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Input/Output in Parallel and Distributed Computer Systems has attracted increasing attention over the last few years, as it has become apparent that input/output performance, rather than CPU performance, may be the key limiting factor in the performance of future systems. This I/O bottleneck is caused by the increasing speed mismatch between processing units and storage devices, the use of multiple processors operating simultaneously in parallel and distributed systems, and by the increasing I/O demands of new classes of applications, like multimedia. It is also important to note that, to varying degrees, the I/O bottleneck exists at multiple levels of the memory hierarchy. All indications are that the I/O bottleneck will be with us for some time to come, and is likely to increase in importance. Input/Output in Parallel and Distributed Computer Systems is based on papers presented at the 1994 and 1995 IOPADS workshops held in conjunction with the International Parallel Processing Symposium. This book is divided into three parts. Part I, the Introduction, contains four invited chapters which provide a tutorial survey of I/O issues in parallel and distributed systems. The chapters in Parts II and III contain selected research papers from the 1994 and 1995 IOPADS workshops; many of these papers have been substantially revised and updated for inclusion in this volume. Part II collects the papers from both years which deal with various aspects of system software, and Part III addresses architectural issues. Input/Output in Parallel and Distributed Computer Systems is suitable as a secondary text for graduate level courses in computer architecture, software engineering, and multimedia systems, and as a reference for researchers and practitioners in industry.

Evidenced by the success of Facebook, Twitter, and LinkedIn, online social networks (OSNs) have become ubiquitous, offering novel ways for people to access information and communicate with each other. As the increasing popularity of social networking is undeniable, scalability is an important issue for any OSN that wants to serve a large number of users. Storing user data for the entire network on a single server can quickly lead to a bottleneck, and, consequently, more servers are needed to expand storage capacity and lower data request traffic per server. Adding more servers is just one step to address scalability. The next step is to determine how best to store the data across multiple servers. This problem has been widely-studied in the literature of distributed and database systems. OSNs, however, represent a different class of data systems. When a user spends time on a social network, the data mostly requested is her own and that of her friends; e.g., in Facebook or Twitter, these data are the status updates posted by herself as well as that posted by the friends. This so-called social locality should be taken into account when determining the server locations to store these data, so that when a user issues a read request, all its relevant data can be returned quickly and efficiently. Social locality is not a design factor in traditional storage systems where data requests are always processed independently. Even for today's OSNs, social locality is not yet considered in their data partition schemes. These schemes rely on distributed hash tables (DHT), using consistent hashing to assign the users'data to the servers. The random nature of DHT leads to weak social locality which has been shown to result in poor performance under heavy request loads. Data Storage for Social Networks: A Socially Aware Approach is aimed at reviewing the current literature of data storage for online social networks and discussing newmethods that take into account social awareness in designing efficient data storage.

A Modular Calculus for the Average Cost of Data Structuring introduces MOQA, a new domain-specific programming language which guarantees the average-case time analysis of its programs to be modular.Time in this context refers to a broad notion of cost, which can be used to estimate the actual running time, but also other quantitative information such as power consumption, while modularity means that the average time of a program can be easily computed from the times of its constituents--something that no programming language of this scope has been able to guarantee so far. MOQA principles can be incorporated in any standard programming language. MOQA supports tracking of data and their distributions throughout computations, based on the notion of random bag preservation. This allows a unified approach to average-case time analysis, and resolves fundamental bottleneck problems in the area. The main techniques are illustrated in an accompanying Flash tutorial, where the visual nature of this method can provide new teaching ideas for algorithms courses. This volume, with forewords by Greg Bollella and Dana Scott, presents novel programs based on the new advances in this area, including the first randomness-preserving version of Heapsort. Programs are provided, along with derivations of their average-case time, to illustrate the radically different approach to average-case timing. The automated static timing tool applies the Modular Calculus to extract the average-case running time of programs directly from their MOQA code. A Modular Calculus for the Average Cost of Data Structuring is designed for a professional audience composed of researchers and practitioners in industry, with an interest in algorithmic analysis and also static timing and power analysis--areas of growing importance. It is also suitable as an advanced-level text or reference book for students in computer science, electrical engineering and mathematics. Michel Schellekens obtained his PhD from Carnegie Mellon University, following which he worked as a Marie Curie Fellow at Imperial College London. Currently he is an Associate Professor at the Department of Computer Science in University College Cork - National University of Ireland, Cork, where he leads the Centre for Efficiency-Oriented Languages (CEOL) as a Science Foundation Ireland Principal Investigator.

