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Big data platforms and applications : case studies, methods, techniques, and performance evaluation / / Florin Pop, Gabriel Neagu, editors
Big data platforms and applications : case studies, methods, techniques, and performance evaluation / / Florin Pop, Gabriel Neagu, editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (300 pages)
Disciplina 005.7
Collana Computer Communications and Networks
Soggetto topico Big data
ISBN 3-030-38836-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Acknowledgments -- Contents -- About the Editors -- 1 Data Center for Smart Cities: Energy and Sustainability Issue -- 1.1 Introduction -- 1.2 State-of-The-Art Overview -- 1.3 Methodology -- 1.3.1 Data Center Facilities and Dataset Description -- 1.3.2 Data Analysis -- 1.3.3 Metrics -- 1.3.4 Energy Waste Analysis -- 1.4 Results: DC Cluster Energy Consumption -- 1.4.1 Energy Use by Applications -- 1.4.2 Energy Analysis of Queues of Jobs -- 1.4.3 Energy Use by Parallel and Serial Jobs -- 1.4.4 Assessment of Useful Work -- 1.4.5 Assessment of Energy Waste -- 1.4.6 Sustainability Analysis -- 1.5 Discussion -- 1.5.1 Energy Efficiency Benefits and Concerns of Jobs Execution in Parallel Mode -- 1.5.2 Data Center Energy Efficiency Policies and Strategies -- 1.5.3 Sustainability-Oriented DC -- 1.6 Conclusion -- References -- 2 Apache Spark for Digitalization, Analysis and Optimization of Discrete Manufacturing Processes -- 2.1 Introduction -- 2.2 Background -- 2.2.1 IoT for Smart Manufacturing Processes -- 2.2.2 Machine Learning Approaches for Manufacturing Process Analysis -- 2.2.3 Manufacturing Processes Optimization Literature Approaches -- 2.2.4 Bio-Inspired Techniques for Tuning the Parameters of Machine Learning Models -- 2.2.5 Approaches Used in Our Research for the Analysis of the Faults in Manufacturing Processes -- 2.3 Materials and Methods -- 2.3.1 Architectural Prototype for Simulating the Manufacturing of FL Series Regulators -- 2.3.2 Machine Learning Methodology for Detecting Faulty Products in Discrete Manufacturing Processes -- 2.3.3 Data Preprocessing in KNIME (Konstanz Information Miner) -- 2.3.4 Discrete Manufacturing Processes Optimization Based on Big Data Technologies -- 2.4 Results -- 2.4.1 Description of the Datasets Used in Experiments -- 2.4.2 Classification Results -- 2.5 Discussion -- 2.6 Conclusions.
References -- 3 An Empirical Study on Teleworking Among Slovakia's Office-Based Academics -- 3.1 Introduction -- 3.2 Methodology -- 3.3 Meaning of Telecommuting or Teleworking -- 3.3.1 Teleworking in Slovakia -- 3.4 Office-Based Teleworking Results -- 3.5 Discussion -- 3.6 Conclusions -- References -- 4 Data and Systems Heterogeneity: Analysis on Data, Processing, Workload, and Infrastructure -- 4.1 Introduction -- 4.2 Data Types, Formats, and Models -- 4.3 Processing Models and Platforms -- 4.4 Workload Types -- 4.5 Infrastructure Types -- 4.6 Conclusion -- References -- 5 exhiSTORY: Smart Self-organizing Exhibits -- 5.1 Introduction -- 5.2 The Stories Told by Exhibits -- 5.3 The Smart Exhibit -- 5.3.1 Centralized System Control -- 5.3.2 Automated Exhibit Geolocation -- 5.3.3 Security Aspects -- 5.3.4 Selecting an Implementation Option for Smart Exhibits -- 5.4 System Architecture -- 5.4.1 The Smart Space -- 5.4.2 The Knowledge Base -- 5.4.3 The Intelligent Modules -- 5.5 The exhiSTORY System in Operation -- 5.6 Discussion and Conclusions -- References -- 6 IoT Cloud Security Design Patterns -- 6.1 Introduction -- 6.2 Design of IoT Architecture Layers -- 6.2.1 Security Aspects -- 6.3 IoT Network Design Patterns -- 6.3.1 Security of IoT Networks -- 6.3.2 Design Patterns for a Secure IoT Network -- 6.4 IoT Cloud Platform Design Patterns -- 6.4.1 Security Division Pattern -- 6.4.2 Digital Twin Pattern -- 6.4.3 Secure Design Through Microservices -- 6.4.4 Push Notification Pattern -- 6.4.5 Cloud and Smartphone Management Pattern -- 6.4.6 Cloud-Assisted Network Access Pattern -- 6.5 Discussion and Conclusion -- References -- 7 Cloud-Based mHealth Streaming IoT Processing -- 7.1 Introduction -- 7.2 Overview of Underlying Technology for mHealth Solutions -- 7.3 Overview of IoT mHealth Solutions -- 7.4 Cloud-Based Architectures.
