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Artificial intelligence and machine learning methods in COVID-19 and related health diseases / / edited by Victor Chang, Harleen Kaur, Simon James Fong
Artificial intelligence and machine learning methods in COVID-19 and related health diseases / / edited by Victor Chang, Harleen Kaur, Simon James Fong
Pubbl/distr/stampa Singapore : , : Springer, , [2022]
Descrizione fisica 1 online resource (254 pages)
Disciplina 060
Collana Studies in Computational Intelligence
Soggetto topico Artificial intelligence - Medical applications
ISBN 3-031-04597-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910735390603321
Singapore : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Catalyzing Development through ICT Adoption : The Developing World Experience / / edited by Harleen Kaur, Ewa Lechman, Adam Marszk
Catalyzing Development through ICT Adoption : The Developing World Experience / / edited by Harleen Kaur, Ewa Lechman, Adam Marszk
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XII, 288 p. 32 illus., 20 illus. in color.)
Disciplina 658.4038
Soggetto topico Management information systems
Computers
Development economics
Business Information Systems
Information Systems and Communication Service
Development Economics
ISBN 3-319-56523-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part I – General and Multi-regional Studies -- 1 Information and Communication Technologies for Economic Development. Identifying the channels of impact -- 2 The impact of ICTs on women’s economic empowerment -- 3 Big Data Analytics for ICT Monitoring and Development -- 4 The role of ICT adoption in curbing corruption in developing countries -- 5 Internet, educational disparities and economic growth: differences between low-middle and high-income countries -- Part II – Asia -- 6 Strengthening the Public Sector Accounting through ICT The Experience of a Developing Country -- 7 Potentials and Challenges of using ICT for Climate Change Adaptation: A Study of Vulnerable Community in Riverine Islands of Bangladesh -- Part III – Africa and Middle East -- 8 Evaluation of E-Infrastructure Deployment in OECD and MENA Countries -- 9 Model for Constructing Institutional Framework for Scientific Knowledge Management Systems: Nigerian Institutional Repository Innovation Case Applicable to Developing Countries -- 10 Linkages between Formal Institutions, ICT Adoption, and Inclusive Human Development in Sub Saharan Africa -- Part IV – Latin America -- 11 Inequalities in the appropriation of digital spaces in metropolitan areas of Latin America -- 12 Internet Use and Public Programs Participation: Evidence from Chile -- 13 E-commerce and Productivity: Evidence from Chile -- Part V – Europe -- 14 Assessing the Economic Potential of Big Data Industries -- 15 Is ICT the Solution of the Problem for Estonia?.
Record Nr. UNINA-9910254909303321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Factories of the future : technological advancements in the manufacturing industry / / edited by Chandan Deep Singh and Harleen Kaur
Factories of the future : technological advancements in the manufacturing industry / / edited by Chandan Deep Singh and Harleen Kaur
Pubbl/distr/stampa Hoboken, NJ : , : John Wiley & Sons, Inc. and Scrivener Publishing LLC, , [2023]
Descrizione fisica 1 online resource (305 pages)
Disciplina 670
Soggetto topico Manufacturing industries - Technological innovations
Manufacturing industries - Management
ISBN 1-119-86521-2
1-119-86520-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Factories of the Future -- 1.0 Introduction -- 1.1 Factory of the Future -- 1.1.1 Plant Structure -- 1.1.2 Plant Digitization -- 1.1.3 Plant Processes -- 1.1.4 Industry of the Future: A Fully Integrated Industry -- 1.2 Current Manufacturing Environment -- 1.3 Driving Technologies and Market Readiness -- 1.4 Connected Factory, Smart Factory, and Smart Manufacturing -- 1.4.1 Potential Benefits of a Connected Factory -- 1.5 Digital and Virtual Factory -- 1.5.1 Digital Factory -- 1.5.2 Virtual Factory -- 1.6 Advanced Manufacturing Technologies -- 1.6.1 Advantages of Advanced Manufacturing Technologies -- 1.7 Role of Factories of the Future (FoF) in Manufacturing Performance -- 1.8 Socio-Econo-Techno Justification of Factories of the Future -- References -- Chapter 2 Industry 5.0 -- 2.1 Introduction -- 2.1.1 Industry 5.0 for Manufacturing -- 2.1.1.1 Industrial Revolutions -- 2.1.2 Real Personalization in Industry 5.0 -- 2.1.3 Industry 5.0 for Human Workers -- 2.2 Individualized Human-Machine-Interaction -- 2.3 Industry 5.0 is Designed to Empower Humans, Not to Replace Them -- 2.4 Concerns in Industry 5.0 -- 2.5 Humans Closer to the Design Process of Manufacturing -- 2.5.1 Enablers of Industry 5.0 -- 2.6 Challenges and Enablers (Socio-Econo-Techno Justification) -- 2.6.1 Social Dimension -- 2.6.2 Governmental and Political Dimension -- 2.6.3 Interdisciplinarity -- 2.6.4 Economic Dimension -- 2.6.5 Scalability -- 2.7 Concluding Remarks -- References -- Chapter 3 Machine Learning - A Survey -- 3.1 Introduction -- 3.2 Machine Learning -- 3.2.1 Unsupervised Machine Learning -- 3.2.2 Variety of Unsupervised Learning -- 3.2.3 Supervised Machine Learning -- 3.2.4 Categories of Supervised Learning -- 3.3 Reinforcement Machine Learning -- 3.3.1 Applications of Reinforcement Learning.
