Search results for "Man-Machine-Environment System Engineering"
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Soft Computing Models in Industrial and Environmental Applications
This book constitutes the proceedings of the 21st International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2026, held in Marbella, Spain, during June 18-19, 2026.The 58 full papers included in this volume were carefully reviewed and selected from 121 submissions. The papers cover the following topical sections: Computer Vision Applications; Prediction and Monitoring; and Systems and Optimization. The papers also include the following special sessions: Efficiency and Explainability in Machine Learning and Soft Computing; Time Series Forecasting in Industrial and Environmental Applications; Quantum Computing; Intelligent Techniques Applied to Modelling and Control in Engineering focused on Marine Energy Systems and Robotics; Machine Learning and Computer Vision in Industry 4.0; Optimization, Modeling and Control by Soft Computing Techniques; EUropean Transnational Educational.
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Intelligent Systems
This book features best selected research papers presented at the Fifth International Conference on Machine Learning, Internet of Things and Big Data (ICMIB 2025) held at Department of Computer Science and Engineering, Parala Maharaja Engineering College, Berhampur, India, during April 4–6, 2025. It comprises high-quality research work by academicians and industrial experts in the field of machine learning, mobile computing, natural language processing, fuzzy computing, green computing, human–computer interaction, information retrieval, intelligent control, data mining and knowledge discovery, evolutionary computing, IoT and applications in smart environments, smart health, smart city, wireless networks, big data, cloud computing, business intelligence, Internet security, pattern recognition, predictive analytics applications in health care, sensor networks and social sensing and statistical analysis of search techniques.
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Engineering Modeling and Design
Engineering Modeling and Design is a comprehensive systems engineering text that focuses on systematic principles for designing systems. Concurrent engineering, which requires that from the very start of a project all players (e.g., engineering, maintenance, marketing, customers) are involved as all facets of the system life cycle are considered, is skillfully illustrated through the use of two major case studies. The text describes how a product design proceeds parallel to the process design, explains key duties of systems engineers throughout the product life cycle, and examines the process of system design in terms of life cycle requirements. Projects and problems are presented throughout the text. A homework solutions/instructor's manual is available from the publisher upon request.Engineering Modeling and Design is an excellent text for engineering design courses in industry and upper division courses on concurrent engineering or total quality management.
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Green Communications for Energy-Efficient Wireless Systems and Networks
The ICT industry is a major consumer of global energy. The energy crisis, global warming problems, dramatic growth in data traffic and the increased complexity of emerging networks are pushing academic and industry research towards the development of energy-saving and energy-efficient architectures, technologies and networks in order to reduce the carbon footprint while ensuring efficient and reliable communication networks, and environmental sustainability. Attractive solutions for the design and implementation of energy efficient wireless networks and 5G technologies include massive MIMO, non-orthogonal multiple access, and energy harvesting communications. Tools from areas such as machine and deep learning are being investigated to establish optimal approaches and understand fundamental limits. Moreover, new promising heterogeneous and decentralized network architectures and the Internet-of-Things (IoT) will have an impact on the successful implementation of future and next generation green wireless communications. The aim of this edited book is to present state-of-the art research from theory to practice, and all aspects of green communication methods and technologies for the design of next generation green wireless communication systems and networks. This advanced research title will be of interest to an audience of researchers, engineers, scientists and developers from academia and the industry working in the fields of ICTs, signal processing, networking, power and energy systems, environmental and sustainable engineering, sensing and electronics. It will also be a very useful text for lecturers, postdocs, PhD and masters students researching the design of the next generation wireless communication systems and networks.
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Satellite Remote Sensing for Forest and Environmental Monitoring
Satellite Remote Sensing for Forest and Environmental Monitoring provides a thorough examination of the applications and methods of satellite remote sensing for analyzing and managing forest environments. From forest height mapping to biodiversity modeling, the book explores a variety of Earth observation applications across cutting-edge sensors and platforms. The book addresses the ability of satelitte technologies to observe and analyse ecological functions, conditions, and socioeconomic benefits for sustainable nature protection in the face of anthropogenic change, offering practical tools and strategies for large-scale forest inventories, fire risk assessment, and freshwater management. Satellite Remote Sensing for Forest and Environmental Monitoring offers postgraduates, researchers, and academics in remote sensing and geospatial technologies, particularly those focusing on forestry applications and related disciplines insights into environmental changes, land use patterns, vegetation mapping, and climate indicators.
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Quantitative Evaluation of Systems and Formal Modeling and Analysis of Timed Systems
This book constitutes the proceedings of the Third International Joint Conference on Quantitative Evaluation of Systems and Formal Modeling and Analysis of Timed Systems, QEST+Formats 2026, which took place in Liverpool, UK, during September 2-4, 2026.The 24 full papers included in this book were carefully reviewed and selected from 54 submissions.They deal with up to date research in the quantitative evaluation and verification of systems, including fundamental and practical aspects of systems with quantitative nature (such as probability, timing, or cost) and particular focus on machine-learning and quantum systems, case studies, and tool papers.
