Matematik til informatikfag

This book constitutes the refereed proceedings of the 16th Italian Workshop on Artificial Life and Evolutionary Computation, WIVACE 2022, held in Gaeta, Italy, during September 14¿16, 2022. The 21 full papers and 3 short papers included in this book were carefully reviewed and selected from 45 submissions. They were organized in topical sections as follows: answer set programming; networks and complex systems, metaheuristics, robotics, and machine learningChapters 7, 8, and 9 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book constitutes the proceedings of the 18th International Workshop on Algorithms and Models for the Web Graph, WAW 2023, held in Toronto, Canada, in May 23¿26, 2023.The 12 Papers presented in this volume were carefully reviewed and selected from 21 submissions. The aim of the workshop was understanding of graphs that arise from the Web and various user activities on the Web, and stimulate the development of high-performance algorithms and applications that exploit these graphs.

This book constitutes the refereed proceedings of the 13th International Conference on Algorithms and Complexity, CIAC 2023, which took place in Larnaca, Cyprus, during June 13¿16, 2023. The 25 full papers included in this book were carefully reviewed and selected from 49 submissions. They cover all important areas of research on algorithms and complexity such as algorithm design and analysis; sequential, parallel and distributed algorithms; data structures; computational and structural complexity; lower bounds and limitations of algorithms; randomized and approximation algorithms; parameterized algorithms and parameterized complexity classes; smoothed analysis of algorithms; alternatives to the worst-case analysis of algorithms (e.g., algorithms with predictions), on-line computation and competitive analysis, streaming algorithms, quantum algorithms and complexity, algorithms in algebra, geometry, number theory and combinatorics, computational geometry, algorithmic game theory and mechanism design, algorithmic economics (including auctions and contests), computational learning theory, computational biology and bioinformatics, algorithmic issues in communication networks, algorithms for discrete optimization (including convex optimization) and algorithm engineering.

Große 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.

This book analyzes the generation of the arrow-categories of a given category, which is a foundational and distinguishable Category Theory phenomena, in analogy to the foundational role of sets in the traditional set-based Mathematics, for defi nition of natural numbers as well. This inductive transformation of a category into the infinite hierarchy of the arrowcategories is extended to the functors and natural transformations. The author considers invariant categorial properties (the symmetries) under such inductive transformations. The book focuses in particular on Global symmetry (invariance of adjunctions) and Internal symmetries between arrows and objects in a category (in analogy to Field Theories like Quantum Mechanics and General Relativity). The second part of the book is dedicated to more advanced applications of Internal symmetry to Computer Science: for Intuitionistic Logic, Untyped Lambda Calculus with Fixpoint Operators, Labeled Transition Systems in Process Algebras and Modal logics as well as Data Integration Theory.

This book is intended for a first-semester course in calculus, which begins by posing a question: how do we model an epidemic mathematically? The authors use this question as a natural motivation for the study of calculus and as a context through which central calculus notions can be understood intuitively. The book¿s approach to calculus is contextual and based on the principle that calculus is motivated and elucidated by its relevance to the modeling of various natural phenomena. The authors also approach calculus from a computational perspective, explaining that many natural phenomena require analysis through computer methods. As such, the book also explores some basic programming notions and skills.

