...

  20. Longwall mining of thin seams

    SciTech Connect (OSTI)

    Curth, E A

    1981-01-01

    Thin seam operations pose a challenge to the ingenuity of mining engineers to overcome the factor of human inconvenience in the restricted environment and associated high cost production. Surprisingly, low seam longwalls in the Federal Republic of Germany in an average thickness of 35 in. and dipping less than 18/sup 0/ come close to achieving the average production rate of all German longwall operations. They are all plow faces, and a consistent production of 3300 tons per day and a productivity of 40 tons per man shift are reported from one of the thin seam longwalls. These results were attained by reliable high-capacity equipment and roof support by shields that can be collapsed to as low as 22 inches. Maximum mining height for plow operated faces lies at 31.5 inches. Technology for mechanized mining of flat lying coalbeds less than 31.5 inches in thickness without rock cutting is not available, and firmness of coal, undulation of the strata, coalbed thickness variation, and the necessity of cutting rock, particularly through faults, set limits to plow application. The in-web shearer can be used in firm coal to a minimum mining height of 40 inches, and a daily production of 1650 to 2200 tons is reported from a longwall in the Saar district of Germany equipped with such a shearer and shields. Numerous in-web shearers are employed in the United Kingdom; reports as to their success are contradictory. Also, experience in the United States, though limited, has been negative. The steady increase in output from single drum shearer faces in Pennsylvania is a remarkable achievement, and occasional record breaking peaks in production indicate the potential of such mining. Technology development for the future is discussed.

  1. Pbm: A new dataset for blog mining

    E-Print Network [OSTI]

    Aziz, Mehwish

    2012-01-01

    Text mining is becoming vital as Web 2.0 offers collaborative content creation and sharing. Now Researchers have growing interest in text mining methods for discovering knowledge. Text mining researchers come from variety of areas like: Natural Language Processing, Computational Linguistic, Machine Learning, and Statistics. A typical text mining application involves preprocessing of text, stemming and lemmatization, tagging and annotation, deriving knowledge patterns, evaluating and interpreting the results. There are numerous approaches for performing text mining tasks, like: clustering, categorization, sentimental analysis, and summarization. There is a growing need to standardize the evaluation of these tasks. One major component of establishing standardization is to provide standard datasets for these tasks. Although there are various standard datasets available for traditional text mining tasks, but there are very few and expensive datasets for blog-mining task. Blogs, a new genre in web 2.0 is a digital...

  2. top-ranked. The College of Business Administration (CBA) at the

    E-Print Network [OSTI]

    Grissino-Mayer, Henri D.

    -ranked. The College of Business Administration (CBA) at the University of Tennessee, Knoxville, consists

  3. Optical ranked-order filtering using threshold decomposition

    DOE Patents [OSTI]

    Allebach, Jan P. (West Lafayette, IN); Ochoa, Ellen (Pleasanton, CA); Sweeney, Donald W. (Alamo, CA)

    1990-01-01

    A hybrid optical/electronic system performs median filtering and related ranked-order operations using threshold decomposition to encode the image. Threshold decomposition transforms the nonlinear neighborhood ranking operation into a linear space-invariant filtering step followed by a point-to-point threshold comparison step. Spatial multiplexing allows parallel processing of all the threshold components as well as recombination by a second linear, space-invariant filtering step. An incoherent optical correlation system performs the linear filtering, using a magneto-optic spatial light modulator as the input device and a computer-generated hologram in the filter plane. Thresholding is done electronically. By adjusting the value of the threshold, the same architecture is used to perform median, minimum, and maximum filtering of images. A totally optical system is also disclosed.

  4. Optical ranked-order filtering using threshold decomposition

    DOE Patents [OSTI]

    Allebach, J.P.; Ochoa, E.; Sweeney, D.W.

    1987-10-09

    A hybrid optical/electronic system performs median filtering and related ranked-order operations using threshold decomposition to encode the image. Threshold decomposition transforms the nonlinear neighborhood ranking operation into a linear space-invariant filtering step followed by a point-to-point threshold comparison step. Spatial multiplexing allows parallel processing of all the threshold components as well as recombination by a second linear, space-invariant filtering step. An incoherent optical correlation system performs the linear filtering, using a magneto-optic spatial light modulator as the input device and a computer-generated hologram in the filter plane. Thresholding is done electronically. By adjusting the value of the threshold, the same architecture is used to perform median, minimum, and maximum filtering of images. A totally optical system is also disclosed. 3 figs.

  5. Spectral thresholding quantum tomography for low rank states

    E-Print Network [OSTI]

    Cristina Butucea; Madalin Guta; Theodore Kypraios

    2015-04-30

    The estimation of high dimensional quantum states is an important statistical problem arising in current quantum technology applications. A key example is the tomography of multiple ions states, employed in the validation of state preparation in ion trap experiments \\cite{Haffner2005}. Since full tomography becomes unfeasible even for a small number of ions, there is a need to investigate lower dimensional statistical models which capture prior information about the state, and to devise estimation methods tailored to such models. In this paper we propose several new methods aimed at the efficient estimation of low rank states in multiple ions tomography. All methods consist in first computing the least squares estimator, followed by its truncation to an appropriately chosen smaller rank. The latter is done by setting eigenvalues below a certain "noise level" to zero, while keeping the rest unchanged, or normalising them appropriately. We show that (up to logarithmic factors in the space dimension) the mean square error of the resulting estimators scales as $r\\cdot d/N$ where $r$ is the rank, $d=2^k$ is the dimension of the Hilbert space, and $N$ is the number of quantum samples. Furthermore we establish a lower bound for the asymptotic minimax risk which shows that the above scaling is optimal. The performance of the estimators is analysed in an extensive simulations study, with emphasis on the dependence on the state rank, and the number of measurement repetitions. We find that all estimators perform significantly better that the least squares, with the "physical estimator" (which is a bona fide density matrix) slightly outperforming the other estimators.

  6. Denoising MR Spectroscopic Imaging Data with Low-Rank Approximations

    E-Print Network [OSTI]

    Do, Minh N.

    1 Denoising MR Spectroscopic Imaging Data with Low-Rank Approximations Hien M. Nguyen, Member, IEEE- temporal imaging data as well. Index Terms--MR spectroscopy, MR spectroscopic imaging, denoising, low spectroscopic (MRS) signal in (k, t)-space can be expressed as s(k, t) = (r, f)e-i2k·r e-i2ft drdf + (k, t), (1

  7. EM's Huizenga Receives Presidential Rank Award | 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:FinancingPetroleum Based|DepartmentStatementof EnergyQuality AssuranceTop1Seriesof

  8. Low-rank coal oil agglomeration product and process

    DOE Patents [OSTI]

    Knudson, C.L.; Timpe, R.C.; Potas, T.A.; DeWall, R.A.; Musich, M.A.

    1992-11-10

    A selectively-sized, raw, low-rank coal is processed to produce a low ash and relative water-free agglomerate with an enhanced heating value and a hardness sufficient to produce a non-degradable, shippable fuel. The low-rank coal is treated, under high shear conditions, in the first stage to cause ash reduction and subsequent surface modification which is necessary to facilitate agglomerate formation. In the second stage the treated low-rank coal is contacted with bridging and binding oils under low shear conditions to produce agglomerates of selected size. The bridging and binding oils may be coal or petroleum derived. The process incorporates a thermal deoiling step whereby the bridging oil may be completely or partially recovered from the agglomerate; whereas, partial recovery of the bridging oil functions to leave as an agglomerate binder, the heavy constituents of the bridging oil. The recovered oil is suitable for recycling to the agglomeration step or can serve as a value-added product.

  9. Low-rank coal oil agglomeration product and process

    DOE Patents [OSTI]

    Knudson, Curtis L. (Grand Forks, ND); Timpe, Ronald C. (Grand Forks, ND); Potas, Todd A. (Plymouth, MN); DeWall, Raymond A. (Grand Forks, ND); Musich, Mark A. (Grand Forks, ND)

    1992-01-01

    A selectively-sized, raw, low-rank coal is processed to produce a low ash and relative water-free agglomerate with an enhanced heating value and a hardness sufficient to produce a non-decrepitating, shippable fuel. The low-rank coal is treated, under high shear conditions, in the first stage to cause ash reduction and subsequent surface modification which is necessary to facilitate agglomerate formation. In the second stage the treated low-rank coal is contacted with bridging and binding oils under low shear conditions to produce agglomerates of selected size. The bridging and binding oils may be coal or petroleum derived. The process incorporates a thermal deoiling step whereby the bridging oil may be completely or partially recovered from the agglomerate; whereas, partial recovery of the bridging oil functions to leave as an agglomerate binder, the heavy constituents of the bridging oil. The recovered oil is suitable for recycling to the agglomeration step or can serve as a value-added product.

  10. My years with Rutishauser By Friedrich L. Bauer, TU Munich

    E-Print Network [OSTI]

    O'Leary, Dianne P.

    My years with Rutishauser By Friedrich L. Bauer, TU Munich February 19, 1952 Heinz Rutishauser class that I became aquainted with in the fifties, he ranks in one line with Klaus Samelson (1918

  11. IT'S BEEN 25 YEARS Twenty-five years ago, the Washington

    E-Print Network [OSTI]

    Matrajt, Graciela

    IT'S BEEN 25 YEARS Twenty-five years ago, the Washington State Legislature authorized two new UW to us by the state of Washington: to provide access to a University of Washington education@uwb.edu THE UNIVERSITY OF WASHINGTON BOTHELL opens the door to an internationally and nationally-ranked university

  12. Data mining and visualization techniques

    DOE Patents [OSTI]

    Wong, Pak Chung (Richland, WA); Whitney, Paul (Richland, WA); Thomas, Jim (Richland, WA)

    2004-03-23

    Disclosed are association rule identification and visualization methods, systems, and apparatus. An association rule in data mining is an implication of the form X.fwdarw.Y where X is a set of antecedent items and Y is the consequent item. A unique visualization technique that provides multiple antecedent, consequent, confidence, and support information is disclosed to facilitate better presentation of large quantities of complex association rules.

  13. Modified Hazard Ranking System/Hazard Ranking System for sites with mixed radioactive and hazardous wastes: Software documentation

    SciTech Connect (OSTI)

    Stenner, R.D.; Peloquin, R.A.; Hawley, K.A.

    1986-11-01

    The mHRS/HRS software package was developed by the Pacific Northwest Laboratory (PNL) under contract with the Department of Energy (DOE) to provide a uniform method for DOE facilities to use in performing their Conservation Environmental Response Compensation and Liability Act (CERCLA) Phase I Modified Hazard Ranking System or Hazard Ranking System evaluations. The program is designed to remove the tedium and potential for error associated with the performing of hand calculations and the interpreting of information on tables and in reference books when performing an evaluation. The software package is designed to operate on a microcomputer (IBM PC, PC/XT, or PC/AT, or a compatible system) using either a dual floppy disk drive or a hard disk storage system. It is written in the dBASE III language and operates using the dBASE III system. Although the mHRS/HRS software package was developed for use at DOE facilities, it has direct applicability to the performing of CERCLA Phase I evaluations for any facility contaminated by hazardous waste. The software can perform evaluations using either the modified hazard ranking system methodology developed by DOE/PNL, the hazard ranking system methodology developed by EPA/MITRE Corp., or a combination of the two. This document is a companion manual to the mHRS/HRS user manual. It is intended for the programmer who must maintain the software package and for those interested in the computer implementation. This manual documents the system logic, computer programs, and data files that comprise the package. Hardware and software implementation requirements are discussed. In addition, hand calculations of three sample situations (problems) with associated computer runs used for the verification of program calculations are included.

  14. West Virginia University 1 Department of Mining Engineering

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    an ability to learn independently Professional technical courses include surface and underground mining, mining equipment, coal and mineral preparation, plant and mine design, geology, and water control of the operation of a mining enterprise. Local coal fields, mines, and preparation plants provide extensive

  15. West Virginia University 1 Department of Mining Engineering

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    include surface and underground mining, rock mechanics and ground control, mine health and safety, mineral/coal · Vladislav Kecojevic - Ph.D. (University of Belgrade) Surface Mining, Aggregates Production, Mine MaterialsWest Virginia University 1 Department of Mining Engineering Degrees Offered · Masters of Science

  16. Mining withdrawals by water quality and State, 2005. EXPLANATION

    E-Print Network [OSTI]

    Mining withdrawals by water quality and State, 2005. 0 to 10 10 to 50 50 to 100 100 to 200 200 mining withdrawals Freshwater mining withdrawals Saline-water mining withdrawals Estimated Use of Water in the United States in 2005 - Mining USGS Water-Science School -- http://ga.water.usgs.gov/edu/wumi.html Source

  17. Legacy of historic mining and water quality in a heavily mined Scottish river catchment 

    E-Print Network [OSTI]

    Haunch, Simon

    2013-11-28

    Mine abandonment and the discharge of contaminated mine water is recognised globally as a major source of surface water and groundwater pollution. Contamination generally arises from the oxidation of sulphide minerals, ...

  18. ITP Mining: Mining Industry of the Future Mineral Processing Technology Roadmap

    Office of Energy Efficiency and Renewable Energy (EERE)

    In June 1998, the Chairman of the National Mining Association and the Secretary of energy entered into a Compact to pursue a collaborative technology research partnership, the Mining Industry of the Future.

  19. Injury experience in coal mining, 1990

    SciTech Connect (OSTI)

    1991-01-01

    This Mine Safety and Health Administration (MSHA) informational report reviews in detail the occupational injury and illness experience of coal mining in the United States for 1990. Data reported by operators of mining establishments concerning work injuries are summarized by work location, accident classification, part of body injured, nature of injury, occupation, and anthracite or bituminous coal. Related information on employment, worktime, and operating activity also is presented. Data reported by independent contractors performing certain work at mining locations are depicted separately in this report. For ease of comparison between coal mining and the metal and nonmetal mineral mining industries, summary reference tabulations are included at the end of both the operator and the contractor sections of this report.