Symmetric multiprocessors (SMPs) dominate the high-end server market and are currently the primary candidate for constructing large scale multiprocessor systems. Yet, the design of e cient parallel algorithms for this platform c- rently poses several challenges. The reason for this is that the rapid progress in microprocessor speed has left main memory access as the primary limitation to SMP performance. Since memory is the bottleneck, simply increasing the n- ber of processors will not necessarily yield better performance. Indeed, memory bus limitations typically limit the size of SMPs to 16 processors. This has at least twoimplicationsfor the algorithmdesigner. First, since there are relatively few processors availableon an SMP, any parallel algorithm must be competitive with its sequential counterpart with as little as one processor in order to be r- evant. Second, for the parallel algorithm to scale with the number of processors, it must be designed with careful attention to minimizing the number and type of main memory accesses. In this paper, we present a computational model for designing e cient al- rithms for symmetric multiprocessors. We then use this model to create e cient solutions to two widely di erent types of problems - linked list pre x com- tations and generalized sorting. Both problems are memory intensive, but in die rent ways. Whereas generalized sorting algorithms typically require a large numberofmemoryaccesses, they areusuallytocontiguousmemorylocations. By contrast, prex computation algorithms typically require a more modest qu- tity of memory accesses, but they are are usually to non-contiguous memory locations.

The four-volume set LNCS 15364-15367 constitutes the refereed proceedings of the 22nd International Conference on Theory of Cryptography, TCC 2024, held in Milan, Italy, in December 2024. The total of 68 full papers presented in the proceedings was carefully reviewed and selected from 172 submissions. They focus on topics such as: proofs; math and foundations; consensus and messaging; quantum; kolmogorov and OWFs; encryption; quantum and black-box separations; authentication and sequentiality; obfuscation and homomorphism; multi-party computation; information-theoretic cryptography; and secret sharing.

This book constitutes the refereed proceedings of the 20th International Conference on Knowledge Management and Acquisition for Intelligent Systems, PKAW 2024, held in Kyoto, Japan, during November 18–19, 2024. The 15 full papers and 9 short papers presented in this volume were carefully reviewed and selected from 52 submissions. These papers demonstrate advanced research on machine learning, natural language processing, computer vision, and intelligent systems.

This book features high-quality research papers presented at Fifth Doctoral Symposium on Computational Intelligence (DoSCI 2024), jointly organised by Institute of Engineering & Technology, Lucknow, India, and School of Open Learning, University of Delhi in association with University of Calabria, Italy, on May 10, 2024. This book discusses the topics such as computational intelligence, artificial intelligence, deep learning, evolutionary algorithms, swarm intelligence, fuzzy sets and vague sets, rough set theoretic approaches, quantum-inspired computational intelligence, hybrid computational intelligence, machine learning, computer vision, soft computing, distributed computing, parallel and grid computing, cloud computing, high-performance computing, biomedical computing, and decision support and decision making.

The four-volume set LNCS 15364-15367 constitutes the refereed proceedings of the 22nd International Conference on Theory of Cryptography, TCC 2024, held in Milan, Italy, in December 2024. The total of 68 full papers presented in the proceedings was carefully reviewed and selected from 172 submissions. They focus on topics such as: proofs; math and foundations; consensus and messaging; quantum; kolmogorov and OWFs; encryption; quantum and black-box separations; authentication and sequentiality; obfuscation and homomorphism; multi-party computation; information-theoretic cryptography; and secret sharing.

This two-volume set constitutes the refereed proceedings of the Second International Conference, ISDS 2024, held in Nha Trang, Vietnam, during November 9–10, 2024. The 38 full papers and 10 short papers were carefully reviewed and selected from 129 submissions. They were categorized under the topical sections as follows: AI in E-Commerce, Agriculture, and Aquaculture; AI in Health Care Analytics; Big Data, IoT, and Cloud Computing; and Natural Language Processing.

This two-volume set constitutes the refereed proceedings of the Second International Conference, ISDS 2024, held in Nha Trang, Vietnam, during November 9–10, 2024. The 38 full papers and 10 short papers were carefully reviewed and selected from 129 submissions. They were categorized under the topical sections as follows: AI in E-Commerce, Agriculture, and Aquaculture; AI in Health Care Analytics; Big Data, IoT, and Cloud Computing; and Natural Language Processing.

