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The impact of artificial intelligence (AI) on business and society has been significant, with the incorporation of AI technologies such as robots, facial recognition, algorithms, and natural language processing into business leading to both corporate benefits and potential challenges for stakeholders. The question of how to engage in responsible business practices in the era of AI is an important one, and there is a need for more research on the relationship between AI and corporate social responsibility (CSR). As AI becomes more prevalent, there is a growing focus on the ethical implications of AI and the potential for AI to perpetuate biases or to displace human workers. CSR initiatives can include considerations of ethical AI in the development and use of AI systems. AI has the potential to solve many global challenges and improve people's lives, but it can also have negative consequences if not developed and used responsibly. CSR initiatives can focus on the social impact of AI,including efforts to ensure that the benefits of AI are distributed fairly and that AI is used for the common good. CSR initiatives often involve engaging with stakeholders, including employees, customers, and communities, to understand their needs and concerns and to ensure that their interests are taken into account. This can include engaging with stakeholders about the use of AI in the organization and its potential impactsThe adoption of AI in business is changing many aspects of doing business in a socially responsible manner, and there is a need to examine the potential unethical behaviors and novel ways of engaging in CSR that may arise. This book aims to focus on AI and CSR, and to advance our understanding of the role of AI in organizations and the literature on CSR by assembling high-quality papers with a strong connection between theory and practice.

This book constitutes the refereed proceedings of the 4th Southern African Conference on Artificial Intelligence Research, SACAIR 2023, held in Muildersdrift, South Africa, in December 2023. The 22 full papers presented in these proceedings were carefully reviewed and selected from 66 submissions. The papers are organized in the following topical sections: Responsible and Ethical AI Track; Socio-Technical and Human-Centered AI Track; Algorithmic, and Data Driven and Symbolic AI.

This book constitutes the refereed proceedings of the Third Southern African Conference on Artificial Intelligence Research, SACAIR 2022, held in Stellenbosch, South Africa, in December 2022. The 26 papers presented were thoroughly reviewed and selected from the 73 submissions. They are organized on the topical sections on​ algorithmic, data driven and symbolic AI; socio-technical and human-centered AI; responsible and ethical AI.

The eight-volume set LNCS 13375 – 13382 constitutes the proceedings of the 22nd International Conference on Computational Science and Its Applications, ICCSA 2022, which was held in Malaga, Spain during July 4 – 7, 2022. The first two volumes contain the proceedings from ICCSA 2022, which are the 57 full and 24 short papers presented in these books were carefully reviewed and selected from 279 submissions. The other six volumes present the workshop proceedings, containing 285 papers out of 815 submissions. These six volumes includes the proceedings of the following workshops:​Advances in Artificial Intelligence Learning Technologies: Blended Learning, STEM, Computational Thinking and Coding (AAILT 2022); Workshop on Advancements in Applied Machine-learning and Data Analytics (AAMDA 2022); Advances in information Systems and Technologies for Emergency management, risk assessment and mitigation based on the Resilience (ASTER 2022); Advances in Web Based Learning (AWBL 2022); Blockchain and Distributed Ledgers: Technologies and Applications (BDLTA 2022); Bio and Neuro inspired Computing and Applications (BIONCA 2022); Configurational Analysis For Cities (CA Cities 2022); Computational and Applied Mathematics (CAM 2022), Computational and Applied Statistics (CAS 2022); Computational Mathematics, Statistics and Information Management (CMSIM); Computational Optimization and Applications (COA 2022); Computational Astrochemistry (CompAstro 2022); Computational methods for porous geomaterials (CompPor 2022); Computational Approaches for Smart, Conscious Cities (CASCC 2022); Cities, Technologies and Planning (CTP 2022); Digital Sustainability and Circular Economy (DiSCE 2022); Econometrics and Multidimensional Evaluation in Urban Environment (EMEUE 2022); Ethical AI applications for a human-centered cyber society (EthicAI 2022); Future Computing System Technologies and Applications (FiSTA 2022); Geographical Computing and Remote Sensing for Archaeology (GCRSArcheo 2022); Geodesign in Decision Making: meta planning and collaborative design for sustainable and inclusive development (GDM 2022); Geomatics in Agriculture and Forestry: new advances and perspectives (GeoForAgr 2022); Geographical Analysis, Urban Modeling, Spatial Statistics (Geog-An-Mod 2022); Geomatics for Resource Monitoring and Management (GRMM 2022); International Workshop on Information and Knowledge in the Internet of Things (IKIT 2022); 13th International Symposium on Software Quality (ISSQ 2022); Land Use monitoring for Sustanability (LUMS 2022); Machine Learning for Space and Earth Observation Data (MALSEOD 2022); Building multi-dimensional models for assessing complex environmental systems (MES 2022); MOdels and indicators for assessing and measuring the urban settlement deVElopment in the view of ZERO net land take by 2050 (MOVEto0 2022); Modelling Post-Covid cities (MPCC 2022); Ecosystem Services: nature's contribution to people in practice. Assessment frameworks, models, mapping, and implications (NC2P 2022); New Mobility Choices For Sustainable and Alternative Scenarios (NEMOB 2022); 2nd Workshop on Privacy in the Cloud/Edge/IoT World (PCEIoT 2022); Psycho-Social Analysis of Sustainable Mobility in The Pre- and Post-Pandemic Phase (PSYCHE 2022); Processes, methods and tools towards RESilient cities and cultural heritage prone to SOD and ROD disasters (RES 2022); Scientific Computing Infrastructure (SCI 2022); Socio-Economic and Environmental Models for Land Use Management (SEMLUM 2022); 14th International Symposium on Software Engineering Processes and Applications (SEPA 2022); Ports of the future - smartness and sustainability (SmartPorts 2022); Smart Tourism (SmartTourism 2022); Sustainability Performance Assessment: models, approaches and applications toward interdisciplinary and integrated solutions (SPA 2022); Specifics of smart cities development in Europe (SPEED 2022); Smart and Sustainable Island Communities (SSIC 202