Dieses Lehrbuch bietet eine kompakte Einführung in die Grundlagen der Graphentheorie und die Methoden der Netzwerkanalyse. Zahlreiche praktische Beispiele und Übungsaufgaben mit Lösungsvorschlägen helfen Leser:innen dabei, die theoretischen Konzepte besser zu verstehen und anzuwenden. Dabei werden unterschiedliche Technologien und Programmiersprachen verwendet, um ein breites Spektrum an Anwendungen abzudecken. Darüber hinaus beleuchten spezielle Kapitel die Methodik mit Blick auf die Planung und Durchführung eigener Netzwerkanalyseprojekte sowie ethische und datenschutzrechtliche Aspekte. So liefert das Buch nicht nur einen theoretischen Überblick, sondern auch praktische Tipps und Anleitungen für die Untersuchung eigener netzwerkanalytischer Fragestellungen. Dieses Buch eignet sich nicht nur als Nachschlagewerk für Studierende und Dozierende vielfältiger Fachdisziplinen mit curricularem Bezug zum Thema, sondern auch als Ergänzung des Repertoires von Praktiker:innen im Bereich Data Science mit Interesse an der Untersuchung von Netzwerken. Ob als theoretischer Einstieg oder als praktischer Ratgeber - dieses Buch leistet einen Beitrag für die Untersuchung und Analyse von Netzwerken und bietet eine Grundlage für weiterführende Studien und Projekte.

This book demonstrates how to formally model various mathematical domains (including algorithms operating in these domains) in a way that makes them amenable to a fully automatic analysis by computer software.The presented domains are typically investigated in discrete mathematics, logic, algebra, and computer science; they are modeled in a formal language based on first-order logic which is sufficiently rich to express the core entities in whose correctness we are interested: mathematical theorems and algorithmic specifications. This formal language is the language of RISCAL, a ¿mathematical model checker¿ by which the validity of all formulas and the correctness of all algorithms can be automatically decided. The RISCAL software is freely available; all formal contents presented in the book are given in the form of specification files by which the reader may interact with the software while studying the corresponding book material.

This book constitutes the refereed proceedings of the 25th International Conference on Applications of Evolutionary Computation, EvoApplications 2023, held as part of Evo*2023, in April 2023, co-located with the Evo*2023 events EuroGP, EvoCOP, and EvoMUSART. The EuroGP focused on the technique of genetic programming, EvoCOP targeted evolutionary computation in combinatorial optimization, and EvoMUSART was dedicated to evolved and bio-inspired music, sound, art, and design.The EvoApplications 2023 presents papers on the different areas: Analysis of Evolutionary Computation Methods: Theory, Empirics, and Real-World Applications, Applications of Bio-inspired Techniques on Social Networks, Evolutionary Computation in Edge, Fog, and Cloud Computing, Evolutionary Computation in Image Analysis, Signal Processing, and Pattern Recognition and others.

This book presents a selection of peer-reviewed contributions on the latest developments in time series analysis and forecasting, presented at the 7th International Conference on Time Series and Forecasting, ITISE 2021, held in Gran Canaria, Spain, July 19-21, 2021. It is divided into four parts. The first part addresses general modern methods and theoretical aspects of time series analysis and forecasting, while the remaining three parts focus on forecasting methods in econometrics, time series forecasting and prediction, and numerous other real-world applications. Covering a broad range of topics, the book will give readers a modern perspective on the subject.The ITISE conference series provides a forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the foundations, theory, models and applications of time series analysis and forecasting. It focuses on interdisciplinary research encompassing computer science, mathematics,statistics and econometrics.

The adoption of multilayer analysis techniques is rapidly expanding across all areas of knowledge, from social sciences (the first facing the complexity of such structures, decades ago) to computer science, from biology to engineering. However, until now, no book has dealt exclusively with the analysis and visualization of multilayer networks. Multilayer Networks: Analysis and Visualization provides a guided introduction to one of the most complete computational frameworks, named muxViz, with introductory information about the underlying theoretical aspects and a focus on the analytical side. Dozens of analytical scripts and examples to use the muxViz library in practice, by means of the Graphical User Interface or by means of the R scripting language, are provided. In addition to researchers in the field of network science, as well as practitioners interested in network visualization and analysis, this book will appeal to researchers without strong technical or computer science background who want to learn how to use muxViz software, such as researchers from humanities, social science and biology: audiences which are targeted by case studies included in the book. Other interdisciplinary audiences include computer science, physics, neuroscience, genetics, urban transport and engineering, digital humanities, social and computational social science.Readers will learn how to use, in a very practical way (i.e., without focusing on theoretical aspects), the algorithms developed by the community and implemented in the free and open-source software muxViz. The data used in the book is available on a dedicated (open and free) site.

