csr prabhu (20 Ergebnisse)

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. pp. 191.

Zustand: New. pp. 191.

Soft cover. Zustand: Near Fine. Wireless data technologies are making significant strides in providing universal connectivity today. Mobile computing combines the capabilities of computing with communications, opening up several application areas. The challenge lies in not only overcoming the limitations posed by narrow bandwidths and intermittent connectivity, but also the extreme vulnerability of wireless networks to security threats. The papers in this book survey the developments in wireless communications technology and give the readers an insight into the major issues and challenges in mobile computing.

Soft cover. Zustand: New. Contents: 1. Analysis and Survey on Grammar Checking and Correction Approaches for Punjabi and Other Languages 2. Early Heart Disorder Prediction System using Artificial Neural Network and K- Fold Cross Validation Model 3. Offline Mobile Finder Application 4. Cognitive Horses of Deep Learning: Regularization and Optimization Practices 5. Transliteration of Sanskrit Scripts using Natural Language Processing and Meta-Heuristic Algorithms 6. A Data-Driven Research on Optimizing Supply Chain Logistics for Manufacturing Companies: A Predictive Modeling Approach 7. Impact of Meteorological Conditions on Air Quality Prediction using Deep Learning 8. ADA_ViT: Adaptive Drawer Algorithm for Vision Transformers to Detect the Severity of Diabetic Retinopathy 9. A Hybrid Deep Learning Model: Integration of CNN and BiLSTM for Malayalam Question Answering from Facebook bAbl Dataset Task 1 10. Evaluating Trade-offs between Model Precision and Traning Performance with Precision Variation 11. The NLP Quest: Unveiling Hidden Topics in 'Autobiography of a Yogi' using BER Topic 12. Revolutionizing Netflix Recommendations: The Power of Transfer Learning.

Soft cover. Zustand: New. 1st Edition. Contents: 1. Overview - Fog Computing and Internet-of-Things (IoT) SECTION - I: TECHNOLOGY. 2. Integrated IoT and Cloud Environment for Fingerprint Recognition. 3. Smartphone-based Real Time Sensing and Actuation with the Cumulocity Internet of Things Platform. 4. Future Technologies to Meet the IoT Needs: Die Level 3-D Packaging of Heterogeneous and Hybrid Systems. 5. Conceptual Fog based Architecture for Monitoring and Acceleration of Bone Fracture Healing .6. Communication Protocols in IoT. 7. Challenges on IoT Stack Model via TCP/IP Architecture. SECTION - II: PRIVACY AND SECURITY: 8. Enhancing Data Security on Fog Computing with Interfacing Technologies. 9. Route Map of Privacy Preservation to IoT: A Review. 10. Role of Risk Perception and Data Security in Enterprise Cloud Networks. 11. Security in IoT. 12. Geo-spatial Land Records Database- A Framework for Rural Development. 13. Controlling of Electrical Gadgets at Home by Utilizing Smart Switch and Web. 14. Comparison of On-demand Taxi Services: Uber and Careem. 15. Internet of Things and Big Data Analytics for Climate Change. 16. A Review on using IoT in Smart Cities. 17. IoT in Transportation and Logistics. 18. Role of IoT in Road Safety .

