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9781119768876 |
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9781119769309 |
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9781119769316 |
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(adobe pdf) |
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9781119768876 |
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(cloth) |
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DLC |
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eng |
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DLC |
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rda |
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eng |
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pcc |
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QA76.585 |
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004.67/82 |
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23 |
| 245 00 - TITLE STATEMENT |
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| Title |
Integration of cloud computing with Internet of things : |
| Remainder of title |
foundations, analytics and applications / |
| Statement of responsibility, etc |
edited by Monika Mangla, Suneeta Satpathy, Bhagirathi Nayak and Sachi Nandan Mohanty. |
| 263 ## - PROJECTED PUBLICATION DATE |
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2105 |
| 264 #1 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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Hoboken, NJ : |
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Wiley-Scrivener, |
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2021. |
| 300 ## - PHYSICAL DESCRIPTION |
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1 online resource |
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computer |
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online resource |
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| 490 ## - SERIES STATEMENT |
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| Series statement |
Advances in Learning Analytics for Intelligent Cloud-IoT Systems |
| 500 ## - GENERAL NOTE |
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| General note |
ABOUT THE AUTHOR<br/>Monika Mangla PhD is an Assistant Professor in the Department of Computer Engineering at Lokmanya Tilak College of Engineering (LTCoE), Mumbai, India. Her research areas include IoT, cloud computing, algorithms and optimization, location modelling and machine learning.<br/><br/>Suneeta Satpathy PhD is an Associate Professor in the Department of Computer Science & Engineering at College of Engineering Bhubaneswar (CoEB), Bhubaneswar. Her research interests include computer forensics, cybersecurity, data fusion, data mining, big data analysis, and decision mining.<br/><br/>Bhagirathi Nayak has 25 years of experience in the areas of computer science and engineering and database designing. Prof. Nayak earned his PhD in Computer Science from IIT Kharagpur. He is currently associated with Sri Sri University, Cuttack as head of the Department of Information & Communication Technology. He has obtained five patents in the area of computer science and engineering and his areas of interest are data mining, big data analytics, artificial intelligence and machine learning.<br/><br/>Sachi Nandan Mohanty obtained his PhD from IIT Kharagpur in 2015 and is now an Associate Professor in the Department of Computer Science & Engineering at ICFAI Foundation for Higher Education Hyderabad. Dr. Mohanty’s research areas include data mining, big data analysis, cognitive science, fuzzy decision making, brain-computer interface, and computational intelligence. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references and index. |