This textbook introduces the fundamental concepts and techniques used in biometric recognition to students, practitioners, and non-experts in the field. Specifically, the book describes key methodologies used for sensing, feature extraction, and matching of commonly used biometric modalities such as fingerprint, face, iris, and voice. In addition, it presents techniques for fusion of biometric information to meet stringent accuracy requirements, also discussing various security issues and associated remedies involved in the deployment of biometric systems. Furthermore, this second edition captures the progress made in the field of biometric recognition, with highlights including: Lucid explanation of core biometric concepts (e.g., individuality and persistence), which builds a strong foundation for more in-depth study and research on biometrics A new chapter on deep neural networks that provides a primer to recent advancements in machine learning and computer vision Illustrative examples of how deep neural network models have contributed to the rapid evolution of biometrics in areas such as robust feature representation and synthetic biometric data generation A new chapter on speaker recognition, which introduces the readers to person recognition based on the human voice characteristics Presentation of emerging security threats such as deepfakes and adversarial attacks and sophisticated countermeasures such as presentation attack detection and template security While this textbook has been designed for senior undergraduate students and first-year graduate students studying a course on biometrics, it is also a useful reference guide for biometric system designers, developers, and integrators.

This book constitutes the proceedings of the 8th International Joint Conference on Rules and Reasoning, RuleML+RR 2024, held in Bucharest, Romania, during September 16-18, 2024. The 12 full papers and 4 short papers included in this book were carefully reviewed and selected from 35 submissions. The RuleML+RR symposia were devoted to disseminating research, applications, languages, and standards for rule technologies, with attention to both theoretical and practical developments, to challenging new ideas and to industrial applications.

This book constitutes the refereed proceedings of the 16th International Conference on Cellular Automata for Research and Industry, Cellular Automata, ACRI 2024, held in Florence, Italy, in September 9–11, 2024. The 20 full papers presented were carefully reviewed and selected from 33 submissions. They were organized in the following topical sections: theory, mathematical and physical models; computational aspects and applications; social and biological models.

This volume LNCS 14918 constitutes the refereed proceedings of 28th European Conference, ADBIS 2024, held in Bayonne, France, during August 28-31, 2024. The 15 full papers presented were carefully reviewed and selected from 43 submissions. The conference focuses on Algebra, Models, Schemata, Discovery and Data Analysis, Algorithms and Optimization, Access Methods and Query Processing, Advanced Architectures, Machine Learning, Large Language Models.

This book constitutes the refereed proceedings of the 22nd International Conference on Business Process Management, BPM 2024, which took place in Krakow, Poland, in September 2024. The 29 full papers included in this book were carefully reviewed and selected from 144 submissions. They were organized in topical sections as follows: Foundations; Engineering; and Management..

This textbook is intended for students of mathematics who have completed the foundational courses of their undergraduate studies and now want to specialize in Data Science and Machine Learning. It introduces the reader to the most important topics in the latter areas focusing on rigorous proofs and a systematic understanding of the underlying ideas. The textbook comes with 121 classroom-tested exercises. Topics covered include k-nearest neighbors, linear and logistic regression, clustering, best-fit subspaces, principal component analysis, dimensionality reduction, collaborative filtering, perceptron, support vector machines, the kernel method, gradient descent and neural networks.

This book introduces pioneering developments in binary representation learning on visual images, a state-of-the-art data transformation methodology within the fields of machine learning and multimedia. Binary representation learning, often known as learning to hash or hashing, excels in converting high-dimensional data into compact binary codes meanwhile preserving the semantic attributes and maintaining the similarity measurements. The book provides a comprehensive introduction to the latest research in hashing-based visual image retrieval, with a focus on binary representations. These representations are crucial in enabling fast and reliable feature extraction and similarity assessments on large-scale data. This book offers an insightful analysis of various research methodologies in binary representation learning for visual images, ranging from basis shallow hashing, advanced high-order similarity-preserving hashing, deep hashing, as well as adversarial and robust deep hashing techniques. These approaches can empower readers to proficiently grasp the fundamental principles of the traditional and state-of-the-art methods in binary representations, modeling, and learning. The theories and methodologies of binary representation learning expounded in this book will be beneficial to readers from diverse domains such as machine learning, multimedia, social network analysis, web search, information retrieval, data mining, and others.

