Algoritmer og datastrukturer

The Role of Blockchain in Disaster Management explores the architecture and implementation of existing blockchain-based IoT frameworks for the detection and prevention of disasters, along with the management of relative supply chains to protect against mismanagement of essential materials. The distributed nature of Blockchain helps to protect data from internal or external attacks, especially in disaster areas or times of crisis when database systems become overloaded and vulnerable to unauthorized access, manipulation, and disruption of critical services. This book can be used as a reference by graduate students, researchers, professors, and professionals in computer science, software design, and disaster management.

After providing an in-depth introduction to derivative-free global optimization with various constraints, this book presents new original results from well-known experts on the subject. A primary focus of this book is the well-known class of deterministic DIRECT (DIviding RECTangle)-type algorithms. This book describes a new set of algorithms derived from newly developed partitioning, sampling, and selection approaches in the box- and generally-constrained global optimization, including extensions to multi-objective optimization. DIRECT-type optimization algorithms are discussed in terms of fundamental principles, potential, and boundaries of their applicability. The algorithms are analyzed from various perspectives to offer insight into their main features. This explains how and why they are effective at solving optimization problems. As part of this book, the authors also present several techniques for accelerating the DIRECT-type algorithms through parallelization and implementing efficient data structures by revealing the pros and cons of the design challenges involved. A collection of DIRECT-type algorithms described and analyzed in this book is available in DIRECTGO, a MATLAB toolbox on GitHub. Lastly, the authors demonstrate the performance of the algorithms for solving a wide range of global optimization problems with various constraints ranging from a few to hundreds of variables.Additionally, well-known practical problems from the literature are used to demonstrate the effectiveness of the developed algorithms. It is evident from these numerical results that the newly developed approaches are capable of solving problems with a wide variety of structures and complexity levels.Since implementations of the algorithms are publicly available, this monograph is full of examples showing how to use them and how to choose the most efficient ones, depending on the nature of the problem being solved. Therefore, many specialists, students, researchers, engineers, economists, computer scientists, operations researchers, and others will find this book interesting and helpful.

This book discusses state-of-the-art stochastic optimization algorithms for distributed machine learning and analyzes their convergence speed. The book first introduces stochastic gradient descent (SGD) and its distributed version, synchronous SGD, where the task of computing gradients is divided across several worker nodes. The author discusses several algorithms that improve the scalability and communication efficiency of synchronous SGD, such as asynchronous SGD, local-update SGD, quantized and sparsified SGD, and decentralized SGD. For each of these algorithms, the book analyzes its error versus iterations convergence, and the runtime spent per iteration. The author shows that each of these strategies to reduce communication or synchronization delays encounters a fundamental trade-off between error and runtime.

In recent years, the field of artificial intelligence has witnessed an extraordinary resurgence, with deep learning emerging as the cornerstone of numerous breakthroughs across various domains. "Deep Learning and Applications" embarks on a journey into the captivating realm of deep learning, unraveling its intricate concepts, techniques, and transformative potential.This book serves as a comprehensive guide for both newcomers and seasoned practitioners, delving into the foundations of deep learning while illuminating its diverse applications. The rapid evolution of this field has not only enriched our understanding of machine learning but has also revolutionized industries, from healthcare and finance to art and entertainment.However, this book is not merely a theoretical exposition. It celebrates the synergy between theory and practice. With practical examples, code snippets, and case studies, readers are empowered to embark on their own deep learning odyssey. We showcase how to wield the power of frameworks like TensorFlow and PyTorch, demystifying the process of constructing, training, and fine-tuning deep learning models."Deep Learning and Applications" is an invitation to be part of the transformative wave that is reshaping technology and society. Whether you are an aspiring data scientist, a researcher pushing the boundaries of AI, or a curious mind seeking to comprehend the forces shaping our digital age, this book promises a rewarding voyage into the depths of knowledge and innovation.So, embark on this adventure with us, as we navigate the intricate seas of deep learning and its boundless applications.

