Advances in Fractional Differential Operators and Their Applications, 2nd Edition
Evolutionary Computation, Metaheuristics, Nature-Inspired Algorithms, and Symmetry
Advances in Study of Time-Delay Systems and Their Applications, 2nd Edition
The International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025)
The International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025)
Sustainable Development of Energy, Water and Environment Systems (SDEWES 2024)
Monitoring and Modelling of Geological Disasters Based on InSAR Observations II
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
Trends in Fixed Point Theory and Fractional Calculus
This reprint, Trends in Fixed Point Theory and Fractional Calculus, brings together a carefully curated collection of contributions that highlight recent developments in two dynamic areas of modern mathematical research. Fixed point theory remains a cornerstone of nonlinear analysis, with wide applications to operator theory, variational inequalities, and functional equations. Fractional calculus, by extending differentiation and integration to non-integer orders, has emerged as a powerful framework for modeling memory effects and hereditary dynamics in complex systems.The reprint illustrates the growing synergy between these fields, showcasing advances in theoretical constructs such as contractive mappings, modular and bipolar metric spaces, enriched contractions, and set-valued mappings. At the same time, it presents practical applications to nonlinear integral equations, fractional differential systems, and stability problems relevant to physics and engineering.Contributions from international experts reflect both rigor and innovation, addressing abstract generalizations in mathematical spaces alongside real-world problem-solving. The works demonstrate the breadth and depth of current research and open avenues for further exploration across mathematics and applied sciences. This reprint will serve as a valuable reference for researchers, graduate students, and professionals seeking to engage with the latest fixed point theory and fractional calculus trends.
New Advances in Distributed Computing and Its Applications
Distributed computing frameworks offer a powerful means to train AI models and deploy AI applications at scale. This reprint aims to introduce those recent advances and practical applications in distributed computing. This reprint presents the most recent research in distributed computing, with a particular emphasis on studies that feature practical methods and experimental results. It aims to help readers quickly grasp emerging trends in the field. In particular, this reprint can assist readers in identifying effective mechanisms to address the challenges they encounter in distributed computing. Much of the content in this reprint is drawn from New Advances in Distributed Computing and Its Applications, a Special Issue of MDPI's journal Electronics. This Special Issue includes 20 papers, covering topics such as artificial intelligence model offloading in mobile networks, blockchain-based data security, throughput optimization for distributed blockchain systems, and resource scheduling in FPGA systems for edge computing. We have selected the most relevant papers and organized them into four chapters based on their themes.
Advance in Control Theory and Optimization
The present reprint compiles a total of 14 articles originally published in the Special Issue "Advance in Control Theory and Optimization" of the MDPI Mathematics journal. These contributions collectively explore the latest applications of mathematical methodologies across the interconnected domains of control theory and optimization, offering both theoretical insights and practical implementations. These topics cover camera calibration; cell voltage; multiple trains systems; digital economy; reinforcement learning; multi-population model; mean-field game; distributed cooperative algorithm; library group therapy behavior; nonlinear constraints; multi-agent systems; hyperchaotic system; continuous-time linear repetitive system; iterative learning control; event-triggered control; fixed-time; constrained multiobjective optimization; high-dimensional solution space; generative adversarial network; consensus; adaptive iterative learning control; hybrid optimization; particle swarm optimization; honey badger optimization algorithm; differential evolution; robust constrained cooperative control; optimization control. The reprint is intended for a wide range of scientific subjects, including complex modeling systems, artificial intelligence, optimization and scheduling, control system analysis, and collaborative control theory.It is hoped that the reprint will be interesting and valuable for those working in the area of control and optimization, as well as for those having the proper mathematical background and willing to become familiar with recent advances of control theory and optimization.
New Theory and Applications of Nonlinear Analysis, Fractional Calculus and Optimization
The ten articles published in this Special Issue, "New Theory and Applications of Nonlinear Analysis, Fractional Calculus and Optimization", demonstrate the profound impact and widespread applications of nonlinear analysis, fractional calculus, and optimization in applied mathematics and modern science.Overall, these papers provide inspiration for future research efforts in these exciting areas and offer novel research questions and avenues.