'Dive deep into the evolving landscape of AI with'Towards Ethical and Socially Responsible Explainable AI'. This transformative book explores the profound impact of AI on society, emphasizing transparency, accountability, and fairness in decision-making processes. It offers invaluable insights into creating AI systems that not only perform effectively but also uphold ethical standards and foster trust. Essential reading for technologists, policymakers, and all stakeholders invested in shaping a responsible AI future.'

The book provides comprehensive and cognitive approach to building and deploying sophisticated information systems. The book utilizes non-linear optimization techniques, fuzzy logic, and rough sets to model various real-world use cases for the digital era. The hybrid information system modeling handles both qualitative and quantitative data and can effectively handle uncertainty and imprecision in the data. The combination of non-linear optimization mechanisms, fuzzy logic, and rough sets provides a robust foundation for next-generation information systems that can fulfill the demands of adaptive, aware, and adroit software applications for the knowledge era. The book emphasizes the importance of the hybrid approach, which combines the strengths of both mathematical and AI techniques, to achieve a more comprehensive and effective modeling process. Hybrid information system modeling techniques combine different approaches, such as fuzzy logic, rough sets, and neural networks, to create models that can handle the complexity and uncertainty of real-world problems. These techniques provide a powerful tool for modeling and analyzing complex systems, and the applications of hybrid information system modeling demonstrate their potential for solving real-world problems in various fields.

This book aims to provide a comprehensive understanding of the interplay between technology and business and its implications for future growth and innovation. In today's rapidly changing world, technology plays a crucial role in shaping the business landscape. Advancements in artificial intelligence, blockchain, data analytics, and automation have revolutionized how organizations operate, compete, and achieve success. Understanding the profound impact of technology on business is vital for entrepreneurs, managers, policymakers, and academics alike. This book aims to explore the connection between technology and business, highlighting its importance in driving transformative changes across various industries. We welcome scholars, researchers, and practitioners to share their expertise and insights in this exciting endeavor.This book captures the essence of exploring the dynamic relationship between technology and business, emphasizing the potential for innovation and growth. It conveys the idea of embracing the transformative power of technology within the business realm and the opportunities it presents for unleashing new ideas and strategies.By delving into various aspects such as emerging technologies, business strategies, innovation, and ethical considerations, it aims to provide a comprehensive understanding of the symbiotic relationship between technology and business. It offers insights into the integration of technology into decision-making processes, the transformative impact on different industries, and strategies for leveraging technology to drive organizational growth and sustainability.Furthermore, the book highlights real-world case studies, explores emerging trends, and discusses the ethical and social implications of technology adoption in the business context. It serves as a valuable resource for entrepreneurs, managers, policymakers, academics, and anyone interested in understanding and harnessing the potential of technology for business success. This book aims to be a valuable resource for individuals interested in the transformative power of technology in the business realm. By compiling a collection of insightful chapters, it offers readers a diverse range of perspectives, frameworks, and case studies that shed light on the complexities and opportunities associated with technology-driven business environments.