Recommender systems, as a highly popular AI technology in recent years, have been widely applied across various industries. They have transformed the way we interact with technology, influencing our choices and shaping our experiences. This book provides a comprehensive introduction to industrial recommender systems, starting with the overview of the technical framework, gradually delving into each core module such as content understanding, user profiling, recall, ranking, re-ranking and so on, and introducing the key technologies and practices in enterprises. The book also addresses common challenges in recommendation cold start, recommendation bias and debiasing. Additionally, it introduces advanced technologies in the field, such as reinforcement learning, causal inference. Professionals working in the fields of recommender systems, computational advertising, and search will find this book valuable. It is also suitable for undergraduate, graduate, and doctoral students majoring in artificial intelligence, computer science, software engineering, and related disciplines. Furthermore, it caters to readers with an interest in recommender systems, providing them with an understanding of the foundational framework, insights into core technologies, and advancements in industrial recommender systems. The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.

This text covers all of the data science, machine learning, and deep learning topics relevant to materials science and engineering, accompanied by numerous examples and applications. Almost all methods and algorithms introduced are implemented “from scratch” using Python and NumPy. The book starts with an introduction to statistics and probabilities, explaining important concepts such as random variables and probability distributions, Bayes'theorem and correlations, sampling techniques, and exploratory data analysis, and puts them in the context of materials science and engineering. Therefore, it serves as a valuable primer for both undergraduate and graduate students, as well as a review for research scientists and practicing engineers. The second part provides an in-depth introduction of (statistical) machine learning. It begins with outlining fundamental concepts and proceeds to explore a variety of supervised learning techniques for regression and classification, including advanced methods such as kernel regression and support vector machines. The section on unsupervised learning emphasizes principal component analysis, and also covers manifold learning (t-SNE and UMAP) and clustering techniques. Additionally, feature engineering, feature importance, and cross-validation are introduced. The final part on neural networks and deep learning aims to promote an understanding of these methods and dispel misconceptions that they are a “black box”. The complexity gradually increases until fully connected networks can be implemented. Advanced techniques and network architectures, including GANs, are implemented “from scratch” using Python and NumPy, which facilitates a comprehensive understanding of all the details and enables the user to conduct their own experiments in Deep Learning.

This book collects selected contributions of the “Optimization and Decision Science - ODS2023” international conference on the theme of optimization in green sustainability and ecological transition. ODS2023 was held in Ischia, 4–7 September 2023, and was organized by AIRO, the Italian Operations Research Society. The book offers new and original contributions on operations research, optimization, decision science, and prescriptive analytics from both a methodological and applied perspectives with a special focus on SDG related topics.It provides a state-of-the art on problem models and solving methods to address a widely class of real-world problems, arising in different application areas such as logistics, transportation, manufacturing, health, ICT and mobile networks, and emergency/disaster management. In addition, the scientific works collected in this book aim at providing significant contributions in the themes of sustainability, traffic and pollution reductions, and energy management.This book is aimed primarily at researchers and Ph.D. students in the Operations Research community. However, due to its interdisciplinary contents, this book is of high interest also for students and researchers from other disciplines, including artificial intelligence, computer sciences, finance, mathematics, and engineering as well as for practitioners facing complex decision-making problems in logistics, manufacturing production, and services.

This book gathers outstanding research papers presented at the 7th International Joint Conference on Advances in Computational Intelligence (IJCACI 2023), held in hybrid mode at South Asian University, New Delhi, India during October 14–15, 2023. IJCACI 2023 is jointly organized by Jahangirnagar University (JU), Bangladesh and South Asian University (SAU), India. The book presents the novel contributions in areas of computational intelligence and it serves as a reference material for advance research. The topics covered are collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.

This book features a collection of high-quality research papers presented at the International Conference on Tourism, Technology and Systems (ICOTTS 2023), held at Anáhuac University, Bacalar, Mexico, from 2 to 4 November 2023. The book is divided into two volumes, and it covers the areas of technology in tourism and the tourist experience, generations and technology in tourism, digital marketing applied to tourism and travel, mobile technologies applied to sustainable tourism, information technologies in tourism, digital transformation of tourism business, e-tourism and tourism 2.0, big data and management for travel and tourism, geotagging and tourist mobility, smart destinations, robotics in tourism, and information systems and technologies.

This book constitutes the revised selected papers of the First International Conference, ICCSST 2023, held in Bangalore, India, during May 8–9, 2023.The 39 full papers included in this volume were carefully reviewed and selected from 200 submissions. They focus on artificial intelligence, blockchain technology, cloud computing, cyber security, data science, e-commerce, computer architecture, image and video processing, pandemic preparedness and digital technology, pattern recognition and classification.

