UID:
almahu_9949747865902882
Format:
1 online resource (311 pages)
Edition:
1st ed.
ISBN:
9789819707799
Note:
Intro -- Preface -- Contents -- Contributors -- Service Composition for Smart Cities -- Consistent and Quality-Aware Service Composition in Smart Cities -- 1 Introduction -- 2 Service Composition in Cyber Space -- 2.1 Background Around 2010 -- 2.2 Different Quality Aspects in Service Selection -- 2.3 Self-Adaptive Network-Aware Service Selection -- 2.4 Consistency in Service Selection -- 2.5 Service Selection in Cloud Computing -- 3 Service Composition in Physical Space -- 3.1 Background Around 2015 -- 3.2 EU-Japan Smart City Projects -- 3.3 Consistency in Physical Service Composition -- 3.4 Verification Framework -- 3.5 Runtime Adaptation -- 4 Retrospective Discussion -- 4.1 Services Computing -- 4.2 Impact on the Author -- 5 Concluding Remarks -- References -- Designing and Analyzing Human-in-the-Loop Service Compositions -- 1 Introduction -- 1.1 Background -- 1.2 Approach -- 1.3 Structure of This Chapter -- 2 Human-in-the-Loop Service Composition -- 2.1 A Language Service Composition Example -- 2.2 Composition of Web Services and Human Activities -- 3 Empirical Study on Human-in-the-Loop Translation Services -- 3.1 Experiment Design -- 3.2 Experiment Results -- 3.3 Discussion -- 4 Human-in-the-Loop Service Design for Supporting Real-World Multilingual Activities -- 4.1 Designing Composite Services for Real-World Applications -- 4.2 Service Design Process -- 4.3 Experiment, Result and Analysis -- 5 Analyzing Crowdsourcing Workflow Models -- 5.1 Crowdsourcing Workflows -- 5.2 Modeling Iterative and Parallel Processes -- 5.3 Workflow Optimization -- 5.4 Implementing Crowdsourcing Workflow Models -- 6 Related Work -- 6.1 Human Activities in Service Composition -- 6.2 User-Centered Composite Service Design -- 6.3 Crowdsourcing Workflow Models -- 7 Conclusion -- References -- Human-Machine Collaboration for a Multilingual Service Platform.
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1 Introduction -- 1.1 Background -- 1.2 Approach -- 1.3 Structure of This Chapter -- 2 Multilingual Service Platform for Smart Cities -- 3 Human-Machine Service Composition -- 3.1 Collaborative Creation Workflow -- 3.2 Crowdsourcing System for Language Resource Creation -- 4 Reliable Crowdsourced Services for Creating Language Resources -- 4.1 Introduction -- 4.2 Issues in Crowdsourcing -- 4.3 Crowdsourced Workflow -- 4.4 Evaluation Aggregation with Hyper-Questions -- 4.5 Task Assignment Based on Workers' Reliability -- 4.6 Evaluation -- 5 AI Services for Augmenting Language Resources -- 5.1 Introduction -- 5.2 Pivot-Based Approach -- 5.3 Experiment for Pivot-Based Approach -- 5.4 Neural Network Approach -- 5.5 Experiment for Neural-Based Approach -- 6 Markov-Based Composite Service for Human-Machine Collaboration -- 6.1 Formalizing Plan Optimization -- 6.2 Experiment -- 6.3 Discussion -- 7 Conclusion -- References -- Data Analysis for Smart Cities -- Automatic Big Data Analysis Using AI-Based Service Composition for Smart City -- 1 Concept of Automatic Service Composition -- 1.1 Introduction -- 1.2 Preliminaries for Service Composition -- 1.3 Workflow Orchestration in a Nested Composition for Scalability -- 1.4 Architecture for Scalable ASC -- 2 Better Service Composition Using Service Graph -- 2.1 Introduction -- 2.2 Background and Related Work -- 2.3 Motivating Example -- 2.4 Connecting Isolated Services into GSSN -- 2.5 Workflow as a Service -- 3 Better Service Discovery Using Attention of Service Invocation -- 3.1 Related Work -- 3.2 Service Embedding -- 3.3 Service Embedding with Deep Neural Language Networks -- 3.4 Semantic Service Clustering Based on Service Embedding -- 3.5 Data Preparation -- 3.6 Experiment and Discussion -- 4 Intelligent Big Data Analysis with ASC for Virtual World -- 4.1 Related Work.