7.5 Issues for Streaming mHealth IoT Solutions -- 7.6 Architectures for Streaming mHealth IoT Solutions -- 7.7 Discusion -- 7.7.1 Comparison of Architectural Concepts -- 7.7.2 Benefits -- 7.7.3 Use Case: A Monitoring Center Based on Streaming IoT mHealth Solutions -- 7.8 Conclusion -- References -- 8 A System for Monitoring Water Quality Parameters in Rivers. Challenges and Solutions -- 8.1 Introduction -- 8.2 Water Quality Monitoring Systems Challenges -- 8.2.1 Water Quality Parameters Acquisition Using WSNs -- 8.2.2 Pollution Detection -- 8.2.3 Standards for Hydrographic and Monitoring Data -- 8.3 A Service-Based System Architecture for Water Quality Monitoring -- 8.3.1 Data Sources -- 8.3.2 Data Storage, Processing and Data Provision Services -- 8.3.3 Information Services -- 8.4 A Pollution Detection System for Somes River -- 8.4.1 Data Acquisitions and Storage -- 8.4.2 Discharge Computation -- 8.4.3 The Rule-Based Automatic Assessment of Water Quality and Pollution Alert Service -- 8.4.4 Simulation of Pollutant Propagation -- 8.4.5 The Water Quality Information Web Application -- 8.5 Conclusions -- References -- 9 A Survey on Privacy Enhancements for Massively Scalable Storage Systems in Public Cloud Environments -- 9.1 Introduction -- 9.2 Cloud Storage Encryption Prerequisites -- 9.3 Scalable Cloud Storage Encryption Schemes -- 9.4 Technology Survey Regarding Service Providers -- 9.5 Technology Survey Regarding Classic and Emerging Cryptographic Primitives -- 9.5.1 Confidentiality Primitives -- 9.5.2 Integrity Primitives -- 9.6 Technology Survey Regarding Third-Party Applications -- 9.6.1 Viivo -- 9.6.2 AES Crypt -- 9.7 Proposed Solution -- 9.7.1 Architecture -- 9.7.2 General Description -- 9.7.3 The Java Card Applet -- 9.7.4 Storage Layout and Data Structures -- References.
10 Energy Efficiency of Arduino Sensors Platform Based on Mobile-Cloud: A Bicycle Lights Use-Case -- 10.1 Introduction -- 10.2 Mobile Cloud Computing -- 10.3 The System for Energy Efficiency of Arduino Sensors -- 10.4 Smart Bicycle Lighting Architecture -- 10.5 Conclusions -- References -- 11 Cloud-Enabled Modeling of Sensor Networks in Educational Settings -- 11.1 Introduction -- 11.2 Related Work -- 11.2.1 Sensor Cloud -- 11.2.2 Education Cloud -- 11.3 Sensor Network Modeling -- 11.3.1 Language and Tools -- 11.3.2 Extensions and Model Interpreters -- 11.4 System Architecture -- 11.5 Educational Service in Cloud -- 11.5.1 Service Request and Handling -- 11.5.2 The Provisioning Process -- 11.6 Experimental Results -- 11.7 Conclusion -- References -- 12 Methods and Techniques for Automatic Identification System Data Reduction -- 12.1 Introduction -- 12.2 Related Work -- 12.3 AIS Technology -- 12.4 Algorithm Analysis -- 12.4.1 Analyzing the Data Set -- 12.5 Experimental Evaluation -- 12.5.1 Analyzed Data -- 12.5.2 Data Reduction Applied on AIS Data Set -- 12.5.3 Data Visualization -- 12.6 Conclusion and Future Work -- References -- 13 Machine-to-Machine Model for Water Resource Sharing in Smart Cities -- 13.1 Introduction -- 13.2 Current Stage of Development in the Field -- 13.2.1 EOMORES Project-Copernicus Platform -- 13.2.2 AquaWatch Project -- 13.2.3 SmartWater4Europe Project -- 13.2.4 OPC UA with MEGA Model Architecture -- 13.2.5 WATER-M Project -- 13.3 Smart City Water Management Available Technologies -- 13.3.1 GIS (Geographic Information System) -- 13.3.2 IBM Water Management Platform -- 13.3.3 TEMBOO Platform-IoT Applications -- 13.3.4 RoboMQ -- 13.4 Proposed Model and Possible Directions -- 13.5 Possibilities of Implementation -- 13.5.1 Message-Oriented Middleware-RabbitMQ -- 13.6 Conclusions -- References -- Index.
