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Computational Humanities (Debates in the Digital Humanities)
by Lauren Tilton Jessica Marie Johnson David MimnoThe first book to intervene in debates on computation in the digital humanities Bringing together leading experts from across North America and Europe, Computational Humanities redirects debates around computation and humanities digital scholarship from dualistic arguments to nuanced discourse centered around theories of knowledge and power. This volume is organized around four questions: Why or why not pursue computational humanities? How do we engage in computational humanities? What can we study using these methods? Who are the stakeholders? Recent advances in technologies for image and sound processing have expanded computational approaches to cultural forms beyond text, and new forms of data, from listservs and code repositories to tweets and other social media content, have enlivened debates about what counts as digital humanities scholarship. Providing case studies of collaborations between humanities-centered and computation-centered researchers, this volume highlights both opportunities and frictions, showing that data and computation are as much about power, prestige, and precarity as they are about p-values. Contributors: Mark Algee-Hewitt, Stanford U; David Bamman, U of California, Berkeley; Kaspar Beelen, U of London; Peter Bell, Philipps U of Marburg; Tobias Blanke, U of Amsterdam; Julia Damerow, Arizona State U; Quinn Dombrowski, Stanford U; Crystal Nicole Eddins, U of Pittsburgh; Abraham Gibson, U of Texas at San Antonio; Tassie Gniady; Crystal Hall, Bowdoin College; Vanessa M. Holden, U of Kentucky; David Kloster, Indiana U; Manfred D. Laubichler, Arizona State U; Katherine McDonough, Lancaster U; Barbara McGillivray, King&’s College London; Megan Meredith-Lobay, Simon Fraser U; Federico Nanni, Alan Turing Institute; Fabian Offert, U of California, Santa Barbara; Hannah Ringler, Illinois Institute of Technology; Roopika Risam, Dartmouth College; Joshua D. Rothman, U of Alabama; Benjamin M. Schmidt; Lisa Tagliaferri, Rutgers U; Jeffrey Tharsen, U of Chicago; Marieke van Erp, Royal Netherlands Academy of Arts and Sciences; Lee Zickel, Case Western Reserve U.
Computational Imaging for Scene Understanding: Transient, Spectral, and Polarimetric Analysis
by Takuya Funatomi Takahiro OkabeMost cameras are inherently designed to mimic what is seen by the human eye: they have three channels of RGB and can achieve up to around 30 frames per second (FPS). However, some cameras are designed to capture other modalities: some may have the ability to capture spectra from near UV to near IR rather than RGB, polarimetry, different times of light travel, etc. Such modalities are as yet unknown, but they can also collect robust data of the scene they are capturing. This book will focus on the emerging computer vision techniques known as computational imaging. These include capturing, processing and analyzing such modalities for various applications of scene understanding.
Computational Inference and Control of Quality in Multimedia Services (Springer Theses)
by Vlado MenkovskiThis thesis focuses on the problem of optimizing the quality of network multimedia services. This problem spans multiple domains, from subjective perception of multimedia quality to computer networks management. The work done in this thesis approaches the problem at different levels, developing methods for modeling the subjective perception of quality based on objectively measurable parameters of the multimedia coding process as well as the transport over computer networks. The modeling of subjective perception is motivated by work done in psychophysics, while using Machine Learning techniques to map network conditions to the human perception of video services. Furthermore, the work develops models for efficient control of multimedia systems operating in dynamic networked environments with the goal of delivering optimized Quality of Experience. Overall this thesis delivers a set of methods for monitoring and optimizing the quality of multimedia services that adapt to the dynamic environment of computer networks in which they operate.
