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Network infrastructures are growing rapidly to meet the needs of
business, but the required repolicing and reconfiguration provide
challenges that need to be addressed. The software-defined network
(SDN) is the future generation of Internet technology that can help
meet these challenges of network management. This book includes
quantitative research, case studies, conceptual papers, model
papers, review papers, and theoretical backing on SDN. This book
investigates areas where SDN can help other emerging technologies
deliver more efficient services, such as IoT, industrial IoT, NFV,
big data, blockchain, cloud computing, and edge computing. The book
demonstrates the many benefits of SDNs, such as reduced costs, ease
of deployment and management, better scalability, availability,
flexibility and fine-grained control of traffic, and security. The
book demonstrates the many benefits of SDN, such as reduced costs,
ease of deployment and management, better scalability,
availability, flexibility and fine-grained control of traffic, and
security. Chapters in the volume address: Design considerations for
security issues and detection methods State-of-the-art approaches
for mitigating DDos attacks using SDN Big data using Apache Hadoop
for processing and analyzing large amounts of data Different tools
used for attack simulation Network policies and policy management
approaches that are widely used in the context of SDN Dynamic flow
tables, or static flow table management A new four-tiered
architecture that includes cloud, SDN-controller, and fog computing
Architecture for keeping computing resources available near the
industrial IoT network through edge computing The impact of SDN as
an innovative approach for smart city development More. The book
will be a valuable resource for SDN researchers as well as
academicians, research scholars, and students in the related areas.
The Internet of Things has revolutionized many industries and
sectors by connecting devices to the Internet with the use of smart
sensors and actuators, resulting in many advantages to businesses
and organizations, such as better information and resource sharing,
better supply chain efficiency, among other benefits, resulting in
better overall efficiency and cost savings. Internet of Things:
Technological Advances and New Applications investigates the
potential for initiating data-enabled and IoT-intensive
applications to provide control and optimization of industrial
operations and services. It presents an informative selection of
quantitative research, case studies, conceptual chapters, model
articles, theoretical backing, and more on many important
technological advances, applications, and challenges in the current
status of Internet of Things (IIoT). The book features examples of
IoT applications in such areas as food processing, automotive
engineering, mental health, health tracking, security, and more. It
discusses applying IoT in reverse logistics processes, developments
in the Internet of Vehicles, the use of smart antennas, and machine
learning in IoT. One chapter discusses a ground-breaking new device
that uses IoT to convert audio recordings to Braille. Also
discussed is the growing use of IoT in biometric technology (the
use of technology to identify a person based on some aspect of
their biology, such as fingerprint and eye unique pattern
recognition). The enlightening information shared here offers
state-of-the-art IoT solutions to many of today’s challenges of
improving efficiency and bringing important information to the
surface more quickly than systems depending on human intervention.
The volume will be of value for computer science engineers and
researchers, instructors and students in the field, and
professionals that are interested in exploring the areas of
next-generations IoT.
Network infrastructures are growing rapidly to meet the needs of
business, but the required repolicing and reconfiguration provide
challenges that need to be addressed. The software-defined network
(SDN) is the future generation of Internet technology that can help
meet these challenges of network management. This book includes
quantitative research, case studies, conceptual papers, model
papers, review papers, and theoretical backing on SDN. This book
investigates areas where SDN can help other emerging technologies
deliver more efficient services, such as IoT, industrial IoT, NFV,
big data, blockchain, cloud computing, and edge computing. The book
demonstrates the many benefits of SDNs, such as reduced costs, ease
of deployment and management, better scalability, availability,
flexibility and fine-grained control of traffic, and security. The
book demonstrates the many benefits of SDN, such as reduced costs,
ease of deployment and management, better scalability,
availability, flexibility and fine-grained control of traffic, and
security. Chapters in the volume address: Design considerations for
security issues and detection methods State-of-the-art approaches
for mitigating DDos attacks using SDN Big data using Apache Hadoop
for processing and analyzing large amounts of data Different tools
used for attack simulation Network policies and policy management
approaches that are widely used in the context of SDN Dynamic flow
tables, or static flow table management A new four-tiered
architecture that includes cloud, SDN-controller, and fog computing
Architecture for keeping computing resources available near the
industrial IoT network through edge computing The impact of SDN as
an innovative approach for smart city development More. The book
will be a valuable resource for SDN researchers as well as
academicians, research scholars, and students in the related areas.
This volume focuses on natural language processing, artificial
intelligence, and allied areas. Natural language processing enables
communication between people and computers and automatic
translation to facilitate easy interaction with others around the
world. This book discusses theoretical work and advanced
applications, approaches, and techniques for computational models
of information and how it is presented by language (artificial,
human, or natural) in other ways. It looks at intelligent natural
language processing and related models of thought, mental states,
reasoning, and other cognitive processes. It explores the difficult
problems and challenges related to partiality, underspecification,
and context-dependency, which are signature features of information
in nature and natural languages. Key features: Addresses the
functional frameworks and workflow that are trending in NLP and AI
Looks at the latest technologies and the major challenges, issues,
and advances in NLP and AI Explores an intelligent field monitoring
and automated system through AI with NLP and its implications for
the real world Discusses data acquisition and presents a real-time
case study with illustrations related to data-intensive
technologies in AI and NLP.