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4.2 Preliminaries for Big Data Analytics -- 4.3 Architecture for Intelligent BDA -- 4.4 Evaluation -- 5 A Scenario of Smart City Simulation on Virtual Space and Conclusion -- 5.1 Motivation Scenario -- 5.2 Conclusion -- References -- Privacy-Preserving Data Collection and Analysis for Smart Cities -- 1 Introduction -- 1.1 Purpose of This Research -- 1.2 Structure of This Chapter -- 2 Background -- 2.1 Motivating Examples -- 2.2 Attack Model -- 2.3 Local Differential Privacy (LDP) -- 3 Measurement Noise Under LDP -- 3.1 Introduction -- 3.2 Models -- 3.3 True-Value-Based Differential Privacy (TDP) -- 3.4 Analysis -- 3.5 Evaluation -- 3.6 Related Research Work -- 4 Missing Values Under LDP -- 4.1 Introduction -- 4.2 Proposed Method -- 4.3 Evaluation -- 5 Human-to-Human Interactions Under LDP -- 5.1 Introduction -- 5.2 Related Work and Real Applications -- 5.3 Problem Definition -- 5.4 Proposed Method -- 5.5 Evaluation -- 6 Conclusion -- References -- Human-Centered Service Integration for Smart Cities -- Automated Negotiations Protocols for Complex Utility Function as Social System -- 1 Introduction -- 1.1 Main Flow of Automated Negotiations -- 1.2 Complex Multi-issue Negotiation with Highly Nonlinear Utility Functions -- 1.3 Main Contributions of This Chapter -- 2 Multi-issue Negotiation with Highly Nonlinear Utility Functions -- 2.1 Basic Model of Multi-issue Negotiation -- 2.2 Basic Bidding Protocol -- 3 Threshold Adjustment Mechanism for Keeping Agents' Privacy -- 3.1 Threshold Adjustment Mechanism -- 3.2 Experiments -- 4 Secure and Efficient Negotiation Protocols -- 4.1 Secure Negotiation Protocol -- 4.2 Hybrid Secure Negotiation Protocol (HSP) -- 4.3 Experiments -- 5 Secure and Fair Protocol that Addresses Weaknesses in Nash Bargaining Solution -- 5.1 Weaknesses of the Nash Bargaining Solution in Nonlinear Negotiation.
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5.2 Secure and Fair Mediator Protocol with Approximated Fairness -- 5.3 Experiments -- 6 Decomposing the Contract Space Based on Issue Interdependencies -- 6.1 Strength of Issue Interdependency -- 6.2 Decomposing the Contract Space -- 6.3 Experiments -- 7 Conclusion and Future Work -- 7.1 Conclusion -- 7.2 Future Work -- References -- Exploiting Smart Systems for Monitoring and Assisting Elderly People at Home -- 1 Introduction -- 1.1 Background -- 1.2 Research Goal and Approach -- 1.3 Scope of Chapter -- 2 Monitoring Elderly Living by Environmental Sensors -- 2.1 Autonomous Sensor Box -- 2.2 Service Platform for In-Home Environment Sensing -- 2.3 Implementation -- 2.4 Deploying Autonomous Sensor Box in Actual Elderly Home -- 3 Recognizing Daily Activities from Environmental Sensor Data -- 3.1 Can System Recognize Activities from Environmental Data? -- 3.2 Proposed Activity Recognition Method -- 3.3 Collecting Data for Activity Recognition -- 3.4 Constructing Machine Learning Recognition Model -- 3.5 Experimental Evaluation -- 3.6 Introducing BLE Beacons to Improve Accuracy -- 3.7 Additional Experiment with BLE Beacon Data -- 4 Monitoring Elderly Mind by Agents -- 4.1 Understanding Internal States -- 4.2 Agent Technologies Developed for Mind Sensing -- 4.3 Mind Sensing Service: Rule-Based Service for Systematic Mind Sensing -- 4.4 Case Study -- 5 Design and Evaluation of Mind Monitoring Service -- 5.1 Monitoring Internal State for Long Term -- 5.2 Concept of Mind Monitoring Service -- 5.3 System Architecture -- 5.4 M1: Interaction with LINE Mei-Chan Using Mind Sensing Service -- 5.5 M2: Inquiry Method Specialized for Acquisition of Mental State -- 5.6 M3: Self-Care Assistance and Feedback by Monitoring Mental State -- 5.7 Operating Mind Monitoring Service in Actual Households -- 6 Conclusion -- References.
Additional Edition:
Print version: Murakami, Yohei Human-Centered Services Computing for Smart Cities Singapore : Springer,c2024 ISBN 9789819707782
Language:
English
Keywords:
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