“…Networks of sensors will be able to enhance the ability to obtain huge amounts of information (big data) and improve precision, which also mirrors the developmental tendency of modern sensors. …”

Tabla de Contenidos: “…Geotechnical Workflows and Big Data Analytics -- Standardization versus Optimization -- Talent -- Operations Management Processes -- Delegation of Decision Rights -- Informal Social Norms and Corporate Culture -- Corporate Culture of "Wall Street" Preoccupation -- The Imperial Chief Executive Officer -- Management by Email -- Implications of Industry Evolution -- Business Model Considerations -- What Others May Operate More Efficiently/Productively -- Partnering Where Capabilities Are Advantaged -- Using Vendor or Customer Capabilities to Reduce Costs -- Notes -- Chapter 4: PMI and Other Event-Driven Redesigns -- The Search for a Perfect Ownership Model -- Preparing to Go Public -- Key Success Factors -- Event-Driven Redesign -- Note -- Chapter 5: National Oil Company Considerations -- National Oil Company Context -- National Oil Company Competitive Landscape -- Sovereign and National Oil Company Strategies -- Importers -- Developers -- Exporters -- Business Model Implications -- Importers -- Developers -- Exporters -- Notes -- Chapter 6: Collaborative Operating Models -- Who Uses Joint Ventures? …”

“…Operations Management and Data Analytics Modelling: Economic Crises Perspective addresses real operation management problems in thrust areas like the healthcare and energy management sectors and Industry 4.0.It discusses recent advances and trends in developing data-driven operation management-based methodologies, big data analysis, application of computers in industrial engineering, optimization techniques, development of decision support systems for industrial operation, the role of a multiple-criteria decision-making (MCDM) approach in operation management, fuzzy set theory-based operation management modelling and Lean Six Sigma.FeaturesDiscusses the importance of data analytics in industrial operations to improve economyProvides step-by-step implementation of operation management models to identify best practicesCovers in-depth analysis using data-based operation management tools and techniquesDiscusses mathematical modelling for novel operation management models to solve industrial problemsThis book is aimed at graduate students and professionals in the field of industrial and production engineering, mechanical engineering and materials science…”

“…Building on its clear and detailed coverage of planning, scheduling and control, this seventh edition includes new advice on information management, including big data, communication, dispute resolution, project governance, and BIM. …”

“…Software development today is embracing functional programming (FP), whether it's for writing concurrent programs or for managing Big Data. Where does that leave Java developers? This concise book offers a pragmatic, approachable introduction to FP for Java developers or anyone who uses an object-oriented language. …”

“…After a history of the ecosystem concept and these derivatives (nature, ecology, environment) from antiquity to the present, the analysis method based on the modeling of socio-semantic ontologies is presented, followed by practical examples of this approach in the areas of software development, digital humanities, Big Data, and more generally in the area of complex analysis…”

“…New technologies such as machine learning, image processing, big data, remote monitoring, cloud computing, deep learning, and enhanced wireless communications are all improving and connecting modern healthcare services and products through IoT. https://www.juniperresearch.com/press/press-releases/iot-platform-revenue-to-grow-20-in-2020"--…”

“…The recent explosion of digital data in a wide variety of domains, including science, engineering, Internet of Things, biomedical, healthcare, and many business sectors, has declared the era of big data, which cannot be analysed by classical statistics but by the more modern, robust machine learning and deep learning techniques. …”

Tabla de Contenidos: “…Chapter 13 Selling to the Good Guys-Regulation, Self-Criticism, and "Clean" Offensive Cybertechnology -- The Israeli regulator -- Offensive cyber as a geopolitical tool -- Final reflections -- Section 4 Building a Cyberstate -- Chapter 14 The Israeli Silicon Valley-Small State, Big Data -- Chapter 15 Unit 8200-Secrets of the IDF's Success -- "We've got to go up a notch" -- The story of Unit 8200 -- Unit 81: Making the impossible, possible -- Cyberintelligence: Challenges and opportunities -- Building the Israeli military's cybersecurity apparatus -- The ARAM Course -- From offense to defense -- The key to success -- Overcoming any obstacle -- The old boys' club -- Closed club? …”

“…Lo sucedido en la campaña presidencial estadounidense de 2016 y en la campaña del referéndum del Brexit en el Reino Unido, con la difusión masiva de desinformación y el empleo del análisis de big data para dirigir mensajes microsegmentados a los electores, hizo saltar las alarmas en las instituciones y en la comunidad académica. …”

“…De esta manera, y la Inteligencia Artificial, los algoritmos y el Big Data ofrecen unas posibilidades hasta ahora no exploradas en su totalidad y pueden contribuir a contrarrestar las carencias derivadas de los mecanismos de reclutamiento tradicional, ofreciendo una plataforma más amplia como son internet y/o las redes sociales que permiten construir una huella digital más exacta del trabajador. …”

“…Parte del análisis de la investigación de marketing en una sociedad y economía de la información, de la importancia de la investigación para adquirir conocimiento, pero también como sector económico, de los aspectos éticos y códigos de conducta en la investigación y de las tendencias de futuro (nuevos datos, nuevos procedimientos, nuevas habilidades, big data, etc.)…”

Tabla de Contenidos: “…""Chapter 18: Forecasting from Known Distributions""""Uniform Distribution""; ""Normal Distribution""; ""Binomial Distribution""; ""Poisson Distribution""; ""Exponential Distribution""; ""Geometric Distribution""; ""Weibull Distribution""; ""Chapter 19: Time Series""; ""Regression""; ""Autocorrelation""; ""Exponential Smoothing""; ""Chapter 20: Control Charts""; ""Sampling by Variable""; ""Sampling by Attribute""; ""Chapter 21: Reliability""; ""Basic Principles""; ""Reliability Data""; ""Distributions""; ""Practical Complications""; ""Part VII: Big Data""; ""Chapter 22: Data Mining""…”

