Matematik til informatikfag

¿This book constitutes the proceedings of the 14th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2023, as well as the Cardiac MRI Reconstruction Challenge, CMRxRecon Challenge. There was a total of 53 submissions to the workshop. The 24 regular workshop papers included in this volume were carefully reviewed and selected from 29 paper submissions. They deal with cardiac segmentation, modelling, strain quantification, registration, statistical shape analysis, and quality control. In addition, 21 papers from the CMRxRecon challenge are included in this volume. They focus on fast CMR image reconstruction and provide a benchmark dataset that enables the broader research community to promote advances in this area of research.

Petri nets model concurrent and distributed systems where active components communicate through the production and absorption of various kinds of resources. Although the dynamic properties of such systems may be very complex, they may sometimes be connected to the static structure of a Petri net. Many properties are decidable, but their complexity may be huge. It is often opportune to restrict oneself to classes of systems, to partial algorithms, and to similar but simpler properties. Instead of analysing a given system, it is also possible to search for a system satisfying some desired properties by construction. This comprehensive textbook/reference presents and discusses these issues in-depth in the context of one of the most fundamental Petri net models, called place/transition nets. The presentation is fortified by means of many examples and worked exercises. Among topics addressed: ¿ In which order may actions may be generated and scheduled? ¿ What states and configurations may be reached in a concurrent system? ¿ Which interesting classes of systems can be analysed relatively efficiently? ¿ Is it possible to synthesise a system of some class from its behaviour? ¿ How can systems be represented algebraically, compositionally, and concisely? This unique text, based on introductory as well as on advanced courses on distributed systems, will serve as an invaluable guide for students and (future) researchers interested in theoretical¿as well as in practical¿aspects of Petri nets and related system models. Eike Best has been a full professor (now retired) affiliated to Carl von Ossietzky Universität Oldenburg, Germany. Raymond Devillers has been a full professor (now retired) affiliated to Université Libre de Bruxelles, Belgium. The authors have a long record as collaborators in the fields of Petri nets and the semantics of concurrency.

Mathematik für die Informatik: Dieses Buch bringt Ihnen die Grundlagen beiDieses Lehrbuch bietet eine Einführung in die grundlegenden Begriffe und Strukturen der Mathematik, welche am Anfang eines Informatikstudiums relevant sind. Weiterhin demonstriert es Anwendungen von mathematischen Konzepten und Methoden in der Informatik. Diese betreffen insbesondere formale Methoden der Programmverifikation und -entwicklung und den Entwurf von generischen Programmen. Ein spezielles Konzept mit einer leicht verständlichen Vermittlung des Stoffs, vielen Beispielen mit Rückgriffen auf die Schulmathematik und detaillierten Beweisen (verbunden mit der Erklärung des logischen Hintergrunds) erleichtert den Einstieg in die Mathematik an einer wissenschaftlichen Hochschule. Dadurch werden die Studierenden auch auf spätere Begriffe und tiefergehende Anwendungen der Mathematik in der Informatik gut vorbereitet. Die 5. Auflage erweitert den Inhalt um die Grundlagen der linearen Algebra. Die Übungsaufgaben zu den einzelnen Kapitel helfen, das Erlernte zu festigen und zu kontrollieren. Zahlreiche Lösungsvorschläge am Ende des Buchs ermöglichen die Überprüfung der eigenen Lösungen.Der InhaltMengentheoretische Grundlagen ¿ Logische Grundlagen ¿ Allgemeine direkte Produkte und Datenstrukturen ¿ Mathematische Beweise ¿ Spezifikation und Programmverifikation ¿ Spezielle Funktionen ¿ Spezielle Relationen und gerichtete Graphen ¿ Elementare Kombinatorik und ungerichtete Graphen ¿ Diskrete Wahrscheinlichkeitstheorie ¿ Generische Programmierung ¿ Grundbegriffe algebraischer Strukturen ¿ Formale Einführung der natürlichen Zahlen - Grundbegriffe der linearen AlgebraMit diesem Buch gelingt der Einstieg ins Informatik-StudiumMit diesem Buch schaffen Sie eine solide Basis für die Mathematikausbildung im Rahmen desInformatikstudiums. Zudem sind Sie durch die vorgestellten Problemstellungen in der Lage, selbstständig mathematische Konzepte und Methoden anzuwenden. Zielgruppen dieses Buchs über Mathematik in der Informatik sind Bachelor-Studierende in den ersten Studiensemestern folgender Fachbereiche:InformatikMathematikIngenieurwissenschaften

This book constitutes the refereed proceedings of the 21st International Workshop on Approximation and Online Algorithms, WAOA 2023, held in Amsterdam, The Netherlands, during September 7¿8, 2023The 16 full papers included in this book are carefully reviewed and selected from 43 submissions. The topics of WAOA 2023 were algorithmic game theory, algorithmic trading, coloring and partitioning, competitive analysis, computational advertising, computational finance, cuts and connectivity, FPT-approximation algorithms, geometric problems, graph algorithms, inapproximability results, mechanism design, network design, packing and covering, paradigms for the design and analysis of approximation and online algorithms, resource augmentation, and scheduling problems

This book includes extended and revised versions of selected papers from the 11th and 12th editions of the International Conference on Operations Research and Enterprise Systems (ICORES 2022 and ICORES 2023). ICORES 2022 was held as a virtual event in February 2022, and ICORES 2023 was held in Lisbon, Portugal, in February 2023. The 5 full papers included in this book were carefully reviewed and selected from the 55 submissions for ICORES 2022, and 8 full papers were reviewed and selected from the 55 submissions for ICORES 2023. The papers are focused on operations research and enterprise systems.

