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Though an individual can process a limitless amount of information,
the human brain can only comprehend a small amount of data at a
time. Using technology can improve the process and comprehension of
information, but the technology must learn to behave more like a
human brain to employ concepts like memory, learning, visualization
ability, and decision making. Emerging Trends and Applications in
Cognitive Computing is a fundamental scholarly source that provides
empirical studies and theoretical analysis to show how learning
methods can solve important application problems throughout various
industries and explain how machine learning research is conducted.
Including innovative research on topics such as deep neural
networks, cyber-physical systems, and pattern recognition, this
collection of research will benefit individuals such as IT
professionals, academicians, students, researchers, and managers.
This book focuses on various advanced technologies which integrate
with machine learning to assist one of the most leading industries,
healthcare. It presents recent research works based on machine
learning approaches supported by medical and information
communication technologies with the use of data and image analysis.
The book presents insight about techniques which broadly deals in
delivery of quality, accurate and affordable healthcare solutions
by predictive, proactive and preventative methods. The book also
explores the possible use of machine learning in enterprises, such
as enhanced medical imaging/diagnostics, understanding medical
data, drug discovery and development, robotic surgery and
automation, radiation treatments, creating electronic smart records
and outbreak prediction.
The book presents advanced AI based technologies in dealing with
COVID-19 outbreak and provides an in-depth analysis of variety of
COVID-19 datasets throughout globe. It discusses recent artificial
intelligence based algorithms and models for data analysis of
COVID-19 symptoms and its possible remedies. It provides a unique
opportunity to present the work on state-of-the-art of modern
artificial intelligence tools and technologies to track and
forecast COVID-19 cases. It indicates insights and viewpoints from
scholars regarding risk and resilience analytics for policy making
and operations of large-scale systems on this epidemic. A snapshot
of the latest architectures, frameworks in machine learning and
data science are also highlighted to gather and aggregate data
records related to COVID-19 and to diagnose the virus. It delivers
significant research outcomes and inspiring new real-world
applications with respect to feasible AI based solutions in
COVID-19 outbreak. In addition, it discusses strong preventive
measures to control such pandemic.
This book provides a comprehensive and balanced description of
learning and teaching by connecting it to secondary and higher
education teachers' experiences and practices in day-to-day life.
Woven around research conducted by educationists, psychologists,
and practitioners around the globe, this book presents key concepts
and addresses significant discussions and concerns with regard to
learning and teaching in the present age. Seeking to help teachers
understand learners' learning needs, preferences, and styles and
manage their teaching plans, priorities, and practices accordingly,
it details the main ideas and emerging practices related to
learning and teaching in a very easy to 'read, understand, and
practice' way. The first five chapters approach learning from
different perspectives, while the next six explain in detail how to
practice teaching to maximize learning outcomes. Combining the
traditional textbook-style approach of content description with a
self-learning approach based on various real-world situations and
activities related to both learning and teaching, this textbook is
particularly valuable for teachers in school education, higher
education, and teacher education. This book is also an essential
resource for fulfilling teachers' continuing professional
development requirements. Although intended for teachers worldwide,
the book especially helps teachers in South Asian countries to
improve learning outcomes in their classrooms and, subsequently,
the quality of their education systems.
This book features selected papers presented at the 3rd
International Conference on Recent Innovations in Computing (ICRIC
2020), held on 20-21 March 2020 at the Central University of Jammu,
India, and organized by the university's Department of Computer
Science & Information Technology. It includes the latest
research in the areas of software engineering, cloud computing,
computer networks and Internet technologies, artificial
intelligence, information security, database and distributed
computing, and digital India.
This book comprises select proceedings of the international
conference ETAEERE 2020. This volume covers latest research in
advanced approaches in automation, control based devices, and
adaptive learning mechanisms. The contents discuss the complex
operations and behaviors of different systems or machines in
different environments. Some of the areas covered include control
of linear and nonlinear systems, intelligent systems, stochastic
control, knowledge-based systems applications, fault diagnosis and
tolerant control, and real-time control applications. The contents
of this volume can be useful for researchers as well as
professionals working in control and automation.
