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  • 1
    Online Resource
    Online Resource
    Cham :Springer International Publishing AG,
    UID:
    almahu_9949602269102882
    Format: 1 online resource (333 pages)
    Edition: 1st ed.
    ISBN: 9783030296650
    Note: Intro -- Foreword -- Preface -- Acknowledgements -- Contents -- Part I: Fundamentals and Concepts -- Chapter 1: Real-time Linked Dataspaces: A Data Platform for Intelligent Systems Within Internet of Things-Based Smart Environm... -- 1.1 Introduction -- 1.2 Foundations -- 1.2.1 Intelligent Systems -- 1.2.2 Smart Environments -- 1.2.3 Internet of Things -- 1.2.4 Data Ecosystems -- 1.2.5 Enabling Data Ecosystem for Intelligent Systems -- 1.3 Real-time Linked Dataspaces -- 1.4 Book Overview -- 1.5 Summary -- Chapter 2: Enabling Knowledge Flows in an Intelligent Systems Data Ecosystem -- 2.1 Introduction -- 2.2 Foundations -- 2.2.1 Intelligent Systems Data Ecosystem -- 2.2.2 System of Systems -- 2.2.3 From Deterministic to Probabilistic Decisions in Intelligent Systems -- 2.2.4 Digital Twins -- 2.3 Knowledge Exchange Between Open Intelligent Systems in Dynamic Environments -- 2.4 Knowledge Value Ecosystem (KVE) Framework -- 2.5 Knowledge: Transfer and Translation -- 2.5.1 Entity-Centric Data Integration -- 2.5.2 Linked Data -- 2.5.3 Knowledge Graphs -- 2.5.4 Smart Environment Example -- 2.6 Value: Continuous and Shared -- 2.6.1 Value Disciplines -- 2.6.2 Data Network Effects -- 2.7 Ecosystem: Governance and Collaboration -- 2.7.1 From Ecology and Business to Data -- 2.7.2 The Web of Data: A Global Data Ecosystem -- 2.7.3 Ecosystem Coordination -- 2.7.4 Data Ecosystem Design -- 2.8 Iterative Boundary Crossing Process: Pay-As-You-Go -- 2.8.1 Dataspace Incremental Data Management -- 2.9 Data Platforms for Intelligent Systems Within IoT-Based Smart Environment -- 2.9.1 FAIR Data Principles -- 2.9.2 Requirements Analysis -- 2.10 Summary -- Chapter 3: Dataspaces: Fundamentals, Principles, and Techniques -- 3.1 Introduction -- 3.2 Big Data and the Long Tail of Data -- 3.3 The Changing Cost of Data Management. , 3.4 Approximate, Best-Effort, and ``Good Enough ́́Information -- 3.5 Fundamentals of Dataspaces -- 3.5.1 Definition and Principles -- 3.5.2 Comparison to Existing Approaches -- 3.6 Dataspace Support Platform -- 3.6.1 Support Services -- 3.6.2 Life Cycle -- 3.6.3 Implementations -- 3.7 Dataspace Technical Challenges -- 3.7.1 Query Answering -- 3.7.2 Introspection -- 3.7.3 Reusing Human Attention -- 3.8 Dataspace Research Challenges -- 3.9 Summary -- Chapter 4: Fundamentals of Real-time Linked Dataspaces -- 4.1 Introduction -- 4.2 Event and Stream Processing for the Internet of Things -- 4.2.1 Timeliness and Real-time Processing -- 4.3 Fundamentals of Real-time Linked Dataspaces -- 4.3.1 Foundations -- 4.3.2 Definition and Principles -- 4.3.3 Comparison -- 4.3.4 Architecture -- 4.4 A Principled Approach to Pay-As-You-Go Data Management -- 4.4.1 TBLś 5 Star Data -- 4.4.2 5 Star Pay-As-You-Go Model for Dataspace Services -- 4.5 Support Platform -- 4.5.1 Data Services -- 4.5.2 Stream and Event Processing Services -- 4.6 Suitability as a Data Platform for Intelligent Systems Within IoT-Based Smart Environments -- 4.6.1 Common Data Platform Requirements -- 4.6.2 Related Work -- 4.7 Summary -- Part II: Data Support Services -- Chapter 5: Data Support Services for Real-time Linked Dataspaces -- 5.1 Introduction -- 5.2 Pay-As-You-Go Data Support Services for Real-time Linked Dataspaces -- 5.3 5 Star Pay-As-You-Go Levels for Data Services -- 5.4 Summary -- Chapter 6: Catalog and Entity Management Service for Internet of Things-Based Smart Environments -- 6.1 Introduction -- 6.2 Working with Entity Data -- 6.3 Catalog and Entity Service Requirements for Real-time Linked Dataspaces -- 6.3.1 Real-time Linked Dataspaces -- 6.3.2 Requirements -- 6.4 Analysis of Existing Data Catalogs -- 6.5 Catalog Service -- 6.5.1 Pay-As-You-Go Service Levels. , 6.6 Entity Management Service -- 6.6.1 Pay-As-You-Go Service Levels -- 6.6.2 Entity Example -- 6.7 Access Control Service -- 6.7.1 Pay-As-You-Go Service Levels -- 6.8 Joining the Real-time Linked Dataspace -- 6.9 Summary -- Chapter 7: Querying and Searching Heterogeneous Knowledge Graphs in Real-time Linked Dataspaces -- 7.1 Introduction -- 7.2 Querying and Searching in Real-time Linked Dataspaces -- 7.2.1 Real-time Linked Dataspaces -- 7.2.2 Knowledge Graphs -- 7.2.3 Searching Versus Querying -- 7.2.4 Search and Query Service Pay-As-You-Go Service Levels -- 7.3 Search and Query over Heterogeneous Data -- 7.3.1 Data Heterogeneity -- 7.3.2 Motivational Scenario -- 7.3.3 Core Requirements for Search and Query -- 7.4 State-of-the-Art Analysis -- 7.4.1 Information Retrieval Approaches -- 7.4.2 Natural Language Approaches -- 7.4.3 Discussion -- 7.5 Design Features for Schema-Agnostic Queries -- 7.6 Summary -- Chapter 8: Enhancing the Discovery of Internet of Things-Based Data Services in Real-time Linked Dataspaces -- 8.1 Introduction -- 8.2 Discovery of Data Services in Real-time Linked Dataspaces -- 8.2.1 Real-time Linked Dataspaces -- 8.2.2 Data Service Discovery -- 8.3 Semantic Approaches for Service Discovery -- 8.3.1 Inheritance Between OWL-S Services -- 8.3.2 Topic Extraction and Formal Concept Analysis -- 8.3.3 Reasoning-Based Matching -- 8.3.4 Numerical Encoding of Ontological Concepts -- 8.3.5 Discussion -- 8.4 Formal Concept Analysis for Organizing IoT Data Service Descriptions -- 8.4.1 Definition: Formal Context -- 8.4.2 Definition: Formal Concept -- 8.4.3 Definition: Sub-concept Ordering -- 8.5 IoT-Enabled Smart Environment Use Case -- 8.6 Conclusions and Future Work -- Chapter 9: Human-in-the-Loop Tasks for Data Management, Citizen Sensing, and Actuation in Smart Environments -- 9.1 Introduction -- 9.2 The Wisdom of the Crowds. , 9.2.1 Crowdsourcing Platform -- 9.3 Challenges of Enabling Crowdsourcing -- 9.4 Approaches to Human-in-the-Loop -- 9.4.1 Augmented Algorithms and Operators -- 9.4.2 Declarative Programming -- 9.4.3 Generalised Stand-alone Platforms -- 9.5 Comparison of Existing Approaches -- 9.6 Human Task Service for Real-time Linked Dataspaces -- 9.6.1 Real-time Linked Dataspaces -- 9.6.2 Human Task Service -- 9.6.3 Pay-As-You-Go Service Levels -- 9.6.4 Applications of Human Task Service -- 9.6.5 Data Processing Pipeline -- 9.6.6 Task Data Model for Micro-tasks and Users -- 9.6.7 Spatial Task Assignment in Smart Environments -- 9.7 Summary -- Part III: Stream and Event Processing Services -- Chapter 10: Stream and Event Processing Services for Real-time Linked Dataspaces -- 10.1 Introduction -- 10.2 Pay-As-You-Go Services for Event and Stream Processing in Real-time Linked Dataspaces -- 10.3 Entity-Centric Real-time Query Service -- 10.3.1 Lambda Architecture -- 10.3.2 Entity-Centric Real-time Query Service -- 10.3.3 Pay-As-You-Go Service Levels -- 10.3.4 Service Performance -- 10.4 Summary -- Chapter 11: Quality of Service-Aware Complex Event Service Composition in Real-time Linked Dataspaces -- 11.1 Introduction -- 11.2 Complex Event Processing in Real-time Linked Dataspaces -- 11.2.1 Real-time Linked Dataspaces -- 11.2.2 Complex Event Processing -- 11.2.3 CEP Service Design -- 11.2.4 Pay-As-You-Go Service Levels -- 11.2.5 Event Service Life Cycle -- 11.3 QoS Model and Aggregation Schema -- 11.3.1 QoS Properties of Event Services -- 11.3.2 QoS Aggregation and Utility Function -- 11.3.3 Event QoS Utility Function -- 11.4 Genetic Algorithm for QoS-Aware Event Service Composition Optimisation -- 11.4.1 Population Initialisation -- 11.4.2 Genetic Encodings for Concrete Composition Plans -- 11.4.3 Crossover and Mutation Operations -- 11.4.3.1 Crossover. , 11.4.3.2 Mutation and Elitism -- 11.5 Evaluation -- 11.5.1 Part 1: Performance of the Genetic Algorithm -- 11.5.1.1 Datasets -- 11.5.1.2 QoS Utility Results and Scalability -- 11.5.1.3 Fine-Tuning the Parameters -- 11.5.2 Part 2: Validation of QoS Aggregation Rules -- 11.5.2.1 Datasets and Experiment Settings -- 11.5.2.2 Simulation Results -- 11.6 Related Work -- 11.6.1 QoS-Aware Service Composition -- 11.6.2 On-Demand Event/Stream Processing -- 11.7 Summary and Future Work -- Chapter 12: Dissemination of Internet of Things Streams in a Real-time Linked Dataspace -- 12.1 Introduction -- 12.2 Internet of Things: A Dataspace Perspective -- 12.2.1 Real-time Linked Dataspaces -- 12.3 Stream Dissemination Service -- 12.3.1 Pay-As-You-Go Service Levels -- 12.4 Point-to-Point Linked Data Stream Dissemination -- 12.4.1 TP-Automata for Pattern Matching -- 12.5 Linked Data Stream Dissemination via Wireless Broadcast -- 12.5.1 The Mapping Between Triples and 3D Points -- 12.5.2 3D Hilbert Curve Index -- 12.6 Experimental Evaluation -- 12.6.1 Evaluation of Point-to-Point Linked Stream Dissemination -- 12.6.2 Evaluation on Linked Stream Dissemination via Wireless Broadcast -- 12.7 Related Work -- 12.7.1 Matching -- 12.7.2 Wireless Broadcast -- 12.8 Summary and Future Work -- Chapter 13: Approximate Semantic Event Processing in Real-time Linked Dataspaces -- 13.1 Introduction -- 13.2 Approximate Event Matching in Real-time Linked Dataspaces -- 13.2.1 Real-time Linked Dataspaces -- 13.2.2 Event Processing -- 13.3 The Approximate Semantic Matching Service -- 13.3.1 Pay-As-You-Go Service Levels -- 13.3.2 Semantic Matching Models -- 13.3.3 Model I: The Approximate Event Matching Model -- 13.3.4 Model II: The Thematic Event Matching Model -- 13.4 Elements for Approximate Semantic Matching of Events -- 13.4.1 Elm 1: Sub-symbolic Distributional Event Semantics. , 13.4.2 Elm 2: Free Event Tagging.