Computational Intelligence (Studies in Computational Intelligence #1119)
by Thomas Bäck Kevin Warwick Hak-Keung Lam Kurosh Madani Christian Wagner Marie Cottrell Jonathan GaribaldiThis book includes a set of selected revised and extended versions of the best papers presented at the 13th International Joint Conference on Computational Intelligence (IJCCI 2021) – held as an online event, from October 25 to 27, 2021. We focus on three outstanding fields of Computational Intelligence through the selected panel, namely: Evolutionary Computation, Fuzzy Computation, and Neural Computation. Besides presenting the recent advances of the selected areas, the book aims to aggregate new and innovative solutions for confirmed researchers and on the other hand to provide a source of information and/or inspiration for young interested researchers or learners in the ever-expanding and current field of Computational Intelligence. It constitutes a precious provision of knowledge for individual researchers as well as represent a valuable sustenance for collective use in academic libraries (of universities and engineering schools) relating innovative techniques in various fields of applications.
Computational Intelligence Aided Systems for Healthcare Domain
by Akshansh GuptaThis book covers recent advances in artificial intelligence, smart computing, and their applications in augmenting medical and health care systems. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields including electrical, electronics and communication, computer, and biomedical. This book- Presents architecture, characteristics, and applications of artificial intelligence and smart computing in health care systems. Highlights privacy issues faced in health care and health informatics using artificial intelligence and smart computing technologies. Discusses nature-inspired computing algorithms for the brain-computer interface. Covers graph neural network application in the medical domain. Provides insights into the state-of-the-art artificial intelligence and smart computing enabling and emerging technologies. This book discusses recent advances and applications of artificial intelligence and smart technologies in the field of healthcare. It highlights privacy issues faced in health care and health informatics using artificial intelligence and smart computing technologies. It covers nature-inspired computing algorithms such as genetic algorithms, particle swarm optimization algorithms, and common scrambling algorithms to study brain-computer interfaces. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and biomedical engineering.
Computational Intelligence Applications in Business Intelligence and Big Data Analytics
by Vijayan Sugumaran Arun Kumar Sangaiah Arunkumar ThangaveluThere are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can learn from other experts and colleagues through this book.
Computational Intelligence Applications in Cyber Security
by Rajeev Kumar Mohammad Faisal Raees Ahmad Khan Nawaf Alharbe Suhel Ahmad KhanThe book provides a comprehensive overview of cyber security in Industry 5.0, data security in emerging technologies, block chain technology, cloud computing security, evolving IoT and OT threats, and considerable data integrity in healthcare. The impact of security risks on various sectors is explored including artificial intelligence in national security, quantum com-puting for security, and AI-driven cyber security techniques. It explores how cyber security is applied across different areas of human life through computational modeling. The book concludes by presenting a roadmap for securing computing environments, addressing the complex interplay between advanced technologies and emerging security challenges, and offering insights into future trends and innovations for sustainable development.This book: • Analyzes the use of AI, support vector machines, and deep learning for dataclassification, vulnerability prediction, and defense.• Provides insights into data protection for Industry 4.0/5.0, cloud computing, and IoT/OT, focusing on risk mitigation.• Explores block chain’s role in smart nations, financial risk management, and the potential of quantum computing for security.• Examines AI’s applications in national security, including India’s AI strategy and securing smart cities.• Evaluate strategies for data integrity in healthcare, secure IoT platforms, and supply chain cyber security. The text is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
Computational Intelligence Applications in Modeling and Control (Studies in Computational Intelligence #575)
by Ahmad Taher Azar Sundarapandian VaidyanathanThe development of computational intelligence (CI) systems was inspired by observable and imitable aspects of intelligent activity of human being and nature. The essence of the systems based on computational intelligence is to process and interpret data of various nature so that that CI is strictly connected with the increase of available data as well as capabilities of their processing, mutually supportive factors. Developed theories of computational intelligence were quickly applied in many fields of engineering, data analysis, forecasting, biomedicine and others. They are used in images and sounds processing and identifying, signals processing, multidimensional data visualization, steering of objects, analysis of lexicographic data, requesting systems in banking, diagnostic systems, expert systems and many other practical implementations. This book consists of 16 contributed chapters by subject experts who are specialized in the various topics addressed in this book. The special chapters have been brought out in the broad areas of Control Systems, Power Electronics, Computer Science, Information Technology, modeling and engineering applications. Special importance was given to chapters offering practical solutions and novel methods for the recent research problems in the main areas of this book, viz. Control Systems, Modeling, Computer Science, IT and engineering applications. This book will serve as a reference book for graduate students and researchers with a basic knowledge of control theory, computer science and soft-computing techniques. The resulting design procedures are emphasized using Matlab/Simulink software.
Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk (Studies in Computational Intelligence #697)
by Tharam Dillon Fahed Mostafa Elizabeth ChangThis book demonstrates the power of neural networks in learning complex behavior from the underlying financial time series data. The results presented also show how neural networks can successfully be applied to volatility modeling, option pricing, and value-at-risk modeling. These features mean that they can be applied to market-risk problems to overcome classic problems associated with statistical models.
Computational Intelligence Applied to Decision-Making in Uncertain Environments (Studies in Computational Intelligence #1195)
by Janusz Kacprzyk Pedro Yobanis Piñero Pérez Iliana Pérez Pupo Rafael Esteban Bello PérezThis book is dedicated to all those interested in the application of computational intelligence techniques for decision-making in uncertain environments. The book is organized into four parts. The first part groups together four works related to conversational systems and decision-making using generative artificial intelligence. The second part includes four articles associated with decision-making in project-oriented environments. The third part includes three works related to decision-making in human health environments and decision-making in sports training. The fourth part of the book contains three articles associated with business decision-making. This book combines different artificial intelligence techniques for solving decision-making problems, among which the following stand out: generative artificial intelligence, linguistic data summarization techniques, neutrosophic theory, computing with words, among other techniques. The techniques proposed in the book aim to simulate human tolerance in decision-making processes in environments with uncertainty and imprecision. The authors of the book stand out for their extensive experience in the development of basic and applied applications of computational intelligence. The authors Pedro Y. Piñero Pérez, Iliana Pérez Pupo, Janusz Kacprzyk, and Rafael E. Bello Pérez have published several books associated with artificial intelligence and applied computational intelligence. They continue to work on fundamental and applied research on different artificial intelligence techniques to assist decision-making in different areas of knowledge. The authors thank all the engineers, professors, and researchers without whose efforts this book could not have been written.
Computational Intelligence Applied to Inverse Problems in Radiative Transfer
by Antônio José da Silva Neto Haroldo Fraga de Campos Velho José Carlos BecceneriThis book offers a careful selection of studies in optimization techniques based on artificial intelligence, applied to inverse problems in radiative transfer. In this book, the reader will find an in-depth exploration of heuristic optimization methods, each meticulously described and accompanied by historical context and natural process analogies.From simulated annealing and genetic algorithms to artificial neural networks, ant colony optimization, and particle swarms, this volume presents a wide range of heuristic methods. Additional approaches such as generalized extreme optimization, particle collision, differential evolution, Luus-Jaakola, and firefly algorithms are also discussed, providing a rich repertoire of tools for tackling challenging problems.While the applications showcased primarily focus on radiative transfer, their potential extends to various domains, particularly nonlinear and large-scale problems where traditional deterministic methods fall short. With clear and comprehensive presentations, this book empowers readers to adapt each method to their specific needs. Furthermore, practical examples of classical optimization problems and application suggestions are included to enhance your understanding.This book is suitable to any researcher or practitioner whose interests lie on optimization techniques based in artificial intelligence and bio-inspired algorithms, in fields like Applied Mathematics, Engineering, Computing, and cross-disciplinary areas.
Computational Intelligence Assisted Design: In Industrial Revolution 4.0
by Yun Li Yi ChenComputational Intelligence Assisted Design framework mobilises computational resources, makes use of multiple Computational Intelligence (CI) algorithms and reduces computational costs. This book provides examples of real-world applications of technology. Case studies have been used to show the integration of services, cloud, big data technology and space missions. It focuses on computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. This book provides readers with wide-scale information on CI paradigms and algorithms, inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without difficulty through a few tested MATLAB source codes
Computational Intelligence Methods for Bioinformatics and Biostatistics: 10th International Meeting, CIBB 2013, Nice, France, June 20-22, 2013, Revised Selected Papers (Lecture Notes in Computer Science #8452)
by Enrico Formenti Roberto Tagliaferri Ernst WitThis 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: 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 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: 14th International Meeting, CIBB 2017, Cagliari, Italy, September 7-9, 2017, Revised Selected Papers (Lecture Notes in Computer Science #10834)
by Leif Peterson Roberto Tagliaferri Alberto Policriti Andrea Bracciali Massimo Bartoletti Annalisa Barla Gunnar W. KlauThis book constitutes the thoroughly refereed post-conference proceedings of the 14th International Meeting on Computational. Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2017, held in Cagliari, Italy, in September 2017.The 19 revised full papers presented were carefully reviewed and selected from 44 submissions. The papers deal with the application of computational intelligence to open problems in bioinformatics, biostatistics, systems and synthetic biology, medical informatics, computational approaches to life sciences in general.