In a world driven by data, the synergy of programming and machine learning has transformed how we perceive and interact with information. Welcome to "Python for Machine Learning," a comprehensive guide designed to empower both beginners and experienced programmers with the tools to harness the power of Python in the realm of machine learning.Machine learning, once considered a futuristic concept, has evolved into an essential discipline that powers everyday applications, from personalized recommendations to self-driving cars. At the heart of this revolution lies Python, a versatile and approachable programming language that has become the lingua franca of machine learning practitioners.Our goal is not only to teach you the syntax and mechanics of Python for machine learning, but also to cultivate a deeper understanding of the underlying principles. As you progress through this book, you will develop the ability to think critically about data, algorithms, and their applications.

This book constitutes the proceedings of the 19th IMA International Conference, IMACC 2023, held in London, UK, during December 12¿14, 2023The 14 full papers included in this volume were carefully reviewed and selected from 36 submissions. This volume presents cutting-edge results in a variety of areas, including coding theory, symmetric cryptography, zeroknowledge protocols, digital signature schemes and extensions, post-quantum cryptography and cryptography in practice.

The book synthesizes research on the analysis of biomedical ontologies using formal concept analysis, including through auditing, curation, and enhancement. As the evolution of biomedical ontologies almost inevitably involves manual work, formal methods are a particularly useful tool for ontological engineering and practice, particularly in uncovering unexpected "e;bugs"e; and content materials.  The book first introduces simple but formalized strategies for discovering undesired and incoherent patterns in ontologies before exploring the application of formal concept analysis for semantic completeness. The book then turns to formal concept analysis, a classical approach used in the mathematical treatment of orders and lattices, as an ontological engineering principle, focusing on the structural property of ontologies with respect to its conformation to lattice or not (non-lattice). The book helpfully covers the development of more efficient algorithms for non-lattice detection and extraction required by exhaustive lattice/non-lattice analysis. The book goes on to highlight the power and utility of uncovering non-lattice structure for debugging ontologies and describes methods that leverage the linguistic information in concept names (labels) for ontological analysis. It also addresses visualization and performance evaluation issues before closing with an overview and forward-looking perspectives on the field.  This book is intended for graduate students and researchers interested in biomedical ontologies and their applications. It can be a useful supplement for courses on knowledge representation and engineering and also provide readers with a reference for related scientific publications and literature to assist in identifying potential research topics. All mathematical concepts and notations used in this book can be found in standard discrete mathematics textbooks, and the appendix at the end of the book provides a list of key ontological resources, as well as annotated non-lattice and lattice examples that were discovered using the authors' methods, demonstrating how "e;bugs are fixed"e; by converting non-lattices to lattices with minimal edit changes.

This book constitutes the refereed proceedings of the 34th Australasian Database Conference on Databases Theory and Applications, ADC 2023, held in Melbourne, VIC, Australia, during November 1-3, 2023.The 26 full papers presented in this volume are carefully reviewed and selected from 41 submissions. They were organized in topical sections named: Mining Complex Types of Data, Natural Language Processing and Text Analysis, Machine Learning and Computer Vision, Database Systems and Data Storage, Data Quality and Fairness for Graphs and Graph Mining and Graph Algorithms.

This book constitutes the refereed proceedings of the 5th Iberoamerican Conference and 4th Indo-American Conference on Knowledge Graphs and Semantic Web, KGSWC 2023, held jointly in Zaragoza, Spain, during November 13¿15, 2023.The 18 full and 2 short papers presented were carefully reviewed and selected from 50 submissions. They focus on the following topics: knowledge representation; natural language processing/text mining; and machine/deep learning research.

This book presents Internet transport economics as a new approach to understanding the packet-switching paradigm of Internet infrastructure as a global transport system for data packets. It is a prescient view of the Internet's evolution into a content-centric service platform where the quality of services (QoS) cannot be guaranteed due to the tens of thousands of autonomous systems that enact business decisions on peering, routing, and pricing in a way that determines aspects of the Internet ecosystem like network topology, latency and throughput of traffic flows, and performance of network applications. The trafficking issues created in this environment are a critical concern and barrier for user applications that require real-time responses, such as telesurgery and teleoperation of autonomous vehicles, and the book presents the Internet transport economics model as the solution.                While engineering and business are the prevailing lenses through which the Internet is viewed, the book builds its methodological framework around transport. Further delving into economics, it establishes how the Internet can be understood as providing transport services for data packets, whose demand and supply are driven by the QoS metrics of delay and loss, which can be regarded as congestion costs that result in equilibrium rates of traffic flows sent by content providers (CPs). The book goes on to present a stylized model of content provider-to-access provider (CP-AP) service as well as congestion equilibrium and rate equilibrium solution concepts under the Internet transport economics framework. These are used to analyze the problem domains of service differentiation, market structure, and data pricing. Finally, it discusses various potential future applications. This book will be of interest to graduate students and researchers in areas of computer networking and performance evaluation.