| 505 ## - CONTENTS |
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| Formatted contents note |
TABLE OF CONTENTS<br/>Preface xv<br/><br/>Acknowledgement xvii<br/><br/>1 Internet of Things: A Key to Unfasten Mundane Repetitive Tasks 1<br/>Hemanta Kumar Palo and Limali Sahoo<br/><br/>1.1 Introduction 1<br/><br/>1.2 The IoT Scenario 2<br/><br/>1.3 The IoT Domains 3<br/><br/>1.3.1 The IoT Policy Domain 3<br/><br/>1.3.2 The IoT Software Domain 5<br/><br/>1.3.2.1 IoT in Cloud Computing (CC) 5<br/><br/>1.3.2.2 IoT in Edge Computing (EC) 6<br/><br/>1.3.2.3 IoT in Fog Computing (FC) 10<br/><br/>1.3.2.4 IoT in Telecommuting 11<br/><br/>1.3.2.5 IoT in Data-Center 12<br/><br/>1.3.2.6 Virtualization-Based IoT (VBIoT) 12<br/><br/>1.4 Green Computing (GC) in IoT Framework 12<br/><br/>1.5 Semantic IoT (SIoT) 13<br/><br/>1.5.1 Standardization Using oneM2M 15<br/><br/>1.5.2 Semantic Interoperability (SI) 18<br/><br/>1.5.3 Semantic Interoperability (SI) 19<br/><br/>1.5.4 Semantic IoT vs Machine Learning 20<br/><br/>1.6 Conclusions 21<br/><br/>References 21<br/><br/>2 Measures for Improving IoT Security 25<br/>Richa Goel, Seema Sahai, Gurinder Singh and Saurav Lall<br/><br/>2.1 Introduction 25<br/><br/>2.2 Perceiving IoT Security 26<br/><br/>2.3 The IoT Safety Term 27<br/><br/>2.4 Objectives 28<br/><br/>2.4.1 Enhancing Personal Data Access in Public Repositories 28<br/><br/>2.4.2 Develop and Sustain Ethicality 28<br/><br/>2.4.3 Maximize the Power of IoT Access 29<br/><br/>2.4.4 Understanding Importance of Firewalls 29<br/><br/>2.5 Research Methodology 30<br/><br/>2.6 Security Challenges 31<br/><br/>2.6.1 Challenge of Data Management 32<br/><br/>2.7 Securing IoT 33<br/><br/>2.7.1 Ensure User Authentication 33<br/><br/>2.7.2 Increase User Autonomy 33<br/><br/>2.7.3 Use of Firewalls 34<br/><br/>2.7.4 Firewall Features 35<br/><br/>2.7.5 Mode of Camouflage 35<br/><br/>2.7.6 Protection of Data 35<br/><br/>2.7.7 Integrity in Service 36<br/><br/>2.7.8 Sensing of Infringement 36<br/><br/>2.8 Monitoring of Firewalls and Good Management 36<br/><br/>2.8.1 Surveillance 36<br/><br/>2.8.2 Forensics 37<br/><br/>2.8.3 Secure Firewalls for Private 37<br/><br/>2.8.4 Business Firewalls for Personal 37<br/><br/>2.8.5 IoT Security Weaknesses 37<br/><br/>2.9 Conclusion 37<br/><br/>References 38<br/><br/>3 An Efficient Fog-Based Model for Secured Data Communication 41<br/>V. Lakshman Narayana and R. S. M. Lakshmi Patibandla<br/><br/>3.1 Introduction 41<br/><br/>3.1.1 Fog Computing Model 42<br/><br/>3.1.2 Correspondence in IoT Devices 43<br/><br/>3.2 Attacks in IoT 45<br/><br/>3.2.1 Botnets 45<br/><br/>3.2.2 Man-In-The-Middle Concept 45<br/><br/>3.2.3 Data and Misrepresentation 46<br/><br/>3.2.4 Social Engineering 46<br/><br/>3.2.5 Denial of Service 46<br/><br/>3.2.6 Concerns 47<br/><br/>3.3 Literature Survey 48<br/><br/>3.4 Proposed Model for Attack Identification Using Fog Computing 49<br/><br/>3.5 Performance Analysis 52<br/><br/>3.6 Conclusion 54<br/><br/>References 54<br/><br/>4 An Expert System to Implement Symptom Analysis in Healthcare 57<br/>Subhasish Mohapatra and Kunal Anand<br/><br/>4.1 Introduction 57<br/><br/>4.2 Related Work 59<br/><br/>4.3 Proposed Model Description and Flow Chart 60<br/><br/>4.3.1 Flowchart of the Model 60<br/><br/>4.3.1.1 Value of Symptoms 60<br/><br/>4.3.1.2 User Interaction Web Module 60<br/><br/>4.3.1.3 Knowledge-Base 60<br/><br/>4.3.1.4 Convolution Neural Network 60<br/><br/>4.3.1.5 CNN-Fuzzy Inference Engine 61<br/><br/>4.4 