Record Nr. UNINA-9910502999503321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Big data platforms and applications : case studies, methods, techniques, and performance evaluation / / Florin Pop, Gabriel Neagu, editors
Big data platforms and applications : case studies, methods, techniques, and performance evaluation / / Florin Pop, Gabriel Neagu, editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (300 pages)
Disciplina 005.7
Collana Computer Communications and Networks
Soggetto topico Big data
ISBN 3-030-38836-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Acknowledgments -- Contents -- About the Editors -- 1 Data Center for Smart Cities: Energy and Sustainability Issue -- 1.1 Introduction -- 1.2 State-of-The-Art Overview -- 1.3 Methodology -- 1.3.1 Data Center Facilities and Dataset Description -- 1.3.2 Data Analysis -- 1.3.3 Metrics -- 1.3.4 Energy Waste Analysis -- 1.4 Results: DC Cluster Energy Consumption -- 1.4.1 Energy Use by Applications -- 1.4.2 Energy Analysis of Queues of Jobs -- 1.4.3 Energy Use by Parallel and Serial Jobs -- 1.4.4 Assessment of Useful Work -- 1.4.5 Assessment of Energy Waste -- 1.4.6 Sustainability Analysis -- 1.5 Discussion -- 1.5.1 Energy Efficiency Benefits and Concerns of Jobs Execution in Parallel Mode -- 1.5.2 Data Center Energy Efficiency Policies and Strategies -- 1.5.3 Sustainability-Oriented DC -- 1.6 Conclusion -- References -- 2 Apache Spark for Digitalization, Analysis and Optimization of Discrete Manufacturing Processes -- 2.1 Introduction -- 2.2 Background -- 2.2.1 IoT for Smart Manufacturing Processes -- 2.2.2 Machine Learning Approaches for Manufacturing Process Analysis -- 2.2.3 Manufacturing Processes Optimization Literature Approaches -- 2.2.4 Bio-Inspired Techniques for Tuning the Parameters of Machine Learning Models -- 2.2.5 Approaches Used in Our Research for the Analysis of the Faults in Manufacturing Processes -- 2.3 Materials and Methods -- 2.3.1 Architectural Prototype for Simulating the Manufacturing of FL Series Regulators -- 2.3.2 Machine Learning Methodology for Detecting Faulty Products in Discrete Manufacturing Processes -- 2.3.3 Data Preprocessing in KNIME (Konstanz Information Miner) -- 2.3.4 Discrete Manufacturing Processes Optimization Based on Big Data Technologies -- 2.4 Results -- 2.4.1 Description of the Datasets Used in Experiments -- 2.4.2 Classification Results -- 2.5 Discussion -- 2.6 Conclusions.
References -- 3 An Empirical Study on Teleworking Among Slovakia's Office-Based Academics -- 3.1 Introduction -- 3.2 Methodology -- 3.3 Meaning of Telecommuting or Teleworking -- 3.3.1 Teleworking in Slovakia -- 3.4 Office-Based Teleworking Results -- 3.5 Discussion -- 3.6 Conclusions -- References -- 4 Data and Systems Heterogeneity: Analysis on Data, Processing, Workload, and Infrastructure -- 4.1 Introduction -- 4.2 Data Types, Formats, and Models -- 4.3 Processing Models and Platforms -- 4.4 Workload Types -- 4.5 Infrastructure Types -- 4.6 Conclusion -- References -- 5 exhiSTORY: Smart Self-organizing Exhibits -- 5.1 Introduction -- 5.2 The Stories Told by Exhibits -- 5.3 The Smart Exhibit -- 5.3.1 Centralized System Control -- 5.3.2 Automated Exhibit Geolocation -- 5.3.3 Security Aspects -- 5.3.4 Selecting an Implementation Option for Smart Exhibits -- 5.4 System Architecture -- 5.4.1 The Smart Space -- 5.4.2 The Knowledge Base -- 5.4.3 The Intelligent Modules -- 5.5 The exhiSTORY System in Operation -- 5.6 Discussion and Conclusions -- References -- 6 IoT Cloud Security Design Patterns -- 6.1 Introduction -- 6.2 Design of IoT Architecture Layers -- 6.2.1 Security Aspects -- 6.3 IoT Network Design Patterns -- 6.3.1 Security of IoT Networks -- 6.3.2 Design Patterns for a Secure IoT Network -- 6.4 IoT Cloud Platform Design Patterns -- 6.4.1 Security Division Pattern -- 6.4.2 Digital Twin Pattern -- 6.4.3 Secure Design Through Microservices -- 6.4.4 Push Notification Pattern -- 6.4.5 Cloud and Smartphone Management Pattern -- 6.4.6 Cloud-Assisted Network Access Pattern -- 6.5 Discussion and Conclusion -- References -- 7 Cloud-Based mHealth Streaming IoT Processing -- 7.1 Introduction -- 7.2 Overview of Underlying Technology for mHealth Solutions -- 7.3 Overview of IoT mHealth Solutions -- 7.4 Cloud-Based Architectures.
