LEADER 01040nam--2200349---450- 001 990006123230203316 005 20160209150904.0 035 $a000612323 035 $aUSA01000612323 035 $a(ALEPH)000612323USA01 035 $a000612323 100 $a20160209d20062008km-y0itay50------ba 101 $aspa 102 $aES 105 $a||||||||001yy 200 1 $aIngeniería de pavimentos$efundamentos, estudios básicos y diseño$fAlfonso Montejo Fonseca 205 $a3. ed. 210 $aBogotà$cUniversidad Católica de Colombia$dcopyr. 2006 (stampa 2008) 215 $avolumi$d24 cm 327 1 $aT. 1.: XXIV, 612 p. - ISBN 410 0$12001 606 0 $aPavimenti$xIngegneria$2BNCF 676 $a690.16 801 0$aIT$bsalbc$gISBD 912 $a990006123230203316 951 $a690.16 MON 1$b1214 Crd.$c690$d00331151 959 $aBK 969 $aCRD 979 $aPAOLA$b90$c20160209$lUSA01$h1439 979 $aPAOLA$b90$c20160209$lUSA01$h1509 996 $aIngeniería de pavimentos$91384812 997 $aUNISA LEADER 10982nam 2200505 450 001 996495567803316 005 20231110233820.0 010 $a3-031-19992-8 035 $a(MiAaPQ)EBC7120743 035 $a(Au-PeEL)EBL7120743 035 $a(CKB)25188965100041 035 $a(PPN)265856043 035 $a(EXLCZ)9925188965100041 100 $a20230310d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aAutomated technology for verification and analysis $e20th International Symposium, ATVA 2022, Beijing, China, October 25-28, 2022, proceedings /$fedited by Ahmed Bouajjani, Luka?s Holi?k, and Zhilin Wu 210 1$aCham, Switzerland :$cSpringer,$d[2022] 210 4$d©2022 215 $a1 online resource (442 pages) 225 1 $aLecture Notes in Computer Science ;$vv.13505 311 08$aPrint version: Bouajjani, Ahmed Automated Technology for Verification and Analysis Cham : Springer International Publishing AG,c2022 9783031199912 327 $aIntro -- Preface -- Organization -- Abstracts of Invited Talks -- Compositional Reasoning about Concurrent Randomized Programs (Extended Abstract) -- Flattening String Constraints -- Runtime Assurance for Verified AI-Based Autonomy -- The Civl Verifier -- Subgame Perfect Equilibrium with an Algorithmic Perspective -- Contents -- Invited Paper -- Learning Monitorable Operational Design Domains for Assured Autonomy -- 1 Introduction -- 2 Motivating Example: Autonomous Lane Keeping -- 3 Optimal Monitors for Operational Design Domains -- 3.1 Learning Monitors for ODDs -- 3.2 Challenges in Learning Monitorable ODDs -- 3.3 Quantitative Monitor Learning -- 3.4 Black-Box vs. White-Box Settings -- 4 Framework -- 4.1 Main Workflow -- 4.2 Simulation-Based Analysis Using VerifAI and Scenic -- 4.3 Data Generation -- 4.4 Conformance Testing -- 5 Experiments -- 5.1 Experimental Setup -- 5.2 Results -- 6 Related Work -- 7 Conclusion -- References -- Reinforcement Learning -- Dynamic Shielding for Reinforcement Learning in Black-Box Environments -- 1 Introduction -- 1.1 Related Works -- 2 Preliminaries -- 2.1 Automata and Games for System Modeling -- 2.2 Safety Automata for Specifications -- 2.3 Shielding for Safe Reinforcement Learning -- 2.4 The RPNI Algorithm for Passive Automata Learning -- 3 Dynamic Shielding with Online Automata Inference -- 3.1 Dynamic Shielding Scheme -- 3.2 Challenge 1: Incompleteness of the Learned FSRS -- 3.3 Challenge 2: Precision in Automata Learning -- 3.4 Theoretical Validity of Our Dynamic Shielding -- 4 Experimental Evaluation -- 4.1 Implementation and Experiments -- 4.2 Benchmarks -- 4.3 RQ1: Safety by Dynamic Shielding in the Training Phase -- 4.4 RQ2: Performance of the Resulting Controller -- 4.5 RQ3: Time Efficiency of Dynamic Shielding -- 5 Conclusions and Perspectives -- References. 