LEADER 03859nam 2200493 450 001 9910495219203321 005 20220427180358.0 010 $a3-030-75220-8 024 7 $a10.1007/978-3-030-75220-0 035 $a(CKB)4100000011996793 035 $a(DE-He213)978-3-030-75220-0 035 $a(MiAaPQ)EBC6698998 035 $a(Au-PeEL)EBL6698998 035 $a(PPN)257352902 035 $a(EXLCZ)994100000011996793 100 $a20220427d2021 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 04$aThe fusion of internet of things, artificial intelligence, and cloud computing in health care /$fPatrick Siarry [and four others], editors 205 $a1st ed. 2021. 210 1$aCham, Switzerland :$cSpringer,$d[2021] 210 4$dİ2021 215 $a1 online resource (VIII, 268 p. 180 illus., 115 illus. in color.) 225 1 $aInternet of Things, Technology, Communications and Computing,$x2199-1081 311 $a3-030-75219-4 327 $aIntroduction -- Remote Patient Monitoring Using IoT, Cloud Computing and AI -- The Internet of M-Health Things (m-IoT) -- Healthcare Data Storage Options Using Cloud -- Cloud-based telemedicine ecosystem and adoption of AI -- The benefits and risks of Integrating IoT, AI in cloud services for healthcare -- Pattern Imaging Analytics using Artificial Intelligence techniques -- Identifying Diseases and Diagnosis using Artificial Intelligence -- Robotic Surgery -- Personalized Treatment with the help of IoT Artificial Intelligence and cloud -- Predicting Epidemic Outbreaks using IoT Artificial Intelligence and Cloud -- Crowd sourced Data Collection -- Maintaining Healthcare Records using Cloud storage -- Privacy and Security issues in health care based IoT -- IoT Healthcare Applications -- Applications of AI, IoT and Cloud computing in battling COVID-19 -- Intelligent Health Informatics for Handling the COVID-19 Situation -- Conclusion. 330 $aThis book reviews the convergence technologies like cloud computing, artificial intelligence (AI) and Internet of Things (IoT) in healthcare and how they can help all stakeholders in the healthcare sector. The book is a proficient guide on the relationship between AI, IoT and healthcare and gives examples into how IoT is changing all aspects of the healthcare industry. Topics include remote patient monitoring, the telemedicine ecosystem, pattern imaging analytics using AI, disease identification and diagnosis using AI, robotic surgery, prediction of epidemic outbreaks, and more. The contributors include applications and case studies across all areas of computational intelligence in healthcare data. The authors also include workflow in IoT-enabled healthcare technologies and explore privacy and security issues in healthcare-based IoT. Covers concepts of artificial intelligence and applications of computational intelligence, IoT and cloud computing in medical domain; Discusses how the fusion of Internet of Things, AI and cloud computing help in diagnosis, prediction, and storage of medical records in health care domain; Includes case studies throughout on applications of computational intelligence in healthcare data. . 410 0$aInternet of Things, Technology, Communications and Computing,$x2199-1081 606 $aArtificial intelligence$xMedical applications 606 $aCloud computing 615 0$aArtificial intelligence$xMedical applications. 615 0$aCloud computing. 676 $a610.28563 702 $aSiarry$b Patrick 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910495219203321 996 $aThe Fusion of Internet of Things, Artificial Intelligence, and Cloud Computing in Health Care$91896779 997 $aUNINA LEADER 11145nam 2200529 450 001 9910590059503321 005 20230113143728.0 010 $a3-031-15707-9 035 $a(MiAaPQ)EBC7078231 035 $a(Au-PeEL)EBL7078231 035 $a(CKB)24750398000041 035 $a(PPN)264191528 035 $a(EXLCZ)9924750398000041 100 $a20230113d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aLogic programming and nonmonotonic reasoning $e16th international conference, LPNMR 2022, Genova, Italy, September 5-9, 2022, proceedings /$fGeorg Gottlob, Daniela Inclezan, Marco Maratea (editors) 210 1$aCham, Switzerland :$cSpringer,$d[2022] 210 4$dİ2022 215 $a1 online resource (536 pages) 225 1 $aLecture notes in computer science. Lecture notes in