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: 16th International Meeting, CIBB 2019, Bergamo, Italy, September 4–6, 2019, Revised Selected Papers (Lecture Notes in Computer Science #12313)
by Luca Manzoni Paolo Cazzaniga Daniela Besozzi Ivan MerelliThis book constitutes revised selected papers from the 16th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2019, which was held in Bergamo, Italy, during September 4-6, 2019. The 28 full papers presented in this volume were carefully reviewed and selected from 55 submissions. The papers are grouped in topical sections as follows: Computational Intelligence Methods for Bioinformatics and Biostatistics; Algebraic and Computational Methods for the Study of RNA Behaviour; Intelligence methods for molecular characterization medicine; Machine Learning in Healthcare Informatics and Medical Biology; Modeling and Simulation Methods for Computational Biology and Systems Medicine.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 17th International Meeting, CIBB 2021, Virtual Event, November 15–17, 2021, Revised Selected Papers (Lecture Notes in Computer Science #13483)
by Paolo Cazzaniga Davide Chicco Angelo Facchiano Erica Tavazzi Enrico Longato Martina Vettoretti Anna Bernasconi Simone AvesaniThis book constitutes revised selected papers from the 17th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2021, which was held virtually during November 15–17, 2021. The 19 papers included in these proceedings were carefully reviewed and selected from 26 submissions, and they focus on bioinformatics, computational biology, health informatics, cheminformatics, biotechnology, biostatistics, and biomedical imaging.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 18th International Meeting, CIBB 2023, Padova, Italy, September 6–8, 2023, Revised Selected Papers (Lecture Notes in Computer Science #14513)
by Erica Tavazzi Enrico Longato Martina Vettoretti Giacomo Baruzzo Massimo BellatoThe book constitutes the refereed post-conference proceedings of the 18th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2023, held in Padova, Italy, during September 6–8, 2023. The 23 full papers presented in these proceedings were carefully reviewed and selected from 24 submissions. They focuses on topics such as machine learning in healthcare informatics and medical biology; machine learning explainability in medical imaging; prediction uncertainty in machine learning; advanced statistical and computational methodologies for single-cell omics data; present and future research in bioinformatics; distributed computing in bioinformatics and computational biology; and modelling and simulation methods for computational biology and systems medicine.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 19th International Meeting, CIBB 2024, Benevento, Italy, September 4–6, 2024, Revised Selected Papers (Lecture Notes in Computer Science #15276)
by Luigi Cerulo Francesco Napolitano Francesco Bardozzo Lu Cheng Annalisa Occhipinti Stefano M. PagnottaThis volume LNCS 15276 constitutes the revised selected papers of the 19th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2024, held in Benevento, Italy, during September 4–6, 2024. The 24 full papers and 3 short papers were carefully reviewed and selected from 28 submissions. They were organized in the following topical sections: Bioinformatics; Medical Informatics; Natural Language Processing (NLP) and Large Language Models (LLM) for Unstructured Data in Health Informatics; Modeling and Simulation Methods for Computational Biology and Systems Medicine; Machine Learning for Structured Data in Clinical Informatics and Medical Biology; Computational Intelligence in Personalized Medicine; and Computational Structural Bioinformatics.
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 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 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 Super-Resolution in Image Processing Applications
by Anand Deshpande Navid Razmjooy Vania V. EstrelaThis 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.