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Mathematics in Cyber Research
by Paul L. GoethalsIn the last decade, both scholars and practitioners have sought novel ways to address the problem of cybersecurity. Innovative outcomes have included applications such as blockchain as well as creative methods for cyber forensics, software development, and intrusion prevention. Accompanying these technological advancements, discussion on cyber matters at national and international levels has focused primarily on the topics of law, policy, and strategy. The objective of these efforts is typically to promote security by establishing agreements among stakeholders on regulatory activities. Varying levels of investment in cyberspace, however, comes with varying levels of risk; in some ways, this can translate directly to the degree of emphasis for pushing substantial change. At the very foundation or root of cyberspace systems and processes are tenets and rules governed by principles in mathematics. Topics such as encrypting or decrypting file transmissions, modeling networks, performing data analysis, quantifying uncertainty, measuring risk, and weighing decisions or adversarial courses of action represent a very small subset of activities highlighted by mathematics. To facilitate education and a greater awareness of the role of mathematics in cyber systems and processes, a description of research in this area is needed. Mathematics in Cyber Research aims to familiarize educators and young researchers with the breadth of mathematics in cyber-related research. Each chapter introduces a mathematical sub-field, describes relevant work in this field associated with the cyber domain, provides methods and tools, as well as details cyber research examples or case studies. Features One of the only books to bring together such a diverse and comprehensive range of topics within mathematics and apply them to cyber research. Suitable for college undergraduate students or educators that are either interested in learning about cyber-related mathematics or intend to perform research within the cyber domain. The book may also appeal to practitioners within the commercial or government industry sectors. Most national and international venues for collaboration and discussion on cyber matters have focused primarily on the topics of law, policy, strategy, and technology. This book is among the first to address the underpinning mathematics.
Mathematics in Programming
by Xinyu LiuThe book presents the mathematical view and tools of computer programming with broad and friendly context. It explains the basic concepts such as recursion, computation model, types, data, and etc. The book serves as an introductory and reference guide to the engineers, students, researchers, and professionals who are interested in functional programming, type system, and computer programming languages. The book covers seven topics. Firstly, it lays out the number system based on Peano Axioms and demonstrates the isomorphic computer data structures. Then, it introduces Lambda calculus as a computing model and recursion, an important programming structure, with the Y-combinator. It next presents the basic abstract algebra, including group and fields, and provides a friendly introduction to Galois theory. After that, it uses category theory as a tool to explain several concepts in computer programming, including the type system, polymorphism, null handler, and recursive data types, then followed by an application of program optimization. In the last two chapters, the author shows how to program with the concept of infinity through stream and lazy evaluation, and then explains the naïve set theory and transfinite numbers, from which the logic paradox arises. Finally, it introduces four historical views of mathematical foundation, as well as Gödel’s incompleteness theorems developed in 1930s, and how they define the boundaries of computer programming. Additionally, the book provides biographies, stories, and anecdotes of 25 mathematicians, along with over 130 exercises and their corresponding answers.
Mathematics of Bioinformatics
by Sergey Petoukhov Matthew HeMathematics of Bioinformatics: Theory, Methods, and Applications provides a comprehensive format for connecting and integrating information derived from mathematical methods and applying it to the understanding of biological sequences, structures, and networks. Each chapter is divided into a number of sections based on the bioinformatics topics and related mathematical theory and methods. Each topic of the section is comprised of the following three parts: an introduction to the biological problems in bioinformatics; a presentation of relevant topics of mathematical theory and methods to the bioinformatics problems introduced in the first part; an integrative overview that draws the connections and interfaces between bioinformatics problems/issues and mathematical theory/methods/applications.
