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Books > Computing & IT > General theory of computing > General
Digital humanities is a dynamic and emerging field that aspires to
enhance traditional research and scholarship through digital media.
Although countries around the world are witnessing the widespread
adoption of digital humanities, only a small portion of the
literature discusses its development in the Asia Pacific region.
Digital Humanities and Scholarly Research Trends in the
Asia-Pacific provides innovative insights into the development of
digital humanities and their ability to facilitate academic
exchange and preserve cultural heritage. The content covers
challenges including the need to maintain digital humanities
momentum in libraries and research communities, to increase
international collaboration, to maintain and promote developed
digital projects, to deploy and redeploy resources to support
research, and to build new skillsets and new professionals in the
library. It is designed for librarians, government agencies,
industry professionals, academicians, and researchers.
In this technological age, the information technology (IT) industry
is an important facet of society and business. The IT industry is
able to become more efficient and successful through the
examination of its structure and a larger understanding of the
individuals that work in the field. Multidisciplinary Perspectives
on Human Capital and Information Technology Professionals is a
critical scholarly resource that focuses on IT as an industry and
examines it from an array of academic viewpoints. Featuring
coverage on a wide range of topics, such as employee online
communities, role stress, and competence frameworks, this book is
targeted toward academicians, students, and researchers seeking
relevant research on IT as an industry.
Due to the increasing availability of affordable internet services,
the number of users, and the need for a wider range of
multimedia-based applications, internet usage is on the rise. With
so many users and such a large amount of data, the requirements of
analyzing large data sets leads to the need for further
advancements to information processing. Big Data Processing with
Hadoop is an essential reference source that discusses possible
solutions for millions of users working with a variety of data
applications, who expect fast turnaround responses, but encounter
issues with processing data at the rate it comes in. Featuring
research on topics such as market basket analytics, scheduler load
simulator, and writing YARN applications, this book is ideally
designed for IoT professionals, students, and engineers seeking
coverage on many of the real-world challenges regarding big data.
Changing business environments and information technology
advancements fundamentally reshaped the traditional information
landscape in our contemporary society, urging companies to seek
innovative ways to diffuse and manage assets on a global scale. It
is crucial for society to understand the new methodologies and
common practices that organizations can utilize to leverage their
knowledge into practice. Global Information Diffusion and
Management in Contemporary Society is an essential reference source
featuring research on the development and implementation of
contemporary global information management initiatives in
organizations. Including coverage on a multitude of topics such as
data security, global manufacturing, and information governance,
this book explores the importance of information management in a
global context. This book is ideally designed for managers,
information systems specialists, professionals, researchers, and
administrators seeking current research on the theories and
applications of global information management.
With new technologies, such as computer vision, internet of things,
mobile computing, e-governance and e-commerce, and wide
applications of social media, organizations generate a huge volume
of data and at a much faster rate than several years ago. Big data
in large-/small-scale systems, characterized by high volume,
diversity, and velocity, increasingly drives decision making and is
changing the landscape of business intelligence. From governments
to private organizations, from communities to individuals, all
areas are being affected by this shift. There is a high demand for
big data analytics that offer insights for computing efficiency,
knowledge discovery, problem solving, and event prediction. To
handle this demand and this increase in big data, there needs to be
research on innovative and optimized machine learning algorithms in
both large- and small-scale systems. Applications of Big Data in
Large- and Small-Scale Systems includes state-of-the-art research
findings on the latest development, up-to-date issues, and
challenges in the field of big data and presents the latest
innovative and intelligent applications related to big data. This
book encompasses big data in various multidisciplinary fields from
the medical field to agriculture, business research, and smart
cities. While highlighting topics including machine learning, cloud
computing, data visualization, and more, this book is a valuable
reference tool for computer scientists, data scientists and
analysts, engineers, practitioners, stakeholders, researchers,
academicians, and students interested in the versatile and
innovative use of big data in both large-scale and small-scale
systems.
