“…A cognitive ethnography of how bioengineering scientists create innovative modeling methods. In this first full-scale, long-term cognitive ethnography by a philosopher of science, Nancy J. …”

Tabla de Contenidos: “…Intro -- Preface -- Contents -- Part I: The Conceptual Framework of Decision Science for a Sustainable Society -- Chapter 1: Decision Science for Future Earth: A Conceptual Framework -- 1 Introduction -- 2 Conceptual Framework of Decision Science for a Sustainable Society -- 2.1 Science of IDEA Cycle, an Iterative Process of Decision-Making and Adaptive Learning -- 2.2 Relationship of the IDEA Cycle with Some Previous Concepts -- 2.3 Evolutionary Theory as a Basis of Decision Science for a Sustainable Society -- 3 Learning from Failures and Guidelines for Co-design -- 3.1 Vulnerability of Group Decision-Making -- 3.2 Predictable Surprise -- 3.2.1 Heuristics -- 3.2.2 Error Management Biases -- 3.3 Guidelines for Co-design Among Stakeholders -- 4 Learning from Successes in Local Communities -- 4.1 Seeds of a Good Anthropocene and Efforts for Adaptive Comanagement -- 4.2 Lessons Learned from Efforts for Adaptive Comanagement -- 4.3 Lessons from Transdisciplinary Projects at the Institute of Decision Science for a Sustainable Society (IDS3) -- 4.3.1 Ecosystem Comanagement in Yakushima, Japan -- 4.3.2 Citizenship Education in an Aging Society of Tsushima, Japan -- 4.3.3 Recovery from Flood Damage in Asakura and Toho, Japan -- 4.3.4 Supporting Community Forestry in Cambodia -- 4.3.5 Development of Portable Health Clinic as Social Business in India -- 4.4 The Roles of Scientists to Drive the Evolution of Knowledge, Institutions, and Social Ties -- 5 How can We Transform Our Society Toward a Sustainable Future? …”

Tabla de Contenidos: “…From Early thinker to Social Scientists -- 1 Knowledge and Wisdom Across Cultures -- 1.1 Introduction -- 1.2 Unabated Learning and Unbounded Knowledge -- 1.3 Pearls of Wisdom Along Highways of Time -- 1.4 Need for a Modern Science of Knowledge -- 1.5 Inception and Use of Business Machines -- 1.6 Information and its Current Deployment -- 1.6.1 Mostly Human: Senate, Legal, and Judiciary Use -- 1.6.2 Current - Organizational (Un, Church, Religious) -- 1.6.3 Evolving Use of Social Machines -- 1.6.4 Use of Federal and Legal Machines -- 1.7 Internet and Knowledge Revolution -- Conclusions -- References -- 2 From Philosophers to Knowledge Machines -- 2.1 Introduction -- 2.2 From Immanuel Kant to george Herbert Mead -- 2.2.1 Kant as a Meta-Physicist -- 2.2.2 Mead as a Social Psychologist -- 2.3 From Henry Ford to Peter Drucker -- 2.3.1 Ford and Model T Automobiles -- 2.3.2 Drucker and Management Sciences -- 2.3.3 The Unison of Social Sciences and Physical Sciences -- 2.3.4 Machine Architecture from Knowledge Functions -- 2.3.5 Generalization of the Structure of Knowledge Science -- Conclusions -- References -- 3 Affirmative Knowledge and Positive Human Nature -- 3.1 Introduction -- 3.2 Use of Scientific and AI-Based Machines -- 3.2.1 Evolving Use of Knowledge and Internet Machines -- 3.2.2 Incremental Changes in Society -- 3.3 Duality of Natural Forces and Human Traits -- 3.4 THE Fine Side of Human Nature -- 3.4.1 Integrated Changes in Society -- 3.4.2 Gradual Transition in the Knowledge Domain -- 3.4.3 Positive Social Change: Betterment and Enhancement -- Conclusions -- References -- 4 Negative Knowledge and Aggressive Human Nature -- 4.1 Introduction -- 4.2 The Coarse Side of Human Nature…”

Tabla de Contenidos: “…Case Study: The Citizen Scientists -- Section 20.8. Case Study: 1984, by George Orwell -- Glossary -- References -- Index -- Back Cover…”

Tabla de Contenidos: “…7.2.7 Machine-generated data, Internet of Things data -- 7.3 Analytics and data -- 7.3.1 Analytics continuum -- 7.3.2 Stage 0: Descriptive statistics -- 7.3.3 Stage 1: Predictive analytics -- 7.3.4 Stage 2: Prescriptive analytics -- 7.3.5 Stage 3: Simulation -- 7.3.6 Stage 4: Optimization -- 7.4 Augmented intelligence -- 7.5 Data scientists and statisticians -- 7.6 Final thoughts -- Summary -- 8 Looking forward: What's next for our data? …”