  20. Injury experience in metallic mineral mining, 1992

    SciTech Connect (OSTI)

    Not Available

    1994-05-01

    This Mine Safety and Health Administration (MSHA) informational report reviews in detail the occupational injury and illness experience of metallic mineral mining in the United States for 1992. Data reported by operators of mining establishments concerning work injuries are summarized by work location, accident classification, part of body injured, nature of injury, occupation, and principal type of mineral. Related information on employment, worktime, and operating activity also is presented. Data reported by independent contractors performing certain work at mining locations are depicted separately in this report. For ease of comparison with other metal and nonmetallic mineral mining industries and with coal mining, summary reference tabulations are included at the end of both the operator and the contractor sections of this report.

  1. Trace element patterns in lichens following uranium mine closures

    SciTech Connect (OSTI)

    Fahselt, D.; Wu, T.W.; Mott, B. [Univ. of Western Ontario, London (Canada)

    1995-09-01

    Instrumental neutron activation analysis was used to determine trace elements in Cladina mitis (Sandst). Hale & Culb. along transects extending from uranium mines at Elliot Lake and Agnew Lake in central Ontario, Canada. Levels of 11 elements were reported and the presence of uranium (U) was confirmed, although U concentrations were much less than in Cladina rangiferina 10 years earlier. Among the elements identified in lichen thalli was Th, which occurred in higher concentrations than U. All trace elements, including the two radionuclides, were found in deteriorating thallus parts as well as living podetia, and five of these seem to have originated as airborne particulates from minesites. In spite of mine closures, levels of Th and U remained higher near sources of ore dust and there was little relationship between radionuclide concentrations in thallus and substrate. 24 refs., 4 figs., 3 tabs.

  2. Data Mining et Statistique Philippe Besse

    E-Print Network [OSTI]

    Besse, Philippe

    Data Mining et Statistique Philippe Besse , Caroline Le Gall , Nathalie Raimbault & Sophie Sarpy§ R´esum´e Cet article propose une introduction au Data Mining. Celle-ci prend la forme d'une r´eflexion sur les quelques ensei- gnements sur les pratiques du data mining : choix d'une m´ethode, comp´etences de l

  3. The Dona Maria Mining and Milling Company

    E-Print Network [OSTI]

    Blackmar, Frank H.

    1912-06-01

    KU ScholarWorks | The University of Kansas Pre-1923 Dissertations and Theses Collection The Dona Maria Mining and Milling Company 1912 by Frank Hollister Blackmar This work was digitized by the Scholarly Communications program staff in the KU... Libraries’ Center for Digital Scholarship. http://kuscholarworks.ku.edu A thesis submitted to the department of Mining Engineering of the University of Kansas in partial fulfillment of the requirements for the degree of Mining Engineer. rJj, •» Jf* T3E...

  4. Mining Industry Profile | Department of Energy

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

    utilities, the primary metals industry, non-metallic minerals industry (glass, cement, lime), and the construction industry. Employment Mining operations are often the leading...

  5. Enterprise Assessments Review of Mine Safety, Stabilization,...

    Energy Savers [EERE]

    with the limited available airflows in the mine, and the status and condition of emergency escape and evacuation systems. Nuclear Waste Partnership, LLC (NWP), the...

  6. The LSST Data Mining Research Agenda

    E-Print Network [OSTI]

    K. D. Borne; J. Becla; I. Davidson; A. Szalay; J. A. Tyson

    2008-11-02

    We describe features of the LSST science database that are amenable to scientific data mining, object classification, outlier identification, anomaly detection, image quality assurance, and survey science validation. The data mining research agenda includes: scalability (at petabytes scales) of existing machine learning and data mining algorithms; development of grid-enabled parallel data mining algorithms; designing a robust system for brokering classifications from the LSST event pipeline (which may produce 10,000 or more event alerts per night); multi-resolution methods for exploration of petascale databases; indexing of multi-attribute multi-dimensional astronomical databases (beyond spatial indexing) for rapid querying of petabyte databases; and more.

  7. Intelligent Simulation Tools for Mining Large Scienti c Data Sets 1 Intelligent Simulation Tools for Mining

    E-Print Network [OSTI]

    Bailey-Kellogg, Chris

    Intelligent Simulation Tools for Mining Large Scienti#12;c Data Sets 1 Intelligent Simulation Tools for Mining Large Scienti#12;c Data Sets Feng ZHAO Xerox Palo Alto Research Center 3333 Coyote Hill Road, Palo. Keywords Intelligent simulation, Scienti#12;c data mining, Qualitative reasoning, Reasoning about physical

  8. CHEN, LOY, GONG, XIANG: FEATURE MINING FOR LOCALISED CROWD COUNTING 1 Feature Mining for Localised Crowd

    E-Print Network [OSTI]

    Gong, Shaogang

    CHEN, LOY, GONG, XIANG: FEATURE MINING FOR LOCALISED CROWD COUNTING 1 Feature Mining for Localised Crowd Counting Ke Chen1 cory@eecs.qmul.ac.uk Chen Change Loy2 ccloy@visionsemantics.com Shaogang Gong1 in print or electronic forms. #12;2 CHEN, LOY, GONG, XIANG: FEATURE MINING FOR LOCALISED CROWD COUNTING

  9. Discoveries far from the lamppost with matrix elements and ranking

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

    Debnath, Dipsikha; Gainer, James S.; Matchev, Konstantin T.

    2015-04-01

    The prevalence of null results in searches for new physics at the LHC motivates the effort to make these searches as model-independent as possible. We describe procedures for adapting the Matrix Element Method for situations where the signal hypothesis is not known a priori. We also present general and intuitive approaches for performing analyses and presenting results, which involve the flattening of background distributions using likelihood information. The first flattening method involves ranking events by background matrix element, the second involves quantile binning with respect to likelihood (and other) variables, and the third method involves reweighting histograms by the inversemore »of the background distribution.« less

  10. Discoveries far from the lamppost with matrix elements and ranking

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

    Debnath, Dipsikha; Gainer, James S.; Matchev, Konstantin T.

    2015-04-01

    The prevalence of null results in searches for new physics at the LHC motivates the effort to make these searches as model-independent as possible. We describe procedures for adapting the Matrix Element Method for situations where the signal hypothesis is not known a priori. We also present general and intuitive approaches for performing analyses and presenting results, which involve the flattening of background distributions using likelihood information. The first flattening method involves ranking events by background matrix element, the second involves quantile binning with respect to likelihood (and other) variables, and the third method involves reweighting histograms by the inverse of the background distribution.

  11. Asymptotics of spherical superfunctions on rank one Riemannian symmetric superspaces

    E-Print Network [OSTI]

    Alexander Alldridge; Wolfgang Palzer

    2014-11-21

    We compute the Harish-Chandra $c$-function for a generic class of rank-one purely non-compact Riemannian symmetric superspaces $X=G/K$ in terms of Euler $\\Gamma$ functions, proving that it is meromorphic. Compared to the even case, the poles of the $c$-function are shifted into the right half-space. We derive the full asymptotic Harish-Chandra series expansion of the spherical superfunctions on $X$. In the case where the multiplicity of the simple root is an even negative number, they have a closed expression as Jacobi polynomials for an unusual choice of parameters.

  12. Robust Learning from Bites for Data Mining Andreas Christmann

    E-Print Network [OSTI]

    Robust Learning from Bites for Data Mining Andreas Christmann Vrije Universiteit Brussel minimization, data mining, distributed computing, influence function, logistic regression, robustness management, respectively. Other examples are large observational data sets in data mining projects and data

  13. Astroinformatics, data mining and the future of astronomical research

    E-Print Network [OSTI]

    Longo, Giuseppe

    Astroinformatics, data mining and the future of astronomical research Massimo Bresciaa , Giuseppe the implementation of advanced data mining procedures. The complexity of astronomical data and the variety of ICT technologies. Keywords: astroinformatics, Data Mining, virtual organizations 1. Introduction

  14. Data Mining for Improving Health-Care Resource Deployment

    E-Print Network [OSTI]

    He, Nannan

    2014-01-01

    model establishments and data mining algorithm application.a comparison of three data mining methods. ArtificialIan H.Witten, E. F. (2011). Data Mining:Practical Machine

  15. Data Mining and Internet Profiling: Emerging Regulatory and Technological Approaches

    E-Print Network [OSTI]

    Schwartz, Paul M.; Lee, Ronald D.; Rubinstein, Ira

    2008-01-01

    creep,” see Mary DeRosa, Data Mining and Data Analysis for29 DeRosa, Data Mining and Data Analysis at 19 (cited in31 See DeRosa, Data Mining and Data Analysis at 17–18 (cited

  16. Text mining for user perspectives on the physical workplace

    E-Print Network [OSTI]

    Goins, John; Moezzi, Mithra

    2011-01-01

    Goins, John (2011) 'Text mining for occupant perspectives onGoins, John (2011) 'Text mining for occupant perspectives onGoins, John (2011) 'Text mining for occupant perspectives on

  17. Data Mining and Internet Profiling: Emerging Regulatory and Technological Approaches

    E-Print Network [OSTI]

    Schwartz, Paul M.; Lee, Ronald D.; Rubinstein, Ira

    2008-01-01

    of consensus safeguards around government data mining tocommercial data mining, the extent and speed of ad- funded2/19/2008 3:00:00 PM Data Mining and Internet Profiling:

  18. Integrated network construction using event based text mining

    E-Print Network [OSTI]

    Gent, Universiteit

    Integrated network construction using event based text mining Yvan Saeys, Sofie Van Landeghem numerous interactions between biological entities. Text mining techniques have been increasingly useful mining in the systems biology field has been restricted mostly to the discovery of protein

  19. Mercury-Contaminated Hydraulic Mining Debris in San Francisco Bay

    E-Print Network [OSTI]

    Bouse, Robin M; Fuller, Christopher C; Luoma, Sam; Hornberger, Michelle I; Jaffe, Bruce E; Smith, Richard E

    2010-01-01

    may 2010 Mercury-Contaminated Hydraulic Mining Debris in SanCA 94025 Abstract The hydraulic gold-mining process usedsediment created by hydraulic gold mining in the Sierra

  20. Distributed Multivariate Regression Using Wavelet-based Collective Data Mining.

    E-Print Network [OSTI]

    Kargupta, Hilol

    Distributed Multivariate Regression Using Wavelet-based Collective Data Mining. Daryl E a method for distributed multivariate regression using wavelet- based Collective Data Mining (CDM employed in parametric multivariate regression to provide an effective data mining technique for use

  1. The Alta Mine: A Multidisciplinary Analysis of an Acid

    E-Print Network [OSTI]

    Maxwell, Bruce D.

    i #12;The Alta Mine: A Multidisciplinary Analysis of an Acid Mine Drainage Environment LRES 442, and environmental microbiology; all disciplines highly appropriate to the study of acid mine/rock drainage

  2. MODELING OF STATIC MINING SUBSIDENCE IN A NONLINEAR MEDIUM

    E-Print Network [OSTI]

    Ratigan, J.L.

    2013-01-01

    Finite Element Program for Static Evaluation of MiningAugust 3-6, 1981 MODELING OF STATIC MINING SUBSIDENCE IN ALBL-11896 MODELING OF STATIC MINING SUBSIDENCE IN A

  3. Data Mining and Internet Profiling: Emerging Regulatory and Technological Approaches

    E-Print Network [OSTI]

    Schwartz, Paul M.; Lee, Ronald D.; Rubinstein, Ira

    2008-01-01

    17 DHS Privacy Office, Data Mining Report: DHS Privacyfor data mining programs, the DHS Privacy Office requestedOffice has argued, strong data quality standards should be adopted for all information used in data mining.

  4. Y YEAR

    National Nuclear Security Administration (NNSA)

    2 40 -4.76% YEAR 2013 2014 Males 37 35 -5.41% Females 5 5 0% YEAR 2013 2014 SES 2 2 0% EJEK 5 4 -20.00% EN 05 5 7 40.00% EN 04 6 6 0% EN 03 1 1 0% NN...

  5. Y YEAR

    National Nuclear Security Administration (NNSA)

    79 67 -15.19% YEAR 2013 2014 Males 44 34 -22.73% Females 35 33 -5.71% YEAR 2013 2014 SES 6 4 -33.33% EJEK 1 1 0% EN 05 9 8 -11.11% EN 04 6 5 -16.67% NN...

  6. Hydrologic and Aquatic Species Implications of the Proposed Pebble Mine, Bristol Bay, Alaska

    E-Print Network [OSTI]

    Cundy, Fiona

    2012-01-01

    causing  acid  mine  drainage   (Moran  2007).     Problem  potential  for  acid  mine  drainage,  due  to  the   high  

  7. CO2 Sequestration Potential of Texas Low-Rank Coals

    SciTech Connect (OSTI)

    Duane McVay; Walter Ayers, Jr.; Jerry Jensen; Jorge Garduno; Gonzola Hernandez; Rasheed Bello; Rahila Ramazanova

    2006-08-31

    Injection of CO{sub 2} in coalbeds is a plausible method of reducing atmospheric emissions of CO{sub 2}, and it can have the additional benefit of enhancing methane recovery from coal. Most previous studies have evaluated the merits of CO{sub 2} disposal in high-rank coals. The objective of this research was to determine the technical and economic feasibility of CO{sub 2} sequestration in, and enhanced coalbed methane (ECBM) recovery from, low-rank coals in the Texas Gulf Coast area. Our research included an extensive coal characterization program, including acquisition and analysis of coal core samples and well transient test data. We conducted deterministic and probabilistic reservoir simulation and economic studies to evaluate the effects of injectant fluid composition (pure CO{sub 2} and flue gas), well spacing, injection rate, and dewatering on CO{sub 2} sequestration and ECBM recovery in low-rank coals of the Calvert Bluff formation of the Texas Wilcox Group. Shallow and deep Calvert Bluff coals occur in two, distinct, coalbed gas petroleum systems that are separated by a transition zone. Calvert Bluff coals < 3,500 ft deep are part of a biogenic coalbed gas system. They have low gas content and are part of a freshwater aquifer. In contrast, Wilcox coals deeper than 3,500 ft are part of a thermogenic coalbed gas system. They have high gas content and are part of a saline aquifer. CO{sub 2} sequestration and ECBM projects in Calvert Bluff low-rank coals of East-Central Texas must be located in the deeper, unmineable coals, because shallow Wilcox coals are part of a protected freshwater aquifer. Probabilistic simulation of 100% CO{sub 2} injection into 20 feet of Calvert Bluff coal in an 80-acre 5-spot pattern indicates that these coals can store 1.27 to 2.25 Bcf of CO{sub 2} at depths of 6,200 ft, with an ECBM recovery of 0.48 to 0.85 Bcf. Simulation results of flue gas injection (87% N{sub 2}-13% CO{sub 2}) indicate that these same coals can store 0.34 to 0.59 Bcf of CO{sub 2} with an ECBM recovery of 0.68 to 1.20 Bcf. Economic modeling of CO{sub 2} sequestration and ECBM recovery indicates predominantly negative economic indicators for the reservoir depths (4,000 to 6,200 ft) and well spacings investigated, using natural gas prices ranging from $2 to $12 per Mscf and CO{sub 2} credits based on carbon market prices ranging from $0.05 to $1.58 per Mscf CO{sub 2} ($1.00 to $30.00 per ton CO{sub 2}). Injection of flue gas (87% N{sub 2} - 13% CO{sub 2}) results in better economic performance than injection of 100% CO{sub 2}. CO{sub 2} sequestration potential and methane resources in low-rank coals of the Lower Calvert Bluff formation in East-Central Texas are significant. The potential CO{sub 2} sequestration capacity of the coals ranges between 27.2 and 49.2 Tcf (1.57 and 2.69 billion tons), with a mean value of 38 Tcf (2.2 billion tons), assuming a 72.4% injection efficiency. Estimates of recoverable methane resources range between 6.3 and 13.6 Tcf, with a mean of 9.8 Tcf, assuming a 71.3% recovery factor. Moderate increases in gas prices and/or carbon credits could generate attractive economic conditions that, combined with the close proximity of many CO{sub 2} point sources near unmineable coalbeds, could enable commercial CO{sub 2} sequestration and ECBM projects in Texas low-rank coals. Additional studies are needed to characterize Wilcox regional methane coalbed gas systems and their boundaries, and to assess potential of other low-rank coal beds. Results from this study may be transferable to other low-rank coal formations and regions.