By applying data analytics techniques and machine learning
algorithms to predict disease, medical practitioners can more
accurately diagnose and treat patients. However, researchers face
problems in identifying suitable algorithms for pre-processing,
transformations, and the integration of clinical data in a single
module, as well as seeking different ways to build and evaluate
models. The Handbook of Research on Disease Prediction Through Data
Analytics and Machine Learning is a pivotal reference source that
explores the application of algorithms to making disease
predictions through the identification of symptoms and information
retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a
wide range of topics including clinical decision support systems,
biomedical image analysis, and prediction models, this book is
ideally designed for clinicians, physicians, programmers, computer
engineers, IT specialists, data analysts, hospital administrators,
researchers, academicians, and graduate and post-graduate students.
Sequential data from Web server logs, online transaction logs, and
performance measurements is collected each day. This sequential
data is a valuable source of information, as it allows individuals
to search for a particular value or event and also facilitates
analysis of the frequency of certain events or sets of related
events. Finding patterns in sequences is of utmost importance in
many areas of science, engineering, and business scenarios. Pattern
Discovery Using Sequence Data Mining: Applications and Studies
provides a comprehensive view of sequence mining techniques and
presents current research and case studies in pattern discovery in
sequential data by researchers and practitioners. This research
identifies industry applications introduced by various sequence
mining approaches.
This book provides an up-to-date review of fasciolosis, a disease
caused by Fasciola hepatica and Fasciola gigantica, including its
biology, transmission, epidemiology, host distribution, economic
impact, and novel approaches for its diagnosis, treatment and
prevention. It first offers a brief overview of the history of the
disease, the genetic diversity of the parasite and its
distribution, and the ecology of the vector snail, which belongs to
the Lymnaeidae/Planorbidae family. It also examines the current
strategies and novel approaches for controlling the parasite,
diagnosing infections and vaccine development. Importantly, it
highlights issues relating to the control of fasciolosis, including
drug resistance, lack of effective diagnostics, and the parasite's
long-term survival strategies based on regulation and modulation of
the host immune system. Lastly, it discusses the novel control
snail vectors using bait formulations, and synergetic and
phototherapy treatment with chlorophyllin, which does not kill the
vector.
This book presents high-quality, original contributions (both
theoretical and experimental) on Information Security, Machine
Learning, Data Mining and Internet of Things (IoT). It gathers
papers presented at ICETIT 2019, the 1st International Conference
on Emerging Trends in Information Technology, which was held in
Delhi, India, in June 2019. This conference series represents a
targeted response to the growing need for research that reports on
and assesses the practical implications of IoT and network
technologies, AI and machine learning, data analytics and cloud
computing, security and privacy, and next generation computing
technologies.
This book comprises select proceedings of the international
conference ETAEERE 2020, and covers latest research in the areas of
electronics, communication and computing. The book includes
different approaches and techniques for specific applications using
particle swarm optimization, Otsu's function and harmony search
optimization algorithm, DNA-NAND gate, triple gate SOI MOSFET,
micro-Raman and FTIR analysis, high-k dielectric gate oxide,
spectrum sensing in cognitive radio, microstrip antenna, GPR with
conducting surfaces, energy efficient packet routing, iBGP route
reflectors, circularly polarized antenna, double fork shaped patch
radiator, implementation of Doppler radar at 24 GHz, iris image
classification using SVM, digital image forgery detection, secure
communication, spoken dialog system, and DFT-DCT spreading
strategies. Given the range of topics covered, this book can be
useful for both students and researchers working in electronics and
communication.
The current trend of learner centeredness in education has been
challenging many of the current ways of working, especially in
higher education institutions. This rapid change in educational
institutions demands educators acquire new sets of skills via
continuous reflective practices. Hence, educators in higher
education institutions are actively involved in research-driven
teaching and learning practices. This change of role from mere
content delivery to learning facilitators could be better achieved
through a strong research-driven community of practice. Preparing
21st Century Teachers for Teach Less, Learn More (TLLM) Pedagogies
is a pivotal reference source that provides vital research on the
application of practice-based learning techniques in higher
education institutions. This publication establishes a platform for
academics to share their best practices to promote teach less,
learn more pedagogies and learn reciprocally from the community of
practice. While highlighting topics such as interactive learning,
experiential technology, and logical thinking skills, this book is
ideally designed for teachers, instructional designers, higher
education faculty, deans, researchers, professionals, universities,
academicians, and students seeking current research on
transformative learning and future teaching practices.
