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Computational Intelligence Methods for Bioinformatics and Biostatistics: 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, Revised Selected Papers (Lecture Notes in Computer Science #10477)
by David Gilbert Roberto Tagliaferri Andrea Bracciali Giulio CaravagnaThis book constitutes the thoroughly refereed post-conference proceedings of the 10th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2013, held in Nice, France in June 2013. The 19 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on bioinformatics, biostatistics, knowledge based medicine, and data integration and analysis in omic-science.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 15th International Meeting, CIBB 2018, Caparica, Portugal, September 6–8, 2018, Revised Selected Papers (Lecture Notes in Computer Science #11925)
by Maria Raposo Paulo Ribeiro Angelo Ciaramella Susana Sério Antonino StaianoThis book constitutes the thoroughly refereed post-conference proceedings of the 15th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics., CIBB 2018, held in Caparica, Portugal, in September 2018. The 32 revised full papers were carefully reviewed and selected from 51 submissions. The papers present current trends at the edge of computer and life sciences, the application of computational intelligence to a system and synthetic biology and the consequent impact on innovative medicine were presented. Theoretical and experimental biologists also presented novel challenges and fostered multidisciplinary collaboration aiming to blend theory and practice, where the founding theories of the techniques used for modelling and analyzing biological systems are investigated and used for practical applications and the supporting technologies.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 12th International Meeting, CIBB 2015, Naples, Italy, September 10-12, 2015, Revised Selected Papers (Lecture Notes in Computer Science #9874)
by Stefano Rovetta Claudia Angelini Paola M. V. RancoitaThis book constitutes the thoroughly refereed post-conference proceedings of the 12th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2015, held in Naples, Italy, in September, 2015. The 21 revised full papers presented were carefully reviewed and selected from 24 submissions. They present problems concerning computational techniques in bioinformatics, systems biology and medical informatics discussing cutting edge methodologies and accelerate life science discoveries, as well as novel challenges with an high impact on molecular biology and translational medicine.
Computational Intelligence Methods for Green Technology and Sustainable Development: Proceedings of the International Conference GTSD2024, Volume 2 (Lecture Notes in Networks and Systems #1199)
by Yo-Ping Huang Wen-June Wang Hieu-Giang Le An-Quoc HoangThis book is presented in two volumes, featuring peer-reviewed research papers from the 7th International Conference on Green Technology and Sustainable Development (GTSD), held in Ho Chi Minh City, Vietnam, from July 25 to 26, 2024. It highlights original research by experts from both academia and industry, centered on the theme of "Green Technology and Sustainable Development in the Industrial Revolution 4.0." The book underscores the critical importance of sustainability in education, technology, and economic development, while also showcasing the vital role of technological innovation in creating a greener future. The papers documented in this book cover a broad range of topics, including renewable energy systems, smart grids, artificial intelligence, robotics and intelligent systems, and computational intelligence, all with a focus on sustainable development, climate change mitigation, and environmental policy. These studies showcase cutting-edge technologies and innovative ideas related to green technology, offering actionable insights for advancing sustainable development across various sectors. The authors present research based on both experimental and numerical methods, offering solutions to current problems and optimizing existing methods. The insights and findings provided are valuable for industry experts, research institutions, universities, and anyone interested in advancing global sustainable development.
Computational Intelligence Methods for Green Technology and Sustainable Development: Proceedings of the International Conference GTSD2024, Volume 1 (Lecture Notes in Networks and Systems #1195)
by Yo-Ping Huang Wen-June Wang Hieu-Giang Le An-Quoc HoangThis book is presented in two volumes, featuring peer-reviewed research papers from the 7th International Conference on Green Technology and Sustainable Development (GTSD), held in Ho Chi Minh City, Vietnam, from July 25 to 26, 2024. It highlights original research by experts from both academia and industry, centered on the theme of "Green Technology and Sustainable Development in the Industrial Revolution 4.0." The book underscores the critical importance of sustainability in education, technology, and economic development, while also showcasing the vital role of technological innovation in creating a greener future. The papers documented in this book cover a broad range of topics, including renewable energy systems, smart grids, artificial intelligence, robotics and intelligent systems, and computational intelligence, all with a focus on sustainable development, climate change mitigation, and environmental policy. These studies showcase cutting-edge technologies and innovative ideas related to green technology, offering actionable insights for advancing sustainable development across various sectors. The authors present research based on both experimental and numerical methods, offering solutions to current problems and optimizing existing methods. The insights and findings provided are valuable for industry experts, research institutions, universities, and anyone interested in advancing global sustainable development.