    Additional Edition: Print version: Curry, Edward Real-Time Linked Dataspaces Cham : Springer International Publishing AG,c2019 ISBN 9783030296643
    Language: English
    Subjects: Computer Science
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  • 2
    Online Resource
    Online Resource
    Singapore :Springer Singapore Pte. Limited,
    UID:
    almahu_9949602269802882
    Format: 1 online resource (846 pages)
    Edition: 1st ed.
    ISBN: 9789813299153
    Note: Intro -- Preface -- Acknowledgements -- List of Editors -- Editors-in-Chief -- Managing Editors -- Contents -- About the Editors-in-Chief -- Digital Earth Technologies -- 2 Digital Earth Platforms -- 2.1 Introduction -- 2.2 Discrete Global Grid Systems -- 2.2.1 Initial Domain -- 2.2.2 Cell Type -- 2.2.3 Refinement -- 2.2.4 Projection -- 2.2.5 Indexing -- 2.3 Scientific Digital Earths -- 2.4 Public and Commercial Digital Earth Platforms -- 2.4.1 Latitude/Longitude Grids -- 2.4.2 Geodesic DGGSs -- 2.4.3 Installations: DESP -- 2.5 Discrete Global Grid System Standards -- 2.5.1 Standardization of Discrete Global Grid Systems -- 2.5.2 Core Requirements of the OGC DGGS Abstract Specification -- 2.5.3 The Future of the DGGS Standard -- 2.5.4 Linkages Between DGGS and Other Standards Activities -- References -- 3 Remote Sensing Satellites for Digital Earth -- 3.1 Development of Remote Sensing -- 3.1.1 Overview of Remote Sensing -- 3.1.2 Development of Remote Sensing Satellites -- 3.2 Land Observation Satellites -- 3.2.1 US Land Observation Satellites -- 3.2.2 European Land Observation Satellites -- 3.2.3 China's Land Observation Satellites -- 3.2.4 Other Land Observation Satellites -- 3.3 Ocean Observation Satellites -- 3.3.1 US Ocean Observation Satellites -- 3.3.2 European Ocean Observation Satellites -- 3.3.3 China's Ocean Observation Satellites -- 3.3.4 Other Ocean Observation Satellites -- 3.4 Meteorological Observation Satellites -- 3.4.1 US Meteorological Observation Satellites -- 3.4.2 European Meteorological Observation Satellites -- 3.4.3 China's Meteorological Observation Satellites -- 3.4.4 Other Meteorological Observation Satellites -- 3.5 Trends in Remote Sensing for Digital Earth -- References -- 4 Satellite Navigation for Digital Earth -- 4.1 Introduction -- 4.2 Global Navigation Satellite System -- 4.2.1 BDS -- 4.2.2 GPS -- 4.2.3 GLONASS. , 4.2.4 Galileo -- 4.3 GNSS Augmentation Systems -- 4.3.1 Wide-Area Differential Augmentation System -- 4.3.2 Global Differential Precise Positioning System -- 4.3.3 Local Area Differential Augmentation System -- 4.3.4 Local Area Precise Positioning System -- 4.4 Applications in Digital Earth Case Studies -- 4.4.1 Terrestrial Reference System -- 4.4.2 Time System -- 4.4.3 High-Precision Positioning -- 4.4.4 Location-Based Service -- References -- 5 Geospatial Information Infrastructures -- 5.1 Introduction -- 5.2 A Brief History of Geospatial Information Infrastructures -- 5.2.1 Geospatial Information Infrastructure Milestones -- 5.2.2 Architectural Evolutions in Geospatial Information Infrastructure Development -- 5.3 Geospatial Information Infrastructures Today -- 5.3.1 The Evolution of Geospatial Information on the Web -- 5.3.2 Geospatial Information Infrastructures Champion Openness -- 5.3.3 Capacity Building and Learning for Geospatial Information Infrastructures -- 5.4 Recent Challenges and Potential for Improvement -- 5.4.1 Strengthened Role of Semantics -- 5.4.2 Is Spatial Still Special? -- 5.5 Conclusion and Outlook -- References -- 6 Geospatial Information Processing Technologies -- 6.1 Introduction -- 6.2 High-Performance Computing -- 6.2.1 The Concept of High-Performance Computing: What and Why -- 6.2.2 High-Performance Computing Platforms -- 6.2.3 Spatial Database Management Systems and Spatial Data Mining -- 6.2.4 Applications Supporting Digital Earth -- 6.2.5 Research Challenges and Future Directions -- 6.3 Online Geospatial Information Processing -- 6.3.1 Web Service-Based Online Geoprocessing -- 6.3.2 Web (Coverage) Processing Services -- 6.3.3 Online Geoprocessing Applications in the Context of Digital Earth -- 6.3.4 Research Challenges and Future Directions -- 6.4 Distributed Geospatial Information Processing. , 6.4.1 The Concept of Distributed Geospatial Information Processing: What and Why -- 6.4.2 Fundamental Concepts and Techniques -- 6.4.3 Application Supporting Digital Earth -- 6.4.4 Research Challenges and Future Directions -- 6.5 Discussion and Conclusion -- References -- 7 Geospatial Information Visualization and Extended Reality Displays -- 7.1 Introduction -- 7.2 Visualizing Geospatial Information: An Overview -- 7.2.1 Representation -- 7.2.2 User Interaction and Interfaces -- 7.3 Understanding Users: Cognition, Perception, and User-Centered Design Approaches for Visualization -- 7.3.1 Making Visualizations Work for Digital Earth Users -- 7.4 Geovisual Analytics -- 7.4.1 Progress in Geovisual Analytics -- 7.4.2 Big Data, Digital Earth, and Geovisual Analytics -- 7.5 Visualizing Movement -- 7.5.1 Trajectory Maps: The Individual Journey -- 7.5.2 Flow Maps: Aggregated Flows Between Places -- 7.5.3 Origin-Destination (OD) Maps -- 7.5.4 In-Flow, Out-Flow and Density of Moving Objects -- 7.6 Immersive Technologies-From Augmented to Virtual Reality -- 7.6.1 Essential Concepts for Immersive Technologies -- 7.6.2 Augmented Reality -- 7.6.3 Mixed Reality -- 7.7 Virtual Reality -- 7.7.1 Virtual Geographic Environments -- 7.7.2 Foundational Structures of VGEs -- 7.8 Dashboards -- 7.9 Conclusions -- References -- 8 Transformation in Scale for Continuous Zooming -- 8.1 Continuous Zooming and Transformation in Scale: An Introduction -- 8.1.1 Continuous Zooming: Foundation of the Digital Earth -- 8.1.2 Transformation in Scale: Foundation of Continuous Zooming -- 8.1.3 Transformation in Scale: A Fundamental Issue in Disciplines Related to Digital Earth -- 8.2 Theories of Transformation in Scale -- 8.2.1 Transformation in Scale: Multiscale Versus Variable Scale -- 8.2.2 Transformations in Scale: Euclidean Versus Geographical Space. , 8.2.3 Theoretical Foundation for Transformation in Scale: The Natural Principle -- 8.3 Models for Transformations in Scale -- 8.3.1 Data Models for Feature Representation: Space-Primary Versus Feature-Primary -- 8.3.2 Space-Primary Hierarchical Models for Transformation in Scale -- 8.3.3 Feature-Primary Hierarchical Models for Transformation in Scale -- 8.3.4 Models of Transformation in Scale for Irregular Triangulation Networks -- 8.3.5 Models for Geometric Transformation of Map Data in Scale -- 8.3.6 Models for Transformation in Scale of 3D City Representations -- 8.4 Mathematical Solutions for Transformations in Scale -- 8.4.1 Mathematical Solutions for Upscaling Raster Data: Numerical and Categorical -- 8.4.2 Mathematical Solutions for Downscaling Raster Data -- 8.4.3 Mathematical Solutions for Transformation (in Scale) of Point Set Data -- 8.4.4 Mathematical Solution for Transformation (in Scale) of Individual Lines -- 8.4.5 Mathematical Solutions for Transformation (in Scale) of Line Networks -- 8.4.6 Mathematical Solutions for Transformation of a Class of Area Features -- 8.4.7 Mathematical Solutions for Transformation (in Scale) of Spherical and 3D Features -- 8.5 Transformation in Scale: Final Remarks -- References -- 9 Big Data and Cloud Computing -- 9.1 Introduction -- 9.2 Big Data Sources -- 9.3 Big Data Analysis Methods -- 9.3.1 Data Preprocessing -- 9.3.2 Statistical Analysis -- 9.3.3 Nonstatistical Analysis -- 9.4 Architecture for Big Data Analysis -- 9.4.1 Data Storage Layer -- 9.4.2 Data Query Layer -- 9.4.3 Data Processing Layer -- 9.5 Cloud Computing for Big Data -- 9.5.1 Cloud Computing and Other Related Computing Paradigms -- 9.5.2 Introduction to Cloud Computing -- 9.5.3 Cloud Computing to Support Big Data -- 9.6 Case Study: EarthCube/DataCube -- 9.6.1 EarthCube -- 9.6.2 Data Cube -- 9.7 Conclusion -- References. , 10 Artificial Intelligence -- 10.1 Introduction -- 10.2 Traditional and Statistical Machine Learning -- 10.2.1 Supervised Learning -- 10.2.2 Unsupervised Learning -- 10.2.3 Dimension Reduction -- 10.3 Deep Learning -- 10.3.1 Convolutional Networks -- 10.3.2 Recurrent Neural Networks -- 10.3.3 Variational Autoencoder -- 10.3.4 Generative Adversarial Networks (GANs) -- 10.3.5 Dictionary-Based Approaches -- 10.3.6 Reinforcement Learning -- 10.4 Discussion -- 10.4.1 Reproducibility -- 10.4.2 Ownership and Fairness -- 10.4.3 Accountability -- 10.5 Conclusion -- References -- 11 Internet of Things -- 11.1 Introduction -- 11.2 Definitions and status quo of the IoT -- 11.2.1 One Concept, Many Definitions -- 11.2.2 Our Definition -- 11.2.3 Early Works on the Interplay Between DE and the IoT -- 11.2.4 IoT Standards Initiatives from DE -- 11.3 Interplay Between the IoT and DE -- 11.3.1 Discoverability, Acquisition and Communication of Spatial Information -- 11.3.2 Spatial Understanding of Objects and Their Relationships -- 11.3.3 Taking Informed Actions and Acting Over the Environment (ACT) -- 11.4 Case Studies on Smart Scenarios -- 11.5 Frictions and Synergies Between the IoT and DE -- 11.5.1 Discoverability, Acquisition and Communication of Spatial Information -- 11.5.2 Spatial Understanding of Objects and Their Relationships -- 11.5.3 Taking Informed Actions and Acting Over the Environment -- 11.6 Conclusion and Outlook for the Future of the IoT in Support of DE -- References -- 12 Social Media and Social Awareness -- 12.1 Introduction: Electronic Footprints on Digital Earth -- 12.2 Multifaceted Implications of Social Media -- 12.3 Opportunities: Human Dynamics Prediction -- 12.3.1 Public Health -- 12.3.2 Emergency Response -- 12.3.3 Decision Making -- 12.3.4 Social Equity Promotion -- 12.4 Challenges: Fake Electronic Footprints -- 12.4.1 Rumors. , 12.4.2 Location Spoofing.