This book covers different technological and business-related issues including ethical use and cultural sensitivity of data used in businesses, managing data privacy and protection, governance standards for digital transformation, executive leadership strategic decisions, and business innovation and sustainability. With the recent development of artificial intelligence (AI), businesses are urged to consider innovation while applying digital transformation. Depending on the nature of the businesses, it is found that innovative digital transformation is required with the use of artificial intelligence. However, the future of AI in businesses is yet unclear, the question is it true that without digital transformation businesses are no longer sustainable? Researchers argue that digital transformation could be an opportunity for business to create a global brand however several implications and challenges should be considered including governance and responsible digital management. This book explores how businesses could benefit from AI and leverage technologies to sustain businesses. The book is authored by leading experts in the field of AI, digitalization, and business innovation and sustainability; the author's diversity reflects quality of research with high level of impact in the research topic. It is written in accessible language that makes it easy for business leaders, researchers, policymakers, and anyone interested in the future of business development to understand the complex concepts and ideas presented in the book. This book provides insight for executive leaders in setting new innovative strategies toward leveraging AI in business at different levels of operations to support business sustainability. The book provides different theoretical and practical practices and case studies that could be used as a guideline for policy making and devising innovative directions.

This book presents a groundbreaking exploration into the dynamic synergy between artificial intelligence and business development. Titled'AI Integration for Business Development: Navigating Opportunities, Unleashing Potential, Managing Risks,'it serves as an indispensable guide for leaders and visionaries aiming to harness the transformative power of AI. The book introduces a comprehensive journey that unveils the strategic integration of AI into business development strategies. This book shows how to navigate a myriad of opportunities, strategically unleash untapped potential, and adeptly manage risks in the ever-evolving landscape of artificial intelligence. Through meticulous insights, real-world examples, and actionable strategies, readers gain the knowledge to make informed decisions and drive competitive advantage. This book presents not only a roadmap for identifying lucrative opportunities but also a blueprint for unlocking the full potential of AI technologies. Whether you are a seasoned executive, entrepreneur, or decision-maker, this book empowers you to proactively manage risks inherent in AI adoption, ensuring resilience and adaptability in your business model. Discover how to stay ahead in the rapidly changing business landscape, shaping the future of your business development initiatives. This book is your indispensable companion, offering profound insights into AI integration and empowering you to seize the transformative potential of AI. This book is your key to charting a course toward sustained success and innovation in the dynamic world of modern business.

This book aims to bring together researchers, academics, and professionals, promoting the sharing and discussing knowledge, new perspectives, experiences, and innovations in Qualitative Research. This book includes selecting the articles accepted for presentation and discussion at WCQR2024, held January 23 to 25, 2024 (face-to-face and virtual conference). WCQR2024 featured four main application fields (Education, Health, Social Sciences, and Engineering/Technology) and seven main subjects: Rationale and Paradigms of Qualitative Research; Systematization of Approaches with Qualitative Studies; Qualitative and Mixed Methods Research; Data Analysis Types; Innovative Processes of Qualitative Data Analysis; Qualitative Research in Web Context; Qualitative Analysis with Software Support. The book is valuable for everyone interested in qualitative research, emphasizing Computer-Assisted Qualitative Data Analysis Software (CAQDAS).

This book contains research papers that were accepted for presentation at the 17th International Conference on Interdisciplinarity in Engineering—INTER-ENG 2023, which was held on 5–6 October 2023, in the city of Târgu Mureș, Romania. The general scope of the conference “Towards transition for a more competitive European industry in a smart, safe and sustainable future” is proposing a new approach related to the development of a new generation of smart factories grounded on the manufacturing and assembly process digitalization. It is related to advance manufacturing technology, lean manufacturing, sustainable manufacturing, additive manufacturing, manufacturing tools and equipment. It is a leading international professional and scientific forum of great interest for engineers and scientists who can read in this book research works contributions and recent developments as well as current practices in advanced fields of engineering.

