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Nachhaltigkeit und Lebensqualität: Durch schlanke, grüne und saubere Konzepte
by K. MuralidharanDieses Buch soll die Leser für das Thema Nachhaltigkeit sensibilisieren und sie ermutigen, die Bedeutung von „lean, green and clean“ (LGC) für den Alltag zu verstehen. Die Notwendigkeit von auf Messungen basierten Auswertungen, statistische Signifikanz bei Materialverbrauch und Energie werden erörtert. Das Buch konzentriert sich auf die Bedeutung von Fragen des Klimawandels und Umweltbelangen im Zusammenhang mit schlanker Produktion und Fertigung. Der Schwerpunkt liegt auf dem Verständnis und der Anwendung von Qualitätskonzepten durch Projektmanagement und messbasierte Bewertungsmethoden. Dieses Buch richtet sich an ein breites Publikum, darunter Studierende, Lehrkräfte, Qualitätsfachleute, Unternehmensberater, Lean- und Six-Sigma-Praktiker, und ist für sie von großem Nutzen.Die Übersetzung wurde mit Hilfe von künstlicher Intelligenz durchgeführt. Eine anschließende menschliche Überarbeitung erfolgte vor allem in Bezug auf den Inhalt.
Computational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part IV (Lecture Notes in Computer Science #14835)
by Valeria V. Krzhizhanovskaya Jack J. Dongarra Peter M. A. Sloot Maciej Paszynski Clélia De Mulatier Leonardo FrancoThe 7-volume set LNCS 14832 – 14838 constitutes the proceedings of the 24th International Conference on Computational Science, ICCS 2024, which took place in Malaga, Spain, during July 2–4, 2024. The 155 full papers and 70 short papers included in these proceedings were carefully reviewed and selected from 430 submissions. They were organized in topical sections as follows: Part I: ICCS 2024 Main Track Full Papers; Part II: ICCS 2024 Main Track Full Papers; Part III: ICCS 2024 Main Track Short Papers; Advances in High-Performance Computational Earth Sciences: Numerical Methods, Frameworks and Applications; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Part IV: Biomedical and Bioinformatics Challenges for Computer Science; Computational Health; Part V: Computational Optimization, Modelling, and Simulation; Generative AI and Large Language Models (LLMs) in Advancing Computational Medicine; Machine Learning and Data Assimilation for Dynamical Systems; Multiscale Modelling and Simulation; Part VI: Network Models and Analysis: From Foundations to Artificial Intelligence; Numerical Algorithms and Computer Arithmetic for Computational Science; Quantum Computing; Part VII: Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks, and Artificial Intelligence; Solving Problems with Uncertainties; Teaching Computational Science
Computational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part V (Lecture Notes in Computer Science #14836)
by Valeria V. Krzhizhanovskaya Jack J. Dongarra Peter M. A. Sloot Maciej Paszynski Clélia De Mulatier Leonardo FrancoThe 7-volume set LNCS 14832 – 14838 constitutes the proceedings of the 24th International Conference on Computational Science, ICCS 2024, which took place in Malaga, Spain, during July 2–4, 2024. The 155 full papers and 70 short papers included in these proceedings were carefully reviewed and selected from 430 submissions. They were organized in topical sections as follows: Part I: ICCS 2024 Main Track Full Papers; Part II: ICCS 2024 Main Track Full Papers; Part III: ICCS 2024 Main Track Short Papers; Advances in High-Performance Computational Earth Sciences: Numerical Methods, Frameworks and Applications; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Part IV: Biomedical and Bioinformatics Challenges for Computer Science; Computational Health; Part V: Computational Optimization, Modelling, and Simulation; Generative AI and Large Language Models (LLMs) in Advancing Computational Medicine; Machine Learning and Data Assimilation for Dynamical Systems; Multiscale Modelling and Simulation; Part VI: Network Models and Analysis: From Foundations to Artificial Intelligence; Numerical Algorithms and Computer Arithmetic for Computational Science; Quantum Computing; Part VII: Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks, and Artificial Intelligence; Solving Problems with Uncertainties; Teaching Computational Science
Measuring Statistical Evidence Using Relative Belief (ISSN)
by Michael EvansThis book provides an overview of recent work on developing a theory of statistical inference based on measuring statistical evidence. It attempts to establish a gold standard for how a statistical analysis should proceed. The book illustrates relative belief theory using many examples and describes the strengths and weaknesses of the theory. The author also addresses fundamental statistical issues, including the meaning of probability, the role of subjectivity, the meaning of objectivity, and the role of infinity and continuity.