327 $aAn Impossibility Result in Automata-Theoretic Reinforcement Learning -- 1 Introduction -- 2 Omega-Automata -- 3 Closure Properties of Acceptance Conditions -- 4 Markov Decision Processes -- 4.1 Optimal Strategies Against Omega-Automata -- 4.2 Optimal Strategies Against Scalar Rewards -- 5 Memoryless Reward Translations for RL -- 5.1 Memoryless Reward Translation -- 5.2 Conditions for Memoryless Reductions -- 6 Conclusion -- References -- Reusable Contracts for Safe Integration of Reinforcement Learning in Hybrid Systems -- 1 Introduction -- 2 Preliminaries -- 2.1 Reinforcement Learning -- 2.2 Simulink and the RL Toolbox -- 2.3 Deductive Verification with the Differential Dynamic Logic -- 2.4 Transformation from Simulink to dL -- 3 Related Work -- 4 Reusable Hybrid Contracts -- 4.1 Illustrating Examples -- 4.2 Recurring Elements -- 4.3 Threshold Pattern -- 4.4 Range Pattern -- 4.5 Range Recovery Pattern -- 4.6 Resilience Contracts -- 4.7 Deductive Verification in KeYmaera X -- 5 Conclusion -- References -- Program Analysis and Verification -- SISL: Concolic Testing of Structured Binary Input Formats via Partial Specification -- 1 Introduction -- 2 Scheme-Based Input Specification Language -- 3 Overview and Implementation -- 4 Experiments and Conclusion -- References -- Fence Synthesis Under the C11 Memory Model -- 1 Introduction -- 2 Overview of FenSying and fFenSying -- 3 Preliminaries -- 4 Background: C11 Memory Model -- 5 Invalidating Buggy Traces with C11 Fences -- 6 Methodology -- 7 Implementation and Results -- 8 Related Work -- 9 Conclusion and Future Work -- References -- Checking Scheduling-Induced Violations of Control Safety Properties -- 1 Introduction -- 2 System Model and Encoding -- 2.1 Control System Model and Evolution -- 2.2 Task Specification -- 2.3 An Abstraction for Task Runs -- 2.4 Control Action Update Modeling. 327 $a2.5 Composing Control and Scheduling Models -- 3 Refining the Abstraction -- 3.1 Overlapping Jobs -- 3.2 Schedule Violation -- 3.3 Work Conservation Violation -- 3.4 Unconstrained Control Updates -- 3.5 Correctness of Refinement -- 4 Tool Design -- 5 Case Study 1: DC Motor Control Model -- 6 Case Study 2: RC Network Control Model -- 7 Case Study 3: F1Tenth Car Model -- 8 Conclusions and Future Work -- References -- Symbolic Runtime Verification for Monitoring Under Uncertainties and Assumptions -- 1 Introduction -- 2 Preliminaries -- 3 A Framework for Symbolic Runtime Verification -- 3.1 Symbolic Expressions -- 3.2 Symbolic Monitor Semantics -- 3.3 A Symbolic Runtime Verification Algorithm -- 4 Symbolic Runtime Verification at Work -- 4.1 Application to Lola Fragments -- 4.2 Temporal Assumptions -- 5 Implementation and Empirical Evaluation -- 6 Conclusion -- References -- SMT and Verification -- Handling Polynomial and Transcendental Functions in SMT via Unconstrained Optimisation and Topological Degree Test -- 1 Introduction -- 2 Background -- 2.1 Unconstrained Global Optimisation -- 2.2 Interval Arithmetic -- 2.3 Robustness and Quasi-decidability -- 2.4 Topological Degree Test -- 3 Local Search Using Unconstrained Global Optimisation -- 4 Solving Bounded Instances with the Topological Degree Test and Interval Arithmetic -- 4.1 Quasi-decidability Procedure -- 4.2 From a Formula with nm to Quasi-dec -- 4.3 A General Procedure -- 5 From Constraint Sets to Formulas -- 5.1 An Eager Approach -- 5.2 A Lazy Approach -- 6 Experimental Evaluation -- 7 Conclusions and Future Work -- References -- Verification of SMT Systems with Quantifiers -- 1 Introduction -- 2 Preliminaries -- 3 Verification of Quantified SMT Systems -- 3.1 Symbolic Formalism -- 3.2 Overview -- 3.3 Ground Instances -- 3.4 Generalizing Invariants from Instances -- 3.5 Invariant Checking. 