The Mathematics of Chip-Firing (Discrete Mathematics and Its Applications)
by Caroline J. KlivansThe Mathematics of Chip-firing is a solid introduction and overview of the growing field of chip-firing. It offers an appreciation for the richness and diversity of the subject. Chip-firing refers to a discrete dynamical system — a commodity is exchanged between sites of a network according to very simple local rules. Although governed by local rules, the long-term global behavior of the system reveals fascinating properties. The Fundamental properties of chip-firing are covered from a variety of perspectives. This gives the reader both a broad context of the field and concrete entry points from different backgrounds. Broken into two sections, the first examines the fundamentals of chip-firing, while the second half presents more general frameworks for chip-firing. Instructors and students will discover that this book provides a comprehensive background to approaching original sources. Features: Provides a broad introduction for researchers interested in the subject of chip-firing The text includes historical and current perspectives Exercises included at the end of each chapter About the Author: Caroline J. Klivans received a BA degree in mathematics from Cornell University and a PhD in applied mathematics from MIT. Currently, she is an Associate Professor in the Division of Applied Mathematics at Brown University. She is also an Associate Director of ICERM (Institute for Computational and Experimental Research in Mathematics). Before coming to Brown she held positions at MSRI, Cornell and the University of Chicago. Her research is in algebraic, geometric and topological combinatorics.
Mathematics of Complexity and Dynamical Systems
by Robert A. MeyersMathematics of Complexity and Dynamical Systems is an authoritative reference to the basic tools and concepts of complexity, systems theory, and dynamical systems from the perspective of pure and applied mathematics. Complex systems are systems that comprise many interacting parts with the ability to generate a new quality of collective behavior through self-organization, e.g. the spontaneous formation of temporal, spatial or functional structures. These systems are often characterized by extreme sensitivity to initial conditions as well as emergent behavior that are not readily predictable or even completely deterministic. The more than 100 entries in this wide-ranging, single source work provide a comprehensive explication of the theory and applications of mathematical complexity, covering ergodic theory, fractals and multifractals, dynamical systems, perturbation theory, solitons, systems and control theory, and related topics. Mathematics of Complexity and Dynamical Systems is an essential reference for all those interested in mathematical complexity, from undergraduate and graduate students up through professional researchers.
Mathematics of Discrete Structures for Computer Science
by Gordon J. PaceMathematics plays a key role in computer science, some researchers would consider computers as nothing but the physical embodiment of mathematical systems. And whether you are designing a digital circuit, a computer program or a new programming language, you need mathematics to be able to reason about the design -- its correctness, robustness and dependability. This book covers the foundational mathematics necessary for courses in computer science. The common approach to presenting mathematical concepts and operators is to define them in terms of properties they satisfy, and then based on these definitions develop ways of computing the result of applying the operators and prove them correct. This book is mainly written for computer science students, so here the author takes a different approach: he starts by defining ways of calculating the results of applying the operators and then proves that they satisfy various properties. After justifying his underlying approach the author offers detailed chapters covering propositional logic, predicate calculus, sets, relations, discrete structures, structured types, numbers, and reasoning about programs. The book contains chapter and section summaries, detailed proofs and many end-of-section exercises -- key to the learning process. The book is suitable for undergraduate and graduate students, and although the treatment focuses on areas with frequent applications in computer science, the book is also suitable for students of mathematics and engineering.
Mathematics of Epidemics on Networks
by Péter L. Simon Joel C. Miller István Z. KissThis textbook provides an exciting new addition to the area of network science featuring a stronger and more methodical link of models to their mathematical origin and explains how these relate to each other with special focus on epidemic spread on networks. The content of the book is at the interface of graph theory, stochastic processes and dynamical systems. The authors set out to make a significant contribution to closing the gap between model development and the supporting mathematics. This is done by: Summarising and presenting the state-of-the-art in modeling epidemics on networks with results and readily usable models signposted throughout the book; Presenting different mathematical approaches to formulate exact and solvable models; Identifying the concrete links between approximate models and their rigorous mathematical representation; Presenting a model hierarchy and clearly highlighting the links between model assumptions and model complexity; Providing a reference source for advanced undergraduate students, as well as doctoral students, postdoctoral researchers and academic experts who are engaged in modeling stochastic processes on networks; Providing software that can solve differential equation models or directly simulate epidemics on networks. Replete with numerous diagrams, examples, instructive exercises, and online access to simulation algorithms and readily usable code, this book will appeal to a wide spectrum of readers from different backgrounds and academic levels. Appropriate for students with or without a strong background in mathematics, this textbook can form the basis of an advanced undergraduate or graduate course in both mathematics and other departments alike.