UML Analysis of Expert Model 62<br/><br/>4.4.1 Expert Module Activity Diagram 63<br/><br/>4.4.2 Ontology Class Collaboration Diagram 65<br/><br/>4.5 Ontology Model of Expert Systems 66<br/><br/>4.6 Conclusion and Future Scope 67<br/><br/>References 68<br/><br/>5 An IoT-Based Gadget for Visually Impaired People 71<br/>Prakash, N., Udayakumar, E., Kumareshan, N., Srihari, K. and Sachi Nandan Mohanty<br/><br/>5.1 Introduction 71<br/><br/>5.2 Related Work 73<br/><br/>5.3 System Design 74<br/><br/>5.4 Results and Discussion 82<br/><br/>5.5 Conclusion 84<br/><br/>5.6 Future Work 84<br/><br/>References 84<br/><br/>6 IoT Protocol for Inferno Calamity in Public Transport 87<br/>Ravi Babu Devareddi, R. Shiva Shankar and Gadiraju Mahesh<br/><br/>6.1 Introduction 87<br/><br/>6.2 Literature Survey 89<br/><br/>6.3 Methodology 94<br/><br/>6.3.1 IoT Message Exchange With Cloud MQTT Broker Based on MQTT Protocol 98<br/><br/>6.3.2 Hardware Requirement 98<br/><br/>6.4 Implementation 103<br/><br/>6.4.1 Interfacing Diagram 105<br/><br/>6.5 Results 106<br/><br/>6.6 Conclusion and Future Work 108<br/><br/>References 109<br/><br/>7 Traffic Prediction Using Machine Learning and IoT 111<br/>Daksh Pratap Singh and Dolly Sharma<br/><br/>7.1 Introduction 111<br/><br/>7.1.1 Real Time Traffic 111<br/><br/>7.1.2 Traffic Simulation 112<br/><br/>7.2 Literature Review 112<br/><br/>7.3 Methodology 113<br/><br/>7.4 Architecture 116<br/><br/>7.4.1 API Architecture 117<br/><br/>7.4.2 File Structure 117<br/><br/>7.4.3 Simulator Architecture 118<br/><br/>7.4.4 Workflow in Application 122<br/><br/>7.4.5 Workflow of Google APIs in the Application 122<br/><br/>7.5 Results 122<br/><br/>7.5.1 Traffic Scenario 122<br/><br/>7.5.1.1 Low Traffic 124<br/><br/>7.5.1.2 Moderate Traffic 124<br/><br/>7.5.1.3 High Traffic 125<br/><br/>7.5.2 Speed Viewer 125<br/><br/>7.5.3 Traffic Simulator 126<br/><br/>7.5.3.1 1st View 126<br/><br/>7.5.3.2 2nd View 128<br/><br/>7.5.3.3 3rd View 128<br/><br/>7.6 Conclusion and Future Scope 128<br/><br/>References 129<br/><br/>8 Application of Machine Learning in Precision Agriculture 131<br/>Ravi Sharma and Nonita Sharma<br/><br/>8.1 Introduction 131<br/><br/>8.2 Machine Learning 132<br/><br/>8.2.1 Supervised Learning 133<br/><br/>8.2.2 Unsupervised Learning 133<br/><br/>8.2.3 Reinforcement Learning 134<br/><br/>8.3 Agriculture 134<br/><br/>8.4 ML Techniques Used in Agriculture 135<br/><br/>8.4.1 Soil Mapping 135<br/><br/>8.4.2 Seed Selection 140<br/><br/>8.4.3 Irrigation/Water Management 141<br/><br/>8.4.4 Crop Quality 143<br/><br/>8.4.5 Disease Detection 144<br/><br/>8.4.6 Weed Detection 145<br/><br/>8.4.7 Yield Prediction 147<br/><br/>8.5 Conclusion 148<br/><br/>References 149<br/><br/>9 An IoT-Based Multi Access Control and Surveillance for Home Security 153<br/>Yogeshwaran, K., Ramesh, C., Udayakumar, E., Srihari, K. and Sachi Nandan Mohanty<br/><br/>9.1 Introduction 153<br/><br/>9.2 Related Work 155<br/><br/>9.3 Hardware Description 156<br/><br/>9.3.1 Float Sensor 158<br/><br/>9.3.2 Map Matching 158<br/><br/>9.3.3 USART Cable 159<br/><br/>9.4 Software Design 161<br/><br/>9.5 Conclusion 162<br/><br/>References 162<br/><br/>10 Application of IoT in Industry 4.0 for Predictive Analytics 165<br/>Ahin Banerjee, Debanshee Datta and Sanjay K. Gupta<br/><br/>10.1 Introduction 165<br/><br/>10.2 Past Literary Works 168<br/><br/>10.2.1 Maintenance-Based Monitoring 168<br/><br/>10.2.2 Data Driven Approach to RUL Finding in Industry 169<br/><br/>10.2.3 Philosophy of Industrial-IoT Systems and its Advantages in Different Domain 173<br/><br/>10.3 Methodology and Results 176<br/><br/>10.4 