Tabla de Contenidos: “…Title Page; Copyright Page; Table of Contents; Introduction; About This Book; Foolish Assumptions; Icons Used in This Book; Beyond the Book; Where to Go from Here; Part I Getting Started with Python for Data Science; Chapter 1 Discovering the Match between Data Science and Python; Defining the Sexiest Job of the 21st Century; Considering the emergence of data science; Outlining the core competencies of a data scientist; Linking data science and big data; Understanding the role of programming; Creating the Data Science Pipeline; Preparing the data; Performing exploratory data analysis…”

Tabla de Contenidos:

Tabla de Contenidos: “…Front Cover; About the Editor; Preface; Contents; Introduction; Review of the Literature; Chapter 1: Polymers; Chapter 2: Compression of Data; Chapter 3: Natural Language Compression; Chapter 4: Formal Language Compression; Chapter 5: Types of Compression Programs; Chapter 6: Algorithmic Compression; Chapter 7: Chemical Formulas; Chapter 8: Fischer Projection; Chapter 9: Compression of Polymers; Chapter 10: Line Notation Systems and Compression; Chapter 11: Current Trends in Research; Chapter 12: Big Data; Chapter 13: Modeling Complexity in Molecular Systems: A Revised Edition…”

Tabla de Contenidos: “…9.3 Research Gaps -- 9.4 Emerging Research Directions -- 9.5 The Broad Concept of FBG Sensor Applications in Industry 4.0 -- 9.6 Conclusion -- References -- Chapter 10 Fog Computing-Enabled Cancer Cell Detection System Using Convolution Neural Network in Internet of Medical Things -- 10.1 Introduction -- 10.2 Fog Computing: Approach of IoMT -- 10.3 Relationship Between IoMT and Deep Neural Network -- 10.4 Fog Computing Enabled CNN for Medical Imaging -- 10.5 Algorithm Approach of Proposed Model -- 10.6 Result and Analysis -- 10.7 Conclusion -- References -- Chapter 11 Application of IoT in Smart Farming and Precision Farming: A Review -- 11.1 Introduction -- 11.2 Methodologies Used in Precision Agriculture -- 11.3 Contribution of IoT in Agriculture -- 11.4 IoT Enabled Smart Farming -- 11.5 IoT Enabled Precision Farming -- 11.6 Machine Learning Enable Precision Farming -- 11.7 Application of Operational Research Method in Farming System -- 11.8 Conclusion -- 11.9 Future Scope -- References -- Chapter 12 Big IoT Data Analytics in Fog Computing -- 12.1 Introduction -- 12.2 Literature Review -- 12.3 Motivation -- 12.4 Fog Computing -- 12.4.1 Fog Node -- 12.4.2 Characteristics of Fog Computing -- 12.4.3 Attributes of Fog Node -- 12.4.4 Fog Computing Service Model -- 12.4.5 Fog Computing Architecture -- 12.4.6 Data Flow and Control Flow in Fog Architecture -- 12.4.7 Fog Deployment Models -- 12.5 Big Data -- 12.5.1 What is Big Data? -- 12.5.2 Source of Big Data -- 12.5.3 Characteristic of Big Data -- 12.6 Big Data Analytics Using Fog Computing -- 12.7 Conclusion -- References -- Chapter 13 IOT-Based Patient Monitoring System in Real Time -- 13.1 Introduction -- 13.2 Components Used -- 13.2.1 Node MCU -- 13.2.2 Heart Rate/Pulse Sensor -- 13.2.3 Temperature Sensor (LM35) -- 13.3 IoT Platform -- 13.3.1 ThingSpeak-IoT Platform Used in This Work…”

“…En particular, los ligados a las nuevas tecnologías, como la big data y la inteligencia artificial, y cómo ellos afectan la participación política del ciudadano en el gobierno abierto, la movilidad, la integración social de grupos excluidos por género o discapacidad, las ciudades ecosostenibles y las dinámicas de la administración local y la propia definición de ciudad. …”

Tabla de Contenidos: “…9.15.3 IoT -- 9.15.4 Big Data -- 9.15.5 Deep Learning -- 9.16 Challenges and Issues -- 9.16.1 Profound Learning Models -- 9.16.2 Deep Learning Paradigms -- 9.16.3 Confidentiality -- 9.16.4 Information Synthesis -- 9.16.5 Distributed Intelligence -- 9.16.6 Restrictions of Deep Learning -- 9.17 Conclusion and Future Scope -- References -- Index -- EULA…”

Tabla de Contenidos: “…John McGagh -- part Section II: Advances in Mining, Oil, and Gas Technologies -- chapter 7 Digital Mining: Past, Present, and Future / chapter 8 An Optimized Command System for Full Automation of Digitally Controlled Mine and Gas Train Plants and Sites / chapter 9 The Case for “n << all”: Why the Big Data Revolution Will Probably Happen Differently in the Mining Sector / chapter 10 Advancement in Digital Oil Field Technology: Maximizing Production and Improving Operational Efficiency through Data-Driven Technologies / chapter 11 A Statistical Framework for Data-Driven Assessment of Unconventional Oil and Gas Resources / chapter 12 Application of Advanced Data Analytics to Improve Haul Trucks Energy Efficiency in Surface Mines / chapter 13 Augmented Reality in Geological Modeling: Development and Use of the Leapfrog Aspect Viewer / chapter 14 Streamlining and Standardizing Data Use in the Extractive Industries. …”