This book constitutes the refereed proceedings of the 21st International Conference on Software Engineering and Formal Methods, SEFM 2023, held in Eindhoven, The Netherlands, during November 6-10, 2023.The 18 regular papers presented in this book, together with 1 invited paper and 1 tool paper, were carefully reviewed and selected from 41 submissions. The SEFM conference series aims to bring together researchers and practitioners from academia, industry and government, to advance the state of the art in formal methods, to facilitate their uptake in the software industry, and to encourage their integration within practical software engineering methods and tools.

The two-volume set CCIS 1896 and 1897 constitutes the refereed post-conference proceedings of the 5th International Conference on Blockchain and Trustworthy Systems, BlockSys 2023, which took place in Haikou, China during August 8-10, 2023. The 45 revised full papers presented in these proceedings were carefully reviewed and selected from 93 submissions. The papers are organized in the following topical sections: Part I: Anomaly detection on blockchain; edge intelligence and metaverse services; blockchain system security; empirical study and surveys; federated learning for blockchain. Part II: AI for blockchain; blockchain applications; blockchain architecture and optimization; protocols and consensus.

This book constitutes the post-conference proceedings of the satellite events held at the 20th Extended Semantic Web Conference, ESWC 2023, held in Hersonissos, Greece, during May 28¿June 1, 2023.The 50 full papers included in this book were carefully reviewed and selected from 109 submissions. They were organized in sections as follows: Posters and Demos, Industry, and PhD Symposium.

This book constitutes the refereed proceedings of the 27th International Conference on Enterprise Design, Operations, and Computing, EDOC 2023, held in Groningen, The Netherlands, during October 30¿November 3, 2023.The 12 full papers included in this book were carefully reviewed and selected from 36submissions. They were organized in topical sections as follows: Enterprise Modeling, Enterprise Architecture & Engineering, Model-Based Software Engineering, Enterprise Analysis with Process Mining, Process Improvement & Engineering, and Modeling in an Enterprise Context.

Securing Next-Generation Connected Healthcare Systems: Artificial Intelligence Technologies focuses on the crucial aspects of IoT security in a connected environment, which will not only benefit from cutting-edge methodological approaches but also assist in the rapid scalability and improvement of these systems. This book shows how to utilize technologies like blockchain and its integration with IoT for communication, data security, and trust management. It introduces the security aspect of next generation technologies for healthcare, covering a wide range of security and computing methodologies.Researchers, data scientists, students, and professionals interested in the application of artificial intelligence in healthcare management, data security of connected healthcare systems and related fields, specifically on data intensive secured systems and computing environments, will finds this to be a welcomed resource.

This book includes a thorough theoretical and computational analysis of unconstrained and constrained optimization algorithms and combines and integrates the most recent techniques and advanced computational linear algebra methods. Nonlinear optimization methods and techniques have reached their maturity and an abundance of optimization algorithms are available for which both the convergence properties and the numerical performances are known. This clear, friendly, and rigorous exposition discusses the theory behind the nonlinear optimization algorithms for understanding their properties and their convergence, enabling the reader to prove the convergence of his/her own algorithms. It covers cases and computational performances of the most known modern nonlinear optimization algorithms that solve collections of unconstrained and constrained optimization test problems with different structures, complexities, as well as those with large-scale real applications. The book is addressed to all those interested in developing and using new advanced techniques for solving large-scale unconstrained or constrained complex optimization problems. Mathematical programming researchers, theoreticians and practitioners in operations research, practitioners in engineering and industry researchers, as well as graduate students in mathematics, Ph.D. and master in mathematical programming will find plenty of recent information and practical approaches for solving real large-scale optimization problems and applications.

