Sleeper Code
Beneath the calm hum of America's power grids, a new kind of weapon is awakening.When a self-learning piece of code-Phantom-is planted deep inside the nation's critical infrastructure, it lies dormant, invisible, and patient. Until the day it is called to life.Max Shaw, a brilliant but battle-worn cybersecurity leader at the National Infrastructure Protection Agency, has spent years defending systems most people never see. But when the grid flickers and a single word appears across his screen-PHANTOM: AWAKE-he and his team realize the enemy is already inside.Together with Tara Lin, an MIT-trained code-breaker haunted by her brother's stolen identity, and Sam Rourke, a field-forged deputy who walks with a limp and the weight of past wars, Max races to trace the infection before it cascades through every network that keeps the nation alive.From Washington's hidden command bunkers to data farms buried in the Kansas plains, Sleeper Code delivers a pulse-pounding journey through the invisible battlefield of the twenty-first century-where power, water, and trust itself can vanish with a single keystroke.Can Max and his team stop a weapon that learns faster than they can think-or has the countdown already begun?Gripping, authentic, and terrifyingly plausible, Sleeper Code blends cutting-edge cyber warfare with human courage, exploring how far we'll go to protect the systems-and the people-we love.
Computer Vision and Pattern Recognition with Applications
The present book contains 18 total articles accepted and published in the Special Issue "Computer Vision and Pattern Recognition with Applications, 2022" of MDPI's Mathematics journal, which covers a wide range of topics connected to the theory and applications of computer vision and pattern recognition and their extensions/generalizations. These topics include, among others, image classification; object detection; vehicle trajectory prediction; image segmentation; image enhancement; medical image processing; multi-modal action recognition; text detection; video-text retrieval; dense non-rigid structure from motion; image-based crowd counting, etc.It is hoped that the book will be interesting and useful for those working in the area of computer vision, pattern recognition, and their applications, as well as for those with the proper mathematical background who are willing to become familiar with recent advances in computer vision and pattern recognition. Computer vision and pattern recognition have entered almost all sectors of human life and activity currently.
Algorithms for Feature Selection (2nd Edition)
This Special Issue brings together cutting-edge research on algorithms, with a particular emphasis on feature selection techniques. Covering a broad range of topics-including evolutionary and ensemble methods, deep learning, high-dimensional data, time-series analysis, and textual applications-it addresses both theoretical advancements and real-world implementations. After undergoing a rigorous peer review process, ten high-quality papers were accepted for publication within this Special Issue. The research highlights include novel models for categorical feature independence, affordable housing analysis via scenario modeling, AI-driven educational engagement strategies, video content synchronization detection, fatigue detection in drivers using multimodal sensors, and advanced feature selection techniques for bioinformatics and cancer genomics. Further contributions demonstrate applications in author identification, time-series human motion analysis, and scheduling optimization through genetic programming. This Special Issue serves as a valuable reference for researchers aiming to explore the evolving landscape of feature selection in diverse, data-intensive domains.
Advances in Fractional Differential Operators and Their Applications, 2nd Edition
This reprint gathers recent advances in fractional differential equations and nonlocal modeling across discrete and continuous settings, united by a common theme: memory and long-range effects as first-class citizens in analysis, computation, and applications. The works here develop new objects (from fractional sequences to nonlocal Schr繹dinger dynamics), prove well-posedness under weak assumptions, and design numerics capable of honoring history dependence.
Agentic AI - A Primer
What happens when artificial intelligence stops being a tool and starts becoming an autonomous partner? Agentic AI is poised to reshape industries, research, and society itself by combining decision-making autonomy, goal-directed learning, and self-reflection. This groundbreaking book offers the first comprehensive guide to the foundations, architectures, and future trajectories of agentic AI systems. From the philosophical roots of agency and autonomy to the technical building blocks of planning, reasoning, memory, and perception, the book bridges theory and practice with clarity and depth. You'll explore classical AI paradigms alongside cutting-edge approaches like LLM-based agents, hybrid cognitive architectures, and multi-agent systems-while also examining their implications for safety, ethics, and human-AI collaboration. Structured in five parts, the journey begins with conceptual foundations, builds through technical architectures, explores real-world applications, and culminates in forward-looking insights into the role of agentic AI in Artificial General Intelligence (AGI) and beyond. Along the way, vivid diagrams, practical examples, and domain-specific use cases make complex concepts accessible without sacrificing rigor. For AI researchers, engineers, business leaders, and policy makers alike, Agentic AI offers not only a roadmap for building intelligent autonomous systems but also a critical lens for evaluating their societal impact. Whether your goal is to design the next generation of adaptive agents, harness AI for transformative applications, or understand the challenges of aligning machine agency with human values, this book provides the foundation you need to navigate and shape the intelligent future.
