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Books > Computing & IT
This book presents and discusses innovative ideas in the design,
modelling, implementation, and optimization of hardware platforms
for neural networks. The rapid growth of server, desktop, and
embedded applications based on deep learning has brought about a
renaissance in interest in neural networks, with applications
including image and speech processing, data analytics, robotics,
healthcare monitoring, and IoT solutions. Efficient implementation
of neural networks to support complex deep learning-based
applications is a complex challenge for embedded and mobile
computing platforms with limited computational/storage resources
and a tight power budget. Even for cloud-scale systems it is
critical to select the right hardware configuration based on the
neural network complexity and system constraints in order to
increase power- and performance-efficiency. Hardware Architectures
for Deep Learning provides an overview of this new field, from
principles to applications, for researchers, postgraduate students
and engineers who work on learning-based services and hardware
platforms.
Between adolescence and adulthood, individuals begin to explore
themselves mentally and emotionally in an attempt to figure out who
they are and where they fit in society. Social technologies in the
modern age have ushered in an era where these evolving adolescents
must circumvent the negative pressures of online influences while
also still trying to learn how to be utterly independent. Recent
Advances in Digital Media Impacts on Identity, Sexuality, and
Relationships is a collection of critical reference materials that
provides imperative research on identity exploration in emerging
adults and examines how digital media is used to help explore and
develop one's identity. While highlighting topics such as mobile
addiction, online intimacy, and cyber aggression, this publication
explores a crucial developmental period in the human lifespan and
how digital media hinders (or helps) maturing adults navigate life.
This book is ideally designed for therapists, psychologists,
sociologists, psychiatrists, researchers, educators, academicians,
and professionals.
Data Simplification: Taming Information With Open Source Tools
addresses the simple fact that modern data is too big and complex
to analyze in its native form. Data simplification is the process
whereby large and complex data is rendered usable. Complex data
must be simplified before it can be analyzed, but the process of
data simplification is anything but simple, requiring a specialized
set of skills and tools. This book provides data scientists from
every scientific discipline with the methods and tools to simplify
their data for immediate analysis or long-term storage in a form
that can be readily repurposed or integrated with other data.
Drawing upon years of practical experience, and using numerous
examples and use cases, Jules Berman discusses the principles,
methods, and tools that must be studied and mastered to achieve
data simplification, open source tools, free utilities and snippets
of code that can be reused and repurposed to simplify data, natural
language processing and machine translation as a tool to simplify
data, and data summarization and visualization and the role they
play in making data useful for the end user.
The second volume will deal with a presentation of the main matrix
and tensor decompositions and their properties of uniqueness, as
well as very useful tensor networks for the analysis of massive
data. Parametric estimation algorithms will be presented for the
identification of the main tensor decompositions. After a brief
historical review of the compressed sampling methods, an overview
of the main methods of retrieving matrices and tensors with missing
data will be performed under the low rank hypothesis. Illustrative
examples will be provided.
Trusted Platform Modules (TPMs) are small, inexpensive chips which
provide a limited set of security functions. They are most commonly
found as a motherboard component on laptops and desktops aimed at
the corporate or government markets, but can also be found on many
consumer-grade machines and servers, or purchased as independent
components. Their role is to serve as a Root of Trust - a highly
trusted component from which we can bootstrap trust in other parts
of a system. TPMs are most useful for three kinds of tasks:
remotely identifying a machine, or machine authentication;
providing hardware protection of secrets, or data protection; and
providing verifiable evidence about a machine's state, or
attestation. This book describes the primary uses for TPMs, and
practical considerations such as when TPMs can and should be used,
when they shouldn't be, what advantages they provide, and how to
actually make use of them, with use cases and worked examples of
how to implement these use cases on a real system. Topics covered
include when to use a TPM; TPM concepts and functionality;
programming introduction; provisioning: getting the TPM ready to
use; first steps: TPM keys; machine authentication; data
protection; attestation; other TPM features; software and
specifications; and troubleshooting. Appendices contain basic
cryptographic concepts; command equivalence and requirements
charts; and complete code samples.
Cloud computing is rapidly expanding in its applications and
capabilities through various parts of society. Utilizing different
types of virtualization technologies can push this branch of
computing to even greater heights. Design and Use of Virtualization
Technology in Cloud Computing is a crucial resource that provides
in-depth discussions on the background of virtualization, and the
ways it can help shape the future of cloud computing technologies.
Highlighting relevant topics including grid computing, mobile
computing, open source virtualization, and virtualization in
education, this scholarly reference source is ideal for computer
engineers, academicians, students, and researchers that are
interested in learning more about how to infuse current cloud
computing technologies with virtualization advancements.
In the era of cyber-physical systems, the area of control of
complex systems has grown to be one of the hardest in terms of
algorithmic design techniques and analytical tools. The 23
chapters, written by international specialists in the field, cover
a variety of interests within the broader field of learning,
adaptation, optimization and networked control. The editors have
grouped these into the following 5 sections: "Introduction and
Background on Control Theory", "Adaptive Control and Neuroscience",
"Adaptive Learning Algorithms", "Cyber-Physical Systems and
Cooperative Control", "Applications". The diversity of the research
presented gives the reader a unique opportunity to explore a
comprehensive overview of a field of great interest to control and
system theorists. This book is intended for researchers and control
engineers in machine learning, adaptive control, optimization and
automatic control systems, including Electrical Engineers, Computer
Science Engineers, Mechanical Engineers, Aerospace/Automotive
Engineers, and Industrial Engineers. It could be used as a text or
reference for advanced courses in complex control systems. *
Collection of chapters from several well-known professors and
researchers that will showcase their recent work * Presents
different state-of-the-art control approaches and theory for
complex systems * Gives algorithms that take into consideration the
presence of modelling uncertainties, the unavailability of the
model, the possibility of cooperative/non-cooperative goals and
malicious attacks compromising the security of networked teams *
Real system examples and figures throughout, make ideas concrete
An integral element of software engineering is model engineering.