    Additional Edition: Print version: Guo, Huadong Manual of Digital Earth Singapore : Springer Singapore Pte. Limited,c2019 ISBN 9789813299146
    Language: English
    Subjects: Geography
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  • 3
    Online Resource
    Online Resource
    Cham :Springer International Publishing AG,
    UID:
    almahu_9949602165102882
    Format: 1 online resource (290 pages)
    Edition: 1st ed.
    ISBN: 9783319583167
    Series Statement: Springer Series on Touch and Haptic Systems Series
    Note: Intro -- Series Editors' Foreword -- Preface -- Contents -- Contributors -- 1 Musical Haptics: Introduction -- 1.1 Scope and Goals -- 1.2 Haptic Cues in Music Practice and Fruition -- 1.3 Musical Devices and Haptic Feedback -- 1.4 Challenges -- 1.5 Outline -- References -- Musical Haptics: Interaction and Perception -- 2 Once More, with Feeling: Revisiting the Role of Touch in Performer-Instrument Interaction -- 2.1 Introduction -- 2.2 A Musician Both Drives and Is Driven by Their Instrument -- 2.3 The Coupled Dynamics: A New Perspective on Control -- 2.4 Inner and Outer Loops in the Interaction Between Player and Instrument -- 2.5 Implications of a Coupled Dynamics Perspective on Learning to Play an Instrument -- 2.6 Conclusions -- References -- 3 A Brief Overview of the Human Somatosensory System -- 3.1 Introduction -- 3.2 Biomechanics of the Hand -- 3.2.1 Hand Structural Organisation -- 3.2.2 Hand Mobility -- 3.2.3 The Volar Hand -- 3.2.4 Bulk Mechanics of the Fingertip and the Skin -- 3.3 Sensory Organs -- 3.3.1 Muscles, Tendons and Joints -- 3.3.2 Glabrous, Hairy and Mucosal Skin -- 3.3.3 Electrophysiological Response -- 3.4 Central Organs -- 3.5 Conclusions -- References -- 4 Perception of Vibrotactile Cues in Musical Performance -- 4.1 Introduction -- 4.1.1 Open-Loop Experimentation -- 4.1.2 Experiments with Musicians -- 4.1.3 Premises to the Present Experiments -- 4.2 Experiment 1: Vibrotactile Sensitivity Thresholds Under Active Touch Conditions -- 4.2.1 Setup -- 4.2.2 Procedure -- 4.2.3 Results -- 4.2.4 Discussion -- 4.3 Experiment 2: Vibration Detection at the Piano Keyboard During Performance -- 4.3.1 Setup -- 4.3.2 Procedure -- 4.3.3 Results -- 4.3.4 Vibration Characterization -- 4.3.5 Discussion -- 4.4 Conclusions -- References -- 5 The Role of Haptic Cues in Musical Instrument Quality Perception -- 5.1 Introduction -- 5.2 Violin. , 5.2.1 Touch and the Conceptualization of Violin Quality by Musicians -- 5.2.2 Vibrotactile Feedback at the Left Hand -- 5.3 Piano -- 5.3.1 Piano Touch and Tone Quality -- 5.3.2 Haptic Cues and Instrument Quality -- 5.4 Conclusions -- References -- 6 A Functional Analysis of Haptic Feedback in Digital Musical Instrument Interactions -- 6.1 Introduction -- 6.2 Experiment Design -- 6.2.1 Functionality Testing -- 6.2.2 Adapting Fitts' Law -- 6.2.3 Context of Evaluation -- 6.2.4 Device Description: The Bowls -- 6.2.5 Device Feedback Implementation -- 6.2.6 Participants -- 6.2.7 Procedure -- 6.3 Results -- 6.3.1 Functionality Results -- 6.3.2 Usability Results -- 6.3.3 User Experience Results -- 6.3.4 Interview Data -- 6.3.5 Empathy Mapping -- 6.4 Discussion -- 6.5 Conclusions -- References -- 7 Auditory-Tactile Experience of Music -- 7.1 Introduction -- 7.2 Experimental Design -- 7.2.1 Stimuli -- 7.2.2 Synchronization -- 7.2.3 Setup -- 7.2.4 Participants -- 7.2.5 Procedure -- 7.3 Vibration Generation: Approaches and Results -- 7.3.1 Low-Pass Filtering -- 7.3.2 Reduction to Fundamental Frequency -- 7.3.3 Octave Shift -- 7.3.4 Substitute Signals -- 7.3.5 Compression of Dynamic Range -- 7.3.6 Summary -- 7.4 Conclusions -- References -- Haptic Musical Interfaces: Design and Applications -- 8 The MSCI Platform: A Framework for the Design and Simulation of Multisensory Virtual Musical Instruments -- 8.1 Introduction -- 8.2 A Physical Approach to Digital Musical Instruments -- 8.2.1 Distributed Approach to Haptic Digital Musical Instruments -- 8.2.2 Unitary Approach to Virtual Musical Instruments -- 8.3 Hardware and Software Solutions for the MSCI Platform -- 8.3.1 The TGR Haptic System -- 8.3.2 The CORDIS-ANIMA Formalism -- 8.3.3 The GENESIS Software Environment -- 8.3.4 Synchronous Real-Time Computing Architecture. , 8.4 Multi-rate Decomposition of the Instrumental Chain -- 8.4.1 Gesture-Sound Dynamics -- 8.4.2 Multi-rate CORDIS-ANIMA Simulations -- 8.5 Virtual Instruments Created with MSCI -- 8.5.1 Workflow and Design Process -- 8.5.2 Specificities of MSCI Haptic Virtual Instruments -- 8.5.3 Real-Time Performance in Hélios -- 8.6 Conclusions -- References -- 9 Force-Feedback Instruments for the Laptop Orchestra of Louisiana -- 9.1 Introduction -- 9.1.1 Multisensory Feedback for Musical Instruments -- 9.1.2 Additional Force-Feedback Device Designs from the Haptics Community -- 9.1.3 Open-Source Technology for the Design of Haptic Musical Instruments -- 9.1.4 Laptop Orchestra of Louisiana -- 9.2 Enabling Precise and Physically Intuitive Control of Sound (``Quartet for Strings'') -- 9.2.1 Instrument Design -- 9.2.2 Performance Techniques -- 9.2.3 Compositional Structure -- 9.3 Traditional Controls Can Be Used Alongside Force-Feedback Controls (``Of Grating Impermanence'') -- 9.3.1 Instrument Design -- 9.3.2 Performance Techniques -- 9.3.3 Compositional Structure -- 9.4 Finding Timbres that Sound Uncannily Familiar but Are Nonetheless Novel (``Guest Dimensions'') -- 9.4.1 Instrument Design -- 9.4.2 Performance Techniques -- 9.4.3 Compositional Structure -- 9.5 Conclusions -- References -- 10 Design of Vibrotactile Feedback and Stimulation for Music Performance -- 10.1 Introduction -- 10.2 Haptic Feedback in Music Technology -- 10.2.1 Models of Haptic-Enabled Interfaces -- 10.2.2 Haptic-Enabled Interfaces -- 10.3 Development and Evaluation of Tactile Icons for Music Performance -- 10.3.1 Hardware and Software -- 10.3.2 Symbolic and Musical Tactons: Design and Evaluation -- 10.3.3 Implementation into Live Performance -- 10.4 Conclusions -- References -- 11 Haptics for the Development of Fundamental Rhythm Skills, Including Multi-limb Coordination. , 11.1 Introduction -- 11.2 Motivation and Theoretical Background -- 11.2.1 Dalcroze Eurhythmics -- 11.2.2 Metrical Hierarchies and Polyrhythms -- 11.2.3 Cognitive Science: Entrainment and Neural Resonance -- 11.3 Applications of the Haptic Bracelets -- 11.3.1 The "Haptic IPod" -- 11.3.2 Drum Teaching with Haptic Bracelets -- 11.3.3 Musician Coordination and Synchronisation -- 11.3.4 Teaching Multi-limb Drum Patterns by Multi-limbed Haptic Cueing -- 11.4 Experimental Results -- 11.4.1 Supporting Learning of Rhythm Skills with the Haptic Drum Kit -- 11.4.2 Learning Multi-limb Rhythms with Improved Haptic Drum Kit -- 11.4.3 Passive Learning of Multi-limb Rhythm Skills -- 11.5 Related Work -- 11.6 Conclusions -- References -- 12 Touchscreens and Musical Interaction -- 12.1 Introduction -- 12.2 Perceptual Aspects of Auditory and Haptic Modalities for Musical Touchscreen Applications -- 12.2.1 Intensity -- 12.2.2 Frequency -- 12.2.3 Temporal Acuity and Rhythm Perception -- 12.2.4 Synchrony -- 12.3 Experiment 1: Identification of Audio-Driven Tactile Feedback on a Touchscreen -- 12.3.1 Stimuli -- 12.3.2 Set-up -- 12.3.3 Subjects -- 12.3.4 Results and Discussion -- 12.3.5 Usability and Attractiveness -- 12.4 Experiment 2: Effect of Loudness on Perceived Tactile Intensity of Virtual Buttons -- 12.4.1 Stimuli -- 12.4.2 Set-up -- 12.4.3 Subjects -- 12.4.4 Procedure -- 12.4.5 Results and Discussion -- 12.5 Conclusions -- References -- 13 Implementation and Characterization of Vibrotactile Interfaces -- 13.1 Introduction -- 13.2 Vibrotactile Actuators' Technology -- 13.3 Interface Examples -- 13.3.1 The Touch-Box -- 13.3.2 The VibroPiano -- 13.3.3 The HSoundplane -- 13.4 Conclusions -- References -- Appendix Glossary and Abbreviations.
    Additional Edition: Print version: Papetti, Stefano Musical Haptics Cham : Springer International Publishing AG,c2018 ISBN 9783319583150
    Language: English
    Keywords: Electronic books. ; Electronic books ; Electronic books ; Aufsatzsammlung
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  • 4
    UID:
    almahu_9949767382902882
    Format: 1 online resource (249 pages)
    Edition: 1st ed.
