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571Published 2017Table of Contents: “...3.3.2.1 Properties with specific PIDs -- 3.3.2.2 Further reasoning about data -- 3.3.3 Monitor Compilation -- 3.4 detectEr in Practice -- 3.4.1 Creating the Target System -- 3.4.1.1 Setting up the Erlang project -- 3.4.1.2 Running and testing the server -- 3.4.2 Instrumenting the Test System -- 3.4.2.1 Property specification -- 3.4.2.2 Monitor synthesis and instrumentation -- 3.4.2.3 Running the monitored system -- 3.4.2.4 Running the correct server -- 3.5 Conclusion -- 3.5.1 Related and Future Work -- References -- Chapter 4 -- How to Verify Your Python Conversations -- 4.1 Framework Overview -- 4.2 Scribble-Based Runtime Verification -- 4.2.1 Verification Steps -- 4.2.2 Monitoring Requirements -- 4.3 Conversation Programming in Python -- 4.4 Monitor Implementation -- 4.5 Monitoring Interruptible Systems -- 4.5.1 Use Case: Resource Access Control (RAC) -- 4.5.2 Interruptible Multiparty Session Types -- 4.5.3 Programming and Verification of Interruptible Systems -- 4.5.4 Monitoring Interrupts -- 4.6 Formal Foundations of MPST-Based Runtime Verification -- 4.7 Concluding Remarks -- References -- Chapter 5 -- The DCR Workbench: Declarative Choreographies for Collaborative Processes -- 5.1 Introduction -- 5.1.1 History of the DCR Workbench -- 5.1.2 The DCR Workbench -- 5.2 Running Example -- 5.3 Dynamic Condition-Response Graphs -- 5.3.1 Event States -- 5.3.2 Relations -- 5.3.3 Executing Events -- 5.3.4 Formal Development -- 5.4 Modelling with the Workbench -- 5.4.1 Inputting a Model: The Parser Panel -- 5.4.2 Visualisation and Simulation: The Visualiser and Activity Log Panels -- 5.5 Refinement -- 5.6 Time -- 5.7 Subprocesses -- 5.8 Data -- 5.9 Other Panels -- 5.10 Conclusion -- References -- Chapter 6 -- A Tool for Choreography-Based Analysis of Message-Passing Software -- 6.1 Introduction -- 6.2 Overview of the Theory -- 6.3 Architecture....”
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572Published 2023Table of Contents: “...Front Cover -- Artificial Intelligence in Healthcare and COVID-19 -- Copyright Page -- Contents -- List of contributors -- Preface -- 1 Improvement of mental health of frontline healthcare workers during COVID-19 pandemic using artificial intelligence -- Other notes -- 1.1 Introduction -- 1.2 Background -- 1.3 Main content -- 1.4 Methodologies and implementation -- 1.5 Discussion -- 1.5.1 Connection to artificial intelligence -- 1.5.2 Strengths -- 1.5.3 Weaknesses -- 1.6 Conclusion -- References -- 2 Effective algorithms for solving statistical problems posed by COVID-19 pandemic -- 2.1 Introduction -- 2.2 Forecasting the epidemic curves of coronavirus -- 2.2.1 Forecasting models for the COVID-19 outbreak -- 2.3 Nonparametric tests used for forecasting models estimation -- 2.3.1 Nonparametric tests for homogeneity -- 2.3.2 Exact nonparametric test for homogeneity -- 2.4 Comparison of forecast models -- 2.5 Conclusion and scope for the future work -- References -- 3 Reconsideration of drug repurposing through artificial intelligence program for the treatment of the novel coronavirus -- 3.1 Introduction -- 3.2 Viral morphology -- 3.2.1 Structured proteins -- 3.2.1.1 Spike protein/spike membrane -- 3.2.1.2 Membranous proteins -- 3.2.1.3 Nucleic acid-protein/nucleocapsid -- 3.2.1.4 Enveloped protein -- 3.2.2 Nonstructured proteins -- 3.2.2.1 Proteases -- 3.2.2.2 RNA-dependent polymerase -- 3.2.2.3 Helicase -- 3.3 Virus lifecycle -- 3.3.1 Life process of severe acute respiratory syndrome 2 -- 3.3.1.1 Attachment and entry -- 3.3.1.2 Replication and transcription -- 3.3.1.3 Assembly and release -- 3.4 Currently available viral targeting drug candidates at various stages of life cycle -- 3.5 Different drug repurposing approaches -- 3.5.1 Target approach -- 3.5.2 Knowledge-dependent approach -- 3.5.3 Molecular docking-based approach....”
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573Published 1999Table of Contents: “...Data Structures --...”
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575by Samek, MiroTable of Contents: “...Game -- 7.3.2 The Active Object Design -- 7.3.3 The Implementation -- 7.3.4 The Port for ARM Cortex-M3 -- 7.3.5 Testing -- 7.4 Summary -- Chapter 8 Design of QF -- 8.1 Handling Errors and Exceptional Conditions -- 8.2 Memory Management -- 8.3 Mutual Exclusion and Blocking -- 8.4 Active Objects -- 8.5 Event Management in QF -- 8.6 Event Delivery Mechanisms in QF -- 8.9 Deferring and Recalling Events in QF -- 8.7 Time Events -- 8.8 Summary -- Chapter 9 Implementation of QF -- 9.1 Code Organization -- 9.2 Critical Section in QF -- 9.3 General QF Policies Enforced by Assertions -- 9.4 Active Object class -- 9.5 Native QF Event Queue -- 9.6 Native QF Memory Pool -- 9.7 Native QF Priority Set -- 9.8 Native QF Scheduler -- Chapter 10 Porting QF -- 10.1 QF Porting Guide -- 10.2 QF on Bare-Metal Targets (the Vanilla Port) -- 10.3 Using QF with a preemptive Real-Time Kernel (æC/OS-II) -- 10.4 QF port to a POSIX-Compliant OS (Linux) -- 10.5 Summary -- Chapter 11 Conclusion -- 11.2 Rules for Developing Event-Driven Embedded Applications -- 11.3 Heuristics -- 11.4 Sizing Event Queues and Event Pools -- 11.5 System Integration -- 11.6 Summary of Key Elements -- 11.7 An Invitation -- Appendix A QK: A Single-Stack Preemptive Kernel -- A.2 Run-to-Completion Processing -- A.3 Synchronous and Asynchronous Preemptions -- A.4 Stack Utilization -- A.4 Comparison with a Traditional RTOS -- A.5 Summary -- Appendix B QS: Software Tracing for Event Driven Systems -- B.1 Software Tracing Concepts -- B.2 Structure of QS Trace Records -- B.3 QS Filters -- B.4 QS Data Protocol -- B.5 QS Trace Buffer -- B.6 Configuring and Porting QS -- B.7 Summary -- Appendix C Inheriting Entire State Models in C++ -- C.1 Statechart Refinement Example in C++ -- C.3 Caveats -- C.4 Summary -- Appendix D Guide to Notation -- D.1 Class Diagrams -- D.2 Statechart Diagrams -- D.3 Sequence Diagrams -- D.4 Timing Diagrams -- Appendix E CD-ROM -- E.1 Source Code Structure -- E.2 Installation -- E.3 Licensing -- E.4 Answers to the Exercises -- E.5 QP Reference Guide (Doxygen) -- E.6 Resources -- Bibliography -- Index....”
Published 2009
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