LEADER 01806oam 2200481I 450 001 9910707137603321 005 20160506145104.0 035 $a(CKB)5470000002462123 035 $a(OCoLC)703645461 035 $a(EXLCZ)995470000002462123 100 $a20110225j199610 ua 0 101 0 $aeng 135 $aurbn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAcoustic emission monitoring of the DC-XA composite liquid hydrogen tank during structural testing /$fC. Wilkerson 210 1$aMSFC, Alabama :$cNational Aeronautics and Space Administration, Marshall Space Flight Center,$dOctober 1996. 215 $a1 online resource (iv, 6 pages) $cillustrations 225 1 $aNASA technical memorandum ;$v108520 300 $aTitle from title screen (viewed May 6, 2016). 300 $a"October 1996." 300 $a"Performing organization: George C. Marshall Space Flight Center, Marshall Space Flight Center, Alabama"--Report documentation page. 606 $aAcoustic emission$2nasat 606 $aCompression loads$2nasat 606 $aFuel tanks$2nasat 606 $aStructural failure$2nasat 606 $aTensile strength$2nasat 615 7$aAcoustic emission. 615 7$aCompression loads. 615 7$aFuel tanks. 615 7$aStructural failure. 615 7$aTensile strength. 700 $aWilkerson$b C.$01400887 712 02$aGeorge C. Marshall Space Flight Center, 712 02$aUnited States.$bNational Aeronautics and Space Administration, 801 0$bSSM 801 1$bSSM 801 2$bGPO 906 $aBOOK 912 $a9910707137603321 996 $aAcoustic emission monitoring of the DC-XA composite liquid hydrogen tank during structural testing$93468578 997 $aUNINA LEADER 03402nam 2200601Ia 450 001 9910298161303321 005 20200520144314.0 010 $a1-4614-7095-1 024 7 $a10.1007/978-1-4614-7095-3 035 $a(CKB)2670000000388201 035 $a(EBL)1317625 035 $a(SSID)ssj0000928934 035 $a(PQKBManifestationID)11490601 035 $a(PQKBTitleCode)TC0000928934 035 $a(PQKBWorkID)10910991 035 $a(PQKB)10692734 035 $a(MiAaPQ)EBC1317625 035 $a(DE-He213)978-1-4614-7095-3 035 $a(PPN)187689156 035 $a(EXLCZ)992670000000388201 100 $a20111102d2014 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aGame theory and business applications /$fKalyan Chatterjee, William Samuelson, editors 205 $a2nd ed. 2014. 210 $aNew York $cSpringer$d2014 215 $a1 online resource (406 p.) 225 0 $aInternational series in operations research & management science 300 $aDescription based upon print version of record. 311 $a1-4899-9815-2 311 $a1-4614-7094-3 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- Game Theory Models in Finance -- Game Theoretic Models in Accounting -- GT and Marketing -- Game Theoretic Models in Operations Management and Information Systems -- Incentive Contracting and Franchise Decisions -- Game Theory and the Practice of Bargaining -- GT Models of Settlement and Litigation -- GT and the Law -- Cooperation in R&D -- A GT Model of Tenure -- GT and Experimental Economics -- Auctions in Theory and Practice -- Auctions and Bidder Collusion. 330 $aGame theory has been applied to a growing list of practical problems, from antitrust analysis to monetary policy; from the design of auction institutions to the structuring of incentives within firms; from patent races to dispute resolution. The purpose of Game Theory and Business Applications is to show how game theory can be used to model and analyze business decisions. The contents of this revised edition contain a wide variety of business functions ? from accounting to operations, from marketing to strategy to organizational design. In addition, specific application areas include market competition, law and economics, bargaining and dispute resolution, and competitive bidding. All of these applications involve competitive decision settings, specifically situations where a number of economic agents in pursuit of their own self-interests and in accordance with the institutional ?rules of the game? take actions that together affect all of their fortunes. As this volume demonstrates, game theory provides a compelling guide for analyzing business decisions and strategies. 