Computational Intelligence Methods for Green Technology and Sustainable Development: Proceedings of the International Conference GTSD2022 (Lecture Notes in Networks and Systems #567)
by Yo-Ping Huang Wen-June Wang Hoang An Quoc Hieu-Giang Le Hoai-Nam QuachThis book provides readers with peer-reviewed research papers presented at the 6th International Conference on Green Technology and Sustainable Development (GTSD) held in Nha Trang City, Vietnam, from July 29 to 30, 2022. The book is original work of researchers from academia and industry focusing on the theme “Green technology and sustainable development in Industrial Revolution 4.0” not only to raise awareness of the vital importance of sustainability in education, technology, and economic development, but also to highlight the essential roles of technology innovation for the green future. The book presents a wide range of research aspects including energy engineering, electric power systems, renewable energy systems, automatic control engineering, robotics, vehicle engineering, material engineering, construction engineering, mechanical engineering, vibrations, computational analysis, numerical investigation, system failure, technological solutions in health care, and so on. Through thorough research basing on both experimental and numerical methods, the authors feature either solutions for existing problems or optimization and improvement for performance of existing methods. The collected research results could be useful alternatives and implications for industry experts, research institutions, universities, and all others who share a common interest in the future global sustainable development.
Computational Intelligence Methods for Super-Resolution in Image Processing Applications
by Anand Deshpande Vania V. Estrela Navid RazmjooyThis book explores the application of deep learning techniques within a particularly difficult computational type of computer vision (CV) problem ─ super-resolution (SR). The authors present and discuss ways to apply computational intelligence (CI) methods to SR. The volume also explores the possibility of using different kinds of CV techniques to develop and enhance the tools/processes related to SR. The application areas covered include biomedical engineering, healthcare applications, medicine, histology, and material science. The book will be a valuable reference for anyone concerned with multiple multimodal images, especially professionals working in remote sensing, nanotechnology and immunology at research institutes, healthcare facilities, biotechnology institutions, agribusiness services, veterinary facilities, and universities.
Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis (Studies in Computational Intelligence #923)
by Khalid RazaThe novel coronavirus disease 2019 (COVID-19) pandemic has posed a major threat to human life and health. This book is beneficial for interdisciplinary students, researchers, and professionals to understand COVID-19 and how computational intelligence can be used for the purpose of surveillance, control, prevention, prediction, diagnosis, and potential treatment of the disease. The book contains different aspects of COVID-19 that includes fundamental knowledge, epidemic forecast models, surveillance and tracking systems, IoT- and IoMT-based integrated systems for COVID-19, social network analysis systems for COVID-19, radiological images (CT, X-ray) based diagnosis system, and computational intelligence and in silico drug design and drug repurposing methods against COVID-19 patients. The contributing authors of this volume are experts in their fields and they are from various reputed universities and institutions across the world. This volume is a valuable and comprehensive resource for computer and data scientists, epidemiologists, radiologists, doctors, clinicians, pharmaceutical professionals, along with graduate and research students of interdisciplinary and multidisciplinary sciences.
Computational Intelligence Paradigms: Theory & Applications using MATLAB
by S. Sumathi Surekha PaneerselvamOffering a wide range of programming examples implemented in MATLAB, Computational Intelligence Paradigms: Theory and Applications Using MATLAB presents theoretical concepts and a general framework for computational intelligence (CI) approaches, including artificial neural networks, fuzzy systems, evolutionary computation, genetic algorithms and pr
Computational Intelligence Paradigms for Optimization Problems Using MATLAB®/SIMULINK®
by S. Sumathi L. Ashok Kumar Surekha. PConsidered one of the most innovative research directions, computational intelligence (CI) embraces techniques that use global search optimization, machine learning, approximate reasoning, and connectionist systems to develop efficient, robust, and easy-to-use solutions amidst multiple decision variables, complex constraints, and tumultuous environments. CI techniques involve a combination of learning, adaptation, and evolution used for intelligent applications. Computational Intelligence Paradigms for Optimization Problems Using MATLAB®/ Simulink® explores the performance of CI in terms of knowledge representation, adaptability, optimality, and processing speed for different real-world optimization problems. Focusing on the practical implementation of CI techniques, this book: Discusses the role of CI paradigms in engineering applications such as unit commitment and economic load dispatch, harmonic reduction, load frequency control and automatic voltage regulation, job shop scheduling, multidepot vehicle routing, and digital image watermarking Explains the impact of CI on power systems, control systems, industrial automation, and image processing through the above-mentioned applications Shows how to apply CI algorithms to constraint-based optimization problems using MATLAB® m-files and Simulink® models Includes experimental analyses and results of test systems Computational Intelligence Paradigms for Optimization Problems Using MATLAB®/ Simulink® provides a valuable reference for industry professionals and advanced undergraduate, postgraduate, and research students.