  8. Student ID Advisor 1st Year Fall __________ (year) 1st Year Spr. __________ (year) 1st Year Sum. __________ (year)

    E-Print Network [OSTI]

    Barrash, Warren

    . HRS. 2nd Year Fall __________ (year) 2nd Year Spr. _________ (year) 2nd Year Sum. _________ (yearName Major Student ID Advisor 1st Year Fall __________ (year) 1st Year Spr. __________ (year) 1st Year Sum. __________ (year) SUBJECT COURSE # CR. HRS. SUBJECT COURSE # CR. HRS. SUBJECT COURSE # CR

  9. DAME: a Web Oriented Infrastructure for Scientific Data Mining & Exploration

    E-Print Network [OSTI]

    Longo, Giuseppe

    DAME: a Web Oriented Infrastructure for Scientific Data Mining & Exploration Massimo Bresciaa (DAta Mining & Exploration) is an innovative, general purpose, Web-based, VObs compliant, distributed

  10. COST AND SCHEDULE FOR DRILLING AND MINING UNDERGROUND TEST FACILITIES

    E-Print Network [OSTI]

    Lamb, D.W.

    2013-01-01

    3.2 - Surface Drilling ------------------------------ COSTNumber In-Mine Drilling Program Cost Estimate for Case 1 -Development In-Mine Drilling The cost and time required for

  11. Program Distinctions U.S. News & World Report Ranking: #11 MBA Supply Chain Program, nationwide, (2015)

    E-Print Network [OSTI]

    Neimark, Alexander V.

    2015-01-01

    ) American Pharmaceuticals-Global Transportation Organization (GTO) (D. Klock) Managing the Outsourced Report Ranking (SCM/Operations Management Specialty): #20 (2013) Gartner SCM Program Ranking: #9 Management (ISM) scholarships (2011-2015) Council of Supply Chain Management Professionals (CSCMP

  12. Data mining for ontology development.

    SciTech Connect (OSTI)

    Davidson, George S.; Strasburg, Jana; Stampf, David; Neymotin,Lev; Czajkowski, Carl; Shine, Eugene; Bollinger, James; Ghosh, Vinita; Sorokine, Alexandre; Ferrell, Regina; Ward, Richard; Schoenwald, David Alan

    2010-06-01

    A multi-laboratory ontology construction effort during the summer and fall of 2009 prototyped an ontology for counterfeit semiconductor manufacturing. This effort included an ontology development team and an ontology validation methods team. Here the third team of the Ontology Project, the Data Analysis (DA) team reports on their approaches, the tools they used, and results for mining literature for terminology pertinent to counterfeit semiconductor manufacturing. A discussion of the value of ontology-based analysis is presented, with insights drawn from other ontology-based methods regularly used in the analysis of genomic experiments. Finally, suggestions for future work are offered.

  13. Department of Geophysics Colorado School of Mines

    E-Print Network [OSTI]

    Department of Geophysics Colorado School of Mines Golden, CO 80401 http://www.geophysics;#12;Department of Geophysics Colorado School of Mines Golden, CO 80401 http://www.geophysics of the requirements for the degree of Master of Science (Geophysics). Golden, Colorado Date: April 14, 2005 Signed

  14. COLORADO SCHOOL OF MINES PERFORMANCE MANAGEMENT PROGRAM

    E-Print Network [OSTI]

    change, the Colorado School of Mine's (CSM) Performance Management Steering Committee was established Program to be effective for the performance management cycle beginning April 1, 2007. Further changes1 COLORADO SCHOOL OF MINES PERFORMANCE MANAGEMENT PROGRAM Revised October 1, 2008 I. HISTORY Since

  15. COLORADO SCHOOL OF MINES PERFORMANCE MANAGEMENT PROGRAM

    E-Print Network [OSTI]

    1 COLORADO SCHOOL OF MINES PERFORMANCE MANAGEMENT PROGRAM Revised October 1, 2008 I. HISTORY Since change, the Colorado School of Mine's (CSM) Performance Management Steering Committee was established the administration in the development and implementation of the School's Performance Pay Program. The original

  16. Visual Web Mining Amir H. Youssefi

    E-Print Network [OSTI]

    Bystroff, Chris

    Visual Web Mining Amir H. Youssefi Rensselaer Polytechnic Institute 110 Eight St. Troy, NY 12180 Rensselaer Polytechnic Institute 110 Eight St. Troy, NY 12180 zaki@cs.rpi.edu ABSTRACT Analysis of web site of the web, and secondly, the structural complexity of web sites. In this paper we apply Data Mining

  17. WEB MINING: A ROADMAP Magdalini Eirinaki

    E-Print Network [OSTI]

    Eirinaki, Magdalini

    1 WEB MINING: A ROADMAP Magdalini Eirinaki Dept. of Informatics Athens University of Economics and Business CHAPTER 1 Introduction ­ The three axes of Web Mining 1.1 WWW Impact The World Wide Web, has grown of the Web content, the creation of some meta- knowledge out of the information which is available on the Web

  18. Data Mining and Knowledge Discovery: Practice Notes

    E-Print Network [OSTI]

    Novak, Petra Kralj

    1 Data Mining and Knowledge Discovery: Practice Notes dr. Petra Kralj Novak Petra.Kralj.Novak@ijs.si and exam · 2013/12/16: Written exam, seminar proposal discussion · 2014/1/8: Data mining seminar gain becomes the root 7. Divide the set S into subsets Si according to the values of A 8. Repeat steps

  19. Jon Espen Ingvaldsen Semantic Process Mining of

    E-Print Network [OSTI]

    Planning (ERP) systems are commonly stated in research as promising areas for process mining. ERP systems have conducted studies on applying process mining techniques on real life ERP transaction data and we and interpret ERP transaction data? RQ2. Can reliable business process traces be extracted from large

  20. Mining Binary Expressions: Applications and Toon Calders

    E-Print Network [OSTI]

    Antwerpen, Universiteit

    Mining Binary Expressions: Applications and Algorithms Toon Calders Jan Paredaens Universiteit Antwerpen, Departement Wiskunde-Informatica, Universiteitsplein 1, B-2610 Wilrijk, Belgium. {calders,pareda}@uia.ua.ac.be Technical report TR0008, June 2000 Abstract In data mining, searching for frequent patterns is a common

  1. Mining Train Delays Boris Cule1

    E-Print Network [OSTI]

    Antwerpen, Universiteit

    Mining Train Delays Boris Cule1 , Bart Goethals1 , Sven Tassenoy2 , and Sabine Verboven2,1 1, Belgium 2 INFRABEL - Network, Department of Innovation, Barastraat 110, 1070 Brussels, Belgium Keywords Pattern Mining, Data Analysis, Train Delays Abstract The Belgian railway network has a high traffic

  2. Technical Report Mining Interesting Sets and Rules

    E-Print Network [OSTI]

    Antwerpen, Universiteit

    Technical Report 09.02 Mining Interesting Sets and Rules in Relational Databases Bart Goethals, Wim Middelheimlaan 1 B-2020 Antwerp ­ Belgium #12;1 Abstract In this paper we propose a new and elegant approach toward the generalization of frequent itemset mining to the multi-relational case. We define relational

  3. CAS CS 565, Data Mining Course logistics

    E-Print Network [OSTI]

    Terzi, Evimaria

    CAS CS 565, Data Mining #12;Course logistics · Course webpage: ­ http://www.cs.bu.edu/~evimaria/cs565-11.html · Schedule: Mon ­ Wed, 2:30-4:00 · Instructor: Evimaria Terzi, evimaria@cs.bu.edu · Office@bu.edu #12;Topics to be covered (tentative) · Introduction to data mining and prototype problems · Frequent

  4. Marine Traffic Engineering through Relational Data Mining

    E-Print Network [OSTI]

    Ceci, Michelangelo

    Marine Traffic Engineering through Relational Data Mining Antonio Bruno1 and Annalisa Appice1,2 1-relational method of frequent pattern discovery into the marine traffic investigation. Multi-relational data mining collected in the gulf of Taranto. 1 Introduction Marine traffic engineering is a research field originally

  5. Low Rank Solutions of Time Dependent Stochastic PDEs Alessio Spantini1

    E-Print Network [OSTI]

    de Weck, Olivier L.

    Low Rank Solutions of Time Dependent Stochastic PDEs Alessio Spantini1 Advisors: Lionel Mathelin2/29/2013 Spantini (MIT) Low Rank Solutions of SPDE ACDL Quals 1 / 20 #12;Outline 1 Motivation 2 General Formulation and Methodology 3 Numerical Example 4 Conclusions Spantini (MIT) Low Rank Solutions of SPDE ACDL Quals 2 / 20 #12

  6. Ranking Bias in Deep Web Size Estimation Using Capture Recapture Method

    E-Print Network [OSTI]

    Lu, Jianguo

    Ranking Bias in Deep Web Size Estimation Using Capture Recapture Method Jianguo Lu Preprint submitted to Elsevier March 12, 2010 #12;Ranking Bias in Deep Web Size Estimation Using Capture Recapture, Canada. email: jlu@uwindsor.ca Abstract Many deep web data sources are ranked data sources, i

  7. Ranking Structured Documents: A Large Margin Based Approach for Patent Prior Art Search

    E-Print Network [OSTI]

    Gomes, Carla P.

    Ranking Structured Documents: A Large Margin Based Approach for Patent Prior Art Search Yunsong Guo propose an approach for automatically rank- ing structured documents applied to patent prior art search. Our model, SVM Patent Ranking (SVMP R) incorporates margin constraints that di- rectly capture

  8. POP: Person Re-Identification Post-Rank Optimisation Chunxiao Liu1

    E-Print Network [OSTI]

    Huang, Jianwei

    POP: Person Re-Identification Post-Rank Optimisation Chunxiao Liu1 , Chen Change Loy2 , Shaogang-rank OPtimisation (POP) method, which allows a user to quickly refine their search by either "one-shot" or a couple- of-the-art distance metric learning based ranking models, even with just "one shot" feedback

  9. Low-rank coal research: Volume 3, Combustion research: Final report. [Great Plains

    SciTech Connect (OSTI)

    Mann, M. D.; Hajicek, D. R.; Zobeck, B. J.; Kalmanovitch, D. P.; Potas, T. A.; Maas, D. J.; Malterer, T. J.; DeWall, R. A.; Miller, B. G.; Johnson, M. D.

    1987-04-01

    Volume III, Combustion Research, contains articles on fluidized bed combustion, advanced processes for low-rank coal slurry production, low-rank coal slurry combustion, heat engine utilization of low-rank coals, and Great Plains Gasification Plant. These articles have been entered individually into EDB and ERA. (LTN)

  10. Statistically significant relational data mining :

    SciTech Connect (OSTI)

    Berry, Jonathan W.; Leung, Vitus Joseph; Phillips, Cynthia Ann; Pinar, Ali; Robinson, David Gerald; Berger-Wolf, Tanya; Bhowmick, Sanjukta; Casleton, Emily; Kaiser, Mark; Nordman, Daniel J.; Wilson, Alyson G.

    2014-02-01

    This report summarizes the work performed under the project (3z(BStatitically significant relational data mining.(3y (BThe goal of the project was to add more statistical rigor to the fairly ad hoc area of data mining on graphs. Our goal was to develop better algorithms and better ways to evaluate algorithm quality. We concetrated on algorithms for community detection, approximate pattern matching, and graph similarity measures. Approximate pattern matching involves finding an instance of a relatively small pattern, expressed with tolerance, in a large graph of data observed with uncertainty. This report gathers the abstracts and references for the eight refereed publications that have appeared as part of this work. We then archive three pieces of research that have not yet been published. The first is theoretical and experimental evidence that a popular statistical measure for comparison of community assignments favors over-resolved communities over approximations to a ground truth. The second are statistically motivated methods for measuring the quality of an approximate match of a small pattern in a large graph. The third is a new probabilistic random graph model. Statisticians favor these models for graph analysis. The new local structure graph model overcomes some of the issues with popular models such as exponential random graph models and latent variable models.

  11. Ranking of sabotage/tampering avoidance technology alternatives

    SciTech Connect (OSTI)

    Andrews, W.B.; Tabatabai, A.S.; Powers, T.B.; Daling, P.M.; Fecht, B.A.; Gore, B.F.; Overcast, T.D.; Rankin, W.R.; Schreiber, R.E.; Tawil, J.J.