    ISBN: 9783031548277
    Note: Intro -- Foreword by Florian Schütz -- Foreword by Jan Kleijssen -- Preface -- Acknowledgments -- Contents -- List of Contributors -- Reviewers -- Acronyms -- Part I Introduction -- 1 From Deep Neural Language Models to LLMs -- 1.1 What LLMs Are and What LLMs Are Not -- 1.2 Principles of LLMs -- 1.2.1 Deep Neural Language Models -- 1.2.2 Generative Deep Neural Language Models -- 1.2.3 Generating Text -- 1.2.4 Memorization vs Generalization -- 1.2.5 Effect of the Model and Training Dataset Size -- References -- 2 Adapting LLMs to Downstream Applications -- 2.1 Prompt Optimization -- 2.2 Pre-Prompting and Implicit Prompting -- 2.3 Model Coordination: Actor-Agents -- 2.4 Integration with Tools -- 2.5 Parameter-Efficient Fine-Tuning -- 2.6 Fine-Tuning -- 2.7 Further Pretraining -- 2.8 From-Scratch Re-Training -- 2.9 Domain-Specific Distillation -- References -- 3 Overview of Existing LLM Families -- 3.1 Introduction -- 3.2 Pre-Transformer LLMs -- 3.3 BERT and Friends -- 3.4 GPT Family Proper -- 3.5 Generative Autoregressors (GPT Alternatives) -- 3.6 Compute-Optimal Models -- 3.6.1 LLaMA Family -- 3.7 Full-Transformer/Sequence-to-Sequence Models -- 3.8 Multimodal and Mixture-of-Experts Models -- 3.8.1 Multimodal Visual LLMs -- 3.8.2 Pathways Language Model, PaLM -- 3.8.3 GPT-4 and BingChat -- References -- 4 Conversational Agents -- 4.1 Introduction -- 4.2 GPT Related Conversational Agents -- 4.3 Alternative Conversational Agent LLMs -- 4.3.1 Conversational Agents Without Auxiliary Capabilities -- 4.3.2 Conversational Agents With Auxiliary Capabilities -- 4.3.2.1 Models With Non-Knowledge Auxiliary Capabilities -- 4.4 Conclusion -- References -- 5 Fundamental Limitations of Generative LLMs -- 5.1 Introduction -- 5.2 Generative LLMs Cannot Be Factual -- 5.3 Generative LLMs With Auxiliary Tools Still Struggle To Be Factual. , 5.4 Generative LLMs Will Leak Private Information -- 5.5 Generative LLMs Have Trouble With Reasoning -- 5.6 Generative LLMs Forget Fast and Have a Short Attention Span -- 5.7 Generative LLMs Are Only Aware of What They Saw at Training -- 5.8 Generative LLMs Can Generate Highly Inappropriate Texts -- 5.9 Generative LLMs Learn and Perpetrate Societal Bias -- References -- 6 Tasks for LLMs and Their Evaluation -- 6.1 Introduction -- 6.2 Natural Language Tasks -- 6.2.1 Reading Comprehension -- 6.2.2 Question Answering -- 6.2.3 Common Sense Reasoning -- 6.2.4 Natural Language Generation -- 6.3 Conclusion -- References -- Part II LLMs in Cybersecurity -- 7 Private Information Leakage in LLMs -- 7.1 Introduction -- 7.2 Information Leakage -- 7.3 Extraction -- 7.4 Jailbreaking -- 7.5 Conclusions -- References -- 8 Phishing and Social Engineering in the Age of LLMs -- 8.1 LLMs in Phishing and Social Engineering -- 8.2 Case Study: Orchestrating Large-Scale Scam Campaigns -- 8.3 Case Study: Shā Zhū Pán Attacks -- References -- 9 Vulnerabilities Introduced by LLMs Through Code Suggestions -- 9.1 Introduction -- 9.2 Relationship Between LLMs and Code Security -- 9.2.1 Vulnerabilities and Risks Introduced by LLM-Generated Code -- 9.3 Mitigating Security Concerns With LLM-Generated Code -- 9.4 Conclusion and The Path Forward -- References -- 10 LLM Controls Execution Flow Hijacking -- 10.1 Faulting Controls: The Genesis of Execution Flow Hijacking -- 10.2 Unpacking Execution Flow: LLMs' Sensitivity to User-Provided Text -- 10.3 Examples of LLMs Execution Flow Attacks -- 10.4 Securing Uncertainty: Security Challenges in LLMs -- 10.5 Security by Design: Shielding Probabilistic Execution Flows -- References -- 11 LLM-Aided Social Media Influence Operations -- 11.1 Introduction -- 11.2 Salience of LLMs -- 11.3 Potential Impact -- 11.4 Mitigation -- References. , 12 Deep(er) Web Indexing with LLMs -- 12.1 Introduction -- 12.2 Innovation Through Integration of LLMs -- 12.3 Navigating Complexities: Challenges and Mitigation Strategies -- 12.3.1 Desired Behavior of LLM-Based Search Query Creation Tools -- 12.3.2 Engineering Challenges and Mitigations -- 12.3.2.1 Ethical and Security Concerns -- 12.3.2.2 Fidelity of Query Responses and Model Accuracy -- 12.3.2.3 Linguistic and Regulatory Variations -- 12.3.2.4 Handling Ambiguous Queries -- 12.4 Key Takeaways -- 12.5 Conclusion and Reflections -- References -- Part III Tracking and Forecasting Exposure -- 13 LLM Adoption Trends and Associated Risks -- 13.1 Introduction -- 13.2 In-Context Learning vs Fine-Tuning -- 13.3 Adoption Trends -- 13.3.1 LLM Agents -- 13.4 Potential Risks -- References -- 14 The Flow of Investments in the LLM Space -- 14.1 General Context: Investments in the Sectors of AI, ML, and Text Analytics -- 14.2 Discretionary Evidence -- 14.3 Future Work with Methods Already Applied to AI and ML -- References -- 15 Insurance Outlook for LLM-Induced Risk -- 15.1 General Context of Cyber Insurance -- 15.1.1 Cyber-Risk Insurance -- 15.1.2 Cybersecurity and Breaches Costs -- 15.2 Outlook for Estimating the Insurance Premia of LLMs Cyber Insurance -- References -- 16 Copyright-Related Risks in the Creation and Useof ML/AI Systems -- 16.1 Introduction -- 16.2 Concerns of Owners of Copyrighted Works -- 16.3 Concerns of Users Who Incorporate Content Generated by ML/AI Systems Into Their Creations -- 16.4 Mitigating the Risks -- References -- 17 Monitoring Emerging Trends in LLM Research -- 17.1 Introduction -- 17.2 Background -- 17.3 Data and Methods: Noun Extraction -- 17.4 Results -- 17.4.1 Domain Experts Validation and Interpretations -- 17.5 Discussion, Limitations and Further Research -- 17.6 Conclusion -- References -- Part IV Mitigation. , 18 Enhancing Security Awareness and Education for LLMs -- 18.1 Introduction -- 18.2 Security Landscape of LLMs -- 18.3 Foundations of LLM Security Education -- 18.4 The Role of Education in Sub-Areas of LLM Deployment and Development -- 18.5 Empowering Users Against Security Breaches and Risks -- 18.6 Advanced Security Training for LLM Users -- 18.7 Conclusion and the Path Forward -- References -- 19 Towards Privacy Preserving LLMs Training -- 19.1 Introduction -- 19.2 Dataset Pre-processing with Anonymization and De-duplication -- 19.3 Differential Privacy for Fine-Tuning Models -- 19.4 Differential Privacy for Deployed Models -- 19.5 Conclusions -- References -- 20 Adversarial Evasion on LLMs -- 20.1 Introduction -- 20.2 Evasion Attacks in Image Classification -- 20.3 Impact of Evasion Attacks on the Theory of Deep Learning -- 20.4 Evasion Attacks for Language Processing and Applicability to Large Language Models -- References -- 21 Robust and Private Federated Learning on LLMs -- 21.1 Introduction -- 21.1.1 Peculiar Challenges of LLMs -- 21.2 Robustness to Malicious Clients -- 21.3 Privacy Protection of Clients' Data -- 21.4 Synthesis of Robustness and Privacy -- 21.5 Concluding Remarks -- References -- 22 LLM Detectors -- 22.1 Introduction -- 22.2 LLMs' Salience -- 22.2.1 General Detectors -- 22.2.2 Specific Detectors -- 22.3 Potential Mitigation -- 22.3.1 Watermarking -- 22.3.2 DetectGPT -- 22.3.3 Retrieval Based -- 22.4 Mitigation -- References -- 23 On-Site Deployment of LLMs -- 23.1 Introduction -- 23.2 Open-Source Development -- 23.3 Technical Solution -- 23.3.1 Serving -- 23.3.2 Quantization -- 23.3.3 Energy Costs -- 23.4 Risk Assessment -- References -- 24 LLMs Red Teaming -- 24.1 History and Evolution of Red-Teaming Large Language Models -- 24.2 Making LLMs Misbehave -- 24.3 Attacks -- 24.3.1 Classes of Attacks on Large Language Models. , 24.3.1.1 Prompt-Level Attacks -- 24.3.1.2 Contextual Limitations: A Fundamental Weakness -- 24.3.1.3 Mechanisms of Distractor and Formatting Attacks -- 24.3.1.4 The Role of Social Engineering -- 24.3.1.5 Integration of Fuzzing and Automated Machine Learning Techniques for Scalability -- 24.4 Datasets -- 24.5 Defensive Mechanisms Against Manual and Automated Attacks on LLMs -- 24.6 The Future -- Appendix -- References -- 25 Standards for LLM Security -- 25.1 Introduction -- 25.2 The Cybersecurity Landscape -- 25.2.1 MITRE CVEs -- 25.2.2 CWE -- 25.2.3 MITRE ATT& -- CK and Cyber Kill Chain -- 25.3 Existing Standards -- 25.3.1 AI RMF Playbook -- 25.3.2 OWASP Top 10 for LLMs -- 25.3.3 AI Vulnerability Database -- 25.3.4 MITRE ATLAS -- 25.4 Looking Ahead -- References -- Part V Conclusion -- 26 Exploring the Dual Role of LLMs in Cybersecurity: Threats and Defenses -- 26.1 Introduction -- 26.2 LLM Vulnerabilities -- 26.2.1 Security Concerns -- 26.2.1.1 Data Leakage -- 26.2.1.2 Toxic Content -- 26.2.1.3 Disinformation -- 26.2.2 Attack Vectors -- 26.2.2.1 Backdoor Attacks -- 26.2.2.2 Prompt Injection Attacks -- 26.2.3 Testing LLMs -- 26.3 Code Creation Using LLMs -- 26.3.1 How Secure is LLM-Generated Code? -- 26.3.2 Generating Malware -- 26.4 Shielding with LLMs -- 26.5 Conclusion -- References -- 27 Towards Safe LLMs Integration -- 27.1 Introduction -- 27.2 The Attack Surface -- 27.3 Impact -- 27.4 Mitigation -- References.
    Additional Edition: Print version: Kucharavy, Andrei Large Language Models in Cybersecurity Cham : Springer International Publishing AG,c2024 ISBN 9783031548260
    Language: English
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  • 5
    UID:
    almahu_9949568766902882
    Format: 1 online resource (310 pages)
    Edition: 1st ed.