Machine Learning Advances and Applications on Natural Language Processing (NLP)
The impressive achievements of recent state-of-the-art machine learning models are revolutionizing the area of text and language applications. On the one hand, popular large language models (LLMs) have demonstrated an enormous capability in automatic and reasonable text generation. On the other hand, Transformer-based models have drastically improved the performance of other, highly important natural language tools, including traditional sentiment analyzers, machine (auto)translators, and multimedia annotators. Furthermore, such natural language processing (NLP) techniques are heavily utilized in social networks, microblogs, eCommerce systems, and numerous other disciplines.This Reprint contains 10 high-quality, peer-reviewed original research papers in the field of natural language processing. These articles have been selected with the aim of providing the research community with insights that will open up new directions in this discipline. The authors of these papers have introduced new models, methods, and techniques related to large language models, sentiment analysis applications, effective text representations, text classification and text clustering.
Knowledge Information Extraction Research
This Reprint presents recent advances in the rapidly evolving field of Knowledge and Information Extraction Research, with a particular emphasis on methods that transform heterogeneous and unstructured data into structured, actionable knowledge. It brings together diverse contributions exploring methodological innovations across natural language processing, machine learning, data mining, information retrieval, and knowledge graph construction. By integrating these perspectives, the Reprint demonstrates how technical progress in algorithm design and system development is reshaping the landscape of intelligent information management.The Reprint highlights the growing importance of precision, scalability, and interpretability in modern extraction techniques. Selected articles address challenges such as extracting semantics from complex texts, modeling relationships within large-scale knowledge graphs, and applying deep learning approaches to enhance efficiency and reliability. Interdisciplinary collaboration emerges as a recurring theme, underscoring how computational methods can be successfully combined with domain-specific expertise to tackle real-world problems. Contributions illustrate how advanced knowledge extraction techniques can drive innovation in healthcare, finance, e-commerce, cybersecurity, and other data-intensive sectors. By bridging theoretical development with implementation in practice, the Reprint demonstrates its role not only as a record of scholarly progress but also as a resource for practitioners seeking solutions to pressing information challenges.
Architecture-Based 5G Security Simulation
The fifth-generation technology standard for mobile networks (5G) introduced a massive increase in capability due to the increased use of Internet of Things devices. However, implementing additional untrusted technology, such as IoT devices, exposes the infrastructure to unsecure hardware and software. As a result, the attack surface of the 5G mobile network has increased after transitioning from LTE to the 5G standard. Three research questions and hypotheses were composed to evaluate the architectural design of the network for the healthcare use case. The Perimeter Security, Zero Trust
A Guide to Desktop Linux in 2025
Perhaps you've heard of Linux before. Maybe you know it as that operating system for computer wizards with the cute penguin mascot. While that characterisation isn't completely *wrong*, Linux is not just for the computer wizards. So many more people, of all stripes, use it on their desktops than you might imagine.If you're wondering if you'll fit in among this crowd, don't worry! Linux is for everyone. Whether you're an accountant or a visual novel fanatic, you can keep doing what you love on your computer with Linux.Whether you're worried Windows no longer has your best interests at heart, or you're just plain curious, this guide will help you get up and running while avoiding all of the usual potholes and footguns along the way.If you tried Linux a long time ago, you'll be glad to know all aspects of the desktop have only gotten better over time. You might not even recognise it!It's not 1998 anymore. It's been over 30 years since Linux was first released, and the Linux Desktop has undergone seismic shifts in usability and capability over the years. This book is designed for the modern age and helps you take advantage of all the latest technology available for desktop Linux. Even if you've used Linux before, things have changed *a lot* in just the last few years.That's not to say the Linux Desktop isn't as quirky as it has ever been, but the jankiness has been sanded off in many areas. There's plenty you can do on Linux, and yet it would be a lie to say there isn't a cost to that freedom most of your penguin friends aren't forthcoming about. This guide acknowledges the limitations of the Linux world and doesn't try to hide them from you.In this book, you'll find chapters about: getting your new Linux distribution setup on your computerproviding step-by-step guidance for installation, software compatibility, gaming, and productivityexploring the history of desktop Linuxthe bright yet uncertain future of LinuxBuy this book now and dip your toes into the weird and wonderful world of Desktop Linux. Just don't blame me when your house starts filling up with penguin plushies and red hats.