Mathematics of Game Development: A Collection of Applied Lessons
by Jacob EnfieldThis introductory textbook introduces students to mathematical concepts and helps them to understand how they apply to the field of game development. This book covers the mathematical concepts commonly used in game development while providing opportunities to apply these concepts in the industry-standard Unity game engine.Most chapters cover mathematical concepts commonly used in game development, a downloadable game project that will provide a context to apply the math concepts learned, exercises for readers to practice the math concepts covered, and challenges for readers to further practice applying those concepts.This book will be ideal for any game development student looking to gain a grounding in the most relevant mathematical concepts to support their trade. It will also be useful as a stepping stone to digesting more advanced mathematical concepts for game development.
Mathematics of Program Construction
by Ralf Hinze Janis VoigtländerThis book constitutes the refereed proceedings of the 12th International Conference on Mathematics of Program Construction, MPC 2015, held in Königswinter, Germany, in June/July 2015. The 15 revised full papers presented together with two invited talks were carefully reviewed and selected from 20 submissions. The papers are about mathematical methods and tools put to use in program construction. They range from algorithmics to support for program construction in programming languages and systems. Some typical areas are type systems, program analysis and transformation, programming-language semantics, security, and program logics.
Mathematics of Program Construction: 13th International Conference, MPC 2019, Porto, Portugal, October 7–9, 2019, Proceedings (Lecture Notes in Computer Science #11825)
by Graham HuttonThis book constitutes the refereed proceedings of the 13th International Conference on Mathematics of Program Construction, MPC 2019, held in Porto, Portugal, in October 2019. The 15 revised full papers presented together with an invited paper were carefully reviewed and selected from 22 submissions. The papers deal with mathematical principles and techniques for constructing computer programs. They range from algorithmics to support for program construction in programming languages and systems. Some typical areas are type systems, program analysis and transformation, programming-language semantics, security, and program logics.
Mathematics of Program Construction: 14th International Conference, MPC 2022, Tbilisi, Georgia, September 26–28, 2022, Proceedings (Lecture Notes in Computer Science #13544)
by Ekaterina KomendantskayaThis book constitutes the refereed proceedings of the 14th International Conference on Mathematics of Program Construction, MPC 2022, held in Tbilisi, Georgia, in September 2022. The 9 revised full papers presented together with three invited papers were carefully reviewed and selected from 14 submissions. The papers deal with mathematical principles and techniques for constructing computer programs.
Mathematics of Public Health: Mathematical Modelling from the Next Generation (Fields Institute Communications #88)
by Jummy David Jianhong WuThis volume addresses SDG 3 from a mathematical standpoint, sharing novel perspectives of existing communicable disease modelling technologies of the next generation and disseminating new developments in modelling methodologies and simulation techniques. These methodologies are important for training and research in communicable diseases and can be applied to other threats to human health. The contributions contained in this collection/book cover a range of modelling techniques that have been and may be used to support decision-making on critical health related issues such as: Resource allocation Impact of climate change on communicable diseases Interaction of human behaviour change, and disease spread Disease outbreak trajectories projection Public health interventions evaluation Preparedness and mitigation of emerging and re-emerging infectious diseases outbreaks Development of vaccines and decisions around vaccine allocation and optimization The diseases and public health issues in this volume include, but are not limited to COVID-19, HIV, Influenza, antimicrobial resistance (AMR), the opioid epidemic, Lyme Disease, Zika, and Malaria. In addition, this volume compares compartmental models, agent-based models, machine learning and network. Readers have an opportunity to learn from the next generation perspective of evolving methodologies and algorithms in modelling infectious diseases, the mathematics behind them, the motivation for them, and some applications to supporting critical decisions on prevention and control of communicable diseases. This volume was compiled from the weekly seminar series organized by the Mathematics for Public Health (MfPH) Next Generation Network. This network brings together the next generation of modellers from across Canada and the world, developing the latest mathematical models, modeling methodologies, and analytical and simulation tools for communicable diseases of global public health concerns. The weekly seminar series provides a unique forum for this network and their invited guest speakers to share their perspectives on the status and future directions of mathematics of public health.
