Advancements in Applied Mathematics and Computational Physics
Research on Fuzzy Logic and Mathematics with Applications II
Recent Progress and Challenges of Artificial Intelligence in Bioinformatics and New Medicine
New Theory and Applications of Nonlinear Analysis, Fractional Calculus and Optimization
Machine Learning Advances and Applications on Natural Language Processing (NLP)
Measurement-Driven Simulation of Complex Engineering Systems
The steadily increasing amount of traffic in the vicinity of their economical centers imposes great difficulties for most western countries. To reduce this steady increase, road pricing has proven to be an effective countermeasure. It has been introduced in different countries throughout the world, forcing people to consider alternative means of traveling. Since, for such measures to be effective, human behavior and social structures are deeply influenced, emotional political discussions have arisen. Considering the importance of such social changes as well as the complexity of techniques involved in a project like "Rekening Rijden", the academic community, having public responsibility, should respond when asked for advice. So, the advice given was to initiate an evaluation study that would include modeling & simulation as well as extensive validation. Cooperating closely with our university, the Dutch government performed a study including all these components, resulting in a thorough overview of the reliability of the techniques, needed to build a system like "Rekening Rijden". The university remained involved in the project until the end, developing the models & methods necessary to carry out the study. If in the future road pricing systems will be introduced, the results & analyses from this research, as well as the models & methods developed, will still be of full importance.
Emerging Standards for Enhanced Publications and Repository Technology
Opbert-Segcn
This book introduces a novel approach that revolutionizes the way sentiment knowledge is integrated and transferred within ABSA models. It proposes a pioneering method that employs sentiment links within a dependency graph, acting as conduits for the efficient transfer of sentiment knowledge from sentiment and opinion nodes to aspect nodes. This innovative mechanism significantly enhances the model's ability to capture sentiment information, leading to more accurate sentiment predictions. Furthermore, ""OPBERT-SEGCN"" introduces the Opinion-Infused BERT (OPBERT) model, which generates text representations that boost the identification of opinion words. This integration of deep learning and sentiment analysis provides a powerful tool for understanding the nuances of public opinion and policy analysis, hospitality and tourism, and financial services. Rich with experimental evidence from five publicly available datasets, the book demonstrates the superior performance of the proposed mechanisms over existing models. It is an essential read for researchers, data scientists, and practitioners in the field of natural language processing and sentiment analysis, offering insights into the future of understanding and reacting to human opinions and reactions at a granular level.
Advancements in Natural Language Processing, Semantic Networks, and Sentiment Analysis
This Special Issue examines the intersection of NLP, semantic networks, and sentiment analysis, exploring how these technologies can contribute to more intelligent systems. The contributions gathered address, among other topics, the detection of irony and sarcasm, the generation of semantic explanations, the automatic construction of semantic graphs, the expansion of linguistic resources for underrepresented languages, and the use of large language models. Ultimately, this Special Issue aims not only to reflect the state of the art in the areas above but also to stimulate critical reflection on the methodological challenges, ethical implications, and interdisciplinary opportunities that arise at the intersection of computational linguistics and artificial intelligence.
Virtual Reality and Metaverse
Virtual reality, augmented reality, and the metaverse are no longer futuristic concepts-they are reshaping how society works, learns, and interacts.This Reprint compiles peer-reviewed studies exploring how diverse sectors such as healthcare, education, industry, and tourism are adapting to these immersive technologies. It offers a concise yet comprehensive view of the opportunities, challenges, and ethical considerations surrounding the digital transformation of society.This Reprint constitutes a significant resource for researchers, professionals, and curious minds interested in the future of human-technology interaction.
Architecting Intelligent Data Systems
""Architecting Intelligent Data Systems: From Big Data Infrastructure to Advanced Analytics and AI"" by Chandrakanth Lekkala is a definitive guide to modern data system architecture. With 28 meticulously crafted chapters organized into six major parts, this groundbreaking work bridges foundational concepts and cutting-edge advancements in data technologies, from distributed infrastructures to sophisticated AI implementations. Lekkala explores the evolution of data systems, offering deep insights into scalable data pipelines, machine learning, advanced analytics, and emerging trends like quantum computing and privacy-preserving AI. Practical examples, architectural patterns, and real-world use cases span industries such as finance, healthcare, and smart cities, making this book an indispensable resource for data professionals. A hallmark of this text is its focus on ethical AI, data governance, and responsible innovation, ensuring that readers are equipped to navigate the complex challenges of modern data systems with integrity and foresight. Whether you're a data architect, engineer, or researcher, ""Architecting Intelligent Data Systems"" provides the tools and insights needed to design scalable, secure, and ethical data solutions. Chandrakanth Lekkala's expertise and vision make this a must-read for anyone shaping the future of data-driven technology.