    1986-01-01

    Pacific Northwest Laboratory conducted a study to evaluate alternatives to the design and operation of nuclear power plants, emphasizing a reduction of their vulnerability to sabotage. Estimates of core melt accident frequency during normal operations and from sabotage/tampering events were used to rank the alternatives. Core melt frequency for normal operations was estimated using sensitivity analysis of results of probabilistic risk assessments. Core melt frequency for sabotage/tampering was estimated by developing a model based on probabilistic risk analyses, historic data, engineering judgment, and safeguards analyses of plant locations where core melt events could be initiated. Results indicate the most effective alternatives focus on large areas of the plant, increase safety system redundancy, and reduce reliance on single locations for mitigation of transients. Less effective options focus on specific areas of the plant, reduce reliance on some plant areas for safe shutdown, and focus on less vulnerable targets.

  12. GRADUATE POPULATION: Spring, 2014 First Year Second Year Third Year Fourth Year Fifth Year DCE Status*

    E-Print Network [OSTI]

    GRADUATE POPULATION: Spring, 2014 First Year Second Year Third Year Fourth Year Fifth Year DCE Program ABX = DCE Absentia *DCE status is assigned to post-5th year enrolled students, whether still 2.5 years) VSRCs: Christine Angel Mc Lauren de Riordan mclderio@princeton.edu (7/31/13 ­ 6

  13. GRADUATE POPULATION: Fall, 2014 First Year Second Year Third Year Fourth Year Fifth Year DCE Status*

    E-Print Network [OSTI]

    Singh, Jaswinder Pal

    GRADUATE POPULATION: Fall, 2014 First Year Second Year Third Year Fourth Year Fifth Year DCE Status Nathaniel (Nat) Tabris Daniel Wolt (Grad Rep) *DCE status is assigned to post-5th year enrolled students Program ABX = DCE Absentia ON LEAVE: Josh O'Rourke (Fall 2014; completed 2.5 years) VSRC: Neil Dewar

  14. Ranking on Cross Domain Manifold forRanking on Cross-Domain Manifold for Sketch-based 3D model Retrieval

    E-Print Network [OSTI]

    Ohbuchi, Ryutarou

    printers,... ­ User generated. T i bl 3D h· Trimble 3D warehouse... 3D model retrieval is essentialRanking on Cross Domain Manifold forRanking on Cross-Domain Manifold for Sketch-based 3D model Retrieval Takahiko FuruyaRyutarou Ohbuchi University of Yamanashi #12;IntroductionIntroduction 3D models

  15. Ranking on Cross Domain Manifold forRanking on Cross-Domain Manifold for Sketch-based 3D model Retrieval

    E-Print Network [OSTI]

    Ohbuchi, Ryutarou

    printers,... ­ User generated. T i bl 3D h· Trimble 3D warehouse... 3D model retrieval is essential scanners, 3D printers,... ­ User generated. T i bl 3D h· Trimble 3D warehouse... 3D model retrievalRanking on Cross Domain Manifold forRanking on Cross-Domain Manifold for Sketch-based 3D model

  16. Low rank positive partial transpose states and their relation to product vectors

    E-Print Network [OSTI]

    Leif Ove Hansen; Andreas Hauge; Jan Myrheim; Per Øyvind Sollid

    2011-04-08

    It is known that entangled mixed states that are positive under partial transposition (PPT states) must have rank at least four. In a previous paper we presented a classification of rank four entangled PPT states which we believe to be complete. In the present paper we continue our investigations of the low rank entangled PPT states. We use perturbation theory in order to construct rank five entangled PPT states close to the known rank four states, and in order to compute dimensions and study the geometry of surfaces of low rank PPT states. We exploit the close connection between low rank PPT states and product vectors. In particular, we show how to reconstruct a PPT state from a sufficient number of product vectors in its kernel. It may seem surprising that the number of product vectors needed may be smaller than the dimension of the kernel.

  17. Soil microbial biomass: an estimator of soil development in reclaimed lignite mine soil 

    E-Print Network [OSTI]

    Swanson, Eric Scott

    1996-01-01

    A two-year study was conducted at the Big Brown lignite mine in Fairfield, Texas, to determine the rate and extent of recovery of the soil microbial biomass (SMB) in mixed overburden. The relationships between SMB carbon (SMBC), basal respiration...

  18. Method of underground mining by pillar extraction

    DOE Patents [OSTI]

    Bowen, Ray J. (1879 Delann, Salt Lake City, UT 84121); Bowen, William R. (1636 Sunnydale La., Salt Lake City, UT 84108)

    1980-08-12

    A method of sublevel caving and pillar and top coal extraction for mining thick coal seams includes the advance mining of rooms and crosscuts along the bottom of a seam to a height of about eight feet, and the retreat mining of the top coal from the rooms, crosscuts and portions of the pillars remaining from formation of the rooms and cross-cuts. In the retreat mining, a pocket is formed in a pillar, the top coal above the pocket is drilled, charged and shot, and then the fallen coal is loaded by a continuous miner so that the operator remains under a roof which has not been shot. The top coal from that portion of the room adjacent the pocket is then mined, and another pocket is formed in the pillar. The top coal above the second pocket is mined followed by the mining of the top coal of that portion of the room adjacent the second pocket, all by use of a continuous miner which allows the operator to remain under a roof portion which has not been shot.

  19. Activity Identification Utilizing Data Mining Techniques Jae Young Lee

    E-Print Network [OSTI]

    Hoff, William A.

    Activity Identification Utilizing Data Mining Techniques Jae Young Lee Dept. of Math. and Computer belong to. The proposed method utilizes various data mining techniques, including clustering Sciences Colorado School of Mines Golden, Colorado, USA jaelee@mines.edu William Hoff Engineering Division

  20. Data Privacy and Data Security Introduction to Data Mining

    E-Print Network [OSTI]

    Zhang, Jun

    Data Privacy and Data Security Chapter 1 Introduction to Data Mining Jun Zhang January 13, 2011 © Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 1 #12;Why Mine Data? Commercial Viewpoint ) © Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 2 Customer Relationship Management) #12;Why

  1. PERFORMANCE EVALUATION AND CHARACTERIZATION OF SCALABLE DATA MINING ALGORITHMS

    E-Print Network [OSTI]

    PERFORMANCE EVALUATION AND CHARACTERIZATION OF SCALABLE DATA MINING ALGORITHMS Ying Liu, choudhar}@ece.northwestern.edu ABSTRACT Data mining has become one of the most essential tools in diverse perspectives for a set of representative data mining programs. We first design MineBench, a benchmarking suite

  2. Off Earth Mining Forum 19-21 February 2013

    E-Print Network [OSTI]

    Sekercioglu, Y. Ahmet

    1 Off Earth Mining Forum 19-21 February 2013 www.acser.unsw.edu.au/oemf Never Stand Still Faculty of Engineering Australian Centre for Space Engineering Research (ACSER) #12;Off Earth Mining Forum, UNSW, Sydney Australia's place in space. Off Earth Mining Forum Sponsors Off Earth Mining Forum The prospect of people

  3. DATA MINING AT THE INTERFACE OF COMPUTER SCIENCE AND STATISTICS

    E-Print Network [OSTI]

    Smyth, Padhraic

    Chapter 1 DATA MINING AT THE INTERFACE OF COMPUTER SCIENCE AND STATISTICS Padhraic Smyth a better understanding of the role of statistical thinking in modern data mining. Data mining has at and highlights the fundamental di erences between statistical and computational views of data mining. In do- ing

  4. Data mining for Action Recognition Andrew Gilbert Richard Bowden

    E-Print Network [OSTI]

    Bowden, Richard

    Data mining for Action Recognition Andrew Gilbert Richard Bowden Centre for Vision Speech of the features used. This paper improves the performance of action recognition through two data mining techniques, APriori association rule mining and Contrast Set Mining. These tech- niques are ideally suited to action

  5. Introduction to Artificial Intelligence An Introduction to Data Mining

    E-Print Network [OSTI]

    Qu, Rong

    Introduction to Artificial Intelligence G51IAI An Introduction to Data Mining #12; Introduce a range of data mining techniques used in AI systems including : · Neural networks · Decision trees · ... Present some real life data mining applications. 2 Learning Objectives Dr Rong Qu G51IAI ­ Data Mining #12

  6. Wil M. P. van der Aalst Process Mining

    E-Print Network [OSTI]

    van der Aalst, Wil

    1 Wil M. P. van der Aalst Process Mining Discovery, Conformance and Enhancement of Business Processes Process Mining Wil M. P. van der Aalst Computer Science ProcessMining Discovery, Conformance organizations diagnose problems based on fiction rather than facts. Process mining is an emerging discipline

  7. DATA MINING AT THE INTERFACE OF COMPUTER SCIENCE AND STATISTICS

    E-Print Network [OSTI]

    Smyth, Padhraic

    Chapter 1 DATA MINING AT THE INTERFACE OF COMPUTER SCIENCE AND STATISTICS \\Lambda Padhraic Smyth a better understanding of the role of statistical thinking in modern data mining. Data mining has at and highlights the fundamental differences between statistical and computational views of data mining. In do­ ing

  8. Foundations of Artificial Intelligence Introduction to Data Mining

    E-Print Network [OSTI]

    Qu, Rong

    Foundations of Artificial Intelligence Introduction to Data Mining #12;Data Mining Objectives Introduce a range of data mining techniques used in AI systems including : · Neural networks · Decision trees · ... Present some real life data mining applications. Student should gain the knowledge on how

  9. West Virginia University 1 Department of Mining Engineering

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    to advanced mining engineering problems. This program provides students the technical knowledge and researchWest Virginia University 1 Department of Mining Engineering Degrees Offered · Master's of science in mining engineering · Master's of science in engineering with a major in mining engineering · Doctor

  10. Twitter Food Photo Mining and Analysis for One

    E-Print Network [OSTI]

    Yanai, Keiji

    Twitter Food Photo Mining and Analysis for One Hundred Kinds of Foods Pacific-Rim Conf-Communications, Tokyo, Japan #12;Twitter Realtime Food Photo Mining System (mm.cs.uec.ac.jp/tw/) ·What kinds of foods analysis #12;Twitter Food Photo Mining ·Twitter Photos represent the current state of the world ! ·Mining

  11. SIMULATING TRANSPORT AND GEOCHEMICAL EVOLUTION OF ACID MINE DRAINAGE THROUGH

    E-Print Network [OSTI]

    Aubertin, Michel

    SIMULATING TRANSPORT AND GEOCHEMICAL EVOLUTION OF ACID MINE DRAINAGE THROUGH DISCRETELY FRACTURED Waste Management ABSTRACT A modelling study is performed to assess the evolution of acid mine drainage-geochemical and geo-mechanical models for predicting environmental impacts of acid mine drainage in complex mining

  12. Non-Derivable Itemset Mining Toon Calders and Bart Goethals

    E-Print Network [OSTI]

    Antwerpen, Universiteit

    .calders,bart.goethals}@ua.ac.be University of Antwerp, Belgium Abstract All frequent itemset mining algorithms rely heavily on the monotonicNon-Derivable Itemset Mining Toon Calders and Bart Goethals {toon-derivable itemsets a useful and tractable alternative to mining all frequent itemsets. Keywords: Data mining

  13. Projects of the year

    SciTech Connect (OSTI)

    Hansen, T.

    2007-01-15

    The Peabody Hotel, Orlando, Florida was the site of Power Engineering magazine's 2006 Projects of the Year Awards Banquet, which kicked-off the Power-Gen International conference and exhibition. The Best Coal-fired Project was awarded to Tri-State Generation and Transmission Association Inc., owner of Springenville Unit 3. This is a 400 MW pulverized coal plant in Springeville, AZ, sited with two existing coal-fired units. Designed to fire Powder River Basin coal, it has low NOx burners and selective catalytic reduction for NOx control, dry flue gas desulfurization for SO{sub 2} control and a pulse jet baghouse for particulate control. It has a seven-stage feedwater heater and condensers to ensure maximum performance. Progress Energy-Carolinas' Asheville Power Station FGD and SCR Project was awarded the 2006 coal-fired Project Honorable Mention. This plant in Skyland, NC was required to significantly reduce NOx emissions. When completed, the improvements will reduce NOx by 93% compared to 1996 levels and SO{sub 2} by 93% compared to 2001 levels. Awards for best gas-fired, nuclear, and renewable/sustainable energy projects are recorded. The Sasyadko Coal-Mine Methane Cogeneration Plant near Donezk, Ukraine, was given the 2006 Honorable Mention for Best Renewable/Sustainable Energy Project. In November 2004, Ukraine was among 14 nations to launch the Methane to Markets partnership. The award-winning plant is fuelled by methane released during coal extraction. It generates 42 MW of power. 4 photos.

  14. IEEE TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 21, NO. 2, FEBRUARY 2013 291 Classification and Ranking Approaches to

    E-Print Network [OSTI]

    Alpaydýn, Ethem

    this both as a classification and a ranking problem and employ the perceptron, the margin infused relaxed, language modeling, ranking per- ceptron, ranking support vector machine (SVM), margin infused relaxed

  15. Rehabilitation of the international coal mines

    E-Print Network [OSTI]

    Cote?, Homer.

    by the motor, while the other carries the cutting tool and is acted upon by the compressed air. The blow is powerful, effective, and capable of dislodging more coal with less power consumption than any other machine of the puncher type, and in addition... or alter­ nating current power. Each machine is f urnished with a cable, reel, tools, picks, running board, truck and sho e - The conditions of mining encountered in the mines of the International Coal Mines Company require the use of two types...

  16. Method of locating underground mines fires

    DOE Patents [OSTI]

    Laage, Linneas (Eagam, MN); Pomroy, William (St. Paul, MN)

    1992-01-01

    An improved method of locating an underground mine fire by comparing the pattern of measured combustion product arrival times at detector locations with a real time computer-generated array of simulated patterns. A number of electronic fire detection devices are linked thru telemetry to a control station on the surface. The mine's ventilation is modeled on a digital computer using network analysis software. The time reguired to locate a fire consists of the time required to model the mines' ventilation, generate the arrival time array, scan the array, and to match measured arrival time patterns to the simulated patterns.

