LEADER 00973nam0-2200325---450- 001 990004088980403321 005 20110614165449.0 010 $a0-8131-1570-1 035 $a000408898 035 $aFED01000408898 035 $a(Aleph)000408898FED01 035 $a000408898 100 $a19990604d1986----km-y0itay50------ba 101 0 $aeng 102 $aUS 105 $a--------001yy 200 1 $a<>return of Astraea$ean astral-imperial myth in Calderon$fFrederick A. De Armas 210 $aLexington(Kentucky)$cThe University press of Kentucky$d1986 215 $aIX, 262 p.$d23 cm 225 1 $aStudies in Romance languages$v32 610 0 $aCalderon de la Barca, Pedro 676 $a862.3 700 1$aDe Armas,$bFrederick Alfred$0158370 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990004088980403321 952 $a862.3 BARCA/S 25$bDip.f.m.2778$fFLFBC 959 $aFLFBC 996 $aReturn of Astraea$9479456 997 $aUNINA LEADER 03889nam 22005535 450 001 9910158674503321 005 20200710224200.0 010 $a3-658-16782-3 024 7 $a10.1007/978-3-658-16782-0 035 $a(CKB)3710000001007862 035 $a(DE-He213)978-3-658-16782-0 035 $a(MiAaPQ)EBC4774760 035 $a(PPN)198339984 035 $a(EXLCZ)993710000001007862 100 $a20170102d2017 u| 0 101 0 $ager 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDigitale Werkzeuge zur integrierten Infrastrukturbauwerksplanung $eAm Beispiel des Schienen- und Straßenbaus /$fvon Mathias Obergrießer 205 $a1st ed. 2017. 210 1$aWiesbaden :$cSpringer Fachmedien Wiesbaden :$cImprint: Springer Vieweg,$d2017. 215 $a1 online resource (X, 245 S. 148 Abb., 16 Abb. in Farbe.) 300 $a"Research"--Cover. 311 $a3-658-16781-5 320 $aIncludes bibliographical references. 327 $aEinführung eines modellgestützten Planungsprozesses im Infrastrukturbau -- Beschreibung geometrischer und parametrisch-assoziativer Modellierungsansätze -- Definition eines infrastruktur-spezifischen Modellierungsleitfadens -- Konzepte zur Umsetzung des parametrisch-assoziativen Infrastrukturinformationsmodells. 330 $aDer Autor entwickelt neue digitale Werkzeuge und Methoden, die eine durchgängige und integrierte Planung einer Infrastrukturmaßnahme anhand eines föderierten Modells ermöglichen. Dabei werden verschiedene Lösungsansätze vorgestellt, die eine Erweiterung der traditionellen Planungsprozesse vorsehen. Mathias Obergrießer fasst diese Methoden und digitalen Werkzeuge zu einem leistungsfähigen Modellierungsleitfaden zusammen, der eine effektive Planung des parametrisch-assoziativen Infrastrukturinformationsmodells erlaubt. Die erfolgreiche Validierung des Leitfadens erfolgt anhand verschiedener Anwendungsbeispiele aus der Praxis. Der Inhalt Einführung eines modellgestützten Planungsprozesses im Infrastrukturbau Beschreibung geometrischer und parametrisch-assoziativer Modellierungsansätze Definition eines infrastruktur-spezifischen Modellierungsleitfadens Konzepte zur Umsetzung des parametrisch-assoziativen Infrastrukturinformationsmodells Die Zielgruppen Dozierende und Studierende des Bauingenieurwesens Praktiker und Praktikerinnen in Ingenieurbüros Der Autor Mathias Obergrießer ist seit 2008 an der Hochschule Regensburg als Lehrbeauftragter tätig. Seine Forschungsschwerpunkte liegen im Bereich der parametrisch-assoziativen 3D-Infrastrukturinformationsmodellierung sowie in der Integration von geotechnischen Planungsprozessen. Seit 2014 ist er hauptverantwortlicher Tragwerksplaner für Infrastrukturbauwerke im einem deutschen Ingenieurbüro. 606 $aConstruction 606 $aApplied mathematics 606 $aEngineering mathematics 606 $aCivil engineering 606 $aBasics of Construction$3https://scigraph.springernature.com/ontologies/product-market-codes/K1700X 606 $aMathematical and Computational Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T11006 606 $aCivil Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T23004 615 0$aConstruction. 615 0$aApplied mathematics. 615 0$aEngineering mathematics. 615 0$aCivil engineering. 615 14$aBasics of Construction. 615 24$aMathematical and Computational Engineering. 615 24$aCivil Engineering. 676 $a720 700 $aObergrießer$b Mathias$4aut$4http://id.loc.gov/vocabulary/relators/aut$01226452 906 $aBOOK 912 $a9910158674503321 996 $aDigitale Werkzeuge zur integrierten Infrastrukturbauwerksplanung$92847723 997 $aUNINA LEADER 01463nam0 22002891i 450 001 UON00202812 005 20250515022120.437 100 $a20030730d1899 |0itac50 ba 101 $aita 102 $aIT 105 $a|||| ||||| 200 1 $aˆIl ‰P. Giusto da Urbino missionario in Abissinia e le esplorazioni africane$fFrancesco Tarducci 210 $aFaenza$ctip. G. Montanari$d1899 215 $a227 p., [1] c. di tav.$critr.$d19 cm 316 $aIl volume è collocato nei cantinati della Sezione Giusso, attualmente non accessibili.$5IT-UONSI I RELIGB/0082 606 $aCappuccini$xEtiopia$3UONC022881$2FI 606 $aCappuccini$xMissioni$xEtiopia$x1864-1881$3UONC104618$2FI 606 $aGiusto da Urbino (1814-1856)$3UONC104765$2FI 620 $aIT$dFaenza$3UONL000235 686 $aRARI AFR.OR VIII$cAFRICA ORIENTALE - GEOGRAFIA E VIAGGI$2A 700 1$aTarducci$bFrancesco$3UONV103324 712 02$aTipografia G. Montanari$3UONV297088$4750 801 $aIT$bSOL$c20250516$gRICA 912 $aUON00202812 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI B 0082 $eSI MR 20396 5 0082 Il volume è collocato nei cantinati della Sezione Giusso, attualmente non accessibili. 