Computational Intelligence Paradigms in Economic and Financial Decision Making (Intelligent Systems Reference Library #99)
by Marina RestaThe book focuses on a set of cutting-edge research techniques, highlighting the potential of soft computing tools in the analysis of economic and financial phenomena and in providing support for the decision-making process. In the first part the textbook presents a comprehensive and self-contained introduction to the field of self-organizing maps, elastic maps and social network analysis tools and provides necessary background material on the topic, including a discussion of more recent developments in the field. In the second part the focus is on practical applications, with particular attention paid to budgeting problems, market simulations, and decision-making processes, and on how such problems can be effectively managed by developing proper methods to automatically detect certain patterns. The book offers a valuable resource for both students and practitioners with an introductory-level college math background.
Computational Intelligence Techniques and Their Applications to Software Engineering Problems (Computational Intelligence Techniques)
by Ankita Bansal Abha Jain Sarika Jain Vishal Jain Ankur ChoudharyComputational Intelligence Techniques and Their Applications to Software Engineering Problems focuses on computational intelligence approaches as applicable in varied areas of software engineering such as software requirement prioritization, cost estimation, reliability assessment, defect prediction, maintainability and quality prediction, size estimation, vulnerability prediction, test case selection and prioritization, and much more. The concepts of expert systems, case-based reasoning, fuzzy logic, genetic algorithms, swarm computing, and rough sets are introduced with their applications in software engineering. The field of knowledge discovery is explored using neural networks and data mining techniques by determining the underlying and hidden patterns in software data sets. Aimed at graduate students and researchers in computer science engineering, software engineering, information technology, this book: Covers various aspects of in-depth solutions of software engineering problems using computational intelligence techniques Discusses the latest evolutionary approaches to preliminary theory of different solve optimization problems under software engineering domain Covers heuristic as well as meta-heuristic algorithms designed to provide better and optimized solutions Illustrates applications including software requirement prioritization, software cost estimation, reliability assessment, software defect prediction, and more Highlights swarm intelligence-based optimization solutions for software testing and reliability problems
Computational Intelligence Techniques for Comparative Genomics: Dedicated to Prof. Allam Appa Rao on the Occasion of His 65th Birthday (SpringerBriefs in Applied Sciences and Technology)
by Vinit Kumar Gunjan Naresh Babu MuppalaneniThis Brief highlights Informatics and related techniques to Computer Science Professionals, Engineers, Medical Doctors, Bioinformatics researchers and other interdisciplinary researchers. Chapters include the Bioinformatics of Diabetes and several computational algorithms and statistical analysis approach to effectively study the disorders and possible causes along with medical applications.
Computational Intelligence Techniques for Trading and Investment (Routledge Advances in Experimental and Computable Economics #6)
by Christian Dunis Spiros Likothanassis Andreas Karathanasopoulos Georgios Sermpinis Konstantinos TheofilatosComputational intelligence, a sub-branch of artificial intelligence, is a field which draws on the natural world and adaptive mechanisms in order to study behaviour in changing complex environments. This book provides an interdisciplinary view of current technological advances and challenges concerning the application of computational intelligence techniques to financial time-series forecasting, trading and investment. The book is divided into five parts. The first part introduces the most important computational intelligence and financial trading concepts, while also presenting the most important methodologies from these different domains. The second part is devoted to the application of traditional computational intelligence techniques to the fields of financial forecasting and trading, and the third part explores the applications of artificial neural networks in these domains. The fourth part delves into novel evolutionary-based hybrid methodologies for trading and portfolio management, while the fifth part presents the applications of advanced computational intelligence modelling techniques in financial forecasting and trading. This volume will be useful for graduate and postgraduate students of finance, computational finance, financial engineering and computer science. Practitioners, traders and financial analysts will also benefit from this book.