This book gives an intuitive and hands-on introduction to Topological Data Analysis (TDA). Covering a wide range of topics at levels of sophistication varying from elementary (matrix algebra) to esoteric (Grothendieck spectral sequence), it offers a mirror of data science aimed at a general mathematical audience. The required algebraic background is developed in detail. The first third of the book reviews several core areas of mathematics, beginning with basic linear algebra and applications to data fitting and web search algorithms, followed by quick primers on algebra and topology. The middle third introduces algebraic topology, along with applications to sensor networks and voter ranking. The last third covers key contemporary tools in TDA: persistent and multiparameter persistent homology. Also included is a user's guide to derived functors and spectral sequences (useful but somewhat technical tools which have recently found applications in TDA), and an appendix illustrating a number of software packages used in the field.  Based on a course given as part of a masters degree in statistics, the book is appropriate for graduate students.

This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas.  All the figures and numerical results are reproducible using the Python codes provided. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Detailed proofs for certain important results are also provided. Modern Python modules like Pandas, Sympy, Scikit-learn, Tensorflow, and Keras are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This updated edition now includes the Fisher Exact Test and the Mann-Whitney-Wilcoxon Test. A new section on survival analysis has been included as well as substantial development of Generalized Linear Models. The new deep learning section for image processing includes an in-depth discussion of gradient descent methods that underpin all deep learning algorithms.   As with the prior edition, there are new and updated *Programming Tips* that the illustrate effective Python modules and methods for scientific programming and machine learning. There are 445 run-able code blocks with corresponding outputs that have been tested for accuracy.  Over 158 graphical visualizations (almost all generated using Python) illustrate the concepts that are developed both in code and in mathematics. We also discuss and use key Python modules such as Numpy, Scikit-learn, Sympy,  Scipy, Lifelines, CvxPy, Theano, Matplotlib, Pandas, Tensorflow, Statsmodels,  and Keras.This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowledge of Python programming.

This book constitutes the refereed proceedings of the 11th International Conference on Code-Based Cryptography, CBCrypto 2023, held in Lyon, France, during April 22¿23, 2023. The 8 full papers included in this book were carefully reviewed and selected from 28 submissions. The conference offers a wide range of many important aspects of code-based cryptography such as cryptanalysis of existing schemes, the proposal of new cryptographic systems and protocols as well as improved decoding algorithms.

These two volumes constitute the proceedings of the 10th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2023, held in Kanazawa, Japan, during November 2-4, 2023. The 58 full papers presented were carefully reviewed and selected from 107 submissions. The papers deal with all aspects of research results, ideas, and experiences of application among researchers and practitioners involved with all aspects of uncertainty modelling and management.

These two volumes constitute the proceedings of the 10th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2023, held in Kanazawa, Japan, during November 2-4, 2023.The 58 full papers presented were carefully reviewed and selected from 107 submissions. The papers deal with all aspects of research results, ideas, and experiences of application among researchers and practitioners involved with all aspects of uncertainty modelling and management.

This book provides essential information on Petri net theory and Petri net-based model checking methods. As for the Petri net theory, it involves the interleaving semantics and concurrency semantics of elementary net systems, some important net structures (e.g., invariant, repetitive vector, siphon, and trap), some classical net subclasses with special structures (e.g., state machine, marked graph, free-choice net,asymmetric-choice net, normal net, and weakly persistent net), and some basic properties (e.g., reachability, liveness, deadlock, and soundness). It also involves four high-level Petri nets: knowledge-oriented Petri nets, Petri nets with insecure places, time Petri nets, and plain time Petri nets with priorities, focusing on different fields of application. As for the model checking methods, this book introduces readers to computation tree logic (CTL), computation tree logic of knowledge (CTLK), and timed computation tree logic (TCTL), as well as Petri net-based methods for checking them. The basic principle of the reduced ordered binary decision diagram (ROBDD) is employed to compress the state space used in these model checking procedures. The book also covers time-soundness for time Petri nets and secure bisimulation for Petri nets with insecure places, both of which are based on the bisimulation theory. As such, it offers an introduction to basic information on bisimulation theory.

This book constitutes refereed proceedings of the 22nd International Conference on Mathematical Optimization Theory and Operations Research: Recent Trends, MOTOR 2023, held in Ekaterinburg, Russia, during July 2¿8, 2023. The 28 full papers and one invited paper presented in this volume were carefully reviewed and selected from a total of 61 submissions. The papers in the volume are organized according to the following topical headings: mathematical programming; stochastic optimization; discrete and combinatorial optimization; operations research; optimal control and mathematical economics; and optimization in machine learning.