  17. Ranking of Chemicals Measured in Emissions from R&D Facilities

    SciTech Connect (OSTI)

    Ballinger, Marcel Y.; Duchsherer, Cheryl J.

    2011-04-01

    The Pacific Northwest National Laboratory (PNNL) operates a number of multidisciplinary laboratory research facilities for the U. S. Department of Energy and has sampled air chemical emissions from some of these facilities since 1998. The primary purpose of this sampling is to obtain data to compare estimated release fractions to those used for emissions estimates, verifying that methods used to determine compliance with air regulations and permits conservatively predict actual emissions. Sampling also identifies and quantifies emissions of air toxics to compare with compliance limits established by regulatory agencies. Hundreds of samples have been taken from four different buildings (325, 329, 331, and EMSL) over a 10-year time period. Results from initial sampling campaigns were evaluated and reported by Woodruff, Benar, and McCarthy (2000) who summarized the compliance approach used by PNNL and described sampling and analytical measurements for the first sampling campaigns. Conclusions reported in this paper were that none of the measurements of the target compounds exceeded an acceptable source impact level (ASIL) (Washington Administrative Code, Chapter 173-460) even using significant overestimation factors, and that an average release fraction calculated from the data provided reasonable validation of the factor used in compliance assessments. Subsequent analysis compared chemical signatures from the buildings (Ballinger, Duchsherer, and Metoyer 2008). Results from this analysis showed that stack emissions from three of the four buildings had relatively similar chemical signatures but the fourth building differed from the other three significantly using the developed metric. This paper presents additional analyses of the measured air chemical emissions to 1) rank the chemical compounds that present the greatest risk to a potential downstream receptor and 2) determine whether the sampling parameters and detection limits provided sufficient resolution to verify compliance at potential receptor locations. The ranking method includes chemical-specific parameters such as measured concentrations, detection limits, and regulatory limits plus building-specific parameters such as location, stack flow-rate, and distance to receptors.

  18. Rock mechanics design in mining and tunneling

    SciTech Connect (OSTI)

    Bieniawski, Z.T.

    1984-01-01

    This book introduces the design process as applied to rock mechanics aspects of underground mining and tunneling. Topics covered include a historical perspective, the design process in engineering, empirical methods of design, observational methods of design, and guided design.

  19. Fuelcell-Hybrid Mine loader (LHD)

    SciTech Connect (OSTI)

    James L Dippo; Tim Erikson; Kris Hess

    2009-07-10

    The fuel cell hybrid mine loader project, sponsored by a government-industry consortium, was implemented to determine the viability of proton exchange membrane (PEM) fuel cells in underground mining applications. The Department of Energy (DOE) sponsored this project with cost-share support from industry. The project had three main goals: (1) to develop a mine loader powered by a fuel cell, (2) to develop associated metal-hydride storage and refueling systems, and (3) to demonstrate the fuel cell hybrid loader in an underground mine in Nevada. The investigation of a zero-emissions fuel cell power plant, the safe storage of hydrogen, worker health advantages (over the negative health effects associated with exposure to diesel emissions), and lower operating costs are all key objectives for this project.

  20. Mining from large image sets (Keynote address)

    E-Print Network [OSTI]

    Grabner, Helmut

    ­ Switzerland Michael D. Breitenstein Computer Vision Laboratory ETH Zurich ­ Switzerland Stephan Gammeter Computer Vision Laboratory ETH Zurich ­ Switzerland Helmut Grabner Computer Vision Laboratory ETH Zurich ­ Switzerland Till Quack Computer Vision Laboratory ETH Zurich ­ Switzerland ABSTRACT So far, most image mining

  1. One Day Seminar Data Mining in Practice

    E-Print Network [OSTI]

    Morik, Katharina

    in 1999 the application rate will raise to n 4 projects in 2009. ... is most often oriented towards ­ Spatial Data Mining ­ Churn of customers in telecommunication ­ ??? ­ Prediction of customers' demands

  2. Clustering Techniques for Data Mining and Protein Design Around The Concept of Locality

    E-Print Network [OSTI]

    Hakkoymaz, Huseyin

    2010-01-01

    Knowledge discovery and data mining, San Jose, California,on Knowledge discovery and data mining, Edmonton, Alberta,Knowledge discovery and data mining, Seattle, WA, USA: ACM,

  3. Mining User Groups in the Social News Website: Community Detection in Bipartite Networks.

    E-Print Network [OSTI]

    YANG, HO-SHUN

    2012-01-01

    Mining user behaviors with indirectmore informative for the mining purpose. On the other hand,of California Los Angeles Mining User Groups in the Social

  4. Image/Time Series Mining Algorithms: Applications to Developmental Biology, Document Processing and Data Streams

    E-Print Network [OSTI]

    Tataw, Oben Moses

    2013-01-01

    International Conference on Data Mining (2001). Khairy, K. ,and Eamonn Keogh (2011). Mining Historical Documents forWang, E. J. Keogh. Querying and mining of time series data.

  5. Community Genomic, Proteomic, and Transcriptomic Analyses of Acid Mine Drainage Biofilm Communities

    E-Print Network [OSTI]

    Goltsman, Daniela

    2013-01-01

    T, Banfield J. 2004. Acid mine drainage biogeochemistry atof eukaryotes in acid mine drainage biofilm communities.III) bacteria in acid mine drainage biofilms. Appl Environ

  6. Kinetics of Pyrrhotite Oxidation in Seawater: Implications for Mining Seafloor Hotsprings

    E-Print Network [OSTI]

    Romano, Gina Yolanda

    2012-01-01

    K.B. , 2005, Acid mine drainage remediation options: aDeul, M. , 1982, Acid Mine Drainage: Control and Abatementcould result in acid mine drainage (Belzile, 2004; Janzen,

  7. Knowledge Discovery and Data Mining (KDDM) survey report.

    SciTech Connect (OSTI)

    Phillips, Laurence R.; Jordan, Danyelle N.; Bauer, Travis L.; Elmore, Mark T.; Treadwell, Jim N.; Homan, Rossitza A.; Chapman, Leon Darrel; Spires, Shannon V.

    2005-02-01

    The large number of government and industry activities supporting the Unit of Action (UA), with attendant documents, reports and briefings, can overwhelm decision-makers with an overabundance of information that hampers the ability to make quick decisions often resulting in a form of gridlock. In particular, the large and rapidly increasing amounts of data and data formats stored on UA Advanced Collaborative Environment (ACE) servers has led to the realization that it has become impractical and even impossible to perform manual analysis leading to timely decisions. UA Program Management (PM UA) has recognized the need to implement a Decision Support System (DSS) on UA ACE. The objective of this document is to research the commercial Knowledge Discovery and Data Mining (KDDM) market and publish the results in a survey. Furthermore, a ranking mechanism based on UA ACE-specific criteria has been developed and applied to a representative set of commercially available KDDM solutions. In addition, an overview of four R&D areas identified as critical to the implementation of DSS on ACE is provided. Finally, a comprehensive database containing detailed information on surveyed KDDM tools has been developed and is available upon customer request.

  8. Low-rank coal research. Quarterly report, January--March 1990

    SciTech Connect (OSTI)

    Not Available

    1990-08-01

    This document contains several quarterly progress reports for low-rank coal research that was performed from January-March 1990. Reports in Control Technology and Coal Preparation Research are in Flue Gas Cleanup, Waste Management, and Regional Energy Policy Program for the Northern Great Plains. Reports in Advanced Research and Technology Development are presented in Turbine Combustion Phenomena, Combustion Inorganic Transformation (two sections), Liquefaction Reactivity of Low-Rank Coals, Gasification Ash and Slag Characterization, and Coal Science. Reports in Combustion Research cover Fluidized-Bed Combustion, Beneficiation of Low-Rank Coals, Combustion Characterization of Low-Rank Coal Fuels, Diesel Utilization of Low-Rank Coals, and Produce and Characterize HWD (hot-water drying) Fuels for Heat Engine Applications. Liquefaction Research is reported in Low-Rank Coal Direct Liquefaction. Gasification Research progress is discussed for Production of Hydrogen and By-Products from Coal and for Chemistry of Sulfur Removal in Mild Gas.

  9. CO2 SEQUESTRATION POTENTIAL OF TEXAS LOW-RANK COALS

    SciTech Connect (OSTI)

    Duane A. McVay; Walter B. Ayers Jr.; Jerry L. Jensen

    2005-05-01

    The objectives of this project are to evaluate the feasibility of carbon dioxide (CO{sub 2}) sequestration in Texas low-rank coals and to determine the potential for enhanced coalbed methane (CBM) recovery as an added benefit of sequestration. The main objective for this reporting period was to perform pressure transient testing to determine permeability of deep Wilcox coal to use as additional, necessary data for modeling performance of CO{sub 2} sequestration and enhanced coalbed methane recovery. To perform permeability testing of the Wilcox coal, we worked with Anadarko Petroleum Corporation in selecting the well and intervals to test and in designing the pressure transient test. Anadarko agreed to allow us to perform permeability tests in coal beds in an existing shut-in well (Well APCT2). This well is located in the region of the Sam K. Seymour power station, a site that we earlier identified as a major point source of CO{sub 2} emissions. A service company, Pinnacle Technologies Inc. (Pinnacle) was contracted to conduct the tests in the field. Intervals tested were 2 coal beds with thicknesses of 3 and 7 feet, respectively, at approximately 4,100 ft depth in the Lower Calvert Bluff Formation of the Wilcox Group in east-central Texas. Analyses of pressure transient test data indicate that average values for coalbed methane reservoir permeability in the tested coals are between 1.9 and 4.2 mD. These values are in the lower end of the range of permeability used in the preliminary simulation modeling. These new coal fracture permeability data from the APCT2 well, along with the acquired gas compositional analyses and sorption capacities of CO{sub 2}, CH{sub 4}, and N{sub 2}, complete the reservoir description phase of the project. During this quarter we also continued work on reservoir and economic modeling to evaluate performance of CO{sub 2} sequestration and enhanced coalbed methane recovery.

  10. Ergonomics - Using Ergonomics to Enhance Safe Production at a Surface Coal Mine - A Case Study with Powder Crews

    SciTech Connect (OSTI)

    Torma-Krajewski, J.; Wiehagen, W.; Etcheverry, A.; Turin, F.; Unger, R.

    2009-07-01

    Job tasks that involve exposure to work-related musculoskeletal disorder (WMSD) risk factors may impact both the risk of injury and production downtime. Common WMSD risks factors associated with mining tasks include forceful exertions, awkward postures, repetitive motion, jolting and jarring, forceful gripping, contact stress, and whole body and segmental vibration. Mining environments that expose workers to temperature/humidity extremes, windy conditions, and slippery and uneven walking surfaces also contribute to injury risk. National Institute for Occupational Safety and Health (NIOSH) researchers worked with powder crew members from the Bridger Coal Company to identify and rank routine work tasks based on perceived exposure to WMSD risk factors. This article presents the process followed to identify tasks that workers believed involved the greatest exposure to risk factors and discusses risk reduction strategies. Specifically, the proposed prill truck design changes addressed cab ingress/egress, loading blast holes, and access to the upper deck of the prill truck.

  11. Conversion of Low-Rank Wyoming Coals into Gasoline by Direct...

    Office of Scientific and Technical Information (OSTI)

    of Low-Rank Wyoming Coals into Gasoline by Direct Liquefaction Polyakov, Oleg 01 COAL, LIGNITE, AND PEAT Under the cooperative agreement program of DOE and funding from...

  12. IR ranking proposal and new beam parameter sets for the LHC upgrade the view of HHH

    E-Print Network [OSTI]

    Scandale, Walter

    2007-01-01

    We propose a ranking for the interaction-region (IR) optics based on the presentations and results from the first two days of the LUMI’06 workshop.

  13. Gauge invariant Lagrangian for non-Abelian tensor gauge fields of fourth rank

    E-Print Network [OSTI]

    G. Savvidy; T. Tsukioka

    2005-12-31

    Using generalized field strength tensors for non-Abelian tensor gauge fields one can explicitly construct all possible Lorentz invariant quadratic forms for rank-4 non-Abelian tensor gauge fields and demonstrate that there exist only two linear combinations of them which form a gauge invariant Lagrangian. Together with the previous construction of independent gauge invariant forms for rank-2 and rank-3 tensor gauge fields this construction proves the uniqueness of early proposed general Lagrangian up to rank-4 tensor fields. Expression for the coefficients of the general Lagrangian is presented in a compact form.

  14. RANKING NATIONAL FOOTBALL LEAGUE TEAMS USING GOOGLE'S ANJELA Y. GOVAN AND CARL D. MEYER

    E-Print Network [OSTI]

    H is H = 0 0 1/3 1/3 1/3 0 0 0 0 0 0 1 0 0 0 1/2 0 1/2 0 0 1/2 0 0 1/2 0 2.3. The rank they are displayed as the result of a web search. In this work we expand Google's idea of webpage ranking to ranking the query relevant web sites and displays them according to their predetermined rank. In order to calculate

  15. ESF Mine Power Center Platforms

    SciTech Connect (OSTI)

    T.A. Misiak

    2000-02-10

    The purpose and objective of this analysis is to structurally evaluate the existing Exploratory Studies Facility (ESF) mine power center (MPC) support frames and to design service platforms that will attach to the MPC support frames. This analysis follows the Development Plan titled ''Produce Additional Design for Title 111 Evaluation Report'' (CRWMS M&O 1999a). This analysis satisfies design recommended in the ''Title III Evaluation Report for the Surface and Subsurface Power System'' (CRWMS M&O 1999b, Section 7.6) and concurred with in the ''System Safety Evaluation of Title 111 Evaluation Reports Recommended Work'' (Gwyn 1999, Section 10.1.1). This analysis does not constitute a level-3 deliverable, a level-4 milestone, or a supporting work product. This document is not being prepared in support of the Monitored Geologic Repository (MGR) Site Recommendation (SR), Environmental Impact Statement (EIS), or License Application (LA) and should not be cited as a reference in the MGR SR, EIS, or LA.

