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Hybrid Artificial Intelligent Systems ; 15th International Conference, HAIS 2020, Gijón, Spain, November 11-13, 2020, Proceedings
This book constitutes the refereed proceedings of the 15th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2020, held in Gijón, Spain, in November 2020. The 65 regular papers presented in this book were carefully reviewed and selected from 106 submissions. The papers are grouped into these topics: advanced data processing and visualization techniques; bio-inspired models and optimization; learning algorithms; data mining, knowledge discovery and big data; and hybrid artificial intelligence applications.
High performance computing for drug discovery and biomedicine
Explores the application of high-performance computing (HPC) technologies to computational drug discovery (CDD) and biomedicine. Collects CDD approaches that, together with HPC, can revolutionize and automate drug discovery process, such as knowledge graphs, natural language processing (NLP), Bayesian optimization, automated virtual screening platforms, alchemical free energy workflows, fragment-molecular orbitals (FMO), HPC-adapted molecular dynamic simulation (MD-HPC), and the potential of cloud computing for drug discovery. And delves into computational algorithms and workflows for biomedicine, featuring an HPC framework to assess drug-induced arrhythmic risk, digital patient applications relevant to the clinic, virtual human simulations, cellular and whole-body blood flow modeling for stroke treatments, prediction of the femoral bone strength from CT data, and many more subjects.
High accuracy detection of mobile malware using machine learning
As increasingly sophisticated and evasive malware attacks continue to emerge, more effective detection solutions to tackle the problem are being sought through the application of advanced machine learning techniques. This reprint presents several advances in the field including: a new method of generating adversarial samples through byte sequence feature extraction using deep learning; a state-of-the-art comparative evaluation of deep learning approaches for mobile botnet detection; a novel visualization-based approach that utilizes images for Android botnet detection; a study on the detection of drive-by exploits in images using deep learning; etc. Furthermore, this reprint presents state-of-the-art reviews about machine learning-based detection techniques that will increase researchers' knowledge in the field and enable them to identify future research and development directions.
Hierarchical Bayesian Optimization Algorithm : Toward a New Generation of Evolutionary Algorithms
This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The book focuses on two algorithms that replace traditional variation operators of evolutionary algorithms by learning and sampling Bayesian networks: the Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA). BOA and hBOA are theoretically and empirically shown to provide robust and scalable solution for broad classes of nearly decomposable and hierarchical problems. A theoretical model is developed that estimates the scalability and adequate parameter settings for BOA and hBOA. The performance of BOA and hBOA is analyzed on a number of artificial problems of bounded difficulty designed to test BOA and hBOA on the boundary of their design envelope.
Hebbian Learning and Negative Feedback Networks
This book is the outcome of a decade’s research into a speci?c architecture and associated learning mechanism for an arti?cial neural network: the - chitecture involves negative feedback and the learning mechanism is simple Hebbian learning. The research began with my own thesis at the University of Strathclyde, Scotland, under Professor Douglas McGregor which culminated with me being awarded a PhD in 1995 [52], the title of which was “Negative Feedback as an Organising Principle for Arti?cial Neural Networks”. Naturally enough, having established this theme, when I began to sup- vise PhD students of my own, we continued to develop this concept and this book owes much to the research and theses of these students at the Applied Computational Intelligence Research Unit in the University of Paisley . All of Chapters 3 to 8 deal with single stream arti?cial neural networks.
Healthcare solutions using machine learning and informatics
Covers novel and innovative solutions for the healthcare that apply machine learning and biomedical informatics technology. The healthcare sector is one of the most critical in society. This book presents a series of artificial intelligence, machine learning, intelligent IoT-based solutions for medical image analysis, medical big data processing, disease predictions. Machine learning and artificial intelligence use cases in healthcare presented in the book give researchers, practitioners, and students a wide range of practical examples of cross-domain convergence. The wide variety of topics covered include: Artificial Intelligence in healthcare Machine learning solutions for such disease as diabetes, arthritis, cardiovascular disease, and COVID-19 Big data analytics solutions for healthcare data processing Reliable biomedical applications using AI models Intelligent IoT in healthcare. The book explains fundamental concepts as well as the advanced use cases illustrating how to apply emerging technologies such as machine learning, AI models, data informatics into practice to tackle challenges in the field of healthcare with real-world scenarios. Chapters contributed by noted academicians and professionals examine various solutions, frameworks, applications, case studies, and best practices in the healthcare domain
Health Information Science ; 9th International Conference, HIS 2020, Amsterdam, The Netherlands, October 20–23, 2020, Proceedings
This book constitutes the proceedings of the 9th International Conference on Health Information Science, HIS 2020, which took place in Amsterdam, The Netherlands, during October 20-23, 2020. The 11 full papers and 6 short papers presented in this volume were carefully reviewed and selected from 62 submissions. They were organized in topical sections named: mental health; medical record processing; medical information systems; medical diagnosis with machine learning; and health behavior and medication.
Hands-on question answering systems with BERT : Applications in neural networks and natural language processing
Begins with an overview of the technology landscape behind BERT. It takes you through the basics of NLP, including natural language understanding with tokenization, stemming, and lemmatization, and bag of words. Next, you’ll look at neural networks for NLP starting with its variants such as recurrent neural networks, encoders and decoders, bi-directional encoders and decoders, and transformer models. Along the way, you’ll cover word embedding and their types along with the basics of BERT. After this solid foundation, you’ll be ready to take a deep dive into BERT algorithms such as masked language models and next sentence prediction. You’ll see different BERT variations followed by a hands-on example of a question answering system. You will: Examine the fundamentals of word embeddings / Apply neural networks and BERT for various NLP tasks / Develop a question-answering system from scratch / Train question-answering systems for your own data
Handbook of marketing analytics : Methods and applications in marketing management, public policy, and litigation support
Shows analytical marketing methods and their high-impact real-life applications in marketing management, Public policy, and litigation support. Fourteen chapters present an overview of specific marketing analytic methods in technical detail, While 22 case studies present thorough examples of the use of each method. Multidisciplinary in scope, This handbook covers experimental methods, non-experimental methods, and their digital-era extensions. It explores topics such as : Classical and bayesian econometrics, Causality, Machine learning, Optimization, And recent advancements in conjoint analysis.