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Routledge Handbook of Smart Built Environment
The primary aim of this edited volume is to document the current theories, best practices, and technological advancements in the move towards a Smart Built Environment (SBE). The needs to accelerate towards the SBE are numerous and include:Increasing complexities and the need for interconnectivity within the built environment (e.g. mega infrastructure projects)Data-driven decision-making resulting in higher demand from clients (e.g. smart design, construction, operation, and end of life [EOL])High requirements from stakeholders (e.g. system efficiency, environmental performance, green procurement)Fast paced technological advancement and integrationNatural disaster resilience of the built environment (e.g. prediction, smart control of building component)Sustainability issues around the built environmentIn this book, the interrelationships among the various lifecycle stages: design, construction, operation, and EOL; the collective benefit of synergy at building level, multi-infrastructure level, and city-level, as well as the ultimate goals in relation to the deployment of smart technologies in the industry are addressed. Part I covers smart design and construction, Part II smart living, and operation, and Part III broadens the scope to the whole smart city. Chapters examine:How smart technologies can improve the effectiveness, productivity, and efficiency of the built environmentAn overview of theories and practices that are enabled by innovations and technologies for developing the SBEThe basis for new research agenda, new concepts, and frameworks for future developmentThis handbook documents the current theories, practices, and technologies and develops a holistic approach for research and practice by adopting a multidimensional outlook for the SBE. It is an essential reference work for all built environment stakeholders, from academia through to the professions.
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Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications
This two-volume set CCIS 2309-2310 constitutes the refereed proceedings of the 11th International Conference on Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications, FDSE 2024, held in Binh Duong, Vietnam, during November 27-29, 2024. The 44 full papers, 12 short papers and 1 keynote paper were carefully reviewed and selected from 189 submissions. They were organized in topical sections as follows: advances in machine learning for big data analytics; security and privacy engineering; data analytics and healthcare systems; smart city and industry 4.0 applications; big data query processing and optimization; and short papers; security and data engineering.
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Web Engineering
The World Wide Web has a massive and permanent influence on our lives. Economy, industry, education, healthcare, public administration, entertainment – there is hardly any part of our daily lives which has not been pervaded by the Internet. Accordingly, modern Web applications are fully-fledged, complex software systems, and in order to be successful their development must be thorough and systematic. This book presents a new discipline called Web Engineering taking a rigorous interdisciplinary approach to the development of Web applications, covering Web development concepts, methods, tools and techniques. It highlights the need to examine and re-use the body of knowledge found within software engineering and demonstrates how to use that knowledge within the Web environment, putting emphasize on current practices, experiences and pitfalls. The book is ideal for undergraduate and graduate students on Web-focused or Software Engineering courses, as well as Web software developers, Web designers and project managers.
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Cryptography for Intelligent Healthcare Systems
Intelligent healthcare systems refer to the use of technologies, such as IoT, big data, AI, and machine learning, to improve the quality and efficiency of healthcare delivery. Healthcare data is both valuable and sensitive, and patients' data is increasingly at risk from cyber attacks on medical devices and critical healthcare infrastructure, posing serious risks to patient health and safety or compromising sensitive user data. As healthcare provision relies upon numerous interconnected systems, to facilitate the diagnosis or treatment of patients' health conditions, these systems rely on advanced cryptography to secure and protect sensitive user information. This edited book in two volumes covers advanced cryptography for intelligent healthcare systems, examining robust cryptography-empowered frameworks and considering external threats, inside vulnerabilities, well-defined risks, and the resilience and robustness of the security architecture. Volume 1 addresses foundations and emerging architectures, including legacy and modern cryptography, advanced cryptographic frameworks, including examples utilising AI, and explores the security of emerging systems and environments such as IoT and the internet-of-medical-things, 6G networks and multi-network emergency communication systems. Volume 2 focuses on privacy, governance and deployment. Chapters cover device-class mappings, protocol profiles and deployment playbooks; FHIR-based systems using authenticated encryption, privacy-preserving federated learning and audit-grade integrity for intelligent matching systems; zkSNARK benchmark frameworks; ethical concerns and governance challenges, ethical-by-design cryptography; patient data autonomy; and security beyond cryptography. Including case studies, highlighting critical lessons and design recommendations, these volumes provides researchers and academics with new insights into the real-world scenarios of the design, development, deployment, application, and management of cryptographic algorithms in modern healthcare systems.