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI RARI AFR.OR VIII 003 $eSI MR 11583 7 003 997 $aUNIOR LEADER 05120nam 22007215 450 001 9910917797503321 005 20250526171211.0 010 $a9783031776847 010 $a3031776844 024 7 $a10.1007/978-3-031-77684-7 035 $a(CKB)37037090600041 035 $a(MiAaPQ)EBC31850030 035 $a(Au-PeEL)EBL31850030 035 $a(DE-He213)978-3-031-77684-7 035 $a(EXLCZ)9937037090600041 100 $a20241218d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPrinciples of Nonlinear Filtering Theory /$fby Stephen S.-T. Yau, Xiuqiong Chen, Xiaopei Jiao, Jiayi Kang, Zeju Sun, Yangtianze Tao 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (477 pages) 225 1 $aAlgorithms and Computation in Mathematics,$x2512-3254 ;$v33 311 08$a9783031776830 311 08$a3031776836 327 $aPreface -- I. Preliminary knowledge -- 1. Probability theory -- 2. Stochastic processes -- 3. Stochastic differential equations -- 4. Optimization -- II. Filtering theory -- 5. The filtering equations -- 6. Estimation algebra -- III. Numerical algorithms -- 7. Yau-Yau algorithm -- 8. Direct methods -- 9. Classical filtering methods -- 10. Estimation algorithms based on deep learning. 330 $aThis text presents a comprehensive and unified treatment of nonlinear filtering theory, with a strong emphasis on its mathematical underpinnings. It is tailored to meet the needs of a diverse readership, including mathematically inclined engineers and scientists at both graduate and post-graduate levels. What sets this book apart from other treatments of the topic is twofold. Firstly, it offers a complete treatment of filtering theory, providing readers with a thorough understanding of the subject. Secondly, it introduces updated methodologies and applications that are crucial in today?s landscape. These include finite-dimensional filters, the Yau-Yau algorithm, direct methods, and the integration of deep learning with filtering problems. The book will be an invaluable resource for researchers and practitioners for years to come. With a rich historical backdrop dating back to Gauss and Wiener, the exposition delves into the fundamental principles underpinning the estimation of stochastic processes amidst noisy observations?a critical tool in various applied domains such as aircraft navigation, solar mapping, and orbit determination, to name just a few. Substantive exercises and examples given in each chapter provide the reader with opportunities to appreciate applications and ample ways to test their understanding of the topics covered. An especially nice feature for those studying the subject independent of a traditional course setting is the inclusion of solutions to exercises at the end of the book. The book is structured into three cohesive parts, each designed to build the reader's understanding of nonlinear filtering theory. In the first part, foundational concepts from probability theory, stochastic processes, stochastic differential equations, and optimization are introduced, providing readers with the necessary mathematical background. The second part delves into theoretical aspects of filtering theory, covering topics such as the stochastic partial differential equation governing the posterior density function of the state, and the estimation algebra theory of systems with finite-dimensional filters. Moving forward, the third part of the book explores numerical algorithms for solving filtering problems, including the Yau-Yau algorithm, direct methods, classical filtering algorithms like the particle filter, and the intersection of filtering theory with deep learning. 410 0$aAlgorithms and Computation in Mathematics,$x2512-3254 ;$v33 606 $aStochastic processes 606 $aAutomatic control 606 $aDifferential equations 606 $aEquacions diferencials$2thub 606 $aProcessos estocàstics$2thub 606 $aStochastic Processes 606 $aControl and Systems Theory 606 $aDifferential Equations 608 $aLlibres electrònics.$2thub 615 0$aStochastic processes. 615 0$aAutomatic control. 615 0$aDifferential equations. 615 7$aEquacions diferencials. 615 7$aProcessos estocàstics 615 14$aStochastic Processes. 615 24$aControl and Systems Theory. 615 24$aDifferential Equations. 676 $a519.23 700 $aYau$b Stephen S. T$01587106 701 $aChen$b Xiuqiong$01780666 701 $aJiao$b Xiaopei$01780667 701 $aKang$b Jiayi$01780668 701 $aSun$b Zeju$01780669 701 $aTao$b Yangtianze$01780670 701 $aYau$b Stephen S. T$01587106 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910917797503321 996 $aPrinciples of Nonlinear Filtering Theory$94304998 997 $aUNINA