Conclusion 179<br/><br/>References 180<br/><br/>11 IoT and Its Role in Performance Enhancement in Business Organizations 183<br/>Seema Sahai, Richa Goel, Parul Bajaj and Gurinder Singh<br/><br/>11.1 Introduction 183<br/><br/>11.1.1 Scientific Issues in IoT 184<br/><br/>11.1.2 IoT in Organizations 185<br/><br/>11.1.3 Technology and Business 187<br/><br/>11.1.4 Rewards of Technology in Business 187<br/><br/>11.1.5 Shortcomings of Technology in Business 188<br/><br/>11.1.6 Effect of IoT on Work and Organization 188<br/><br/>11.2 Technology and Productivity 190<br/><br/>11.3 Technology and Future of Human Work 193<br/><br/>11.4 Technology and Employment 194<br/><br/>11.5 Conclusion 195<br/><br/>References 195<br/><br/>12 An Analysis of Cloud Computing Based on Internet of Things 197<br/>Farhana Ajaz, Mohd Naseem, Ghulfam Ahamad, Sparsh Sharma and Ehtesham Abbasi<br/><br/>12.1 Introduction 197<br/><br/>12.1.1 Generic Architecture 199<br/><br/>12.2 Challenges in IoT 202<br/><br/>12.3 Technologies Used in IoT 203<br/><br/>12.4 Cloud Computing 203<br/><br/>12.4.1 Service Models of Cloud Computing 204<br/><br/>12.5 Cloud Computing Characteristics 205<br/><br/>12.6 Applications of Cloud Computing 206<br/><br/>12.7 Cloud IoT 207<br/><br/>12.8 Necessity for Fusing IoT and Cloud Computing 207<br/><br/>12.9 Cloud-Based IoT Architecture 208<br/><br/>12.10 Applications of Cloud-Based IoT 208<br/><br/>12.11 Conclusion 209<br/><br/>References 209<br/><br/>13 Importance of Fog Computing in Emerging Technologies-IoT 211<br/>Aarti Sahitya<br/><br/>13.1 Introduction 211<br/><br/>13.2 IoT Core 212<br/><br/>13.3 Need of Fog Computing 227<br/><br/>References 230<br/><br/>14 Convergence of Big Data and Cloud Computing Environment 233<br/>Ranjan Ganguli<br/><br/>14.1 Introduction 233<br/><br/>14.2 Big Data: Historical View 234<br/><br/>14.2.1 Big Data: Definition 235<br/><br/>14.2.2 Big Data Classification 236<br/><br/>14.2.3 Big Data Analytics 236<br/><br/>14.3 Big Data Challenges 237<br/><br/>14.4 The Architecture 238<br/><br/>14.4.1 Storage or Collection System 240<br/><br/>14.4.2 Data Care 240<br/><br/>14.4.3 Analysis 240<br/><br/>14.5 Cloud Computing: History in a Nutshell 241<br/><br/>14.5.1 View on Cloud Computing and Big Data 241<br/><br/>14.6 Insight of Big Data and Cloud Computing 241<br/><br/>14.6.1 Cloud-Based Services 242<br/><br/>14.6.2 At a Glance: Cloud Services 244<br/><br/>14.7 Cloud Framework 245<br/><br/>14.7.1 Hadoop 245<br/><br/>14.7.2 Cassandra 246<br/><br/>14.7.2.1 Features of Cassandra 246<br/><br/>14.7.3 Voldemort 247<br/><br/>14.7.3.1 A Comparison With Relational Databases and Benefits 247<br/><br/>14.8 Conclusions 248<br/><br/>14.9 Future Perspective 248<br/><br/>References 248<br/><br/>15 Data Analytics Framework Based on Cloud Environment 251<br/>K. Kanagaraj and S. Geetha<br/><br/>15.1 Introduction 251<br/><br/>15.2 Focus Areas of the Chapter 252<br/><br/>15.3 Cloud Computing 252<br/><br/>15.3.1 Cloud Service Models 253<br/><br/>15.3.1.1 Software as a Service (SaaS) 253<br/><br/>15.3.1.2 Platform as a Service (PaaS) 254<br/><br/>15.3.1.3 Infrastructure as a Service (IaaS) 255<br/><br/>15.3.1.4 Desktop as a Service (DaaS) 256<br/><br/>15.3.1.5 Analytics as a Service (AaaS) 257<br/><br/>15.3.1.6 Artificial Intelligence as a Service (AIaaS) 258<br/><br/>15.3.2 Cloud Deployment Models 259<br/><br/>15.3.3 Virtualization of Resources 260<br/><br/>15.3.4 Cloud Data Centers 261<br/><br/>15.4 Data Analytics 263<br/><br/>15.4.1 Data Analytics Types 263<br/><br/>15.4.1.1 Descriptive Analytics 263<br/><br/>15.4.1.2 Diagnostic Analytics 264<br/><br/>15.4.1.3 Predictive