410 0$aInternational Series in Operations Research & Management Science,$x0884-8289 ;$v194 606 $aGame theory 606 $aEconomics, Mathematical 615 0$aGame theory. 615 0$aEconomics, Mathematical. 676 $a658.4 676 $a658.40353 701 $aChatterjee$b Kalyan$0125606 701 $aSamuelson$b William$0248823 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910298161303321 996 $aGame theory and business applications$94187285 997 $aUNINA LEADER 03892nam 2201045z- 450 001 9910557759303321 005 20210501 035 $a(CKB)5400000000045769 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/68569 035 $a(oapen)doab68569 035 $a(EXLCZ)995400000000045769 100 $a20202105d2021 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aApplications of Information Theory to Epidemiology 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021 215 $a1 online resource (238 p.) 311 08$a3-0365-0316-1 311 08$a3-0365-0317-X 330 $a? Applications of Information Theory to Epidemiology collects recent research findings on the analysis of diagnostic information and epidemic dynamics. ? The collection includes an outstanding new review article by William Benish, providing both a historical overview and new insights. ? In research articles, disease diagnosis and disease dynamics are viewed from both clinical medicine and plant pathology perspectives. Both theory and applications are discussed. ? New theory is presented, particularly in the area of diagnostic decision-making taking account of predictive values, via developments of the predictive receiver operating characteristic curve. ? New applications of information theory to the analysis of observational studies of disease dynamics in both human and plant populations are presented. 606 $aBiology, life sciences$2bicssc 606 $aResearch & information: general$2bicssc 610 $aAsiatic citrus canker 610 $aAtangana-Baleanu derivative 610 $aaverage mutual information 610 $abalance 610 $aBayes' rule 610 $abinormal 610 $aCaputo derivative 610 $aCaputo-Fabrizio derivative 610 $adeployment 610 $adeterministic dynamics 610 $adiagnostic information 610 $adiagnostic test 610 $adirect assay 610 $aearly detection 610 $aEbola model 610 $aempirical 610 $aentropy 610 $aepidemic model 610 $aevaluation 610 $aexpected mutual information 610 $afield diagnostic 610 $aFisher scoring algorithm 610 $aforecast 610 $aHIV/AIDS epidemic 610 $ainformation theory 610 $aJensen-Shannon divergence 610 $alatent class 610 $aleaf plot 610 $alikelihood ratio 610 $amultiple diagnostic tests 610 $amutual information 610 $an/a 610 $anegative predictive value 610 $aNewton-Raphson procedure 610 $anumerical results 610 $aobservational study 610 $apositive predictive value 610 $apredictive ROC curve 610 $aprevalence 610 $aprobability 610 $aPROC curve 610 $aPV-ROC curve 610 $aregression model 610 $arelative entropy 610 $aROC curve 610 $ascent signature 610 $aselection bias 610 $asensitivity 610 $aShannon entropy 610 $aspecificity 610 $aSS-ROC curve 610 $aSS/PV-ROC plot 610 $astochastic processes 610 $atime series 610 $atransient behavior 610 $aurinary bladder cancer 610 $avaccination and treatment intervention controls 615 7$aBiology, life sciences 615 7$aResearch & information: general 700 $aHughes$b Gareth$4edt$01299456 702 $aHughes$b Gareth$4oth 906 $aBOOK 912 $a9910557759303321 996 $aApplications of Information Theory to Epidemiology$93025186 997 $aUNINA LEADER 01282nam0 22003373i 450 001 CFI0656702 005 20251003044144.0 010 $a0127519661 010 $a9780127519661 100 $a20111114d2006 ||||0itac50 ba 101 | $aeng 102 $anl 181 1$6z01$ai $bxxxe 182 1$6z01$an 200 1 $aStatistical methods in the atmospheric sciences$fD. 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