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Integrated Technologies in Electrical, Electronics and Bio-technology Engineering
The 2nd International Conference on Innovative Trends in Electrical, Electronics and Bio-Technology Engineering (ICITEEB 2025) is a multidisciplinary book designed to foster collaboration and exploration at the intersection of the dynamic fields of Semiconductor Devices & Electronic Circuit Design, Machine Vision & Signal Processing, Communication Technologies and Systems, Electromagnetic, RF, Microwave & Wearable Technology, Nano-Technologies & IC Fabrication, Biotechnology, Automation & Robotics. The book seeks to facilitate the exchange of knowledge, ideas, and best practices to address the evolving challenges and opportunities in these interconnected domains.ICITEEB 2025 features high-quality research contributions spanning Smart Power and Sustainable Energy Systems, Semiconductor Devices and Fabrication Technologies, Advanced Signal and Image Processing, Intelligent Communication Systems, IoT and Embedded Applications, Biomedical and Bio-Technology Innovations, Mechatronics, and Electric/Hybrid Mobility Solutions. The presentations and discussions reflect the rapidly accelerating pace of global technological innovation and the growing need for integrated, cross-disciplinary research.This book is a key resource for leaders, academia, professionals, and researchers in the field of Electrical Engineering, Electronics Engineering and related fields.
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Robust Environmental Perception and Reliability Control for Intelligent Vehicles
This book presents the most recent state-of-the-art algorithms on robust environmental perception and reliability control for intelligent vehicle systems. By integrating object detection, semantic segmentation, trajectory prediction, multi-object tracking, multi-sensor fusion, and reliability control in a systematic way, this book is aimed at guaranteeing that intelligent vehicles can run safely in complex road traffic scenes.Adopts the multi-sensor data fusion-based neural networks to environmental perception fault tolerance algorithms, solving the problem of perception reliability when some sensors fail by using data redundancy.Presents the camera-based monocular approach to implement the robust perception tasks, which introduces sequential feature association and depth hint augmentation, and introduces seven adaptive methods.Proposes efficient and robust semantic segmentation of traffic scenes through real-time deep dual-resolution networks and representation separation of vision transformers.Focuses on trajectory prediction and proposes phased and progressive trajectory prediction methods that is more consistent with human psychological characteristics, which is able to take both social interactions and personal intentions into account.Puts forward methods based on conditional random field and multi-task segmentation learning to solve the robust multi-object tracking problem for environment perception in autonomous vehicle scenarios. Presents the novel reliability control strategies of intelligent vehicles to optimize the dynamic tracking performance and investigates the completely unknown autonomous vehicle tracking issues with actuator faults.
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Convergence of AI, IoT, Smart Sensors and Remote Sensing for Sustainable Smart Environment Applications
AI and data-driven methods, particularly machine and deep learning models, have revolutionized image processing tasks such as object detection and segmentation, as well as inverse sensing tasks such as atmospheric condition monitoring. These models enable highly accurate predictions from large, labelled datasets. However, one of the key challenges with current AI systems is their opacity. While they deliver precise results, they often fail to provide clear insights into the underlying mechanisms driving these predictions. The lack of interpretability, especially in the context of sensing data, complicates the understanding of how internal features are represented and utilized. This issue is particularly pronounced in smart environment applications, where artificial intelligence techniques are increasingly employed, yet their internal workings remain largely opaque. In this edited book, the contributors explore the potential of machine intelligence, deep learning and sensing technologies, with a focus on their integration and applications. They present new methods, cutting-edge technologies and practical solutions to real-world challenges. The goal is to help readers better grasp the concepts necessary for designing and deploying the next generation of smarter and more sustainable systems and environments. The Convergence of AI, IoT, Smart Sensors and Remote Sensing for Sustainable Smart Environment Applications is a useful reference for researchers, engineers and scientists in academia and industry, as well as advanced students in the fields of data science and security, AI and networking, communication engineering, smart sensing, remote sensing and automation. It will also be of interest to system designers and developers of AI and sensing technologies for smart environment applications.
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Condition Monitoring of Rotating Electrical Machines
Condition monitoring of engineering plant has increased in importance as engineering processes are automated and manpower is reduced. However, electrical machinery receives attention only at infrequent intervals when plant is shut down and the application of protective relays to machines has also reduced operator surveillance. A first edition of Condition Monitoring of Electrical Machines, written by Tavner and Penman, was published in 1987. The economics of industry have now changed, as a result of the privatisation and deregulation of the energy industry, placing emphasis on the importance of reliable operation of plant, throughout the whole life cycle, regardless of first cost. The availability of advanced electronics and software in powerful instrumentation, computers, and digital signal processors (DSP) has simplified our ability to instrument and analyse machinery. As a result condition monitoring is now being applied to a wider range of systems, from fault-tolerant drives of a few hundred watts in the aerospace industry, to machinery of a few hundred megawatts in major capital plant. In this new book the original authors have been joined by Ran, an expert in power electronics and control, and Sedding, an expert in the monitoring of electrical insulation systems. Together the authors have revised and expanded the earlier book, merging their own experience with that of machine analysts to bring it up to date. The book is aimed at professional engineers in the energy, process engineering and manufacturing industries, plus research workers and students.