Analytics 265<br/><br/>15.4.1.4 Prescriptive Analytics 265<br/><br/>15.4.1.5 Big Data Analytics 265<br/><br/>15.4.1.6 Augmented Analytics 266<br/><br/>15.4.1.7 Cloud Analytics 266<br/><br/>15.4.1.8 Streaming Analytics 266<br/><br/>15.4.2 Data Analytics Tools 266<br/><br/>15.5 Real-Time Data Analytics Support in Cloud 266<br/><br/>15.6 Framework for Data Analytics in Cloud 268<br/><br/>15.6.1 Data Analysis Software as a Service (DASaaS) 268<br/><br/>15.6.2 Data Analysis Platform as a Service (DAPaaS) 268<br/><br/>15.6.3 Data Analysis Infrastructure as a Service (DAIaaS) 269<br/><br/>15.7 Data Analytics Work-Flow 269<br/><br/>15.8 Cloud-Based Data Analytics Tools 270<br/><br/>15.8.1 Amazon Kinesis Services 271<br/><br/>15.8.2 Amazon Kinesis Data Firehose 271<br/><br/>15.8.3 Amazon Kinesis Data Streams 271<br/><br/>15.8.4 Amazon Textract 271<br/><br/>15.8.5 Azure Stream Analytics 271<br/><br/>15.9 Experiment Results 272<br/><br/>15.10 Conclusion 272<br/><br/>References 274<br/><br/>16 Neural Networks for Big Data Analytics 277<br/>Bithika Bishesh<br/><br/>16.1 Introduction 277<br/><br/>16.2 Neural Networks—An Overview 278<br/><br/>16.3 Why Study Neural Networks? 279<br/><br/>16.4 Working of Artificial Neural Networks 279<br/><br/>16.4.1 Single-Layer Perceptron 279<br/><br/>16.4.2 Multi-Layer Perceptron 280<br/><br/>16.4.3 Training a Neural Network 281<br/><br/>16.4.4 Gradient Descent Algorithm 282<br/><br/>16.4.5 Activation Functions 284<br/><br/>16.5 Innovations in Neural Networks 288<br/><br/>16.5.1 Convolutional Neural Network (ConvNet) 288<br/><br/>16.5.2 Recurrent Neural Network 289<br/><br/>16.5.3 LSTM 291<br/><br/>16.6 Applications of Deep Learning Neural Networks 292<br/><br/>16.7 Practical Application of Neural Networks Using Computer Codes 293<br/><br/>16.8 Opportunities and Challenges of Using Neural Networks 293<br/><br/>16.9 Conclusion 296<br/><br/>References 296<br/><br/>17 Meta-Heuristic Algorithms for Best IoT Cloud Service Platform Selection 299<br/>Sudhansu Shekhar Patra, Sudarson Jena, G.B. Mund, Mahendra Kumar Gourisaria and Jugal Kishor Gupta<br/><br/>17.1 Introduction 299<br/><br/>17.2 Selection of a Cloud Provider in Federated Cloud 301<br/><br/>17.3 Algorithmic Solution 307<br/><br/>17.3.1 TLBO Algorithm (Teaching-Learning-Based Optimization Algorithm) 307<br/><br/>17.3.1.1 Teacher Phase: Generation of a New Solution 308<br/><br/>17.3.1.2 Learner Phase: Generation of New Solution 309<br/><br/>17.3.1.3 Representation of the Solution 309<br/><br/>17.3.2 JAYA Algorithm 309<br/><br/>17.3.2.1 Representation of the Solution 311<br/><br/>17.3.3 Bird Swarm Algorithm 311<br/><br/>17.3.3.1 Forging Behavior 313<br/><br/>17.3.3.2 Vigilance Behavior 313<br/><br/>17.3.3.3 Flight Behavior 313<br/><br/>17.3.3.4 Representation of the Solution 313<br/><br/>17.4 Analyzing the Algorithms 314<br/><br/>17.5 Conclusion 316<br/><br/>References 316<br/><br/>18 Legal Entanglements of Cloud Computing In India 319<br/>Sambhabi Patnaik and Lipsa Dash<br/><br/>18.1 Cloud Computing Technology 319<br/><br/>18.2 Cyber Security in Cloud Computing 322<br/><br/>18.3 Security Threats in Cloud Computing 323<br/><br/>18.3.1 Data Breaches 323<br/><br/>18.3.2 Denial of Service (DoS) 323<br/><br/>18.3.3 Botnets 323<br/><br/>18.3.4 Crypto Jacking 324<br/><br/>18.3.5 Insider Threats 324<br/><br/>18.3.6 Hijacking Accounts 324<br/><br/>18.3.7 Insecure Applications 324<br/><br/>18.3.8 Inadequate Training 325<br/><br/>18.3.9 General Vulnerabilities 325<br/><br/>18.4 Cloud Security Probable Solutions 325<br/><br/>18.4.1 Appropriate Cloud Model for Business 325<br/><br/>18.4.2 Dedicated