Algoritmer og datastrukturer

This book presents recent advances in computational optimization. Our everyday life is unthinkable without optimization. We try to minimize our effort and to maximize the achieved profit. Many real-world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks.The book is a comprehensive collection of extended contributions from the Workshops on Computational Optimization 2020. The book includes important real problems like modeling of physical processes, workforce planning, parameter settings for controlling different processes, transportation problems, wireless sensor networks, machine scheduling, air pollution modeling, solving multiple integrals and systems of differential equations which describe real processes, solving engineering problems. It shows how to develop algorithms for them based on new intelligent methods like evolutionary computations, ant colony optimization, constrain programming and others. This research demonstrates how some real-world problems arising in engineering, economics and other domains can be formulated as optimization problems.

This book constitutes the refereed proceedings of the 12th International Conference on Health Information Science, HIS 2023, held in Melbourne, VIC, Australia, during October 23¿24, 2023.The 20 full papers and 9 short papers included in this book were carefully reviewed and selected from 54 submissions. They were organized in topical sections as follows: Depression & Mental Health, Data Security, Privacy & Healthcare Systems, Neurological & Cognitive Disease Studies, COVID-19 Impact Studies, Advanced Medical Data & AI Techniques, Predictive Analysis & Disease Recognition, Medical Imaging & Dataset Exploration, Elderly Care and Knowledge Systems.

Dieses Buch betont die grundlegenden Konzepte des CS-Algorithmus und seiner Varianten sowie deren Anwendung zur Lösung unterschiedlicher Optimierungsprobleme in medizinischen und ingenieurwissenschaftlichen Anwendungen. Evolutionäre metaheuristische Ansätze werden zunehmend zur Lösung komplexer Optimierungsprobleme in verschiedenen realen Anwendungen eingesetzt. Einer der erfolgreichsten Optimierungsalgorithmen ist die Cuckoo-Suche (CS), die zu einem aktiven Forschungsbereich geworden ist, um N-dimensionale und lineare/nichtlineare Optimierungsprobleme mithilfe einfacher mathematischer Prozesse zu lösen. CS hat die Aufmerksamkeit verschiedener Forscher auf sich gezogen, was zur Entstehung zahlreicher Varianten des grundlegenden CS mit verbesserten Leistungsmerkmalen seit 2019 geführt hat.

This book constitutes the proceedings of the 22nd International Conference on Computer Information Systems and Industrial Management, CISIM 2023, held in Tokio, Japan, during September 22-24, 2023.The 36 papers presented in this book were carefully reviewed and selected from 77 submissions. They were organized in topical sections as follows: biometrics and pattern recognition applications; computer information systems and security; industrial management and other applications; machine learning and artificial neural networks; modelling and optimization; wellbeing and affective engineering; and machine learning using biometric data and kansei data.

Explore essential quantum computing algorithms and master concepts intuitively with minimal math expertise required Key Features:Learn the fundamentals with an introduction to matrix arithmeticWrite quantum computing programs in Qiskit-IBM's publicly available quantum computing websiteEmail your questions directly to the author-no question is too elementaryPurchase of the print or Kindle book includes a free PDF eBookBook Description:Navigate the quantum computing spectrum with this book, bridging the gap between abstract, math-heavy texts and math-avoidant beginner guides. Unlike intermediate-level books that often leave gaps in comprehension, this all-encompassing guide offers the missing links you need to truly understand the subject.Balancing intuition and rigor, this book empowers you to become a master of quantum algorithms. No longer confined to canned examples, you'll acquire the skills necessary to craft your own quantum code. Quantum Computing Algorithms is organized into four sections to build your expertise progressively.The first section lays the foundation with essential quantum concepts, ensuring that you grasp qubits, their representation, and their transformations. Moving to quantum algorithms, the second section focuses on pivotal algorithms - specifically, quantum key distribution and teleportation.The third section demonstrates the transformative power of algorithms that outpace classical computation and makes way for the fourth section, helping you to expand your horizons by exploring alternative quantum computing models.By the end of this book, quantum algorithms will cease to be mystifying as you make this knowledge your asset and enter a new era of computation, where you have the power to shape the code of reality.What You Will Learn:Define quantum circuitsHarness superposition and entanglement to solve classical problemsGain insights into the implementation of quantum teleportationExplore the impact of quantum computing on cryptographyTranslate theoretical knowledge into practical skills by writing and executing code on real quantum hardwareExpand your understanding of this domain by uncovering alternative quantum computing modelsWho this book is for:This book is for individuals familiar with algebra and computer programming, eager to delve into modern physics concepts. Whether you've dabbled in introductory quantum computing material or are seeking deeper insights, this quantum computing book is your gateway to in-depth exploration.