Mathematics of Quantum Computing: An Introduction
by Wolfgang SchererThis textbook presents the elementary aspects of quantum computing in a mathematical form. It is intended as core or supplementary reading for physicists, mathematicians, and computer scientists taking a first course on quantum computing. It starts by introducing the basic mathematics required for quantum mechanics, and then goes on to present, in detail, the notions of quantum mechanics, entanglement, quantum gates, and quantum algorithms, of which Shor's factorisation and Grover's search algorithm are discussed extensively. In addition, the algorithms for the Abelian Hidden Subgroup and Discrete Logarithm problems are presented and the latter is used to show how the Bitcoin digital signature may be compromised. It also addresses the problem of error correction as well as giving a detailed exposition of adiabatic quantum computing. The book contains around 140 exercises for the student, covering all of the topics treated, together with an appendix of solutions.
The Mathematics of the Uncertain: A Tribute To Pedro Gil (Studies In Systems, Decision And Control #142)
by Eduardo Gil Eva Gil Juan Gil María Ángeles GilThis book is a tribute to Professor Pedro Gil, who created the Department of Statistics, OR and TM at the University of Oviedo, and a former President of the Spanish Society of Statistics and OR (SEIO). In more than eighty original contributions, it illustrates the extent to which Mathematics can help manage uncertainty, a factor that is inherent to real life. Today it goes without saying that, in order to model experiments and systems and to analyze related outcomes and data, it is necessary to consider formal ideas and develop scientific approaches and techniques for dealing with uncertainty. Mathematics is crucial in this endeavor, as this book demonstrates. As Professor Pedro Gil highlighted twenty years ago, there are several well-known mathematical branches for this purpose, including Mathematics of chance (Probability and Statistics),Mathematics of communication (Information Theory), andMathematics of imprecision (Fuzzy Sets Theory and others).These branches often intertwine, since different sources of uncertainty can coexist, and they are not exhaustive. While most of the papers presented here address the three aforementioned fields, some hail from other Mathematical disciplines such as Operations Research; others, in turn, put the spotlight on real-world studies and applications. The intended audience of this book is mainly statisticians, mathematicians and computer scientists, but practitioners in these areas will certainly also find the book a very interesting read.
The Mathematics Teacher in the Digital Era: An International Perspective on Technology Focused Professional Development (Mathematics Education in the Digital Era #2)
by Nathalie Sinclair Alison Clark-Wilson Ornella RobuttiThis volume addresses the key issue of the initial education and lifelong professional learning of teachers of mathematics to enable them to realize the affordances of educational technology for mathematics. With invited contributions from leading scholars in the field, this volume contains a blend of research articles and descriptive texts.In the opening chapter John Mason invites the reader to engage in a number of mathematics tasks that highlight important features of technology-mediated mathematical activity. This is followed by three main sections:An overview of current practices in teachers’ use of digital technologies in the classroom and explorations of the possibilities for developing more effective practices drawing on a range of research perspectives (including grounded theory, enactivism and Valsiner’s zone theory).A set of chapters that share many common constructs (such as instrumental orchestration, instrumental distance and double instrumental genesis) and research settings that have emerged from the French research community, but have also been taken up by other colleagues.Meta-level considerations of research in the domain by contrasting different approaches and proposing connecting or uniting elements
Mathematik für Informatiker: Ein praxisbezogenes Lehrbuch
by Peter HartmannDieses Buch enthält den Mathematikstoff, der für das Informatikstudium in anwendungsorientierten Bachelorstudiengängen benötigt wird. Der Inhalt entspringt der langjährigen Lehrerfahrung des Autors.Das heißt:Sie finden immer wieder Anwendungen aus der Informatik.Sie lernen nicht nur mathematische Methoden, es werden auch die Denkweisen der Mathematik vermittelt, die eine Grundlage zum Verständnis der Informatik bilden.Beweise werden dann geführt, wenn Sie daraus etwas lernen können, nicht um des Beweisens willen.Mathematik ist für viele Studierende zunächst ein notwendiges Übel. Das Buch zeigt durch ausführliche Motivation, durch viele Beispiele, durch das ständige Aufzeigen von Querbezügen zwischen Mathematik und Informatik, dass Mathematik nicht nur nützlich ist, sondern interessant sein kann und manchmal auch Spaß macht.