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Future Data and Security Engineering
This book constitutes the refereed proceedings of the 12th International Conference on Future Data and Security Engineering, FDSE 2025, held in Ho Chi Minh City, Vietnam, during November 27–29, 2025.The 56 full papers and 10 short papers presented in these two volumes were carefully reviewed and selected from 215 submissions.The papers are organized in the following topical sections:Part I: Invited Keynote; Advances in Machine Learning for Big Data Analytics; Security and Privacy Engineering; Query Processing and Optimization; Data Analytics and Healthcare Systems; Smart City and Industry 4.0 Applications.Part II: Invited Keynote; Advances in Machine Learning for Big Data Analytics; Security and Privacy Engineering; Query Processing and Optimization; Data Analytics and Healthcare Systems; Smart City and Industry 4.0 Applications; Short Papers: Security and Data Engineering.
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Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models
Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models focuses on the relationship between three different multidisciplinary branches of engineering: Biomedical Engineering, Cognitive Science and Computer Science through Artificial Intelligence models. These models will be used to study how the nervous system and musculoskeletal system obey movement orders from the brain, as well as the mental processes of the information during cognition when injuries and neurologic diseases are present in the human body. The interaction between these three areas are studied in this book with the objective of obtaining AI models on injuries and neurologic diseases of the human body, studying diseases of the brain, spine and the nerves that connect them with the musculoskeletal system. There are more than 600 diseases of the nervous system, including brain tumors, epilepsy, Parkinson's disease, stroke, and many others. These diseases affect the human cognitive system that sends orders from the central nervous system (CNS) through the peripheral nervous systems (PNS) to do tasks using the musculoskeletal system. These actions can be detected by many Bioinstruments (Biomedical Instruments) and cognitive device data, allowing us to apply AI using Machine Learning-Deep Learning-Cognitive Computing models through algorithms to analyze, detect, classify, and forecast the process of various illnesses, diseases, and injuries of the human body. Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models provides readers with the study of injuries, illness, and neurological diseases of the human body through Artificial Intelligence using Machine Learning (ML), Deep Learning (DL) and Cognitive Computing (CC) models based on algorithms developed with MATLAB® and IBM Watson®.
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Engineering Innovation Nexus
In today’s rapidly evolving industrial landscape, professionals face unprecedented challenges at the intersection of scientific advancement and organizational leadership. This comprehensive volume explores the fundamental principles that drive progress across sectors, examining how interdisciplinary approaches foster breakthrough applications and sustainable development. The authors provide a detailed exploration of the theoretical frameworks and practical methodologies that underpin successful project implementation in complex environments.Engineering Innovation Nexus: Technology and R&D Management offers several distinctive features that set it apart from conventional texts in the field. Analyzing real-world case studies, it demonstrates how research applications transform industries through systematic approaches to problem-solving. The chapters examine leadership practices that cultivate team dynamics conducive to innovation, while providing actionable strategies for risk assessment and mitigation. Additionally, readers will discover frameworks for evaluating development initiatives, implementing interdisciplinary methodologies, and fostering environments where creative solutions can thrive in response to emerging global challenges.This resource serves diverse professionals such as academics, researchers, industry practitioners, and policymakers, providing critical insights and practical tools for both established experts and emerging leaders navigating today’s complex interdisciplinary landscape.
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Engineering Psychology and Cognitive Ergonomics
This book constitutes the refereed proceedings of the 13th International Conference on Engineering Psychology and Cognitive Ergonomics, EPCE 2016, held as part of the 18th International Conference on Human-Computer Interaction, HCII 2016, held in Toronto, ON, Canada, in July 2016.The total of 1287 regular papers and 186 poster papers presented at the HCII 2016 conferences was carefully reviewed and selected from 4354 submissions. These papers address the latest research and development efforts and highlight the human aspects of design and use of computing systems. The papers accepted for presentation thoroughly cover the entire field of human-computer interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas. The 47 contributions included in the EPCE proceedings were organized in the following topical sections: mental workload and performance; interaction and cognition; team cognition; cognition in complex and high risk environments; and cognition in aviation.
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Advances in Sustainable Energy Systems, Storage, and Conservation
This book covers the latest advancements and emerging trends in the renewable energy field. It focuses on novel research directions and cutting-edge technologies related to renewable energy grid infrastructures, engineering design methodologies, and innovative solutions to industrial challenges. The book delves into critical topics such as integrating renewable energy sources into existing grids, advancements in energy storage technologies, and the role of artificial intelligence and machine learning in optimizing renewable energy systems. The contributions are based on selected high-quality research from the 9th International Conference on Renewable Energy and Conservation (ICREC 2024), providing readers with a comprehensive understanding of the multifaceted nature of renewable energy engineering.Advances in Sustainable Energy Systems, Storage, and Conservation is a valuable resource for researchers, practitioners, professionals, and scientists seeking to stay ahead of the curve in the rapidly evolving renewable energy field.Provides insights into the latest trends and emerging technologies in renewable energy engineering;Integrates insights from engineering, environmental science, and policy analysis;Features case studies and practical applications of implementing renewable energy solutions.
