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This book constitutes the refereed proceedings of the 21st International Conference on Information Technologies and Mathematical Modelling. Queueing Theory and Applications, ITMM 2022, held in Karshi, Uzbekistan, during October 25–29, 2022. The 19 full papers included in this book were carefully reviewed and selected from 89 submissions. The papers are devoted to new results in queueing theory and its applications. Its target audience includes specialists in probabilistic theory, random processes, mathematical modeling as well as engineers engaged in logical and technical design and operational management of data processing systems, communication, and computer networks.

Computer science—Mathematics. --- Mathematical statistics. --- Probability and Statistics in Computer Science. --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Statistical methods --- Technology --- Technology & Engineering

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This book presents the latest developments in the theory and applications of time series analysis and forecasting. Comprising a selection of refereed papers, it is divided into several parts that address modern theoretical aspects of time series analysis, forecasting and prediction, with applications to various disciplines, including econometrics and energy research. The broad range of topics discussed, including matters of particular relevance for sustainable development, will give readers a modern perspective on the subject. The included contributions were originally presented at the 8th International Conference on Time Series and Forecasting, ITISE 2022, held in Gran Canaria, Spain, June 27-30, 2022. 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. .

Time-series analysis. --- Econometrics. --- Statistics. --- Computer science --- Mathematical statistics. --- Time Series Analysis. --- Statistics in Business, Management, Economics, Finance, Insurance. --- Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. --- Applied Statistics. --- Probability and Statistics in Computer Science. --- Mathematics.

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The third edition of this authoritative and comprehensive handbook is the definitive work on the current state of the art of Biometric Presentation Attack Detection (PAD) – also known as Biometric Anti-Spoofing. Building on the success of the previous editions, this thoroughly updated third edition has been considerably revised to provide even greater coverage of PAD methods, spanning biometrics systems based on face, fingerprint, iris, voice, vein, and signature recognition. New material is also included on major PAD competitions, important databases for research, and on the impact of recent international legislation. Valuable insights are supplied by a selection of leading experts in the field, complete with results from reproducible research, supported by source code and further information available at an associated website. Topics and features: reviews the latest developments in PAD for fingerprint biometrics, covering recent technologies like Vision Transformers, and review of competition series; examines methods for PAD in iris recognition systems, the use of pupil size measurement or multiple spectra for this purpose; discusses advancements in PAD methods for face recognition-based biometrics, such as recent progress on detection of 3D facial masks and the use of multiple spectra with Deep Neural Networks; presents an analysis of PAD for automatic speaker recognition (ASV), including a study of the generalization to unseen attacks; describes the results yielded by key competitions on fingerprint liveness detection, iris liveness detection, and face anti-spoofing; provides analyses of PAD in finger-vein recognition, in signature biometrics, and in mobile biometrics; includes coverage of international standards in PAD and legal aspects of image manipulations like morphing.This text/reference is essential reading for anyone involved in biometric identity verification, be they students, researchers, practitioners, engineers, or technology consultants. Those new to the field will also benefit from a number of introductory chapters, outlining the basics for the most important biometrics. This text/reference is essential reading for anyone involved in biometric identity verification, be they students, researchers, practitioners, engineers, or technology consultants. Those new to the field will also benefit from a number of introductory chapters, outlining the basics for the most important biometrics.

Electronic digital computers—Evaluation. --- Biometric identification. --- Computer science—Mathematics. --- Mathematical statistics. --- System Performance and Evaluation. --- Biometrics. --- Probability and Statistics in Computer Science. --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Biometric person authentication --- Biometrics (Identification) --- Anthropometry --- Identification --- Statistical methods --- Biometric identification --- Computer security. --- Security measures. --- Computer privacy --- Computer system security --- Computer systems --- Computers --- Cyber security --- Cybersecurity --- Electronic digital computers --- Protection of computer systems --- Security of computer systems --- Data protection --- Security systems --- Hacking --- Protection --- Security measures