This book includes high-quality research papers presented at 22nd International Conference on Informatics in Economy (IE 2023), which is held in Bucharest, Romania, during May 2023. This book covers research results in business informatics and related computer science topics, such as IoT, mobile-embedded and multimedia solutions, e-society, enterprise and business solutions, databases and big data, artificial intelligence, data mining and machine learning, quantitative economics.

This book constitutes revised papers from the International Workshops held at the 21st International Conference on Business Process Management, BPM 2023, in Utrecht, The Netherlands, during September 2023.Papers from the following workshops are included:• 7th International Workshop on Artificial Intelligence for Business Process Management (AI4BPM 2023)• 7th International Workshop on Business Processes Meet Internet-of-Things (BP-Meet-IoT 2023)• 19th International Workshop on Business Process Intelligence (BPI 2023)• 16th International Workshop on Social and Human Aspects of Business Process Management (BPMS2 2023)• 2nd International Workshop on Data-Driven Business Process Optimization (BPO 2023)• 11th International Workshop on Declarative, Decision and Hybrid Approaches to Processes (DEC2H 2023)• 1st International Workshop on Digital Twins for Business Processes (DT4BP 2023)• 1st International Workshop on Formal Methods for Business Process Management (FM-BPM 2023) • 2nd International Workshop on Natural Language Processing for Business Process Management (NLP4BPM 2023)• 1st International Workshop on Object-Centric Processes from A to Z (OBJECTS 2023)• 3rd International Workshop on Change, Drift, and Dynamics of Organizational Processes (ProDy 2023) Each of the workshops focused on particular aspects of business process management. Overall, after a thorough review process, 42 full papers were selected from a total of 86 submissions.

This book constitutes the refereed proceedings of the 24th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2024, held in Amsterdam, The Netherlands, during November 26–28, 2024. The 28 full papers presented together were carefully reviewed and selected from 115 submissions. They focus on all aspects of knowledge in constructing systems and services for the semantic web, knowledge management, knowledge discovery, information integration, natural language processing, intelligent systems, e-business, e-health, humanities, cultural heritage, and beyond.

The two volume set CCIS 2032 and 2033 constitutes the proceedings of the 11th Congress on Simulation for a Sustainable Future, EUROSIM 2023, which was held in Amsterdam, The Netherlands, during July 3–5, 2023. The 47 full papers included in the proceedings were carefully reviewed and selected from 99 submissions. The papers are divided in the following topical sections: ​environmental sustainability; healthcare; production systems; business and industries; logistics and transportation systems; monitor, control, and theoretical systems.

The seven-volume set LNCS 14850-14856 constitutes the proceedings of the 29th International Conference on Database Systems for Advanced Applications, DASFAA 2024, held in Gifu, Japan, in July 2024. The total of 147 full papers, along with 85 short papers, presented together in this seven-volume set was carefully reviewed and selected from 722 submissions. Additionally, 14 industrial papers, 18 demo papers and 6 tutorials are included. The conference presents papers on subjects such as: Part I: Spatial and temporal data; database core technology; federated learning. Part II: Machine learning; text processing. Part III: Recommendation; multi-media. Part IV: Privacy and security; knowledge base and graphs. Part V: Natural language processing; large language model; time series and stream data. Part VI: Graph and network; hardware acceleration. Part VII: Emerging application; industry papers; demo papers.

The five-volume set LNCS 14961, 14962, 14963, 14964 and 14965 constitutes the refereed proceedings of the 8th International Joint Conference on Web and Big Data, APWeb-WAIM 2024, held in Jinhua, China, during August 30–September 1, 2024. The 171 full papers presented in these proceedings were carefully reviewed and selected from 558 submissions. The papers are organized in the following topical sections: Part I: Natural language processing, Generative AI and LLM, Computer Vision and Recommender System. Part II: Recommender System, Knowledge Graph and Spatial and Temporal Data. Part III: Spatial and Temporal Data, Graph Neural Network, Graph Mining and Database System and Query Optimization. Part IV: Database System and Query Optimization, Federated and Privacy-Preserving Learning, Network, Blockchain and Edge computing, Anomaly Detection and Security Part V: Anomaly Detection and Security, Information Retrieval, Machine Learning, Demonstration Paper and Industry Paper.