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Safety Assurance under Uncertainties
Safety assurance of software systems has never been as imminent a problem as it is today. Practitioners and researchers who work on the problem face a challenge unique to modern software systems: uncertainties. For one, the cyber-physical nature of modern software systems as exemplified by automated driving systems mandates environmental uncertainties to be addressed and the resulting hazards to be mitigated. Besides, the abundance of statistical machine-learning components massive numerical computing units for statistical reasoning such as deep neural networks make systems hard to explain, understand, analyze or verify.The book is the first to provide a comprehensive overview of such united and interdisciplinary efforts. Driven by automated driving systems as a leading example, the book describes diverse techniques to specify, model, test, analyze, and verify modern software systems. Coming out of a collaboration between industry and basic academic research, the book covers both practical analysis techniques (readily applicable to existing systems) and more long-range design techniques (that call for new designs but bring a greater degree of assurance).The book provides high-level intuitions and use-cases of each technique, rather than technical details, with plenty of pointers for interested readers.
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Computer Vision and Machine Intelligence for Renewable Energy Systems
Computer Vision and Machine Intelligence in Renewable Energy Systems, the first release in Elsevier's cutting-edge new series, Advances in Intelligent Energy Systems, offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration. The book equips readers with a variety of essential tools and applications, outlining the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence and breaking down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures.Other sections offer case studies and applications to a wide range of renewable energy source and the future possibilities of the technology. This book provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids.
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Environmental Science
Environmental Science: An Empirical Approach provides students with an engaging examination of Earth's dynamic environmental systems, exploring the complexities of life on Earth, the interrelationships of its biosphere, and humanity's interaction with the environment. The book weaves together natural sciences with insights from scientific, formal, and social disciplines to offer a comprehensive understanding of environmental stewardship. This text anchors its discussion in empirical evidence and scientific methods, ensuring a fact-based approach to environmental science. Through clear delineations of scientific methods alongside discussions of Earth's systems and resources, students develop a deep understanding of ecological and biological principles, the rock cycle, atmospheric processes, and the profound interconnectedness of Earth's components. Serving as a foundational text that examines Earth's natural mechanisms and our role within them, Environmental Science is ideal for courses and programs in environmental science, ecology, and sustainability studies.
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Deep Learning on Embedded Systems
Comprehensive, accessible introduction to deep learning for engineering tasks through Python programming, low-cost hardware, and freely available software Deep Learning on Embedded Systems is a comprehensive guide to the practical implementation of deep learning for engineering tasks through computers and embedded hardware such as Raspberry Pi and Nvidia Jetson Nano. After an introduction to the field, the book provides fundamental knowledge on deep learning, convolutional and recurrent neural networks, computer vision, and basics of Linux terminal and docker engines. This book shows detailed setup steps of Jetson Nano and Raspberry Pi for utilizing essential frameworks such as PyTorch and OpenCV. GPU configuration and dependency installation procedure for using PyTorch is also discussed allowing newcomers to seamlessly navigate the learning curve. A key challenge of utilizing deep learning on embedded systems is managing limited GPU and memory resources. This book outlines a strategy of training complex models on a desktop computer and transferring them to embedded systems for inference. Also, students and researchers often face difficulties with the varying probabilistic theories and notations found in data science literature. To simplify this, the book mainly focuses on the practical implementation part of deep learning using Python programming, low-cost hardware, and freely available software such as Anaconda and Visual Studio Code. To aid in reader learning, questions and answers are included at the end of most chapters. Written by a highly qualified author, Deep Learning on Embedded Systems includes discussion on: Fundamentals of deep learning, including neurons and layers, activation functions, network architectures, hyperparameter tuning, and convolutional and recurrent neural networks (CNNs & RNNs)PyTorch, OpenCV, and other essential framework setups for deep transfer learning, along with Linux terminal operations, docker engine, docker images, and virtual environments in embedded devicesTraining models for image classification and object detection with classification, then converting trained PyTorch models to ONNX format for efficient deployment on Jetson Nano and Raspberry Pi Deep Learning on Embedded Systems serves as an excellent introduction to the field for undergraduate engineering students seeking to learn deep learning implementations for their senior capstone or class projects and graduate researchers and educators who wish to implement deep learning in their research.
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Numerical Methods for Nonlinear Engineering Models
There are many books on the use of numerical methods for solving engineering problems and for modeling of engineering artifacts. In addition there are many styles of such presentations ranging from books with a major emphasis on theory to books with an emphasis on applications. The purpose of this book is hopefully to present a somewhat different approach to the use of numerical methods for - gineering applications. Engineering models are in general nonlinear models where the response of some appropriate engineering variable depends in a nonlinear manner on the - plication of some independent parameter. It is certainly true that for many types of engineering models it is sufficient to approximate the real physical world by some linear model. However, when engineering environments are pushed to - treme conditions, nonlinear effects are always encountered. It is also such - treme conditions that are of major importance in determining the reliability or failure limits of engineering systems. Hence it is essential than engineers have a toolbox of modeling techniques that can be used to model nonlinear engineering systems. Such a set of basic numerical methods is the topic of this book. For each subject area treated, nonlinear models are incorporated into the discussion from the very beginning and linear models are simply treated as special cases of more general nonlinear models. This is a basic and fundamental difference in this book from most books on numerical methods.