The first conscience curriculum for AI in human history
This curriculum is built for educators, team leads, and builders who want results without the hype. Each module translates core AI concepts into plain English, then moves straight into action: mapping real problems, designing human-in-the-loop workflows, and shipping small projects that compound. Checklists and rubrics strengthen judgment-when to automate, when to slow down, how to verify outputs, and how to protect people's data and dignity. Topics include: foundations of modern AI; prompt craft across text/image/audio; data literacy and evaluation; red-teaming and risk mitigation; policy, governance, and public accountability. By the end, learners share a common language, a set of repeatable practices, and publishable artifacts. The aim isn't novelty; it's good work, done well-AI adoption that serves people.Audience & use cases Educators, institutes, nonprofits, founders, public-sector teams; semester course, bootcamp, staff training, community program.
The first global casebook of AI harms
The First Global Casebook of AI Harms: 100 Sectors, 10,000 Subdomains of a Machine-Ruled World - One Human ConscienceArtificial intelligence has already entered every sector of human life - from health and justice to education, labor, governance, culture, and war. But the world has no common canon for remembering its failures. This book changes that.The First Global Casebook of AI Harms is the first comprehensive map of how intelligent machines are damaging human life across 100 sectors and 10,000 subsectors worldwide. Structured in the tradition of law school casebooks but elevated into a global moral canon, it documents harms not as isolated "glitches" but as systemic failures: misdiagnosed patients, students erased by exam bots, workers fired by algorithms, refugees denied entry by automated risk scores.Each case follows a locked teaching model: Introductory warning - prophetic insight into what happens when AI is built without values.Narrative case study - 700+ words of lived harm from across continents.Explainer box - plain-language guide for public and student understanding.Core value violated - grounded in the Universal Ruhangariyo Reflection Protocol (URRP).Conscience code reflection - moral and practical remedies.Exercises - reflection, debate, and policy scenarios for classrooms and communities.Just as Health Law: Cases, Materials, and Problems became the definitive canon for medicine and law, this Casebook is designed to become the reference text for humanity's encounter with AI. Its coordinates system (Sector-Family-Subsector-Case) functions like a Dewey Decimal for AI harms, ensuring every harm has an address and no injustice can be orphaned or forgotten.Across various sectors of human life - Health, Justice, Education, Labor & Economy, Governance & Politics, Social & Cultural Life, Environment & Resources, Global Inequalities, Technology & Infrastructure, and The Future of Humanity - the Casebook captures harms already unfolding: What emerges is a canon equal to the crisis: 40,000 cases mapped, structured, and preserved with evidence, methodology, and moral fire. Every sector is tied back to six continents' wisdom traditions - Ubuntu from Africa, Ahimsa from Asia, Kinship from the Americas, Manaakitanga from Oceania, Memory from Europe, Resistance from the Global South - to ensure this canon speaks with a truly global conscience.This Casebook is more than testimony. It is a thunderbolt. It warns that the greatest danger of AI is not its power, but its lack of conscience. By cataloguing harms with rigor and moral clarity, it equips professors, policymakers, activists, and citizens with the memory and tools to resist the orphaning of humanity.If the twentieth century required constitutions and health law, the twenty-first requires a canon of conscience. The First Global Casebook of AI Harms is that canon - a reference text for classrooms, governments, and movements worldwide.
The first global casebook of AI harms
The First Global Casebook of AI Harms: 100 Sectors, 10,000 Subdomains of a Machine-Ruled World - One Human ConscienceArtificial intelligence has already entered every sector of human life - from health and justice to education, labor, governance, culture, and war. But the world has no common canon for remembering its failures. This book changes that.The First Global Casebook of AI Harms is the first comprehensive map of how intelligent machines are damaging human life across 100 sectors and 10,000 subsectors worldwide. Structured in the tradition of law school casebooks but elevated into a global moral canon, it documents harms not as isolated "glitches" but as systemic failures: misdiagnosed patients, students erased by exam bots, workers fired by algorithms, refugees denied entry by automated risk scores.Each case follows a locked teaching model: Introductory warning - prophetic insight into what happens when AI is built without values.Narrative case study - 700+ words of lived harm from across continents.Explainer box - plain-language guide for public and student understanding.Core value violated - grounded in the Universal Ruhangariyo Reflection Protocol (URRP).Conscience code reflection - moral and practical remedies.Exercises - reflection, debate, and policy scenarios for classrooms and communities.Just as Health Law: Cases, Materials, and Problems became the definitive canon for medicine and law, this Casebook is designed to become the reference text for humanity's encounter with AI. Its coordinates system (Sector-Family-Subsector-Case) functions like a Dewey Decimal for AI harms, ensuring every harm has an address and no injustice can be orphaned or forgotten.Across various sectors of human life - Health, Justice, Education, Labor & Economy, Governance & Politics, Social & Cultural Life, Environment & Resources, Global Inequalities, Technology & Infrastructure, and The Future of Humanity - the Casebook captures harms already unfolding: What emerges is a canon equal to the crisis: 40,000 cases mapped, structured, and preserved with evidence, methodology, and moral fire. Every sector is tied back to six continents' wisdom traditions - Ubuntu from Africa, Ahimsa from Asia, Kinship from the Americas, Manaakitanga from Oceania, Memory from Europe, Resistance from the Global South - to ensure this canon speaks with a truly global conscience.This Casebook is more than testimony. It is a thunderbolt. It warns that the greatest danger of AI is not its power, but its lack of conscience. By cataloguing harms with rigor and moral clarity, it equips professors, policymakers, activists, and citizens with the memory and tools to resist the orphaning of humanity.If the twentieth century required constitutions and health law, the twenty-first requires a canon of conscience. The First Global Casebook of AI Harms is that canon - a reference text for classrooms, governments, and movements worldwide.
