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The book discusses Society 5.0 which fills the gap between cyber
and physical space by providing a balanced environment between
economic and social needs. The book is divided into two parts; part
A focuses on various concepts related to Society 5.0 such as cyber
space, physical space, information management and digital
transformation. Part B discusses various integrated fields in
Society 5.0, such as super-smart healthcare system, super-smart
hospitality system, smart building, and transport management
system. It also illustrates the concepts of big data, real-time
analytics for smart Society 5.0 with an insight of real-time case
studies.
This book discusses the advancements in artificial intelligent
techniques used in the well-being of human healthcare. It details
the techniques used in collection, storage and analysis of data and
their usage in different healthcare solutions. It also discusses
the techniques of predictive analysis in early diagnosis of
critical diseases. The edited book is divided into four parts -
part A discusses introduction to artificial intelligence and
machine learning in healthcare; part B highlights different
analytical techniques used in healthcare; part C provides various
security and privacy mechanisms used in healthcare; and finally,
part D exemplifies different tools used in visualization and data
analytics.
This book discusses the advancements in artificial intelligent
techniques used in the well-being of human healthcare. It details
the techniques used in collection, storage and analysis of data and
their usage in different healthcare solutions. It also discusses
the techniques of predictive analysis in early diagnosis of
critical diseases. The edited book is divided into four parts -
part A discusses introduction to artificial intelligence and
machine learning in healthcare; part B highlights different
analytical techniques used in healthcare; part C provides various
security and privacy mechanisms used in healthcare; and finally,
part D exemplifies different tools used in visualization and data
analytics.
This book discusses topics related to bioinformatics, statistics,
and machine learning, presenting the latest research in various
areas of bioinformatics. It also highlights the role of computing
and machine learning in knowledge extraction from biological data,
and how this knowledge can be applied in fields such as drug
design, health supplements, gene therapy, proteomics and
agriculture.
This book discusses topics related to bioinformatics, statistics,
and machine learning, presenting the latest research in various
areas of bioinformatics. It also highlights the role of computing
and machine learning in knowledge extraction from biological data,
and how this knowledge can be applied in fields such as drug
design, health supplements, gene therapy, proteomics and
agriculture.
The authors have consolidated their research work in this volume
titled Soft Computing for Data Mining Applications. The monograph
gives an insight into the research in the ?elds of Data Mining in
combination with Soft Computing methodologies. In these days, the
data continues to grow - ponentially. Much of the data is
implicitly or explicitly imprecise. Database discovery seeks to
discover noteworthy, unrecognized associations between the data
items in the existing database. The potential of discovery comes
from the realization that alternate contexts may reveal additional
valuable information. The rate at which the data is storedis
growing at a phenomenal rate. Asaresult,
traditionaladhocmixturesofstatisticaltechniquesanddata
managementtools are no longer adequate for analyzing this vast
collection of data.
Severaldomainswherelargevolumesofdataarestoredincentralizedor
distributeddatabasesincludesapplicationslikeinelectroniccommerce,
bio- formatics, computer security, Web intelligence, intelligent
learning database systems, ?nance, marketing, healthcare,
telecommunications, andother?elds. E?cient tools and algorithms for
knowledge discovery in large data sets have been devised during the
recent years. These methods exploit the ca- bility of computers to
search huge amounts of data in a fast and e?ective manner. However,
the data to be analyzed is imprecise and a?icted with - certainty.
In the case of heterogeneous data sources such as text and video,
the data might moreover be ambiguous and partly con?icting.
Besides, p- terns and relationships of interest are usually
approximate. Thus, in order to make the information mining process
more robust it requires tolerance toward imprecision, uncertainty
and exc
The authors have consolidated their research work in this volume
titled Soft Computing for Data Mining Applications. The monograph
gives an insight into the research in the ?elds of Data Mining in
combination with Soft Computing methodologies. In these days, the
data continues to grow - ponentially. Much of the data is
implicitly or explicitly imprecise. Database discovery seeks to
discover noteworthy, unrecognized associations between the data
items in the existing database. The potential of discovery comes
from the realization that alternate contexts may reveal additional
valuable information. The rate at which the data is storedis
growing at a phenomenal rate. Asaresult,
traditionaladhocmixturesofstatisticaltechniquesanddata
managementtools are no longer adequate for analyzing this vast
collection of data.