Evolutionary Computation, Metaheuristics, Nature-Inspired Algorithms, and Symmetry
Computational intelligence is an important branch of artificial intelligence. Nowadays, evolutionary computation as a part of computational intelligence is widely used to solve various numerical problems and real-world engineering problems. Its application and development bring a great contribution to the optimization domain. Thus, it is of great interest to investigate the role and significance of evolutionary computation, metaheuristics, and nature-inspired algorithms in optimizing distinctive problems.This Reprint aims to bring together both experts and newcomers from either academia or industry to discuss new and existing issues concerning evolutionary computation and optimization. The research topics include cloud-edge-end collaborative task offloading, time-series analysis of brent oil price, high-efficiency and ultrawideband polarization conversion metasurface, many-objective optimization, imperative programs, maize water and fertilizer irrigation simulation, multi-objective vehicle routing problems with time windows, and short-term electrical load forecasting. Various optimization algorithms such as particle swarm optimization, genetic programming, and non-dominated sorting genetic algorithm are successfully applied to these topics and show superior performance. These algorithms not only greatly promote the development of evolutionary computation and community, but also effectively address some existing limitation of optimization problems.
Advances in Study of Time-Delay Systems and Their Applications, 2nd Edition
The delay phenomenon is a common feature of industrial, communication, economic, biological, and similar systems and processes, and it significantly affects their stability and dynamics. It can markedly deteriorate the quality of control performance in feedback loops. Studying the influence of delays on system stability, dynamics, and control performance poses a challenging mathematical problem. System and control theories have addressed this issue for nearly a century, dating back to a century ago. Modern control theory faces growing demands for enhanced quality and performance in both industrial applications and everyday life-demands that are difficult to meet using conventional methods. Achieving these goals requires a deeper understanding of controlled systems with delays. Despite significant advances in artificial intelligence techniques and strategies in recent years, distinguished scholars continue to propose innovative solutions to longstanding challenges and identify new open problems stemming from an increasingly profound understanding of this domain.This Special Issue focuses on recent developments in the analysis and control design of time-delay systems. The goal was to attract quality and novel papers in the field of "Time-Delay Systems and Their Applications". It is anticipated that these top-tier research papers will have a considerable impact on the international scientific community and will inspire further advancements in the field.
The International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025)
The fourth edition of the International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025) was held in a hybrid format in Alexandroupolis, Greece from 18 to 20 June, 2025. The EEPES Conference is the premier international gathering, organized by the Association CIEES with financial support from EEPES Ltd., both from Bulgaria, focusing on understanding the current state and evolution of science through the lens of engineering physics, electronic devices and microelectronics, telecommunications, optical and electromagnetic communication, artificial intelligence and soft computing, environmental physics and renewable energy, and many other disciplines. It is a place where researchers, academics, industry representatives, students, and others can present and discuss their progress in research, development, standards, and applications related to applied and engineering physics.
Evolutionary Multi-Criteria Optimization
This Reprint compiles all articles accepted and published in the Special Issue of Mathematics entitled "Evolutionary Multi-Criteria Optimization: Methods and Applications". This Special Issue seeks to bring together both experts and newcomers to explore emerging and existing issues in these domains, with a particular focus on advancing the integration and synthesis of ideas between EMO and MCDM researchers. By fostering such collaboration, this collection seeks to enhance engagement with the user community and promote practical applications of these methodologies. We hope that the papers featured in this Special Issue will be of interest to our readers.
The International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025)
The fourth edition of the International Conference on Electronics, Engineering Physics and Earth Science (EEPES 2025) was held in a hybrid format in Alexandroupolis, Greece from 18 to 20 June, 2025. The EEPES Conference is the premier international gathering, organized by the Association CIEES with financial support from EEPES Ltd., both from Bulgaria, focusing on understanding the current state and evolution of science through the lens of engineering physics, electronic devices and microelectronics, telecommunications, optical and electromagnetic communication, artificial intelligence and soft computing, environmental physics and renewable energy, and many other disciplines. It is a place where researchers, academics, industry representatives, students, and others can present and discuss their progress in research, development, standards, and applications related to applied and engineering physics.