327 $a3.6 Termination -- 4 Related Work -- 5 Experimental Evaluation -- 6 Conclusions and Future Work -- References -- Projected Model Counting: Beyond Independent Support -- 1 Introduction -- 2 Notation and Preliminaries -- 3 Related Work -- 4 Technical Contribution -- 4.1 Extremal Properties of GIS and UBS -- 4.2 Algorithm to Compute Projected Count Using UBS -- 5 Experimental Evaluation -- 6 Conclusion -- References -- Automata and Applications -- Minimization of Automata for Liveness Languages -- 1 Introduction -- 2 Preliminaries -- 2.1 Automata -- 2.2 Liveness Languages -- 2.3 Graphs, Nice Graphs, and the Vertex-Cover Problem -- 3 Live1 Languages -- 3.1 Minimizing Automata for Live1 and Doom1 Languages -- 4 Live2 Languages -- 4.1 Minimizing DBWs and GFG-NBWs for Live2 Languages -- 4.2 Minimizing DCWs and GFG-NCWs for Doom2 Languages -- 4.3 Minimizing Automata with Transition-Based Acceptance for Live2 Languages -- 5 Live3 Languages -- References -- Temporal Causality in Reactive Systems -- 1 Introduction -- 2 Preliminaries -- 3 Motivating Example -- 4 Property Causality -- 4.1 Interventions -- 4.2 Contingencies -- 4.3 Actual Causality for Trace Properties -- 5 Checking -Regular Causality -- 5.1 Interventions -- 5.2 Contingencies -- 5.3 Minimality -- 5.4 Deciding -Regular Causality -- 6 Related Work -- 7 Conclusion -- References -- PDAAAL: A Library for Reachability Analysis of Weighted Pushdown Systems -- 1 Introduction -- 2 Weighted Pushdown Systems and Reachability -- 3 Implemented Algorithms and PDAAAL Architecture -- 4 Comparison with State-of-the-Art -- 5 Applications -- 6 Conclusion -- References -- Active Learning -- Learning Deterministic One-Clock Timed Automata via Mutation Testing -- 1 Introduction -- 2 Preliminaries -- 2.1 Deterministic One-Clock Timed Automata -- 2.2 Active Learning Algorithm for DOTAs -- 2.3 Model-Based Mutation Testing. 327 $a3 Mutation-Based Testing for DOTAs -- 3.1 The Process Overview -- 3.2 Heuristic Test-Case Generation -- 3.3 Mutation and Score-Based Test-Case Selection -- 4 Learning-Friendly Mutation Operators for DOTAs -- 4.1 Timed Mutation Operator -- 4.2 Split-Location Mutation Operator -- 5 Implementation and Experiments -- 5.1 Case Studies -- 5.2 Evaluation of Improvements -- 6 Conclusion -- References -- Active Learning of One-Clock Timed Automata Using Constraint Solving -- 1 Introduction -- 2 Preliminaries -- 3 Learning Algorithm -- 3.1 Alignment and Comparison of Timed Words -- 3.2 Timed Observation Table -- 3.3 Encoding of Readiness Constraints -- 3.4 Hypothesis Construction -- 3.5 Main Algorithm and Correctness -- 4 Extension to Deterministic Timed Mealy Machines -- 5 Implementation and Experiments -- 5.1 Experiments on DOTAs -- 5.2 Experiments on TMMs -- 6 Conclusion -- References -- Learning and Characterizing Fully-Ordered Lattice Automata -- 1 Introduction -- 2 Preliminaries -- 3 A Myhill-Nerode Characterization for FOLAs -- 3.1 No Unique Minimal