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Books > Computing & IT > Computer programming > Algorithms & procedures
This title is a Pearson Global Edition. The Editorial team at
Pearson has worked closely with educators around the world to
include content which is especially relevant to students outside
the United States. The Third Edition of Data Abstraction and
Problem Solving with Java: Walls and Mirrors employs the analogies
of Walls (data abstraction) and Mirrors (recursion) to teach Java
programming design solutions, in a way that beginning students find
accessible. The book has a student-friendly pedagogical approach
that carefully accounts for the strengths and weaknesses of the
Java language. With this book, students will gain a solid
foundation in data abstraction, object-oriented programming, and
other problem-solving techniques.
In Algorithms Illuminated, Tim Roughgarden teaches the basics of
algorithms in the most accessible way imaginable. This Omnibus
Edition contains the complete text of Parts 1-4, with thorough
coverage of asymptotic analysis, graph search and shortest paths,
data structures, divide-and-conquer algorithms, greedy algorithms,
dynamic programming, and NP-hard problems. Hundreds of worked
examples, quizzes, and exercises, plus comprehensive online videos,
help readers become better programmers; sharpen their analytical
skills; learn to think algorithmically; acquire literacy with
computer science's greatest hits; and ace their technical
interviews.
High-performance computing (HPC) describes the use of connected
computing units to perform complex tasks. It relies on
parallelization techniques and algorithms to synchronize these
disparate units in order to perform faster than a single processor
could, alone. Used in industries from medicine and research to
military and higher education, this method of computing allows for
users to complete complex data-intensive tasks. This field has
undergone many changes over the past decade, and will continue to
grow in popularity in the coming years. Innovative Research
Applications in Next-Generation High Performance Computing aims to
address the future challenges, advances, and applications of HPC
and related technologies. As the need for such processors
increases, so does the importance of developing new ways to
optimize the performance of these supercomputers. This timely
publication provides comprehensive information for researchers,
students in ICT, program developers, military and government
organizations, and business professionals.
The aim of the book is to serve as a text for students learning
programming in 'C' on Data Structures such as array, linked list,
stack, queue, trees, graph and sorting and searching methodology.
The book illustrates in detail the methods, algorithms, functions
and implementation of each and every concept of data structures.
Algorithms are written in pseudo syntax i.e., near to 'C' language
for easy understanding. It contains worked examples to amplify the
material, and enhance the pedagogy. The content is not overburdened
with math, and instead pays attention to the key components of the
subject, especially link listing. By discussing the practical
applications of the subject, the author has lessened the dry theory
involved, and made the book more approachable.
In recent years, swarm intelligence has become a popular
computational approach among researchers working on optimization
problems throughout the globe. Several algorithms inside swarm
intelligence have been implemented due to their application to
real-world issues and other advantages. A specific procedure,
Fireworks Algorithm, is an emerging method that studies the
explosion process of fireworks within local areas. Applications of
this developing program are undiscovered, and research is necessary
for scientists to fully understand the workings of this innovative
system. The Handbook of Research on Fireworks Algorithms and Swarm
Intelligence is a pivotal reference source that provides vital
research on theory analysis, improvements, and applications of
fireworks algorithm. While highlighting topics such as convergence
rate, parameter applications, and global optimization analysis,
this publication explores up-to-date progress on the specific
techniques of this algorithm. This book is ideally designed for
researchers, data scientists, mathematicians, engineers, software
developers, postgraduates, and academicians seeking coverage on
this evolutionary computation method.
The latest edition of a classic text on concurrency and
distributed programming - from a winner of the ACM/SIGCSE Award for
Outstanding Contribution to Computer Science Education.
Text analysis tools aid in extracting meaning from digital content.
As digital text becomes more and more complex, new techniques are
needed to understand conceptual structure. Concept Parsing
Algorithms (CPA) for Textual Analysis and Discovery: Emerging
Research and Opportunities provides an innovative perspective on
the application of algorithmic tools to study unstructured digital
content. Highlighting pertinent topics such as semantic tools,
semiotic systems, and pattern detection, this book is ideally
designed for researchers, academics, students, professionals, and
practitioners interested in developing a better understanding of
digital text analysis.
Modern computing systems preserve all information in intricate
binary codes. The evolution of systems and technologies that aid in
this preservation process must be continually assessed to ensure
that they are keeping up with the demands of society. Formation
Methods, Models, and Hardware Implementation of Pseudorandom Number
Generators: Emerging Research and Opportunities is a crucial
scholarly resource that examines the current methodologies used in
number generator construction, and how they pertain to the overall
advancement of contemporary computer systems. Featuring coverage on
relevant topics such as cellular automata theory, inhomogeneous
cells, and sequence generators, this publication is ideal for
software engineers, computer programmers, academicians, students,
and researchers that are interested in staying abreast of
innovative trends within the computer engineering field.