This book constitutes the refereed proceedings of the 23rd European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2023, held as part of Evo*2023, in Brno, Czech Republic in April 2023, co-located with the Evo*2023 events: EvoMUSART, EvoApplications, and EuroGP.The 15 revised full papers presented in this book were carefully reviewed and selected from 32 submissions. They present recent theoretical and experimental advances in combinatorial optimization, evolutionary algorithms, and related research fields.

These are the proceedings of Eurocrypt 2010, the 29th in the series of Eu- pean conferences on the Theory and Application of Cryptographic Techniques. The conference was sponsored by the International Association for Cryptologic Research and held on the French Riviera, May 30¿June 3, 2010. A total of 191 papers were received of which 188 were retained as valid submissions. These were each assigned to at least three Program Committee members and a total of 606 review reports were produced. The printed record of the reviews and extensive online discussions that followed would be almost as voluminous as these proceedings. In the end 35 submissions were accepted with twosubmissionpairsbeingmergedtogive33paperspresentedattheconference. The ?nal papers in these proceedings were not subject to a second review before publication and the authors are responsible for their contents. The ProgramCommittee, listed on the next page, deservesparticular thanks for all their hard work, their outstanding expertise, and their constant c- mitment to all aspects of the evaluation process. These thanks are of course extended to the very many external reviewers who took the time to help out during the evaluation process.It was also a greatpleasure to honor and welcome Moti Yung who gave the 2010 IACR Distinguished Lecture.

in die Statistik 5., durchgesehene Auflage Bibliografische Information Der Deutschen Bibliothek Die Deutsche Bibliothek verzeichnet diese Publikation in der Deutschen Nationalbibliografie; detaillierte bibliografische Daten sind im Internet uber abrufbar. Prof. Dr. rer. nat. Jurgen Lehn Geboren 1941 in Karlsruhe. Studium der Mathematik an den Universitaten Karlsruhe und Regensburg. 1968 Diplom in Karlsruhe, 1972 Promotion in Regensburg, 1978 Habilitation in Karlsruhe. 1978 Professor an der Technischen Hochschule Darmstadt. Prof. Dr. rer. nat. Helmut Wegmann Geboren 1938 in Worms. Studium der Mathematik und Physik an den Universitaten Mainz und Tubingen. Wiss. Assistent an den Universitaten Mainz und Stuttgart. 1962 Staats- amen in Mainz, 1964 Promotion in Mainz, 1969 Habilitation in Stuttgart. 1970 Professor fur Mathematik an der Technischen Hochschule Darmstadt. 1. Auflage 1985 2. Auflage 1992 3. Auflage 2000 4. Auflage 2004 5., durchgesehene Auflage Juni 2006 Alle Rechte vorbehalten (c) B.G.Teubner Verlag / GWV Fachverlage GmbH, Wiesbaden 2006 Lektorat: Ulrich Sandten / Kerstin Hoffmann Der B. G. Teubner Verlag ist ein Unternehmen von Springer Science+Business Media. www.teubner.de Das Werk einschlielich aller seiner Teile ist urheberrechtlich geschutzt. Jede Verwertung auerhalb der engen Grenzen des Urheberrech- gesetzes ist ohne Zustimmung des Verlags unzulassig und strafbar. Das gilt insbesondere fur Vervielfaltigungen, Ubersetzungen, Mikroverfilmungen und die Einspeicherung und Verarbeitung in elektronischen Systemen.

