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This text discusses the applications and optimization of emerging
smart technologies in the field of healthcare. It further explains
different modeling scenarios of the latest technologies in the
health care system and compare the results to better understand the
nature and progress of the disease in the human body that leads to
early diagnosis and better cure of disease and treatment with the
help of distributed technology. Covers the implementation models
using technologies such as artificial intelligence, machine
learning, deep learning with distributed systems for better
diagnosis and treatment of diseases. Gives in-depth review of the
technological advancements like advanced sensing technologies like
Plasmonic sensors, usage of RFIDs and electronic diagnostic tools
in the field of healthcare engineering Discusses possibilities of
augmented reality and virtual reality interventions for providing
unique solutions in medical science, clinical research, psychology,
and neurological disorders Highlights the future challenges and
risks involved in the application of smart technologies like Cloud
computing, fog computing, IOT and distributed computing in
heathcare. Confers to utilize the AI and ML and associated aids in
healthcare sectors in the post Covid 19 to revitalize the medical
set up Contributions included in the book will motivate the
technological developers and researchers to develop new algorithms
and protocols in healthcare field. It will serve as the vast place
for knowledge regarding healthcare health care delivery, health
care management, health care in governance, and health monitoring
approaches using distributed environments. It will serve as an
ideal reference text for graduate students and researchers in
diverse engineering fields including electrical, electronics and
communication, computer, and biomedical.
This book embodies principles and applications of advanced soft
computing approaches in engineering, healthcare and allied domains
directed toward the researchers aspiring to learn and apply
intelligent data analytics techniques. The first part covers AI,
machine learning and data analytics tools and techniques and their
applications to the class of several hospital and health real-life
problems. In the later part, the applications of AI, ML and data
analytics shall be covered over the wide variety of applications in
hospital, health, engineering and/or applied sciences such as the
clinical services, medical image analysis, management support,
quality analysis, bioinformatics, device analysis and operations.
The book presents knowledge of experts in the form of chapters with
the objective to introduce the theme of intelligent data analytics
and discusses associated theoretical applications. At last, it
presents simulation codes for the problems included in the book for
better understanding for beginners.
This book embodies principles and applications of advanced soft
computing approaches in engineering, healthcare and allied domains
directed toward the researchers aspiring to learn and apply
intelligent data analytics techniques. The first part covers AI,
machine learning and data analytics tools and techniques and their
applications to the class of several hospital and health real-life
problems. In the later part, the applications of AI, ML and data
analytics shall be covered over the wide variety of applications in
hospital, health, engineering and/or applied sciences such as the
clinical services, medical image analysis, management support,
quality analysis, bioinformatics, device analysis and operations.
The book presents knowledge of experts in the form of chapters with
the objective to introduce the theme of intelligent data analytics
and discusses associated theoretical applications. At last, it
presents simulation codes for the problems included in the book for
better understanding for beginners.
This book covers the design, construction, and implementation of
algebraic-geometric codes from Hermitian curves. Matlab simulations
of algebraic-geometric codes and Reed-Solomon codes compare their
bit error rate using different modulation schemes over additive
white Gaussian noise channel model. Simulation results of
Algebraic-geometric codes bit error rate performance using
quadrature amplitude modulation (16QAM and 64QAM) are presented for
the first time and shown to outperform Reed-Solomon codes at
various code rates and channel models. The book proposes
algebraic-geometric block turbo codes. It also presents simulation
results that show an improved bit error rate performance at the
cost of high system complexity due to using algebraic-geometric
codes and Chase-Pyndiah's algorithm simultaneously. The book
proposes algebraic-geometric irregular block turbo codes (AG-IBTC)
to reduce system complexity. Simulation results for AG-IBTCs are
presented for the first time.
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