This book contains research papers that were accepted for presentation at the 17th International Conference on Interdisciplinarity in Engineering—INTER-ENG 2023, which was held on 5–6 October 2023, in the city of Târgu Mureș, Romania. The general scope of the conference “Towards transition for a more competitive European industry in a smart, safe and sustainable future” is proposing a new approach related to the development of a new generation of smart factories grounded on the manufacturing and assembly process digitalization. It is related to advance manufacturing technology, lean manufacturing, sustainable manufacturing, additive manufacturing, manufacturing tools and equipment. It is a leading international professional and scientific forum of great interest for engineers and scientists who can read in this book research works contributions and recent developments as well as current practices in advanced fields of engineering.

This book presents high-quality research papers presented at 4th International Conference on Smart Data Intelligence (ICSMDI 2024) organized by Kongunadu College of Engineering and Technology at Trichy, Tamil Nadu, India, during February 2024. This book brings out the new advances and research results in the fields of algorithmic design, data analysis, and implementation on various real-time applications. It discusses many emerging related fields like big data, data science, artificial intelligence, machine learning, and deep learning which have deployed a paradigm shift in various data-driven approaches that tends to evolve new data-driven research opportunities in various influential domains like social networks, health care, information, and communication applications.

In an era defined by technological breakthroughs such as AI, blockchain, and IoT, this book offers a fresh and practical approach to Business Model Innovation (BMI). It delves into how technological advancements drive new business models and enhance operational efficiency, providing actionable insights and real-world examples for business leaders, strategists, operations managers, entrepreneurs, and students in business and technology disciplines. Encouraging diverse research methods, including theoretical, empirical, and multimethod studies, it welcomes manuscripts with clear managerial or policy implications. Aimed at students, scholars, researchers, professionals, executives, government agencies, and policymakers, this book equips readers with tools to succeed in today's dynamic business environment and supports multidisciplinary research to advance innovation management practices.

This book features papers focusing on the implementation of new and future technologies, which were presented at the International Conference on New Technologies, Development and Application—Advanced Production Processes and Intelligent Systems held at the Academy of Science and Arts of Bosnia and Herzegovina in Sarajevo on 20–22 June 2024. It covers a wide range of future technologies and technical disciplines, including complex systems such as Industry 4.0; robotics; mechatronics systems; automation; manufacturing; cyber-physical and autonomous systems; sensors; networks; control, energy, renewable energy sources; automotive and biological systems; vehicular networking and connected vehicles; and intelligent transport, effectiveness and logistics systems, smart grids, nonlinear systems, power, social and economic systems, education, and IoT. The book New Technologies, Development and Application VII is oriented toward Fourth Industrial Revolution “Industry 4.0”, which implementation will improve many aspects of human life in all segments and lead to changes in business paradigms and production models. Further, new business methods are emerging, transforming production systems, transport, delivery, and consumption, which need to be monitored and implemented by every company involved in the global market.

The 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

This book constitutes the refereed proceedings of the Sescond Southwest Data Science Conference, SDSC 2023, held in Waco, TX, USa, during March 24-25, 2023. The 16 full and 1 short paper included in this book were carefully reviewed and selected from 72 submissions. They were oragnized in topical sections named: Business social and foundation data science; and applied data science, artifiicial intelligence and data engineering.

This comprehensive book explores the transformative role of artificial intelligence (AI) in business innovation and research. It provides a solid foundation in AI technologies, such as machine learning, natural language processing, and computer vision, and examines how they reshape business models and revolutionize industries. The book highlights the strategic implications of AI in enhancing customer experience, optimizing operations, and enabling data-driven decision-making. It explores the integration of AI with emerging trends like IoT, blockchain, and cloud computing for innovation. The role of AI in advancing scientific discovery and academic research is also explored, addressing challenges and opportunities in AI-driven methodologies. Organizational and ethical dimensions of AI implementation are considered, including talent acquisition, skills development, and data governance. Real-world case studies showcase AI's transformative power across diverse industries. This forward-thinking guide equips academics, researchers, and business leaders with knowledge and insights to harness the potential of AI and contribute to innovation and research.