Computational Intelligence Techniques in Diagnosis of Brain Diseases (SpringerBriefs in Applied Sciences and Technology)
by Xiao-Zhi Gao Naresh Babu Muppalaneni Sasikumar GurumoorthyThis book highlights a new biomedical signal processing method of extracting a specific underlying signal from possibly noisy multi-channel recordings, and shows that the method is suitable for extracting independent components from the measured electroencephalogram (EEG) signal. The system efficiently extracts memory spindles and is also effective in Alzheimer seizures. Current developments in computer hardware and signal processing have made it possible for EEG signals or "brain waves" to communicate between humans and computers - an area that can be extended for use in this domain.
Computational Intelligence Techniques in Earth and Environmental Sciences
by Saumitra Mukherjee Xuan Zhu Tanvir Islam Prashant K. Srivastava Manika GuptaComputational intelligence techniques have enjoyed growing interest in recent decades among the earth and environmental science research communities for their powerful ability to solve and understand various complex problems and develop novel approaches toward a sustainable earth. This book compiles a collection of recent developments and rigorous applications of computational intelligence in these disciplines. Techniques covered include artificial neural networks, support vector machines, fuzzy logic, decision-making algorithms, supervised and unsupervised classification algorithms, probabilistic computing, hybrid methods and morphic computing. Further topics given treatment in this volume include remote sensing, meteorology, atmospheric and oceanic modeling, climate change, environmental engineering and management, catastrophic natural hazards, air and environmental pollution and water quality. By linking computational intelligence techniques with earth and environmental science oriented problems, this book promotes synergistic activities among scientists and technicians working in areas such as data mining and machine learning. We believe that a diverse group of academics, scientists, environmentalists, meteorologists and computing experts with a common interest in computational intelligence techniques within the earth and environmental sciences will find this book to be of great value.
Computational Intelligence Techniques in Health Care (SpringerBriefs in Applied Sciences and Technology)
by P. V. Lakshmi Wengang Zhou P. SatheeshThis book presentsresearch on emerging computational intelligence techniques and tools, with aparticular focus on newtrends and applications in health care. Healthcare is a multi-faceted domain,which incorporates advanced decision-making, remote monitoring, healthcarelogistics, operational excellence and modern information systems. In recentyears, the use of computationalintelligence methods to address the scale and the complexity of the problems in healthcarehas been investigated. This book discusses various computationalintelligence methods that are implemented in applications in different areas of healthcare. It includes contributions bypractitioners, technology developers and solution providers.
Computational Intelligent Data Analysis for Sustainable Development (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
by Ting Yu Nitesh V. Chawla Simeon SimoffGoing beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development present
A Computational Introduction to Digital Image Processing
by Alasdair McAndrewHighly Regarded, Accessible Approach to Image Processing Using Open-Source and Commercial SoftwareA Computational Introduction to Digital Image Processing, Second Edition explores the nature and use of digital images and shows how they can be obtained, stored, and displayed. Taking a strictly elementary perspective, the book only covers topics that
A Computational Introduction To Digital Image Processing, Second Edition
by Alasdair McandrewHighly Regarded, Accessible Approach to Image Processing Using Open-Source and Commercial Software A Computational Introduction to Digital Image Processing, Second Editionexplores the nature and use of digital images and shows how they can be obtained, stored, and displayed. Taking a strictly elementary perspective, the book only covers topics that involve simple mathematics yet offer a very broad and deep introduction to the discipline. New to the Second Edition This second edition provides users with three different computing options. Along with MATLAB®, this edition now includes GNU Octave and Python. Users can choose the best software to fit their needs or migrate from one system to another. Programs are written as modular as possible, allowing for greater flexibility, code reuse, and conciseness. This edition also contains new images, redrawn diagrams, and new discussions of edge-preserving blurring filters, ISODATA thresholding, Radon transform, corner detection, retinex algorithm, LZW compression, and other topics. Principles, Practices, and Programming Based on the author's successful image processing courses, this bestseller is suitable for classroom use or self-study. In a straightforward way, the text illustrates how to implement imaging techniques in MATLAB, GNU Octave, and Python. It includes numerous examples and exercises to give students hands-on practice with the material.