    ISBN: 9789819936687
    Series Statement: Springer Tracts in Electrical and Electronics Engineering Series
    Note: Intro -- Preface -- Contents -- Editors and Contributors -- 1 Evolution of Next-Generation Communication Technology -- Introduction -- Existing Cellular Network and Its Challenges -- First Generation -- Second Generation -- Third Generation -- Fourth Generation -- Fifth Generation -- Conventional Cellular Systems-Limitations -- Vision and Mission-5G -- Architecture-5G -- C-Ran -- SBA-Based Core Network -- Next-Generation Network-Applications -- Example of Next-Generation Network Applications -- Conclusion and Future Scope -- References -- 2 Third Industrial Revolution: 5G Wireless Systems, Internet of Things, and Beyond -- Introduction -- IoT and Its Devices -- A 5G and IoT -- 5G and Ubiquitous Computing -- The Internet of Things -- A 5G Network -- History and Present Researches on IoT as Well as 5G -- Requirements of IoT and Shortcomings of Wireless 4G Network -- Needs for IoT that is 5G Enabled -- The Vision of 5G IOT: Industrial and Research Context -- Unification of Technologies -- Enabling Technology Drivers in 5G IoT -- Challenges and Trends of Future of the Research -- Conclusion and Future Scope -- Appendix 1: Wireless Technology Features -- Appendix 2: Information Speed Increment -- Appendix 3: 5G Network Architecture -- Appendix 4: 5G Tower Signals -- References -- 3 Network Architectures and Protocols for Efficient Exploitation of Spectrum Resources in 5G -- Introduction -- Enabler Technologies -- Architecture of 5G -- Multiple-Input Multiple-Output Technology in 5G -- Antenna Array for MIMO in 5G -- Device-to-Device Communication in 5G -- Interference Management for 5G -- Multi-tier 5G Architecture -- Spectrum Sharing with Cognitive Radio in 5G -- Ultra-dense Networks in Multi-radio Access Technology Association in 5G -- UDN Moving Cells with 5G+ Network -- Cloud Technologies for 5G -- Methodology. , The Methodology of the Proposed Scheme -- Spectrum Band -- 5G Base Station -- Energy Module -- Energy Controller -- Challenges and Future Research Directions -- Conclusion -- References -- 4 Wireless Backhaul Optimization Algorithm in 5G Communication -- Introduction -- Network Scenarios and System Assumptions -- Analysis of Delay Jitter Indicators -- Delay Analysis -- Delay Jitter Analysis -- Optimization Model Establishments -- Basic Backhaul Model -- Improved Model 1 -- Improved Model 2 -- Improved Model Solutions -- Improved Model 1 Solution -- Improved Model 2 Solution -- Simulation Analysis -- Conclusions -- References -- 5 Security Attacks and Vulnerability Analysis in Mobile Wireless Networking -- Introduction -- Types of Wireless Mobile Network -- Wireless PAN -- Wireless LAN -- Manet -- Wireless MAN -- Wireless WAN -- Mobile Network -- Gan -- Aerospace Network -- Challenges and Issues in Wireless Mobile Network -- Information Management -- Endless Communication -- Delay Tolerance -- Heterogeneity -- Contextual Awareness -- Buffer Management -- Power Features -- Privacy and Security -- Security Goals of Wireless Mobile Network -- Classification of Security Attacks -- Most Prevalent Attacks in Wireless Systems -- Denial of Service (DoS) Attack -- Flooding Attack -- Jamming -- Intervention -- Sleep Deprivation Attack -- Blackhole Attack -- Rushing Attack -- Sybil Attack -- Sinkhole Attack -- Gray Hole Attack -- Byzantine Attack -- Jellyfish Attack -- Wormhole Attack -- Eavesdropping -- Disclosure of Information Attack -- Man-In-The-Middle Attack -- Replay Attack -- ACK Attack -- Spoofing Attack -- Link Spoofing Attack -- Spear-Phishing Attack -- Repudiation Attack -- Infected Code Injection -- Colluding Mis-Relay Attack -- Selective-Forwarding Attack -- Database Hack Attack -- Conclusion -- References. , 6 Utilities of 5G Communication Technologies for Promoting Advancement in Agriculture 4.0: Recent Trends, Research Issues and Review of Literature -- Introduction -- Challenges Faced by Existing Network Technologies -- Motivation of the Work -- Existing Problems and Contribution -- Scope of 5G-Enabled Networks in AgriIoT -- Energy Consumption Management Methods in 5G Networks -- Application Areas of 5G in Smart Farming -- Data Aggregation -- Predictive Analytics -- Drone Operations -- Animal Tracking and Real-Time Monitoring -- Autonomous Agriculture Vehicles -- Weather Stations -- 5G Enabled Components in Agriculture -- Drones and Unmanned Aerial Vehicles (UAVs) -- Virtual Consultation and Predictive Maintenance -- Augmented and Virtual Reality -- Agriculture Robots -- Cloud-Based Data Analytics -- Recent Development Scenarios in 5G-Based Agriculture -- Conclusion and Future Work -- References -- 7 Security Attacks and Countermeasures in 5G Enabled Internet of Things -- Introduction -- Overview of 5G -- Overview of IoT -- 5G Enabled IoT -- 5G Enabled IoT Architecture -- L1 Physical Device Layer -- L2 Communication Layer -- L3 Fog Computing Layer -- L4 Data Storage Layer -- L5 Management Service Layer -- L6 Application Layer -- L7 Process and Collaboration Layer -- L8 Security Layer -- Technologies in 5G Enabled IoT -- Threat Analysis in 5G IoT -- Eavesdropping -- Contaminating -- Spoofing -- Jamming -- Physical Layer Security -- Trust Mechanism in WSN -- Crowdsourcing Analysis -- Attacks at the Architecture Level -- Current Research for 5G and IoT -- Future Research Directions and Challenges -- Characteristics Synthesis -- Signal Revoking -- Location Awareness -- Technical Challenges -- Wireless Software Defined Network -- Security Assurance and Privacy Analysis -- Standardization Issues -- Conclusion -- References. , 8 Energy Efficiency and Scalability of 5G Networks for IoT in Mobile Wireless Sensor Networks -- Introduction -- Energy Efficiency in Mobile Wireless Sensor Networks -- Basic Concept of 5G Technology -- Evolution of 5G -- Frequency Band of 5G System -- 5G Innovative Technologies -- IoT Services Based on 5G -- IoT Industry Supported by 5G Technology -- Industry 4.0 -- Palpable Internet -- Security of IoT in 5G System -- Conclusion -- References -- 9 Security Services for Wireless 5G Internet of Things (IoT) Systems -- Introduction -- Inspiration and Ideas for 5G Based on IoT -- Structure of IoT in Cooperation with 5G -- Sensor Layer -- Network Layer -- Communication Layer -- Architecture Layer -- Application Layer -- Current Resolutions for Communication for IoT in 5G -- Bluetooth Low Energy (BLE) -- SigFox -- IEEE 802.15.4 -- LoRa -- Wi-Fi -- ZigBee -- NarrowBand IoT -- Challenges and Security Vulnerabilities -- Confidentiality and Safety -- Energy Efficacy -- Future Research Directions -- Structure of Network Based on Big Data -- 5G New Radio (NR): A New Wave-Form Design Consideration -- Energy Efficacy -- Interchange Between Communication, Gathering, and Computing -- Design of Synchronized Multi-Band, and High-Power Effective Amplifier -- Conclusion -- References -- 10 Securing the IoT-Based Wireless Sensor Networks in 5G and Beyond -- Introduction -- Literature Survey -- IoT-Based Wireless Networks -- Different Types of Attacks -- Perception Layer -- Abstraction Layer -- Network Layer -- Computing Layer -- Operation Layer -- Application Layer -- Importance of 5G -- Background -- Mathematical Explanation for Euclidean Distance -- Proposed Work -- Assumptions -- Creating Trial Data Sets -- Transmitting the Messages -- Analysis of the Proposal -- Security -- Conclusion -- References. , 11 5G and Internet of Things-Integration Trends, Opportunities, and Future Research Avenues -- Introduction -- Overview of 5G -- Evolution of 5G -- Characteristics and Requirements of 5G Ecosystem -- 5G Architecture -- An Insight into IoT -- Characteristics of IoT -- Layered Architecture of IoT -- Requirements for 5G Integrated IoT Architecture -- Edge Layer of 5G IoT -- Network Layer of 5G IoT -- Application Layer of 5G IoT -- Blockchain-Based 5G IoT -- 5G IoT with Artificial Intelligence -- Opportunities of 5G Integrated IoT -- Technological Advancement -- Smart Cities -- Business -- Aerial and Satellite Research -- Mitigating Pandemic Situation -- Industrial Usage with Other Technologies -- Video Surveillance -- Challenges of 5G Integrated IoT -- General Challenges -- Heterogeneity of 5G and IoT Data -- Blockchain Integrating 5G IoT Issues -- 5G mm-Wave Issues -- Threat Protection of 5G IoT -- Conclusion -- References -- 12 Post-Quantum Cryptographic Schemes for Security Enhancement in 5G and B5G (Beyond 5G) Cellular Networks -- Introduction -- Emerging Cellular Networks -- 5G Overview -- Evolution of 6G/B5G Overview -- State-Of-The-Art -- Taxonomy of 6G/B5G Wireless Systems -- Security Services in 6G/B5G Wireless Networks -- Data Security Techniques for 5G Heterogeneous Networks -- Visual Secret Sharing -- Steganography -- Cryptographic Algorithms -- Key Management -- Overview and Fundamentals of Quantum Computing -- Architecture of Classical Computing Versus Quantum Computing -- Mathematical Representation for Quantum Computing -- The Impact of Quantum Computing on Modern Cryptography -- Quantum Algorithms Affecting Cryptosystems -- Post-Quantum Cryptography -- Mathematical View -- Post-Quantum Analysis -- Conclusion -- References -- 13 Enhanced Energy Efficiency and Scalability in Cellular Networks for Massive IoT -- Introduction. , Literature Review.
    Additional Edition: Print version: Bhushan, Bharat 5G and Beyond Singapore : Springer,c2023 ISBN 9789819936670
    Language: English
    Keywords: Electronic books. ; Electronic books.
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  • 6
    UID:
    almahu_9948609774302882
    Format: VIII, 137 p. 26 illus., 24 illus. in color. , online resource.
    Edition: 1st ed. 2021.
    ISBN: 9783030523916
    Series Statement: Science Policy Reports,
    Content: The essays in this open access volume identify the key ingredients for success in capitalizing on public investments in scientific projects and the development of large-scale research infrastructures. Investment in science - whether in education and training or through public funding for developing new research tools and technologies - is a crucial priority. Authors from big research laboratories/organizations, funding agencies and academia discuss how investing in science can produce societal benefits as well as identifying future challenges for scientists and policy makers. The volume cites different ways to assess the socio-economic impact of Research Infrastructures and their role as hubs of global collaboration, creativity and innovation. It highlights the different benefits stemming from fundamental research at the local, national and global level, while also inviting us to rethink the notion of "benefit" in the 21st century. Public investment is required to maintain the pace of technological and scientific advancements over the next decades. Far from advocating a radical transformation and massive expansion in funding, the authors suggest ways for maintaining a strong foundation of science and research to ensure that we continue to benefit from the outputs. The volume draws inspiration from the first "Economics of Big Science" workshop, held in Brussels in 2019 with the aim of creating a new space for dialogue and interaction between representatives of Big Science organizations, policy makers and academia. It aspires to provide useful reading for policy makers, scientists and students of science, who are increasingly called upon to explain the value of fundamental research and adopt the language and logic of economics when engaging in policy discussions.
    Note: Introduction -- Towards a Sustainable European Research Infrastructures Ecosystem -- Economics of Science in the Time of Data Economy and Gigabit Society -- The SKA Approach to Sustainable Research -- The European Spallation Source: Designing a Sustainable Research Infrastructure for Europe -- Optimising the Benefits from Research Institutes -- Rethinking the Socio-economic Value of Big Science: Lessons from the FCC Study -- Socio-Economic Impact Assessments of ESA Programmes: A Brief Overview -- Designing a Socio-Economic Impact Framework for Research Infrastructures: Preliminary Lessons from the RI-PATHS Project -- Findings from the LHC/HL-LHC Programme -- Designing a Research Infrastructure with Impact in Mind -- Leveraging the Economic Potential of FCC's Technologies and Processes -- How to Value Public Science Employing Social Big Data? -- R&D, Innovative Collaborations and the Role of Public Policies -- Large-Scale Investment in Science: Economic Impact and Social Justice -- Investing in Fundamental Research: For Whom? A Philosopher's Perspective -- Investing in Fundamental Research: Evaluation of the Benefits that the UK Has Derived from CERN -- Fundamental Science Drives Innovation -- Epilogue: Productive Collisions-Blue-Sky Science and Today's Innovations.
