This new volume, Cognitive Computing Systems: Applications and Technological Advancements, explores the emerging area of artificial intelligence that encompasses machine self-learning, human-computer interaction, natural language processing, data mining and more. It introduces cognitive computing systems, highlights their key applications, discusses the technologies used in cognitive systems, and explains underlying models and architectures.
Focusing on scientific work for real-world applications, each chapter presents the use of cognitive computing and machine learning in specific application areas. These include the use of speech recognition technology, application of neural networks in construction management, elevating competency in education, comprehensive health monitoring systems, predicting type 2 diabetes, applications for smart agricultural technology, human resource management, and more.
With chapters from knowledgeable researchers in the area of artificial intelligence, cognitive computing, and allied areas, this book will be an asset for researchers, faculty, advances students, and industry professionals in many fields.
| Contributors |
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ix | |
| Abbreviations |
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xi | |
| Preface |
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xv | |
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PART I Using Assistive Learning to Solve Computationally Intense Problems |
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1 | (190) |
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1 High-Frequency Stochastic Data Analysis Using a Machine Learning Framework: A Comparative Study |
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3 | (30) |
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2 Cognitive Machine Learning Framework to Evaluate Competency during the Course Endorsement for Computer Science Postgraduates |
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33 | (30) |
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3 Cognitive Decision-Making through an Intelligent Database Agent for Predictive Analysis |
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63 | (34) |
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4 A Convergence of Mining and Machine Learning: The New Angle for Educational Data Mining |
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97 | (22) |
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5 ApnaDermato: Human Skin Disease Finder Using Machine Learning |
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119 | (36) |
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6 Artificial Intelligence Technique for Predicting Type 2 Diabetes |
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155 | (36) |
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PART II Designing IoT-Based Smart Solutions for Monitoring and Surveillance |
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191 | (42) |
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7 Smart Interfaces for Development of Comprehensive Health Monitoring Systems |
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193 | (26) |
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8 IoT-Based Smart Agriculture in India |
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219 | (14) |
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PART III Statistical and Mathematical Model-Based Solutions |
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233 | (32) |
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9 Analysis of Epidemiology: Integrating Computational Models |
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235 | (30) |
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PART IV Applying Neural Networks and Deep Learning Models for Cognitive Problems |
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265 | (60) |
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10 Recent Issues with Machine Vision Applications for Deep Network Architectures |
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267 | (18) |
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11 Applications of Backpropagation and Conjugate Gradient Neural Networks in Structural Engineering |
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285 | (20) |
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Kirthanashri S. Vasanthan |
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12 Application of Neural Networks in Construction Management |
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305 | (20) |
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Kirthanashri S. Vasanthan |
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PART V Speech and NLP Applications in Cognition |
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325 | (76) |
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13 Speech Recognition Fundamentals and Features |
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327 | (22) |
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14 Natural Language Processing |
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349 | (52) |
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| Index |
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401 | |
Vishal Jain, PhD, is an Associate Professor with Bharati Vidyapeeths Institute of Computer Applications and Management (BVICAM), New Delhi, India (affiliated with Guru Gobind Singh Indraprastha University, and accredited by the All India Council for Technical Education).
Akash Tayal, PhD, is an Assistant Professor of the Department of Electronics and Communication at the Indira Gandhi Delhi Technical University for Women, Delhi, India.
Jaspreet Singh, PhD, is an Associate Professor in the Department of Computer Science, School of Engineering, GD Goenka University, Gurgaon, India.
Arun Solanki, PhD, is an Assistant Professor in the Department of Computer Science and Engineering, Gautam Buddha University, Greater Noida, India, where he has also held various additional roles over the years.
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