INTERNET OF MEDICAL THINGS (IOMT) Providing an essential addition to the reference material available in the field of IoMT, this timely publication covers a range of applied research on healthcare, biomedical data mining, and the security and privacy of health records. With their ability to collect, analyze and transmit health data, IoMT tools are rapidly changing healthcare delivery. For patients and clinicians, these applications are playing a central part in tracking and preventing chronic illnesses -- and they are poised to evolve the future of care. In this book, the authors…mehr
Providing an essential addition to the reference material available in the field of IoMT, this timely publication covers a range of applied research on healthcare, biomedical data mining, and the security and privacy of health records.
With their ability to collect, analyze and transmit health data, IoMT tools are rapidly changing healthcare delivery. For patients and clinicians, these applications are playing a central part in tracking and preventing chronic illnesses -- and they are poised to evolve the future of care.
In this book, the authors explore the potential applications of a wave of sensor-based tools--including wearables and stand-alone devices for remote patient monitoring--and the marriage of internet-connected medical devices with patient information that ultimately sets the IoMT ecosystem apart.
This book demonstrates the connectivity between medical devices and sensors is streamlining clinical workflow management and leading to an overall improvement in patient care, both inside care facilities and in remote locations.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
Produktdetails
Advances in Learning Analytics for Intelligent Cloud-IoT Systems
Audience This book will be suitable for a wide range of researchers who are interested in acquiring in-depth knowledge on the latest IoMT-based solutions for healthcare-related problems. The book is specifically for those in artificial intelligence, cyber-physical systems, robotics, information technology, safety-critical systems, digital forensics, and application domain communities such as critical infrastructures, smart healthcare, manufacturing, and smart cities. R.J. Hemalatha, PhD in Electronics Engineering from Sathyabama University, India. She is currently the Head of the Department of Biomedical Engineering, in Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai, Tamil Nadu, India. She has published more than 50 research papers in various international journals. D. Akila, PhD received his degree in Computer Science from Bharathiar University, Tamilnadu, India. She is an associate professor in the Department of Information Technology, School of Computing Sciences, Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai, Tamil Nadu, India. She has published more than 25 research papers in various international journals. D. Balaganesh, PhD is a Dean of Faculty Computer Science and Multimedia, Lincoln University College, Malaysia. Anand Paul, PhD is an associate professor in the School of Computer Science and Engineering, Kyungpook National University, South Korea. He received his PhD degree in Electrical Engineering from National Cheng Kung University, Taiwan, R.O.C. in 2010.
Inhaltsangabe
Preface xv
1 In Silico Molecular Modeling and Docking Analysis in Lung Cancer Cell Proteins 1 Manisha Sritharan and Asita Elengoe
1.1 Introduction 2
1.2 Methodology 4
1.2.1 Sequence of Protein 4
1.2.2 Homology Modeling 4
1.2.3 Physiochemical Characterization 4
1.2.4 Determination of Secondary Models 4
1.2.5 Determination of Stability of Protein Structures 4
1.2.6 Identification of Active Site 4
1.2.7 Preparation of Ligand Model 5
1.2.8 Docking of Target Protein and Phytocompound 5
1.3 Results and Discussion 5
1.3.1 Determination of Physiochemical Characters 5
1.3.2 Prediction of Secondary Structures 7
1.3.3 Verification of Stability of Protein Structures 7
1.3.4 Identification of Active Sites 14
1.3.5 Target Protein-Ligand Docking 14
1.4 Conclusion 18
References 18
2 Medical Data Classification in Cloud Computing Using Soft Computing With Voting Classifier: A Review 23 Saurabh Sharma, Harish K. Shakya and Ashish Mishra
2.1 Introduction 24
2.1.1 Security in Medical Big Data Analytics 24
2.1.1.1 Capture 24
2.1.1.2 Cleaning 25
2.1.1.3 Storage 25
2.1.1.4 Security 26
2.1.1.5 Stewardship 26
2.2 Access Control-Based Security 27
2.2.1 Authentication 27
2.2.1.1 User Password Authentication 28
2.2.1.2 Windows-Based User Authentication 28
2.2.1.3 Directory-Based Authentication 28
2.2.1.4 Certificate-Based Authentication 28
2.2.1.5 Smart Card-Based Authentication 29
2.2.1.6 Biometrics 29
2.2.1.7 Grid-Based Authentication 29
2.2.1.8 Knowledge-Based Authentication 29
2.2.1.9 Machine Authentication 29
2.2.1.10 One-Time Password (OTP) 30
2.2.1.11 Authority 30
2.2.1.12 Global Authorization 30
2.3 System Model 30
2.3.1 Role and Purpose of Design 31
2.3.1.1 Patients 31
2.3.1.2 Cloud Server 31
2.3.1.3 Doctor 31
2.4 Data Classification 32
2.4.1 Access Control 32
2.4.2 Content 33
2.4.3 Storage 33
2.4.4 Soft Computing Techniques for Data Classification 34
2.5 Related Work 36
2.6 Conclusion 42
References 43
3 Research Challenges in Pre-Copy Virtual Machine Migration in Cloud Environment 45 Nirmala Devi N. and Vengatesh Kumar S.