This playbook is the third volume of the series Introduction to Algorithms & Data Structures. It is written in the form of a course. It is a very comprehensive data structures and algorithms book, packed with:> text tutorials with a lot of illustrations > 5 hours of HD video tutorials, > popular interview questions asked by Google, Microsoft, Amazon and other big companies, > hands on lessons, practice exercises and solutions, > codes written during the course and > screenshots used in this book.Most data structure books and courses are too academic and boring. They have too much math and their codes look ugly, old and disgusting! This book is bundled with tutorial videos that are fun and easy to follow along, and show you how to write beautiful code like a software engineer, not a mathematician. Mastering data structures and algorithms is essential to getting your dream job. So, don't waste your time browsing disconnected tutorials or super long, boring courses.If you failed a job interview because you couldn't answer basic data structure and algorithm questions, just study this book and its accompanying videos. Understanding data structures and algorithms is crucial to excel as a software engineer. That's why companies like Google, Microsoft and Amazon, always include interview questions on data structures and algorithms.I will teach you everything you need to know about data structures and algorithms so you can ace your coding interview with confidence. This course is a perfect mix of theory and practice, packed with over 100 popular interview questions.Another benefit is that data structures and algorithms will make you think more logically. They can help you design better systems for storing and processing data. They also serve as a tool for optimization and problem-solving.As a result, the concepts of algorithms and data structures are very valuable in any field. For example, you can use them when building a web app or writing software for other devices. You can apply them to machine learning and data analytics, which are two hot areas right now. If you are a hacker, algorithms and data structures are also important for you everywhere.Now, whatever your preferred learning style, I've got you covered. If you're a visual learner, you'll love my HD videos, and illustrations throughout this book. If you're a practical learner, you'll love my hands-on lessons and practice exercises so that you can get practical with algorithms and data structures and learn in a hands-on way.

Beneficios acerca del aprendizaje de algoritmos y estructuras de datos.Primero, te ayudarán a convertirte en un mejor programador. Otro beneficio es que te harán pensar más lógicamente. Además, te pueden ayudar a diseñar mejores sistemas para almacenar y procesar datos. También sirven como una herramienta para la optimización y solución de problemas.Como resultado, los conceptos de algoritmos y estructuras de datos son muy valiosos en cualquier campo. Por ejemplo, puedes utilizarlos cuando construyas una aplicación web o escribes software para otros dispositivos. Puedes utilizarlos para aprendizaje de máquinas y analíticas de datos, las cuales son actualmente dos áreas excitantes. Si eres un hacker, los algoritmos y las estructuras de datos en Python también son importantes para ti en cualquier parte.Ahora, cualquiera que sea tu estilo de aprendizaje preferido, te tendré cubierto. Si eres un aprendiz visual, te encantarán mis diagramas claros e ilustraciones a través de este libro. Si eres un aprendiz práctico, te encantarán mis lecciones de práctica, de manera que puedas obtener práctica con algoritmos y estructuras de datos de una forma práctica. Estructura del curso.Hay cinco volúmenes en este curso. Este es el volumen uno. En este volumen, tomarás una inmersión profunda en el mundo de los algoritmos. Con frecuencia incremental, los algoritmos comienzan a moldear nuestras vidas de muchas maneras - desde los productos que nos recomiendan, hasta los amigos en que interactuamos en los medios sociales, y aún más importante que los aspectos sociales, como las políticas, privacía y cuidado de la salud. Por lo tanto, la primera parte de este curso cubre lo que son los algoritmos, como trabajan, donde se les puede encontrar (en aplicaciones de la vida real).En el segundo volumen, trabajarás a través de la introducción de las estructuras de datos. Aprenderás acerca de las estructuras de datos introductorios - arreglos y listas ligadas. Los observarás en operaciones comunes, y como los tiempos de proceso de estas operaciones afectan nuestro código de todos los días.En el tercer volumen, tomarás tu conocimiento de algoritmos y estructuras de datos juntos, para resolver el problema de clasificar datos utilizando el algoritmo de Merge Sort (clasificar por mezcla). Veremos los algoritmos en dos categorías: sorting (clasificar) y searching (búsqueda). Implementarás algoritmos para clasificar bien conocidos, como Selection Sort, Quicksort, y Merge Sort. También Aprenderás los algoritmos de búsqueda básicos como Sequential Search (búsqueda secuencial) y Binary Search (búsqueda binaria).Al final de muchas secciones de este curso, ejercicios de práctica cortos se proveen para probar tu entendimiento de los tópicos discutidos. También se proveen respuestas de manera que puedas verificar que tan bien has ejecutado cada sección. Al finalizar el curso, encontrarás una liga para bajar más recursos útiles, como códigos y pantallas utilizados en ese libro y más ejercicios de práctica. Puedes utilizarlos para referencias y revisión también. Mi liga de soporte también se provee, de manera que puedas contactarme en cualquier momento que tengas preguntas o requieras ayuda en el futuro.Al final del curso, entenderás que son los algoritmos y las estructuras de datos, cómo son medidos y evaluados, y cómo se utilizan para resolver problemas de la vida real. Por lo tanto, todo lo que requieras está aquí mismo en este libro. Realmente espero que lo disfrutes. ¿estás listo? ¡Sumerjámonos!

