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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 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.
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.
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.
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