  16. Denys Poshyvanyk CSci 780: Mining Software Repositories CSci 780: Mining Software Repositories

    E-Print Network [OSTI]

    Poshyvanyk, Denys

    Denys Poshyvanyk CSci 780: Mining Software Repositories 1 CSci 780: Mining:50pm Location: McGlothlin-Street Hall 002 Instructor: Denys Poshyvanyk Office Hours: MW, 11:30am-1pm Office: McGlothlin-Street Hall, 006 Email: denys [at-sign] cs

  17. Colorado - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price to fall toUranium MarketingYear Jan Feb MarYearX I A O J I E

  18. Connecticut - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price to fall toUranium MarketingYear Jan Feb MarYearX I AYear JanConnecticut

  19. Delaware - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price to fall toUranium MarketingYear Jan Feb MarYearXRail272/SDelaware

  20. District of Columbia - Rankings - U.S. Energy Information Administration

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price to fall toUranium MarketingYear Jan FebFoot) Year(EIA)

  1. Kentucky - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010 2011 2012Foot)Year JanYear

  2. Michigan - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010 2011Year JanFeet) Year Jan FebMichigan

  3. New York - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010Fuel)throughFoot)Year JanYear

  4. Parallel Boosted Regression Trees for Web Search Ranking Stephen Tyree

    E-Print Network [OSTI]

    Weinberger, Kilian

    LETOR data. In addition, on shared memory machines, we obtain almost perfect lin- ear speed-up with up by others. WWW 2011, March 28­April 1, 2011, Hyderabad, India. ACM 978-1-4503-0632-4/11/03. 1. INTRODUCTION the document's degree of relevance to the query. In recent years, fueled by the pub- lication of real

  5. CO2 SEQUESTRATION POTENTIAL OF TEXAS LOW-RANK COALS

    SciTech Connect (OSTI)

    Duane A. McVay; Walter B. Ayers, Jr.; Jerry L. Jensen

    2004-07-01

    The objectives of this project are to evaluate the feasibility of carbon dioxide (CO{sub 2}) sequestration in Texas low-rank coals and to determine the potential for enhanced coalbed methane (CBM) recovery as an added benefit of sequestration. The main tasks for this reporting period were to correlate well logs and refine coal property maps, evaluate methane content and gas composition of Wilcox Group coals, and initiate discussions concerning collection of additional, essential data with Anadarko. To assess the volume of CO{sub 2} that may be sequestered and volume of methane that can be produced in the vicinity of the proposed Sam Seymour sequestration site, we used approximately 200 additional wells logs from Anadarko Petroleum Corp. to correlate and map coal properties of the 3 coal-bearing intervals of Wilcox group. Among the maps we are making are maps of the number of coal beds, number of coal beds greater than 5 ft thick, and cumulative coal thickness for each coal interval. This stratigraphic analysis validates the presence of abundant coal for CO{sub 2} sequestration in the Wilcox Group in the vicinity of Sam Seymour power plant. A typical wellbore in this region may penetrate 20 to 40 coal beds with cumulative coal thickness between 80 and 110 ft. Gas desorption analyses of approximately 75 coal samples from the 3 Wilcox coal intervals indicate that average methane content of Wilcox coals in this area ranges between 216 and 276 scf/t, basinward of the freshwater boundary indicated on a regional hydrologic map. Vitrinite reflectance data indicate that Wilcox coals are thermally immature for gas generation in this area. Minor amounts of biogenic gas may be present, basinward of the freshwater line, but we infer that most of the Wilcox coalbed gas in the deep coal beds is migrated thermogenic gas. Analysis based on limited data suggest that sites for CO{sub 2} sequestration and enhanced coalbed gas recovery should be located basinward of the Wilcox freshwater contour, where methane content is high and the freshwater aquifer can be avoided.

  6. Recovery of Carbon and Nitrogen Cycling and Microbial Community Functionality in a Post-Lignite Mining Rehabilitation Chronosequence in East Texas 

    E-Print Network [OSTI]

    Ng, Justin

    2012-10-19

    chronosequence of 40 years to determine when a reclaimed mine soil (RMS) returned to premined conditions. We sampled 5 sites aged 0 to 20 years reclaimed by the crosspit spreader technique (CP) and 3 sites aged 20 to 40 years reclaimed by the mixed overburden...

  7. Data Mining Empowers the Generation of a Novel Class of Chromosome-specific DNA Probes

    E-Print Network [OSTI]

    Zeng, Hui

    2012-01-01

    eds. ), Zeng et al. : Data mining for probes Excerpta330. Zeng et al. : Data mining for probes 31. Fung J, WeierZeng et al. : Data mining for probes Data Mining Empowers

  8. International Journal of Data Warehousing and Mining, 8(4), 1-21, October-December 2012 1 Copyright 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

    E-Print Network [OSTI]

    Ezeife, Christie

    of IGI Global is prohibited. Keywords: Non-DeterministicFiniteAutomata(NFA),ObjectOrientedMining,WebContentMining, WebDataIntegration,Wrappers INTRODUCTION World Wide Web (WWW) is growing expo- nentially over the years and web documents constitute some of the largest repositories of information (Kosala & Blockeel

  9. California - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price to fall toUranium MarketingYear Jan Feb Mar OILMexico's

  10. Louisiana - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010 2011Year Jan Feb Mar Apr May

  11. Maryland - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010 2011Year Jan Feb

  12. Massachusetts - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010 2011Year Jan FebFoot)

  13. Time and Energy Optimal List Ranking Algorithms on the k-Channel Broadcast

    E-Print Network [OSTI]

    Nakano, Koji

    Time and Energy Optimal List Ranking Algorithms on the k-Channel Broadcast Communication Model Koji- nels. The main contribution of this paper is to present time and energy optimal list ranking algorithms Nakano School of Information Science Japan Advanced Insitute of Science and Technology Tatsunokuchi

  14. Necessary and Sufficient Conditions for Success of the Nuclear Norm Heuristic for Rank Minimization

    E-Print Network [OSTI]

    Qiu, Robert Caiming

    Necessary and Sufficient Conditions for Success of the Nuclear Norm Heuristic for Rank Minimization that yield exact solutions. A popular heuristic algorithm replaces the rank function with the nuclear norm of this heuristic to non-symmetric matrices introduced by Fazel in [8] minimizes the nuclear norm, *Center

  15. Biological Question Answering with Syntactic and Semantic Feature Matching an Improved Mean Reciprocal Ranking Measurement

    E-Print Network [OSTI]

    Chu, Hao-hua

    . An improved mean reciprocal rank (MRR) measurement, mean average reciprocal rank (MARR), and an efficient formula to reduce the computational complexity of the MARR are proposed to address the same score problem. With our syntactic and semantic features, our system achieves a Top-1 MARR of 74.11% and Top-5 MARR of 76

  16. Mixed Membership Models for Rank Data: Investigating Structure in Irish Voting Data

    E-Print Network [OSTI]

    Wolfe, Patrick J.

    the population. Thus, mixed membership models provide a method for model-based soft clustering of data. The mixed21 Mixed Membership Models for Rank Data: Investigating Structure in Irish Voting Data Isobel ........................................................................ 444 21.3.1 The Plackett-Luce Model for Rank Data ............................................ 445 21

  17. Low-rank coal research: Volume 1, Control technology, liquefaction, and gasification: Final report

    SciTech Connect (OSTI)

    Weber, G.F.; Collings, M.E.; Schelkoph, G.L.; Steadman, E.N.; Moretti, C.J.; Henke, K.R.; Rindt, J.R.; Hetland, M.D.; Knudson, C.L.; Willson, W.G.

    1987-04-01

    Volume I contains articles on SO/sub x//NO/sub x/ control, waste management, low-rank direct liquefaction, hydrogen production from low-rank coals, and advanced wastewater treatment. These articles have been entered individually into EDB and ERA. (LTN)

  18. The Effect of Ad Rank on the Performance of Keyword Advertising Campaigns

    E-Print Network [OSTI]

    Jansen, James

    The Effect of Ad Rank on the Performance of Keyword Advertising Campaigns Bernard J. Jansen and Zhe on the performance of keyword advertising cam- paigns. We examined a large-scale data file comprised of nearly 7 tests to examine the effect of ad rank on critical keyword advertising metrics, including clicks, cost

  19. Unit Computation in Purely Cubic Function Fields of Unit Rank 1

    E-Print Network [OSTI]

    Scheidler, Renate

    Unit Computation in Purely Cubic Function Fields of Unit Rank 1 Renate Scheidler .1 and Andreas for computing the fundamen- tal unit and regulator of a purely cubic congruence function field of unit rank 1 cubic lattice which is used for calculating the fundamental unit and regulator of a purely cubic number

  20. A PECULIARITY OF THE WILCOXON-MANN-WHITNEY RANK-SUM TEST

    E-Print Network [OSTI]

    A PECULIARITY OF THE WILCOXON-MANN-WHITNEY RANK-SUM TEST Scotia Canada B3H 3C3 Keywords: intransitivity, rank-sum test, Behrens-Mann-Whitney test is a test of relative location whenever the two distributions are symmetric. By con- trast

  1. Fast matrix algebra for dense matrices with rank-deficient off-diagonal blocks

    E-Print Network [OSTI]

    Martinsson, Gunnar

    CHAPTER 2 Fast matrix algebra for dense matrices with rank-deficient off-diagonal blocks Chapter whose off diagonal blocks are of low (numerical) rank. The primary focus is on matrix inversion, but algorithms for matrix-vector and matrix-matrix multiplication are also described. 2.1. Introduction All

  2. Distributing medicine using PageRank Department of Mathematics and Computer Science

    E-Print Network [OSTI]

    Goddard, Wayne

    Background Approach Results Distributing medicine using PageRank Paul Horn Department October 7, 2010 Horn Distributing medicine using PageRank #12;Background Approach Results The Problem Disease breaks out! We need to stop it before it becomes an epidemic! We want to distribute medicine so

  3. RankSQL: Query Algebra and Optimization for Relational Top-k Queries

    E-Print Network [OSTI]

    Ilyas, Ihab Francis

    RankSQL: Query Algebra and Optimization for Relational Top-k Queries Chengkai Li1 Kevin Chen systems (RDBMS), by extending relational algebra and query optimization. Previously, top-k query and principled framework to support efficient evaluations of ranking (top-k) queries in relational database

  4. Jared C. Carbone April 2015 Colorado School of Mines Phone: 303-384-2175

    E-Print Network [OSTI]

    and Economics Email: jcarbone@mines.edu Engineering Hall Web: http://www.mines.edu/~jcarbone 816 15th Street

  5. Rehabilitation of semi-arid coal mine spoil bank soils with mine residues and farm organic by-products

    SciTech Connect (OSTI)

    Salazar, M.; Bosch-Serra, A.; Estudillos, G.; Poch, R.M. [University of Lleida, Lleida (Spain). Dept. of Environmental & Soil Science

    2009-07-01

    A method of rehabilitating coal mine soils was studied under the conditions of a semi-arid climate, lack of topsoil but availability of farm by-products in NE Spain. The objectives of the research were to assess a new method in order to achieve a suitable substrate for the establishment of native vegetation, to evaluate environmental impacts associated with the reclamation process, and to determine the time necessary to integrate the treated area into the surrounding environment. Eight plots (10 x 35 m{sup 2}) were established in September 1997. Substrate combinations of two types of mine spoil (coal dust and coarse-sized material), two levels of pig slurry (39 and 94 Mg ha{sup -1}dry-wt), and cereal straw (0 and 15 Mg ha{sup -1}) were applied. Monitoring of select physical and chemical soil properties and vegetation characteristics was performed from 1997 until 2005. The bulk density and the saturated hydraulic conductivity measured did not limit plant development and water availability. Initial substrate salinity (1.37 S m{sup -1}) decreased with time and in the long term did not limit plant colonization to salinity-adapted species. Initial nitrate concentration was 298 mg kg{sup -1}, but was reduced significantly to acceptable values in 3 years (55 mg kg{sup -1}) and the measured pH (7.6) was maintained at the level of initial spoil values. Vegetation cover reached up to 90%. In the treated area, spontaneous vegetation cover (15 to 70%) colonized the nonsown areas widely. In the medium term, vegetation cover tended to be higher in plots with a thicker layer of coal dust material and the higher slurry rate. Soil rehabilitation and environmental reintegration, taking into account soil and vegetation indicators, was possible in the studied area with low cost inputs using residual materials from mining activities and animal husbandry by-products.

  6. CO2 SEQUESTRATION POTENTIAL OF TEXAS LOW-RANK COALS

    SciTech Connect (OSTI)

    Duane A. McVay; Walter B. Ayers Jr; Jerry L. Jensen

    2004-11-01

    The objectives of this project are to evaluate the feasibility of carbon dioxide (CO{sub 2}) sequestration in Texas low-rank coals and to determine the potential for enhanced coalbed methane (CBM) recovery as an added benefit of sequestration. there were two main objectives for this reporting period. first, they wanted to collect wilcox coal samples from depths similar to those of probable sequestration sites, with the objective of determining accurate parameters for reservoir model description and for reservoir simulation. The second objective was to pursue opportunities for determining permeability of deep Wilcox coal to use as additional, necessary data for modeling reservoir performance during CO{sub 2} sequestration and enhanced coalbed methane recovery. In mid-summer, Anadarko Petroleum Corporation agreed to allow the authors to collect Wilcox Group coal samples from a well that was to be drilled to the Austin Chalk, which is several thousand feet below the Wilcox. In addition, they agreed to allow them to perform permeability tests in coal beds in an existing shut-in well. Both wells are in the region of the Sam K. Seymour power station, a site that they earlier identified as a major point source of CO{sub 2}. They negotiated contracts for sidewall core collection and core analyses, and they began discussions with a service company to perform permeability testing. To collect sidewall core samples of the Wilcox coals, they made structure and isopach maps and cross sections to select coal beds and to determine their depths for coring. On September 29, 10 sidewall core samples were obtained from 3 coal beds of the Lower Calvert Bluff Formation of the Wilcox Group. The samples were desorbed in 4 sidewall core canisters. Desorbed gas samples were sent to a laboratory for gas compositional analyses, and the coal samples were sent to another laboratory to measure CO{sub 2}, CH{sub 4}, and N{sub 2} sorption isotherms. All analyses should be finished by the end of December. A preliminary report shows methane content values for the desorbed coal samples ranged between 330 and 388 scf/t., on ''as received'' basis. Residual gas content of the coals was not included in the analyses, which results in an approximate 5-10% underestimation of in-situ gas content. Coal maps indicate that total coal thickness is 40-70 ft in the Lower Calvert Bluff Formation of the Wilcox Group in the vicinity of the Sam K. Seymour power plant. A conservative estimate indicates that methane in place for a well on 160-acre spacing is approximately 3.5 Bcf in Lower Calvert Bluff coal beds. When they receive sorption isotherm data from the laboratory, they will determine the amount of CO{sub 2} that it may be possible to sequester in Wilcox coals. In December, when the final laboratory and field test data are available, they will complete the reservoir model and begin to simulate CO{sub 2} sequestration and enhanced CH{sub 4} production.

