Computational and Intelligent Systems – serie

This book presents the basics and recent advancements in natural language processing and information retrieval in a single volume. It will serve as an ideal reference text for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology. This text emphasizes the existing problem domains and possible new directions in natural language processing and information retrieval. It discusses the importance of information retrieval with the integration of machine learning, deep learning, and word embedding. This approach supports the quick evaluation of real-time data. It covers important topics including rumor detection techniques, sentiment analysis using graph-based techniques, social media data analysis, and language-independent text mining.Features:• Covers aspects of information retrieval in different areas including healthcare, data analysis, and machine translation• Discusses recent advancements in language- and domain-independent information extraction from textual and/or multimodal data• Explains models including decision making, random walk, knowledge graphs, word embedding, n-grams, and frequent pattern mining• Provides integrated approaches of machine learning, deep learning, and word embedding for natural language processing• Covers latest datasets for natural language processing and information retrieval for social media like TwitterThe text is primarily written for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology.

This book presents the basics and recent advancements in natural language processing and information retrieval in a single volume. It will serve as an ideal reference text for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology. This text emphasizes the existing problem domains and possible new directions in natural language processing and information retrieval. It discusses the importance of information retrieval with the integration of machine learning, deep learning, and word embedding. This approach supports the quick evaluation of real-time data. It covers important topics including rumor detection techniques, sentiment analysis using graph-based techniques, social media data analysis, and language-independent text mining.Features:• Covers aspects of information retrieval in different areas including healthcare, data analysis, and machine translation• Discusses recent advancements in language- and domain-independent information extraction from textual and/or multimodal data• Explains models including decision making, random walk, knowledge graphs, word embedding, n-grams, and frequent pattern mining• Provides integrated approaches of machine learning, deep learning, and word embedding for natural language processing• Covers latest datasets for natural language processing and information retrieval for social media like TwitterThe text is primarily written for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology.

This text covers the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of mechanical engineering. It covers important topics including computational fluid dynamics for advanced thermal systems, optimizing performance parameters by Fuzzy logic, design of experiments, numerical simulation, and optimizing flow network by artificial intelligence. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields including industrial, manufacturing, computer, mechanical, and materials science. The book- Introduces novel soft computing techniques needed to address sustainable solutions for the issues related to materials and manufacturing process. Provides perspectives for the design, development, and commissioning of intelligent applications. Discusses the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of sustainable engineering. Explores future generation sustainable and intelligent monitoring techniques beneficial for mechanical engineering. Covers implementation of soft computing in the various areas of engineering applications. This book introduces soft computing techniques in addressing sustainable solutions for the issues related to materials and manufacturing process. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields including industrial, manufacturing, thermal, fluid, and materials science.

This text covers the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of mechanical engineering. It covers important topics including computational fluid dynamics for advanced thermal systems, optimizing performance parameters by Fuzzy logic, design of experiments, numerical simulation, and optimizing flow network by artificial intelligence. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields including industrial, manufacturing, computer, mechanical, and materials science. The book- Introduces novel soft computing techniques needed to address sustainable solutions for the issues related to materials and manufacturing process. Provides perspectives for the design, development, and commissioning of intelligent applications. Discusses the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of sustainable engineering. Explores future generation sustainable and intelligent monitoring techniques beneficial for mechanical engineering. Covers implementation of soft computing in the various areas of engineering applications. This book introduces soft computing techniques in addressing sustainable solutions for the issues related to materials and manufacturing process. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields including industrial, manufacturing, thermal, fluid, and materials science.

The text comprehensively discusses computational models including artificial neural networks, agent-based models, and decision field theory for reliability engineering. It will serve as an ideal reference text for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, computer engineering, and materials science. Discusses the development of sustainable materials using metaheuristic approaches. Covers computational models such as agent-based models, ontology, and decision field theory for reliability engineering. Presents swarm intelligence methods such as ant colony optimization, particle swarm optimization, and grey wolf optimization for solving the manufacturing process. Include case studies for industrial optimizations. Explores the use of computational optimization for reliability and maintainability theory. The text covers swarm intelligence techniques including ant colony optimization, particle swarm optimization, cuckoo search, and genetic algorithms for solving complex industrial problems of the manufacturing industry as well as predicting reliability, maintainability, and availability of several industrial components.