This book describes the importance of sustainable livestock
production from a food security perspective in the changing climate
scenario. It covers the amelioration of climate change impacts and
describes the various mitigation strategies to reduce enteric
methane emissions. The book targets sustainable livestock
production by covering diverse concepts of amelioration,
mitigation, and policy up-gradation. Further, it examines various
adverse impacts of climate change on growth, meat, milk, and
reproduction in livestock. Most importantly, the book covers novel
aspects of quantifying heat stress response of livestock based on
non-invasive methodologies, including infrared thermal imaging,
sensor-based applications, hair, urine, and fecal cortisol
estimation. Particular emphasis was given to describing the
skin-based novel approaches to establish climate resilience in
indigenous breeds. The book provides detailed descriptions of
alleviating climate change impacts on shelter management,
nutritional interventions, and genetics-based strategies involving
advanced genomic tools. Lastly, it highlights the livestock species
which could be considered ideal climate-resilient animal models to
withstand the adversities associated with climate change.
Constant improvements in technological applications have allowed
for more opportunities to develop automated systems. This not only
leads to higher success in smart data analysis, but also ensures
that technological progression will continue. Ubiquitous Machine
Learning and its Applications is a pivotal reference source for the
latest research on the issues and challenges machines face in the
new millennium. Featuring extensive coverage on relevant areas such
as computational advertising, software engineering, and
bioinformatics, this publication is an ideal resource for
academicians, graduate students, engineering professionals, and
researchers interested in discovering how they can apply these
advancements to various disciplines.
The book, 'Laser Physics and Technology', addresses fundamentals of
laser physics, representative laser systems and techniques, and
some important applications of lasers. The present volume is a
collection of articles based on some of the lectures delivered at
the School on 'Laser Physics and Technology' organized at Raja
Ramanna Centre for Advanced Technology during March, 12-30, 2012.
The objective of the School was to provide an in-depth knowledge of
the important aspects of laser physics and technology to doctoral
students and young researchers and motivate them for further work
in this area. In keeping with this objective, the fourteen
chapters, written by leading Indian experts, based on the lectures
delivered by them at the School, provide along with class room type
coverage of the fundamentals of the field, a brief review of the
current status of the field. The book will be useful for doctoral
students and young scientists who are embarking on a research in
this area as well as to professionals who would be interested in
knowing the current state of the field particularly in Indian
context.
A must-read for every teacher in the 21st Century, this book
provides a comprehensive guide to facilitating joyful, sustainable,
holistic, multidisciplinary, and active learning. The book
discusses different approaches, principles, techniques, and
activities for making a classroom where different learning types
can thrive. The methods outlined in this volume help teachers
ensure that every learner, regardless of background or orientation,
can engage in participatory, reflective, self-directed,
experiential, entrepreneurial, and collaborative learning and
develop holistically. Essential for the 21st Century, the book
highlights the significance of digital technologies and examines
how teachers can easily use digital technologies to offer
personalized and blended learning. This book is a vital resource
for teachers who want to improve their teaching skills and create a
positive and engaging learning environment for their learners. This
book helps teachers across the globe to enhance learning outcomes
in classrooms and, subsequently, develop the quality of their
education systems. This volume is useful to students, researchers,
and teachers in education, psychology, development studies, social
work, and Sociology. It is also an invaluable companion to
policymakers and professionals from government and non-government
organizations working in the education and social development
sector.
The volume, complexity, and irregularity of computational data in
modern algorithms and simulations necessitates an unorthodox
approach to computing. Understanding the facets and possibilities
of soft computing algorithms is necessary for the accurate and
timely processing of complex data. Research Advances in the
Integration of Big Data and Smart Computing builds on the available
literature in the realm of Big Data while providing further
research opportunities in this dynamic field. This publication
provides the resources necessary for technology developers,
scientists, and policymakers to adopt and implement new paradigms
in computational methods across the globe. The chapters in this
publication advance the body of knowledge on soft computing
techniques through topics such as transmission control protocol for
mobile ad hoc networks, feature extraction, comparative analysis of
filtering techniques, big data in economic policy, and advanced
dimensionality reduction methods.