Sustainable Development of Energy, Water and Environment Systems (SDEWES 2024)
Sustainable development requires a holistic approach that promotes interdependency between humans and nature. As global demands for energy, water, transport, housing and food systems rise, so does the challenge of embedding these needs within a framework that balances long-term ecological and human well-being. Technical innovation will be important for achieving this. The political economy aspects of sustainable development also need to be considered along with the roles of political leaders and voters, energy democracy, and community and citizen participation in the energy transition. At its core, sustainability is a systems concept, concerned not only with resource efficiency and environmental stewardship but also with the interdependencies between human well-being, economic performance, technological progress, and governance. Finally, the importance of digital technologies, particularly through the recent emergence of generative artificial intelligence (AI), presents a potential enabler of sustainability. They can enhance decision-making, optimize resource use, and enable new forms of education and governance. However, this is counter-balanced by important ethical and governance questions, particularly around data privacy, security and equity. These tensions underscore the need for robust governance frameworks and inclusive dialogue in guiding 'digital innovation' towards sustainable development goals. Consequently, the intersection of AI and sustainability is poised to become a vital area of research and inquiry, shaping both policy and practice in the years to come.
Monitoring and Modelling of Geological Disasters Based on InSAR Observations II
Interferometric synthetic aperture radar (InSAR) has demonstrated its potential in monitoring geological disasters, e.g., those related to subsidence, landslides, earthquakes, and volcanoes. Such monitoring results provide significant information for further physical modeling, driving mechanism interpretation, developments in early warning technology, and the management and formulation of policies by authorities and stakeholders. This reprint focuses on the monitoring and modeling of geological disasters using InSAR observations, with content covering topics such as PS/DS processing, deformation parameter inversion, motoring deformation (e.g., earthquakes, volcanoes, and oil extraction), and driving mechanism interpretation. These excellent reports significantly contribute to further developing the monitoring and modeling of geological disasters using InSAR techniques.
IoT Security
Internet of Things technologies, which connect various devices and sensors together, are increasingly at the basis of modern communication, enabling the autonomous exchange of data between billions of physical and virtual objects, creating smart environments in sectors such as healthcare, logistics, etc.However, the advancement of IoT communication also brings new security challenges. Managing the security of the IoT raises major concerns, especially when devices are deeply integrated into critical infrastructure, hospitals, and vehicles. Furthermore, the IoT is a key component of 5G/6G architecture and Industry 4.0. All these technologies are designed to support critical applications.The increased number of related potential attack vectors poses a substantial risk for malicious attackers. Also, the focus of security has been put on large-scale, software-oriented systems, such as the Cloud or datacenter systems, rather than embedded electronics. Consequently, the establishment of IoT ecosystems across different domains remains highly vulnerable to a wide range of threats.This Special Issue gathers high-quality original research contributions and the latest research results in the field of threat detection within the IoT. It also covers threat analysis and corresponding defense techniques. The threats are related to privacy issues, trust issues, IoT management issues, IoT intrusion, vulnerability issues, malware detection, cryptographic key management, reliability of IoT communication (including secure routing aspects), IoT forensics techniques, Cloud-related IoT issues, etc.
Advancements in Applied Mathematics and Computational Physics
Mathematics and physics are basic natural sciences. They are the root of almost all processes in nature and technology. There are a large number of situations where these two sciences can offer the best models and most appropriate explanations for natural processes or technological problems.This Special Issue Reprint presents various methods and new solutions to explain the nature of matter, biophysical systems, and systems in technical sciences in the frame of overall reality, using the latest achievements in applied mathematics and computational physics. The focus is on new results and solutions in contemporary applied mathematics, algebra, mathematical logic, graph theory, fractals, chaos theory, numerical mathematics, mathematical physics, as well as the latest results in experimental physics, computational physics, and physical electronics for problems in nature, technology, technics, and electronics.This Special Issue Reprint covers a broad range of topics to provide new insights into the exploration of the world of electronics, physical electronics, nuclear and hyper-nuclear physics, nanotechnology, material science, photonics and photovoltaics, cosmology, genomics, and nature.