This volume provides informative chapters on the emerging issues,
challenges, and new methods and state-of-the-art technologies on
the Internet of Things and blockchain technology. It presents case
studies and solutions that can be applied in the current business
scenario, resolving challenges and providing solutions by
integrating IoT with blockchain technology. The chapters discuss
how the Internet of Things (IoT) represents a revolution of the
Internet that can connect nearly all environment devices over the
Internet to share data to create novel services and applications
for improving quality of life. Although the centralized IoT system
provides countless benefits, it raises several challenges. The
volume presents IoT techniques and methodologies, blockchain
techniques and methodologies, and case studies and applications for
data mining algorithms, heart rate monitoring, climate prediction,
disease prediction, security issues, automotive supply chains,
voting prediction, forecasting particulate matter pollution,
customer relationship management, and more.
This volume focuses on natural language processing, artificial
intelligence, and allied areas. Natural language processing enables
communication between people and computers and automatic
translation to facilitate easy interaction with others around the
world. This book discusses theoretical work and advanced
applications, approaches, and techniques for computational models
of information and how it is presented by language (artificial,
human, or natural) in other ways. It looks at intelligent natural
language processing and related models of thought, mental states,
reasoning, and other cognitive processes. It explores the difficult
problems and challenges related to partiality, underspecification,
and context-dependency, which are signature features of information
in nature and natural languages. Key features: Addresses the
functional frameworks and workflow that are trending in NLP and AI
Looks at the latest technologies and the major challenges, issues,
and advances in NLP and AI Explores an intelligent field monitoring
and automated system through AI with NLP and its implications for
the real world Discusses data acquisition and presents a real-time
case study with illustrations related to data-intensive
technologies in AI and NLP.
This book includes selected papers from the International
Conference on Next Generation of Internet of Things (ICNGIoT 2021),
organized by the Department of Computer Science and Engineering,
School of Engineering, GIET University, Gunupur, Odisha, India,
during 5-6 February 2021. The book covers topics such as IoT
network design and architecture, IoT network virtualization, IoT
sensors, privacy and security for IoT, SMART environment, social
networks, data science and data analytics, cognitive intelligence
and augmented intelligence, and case studies and applications.
Handbook of IoT and Blockchain: Methods, solutions, and Recent
Advancements includes contributions from around the globe on recent
advances and findings in the domain of Internet of Things (IoT) and
Blockchain. Chapters include theoretical analysis, practical
implications, and extensive surveys with analysis on methods,
algorithms, and processes for new product development. IoT and
Blockchain are the emerging topics in the current manufacturing
scenario.This handbook includes recent advances; showcases the work
of research around the globe; offers theoretical analysis and
practical implications; presents extensive surveys with analysis,
new contributions, and proposals on methods, algorithms, and
processes; and also covers recent advances from quantitative and
qualitative articles, case studies, conceptual works, and
theoretical backing. This handbook will be of interest to graduate
students, researchers, academicians, institutions, and
professionals that are interested in exploring the areas of IoT and
Blockchain.
There are a lot of e-business security concerns. Knowing about
e-business security issues will likely help overcome them. Keep in
mind, companies that have control over their e-business are likely
to prosper most. In other words, setting up and maintaining a
secure e-business is essential and important to business growth.
This book covers state-of-the art practices in e-business security,
including privacy, trust, security of transactions, big data, cloud
computing, social network, and distributed systems.
There are a lot of e-business security concerns. Knowing about
e-business security issues will likely help overcome them. Keep in
mind, companies that have control over their e-business are likely
to prosper most. In other words, setting up and maintaining a
secure e-business is essential and important to business growth.
This book covers state-of-the art practices in e-business security,
including privacy, trust, security of transactions, big data, cloud
computing, social network, and distributed systems.
This book includes high-quality papers presented at the Second
International Conference on Data Science and Management (ICDSM
2021), organized by the Gandhi Institute for Education and
Technology, Bhubaneswar, from 19 to 20 February 2021. It features
research in which data science is used to facilitate the
decision-making process in various application areas, and also
covers a wide range of learning methods and their applications in a
number of learning problems. The empirical studies, theoretical
analyses and comparisons to psychological phenomena described
contribute to the development of products to meet market demands.
Deep Learning (DL) is a method of machine learning, running over
Artificial Neural Networks, that uses multiple layers to extract
high-level features from large amounts of raw data. Deep Learning
methods apply levels of learning to transform input data into more
abstract and composite information. Handbook for Deep Learning in
Biomedical Engineering: Techniques and Applications gives readers a
complete overview of the essential concepts of Deep Learning and
its applications in the field of Biomedical Engineering. Deep
learning has been rapidly developed in recent years, in terms of
both methodological constructs and practical applications. Deep
Learning provides computational models of multiple processing
layers to learn and represent data with higher levels of
abstraction. It is able to implicitly capture intricate structures
of large-scale data and is ideally suited to many of the hardware
architectures that are currently available. The ever-expanding
amount of data that can be gathered through biomedical and clinical
information sensing devices necessitates the development of machine
learning and AI techniques such as Deep Learning and Convolutional
Neural Networks to process and evaluate the data. Some examples of
biomedical and clinical sensing devices that use Deep Learning
include: Computed Tomography (CT), Magnetic Resonance Imaging
(MRI), Ultrasound, Single Photon Emission Computed Tomography
(SPECT), Positron Emission Tomography (PET), Magnetic Particle
Imaging, EE/MEG, Optical Microscopy and Tomography, Photoacoustic
Tomography, Electron Tomography, and Atomic Force Microscopy.
Handbook for Deep Learning in Biomedical Engineering: Techniques
and Applications provides the most complete coverage of Deep
Learning applications in biomedical engineering available,
including detailed real-world applications in areas such as
computational neuroscience, neuroimaging, data fusion, medical
image processing, neurological disorder diagnosis for diseases such
as Alzheimer's, ADHD, and ASD, tumor prediction, as well as
translational multimodal imaging analysis.
The rapid growth and capability of artificial intelligence, digital
twin, and the internet of things are unlocking incredible
opportunities to overcome some of the greatest environmental and
social impact challenges currently facing the global community,
such as feeding a growing population, safety, affordable housing,
and environmental sustainability. Applications of Artificial
Intelligence, Digital Twin, and Internet of Things for Sustainable
Development provides an interdisciplinary platform encompassing
research on the potential opportunities and risks of reaching
sustainable development using artificial intelligence, digital
twin, and the internet of things. Covering key topics such as big
data, environmental protection, and smart cities, this reference
work is ideal for computer scientists, industry professionals,
researchers, scholars, academicians, librarians, policymakers,
practitioners, educators, and students.
Quantum computing is radically different from the conventional
approach of transforming bit-strings from one set of zeros and ones
to another. With quantum computing, everything changes. The physics
used to understand bits of information and the devices that
manipulate them are vastly different. Quantum engineering is a
revolutionary approach to quantum technology. Technology Road
Mapping for Quantum Computing and Engineering explores all the
aspects of quantum computing concepts, engineering, technologies,
operations, and applications from the basics to future
advancements. Covering topics such as machine learning, quantum
software technology, and technology road mapping, this book is an
excellent resource for data scientists, engineers, students and
professors of higher education, computer scientists, researchers,
and academicians.
Data has increased due to the growing use of web applications and
communication devices. It is necessary to develop new techniques of
managing data in order to ensure adequate usage. Modern
Technologies for Big Data Classification and Clustering is an
essential reference source for the latest scholarly research on
handling large data sets with conventional data mining and provide
information about the new technologies developed for the management
of large data. Featuring coverage on a broad range of topics such
as text and web data analytics, risk analysis, and opinion mining,
this publication is ideally designed for professionals,
researchers, and students seeking current research on various
concepts of big data analytics. Topics Covered: The many academic
areas covered in this publication include, but are not limited to:
Data visualization Distributed Computing Systems Opinion Mining
Privacy and security Risk analysis Social Network Analysis Text
Data Analytics Web Data Analytics
Because of the increased access to high-speed Internet and smart
phones, many patients have started to use mobile applications to
manage various health needs. These devices and mobile apps are now
increasingly used and integrated with telemedicine and telehealth
via the medical Internet of Things (IoT). The Handbook of Research
on Big Data Management and the Internet of Things for Improved
Health Systems is a critical scholarly resource that examines the
digital transformation of healthcare. Featuring coverage on a broad
range of topics, such as brain computer interface, data reduction
techniques, and risk factors, this book is geared towards
academicians, practitioners, researchers, and students seeking
research on health and well-being data.
Quantum computing is radically different from the conventional
approach of transforming bits strings from one set of 0's and 1's
to another. With quantum computing, everything changes. The physics
that we use to understand bits of information and the devices that
manipulate them are totally different. The way in which we build
such devices is different, requiring new materials, new design
rules and new processor architectures. Finally, the way we program
these systems is entirely different. Quantum engineering is a
revolutionary approach to quantum technology. It encompasses both
fundamental physics and the broad engineering skill-set necessary
to meet the practical challenges of the future. The proposed book
will cover the high-quality reviewed book chapters on original
research & innovations and compelling insights in Quantum
Computing and Engineering. Data scientists, Engineers, Industry,
researchers and students working in the field of quantum computing
and its allied research will benefit greatly from this publication.
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