FOLA -- 3.2 Difficulties in Defining f -- 3.3 Defining the Equivalence Relation -- 3.4 The Correspondence Between f and a Minimal FOLA -- 4 The Learning Algorithm -- 5 Empirical Results -- 6 Conclusions -- References -- Probabilistic and Stochastic Systems -- Optimistic and Topological Value Iteration for Simple Stochastic Games -- 1 Introduction -- 2 Preliminaries -- 2.1 Simple Stochastic Games -- 2.2 Value Iteration and Bounded Value Iteration -- 3 Optimistic Value Iteration -- 4 Precise Topological Value Iteration -- 5 Random Generation of Simple Stochastic Games -- 6 Experiments -- 6.1 Experimental Setup -- 6.2 Overview -- 6.3 Detailed Analysis of Precise Algorithms -- 6.4 Detailed Analysis of Approximate (-Precise) Algorithms -- 7 Conclusion -- References -- Alternating Good-for-MDPs Automata. 327 $a1 Introduction. 410 0$aLecture Notes in Computer Science 606 $aAutomatic theorem proving 615 0$aAutomatic theorem proving. 676 $a511.3 702 $aHoli?k$b Luka?s 702 $aBouajjani$b Ahmed 702 $aWu$b Zhilin 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996495567803316 996 $aAutomated Technology for Verification and Analysis$9772478 997 $aUNISA LEADER 06292oam 22012014 450 001 9910788234803321 005 20230721045630.0 010 $a1-4623-4369-4 010 $a1-4527-2284-6 010 $a1-4518-7019-1 010 $a9786612841125 010 $a1-282-84112-2 035 $a(CKB)3170000000055061 035 $a(EBL)1607934 035 $a(SSID)ssj0000943958 035 $a(PQKBManifestationID)11505877 035 $a(PQKBTitleCode)TC0000943958 035 $a(PQKBWorkID)10982805 035 $a(PQKB)11299459 035 $a(OCoLC)763099184 035 $a(MiAaPQ)EBC1607934 035 $a(IMF)WPIEE2008161 035 $a(EXLCZ)993170000000055061 100 $a20020129d2008 uf 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 12$aA U.S. Financial Conditions Index : $ePutting Credit Where Credit is Due /$fAndrew Swiston 210 1$aWashington, D.C. :$cInternational Monetary Fund,$d2008. 215 $a1 online resource (37 p.) 225 1 $aIMF Working Papers 225 0$aIMF working paper ;$vWP/08/161 300 $aDescription based upon print version of record. 311 $a1-4519-1472-5 320 $aIncludes bibliographical references. 327 $aContents; I. Introduction and Literature Review; II. Building a Better Financial Conditions Index; A. Why VAR and IRF?; B. Whose Lending? Which Standards?; Figures; 1. Lending Standards and GDP Growth; Tables; 1. Lending Standards and Real Activity: Correlations; 2. Lending Standards and Financial Variables: Correlations; 2. Response of GDP to Lending Standards; C. Which Other Variables Enter the Mix?; 3. Response of GDP to Risk-Free Interest Rates; 4. Response of GDP to Default Risk and Volatility; 5. Response of GDP to Asset Prices; 6. Lending Standards and the High Yield Spread 327 $aIII. Financial Conditions and GrowthA. What are the Guts of the FCI?; B. Which Financial Conditions Matter?; 7. Response of GDP to Financial Shocks; 8. Response of Financial Conditions to Lending Standards; C. What Role for Credit Aggregates?; 9. Credit Availability and the Impact of Monetary Policy on Growth; 10. Response of GDP to Credit Aggregates; D. What is the FCI's Contribution to Growth?; 3. Financial Conditions and Real Activity: Correlations and Variance Decompositions; 11. Financial Conditions Index; 12. Financial Shocks and Contributions to the FCI 327 $aE. Where Do Financial Conditions Hit Hardest?13. Individual Contributions to the FCI; 14. Response of Components of Demand to