3.3.2 Dimensionality Reduction -- 3.4 Importance of Dimensionality Reduction in Machine Learning -- 3.4.1 Methods of Dimensionality Reduction -- 3.4.1.1 Principal Component Analysis (PCA) -- 3.4.1.2 Linear Discriminant Analysis (LDA) -- 3.4.1.3 Generalized Discriminant Analysis (GDA) -- 3.5 Distance Measures -- 3.6 Clustering -- 3.6.1 Algorithms in Clustering -- 3.6.2 Applications of Clustering -- 3.6.3 Iterative Distance-Based Clustering -- 3.7 Hierarchical Model -- 3.8 Density-Based Clustering -- 3.8.1 DBSCAN -- 3.8.2 OPTICS -- 3.9 Role of Machine Learning in Factories of the Future -- 3.10 Identification of the Probable Customers -- 3.11 Conclusion -- References -- Chapter 4 Understanding Neural Networks -- 4.1 Introduction -- 4.2 Components of Neural Networks -- 4.2.1 Neurons -- 4.2.2 Synapses and Weights -- 4.2.3 Bias -- 4.2.4 Architecture of Neural Networks -- 4.2.5 How Do Neural Networks Work? -- 4.2.6 Types of Neural Networks -- 4.2.6.1 Artificial Neural Network (ANN) -- 4.2.6.2 Recurrent Neural Network (RNN) -- 4.2.6.3 Convolutional Neural Network (CNN) -- 4.2.7 Learning Techniques in Neural Network -- 4.2.8 Applications of Neural Network -- 4.2.9 Advantages of Neural Networks -- 4.2.10 Disadvantages of Neural Network -- 4.2.11 Limitations of Neural Networks -- 4.3 Back-Propagation -- 4.3.1 Working of Back-Propagation -- 4.3.2 Types of Back-Propagation -- 4.3.2.1 Static Back-Propagation -- 4.3.2.2 Recurrent Back-Propagation -- 4.3.2.3 Advantages of Back-Propagation -- 4.3.2.4 Disadvantages of Back-Propagation -- 4.4 Activation Function (AF) -- 4.4.1 Sigmoid Active Function -- 4.4.1.1 Advantages -- 4.4.1.2 Disadvantages -- 4.4.2 RELU Activation Function -- 4.4.2.1 Advantages -- 4.4.2.2 Disadvantages -- 4.4.3 TANH Active Function -- 4.4.3.1 Advantages -- 4.4.3.2 Disadvantages -- 4.4.4 Linear Function -- 4.4.5 Advantages -- 4.4.6 Disadvantages.
