Mathematics of Discrete Structures for Computer Science

Computer Vision: A Modern Approach, 2e, is appropriate for upper-division undergraduate- and graduate-level courses in computer vision found in departments of Computer Science, Computer Engineering an

This book serves as a valuable resource for mathematics and science teachers at secondary school level, teenagers and parents. It contains written versions of Royal Institution masterclasses on a wide

Information retrieval is a sub-field of computer science that deals with the automated storage and retrieval of documents. Providing the latest information retrieval techniques, this guide discusses I

The Courage to Soar Higher was written for two main purposes. The first was to tell the story of the National Aeronautics and Space Administration (NASA) and the United States (U.S.) space program wit

The integration of scientific knowledge and military power began long before theManhattan Project. In the third century BC, Archimedes was renowned for his research in mechanicsand mathematics as well

Recent years have seen the development of powerful tools for verifying hardware and software systems, as companies worldwide realise the need for improved means of validating their products. There is increasing demand for training in basic methods in formal reasoning so that students can gain proficiency in logic-based verification methods. The second edition of this successful textbook addresses both those requirements, by continuing to provide a clear introduction to formal reasoning which is both relevant to the needs of modern computer science and rigorous enough for practical application. Improvements to the first edition have been made throughout, with extra and expanded sections on SAT solvers, existential/universal second-order logic, micro-models, programming by contract and total correctness. The coverage of model-checking has been substantially updated. Further exercises have been added. Internet support for the book includes worked solutions for all exercises for teachers,

The goal of this book is to present a unified mathematical treatment of diverse problems in mathematics, physics, computer science, and engineer- ing using geometric algebra. Geometric algebra was inv

Is your worldview enlightened enough to accommodate both science and God at the same time?Dr. Michael Guillen, a best-selling author, Emmy award-winning journalist and former physics instructor at Harvard, used to be an Atheist--until science changed his mind. Once of the opinion that people of faith are weak, small-minded folks who just don't understand science, Dr. Guillen ultimately concluded that not only does science itself depend on faith, but faith is actually the mightiest power in the universe.In Believing Is Seeing, Dr. Guillen recounts the fascinating story of his journey from Atheism to Christianity, citing the latest discoveries in neuroscience, physics, astronomy, and mathematics to pull back the curtain on the mystery of faith as no one ever has.Is it true that "seeing is believing?" Or is it possible that reality can be perceived most clearly with the eyes of faith--and that truth is bigger than proof? Let Dr. Guillen be your guide as he brilliantly argues for a large a

This is an introductory textbook on computational methods and techniques intended for undergraduates at the sophomore or junior level in the fields of science, mathematics, and engineering. It provide

This SpringerBrief provides an interdisciplinary synthesis based on psychology, logic, mathematics, cognitive science, and the history of science. It presents psychology as a science that suffers from

This book helps the undergraduate and graduate student in computer science better design and conduct computer science research—particularly with an eye toward developing and writing a successful gradu

Computer scientists, electrical engineers, and other researchers from India and Iran present 12 essays on the use of bio-inspired computing for information retrieval applications. They discuss the

Contributed by an international group of researchers working in computer science, engineering, psychology, and other fields, the 23 chapters in this volume explore the application of 3D virtual realit

AMERICAN GOVERNMENT AND POLITICS TODAY is known nationwide for its balanced, unbiased, and up-to-date coverage of constitutional, governmental, political, social, and economic structures and their pro

AMERICAN GOVERNMENT AND POLITICS TODAY is known nationwide for its balanced, unbiased, and up-to-date coverage of constitutional, governmental, political, social, and economic structures and their pro

Theoretical computer science provides the foundations for understanding and exploiting the concepts and mechanisms in computing and information processing. This handbook will provide professionals and

Theoretical computer science provides the foundations for understanding and exploiting the concepts and mechanisms in computing and information processing. This handbook will provide professionals and

Linear algebra permeates mathematics,perhaps more so than any other single subject.It plays an essential role in pure and applied mathematics,statistics,computer science,and many aspects of physics and engineering.This book conveys in a user-friendly way the basic and advanced techniques of linear algebra from the point of view of a working analyst.The techniques are illustrated by a wide sample of applications and examples that are chosen to highlight the tools of the trade.In short,this is material that many of us wish we had been taught as graduate students.Roughly the first third of the book covers the basic material of a first course in linear algebra.The remaining chapters are devoted to applications drawn from vector calculus,numerical analysis,control theory,complex analysis,convexity and functional analysis.In particular,fixed point theorems,extremal problems,matrix equations,zero location and eigenvalue location problems,and matrices with nonnegative entries are discussed.App

This book provides a comprehensive foundation of machine learning. To answer the questions of what to learn, how to learn, what to get from learning, and how to evaluate, as well as what is meant by learning, the book focuses on the fundamental basics of machine learning, its methodology, theory, algorithms, and evaluations, together with some philosophical thinking on comparison between machine learning and human learning for machinery intelligence.The book is organized as follows: Introduction (Chapter 1), Evaluation (Chapter 2), Supervised learning (Chapters 3, 4, and 5), Unsupervised learning (Chapter 6), Representation learning (Chapter 7), Problem decomposition (Chapter 8), Ensemble learning (Chapter 9), Deep learning (Chapter 10), Application (Chapter 11), and Challenges (Chapter 12).The book can be used as a textbook for college, undergraduate, graduate and PhD students majored in computer science, automation, electronic engineering, communication, ect. It can also be used as