Financial Shocks; F. Can the FCI See Into the Future?; 15. Leading Financial Conditions Index; IV. Conclusions; References 330 3 $aThis paper uses vector autoregressions and impulse-response functions to construct a U.S. financial conditions index (FCI). Credit availability?proxied by survey results on lending standards?is an important driver of the business cycle, accounting for over 20 percent of the typical contribution of financial factors to growth. A net tightening in lending standards of 20 percentage points reduces economic activity by ¾ percent after one year and 1¼ percent after two years. Much of the impact of monetary policy on the economy also works through its effects on credit supply, which is evidence supporting the existence of a credit channel of monetary policy. Shocks to corporate bond yields, equity prices, and real exchange rates also contribute to fluctuations in the FCI. This FCI is an accurate predictor of real GDP growth, anticipating turning points in activity with a lead time of six to nine months. 15B. 410 0$aIMF Working Papers; Working Paper ;$vNo. 2008/161 606 $aLoans$zUnited States$xEconometric models 606 $aCredit$zUnited States$xEconometric models 606 $aBanks and Banking$2imf 606 $aEconometrics$2imf 606 $aInvestments: Stocks$2imf 606 $aMoney and Monetary Policy$2imf 606 $aMonetary Policy, Central Banking, and the Supply of Money and Credit: General$2imf 606 $aTime-Series Models$2imf 606 $aDynamic Quantile Regressions$2imf 606 $aDynamic Treatment Effect Models$2imf 606 $aDiffusion Processes$2imf 606 $aInterest Rates: Determination, Term Structure, and Effects$2imf 606 $aPension Funds$2imf 606 $aNon-bank Financial Institutions$2imf 606 $aFinancial Instruments$2imf 606 $aInstitutional Investors$2imf 606 $aMonetary economics$2imf 606 $aEconometrics & economic statistics$2imf 606 $aFinance$2imf 606 $aInvestment & securities$2imf 606 $aCredit$2imf 606 $aVector autoregression$2imf 606 $aBank credit$2imf 606 $aShort term interest rates$2imf 606 $aStocks$2imf 606 $aInterest rates$2imf 607 $aUnited States$xEconomic conditions$xEconometric models 607 $aUnited States$2imf 615 0$aLoans$xEconometric models. 615 0$aCredit$xEconometric models. 615 7$aBanks and Banking 615 7$aEconometrics 615 7$aInvestments: Stocks 615 7$aMoney and Monetary Policy 615 7$aMonetary Policy, Central Banking, and the Supply of Money and Credit: General 615 7$aTime-Series Models 615 7$aDynamic Quantile Regressions 615 7$aDynamic Treatment Effect Models 615 7$aDiffusion Processes 615 7$aInterest Rates: Determination, Term Structure, and Effects 615 7$aPension Funds 615 7$aNon-bank Financial Institutions 615 7$aFinancial Instruments 615 7$aInstitutional Investors 615 7$aMonetary economics 615 7$aEconometrics & economic statistics 615 7$aFinance 615 7$aInvestment & securities 615 7$aCredit 615 7$aVector autoregression 615 7$aBank credit 615 7$aShort term interest rates 615 7$aStocks 615 7$aInterest rates 676 $a354.2799273 700 $aSwiston$b Andrew$01462133 801 0$bDcWaIMF 906 $aBOOK 912 $a9910788234803321 996 $aA U.S. Financial Conditions Index$93704177 997 $aUNINA LEADER 04264nam 22007455 450 001 9910298289503321 005 20200702115527.0 010 $a94-017-9165-1 024 7 $a10.1007/978-94-017-9165-6 035 $a(CKB)3710000000281400 035 $a(EBL)1966737 035 $a(OCoLC)896116885 035 $a(SSID)ssj0001385818 035 $a(PQKBManifestationID)11781008 035 $a(PQKBTitleCode)TC0001385818 035 $a(PQKBWorkID)11349391 035 $a(PQKB)10542168 035 $a(DE-He213)978-94-017-9165-6 035 $a(MiAaPQ)EBC1966737 035 $a(PPN)183086872 035 $a(EXLCZ)993710000000281400 100 $a20141117d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 14$aThe Conquest of Cancer $eA distant goal /$fby Guy Faguet 205 $a1st ed. 2015. 