7.5 Issues for Streaming mHealth IoT Solutions -- 7.6 Architectures for Streaming mHealth IoT Solutions -- 7.7 Discusion -- 7.7.1 Comparison of Architectural Concepts -- 7.7.2 Benefits -- 7.7.3 Use Case: A Monitoring Center Based on Streaming IoT mHealth Solutions -- 7.8 Conclusion -- References -- 8 A System for Monitoring Water Quality Parameters in Rivers. Challenges and Solutions -- 8.1 Introduction -- 8.2 Water Quality Monitoring Systems Challenges -- 8.2.1 Water Quality Parameters Acquisition Using WSNs -- 8.2.2 Pollution Detection -- 8.2.3 Standards for Hydrographic and Monitoring Data -- 8.3 A Service-Based System Architecture for Water Quality Monitoring -- 8.3.1 Data Sources -- 8.3.2 Data Storage, Processing and Data Provision Services -- 8.3.3 Information Services -- 8.4 A Pollution Detection System for Somes River -- 8.4.1 Data Acquisitions and Storage -- 8.4.2 Discharge Computation -- 8.4.3 The Rule-Based Automatic Assessment of Water Quality and Pollution Alert Service -- 8.4.4 Simulation of Pollutant Propagation -- 8.4.5 The Water Quality Information Web Application -- 8.5 Conclusions -- References -- 9 A Survey on Privacy Enhancements for Massively Scalable Storage Systems in Public Cloud Environments -- 9.1 Introduction -- 9.2 Cloud Storage Encryption Prerequisites -- 9.3 Scalable Cloud Storage Encryption Schemes -- 9.4 Technology Survey Regarding Service Providers -- 9.5 Technology Survey Regarding Classic and Emerging Cryptographic Primitives -- 9.5.1 Confidentiality Primitives -- 9.5.2 Integrity Primitives -- 9.6 Technology Survey Regarding Third-Party Applications -- 9.6.1 Viivo -- 9.6.2 AES Crypt -- 9.7 Proposed Solution -- 9.7.1 Architecture -- 9.7.2 General Description -- 9.7.3 The Java Card Applet -- 9.7.4 Storage Layout and Data Structures -- References.
10 Energy Efficiency of Arduino Sensors Platform Based on Mobile-Cloud: A Bicycle Lights Use-Case -- 10.1 Introduction -- 10.2 Mobile Cloud Computing -- 10.3 The System for Energy Efficiency of Arduino Sensors -- 10.4 Smart Bicycle Lighting Architecture -- 10.5 Conclusions -- References -- 11 Cloud-Enabled Modeling of Sensor Networks in Educational Settings -- 11.1 Introduction -- 11.2 Related Work -- 11.2.1 Sensor Cloud -- 11.2.2 Education Cloud -- 11.3 Sensor Network Modeling -- 11.3.1 Language and Tools -- 11.3.2 Extensions and Model Interpreters -- 11.4 System Architecture -- 11.5 Educational Service in Cloud -- 11.5.1 Service Request and Handling -- 11.5.2 The Provisioning Process -- 11.6 Experimental Results -- 11.7 Conclusion -- References -- 12 Methods and Techniques for Automatic Identification System Data Reduction -- 12.1 Introduction -- 12.2 Related Work -- 12.3 AIS Technology -- 12.4 Algorithm Analysis -- 12.4.1 Analyzing the Data Set -- 12.5 Experimental Evaluation -- 12.5.1 Analyzed Data -- 12.5.2 Data Reduction Applied on AIS Data Set -- 12.5.3 Data Visualization -- 12.6 Conclusion and Future Work -- References -- 13 Machine-to-Machine Model for Water Resource Sharing in Smart Cities -- 13.1 Introduction -- 13.2 Current Stage of Development in the Field -- 13.2.1 EOMORES Project-Copernicus Platform -- 13.2.2 AquaWatch Project -- 13.2.3 SmartWater4Europe Project -- 13.2.4 OPC UA with MEGA Model Architecture -- 13.2.5 WATER-M Project -- 13.3 Smart City Water Management Available Technologies -- 13.3.1 GIS (Geographic Information System) -- 13.3.2 IBM Water Management Platform -- 13.3.3 TEMBOO Platform-IoT Applications -- 13.3.4 RoboMQ -- 13.4 Proposed Model and Possible Directions -- 13.5 Possibilities of Implementation -- 13.5.1 Message-Oriented Middleware-RabbitMQ -- 13.6 Conclusions -- References -- Index.
Record Nr. UNISA-996464402403316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Big Data Preprocessing [[electronic resource] ] : Enabling Smart Data / / by Julián Luengo, Diego García-Gil, Sergio Ramírez-Gallego, Salvador García, Francisco Herrera
Big Data Preprocessing [[electronic resource] ] : Enabling Smart Data / / by Julián Luengo, Diego García-Gil, Sergio Ramírez-Gallego, Salvador García, Francisco Herrera
Autore Luengo Julián
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Descrizione fisica 1 online resource (XIII, 186 p. 57 illus., 54 illus. in color.)
Disciplina 005.7
Soggetto topico Big data
Machine learning
Computers
Big Data
Machine Learning
Information Systems and Communication Service
ISBN 3-030-39105-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 1. Introduction -- 2. Big Data: Technologies and Tools -- 3. Smart Data -- 4. Dimensionality Reduction for Big Data -- 5. Data Reduction for Big Data -- 6. Imperfect Big Data -- 7. Big Data Discretization -- 8. Imbalanced Data Preprocessing for Big Data -- 9. Big Data Software -- 10. Final Thoughts: From Big Data to Smart Data.-.