XXVI, 412 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

Paperback. Zustand: New. Language: English. About The Author: C.S.R. Prabhu, Director General(Retd.) National, Informatics Centre (NIC), New Delhi (Ministry of, Communications and Information Technology, Department of Electronics and Information, Technology). After obtaining Master of, Technology degree in Electrical Engineering with, specialisation in Computer Science from IIT, Mumbai in 1978, he has worked in various, capacities at Tata Consultancy Services, CMC, TES and TELCO (Tata Motors) before joining, NIC. He also has teaching and research experience, at the University of Central Florida, Orlando, Florida. He has been a software consultant to, NASA; Florida Savings and Loans, Orlando and, Hughes Aircraft Corporation, Irvine, California., An author of several books including (1) Semantic, Database Systems, (2) ObjectOriented Database, Systems; Approaches and Architectures, 2nd ed., (3) Data Warehousing; Concepts, Techniques, Products and Applications, 3rd ed., (4) EGovernance:, Concepts and Case Studies, (5) Blue, Tooth and (6) Grid and Cluster Computing. He, was also the Editor of Proceedings of the 9th, International Conference on Management of Data, (COMAD 98) and also Mobile Computing (2000)., He was State Informatics Officer (SIO), National Informatics Centre (NIC) for Andhra, Pradesh and Tamilnadu where he was responsible, for implementing egovernance projects as e, Panchayat, Eucalyptus Cloud, National Data, Centre and National Training Centre., at NIC Hqrs., New Delhi he is, coordinating the Energy Sector, National, Information Infrastructure (NII) 2.0, National, Optic Fibre Network (NOFN) Applications, Knowledge Management and Project Evaluation, and Management activities of NIC Contents: Contents, Preface 9, Acknowledgements 11, 1. Knowledge and its Management in 13, an Organisation, 1.1. Knowledge Management (KM), 1.1.1. Knowledge Management (KM) , Schools of Thought A Summary, View, 1.1.2. Intellectual Capital, 1.1.3. Knowledge Transfer, 1.1.4. Organisational learning, 1.1.5. Knowledge Innovation, 1.2. Motivation for Knowledge Management, 1.3. The Knowledge Lens, 1.4. Organisation as a Knowledge Ecosystem, 1.4.1. Aim of Knowledge Management in the, Knowledge Ecosystem of the, Organisation, 1.4.2. Implementing Knowledge Management, Interventions the Map/Build/, Operationalise Cycle, 1.5. Conclusion, 2. Knowledge Mapping 31, 2.1. The Methodology of Mapping, 2.2. Existing Knowledge Ecosystem, 2.2.1. How to Perform mapping of an, Existing Knowledge System?, 2.3. Enablers for Knowledge Analysis, 2.4. Knowledge Management Maturity Model, (KMMM), 2.5. Results of Mapping Phase, 6 Knowledge Management and Information Technology, 2.6. Conclusion, 3. Building Phase for KM 39, 3.1. Activities for KM Intervention, 3.2. Evolution of KM in the Organisation, 3.3. Enablers, 3.4. Prototyping and Pilot Projects, 3.5. Building Organisational Structures and, Linkages, 3.6. Communicating Knowledge Intervention, 3.7. Building Champions, Advocates, Promoters, Mandate and Organisational, Competetiveness, 3.8. Resistance Maangement, 3.9. Outcomes of Build Phase, 3.10. Conclusion, 4. Operationalisation 47, 4.1. Operationalisation of Knowledge and, Knowledge Management Initiatives and, Interventions, 4.2. Operational Environments, 4.3. Branding and its Benefits, 4.4. Operational Champions, Advocates and, Mandate, 4.5. Competencies and Skills in Operationalisation., 4.6. Sustainability beyond Operationalisation, Phase, 4.7. Indications of success, 4.8. Conclusion, 5. Critical Success Factors 53, 5.1. Status and Maturity Level of IT, implementation in the organisation., 5.2. Knowledge Repositories, 5.3. Organisational Culture, 5.4. Top Management Commitment, 5.5. Motivation of Employees, 5.6. Human Resources, 5.7. Conclusion, 6. Enablers for Knowledge 63, Management (KM), 6.1. Action Taken Reviews (ATR), 6.2. Business Process Reengineering, CONTENTS: 7, 6.3. Champions and Advocates, 6.4. Communities of Interest, 6.5. Communities of Practice, 6.6. Change Management, 6.7. Content Management, 6.8. Document Management, 6.9. Environmental Scanning, 6.10. Auditing of Information, 6.11. Knowledge Auditing, 6.12. Knowledge Literacy, 6.13. Knowledge Mapping, 6.14. Leadership for KM, 6.15. Conclusion, 7. Information Technology and 73, Knowledge Management, 7.1. KM and Workflow Processes, 7.2. Organisational Memories, 7.3. Information Filtering, 7.4. Software Process Improvement using, Knowledge Management, 7.4.1. Knowledge Management in Virtual, Software Corporation (VSC), 7.4.2. Methodology for KM Implementation, in Virtual Software Corporations, (VSCs), 7.4.3. KM Process Model Utilisation in a, Virtual Software Corporation (VSC)., 7.5. Knowledge Management (KM) and, Information Security Management (ISM), (KM and ISM), 7.5.1. Similarities between KM and ISM, 7.5.2. Dependence on People, 7.5.3. Public Good Production, 7.5.4. Exclusively Usable Knowledge, 7.6. Organisational Challenge, 7.7. Conclusion, 8. Knowledge Transfer 89, 8.1. Successive Knowledge Transfer (KT), 8.2. Knowledge Source, 8.3. Knowledge Development Stages and Cycles, 8.4. External and Internal Factors Affecting, 8 Knowledge Management and Information Technology, Knowledge Development Cycle, 8.5. Knowledge Transfer, 8.6. Knowledge Transfer (KT) Methods, 9. Distributed Knowledge Management 109, Systems (DKMS) for Internet Age, 9.1. Distributed/Object Oriented Datawarehouse/, Distributed Knowledge Management System, 9.2. DKMS Definition and Characteristics, 9.3. How to Create a DKMS?, 9.4. Identifying business Objectives and Goals of, the Enterprise, 9.5. Major Subsystem Definition, 9.5.1. Business Process, 9.5.2. Subprocess as a Process, 9.5.3. Actors, 9.5.4. Use Cases, 9.6. Requirement Analysis, 9.7. Object Model for the Enterprise, 9.7.1. Components, 9.7.2. Storage Object Modelling, 9.7.3. System Design, 9.8. Object Interaction Modelling (OIM), 9.9. Dynamic Modelling, 9.9.1. Detailed Design of Object Types, Relationships and Interactions, 9.9.2. SOM Database Di.