Your government warns that 10% of your neighbors have a deadly contagious virus. The producer of a diagnostic test advertises that 90% of its tests are correct for any population. The test indicates that you have the virus. This book's author claims your test has a 50% chance of being false, given your test's result. Who do you believe? This book gives you insights necessary to interpret metrics that make a difference in life's decisions.This book gives methods and software that are essential to analyze change and error. Change describes a phenomenon across time points. Error compares diagnoses with the truth. Other texts give insufficient attention to these topics. This book's novel ideas dispel popular misconceptions and replace previous methods. The author uses carefully designed graphics and high school mathematics to communicate easily with college students and advanced scientists. Applications include but are not limited to Remote Sensing, Land Change Science, and Geographic Information Science."e;A wide range of tools to aid understanding of land cover and its change has been used but scientific progress has sometimes been limited through misuse and misunderstanding. Professor Pontius seeks to rectify this situation by providing a book to accompany the researcher's toolbox. Metrics That Make a Difference addresses basic issues of relevance to a broad community in a mathematically friendly way and should greatly enhance the ability to elicit correct information. I wish this book existed while I was a grad student."e; - Giles Foody, Professor of Geographical Information Science, The University of Nottingham"e;Metrics That Make a Difference provides a comprehensive synthesis of over two decades of work during which Dr. Pontius researched, developed, and applied these metrics. The book meticulously and successfully guides the reader through the conceptual basis, computations, and proper interpretation of the many metrics derived for different types of variables. The book is not just a mathematical treatise but includes practical guidance to good data analysis and good science. Data scientists from many fields of endeavor will benefit substantially from Dr. Pontius' articulate review of traditionally used metrics and his presentation of the innovative and novel metrics he has developed. While reading this book, I had multiple 'aha' moments about metrics that I shouldn't be using and metrics that I should be using instead."e; - Stephen Stehman, Distinguished Teaching Professor, State University of New York

This book constitutes the refereed proceedings of the 4th International Conference on Distributed Artificial Intelligence, DAI 2022, held in Tianjin, China, in December 2022. The 5 full papers presented in this book were carefully reviewed and selected from 12 submissions. DAI aims at bringing together international researchers and practitioners in related areas including general AI, multiagent systems, distributed learning, computational game theory, etc., to provide a single, high-profile, internationally renowned forum for research in the theory and practice of distributed AI.

This proceedings, ICAST 2022, constitutes the refereed post-conference proceedings of the 10th International Conference on Advancement of Science and Technology, ICAST 2022, which took place in Bahir Dar, Ethiopia, in November 2022. The 17 revised full papers and one short paper were carefully reviewed and selected from 174 submissions. The papers present economic and technologic developments in modern societies related to important issues such digitization, energy transformation, impact on national economy, and its recent advancements.

This volume constitutes selected papers presented at the First International Conference on Artificial Intelligence: Theories and Applications, ICAITA 2022, held in Mascara, Algeria, in November 2022. The 23 papers were thoroughly reviewed and selected from the 66 qualified submissions. They are organized in topical sections on ¿artificial vision; and articial intelligence in big data and natural language processing.

This book provides an introduction to information theory, focussing on Shannon¿s three foundational theorems of 1948¿1949. Shannon¿s first two theorems, based on the notion of entropy in probability theory, specify the extent to which a message can be compressed for fast transmission and how to erase errors associated with poor transmission. The third theorem, using Fourier theory, ensures that a signal can be reconstructed from a sufficiently fine sampling of it. These three theorems constitute the roadmap of the book. The first chapter studies the entropy of a discrete random variable and related notions. The second chapter, on compression and error correcting, introduces the concept of coding, proves the existence of optimal codes and good codes (Shannon's first theorem), and shows how information can be transmitted in the presence of noise (Shannon's second theorem). The third chapter proves the sampling theorem (Shannon's third theorem) and looks at its connections with other results, such as the Poisson summation formula. Finally, there is a discussion of the uncertainty principle in information theory.Featuring a good supply of exercises (with solutions), and an introductory chapter covering the prerequisites, this text stems out lectures given to mathematics/computer science students at the beginning graduate level.