    In: Springer Nature eBook
    Additional Edition: Printed edition: ISBN 9783030523909
    Additional Edition: Printed edition: ISBN 9783030523923
    Additional Edition: Printed edition: ISBN 9783030523930
    Language: English
    Keywords: Conference papers and proceedings. ; Conference papers and proceedings. ; Conference papers and proceedings. ; Conference papers and proceedings.
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  • 7
    Online Resource
    Online Resource
    Bristol :Policy Press,
    UID:
    almahu_9949767559102882
    Format: 1 online resource (167 pages)
    Edition: 1st ed.
    ISBN: 9781447367352
    Content: This important book uses empirical evidence to explore the concept of public trust in health systems. In doing so, it provides a comprehensive contemporary explanation of public trust, how it affects health systems and how it can be nurtured and maintained as an integral component of health system governance.
    Note: Front Cover -- What is Public Trust in the Health System?: Insights into Health Data Use -- Copyright information -- Table of Contents -- List of figures and tables -- About the author -- Acknowledgements -- ONE Introduction -- Part I Why do we care about public trust in the health system? -- TWO What is trust? -- Relationship - we need a relation to trust -- Communication - we need to communicate to place trust -- Truth - we need truthful information to place trust -- Autonomy - we need free choice to place trust -- Alternatives - we need alternatives between which we choose to trust -- No guarantee - we cannot guarantee trust -- Concluding remarks -- THREE Three health system examples -- Public trust in vaccination -- What is public trust in vaccination? -- What builds trust in vaccination? -- Public trust in non-pharmaceutical interventions to fight the COVID-19 pandemic -- What is public trust in non-pharmaceutical interventions to fight the COVID-19 pandemic? -- What builds public trust in non-pharmaceutical interventions to fight the COVID-19 pandemic? -- Public trust in health data use in health systems -- What is public trust in health data use in health systems? -- What builds public trust in health data use in health systems? -- Concluding remarks -- Part II What is public trust in the health system? -- FOUR Where does public trust develop? -- How misinformation and conspiracy threaten public trust building in the public sphere -- Public trust develops in the public sphere -- Concluding remarks -- FIVE What builds public trust? -- Theme relating to the past -- Familiarity -- Themes relating to the present -- Active regulatory systems -- Anonymity -- Autonomy -- Gut feeling -- Information quality -- Privacy -- Potential -- Respect -- Security -- Themes relating to the future -- Certainty about the future -- Net benefit -- Time. , Concluding remarks -- SIX What are the effects of public trust? -- Participation -- Legitimisation -- Concluding remarks -- SEVEN What frames public trust? -- Communication -- Reason for the need of public trust -- Risk -- Fear -- Human error -- World-view -- Religion and afterlife -- Public mood -- Trust cannot be expected -- Concluding remarks -- Part III How can we foster public trust in the health system? -- EIGHT How can we build public trust by means of effective health policy and governance? -- 1. Do not rush trust building -- 2. Engage with the public -- 3. Keep the public safe -- 4. Offer autonomy to the public -- 5. Plan for diverse trust relationships -- 6. Recognise that trust is shaped by both emotion and rational thought -- 7. Represent the public interest -- 8. Work towards realising a net benefit for the health system and the public -- Concluding remarks -- NINE How can we foster public trust by means of effective communications? -- Understand the present and historical context as well as the actors involved in the health system -- Understand the mechanisms that are fundamental to building public trust -- Understand how public trust-building actions are embedded in the wider societal and political context -- Communicate via credible and reputable spokespersons -- Make the information easily understandable and tangible, and tailor the information to different target audiences -- Convene public discussion fora -- Meaningfully engage and involve responsible actors when developing a consistent communication strategy -- Provide the opportunity for public engagement and response when developing and implementing communication strategies -- Consider the potential impact of conspiracy and misinformation on the public trust-building processes -- Develop a contingency plan for events that diminish public trust -- Concluding remarks. , TEN How can we foster public trust through effective observation? -- Concluding remarks -- ELEVEN Conclusion -- How can we evaluate the performance of health policies to build public trust? -- What is the economic power of public trust in health systems? -- How does public trust develop in unstable societies? -- How does public trust develop in international and national health politics? -- How does history influence trust in present digital health activities? -- References -- Index.
    Additional Edition: Print version: Gille, Felix What Is Public Trust in the Health System? Bristol : Policy Press,c2023
    Language: English
    Keywords: Electronic books.
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  • 8
    UID:
    almahu_9949846772302882
    Format: 1 online resource (169 pages)
    Edition: 1st ed.
    ISBN: 9783031533976
    Series Statement: Springer Aerospace Technology Series
    Note: Intro -- Preface I -- A Note by the Delegates to the Research -- Contents -- Historical Background and Evolution in the Decade -- Naval Architecture and Marine Engineering -- 1 Introduction -- 2 Background and Legacy -- 3 Evolution -- 4 Main Research Programmes -- 4.1 Hull Performance and Shape Optimization -- 4.2 Low Environmental Impact Ships -- 4.3 Sea Keeping and Structural Loads -- 4.4 Ship Propulsion -- 4.5 Ship Stability and Safety -- 4.6 Ship Structural Analysis-Noise and Vibrations -- 5 Future -- References -- Aerospace Engineering -- 1 Introduction -- 2 Background and Legacy -- 3 Congresses -- 4 Main Research Groups and Programmes -- 4.1 Design of Aircraft and Flight Technologies (DAF) -- 4.2 Structural Technologies, Methods and Applications -- 4.3 Fluid-Dynamics, Aerodynamics and Propulsion -- 4.4 Aerospace Systems -- 5 Future -- 6 Awards -- References -- Fluid Machinery, Energy Systems and Power Generation -- 1 Internal Combustion Engines -- 1.1 Introduction -- 1.2 Research Areas -- 1.3 Results and Discussion -- 2 Turbomachinery -- 2.1 Turbochargers -- 2.2 Wind Turbines and Propellers -- 2.3 Fundamental Study on Wall Turbulence -- 2.4 Turbomachines for Real Gas Applications -- 3 Energy Conversion Systems -- 3.1 Introduction -- 3.2 Research Areas -- 3.3 Results -- 4 Fluid Power Systems -- References -- Thermal Engineering and Building Energy Systems -- 1 Introduction -- 2 Background and Legacy -- 3 Main Research Programs -- 3.1 Applied Acoustics -- 3.2 Energy Efficiency and Renewable Energy (EERE) -- 3.3 Heat Transfer in Civil, Industrial and Biological Systems -- 3.4 Heating, Ventilation and Air Conditioning (HVAC) and Energy Efficiency of the Building-Plant System -- 3.5 Indoor Environmental Quality -- 3.6 Lighting -- 3.7 Experiments and Modelling of Innovative Systems for Refrigeration. , 3.8 Refrigeration and Heat Transfer on Systems Alternative to Vapor Compression -- 3.9 Sustainable Energy Systems (SES) -- 4 Future -- 5 Awards -- References -- From Mechanical to Complex System Modeling and Design -- 1 Introduction -- 2 Background and Legacy -- 2.1 Mechanics Applied to Machines -- 2.2 Mechanical Design, Machine Construction and Design Methods for Industrial Engineering -- 3 Main Research Programmes -- 3.1 Integrated Navigation Solutions Based on Cost-Effective Inertial Measurement Units -- 3.2 AR-Based Applications for Remote Control of Measurement Instrumentation for Didactical Applications -- 3.3 Control, Health Monitoring and Predictive Diagnostics of Mechanical Systems -- 3.4 Dynamic Behaviour of Rotors and Lubricated Pairs -- 3.5 Dynamics of Railway Vehicles -- 3.6 The ``Gear Rattle'' in Automotive Transmissions -- 3.7 Robotics -- 3.8 Use of Magnetorheological Elastomers as SMART Material in Insulators and Energy Harvesting -- 3.9 Vehicle Dynamics and Tyre Behaviour -- 3.10 Railways Thermal Buckling Assessment -- 3.11 Railways Fatigue and Fracture Assessment -- 3.12 Adhesive Bonding in Structural Junctions -- 3.13 Model Based Systems Engineering (MBSE)-Digital Twin of Complex Systems -- 3.14 Virtual Prototyping-Computer Geometric Modelling and Simulation -- 3.15 Design for Additive Manufacturing and Reverse Engineering -- 3.16 Nuclear Fusion -- 3.17 Extended Reality for Industrial Engineering -- 3.18 Human Centered Design of Sports Equipment and Safety Tools -- 3.19 Soft Robotics -- 4 Future -- References -- Business and Management Engineering -- 1 Introduction -- 2 Background and Legacy -- 3 Congresses -- 4 Main Research Programmes -- 4.1 Complexity in Organizational and Innovation Management Studies -- 4.2 Empowering Academic Entrepreneurship in the Digital Age: Insights, Innovations, and Future Directions. , 4.3 Links Between Open Innovation Strategies, Sustainability and Digitization of Companies -- 4.4 Decision Support Systems for Supply Chain and Logistics Design and Management -- 4.5 Managing Digital and Sustainable Innovation in Individual Firms and Supply Chains -- 4.6 Organizational and Innovation Management in Healthcare -- 4.7 Project Management in World of Research, Public Administration and Business Start up -- 5 Future -- References -- Statistics for Experimental and Technological Research -- 1 Background and Legacy -- 2 Main Research Programmes -- 2.1 Stochastic Modelling of Degradation Processes and Their Use in Reliability and Maintenance -- 2.2 Software Reliability Growth Modeling -- 2.3 Natural Risk Assessment and Mitigation -- 2.4 Statistical Learning and Monitoring of Complex Data from Industrial Processes -- 2.5 Statistical Methods for the Evaluation of Automotive and Aircraft Seat Comfort -- 2.6 Quality of Subjective Evaluations Expressed as Ratings or Preferences -- 2.7 Evaluation of Classifier Predictive Performance -- 2.8 Deep Learning for Smart and Sustainable Agriculture -- References -- Electrical Power Systems -- 1 Introduction -- 2 Background and Legacy -- 3 Evolution -- 4 Main Research Programs -- 5 Awards -- 6 Future -- References -- Real Estate Appraisal -- 1 Introduction -- 2 Background and Legacy -- 3 Evolution -- 4 Main Research Programmes -- 5 Awards -- 6 Future -- References -- The Project for the Excellence: A Guide for the Next Decade -- 1 Before the Project for the Excellence -- 1.1 Some Numbers -- 1.2 Points of Strength and Weakness -- 2 The Project for the Excellence -- 2.1 Main Points -- 2.2 Future Research Infrastructures -- 2.3 Future Teaching Activities -- 3 A Final Word.
    Additional Edition: Print version: Bianco, Nicola A Decade of Research Activities at the Department of Industrial Engineering (UniNa-DII) Cham : Springer,c2024 ISBN 9783031533969
    Language: English
    Keywords: Electronic books. ; Electronic books.
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  • 9
    UID:
    almahu_9949616271002882
    Format: 1 online resource (1210 pages)
    Edition: 1st ed.