IoT Implemented Indoor Air Quality and Health Monitoring System Using IoT
Environmental and air pollution present significant health risks to humans, often leading to previously unrecognized health complications. One critical factor is that the impact of indoor air quality on respiratory and overall physical health can be more pronounced than outdoor air quality. While research has explored the connection between health and the environment, there is an increasing focus on analyzing public and large-scale synergistic data. However, many of these studies lack real-time data analysis. This book focuses on developing an environmental detection sensor system that utilizes devices to monitor air quality for indoor and outdoor applications. In addition, this book focuses on developing an environmental detection sensor system that utilizes devices to monitor air quality for indoor and outdoor applications. Furthermore, this investigation highlights the importance of real-time verification, collection, and analysis of health and environmental data from various sources to implement effective health monitoring systems. Techniques such as fuzzy logic, artificial intelligence, machine learning, and deep learning have proven valuable in accurately predicting health outcomes and identifying hazardous situations. Additionally, this work explores strategies for preventing respiratory and related diseases, emphasizing minimizing health risks.
Overcoming Barriers to Digital Transformation
In the definition of the term IT infrastructure, one of the important characteristics is that it focuses on people, in particular on the fact that they are key part of the information system. Most of the existing technology management literature is limited to the manufacturing sector. The books on technology management are generally very applied and narrow in focus, emphasizing the research and development process, and the engineering process. This work is to fill the void by presenting an integrative, strategic, and innovative approach to digitalizing a production system for today and for the next twenty years.
Mastering Machine Learning
Mastering Machine Learning: How to Build Smarter AI Systems with Real-World Applications is your essential guide to understanding and applying machine learning in real-world scenarios. From self-driving cars and personalized recommendations to fraud detection and medical diagnoses, machine learning is revolutionizing industries. Yet, for many, it remains an enigma. This book breaks down complex ML concepts into an accessible, structured, and hands-on learning experience. Whether you're a beginner, an aspiring data scientist, or an industry professional, you'll gain the knowledge and skills needed to master ML-from foundational principles to cutting-edge techniques like deep learning and reinforcement learning. With practical case studies, Python coding exercises, and expert insights, this book empowers you to build, train, and deploy ML models with confidence. Get ready to unlock the secrets of intelligent systems and shape the future with machine learning!
The AI Revolution
Artificial Intelligence is reshaping our world. However, for many individuals, it appears to be complicated and out of reach-an overwhelming world of algorithms and data. Sunny Okonkwo, a renowned data scientist, AI consultant, Energy expert and storyteller, is here to change that. In The AI Alchemist, Sunny guides readers on a life-changing exploration to illuminate AI and demonstrate its capacity to produce tangible solutions. Through real-world case studies and engaging examples, this book covers: How AI is revolutionizing industries like finance, healthcare, energy, and business The process of transforming complex data into actionable insights The ethical challenges of AI and the responsibility of innovators The future of AI innovations and how they can shape tomorrow's world. Whether you are a technology enthusiast, a business executive, or someone inquisitive about AI's possibilities, this book will inspire you to view AI as a means for clarity, simplicity, and progress.
Recognizing Arabic Digits Techniques and Applications
In an increasingly digitized world, the ability to accurately recognize Arabic digits is essential across various applications, from banking to education. This book provides a thorough exploration of the methodologies and technologies behind Arabic digit recognition. It covers the fundamental concepts, advanced techniques, and practical implementations, making it an invaluable resource for researchers, developers, and students alike. Inside, you will discover: A detailed overview of digit recognition systems Insights into machine learning and deep learning approaches Case studies showcasing real-world applications Best practices for developing robust recognition algorithms Challenges and future directions in the field Whether you are an experienced engineer or a novice eager to learn, this book will equip you with the knowledge and tools to excel in Arabic digit recognition.