Record Nr. UNINA-9910410052203321
Luengo Julián  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Big Data Preprocessing [[electronic resource] ] : Enabling Smart Data / / by Julián Luengo, Diego García-Gil, Sergio Ramírez-Gallego, Salvador García, Francisco Herrera
Big Data Preprocessing [[electronic resource] ] : Enabling Smart Data / / by Julián Luengo, Diego García-Gil, Sergio Ramírez-Gallego, Salvador García, Francisco Herrera
Autore Luengo Julián
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Descrizione fisica 1 online resource (XIII, 186 p. 57 illus., 54 illus. in color.)
Disciplina 005.7
Soggetto topico Big data
Machine learning
Computers
Big Data
Machine Learning
Information Systems and Communication Service
ISBN 3-030-39105-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 1. Introduction -- 2. Big Data: Technologies and Tools -- 3. Smart Data -- 4. Dimensionality Reduction for Big Data -- 5. Data Reduction for Big Data -- 6. Imperfect Big Data -- 7. Big Data Discretization -- 8. Imbalanced Data Preprocessing for Big Data -- 9. Big Data Software -- 10. Final Thoughts: From Big Data to Smart Data.-.
Record Nr. UNISA-996465345703316
Luengo Julián  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Big data privacy and security in smart cities / / Richard Jiang [and six others], editors
Big data privacy and security in smart cities / / Richard Jiang [and six others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022]
Descrizione fisica 1 online resource (248 pages)
Disciplina 005.7
Collana Advanced sciences and technologies for security applications
Soggetto topico Cities and towns
Big data
Smart cities
ISBN 3-031-04424-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Contents -- Smart Cities: A Survey of Tech-Induced Privacy Concerns -- 1 Introduction -- 2 Related Work -- 2.1 Internet of Things (IoT) -- 2.2 Big Data -- 2.3 Information and Communication Technology (ICT) -- 3 Smart Cities Technologies -- 3.1 Smart Mobility and Transportation Technology -- 3.2 Smart Energy Technology -- 3.3 Smart Health Technology -- 3.4 Smart Governance Technology -- 4 Conclusion -- References -- Ethics of Face Recognition in Smart Cities Toward Trustworthy AI -- 1 Introduction -- 2 Representative Scene -- 2.1 Demographic Aspect -- 2.2 Smart-City Surveillance -- 2.3 Facepay -- 2.4 Face to DNA -- 3 Relevant Laws or Regulations -- 3.1 Related U.S. Laws and Regulations -- 3.2 European Private Privacy Laws -- 4 Proposal to Trustworthy -- 4.1 Explainability -- 4.2 Privacy -- 4.3 Nondiscrimination & -- Fairness -- 4.4 Integrity -- 4.5 Environmental Friendliness -- 5 Conclusion -- References -- A Technical Review on Driverless Vehicle Technologies in Smart Cities -- 1 Introduction -- 2 Prospects and Challenges -- 3 Architecture of Automated Driving Systems -- 4 Sensors and Hardware -- 5 Localization and Mapping -- 6 Perception -- 7 Planning and Decision Making -- 8 Datasets -- 9 Transportation in Smart City -- 10 Deep Learning in Driverless Vehicles -- 11 Driverless Vehicle Cases -- 12 Conclusion -- References -- A Mechanism to Maintain Node Integrity in Decentralised Systems -- 1 Introduction -- 2 Related Study -- 3 Proposed Mechanism -- 4 Discussions and Future Development -- 5 Conclusions -- References -- Incident Detection System for Industrial Networks -- 1 Introduction -- 2 Related Works -- 3 Industrial Protocol Modbus/TCP -- 4 Modbus/TCP Security Module -- 4.1 Phase 1-Databases Approach -- 4.2 Phase 2 -- 5 Graphical Visualization -- 6 Conclusion -- References.