Computational Kinematics: Proceedings of the 6th International Workshop on Computational Kinematics (CK2013) (Mechanisms and Machine Science #15)
by Federico Thomas Alba Pérez GraciaComputational kinematics is an enthralling area of science with a rich spectrum of problems at the junction of mechanics, robotics, computer science, mathematics, and computer graphics. The covered topics include design and optimization of cable-driven robots, analysis of parallel manipulators, motion planning, numerical methods for mechanism calibration and optimization, geometric approaches to mechanism analysis and design, synthesis of mechanisms, kinematical issues in biomechanics, construction of novel mechanical devices, as well as detection and treatment of singularities. The results should be of interest for practicing and research engineers as well as Ph. D. students from the fields of mechanical and electrical engineering, computer science, and computer graphics.
Computational Kinematics: Proceedings of the 7th International Workshop on Computational Kinematics that was held at Futuroscope-Poitiers, France, in May 2017 (Mechanisms and Machine Science #50)
by Saïd Zeghloul Med Amine Laribi Lotfi RomdhaneThis is the proceedings of IFToMM CK 2017, the 7th International Workshop on Computational Kinematics that was held in Futuroscope-Poitiers, France in May 2017. Topics treated include: kinematic design and synthesis, computational geometry in kinematics, motion analysis and synthesis, theory of mechanisms, mechanism design, kinematical analysis of serial and parallel robots, kinematical issues in biomechanics, molecular kinematics, kinematical motion analysis and simulation, geometric constraint solvers, deployable and tensegrity structures, robot motion planning, applications of computational kinematics, education in computational kinematics, and theoretical foundations of kinematics. Kinematics is an exciting area of computational mechanics and plays a central role in a great variety of fields and industrial applications nowadays. Apart from research in pure kinematics, the field deals with problems of practical relevance that need to be solved in an interdisciplinary manner in order for new technologies to develop. The results presented in this book should be of interest for practicing and research engineers as well as Ph. D. students from the fields of mechanical and electrical engineering, computer science, and computer graphics.
Computational Life Sciences: Data Engineering and Data Mining for Life Sciences (Studies in Big Data #112)
by Jens Dörpinghaus Vera Weil Sebastian Schaaf Alexander ApkeThis book broadly covers the given spectrum of disciplines in Computational Life Sciences, transforming it into a strong helping hand for teachers, students, practitioners and researchers. In Life Sciences, problem-solving and data analysis often depend on biological expertise combined with technical skills in order to generate, manage and efficiently analyse big data. These technical skills can easily be enhanced by good theoretical foundations, developed from well-chosen practical examples and inspiring new strategies. This is the innovative approach of Computational Life Sciences-Data Engineering and Data Mining for Life Sciences: We present basic concepts, advanced topics and emerging technologies, introduce algorithm design and programming principles, address data mining and knowledge discovery as well as applications arising from real projects. Chapters are largely independent and often flanked by illustrative examples and practical advise.
Computational Linguistics: 15th International Conference Of The Pacific Association For Computational Linguistics, Pacling 2017, Yangon, Myanmar, August 16-18, 2017, Revised Selected Papers (Communications In Computer And Information Science #781)
by Kôiti Hasida Win Pa PaThis book constitutes the refereed proceedings of the 15th International Conference of the Pacific Association for Computational Linguistics, PACLING 2017, held in Yangon, Myanmar, in August 2017.The 28 revised full papers presented were carefully reviewed and selected from 50 submissions. The papers are organized in topical sections on semantics and semantic analysis; statistical machine translation; corpora and corpus-based language processing; syntax and syntactic analysis; document classification; information extraction and text mining; text summarization; text and message understanding; automatic speech recognition; spoken language and dialogue; speech pathology; speech analysis.
Computational Linguistics: 14th International Conference of the Pacific Association for Computational Linguistics, PACLING 2015, Bali, Indonesia, May 19-21, 2015, Revised Selected Papers (Communications in Computer and Information Science #593)
by Kôiti Hasida Ayu PurwariantiThis bookconstitutes the refereed proceedings of the 14th International Conference of the PacificAssociation for Computational Linguistics, PACLING 2015, held in Bali,Indonesia, in May 2015. The 18revised full papers presented were carefully reviewed and selected from 45papers. The papers are organized around the following topics: syntax andsyntactic analysis; semantics and semantic analysis; spoken language anddialogue; corpora and corpus-based language processing; text and messageunderstanding; information extraction and text mining; information retrievaland question answering; language learning; machine translation.