artificial intelligence ;$vVolume 13416 311 08$aPrint version: Gottlob, Georg Logic Programming and Nonmonotonic Reasoning Cham : Springer International Publishing AG,c2022 9783031157066 327 $aIntro -- Preface -- Organization -- Abstracts of Invited Talks -- DLV Evolution from Datalog to Ontology and Stream Reasoning -- Reward Machines: Formal Languages and Automata for Reinforcement Learning -- Logic-Based Machine Learning: Recent Advances and Their Role in Neuro-Symbolic AI -- Abstract Argumentation with Focus on Argument Claims - An Overview -- Contents -- Technical Contributions -- Syntactic ASP Forgetting with Forks -- 1 Introduction -- 2 Background -- 3 The Cut Operator -- 4 Forgetting into Forks: The Unfolding Operator -- 5 Conclusions -- References -- Modal Logic S5 in Answer Set Programming with Lazy Creation of Worlds -- 1 Introduction -- 2 Background -- 3 S5 Satisfiability Checking Encodings -- 4 Implementation in Answer Set Programming -- 5 Evaluation -- 6 Related Work -- 7 Conclusion -- References -- Enumeration of Minimal Models and MUSes in WASP -- 1 Introduction -- 2 Preliminaries -- 3 Enumeration of Minimal Stable Models -- 4 Enumeration of MUSes -- 5 Experiments -- 6 Related Work -- 7 Conclusions -- References -- Statistical Statements in Probabilistic Logic Programming -- 1 Introduction -- 2 Background -- 2.1 Answer Set Programming -- 2.2 Probabilistic Logic Programming -- 2.3 Credal Semantics -- 2.4 Probabilistic Conditionals -- 3 Probabilistic Answer Set Programming for Statistical Probabilities (PASTA) -- 4 Inference in PASTA -- 5 Experiments -- 6 Related Work -- 7 Conclusions -- References -- A Comparative Study of Three Neural-Symbolic Approaches to Inductive Logic Programming -- 1 Introduction -- 2 Studied Neural-Symbolic Algorithms for ILP -- 3 A Comparison Based on Four Characteristics -- 3.1 Representation of Data -- 3.2 Language Bias -- 3.3 Recursion -- 3.4 Predicate Invention -- 4 Open Challenges and Conclusion -- References -- A Definition of Sceptical Semantics in the Constellations Approach. 327 $a1 Introduction -- 2 The Constellations Approach -- 3 Related Work -- 4 The Grounded Semantics of a PrAF -- 5 Further Sceptical Semantics -- 6 Conclusions and Future Work -- References -- SHACL: A Description Logic in Disguise -- 1 Introduction -- 2 The Wedge -- 3 SHACL, OWL, and Description Logics -- 4 SHACL: The Logical Perspective -- 5 From Graphs to Interpretations -- 6 Related Work and Conclusion -- References -- Tunas - Fishing for Diverse Answer Sets: A Multi-shot Trade up Strategy -- 1 Introduction -- 2 Preliminaries -- 2.1 Multi-shot Answer Set Programming -- 2.2 Diverse Solutions -- 3 Iterative Reworking Strategies -- 3.1 Problem Definition and Complexity -- 3.2 Reworking Methods -- 4 Experimental Evaluation -- 5 Conclusion and Future Work -- References -- Emotional Reasoning in an Action Language for Emotion-Aware Planning -- 1 Introduction -- 2 Related Work -- 3 Theoretical Background -- 3.1 Emotion Theories: AE and HER -- 3.2 Action Reasoning and Transition Systems -- 4 Emotional Reasoning -- 4.1 Emotion Decision-Graph (EDG) -- 4.2 Action Language Specifications -- 4.3 Proving Safe Emotional Change -- 4.4 Example Scenario: Backward Reasoning -- 4.5 Example Scenario: Forward Reasoning -- 5 Discussion -- 6 Conclusion and Future Work -- References -- Metric Temporal Answer Set Programming over Timed Traces -- 1 Introduction -- 2 Metric Temporal Logic -- 3 Translation into Monadic Quantified Here-and-There with Difference Constraints -- 4 Discussion -- References -- Epistemic Logic Programs: A Study of Some Properties -- 1 Introduction -- 2 Answer Set Programming and Answer Set Semantics -- 3 Epistemic Logic Programs and Their Properties -- 4 Our Observations and Proposal -- 5 Discussion and Conclusions -- A Epistemic Logic Programs: Useful Properties -- References. 