The text comprehensively discusses computational models including artificial neural networks, agent-based models, and decision field theory for reliability engineering. It will serve as an ideal reference text for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, computer engineering, and materials science. Discusses the development of sustainable materials using metaheuristic approaches. Covers computational models such as agent-based models, ontology, and decision field theory for reliability engineering. Presents swarm intelligence methods such as ant colony optimization, particle swarm optimization, and grey wolf optimization for solving the manufacturing process. Include case studies for industrial optimizations. Explores the use of computational optimization for reliability and maintainability theory. The text covers swarm intelligence techniques including ant colony optimization, particle swarm optimization, cuckoo search, and genetic algorithms for solving complex industrial problems of the manufacturing industry as well as predicting reliability, maintainability, and availability of several industrial components.

This book comprehensively discusses the modeling of real-world industrial problems and innovative optimization techniques such as heuristics, finite methods, operation research techniques, intelligent algorithms, and agent- based methods.Discusses advanced techniques such as key cell, Mobius inversion, and zero suffix techniques to find initial feasible solutions to optimization problemsProvides a useful guide toward the development of a sustainable model for disaster managementPresents optimized hybrid block method techniques to solve mathematical problems existing in the industriesCovers mathematical techniques such as Laplace transformation, stochastic process, and differential techniques related to reliability theoryHighlights application on smart agriculture, smart healthcare, techniques for disaster management, and smart manufacturingAdvanced Mathematical Techniques in Computational and Intelligent Systems is primarily written for graduate and senior undergraduate students, as well as academic researchers in electrical engineering, electronics and communications engineering, computer engineering, and mathematics.

This book comprehensively discusses the modeling of real-world industrial problems and innovative optimization techniques such as heuristics, finite methods, operation research techniques, intelligent algorithms, and agent- based methods.Discusses advanced techniques such as key cell, Mobius inversion, and zero suffix techniques to find initial feasible solutions to optimization problemsProvides a useful guide toward the development of a sustainable model for disaster managementPresents optimized hybrid block method techniques to solve mathematical problems existing in the industriesCovers mathematical techniques such as Laplace transformation, stochastic process, and differential techniques related to reliability theoryHighlights application on smart agriculture, smart healthcare, techniques for disaster management, and smart manufacturingAdvanced Mathematical Techniques in Computational and Intelligent Systems is primarily written for graduate and senior undergraduate students, as well as academic researchers in electrical engineering, electronics and communications engineering, computer engineering, and mathematics.

The book provides a comprehensive discussion for utilizing computational models such as artificial neural networks, agent-based models, and decision field theory, for reliability engineering. It further presents optimization solutions for smart and secure healthcare services. The text showcases how to predict the failure and repair rates of healthcare subsystems using computational intelligence.This book:Explores how data-driven methodologies and advanced computational intelligence are revolutionizing the healthcare industry, promoting efficiency, accessibility, and sustainabilityHighlights the pivotal role that big data analytics plays in harnessing vast amounts of patient records, clinical information, and real-time medical data to provide timely insights for healthcare professionals and policymakersDiscusses the integration of artificial intelligence and machine learning techniques in healthcare, with a focus on revolutionizing disease detection, treatment planning, and resource allocationLays the foundation for developing sustainable healthcare systems that are adaptable to long-term challenges, such as population growth, emerging diseases, and resource constraintsCovers computational intelligence techniques, like fuzzy logic, neural networks, and evolutionary computations, emphasizing their role in solving complex, data-driven healthcare problemsIncludes topics like data management, visualization, protection, and complex adaptive systems, as well as hybrid computational intelligence techniques for synergistic problem-solving strategiesThis volume will serve as an ideal text for senior undergraduates, graduate students, and academic researchers in fields including electrical engineering, electronics and communications engineering, computer engineering, and mathematics.

The book provides a comprehensive discussion for utilizing computational models such as artificial neural networks, agent-based models, and decision field theory, for reliability engineering. It further presents optimization solutions for smart and secure healthcare services. The text showcases how to predict the failure and repair rates of healthcare subsystems using computational intelligence.This book:Explores how data-driven methodologies and advanced computational intelligence are revolutionizing the healthcare industry, promoting efficiency, accessibility, and sustainabilityHighlights the pivotal role that big data analytics plays in harnessing vast amounts of patient records, clinical information, and real-time medical data to provide timely insights for healthcare professionals and policymakersDiscusses the integration of artificial intelligence and machine learning techniques in healthcare, with a focus on revolutionizing disease detection, treatment planning, and resource allocationLays the foundation for developing sustainable healthcare systems that are adaptable to long-term challenges, such as population growth, emerging diseases, and resource constraintsCovers computational intelligence techniques, like fuzzy logic, neural networks, and evolutionary computations, emphasizing their role in solving complex, data-driven healthcare problemsIncludes topics like data management, visualization, protection, and complex adaptive systems, as well as hybrid computational intelligence techniques for synergistic problem-solving strategiesThis volume will serve as an ideal text for senior undergraduates, graduate students, and academic researchers in fields including electrical engineering, electronics and communications engineering, computer engineering, and mathematics.