Tabla de Contenidos: “…15.2 Core Areas of Deep Learning and ML-Modeling in Medical Healthcare -- 15.3 Use Cases of Machine Learning Modelling in Healthcare Informatics -- 15.3.1 Breast Cancer Detection Using Machine Learning -- 15.3.2 COVID-19 Disease Detection Modelling Using Chest X-Ray Images with Machine and Transfer Learning Framework -- 15.4 Improving the Quality of Services During the Diagnosing and Treatment Processes of Chronicle Diseases -- 15.4.1 Evolution of New Diagnosing Methods and Tools -- 15.4.2 Improving Medical Care -- 15.4.3 Visualization of Biomedical Data -- 15.4.4 Improved Diagnosis and Disease Identification -- 15.4.5 More Accurate Health Records -- 15.4.6 Ethics of Machine Learning in Healthcare -- 15.5 Limitations and Challenges of ML, DL Modelling in Healthcare Systems -- 15.5.1 Dealing With the Shortage of Knowledgeable-ML-Data Scientists and Engineers -- 15.5.2 Handling of the Bias in ML Modelling of Healthcare Information -- 15.5.3 Accuracy of Data Attenuation -- 15.5.4 Lack of Data Quality -- 15.5.5 Tuning of Hyper-Parameters for Improving the Modelling of Healthcare -- 15.6 Conclusion -- References -- Chapter 16 Developing a Cognitive Learning and Intelligent Data Analysis-Based Framework for Early Disease Detection and Prevention in Younger Adults with Fatigue -- 16.1 Introduction -- 16.2 Proposed Framework "Cognitive-Intelligent Fatigue Detection and Prevention Framework (CIFDPF)" -- 16.2.1 Framework Components -- 16.2.2 Learning Module -- 16.2.3 System Design -- 16.2.4 Tools and Usage -- 16.2.5 Architecture -- 16.2.6 Architecture of CNN-RNN -- 16.2.7 Fatigue Detection Methods and Techniques -- 16.3 Potential Impact -- 16.3.1 Claims for the Accurate Detection of Fatigue -- 16.3.2 Similar Study and Results Analysis -- 16.3.3 Application and Results -- 16.4 Discussion and Limitations -- 16.5 Future Work…”

“…In recent years, academic advancement and access to funds that stimulate scientific research have been conditioned by the scientific production of individual scientists as well as the production of scientific centers, institutes and universities. …”

“…See the industries data scientists work in and the tasks they work on Compare salaries paid to data scientists in the U.S., Asia, UK/Ireland, and the rest of Europe Compare salaries paid to data scientists in different regions of the U.S. …”

“…As a multi-disciplinary journal, natural scientists and social scientists from all around the world are welcome to engage in this forum as contributors."…”

“…Many scientists and engineers had been exiled, imprisoned, or executed by the regime. …”

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“…The journal encourages the interaction between physicists, statisticians, mathematicians, computer scientists, and earth scientists in the development of new models and methods applied to the analysis of the climate system…”

Tabla de Contenidos: “…Intro -- Foreword -- Preface -- Pioneering Space-Borne SAR Interferometry -- Organising Airborne Polarimetric SAR Campaigns and Scientific Studies -- Dialoguing with POLinSAR Scientists and Training the Next Generation -- Pioneering Space-Borne SAR Polarimetric Interferometry -- Future Missions -- From Science to Applications -- Outlook -- In Memoriam -- Contents -- Symbols -- 1: Basic Principles of SAR Polarimetry -- 1.1 Theory of Radar Polarimetry -- 1.1.1 Wave Polarimetry -- 1.1.1.1 Electromagnetic Waves and Wave Polarization Descriptors -- 1.1.1.2 Totally and Partially Polarized Waves -- 1.1.1.3 Change of Polarization Basis -- 1.1.2 Scattering Polarimetry -- 1.1.2.1 The Scattering Matrix -- 1.1.2.2 Scattering Polarimetry Descriptors -- 1.1.2.3 Partial Scattering Polarimetry -- 1.1.2.4 Change of Polarization Basis -- 1.1.2.5 Scatterers Characterization by Single, Dual, Compact and Full Polarimetry -- 1.2 SAR Data Statistical Description and Speckle Noise Filtering -- 1.2.1 One-Dimensional Gaussian Distribution -- 1.2.2 Multidimensional Gaussian Distribution -- 1.2.3 The Wishart Distribution -- 1.2.4 The Polarimetric Covariance and Coherency Matrix -- 1.2.5 The Polarimetric Coherence -- 1.2.6 Polarimetric Speckle Noise Filtering -- 1.2.6.1 PolSAR Speckle Noise Filtering Principles -- 1.2.6.2 PolSAR Speckle Noise Filtering Alternatives -- 1.3 Polarimetric Scattering Decomposition Theorems -- 1.3.1 Coherent Scattering Decomposition Techniques -- 1.3.1.1 The Pauli Decomposition -- 1.3.2 Incoherent Scattering Decompositions Techniques -- 1.3.2.1 Three-Component Freeman Decomposition -- 1.3.2.2 Four-Component Yamaguchi Decomposition -- 1.3.2.3 Non-negative Eigenvalue Decomposition -- 1.3.2.4 Eigenvector-Eigenvalue-Based Decomposition -- 1.3.2.5 The Touzi Target Scattering Decompositions -- 1.4 Polarimetric SAR Interferometry…”