Intelligent Technologies and Robotics (R0)

This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a concentration on advances of deep learning architectures. The book discusses various artificial intelligence (AI) techniques based on deep learning architecture with applications in natural language processing, semantic knowledge, forecasting and many more.  The authors shed light on various applications that can benefit from the use of deep learning in pattern recognition, person re-identification in surveillance videos, action recognition in videos, image and video captioning. The book also highlights how deep learning concepts can be interwoven with more modern concepts to yield applications in multidisciplinary fields.

• Presents a comprehensive look at deep learning and its multidisciplinary applications, concentrating on advances of deep learning architectures;
• Includes a survey of deep learning problems and solutions, identifying the main open issues, innovations and latest technologies;
• Shows industrial deep learning in practice with examples/cases, efforts, challenges, and strategic approaches.

This book addresses the key problems that computational intelligence aims to solve, including (i) the involved computational process might be too complex for mathematical reasoning; (ii) it might contain some uncertainties during the process, or (iii) by nature, the computational process is a randomly determined one (heuristic). The contributors make use of methods that are close to the human's way of reasoning, that is, available information might be inexact or incomplete, yet it would be able to produce controlled actions in an adaptive way. Approaches presented in the book include swarm intelligence, artificial immune systems, image processing, data mining, natural language processing, text mining, and other solutions involving artificial intelligence methodologies.  

This book presents the most recent innovations, trends, and challenges in several aspects of Industry 4.0, including the key technologies and business impacts. The book is relevant to a variety of stakeholders due to Industry 4.0’s broad impact in many fields.  Topics include digital workplace solutions for employee engagement, entrepreneurship and innovation, and Blockchain for business security. The authors cover Industry 4.0 both from a theoretical and applicable standpoint.

This book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. In this book, new horizons on the theoretical developments of fuzzy logic, neural networks and optimization algorithms are envisioned. In addition, the abovementioned methods are discussed in application areas such as control and robotics, pattern recognition, medical diagnosis, decision-making, prediction and optimization of complex problems. There are a group of papers with the main theme of type-1, type-2 and type-3 fuzzy systems, which basically consists of papers that propose new concepts and algorithms based on type-1, type-2 and type-3 fuzzy logic and their applications. There is also a group of papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers outlines diverse applications of hybrid intelligent systems in real problems. There are also a group papers that present theory and practice of neural networks in different applications. Finally, there are papers that offer theory and practice of optimization and evolutionary algorithms in different application areas.

This book presents the proceedings of the 6th International Conference on Emerging Technologies: Micro to Nano (ETMN), held in New Delhi, India, on November 22-23, 2024. It showcases advances and innovations in micro and nanotechnologies and covers topics such as nano composites, nano materials, micro/nano fluidics, micro optics, organic and flexible electronics, advanced materials for nano devices, MEMS, smart biomimetic sensors, electrochemical sensors, acoustic and optical sensors, micro/nano sensors, wearable sensors, intelligent instrumentation, micro/nano electronics, nano antenna and RF system design, wireless sensor networks, applications of AI and IoT-based system, and structural health monitoring (SHM).

This book simplifies complex AI and ML concepts, making them accessible to security analysts, IT professionals, researchers, and decision-makers. Cyber threats have become increasingly sophisticated in the ever-evolving digital landscape, making traditional security measures insufficient to combat modern attacks. Artificial intelligence (AI) and machine learning (ML) have emerged as transformative tools in cybersecurity, enabling organizations to detect, prevent, and respond to threats with greater efficiency. This book is a comprehensive guide, bridging the gap between cybersecurity and AI/ML by offering clear, practical insights into their role in threat intelligence. Readers will gain a solid foundation in key AI and ML principles, including supervised and unsupervised learning, deep learning, and natural language processing (NLP) while exploring real-world applications such as intrusion detection, malware analysis, and fraud prevention. Through hands-on insights, case studies, and implementation strategies, it provides actionable knowledge for integrating AI-driven threat intelligence into security operations. Additionally, it examines emerging trends, ethical considerations, and the evolving role of AI in cybersecurity. Unlike overly technical manuals, this book balances theoretical concepts with practical applications, breaking down complex algorithms into actionable insights. Whether a seasoned professional or a beginner, readers will find this book an essential roadmap to navigating the future of cybersecurity in an AI-driven world. This book empowers its audience to stay ahead of cyber adversaries and embrace the next generation of intelligent threat detection.

This book bridges Industry 4.0 principles with educational innovation, offering groundbreaking approaches that transform learning environments across diverse contexts. Readers discover practical applications ranging from AI-powered diagnostics to gamification strategies, all designed to make education more accessible, engaging, and effective.
The unique collaboration between Hispanic American and European researchers brings fresh perspectives to educational technology, organizing cutting-edge research into six comprehensive sections. What distinguishes this work is its human-centered approach—each technological advancement connects directly to pedagogical improvement.
Educators, researchers, and technology specialists find value in the book’s exploration of solutions like holographic displays, 3D-printed prosthetics for STEM education, and psychological self-assessment platforms. Beyond serving as a reference, this book establishes a foundation for continued cross-cultural dialogue and future innovation, helping institutions integrate emerging technologies while keeping human development at the core of educational transformation.

This book focuses on collecting some of the best results with the goal, dealing with the important and efficient combination of mathematics and computational intelligence, with a stress of fuzzy systems, and fuzzy logic.