Predictive Maintenance of Vehicle Fleets Using LSTM Autoencoders for Industrial IoT Datasets -- 1 Introduction -- 2 Related Work -- 3 Computational Method -- 3.1 Datasets -- 3.2 LSTM Autoencoder for Predictive Maintenance -- 4 Experiments and Results -- 5 Conclusion -- References -- A Comparative Study on the User Experience on Using Secure Messaging Tools -- 1 Introduction -- 2 Literature Review -- 2.1 User Experience Research -- 2.2 Obstacles to the Adoption of Secure Communication Tools -- 2.3 Previous Email Encryption Studies -- 3 Problem Statement -- 4 Research Methodology -- 4.1 Heuristic Review for Thunderbird Email Client -- 4.2 System Settings Versus App Settings -- 5 Recommendations and Future Directions -- 6 Conclusions -- References -- A Survey on AI-Enabled Pandemic Prediction and Prevention: What We Can Learn from COVID -- 1 Introduction -- 2 Prediction and Forecasting -- 3 Screening and Treatment -- 4 Contact Tracing -- 5 Drugs and Vaccination -- 6 Other AI Application of COVID-19 -- 7 Pandemic Prevention in Smart City -- 8 Conclusion and Discussion -- References -- Blockchain Based Health Information Exchange Ecosystem: Usecase on Travellers -- 1 Introduction -- 2 Related Work -- 3 Proposed Transformation Centered Around Smart Contract -- 4 Discussion -- 5 Conclusion -- References -- Video-Based Heart Rate Detection: A Remote Healthcare Surveillance Tool for Smart Homecare -- 1 Introduction -- 2 Literature Review -- 2.1 Previous Research Which Use PPG/RIPPG -- 2.2 Previous Research Which Use BCG -- 2.3 Results from Previous Work -- 3 Methodology -- 3.1 Data Collection -- 3.2 ROI Selection and Tracking -- 3.3 Implementation of Tracking Algorithm -- 3.4 Validity of Obtained Frequencies -- 3.5 Noise Filtration -- 3.6 Synchronising the Waveforms -- 3.7 Estimating the Beats per Minute Using Peak FFT Analysis.
3.8 Estimating Beats per Minute from the Number of Prominent Peaks in the Signal -- 3.9 Detecting BPM Through Short-time Fourier Transform -- 3.10 Generating ECG Like Signal -- 4 Results -- 4.1 From FFT Signal Analysis -- 4.2 Short Time Fourier Analysis -- 4.3 Generating ECG Like Signal -- 5 Conclusion -- 5.1 Key Findings -- 5.2 Limitations -- 5.3 Future Research -- References -- A Survey on the Integration of Blockchain and IoT: Challenges and Opportunities -- 1 Introduction -- 2 Literature Review -- 3 An Overview of IoT and Blockchain -- 3.1 Internet of Things (IoT) -- 3.2 IoT Framework -- 3.3 IoT Security Challenges -- 3.4 IoT on Blockchain -- 4 Blockchain Implementation in Different IoT Domain -- 4.1 Internet of Energy (IoE) -- 4.2 Internet of Vehicles -- 4.3 Internet of Healthcare Things -- 4.4 Access Management in IoT -- 4.5 Authentication and Identity Management -- 4.6 Fog Computing -- 4.7 Internet of Agriculture -- 4.8 Software-Defined Networking -- 4.9 Internet of Smart Cities -- 4.10 Intrusion Detection -- 4.11 Internet of Cloud -- 4.12 Blockchain for 5G -- 5 Blockchain Limitations -- 5.1 Scalability -- 5.2 Throughput -- 5.3 Energy Consumption -- 5.4 Latency -- 5.5 Block Size and Bandwidth Related Issues -- 5.6 The Smart Contract Deployment Cost -- 5.7 Usability -- 5.8 Currently Introduced Solutions -- 6 The Future Research Directions -- 7 Conclusion -- References -- Quantum Bitcoin: The Intersection of Bitcoin, Quantum Computing and Blockchain -- 1 Introduction: Background on Quantum Computing Meets Bitcoin -- 2 What's Blockchain and Cryptocurrency -- 3 A Brief Introduction to Quantum Computing -- 4 Grover's Algorithm, Shor's Algorithm and Impact on Bitcoin -- 5 Possible: Quantum Bitcoin -- 6 Discussion -- 7 Conclusion -- References -- Biometric Blockchain (BBC) Based e-Passports for Smart Border Control -- 1 Introduction.
2 Literature Review -- 3 Preliminaries -- 3.1 Blockchain -- 3.2 Verifiable Credential and Decentralized Identifier -- 4 The Proposed e-password System -- 4.1 Main Entities -- 4.2 Biometric Authentication -- 4.3 System Modelling -- 5 Implementations and Performance -- 6 Conclusion -- References.