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International Conference on Smart Environment and Green Technologies – ICSEGT2024
This book compiles state-of-the-art studies and real-world applications in ecosystems and smart environments. It covers important subjects like creating a sustainable economy, green and renewable energy, and IoT-powered industrial and agricultural systems. Along with providing insights into theory, modelling, and the deployment of smart cities and infrastructure, the book also examines the use of AI in the earth and environmental sciences and economy. The book is intended to be a priceless tool for scholars, professionals, and recent graduates. It acts as a manual and source of inspiration for promoting environmentally friendly technologies and sustainable solutions. It opens the door for creating intelligent systems that maximise resource use, reduce carbon footprints, and enhance general quality of life by incorporating the most recent technological developments.
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Control of Electric Machine Drive Systems
A unique approach to sensorless control and regulator design of electric drives Based on the author's vast industry experience and collaborative works with other industries, Control of Electric Machine Drive Systems is packed with tested, implemented, and verified ideas that engineers can apply to everyday problems in the field. Originally published in Korean as a textbook, this highly practical updated version features the latest information on the control of electric machines and apparatus, as well as a new chapter on sensorless control of AC machines, a topic not covered in any other publication. The book begins by explaining the features of the electric drive system and trends of development in related technologies, as well as the basic structure and operation principles of the electric machine. It also addresses steady state characteristics and control of the machines and the transformation of physical variables of AC machines using reference frame theory in order to provide a proper foundation for the material. The heart of the book reviews several control algorithms of electric machines and power converters, explaining active damping and how to regulate current, speed, and position in a feedback manner. Seung-Ki Sul introduces tricks to enhance the control performance of the electric machines, and the algorithm to detect the phase angle of an AC source and to control DC link voltages of power converters. Topics also covered are: Vector controlControl algorithms for position/speed sensorless drive of AC machinesMethods for identifying the parameters of electric machines and power convertersThe matrix algebra to model a three-phase AC machine in d-q-n axes Every chapter features exercise problems drawn from actual industry experience. The book also includes more than 300 figures and offers access to an FTP site, which provides MATLAB programs for selected problems. The book's practicality and realworld relatability make it an invaluable resource for professionals and engineers involved in the research and development of electric machine drive business, industrial drive designers, and senior undergraduate and graduate students. To obtain instructor materials please send an email to pressbooks@ieee.org To visit this book's FTP site to download MATLAB codes, please click on this link: ftp://ftp.wiley.com/public/scitechmed/electricmachine/ MATLAB codes are also downloadable from Wiley Booksupport Site at http://booksupport.wiley.com
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Biologically Inspired Techniques in Many Criteria Decision-Making
This book includes selected high-quality research papers presented at 3rd International Conference on Biologically Inspired Techniques in Many Criteria Decision Making (BITMDM 2024) organized by School of Engineering and Technology, Nagaland University, Dimapur, India on 6th and 7th December 2024. This book presents the recent advances in techniques which are biologically inspired and their usage in the field of single and many criteria decision making. Further, the topics covered in this book are divided into different sections like: i) healthcare and biomedical applications, ii) security, fraud detection, and cybersecurity, iii) intelligent systems and decision support, iv) agriculture and environment, v) image processing and multi-media analysis, and vi) emerging technologies and applications.
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Machine Learning for Future Wireless Communications
A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networksCovers a range of topics from architecture and optimization to adaptive resource allocationsReviews state-of-the-art machine learning based solutions for network coverageIncludes an overview of the applications of machine learning algorithms in future wireless networksExplores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.
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Present Approach to Traffic Flow Theory and Research in Civil and Transportation Engineering
This book presents many valuable tips for making decisions related to traffic flow in the transport networks. The knowledge base in practical examples, as well as the decision support systems described in this book, finds interest among people who face the daily challenge of searching for solutions to the problems of contemporary transport networks and systems. The publication is therefore addressed to local authorities related to the planning and development of development strategies for selected areas with regard to transport (both in the urban and regional dimension) and to representatives of business and industry, as people directly involved in the implementation of traffic engineering solutions. The tips contained in individual sections of the publication allow to look at a given problem in an advanced way and facilitate the selection of the appropriate strategy (among others, in relation to the evaluation of BEV and FCHEV electric vehicles in the creation of a sustainable transport systems, development of ecological public transport on the example of selected cities, impact of drivers' waiting time on the gap acceptance at median, uncontrolled T-intersections). In turn, due to a new approach to theoretical models (including, inter alia, the application of genetic algorithms for the planning of urban rail transportation system, comprehensive estimate of life cycle costs of new technical systems using reliability verification algorithm, application and comparison of machine learning algorithms in traffic signals prediction), the publication also interests scientists and researchers carrying out research in this area.