  7. Marcelo Godoy Simes e-mail: msimoes@mines.edu

    E-Print Network [OSTI]

    Simões, Marcelo Godoy

    1 Marcelo Godoy Simões e-mail: msimoes@mines.edu webpage: http://inside.mines.edu/~msimoes, http://aceps for Advanced Control of Energy and Power Systems ­ ACEPS and is currently spearheading the new Colorado

  8. New Mexico Institute of Mining and Masters Independent Study

    E-Print Network [OSTI]

    Borchers, Brian

    New Mexico Institute of Mining and Technology Masters Independent Study Estimation Methods is the only choice you have." Bob Marley #12;NEW MEXICO INSTITUTE OF MINING AND TECHNOLOGY Abstract Jan

  9. Dynamic Filtering and Mining Triggers in Mesoscale Meteorology Forecasting

    E-Print Network [OSTI]

    Plale, Beth

    Dynamic Filtering and Mining Triggers in Mesoscale Meteorology Forecasting Nithya N. Vijayakumar {rramachandran, xli}@itsc.uah.edu Abstract-- Mesoscale meteorology forecasting as a data driven application Triggers, Data Mining, Stream Processing, Meteorology Forecasting I. INTRODUCTION Mesoscale meteorologists

  10. Chemistry & Biology Genome-Wide High-Throughput Mining

    E-Print Network [OSTI]

    Yin, Jun

    Chemistry & Biology Article Genome-Wide High-Throughput Mining of Natural-Product Biosynthetic Gene.01.006 SUMMARY We have developed a phage-display method for high-throughput mining of bacterial gene clus- ters

  11. WIPP’s Mine Rescue Teams Lead Competition

    Broader source: Energy.gov [DOE]

    CARLSBAD, N.M. – The Waste Isolation Pilot Plant’s (WIPP) two mine rescue teams recently led the field of 13 groups competing in the Southwest Regional Mine Rescue Contest.

  12. An experimental investigation of mine burial penetration in soft sediments 

    E-Print Network [OSTI]

    Munim, Mohammed Abdul

    2003-01-01

    An experimental program was conducted to study the penetration behavior of mines in soft sediment. Model tests were conducted on sediments collected from the Gulf of Mexico seabed. The size of the model mine was approximately one third...

  13. ADVANCED UNDERGROUND GAS STORAGE CONCEPTS REFRIGERATED-MINED CAVERN STORAGE

    SciTech Connect (OSTI)

    1998-09-01

    Limited demand and high cost has prevented the construction of hard rock caverns in this country for a number of years. The storage of natural gas in mined caverns may prove technically feasible if the geology of the targeted market area is suitable; and economically feasible if the cost and convenience of service is competitive with alternative available storage methods for peak supply requirements. It is believed that mined cavern storage can provide the advantages of high delivery rates and multiple fill-withdrawal cycles in areas where salt cavern storage is not possible. In this research project, PB-KBB merged advanced mining technologies and gas refrigeration techniques to develop conceptual designs and cost estimates to demonstrate the commercialization potential of the storage of refrigerated natural gas in hard rock caverns. Five regions of the U.S.A. were studied for underground storage development and PB-KBB reviewed the literature to determine if the geology of these regions was suitable for siting hard rock storage caverns. Area gas market conditions in these regions were also studied to determine the need for such storage. Based on an analysis of many factors, a possible site was determined to be in Howard and Montgomery Counties, Maryland. The area has compatible geology and a gas industry infrastructure for the nearby market populous of Baltimore and Washington D.C.. As Gas temperature is lowered, the compressibility of the gas reaches an optimum value. The compressibility of the gas, and the resultant gas density, is a function of temperature and pressure. This relationship can be used to commercial advantage by reducing the size of a storage cavern for a given working volume of natural gas. This study looks at this relationship and and the potential for commercialization of the process in a storage application. A conceptual process design, and cavern design were developed for various operating conditions. Potential site locations were considered and a typical plant layout was developed. In addition a geomechanical review of the proposed cavern design was performed, evaluating the stability of the mine rooms and shafts, and the effects of the refrigerated gas temperatures on the stability of the cavern. Capital and operating cost estimates were also developed for the various temperature cases considered. The cost estimates developed were used to perform a comparative market analysis of this type of gas storage system to other systems that are commercially used in the region of the study.

  14. Alaska - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price to fall toUranium Marketing AnnualFoot) Year JanShale

  15. Arkansas - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price to fall toUranium MarketingYear Jan Feb Mar Apr May Jun

  16. Hawaii - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010 2011 2012 2013Feet) YearHas Driving

  17. Indiana - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010 2011 2012Foot) Year Jan2014

  18. Kansas - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010 2011 2012Foot)Year Jan Feb

  19. Maine - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010 2011Year Jan Feb Mar AprperRenato2007

  20. Minnesota - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010 2011YearGE Power &Cubic8.1 64.133.0

  1. Mississippi - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010 2011YearGE Powerper Thousand CubicTHEMississippi

  2. Missouri - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010 2011YearGE Powerper(Dollars perMissouri Missouri

  3. Montana - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010 2011YearGE Powerper(DollarsYearperMontanaMontana

  4. New Hampshire - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010Fuel)throughFoot) Year JanHampshire New

  5. New Jersey - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010Fuel)throughFoot) YearFeet)

  6. New Mexico - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009 2010Fuel)throughFoot)Year Jan Feb MarMexico

  7. Oklahoma - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009Cubic Foot) Year Jan Feb Mar OYear

  8. Oregon - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocks 2009Cubic Foot) Year Jan FebThousand Cubic9:-Oregon

  9. Texas - Rankings - U.S. Energy Information Administration (EIA)

    U.S. Energy Information Administration (EIA) 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| Open Energy Informationmonthly gasoline price toStocksU.S. shale gasMoroccoCubic Foot) Year

  10. A generic study of strip mining impacts on groundwater resources

    E-Print Network [OSTI]

    Hamilton, David Andrew

    1977-01-01

    This report evaluates the influence of strip mining features, commonly found in the Northern Great Plains Coal Region, on ground

  11. A Three-layered Conceptual Framework of Data Mining

    E-Print Network [OSTI]

    Yao, Yiyu

    A Three-layered Conceptual Framework of Data Mining Y.Y. Yao1 , N. Zhong2 and Y. Zhao1 1 Department-Cho, Maebashi 371, Japan E-mail: zhong@maebashi-it.ac.jp Summary. The study of the foundations of data mining may be viewed as a scien- tific inquiry into the nature of data mining and the scope of data mining

  12. Emission control options for mine diesels

    SciTech Connect (OSTI)

    Waytulonis, R.W. (Bureau of Mines, Twin Cities, MN (USA). Twin Cities Research Center)

    1991-03-01

    New exhaust control techniques and devices may be necessary to meet future diesel particulate matter emission standards in underground coal mines. This paper reviews conventional work practices and devices used to control diesel exhaust emissions, and new techniques being tested by the US Bureau of Mines. Discussions center on important work practices and on the function and efficiency of exhaust aftertreatment devices. An industry-government cooperative research project to develop and test an exhaust aftertreatment system for part 36 equipment is also discussed.

  13. High pressure water jet mining machine

    DOE Patents [OSTI]

    Barker, Clark R. (Rolla, MO)

    1981-05-05

    A high pressure water jet mining machine for the longwall mining of coal is described. The machine is generally in the shape of a plowshare and is advanced in the direction in which the coal is cut. The machine has mounted thereon a plurality of nozzle modules each containing a high pressure water jet nozzle disposed to oscillate in a particular plane. The nozzle modules are oriented to cut in vertical and horizontal planes on the leading edge of the machine and the coal so cut is cleaved off by the wedge-shaped body.

  14. Coal recovery from mine wastes of the historic longwall mining district of north-central illinois. Illinois mineral notes

    SciTech Connect (OSTI)

    Khan, L.A.; Berggren, D.J.; Camp, L.R.

    1986-01-01

    Recovery of coal from mine wastes produced by historic longwall mines in northeastern Illinois was studied as part of a project undertaken in 1982 for the Illinois Abandoned Mined Lands Reclamation Council. About 100 of these mines operated in the Wilmington and La Salle Districts of the Illinois Coal Field between about 1870 and 1940; all worked the Colchester (No. 2) Coal Seam, using a manual high-extraction mining method. Large samples of the three major kinds of mine waste - gray mining gob, preparation gob, and preparation slurry - were collected from deposits at nine of the larger mine sites and analyzed to determine their general ranges of sulfur, ash, and heating values. Preparation gob and slurry from six of the sites had significant combustible contents, and were evaluated by a simple procedure in which ash analyses and wet-screening tests were used to determine the washability and yield of combustibles to recovery processes.

  15. 1 INTRODUCTION Appalachian coal recovered during mining fre-

    E-Print Network [OSTI]

    overlies a section of the mine workings and, therefore, long term stability of the mine work- ings (Newman, 2003). In this paper, a "risk analysis" approach was util- ized to evaluate the potential impacts of room-and- pillar mine workings on the impoundment site. Un- der this methodology, a "worst case

  16. Underground Mine Communication and Tracking Systems : A Survey

    E-Print Network [OSTI]

    New South Wales, University of

    . The underground mining environment is remarkably different from the condi- tions present on the surface the mine. The self ignition of coal seams results from an exothermic reaction of coal and oxygenUnderground Mine Communication and Tracking Systems : A Survey Prasant Misra1 Diet Ostry2 Sanjay

  17. UTILIZATION OF SEISMIC AND INFRASOUND SIGNALS FOR CHARACTERIZING MINING EXPLOSIONS

    E-Print Network [OSTI]

    Stump, Brian W.

    on the Western US, where a variety of different types of mining operations exist, ranging from surface coal cast, single-fired explosions of varying yield were conducted in the coal mine. At regional distances in developing ground truth. Unlike coal cast or taconite blasts, Morenci Copper Mine often shoots several

  18. Underground Coal Mine Monitoring with Wireless Sensor Networks

    E-Print Network [OSTI]

    Liu, Yunhao

    10 Underground Coal Mine Monitoring with Wireless Sensor Networks MO LI and YUNHAO LIU Hong Kong University of Science and Technology Environment monitoring in coal mines is an important application queries under instable circumstances. A prototype is deployed with 27 mica2 motes in a real coal mine. We

  19. Visiting Assistant Professor New Mexico Institute of Mining and Technology

    E-Print Network [OSTI]

    Borchers, Brian

    Visiting Assistant Professor New Mexico Institute of Mining and Technology The Department. Send all material to New Mexico Institute of Mining and Technology, Human Resources, Socorro, NM 87801 of Mathematics at New Mexico Institute of Mining and Tech- nology invites applications for a Visiting Assistant

  20. A Visualization Application for the Mining Industry Using Standard Tools

    E-Print Network [OSTI]

    1/1 A Visualization Application for the Mining Industry Using Standard Tools Steven J. Schafrik visualization tools for modeling an orebody, or a mining process such as loading and tramming. This is usually accomplished using commercial tools, such as mine design packages, process simulators, etc., that have a custom

  1. Open DMIX: High Performance Web Services for Distributed Data Mining

    E-Print Network [OSTI]

    Grossman, Robert

    Open DMIX: High Performance Web Services for Distributed Data Mining Robert Grossman , Yunhong Gu Krishnaswamy, Web-Service Based Data Mining Middleware for Grid Computing Environments, 7th Interna- tional collection of web services for the mining, integration, and exploration of remote and dis- tributed data. We

  2. Revised October 1, 2012 COLORADO SCHOOL OF MINES

    E-Print Network [OSTI]

    Revised October 1, 2012 COLORADO SCHOOL OF MINES PERFORMANCE MANAGEMENT USER GUIDE Table ........................................................................................29 #12;2 PREFACE The Colorado School of Mines Performance Management System and this associated, the Colorado School of Mines performance management system has been designed to encourage collaborative efforts

  3. Data Mining Using Light Weight Object Management in Clustered Computing

    E-Print Network [OSTI]

    Grossman, Robert

    Data Mining Using Light Weight Object Management in Clustered Computing Environments R. L. Grossman, Inc. Oak Park, Illinois February, 1996 This is a draft of the following article: Data Mining Using, and infrequently updated. These operations and access patterns are common when data mining large data stores, which

  4. Fuzzy Rules in Data Mining: From Fuzzy Associations to Gradual

    E-Print Network [OSTI]

    Hüllermeier, Eyke

    Fuzzy Rules in Data Mining: From Fuzzy Associations to Gradual Dependencies Eyke H recently also in the field of data mining. In this chapter, we provide a synthesis of different approaches of knowledge discovery in databases (KDD) and its core methodological component, data mining, have attracted

  5. Dynamic Data Mining* Vijay Raghavan and Alaaeldin Hafez1

    E-Print Network [OSTI]

    Raghavan, Vijay

    Dynamic Data Mining* Vijay Raghavan and Alaaeldin Hafez1 (raghavan, ahafez Abstract. Business information received from advanced data analysis and data mining is a critical success as a local procedure to generate large itemsets. We prove that the Dynamic Data Mining algorithm is correct

  6. Data Mining et Statistique Philippe Besse # , Caroline Le Gall + ,

    E-Print Network [OSTI]

    Besse, Philippe

    Data Mining et Statistique Philippe Besse # , Caroline Le Gall + , Nathalie Raimbault # & Sophie Sarpy § Râ??esumâ??e Cet article propose une introduction au Data Mining. Celle­ci prend la forme d'une r permettent de tirer quelques ensei­ gnements sur les pratiques du data mining : choix d'une mâ??ethode, comp

  7. Interactive Data Mining Considered Harmful (If Done Wrong)

    E-Print Network [OSTI]

    Waldmann, Uwe

    Interactive Data Mining Considered Harmful (If Done Wrong) Pauli Miettinen Max-Planck-Institut für Informatik Saarbrücken, Germany pauli.miettinen@mpi-inf.mpg.de ABSTRACT Interactive data mining can, there is a serious risk that the user of powerful interactive data mining tools will only find the results she

  8. A Survey on Wavelet Applications in Data Mining Department of

    E-Print Network [OSTI]

    Li, Tao

    A Survey on Wavelet Applications in Data Mining Tao Li Department of Computer Science Univ in the use of wavelet methods in various data mining processes. However, there has been written presents a high-level data-mining framework that reduces the overall process into smaller components

  9. Data Mining: Spring 2013 Statistics 36-462/36-662

    E-Print Network [OSTI]

    Tibshirani, Ryan

    Data Mining: Spring 2013 Statistics 36-462/36-662 Instructor: Ryan Tibshirani, Dept. of Statistics:30-2:50pm, Porter Hall 125C Overview and objectives Data mining is the science of discovering structure and making predictions in data sets (typically, large ones). Applications of data mining are happening all

  10. A Perspective on Statistical Tools for Data Mining Applications

    E-Print Network [OSTI]

    Rocke, David M.