210 1$aDordrecht :$cSpringer Netherlands :$cImprint: Springer,$d2015. 215 $a1 online resource (251 p.) 300 $aDescription based upon print version of record. 311 $a94-017-9164-3 320 $aIncludes bibliographical references and index. 327 $aPreface. Part I An Historical overview of the war on cancer. The four-decade journey to the National Cancer Act of 1971. Part II Cancer through the ages -- An historical overview: From prehistory to WW11 -- Our current knowledge -- Environmental carcinogens -- Part III Cancer statistics -- Assessing the enormity of the problem -- An uncontrolled problem -- Part IV How is advanced cancer treated?-The cancer-cell kill paradigm and beyond.- Complementary and alternative medicine -- The cell-kill paradigm: Bleak outcomes. Part V Stakeholders' role in the status quo -- The role of the National Cancer Institute -- Factors that impact Oncology research and practice -- The complex physician-patient interaction: Expectations vs. reality. Part VI A paradigm shift in cancer management.- Prevention & Early detection -- The holistic management of advanced cancer: A three-stage blueprint. Conclusions. References. Index. 330 $aBased on 30 years of clinical and research experience, backed by a careful assessment of four decades of published data, Dr. Faguet documented in The War on Cancer (Springer 2005), early advances in cancer treatment and patient survival that soon stalled. Ten years later, and after an exhaustive analysis of evidence-based data available through 2013 that incorporates 755 references, he reveals the root causes of the stagnation in cancer control, including the role played by major stakeholders, and advocates a coordinated national effort, akin to the Apollo program, to unveil the causes of cancer and their mastery. In the interim, Dr. Faguet urges caregivers to manage patients according to the four ethical principles of beneficence, non-maleficence, respect for patients? autonomy, and justice especially at the end of life. 606 $aCancer$xResearch 606 $aOncology 606 $aMolecular biology 606 $aMedicine 606 $aHuman genetics 606 $aCancer Research$3https://scigraph.springernature.com/ontologies/product-market-codes/B11001 606 $aOncology$3https://scigraph.springernature.com/ontologies/product-market-codes/H33160 606 $aMolecular Medicine$3https://scigraph.springernature.com/ontologies/product-market-codes/B1700X 606 $aMedicine/Public Health, general$3https://scigraph.springernature.com/ontologies/product-market-codes/H00007 606 $aHuman Genetics$3https://scigraph.springernature.com/ontologies/product-market-codes/B12008 615 0$aCancer$xResearch. 615 0$aOncology. 615 0$aMolecular biology. 615 0$aMedicine. 615 0$aHuman genetics. 615 14$aCancer Research. 615 24$aOncology. 615 24$aMolecular Medicine. 615 24$aMedicine/Public Health, general. 615 24$aHuman Genetics. 676 $a599935 676 $a610 676 $a611.01816 676 $a614.5999 700 $aFaguet$b Guy$4aut$4http://id.loc.gov/vocabulary/relators/aut$01061908 906 $aBOOK 912 $a9910298289503321 996 $aThe Conquest of Cancer$92521362 997 $aUNINA