Accelerating Discoveries in Data Science and Artificial Intelligence I: ICDSAI 2023, LIET Vizianagaram, India, April 24–25 (Springer Proceedings in Mathematics & Statistics #421)
by Nishtha Kesswani Frank M. Lin Ashokkumar Patel Bosubabu SambanaThe Volume 1 book on Accelerating Discoveries in Data Science and Artificial Intelligence (Proceedings of ICDSAI 2023), that was held on April 24-25, 2023 by CSUSB USA, the International Association of Academicians (IAASSE), and the Lendi Institute of Engineering and Technology, Vizianagaram, India is intended to be used as a reference book for researchers and practitioners in the disciplines of AI and data science. The book introduces key topics and algorithms and explains how these contribute to healthcare, manufacturing, law, finance, retail, real estate, accounting, digital marketing, and various other fields. The book is primarily meant for academics, researchers, and engineers who want to employ data science techniques and AI applications to address real-world issues. Besides that, businesses and technology creators will also find it appealing to use in industry.
Anwendungen des Cuckoo-Suchalgorithmus und seiner Varianten
by Nilanjan DeyDieses 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.
Advanced Computing and Intelligent Technologies: Proceedings of ICACIT 2023 (Lecture Notes in Networks and Systems #958)
by Marcin Paprzycki Monica Bianchini Ankush Ghosh Rabindra Nath Shaw Sanjoy DasThis book gathers selected high-quality research papers presented at International Conference on Advanced Computing and Intelligent Technologies (ICACIT 2023), which is organized by Indira Gandhi National Tribal University, Regional Campus Manipur (IGNTU-RCM), during December 8–9, 2023. It discusses emerging topics pertaining to advanced computing, intelligent technologies and networks including AI and machine learning, data mining, big data analytics, high-performance computing network performance analysis, Internet of things networks, wireless sensor networks, and others. The book offers an asset for researchers from both academia and industries involved in advanced studies.
A Life Course Perspective on Chinese Youths: From the Transformation of Social Policies to the Individualization of the Transition to Adulthood (Life Course Research and Social Policies #17)
by Sandra V. ConstantinThis open access book investigates from a life-course perspective the individualization process and the challenges faced by young adults in post-collectivist China, where people are enjoined to "liberate" (jiefang) their individual capacities, to "rely on themselves" (kao ziji) and to no longer "depend on the state" (kao guojia). Based on unique quantitative and qualitative data, this book provides a solid empirical portrait of Chinese youths and transformation of social policies in post-collectivist ChinaThis book will be a great resource to students, academics as well as social scientists and policy-makers who wish not only to understand how, in such a short period of time, young adults and their families have managed to navigate from a relatively egalitarian society to one of the most unequal, but also how the articulation between socialist and neoliberal ideologies is reconfiguring social and economic relations as well as women’s and men’s life-course.The basis of the English translation of this book from its French original manuscript was done with the help of artificial intelligence. A subsequent human revision and rewriting of the content was done by the author.
Distributed Machine Learning and Computing: Theory and Applications (Big and Integrated Artificial Intelligence #2)
by M. Hadi AminiThis book focuses on a wide range of distributed machine learning and computing algorithms and their applications in healthcare and engineering systems. The contributors explore how these techniques can be applied to different real-world problems. It is suitable for students and researchers interested in conducting research in multidisciplinary areas that rely on distributed machine learning and computing techniques.