Fixed Point Theory and Fractals
In recent decades, fractal theory has proven to be extremely useful for the modelling of a great quantity of natural and social phenomena. Its fields of application range from biotechnology to financial markets, for instance.Fractal geometry builds a bridge between classical geometry and modern analysis. The static models of the old geometry are enriched with the dynamics of an infinite iterative process, where the outputs are not merely points but more sophisticated geometric objects and structures. A fractal set can be described in very different ways, but the current mathematical research tends to define a fractal as the fixed point of an operator on the space of compact subsets of a space of a metric type. Iterated function systems provide a way of constructing an operator of this kind, and a procedure for the approximation of its fixed points. Thus, the relationships between fractal and fixed-point theories are deep and increasingly intricate.This Reprint is aimed at emphasizing the relationships between both fields, including their theoretical and their applied aspects.
Modeling and Simulation in Engineering, 3rd Edition
The Special Issue, Modeling and Simulation in Engineering, belonging to the section Control Theory and Mechanics of the Journal Mathematics, publishes original research papers involving advanced simulation and modeling techniques.The present reprint, "Modeling and Simulation in Engineering, 3rd Edition" contains 8 papers accepted after peer review by recognized specialists in the field. The papers address different topics in engineering that use modeling and optimization as well as experimental and numerical methods based on state-of-the art devices and software. The subjects of the papers address technical problems such as error mitigation in ultra-wide-band range measurements, trajectory control of differential drive mobile robots, motion controllers for the trajectory of mobile robots, propellant distribution optimization in space exploration missions, modeling trafic flow as a tool for vehicle adaptive cruise control systems, monitoring vehicle convoys using a drone-based platooning system, communication and navigation systems for Earth-Moon communication and rover movement on the Moon's surface and solving optimal control problems using a new state parametrization method.We hope that the papers selected for this issue will attract a significant audience in the scientific community and will further stimulate research involving modeling and simulation in mathematical physics and in engineering.
Redefining Humanity in the Age of Intelligent Machines
What does it truly mean to be human when machines compose symphonies, craft poetry, and offer moral guidance? In Redefining Humanity in the Age of Intelligent Machines, readers journey through the profound shifts reshaping human identity and purpose in our increasingly AI-driven world. From historical beliefs about human uniqueness to today's astonishing AI breakthroughs, this book challenges long-held assumptions of human exceptionalism. Provocative yet accessible, it explores art, ethics, empathy, and consciousness as it reimagines what our future looks like when machines not only match-but surpass-human capabilities. Prepare to question your deepest beliefs and embrace a thoughtful, inspiring vision for coexistence in the era of intelligent machines.
Transforming Digital Healthcare with AI
AI and emerging technologies are revolutionizing digital healthcare, transforming everything from diagnostics and treatment to data security and smart hospital systems. Transforming Digital Healthcare with AI explores the profound impact of AI, data science, and smart technologies in shaping the future of healthcare. This book delves into cutting-edge innovations such as quantum computing, blockchain, digital twins, and telehealth, offering insights into how these advancements are enhancing efficiency, security, and patient outcomes. Bringing together critical discussions on automation, privacy, and ethical AI, this book provides a comprehensive view of the digital healthcare landscape. Whether you're a healthcare professional, technologist, policymaker, or researcher, this essential read unpacks the opportunities, challenges, and transformative potential of AI-driven digital healthcare.
Transforming UX Design with OpenAI Canvas
Artificial intelligence is no longer a futuristic concept - it is actively reshaping the way we create, interact, and design digital experiences. OpenAI Canvas: Enhancing the UX Design Process explores the transformative impact of OpenAI's innovations on UX design, research, and accessibility. Written by UX expert and researcher Okpala Blessing, this insightful book dives deep into the intersection of generative AI and inclusive design, offering fresh perspectives for designers, researchers, and tech enthusiasts. As AI becomes an integral part of design workflows, professionals must navigate new challenges and opportunities. This book takes a close look at how AI is revolutionizing design thinking, content generation, and user research while addressing its ethical implications. It provides a thoughtful discussion on the role of AI in creating more inclusive digital experiences and how designers can harness these advancements responsibly. Through real-world applications, expert insights, and a forward-looking perspective, OpenAI Canvas serves as an essential resource for UX professionals, AI researchers, and product designers. Whether you are integrating AI into your workflow, studying its impact on human-centered design, or leading AI-driven innovation, this book offers the knowledge and strategies needed to stay ahead in an ever-evolving field. Beyond the technical aspects, OpenAI Canvas delves into the human side of AI-driven design, exploring how these tools can enhance creativity, streamline complex processes, and foster collaboration between designers and AI systems. It also highlights the importance of ethical AI practices, ensuring that advancements in technology lead to more accessible and inclusive digital experiences for diverse users. Engaging, insightful, and deeply relevant, OpenAI Canvas goes beyond academic discourse - it is a visionary guide to the future of AI-powered UX design.