The five-volume set LNCS 14961, 14962, 14963, 14964 and 14965 constitutes the refereed proceedings of the 8th International Joint Conference on Web and Big Data, APWeb-WAIM 2024, held in Jinhua, China, during August 30–September 1, 2024. The 171 full papers presented in these proceedings were carefully reviewed and selected from 558 submissions. The papers are organized in the following topical sections: Part I: Natural language processing, Generative AI and LLM, Computer Vision and Recommender System. Part II: Recommender System, Knowledge Graph and Spatial and Temporal Data. Part III: Spatial and Temporal Data, Graph Neural Network, Graph Mining and Database System and Query Optimization. Part IV: Database System and Query Optimization, Federated and Privacy-Preserving Learning, Network, Blockchain and Edge computing, Anomaly Detection and Security Part V: Anomaly Detection and Security, Information Retrieval, Machine Learning, Demonstration Paper and Industry Paper.

The five-volume set LNCS 14961, 14962, 14963, 14964 and 14965 constitutes the refereed conference proceedings of the 8th International Joint Conference on Web and Big Data, APWeb-WAIM 2024, held in Jinhua, China, during August 30–September 1, 2024. The 171 full papers presented in these proceedings were carefully reviewed and selected from 558 submissions. The papers are organized in the following topical sections: Volume I: Natural language processing, Generative AI and LLM, Computer Vision and Recommender System. Volume II: Recommender System, Knowledge Graph and Spatial and Temporal Data. Volume III: Spatial and Temporal Data, Graph Neural Network, Graph Mining and Database System and Query Optimization. Volume IV: Database System and Query Optimization, Federated and Privacy-Preserving Learning, Network, Blockchain and Edge computing, Anomaly Detection and Security Volume V: Anomaly Detection and Security, Information Retrieval, Machine Learning, Demonstration Paper and Industry Paper.

The five-volume set LNCS 14961, 14962, 14963, 14964 and 14965 constitutes the refereed proceedings of the 8th International Joint Conference on Web and Big Data, APWeb-WAIM 2024, held in Jinhua, China, during August 30–September 1, 2024. The 171 full papers presented in these proceedings were carefully reviewed and selected from 558 submissions. The papers are organized in the following topical sections: Part I: Natural language processing, Generative AI and LLM, Computer Vision and Recommender System. Part II: Recommender System, Knowledge Graph and Spatial and Temporal Data. Part III: Spatial and Temporal Data, Graph Neural Network, Graph Mining and Database System and Query Optimization. Part IV: Database System and Query Optimization, Federated and Privacy-Preserving Learning, Network, Blockchain and Edge computing, Anomaly Detection and Security Part V: Anomaly Detection and Security, Information Retrieval, Machine Learning, Demonstration Paper and Industry Paper.

The five-volume set LNCS 14961, 14962, 14963, 14964 and 14965 constitutes the refereed proceedings of the 8th International Joint Conference on Web and Big Data, APWeb-WAIM 2024, held in Jinhua, China, during August 30–September 1, 2024. The 171 full papers presented in these proceedings were carefully reviewed and selected from 558 submissions. The papers are organized in the following topical sections: Part I: Natural language processing, Generative AI and LLM, Computer Vision and Recommender System. Part II: Recommender System, Knowledge Graph and Spatial and Temporal Data. Part III: Spatial and Temporal Data, Graph Neural Network, Graph Mining and Database System and Query Optimization. Part IV: Database System and Query Optimization, Federated and Privacy-Preserving Learning, Network, Blockchain and Edge computing, Anomaly Detection and Security Part V: Anomaly Detection and Security, Information Retrieval, Machine Learning, Demonstration Paper and Industry Paper.

This book includes new research results of scholars from the Fourth International Conference on Advanced Intelligent Technologies (ICAIT 2023) organized by IRNet International Academic Communication Center, held during November 3–5, 2023. The book covers research work from active researchers who are working on collaboration of industry and various intelligent technologies such as intelligent technologies applicable/applied to manufacturing and distribution of industrial products, factory automation, business, etc. The topics included are all computational intelligence techniques applicable/applied to industry, intelligent techniques in data science applicable/applied to business and management, intelligent network systems applicable/applied to industrial production, intelligent technologies applicable to smart agriculture, and intelligent information systems for agriculture.

The emergence of Artificial Intelligence (AI) has had a tremendous impact on embedded and mobile systems. This book presents a diverse collection of papers that showcase cutting-edge research and practical applications of AI in this field. The peer-reviewed research articles stem from the First International Conference on Embedded and Mobile Systems (ICTA-EMOS), which was held on November 24th – 25th, 2022, in Arusha, Tanzania, East Africa. They demonstrate the breadth and depth of AI's impact across various domains, exploring topics such as healthcare advances, transportation optimization, sustainable solutions, and business and process optimization.

