دانلود کتاب Special Topics in Multimedia, IoT and Web Technologies

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Foreword\nPreface\nAcknowledgments\nContents\nContributors\nAbout the Editors\nAbout the Authors\nAcronyms\nPart I System Architectures and Environment\n 1 Evolution of Web Systems Architectures: A Roadmap\n 1.1 Introduction\n 1.2 Fundamentals of Web Systems\n 1.2.1 History and Evolution of the Web\n 1.2.2 URL and HTTP\n 1.3 Client Technologies for Web Systems Development\n 1.3.1 Single Page Application\n 1.3.2 ReactJS\n 1.3.2.1 Single Page Application and ReactJS\n 1.3.2.2 Virtual DOM\n 1.4 Architectural Patterns for Implementing SPA\n 1.5 Web Systems Architecture\n 1.6 Case Study: Você Digital\n 1.6.1 Vsocê Digital Architectural Project\n 1.6.2 Você Digital Frontend Architectural Project\n 1.7 Final Remarks\n References\n 2 Fog of Things: Fog Computing in Internet of Things Environments\n 2.1 Introduction\n 2.2 Fog of Things (FoT)\n 2.3 IoT Architecture with Fog of Things\n 2.3.1 Perception and Network Layers\n 2.3.1.1 TATU Methods\n 2.3.2 Middleware Layer\n 2.3.3 Application and Business Layers\n 2.3.4 Security Layer\n 2.3.4.1 Security Models and Concepts in IoT\n 2.3.4.2 Security in Perception and Network Layer\n 2.3.4.3 Security in Middleware Layer\n 2.3.4.4 Security in Application and Business Layers\n 2.3.4.5 Blockchain-Based Security Solutions for the IoT\n 2.4 SOFT-IoT Platform on Fog of Things\n 2.4.1 SOFT-IoT Devices\n 2.4.2 SOFT-IoT Gateway\n 2.4.3 SOFT-IoT Server\n 2.4.4 SOFT-IoT Applications\n 2.5 SOFT-IoT Related Research Topics\n 2.5.1 Reactive Microservices\n 2.5.2 IoT Stream Analytics in Fog Computing\n 2.5.3 Blockchain-Based Distributed Fog Solutions\n 2.6 Final Remarks\n References\n 3 Using Mobile Cloud Computing for Developing Context-Aware Multimedia Applications\n 3.1 Contextualization\n 3.2 Theoretical Background\n 3.2.1 Context-Aware Computing\n 3.2.1.1 Solutions\n 3.2.1.2 LoCCAM\n 3.2.2 Mobile Cloud Computing\n 3.2.2.1 Types of Mobile Applications\n 3.2.2.2 Where to Perform Offloading?\n 3.2.2.3 Why to Perform Offloading?\n 3.2.2.4 When to Perform Offloading?\n 3.2.2.5 What to Offload?\n 3.2.2.6 How to Perform Offloading?\n 3.2.2.7 Taxonomy\n 3.2.2.8 Solutions\n 3.2.2.9 MpOS\n 3.2.3 Context-Aware and MCC Integration\n 3.2.3.1 Motivating Scenarios\n 3.3 Context-Aware and Offloading System (CAOS)\n 3.3.1 Architecture and Components\n 3.3.1.1 The Mobile Side\n 3.3.1.2 The Cloud Side\n 3.3.1.3 Implementation Details\n 3.3.2 CAOS Experiments—MyPhotos App\n 3.4 Trends and Research Challenges\n 3.4.1 Costs for Raw Data Transfer to Compute the Context Inference on Cloud Services\n 3.4.2 High Latency Between Mobile Devices and Cloud Resources\n 3.4.3 Security and Privacy\n 3.4.4 Power Consumption\n 3.4.5 Large-Scale Availability of MCC Infrastructures\n 3.4.6 Missing Killer Applications\n 3.5 Conclusion\n References\n 4 Embedding Deep Learning Models into Hypermedia Applications\n 4.1 Introduction\n 4.2 NCM 3.0\n 4.3 Deep Learning Features for Hypermedia Models\n 4.4 K-NCM (knowledge-based NCM)\n 4.4.1 Multimedia Knowledge\n 4.4.2 Semantic Anchor\n 4.5 K-NCM Instantiation\n 4.6 Usage Scenario\n 4.6.1 Application Knowledge\n 4.6.2 Debugging Recognition Events\n 4.6.3 Creating a Dynamic Interactive Menu\n 4.7 Related Work\n 4.8 