Inspired by this symposium we would like to rethink and provide an insight about the use of new technologies in architecture and design. The consideration spans over (but not limited to) computational design, virtual experience, digital fabrication, artificial intelligence and sustainability/environment. Readers of the proceedings will benefit from discussions on how adoption of new technologies can benefit the Construction Industry rather than just for the sake of leveraging new technologies. The book targets scholars and high-education level students, as well as Ph.D.s which research falls into the broad realm of digital design.

Computer and Information Security Handbook, Fourth Edition, provides the most current and complete reference on computer security available on the market. The book offers deep coverage of an extremely wide range of issues in computer and cybersecurity theory, applications, and best practices, offering the latest insights into established and emerging technologies and advancements. With new parts devoted to such current topics as Cyber Security for the Smart City and Smart Homes, Cyber Security of Connected and Automated Vehicles, and Future Cyber Security Trends and Directions, the book now has 115 chapters written by leading experts in their fields, as well as 8 updated appendices and an expanded glossary. It continues its successful format of offering problem-solving techniques that use real-life case studies, checklists, hands-on exercises, question and answers, and summaries. Chapters new to this edition include such timely topics as Threat Landscape and Good Practices for Internet Infrastructure, Cyber Attacks Against the Grid Infrastructure, Threat Landscape and Good Practices for the Smart Grid Infrastructure, Energy Infrastructure Cyber Security, Smart Cities Cyber Security Concerns, Community Preparedness Action Groups for Smart City Cyber Security, Smart City Disaster Preparedness and Resilience, Cyber Security in Smart Homes, Threat Landscape and Good Practices for Smart Homes and Converged Media, Future Trends for Cyber Security for Smart Cities and Smart Homes, Cyber Attacks and Defenses on Intelligent Connected Vehicles, Cyber Security Issues in VANETs, Use of AI in Cyber Security, New Cyber Security Vulnerabilities and Trends Facing Aerospace and Defense Systems, How Aerospace and Defense Companies Will Respond to Future Cyber Security Threats, Fighting the Rising Trends of Cyber Attacks on Aviation, Future Trends for Cyber Security in the Gaming Industry, Future Trends for Cyber Attacks in the Healthcare Industry, and much more. - Written by leaders in the field - Comprehensive and up-to-date coverage of the latest security technologies, issues, and best practices - Presents methods for analysis, along with problem-solving techniques for implementing practical solutions

This book offers a fresh approach to harnessing the power of artificial intelligence and digital technologies to drive growth and success. With a wide-ranging scope that covers various industries and sectors, this book provides invaluable insights and practical guidance for individuals and organizations seeking to thrive in a rapidly evolving business landscape. Designed for business professionals, entrepreneurs, and marketing enthusiasts, this book unlocks the potential of AI and digitalization, offering key strategies and real-world examples to transform your business and stay ahead of the competition. Whether you're looking to optimize customer experiences, leverage data analytics, or streamline operations, this book is your ultimate resource for achieving sustainable business development through cutting-edge technologies.

This comprehensive book explores the transformative role of artificial intelligence (AI) in business innovation and research. It provides a solid foundation in AI technologies, such as machine learning, natural language processing, and computer vision, and examines how they reshape business models and revolutionize industries. The book highlights the strategic implications of AI in enhancing customer experience, optimizing operations, and enabling data-driven decision-making. It explores the integration of AI with emerging trends like IoT, blockchain, and cloud computing for innovation. The role of AI in advancing scientific discovery and academic research is also explored, addressing challenges and opportunities in AI-driven methodologies. Organizational and ethical dimensions of AI implementation are considered, including talent acquisition, skills development, and data governance. Real-world case studies showcase AI's transformative power across diverse industries. This forward-thinking guide equips academics, researchers, and business leaders with knowledge and insights to harness the potential of AI and contribute to innovation and research.

This book explores issues related to information and communication technology in management and higher education, intelligent computing, and information security. In this book, the authors investigate various aspects of information and communication technology and systems, their development and applications in education, science, and management. The authors develop new models, methods, and approaches for digital transformation in management processes including digital project management, intelligent systems, particularly those that deploy artificial intelligence, data protection, and reliability. A part of this book is devoted to the application of information and communication technology in higher education to ensure the process of digital transformation in higher education institutions. The book is of interest to experts in the field of information and communication technology and systems, project managers, scientists, and Ph.D. students.