4.4.7 Softmax Function -- 4.4.8 Advantages -- 4.5 Comparison of Activation Functions -- 4.6 Machine Learning -- 4.6.1 Applications of Machine Learning -- 4.7 Conclusion -- References -- Chapter 5 Intelligent Machining -- 5.1 Introduction -- 5.2 Requirements for the Developments of Intelligent Machining -- 5.3 Components of Intelligent Machining -- 5.3.1 Intelligent Sensors -- 5.3.1.1 Features of Intelligent Sensors -- 5.3.1.2 Functions of Intelligent Sensors -- 5.3.1.3 Data Acquisition and Management System to Process and Store Signals -- 5.3.2 Machine Learning and Knowledge Discovery Component -- 5.3.3 Database Knowledge Discovery -- 5.3.4 Programmable Logical Controller (PLC) -- 5.3.5 Role of Intelligent Machining for Implementation of Green Manufacturing -- 5.3.6 Information Integration via Knowledge Graphs -- 5.4 Conclusion -- References -- Chapter 6 Advanced Maintenance and Reliability -- 6.1 Introduction -- 6.2 Condition-Based Maintenance -- 6.3 Computerized Maintenance Management Systems (CMMS) -- 6.4 Preventive Maintenance (PM) -- 6.5 Predictive Maintenance (PdM) -- 6.6 Reliability Centered Maintenance (RCM) -- 6.6.1 RCM Principles -- 6.7 Condition Monitoring and Residual Life Prediction -- 6.8 Sustainability -- 6.8.1 Role of Sustainability in Manufacturing -- 6.9 Concluding Remarks -- References -- Chapter 7 Digital Manufacturing -- 7.1 Introduction -- 7.2 Product Life Cycle and Transition -- 7.3 Digital Thread -- 7.4 Digital Manufacturing Security -- 7.5 Role of Digital Manufacturing in Future Factories -- 7.6 Digital Manufacturing and CNC Machining -- 7.6.1 Introduction to CNC Machining -- 7.6.2 Equipment's Used in CNC Machining -- 7.6.3 Analyzing Digital Manufacturing Design Considerations -- 7.6.4 Finishing of Part After Machining -- 7.7 Additive Manufacturing -- 7.7.1 Objective of Additive Manufacturing -- 7.7.2 Design Consideration.
7.8 Role of Digital Manufacturing for Implementation of Green Manufacturing in Future Industries -- 7.9 Conclusion -- References -- Chapter 8 Artificial Intelligence in Machine Learning -- 8.1 Introduction -- 8.2 Case Studies -- 8.3 Advantages of A.I. in ML -- 8.4 Artificial Intelligence - Basics -- 8.4.1 History of A.I. -- 8.4.2 Limitations of Human Mind -- 8.4.3 Real Artificial Intelligence -- 8.4.4 Artificial Intelligence Subfields -- 8.4.5 The Positives of A.I. -- 8.4.6 Machine Learning -- 8.4.7 Machine Learning Models -- 8.4.8 Neural Networks -- 8.4.9 Constraints of Machine Learning -- 8.4.10 Different Kinds of Machine Learning -- 8.5 Application of Artificial Intelligence -- 8.5.1 Expert Systems -- 8.5.2 Natural Language Processing -- 8.5.3 Speech Recognition -- 8.5.4 Computer Vision -- 8.5.5 Robotics -- 8.6 Neural Networks (N.N.) Basics -- 8.6.1 Application of Neural Networks -- 8.6.2 Architecture of Neural Networks -- 8.6.3 Working of Artificial Neural Networks -- 8.7 Convolution Neural Networks -- 8.7.1 Working of Convolutional Neural Networks -- 8.7.2 Overview of CNN -- 8.7.3 Working of CNN -- 8.8 Image Classification -- 8.8.1 Concept of Image Classification -- 8.8.2 Type of Learning -- 8.8.3 Features of Image Classification -- 8.8.4 Examples of Image Classification -- 8.9 Text Classification -- 8.9.1 Text Classification Examples -- 8.9.2 Phases of Text Classification -- 8.9.3 Text Classification API -- 8.10 Recurrent Neural Network -- 8.10.1 Type of Recurrent Neural Network -- 8.11 Building Recurrent Neural Network -- 8.12 Long Short Term Memory Networks (LSTMs) -- References -- Chapter 9 Internet of Things -- 9.1 Introduction -- 9.2 M2M and Web of Things -- 9.3 Wireless Networks -- 9.4 Service Oriented Architecture -- 9.5 Complexity of Networks -- 9.6 Wireless Sensor Networks -- 9.7 Cloud Computing -- 9.8 Cloud Simulators.