This book is a hands-on guide for programmers who want to learn how C++ is used to develop solutions for options and derivatives trading in the financial industry. It explores the main algorithms and programming techniques used in implementing systems and solutions for trading options and derivatives. This updated edition will bring forward new advances in C++ software language and libraries, with a particular focus on the new C++23 standard.The book starts by covering C++ language features that are frequently used to write financial software for options and derivatives. These features include the STL (standard template library), generic templates, functional programming, and support for numerical code. Examples include additional support for lambda functions with simplified syntax, improvements in automatic type detection for templates, custom literals, modules, constant expressions, and improved initialization strategies for C++ objects. This book also provides how-to examples that cover all the major tools and concepts used to build working solutions for quantitative finance. It discusses how to create bug-free and efficient applications, leveraging the knowledge of object-oriented and template-based programming. It has two new chapters covering backtesting option strategies and processing financial data.. It introduces the topics covered in the book in a logical and structured way, with lots of examples that will bring them to life.Options and Derivatives Programming in C++23 has been written with the goal of reaching readers who are looking for a concise, algorithms-based book that provides basic information through well-targeted examples and ready to use solutions.What You Will LearnGain insight into the fundamental challenges of the options and derivatives marketMaster the features of the C++ language used in quantitative financial programmingUnderstand quantitative finance algorithms for options and derivativesBuild pricing algorithms around the Black-Scholes model, and use binomial and differential equations methodsWho This Book Is ForProfessional developers who have some experience with the C++ language and would like to leverage that knowledge into financial software development.

This book constitutes the refereed proceedings of the Doctoral Consortium and Workshops on New Trends in Database and Information Systems, ADBIS 2023, held in Barcelona, Spain, during September 4¿7, 2023.The 29 full papers, 25 short papers and 7 doctoral consortium included in this book were carefully reviewed and selected from 148. They were organized in topical sections as follows: ADBIS Short Papers: Index Management & Data Reconstruction, ADBIS Short Papers: Query Processing, ADBIS Short Papers: Advanced Querying Techniques, ADBIS Short Papers: Fairness in Data Management, ADBIS Short Papers: Data Science, ADBIS Short Papers: Temporal Graph Management, ADBIS Short Papers: Consistent Data Management, ADBIS Short Papers: Data Integration, ADBIS Short Papers: Data Quality, ADBIS Short Papers: Metadata Management, Contributions from ADBIS 2023 Workshops and Doctoral Consortium, AIDMA: 1st Workshop on Advanced AI Techniques for Data Management, Analytics, DOING: 4th Workshop on Intelligent Data - From Data to Knowledge, K-Gals: 2nd Workshop on Knowledge Graphs Analysis on a Large Scale, MADEISD: 5th Workshop on Modern Approaches in Data Engineering, Information System Design, PeRS: 2nd Workshop on Personalization, Recommender Systems, Doctoral Consortium.

This book constitutes the refereed proceedings of the 17th International Joint Conference on Theoretical Computer Science-Frontier of Algorithmic Wisdom (IJTCS-FAW 2023), consisting of the 17th International Conference on Frontier of Algorithmic Wisdom (FAW) and the 4th International Joint Conference on Theoretical Computer Science (IJTCS), held in Macau, China, during August 14¿18, 2023.FAW started as the Frontiers of Algorithmic Workshop in 2007 at Lanzhou, China, and was held annually from 2007 to 2021 and published archival proceedings. IJTCS, the International joint theoretical Computer Science Conference, started in 2020, aimed to bring in presentations covering active topics in selected tracks in theoretical computer science. To accommodate the diversified new research directions in theoretical computer science, FAW and IJTCS joined their forces together to organize an event for information exchange of new findings and work of enduring value in the field. The 21 full papers included in this book were carefully reviewed and selected from 34 submissions. They were organized in topical sections as follows: algorithmic game theory; algorithms and data structures; combinatorial optimization; and computational economics.