Multiobjective Optimization Algorithms for Bioinformatics
by Ujjwal Maulik Sanghamitra Bandyopadhyay Anirban Mukhopadhyay Sumanta RayThis book provides an updated and in-depth introduction to the application of multiobjective optimization techniques in bioinformatics. In particular, it presents multiobjective solutions to a range of complex real-world bioinformatics problems. The authors first provide a comprehensive yet concise and self-contained introduction to relevant preliminary methodical constructions such as genetic algorithms, multiobjective optimization, data mining and several challenges in the bioinformatics domain. This is followed by several systematic applications of these techniques to real-world bioinformatics problems in the areas of gene expression and network biology. The book also features detailed theoretical and mathematical notes to facilitate reader comprehension. The book offers a valuable asset for a broad range of readers – from undergraduate to postgraduate, and as a textbook or reference work. Researchers and professionals can use the book not only to enrich their knowledge of multiobjective optimization and bioinformatics, but also as a comprehensive reference guide to applying and devising novel methods in bioinformatics and related domains.
Optimiertes Babymanagement: Den Elternalltag mit betriebswirtschaftlichen Methoden perfektionieren
by Marko SarstedtEines Tages ist es so weit: Der Nachwuchs steht ins Haus und damit eine Reihe von Planungsproblemen. Ein sozialverträglicher Name und ein Kinderwagen mit maximaler sozialer Anerkennung müssen gefunden werden. Nach der Geburt wird es nicht einfacher! Wie viele Windeln muss ich vorrätig halten? Wie bestimme ich die kürzeste Kinderwagentour zwischen Bäckerei, Spielplatz, Apotheke, Supermarkt und Drogeriemarkt? Viele Unwägbarkeiten machen das Elterndasein anstrengend. Aber das muss nicht sein! Dieses Buch schafft Abhilfe. Marko Sarstedt analysiert wichtige Planungsprobleme des elterlichen Alltags mit betriebswirtschaftlichen Methoden und trägt in der 4. Auflage mit einem neuen Beitrag zum Einschlafmanagement und Hinweisen zur Nutzung von ChatGPT weiter zur Maximierung der elterlichen Zufriedenheit bei: Karriereoptimierte Namenswahl mit Name Concept Maps Kinderwagenkonfiguration mit der Choice-based Conjoint Analyse Krippenauswahl mit dem Scoring-Modell Kinderzimmereinrichtung mit der Netzplantechnik Babyphone-Kauf mit der Two-step Clusteranalyse Text Mining von Babyratgebern Windelbestandsmanagement Make-or-Buy Babybrei Einschlafmanagement mit der logistischen Regression Nächtliches Aufstehmanagement mit Markovketten Wellness-Planung mit der deterministischen Simulation Kinderwagentourenplanung mit genetischen Algorithmen Sitzordnungsplanung bei der Taufe mit Ameisenalgorithmen Prognose von Spielplatzfreundschaften mit der Netzwerkanalyse Kofferraum-Tetris mit der Branch-and-Bound-Methode
Empowering Independent Living using the ICF: An Unobtrusive Home Monitoring Sensor System for Older Adults
by Björn FriedrichFunctional decline in older adults can lead to an increased need of assistance or even moving to a nursing home. Utilising home automation, power and wearable sensors, the system developed by the author continuously keeps track of the functional status of older adults through monitoring their daily life and allows health care professionals to create individualised rehabilitation programmes based on the changes in the older adult’s functional capacity and performance in daily life. The system uses the taxonomy of the International Classification of Functioning, Disability and Health (ICF) by the World Health Organization (WHO). It links sensor data to fve ICF items from three ICF categories and measures their change over time. The system successfully passed the first pre-clinical validation step on the real-world data of the OTAGO study, a 10-month randomised pilot intervention study with 20 (pre-)frail older adults (aged ≥ 75 years). Since this research is in an early stage further clinical studies are needed to fully validate the system.