3.1 Introduction 46
3.1.1 Cloud Computing 46
3.1.1.1 Cloud Service Provider 47
3.1.1.2 Data Storage and Security 47
3.1.2 Virtualization 48
3.1.2.1 Virtualization Terminology 49
3.1.3 Approach to Virtualization 50
3.1.4 Processor Issues 51
3.1.5 Memory Management 51
3.1.6 Benefits of Virtualization 51
3.1.7 Virtual Machine Migration 51
3.1.7.1 Pre-Copy 52
3.1.7.2 Post-Copy 52
3.1.7.3 Stop and Copy 53
3.2 Existing Technology and Its Review 54
3.3 Research Design 56
3.3.1 Basic Overview of VM Pre-Copy Live Migration 57
1 In Silico Molecular Modeling and Docking Analysis in Lung Cancer Cell Proteins 1 Manisha Sritharan and Asita Elengoe
1.1 Introduction 2
1.2 Methodology 4
1.2.1 Sequence of Protein 4
1.2.2 Homology Modeling 4
1.2.3 Physiochemical Characterization 4
1.2.4 Determination of Secondary Models 4
1.2.5 Determination of Stability of Protein Structures 4
1.2.6 Identification of Active Site 4
1.2.7 Preparation of Ligand Model 5
1.2.8 Docking of Target Protein and Phytocompound 5
1.3 Results and Discussion 5
1.3.1 Determination of Physiochemical Characters 5
1.3.2 Prediction of Secondary Structures 7
1.3.3 Verification of Stability of Protein Structures 7
1.3.4 Identification of Active Sites 14
1.3.5 Target Protein-Ligand Docking 14
1.4 Conclusion 18
References 18
2 Medical Data Classification in Cloud Computing Using Soft Computing With Voting Classifier: A Review 23 Saurabh Sharma, Harish K. Shakya and Ashish Mishra
2.1 Introduction 24
2.1.1 Security in Medical Big Data Analytics 24
2.1.1.1 Capture 24
2.1.1.2 Cleaning 25
2.1.1.3 Storage 25
2.1.1.4 Security 26
2.1.1.5 Stewardship 26
2.2 Access Control-Based Security 27
2.2.1 Authentication 27
2.2.1.1 User Password Authentication 28
2.2.1.2 Windows-Based User Authentication 28
2.2.1.3 Directory-Based Authentication 28
2.2.1.4 Certificate-Based Authentication 28
2.2.1.5 Smart Card-Based Authentication 29
2.2.1.6 Biometrics 29
2.2.1.7 Grid-Based Authentication 29
2.2.1.8 Knowledge-Based Authentication 29
2.2.1.9 Machine Authentication 29
2.2.1.10 One-Time Password (OTP) 30
2.2.1.11 Authority 30
2.2.1.12 Global Authorization 30
2.3 System Model 30
2.3.1 Role and Purpose of Design 31
2.3.1.1 Patients 31
2.3.1.2 Cloud Server 31
2.3.1.3 Doctor 31
2.4 Data Classification 32
2.4.1 Access Control 32
2.4.2 Content 33
2.4.3 Storage 33
2.4.4 Soft Computing Techniques for Data Classification 34
2.5 Related Work 36
2.6 Conclusion 42
References 43
3 Research Challenges in Pre-Copy Virtual Machine Migration in Cloud Environment 45 Nirmala Devi N. and Vengatesh Kumar S.
3.1 Introduction 46
3.1.1 Cloud Computing 46
3.1.1.1 Cloud Service Provider 47
3.1.1.2 Data Storage and Security 47
3.1.2 Virtualization 48
3.1.2.1 Virtualization Terminology 49
3.1.3 Approach to Virtualization 50
3.1.4 Processor Issues 51
3.1.5 Memory Management 51
3.1.6 Benefits of Virtualization 51
3.1.7 Virtual Machine Migration 51
3.1.7.1 Pre-Copy 52
3.1.7.2 Post-Copy 52
3.1.7.3 Stop and Copy 53
3.2 Existing Technology and Its Review 54
3.3 Research Design 56
3.3.1 Basic Overview of VM Pre-Copy Live Migration 57
3.3.2 Improved Pre-Copy Approach 58
3.3.3 Time Series-Based Pre-Copy Approach 60
3.3.4 Memory-Bound Pre-Copy Live Migration 62
3.3.5 Three-Phase Optimization Method (TPO) 62
3.3.6 Multiphase Pre-Copy Strategy 64
3.4 Results 65
3.4.1 Finding 65
3.5 Discussion 69
3.5.1 Limitation 69
3.5.2 Future Scope 70
3.6 Conclusion 70
References 71<
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