الصفحة 11
الصفحة 11
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Grammatical Inference ; Algorithms and Applications : 9th International Colloquium, ICGI 2008 Saint-Malo, France, September 22-24, 2008 Proceedings

This book constitutes the refereed proceedings of the 9th International Colloquium on Grammatical Inference, ICGI 2008, held in Saint-Malo, France, in September 2008.The 21 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 36 submissions. The topics of the papers presented vary from theoretical results of learning algorithms to innovative applications of grammatical inference, and from learning several interesting classes of formal grammars to applications to natural language processing.

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Grammatical Inference : Algorithms and Applications ; 8th International Colloquium, ICGI 2006, Tokyo, Japan, September 20-22, 2006, Proceedings

The topics discussed range from theoretical results of learning algorithms to innovative applications of grammatical inference and from learning several interesting classes of formal grammars to applications to natural language processing.

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Genetic rogramming ; Vol. 3447 : 8th European conference, EuroGP 2005, Lausanne, Switzerland, March 30-April 1, 2005, Proceedings

In this volume we present the contributions for the 18th European Conference on Genetic Programming (EuroGP 2005). The conference took place from 30 March to 1 April in Lausanne, Switzerland. EuroGP is a well-established conf- ence and the only one exclusively devoted to genetic programming. All previous proceedings were published by Springer in the LNCS series. From the outset, EuroGP has been co-located with the EvoWorkshops focusing on applications of evolutionary computation. Since 2004, EvoCOP, the conference on evolutionary combinatorial optimization, has also been co-located with EuroGP, making this year’s combined events one of the largest dedicated to evolutionary computation in Europe. Genetic programming (GP) is evolutionary computation that solves complex problems or tasks by evolving and adapting a population of computer programs, using Darwinian evolution and Mendelian genetics as its sources of inspiration. Some of the 34 papers included in these proceedings address foundational and theoretical issues and there is also a wide variety of papers dealing with di?erent application areas, such as computer science, engineering, language processing, biology and computational design, demonstrating that GP is a powerful and practical problem-solving paradigm.

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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.

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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.

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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.

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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.

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Genetic Programming ; 10th European Conference, EuroGP 2007, Valencia, Spain, April 11-13, 2007, Proceedings

This book constitutes the refereed proceedings of the 10th European Conference on Genetic Programming, EuroGP 2007, held in Valencia, Spain in April 2007 colocated with EvoCOP 2007.

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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.

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Generative adversarial text to image synthesis

Synthesizing high-quality images from text descriptions is a challenging problem in computer vision and has many practical applications. Samples generated by existing text-to-image approaches can roughly reflect the meaning of the given descriptions, but they fail to contain necessary details and vivid object parts. In order to make the project more specialized, it was approved that the project be dedicated to fashion image generation, we present an effective approach for generating new clothing through generative adversarial learning. Generative Adversarial Networks (GANs) successfully show the capability of synthesizing sharper images compared to other generative models.

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Fuzzy Systems Engineering : Theory and Practice

This book is devoted to reporting innovative and significant progress in fuzzy system engineering. Given the maturation of fuzzy logic, this book is dedicated to exploring the recent breakthroughs in fuzziness and soft computing in favour of intelligent system engineering. This monograph presents novel developments of the fuzzy theory as well as interesting applications of the fuzzy logic exploiting the theory to engineer intelligent systems.

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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.

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Future data and security engineering : Big data, security and privacy, smart city and industry 4.0 applications ; 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, held in Quy Nhon, Vietnam, in November 2020.* The 29 full papers and 8 short were carefully reviewed and selected from 161 submissions. The selected papers are organized into the following topical headings: big data analytics and distributed systems; security and privacy engineering; industry 4.0 and smart city: data analytics and security; data analytics and healthcare systems; machine learning-based big data processing; emerging data management systems and applications; and short papers: security and data engineering.

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Fundamentals of pattern recognition and machine learning

Fundamentals of Pattern Recognition and Machine Learning is designed for a one or two-semester introductory course in Pattern Recognition or Machine Learning at the graduate or advanced undergraduate level. The book combines theory and practice and is suitable to the classroom and self-study.

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Fundamentals of manufacturing engineering using digital visualization

Offers a guide to core principles and practices of manufacturing engineering. It covers the design of, together with technological and measurement issues for, technical systems. Locating charts and setup schemes describing different machining processes are included. Concepts of product quality, with a focus on accuracy indicators, machining accuracy, roughness, and the impact of surface quality on exploitation properties are also explained. Furthermore, key machining methods, including turning, milling, hole machining, grinding, and gear machining, are analyzed in depth, covering their principles, applications, and techniques. The book is enriched by QR codes, linking to a mobile application presenting additional information about the content, for an interactive and extended learning experience. It also uses illustrations visualized with digital tools to promote a better understanding of the concepts.

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Fundamentals of information systems security ; 3rd ed.

Provides a comprehensive overview of the essential concepts readers must know as they pursue careers in information systems security. The text opens with a discussion of the new risks, threats, and vulnerabilities associated with the transition to a digital world. Part 2 presents a high level overview of the Security+ Exam and provides students with information as they move toward this certification. The book closes with information on information security standards, education, professional certifications, and compliance laws. With its practical, conversational writing style and step-by-step examples, this text is a must-have resource for those entering the world of information systems security.

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Fundamentals of information systems security ; 4th ed.

Provides a comprehensive overview of the concepts readers must know as they pursue careers in information systems security. The text opens with a discussion of emerging technologies and the risks, threats, and vulnerabilities associated with our digital world. Part II takes a deeper dive into the foundational knowledge areas and functions associated with a career in information security. The book closes with a survey of information security standards, professional certifications, and compliance laws. With its practical, conversational writing style and step-by-step examples, this text is a must-have resource for those entering the world of information systems security.

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Fundamentals of image data mining : Analysis, features, classification and retrieval

Presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image analysis and understanding, offering deep insights into areas of feature extraction, machine learning, and image retrieval. The theoretical coverage is supported by practical mathematical models and algorithms, utilizing data from real-world examples and experiments. Topics and features: Describes essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms / Develops many new exercises (most with MATLAB code and instructions) / Includes review summaries at the end of each chapter / Analyses state-of-the-art models, algorithms, and procedures for image mining / Integrates new sections on pre-processing, discrete cosine transform, and statistical inference and testing / Demonstrates how features like color, texture, and shape can be mined or extracted for image representation / Applies powerful classification approaches: Bayesian classification, support vector machines, neural / networks, and decision trees / Implements imaging techniques for indexing, ranking, and presentation, as well as database visualization

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Fundamentals of Clinical Data Science

This book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare.

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Fundamentals of Artificial Intelligence

Fundamentals of Artificial Intelligence introduces the foundations of present day AI and provides coverage to recent developments in AI such as Constraint Satisfaction Problems, Adversarial Search and Game Theory, Statistical Learning Theory, Automated Planning, Intelligent Agents, Information Retrieval, Natural Language & Speech Processing, and Machine Vision. The book features a wealth of examples and illustrations, and practical approaches along with the theoretical concepts. It covers all major areas of AI in the domain of recent developments. The book is intended primarily for students who major in computer science at undergraduate and graduate level but will also be of interest as a foundation to researchers in the area of AI.

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