327 $aDeep Learning for the Generation of Heuristics in Answer Set Programming: A Case Study of Graph Coloring -- 1 Introduction -- 2 Background -- 2.1 Graph Coloring Problem -- 2.2 Stable Model Search -- 2.3 Deep Neural Networks -- 3 Generation of Domain-Specific Heuristics in ASP -- 3.1 Representation of ASP Instances -- 3.2 Generation of the Training Set -- 3.3 Generation of the Deep Learning Model -- 3.4 Integration of the Deep Learning Model in wasp -- 4 Experiment -- 5 Related Work -- 6 Conclusion -- References -- A Qualitative Temporal Extension of Here-and-There Logic -- 1 Introduction -- 2 Preliminaries -- 3 Qualitative Temporal Here-and-There Logic -- 4 Temporal Tableau Calculus -- 5 Prototypical Implementation -- 6 Related Work and Conclusion -- References -- Representing Abstract Dialectical Frameworks with Binary Decision Diagrams -- 1 Introduction -- 2 Background -- 3 Representing ADFs as BDDs -- 4 Search Space Exploitation: Profiting from BDDs -- 5 Preliminary Experiments -- 6 Conclusions -- References -- Arguing Correctness of ASP Programs with Aggregates -- 1 Introduction -- 2 Review: Logic Programs via the Many-Sorted Approach -- 2.1 Syntax of Logic Programs with Aggregates -- 2.2 From Rules to Many-Sorted First-Order Formulas -- 2.3 Semantics via the SM Operator -- 3 Proving the Correctness of Logic Programs -- 3.1 The Graph Coloring Problem -- 3.2 The Traveling Salesman Problem -- 4 Conclusions and Future Work -- References -- Efficient Computation of Answer Sets via SAT Modulo Acyclicity and Vertex Elimination -- 1 Introduction -- 2 Preliminaries -- 3 Translating ASP into SAT Modulo Graphs/Acyclicity -- 3.1 Normalization -- 3.2 Instrumentation with Acyclicity Constraint -- 3.3 Program Completion Modulo Acyclicity -- 4 Vertex Elimination -- 5 Translating SAT Modulo Acyclicity into Pure SAT -- 6 Translating ASP into Pure SAT. 327 $a7 Experimental Evaluation -- 8 Discussion and Conclusion -- References -- IASCAR: Incremental Answer Set Counting by Anytime Refinement -- 1 Introduction -- 2 Preliminaries -- 3 Counting Supported Models -- 3.1 Counting Supported Models Under Assumptions -- 3.2 Compressing Counting Graphs -- 4 Incremental Counting by Inclusion-Exclusion -- 5 Preliminary Empirical Evaluation -- 6 Conclusion and Future Work -- References -- Reasoning About Actions with EL Ontologies and Temporal Answer Sets for DLTL -- 1 Introduction -- 2 The Description Logic EL -- 3 Temporal Action Theories in DLTL and Temporal Answer Sets -- 4 Combining Temporal Action Theories with EL Ontologies -- 5 Ontology Axioms as State Constraints -- 6 Causal Laws for Repairing Inconsistencies: Sufficient Conditions -- 7 Conclusions and Related Work -- References -- Inference to the Stable Explanations -- 1 Introduction -- 2 The Logical Framework of Defeasible Logic -- 3 Computational Problem and Methodology -- 4 Complexity Results -- 5 Abduction and Theory Change -- 6 Related Work -- 7 Conclusions and Future Investigations -- References -- Semantics for Conditional Literals via the SM Operator -- 1 Introduction -- 2 Syntax of Conditional Programs -- 3 Semantics via the SM Operator -- 4 Semantics via Infinitary Propositional Logic -- 5 Connecting Two Semantics of Conditional Programs -- 6 Arguing Correctness of the K-Coloring Problem -- References -- State Transition in Multi-agent Epistemic Domains Using Answer Set Programming -- 1 Introduction -- 2 Preliminaries -- 3 State Transition Using ASP -- 4 Properties of the State Transition Function -- 5 Example Scenarios -- 6 Related Literature -- 7 Conclusion -- References -- Towards Provenance in Heterogeneous Knowledge Bases -- 1 Introduction -- 2 Provenance Semirings -- 3 Provenance Multi-context Systems -- 4 Grounded Equilibria. 