This book constitutes the proceedings of the 21st International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2024, held in Uppsala, Sweden, during May 28–31, 2024.The 33 full papers and the 9 short papers presented in the proceedings were carefully reviewed and selected from a total of 104 submissions. The content of the papers focus on new techniques or applications in the area and foster the integration of techniques from different fields dealing with large and complex problems.

This book constitutes the proceedings of the 23rd International TRIZ Future Conference on Towards AI-Aided Invention and Innovation, TFC 2023, which was held in Offenburg, Germany, during September 12–14, 2023. The event was sponsored by IFIP WG 5.4.The 43 full papers presented in this book were carefully reviewed and selected from 80 submissions. The papers are divided into the following topical sections: AI and TRIZ; sustainable development; general vision of TRIZ; TRIZ impact in society; and TRIZ case studies.

This book gathers contributions from the fourth edition of the Conference on'Philosophy and Theory of Artificial Intelligence'(PT-AI), held on 27-28th of September 2021 at Chalmers University of Technology, in Gothenburg, Sweden. It covers topics at the interface between philosophy, cognitive science, ethics and computing. It discusses advanced theories fostering the understanding of human cognition, human autonomy, dignity and morality, and the development of corresponding artificial cognitive structures, analyzing important aspects of the relationship between humans and AI systems, including the ethics of AI. This book offers a thought-provoking snapshot of what is currently going on, and what are the main challenges, in the multidisciplinary field of the philosophy of artificial intelligence.

How is it possible to allow multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private? Traditional machine learning approaches need to combine all data at one location, typically a data center, which may very well violate the laws on user privacy and data confidentiality. Today, many parts of the world demand that technology companies treat user data carefully according to user-privacy laws. The European Union's General Data Protection Regulation (GDPR) is a prime example. In this book, we describe how federated machine learning addresses this problem with novel solutions combining distributed machine learning, cryptography and security, and incentive mechanism design based on economic principles and game theory. We explain different types of privacy-preserving machine learning solutions and their technological backgrounds, and highlight some representative practical use cases. We show how federated learning can become the foundation of next-generation machine learning that caters to technological and societal needs for responsible AI development and application.

In this book, Dr. Soofastaei and his colleagues reveal how all mining managers can effectively deploy advanced analytics in their day-to-day operations- one business decision at a time.Most mining companies have a massive amount of data at their disposal. However, they cannot use the stored data in any meaningful way. The powerful new business tool-advanced analytics enables many mining companies to aggressively leverage their data in key business decisions and processes with impressive results.From statistical analysis to machine learning and artificial intelligence, the authors show how many analytical tools can improve decisions about everything in the mine value chain, from exploration to marketing.Combining the science of advanced analytics with the mining industrial business solutions, introduce the “Advanced Analytics in Mining Engineering Book” as a practical road map and tools for unleashing the potential buried in yourcompany's data.The book is aimed at providing mining executives, managers, and research and development teams with an understanding of the business value and applicability of different analytic approaches and helping data analytics leads by giving them a business framework in which to assess the value, cost, and risk of potential analytical solutions. In addition, the book will provide the next generation of miners – undergraduate and graduate IT and mining engineering students – with an understanding of data analytics applied to the mining industry. By providing a book with chapters structured in line with the mining value chain, we will provide a clear, enterprise-level view of where and how advanced data analytics can best be applied. This book highlights the potential to interconnect activities in the mining enterprise better. Furthermore, the book explores the opportunities for optimization and increased productivity offered by better interoperability along the mining value chain – in line with the emerging vision of creating a digital mine with much-enhanced capabilities for modeling, simulation, and the use of digital twins – in line with leading “digital” industries.

This book constitutes the refereed proceedings of the 45th German Conference on Artificial Intelligence, KI 2022, held in September 2022.The 12 full and 5 short papers were carefully reviewed and selected from 51 submissions. Additionally, five abstracts of invited talks are included. As well-established annual conference series KI is dedicated to research on theory and applications across all methods and topic areas of AI research.Due to COVID-19 the conference was held virtually.The chapter'Dynamically Self-Adjusting Gaussian Processes for Data Stream Modelling'is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book presents the state of the art in High Performance Computing on modern supercomputer architectures. It addresses trends in hardware and software development in general. The contributions cover a broad range of topics, from performance evaluations in context with power efficiency to Computational Fluid Dynamics and High Performance Data Analytics. In addition, they explore new topics like the use of High Performance Computers in the field of Artificial Intelligence and Machine Learning. All contributions are based on selected papers presented at the 30th Workshop on Sustained Simulation Performance (WSSP) held at the High Performance Computing Center, University of Stuttgart, Germany in October 2019 and on the papers for the planned Workshop on Sustained Simulation Performance in March 2020, which could not take place due to the Covid-19 pandemic.