Computational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part VII (Lecture Notes in Computer Science #14838)
by Valeria V. Krzhizhanovskaya Jack J. Dongarra Peter M. A. Sloot Maciej Paszynski Clélia De Mulatier Leonardo FrancoThe 7-volume set LNCS 14832 – 14838 constitutes the proceedings of the 24th International Conference on Computational Science, ICCS 2024, which took place in Malaga, Spain, during July 2–4, 2024. The 155 full papers and 70 short papers included in these proceedings were carefully reviewed and selected from 430 submissions. They were organized in topical sections as follows: Part I: ICCS 2024 Main Track Full Papers; Part II: ICCS 2024 Main Track Full Papers; Part III: ICCS 2024 Main Track Short Papers; Advances in High-Performance Computational Earth Sciences: Numerical Methods, Frameworks and Applications; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Part IV: Biomedical and Bioinformatics Challenges for Computer Science; Computational Health; Part V: Computational Optimization, Modelling, and Simulation; Generative AI and Large Language Models (LLMs) in Advancing Computational Medicine; Machine Learning and Data Assimilation for Dynamical Systems; Multiscale Modelling and Simulation; Part VI: Network Models and Analysis: From Foundations to Artificial Intelligence; Numerical Algorithms and Computer Arithmetic for Computational Science; Quantum Computing; Part VII: Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks, and Artificial Intelligence; Solving Problems with Uncertainties; Teaching Computational Science
Computational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part III (Lecture Notes in Computer Science #14834)
by Valeria V. Krzhizhanovskaya Jack J. Dongarra Peter M. A. Sloot Maciej Paszynski Clélia De Mulatier Leonardo FrancoThe 7-volume set LNCS 14832 – 14838 constitutes the proceedings of the 24th International Conference on Computational Science, ICCS 2024, which took place in Malaga, Spain, during July 2–4, 2024. The 155 full papers and 70 short papers included in these proceedings were carefully reviewed and selected from 430 submissions. They were organized in topical sections as follows: Part I: ICCS 2024 Main Track Full Papers; Part II: ICCS 2024 Main Track Full Papers; Part III: ICCS 2024 Main Track Short Papers; Advances in High-Performance Computational Earth Sciences: Numerical Methods, Frameworks and Applications; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Part IV: Biomedical and Bioinformatics Challenges for Computer Science; Computational Health; Part V: Computational Optimization, Modelling, and Simulation; Generative AI and Large Language Models (LLMs) in Advancing Computational Medicine; Machine Learning and Data Assimilation for Dynamical Systems; Multiscale Modelling and Simulation; Part VI: Network Models and Analysis: From Foundations to Artificial Intelligence; Numerical Algorithms and Computer Arithmetic for Computational Science; Quantum Computing; Part VII: Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks, and Artificial Intelligence; Solving Problems with Uncertainties; Teaching Computational Science
Verkannt, verfemt, vergessen: Geschichten aus der europäischen Mathematik der Neuzeit
by Heinz Klaus StrickSobald Sie sich eingehender mit der Geschichte der Mathematik beschäftigen, werden Sie auch auf Personen stoßen, deren Namen Ihnen bislang unbekannt waren oder von deren Bedeutung für die Entwicklung der Mathematik Sie bisher nichts wussten. Dieses Buch bietet Ihnen einen Einblick in das Leben und Wirken von 67 besonderen Persönlichkeiten aus dem europäischen Raum – und geht bei der Betrachtung der Einzelschicksale jeweils auch der Frage nach, warum diese Personen vergleichsweise unbekannt sind, warum sie regelrecht „vergessen“ wurden. Die Gründe dafür sind vielfältig und meist in den jeweiligen politischen, gesellschaftlichen oder individuellen Lebensumständen zu finden – viele wurden diskriminiert und konnten ihre Fähigkeiten gar nicht erst entfalten, andere waren Ihrer Zeit voraus und blieben lange Zeit unverstanden. Über die historische Einordnung hinaus werden einige der mathematischen Beiträge dieser Personen dargestellt – so ausgewählt, dass sie mit denin der gymnasialen Oberstufe üblicherweise vermittelten Kenntnissen nachvollzogen werden können. Die in diesem Buch enthaltenen Darstellungen beginnen mit Persönlichkeiten aus dem 16. Jahrhundert und schließen somit chronologisch an das Buch Geschichten aus der Mathematik desselben Autors an, sind aber unabhängig davon lesbar. Das Buch richtet sich an alle, die sich für die Entwicklung der Wissenschaften interessieren und dabei insbesondere ein tieferes Verständnis für die menschlichen Aspekte der Mathematik entwickeln möchten.