327 $a5 Conclusions -- References -- Computing Smallest MUSes of Quantified Boolean Formulas -- 1 Introduction -- 2 Preliminaries -- 3 Smallest Strong Explanations -- 4 On Complexity of Computing Smallest MUSes of QBFs -- 5 Computing Smallest MUSes via Implicit Hitting Sets -- 6 Empirical Evaluation -- 7 Conclusions -- References -- Pinpointing Axioms in Ontologies via ASP -- 1 Introduction -- 2 Preliminaries -- 3 Reasoning Through Rules -- 4 Axiom Pinpointing Through ASP -- 5 Conclusions -- References -- Interlinking Logic Programs and Argumentation Frameworks -- 1 Introduction -- 2 Preliminaries -- 3 Linking LP and AF -- 3.1 From AF to LP -- 3.2 From LP to AF -- 3.3 Bidirectional Framework -- 4 Applications -- 4.1 Deductive Argumentation -- 4.2 Argument Aggregation -- 4.3 Multi-context System -- 4.4 Constrained Argumentation Frameworks -- 5 Complexity -- 6 Concluding Remarks -- References -- Gradient-Based Supported Model Computation in Vector Spaces -- 1 Introduction -- 2 Background -- 3 Representing Logic Programs with Matrices -- 3.1 Relationship Between Positive Forms and Supported Models -- 3.2 Matrix Encoding of Logic Programs -- 4 Gradient Descent for Computing Supported Models -- 4.1 Computing the TP Operator in Vector Spaces -- 4.2 Loss Function for Computing Supported Models -- 5 Experiments -- 5.1 N-negative Loops -- 5.2 Choose 1 Out of N -- 5.3 Random Programs -- 6 Conclusion -- References -- Towards Causality-Based Conflict Resolution in Answer Set Programs -- 1 Introduction -- 2 Preliminaries -- 3 Causality-Based Conflict Resolution -- 3.1 Conflicts and Inconsistency -- 3.2 Conflict Resolution -- 4 Strategies for Conflict Resolution -- 4.1 General Satisfaction Interdependencies -- 4.2 Blocking Rules Using Opposing Rules -- 4.3 Relevant Rule Modification -- 5 Related Work -- 6 Conclusion and Future Work -- References. 327 $axASP: An Explanation Generation System for Answer Set Programming. 410 0$aLecture notes in computer science. Lecture notes in artificial intelligence ;$vVolume 13416. 606 $aLogic programming$vCongresses 606 $aNonmonotonic reasoning$vCongresses 615 0$aLogic programming 615 0$aNonmonotonic reasoning 676 $a005.115 702 $aGottlob$b G$g(Georg), 702 $aInclezan$b Daniela 702 $aMaratea$b Marco 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910590059503321 996 $aLogic Programming and Nonmonotonic Reasoning$9772042 997 $aUNINA LEADER 02345nam 2200673 a 450 001 9910813867403321 005 20230617042603.0 010 $a1-280-65618-2 010 $a0-87586-301-9 010 $a9786610656189 035 $a(CKB)1000000000447714 035 $a(EBL)318698 035 $a(OCoLC)476114136 035 $a(SSID)ssj0000156688 035 $a(PQKBManifestationID)11170528 035 $a(PQKBTitleCode)TC0000156688 035 $a(PQKBWorkID)10130064 035 $a(PQKB)10113877 035 $a(MiAaPQ)EBC318698 035 $a(Au-PeEL)EBL318698 035 $a(CaPaEBR)ebr10476775 035 $a(EXLCZ)991000000000447714 100 $a20040319d2004 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aFootprints of the Welsh Indians$b[electronic resource] $esettlers in North America before 1492 /$fWilliam L. Traxel 210 $aNew York $cAlgora Pub.$dc2004 215 $a1 online resource (279 p.) 300 $aDescription based upon print version of record. 311 $a0-87586-299-3 311 $a0-87586-300-0 320 $aIncludes bibliographical references (p. 207-213) and index. 330 $aThe legend of Prince Madoc and the Welsh Indians is a remarkable story of a brave, resourceful and intelligent people and the footprints they left in the New World - a story that has been scorned and neglected by modern historians. It is not a happy story 606 $aExplorers$zWales$xHistory 606 $aWelsh$zAmerica$xHistory 606 $aWelsh Indians$xHistory 606 $aIndians of North America$xHistory 606 $aExplorers$zAmerica$xHistory 607 $aAmerica$xDiscovery and exploration$xWelsh 607 $aAmerica$xDiscovery and exploration 607 $aAmerica$xAntiquities 607 $aSouthern States$xAntiquities 615 0$aExplorers$xHistory. 615 0$aWelsh$xHistory. 615 0$aWelsh Indians$xHistory. 615 0$aIndians of North America$xHistory. 615 0$aExplorers$xHistory. 