Artificial intelligence appears nowadays very much in the media, and also in the practice. In addition, every day, thousands of automatic intelligent systems for decision making are designed and applied around the world. In their design, many advanced techniques based on mathematics and computational intelligence are considered and used. Therefore, it is fundamental to continuously work on novel approaches in these areas and research models and algorithms with foundation in the mutual relationship of these two fields. 

Naturally, an important part of this issue focuses on the applications of these both areas, taking a special interest in the development and application of mathematics, artificial intelligence, and automatic reasoning tools applicable to Digital Forensics, also following the main objective of the COST Action DigForASP-CA17124.

This book captures extraordinary research from the VI International Conference on Computer Science, Electronics, and Industrial Engineering (CSEI 2024), where innovation meets real-world impact.

Discover how AI transforms lives in ways you never imagined. Researchers are helping doctors detect Parkinson's disease simply by analyzing handwriting, while others are creating smarter prosthetics that respond naturally to human thoughts. From fighting political propaganda to designing buildings that think, these breakthrough applications show AI's incredible potential to make our world better.

See how 5G, blockchain, and cloud computing are reshaping everything from healthcare to city water systems. Engineers are finding ingenious ways to power tiny IoT devices and help us navigate more intelligently through increasingly connected environments.

Learn how big data is driving the green revolution, optimizing everything from industrial processes to renewable energy systems. These aren't just theoretical concepts—they're practical solutions addressing the sustainability challenges we face today.

What ties all this research together? A shared vision of technology that truly serves humanity:

• AI that seamlessly integrates into every field, enhancing rather than replacing human expertise
• Solutions designed with people at the center, not as an afterthought
• Green technologies that protect our planet for future generations
• Smart monitoring systems that help us make better decisions faster
• Creative combinations of different technologies tackling complex, real-world problems

Whether you're a researcher pushing boundaries, a practitioner implementing solutions, an educator inspiring the next generation, or a student eager to change the world, this book offers both practical insights and inspiration. It's your window into the innovations shaping our technological future.

This textbook introduces major topics that include quantum bits, superposition, entanglement, logic gates, quantum search algorithm, quantum Fourier transform, inverse quantum Fourier transform, Shor’s order-finding algorithm and phase estimation. Everyone can write algorithms and programs in the cloud making using IBM’s quantum computers that support IBM Q Experience which contains the composer, open quantum assembly language, simulators and real quantum devices. Furthermore, this book teaches you how to use open quantum assembly language to write quantum programs for dealing with complex problems. Through numerous examples and exercises, readers will learn how to write a quantum program with open quantum assembly language for solving any problem from start to complete.   

This book includes six main chapters:  

·Quantum Bits and Quantum Gates—learn what quantum bits are, how to declare and measure them, what quantum gates are and how they work on a simulator or a real device in the cloud.   

·Order-Finding and Factoring—learn core concepts of Shor’s order-finding algorithm and how to write quantum programs to implement Shor’s order-finding algorithm for completing the prime factorization to 15.   

Phase Estimation and its Applications—learn core concepts of phase estimation and quantum counting and how to write quantum programs to implement them to compute the number of solution(s) in the independent set problem in a graph with two vertices and one edge.   

The authors explore various aspects of information processing for the design of service systems, efficient management, secure storage, and transmission. In addition, the subline provides knowledge and practice in decentralized ICT technologies, including those based on blockchain. The aim of this book is to analyze and develop methods of building decentralized private databases without the presence of a trusted party, methods of data processing in encrypted form to ensure the confidentiality of information, and accessibility of the corresponding fragment of the original or transformed data. In this book it is also relevant to research methods and protocols routing in infocommunication networks, which provides load balancing in the network, and analysis of intrusion detection methods based on analysis of signatures and anomalies in network behavior (state changes) based on machine learning and fractal analysis methods.

This book explains that the coming years undoubtedly bring new developments in mechatronics. These advances are stimulated by the growing demand for intelligent, autonomous solutions in various branches of industry and consumer products. The development of economically justified new mechatronic products is not possible without the ongoing progress in manufacturing technology, metrology, measurements systems, new materials and control techniques. Those are the key for reducing costs and enhancing functionality of new products.  Therefore, the scope of the 5^th International Conference Mechatronics spanned from advanced mechatronic systems to manufacturing processes. The new results of research in this areas are reported in this book. We strongly believe that the solutions and guidelines presented during the conference held in Szczecin (Poland) from 8^th to 10^th September 2021 are useful for both researchers and engineers solving problems associatedwith mechatronic products.

This book is an overview of latest successes and applications of fuzzy techniques—techniques that use expert knowledge formulated by natural-language words like "small". Engineering applications deal with aerospace (control of spacecrafts and unmanned aerial vehicles, air traffic control, airport passenger flow predictions), materials (designing gold nano-structures for medicine, catalysis, and sensors), and robot navigation and manipulation. Other application areas include cosmology, demographics, finances, wine production, medicine (diagnostics, epidemics control), and predicting human behavior.

 In many cases, fuzzy techniques are combined with machine learning AI. Due to natural-language origin of fuzzy techniques, such combination adds explainability (X) to AI. This book is recommended to students and practitioners interested in the state-of-the-art fuzzy-related XAI and to researchers willing to take on numerous remaining challenges.