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Books > Computing & IT > Applications of computing
Artificial Intelligence (AI) is being rapidly introduced into the
workplace, creating debate around what AI means for our work and
organizations. This book gives grounded counterweight to
provocative newspaper headlines by using in-depth case studies of
eight organizations' experiences of implementing and using AI,
providing readers with a solid understanding of what is actually
happening in practice. Critical yet constructive, the authors
address the challenges of implementing AI: organizing for data,
testing and validating, algorithmic brokering, and changing work.
Using a combination of existing literature and thorough practical
examples, they provide answers to questions such as: What data do I
need? When is a system good enough to actually take over tasks? And
how can my employees be prepared for working with AI? The book
presents four recommendations for WISE management of AI, requiring
work-related insights, interdisciplinary knowledge, sociotechnical
change processes, and ethical awareness. Offering insight into the
unique characteristics of AI in organizations, this book will be
essential reading for scholars of business and management, data
analytics and information systems, technology and innovation, and
computer science. With practical recommendations for managing the
challenges of AI, it will also provide business managers with
reflections to improve their own AI development and implementation
processes.
The proliferation of virtual and augmented reality technologies
into society raise significant questions for judges, legal
institutions, and policy makers. For example, when should
activities that occur in virtual worlds, or virtual images that are
projected into real space (that is, augmented reality), count as
protected First Amendment 'speech'? When should they instead count
as a nuisance or trespass? Under what circumstances would the
copying of virtual images infringe intellectual property laws, or
the output of intelligent virtual avatars be patentable inventions
or works of authorship eligible for copyright? And when should a
person (or computer) face legal consequences for allegedly harmful
virtual acts? The Research Handbook on the Law of Virtual and
Augmented Reality addresses these questions and others, drawing
upon free speech doctrine, criminal law, the law of data protection
and privacy, and of jurisdiction, as well as upon potential legal
rights for increasingly intelligent virtual avatars in VR worlds.
The Handbook offers a comprehensive look at challenges to various
legal doctrines raised by the emergence - and increasing use of -
virtual and augmented reality worlds, and at how existing law in
the USA, Europe, and other jurisdictions might apply to these
emerging technologies, or evolve to address them. It also considers
what legal questions about virtual and augmented reality are likely
to be important, not just for judges and legal scholars, but also
for the established businesses and start-ups that wish to make use
of, and help shape, these important new technologies. This
comprehensive Research Handbook will be an invaluable reference to
those looking to keep pace with the dynamic field of virtual and
augmented reality, including students and researchers studying
intellectual property law as well as legal practitioners, computer
scientists, engineers, game designers, and business owners.
Contributors include: W. Barfield, P.S. Berman, M.J. Blitz, S.J.
Blodgett-Ford, J. Danaher, W. Erlank, J.A.T. Fairfield, J. Garon,
G. Hallevy, B. Lewis, H.Y.F. Lim, C. Nwaneri, S.R. Peppet, M.
Risch, A.L. Rossow, J. Russo, M. Supponen, A.M. Underhill, B.D.
Wassom, A. Williams, G. Yadin
Innovations in Artificial Intelligence and Human Computer
Interaction in the Digital Era investigates the interaction and
growing interdependency of the HCI and AI fields, which are not
usually addressed in traditional approaches. Chapters explore how
well AI can interact with users based on linguistics and
user-centered design processes, especially with the advances of AI
and the hype around many applications. Other sections investigate
how HCI and AI can mutually benefit from a closer association and
the how the AI community can improve their usage of HCI methods
like “Wizard of Oz” prototyping and “Thinking aloud” protocols.
Moreover, HCI can further augment human capabilities using new
technologies. This book demonstrates how an interdisciplinary team
of HCI and AI researchers can develop extraordinary applications,
such as improved education systems, smart homes, smart healthcare
and map Human Computer Interaction (HCI) for a multidisciplinary
field that focuses on the design of computer technology and the
interaction between users and computers in different domains.
Stochastic processes have a wide range of applications ranging from
image processing, neuroscience, bioinformatics, financial
management, and statistics. Mathematical, physical, and engineering
systems use stochastic processes for modeling and reasoning
phenomena. While comparing AI-stochastic systems with other
counterpart systems, we are able to understand their significance,
thereby applying new techniques to obtain new real-time results and
solutions. Stochastic Processes and Their Applications in
Artificial Intelligence opens doors for artificial intelligence
experts to use stochastic processes as an effective tool in
real-world problems in computational biology, speech recognition,
natural language processing, and reinforcement learning. Covering
key topics such as social media, big data, and artificial
intelligence models, this reference work is ideal for
mathematicians, industry professionals, researchers, scholars,
academicians, practitioners, instructors, and students.