    ISBN: 9783031265884
    Note: Intro -- Foreword -- Introduction -- Fundamentals -- Part I: Programming and Remote Sensing Basics -- Part II: Interpreting Images -- Part III: Advanced Image Processing -- Part IV: Interpreting Image Series -- Part V: Vectors and Tables -- Part VI: Advanced Topics -- Applications -- Part VII: Human Applications -- Part VIII: Aquatic and Hydrological Applications -- Part IX: Terrestrial Applications -- Uses of This Book -- We Want Your Feedback -- Acknowledgements -- Other Sources -- Contents -- Part IProgramming and Remote Sensing Basics -- 1 JavaScript and the Earth Engine API -- 1.1 Introduction to Theory -- 1.2 Practicum -- 1.2.1 Section 1: Getting Started in the Code Editor -- 1.2.2 Section 2: JavaScript Basics -- 1.2.3 Section 3: Earth Engine API Basics -- 1.3 Synthesis -- 1.4 Conclusion -- 2 Exploring Images -- 2.1 Practicum -- 2.1.1 Section 1: Accessing an Image -- 2.1.2 Section 2: Visualizing an Image -- 2.1.3 Section 3: True-Color Composites -- 2.1.4 Section 4: False-Color Composites -- 2.1.5 Section 5: Additive Color System -- 2.1.6 Section 6: Attributes of Locations -- 2.1.7 Section 7: Abstract RGB Composites -- 2.2 Synthesis -- 2.3 Conclusion -- 3 Survey of Raster Datasets -- 3.1 Introduction to Theory -- 3.2 Practicum -- 3.2.1 Section 1: Image Collections: An Organized Set of Images -- 3.2.2 Section 2: Collections of Single Images -- 3.2.3 Section 3: Pre-made Composites -- 3.2.4 Section 4: Other Satellite Products -- 3.2.5 Section 5: Pre-classified Land Use and Land Cover -- 3.2.6 Section 6: Other Datasets -- 3.3 Synthesis -- 3.4 Conclusion -- References -- 4 The Remote Sensing Vocabulary -- 4.1 Introduction to Theory -- 4.2 Practicum -- 4.2.1 Section 1: Searching for and Viewing Image Collection Information -- 4.2.2 Section 2: Spatial Resolution -- 4.2.3 Section 3: Temporal Resolution -- 4.2.4 Section 4: Spectral Resolution. , 4.2.5 Section 5: Per-Pixel Quality -- 4.2.6 Section 6: Metadata -- 4.3 Synthesis -- 4.4 Conclusion -- Reference -- Part IIInterpreting Images -- 5 Image Manipulation: Bands, Arithmetic, Thresholds, and Masks -- 5.1 Introduction to Theory -- 5.2 Practicum -- 5.2.1 Section 1: Band Arithmetic in Earth Engine -- 5.2.2 Section 2: Thresholding, Masking, and Remapping Images -- 5.3 Synthesis -- 5.4 Conclusion -- References -- 6 Interpreting an Image: Classification -- 6.1 Introduction to Theory -- 6.2 Practicum -- 6.2.1 Section 1: Supervised Classification -- 6.2.2 Section 2: Unsupervised Classification -- 6.3 Synthesis -- 6.4 Conclusion -- References -- 7 Accuracy Assessment: Quantifying Classification Quality -- 7.1 Introduction to Theory -- 7.2 Practicum -- 7.2.1 Quantifying Classification Accuracy Through a Confusion Matrix -- 7.2.2 Hyperparameter Tuning -- 7.2.3 Spatial Autocorrelation -- 7.3 Synthesis -- 7.4 Conclusion -- References -- Part IIIAdvanced Image Processing -- 8 Interpreting an Image: Regression -- 8.1 Introduction to Theory -- 8.2 Practicum -- 8.2.1 Reducers -- 8.3 Section 1: Linear Fit -- 8.3.1 Section 2: Linear Regression -- 8.3.2 Section 3: Nonlinear Regression -- 8.3.3 Section 4: Assessing Regression Performance Through RMSE -- 8.4 Synthesis -- 8.5 Conclusion -- References -- 9 Advanced Pixel-Based Image Transformations -- 9.1 Introduction to Theory -- 9.2 Practicum -- 9.2.1 Section 1: Manipulating Images with Expressions -- 9.2.2 Section 2: Manipulating Images with Matrix Algebra -- 9.2.3 Section 3: Spectral Unmixing -- 9.2.4 Section 4: The Hue, Saturation, Value Transform -- 9.3 Synthesis -- 9.4 Conclusion -- References -- 10 Neighborhood-Based Image Transformation -- 10.1 Introduction to Theory -- 10.2 Practicum -- 10.2.1 Section 1: Linear Convolution -- 10.2.2 Section 2: Nonlinear Convolution. , 10.2.3 Section 3: Morphological Processing -- 10.2.4 Section 4: Texture -- 10.3 Synthesis -- 10.4 Conclusion -- References -- 11 Object-Based Image Analysis -- 11.1 Introduction to Theory -- 11.2 Practicum -- 11.2.1 Section 1: Unsupervised Classification -- 11.2.2 Section 2: Detecting Objects in Imagery with the SNIC Algorithm -- 11.2.3 Section 3: Object-Based Unsupervised Classification -- 11.2.4 Section 4: Classifications with More or Less Categorical Detail -- 11.2.5 Section 5: Effects of SNIC Parameters -- 11.3 Synthesis -- 11.4 Conclusion -- References -- Part IVInterpreting Image Series -- 12 Filter, Map, Reduce -- 12.1 Introduction to Theory -- 12.2 Practicum -- 12.2.1 Section 1: Filtering Image Collections in Earth Engine -- 12.2.2 Section 2: Mapping over Image Collections in Earth Engine -- 12.2.3 Section 3: Reducing an Image Collection -- 12.3 Synthesis -- 12.4 Conclusion -- 13 Exploring Image Collections -- 13.1 Practicum -- 13.1.1 Section 1: Filtering and Inspecting an Image Collection -- 13.1.2 Section 2: How Many Images Are There, Everywhere on Earth? -- 13.1.3 Section 3: Reducing Image Collections to Understand Band Values -- 13.1.4 Section 4: Compute Multiple Percentile Images for an Image Collection -- 13.2 Synthesis -- 13.3 Conclusion -- Reference -- 14 Aggregating Images for Time Series -- 14.1 Introduction to Theory -- 14.2 Practicum -- 14.2.1 Section 1: Filtering an Image Collection -- 14.2.2 Section 2: Working with Dates -- 14.2.3 Section 3: Aggregating Images -- 14.2.4 Section 4: Plotting Time Series -- 14.3 Synthesis -- 14.4 Conclusion -- References -- 15 Clouds and Image Compositing -- 15.1 Introduction to Theory -- 15.2 Practicum -- 15.2.1 Section 1: Cloud Filter and Cloud Mask -- 15.2.2 Section 2: Incorporating Data from Other Satellites -- 15.2.3 Section 3: Best-Available-Pixel Compositing Earth Engine Application. , 15.3 Synthesis -- 15.4 Conclusion -- References -- 16 Change Detection -- 16.1 Introduction to Theory -- 16.2 Practicum -- 16.2.1 Section 1: Preparing Imagery -- 16.2.2 Section 2: Creating False-Color Composites -- 16.2.3 Section 3: Calculating NBR -- 16.2.4 Section 4: Single Date Transformation -- 16.2.5 Section 5: Classifying Change -- 16.3 Synthesis -- 16.4 Conclusion -- References -- 17 Interpreting Annual Time Series with LandTrendr -- 17.1 Introduction to Theory -- 17.2 Practicum -- 17.2.1 Section 1: Pixel Time Series -- 17.2.2 Section 2: Translating Pixels to Maps -- 17.3 Synthesis -- 17.4 Conclusion -- References -- 18 Fitting Functions to Time Series -- 18.1 Introduction to Theory -- 18.2 Practicum -- 18.2.1 Section 1: Multi-temporal Data in Earth Engine -- 18.2.2 Section 2: Data Preparation and Preprocessing -- 18.2.3 Section 3: Estimating Linear Trend Over Time -- 18.2.4 Section 4: Estimating Seasonality with a Harmonic Model -- 18.2.5 Section 5: An Application of Curve Fitting -- 18.2.6 Section 6: Higher-Order Harmonic Models -- 18.3 Synthesis -- 18.4 Conclusion -- References -- 19 Interpreting Time Series with CCDC -- 19.1 Introduction to Theory -- 19.2 Practicum -- 19.2.1 Section 1: Understanding Temporal Segmentation with CCDC -- 19.2.2 Section 2: Running CCDC -- 19.2.3 Section 3: Extracting Break Information -- 19.2.4 Section 4: Extracting Coefficients Manually -- 19.2.5 Section 5: Extracting Coefficients Using External Functions -- 19.3 Synthesis -- 19.4 Conclusion -- References -- 20 Data Fusion: Merging Classification Streams -- 20.1 Introduction to Theory -- 20.2 Practicum -- 20.2.1 Section 1: Imagery and Classifications of the Roosevelt River -- 20.2.2 Section 2: Basics of the BULC Interface -- 20.2.3 Section 3: Detailed LULC Inspection with BULC -- 20.2.4 Section 4: Change Detection with BULC-D. , 20.2.5 Section 5: Change Detection with BULC and Dynamic World -- 20.3 Synthesis -- 20.4 Conclusion -- References -- 21 Exploring Lagged Effects in Time Series -- 21.1 Introduction to Theory -- 21.2 Practicum -- 21.2.1 Section 1: Autocovariance and Autocorrelation -- 21.2.2 Section 2: Cross-Covariance and Cross-Correlation -- 21.2.3 Section 3: Auto-Regressive Models -- 21.3 Synthesis -- 21.4 Conclusion -- References -- Part VVectors and Tables -- 22 Exploring Vectors -- 22.1 Introduction to Theory -- 22.2 Practicum -- 22.2.1 Section 1: Using Geometry Tools to Create Features in Earth Engine -- 22.2.2 Section 2: Loading Existing Features and Feature Collections in Earth Engine -- 22.2.3 Section 3: Importing Features into Earth Engine -- 22.2.4 Section 4: Filtering Feature Collections by Attributes -- 22.2.5 Section 5: Reducing Images Using Feature Geometry -- 22.2.6 Section 6: Identifying the Block in the Neighborhood Surrounding USF with the Highest NDVI -- 22.3 Synthesis -- 22.4 Conclusion -- 23 Raster/Vector Conversions -- 23.1 Introduction to Theory -- 23.2 Practicum -- 23.2.1 Section 1: Raster to Vector Conversion -- 23.2.2 Section 2: Vector-To-Raster Conversion -- 23.3 Synthesis -- 23.4 Conclusion -- 24 Zonal Statistics -- 24.1 Introduction to Theory -- 24.2 Practicum -- 24.2.1 Section 1: Functions -- 24.2.2 Section 2: Point Collection Creation -- 24.2.3 Section 3: Neighborhood Statistic Examples -- 24.2.4 Section 4: Additional Notes -- 24.3 Synthesis -- 24.4 Conclusion -- References -- 25 Advanced Vector Operations -- 25.1 Practicum -- 25.1.1 Section 1: Visualizing Feature Collections -- 25.1.2 Section 2: Joins with Feature Collections -- 25.2 Synthesis -- 25.3 Conclusion -- 26 GEEDiT-Digitizing from Satellite Imagery -- 26.1 Introduction to Theory -- 26.2 Practicum. , 26.2.1 Section 1: Loading GEEDiT and Selecting Imagery Options and a Location.
    Additional Edition: Print version: Cardille, Jeffrey A. Cloud-Based Remote Sensing with Google Earth Engine Cham : Springer International Publishing AG,c2023 ISBN 9783031265877
    Language: English
    Keywords: Electronic books.