Severaldomainswherelargevolumesofdataarestoredincentralizedor
distributeddatabasesincludesapplicationslikeinelectroniccommerce,
bio- formatics, computer security, Web intelligence, intelligent
learning database systems, ?nance, marketing, healthcare,
telecommunications, andother?elds. E?cient tools and algorithms for
knowledge discovery in large data sets have been devised during the
recent years. These methods exploit the ca- bility of computers to
search huge amounts of data in a fast and e?ective manner. However,
the data to be analyzed is imprecise and a?icted with - certainty.
In the case of heterogeneous data sources such as text and video,
the data might moreover be ambiguous and partly con?icting.
Besides, p- terns and relationships of interest are usually
approximate. Thus, in order to make the information mining process
more robust it requires tolerance toward imprecision, uncertainty
and exc
This textbook tackles the matter of contemporary learners' needs,
and introduces modern learning, teaching, and assessment methods.
It provides a deeper understanding of these methods so that the
students and teachers can create teaching and learning
opportunities for themselves and others. It explores the meaning of
'pedagogy', why it is essential, and how pedagogy has evolved to
take 21st-century skills and learning into account. This textbook
showcases various modern learning, teaching, and assessment methods
for contemporary learners in an increasingly digital environment.
Each chapter presents insights and case studies that show how such
modern methods can be applied to classrooms, and how they can
support the existing curriculum. It shows students, educators, and
researchers alike how to effectively make sense of and use modern
learning, teaching, and assessment methods in everyday practice.
With the immense growth of information, the prevalence of
ubiquitously connected smart devices is rapidly increasing.
Providing platforms that support computation, storage, and
networking services between end devices is an essential aspect of
an expanding digital society. The Rise of Fog Computing in the
Digital Era provides innovative insights into the present
generation of computing devices, as well as new approaches to
computational platforms through fog computing. The content within
this publication presents concepts and theories on data analytics,
management systems, networking architectures, and many more. It is
a vital reference source for IT professionals, computer
programmers, software developers, computer engineers, researchers,
and upper-level students seeking topics centered on the challenges
and benefits of fog computing in mobile environments.
Computer software and technologies are advancing at an amazing
rate. The accessibility of these software sources allows for a
wider power among common users as well as rapid advancement in
program development and operating information. Free and Open Source
Software in Modern Data Science and Business Intelligence: Emerging
Research and Opportunities is a critical scholarly resource that
examines the differences between the two types of software,
integral in the FOSS movement, and their effect on the distribution
and use of software. Featuring coverage on a wide range of topics,
such as FOSS Ecology, graph mining, and project tasks, this book is
geared towards academicians, researchers, and students interested
in current research on the growing importance of FOSS and its
expanding reach in IT infrastructure.
Like electricity and water, data and computing power are necessary
commodities in the modern-day economy. A model for the effective
regulation and provisioning of computational services will follow a
similar paradigm as the existent model for traditional utilities.
Emerging Research Surrounding Power Consumption and Performance
Issues in Utility Computing explores methods of treating computing
resources and materials as a standard utility, charging customers
based on their usage and promoting competition among service
providers. Including both benefits and hindrances, as well as
theoretical concepts and practical considerations, this book
provides an in-depth discussion of the utility computing paradigm
for computer engineers, service providers, consumers, and academics
in the field of computer science. This book includes emerging
research on subjects including, but not limited to, Graphical
Processing Unit (GPU) architectures, green computing, VMware, and
device manufacturing techniques.
With the immense growth of information, the prevalence of
ubiquitously connected smart devices is rapidly increasing.
Providing platforms that support computation, storage, and
networking services between end devices is an essential aspect of
an expanding digital society. The Rise of Fog Computing in the
Digital Era provides innovative insights into the present
generation of computing devices, as well as new approaches to
computational platforms through fog computing. The content within
this publication presents concepts and theories on data analytics,
management systems, networking architectures, and many more. It is
a vital reference source for IT professionals, computer
programmers, software developers, computer engineers, researchers,
and upper-level students seeking topics centered on the challenges
and benefits of fog computing in mobile environments.
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