Mathematics of Discrete Structures for Computer Science

The connections between origami, mathematics, science, technology, and education have been a topic of considerable interest now for several decades. While many individuals have happened upon discrete

The conception of real-time control networks taking into account, as an integrating approach, both the specific aspects of information and knowledge processing and the dynamic and energetic particular

Based on the author’s introductory course at the University of Oregon, Explorations in Computing: An Introduction to Computer Science focuses on the fundamental idea of computation and offers insight

This engaging and accessible book presents a set of representative concepts connected by the theme of information security, demonstrating how each allows us to solve real problems. The discussions are

Provides a solid integration of basic computing concepts with Pascal programming to foster the use of programming as a problem-solving tool. Topics run the gamut from algorithms and artificial intelli

The aim of IeCCS 2005, which was held in May 2005, was to bring together leading scientists of the international Computer Science community and to attract original research papers. This volume in the

Computer science is a fast growing field and has occupied an important place in today’s time. The subject of computer science studies the theories and experiments used in building new designs of compu

Everything students need to succeed on the AP Computer Science A Exam, with (4 full-length practice tests!).AP Computer Science A Prep, 2023 provides students with a comprehensive approach to this course and exam, including thorough subject reviews of all relevant topics, techniques to help them strategically approach the exam, and plenty of drills and practice questions to hone their skills.

This introduction to the conceptual design of structures for students of architecture and civil engineering presents the material in separate columns of text and illustrations. Part I explains the ba

This outstanding introductory treatment is geared toward advanced undergraduates and graduate students in all areas that require knowledge of graph theory. The first nine chapters constitute

This 5-volume set (CCIS 214-CCIS 218) constitutes the refereed proceedings of the International Conference on Computer Science, Environment, Ecoinformatics, and Education, CSEE 2011, held in Wuhan, Ch

This 5-volume set (CCIS 214-CCIS 218) constitutes the refereed proceedings of the International Conference on Computer Science, Environment, Ecoinformatics, and Education, CSEE 2011, held in Wuhan, Ch

This 5-volume set (CCIS 214-CCIS 218) constitutes the refereed proceedings of the International Conference on Computer Science, Environment, Ecoinformatics, and Education, CSEE 2011, held in Wuhan, Ch

This 5-volume set (CCIS 214-CCIS 218) constitutes the refereed proceedings of the International Conference on Computer Science, Environment, Ecoinformatics, and Education, CSEE 2011, held in Wuhan, Ch

This two-volume set (CCIS 152 and CCIS 153) constitutes the refereed proceedings of the International Conference on Computer Science and Information Engineering, CSIE 2011, held in Zhengzhou, China, i

1 Computer Basics2 HTML and Web Pages3 The Internet and the Web4 JavaScript and Dynamic Web Pages5 JavaScript and User Interaction6 The History of Computers7 Functions and Randomness8 Algorithms and P

"When Ben discovers that his Facebook page has been changed, he is worried. Then someone sends emails from his account! Have his personal and work files been hacked? This book looks at the topics of c

Synthesis of Computational Structures for Analog Signal Processing focuses on analysis and design of analog signal processing circuits. The author presents a multitude of design techniques for improvi

This book is the first volume of an intensive “Russian-style” two-year graduate course in abstract algebra, and introduces readers to the basic algebraic structures – fields, rings, modules, algebras,

This Element aims to present an outline of mathematics and its history, with particular emphasis on events that shook up its philosophy. It ranges from the discovery of irrational numbers in ancient Greece to the nineteenth- and twentieth-century discoveries on the nature of infinity and proof. Recurring themes are intuition and logic, meaning and existence, and the discrete and the continuous. These themes have evolved under the influence of new mathematical discoveries and the story of their evolution is, to a large extent, the story of philosophy of mathematics.

While many individuals have discovered discrete connections among origami, mathematics, science, technology, and education during the twentieth century, the field really took off when previously isola

This textbook on aircraft structures is aimed at undergraduate students of aeronautical engineering and covers the fundamentals of elasticity and aircraft structural analysis and the related topics of

Elastic structures, conceived as slender bodies able to transmit loads, have been studied by scientists and engineers for centuries. By the seventeenth century several useful theories of elastic structures had emerged, with applications to civil and mechanical engineering problems. In recent years improved mathematical tools have extended applications into new areas such as geomechanics and biomechanics. This book, first published in 1998, offers a critically filtered collection of the most significant theories dealing with elastic slender bodies. It includes mathematical models involving elastic structures, which are used to solve practical problems with particular emphasis on nonlinear problems. This collection of interesting and important problems in elastic structures will appeal to a broad range of scientists, engineers and graduate students working in the area of structural mechanics.

Elastic structures, conceived as slender bodies able to transmit loads, have been studied by scientists and engineers for centuries. By the seventeenth century several useful theories of elastic structures had emerged, with applications to civil and mechanical engineering problems. In recent years improved mathematical tools have extended applications into new areas such as geomechanics and biomechanics. This book, first published in 1998, offers a critically filtered collection of the most significant theories dealing with elastic slender bodies. It includes mathematical models involving elastic structures, which are used to solve practical problems with particular emphasis on nonlinear problems. This collection of interesting and important problems in elastic structures will appeal to a broad range of scientists, engineers and graduate students working in the area of structural mechanics.

This volume presents the major outcome of the IUTAM symposium on Advanced Materials Modeling for Structures . It discusses advances in high temperature materials research, and also to provides a discu

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every cha

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every cha