Ordered Regression Models: Parallel, Partial, and Non-Parallel Alternatives (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)
by Jun Xu Andrew S. FullertonOrdered Regression Models: Parallel, Partial, and Non-Parallel Alternatives presents regression models for ordinal outcomes, which are variables that have ordered categories but unknown spacing between the categories. The book provides comprehensive coverage of the three major classes of ordered regression models (cumulative, stage, and adjacent) as well as variations based on the application of the parallel regression assumption.The authors first introduce the three "parallel" ordered regression models before covering unconstrained partial, constrained partial, and nonparallel models. They then review existing tests for the parallel regression assumption, propose new variations of several tests, and discuss important practical concerns related to tests of the parallel regression assumption. The book also describes extensions of ordered regression models, including heterogeneous choice models, multilevel ordered models, and the Bayesian approach to ordered regression models. Some chapters include brief examples using Stata and R.This book offers a conceptual framework for understanding ordered regression models based on the probability of interest and the application of the parallel regression assumption. It demonstrates the usefulness of numerous modeling alternatives, showing you how to select the most appropriate model given the type of ordinal outcome and restrictiveness of the parallel assumption for each variable.Web ResourceMore detailed examples are available on a supplementary website. The site also contains JAGS, R, and Stata codes to estimate the models along with syntax to reproduce the results.
Computational Methods in Finance (Chapman and Hall/CRC Financial Mathematics Series)
by Ali HirsaHelping readers accurately price a vast array of derivatives, this self-contained text explains how to solve complex functional equations through numerical methods. It addresses key computational methods in finance, including transform techniques, the finite difference method, and Monte Carlo simulation. Developed from his courses at Columbia University and the Courant Institute of New York University, the author also covers model calibration and optimization and describes techniques, such as Kalman and particle filters, for parameter estimation.
Real Time Reduced Order Computational Mechanics: Parametric PDEs Worked Out Problems (SISSA Springer Series #5)
by Gianluigi Rozza Francesco Ballarin Leonardo Scandurra Federico PichiThe book is made up by several worked out problems concerning the application of reduced order modeling to different parametric partial differential equations problems with an increasing degree of complexity.This work is based on some experience acquired during lectures and exercises in classes taught at SISSA Mathematics Area in the Doctoral Programme “Mathematical Analysis, Modelling and Applications”, especially in computational mechanics classes, as well as regular courses previously taught at EPF Lausanne and during several summer and winter schools. The book is a companion for master and doctoral degree classes by allowing to go more deeply inside some partial differential equations worked out problems, examples and even exercises, but it is also addressed for researchers who are newcomers in computational mechanics with reduced order modeling. In order to discuss computational results for the worked out problems presented in this booklet, we will rely on the RBniCS Project. The RBniCS Project contains an implementation in FEniCS of the reduced order modeling techniques (such as certified reduced basis method and Proper Orthogonal Decomposition-Galerkin methods) for parametric problems that will be introduced in this booklet.