Hardcover. Zustand: New. Language: English. About The Author: C.S.R. Prabhu, Director General(Retd.) National, Informatics Centre (NIC), New Delhi (Ministry of, Communications and Information Technology, Department of Electronics and Information, Technology). After obtaining Master of, Technology degree in Electrical Engineering with, specialisation in Computer Science from IIT, Mumbai in 1978, he has worked in various, capacities at Tata Consultancy Services, CMC, TES and TELCO (Tata Motors) before joining, NIC. He also has teaching and research experience, at the University of Central Florida, Orlando, Florida. He has been a software consultant to, NASA; Florida Savings and Loans, Orlando and, Hughes Aircraft Corporation, Irvine, California., An author of several books including (1) Semantic, Database Systems, (2) ObjectOriented Database, Systems; Approaches and Architectures, 2nd ed., (3) Data Warehousing; Concepts, Techniques, Products and Applications, 3rd ed., (4) EGovernance:, Concepts and Case Studies, (5) Blue, Tooth and (6) Grid and Cluster Computing. He, was also the Editor of Proceedings of the 9th, International Conference on Management of Data, (COMAD 98) and also Mobile Computing (2000)., He was State Informatics Officer (SIO), National Informatics Centre (NIC) for Andhra, Pradesh and Tamilnadu where he was responsible, for implementing egovernance projects as e, Panchayat, Eucalyptus Cloud, National Data, Centre and National Training Centre., at NIC Hqrs., New Delhi he is, coordinating the Energy Sector, National, Information Infrastructure (NII) 2.0, National, Optic Fibre Network (NOFN) Applications, Knowledge Management and Project Evaluation, and Management activities of NIC Contents: Contents, Preface 9, Acknowledgements 11, 1. Knowledge and its Management in 13, an Organisation, 1.1. Knowledge Management (KM), 1.1.1. Knowledge Management (KM) , Schools of Thought A Summary, View, 1.1.2. Intellectual Capital, 1.1.3. Knowledge Transfer, 1.1.4. Organisational learning, 1.1.5. Knowledge Innovation, 1.2. Motivation for Knowledge Management, 1.3. The Knowledge Lens, 1.4. Organisation as a Knowledge Ecosystem, 1.4.1. Aim of Knowledge Management in the, Knowledge Ecosystem of the, Organisation, 1.4.2. Implementing Knowledge Management, Interventions the Map/Build/, Operationalise Cycle, 1.5. Conclusion, 2. Knowledge Mapping 31, 2.1. The Methodology of Mapping, 2.2. Existing Knowledge Ecosystem, 2.2.1. How to Perform mapping of an, Existing Knowledge System?, 2.3. Enablers for Knowledge Analysis, 2.4. Knowledge Management Maturity Model, (KMMM), 2.5. Results of Mapping Phase, 6 Knowledge Management and Information Technology, 2.6. Conclusion, 3. Building Phase for KM 39, 3.1. Activities for KM Intervention, 3.2. Evolution of KM in the Organisation, 3.3. Enablers, 3.4. Prototyping and Pilot Projects, 3.5. Building Organisational Structures and, Linkages, 3.6. Communicating Knowledge Intervention, 3.7. Building Champions, Advocates, Promoters, Mandate and Organisational, Competetiveness, 3.8. Resistance Maangement, 3.9. Outcomes of Build Phase, 3.10. Conclusion, 4. Operationalisation 47, 4.1. Operationalisation of Knowledge and, Knowledge Management Initiatives and, Interventions, 4.2. Operational Environments, 4.3. Branding and its Benefits, 4.4. Operational Champions, Advocates and, Mandate, 4.5. Competencies and Skills in Operationalisation., 4.6. Sustainability beyond Operationalisation, Phase, 4.7. Indications of success, 4.8. Conclusion, 5. Critical Success Factors 53, 5.1. Status and Maturity Level of IT, implementation in the organisation., 5.2. Knowledge Repositories, 5.3. Organisational Culture, 5.4. Top Management Commitment, 5.5. Motivation of Employees, 5.6. Human Resources, 5.7. Conclusion, 6. Enablers for Knowledge 63, Management (KM), 6.1. Action Taken Reviews (ATR), 6.2. Business Process Reengineering, CONTENTS: 7, 6.3. Champions and Advocates, 6.4. Communities of Interest, 6.5. Communities of Practice, 6.6. Change Management, 6.7. Content Management, 6.8. Document Management, 6.9. Environmental Scanning, 6.10. Auditing of Information, 6.11. Knowledge Auditing, 6.12. Knowledge Literacy, 6.13. Knowledge Mapping, 6.14. Leadership for KM, 6.15. Conclusion, 7. Information Technology and 73, Knowledge Management, 7.1. KM and Workflow Processes, 7.2. Organisational Memories, 7.3. Information Filtering, 7.4. Software Process Improvement using, Knowledge Management, 7.4.1. Knowledge Management in Virtual, Software Corporation (VSC), 7.4.2. Methodology for KM Implementation, in Virtual Software Corporations, (VSCs), 7.4.3. KM Process Model Utilisation in a, Virtual Software Corporation (VSC)., 7.5. Knowledge Management (KM) and, Information Security Management (ISM), (KM and ISM), 7.5.1. Similarities between KM and ISM, 7.5.2. Dependence on People, 7.5.3. Public Good Production, 7.5.4. Exclusively Usable Knowledge, 7.6. Organisational Challenge, 7.7. Conclusion, 8. Knowledge Transfer 89, 8.1. Successive Knowledge Transfer (KT), 8.2. Knowledge Source, 8.3. Knowledge Development Stages and Cycles, 8.4. External and Internal Factors Affecting, 8 Knowledge Management and Information Technology, Knowledge Development Cycle, 8.5. Knowledge Transfer, 8.6. Knowledge Transfer (KT) Methods, 9. Distributed Knowledge Management 109, Systems (DKMS) for Internet Age, 9.1. Distributed/Object Oriented Datawarehouse/, Distributed Knowledge Management System, 9.2. DKMS Definition and Characteristics, 9.3. How to Create a DKMS?, 9.4. Identifying business Objectives and Goals of, the Enterprise, 9.5. Major Subsystem Definition, 9.5.1. Business Process, 9.5.2. Subprocess as a Process, 9.5.3. Actors, 9.5.4. Use Cases, 9.6. Requirement Analysis, 9.7. Object Model for the Enterprise, 9.7.1. Components, 9.7.2. Storage Object Modelling, 9.7.3. System Design, 9.8. Object Interaction Modelling (OIM), 9.9. Dynamic Modelling, 9.9.1. Detailed Design of Object Types, Relationships and Interactions, 9.9.2. SOM Database Di.

