Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithms -

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Résumé :

Preface xv

1 Cognitive Behavior: Different Human-Computer Interaction Types 1
S. Venkata Achyuth Rao, Sandeep Kumar and GVRK Acharyulu

1.1 Introduction: Cognitive Models and Human-Computer User Interface Management Systems 2

1.1.1 Interactive User Behavior Predicting Systems 2

1.1.2 Adaptive Interaction Observatory Changing Systems 3

1.1.3 Group Interaction Model Building Systems 4

1.1.4 Human-Computer User Interface Management Systems 5

1.1.5 Different Types of Human-Computer User Interfaces 5

1.1.6 The Role of User Interface Management Systems 6

1.1.7 Basic Cognitive Behavioral Elements of Human- Computer User Interface Management Systems 7

1.2 Cognitive Modeling: Decision Processing User Interacting Device System (DPUIDS) 9

1.2.1 Cognitive Modeling Automation of Decision Process Interactive Device Example 9

1.2.2 Cognitive Modeling Process in the Visualization Decision Processing User Interactive Device System 11

1.3 Cognitive Modeling: Decision Support User Interactive Device Systems (DSUIDS) 12

1.3.1 The Core Artifacts of the Cognitive Modeling of User Interaction 13

1.3.2 Supporting Cognitive Model for Interaction Decision Supportive Mechanism 13

1.3.3 Representational Uses of Cognitive Modeling for Decision Support User Interactive Device Systems 14

1.4 Cognitive Modeling: Management Information User Interactive Device System (MIUIDS) 17

1.5 Cognitive Modeling: Environment Role With User Interactive Device Systems 19

1.6 Conclusion and Scope 20

References 20

2 Classification of HCI and Issues and Challenges in Smart Home HCI Implementation 23
Pramod Vishwakarma, Vijay Kumar Soni, Gaurav Srivastav and Abhishek Jain

2.1 Introduction 23

2.2 Literature Review of Human-Computer Interfaces 26

2.2.1 Overview of Communication Styles and Interfaces 33

2.2.2 Input/Output 37

2.2.3 Older Grown-Ups 37

2.2.4 Cognitive Incapacities 38

2.3 Programming: Convenience and Gadget Explicit Substance 40

2.4 Equipment: BCI and Proxemic Associations 41

2.4.1 Brain-Computer Interfaces 41

2.4.2 Ubiquitous Figuring-Proxemic Cooperations 43

2.4.3 Other Gadget-Related Angles 44

2.5 CHI for Current Smart Homes 45

2.5.1 Smart Home for Healthcare 45

2.5.2 Savvy Home for Energy Efficiency 46

2.5.3 Interface Design and Human-Computer Interaction 46

2.5.4 A Summary of Status 48

2.6 Four Approaches to Improve HCI and UX 48

2.6.1 Productive General Control Panel 49

2.6.2 Compelling User Interface 50

2.6.3 Variable Accessibility 52

2.6.4 Secure Privacy 54

2.7 Conclusion and Discussion 55

References 56

3 Teaching-Learning Process and Brain-Computer Interaction Using ICT Tools 63
Rohit Raja, Neelam Sahu and Sumati Pathak

3.1 The Concept of Teaching 64

3.2 The Concept of Learning 65

3.2.1 Deficient Visual Perception in a Student 67

3.2.2 Proper Eye Care (Vision Management) 68

3.2.3 Proper Ear Care (Hearing Management) 68

3.2.4 Proper Mind Care (Psychological Management) 69

3.3 The Concept of Teaching-Learning Process 70

3.4 Use of ICT Tools in Teaching-Learning Process 76

3.4.1 Digital Resources as ICT Tools 77

3.4.2 Special ICT Tools for Capacity Building of Students and Teachers 77

3.4.2.1 CogniFit 77

3.4.2.2 Brain-Computer Interface 78

3.5 Conclusion 80

References 81

4 Denoising of Digital Images Using Wavelet-Based Thresholding Techniques: A Comparison 85
Devanand Bhonsle...

Biographie:

Sandeep Kumar, PhD is a Professor in the Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India. He has published more than 100 research papers in various international/national journals and 6 patents. He has been awarded the Best Excellence Award in New Delhi, 2019.

Rohit Raja, PhD is an associate professor in the IT Department at the Guru Ghasidas, Vishwavidyalaya, Bilaspur (Central University-CG). He gained his PhD in Computer Science and Engineering in 2016 from C. V. Raman University India. He has filed successfully 10 (9 national + 1 international) patents and published more than 80 research papers in various international/national journals.

Shrikant Tiwari, PhD is an assistant professor in the Department of Computer Science & Engineering (CSE) at Shri Shankaracharya Technical Campus, Junwani, Bhilai, Distt. Chattisgarh, India. He received his PhD from the Department of Computer Science & Engineering (CSE) from the Indian Institute of Technology (Banaras Hindu University), Varanasi (India) in 2012.

Shilpa Rani, PhD is an assistant professor in the Department of Computer Science & Engineering, Neil Gogte Institute of Technology, Hyderabad, India....

Sommaire:
COGNITIVE BEHAVIOR AND HUMAN COMPUTER INTERACTION BASED ON MACHINE LEARNING ALGORITHMS

The objective of this book is to provide the most relevant information on Human-Computer Interaction to academics, researchers, and students and for those from industry who wish to know more about the real-time application of user interface design.

Human-computer interaction (HCI) is the academic discipline, which most of us think of as UI design, that focuses on how human beings and computers interact at ever-increasing levels of both complexity and simplicity. Because of the importance of the subject, this book aims to provide more relevant information that will be useful to students, academics, and researchers in the industry who wish to know more about its real-time application. In addition to providing content on theory, cognition, design, evaluation, and user diversity, this book also explains the underlying causes of the cognitive, social and organizational problems typically devoted to descriptions of rehabilitation methods for specific cognitive processes. Also described are the new modeling algorithms accessible to cognitive scientists from a variety of different areas.

This book is inherently interdisciplinary and contains original research in computing, engineering, artificial intelligence, psychology, linguistics, and social and system organization as applied to the design, implementation, application, analysis, and evaluation of interactive systems. Since machine learning research has already been carried out for a decade in various applications, the new learning approach is mainly used in machine learning-based cognitive applications. Since this will direct the future research of scientists and researchers working in neuroscience, neuroimaging, machine learning-based brain mapping, and modeling, etc., this book highlights the framework of a novel robust method for advanced cross-industry HCI technologies. These implementation strategies and future research directions will meet the design and application requirements of several modern and real-time applications for a long time to come.

Audience: A wide range of researchers, industry practitioners, and students will be interested in this book including those in artificial intelligence, machine learning, cognition, computer programming and engineering, as well as social sciences such as psychology and linguistics....