This book gathers the proceedings of the fifteenth International Conference on Management Science and Engineering Management (ICMSEM 2021) held on August 1-4, 2021, at the University of Castilla-La Mancha (UCLM), Toledo, Spain. The proceedings contains theoretical and practical research of decision support systems, complex systems, empirical studies, sustainable development, project management, and operation optimization, showing advanced management concepts and demonstrates substantial interdisciplinary developments in MSEM methods and practical applications. It allows researchers and practitioners in management science and engineering management (MSEM) to share their latest insights and contribution. Meanwhile, it appeals to readers interested in these areas, especially those looking for new ideas and research directions.

This book gathers the proceedings of the 14th International Conference on Management Science and Engineering Management (ICMSEM 2020). Held at the Academy of Studies of Moldova from July 30 to August 2, 2020, the conference provided a platform for researchers and practitioners in the field to share their ideas and experiences. Covering a wide range of topics, including hot management issues in engineering science, the book presents novel ideas and the latest research advances in the area of management science and engineering management. It includes both theoretical and practical studies of management science applied in computing methodology, highlighting advanced management concepts, and computing technologies for decision-making problems involving large, uncertain and unstructured data. The book also describes the changes and challenges relating to decision-making procedures at the dawn of the big data era, and discusses new technologies for analysis, capture, search, sharing, storage, transfer and visualization, and in the context of privacy violations, as well as advances in the integration of optimization, statistics and data mining. Given its scope, it will appeal to a wide readership, particularly those looking for new ideas and research directions.

Communication based on the internet of things (IoT) generates huge amounts of data from sensors over time, which opens a wide range of applications and areas for researchers. The application of analytics, machine learning, and deep learning techniques over such a large volume of data is a very challenging task. Therefore, it is essential to find patterns, retrieve novel insights, and predict future behavior using this large amount of sensory data. Artificial intelligence (AI) has an important role in facilitating analytics and learning in the IoT devices. Applying AI-Based IoT Systems to Simulation-Based Information Retrieval provides relevant frameworks and the latest empirical research findings in the area. It is ideal for professionals who wish to improve their understanding of the strategic role of trust at different levels of the information and knowledge society and trust at the levels of the global economy, networks and organizations, teams and work groups, information systems, and individuals as actors in the networked environments. Covering topics such as blockchain visualization, computer-aided drug discovery, and health monitoring, this premier reference source is an excellent resource for business leaders and executives, IT managers, security professionals, data scientists, students and faculty of higher education, librarians, hospital administrators, researchers, and academicians.

This book gathers the proceedings of the 14th International Conference on Management Science and Engineering Management (ICMSEM 2020). Held at the Academy of Studies of Moldova from July 30 to August 2, 2020, the conference provided a platform for researchers and practitioners in the field to share their ideas and experiences. Covering a wide range of topics, including hot management issues in engineering science, the book presents novel ideas and the latest research advances in the area of management science and engineering management. It includes both theoretical and practical studies of management science applied in computing methodology, highlighting advanced management concepts, and computing technologies for decision-making problems involving large, uncertain and unstructured data. The book also describes the changes and challenges relating to decision-making procedures at the dawn of the big data era, and discusses new technologies for analysis, capture, search, sharing, storage, transfer and visualization, as well as advances in the integration of optimization, statistics and data mining. Given its scope, it will appeal to a wide readership, particularly those looking for new ideas and research directions.

Intelligent systems are technologically advanced machines that perceive and respond to the world around them. Artificial Intelligence and Machine Learning for Smart Community: Concepts and Applications presents the evolution, challenges, and limitations of the application of machine learning and artificial intelligence to intelligent systems and smart communities. Covers the core and fundamental aspects of artificial intelligence, machine learning, and computational algorithms in smart intelligent systems Discusses the integration of artificial intelligence with machine learning using mathematical modeling Elaborates concepts like supervised and unsupervised learning, and machine learning algorithms, such as linear regression, logistic regression, random forest, and performance evaluation matrices Introduces modern algorithms such as convolutional neural networks and support vector machines Presents case studies on smart healthcare, smart traffic management, smart buildings, autonomous vehicles, smart education, modern community, and smart machines Artificial Intelligence and Machine Learning for Smart Community: Concepts and Applications is primarily written for graduate students and academic researchers working in the fields of computer science and engineering, electrical engineering, and information technology. Seasonal Blurb: This reference text presents the most recent and advanced research on the application of artificial intelligence and machine learning on intelligent systems. It will discuss important topics such as business intelligence, reinforcement learning, supervised learning, and unsupervised learning in a comprehensive manner.

This book represents an important voice in the discourse on the adoption of emerging ICT for sustainability. It focuses on how emerging ICT acts as a crucial enabler of sustainability, offering new forward-looking approaches to this field. The book explores how emerging ICT adoption drives sustainability efforts in business and public organizations, promoting ecological, economic, social, cultural, and political sustainability. The book's theoretical discussions, conceptual approaches, empirical studies, diverse perspectives, and views make it a valuable and comprehensive reference work. Appealing to both researchers and practitioners, this book provides significant areas for research and practice related to the contribution of emerging ICT adoption to sustainability. It also suggests vital considerations for programming and building sustainable development-driven emerging ICT adoption. Readers will find answers to important contemporary questions, such as: • What are the concepts, frameworks, models, and approaches to enhance sustainable development through the adoption of emerging ICT? • How does the adoption of emerging ICT influence sustainability? • How can emerging ICT be adopted to enhance sustainability? • What are the current practices and successful cases of emerging ICT adoption for sustainability? • What factors influence emerging ICT adoption to enhance sustainability?

The book introduces concepts, principles, methods and procedures that will be valuable to students and scholars in thinking about existing organization systems, proposing new systems and working with management professionals in implementing new information systems. This book of Information Systems and Management Science (proceedings of ISMS 2020) is intended to be used as a reference by students and researchers who collect scientific and technical contributions with respect to models, tools, technologies and applications in the field of information systems and management science. This textbook shows how to exploit information systems in a technology-rich management field.