This textbook aims to point out the most important principles of data analysis from the mathematical point of view. Specifically, it selected these questions for exploring: Which are the principles necessary to understand the implications of an application, and which are necessary to understand the conditions for the success of methods used? Theory is presented only to the degree necessary to apply it properly, striving for the balance between excessive complexity and oversimplification. Its primary focus is on principles crucial for application success. Topics and features:Focuses on approaches supported by mathematical arguments, rather than sole computing experiencesInvestigates conditions under which numerical algorithms used in data science operate, and what performance can be expected from themConsiders key data science problems: problem formulation including optimality measure; learning and generalization in relationships to training set size and number of free parameters; and convergence of numerical algorithmsExamines original mathematical disciplines (statistics, numerical mathematics, system theory) as they are specifically relevant to a given problemAddresses the trade-off between model size and volume of data available for its identification and its consequences for model parametrizationInvestigates the mathematical principles involves with natural language processing and computer visionKeeps subject coverage intentionally compact, focusing on key issues of each topic to encourage full comprehension of the entire bookAlthough this core textbook aims directly at students of computer science and/or data science, it will be of real appeal, too, to researchers in the field who want to gain a proper understanding of the mathematical foundations ¿beyond¿ the sole computing experience.

The once esoteric idea of embedding scientific computing into a probabilistic framework, mostly along the lines of the Bayesian paradigm, has recently enjoyed wide popularity and found its way into numerous applications. This book provides an insider¿s view of how to combine two mature fields, scientific computing and Bayesian inference, into a powerful language leveraging the capabilities of both components for computational efficiency, high resolution power and uncertainty quantification ability. The impact of Bayesian scientific computing has been particularly significant in the area of computational inverse problems where the data are often scarce or of low quality, but some characteristics of the unknown solution may be available a priori. The ability to combine the flexibility of the Bayesian probabilistic framework with efficient numerical methods has contributed to the popularity of Bayesian inversion, with the prior distribution being the counterpart of classical regularization. However, the interplay between Bayesian inference and numerical analysis is much richer than providing an alternative way to regularize inverse problems, as demonstrated by the discussion of time dependent problems, iterative methods, and sparsity promoting priors in this book. The quantification of uncertainty in computed solutions and model predictions is another area where Bayesian scientific computing plays a critical role. This book demonstrates that Bayesian inference and scientific computing have much more in common than what one may expect, and gradually builds a natural interface between these two areas.

This book constitutes the proceedings of the 20th International Conference on Relational and Algebraic Methods in Computer Science, RAMiCS 2023, which took place in Augsburg, Germany, during April 3¿6, 2023.The 17 papers presented in this book were carefully reviewed and selected from 26 submissions.They deal with the development and dissemination of relation algebras, Kleene algebras, and similar algebraic formalisms. Topics covered range from mathematical foundations to applications as conceptual and methodological tools in computer science and beyond.Apart from the submitted articles, this volume features the abstracts of the presentations of the three invited speakers.

Facilitate coding in generating geometric motives with a special focus on analyzing their geometric formulations. This book aims to teach analytical coding skills by combining arts and mathematics. Geometric patterns are quintessentially important for understanding today¿s media arts and their relationship with mathematics. With the main emphasis on this, author Selçuk Artut proposes a certain workflow to mathematically analyze a geometric pattern and use creative coding skills to render it on a computer screen. When done, you'll understand the basics of coding and expand the provided structure to cover issues of creative coding in particular. This book will also present a workflow to geometrically analyze and build patterns with detailed examples.What You Will LearnGain insight into the field of geometric patterns and its cultural valueReview dialectic creativity thattakes place between humans and computersUse code as a creative tool to use human-computer interaction to develop one's creative skillsWho This Book Is ForAny person who has an interest in using coding as a creative tool. University students from Arts, Design, Architecture, and Computer Science departments. Artists and designers who are eager to implement creative coding in their artistic production.