Algorithmic graph theory has been expanding at an extremely rapid rate since the middle of the twentieth century, in parallel with the growth of computer science and the accompanying utilization of computers, where efficient algorithms have been a prime goal. This book presents material on developments on graph algorithms and related concepts that will be of value to both mathematicians and computer scientists, at a level suitable for graduate students, researchers and instructors. The fifteen expository chapters, written by acknowledged international experts on their subjects, focus on the application of algorithms to solve particular problems. All chapters were carefully edited to enhance readability and standardize the chapter structure as well as the terminology and notation. The editors provide basic background material in graph theory, and a chapter written by the book's Academic Consultant, Martin Charles Golumbic (University of Haifa, Israel), provides background material on al

Many machine learning algorithms require real-valued feature vectors of data instances as inputs. By projecting data into vector spaces, representation learning techniques have achieved promising performance in many areas such as computer vision and natural language processing. There is also a need to learn representations for discrete relational data, namely networks or graphs. Network Embedding (NE) aims at learning vector representations for each node or vertex in a network to encode the topologic structure. Due to its convincing performance and efficiency, NE has been widely applied in many network applications such as node classification and link prediction.This book provides a comprehensive introduction to the basic concepts, models, and applications of network representation learning (NRL). The book starts with an introduction to the background and rising of network embeddings as a general overview for readers. Then it introduces the development of NE techniques by presenting se

The achievement of unity and perfection in human action begins with a struggle for these ideals in human thought. Dr. Klaus Vondung in his collection of essays that span four decades explores examples of this in different fields of human inquiry: striving for harmonious existential unity of talents and morals, intellect and emotion; seeking to make natural sciences consonant with the humanities and thereby moving toward a more universal, "perfect" science; and establishing unity in political structures and cultivating in this unity a homogenous society. Vondung devotes himself especially to exposing National Socialism, and revisits its perverted motivations and the murderous consequences of its ideology. Particular focus in following the thread of unity and perfection in human intellectual and practical ambitions ultimately hones in on the combination of religion and politics. Vondung in these essays unpacks the ways in which this continues to fascinate and disturb us, and in his exper

Network flow theory has been used across a number of disciplines, including theoretical computer science, operations research, and discrete math, to model not only problems in the transportation of goods and information, but also a wide range of applications from image segmentation problems in computer vision to deciding when a baseball team has been eliminated from contention. This graduate text and reference presents a succinct, unified view of a wide variety of efficient combinatorial algorithms for network flow problems, including many results not found in other books. It covers maximum flows, minimum-cost flows, generalized flows, multicommodity flows, and global minimum cuts and also presents recent work on computing electrical flows along with recent applications of these flows to classical problems in network flow theory.

Preprocessing, or data reduction, is a standard technique for simplifying and speeding up computation. Written by a team of experts in the field, this book introduces a rapidly developing area of preprocessing analysis known as kernelization. The authors provide an overview of basic methods and important results, with accessible explanations of the most recent advances in the area, such as meta-kernelization, representative sets, polynomial lower bounds, and lossy kernelization. The text is divided into four parts, which cover the different theoretical aspects of the area: upper bounds, meta-theorems, lower bounds, and beyond kernelization. The methods are demonstrated through extensive examples using a single data set. Written to be self-contained, the book only requires a basic background in algorithmics and will be of use to professionals, researchers and graduate students in theoretical computer science, optimization, combinatorics, and related fields.

This book covers computational group theory (CGT), an active, rapidly expanding field at the interface of mathematics and computer science. It is the first systematic effort to establish computing wit

The subject of Finite Geometries is a central part of discrete mathematics. Structures from Finite Geometries have led to solutions of open problems in extremal combinatorics, design theory, and codin

Meet four amazing women - astronauts, scientists, and mathematicians - who helped make space travel a reality. Illustrated with photography from the new LEGO® Ideas Women of NASA set, this book for children learning to read is a fun way to discover the achievements of some of space travel's greatest pioneers.Read about Mae Jemison, the first African American women to travel in space. Find out how Sally Ride inspired future scientists after her career as an astronaut. Discover how Margaret Hamilton created computer software for the Apollo mission, and see the stars with Nancy Grace Roman through the giant Hubble Telescope. Learn about NASA, and explore what life is like aboard the Endeavour Space Shuttle!Presented with fun images, simple vocabulary and lots of word repetition to engage young readers and help them build their literary skills,DK Reader L1:LEGOWomen ofNASA celebrates achievements in science, technology, engineering and mathematics.©2018 The LEGO Group.

This book presents theoretical and numerical tools for studying materials and structures under fully coupled thermomechanical conditions, with a special focus on composites. The authors cover many asp

This book is intended to be an introductory bioinformatics textbook for mathematicians and computer scientists. It focuses on using algorithms and discrete mathematics to solve biological problems. Th

Introduce young children to the building and programming of robots through playful, developmentally appropriate activities. Many early childhood professionals are unfamiliar with computer science, rob

The book is written for students studying Management Information Systems, Accounting Information Systems or Computer Science, and exposed to the subject for the first time. With 12 chapters of roughly

The first cultural history of early modern cryptography, this collection brings together scholars in history, literature, music, the arts, mathematics, and computer science who study ciphering and dec