Zustand: New. In.

Zustand: New. In.

Hardcover. Zustand: Brand New. 194 pages. 5.50x0.56x8.50 inches. In Stock.

Buch. Zustand: Neu. Neuware - The Title 'Knowledge Management And Information Technology written by C. S. R. Prabhu' was published in the year 2014. The ISBN number 9788121212199 is assigned to the Hardcover version of this title. This book has total of pp. 191 (Pages). The publisher of this title is Gyan Publishing House. This Book is in English. The subject of this book is Management, , About The Author:- C.S.R. Prabhu, Director General(Retd.) National, Informatics Centre (NIC), New Delhi (Ministry of, Communications and I.

Taschenbuch. Zustand: Neu. Big Data Analytics: Systems, Algorithms, Applications | C. S. R. Prabhu (u. a.) | Taschenbuch | xxvi | Englisch | 2020 | Springer | EAN 9789811500961 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy.With regard to machine learning techniques, the book presents all the standard algorithms for learning - including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered.In turn,the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition.Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.

Zustand: New. In.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy.With regard to machine learning techniques, the book presents all the standard algorithms for learning - including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered.In turn,the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition.Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a comprehensive picture of fog computing technology, including of fog architectures, latency aware application management issues with real time requirements, security and privacy issues and fog analytics, in wide ranging application scenarios such as M2M device communication, smart homes, smart vehicles, augmented reality and transportation management.This book explores the research issues involved in the application of traditional shallow machine learning and deep learning techniques to big data analytics. It surveys global research advances in extending the conventional unsupervised or clustering algorithms, extending supervised and semi-supervised algorithms and association rule mining algorithms to big data Scenarios. Further it discusses the deep learning applications of big data analytics to fields of computer vision and speech processing, and describes applications such as semantic indexing and data tagging. Lastly it identifies 25 unsolved research problems and research directions in fog computing, as well as in the context of applying deep learning techniques to big data analytics, such as dimensionality reduction in high-dimensional data and improved formulation of data abstractions along with possible directions for their solutions.

Hardcover. Zustand: Brand New. 71 pages. 9.25x6.25x0.25 inches. In Stock.