AI-Integrated Business Analytics for SMEs
In today's fast-paced digital economy, small and medium enterprises (SMEs) face the challenge of leveraging data and artificial intelligence to stay competitive. AI-Integrated Business Analytics for SMEs: A Practical Framework provides a step-by-step guide to transforming business operations with AI-driven analytics, making data a strategic asset rather than a complex burden. Drawing from real-world case studies and proven methodologies, this book introduces the DAIAM Framework, a structured approach designed specifically for SMEs to adopt, integrate, and scale AI-powered analytics without the need for massive budgets or technical expertise. From sales forecasting and inventory optimization to financial reporting and customer segmentation, this book offers practical insights, actionable strategies, and tangible results to help SMEs unlock the power of AI. Whether you're a business owner, analyst, or consultant, this book will equip you with the tools to navigate AI adoption, overcome implementation challenges, and build a data-driven, future-ready enterprise.
Mastering Dynamic Authentication
This book delves into Dynamic Knowledge-Based Authentication (KBA), a cutting-edge approach designed to safeguard sensitive data from evolving cyber threats. It provides an in-depth comparison between online and offline dynamic KBA techniques, evaluating how each method leverages personalized, behavior-driven questions to significantly enhance security measures. Unlike traditional static KBA, which relies on fixed questions and answers, dynamic KBA offers a more robust defense by adapting to users' unique behavioral patterns and real-time context, such as their location, device usage, or interaction history. The book emphasizes the superior security benefits of dynamic KBA over its static counterpart, which is vulnerable to common threats such as phishing attacks and data breaches. By incorporating dynamic elements, such as time-sensitive or activity-related questions, dynamic KBA creates a more fluid and challenging barrier for cyber attackers. The book also explores the practical applications of dynamic KBA in key sectors like finance, healthcare, and government. These industries, which handle highly sensitive data, benefit significantly from enhanced security protocols, as dynamic KBA can help prevent unauthorized access and protect against identity theft, fraud, and data breaches. Additionally, the book provides a comprehensive analysis of the operational mechanisms of both online and offline dynamic KBA methods. It discusses the technological and infrastructural challenges associated with implementing these methods, such as ensuring user convenience while maintaining high levels of security. This book aims to contribute valuable insights into the evolving landscape of digital asset protection, highlighting the future potential and challenges of dynamic knowledge-based authentication.
Sentiment Analysis With ML
This book explores the impact of sentiment analysis on social media platforms, examining how it influences public perception and behavior. It also delves into the role of machine learning in analyzing and understanding the dynamics of online interactions and the behavioral patterns associated with specific situations. In the rapidly evolving digital landscape, social media has become an integral part of daily life, shaping public discourse, influencing opinions, and fostering global interactions. The proliferation of various platforms, such as Facebook, Twitter, Instagram, and LinkedIn, has created vast digital ecosystems where individuals, organizations, and even governments engage in discussions, debates, and content sharing. The continuous flow of information in these online spaces has led to a growing interest in understanding how opinions and emotions expressed on these platforms impact society. One of the most effective methods for analyzing and interpreting these interactions is sentiment analysis, a field that employs computational techniques to assess and categorize opinions expressed in text, images, and videos. This book delves into the profound impact of sentiment analysis on social media platforms, exploring how it influences public perception and human behavior. Sentiment analysis, also known as opinion mining .