Handbook of Digital Face Manipulation and Detection: From DeepFakes to Morphing Attacks
Provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the research fields of biometrics and media forensics including contributions from academia and industry. Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers. Moreover, the book provides a good starting point for young researchers as well as a reference guide pointing at further literature. Hence, the primary readership is academic institutions and industry currently involved in digital face manipulation and detection. The book could easily be used as a recommended text for courses in image processing, machine learning, media forensics, biometrics, and the general security area.
Green, pervasive, and cloud computing ; 15th International conference, GPC 2020, Xi'an, China, November 13–15, 2020, Proceedings
This book constitutes the refereed proceedings of the 15th International Conference on Green, Pervasive, and Cloud Computing, GPC 2020, held in Xi'an, China, in November 2020. The 30 full papers presented in this book together with 8 short papers were carefully reviewed and selected from 96 submissions. They cover the following topics: Device-free Sensing; Machine Learning; Recommendation Systems; Urban Computing; Human Computer Interaction; Internet of Things and Edge Computing; Positioning; Applications of Computer Vision; CrowdSensing; and Cloud and Related Technologies.
Granular computing : At the junction of rough sets and fuzzy sets
This volume is a compilation of the best papers presented at the First International Symposium on Fuzzy and Rough Sets (ISFUROS 2006) held in Santa Clara, Cuba. You will therefore find valuable contributions both in the theoretical field as in several application domains.
geoENV VI - Geostatistics for Environmental Applications : Proceedings of the Sixth European Conference on Geostatistics for Environmental Applications
This volume contains how geostatistics is applied within the environmental sciences. A few selected theoretical contributions are also included.
Genetic Programming Theory and Practice V
Genetic Programming Theory and Practice V was developed from the fifth workshop at the University of Michigan’s Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming (GP). Contributions from the foremost international researchers and practitioners in the GP arena examine the similarities and differences between theoretical and empirical results on real-world problems. The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application.
Genetic Programming Theory and Practice IV
Genetic Programming Theory and Practice IV was developed from the fourth workshop at the University of Michigan’s Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming (GP). Contributions from the foremost international researchers and practitioners in the GP arena examine the similarities and differences between theoretical and empirical results on real-world problems.
Genetic Programming Theory and Practice III
Genetic Programming Theory and Practice III explores the emerging interaction between theory and practice in the cutting-edge, machine learning method of Genetic Programming (GP). This contributed volume was developed from the third workshop at the University of Michigan’s Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to this rapidly advancing field. The text provides a cohesive view of the issues facing both practitioners and theoreticians and examines the synergy between GP theory and application.
Genetic Programming ; Vol. 3905 ; 9th European Conference, EuroGP 2006, Budapest, Hungary, April 10-12, 2006. Proceedings
This book constitutes the refereed proceedings of the 9th European Conference on Genetic Programming, EuroGP 2006, held in Budapest, Hungary, in April 2006, colocated with EvoCOP 2006. The 21 revised plenary papers and 11 revised poster papers were carefully reviewed and selected from 59 submissions. The papers address fundamental and theoretical issues, along with a wide variety of papers dealing with different application areas, such as computer science, engineering, machine learning, Kolmogorov complexity, biology and computational design.
Genetic programming : Theory and practice II
This volume explores the emerging interaction between theory and practice in the cutting-edge, machine learning method of Genetic Programming (GP). The contributions developed from a second workshop at the University of Michigan's Center for the Study of Complex Systems where leading international genetic programming theorists from major universities and active practitioners from leading industries and businesses met to examine how GP theory informs practice and how GP practice impacts GP theory. Chapters include such topics as financial trading rules, industrial statistical model building, population sizing, the roles of structure in problem solving by computer, stock picking, automated design of industrial-strength analog circuits, topological synthesis of robust systems, algorithmic chemistry, supply chain reordering policies, post docking filtering, an evolved antenna for a NASA mission and incident detection on highways.
Fuzzy sets and their extensions : Representation, aggregation and models : Intelligent systems from decision making to data mining, web intelligence and computer vision
This book presents an up-to-date state of current research in the use of fuzzy sets and their extensions, paying attention to foundation issues and to their application to four important areas where fuzzy sets are seen to be an important tool for modelling and solving problems.
Future data and security engineering ; 7th International conference, FDSE 2020, Quy Nhon, Vietnam, November 25–27, 2020, Proceedings
This book constitutes the proceedings of the 7th International Conference on Future Data and Security Engineering, FDSE 2020, which was supposed to be held in Quy Nhon, Vietnam, in November 2020, but the conference was held virtually due to the COVID-19 pandemic. The 24 full papers (of 53 accepted full papers) presented together with 2 invited keynotes were carefully reviewed and selected from 161 submissions. The other 29 accepted full and 8 short papers are included in CCIS 1306. The selected papers are organized into the following topical headings: security issues in big data; big data analytics and distributed systems; advances in big data query processing and optimization; blockchain and applications; industry 4.0 and smart city: data analytics and security; advanced studies in machine learning for security; and emerging data management systems and applications.