In the era of 'Algorithmic Medicine,' the integration of Artificial Intelligence (AI) in healthcare holds immense potential to address critical challenges faced by the industry. This textbook goes beyond theoretical discussions to outline practical steps for transitioning

This book is a compilation of research papers and presentations from the Fourth Annual International Conference on Data Science, Machine Learning and Blockchain Technology (AICDMB 2023, Mysuru, India, 16-17 March 2023).

Deep Fakes: Algorithms and Society focuses on the use of artificial intelligence technologies to produce fictitious photorealistic audiovisual clips that are indistinguishable from traditional video media.For over a century, the indexical relationship of the photographic image, and its related media of film and video, to the scene of capture has served as a basis for truth claims. Historically, the iconicity of these images has featured a causal traceback to actual light rays in a particular time and space, which were fixed by chemical reactions or digital sensors to the resultant image. Today, photorealistic audiovisual media can be generated from deep learning networks that sever any connection to an actual event. Should society instantiate new regimes to manage this new challenge to our sense of reality and the traditional evidential capacities of the 'mechanical image'? How do these images generate information disorder while also providing the basis for legitimate tools used in entertainment and creative industries?Scholars and students from many backgrounds, as well as policymakers, journalists and the general reading public, will find a multidisciplinary approach to questions posed by deep fake research from Communication, International Studies, Writing and Rhetoric.

The aim of this book is to present new computational techniques and methodologies for the analysis of the clinical, epidemiological and public health aspects of SARS-CoV-2 and COVID-19 pandemic. The book presents the use of soft computing techniques such as machine learning algorithms for analysis of the epidemiological aspects of the SARS-CoV-2. This book clearly explains novel computational image processing algorithms for the detection of COVID-19 lesions in lung CT and X-ray images. It explores various computational methods for computerized analysis of the SARS-CoV-2 infection including severity assessment. The book provides a detailed description of the algorithms which can potentially aid in mass screening of SARS-CoV-2 infected cases. Finally the book also explains the conventional epidemiological models and machine learning techniques for the prediction of the course of the COVID-19 epidemic. It also provides real life examples through case studies. The book is intended for biomedical engineers, mathematicians, postgraduate students; researchers; medical scientists working on identifying and tracking infectious diseases.

This book is a complete guide to using functions in Power Query and is designed to help users of all skill levels learn and master its various functions.The Ultimate Guide to Functions in Power Query begins with an introduction to Power Query and an overview of the different types of functions available, along with detailed explanations of how to use each of them. Yoüll see how to leverage power functions to process and transform large datasets from various sources and learn advanced techniques such as creating custom functions and using conditional statements. The book also covers best practices for using functions, including tips on how to optimize query performance and troubleshoot common errors. Using practical example applications, Author Omid Motamedisedeh demonstrates how to optimize your data processing workflows, saving time and boosting productivity.By the end of the book, readers will have a deep understanding of Power Query functions and be ableto apply their knowledge to a wide range of data analysis tasks.What You Will LearnMaster the fundamentals of Power Query, including how to load and transform data from various sourcesUnderstand all the functions available in Power Query, including text, date/time, logical, numeric, and moreUse functions to transform data and perform complex calculationsEmploy advanced techniques such as custom functions, conditional statements, and working with parametersOptimize query performance, handle errors, and use the M language effectivelyUse real-world examples and exercises to hone your skills and gain practical experience with the toolWho This Book Is ForAnyone who wants to learn how to use functions in Power Query to transform and analyze data. This includes data analysts, business analysts, Excel users, and data scientists. Readers should have a basic understanding of Excel and data analysis concepts, but may be new to Power Query and functions.