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Human-Centered Artificial Intelligence For Industrial Safety
This book examines the transformative role of artificial intelligence (AI) in industrial safety, focusing on the shift from traditional reactive systems to proactive, predictive safety architectures in smart factories. It explores how AI technologies, including machine learning, computer vision, biometrics, wearables, augmented reality, and digital twins, are revolutionising occupational health and safety across industries such as manufacturing, logistics, energy, aviation, and construction. The book highlights the integration of AI-enabled safety systems, addressing real-time risk monitoring, predictive maintenance, employee well-being, and accident prevention. It also delves into the ethical, legal, and regulatory implications of AI in safety-critical systems, including GDPR compliance, algorithm transparency, and ISO 45001 standards. Case studies from global companies like Siemens, Boeing, Samsung, and INVISTA provide practical insights into implementation, challenges, and outcomes.
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R 1,329.41
Machine Learning Security Principles
Thwart hackers by preventing, detecting, and misdirecting access before they can plant malware, obtain credentials, engage in fraud, modify data, poison models, corrupt users, eavesdrop, and otherwise ruin your dayKey FeaturesDiscover how hackers rely on misdirection and deep fakes to fool even the best security systemsRetain the usefulness of your data by detecting unwanted and invalid modificationsDevelop application code to meet the security requirements related to machine learningBook DescriptionBusinesses are leveraging the power of AI to make undertakings that used to be complicated and pricy much easier, faster, and cheaper. The first part of this book will explore these processes in more depth, which will help you in understanding the role security plays in machine learning.As you progress to the second part, you'll learn more about the environments where ML is commonly used and dive into the security threats that plague them using code, graphics, and real-world references.The next part of the book will guide you through the process of detecting hacker behaviors in the modern computing environment, where fraud takes many forms in ML, from gaining sales through fake reviews to destroying an adversary's reputation. Once you've understood hacker goals and detection techniques, you'll learn about the ramifications of deep fakes, followed by mitigation strategies.This book also takes you through best practices for embracing ethical data sourcing, which reduces the security risk associated with data. You'll see how the simple act of removing personally identifiable information (PII) from a dataset lowers the risk of social engineering attacks.By the end of this machine learning book, you'll have an increased awareness of the various attacks and the techniques to secure your ML systems effectively.What you will learnExplore methods to detect and prevent illegal access to your systemImplement detection techniques when access does occurEmploy machine learning techniques to determine motivationsMitigate hacker access once security is breachedPerform statistical measurement and behavior analysisRepair damage to your data and applicationsUse ethical data collection methods to reduce security risksWho this book is forWhether you're a data scientist, researcher, or manager working with machine learning techniques in any aspect, this security book is a must-have. While most resources available on this topic are written in a language more suitable for experts, this guide presents security in an easy-to-understand way, employing a host of diagrams to explain concepts to visual learners. While familiarity with machine learning concepts is assumed, knowledge of Python and programming in general will be useful.
R 1,596.00
Machine Design with CAD and Optimization
MACHINE DESIGN WITH CAD AND OPTIMIZATION A guide to the new CAD and optimization tools and skills to generate real design synthesis of machine elements and systemsMachine Design with CAD and Optimization offers the basic tools to design or synthesize machine elements and assembly of prospective elements in systems or products. It contains the necessary knowledge base, computer aided design, and optimization tools to define appropriate geometry and material selection of machine elements. A comprehensive text for each element includes: a chart, excel sheet, a MATLAB® program, or an interactive program to calculate the element geometry to guide in the selection of the appropriate material.The book contains an introduction to machine design and includes several design factors for consideration. It also offers information on the traditional rigorous design of machine elements. In addition, the author reviews the real design synthesis approach and offers material about stresses and material failure due to applied loading during intended performance. This comprehensive resource also contains an introduction to computer aided design and optimization. This important book:Provides the tools to perform a new direct design synthesis rather than design by a process of repeated analysisContains a guide to knowledge-based design using CAD tools, software, and optimum component design for the new direct design synthesis of machine elementsAllows for the initial suitable design synthesis in a very short timeDelivers information on the utility of CAD and OptimizationAccompanied by an online companion site including presentation filesWritten for students of engineering design, mechanical engineering, and automotive design. Machine Design with CAD and Optimization contains the new CAD and Optimization tools and defines the skills needed to generate real design synthesis of machine elements and systems on solid ground for better products and systems.