    A Perspective on Statistical Tools for Data Mining Applications David M. Rocke Center for Image Processing and Integrated Computing University of California, Davis Statistics and Data Mining Statistics in the field are aimed at more exploratory ends. In this sense, data mining (defined as the exploratory

  11. Data Mining Middleware for Wide Area High Performance Networks

    E-Print Network [OSTI]

    Grossman, Robert

    1 Data Mining Middleware for Wide Area High Performance Networks Robert L. Grossman*, Yunhong Gu, David Hanley, and Michal Sabala National Center for Data Mining, University of Illinois at Chicago, USA multiple high volume data streams. Both rely on newly developed data transport and data mining middleware

  12. A Data Stream Mining System Hetal Thakkar Barzan Mozafari

    E-Print Network [OSTI]

    A Data Stream Mining System Hetal Thakkar Barzan Mozafari University of California at Los Angeles {hthakkar, barzan, zaniolo}@cs.ucla.edu Carlo Zaniolo Abstract On-line data stream mining has attracted much library of mining algorithms that are fast & light enough to be effective on data streams, and (iii) sup

  13. A Statistical Perspective on Data Mining Ranjan Maitra

    E-Print Network [OSTI]

    Maitra, Ranjan

    A Statistical Perspective on Data Mining Ranjan Maitra Abstract Technological advances have led. Such capability is provided by data mining which combines core statistical techniques with those from machine of data mining from the point of view of a researcher in databases and for help with Figure 4, Rouben

  14. Text and spatial data mining Finn Arup Nielsen

    E-Print Network [OSTI]

    Nielsen, Finn Årup

    Text and spatial data mining Finn °Arup Nielsen Lundbeck Foundation Center for Integrated Molecular data mining Parcellation of the human brain Parcellation of the human brain by combining text min- ing and spatial data min- ing within a neuroinformatics database. Text mining: Analysis of sci- entific abstracts

  15. Data Mining and Knowledge ISSN 1384-5810

    E-Print Network [OSTI]

    Droegemeier, Kelvin K.

    1 23 Data Mining and Knowledge Discovery ISSN 1384-5810 Volume 22 Combined 1-2 Data Min Knowl Disc this knowledge for future severe weather detection and prediction algorithms. Keywords Temporal data mining accuracy are to take place. The long-term goals of our work in spatiotemporal data mining

  16. DISCUSSIONS AND CLOSURES Discussion of "Data Mining Process for

    E-Print Network [OSTI]

    Chahar, B. R.

    DISCUSSIONS AND CLOSURES Discussion of "Data Mining Process for Integrated Evaporation Model" by M should be commended for presenting an investigation on the ability and accuracy of the data mining-based evapotranspiration esti- mation models Abtew 2001 . On the other hand, the data mining process appears under

  17. MINING MEDLINE: ABSTRACTS, SENTENCES, OR PHRASES? , D. BERLEANTa,d

    E-Print Network [OSTI]

    Wurtele, Eve Syrkin

    MINING MEDLINE: ABSTRACTS, SENTENCES, OR PHRASES? J. DINGa , D. BERLEANTa,d , D. NETTLETONb , AND E addresses automated mining for biochemical information from digital repositories of scientific literature, and effectiveness for the task of mining interactions among biochemical terms based on term co- occurrence. Results

  18. Efficient Mining of Partial Periodic Patterns in Time Series Database

    E-Print Network [OSTI]

    Dong, Guozhu

    Efficient Mining of Partial Periodic Patterns in Time Series Database In ICDE 99 Jiawei Han \\Lambda peri­ odic patterns in time­series databases, is an interesting data mining problem. Previous studies several algorithms for efficient mining of par­ tial periodic patterns, by exploring some interesting

  19. Mining gene sets for measuring similarities CHRISTINE NARDINI1

    E-Print Network [OSTI]

    Nardini, Christine

    Mining gene sets for measuring similarities CHRISTINE NARDINI1 , DANIELE MASOTTI2 , SUNGROH YOON3 and data mining of these new, large types of data. The proliferation of devices able to process in paral of number of genes under different environmental conditions. Data mining algorithms demanded to the analysis

  20. PROOF MINING: A SYSTEMATIC WAY OF ANALYSING PROOFS IN MATHEMATICS

    E-Print Network [OSTI]

    Haller-Dintelmann, Robert

    PROOF MINING: A SYSTEMATIC WAY OF ANALYSING PROOFS IN MATHEMATICS ULRICH KOHLENBACH AND PAULO OLIVA Abstract. We call proof mining the process of logically analyzing proofs in mathe- matics with the aim of the main techniques used in proof mining. We show that those techniques not only apply to proofs based

  1. Data Mining: Data Analysis on a Grand Scale? Padhraic Smyth

    E-Print Network [OSTI]

    Smyth, Padhraic

    Data Mining: Data Analysis on a Grand Scale? Padhraic Smyth Information and Computer Science informationfrommassiveobservationaldatasets. Because of this historical context, data mining to date has largely focused on computational a brief review of the origins of data mining as well as discussing some of the primary themes in current

  2. Data mining in design of products and production systems

    E-Print Network [OSTI]

    Kusiak, Andrew

    Data mining in design of products and production systems Andrew Kusiak *, Matthew Smith Intelligent Data mining is acquiring its own identity by refining concepts from other disciplines, developing affected by the data mining pursuit. This paper outlines areas of product and manufacturing system design

  3. Sparse Component Analysis: a New Tool for Data Mining

    E-Print Network [OSTI]

    Cichocki, Andrzej

    Sparse Component Analysis: a New Tool for Data Mining Pando Georgiev1 , Fabian Theis2 , Andrzej,hova}@bsp.brain.riken.go.jp Summary. In many practical problems for data mining the data X under consid- eration (given as (m × N Separation, cluster- ing. 1 Introduction Data mining techniques can be divided into the following classes [3

  4. DATA MINING FOR A WEB-BASED EDUCATIONAL SYSTEM

    E-Print Network [OSTI]

    DATA MINING FOR A WEB-BASED EDUCATIONAL SYSTEM By Behrouz Minaei-Bidgoli A DISSERTATION Submitted Department of Computer Science and Engineering 2004 #12;ii ABSTRACT DATA MINING FOR A WEB-BASED EDUCATIONAL mining and knowledge discovery techniques can be applied to find interesting relationships between

  5. van der Waerden's Theorem and Topological Dynamics Proof Mining

    E-Print Network [OSTI]

    Gerhardy, Philipp

    Outline van der Waerden's Theorem and Topological Dynamics Proof Mining Proof Analysis Comparison with van der Waerden's proof Proof Mining in Topological Dynamics Philipp Gerhardy Department of Mathematics University of Oslo Oberwolfach, April 6 - April 12, 2008. Philipp Gerhardy Proof Mining

  6. Feature Mining Paradigms for Scientific Data Tat-Sang Choy

    E-Print Network [OSTI]

    Wilkins, John

    Feature Mining Paradigms for Scientific Data Ming Jiang Tat-Sang Choy Sameep Mehta Matt Coatney techniques that can mine, track, and visualize the important features in the data. In this paper, we present to their complex evolution. Our framework includes two paradigms for feature mining, and the choice of one over

  7. When do Data Mining Results Violate Privacy? Murat Kantarcioglu

    E-Print Network [OSTI]

    Jin, Jiashun

    When do Data Mining Results Violate Privacy? Murat Kantarcioglu Purdue University Computer Sciences Privacy-preserving data mining has concentrated on obtain- ing valid results when the input data. Categories and Subject Descriptors H.2.8 [Database Management]: Database Applications-- Data mining; H.2

  8. Text Mining: The state of the art and the challenges

    E-Print Network [OSTI]

    Tan, Ah-Hwee

    Text Mining: The state of the art and the challenges Ah-Hwee Tan Kent Ridge Digital Labs 21 Heng Mui Keng Terrace Singapore 119613 Email: ahhwee@krdl.org.sg Abstract Text mining, also known as text data mining or knowledge discovery from textual databases, refers to the process of extracting

  9. Data Mining to Characterize Signatures of Impending System Events

    E-Print Network [OSTI]

    Data Mining to Characterize Signatures of Impending System Events or Performance from PMU the Future Electric Energy System #12;#12;Data Mining to Characterize Signatures of Impending System Events Mining to Characterize Signatures of Impending System Events or Performance from PMU Measurements

  10. Standardization of Components, Products and Processes with Data Mining

    E-Print Network [OSTI]

    Kusiak, Andrew

    1 Standardization of Components, Products and Processes with Data Mining Bruno AGARD Département de - 1527, USA andrew-kusiak@uiowa.edu ABSTRACT Data mining offers tools for extracting knowledge from databases. This paper discusses applications of data mining in standardization of components, products

  11. Data Mining and Applied Linear Algebra Department of Mathematics

    E-Print Network [OSTI]

    Data Mining and Applied Linear Algebra Moody Chu Department of Mathematics North Carolina State area of disciplines. Extract- ing interesting knowledge from raw data, or data mining in a broader precisely defined. The ba- sic principle of data mining is to distinguish which variable is related to which

  12. Proof Mining in Ergodic Theory and Topological Dynamics

    E-Print Network [OSTI]

    Gerhardy, Philipp

    Proof Mining in Ergodic Theory and Topological Dynamics Philipp Gerhardy Department of Mathematics, University of Oslo Proof Mining in Ergodic Theory and Topological Dynamics ­ p.1/10 #12;Introduction "Proof mining" is the subfield of mathematical logic concerned with extracting additional information from

  13. CHARM: An Efficient Algorithm for Closed Association Rule Mining

    E-Print Network [OSTI]

    Bystroff, Chris

    CHARM: An Efficient Algorithm for Closed Association Rule Mining Mohammed J. Zaki and Ching,hsiaocg@cs.rpi.edu http://www.cs.rpi.edu/#24;zaki Abstract The task of mining association rules consists of two main steps all high confidence rules among itemsets. In this paper we show that it is not necessary to mine all

  14. Mining of EL-GCIs Daniel Borchmann and Felix Distel

    E-Print Network [OSTI]

    Baader, Franz

    Mining of EL-GCIs Daniel Borchmann and Felix Distel Faculty of Computer Science TU Dresden Dresden, Germany {borch,felix}@tcs.inf.tu-dresden.de Abstract--We consider an existing approach for mining general mining, this approach allows more complex patterns to be obtained. Ours is the first implementation

  15. TextVis: An Integrated Visual Environment for Text Mining *

    E-Print Network [OSTI]

    Lindell, Yehuda

    TextVis: An Integrated Visual Environment for Text Mining * David Landau, Ronen Feldman, Yonatan University of Washington Seattle, WA zamir@cs.washington.edu Abstract. TextVis is a visual data mining system can be used to browse the collection. TextVis takes a multi­strategy approach to text mining

  16. An Extreme Point Tabu Search Method for Data Mining

    E-Print Network [OSTI]

    Mitchell, John E.

    An Extreme Point Tabu Search Method for Data Mining Kristin P. Bennett \\Lambda Jennifer A. Blue error of all the decisions in the tree concurrently. Decision trees are ideal for data­mining because optimize existing decision trees. This capability can be used in data mining for avoiding overfitting

  17. Data mining in high energy physics Bertrand Brelier

    E-Print Network [OSTI]

    Prodiæ, Aleksandar

    Data mining in high energy physics Bertrand Brelier SOSCIP July 3, 2014 Bertrand Brelier (SOSCIP) Data mining in high energy physics July 3, 2014 1 / 8 #12;The Large Hadron Collider (LHC) Bertrand Brelier (SOSCIP) Data mining in high energy physics July 3, 2014 2 / 8 #12;The ATLAS detector Bertrand

  18. Efficiently Mining Long Patterns from Databases Roberto J. Bayardo Jr.

    E-Print Network [OSTI]

    Fiat, Amos

    Efficiently Mining Long Patterns from Databases Roberto J. Bayardo Jr. IBM Almaden Research Center http:Nwww.almaden.ibm.com/cs/people/bayardo/ bayardo@alum.mit.edu Abstract Wepresenta pattern-mining the fundamentaloperationbehind several common data-mining tasksincluding associationrule [l] andsequentialpatternmining [4

  19. RUTGERS -THE STATE UNIVERSITY OF NEW JERSEY Data Mining

    E-Print Network [OSTI]

    RUTGERS - THE STATE UNIVERSITY OF NEW JERSEY Data Mining Fall 2012 Instructor: Dr. Hui Xiong E or by appointment Text Book: "Introduction to Data Mining", by Pang-Ning Tan, Michael Steinbach, Vipin Kumar for analysts to sift through the data even though it may contain useful information. Data mining holds great

  20. Data Mining: Where is it Heading? Database Systems Research Laboratory

    E-Print Network [OSTI]

    Han, Jiawei

    Data Mining: Where is it Heading? (Panel) Jiawei Han Database Systems Research Laboratory School of Computing Science Simon Fraser University, B.C., Canada V5A 1S6 E-mail: han@cs.sfu.ca Abstract Data mining on the issues in the field. Data mining has attracted popular interest recently, due to the high demand