Final Remarks\n References\nPart II Tools and Application Development\n 5 Building Models for Ubiquitous Application Developmentin a Model-Driven Engineering Approach\n 5.1 Introduction\n 5.2 Theoretical and Conceptual Foundations\n 5.2.1 Ubiquitous Computing\n 5.2.2 Context-Aware Computing\n 5.2.3 Smart Spaces\n 5.2.4 Personal Smart Spaces\n 5.2.5 Smart Objects\n 5.2.6 Model-Driven Engineering\n 5.3 Technological Foundation\n 5.3.1 Eclipse Modeling Framework (EMF)\n 5.3.2 Eclipse Graphical Modeling Framework (GMF)\n 5.3.3 Epsilon\n 5.3.4 Epsilon Object Language (EOL)\n 5.3.5 Epsilon Validation Language (EVL)\n 5.3.6 Eugenia\n 5.4 A Graphical Modeling Tool for Ubiquitous Computing Scenarios\n 5.5 Final Considerations\n References\n 6 Authoring Hypervideos Learning Objects\n 6.1 Introduction\n 6.2 Authoring Requirements for Hypervideo LOs\n 6.2.1 Definition and Features\n 6.2.2 Participatory Design\n 6.2.2.1 Focus Group and Card Sorting\n 6.2.2.2 Design and Prototyping\n 6.2.3 Comparative Analysis\n 6.2.4 Summary\n 6.3 Cacuriá Authoring Tool\n 6.3.1 Interface Design\n 6.3.1.1 User Interface Design\n 6.3.2 The SceneSync Model\n 6.3.3 The SceneSync Language\n 6.3.3.1 Structure Module\n 6.3.3.2 Content Module\n 6.3.3.3 Synchronization Module\n 6.3.4 Modeling an LO Using SceneSync\n 6.4 Evaluation\n 6.4.1 Case Study\n 6.4.2 Usability Test\n 6.4.2.1 Results\n 6.4.3 Analysis\n 6.5 Conclusion\n References\nPart III Data Collection and Analysis\n 7 A Basic Approach for Extracting and Analyzing Data from Twitter\n 7.1 Introduction\n 7.2 Extracting Data from Twitter\n 7.2.1 Twitter API\n 7.2.1.1 API Access\n 7.2.2 Collect Data Without Accessing the API\n 7.2.3 Practical Examples\n 7.2.3.1 User Information\n 7.2.3.2 User Followers\n 7.2.3.3 Who the User Follows\n 7.2.3.4 Get Tweets\n 7.2.3.5 Search Results\n 7.3 Polarity Analysis\n 7.3.1 Approaches\n 7.3.1.1 Rule-Based Approach\n 7.3.1.2 Lexical-Based Approach\n 7.3.1.3 Machine Learning-Based Approach\n 7.3.2 Practical Example\n 7.3.2.1 Feature Extraction\n 7.3.2.2 Training\n 7.3.2.3 Classification\n 7.4 Entity Extraction\n 7.4.1 Practical Example\n 7.4.1.1 Training\n 7.4.1.2 Learning\n 7.5 Twitter Text Processing Challenges\n 7.6 Conclusion\n References\n 8 Data from Multiple Web Sources: Crawling, Integrating, Preprocessing, and Designing Applications\n 8.1 Introduction\n 8.2 Web Data Sources\n 8.2.1 Open Data\n 8.2.2 Linked Data\n 8.2.3 Web Pages\n 8.2.4 APIs\n 8.3 Web Data Crawling\n 8.3.1 Crawling Challenges\n 8.3.2 Main Crawling Strategies\n 8.4 Data Integration\n 8.5 Data Preprocessing\n 8.6 Practical Example with GitHub\n 8.6.1 Preprocessing\n 8.6.2 Applicability\n 8.6.3 Data Crawler\n 8.6.4 Data Integration\n 8.7 Conclusion\n References\n 9 Multimedia Games User Experience Data Collection: An Approach for Non-experts Researchers\n 9.1 Introduction\n 9.2 Terms and Definitions\n 9.2.1 Games and Data Collection\n 9.2.2 Games and User Experience\n 9.2.3 Games and Accessibility\n 9.3 An Approach for Non-experts Researchers\n 9.3.1 Experiments Design\n 9.3.2 Data Collection\n 9.3.2.1 Speech Recognition Data Audio Collection\n 9.3.2.2 Video Screen Recorder Data Collection\n 9.3.2.3 User Photos Data Collection\n 9.3.3 Data Storage\n 9.3.4 Data Analysis\n 9.3.5 Others Data Collection Possibilities\n 9.4 Conclusions\n References