Measurement-Driven Simulation of Complex Engineering Systems
The Dutch polder model recently dubbed a 'success story' by Bill Clinton and Jacques Delors - plays a prominent role in current discussions about possibilities for a new 'capitalism with a social face', and appeals to experts all over the world. Just ten years ago the Swedish sociologist G繹ran Therborn described the Dutch employment policy as a 'spectacular failure'. The authors single out three policy changes to explain the 'miracle' that has taken place since then. The 'Dutch miracle' shows that it is difficult but not impossible to overcome the drawbacks of the welfare state and that in this age of globalization and integration, it remains necessary to coordinate policy on a national level as well. In the last section the authors investigate the dynamics of social-economic policy which will have to be developed under increasingly stringent international conditions
Enhanced Publications
The traditional publication will be overhauled by the 'Enhanced Publication'. This is a publication that is enhanced with research data, extra materials, post publication data, and database records. It has anobject-based structure with explicit links between the objects. In this book a state-of-the-art overview is given of the structural elements of an Enhanced Publication, as well as publication models, interrelationship andrepository issues. The use of Enhanced Publications evokes questions on object models and functionalities. An in-depth study is made of these subjects. More practically, a sample is given of datasets together witha demonstrator-project. In the final section, this book deals with long-term preservation issues, linking to thedevelopments of digital repositories that are studied in other books in this series.
Emerging Standards for Enhanced Publications and Repository Technology
Emerging Standards for Enhanced Publications and Repository Technology serves as a technology watch on the rapidly evolving world of digital publication. It provides an up-to-date overview of technical issues, underlying the development of universally accessible publications, their elemental components and linked information. More specifically it deals with questions as how to bring together the communities of the Current Research Information Systems (CRIS) and the Common European Research Information Format (CERIF). Case studies like EGEE, DILIGENT and DRIVER are analyzed, as well as implementations in projects in Ireland, Denmark and The Netherlands. Interoperability is the keyword in this context and this book introduces to new standards and concepts used in the design of envelopes and packages, overlays and feeds, embedding, publishing formats and Web services and service-oriented architecture. It is a must-read for quick and comprehensive orientation.
AI for Smart Students
AI for Smart Students is a practical, hands-on guide that teaches students how to use Artificial Intelligence to study smarter, build meaningful projects, and grow personally and professionally. Written in clear, simple language, the book translates complex concepts into real-world tools and step-by-step examples so beginners-and B.Tech students in particular-can start applying AI right away.Inside you'll find concise explanations of core AI ideas plus dozens of ready-to-use tutorials: study planners and productivity hacks, AI writing and coding assistants, note-taking and summarization tools, no-code app builders, IoT/robotics project recipes, API how-tos, and presentation templates. Each chapter mixes short theory with hands-on exercises, real student case studies, mini-project blueprints, and practical tips for hackathons, portfolios, and job preparation.Whether you want to save study time, win a hackathon, build a portfolio that gets noticed, or use AI to improve wellbeing and creativity, this book gives you the tools and the confidence to do it. Straightforward, action-oriented, and packed with examples, AI for Smart Students turns curious learners into creators. Start small - build something big.
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!