This book addresses the mapping of soil-landscape parameters in the
geospatial domain. It begins by discussing the fundamental
concepts, and then explains how machine learning and geomatics can
be applied for more efficient mapping and to improve our
understanding and management of 'soil'. The judicious utilization
of a piece of land is one of the biggest and most important current
challenges, especially in light of the rapid global urbanization,
which requires continuous monitoring of resource consumption. The
book provides a clear overview of how machine learning can be used
to analyze remote sensing data to monitor the key parameters,
below, at, and above the surface. It not only offers insights into
the approaches, but also allows readers to learn about the
challenges and issues associated with the digital mapping of these
parameters and to gain a better understanding of the selection of
data to represent soil-landscape relationships as well as the
complex and interconnected links between soil-landscape parameters
under a range of soil and climatic conditions. Lastly, the book
sheds light on using the network of satellite-based Earth
observations to provide solutions toward smart farming and smart
land management.
In recent decades, significant advances in new methodologies like
DNA sequencing and high-throughput sequencing have been used to
identify microorganisms and monitor their interactions with
different environments. Microbial genomics techniques are opening
new approaches to microbiology by revealing how microorganisms
affect human beings and the environment. This book covers four
major areas: 1) Environmental microbial genomics, 2) Microbial
genomics in human health, 3) Microbial genomics in crop improvement
and plant health protection, and 4) Genome analysis of microbial
pathogens. Within these areas, the topics addressed include:
microbial genome diversity, evolution, and microbial genome
sequencing; bioinformatics and microarray-based genomic
technologies; functional genomics of bioremediation of soil and
water from organic and inorganic pollutants and carbon management;
functional genomics of microbial pathogens and relevant
microorganisms; functional genomics of model microorganisms; and
applied functional genomics. Given its scope, the book offers a
comprehensive source of information on the latest applications of
microorganisms and microbial genomics to enhance the sustainability
of agriculture and the environment.
This book analyzes the issues associated with climate change in the
Himalayas. The purpose of choosing the Himalayas as a focus is
because it is a particularly fragile mountain system, highly
sensitive to climate change impacts, and it contains one of the
largest human populations affected by climate change. The book
provides extensive data and information regarding the climate
history of the Himalayas, and the current effects of climate change
on Himalayan weather systems, and on human and animal populations
in the region. The book begins with an overview of global climate
change with discussions of data trends and international
initiatives, then segues into a history of climate changes and
weather trends in the Himalayas. Weather systems of the Himalayas,
both past and current, are analyzed and detailed through climate
models, seasonal observations of weather fronts, and overviews of
various climate scenarios. The book then discusses climate change
impacts and signat ures specific to the Central Himalayan region,
where the largest effects of impacts are observed. Readers will
discover analysis presented on water resources, meteorological
changes, biodiversity, agriculture and human health along with
perspectives of management and policy. This book will appeal to
researchers studying climate science, climatology, environmental
scientists and policymakers.
This book presents selected articles from INDIA SMART GRID WEEK
(ISGW 2017), which is the third edition of the Conference cum
Exhibition on Smart Grids and Smart Cities, organized by India
Smart Grid Forum from 07-10 March 2017 at Manekshaw Centre, Dhaula
Kuan, New Delhi, India. ISGF is a public private partnership
initiative of the Ministry of Power, Govt. of India with the
mandate of accelerating smart grid deployments across the country.
This book gives current scenario updates of Indian power sector
business. It also highlights various disruptive technologies for
power sector business.
This book provides readers to the vision of Society 5.0, which was
originally proposed in the fifth Basic Science and Technology Plan
by Japan's government for a technology-based, human-centered
society, emerging from the 4th industrial revolution (Industry
4.0). The implementation of AI and other modern techniques in a
smart society requires automated data scheduling and analysis using
smart applications, a smart infrastructure, smart systems, and a
smart network. Features Provides an overview of basic concepts of
Society 5.0 as well as the main pillars that supports the
implementation of Society 5.0. Contains the most recent research
analysis in the domain of computer vision, signal processing and
computing sciences for facilitating the smart homes, buildings,
transport, facilities, environmental conditions and cities, and the
benefits these offer to a nation. Presents the readers with
practical approaches of using AI and other algorithms for smart
ecosystem to deals with human dynamics, the social objects, and
their relations. Deals with the utilization of AI tools and other
modern techniques for smart society as well as the current
challenging issues and its solutions for transformation to Society
5.0. This book is aimed at graduate and post graduate students,
researchers, academicians working in the field of computer science,
artificial intelligence, and machine learning.
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