User Centered Design for Medical Visualization features a comprehensive review of leading advances in medical visualization and human-computer interaction. This book investigates the human roles during a visualization process, specifically motivation-based design, user-based design, and perception-and-cognitive-based design. An essential resource for researchers, scholars, healthcare practitioners, and medical technology specialists, ""User Centered Design for Medical Visualization"" provides real-world examples and insight into the analytical and architectural aspects of user centered design.

Provides a synopsis of the various technologies in perceptual-based multimedia design.

This book aimed at bringing an insight to the ICN network, particularly various architectures, issues and challenges in the new networking paradigm. The book starts with an introduction to the new promising concept of ICN and its origin along with the reason behind this interesting innovation. Different architectures proposed so far in support of implementing the ICN is also discussed in details. Few of the challenges of ICN implementation are enlisted as caching, naming, routing, and security. Each of these challenges with recent development is covered in individual chapters. Moreover, integration of current trends in communication and computing like software defined networking and machine learning approach are another area that this book is focusing. All these chapters highlight the recent developments reported in the area and also discusses the future trends. The book provides an overview of the recent developments in future internet technologies, bringing together the advancements that have been made in ICN. The book includes three unique chapters in the field of ICN research. The first, is the SDN framework for implementing ICN by decoupling data and control plan. The machine learning models for predicting future trends in network traffic and other management activities is another important chapter. This chapter includes the possibilities of using machine learning models for trend prediction to help network administrators and service providers to take care of unexpected sudden change traffic pattern and user behaviour. The third most vital chapter is the security issues in ICN. This chapter includes various facts that influences the security of ICN. Issues involved in naming, caching and routing are discussed separately along with few recent works in these areas. Various types of attacks in ICN are also part of the discussion. The stated book would be useful for researchers in this area and will work as a reference for future work. Moreover, the content of the book would also be suitable as a supporting material for undergraduate and graduate level courses in computer science and electrical engineering.

This book presents original, peer-reviewed select articles from the International Conference on Cognitive & Intelligent Computing (ICCIC - 2021), held on December 11-12, 2021, at Hyderabad, India. The proceedings has cutting edge Research outcome related to Machine learning in control applications, Soft computing, Pattern Recognition, Decision Support Systems, Text analytics and NLP, Statistical Learning, Neural Network Learning, Learning Through Fuzzy Logic, Learning Through Evolution (Evolutionary Algorithms), Reinforcement Learning, Multi-Strategy Learning, Cooperative Learning, Planning And Learning, Multi-Agent Learning, Online And Incremental Learning, Scalability Of Learning Algorithms, Inductive Learning, Inductive Logic Programming, Bayesian Networks, Support Vector Machines, Case-Based Reasoning, Multi-Agent Systems, Human-Computer Interaction, Data Mining and Knowledge Discovery, Knowledge Management and Networks, Data Intensive Computing Architecture, Medicine, Health, Bioinformatics, and Systems Biology, Industrial and Engineering Applications, Security Applications, Smart Cities, Game Playing and Problem Solving, Intelligent Virtual Environments, Economics, Business, And Forecasting Applications. Articles in the book are carefully selected on the basis of their application orientation. The content is expected to be especially useful for Professionals, Researchers, Research students working in the area of cognitive and intelligent computing.

The book IoT and Big Data Analytics (IoT-BDA) for Smart Cities - A Global Perspective, emphasizes the challenges, architectural models, and intelligent frameworks with smart decisionmaking systems using Big Data and IoT with case studies. The book illustrates the benefits of Big Data and IoT methods in framing smart systems for smart applications. The text is a coordinated amalgamation of research contributions and industrial applications in the field of smart cities. Features: Provides the necessity of convergence of Big Data Analytics and IoT techniques in smart city application Challenges and Roles of IoT and Big Data in Smart City applications Provides Big Data-IoT intelligent smart systems in a global perspective Provides a predictive framework that can handle the traffic on abnormal days, such as weekends and festival holidays Gives various solutions and ideas for smart traffic development in smart cities Gives a brief idea of the available algorithms/techniques of Big Data and IoT and guides in developing a solution for smart city applications This book is primarily aimed at IT professionals. Undergraduates, graduates, and researchers in the area of computer science and information technology will also find this book useful.

This book aimed at bringing an insight to the ICN network, particularly various architectures, issues and challenges in the new networking paradigm. The book starts with an introduction to the new promising concept of ICN and its origin along with the reason behind this interesting innovation. Different architectures proposed so far in support of implementing the ICN is also discussed in details. Few of the challenges of ICN implementation are enlisted as caching, naming, routing, and security. Each of these challenges with recent development is covered in individual chapters. Moreover, integration of current trends in communication and computing like software defined networking and machine learning approach are another area that this book is focusing. All these chapters highlight the recent developments reported in the area and also discusses the future trends. The book provides an overview of the recent developments in future internet technologies, bringing together the advancements that have been made in ICN. The book includes three unique chapters in the field of ICN research. The first, is the SDN framework for implementing ICN by decoupling data and control plan. The machine learning models for predicting future trends in network traffic and other management activities is another important chapter. This chapter includes the possibilities of using machine learning models for trend prediction to help network administrators and service providers to take care of unexpected sudden change traffic pattern and user behaviour. The third most vital chapter is the security issues in ICN. This chapter includes various facts that influences the security of ICN. Issues involved in naming, caching and routing are discussed separately along with few recent works in these areas. Various types of attacks in ICN are also part of the discussion. The stated book would be useful for researchers in this area and will work as a reference for future work. Moreover, the content of the book would also be suitable as a supporting material for undergraduate and graduate level courses in computer science and electrical engineering.

This book presents original, peer-reviewed select articles from the International Conference on Cognitive & Intelligent Computing (ICCIC - 2021), held on December 11-12, 2021, at Hyderabad, India. The proceedings has cutting edge Research outcome related to Machine learning in control applications, Soft computing, Pattern Recognition, Decision Support Systems, Text analytics and NLP, Statistical Learning, Neural Network Learning, Learning Through Fuzzy Logic, Learning Through Evolution (Evolutionary Algorithms), Reinforcement Learning, Multi-Strategy Learning, Cooperative Learning, Planning And Learning, Multi-Agent Learning, Online And Incremental Learning, Scalability Of Learning Algorithms, Inductive Learning, Inductive Logic Programming, Bayesian Networks, Support Vector Machines, Case-Based Reasoning, Multi-Agent Systems, Human-Computer Interaction, Data Mining and Knowledge Discovery, Knowledge Management and Networks, Data Intensive Computing Architecture, Medicine, Health, Bioinformatics, and Systems Biology, Industrial and Engineering Applications, Security Applications, Smart Cities, Game Playing and Problem Solving, Intelligent Virtual Environments, Economics, Business, And Forecasting Applications. Articles in the book are carefully selected on the basis of their application orientation. The content is expected to be especially useful for Professionals, Researchers, Research students working in the area of cognitive and intelligent computing.