​This book constitutes the refereed proceedings of the 11th International Conference on Recent Trends in Analysis of Images, Social Networks and Texts, AIST 2023, held in Yerevan, Armenia, during September 28–30, 2023. The 19 full papers 2 short papers and 1 demo paper included in this book were carefully reviewed and selected from 52 submissions. They were organized in topical sections as follows: Natural Language Processing; Computer Vision; Data Analysis and Machine Learning; Network Analysis; Theoretical Machine Learning and Optimization; and Demo Paper.

This two-volume set LNAI 14844-14845 constitutes the refereed proceedings of the 22nd International Conference on Artificial Intelligence in Medicine, AIME 2024, held in Salt Lake City, UT, USA, during July 9-12, 2024. The 54 full papers and 22 short papers presented in the book were carefully reviewed and selected from 335 submissions. The papers are grouped in the following topical sections: Part I: Predictive modelling and disease risk prediction; natural language processing; bioinformatics and omics; and wearable devices, sensors, and robotics. Part II: Medical imaging analysis; data integration and multimodal analysis; and explainable AI.

This book constitutes the refereed proceedings of the 16th International Baltic Conference on Digital Business and Intelligent Systems, Baltic DB&IS 2024, held in Vilnius, Lithuania, during June 30–July 3, 2024. The 13 full papers and 3 short papers presented here, were carefully reviewed and selected from 36 submissions, and focus on the various fields of Business digitalization and development of intelligent business systems. Abstracts from the keynote speeches from the conference are also included in these proceedings.

This book constitutes the refereed proceedings of the 6th CCF China Blockchain Summit, CBCS 2023, held in Haikou, China, in December 2023. The 13 revised full papers presented were carefully reviewed and selected from 72 submissions. The papers deal with research results and development activities in all aspects of blockchain science and technology.

The book includes a thorough examination of the many types of algorithms for recommender systems, as well as a comparative analysis of them. It addresses the problem of dealing with the large amounts of data generated by the recommender system. The book also includes two case studies on recommender system applications in healthcare monitoring and military surveillance. It demonstrates how to create attack-resistant and trust-centric recommender systems for sensitive data applications. This book provides a solid foundation for designing recommender systems for use in healthcare and defense.

This book constitutes the proceedings of the 36th International Conference on Advanced Information Systems Engineering, CAiSE 2024, which was held in Limassol, Cyprus, during June 3-7, 2024. The 36 full papers included in these proceedings were carefully reviewed and selected from 180 submissions. They were organized in topical sections as follows: Process alignment, comparison and discovery; process discovery, monitoring and correction; graphs and graph networks; process modelling and management; prediction, monitoring and planning; data preparation, sharing, and architecture; requirements; process and decision mining; event and process discovery; session trust, security and risk; social aspects and LLMs; model-driven engineering and quantum workflows.

This 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.

This book introduces readers to big data analytics. It covers the background to and the concepts of big data, big data analytics, and cloud computing, along with the process of setting up, configuring, and getting familiar with the big data analytics working environments in the first two chapters. The third chapter provides comprehensive information on big data processing systems - from installing these systems to implementing real-world data applications, along with the necessary codes. The next chapter dives into the details of big data storage technologies, including their types, essentiality, durability, and availability, and reveals their differences in their properties. The fifth and sixth chapters guide the reader through understanding, configuring, and performing the monitoring and debugging of big data systems and present the available commercial and open-source tools for this purpose. Chapter seven gives information about a trending machine learning, Bayesian network: a probabilistic graphical model, by presenting a real-world probabilistic application to understand causal, complex, and hidden relationships for diagnosis and forecasting in a scalable manner for big data. Special sections throughout the eighth chapter present different case studies and applications to help the readers to develop their big data analytics skills using various big data analytics frameworks.The book will be of interest to business executives and IT managers as well as university students and their course leaders, in fact all those who want to get involved in the big data world.

This book constitutes the refereed conference proceedings of the second International Conference on Speech and Language Technologies for Low-Resource Languages, SPELLL 2023, held in Perundurai, Erode, India, during December 6–8, 2023. The 27 full papers and 6 short papers presented in this book were carefully reviewed and selected from 94 submissions. The papers are divided into the following topical sections: language resources; language technologies; speech technologies; and workshops - regional fake, MMLOW, LC4.