Record Nr. UNINA-9910592984303321
Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Big data privacy and security in smart cities / / Richard Jiang [and six others], editors
Big data privacy and security in smart cities / / Richard Jiang [and six others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022]
Descrizione fisica 1 online resource (248 pages)
Disciplina 005.7
Collana Advanced sciences and technologies for security applications
Soggetto topico Cities and towns
Big data
Smart cities
ISBN 3-031-04424-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Contents -- Smart Cities: A Survey of Tech-Induced Privacy Concerns -- 1 Introduction -- 2 Related Work -- 2.1 Internet of Things (IoT) -- 2.2 Big Data -- 2.3 Information and Communication Technology (ICT) -- 3 Smart Cities Technologies -- 3.1 Smart Mobility and Transportation Technology -- 3.2 Smart Energy Technology -- 3.3 Smart Health Technology -- 3.4 Smart Governance Technology -- 4 Conclusion -- References -- Ethics of Face Recognition in Smart Cities Toward Trustworthy AI -- 1 Introduction -- 2 Representative Scene -- 2.1 Demographic Aspect -- 2.2 Smart-City Surveillance -- 2.3 Facepay -- 2.4 Face to DNA -- 3 Relevant Laws or Regulations -- 3.1 Related U.S. Laws and Regulations -- 3.2 European Private Privacy Laws -- 4 Proposal to Trustworthy -- 4.1 Explainability -- 4.2 Privacy -- 4.3 Nondiscrimination & -- Fairness -- 4.4 Integrity -- 4.5 Environmental Friendliness -- 5 Conclusion -- References -- A Technical Review on Driverless Vehicle Technologies in Smart Cities -- 1 Introduction -- 2 Prospects and Challenges -- 3 Architecture of Automated Driving Systems -- 4 Sensors and Hardware -- 5 Localization and Mapping -- 6 Perception -- 7 Planning and Decision Making -- 8 Datasets -- 9 Transportation in Smart City -- 10 Deep Learning in Driverless Vehicles -- 11 Driverless Vehicle Cases -- 12 Conclusion -- References -- A Mechanism to Maintain Node Integrity in Decentralised Systems -- 1 Introduction -- 2 Related Study -- 3 Proposed Mechanism -- 4 Discussions and Future Development -- 5 Conclusions -- References -- Incident Detection System for Industrial Networks -- 1 Introduction -- 2 Related Works -- 3 Industrial Protocol Modbus/TCP -- 4 Modbus/TCP Security Module -- 4.1 Phase 1-Databases Approach -- 4.2 Phase 2 -- 5 Graphical Visualization -- 6 Conclusion -- References.
Predictive Maintenance of Vehicle Fleets Using LSTM Autoencoders for Industrial IoT Datasets -- 1 Introduction -- 2 Related Work -- 3 Computational Method -- 3.1 Datasets -- 3.2 LSTM Autoencoder for Predictive Maintenance -- 4 Experiments and Results -- 5 Conclusion -- References -- A Comparative Study on the User Experience on Using Secure Messaging Tools -- 1 Introduction -- 2 Literature Review -- 2.1 User Experience Research -- 2.2 Obstacles to the Adoption of Secure Communication Tools -- 2.3 Previous Email Encryption Studies -- 3 Problem Statement -- 4 Research Methodology -- 4.1 Heuristic Review for Thunderbird Email Client -- 4.2 System Settings Versus App Settings -- 5 Recommendations and Future Directions -- 6 Conclusions -- References -- A Survey on AI-Enabled Pandemic Prediction and Prevention: What We Can Learn from COVID -- 1 Introduction -- 2 Prediction and Forecasting -- 3 Screening and Treatment -- 4 Contact Tracing -- 5 Drugs and Vaccination -- 6 Other AI Application of COVID-19 -- 7 Pandemic Prevention in Smart City -- 8 Conclusion and Discussion -- References -- Blockchain Based Health Information Exchange Ecosystem: Usecase on Travellers -- 1 Introduction -- 2 Related Work -- 3 Proposed Transformation Centered Around Smart Contract -- 4 Discussion -- 5 Conclusion -- References -- Video-Based Heart Rate Detection: A Remote Healthcare Surveillance Tool for Smart Homecare -- 1 Introduction -- 2 Literature Review -- 2.1 Previous Research Which Use PPG/RIPPG -- 2.2 Previous Research Which Use BCG -- 2.3 Results from Previous Work -- 3 Methodology -- 3.1 Data Collection -- 3.2 ROI Selection and Tracking -- 3.3 Implementation of Tracking Algorithm -- 3.4 Validity of Obtained Frequencies -- 3.5 Noise Filtration -- 3.6 Synchronising the Waveforms -- 3.7 Estimating the Beats per Minute Using Peak FFT Analysis.
3.8 Estimating Beats per Minute from the Number of Prominent Peaks in the Signal -- 3.9 Detecting BPM Through Short-time Fourier Transform -- 3.10 Generating ECG Like Signal -- 4 Results -- 4.1 From FFT Signal Analysis -- 4.2 Short Time Fourier Analysis -- 4.3 Generating ECG Like Signal -- 5 Conclusion -- 5.1 Key Findings -- 5.2 Limitations -- 5.3 Future Research -- References -- A Survey on the Integration of Blockchain and IoT: Challenges and Opportunities -- 1 Introduction -- 2 Literature Review -- 3 An Overview of IoT and Blockchain -- 3.1 Internet of Things (IoT) -- 3.2 IoT Framework -- 3.3 IoT Security Challenges -- 3.4 IoT on Blockchain -- 4 Blockchain Implementation in Different IoT Domain -- 4.1 Internet of Energy (IoE) -- 4.2 Internet of Vehicles -- 4.3 Internet of Healthcare Things -- 4.4 Access Management in IoT -- 4.5 Authentication and Identity Management -- 4.6 Fog Computing -- 4.7 Internet of Agriculture -- 4.8 Software-Defined Networking -- 4.9 Internet of Smart Cities -- 4.10 Intrusion Detection -- 4.11 Internet of Cloud -- 4.12 Blockchain for 5G -- 5 Blockchain Limitations -- 5.1 Scalability -- 5.2 Throughput -- 5.3 Energy Consumption -- 5.4 Latency -- 5.5 Block Size and Bandwidth Related Issues -- 5.6 The Smart Contract Deployment Cost -- 5.7 Usability -- 5.8 Currently Introduced Solutions -- 6 The Future Research Directions -- 7 Conclusion -- References -- Quantum Bitcoin: The Intersection of Bitcoin, Quantum Computing and Blockchain -- 1 Introduction: Background on Quantum Computing Meets Bitcoin -- 2 What's Blockchain and Cryptocurrency -- 3 A Brief Introduction to Quantum Computing -- 4 Grover's Algorithm, Shor's Algorithm and Impact on Bitcoin -- 5 Possible: Quantum Bitcoin -- 6 Discussion -- 7 Conclusion -- References -- Biometric Blockchain (BBC) Based e-Passports for Smart Border Control -- 1 Introduction.