Security Policies Plan 325<br/><br/>18.4.3 Multifactor Authentication 325<br/><br/>18.4.4 Data Accessibility 326<br/><br/>18.4.5 Secure Data Destruction 326<br/><br/>18.4.6 Encryption of Backups 326<br/><br/>18.4.7 Regulatory Compliance 326<br/><br/>18.4.8 External Third-Party Contracts and Agreements 327<br/><br/>18.5 Cloud Security Standards 327<br/><br/>18.6 Cyber Security Legal Framework in India 327<br/><br/>18.7 Privacy in Cloud Computing—Data Protection Standards 329<br/><br/>18.8 Recognition of Right to Privacy 330<br/><br/>18.9 Government Surveillance Power vs Privacy of Individuals 332<br/><br/>18.10 Data Ownership and Intellectual Property Rights 333<br/><br/>18.11 Cloud Service Provider as an Intermediary 335<br/><br/>18.12 Challenges in Cloud Computing 337<br/><br/>18.12.1 Classification of Data 337<br/><br/>18.12.2 Jurisdictional Issues 337<br/><br/>18.12.3 Interoperability of the Cloud 338<br/><br/>18.12.4 Vendor Agreements 339<br/><br/>18.13 Conclusion 339<br/><br/>References 341<br/><br/>19 Securing the Pharma Supply Chain Using Blockchain 343<br/>Pulkit Arora, Chetna Sachdeva and Dolly Sharma<br/><br/>19.1 Introduction 343<br/><br/>19.2 Literature Review 345<br/><br/>19.2.1 Current Scenario 346<br/><br/>19.2.2 Proposal 347<br/><br/>19.3 Methodology 349<br/><br/>19.4 Results 354<br/><br/>19.5 Conclusion and Future Scope 358<br/><br/>References 358<br/><br/>Index 361<br/><br/> |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
"The book aims to integrate the aspects of IoT, Cloud computing and data analytics from diversified perspectives. The book also plans to discuss the recent research trends and advanced topics in the field which will be of interest to academicians and researchers working in this area. Thus, the book intends to help its readers to understand and explore the spectrum of applications of IoT, cloud computing and data analytics. Here, it is also worth mentioning that the book is believed to draw attention on the applications of said technology in various disciplines in order to obtain enhanced understanding of the readers. Also, this book focuses on the researches and challenges in the domain of IoT, Cloud computing and Data analytics from perspectives of various stakeholders."-- |
| Assigning source |
Provided by publisher. |
| 588 ## - SOURCE OF DESCRIPTION NOTE |
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| Source of description note |
Description based on print version record and CIP data provided by publisher; resource not viewed. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Cloud computing. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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Internet of things. |
| 655 #0 - INDEX TERM--GENRE/FORM |
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Electronic books. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Mangla, Monika, |
| Relator term |
editor. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Satpathy, Suneeta, |
| Relator term |
editor. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Nayak, Bhagirathi, |
| Dates associated with a name |
1963- |
| Relator term |
editor. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Mohanty, Sachi Nandan, |
| Relator term |
editor. |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
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| Link text |
Full text is available at Wiley Online Library Click here to view |
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https://onlinelibrary.wiley.com/doi/book/10.1002/9781119769323 |
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EBOOK |