Mathematik für Informatiker für Dummies (Für Dummies)
by Hans-Jürgen Steffens Christian Zöllner Kathrin MühlmannIst der Mathematik-Schein auch für Sie die größte Hürde im Studium? Dabei brauchen Sie als Informatiker solide mathematische Grundkenntnisse, um Algorithmen zu verstehen und mit Anwendern aus Naturwissenschaft und Technik auf Augenhöhe zu kommunizieren. Dieses Buch vermittelt Ihnen auf verständliche Weise und immer mit Querbezügen zur Informatik die mathematischen Grundlagen, die alle Informatiker benötigen: Aussagenlogik, Rekursion, Induktion, Relationen, Analysis, Wahrscheinlichkeitsrechnung, Statistik und lineare Algebra. Keine Sorge: Es werden lediglich Schulkenntnisse in Mathematik vorausgesetzt.
Mathematik für Ingenieure: Eine anschauliche Einführung für das praxisorientierte Studium
by Thomas Rießinger"Mathematik in entspannter Atmosphäre" ist das Leitbild dieses leicht verständlichen Lehrbuchs. Im Erzählstil und mit vielen Beispielen beleuchtet der Autor nicht nur die Höhere Mathematik, sondern er stellt auch den Lehrstoff in Bezug zu den Anwendungen. Die gesamte für den Ingenieurstudenten wichtige Mathematik wird in einem Band behandelt. Dies gelingt durch Verzicht auf abstrakte Höhen und durch eine prüfungsgerechte Stoffauswahl, die sich streng an den Bedürfnissen des späteren Ingenieurs ausrichtet. Das Buch kann vorlesungsbegleitend oder zum Selbststudium eingesetzt werden. Die 159 Übungsaufgaben mit Lösungen unterstützen das Einüben des Lehrstoffs und sind im Band "Übungsaufgaben zur Mathematik für Ingenieure" ausführlich durchgerechnet. Der "Brückenkurs" auf http://extras.springer.com/2013/978-3-642-36858-5 erleichtert Anfängern den Einstieg.
Mathematik für Ingenieure
by Thomas Rießinger"Mathematik in entspannter Atmosphäre" ist das Leitbild dieses leicht verständlichen Lehrbuchs. Im Erzählstil und mit vielen Beispielen beleuchtet der Autor nicht nur die Höhere Mathematik, sondern er stellt auch den Lehrstoff in Bezug zu den Anwendungen. Die gesamte für den Ingenieurstudenten wichtige Mathematik wird in einem Band behandelt. Dies gelingt durch Verzicht auf abstrakte Höhen und durch eine prüfungsgerechte Stoffauswahl, die sich streng an den Bedürfnissen des späteren Ingenieurs ausrichtet. Das Buch kann vorlesungsbegleitend oder zum Selbststudium eingesetzt werden. Die 159 Übungsaufgaben mit Lösungen unterstützen das Einüben des Lehrstoffs und sind im Band "Übungsaufgaben zur Mathematik für Ingenieure" ausführlich durchgerechnet.Der "Brückenkurs" beim Buch auf springer.com erleichtert Anfängern den Einstieg.
Mathematik kompakt
by Rainer Schwenkert Yvonne StryDas kompakte einbändige Werk bietet eine aktuelle Stoffauswahl mit Themen wie Wahrscheinlichkeitsrechnung und Statistik, dafür wird auf überflüssige Beweise verzichtet. Die Autoren präsentieren den gesamten Stoff in einem anschaulichen, aufgelockerten Stil - mit Zusammenfassungen und Verständnistests zu jedem Kapitel, Randnotizen für die schnelle Orientierung, Beispielen und Anwendungen sowie zahlreichen Übungsaufgaben mit Lösungen. Ergänzendes Material wie Folien und kommentierte Lösungen stehen im Internet zum Download bereit.