Backdoor Attacks against Learning-Based Algorithms (Wireless Networks)
by Haojin Zhu Shaofeng Li Xuemin (Sherman) Shen Wen WuThis book introduces a new type of data poisoning attack, dubbed, backdoor attack. In backdoor attacks, an attacker can train the model with poisoned data to obtain a model that performs well on a normal input but behaves wrongly with crafted triggers. Backdoor attacks can occur in many scenarios where the training process is not entirely controlled, such as using third-party datasets, third-party platforms for training, or directly calling models provided by third parties. Due to the enormous threat that backdoor attacks pose to model supply chain security, they have received widespread attention from academia and industry. This book focuses on exploiting backdoor attacks in the three types of DNN applications, which are image classification, natural language processing, and federated learning.Based on the observation that DNN models are vulnerable to small perturbations, this book demonstrates that steganography and regularization can be adopted to enhance the invisibility of backdoor triggers. Based on image similarity measurement, this book presents two metrics to quantitatively measure the invisibility of backdoor triggers. The invisible trigger design scheme introduced in this book achieves a balance between the invisibility and the effectiveness of backdoor attacks. In the natural language processing domain, it is difficult to design and insert a general backdoor in a manner imperceptible to humans. Any corruption to the textual data (e.g., misspelled words or randomly inserted trigger words/sentences) must retain context-awareness and readability to human inspectors. This book introduces two novel hidden backdoor attacks, targeting three major natural language processing tasks, including toxic comment detection, neural machine translation, and question answering, depending on whether the targeted NLP platform accepts raw Unicode characters.The emerged distributed training framework, i.e., federated learning, has advantages in preserving users' privacy. It has been widely used in electronic medical applications, however, it also faced threats derived from backdoor attacks. This book presents a novel backdoor detection framework in FL-based e-Health systems. We hope this book can provide insightful lights on understanding the backdoor attacks in different types of learning-based algorithms, including computer vision, natural language processing, and federated learning. The systematic principle in this book also offers valuable guidance on the defense of backdoor attacks against future learning-based algorithms.
Probabilistic Models of Cosmic Backgrounds
by Anatoliy MalyarenkoCombining research methods from various areas of mathematics and physics, Probabilistic Models of Cosmic Backgrounds describes the isotropic random sections of certain fiber bundles and their applications to creating rigorous mathematical models of both discovered and hypothetical cosmic backgrounds.Previously scattered and hard-to-find mathematical and physical theories have been assembled from numerous textbooks, monographs, and research papers, and explained from different or even unexpected points of view. This consists of both classical and newly discovered results necessary for understanding a sophisticated problem of modelling cosmic backgrounds.The book contains a comprehensive description of mathematical and physical aspects of cosmic backgrounds with a clear focus on examples and explicit calculations. Its reader will bridge the gap of misunderstanding between the specialists in various theoretical and applied areas who speak different scientific languages.The audience of the book consists of scholars, students, and professional researchers. A scholar will find basic material for starting their own research. A student will use the book as supplementary material for various courses and modules. A professional mathematician will find a description of several physical phenomena at the rigorous mathematical level. A professional physicist will discover mathematical foundations for well-known physical theories.
Probabilistic Models of Cosmic Backgrounds
by Anatoliy MalyarenkoCombining research methods from various areas of mathematics and physics, Probabilistic Models of Cosmic Backgrounds describes the isotropic random sections of certain fiber bundles and their applications to creating rigorous mathematical models of both discovered and hypothetical cosmic backgrounds.Previously scattered and hard-to-find mathematical and physical theories have been assembled from numerous textbooks, monographs, and research papers, and explained from different or even unexpected points of view. This consists of both classical and newly discovered results necessary for understanding a sophisticated problem of modelling cosmic backgrounds.The book contains a comprehensive description of mathematical and physical aspects of cosmic backgrounds with a clear focus on examples and explicit calculations. Its reader will bridge the gap of misunderstanding between the specialists in various theoretical and applied areas who speak different scientific languages.The audience of the book consists of scholars, students, and professional researchers. A scholar will find basic material for starting their own research. A student will use the book as supplementary material for various courses and modules. A professional mathematician will find a description of several physical phenomena at the rigorous mathematical level. A professional physicist will discover mathematical foundations for well-known physical theories.
Kolmogorov Operators and Their Applications (Springer INdAM Series #56)
by Sergio Polidoro Andrea Pascucci Stéphane MenozziKolmogorov equations are a fundamental bridge between the theory of partial differential equations and that of stochastic differential equations that arise in several research fields. This volume collects a selection of the talks given at the Cortona meeting by experts in both fields, who presented the most recent developments of the theory. Particular emphasis has been given to degenerate partial differential equations, Itô processes, applications to kinetic theory and to finance.
