Petroleum Characterization and Bioprocesses
This Special Issue aims to showcase cutting-edge research on numerical modeling and experimental investigation in the characterization of petroleum and its derivatives and bioprocesses. The scope of this Special Issue includes cases of investigations on petroleum property relationships, the modeling of petroleum properties, the application of different methods for the characterization of petroleum and its derivatives, sustainable fuels, biofuels, petroleum refining process performance optimization, and bioprocesses. Included in this Special Issue are seventeen contributions from researchers across the globe in the fields of petroleum fluid characterization and bioprocesses.
Computational Intelligence and Human-Computer Interaction
The present Special Issue contains all of the articles accepted and published in the Special Issue of MDPI's journal Mathematics titled "Computational Intelligence and Human-Computer Interaction: Modern Methods and Applications, 2nd Edition", as a follow-up on the first edition. This Special Issue covered a wide range of topics connected to the theory and application of different computational intelligence techniques to the domain of human-computer interaction, such as automatic speech recognition, speech processing and analysis, virtual reality, emotion-aware applications, digital storytelling, natural language processing, smart cars and devices, and online learning. We hope that this Special Issue will be interesting and useful for those working in various areas of artificial intelligence, human-computer interaction, and software engineering and those interested in how these domains are connected in real-life situations.
Application of Artificial Intelligence in the New Era of Communication Networks
This Special Issue highlights the valuable contributions to wireless and mobile communication technologies, mobile edge computing, and blockchain using modern artificial intelligence and machine learning techniques. The applications of machine learning in wireless and mobile communication networks have been receiving increasing attention, especially in the new era of big data and the Internet of Things (IoT), where data mining and data analysis technologies are effective approaches to solving wireless system issues. Artificial intelligence is one of the leading technologies in 5G, beyond 5G, and future 6G networks. Intelligence is playing a crucial role in unlocking the full potential of the 5G networks and the future 6G mobile wireless networks by leveraging universal infrastructure, open network architectures, software-defined networking, network function virtualization, multi-access edge compu-ting, vehicular networks, etc. The implementation of blockchain and mobile edge computing has become a significant part of new wireless and mobile communication networks, helping to perform computations as close to IoT devices as possible.
Synergy and Redundancy Measures
The following Special Issue covers advances in both the theoretical formulation and applications of information-theoretic measures of synergy and redundancy. An important aspect of how sources of information are distributed across a set of variables concerns whether different variables provide redundant, unique, or synergistic information when combined with other variables. Intuitively, variables share redundant information if each variable individually carries the same information carried by other variables. Information carried by a certain variable is unique if it is not carried by any other variables or their combination, and a group of variables carries synergistic information if some information arises only when they are combined. Recent advances have contributed to building an information-theoretic framework to determine the distribution and nature of information extractable from multivariate data sets. Measures of redundant, unique, or synergistic information characterize dependencies between the parts of a multivariate system and can help to understand its function and mechanisms. This Special issue provides updates on advances in the formulation and application of decompositions of the information carried by a set of variables about a target of interest. Advances in the theoretical formulation comprise the connection with channel ordering, with information compression, and the characterization of decision regions. Applications extend to, among others, structure learning, characterizing emergence in complex systems, and understanding representations in cognition.
Mathematics in Robot Control for Theoretical and Applied Problems
Robot control and navigation represent one of the most challenging topics in terms of industrial applications, as well as scientific issues. In particular, in engineering mathematics, this topic is significant and continues to attract international interest. In fact, theoretical and application aspects are strictly connected in this field. Applied mathematical aspects in engineering play a crucial role in driving future investigations and advancements. Advanced mathematical algorithms play a tremendous role in robot industrial applications and represent the basis of any progress in this area. The present reprint contains 13 articles accepted and published in the Special Issue "Mathematics in Robot Control for Theoretical and Applied Problems, 2023" of the MDPI journal Mathematics, covering a wide range of topics connected to the theory and applications in robot control. These topics include, among others, elements related to robotics, control, navigation, and machine vision. It is hoped that the reprint will be interesting and useful for those working in the area of robot control, as well as for those with the proper mathematical background who are willing to become familiar with recent advances in applications in engineering mathematics, particularly in mathematics for robot control, which has now entered almost all sectors of human life and activity.
Advances in Explainability, Agents, and Large Language Models
The Resonant Brain
This Special Issue is dedicated to Stephen Grossberg, Professor Emeritus at the Department of Biomedical Engineering of Boston University (BU), Wang Professor of Cognitive and Neural Systems, and a former Director of the Center for Adaptive Systems of BU. Grossberg is an internationally acclaimed scientist and a pioneer in fundamental principles, mechanisms, and model architectures that form the foundation of contemporary neural network research. Articles in this collection focus on the perceptual integration of sensory information, cognitive representation, and mechanisms feeding consciousness.
Current trends in ICT applications to library and office processes
Innovations and Interdisciplinary Solutions for Underserved Areas
Artificial Intelligence Adoption and It's Impact on the Sustainability
The Rise And Fall Of Minotaur In The Ages Of The Gods Beside The Seas Of Death On Mount Olympus
Industrial Engineering Strategy for Constructive Technologies
There is an urgent need to develop robust strategies to respond to and leverage new and emerging technologies, particularly those based on Artificial Intelligence. An Industrial Engineering's systems-focused approach offers the best mechanism to address this urgent global need.Industrial Engineering Strategy for Disruptive Technologies: A Systems-Based Approach for the Global Economy focuses on managing digital engineering using a systems methodology to ensure that all the parts and pieces fit together. It addresses the role of AI, is cognizant of social concerns about technological encroachment, and highlights the sustainability of operations. The book leverages resilience engineering in technology utilization and at the same time recognizes humans in the loop of technology. Also covered is using a systems basis for accepting and integrating new technologies. The global market is yearning for new guidelines and strategies for coping with the ever-increasing and changing technological landscape.This book is a necessary read for university students and instructors along with all areas of engineering as well as industry, business, government, and the military.
Sustainable Materials and Technologies in VLSI and Information Processing
Digital Product Management
This book is designed to equip readers with essential knowledge and skills in digital product management. It covers strategic planning and market opportunity, offering a clear and accessible guide to navigating the complex world of digital product management in today's fast-changing environment.Chapters explore key topics, including understanding digital transformation, identifying market dynamics, and developing a comprehensive product strategy. Readers will learn how to conduct market research, build strong business cases, and define product positioning. The book also covers practical methods for selecting pricing and packaging strategies, as well as crafting a go-to-market plan. Real-world examples, such as the growth of Grab in Southeast Asia, the rise of Zoom during the global pandemic, and Shopify's role in empowering small businesses globally, provide insight into how companies leverage strategic planning and market insights to thrive. The content reflects both current and future trends, making it relevant for global markets and today's digitally-driven economy.This book is especially useful for product managers, entrepreneurs, and business leaders who are keen to refine their strategic planning skills. It offers actionable advice and frameworks that can be applied across various industries, empowering readers to successfully manage digital products and drive business growth.