2 Literature Review -- 3 Preliminaries -- 3.1 Blockchain -- 3.2 Verifiable Credential and Decentralized Identifier -- 4 The Proposed e-password System -- 4.1 Main Entities -- 4.2 Biometric Authentication -- 4.3 System Modelling -- 5 Implementations and Performance -- 6 Conclusion -- References.
Record Nr. UNISA-996490352403316
Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
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Big Data Processing Using Spark in Cloud [[electronic resource] /] / edited by Mamta Mittal, Valentina E. Balas, Lalit Mohan Goyal, Raghvendra Kumar
Big Data Processing Using Spark in Cloud [[electronic resource] /] / edited by Mamta Mittal, Valentina E. Balas, Lalit Mohan Goyal, Raghvendra Kumar
Edizione [1st ed. 2019.]
Pubbl/distr/stampa Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019
Descrizione fisica 1 online resource (XIII, 264 p. 89 illus., 62 illus. in color.)
Disciplina 005.7
Collana Studies in Big Data
Soggetto topico Big data
Computer security
Big Data
Systems and Data Security
Big Data/Analytics
ISBN 981-13-0550-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Concepts of Big Data and Apache Spark -- Big Data Analysis in Cloud and Machine Learning -- Security Issues and Challenges related to Big Data -- Big Data Security Solutions in Cloud -- Data Science and Analytics -- Big Data Technologies -- Data Analysis with Casandra and Spark -- Spin up the Spark Cluster -- Learn Scala -- IO for Spark -- Processing with Spark -- Spark Data Frames and Spark SQL -- Machine Learning and Advanced Analytics -- Parallel Programming with Spark -- Distributed Graph Processing with Spark -- Real Time Processing with Spark -- Spark in Real World -- Case Studies. .
Record Nr. UNINA-9910739483403321
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Big Data Research for Social Sciences and Social Impact / / edited by Kwok Tai Chui, Anna Visvizi, Miltiadis Lytras
Big Data Research for Social Sciences and Social Impact / / edited by Kwok Tai Chui, Anna Visvizi, Miltiadis Lytras
Pubbl/distr/stampa Basel : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2020
Descrizione fisica 1 online resource (403 pages)
Disciplina 005.7
Soggetto topico Big data - Social aspects - United States
Big data - Moral and ethical aspects
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910674032403321
Basel : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Big data science in finance / / by Irene Aldridge, Marco Avellaneda
Big data science in finance / / by Irene Aldridge, Marco Avellaneda
Autore Aldridge Irene <1975->
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley, , [2021]
Descrizione fisica 1 online resource (339 pages)
Disciplina 005.7
Soggetto topico Big data
Finance - Decision making - Data processing
ISBN 1-119-60299-8
1-119-60297-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Why big data? -- Neural networks in finance -- Supervised models -- Semi-supervised learning -- Letting the data speak with unsupervised learning -- Big data factor models -- Data as a signal versus noise -- Applications : big data in options pricing and stochastic modeling -- Data clustering.
Record Nr. UNINA-9910798929203321
Aldridge Irene <1975->  
Hoboken, New Jersey : , : Wiley, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Big data science in finance / / by Irene Aldridge, Marco Avellaneda
Big data science in finance / / by Irene Aldridge, Marco Avellaneda
Autore Aldridge Irene <1975->
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley, , [2021]
Descrizione fisica 1 online resource (339 pages)
Disciplina 005.7
Soggetto topico Big data
Finance - Decision making - Data processing
ISBN 1-119-60299-8
1-119-60297-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Why big data? -- Neural networks in finance -- Supervised models -- Semi-supervised learning -- Letting the data speak with unsupervised learning -- Big data factor models -- Data as a signal versus noise -- Applications : big data in options pricing and stochastic modeling -- Data clustering.
Record Nr. UNINA-9910816064703321
Aldridge Irene <1975->  
Hoboken, New Jersey : , : Wiley, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui

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