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  • 10
    Online Resource
    Online Resource
    Cham :Springer International Publishing AG,
    UID:
    almahu_9949602147302882
    Format: 1 online resource (562 pages)
    Edition: 1st ed.
    ISBN: 9783319732503
    Series Statement: Aquatic Ecology Series ; v.8
    Note: Intro -- Contents -- Chapter 1: Challenges in Riverine Ecosystem Management -- 1.1 Justification of Book -- 1.2 Past and Future Trends -- 1.2.1 Future Trends in River Engineering -- 1.3 Managing River Systems -- 1.3.1 Assessing Degradation -- 1.3.2 Integrating Assessment, Policy, and Action -- 1.3.3 Adaptive Management and Governance -- 1.4 Structure of the Book -- References -- Part I: Human Impacts, Mitigation and Restoration -- Chapter 2: Historic Milestones of Human River Uses and Ecological Impacts -- 2.1 Introduction -- 2.2 Historical River Uses and Resulting Impacts -- 2.2.1 General Patterns of River Uses -- 2.2.2 Milestones of Dam Building -- 2.2.3 River Channelization to Secure Transport and Land Use -- 2.2.4 Water Supply from Rivers: Increasing Imprint on Urban Hinterland -- 2.2.5 Pollution of Rivers and Its Legacies -- 2.2.6 Land-Use Change, Hydrology, and Erosion -- 2.2.7 Fisheries: Intended and Unintended Dispersal of Nonnative Species -- 2.3 Conclusions -- References -- Chapter 3: River Morphology, Channelization, and Habitat Restoration -- 3.1 River Channels as One Piece in the Puzzle -- 3.2 River Types: Complex Diversity or Confusing Variety? -- 3.3 A Shifting Balance of Form and Motion -- 3.4 Channelized Rivers -- 3.5 Assessing the Hydromorphological State of Rivers -- 3.6 Conclusion -- References -- Chapter 4: River Hydrology, Flow Alteration, and Environmental Flow -- 4.1 The Water Cycle and Hydrological Regimes -- 4.2 Flow Determines Habitats and Biotic Communities -- 4.3 Flow Regulation -- 4.4 Human Alteration of Flow Regimes -- 4.5 Ecological Responses to Altered Flow Regime -- 4.6 Environmental Flow -- 4.6.1 The Concept and Definitions of Environmental Flow -- 4.6.2 Assessing and Implementing Environmental Flows -- 4.7 Conclusions -- References -- Chapter 5: Hydropeaking Impacts and Mitigation -- 5.1 Introduction. , 5.2 Detection and Characterization of Flow Fluctuation Intensity and Frequency -- 5.3 Hydropeaking Impacts on Aquatic Biota -- 5.3.1 Flow Velocity, Shear Stress, and Sediment Transport -- 5.3.2 Ramping Rate -- 5.3.3 Frequency, Periodicity, and Timing of Hydropeaking -- 5.3.4 Channel Morphology -- 5.3.5 Water Temperature -- 5.4 Research Application and Hydropeaking Mitigation -- 5.4.1 Potential Hydropeaking Mitigation Measures -- 5.4.2 Integrative Hydropeaking Mitigation and Example of Application -- 5.4.3 Summary and Outlook -- References -- Chapter 6: Dams: Ecological Impacts and Management -- 6.1 Introduction -- 6.2 Transforming Rivers to Reservoirs -- 6.3 Downstream Effects -- 6.4 Other Downstream Impacts -- 6.5 Mitigation Measures -- 6.5.1 Reestablishing Longitudinal Continuity -- 6.5.2 Sediment Management -- 6.5.3 Habitat Improvements in Reservoirs -- References -- Chapter 7: Aquatic Habitat Modeling in Running Waters -- 7.1 Introduction -- 7.2 Principles of Habitat Modeling -- 7.2.1 Biotic Habitat Modeling -- 7.2.2 Abiotic Habitat Modeling -- 7.2.3 Integrative Habitat Assessment -- 7.3 Managing River Systems Through Habitat Assessment -- 7.3.1 Case Study on Microhabitat Scale: E-Flow Study at River Ybbs, Austria -- 7.3.2 Example at Mesohabitat Scale: Mesohabitat Evaluation Model (MEM) -- References -- Chapter 8: The Role of Sediment and Sediment Dynamics in the Aquatic Environment -- 8.1 Introduction -- 8.2 Sediments and River Morphology -- 8.2.1 River Morphology and Substrate Size -- 8.2.2 Sediment Sources -- 8.2.3 Scaling of Sediment Dynamics in the River Environment -- 8.3 Sediment Dynamics and Anthropogenic Alterations of the Sediment Flux: What Aquatic Biota Need and How They React to Altera... -- 8.3.1 Ecological Adaptations of Macroinvertebrates to Sediment Dynamics -- 8.3.2 Ecological Adaptations of Lithophilic Fishes. , 8.4 Sediment Management Options -- 8.5 Conclusions and Outlook -- References -- Chapter 9: River Connectivity, Habitat Fragmentation and Related Restoration Measures -- 9.1 The Importance of Connectivity in Riverine Ecology -- 9.2 River Fragmentation -- 9.3 Restoration of Longitudinal Continuity -- 9.3.1 Large-Scale Concepts -- 9.3.2 Fish Migration Aids -- References -- Chapter 10: Phosphorus and Nitrogen Dynamics in Riverine Systems: Human Impacts and Management Options -- 10.1 Introduction -- 10.2 Historic and Current Emission Situation in the Danube River Basin -- 10.3 Forms and Sources of Phosphorus and Nitrogen -- 10.4 Nutrient Cycling in Streams and Rivers -- 10.5 Human Impacts on Nutrient Cycling -- 10.6 Potential and Limitations of Mitigation Measures -- 10.7 Conclusions and Open Questions -- References -- Chapter 11: Climate Change Impacts in Riverine Ecosystems -- 11.1 Introduction -- 11.2 Water Temperature -- 11.3 Impacts -- 11.3.1 Climate Change Impacts on Thermal Regimes -- 11.3.2 Climatic Aspects in Hydrology -- 11.3.3 Interactions of Climate Change with Other Stressors -- 11.3.4 Ecological Impacts of Thermal Regimes on Aquatic Fauna -- 11.4 Adaptation and Restoration -- 11.4.1 Case Study BIO_CLIC: Potential of Riparian Vegetation to Mitigate Effects of Climate Change on Biological Assemblages o... -- 11.5 Conclusions, Open Questions, and Outlook -- References -- Chapter 12: Ecotoxicology -- 12.1 Introduction -- 12.2 Impacts -- 12.2.1 Propagation of Impacts Across Levels of Biological Organization -- 12.2.2 Relevance of Chemical Input into River Ecosystems -- 12.2.3 Assessing and Predicting Impacts of Chemicals in River Systems -- 12.3 Mitigation -- 12.4 Conclusions -- References -- Chapter 13: Land Use -- 13.1 Introduction -- 13.2 Land Use and Land Cover Definitions -- 13.3 Methods and Data in Land Use Analysis. , 13.4 Land Use as Human Pressure and Its Impacts on Rivers -- 13.5 Research Outlook -- References -- Chapter 14: Recreational Fisheries: The Need for Sustainability in Fisheries Management of Alpine Rivers -- 14.1 Introduction -- 14.2 The Ybbs Case Study -- 14.3 Managing Impacted Habitats -- 14.3.1 Analyzing Habitat Quality -- 14.3.2 Stocking Fish: Restrictions and Possibilities -- 14.4 Conclusions -- References -- Part II: Management, Methodologies, Governance -- Chapter 15: Restoration in Integrated River Basin Management -- 15.1 Introduction -- 15.2 Guiding Principles for River Restoration -- 15.2.1 The Riverine Landscape Perspective: Restoration Strategies Across Spatial Scales -- 15.2.2 Process-Orientated Versus Static Approaches -- 15.2.3 Setting Goals and Benchmarks for River Restoration: The ``Leitbild Concept ́́-- 15.2.4 Socio-political Forces That Restore River Basins -- 15.3 Comprehensive Restoration Planning -- 15.4 Restoration Measures -- 15.4.1 Common Restoration Measures Improving the Morphological Character of the River-Floodplain Systems -- 15.5 Good Practice Examples of Morphological River Restoration -- 15.5.1 River Restoration Drava -- 15.5.2 River Restoration ``Traisen ́́-- 15.6 Conclusions -- References -- Chapter 16: Adaptive Management of Riverine Socio-ecological Systems -- 16.1 Becoming Adaptive in an Increasingly Variable World -- 16.2 Management as an Adaptive Learning Process -- 16.2.1 Fundamentals of Adaptive Management -- 16.2.2 Challenges to the Adoption of Adaptive Management -- 16.2.3 Advances in Adaptive Management -- 16.2.4 Specific Barriers to Different Phases of the Adaptive Management Cycle -- 16.3 Diverse Approaches to Adaptive Water Management -- 16.4 Adaptive Management: The Law and Governance -- 16.4.1 Law -- 16.4.2 Governance -- 16.5 Putting Adaptive Management in Action. , 16.5.1 Case Study: Active Adaptive Governance in Colorado -- 16.6 Comparing Adaptive Management with Other Management Approaches -- References -- Chapter 17: Legislative Framework for River Ecosystem Management on International and European Level -- 17.1 Introduction -- 17.2 International Law -- 17.2.1 International Water Conventions -- 17.2.2 Convention on Wetlands of International Importance -- 17.3 European Union Law -- 17.3.1 Water Framework Directive -- 17.3.2 Birds and Habitats Directives -- 17.4 Challenges for the Future: How Can Modern Water Legislation Address and Adapt to It? -- 17.4.1 Is European Water Law Fit for Future Challenges? -- 17.4.2 Review of European Water Legislation -- 17.5 Conclusions -- References -- Sources of Law -- Bibliography -- Chapter 18: Ensuring Long-Term Cooperation Over Transboundary Water Resources Through Joint River Basin Management -- 18.1 Introduction -- 18.2 The Global Legal Framework for Managing Shared Watercourses -- 18.3 International Water Treaties and River Basin Organizations: Institutionalizing Cooperation Over Shared Watercourses at th... -- 18.4 Specific Mechanisms for River Basin Management: Implementing Cooperation Over Shared Rivers -- 18.4.1 Data and Information Management and Sharing for River Basin Management -- 18.4.2 River Basin Management Plans -- 18.4.2.1 Case Study: Danube River Basin Management Plan -- 18.4.3 Prior Notification and Consultation Mechanisms -- 18.4.3.1 Case Study: Xayaburi Hydropower Project in the Mekong River Basin -- 18.5 Conclusion -- References -- Chapter 19: Biomonitoring and Bioassessment -- 19.1 Introduction -- 19.2 History of Water Quality Assessment -- 19.3 The Saprobic System -- 19.4 Biotic Indices and Scoring -- 19.5 The Multivariate Approach -- 19.6 The Multi-metric Approach -- 19.7 Integrative Assessment Systems -- 19.8 Indicator Groups. , 19.8.1 Periphyton (Contributed by Peter Pfister, ARGE Limnologie, Innsbruck, Austria).
    Additional Edition: Print version: Schmutz, Stefan Riverine Ecosystem Management Cham : Springer International Publishing AG,c2018 ISBN 9783319732497
    Language: English
    Subjects: Biology
    RVK:
    Keywords: Electronic books. ; Aufsatzsammlung
    URL: OAPEN
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