García Márquez, Fausto Pedro.

Big Data Management. - 1 online resource (274 pages) - eBooks on Demand .

Preface -- Contents -- About the Editors -- Visualizing Big Data: Everything Old Is New Again -- 1 Introduction -- 2 Case Study Data: Dominick's Finer Foods -- 3 Big Data: Pre-processing and Management -- 3.1 Data Pre-processing -- 3.2 Data Management -- 4 Big Data Visualization -- 4.1 Visualization Semiotics -- 4.2 Visualization of the DFF Database -- 5 Conclusions -- References -- Managing Cloud-Based Big Data Platforms: A Reference Architecture and Cost Perspective -- 1 Introduction -- 2 Big Data Processing in Cloud Environments -- 2.1 Generic Reference Architecture -- 2.2 Implementations of the Generic Reference Architecture -- 3 Cloud Pricing and Cost Perspective -- 3.1 Data Streams and Stream Processing -- 3.2 Data Storage -- 3.3 Hadoop Cluster -- 3.4 Data Warehouse -- 3.5 Machine Learning -- 4 Discussion -- 5 Conclusions and Outlook -- References -- 3 The Strategic Business Value of Big Data -- Abstract -- 1 Introduction -- 2 Strategic and Organizational Opportunities -- 2.1 Mapping a New Position on a Dynamic Industry -- 2.2 A Dynamic Organization in a Dynamic World -- 3 Big Data Strategies -- 4 Decision Making Under Big Data -- 5 Industry Applications -- 5.1 Retail -- 5.2 Manufacturing -- 5.3 Telecommunications -- 5.4 Public Sector Administration -- 5.5 Health Care -- 6 Conclusions -- References -- 4 A Review on Big Data Security and Privacy in Healthcare Applications -- Abstract -- 1 Big Data -- 1.1 Introduction -- 1.2 Big Data Technologies -- 2 E-Health or Medical and Health Informatics -- 2.1 Electronic Health Records (EHRs) -- 2.2 Social Health -- 3 Data Collection via Bio Informatics -- 3.1 Pharmacogenomics -- 4 Security and Privacy Issues in Big Data -- 4.1 Overview -- 4.2 Data Control -- 4.3 Instantaneous Security Analytics -- 4.4 Privacy-Maintaining Analytics -- 4.5 Data Leakage -- 4.5.1 Current Keys to Counter Data Leakage. 4.5.2 Data Leakage Prevention -- 4.6 Data Privacy -- 4.7 Data Sharing -- 5 Open Questions -- 5.1 Who Will Own the Collected Data? -- 5.2 Which Type of Data to Be Collected and What Will Be the Amount, of Data to Be Stored? -- 5.3 What Will Be the Storage Location? -- 5.4 To Whom Patient's Medical Record Should Be Visible? -- 5.5 Is Disclosure of Information Without Patient Permission Allowed? -- 6 Conclusions -- References -- What Is Big Data -- 1 What Is Big Data -- 1.1 Predictions by Use of Big Data -- 1.2 Big Data and Hypotheses -- 1.3 Big Data and Electric Power -- 2 Why We Need Big Data -- 3 The Example of Big Data -- 4 Conclusions -- References -- Big Data for Conversational Interfaces: Current Opportunities and Prospects -- 1 Introduction -- 2 Spoken Language Recognition -- 3 Spoken Language Understanding -- 4 Dialog Management -- 5 Natural Language Generation -- 6 Text-To-Speech Synthesis -- 7 User Modeling and Evaluation of the System -- 8 Future Research and Challenges -- 9 Conclusions -- References -- 7 Big Data Analytics in Telemedicine: A Role of Medical Image Compression -- Abstract -- 1 Telemedicine -- 1.1 Types of Telemedicine -- 1.1.1 Real-Time -- 1.1.2 Store-and-Forward -- 1.2 Applications of Telemedicine -- 1.3 Use of ICT in Medical Field -- 2 Telemedicine in Rural Area -- 2.1 Application to Rural Areas -- 2.2 Connectivity and Bandwidth in Rural Area -- 2.3 Role of Compression in Telemedicine -- 3 DICOM Format -- 4 Image Compression -- 5 Static Predictors -- 5.1 Differential Coding -- 5.2 Lossless JPEG -- 5.3 EDPCM -- 6 Dynamic Predictor -- 6.1 Median Edge Detector -- 6.2 Gradient Adjusted Predictor -- 6.3 Calic -- 6.4 JPEG Lossless -- 6.5 Edge Enhanced Predictor -- 6.6 GAP with Positive Error Modelling -- 7 Block Coding -- 7.1 Block Truncation Coding -- 7.2 Predictor with Block Coding. 7.3 Blocking Coding with Variable Block Size -- 7.4 Multidimensional Scanning of Blocks -- 8 Symmetry Based Compression -- 8.1 Concept of Symmetry -- 9 Volumetric Image Compression -- 10 Conclusion -- References -- 8 A Bundle-Like Algorithm for Big Data Network Design with Risk-Averse Signal Control Optimization -- Abstract -- 1 Introduction -- 2 A Big Data Network Design Model -- 2.1 Notation -- 2.2 The Lower Level Problem -- 2.2.1 The Cost Minimum (CM) Model -- 2.2.2 A Maximum Risk Model (MM) -- 2.2.3 A Maximum Risk Model with Mixed Routes (MM2) -- 2.2.4 A Weighted Sum Risk Equilibrium Model (WSM) -- 2.3 The Upper Level Problem -- 3 A Bundle-like Method -- 3.1 A Cutting Plane (CP) Model -- 3.2 A Proximal Bundle Method (PBM) -- 3.3 A Bounding Strategy -- 4 Numerical Computations -- 4.1 The First Example Road Network -- 4.2 The Second Example Road Network -- 4.3 The Third Example Road Network -- 5 Conclusions and Discussions -- Acknowledgements -- References -- 9 Evaluation of Evacuation Corridors and Traffic Big Data Management Strategies for Short-Notice Evacuation -- Abstract -- 1 Introduction -- 2 Literature Review -- 2.1 Contra-Flow Operation -- 2.2 Demand Loading and Staging Strategy -- 2.3 Traffic Simulation Tool DynusT -- 3 Background Description for Simulation -- 4 Evacuation Trip Demand Modeling -- 4.1 Background and Evacuation Trip Demands -- 4.2 Evacuation Trip Production and Attraction -- 4.3 Evacuation Trip Distribution and O-D Demand Table -- 5 Traffic Management Strategy Development -- 5.1 Baseline Traffic Management -- 5.2 Advanced Traffic Management Strategies -- 5.3 Traffic Signal Consideration -- 5.4 Simulation Calibration -- 6 Simulation Results and Analysis -- 6.1 Step 1-Evacuation Corridor Selection -- 6.2 Step 2-Traffic Management Strategy Evaluation -- 6.3 Step 3-Evacuation Demand Staging Effect -- 7 Conclusions. Acknowledgments -- References -- 10 Analyzing Network Log Files Using Big Data Techniques -- Abstract -- 1 Introduction -- 2 Big Data State-of-the-Art -- 2.1 The Hadoop Framework -- 3 Problem Description -- 3.1 Modeling the WiFi Log System -- 3.2 Solution Achieved -- 3.2.1 Layered Viewpoint -- 3.2.2 Application Behavior Viewpoint -- 4 Project Development -- 4.1 Working Methodology -- 5 Results -- 5.1 Cluster Configuration -- 5.2 Sample Results for Each Task -- 5.3 Dashboards Using R Charts and Data from Counters -- 5.4 Graphical Results -- 6 Conclusions -- Acknowledgments -- References -- 11 Big Data and Earned Value Management in Airspace Industry -- Abstract -- 1 Introduction -- 2 Big Data -- 3 Earned Value Management -- 4 EVM Extensions -- 5 Big Data and Earned Value Management -- 6 Conclusions -- References.

9783319454986


Big data.


Electronic books.

HF4999.2-6182

650