This book collects selected contributions presented at the INdAM Workshop "e;Geometric Challenges in Isogeometric Analysis"e;, held in Rome, Italy on January 27-31, 2020. It gives an overview of the forefront research on splines and their efficient use in isogeometric methods for the discretization of differential problems over complex and trimmed geometries. A variety of research topics in this context are covered, including (i) high-quality spline surfaces on complex and trimmed geometries, (ii) construction and analysis of smooth spline spaces on unstructured meshes, (iii) numerical aspects and benchmarking of isogeometric discretizations on unstructured meshes, meshing strategies and software. Given its scope, the book will be of interest to both researchers and graduate students working in the areas of approximation theory, geometric design and numerical simulation.Chapter 10 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Dieses Open Buch schlägt eine Brücke zwischen Theorie und Praxis für das produzierende Gewerbe im Zeitalter der Digitalisierung, der Industrie 4.0 und der Künstlichen Intelligenz. Es ist das Resultat eines vierjährigen Forschungsprojekts, das unter der Leitung des Instituts für Produktionssysteme der Technischen Universität Dortmund und der RapidMiner GmbH in Zusammenarbeit mit zwölf weiteren Partnern durchgeführt wurde. Das Hauptziel des Projekts war die Entwicklung einer Datenanalyse-Plattform zur Förderung einer effektiven und kompetenzorientierten Zusammenarbeit in dynamischen Wertschöpfungsnetzwerken.Die zwanzig Beiträge in diesem Sammelband liefern umfassende Einblicke in die Forschungsergebnisse und schildern die gemeinsamen Erfahrungen der Partner aus produzierenden Unternehmen, Software- und Hardware-Anbietern sowie Forschungseinrichtungen. Im Fokus steht die Entwicklung von Lösungen, die in einem modularen Referenzbaukasten zusammengefasst sind. Dieser Baukasten unterstützt industrielle Datenanalysen und deren Integration in betriebliche Abläufe. Er fördert darüber hinaus eine kompetenzorientierte Zusammenarbeit und ermöglicht somit die Initiierung neuer Geschäftsmodelle und Kollaborationen.Das Buch richtet sich an Praktiker:innen aus der Industrie ebenso wie an Wissenschaftler:innen. Es liefert Impulse und bietet Hilfestellungen, um den Herausforderungen der digitalen Transformation zu begegnen und die Zukunft der industriellen Datenanalyse erfolgreich zu gestalten.

"This largely self-contained text introduces discrete probability and its applications, at a level suitable for beginning graduate students in mathematics, computer science, statistics and engineering. Each chapter includes exercises and pointers to the wider literature, covering a wide spectrum of essential techniques and key examples"--

Intelligent Fractal-Based Image Analysis: Application in Pattern Recognition and Machine Vision provides insights into the current strengths and weaknesses of different applications as well as research findings on fractal graphics in engineering and science applications. The book aims to improve the exchange of ideas and coherence between various core computing methods and highlights the relevance of related application areas for advanced as well as novice-user application. The book presents core concepts, methodological aspects, and advanced feature opportunities, focusing on major, real-time applications in engineering and health science. It will appeal to researchers, data scientists, industry professionals, and graduate students. Fractals are infinite, complex patterns used in modeling physical and dynamic systems. Fractal theory research has increased across different fields of applications including engineering science, health science, and social science. Recent literature shows the vital role fractals play in digital image analysis, specifically in biomedical image processing. Fractal graphics is an interdisciplinary field that deals with how computers can be used to gain high-level understanding from digital images. Integrating artificial intelligence with fractal characteristics has resulted in new interdisciplinary research in the fields of pattern recognition and image processing analysis.

This proceedings volume presents a selection of peer-reviewed contributions from the Second Non-Associative Algebras and Related Topics (NAART II) conference, which was held at the University of Coimbra, Portugal, from July 18¿22, 2022. The conference was held in honor of mathematician Alberto Elduque, who has made significant contributions to the study of non-associative structures such as Lie, Jordan, and Leibniz algebras. The papers in this volume are organized into four parts: Lie algebras, superalgebras, and groups; Leibniz algebras; associative and Jordan algebras; and other non-associative structures. They cover a variety of topics, including classification problems, special maps (automorphisms, derivations, etc.), constructions that relate different structures, and representation theory.One of the unique features of NAART is that it is open to all topics related to non-associative algebras, including octonion algebras, composite algebras, Banach algebras, connections with geometry, applications in coding theory, combinatorial problems, and more. This diversity allows researchers from a range of fields to find the conference subjects interesting and discover connections with their own areas, even if they are not traditionally considered non-associative algebraists. Since its inception in 2011, NAART has been committed to fostering cross-disciplinary connections in the study of non-associative structures.

You can't tell how deep a puddle is until you step in it. When I am asked about my profession, I have two ways of answering. If I want a short discussion, I say that I am a mathematician; if I want a long discussion, I say that I try to understand how the human brain works. A long discussion often leads to further questions: What does it mean to understand "e;how the brain works"e;? Does it help to be trained in mathematics when you try to understand the brain, and what kind of mathematics can help? What makes a mathematician turn into a neuroscientist? This may lead into a metascientific discussion which I do not like par- ticularly because it is usually too far off the ground. In this book I take quite a different approach. I just start explaining how I think the brain works. In the course of this explanation my answers to the above questions will become clear to the reader, and he will perhaps learn some facts about the brain and get some insight into the construc- tions of artificial intelligence.