Originating from papers presented at the 18th International
Conference on Railway Engineering Design and Operation, this book
provides up-to-date research on the use of advanced systems,
promoting their general awareness throughout the management,
design, manufacture and operation of railways and other emerging
passenger, freight and transit systems. A key emphasis is placed on
the use of computer systems in advanced railway engineering. The
included works are compiled from a variety of specialists
interested in the development of railways, including managers,
consultants, railway engineers, designers of advanced train control
systems and computer specialists. Topics covered include: Traffic
safety, security and monitoring; Train and railways analysis;
Operation of rail networks; Advanced train control;
Energy-efficient design; Traffic modelling and simulation.
From the inventor of the PalmPilot comes a new and compelling
theory of intelligence, brain function, and the future of
intelligent machines
Jeff Hawkins, the man who created the PalmPilot, Treo smart phone,
and other handheld devices, has reshaped our relationship to
computers. Now he stands ready to revolutionize both neuroscience
and computing in one stroke, with a new understanding of
intelligence itself.
Hawkins develops a powerful theory of how the human brain works,
explaining why computers are not intelligent and how, based on this
new theory, we can finally build intelligent machines.
The brain is not a computer, but a memory system that stores
experiences in a way that reflects the true structure of the world,
remembering sequences of events and their nested relationships and
making predictions based on those memories. It is this
memory-prediction system that forms the basis of intelligence,
perception, creativity, and even consciousness.
In an engaging style that will captivate audiences from the merely
curious to the professional scientist, Hawkins shows how a clear
understanding of how the brain works will make it possible for us
to build intelligent machines, in silicon, that will exceed our
human ability in surprising ways.
Written with acclaimed science writer Sandra Blakeslee, "On
Intelligence" promises to completely transfigure the possibilities
of the technology age. It is a landmark book in its scope and
clarity.
This book proposes various deep learning models featuring how deep
learning algorithms have been applied and used in real-life
settings. The complexity of real-world scenarios and constraints
imposed by the environment, together with budgetary and resource
limitations, have posed great challenges to engineers and
developers alike, to come up with solutions to meet these demands.
This book presents case studies undertaken by its contributors to
overcome these problems. These studies can be used as references
for designers when applying deep learning in solving real-world
problems in the areas of vision, signals, and networks.The contents
of this book are divided into three parts. In the first part, AI
vision applications in plant disease diagnostics, PM2.5
concentration estimation, surface defect detection, and ship plate
identification, are featured. The second part introduces deep
learning applications in signal processing; such as time series
classification, broad-learning based signal modulation recognition,
and graph neural network (GNN) based modulation recognition.
Finally, the last section of the book reports on graph embedding
applications and GNN in AI for networks; such as an end-to-end
graph embedding method for dispute detection, an autonomous
System-GNN architecture to infer the relationship between Apache
software, a Ponzi scheme detection framework to identify and detect
Ponzi schemes, and a GNN application to predict molecular
biological activities.
Affective computing is a nascent field situated at the intersection
of artificial intelligence with social and behavioral science. It
studies how human emotions are perceived and expressed, which then
informs the design of intelligent agents and systems that can
either mimic this behavior to improve their intelligence or
incorporate such knowledge to effectively understand and
communicate with their human collaborators. Affective computing
research has recently seen significant advances and is making a
critical transformation from exploratory studies to real-world
applications in the emerging research area known as applied
affective computing. This book offers readers an overview of the
state-of-the-art and emerging themes in affective computing,
including a comprehensive review of the existing approaches to
affective computing systems and social signal processing. It
provides in-depth case studies of applied affective computing in
various domains, such as social robotics and mental well-being. It
also addresses ethical concerns related to affective computing and
how to prevent misuse of the technology in research and
applications. Further, this book identifies future directions for
the field and summarizes a set of guidelines for developing
next-generation affective computing systems that are effective,
safe, and human-centered. For researchers and practitioners new to
affective computing, this book will serve as an introduction to the
field to help them in identifying new research topics or developing
novel applications. For more experienced researchers and
practitioners, the discussions in this book provide guidance for
adopting a human-centered design and development approach to
advance affective computing.
