LEADER 01917nam 2200409z- 450 001 9910557234503321 005 20211118 035 $a(CKB)5400000000041598 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/73010 035 $a(oapen)doab73010 035 $a(EXLCZ)995400000000041598 100 $a20202111d2019 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aChemometrics-based Spectroscopy for Pharmaceutical and Biomedical Analysis 210 $cFrontiers Media SA$d2019 215 $a1 online resource (177 p.) 311 08$a2-88945-845-8 330 $aThis eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact 606 $aScience: general issues$2bicssc 610 $abiomedical analysis 610 $achemometrics 610 $apharmaceutical analysis 610 $aspectra 610 $awavelet transform 615 7$aScience: general issues 700 $aVu Dang$b Hoang$4edt$01286898 702 $aMarini$b  Federico$4edt 702 $aVu Dang$b Hoang$4oth 702 $aMarini$b  Federico$4oth 906 $aBOOK 912 $a9910557234503321 996 $aChemometrics-based Spectroscopy for Pharmaceutical and Biomedical Analysis$93019972 997 $aUNINA LEADER 04702nam 22006975 450 001 9910919645803321 005 20250919135504.0 010 $a9783031748707 010 $a3031748700 024 7 $a10.1007/978-3-031-74870-7 035 $a(MiAaPQ)EBC31862760 035 $a(Au-PeEL)EBL31862760 035 $a(CKB)37099104500041 035 $a(DE-He213)978-3-031-74870-7 035 $a(OCoLC)1485003000 035 $a(EXLCZ)9937099104500041 100 $a20241229d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aQPLEX: A Computational Modeling and Analysis Methodology for Stochastic Systems /$fby Antonius B. Dieker, Steven T. Hackman 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (357 pages) 225 1 $aSpringer Series in Operations Research and Financial Engineering,$x2197-1773 311 08$a9783031748691 311 08$a3031748697 327 $a-- Preliminaries. -- First Look at QPLEX. -- Part 1 QPLEX Modeling and Calculus. -- Introduction to QPLEX Modeling and Calculus. -- Simple Transition Dynamics. -- Models with Simple Transition Dynamics. -- Advanced Transition Dynamics. -- Models with Advanced Transition Dynamics. -- Conditional and Joint Probabilities. -- Part 2 Graphical QPLEX Calculus. -- Introduction to Graphical QPLEX Calculus. -- Subsystem QPLEX Calculus. -- Conditional Independence. -- Information Structure. -- Graphical QPLEX Calculus with Distributional Programs. -- Efficient Calculation for Distributional Programs. -- Part 3 Foundations. -- Introduction to Foundations. -- Optimality of QPLEX Iterates. -- Exactness Results. 330 $aThis book introduces QPLEX, a powerful computational framework designed for modeling and analyzing nonstationary stochastic systems with large state spaces. The methodology excels at rapidly and accurately generating approximate distributions of system performance over time, offering a robust tool for understanding the dynamics of such systems. QPLEX circumvents the curse of dimensionality by imposing conditional independence, which may be represented via a probabilistic graphical model, and exploiting model dynamics. It is specifically crafted for transient analysis of nonstationary systems, often encountered in practical applications but rarely addressed by traditional techniques. It can work directly with empirical distributions and requires no stability assumptions. Since its output is not noisy, QPLEX is tailor-made for sensitivity analysis and optimization. The methodology?s few model primitives are flexible enough to specify a rich array of models. For example, models representing queueing networks can exhibit challenging characteristics such as short operational horizons; time-varying arrival rates, service durations, and numbers of servers; and complex routing of entities. The text is accessible to those with engineering, computer science, or mathematics backgrounds and knowledge of probability and stochastic models at the advanced undergraduate level. Many fully worked-out examples aid the comprehension of the concepts and calculations, ensuring readers can effectively apply the methods to real-world systems and making this book a valuable resource for researchers and practitioners alike. This is an open access book. 410 0$aSpringer Series in Operations Research and Financial Engineering,$x2197-1773 606 $aMathematical models 606 $aStochastic analysis 606 $aStochastic processes 606 $aMathematical Modeling and Industrial Mathematics 606 $aStochastic Analysis 606 $aStochastic Processes 606 $aModels matemātics$2thub 606 $aAnālisi estocāstica$2thub 606 $aProcessos estocāstics$2thub 608 $aLlibres electrōnics$2thub 615 0$aMathematical models. 615 0$aStochastic analysis. 615 0$aStochastic processes. 615 14$aMathematical Modeling and Industrial Mathematics. 615 24$aStochastic Analysis. 615 24$aStochastic Processes. 615 7$aModels matemātics 615 7$aAnālisi estocāstica 615 7$aProcessos estocāstics 676 $a003.3 700 $aDieker$b Antonius B$01781433 701 $aHackman$b Steven T$0312976 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910919645803321 996 $aQPLEX: A Computational Modeling and Analysis Methodology for Stochastic Systems$94306251 997 $aUNINA