LEADER 01479nam 2200409 a 450 001 9910697044903321 005 20230902161904.0 035 $a(CKB)5470000002384454 035 $a(OCoLC)710807769 035 $a(EXLCZ)995470000002384454 100 $a20110401d2005 ua 0 101 0 $aeng 135 $aurmn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aPredicting the viscosity of low VOC vinyl ester and fatty acid-based resins$b[electronic resource] /$fby John J. La Scala ... [and others] 210 1$aAberdeen Proving Ground, MD :$cArmy Research Laboratory,$d[2005] 215 $a1 online resource (vi, 38 pages) 225 1 $aARL-TR ;$v3681 300 $aTitle from title screen (viewed on Mar. 31, 2011). 300 $a"December 2005." 320 $aIncludes bibliographical references. 410 0$aARL-TR (Aberdeen Proving Ground, Md.) ;$v3681. 517 3 $aPredicting the viscosity of low volatile organic compound vinyl ester and fatty acid-based resins 606 $aGums and resins$xViscosity 606 $aStyrene 615 0$aGums and resins$xViscosity. 615 0$aStyrene. 701 $aLa Scala$b John J$01404133 712 02$aU.S. Army Research Laboratory. 801 0$bGPO 801 1$bGPO 906 $aBOOK 912 $a9910697044903321 996 $aPredicting the viscosity of low VOC vinyl ester and fatty acid-based resins$93478171 997 $aUNINA LEADER 03196nam 22006015 450 001 9910254836203321 005 20200706055700.0 010 $a981-10-5278-6 024 7 $a10.1007/978-981-10-5278-1 035 $a(CKB)3710000001631431 035 $a(MiAaPQ)EBC4935683 035 $a(DE-He213)978-981-10-5278-1 035 $z(PPN)258861436 035 $a(PPN)203851722 035 $a(EXLCZ)993710000001631431 100 $a20170802d2017 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aQoS Prediction in Cloud and Service Computing $eApproaches and Applications /$fby Yilei Zhang, Michael R. Lyu 205 $a1st ed. 2017. 210 1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2017. 215 $a1 online resource (130 pages) 225 1 $aSpringerBriefs in Computer Science,$x2191-5768 311 $a981-10-5277-8 320 $aIncludes bibliographical references at the end of each chapters. 327 $a1. Introduction -- 2. Neighborhood-Based QoS Prediction -- 3. Time-Aware Model-Based QoS Prediction -- 4. Online QoS Prediction -- 5. QoS-AwareWeb Service Searching -- 6. QoS-Aware Byzantine Fault Tolerance -- 7. Conclusion and Discussion. 330 $aThis book offers a systematic and practical overview of Quality of Service prediction in cloud and service computing. Intended to thoroughly prepare the reader for research in cloud performance, the book first identifies common problems in QoS prediction and proposes three QoS prediction models to address them. Then it demonstrates the benefits of QoS prediction in two QoS-aware research areas. Lastly, it collects large-scale real-world temporal QoS data and publicly releases the datasets, making it a valuable resource for the research community. The book will appeal to professionals involved in cloud computing and graduate students working on QoS-related problems. . 410 0$aSpringerBriefs in Computer Science,$x2191-5768 606 $aComputer software?Reusability 606 $aSoftware engineering 606 $aApplication software 606 $aPerformance and Reliability$3https://scigraph.springernature.com/ontologies/product-market-codes/I12077 606 $aSoftware Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/I14029 606 $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040 615 0$aComputer software?Reusability. 615 0$aSoftware engineering. 615 0$aApplication software. 615 14$aPerformance and Reliability. 615 24$aSoftware Engineering. 615 24$aInformation Systems Applications (incl. Internet). 676 $a005.8 700 $aZhang$b Yilei$4aut$4http://id.loc.gov/vocabulary/relators/aut$01061835 702 $aLyu$b Michael R$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910254836203321 996 $aQoS Prediction in Cloud and Service Computing$92520448 997 $aUNINA