Unleash the power of algorithms and transform your programming skills!In today's tech-driven world, mastering algorithms is a brilliant way to boost your career, pick up a fun new hobby, and stay at the forefront of innovation. But where do you start if you are a complete beginner?Making Sense of Programming Algorithms Foundations is a deeply practical handbook that empowers readers to unleash the power of algorithms with real-world examples and easy-to-digest lessons. Specially written by seasoned IT professional Robert Setiadi, PhD, this guide walks you through the fundamentals of algorithms, revealing how you can master the essentials of coding and become a problem-solving virtuoso.Specially written with handy illustrations and pseudocodes that suit beginner and experienced programmers alike, this book reveals the secret to designing efficient algorithms for a diverse set of challenges. Readers will explore the world of divide and conquer technique, greedy algorithms, dynamic programming, search tree traversal, and many others.Here is just a little of what you will discover inside:Abstract data typesDivide and conquer, greedy algorithm, dynamic programmingHuffman coding, search tree, branch and boundBig O complexity analysisTest coverageTopics beyond basic, including brief introduction to artificial intelligenceand much more...This book is a must-read for students, aspiring programmers, experienced software developers revisiting the basics, or anyone who wants to understand how algorithms work.

Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications focuses on recent, up-to-date technologies, combining other intelligent tools with swarm intelligence techniques to yield robust and failsafe solutions to real world problems. This book aims to provide audiences with a platform to learn and gain insights into the latest developments in hybrid swarm intelligence. It will be useful to researchers, engineers, developers, practitioners, and graduate students working in the major and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing. With the advent of data-intensive applications, the elimination of redundancy in disseminated information has become a serious challenge for researchers who are on the lookout for evolving metaheuristic algorithms which can explore and exploit the information feature space to derive the optimal settings for specific applications. Swarm intelligence algorithms have developed as one of the most widely used metaheuristic techniques for addressing this challenge in an effective way. Inspired by the behavior of a swarm of bees, these swarm intelligence techniques emulate the corresponding natural instincts to derive optimal solutions for data-intensive applications.

Decision Making Models: A Perspective of Fuzzy Logic and Machine Learning presents the latest developments in the field of uncertain mathematics and decision science. The book aims to deliver a systematic exposure to soft computing techniques in fuzzy mathematics as well as artificial intelligence in the context of real-life problems and is designed to address recent techniques to solving uncertain problems encountered specifically in decision sciences. Researchers, professors, software engineers, and graduate students working in the fields of applied mathematics, software engineering, and artificial intelligence will find this book useful to acquire a solid foundation in fuzzy logic and fuzzy systems.Other areas of note include optimization problems and artificial intelligence practices, as well as how to analyze IoT solutions with applications and develop decision-making mechanisms realized under uncertainty.

Smart Spaces covers the latest concepts and technologies surrounding smart spaces, providing technical personnel engaged in smart space related research and industries a more in-depth understanding of smart spaces. This book can be used as a reference for practicing this emerging discipline, but it will also be useful for researchers, scientists, developers, practitioners, and graduate students working in the fields of smart spaces and artificial intelligence. It combines the study of working or living spaces with computing, information equipment, and multimodal sensing devices, and with natural and convenient interactive interfaces to support how people can easily obtain services from computer systems. People's work and life in smart spaces use computer systems; it is a process of uninterrupted interaction between people and the computer system. In this process, the computer is no longer just an information processing tool that passively executes explicit human operation commands but a collaborator with people to complete tasks - a partner to human beings. International research on smart spaces is quite extensive, which shows the important role of smart spaces in ubiquitous computing research.

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.

This book constitutes the refereed conference proceedings of the 14th International Conference on Bio-inspired Information and Communications Technologies, held in Okinawa, Japan, during April 11-12, 2023. The 17 full papers were carefully reviewed and selected from 33 submissions. The papers focus on the latest research that leverages the understanding of key principles, processes, and mechanisms in biological systems for development of novel information and communications technologies (bio-inspired ICT). BICT 2023 will also highlight innovative research and technologies being developed for biomedicine that are inspired by ICT (ICT-inspired biomedicine).

This volume LNCS 14240 constitutes the refereed proceedings of the 30th International Symposium on String Processing and Information Retrieval, SPIRE 2023, held in Pisa, Italy, during September 26¿28, 2023. The 31 full papers presented were carefully reviewed and selected from 47 submissions. They cover topics such as: data structures; algorithms; constrained Substring complexity; data compression codes; succinct k-spectra; and LCP array of wheeler DFAs.