Data Ethics of Power takes a reflective and fresh look at the
ethical implications of transforming everyday life and the world
through the effortless, costless, and seamless accumulation of
extra layers of data. By shedding light on the constant tensions
that exist between ethical principles and the interests invested in
this socio-technical transformation, the book bridges the theory
and practice divide in the study of the power dynamics that
underpin these processes of the digitalization of the world. Gry
Hasselbalch expertly draws on nearly two decades of experience in
the field, and key literature, to advance a better understanding of
the challenges faced by big data and AI developers. She provides an
innovative ethical framework for studying and governing Big-Data
and Artificial Intelligence. Offering both a historical account and
a theoretical analysis of power dynamics and their ethical
implications, as well as incisive ideas to guide future research
and governance practices, the book makes a significant contribution
to the establishment of an emerging data and AI ethics discipline.
This timely book is a must-read for scholars studying AI, data, and
technology ethics. Policymakers in the regulatory, governance,
public administration, and management sectors will find the
practical proposals for a human-centric approach to big data and AI
to be a valuable resource for revising and developing future
policies.
This thought-provoking book challenges the way we think about the
regulation of cryptoassets based on cryptographic consensus
technology. Bringing a timely new perspective, Syren Johnstone
critiques the application of a financial regulation narrative to
cryptoassets, questions the assumptions on which it is based, and
considers its impact on industry development. Providing new
insights into the dynamics of oversight regulation, Johnstone
argues that the financial narrative stifles the 'New Prospect' for
the formation of novel commercial relationships and institutional
arrangements. The book asks whether regulations developed in the
20th century remain appropriate to apply to a technology emerging
in the 21st, suggesting it is time to think about how to regulate
for ecosystem development. Johnstone concludes with proposals for
reform, positing a new framework that facilitates industry
aspirations while remaining sustainable and compatible with
regulatory objectives. Rethinking the Regulation of Cryptoassets
will be an invaluable read for policy makers, regulators and
technologists looking for a deeper understanding of the issues
surrounding cryptoasset regulation and possible alternative
approaches. It will also be of interest to scholars and students
researching the intersection of law, technology, regulation and
finance.
Creativity has been integral to the development of the modern
State, and yet it is becoming increasingly sidelined, especially as
a result of the development of new machinic technologies including
3D printing. Arguing that inner creativity has been endangered by
the rise of administrative regulation, James Griffin explores a
number of reforms to ensure that upcoming regulations do take
creativity into account. The State of Creativity examines how the
State has become distanced from individual processes of creativity.
This book investigates how the failure to incorporate creativity
into administrative regulation is, in fact, adversely impacting the
regulation of new technologies such as 3D and 4D printing and
augmented reality, by focusing on issues concerning copyright and
patents. This is an important read for intellectual property law
scholars, as well as those studying computer science who wish to
gain a more in-depth understanding of the current laws surrounding
digital technologies such as 3D printing in our modern world. Legal
practitioners wanting to remain abreast of developments surrounding
3D printing will also benefit from this book.
Zeroing Neural Networks Describes the theoretical and practical
aspects of finite-time ZNN methods for solving an array of
computational problems Zeroing Neural Networks (ZNN) have become
essential tools for solving discretized sensor-driven time-varying
matrix problems in engineering, control theory, and on-chip
applications for robots. Building on the original ZNN model,
finite-time zeroing neural networks (FTZNN) enable efficient,
accurate, and predictive real-time computations. Setting up
discretized FTZNN algorithms for different time-varying matrix
problems requires distinct steps. Zeroing Neural Networks provides
in-depth information on the finite-time convergence of ZNN models
in solving computational problems. Divided into eight parts, this
comprehensive resource covers modeling methods, theoretical
analysis, computer simulations, nonlinear activation functions, and
more. Each part focuses on a specific type of time-varying
computational problem, such as the application of FTZNN to the
Lyapunov equation, linear matrix equation, and matrix inversion.
Throughout the book, tables explain the performance of different
models, while numerous illustrative examples clarify the advantages
of each FTZNN method. In addition, the book: Describes how to
design, analyze, and apply FTZNN models for solving computational
problems Presents multiple FTZNN models for solving time-varying
computational problems Details the noise-tolerance of FTZNN models
to maximize the adaptability of FTZNN models to complex
environments Includes an introduction, problem description, design
scheme, theoretical analysis, illustrative verification,
application, and summary in every chapter Zeroing Neural Networks:
Finite-time Convergence Design, Analysis and Applications is an
essential resource for scientists, researchers, academic lecturers,
and postgraduates in the field, as well as a valuable reference for
engineers and other practitioners working in neurocomputing and
intelligent control.
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