Mathematische Grundlagen der Informatik: Mathematisches Denken und Beweisen - Eine Einführung
by Christoph Meinel Martin MundhenkDie mathematischen Grundlagen der Informatik werden anhand von Definitionen und Beispielen anschaulich eingeführt. Ziel des Buches, nun in einer korrigierten und aktualisierten Fassung, ist es, systematisch die für die Informatik typischen und grundlegenden mathematischen Denkweisen vorzustellen – ohne dabei auf besondere, die übliche Schulmathematik übersteigende Vorkenntnisse aufzubauen.
Mathematische Grundlagen des überwachten maschinellen Lernens: Optimierungstheoretische Methoden
by Konrad EngelDieses Buch behandelt die gängigsten Methoden zur Klassifikation von digitalisierten Objekten. Jedem Objekt ist ein Punkt im Euklidischen Raum passender Dimension zugeordnet. Das Lernen basiert auf einer Menge von Punkten, für die die zugehörige Klasse bekannt ist. Eine Reduktion der Dimension sowie elementare und anspruchsvollere Methoden zur Ermittlung schnell berechenbarer Funktionen, mit denen man aus einem Punkt die zugehörige Klasse mit einer möglichst geringen Fehlerrate ableiten kann, werden hergeleitet und in einer einheitlichen Herangehensweise begründet. Die recht elementaren Beweise werden im Wesentlichen mit Mitteln der Linearen Algebra geführt, nur für die neuronalen Netze wird etwas Analysis benötigt.Die Produktfamilie WissensExpress bietet Ihnen Lehr- und Lernbücher in kompakter Form. Die Bücher liefern schnell und verständlich fundiertes Wissen.
Mathematische Methoden der Bioinformatik - Eine Einführung
by Werner TimischlGroße Datenmengen lassen sich ohne den Einsatz von einschlägigen Softwareprodukten kaum bearbeiten. Mit den bereitgestellten Algorithmen können Daten statistisch ausgewertet und Optimierungsaufgaben oder kombinatorische Problemstellungen gelöst werden. Auch wenn dies zumeist im „Black Box“-Verfahren geschieht, ist es doch hilfreich, etwa bei der Auswahl der Algorithmen oder bei der Einschätzung der erforderlichen Zeit-Ressourcen, die hinter den Algorithmen steckenden mathematischen Ideen zu kennen. Das Buch lädt Biologen und Mediziner ein, sich mit den mathematischen Grundlagen von ausgewählten Algorithmen der Bioinformatik vertraut zu machen. Es ist eine Einführung mit vielen durchgerechneten Beispielen und zahlreichen Aufgaben mit ausführlichen Lösungen zum Einüben der mathematischen Inhalte. Inhaltliche Schwerpunkte sind Matrizen, lineare Gleichungssysteme, Rekursionen, Abzähltechniken, diskrete dynamische Optimierung, Markov-Ketten, Hidden Markov-Modelle und distanzbasierte Klassifikationsverfahren.
Matheuristics: Algorithms and Implementations (EURO Advanced Tutorials on Operational Research)
by Vittorio Maniezzo Marco Antonio Boschetti Thomas StützleThis book is the first comprehensive tutorial on matheuristics. Matheuristics are based on mathematical extensions of previously known heuristics, mainly metaheuristics, and on original, area-specific approaches. This tutorial provides a detailed discussion of both contributions, presenting the pseudocodes of over 40 algorithms, abundant literature references, and for each case a step-by-step description of a sample run on a common Generalized Assignment Problem example. C++ source codes of all algorithms are available in an associated SW repository.
Mathletics: How Gamblers, Managers, and Fans Use Mathematics in Sports, Second Edition
by Wayne L. Winston Konstantinos Pelechrinis Scott NestlerHow to use math to improve performance and predict outcomes in professional sportsMathletics reveals the mathematical methods top coaches and managers use to evaluate players and improve team performance, and gives math enthusiasts the practical skills they need to enhance their understanding and enjoyment of their favorite sports—and maybe even gain the outside edge to winning bets. This second edition features new data, new players and teams, and new chapters on soccer, e-sports, golf, volleyball, gambling Calcuttas, analysis of camera data, Bayesian inference, ridge regression, and other statistical techniques. After reading Mathletics, you will understand why baseball teams should almost never bunt; why football overtime systems are unfair; why points, rebounds, and assists aren’t enough to determine who’s the NBA’s best player; and more.