The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic.The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. The volumes are organized in topical sections as follows: Part I: Pattern Mining; clustering; privacy and fairness; (social) network analysis and computational social science; dimensionality reduction and autoencoders; domain adaptation; sketching, sampling, and binary projections; graphical models and causality; (spatio-) temporal data and recurrent neural networks; collaborative filtering and matrix completion. Part II: deep learning optimization and theory;active learning; adversarial learning; federated learning; Kernel methods and online learning; partial label learning; reinforcement learning; transfer and multi-task learning; Bayesian optimization and few-shot learning. Part III: Combinatorial optimization; large-scale optimization and differential privacy; boosting and ensemble methods; Bayesian methods; architecture of neural networks; graph neural networks; Gaussian processes; computer vision and image processing; natural language processing; bioinformatics. Part IV: applied data science: recommendation; applied data science: anomaly detection; applied data science: Web mining; applied data science: transportation; applied data science: activity recognition; applied data science: hardware and manufacturing; applied data science: spatiotemporal data. Part V: applied data science: social good; applied data science: healthcare; applied data science: e-commerce and finance; applied data science: computational social science; applied data science: sports; demo track.

How is it possible to allow multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private? Traditional machine learning approaches need to combine all data at one location, typically a data center, which may very well violate the laws on user privacy and data confidentiality. Today, many parts of the world demand that technology companies treat user data carefully according to user-privacy laws. The European Union's General Data Protection Regulation (GDPR) is a prime example. In this book, we describe how federated machine learning addresses this problem with novel solutions combining distributed machine learning, cryptography and security, and incentive mechanism design based on economic principles and game theory. We explain different types of privacy-preserving machine learning solutions and their technological backgrounds, and highlight some representative practical use cases. We show how federated learning can become the foundation of next-generation machine learning that caters to technological and societal needs for responsible AI development and application.

This volume provides resourceful thinking and insightful management solutions to the many challenges that decision makers face in their predictions, preparations, and implementations of the key elements that our societies and industries need to take as they move toward digitalization and smartness. The discussions within the book aim to uncover the sources of large-scale problems in socio-industrial dilemmas, and the theories that can support these challenges. How theories might also transition to real applications is another question that this book aims to uncover. In answer to the viewpoints expressed by several practitioners and academicians, this book aims to provide both a learning platform which spotlights open questions with related case studies. The relationship between Industry 4.0 and Society 5.0 provides the basis for the expert contributions in this book, highlighting the uses of analytical methods such as mathematical optimization, heuristic methods, decomposition methods, stochastic optimization, and more. The book will prove useful to researchers, students, and engineers in different domains who encounter large scale optimization problems and will encourage them to undertake research in this timely and practical field. The book splits into two parts. The first part covers a general perspective and challenges in a smart society and in industry. The second part covers several case studies and solutions from the operations research perspective for large scale challenges specific to various industry and society related phenomena.

The book presents research that contributes to the development of intelligent dialog systems to simplify diverse aspects of everyday life, such as medical diagnosis and entertainment. Covering major thematic areas: machine learning and artificial neural networks; algorithms and models; and social and biometric data for applications in human–computer interfaces, it discusses processing of audio-visual signals for the detection of user-perceived states, the latest scientific discoveries in processing verbal (lexicon, syntax, and pragmatics), auditory (voice, intonation, vocal expressions) and visual signals (gestures, body language, facial expressions), as well as algorithms for detecting communication disorders, remote health-status monitoring, sentiment and affect analysis, social behaviors and engagement. Further, it examines neural and machine learning algorithms for the implementation of advanced telecommunication systems, communication with people with special needs, emotionmodulation by computer contents, advanced sensors for tracking changes in real-life and automatic systems, as well as the development of advanced human–computer interfaces. The book does not focus on solving a particular problem, but instead describes the results of research that has positive effects in different fields and applications.