Avionics Software Verification & Validation
Mastering Software Testing for DO-178C compliance: A Practical Guide for Aerospace Safety"". Ensuring the safety and reliability of airborne software is critical in the aerospace industry. DO-178C, the gold standard for aviation software certification, mandates a rigorous testing process to achieve compliance. This book provides a Comprehensive, hands-on approach to software testing in line with DO-178C guidelines, Covering: Test planning, case design, and execution strategies, Structural Coverage Analysis' Your definitive guide to achieving DO-178C compliance through effective testing!
The Investigator's Guide to Online Research & OSINT
The Investigator's Guide to Online Research & OSINT is an essential, practical reference for modern-day investigators, researchers, and analysts navigating the ever-evolving landscape of digital intelligence. Authored by former British Transport Police detective Tony Bennett, MSc, this comprehensive guide offers a UK-focused perspective on Open Source Intelligence (OSINT), blending professional experience with current best practices in online research and cyber investigations.Drawing on decades of experience in frontline law enforcement and high-tech crime units, Tony demystifies OSINT with clear, methodical instructions and real-world examples tailored for both beginners and seasoned professionals. Whether you're working in law enforcement, compliance, corporate investigations, journalism, or private research, this guide equips you with the tools to collect, verify, and analyse open-source data legally and ethically.
Research on Fuzzy Logic and Mathematics with Applications II
This Special Issue deals with the uncertainty of information in real-world problems and use cases. It is now well-known that fuzzy set theory is a suitable theory in this regard. This theory is a valuable conceptual tool for handling vague concepts and sets forth a unifying framework for modeling various types of information. The motivation and the goal of this Special Issue is to bring together researchers contributing to this exciting field of research and also inspire interested readers and researchers alike to develop effective tools to deal with imprecise and uncertain environments.
Experiments and Simulations of Superalloys
This Special Issue presents the latest advances in the design, processing, and performance evaluation of Ni-based superalloys. The presented articles highlight key aspects such as microstructural evolution, high-temperature tensile behavior, low-cycle fatigue, and the effects of alloying and processing on mechanical properties. Covering both single-crystal and directionally solidified superalloys, the contributions provide insights into γ/γ′ phase interactions, deformation mechanisms, and phase stability. This compilation can serve as a valuable reference for researchers and engineers working on high-performance alloys for turbine, aerospace, and power-generation applications.
Recent Progress and Challenges of Artificial Intelligence in Bioinformatics and New Medicine
This Reprint showcases cutting-edge research at the intersection of artificial intelligence (AI), bioinformatics, and new medicine. It highlights recent advances and persistent challenges in leveraging AI to address complex biological and clinical problems, such as multi-omics integration, cancer discovery, single-cell analysis, and network modeling. Contributions include innovative deep learning methods, data mining approaches, and computational tools designed to decode disease mechanisms, identify risk factors, and accelerate translational medicine. By compiling high-quality studies and reviews, this Reprint provides a comprehensive resource for researchers exploring how AI-driven technologies are reshaping bioinformatics and pioneering the future of precision medicine.
The Immortal Mirror
In a world racing toward digital immortality, where minds can be uploaded and consciousness may one day be preserved forever, humanity stands on the brink of its most profound transformation. This groundbreaking exploration dives deep into the heart of mind uploading, where the lines between life and death, memory and code, body and machine blur into unsettling new realities. Are we simply collections of data waiting to be cloned? Or does our essence transcend what technology can capture? Through gripping real-world stories, cutting-edge research, and timeless philosophy, this book confronts the emotional, ethical, and psychological dilemmas surrounding AI clones and digital consciousness. It boldly questions whether preserving consciousness is the ultimate triumph over mortality or a dangerous illusion that threatens the very core of what it means to be human. Readers will discover: - How the rise of virtual self identity challenges our deepest assumptions about personal existence. - The hidden dangers and seductive promises of technology and mortality in an age of brain simulation. - The spiritual and emotional costs of attempting to defy death through digital afterlife technologies. - The complex ethics of brain upload, from questions of consent to the haunting risks of eternal suffering. - Why philosophers, scientists, and spiritual teachers warn that true meaning may lie not in living forever, but in accepting the beauty of impermanence. Whether you're fascinated by cutting-edge technology, captivated by the mysteries of the human mind, or seeking answers to the ultimate questions of life and death, this is a book that will challenge, inspire, and transform your understanding of the coming age of AI cloning. Prepare to confront your digital shadow and glimpse the unsettling future of human existence.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