Unsupervised domain adaptation (UDA) is a challenging problem in machine learning where the model is trained on a source domain with labeled data and tested on a target domain with unlabeled data. In recent years, UDA has received significant attention from the research community due to its applicability in various real-world scenarios. This book provides a comprehensive review of state-of-the-art UDA methods and explores new variants of UDA that have the potential to advance the field. The book begins with a clear introduction to the UDA problem and is mainly organized into four technical sections, each focused on a specific piece of UDA research. The first section covers criterion optimization-based UDA, which aims to learn domain-invariant representations by minimizing the discrepancy between source and target domains. The second section discusses bi-classifier adversarial learning-based UDA, which creatively leverages adversarial learning by conducting a minimax game between the feature extractor and two task classifiers. The third section introduces source-free UDA, a novel UDA setting that does not require any raw data from the source domain. The fourth section presents active learning for UDA, which combines domain adaptation and active learning to reduce the amount of labeled data needed for adaptation. This book is suitable for researchers, graduate students, and practitioners who are interested in UDA and its applications in various fields, primarily in computer vision. The chapters are authored by leading experts in the field and provide a comprehensive and in-depth analysis of the current UDA methods and new directions for future research. With its broad coverage and cutting-edge research, this book is a valuable resource for anyone looking to advance their knowledge of UDA.

This book constitutes revised selected papers from the scientific satellite events held in conjunction with the 21st International Conference on Service-Oriented Computing, ICSOC 2023. The conference was held in Rome, Italy, during November 28 – December 1, 2023.This year, these satellite events were organized around four main tracks, including a workshop track, a demonstration track, a Ph.D. symposium, and an invited tutorial track.The ICSOC 2023 workshop track consisted of the following six workshops covering a wide range of topics that fall into the general area of service computing:Third International Workshop on AI-Enabled Process Automation (AI-PA 2023)7th Workshop on Adaptive Service-Oriented and Cloud Applications (ASOCA2023)First International Workshop on Secure, Accountable and Privacy-Preserving Data-Driven Service-Oriented Computing (SAPD 2023)First Services and Quantum Software Workshop (SQS 2023)First International Workshop on Sustainable Service-Oriented Computing: Addressing Environmental, Social, and Economic Dimensions (SSCOPE 2023) 19th International Workshop on Engineering Service-Oriented Applications and Cloud Services (WESOACS 2023)

This book includes high-quality research papers presented at the Second International Conference on Human-Centric Smart Computing (ICHCSC 2023), organized by the University of Engineering and Management, Jaipur, India, on 5–6 July 2023 in New Delhi, India. The topics covered in the book are human-centric computing, hyper connectivity, and data science. The book presents innovative work by leading academics, researchers, and experts from industry.

The continuous evolution and widespread application of communication technology, network technology and computing technology have promoted the intelligent interconnection of all things and ubiquitous sharing of information. The cross-border, cross-system, and cross-ecosystem exchange of user data has become commonplace. At the same time, difficulties in the prevention of private information abuse and lack of protection methods have become global problems. As such, there is an urgent need to intensify basic theoretical research in this field to support the protection of personal information in a ubiquitously interconnected environment. The authors of this book proposed the concept, definition and research scope of privacy computing for the first time in 2015. This book represents their original and innovative scientific research achievement dedicated to privacy computing research, and systematically explains the basic theory and technology involved. It introduces readers to the connection between personal information and privacy protection, defines privacy protection and privacy desensitization, clarifies and summarizes the limitations of existing privacy-preserving technologies in practical information system applications, analyzes the necessity of conducting privacy computing research, and proposes the concept, definition and research scope of privacy computing. It comprehensively expounds the theoretical system of privacy computing and some privacy-preserving algorithms based on the idea of privacy computing. In closing, it outlines future research directions.

This book constitutes the revised selected papers of the 15th International Conference, MEDES 2023, Heraklion, Crete, Greece, May 5–7, 2023The 29 full papers included in this volume were carefully reviewed and selected from 52 submissions. The papers focus on the following topics: Design Issues & BlockChain, Query Processing and Visualization, Learning Issues, Services and Systems, Business and Communication Technologies, Digital Twin and Security, Architecture Technologies, Time and Text Management.

These two volumes constitute the revised selected papers of the 5th International Conference, CSEI 2023, held in Kunming, China, during August 11–13, 2023.The 76 full papers and the 21 short papers included in this volume were carefully reviewed and selected from 297 submissions. They focus on computer science, education informatization and engineering education, innovative application for the deeper integration of education practice and information technology, educational informatization and big data for education.