This book discusses the components and foundations of precision agriculture, followed by smart farming practices, sustainable development in precision agriculture, and use of artificial intelligence techniques in the field of agriculture.Features:Discusses remote sensing techniques, global positioning system, robotics, and unmanned aerial vehicles in precision agriculture.Covers sustainable development in precision agriculture, data management and analytics, and variable rate technology.Highlights the implementation of artificial intelligence techniques, and use of prediction algorithms in improving crop efficiency.Presents machine learning, deep learning, and computer vision applications in precision agriculture.Showcases case studies on cotton crops, tea pests, and crop recommendations.The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, smart grids, environmental engineering, agricultural engineering, computer science and engineering.

Soft robotics is an emerging field that involves the development and application of robots and robotic systems made from soft and flexible materials. Soft Robotics for Medical and Healthcare Applications discusses the use of soft robotics in minimally invasive vascular surgery, for clubfoot, and filariasis leg.The title:Discusses soft robot design which is helpful for researchers and students to design the mechanisms for problems like filariasis leg, and personalized rehabilitation devicesCovers metal additive manufacturing processes used for soft robot parts printingExplains design, actuation, manufacturing, and analysis of soft robots for healthcare applicationsExplores 3D and 4D printing for soft robotics, data-driven soft robotics, and the use of soft robotics in drug deliveryPresents case studies including the creation of custom filariasis limbs and the application of soft robots in minimally invasive vascular surgeryThe text is primarily written for senior undergraduates, graduate students, and academic researchers in fields including electrical engineering, electronics and communications engineering, computer engineering, and biomedical engineering.

Soft robotics is an emerging field that involves the development and application of robots and robotic systems made from soft and flexible materials. Soft Robotics for Medical and Healthcare Applications discusses the use of soft robotics in minimally invasive vascular surgery, for clubfoot, and filariasis leg.The title:Discusses soft robot design which is helpful for researchers and students to design the mechanisms for problems like filariasis leg, and personalized rehabilitation devicesCovers metal additive manufacturing processes used for soft robot parts printingExplains design, actuation, manufacturing, and analysis of soft robots for healthcare applicationsExplores 3D and 4D printing for soft robotics, data-driven soft robotics, and the use of soft robotics in drug deliveryPresents case studies including the creation of custom filariasis limbs and the application of soft robots in minimally invasive vascular surgeryThe text is primarily written for senior undergraduates, graduate students, and academic researchers in fields including electrical engineering, electronics and communications engineering, computer engineering, and biomedical engineering.

Smart cyber‑physical systems (SCPS) are revolutionizing the interaction between the physical and digital realms, driving innovation across diverse fields. This book provides an extensive overview of cutting‑edge SCPS technologies, highlighting their applications, challenges, and transformative potential. Designed for researchers, professionals, and students, it offers foundational insights and advanced applications in urban planning, healthcare, transportation, finance, and cybersecurity. It also bridges the gap between theory and practice through real‑world case studies and in‑depth analysis, showcasing how SCPS address critical global challenges. This book:Provides a comprehensive introduction to SCPS, their components, and their applications in various domains and explores their role in enabling sustainable smart cities and urban planningProvides advanced SCPS‑based solutions for optimizing supply chain logistics and route planning and real‑world applications of SCPS in healthcare, including wearable technology and remote patient monitoring, and financial modeling, comparing investment indices using advanced techniquesDiscusses the integration of artificial intelligence and machine learning in autonomous vehicle systems and transportationAnalyzes cybersecurity challenges in cryptocurrency and blockchain ecosystemsFocuses on innovations in energy management, including smart grids and sustainable practices powered by SCPS, and explores adaptive human–machine interaction frameworks for enhanced decision‑makingThis book serves as a vital resource for understanding the transformative power of SCPS and inspires further research and development in this dynamic and rapidly evolving field.

This book serves as a comprehensive guide, covering the fundamentals of cloud computing, advanced concepts, and practical applications.Discusses cyber-physical systems, cloud integration for environmental management, and cloud security intelligence systems for sustainable operationsPresents case studies based on computational intelligence-based optimization for sustainable operations and cloud integrationEmphasizes how cloud computing revolutionizes traditional processes, enabling direct input of assembly details into a computation model, streamlining development cycles, and reducing costsBridges the gap between theory and practice by offering guidelines on problem encoding and implementation strategies, empowering readers to apply their acquired knowledge to solve complex industrial problemsCovers wireless security in the cloud era, mechatronics and cloud integration, and cloud-enabled manufacturing for eco-friendly operationsThe text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer engineering, and information technology.