R 4,557.00
Life Engineering
Maschinelle Intelligenz verändert unser Leben. Der Datenverkehr im Internet, digitale Assistenten sowie Sensoren in Haushalten, Autos und Wearables liefern Daten, die von Unternehmen gesammelt und genutzt werden, um Muster des menschlichen Verhaltens zu extrahieren. Es ist an der Zeit, zu entscheiden, ob diese Entwicklung dem Wohle der Menschen zugutekommt oder nur zur Ansammlung von Kapital und Macht ohne Rücksicht auf die menschliche Lebensqualität führt.Dieses Buch integriert die Perspektiven verschiedener Disziplinen – Informatik, Wirtschafts- und Sozialwissenschaften, Politikwissenschaft, Psychologie, Philosophie, Neurowissenschaften, Ethik und Religion. Hubert Österle fördert damit die Debatte über die Zukunft von Mensch und Maschine, über Glück und Evolution sowie über die großen Veränderungen, die die digitale Technologie mit sich bringt. Das Buch ist ein Manifest, das zur Gründung einer neuen –integrierten – Disziplin aufruft: Life Engineering.Der InhaltLeben mit maschineller IntelligenzLebensassistenz im Jahre 2030Maschinelle Intelligenz im Jahre 2030LebensqualitätEvolution mit LebensqualitätKonsequenzen für Individuen, Unternehmen und GesellschaftDisziplin Life EngineeringAgenda für das Life EngineeringStimmen zum BuchDie maschinelle Intelligenz ist eine Herausforderung für Menschen, Unternehmen und Politik. Das Buch liefert eine gründliche Analyse der technologischen Trends und ihrer Chancen und Gefahren für die Lebensqualität. Ausgehend von der Maxime des Glücks des Homo Digitalis formuliert Österle teilweise außerordentlich provokative Fragen wie etwa nach dem Wert der Privatheit. Gerade derartige Fragen und die vom Mainstream abweichenden Antworten auf Basis nachvollziehbarer Überlegungen machen es zur Pflichtlektüre.Thomas Hess, Professor und Direktor des Instituts für Wirtschaftsinformatik und neue Medien der Ludwig-Maximilians-Universität München und Sprecher des Internet Business ClustersDieses Buch ist eine äußerst realistische Aufarbeitung technologischer Trends und ihrer Konsequenzen für die Lebensqualität der Menschen. Die aufgeworfenen Fragen und die Versuche rationaler Antworten widersprechen vielen der heute breit akzeptierten Ansichten, insbesondere zur Autonomie des Menschen. Ob man zustimmt oder nicht, den Herausforderungen für das Individuum, die Unternehmen, die Politik und die Zivilgesellschaft müssen wir uns stellen.Henning Kagermann, ehemaliger CEO der SAP AG sowie Vorsitzender der Nationalen Plattform Elektromobilität, des Arbeitskreises Industrie 4.0 und des Fachforums Autonome Systeme
R 570.00
R 244.00
Digital Technologies for Engineering Construction Information Productivity
Digital Technologies for Engineering Construction Information Productivity goes beyond other digital construction books by examining how emerging digital construction technologies and other popular technologies developed by, for example, Microsoft can be used in improving the productivity of construction information.The book discusses both the theory and practice through use-case illustrations in integrated software environments and successfully blends applications and workflows of construction technologies with more common and non-industry-specific software systems. It seeks to unleash the power of readily available digital technologies in optimizing the productivity of construction project information management.This book is essential for students, academics, educators, construction professionals, and construction software developers. For students, the book provides a solid foundation in understanding digital construction technologies including building information modelling (BIM) and some selected Microsoft Products and their applications in managing construction project information. For academics and educators, it will provide insights into research niches around integration of the different digital technologies and serve as a useful text for teaching at undergraduate and postgraduate levels in Architecture, Engineering, and Construction (AEC) subjects. Professionals will find this useful for the adoption of digital technologies in their own practice while software developers will find this beneficial in the development of interoperability software for efficient information exchange between the various software systems.
R 10,751.26
Ecological Wisdom Inspired Restoration Engineering
This book focuses on ecological wisdom inspired restoration engineering through theories, hypotheses, policies, practical understanding, and case studies. Understanding nature’s processes is a prerequisite for the healthy and sustainable functioning of a habitable Earth. As such, the book provides a guide for readers seeking to understand and build sustainable, urban socio-ecological systems using restoration technologies based on wisdom. Motivated by recent rapid advances in restoration engineering, such as the role of green building materials in urban infrastructures, and developing sustainable landscapes to benefit the environment, economy and communities, it is an essential reference on the most promising innovative technologies. It discusses engineering methods and practices in the restoration of soil, water, heritage sites, and other ecosystems, as well as the development and applications of green building materials. It presents a holistic and systematic approach that utilizes natural resources and the concept of ecological wisdom to reap sustainable environmental, economic and social benefits to fulfill the concept of living in harmony with nature. This book is a valuable resource for civil- and environmental engineering researchers as well as organizations engaged in eco-restoration practices.
R 5,038.02
Advances in Power and Control Engineering
The book features selected high-quality papers presented at the International Conference on Computing, Power and Communication Technologies 2019 (GUCON 2019), organized by Galgotias University, India, in September 2019. Divided into three sections, the book discusses various topics in the fields of power electronics and control engineering, power and energy systems, and machines and renewable energy. This interesting compilation is a valuable resource for researchers, engineers and students.
R 5,284.63