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This essential textbook presents an introduction to the mathematical foundations of software engineering. It presents the rich applications of mathematics in areas such as error-correcting codes, cryptography, the safety and security critical fields, the banking and insurance fields, as well as traditional engineering applications. Topics and features: Addresses core mathematics for critical thinking and problem solving Discusses propositional and predicate logic and various proof techniques to demonstrate the correctness of a logical argument. Examines number theory and its applications to cryptography Considers the underlying mathematics of error-correcting codes Discusses graph theory and its applications to modelling networks Reviews tools to support software engineering mathematics, including automated and interactive theorem provers and model checking Discusses financial software engineering, including simple and compound interest, probability and statistics, and operations research Discusses software reliability and dependability and explains formal methods used to derive a program from its specification Discusses calculus, matrices, vectors, complex numbers, and quaternions, as well as applications to graphics and robotics Includes key learning topics, summaries, and review questions in each chapter, together with a useful glossary This practical and easy-to-follow textbook/reference is ideal for computer science students seeking to learn how mathematics can assist them in building high-quality and reliable software on time and on budget. The text also serves as an excellent self-study primer for software engineers, quality professionals, and software managers. Dr. Gerard O’Regan is an Assistant Professor in Mathematics at the University of Central Asia in Kyrgyzstan. His research interests include software quality and software process　improvement, mathematical approaches to software quality, and the history of computing. He is the author of several books in the Mathematics and Computing fields with Springer.

Computer science --- Discrete mathematics. --- Software engineering. --- Computer science. --- Mathematical statistics. --- Discrete Mathematics in Computer Science. --- Software Engineering. --- Computer Science Logic and Foundations of Programming. --- Probability and Statistics in Computer Science. --- Mathematics. --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Informatics --- Science --- Computer software engineering --- Engineering --- Discrete mathematical structures --- Mathematical structures, Discrete --- Structures, Discrete mathematical --- Numerical analysis --- Computer mathematics --- Electronic data processing --- Statistical methods --- Software engineering --- Computer Software --- Computer Programming --- Computers

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This book introduces the basic principles underlying the design and analysis of the digital communication systems that have heralded the information revolution. One major goal of the book is to demonstrate the role of the digital communication principles in a wide variety of data science applications, including community detection, computational biology, speech recognition and machine learning. One defining feature of this book is to make an explicit connection between the communication principles and data science problems, as well as to succinctly deliver the “story” of how the communication principles play a role for trending data science applications. All the key “plots” involved in the story are coherently developed with the help of tightly coupled exercise problem sets, and the associated fundamentals are explored mostly from first principles. Another key feature is that it includes programming implementation of a variety of algorithms inspired by fundamentals, together with a brief tutorial of the used programming tools. The implementation is based on Python and TensorFlow. This book does not follow a traditional book-style organization, but is streamlined via a series of lecture notes that are intimately related, centered around coherent storylines and themes. It serves as a textbook mainly for a junior- or senior-level undergraduate course, yet is also suitable for a first-year graduate course. Readers benefit from having a good background in probability and random processes, and basic familiarity with Python. But the background can be supplemented by almost self-contained materials, as well as by numerous exercise problems intended for elaborating on non-trivial concepts. In addition, Part III for data science applications should provide motivation and insights to students and even professional scientists who are interested in the field.

Digital communications. --- Python (Computer program language) --- Scripting languages (Computer science) --- Communications, Digital --- Digital transmission --- Pulse communication --- Digital electronics --- Pulse techniques (Electronics) --- Telecommunication --- Digital media --- Signal processing --- Digital techniques --- Artificial intelligence—Data processing. --- Digital media. --- Computer science—Mathematics. --- Mathematical statistics. --- Signal processing. --- Data Science. --- Digital and New Media. --- Probability and Statistics in Computer Science. --- Signal, Speech and Image Processing . --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Electronic media --- New media (Digital media) --- Mass media --- Digital communications --- Online journalism --- Statistical methods