676 $a970/.0049166 700 $aTraxel$b William L$01723104 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910813867403321 996 $aFootprints of the Welsh Indians$94124084 997 $aUNINA LEADER 04964nam 2200625Ia 450 001 9910820856503321 005 20200520144314.0 010 $a0-309-18574-2 010 $a1-281-97299-1 010 $a0-309-12029-2 010 $a9786611972998 035 $a(CKB)1000000000721511 035 $a(EBL)3564160 035 $a(SSID)ssj0000136834 035 $a(PQKBManifestationID)11144664 035 $a(PQKBTitleCode)TC0000136834 035 $a(PQKBWorkID)10084110 035 $a(PQKB)11287972 035 $a(MiAaPQ)EBC3564160 035 $a(Au-PeEL)EBL3564160 035 $a(CaPaEBR)ebr10267572 035 $a(CaONFJC)MIL197299 035 $a(OCoLC)567928266 035 $a(EXLCZ)991000000000721511 100 $a20081008d2008 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aDepartment of Homeland Security bioterrorism risk assessment $ea call for change 210 $aWashington, D. C. $cNational Academies Press$d2008 215 $a1 online resource (xiii, 157 pages) $cillustrations 300 $a"Committee on Methodological Improvements to the Department of Homeland Security's Biological Agent Risk Analysis, Board on Mathematical Science and their Applications Division on Engineering and Physical Sciences, Board on Life Sciences Division on Earth and Life Studies, National Research Council of the National Academies". 311 1 $a0-309-12028-4 320 $aIncludes bibliographical references. 327 $a""Acknowledgments""; ""Contents""; ""Summary""; ""1 Introduction""; ""2 The Critical Contribution of Risk Analysis to Risk Management and Reduction of Bioterrorism Risk""; ""3 Description and Analysis of the Department of Homeland Security's Biological Threat Risk Assessment of 2006""; ""4 Department of Homeland Security Decision Requirements for Risk Management""; ""5 Risk Assessment for Unknown and Engineered Biothreat Agents""; ""6 Improving Bioterrorism Consequence Assessment"" 327 $a""7 Improving the Department of Homeland Security's Biological Threat Risk Assessment and Adding Risk Management"" ""Appendix A: Lexicon""; ""Appendix B: Mathematical Characterization of the Biological Threat Risk Assessment Event Tree and Risk Assessment""; ""Appendix C: Computational Example Illustrating the Replacement of a Joint Distribution of Arc Probabilities with Marginal Expected Values of Individual Arc Probabilities""; ""Appendix D: Bioterrorism Risk Analysis with Decision Trees"" 327 $a""Appendix E: Optimizing Department of Homeland Security Defense Investments: Applying Defender-Attacker (-Defender) Optimization to Terror Risk Assessment and Mitigation"" ""Appendix F: Combining Game Theory and Risk Analysis in Counterterrorism: A Smallpox Example""; ""Appendix G: On the Quantification of Uncertainty and Enhancing Probabilistic Risk Analysis""; ""Appendix H: Game Theory and Interdependencies""; ""Appendix I: Review of BTRA Modeling""; ""Appendix J: Reprinted Interim Report""; ""Appendix K: Meeting Agendas""; ""Appendix L: Biographies of Committee Members"" 327 $a""Appendix M: Acronyms"" 330 $a"The mission of Department of Homeland Security Bioterrorism Risk Assessment: A Call for Change, the new book from the National Research Council, is to independently and scientifically review the methodology that led to the 2006 Department of Homeland Security report, Bioterrorism Risk Assessment (BTRA) and provide a foundation for future updates. This book identifies a number of fundamental concerns with the BTRA of 2006, ranging from mathematical and statistical mistakes that have corrupted results, to unnecessarily complicated probability models and models with fidelity far exceeding existing data, to more basic questions about how terrorist behavior should be modeled. Rather than merely criticizing what was done in the BTRA of 2006, this new NRC book consults outside experts and collects a number of proposed alternatives that could improve DHS's ability to assess potential terrorist behavior as a key element of risk-informed decision making, and it explains these alternatives in the specific context of the BTRA and the bioterrorism threat."--Publisher's website 517 3 $aBioterrorism risk assessment 606 $aBioterrorism$xMathematical models 606 $aBioterrorism$xRisk assessment 615 0$aBioterrorism$xMathematical models. 615 0$aBioterrorism$xRisk assessment. 676 $a353.6 712 02$aNational Research Council (U.S.).$bBoard on Mathematical Sciences and their Applications.$bCommittee on Methodological Improvements to the Department of Homeland Security's Biological Agent Risk Analysis. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910820856503321 996 $aDepartment of Homeland Security bioterrorism risk assessment$94123795 997 $aUNINA