The idea of this book grew out of a symposium that was held at
Stony Brook in September 2012 in celebration of David S.Warren's
fundamental contributions to Computer Science and the area of Logic
Programming in particular. Logic Programming (LP) is at the nexus
of Knowledge Representation, Artificial Intelligence, Mathematical
Logic, Databases, and Programming Languages. It is fascinating and
intellectually stimulating due to the fundamental interplay among
theory, systems, and applications brought about by logic. Logic
programs are more declarative in the sense that they strive to be
logical specifications of "what" to do rather than "how" to do it,
and thus they are high-level and easier to understand and maintain.
Yet, without being given an actual algorithm, LP systems implement
the logical specifications automatically. Several books cover the
basics of LP but focus mostly on the Prolog language with its
incomplete control strategy and non-logical features. At the same
time, there is generally a lack of accessible yet comprehensive
collections of articles covering the key aspects in declarative LP.
These aspects include, among others, well-founded vs. stable model
semantics for negation, constraints, object-oriented LP, updates,
probabilistic LP, and evaluation methods, including top-down vs.
bottom-up, and tabling. For systems, the situation is even less
satisfactory, lacking accessible literature that can help train the
new crop of developers, practitioners, and researchers. There are a
few guides onWarren's Abstract Machine (WAM), which underlies most
implementations of Prolog, but very little exists on what is needed
for constructing a state-of-the-art declarative LP inference
engine. Contrast this with the literature on, say, Compilers, where
one can first study a book on the general principles and algorithms
and then dive in the particulars of a specific compiler. Such
resources greatly facilitate the ability to start making meaningful
contributions quickly. There is also a dearth of articles about
systems that support truly declarative languages, especially those
that tie into first-order logic, mathematical programming, and
constraint solving. LP helps solve challenging problems in a wide
range of application areas, but in-depth analysis of their
connection with LP language abstractions and LP implementation
methods is lacking. Also, rare are surveys of challenging
application areas of LP, such as Bioinformatics, Natural Language
Processing, Verification, and Planning. The goal of this book is to
help fill in the previously mentioned void in the LP literature. It
offers a number of overviews on key aspects of LP that are suitable
for researchers and practitioners as well as graduate students. The
following chapters in theory, systems, and applications of LP are
included.
As technology weaves itself more tightly into everyday life,
socio-economic development has become intricately tied to these
ever-evolving innovations. Technology management is now an integral
element of sound business practices, and this revolution has opened
up many opportunities for global communication. However, such swift
change warrants greater research that can foresee and possibly
prevent future complications within and between organizations. The
Handbook of Research on Engineering Innovations and Technology
Management in Organizations is a collection of innovative research
that explores global concerns in the applications of technology to
business and the explosive growth that resulted. Highlighting a
wide range of topics such as cyber security, legal practice, and
artificial intelligence, this book is ideally designed for
engineers, manufacturers, technology managers, technology
developers, IT specialists, productivity consultants, executives,
lawyers, programmers, managers, policymakers, academicians,
researchers, and students.
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The Cendovian
(Hardcover)
Mark Hennessy; Edited by Rebecca Brewer, Smulski Lauren
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R816
Discovery Miles 8 160
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Ships in 18 - 22 working days
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Competition in today's global market offers strong motivation for
the development of sophisticated tools within computer science. The
neuron multi-functional technology platform is a developing field
of study that regards the various interactive approaches that can
be applied within this subject matter. As advancing technologies
continue to emerge, managers and researchers need a compilation of
research that discusses the advancements and specific
implementations of these intelligent approaches with this platform.
Avatar-Based Control, Estimation, Communications, and Development
of Neuron Multi-Functional Technology Platforms is a pivotal
reference source that provides vital research on the application of
artificial and natural approaches towards neuron-based programs.
While highlighting topics such as natural intelligence,
neurolinguistics, and smart data storage, this publication presents
techniques, case studies, and methodologies that combine the use of
intelligent artificial and natural approaches with optimization
techniques for facing problems and combines many types of hardware
and software with a variety of communication technologies to enable
the development of innovative applications. This book is ideally
designed for researchers, practitioners, scientists, field experts,
professors, and students seeking current research on the
optimization of avatar-based advancements in multifaceted
technology systems.
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