CompTIA Tech+(TM) Certification All-in-One Exam Guide, Third Edition (Exam FC0-U71)
This up-to-date exam guide delivers complete coverage of every topic on the FC0-U71 version of the CompTIA Tech+ Certification examTake the CompTIA Tech+ exam with complete confidence using this effective self-study system. Part of the bestselling series created and edited by Mike Meyers, the leading expert on CompTIA certification and training, and written by a CompTIA certification and training expert, this authoritative guide explains foundational computer technologies in full detail. You'll find learning objectives at the beginning of each chapter, exam tips, exam objective review sections, practice exam questions, and in-depth explanations throughout. Designed to help you pass the CompTIA Tech+ exam with ease, this definitive guide also serves as an essential on-the-job reference. Covers all exam topics, including: IT concepts and terminologySystem hardware and peripheralsData storage and sharingOperating system types and purposesSelecting, installing, and using applicationsMobile device connectivity, security, and configurationNetwork concepts and internet connectivitySecuring hardware, software, data, and networksBest practices for preventing security breachesCustomizing and configuring web browsersTroubleshooting common computer problemsRelational and non-relational databasesSoftware development concepts and structuresOnline content includes: 180+ practice exam questions in a customizable test engineOne hour of video training from Mike MeyersMike Meyers' favorite shareware and freeware networking tools and utilities
Recent Advances in Chaos, Fractal and Complex Dynamics in Nonlinear Systems
This reprint collates all of the articles published in the Special Issue of Mathematics titled "Recent Advances in Chaos, Fractal and Complex Dynamics in Nonlinear Systems". This Special Issue was devoted to showcasing the latest theoretical advances and practical developments in the field of nonlinear dynamics, with a particular focus on chaotic behavior, bifurcation phenomena, fractal structures, and the emerging dynamics in fractional-order, discrete, and discontinuous systems.The collected works reflect the rapid progress that has been achieved in understanding the interplay among nonlinear systems, chaos, bifurcation, and fractals. The topics include new methods for detecting chaos, novel types of attractors (including hidden attractors), fractal features in fractional-order systems, and the applications of chaotic and fractal dynamics in areas such as secure communication and optimization algorithms.We hope that this reprint will serve as a valuable reference for researchers and practitioners engaged in the study of nonlinear systems, and in particular, those exploring chaos theory, bifurcation analysis, fractal geometry, and the complex behavior of emerging dynamical models.
Theory and Applications of Fuzzy Systems and Neural Networks
Data-Driven Intelligent Modeling and Optimization Algorithms for Industrial Processes
The aim of this Special Issue is to explore the multifaceted aspects of data-driven intelligent modeling and optimization algorithms for industrial processes. The main goals are to harness the power of data to improve control, decision making, and parameter optimization, and to drive industrial systems to unprecedented levels of efficiency, reliability, and adaptability. Research areas in this Special Issue include digital twin technology, multimodal data recognition, sensor data ingestion and real-time processing, multi-objective path-planning, conditional generative adversarial network, generating job recommendations, comprehensive risk assessment, large language models, self-supervised key-point learning, trustworthy article ranking, engine optimization model, and bioinspired generative design. These powerful and intelligent algorithms use data for control, decision making, and parameter optimization, driving industrial systems to unprecedented levels of efficiency, reliability, and adaptability. By sharing their practice and insights in the development and application of these new technologies, the authors of the articles in this reprint have demonstrated the value of data-driven intelligent modeling and optimization algorithms for industrial processes, providing readers with valuable ideological inspiration in the field.
Computable Structure Theory
This is the first book which gives a unified theory for countable and uncountable computable structures. The work treats computable linear orderings, graphs, groups and Boolean algebras unified with computable metric and Banach spaces, profinite groups, and the like. Further, it provides the first account of these that exploits effective versions of dualities, such as Stone and Pontryagin dualities. The themes are effective classification and enumeration. Topics and features: - - - - - This unique volume is aimed at graduate students and researchers in computability theory, as well as mathematicians seeking to understand the algorithmic content of structure theory. Being self-contained, it provides ample opportunity for self-study.
Systems, Software and Services Process Improvement
The two-volume set CCIS 2657 + 2658 constitutes the refereed proceedings of the 32nd European Conference on Systems, Software and Services Process Improvement, EuroSPI 2025, held in Riga, Latvia, during September 17-19, 2025. The 42 papers included in these proceedings were carefully reviewed and selected from 72 submissions. They were organized in topical sections as follows: Part I: SPI and Emerging and Multidisciplinary Approaches to Software Engineering; SPI and Standards and Safety and Security Norms; SPI and Functional Safety and Cybersecurity. Part II: Sustainability and Life Cycle Challenges; SPI and Recent Innovations; Digitalisation of Industry, Infrastructure and E-Mobility; SPI and Agile.
IMU, ICM, Medals, Prizes, and Laureates
The book begins with the formal establishment of the International Mathematical Union (IMU) and its purpose of promoting international cooperation in mathematics by supporting and assisting the international Congress of Mathematicians (ICM) every four years. The book presents the most important features of each ICM (from 1897 to 2022) including the history of various medals and awards, particularly the Fields Medal, which is regarded as one of the highest honors a mathematician can receive and has been described as the Nobel Prize of mathematics. For each Laureate, the book provides their family background, a short description of the work that led to the award, a history of academic jobs, research conducted after receiving the award, and a list of further honors and awards. This book will stimulate all mathematicians, especially students who think that mathematics is less rewarding compared to other disciplines.