Computational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part VI (Lecture Notes in Computer Science #14837)
by Valeria V. Krzhizhanovskaya Jack J. Dongarra Peter M. A. Sloot Maciej Paszynski Clélia De Mulatier Leonardo FrancoThe 7-volume set LNCS 14832 – 14838 constitutes the proceedings of the 24th International Conference on Computational Science, ICCS 2024, which took place in Malaga, Spain, during July 2–4, 2024. The 155 full papers and 70 short papers included in these proceedings were carefully reviewed and selected from 430 submissions. They were organized in topical sections as follows: Part I: ICCS 2024 Main Track Full Papers; Part II: ICCS 2024 Main Track Full Papers; Part III: ICCS 2024 Main Track Short Papers; Advances in High-Performance Computational Earth Sciences: Numerical Methods, Frameworks and Applications; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Part IV: Biomedical and Bioinformatics Challenges for Computer Science; Computational Health; Part V: Computational Optimization, Modelling, and Simulation; Generative AI and Large Language Models (LLMs) in Advancing Computational Medicine; Machine Learning and Data Assimilation for Dynamical Systems; Multiscale Modelling and Simulation; Part VI: Network Models and Analysis: From Foundations to Artificial Intelligence; Numerical Algorithms and Computer Arithmetic for Computational Science; Quantum Computing; Part VII: Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks, and Artificial Intelligence; Solving Problems with Uncertainties; Teaching Computational Science
Spatial Networking in the United Physical, Virtual, and Mental World (Studies in Systems, Decision and Control #533)
by Peter S. SapatyThe current book chooses graphs and networks as primary and global research objectives after reviewing different types and areas of networking and existing works on graph and network operations. The ideas of this book originate from the WAVE approach which allowed us, more than half a century ago, to implement citywide heterogeneous computer networks and solve distributed problems on them in flexible and mobile way. The invented management paradigm evolved into Spatial Grasp Technology resulted in European patent and nine previous books oriented on concrete applications in social and defense systems, security, crises management, collective robotics, space research, and others. Many obtained results were dealing with graph and network structures and problems which were extremely important in the researched areas. It aims at development of higher-level social infrastructures effectively integrating different types of networking under the same universal approach, also application of networking in new areas like organoids and brain research. This book is oriented toward system scientists, application programmers, industry managers, university students, philosophers, psychologists, and United Nations personnel too.
Finding Communities in Social Networks Using Graph Embeddings (Lecture Notes in Social Networks)
by David B. Skillicorn Mosab AlfaqeehCommunity detection in social networks is an important but challenging problem. This book develops a new technique for finding communities that uses both structural similarity and attribute similarity simultaneously, weighting them in a principled way. The results outperform existing techniques across a wide range of measures, and so advance the state of the art in community detection. Many existing community detection techniques base similarity on either the structural connections among social-network users, or on the overlap among the attributes of each user. Either way loses useful information. There have been some attempts to use both structure and attribute similarity but success has been limited. We first build a large real-world dataset by crawling Instagram, producing a large set of user profiles. We then compute the similarity between pairs of users based on four qualitatively different profile properties: similarity of language used in posts, similarity of hashtags used (which requires extraction of content from them), similarity of images displayed (which requires extraction of what each image is 'about'), and the explicit connections when one user follows another. These single modality similarities are converted into graphs. These graphs have a common node set (the users) but different sets a weighted edges. These graphs are then connected into a single larger graph by connecting the multiple nodes representing the same user by a clique, with edge weights derived from a lazy random walk view of the single graphs. This larger graph can then be embedded in a geometry using spectral techniques. In the embedding, distance corresponds to dissimilarity so geometric clustering techniques can be used to find communities. The resulting communities are evaluated using the entire range of current techniques, outperforming all of them. Topic modelling is also applied to clusters to show that they genuinely represent users with similar interests. This can form the basis for applications such as online marketing, or key influence selection.