9.9 Fog Computing -- 9.10 Applications of IoT -- 9.11 Research Gaps and Challenges in IoT -- 9.12 Concluding Remarks -- References -- Chapter 10 Product Life Cycle -- 10.1 Introduction -- 10.2 Product Lifecycle Management (PLM) -- 10.2.1 Why Product Lifecycle Management? -- 10.2.2 Biological Product Lifecycle Stages -- 10.2.3 An Example Related to Stages in Product Lifecycle Management -- 10.2.4 Advanced Stages in Product Lifecycle Management -- 10.2.5 Strategies of Product Lifecycle Management -- 10.3 High and Low-Level Skimming Strategies/Rapid or Slow Skimming Strategies -- 10.3.1 Considerations in High and Low-Level Pricing -- 10.3.2 Penetration Pricing Strategy -- 10.3.3 Example for Penetration Pricing Strategy -- 10.3.4 Considerations in Penetration Pricing -- 10.4 How Do Product Lifecycle Management Work? -- 10.5 Application Process of Product Lifecycle Management (PLM) -- 10.6 Role of Unified Modelling Language (UML) -- 10.6.1 UML Activity Diagrams -- 10.7 Management of Product Information Throughout the Entire Product Lifecycle -- 10.8 PDM System in an Organization -- 10.8.1 Benefits of PDM -- 10.8.2 How Does the PDM Work? -- 10.8.3 The Services of Product Data Management -- 10.9 System Architecture -- 10.9.1 Process of System Architecture -- 10.10 Concepts of Model-Based System Engineering (MBSE) -- 10.10.1 Benefits of Model-Based System Engineering (MBSE) -- 10.11 Challenges of Post-COVID 19 in Manufacturing Sector -- 10.12 Recent Updates in Product Life Cycle -- 10.13 Conclusion -- References -- Chapter 11 Case Studies -- 11.1 Case Study in a Two-Wheeler Manufacturing Industry -- 11.1.1 Company Strategy -- 11.1.2 Initiatives Towards Technological Advancement -- 11.1.3 Management Initiatives -- 11.1.4 Sustainable Development Goals -- 11.1.5 Growth Framework with Customer Needs -- 11.1.6 Vision for the Future.
11.2 Case Study in a Four-Wheeler Manufacturing Unit.
Record Nr. UNINA-9910830556703321
Hoboken, NJ : , : John Wiley & Sons, Inc. and Scrivener Publishing LLC, , [2023]
Materiale a stampa
Lo trovi qui: Univ. Federico II
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ICTs and the Millennium Development Goals : A United Nations Perspective / / edited by Harleen Kaur, Xiaohui Tao
ICTs and the Millennium Development Goals : A United Nations Perspective / / edited by Harleen Kaur, Xiaohui Tao
Edizione [1st ed. 2014.]
Pubbl/distr/stampa New York, NY : , : Springer US : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (273 p.)
Disciplina 004
005.7
303.4834
502.85
Soggetto topico Computers
Information technology
Business—Data processing
Health informatics
Information Systems and Communication Service
IT in Business
Health Informatics
ISBN 1-4899-7439-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Learning, Communication and Interaction via Wiki: An Australian Perspective -- ICTs Diffusion Trajectories and Economic Development -- An Empirical Analysis of Gendered Differences in MDG Awareness Across Sources of Information -- Global Evidence of Age-Structured Differences in MDG Awareness Among Users of Personal Computers -- Finding Weighted Positive Influence Dominating Set to Make Impact to Negatives -- A Conceptual Interdisciplinary Plug-and-Play Cyber Security Framework -- Mobile Phone and Development: Synthesis on New Misuse Perspective -- Incorporating ICTs in Schools for Effective Education -- Implementing ICT in Schools in a Developing Country -- Information and Communication Technology (ICT) Applications for Customer Relationship Management (CRM) -- Information Retrieval Using Rough Set Approximations -- The Role of ICTs in Poverty Eradication -- ICT-Based Trade Facilitation and the MDGs -- A Case Study: From Game-Programming to ICTs -- Challenges for Mobile Governance in India.
Record Nr. UNINA-9910299045503321
New York, NY : , : Springer US : , : Imprint : Springer, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui