|
Showing 1 - 25 of
39 matches in All Departments
The book investigates various MPPT algorithms, and the optimization
of solar energy using machine learning and deep learning. It will
serve as an ideal reference text for senior undergraduate, graduate
students, and academic researchers in diverse engineering domains
including electrical, electronics and communication, computer, and
environmental. This book: Discusses data acquisition by the
internet of things for real-time monitoring of solar cells. Covers
artificial neural network techniques, solar collector optimization,
and artificial neural network applications in solar heaters, and
solar stills. Details solar analytics, smart centralized control
centers, integration of microgrids, and data mining on solar data.
Highlights the concept of asset performance improvement, effective
forecasting for energy production, and Low-power wide-area network
applications. Elaborates solar cell design principles, the
equivalent circuits of single and two diode models, measuring
idealist factors, and importance of series and shunt resistances.
The text elaborates solar cell design principles, the equivalent
circuit of single diode model, the equivalent circuit of two diode
model, measuring idealist factor, and importance of series and
shunt resistances. It further discusses perturb and observe
technique, modified P&O method, incremental conductance method,
sliding control method, genetic algorithms, and neuro-fuzzy
methodologies. It will serve as an ideal reference text for senior
undergraduate, graduate students, and academic researchers in
diverse engineering domains including electrical, electronics and
communication, computer, and environmental.
Reviews different machine learning and deep learning techniques
with a biomedical perspective Provides the relevant case studies
that demonstrate applicability of different AI techniques Explain
different kinds of inputs like various image modalities, biomedical
signals types, etc. Covers the latest trends of AI-based biomedical
domains including IoT, drug discovery, biomechanics, robotics,
electronic health records, etc. Discusses the research challenges
and opportunities in AI and biomedical domain
Computational Intelligence and Deep Learning Methods for
Neuro-rehabilitation Applications explores the different
possibilities of providing AI based neuro-rehabilitation methods to
treat neurological disorders. This book provides in-depth knowledge
on the challenges and solutions associated with the different
varieties of neuro-rehabilitation through the inclusion of case
studies and real-time scenarios in different geographical
locations. Beginning with an overview of neuro-rehabilitation
applications, the book discusses the role of machine learning
methods in brain function grading for adults with Mild Cognitive
Impairment, Brain Computer Interface for post-stroke patients,
developing assistive devices for paralytic patients, and cognitive
treatment for spinal cord injuries. Topics also include
AI-based video games to improve the brain performances in children
with autism and ADHD, deep learning approaches and
magnetoencephalography data for limb movement, EEG signal analysis,
smart sensors, and the application of robotic concepts for gait
control.
Computational Intelligence and Modelling Techniques for Disease
Detection in Mammogram Images comprehensively examines the wide
range of AI-based mammogram analysis methods for medical
applications. Beginning with an introductory overview of mammogram
data analysis, the book covers the current technologies such as
ultrasound, molecular breast imaging (MBI), magnetic resonance
(MR), and Positron Emission mammography (PEM), as well as the
recent advancements in 3D breast tomosynthesis and 4D mammogram.
Deep learning models are presented in each chapter to show how they
can assist in the efficient processing of breast images. The book
also discusses hybrid intelligence approaches for early-stage
detection and the use of machine learning classifiers for cancer
detection, staging and density assessment in order to develop a
proper treatment plan. This book will not only aid computer
scientists and medical practitioners in developing a real-time AI
based mammogram analysis system, but also addresses the issues and
challenges with the current processing methods which are not
conducive for real-time applications.
This book is a detailed reference on biomedical applications using
Deep Learning. Because Deep Learning is an important actor shaping
the future of Artificial Intelligence, its specific and innovative
solutions for both medical and biomedical are very critical. This
book provides a recent view of research works on essential, and
advanced topics. The book offers detailed information on the
application of Deep Learning for solving biomedical problems. It
focuses on different types of data (i.e. raw data, signal-time
series, medical images) to enable readers to understand the
effectiveness and the potential. It includes topics such as disease
diagnosis, image processing perspectives, and even genomics. It
takes the reader through different sides of Deep Learning oriented
solutions. The specific and innovative solutions covered in this
book for both medical and biomedical applications are critical to
scientists, researchers, practitioners, professionals, and
educations who are working in the context of the topics.
This book emphasizes recent advances in the creation of biometric
identification systems for various applications in the field of
human activity. The book displays the problems that arise in modern
systems of biometric identification, as well as the level of
development and prospects for the introduction of biometric
technologies. The authors classify biometric technologies into two
groups, distinguished according to the type of biometric
characteristics used. The first group uses static biometric
parameters: fingerprints, hand geometry, retina pattern, vein
pattern on the finger, etc. The second group uses dynamic
parameters for identification: the dynamics of the reproduction of
a signature or a handwritten keyword, voice, gait, dynamics of work
on the keyboard, etc. The directions of building information
systems that use automatic personality identification based on the
analysis of unique biometric characteristics of a person are
discussed. The book is intended for professionals working and
conducting research in the field of intelligent information
processing, information security, and robotics and in the field of
real-time identification systems. The book contains examples and
problems/solutions throughout.
This book features a collection of high-quality research papers
presented at the International Conference on Advanced Computing
Technology (ICACT 2020), held at the SRM Institute of Science and
Technology, Chennai, India, on 23-24 January 2020. It covers the
areas of computational intelligence, artificial intelligence,
machine learning, deep learning, big data, and applications of
artificial intelligence in networking, IoT and bioinformatics
This book solicits the innovative research ideas and solutions for
almost all the intelligent data intensive theories and application
domains. The proliferation of various mobile and wireless
communication networks has paved way to foster a high demand for
intelligent data processing and communication technologies. The
potential of data in wireless mobile networks is enormous, and it
constitutes to improve the communication capabilities profoundly.
As the networking and communication applications are becoming more
intensive, the management of data resources and its flow between
various storage and computing resources are posing significant
research challenges to both ICT and data science community. The
general scope of this book covers the design, architecture,
modeling, software, infrastructure and applications of intelligent
communication architectures and systems for big data or
data-intensive applications. In particular, this book reports the
novel and recent research works on big data, mobile and wireless
networks, artificial intelligence, machine learning, social network
mining, intelligent computing technologies, image analysis,
robotics and autonomous systems, data security and privacy.
This book includes original research findings in the field of
memetic algorithms for image processing applications. It gathers
contributions on theory, case studies, and design methods
pertaining to memetic algorithms for image processing applications
ranging from defence, medical image processing, and surveillance,
to computer vision, robotics, etc. The content presented here
provides new directions for future research from both theoretical
and practical viewpoints, and will spur further advances in the
field.
Human-computer interaction (HCI) is one of the most significant
areas of computational intelligence. This book focuses on the human
emotion analysis aspects of HCI, highlighting innovative
methodologies for emotion analysis by machines/computers and their
application areas. The methodologies are presented with numerical
results to enable researchers to replicate the work. This
multidisciplinary book is useful to researchers and academicians,
as well as students wanting to pursue a career in computational
intelligence. It can also be used as a handbook, reference book,
and a textbook for short courses.
This book features a collection of high-quality research papers
presented at the International Conference on Advanced Computing
Technology (ICACT 2020), held at the SRM Institute of Science and
Technology, Chennai, India, on 23-24 January 2020. It covers the
areas of computational intelligence, artificial intelligence,
machine learning, deep learning, big data, and applications of
artificial intelligence in networking, IoT and bioinformatics
This book features research presented at the 1st International
Conference on Artificial Intelligence and Applied Mathematics in
Engineering, held on 20-22 April 2019 at Antalya, Manavgat
(Turkey). In today's world, various engineering areas are essential
components of technological innovations and effective real-world
solutions for a better future. In this context, the book focuses on
problems in engineering and discusses research using artificial
intelligence and applied mathematics. Intended for scientists,
experts, M.Sc. and Ph.D. students, postdocs and anyone interested
in the subjects covered, the book can also be used as a reference
resource for courses related to artificial intelligence and applied
mathematics.
This book includes original research findings in the field of
memetic algorithms for image processing applications. It gathers
contributions on theory, case studies, and design methods
pertaining to memetic algorithms for image processing applications
ranging from defence, medical image processing, and surveillance,
to computer vision, robotics, etc. The content presented here
provides new directions for future research from both theoretical
and practical viewpoints, and will spur further advances in the
field.
This book focuses on the emerging advances in distributed
communication systems, big data, intelligent computing and Internet
of Things, presenting state-of-the-art research in frameworks,
algorithms, methodologies, techniques and applications associated
with data engineering and wireless distributed communication
technologies. In addition, it discusses potential topics like
performance analysis, wireless communication networks, data
security and privacy, human computer interaction, 5G Networks, and
smart automated systems, which will provide insights for the
evolving data communication technologies. In a nutshell, this
proceedings book compiles novel and high-quality research that
offers innovative solutions for communications in IoT networks.
This book presents the fundamentals and advances in the field of
data visualization and knowledge engineering, supported by case
studies and practical examples. Data visualization and engineering
has been instrumental in the development of many data-driven
products and processes. As such the book promotes basic research on
data visualization and knowledge engineering toward data
engineering and knowledge. Visual data exploration focuses on
perception of information and manipulation of data to enable even
non-expert users to extract knowledge. A number of visualization
techniques are used in a variety of systems that provide users with
innovative ways to interact with data and reveal patterns. A
variety of scalable data visualization techniques are required to
deal with constantly increasing volume of data in different
formats. Knowledge engineering deals with the simulation of the
exchange of ideas and the development of smart information systems
in which reasoning and knowledge play an important role. Presenting
research in areas like data visualization and knowledge
engineering, this book is a valuable resource for students,
scholars and researchers in the field. Each chapter is
self-contained and offers an in-depth analysis of real-world
applications. It discusses topics including (but not limited to)
spatial data visualization; biomedical visualization and
applications; image/video summarization and visualization;
perception and cognition in visualization; visualization taxonomies
and models; abstract data visualization; information and graph
visualization; knowledge engineering; human-machine cooperation;
metamodeling; natural language processing; architectures of
database, expert and knowledge-based systems; knowledge acquisition
methods; applications, case studies and management issues: data
administration issues and knowledge; tools for specifying and
developing data and knowledge bases using tools based on
communication aspects involved in implementing, designing and using
KBSs in cyberspace; Semantic Web.
|
Artificial Intelligence - Second International Conference, SLAAI-ICAI 2018, Moratuwa, Sri Lanka, December 20, 2018, Revised Selected Papers (Paperback, 1st ed. 2019)
Jude Hemanth, Thushari Silva, Asoka Karunananda
|
R1,574
Discovery Miles 15 740
|
Ships in 10 - 15 working days
|
This book constitutes the refereed proceedings of the Second
International Conference, SLAAI-ICAI 2018, held in Moratuwa, Sri
Lanka, in December 2018. The 32 revised full papers presented were
carefully reviewed and selected from numerous submissions. The
papers are organized in the following topical sections:
intelligence systems; neural networks; game theory; ontology
engineering; natural language processing; agent based system;
signal and image processing.
THE SERIES: FRONTIERS IN COMPUTATIONAL INTELLIGENCE The series
Frontiers In Computational Intelligence is envisioned to provide
comprehensive coverage and understanding of cutting edge research
in computational intelligence. It intends to augment the scholarly
discourse on all topics relating to the advances in artifi cial
life and machine learning in the form of metaheuristics,
approximate reasoning, and robotics. Latest research findings are
coupled with applications to varied domains of engineering and
computer sciences. This field is steadily growing especially with
the advent of novel machine learning algorithms being applied to
different domains of engineering and technology. The series brings
together leading researchers that intend to continue to advance the
field and create a broad knowledge about the most recent research.
Series Editor Dr. Siddhartha Bhattacharyya, CHRIST (Deemed to be
University), Bangalore, India Editorial Advisory Board Dr.
Elizabeth Behrman, Wichita State University, Kansas, USA Dr. Goran
Klepac Dr. Leo Mrsic, Algebra University College, Croatia Dr. Aboul
Ella Hassanien, Cairo University, Egypt Dr. Jan Platos,
VSB-Technical University of Ostrava, Czech Republic Dr. Xiao-Zhi
Gao, University of Eastern Finland, Finland Dr. Wellington Pinheiro
dos Santos, Federal University of Pernambuco, Brazil
This book briefly covers internationally contributed chapters with
artificial intelligence and applied mathematics-oriented
background-details. Nowadays, the world is under attack of
intelligent systems covering all fields to make them practical and
meaningful for humans. In this sense, this edited book provides the
most recent research on use of engineering capabilities for
developing intelligent systems. The chapters are a collection from
the works presented at the 2nd International Conference on
Artificial Intelligence and Applied Mathematics in Engineering held
within 09-10-11 October 2020 at the Antalya, Manavgat (Turkey). The
target audience of the book covers scientists, experts, M.Sc. and
Ph.D. students, post-docs, and anyone interested in intelligent
systems and their usage in different problem domains. The book is
suitable to be used as a reference work in the courses associated
with artificial intelligence and applied mathematics.
As general, this book is a collection of the most recent, quality
research papers regarding applications of Artificial Intelligence
and Applied Mathematics for engineering problems. The papers
included in the book were accepted and presented in the 4th
International Conference on Artificial Intelligence and Applied
Mathematics in Engineering (ICAIAME 2022), which was held in Baku,
Azerbaijan (Azerbaijan Technical University) between May 20 and 22,
2022. Objective of the book content is to inform the international
audience about the cutting-edge, effective developments and
improvements in different engineering fields. As a collection of
the ICAIAME 2022 event, the book gives consideration for the
results by especially intelligent system formations and the
associated applications. The target audience of the book is
international researchers, degree students, practitioners from
industry, and experts from different engineering disciplines.
This book gathers selected papers presented at the
5th International Conference on Intelligent Data
Communication Technologies and Internet of Things (ICICI 2021),
organized by JCT College of Engineering and Technology, Coimbatore,
Tamil Nadu, India during 27 – 28 August 2021. This book solicits
the innovative research ideas and solutions for almost all the
intelligent data intensive theories and application domains. The
general scope of this book covers the design, architecture,
modeling, software, infrastructure and applications of intelligent
communication architectures and systems for big data or
data-intensive applications. In particular, this book reports the
novel and recent research works on big data, mobile and wireless
networks, artificial intelligence, machine learning, social network
mining, intelligent computing technologies, image analysis,
robotics and autonomous systems, data security and privacy.
Intelligent Edge Computing for Cyber Physical Applications
introduces state-of-the-art research methodologies, tools and
techniques, challenges, and solutions with further research
opportunities in the area of edge-based cyber-physical systems. The
book presents a comprehensive review of recent literature and
analysis of different techniques for building edge-based CPS. In
addition, it describes how edge-based CPS can be built to
seamlessly interact with physical machines for optimal performance,
covering various aspects of edge computing architectures for
dynamic resource provisioning, mobile edge computing, energy saving
scenarios, and different security issues. Sections feature
practical use cases of edge-computing which will help readers
understand the workings of edge-based systems in detail, taking
into account the need to present intellectual challenges while
appealing to a broad readership, including academic researchers,
practicing engineers and managers, and graduate students.
This book looks at the growing segment of Internet of Things
technology (IoT) known as Internet of Medical Things (IoMT), an
automated system that aids in bridging the gap between isolated and
rural communities and the critical healthcare services that are
available in more populated and urban areas. Many technological
aspects of IoMT are still being researched and developed, with the
objective of minimizing the cost and improving the performance of
the overall healthcare system. This book focuses on innovative IoMT
methods and solutions being developed for use in the application of
healthcare services, including post-surgery care, virtual home
assistance, smart real-time patient monitoring, implantable sensors
and cameras, and diagnosis and treatment planning. It also examines
critical issues around the technology, such as security
vulnerabilities, IoMT machine learning approaches, and medical data
compression for lossless data transmission and archiving. Internet
of Medical Things is a valuable reference for researchers,
students, and postgraduates working in biomedical, electronics, and
communications engineering, as well as practicing healthcare
professionals.
This book gathers selected papers presented at the 5th
International Conference on Intelligent Data Communication
Technologies and Internet of Things (ICICI 2021), organized by JCT
College of Engineering and Technology, Coimbatore, Tamil Nadu,
India during 27 - 28 August 2021. This book solicits the innovative
research ideas and solutions for almost all the intelligent data
intensive theories and application domains. The general scope of
this book covers the design, architecture, modeling, software,
infrastructure and applications of intelligent communication
architectures and systems for big data or data-intensive
applications. In particular, this book reports the novel and recent
research works on big data, mobile and wireless networks,
artificial intelligence, machine learning, social network mining,
intelligent computing technologies, image analysis, robotics and
autonomous systems, data security and privacy.
Handbook of Decision Support Systems for Neurological Disorders
provides readers with complete coverage of advanced computer-aided
diagnosis systems for neurological disorders. While computer-aided
decision support systems for different medical imaging modalities
are available, this is the first book to solely concentrate on
decision support systems for neurological disorders. Due to the
increase in the prevalence of diseases such as Alzheimer,
Parkinson's and Dementia, this book will have significant
importance in the medical field. Topics discussed include recent
computational approaches, different types of neurological
disorders, deep convolution neural networks, generative adversarial
networks, auto encoders, recurrent neural networks, and
modified/hybrid artificial neural networks.
|
You may like...
Tenet
John David Washington, Robert Pattinson
Blu-ray disc
(1)
R54
Discovery Miles 540
|