Security video surveillance systems, such as homeland security and
national defence, rely on specific mathematical algorithms in order
to run effectively. It is essential for these parameters to be
understood in order to design and create a successful system. Video
Surveillance Techniques and Technologies presents empirical
research and acquired experience on the original solutions and
mathematical algorithms for motion detection and object
identification problems. Emphasising a wide variety of applications
of security systems, this book is an essential tool for graduate
students and professionals in the field of signal and image
processing applied in static/moving object detection, tracking, and
identification.
This book describes concepts and tools needed for water resources
management, including methods for modeling, simulation,
optimization, big data analysis, data mining, remote sensing,
geographical information system, game theory, conflict resolution,
System dynamics, agent-based models, multiobjective, multicriteria,
and multiattribute decision making and risk and uncertainty
analysis, for better and sustainable management of water resources
and consumption, thus mitigating the present and future global
water shortage crisis. It presents the applications of these tools
through case studies which demonstrate its benefits of proper
management of water resources systems. This book acts as a
reference for students, professors, industrial practitioners, and
stakeholders in the field of water resources and hydrology.
This textbook aims to help the reader develop an in-depth
understanding of logical reasoning and gain knowledge of the theory
of computation. The book combines theoretical teaching and
practical exercises; the latter is realised in Isabelle/HOL, a
modern theorem prover, and PAT, an industry-scale model checker. I
also give entry-level tutorials on the two software to help the
reader get started. By the end of the book, the reader should be
proficient in both software. Content-wise, this book focuses on the
syntax, semantics and proof theory of various logics; automata
theory, formal languages, computability and complexity. The final
chapter closes the gap with a discussion on the insight that links
logic with computation. This book is written for a high-level
undergraduate course or a Master's course. The hybrid skill set of
practical theorem proving and model checking should be helpful for
the future of readers should they pursue a research career or
engineering in formal methods.
This book discusses machine learning and artificial intelligence
(AI) for agricultural economics. It is written with a view towards
bringing the benefits of advanced analytics and prognostics
capabilities to small scale farmers worldwide. This volume provides
data science and software engineering teams with the skills and
tools to fully utilize economic models to develop the software
capabilities necessary for creating lifesaving applications. The
book introduces essential agricultural economic concepts from the
perspective of full-scale software development with the emphasis on
creating niche blue ocean products. Chapters detail several
agricultural economic and AI reference architectures with a focus
on data integration, algorithm development, regression, prognostics
model development and mathematical optimization. Upgrading
traditional AI software development paradigms to function in
dynamic agricultural and economic markets, this volume will be of
great use to researchers and students in agricultural economics,
data science, engineering, and machine learning as well as
engineers and industry professionals in the public and private
sectors.
This book focuses on the combination of IoT and data science, in
particular how methods, algorithms, and tools from data science can
effectively support IoT. The authors show how data science
methodologies, techniques and tools, can translate data into
information, enabling the effectiveness and usefulness of new
services offered by IoT stakeholders. The authors posit that if IoT
is indeed the infrastructure of the future, data structure is the
key that can lead to a significant improvement of human life. The
book aims to present innovative IoT applications as well as ongoing
research that exploit modern data science approaches. Readers are
offered issues and challenges in a cross-disciplinary scenario that
involves both IoT and data science fields. The book features
contributions from academics, researchers, and professionals from
both fields.
This book provides awareness of methods used for functional
encryption in the academic and professional communities. The book
covers functional encryption algorithms and its modern applications
in developing secure systems via entity authentication, message
authentication, software security, cyber security, hardware
security, Internet of Thing (IoT), cloud security, smart card
technology, CAPTCHA, digital signature, and digital watermarking.
This book is organized into fifteen chapters; topics include
foundations of functional encryption, impact of group theory in
cryptosystems, elliptic curve cryptography, XTR algorithm, pairing
based cryptography, NTRU algorithms, ring units, cocks IBE schemes,
Boneh-Franklin IBE, Sakai-Kasahara IBE, hierarchical identity based
encryption, attribute based Encryption, extensions of IBE and
related primitives, and digital signatures. Explains the latest
functional encryption algorithms in a simple way with examples;
Includes applications of functional encryption in information
security, application security, and network security; Relevant to
academics, research scholars, software developers, etc.
This book introduces the state-of-the-art algorithms for data and
computation privacy. It mainly focuses on searchable symmetric
encryption algorithms and privacy preserving multi-party
computation algorithms. This book also introduces algorithms for
breaking privacy, and gives intuition on how to design algorithm to
counter privacy attacks. Some well-designed differential privacy
algorithms are also included in this book. Driven by lower cost,
higher reliability, better performance, and faster deployment, data
and computing services are increasingly outsourced to clouds. In
this computing paradigm, one often has to store privacy sensitive
data at parties, that cannot fully trust and perform privacy
sensitive computation with parties that again cannot fully trust.
For both scenarios, preserving data privacy and computation privacy
is extremely important. After the Facebook-Cambridge Analytical
data scandal and the implementation of the General Data Protection
Regulation by European Union, users are becoming more privacy aware
and more concerned with their privacy in this digital world. This
book targets database engineers, cloud computing engineers and
researchers working in this field. Advanced-level students studying
computer science and electrical engineering will also find this
book useful as a reference or secondary text.
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