They both endeavor to minimize cost, time, and risks with quality
software. As such, model engineering is a highly useful field that
demands in-depth research on the most current approaches and
techniques. Only by understanding the most up-to-date research can
these methods reach their fullest potential. Advancements in
Model-Driven Architecture in Software Engineering is an essential
publication that prepares readers to exercise modeling and model
transformation and covers state-of-the-art research and
developments on various approaches for methodologies and platforms
of model-driven architecture, applications and software development
of model-driven architecture, modeling languages, and modeling
tools. Highlighting a broad range of topics including cloud
computing, service-oriented architectures, and modeling languages,
this book is ideally designed for engineers, programmers, software
designers, entrepreneurs, researchers, academicians, and students.
Advances in Computers carries on a tradition of excellence,
presenting detailed coverage of innovations in computer hardware,
software, theory, design, and applications. The book provides
contributors with a medium in which they can explore their subjects
in greater depth and breadth than journal articles typically allow.
The articles included in this book will become standard references,
with lasting value in this rapidly expanding field.
Intelligent systems and related designs have become important
instruments leading to profound innovations in automated control
and interaction with computers and machines. Such systems depend
upon established methods and tools for solving complex learning and
decision-making problems under uncertain and continuously varying
conditions. Intelligent Applications for Heterogeneous System
Modeling and Design examines the latest developments in intelligent
system engineering being used across industries with an emphasis on
transportation, aviation, and medicine. Focusing on the latest
trends in artificial intelligence, systems design and testing, and
related topic areas, this publication is designed for use by
engineers, IT specialists, academicians, and graduate-level
students.
The development of artificial intelligence (AI) involves the
creation of computer systems that can do activities that would
ordinarily require human intelligence, such as visual perception,
speech recognition, decision making, and language translation.
Through increasingly complex programming approaches, it has been
transforming and advancing the discipline of computer science.
Artificial Intelligence Methods and Applications in Computer
Engineering illuminates how today's computer engineers and
scientists can use AI in real-world applications. It focuses on a
few current and emergent AI applications, allowing a more in-depth
discussion of each topic. Covering topics such as biomedical
research applications, navigation systems, and search engines, this
premier reference source is an excellent resource for computer
scientists, computer engineers, IT managers, students and educators
of higher education, librarians, researchers, and academicians.
Machine Learning is evolving computation and its application like
never before. It is now widely recognized that machine learning is
playing a similar role as electricity played in modernizing the
world. From simple high school science projects to large-scale
radio astronomy, machine learning has revolutionized it all.
However, a few of the applications stand out as transforming the
world and opening up a new era. The book intends to showcase
applications of machine learning that are leading us to the next
generation of computing and living standards. The book portrays the
application of machine learning to cutting-edge technologies that
are playing a prominent role in improving the quality of life and
the progress of civilization. The focus of the book is not just
machine learning, but its application to specific domains that are
resulting in substantial progress of civilization. It is ideal for
scientists and researchers, academic and corporate libraries,
students, lecturers and teachers, and practitioners and
professionals.
This book explores 10 unique facets of Internet health and safety,
including physical safety, information security, and the
responsible use of technology, offering takeaways from interviews
with experts in the field and suggestions for proactively improving
users' Internet safety. The Internet has become for many
people—especially students and young adults—an essential and
intrinsic part of their lives. It makes information available to be
shared worldwide, at any time; enables learning about any topic;
and allows for instantaneous communication. And it provides endless
entertainment as well. But the benefits of online access are
accompanied by serious potential risks. This book covers the key
elements of Internet health and safety, including physical safety,
information security, and the responsible use of technology. It
begins with an introductory essay that gives readers the necessary
conceptual framework, and then explains specific topics such as
cyberbullying, file sharing, online predators, Internet fraud, and
obscene and offensive content. The book also answers readers'
questions in a "Q & A" section with a subject expert and
includes a directory of resources that provides additional
information and serves as a gateway to further study.
Even though terrorism poses an increasing threat to multinational
companies, corporate leaders can thwart attacks by learning to
navigate the complexities of foreign governments, social unrest,
and cultural dissonance. Multinational corporations are on the
front lines of terrorism and cyberattacks—two of the world's
biggest threats to global security. How can corporate leaders
mitigate their organizations' risks and develop an infrastructure
that detects and deters a security menace before it happens? This
timely reference lays out essential political context and
historical background to help executives identify contemporary
threats and understand the interconnections between threat dynamics
in an increasingly dangerous international environment. This
compelling work is organized into seven chapters. The beginning
chapters profile the specific risks for multinational companies and
detail which global—and regional—factors might propagate
violence targeted at American-based businesses. Next, two
historical case studies on terrorist assaults at Tigantourine and
Mombasa illustrate how counterterrorism can successfully thwart
potential attacks against business targets. The final part
describes industrial espionage and criminal activity and then
outlines a corporate counterterror blueprint to combat the prospect
of terrorism, providing specific recommendations for preventative
measures.
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