الصفحة 2
الصفحة 2
Information security and privacy ; 6th Australasian Conference, ACISP 2001, Sydney, Australia, July 11-13, 2001. Proceedings
A Few Thoughts on E-Commerce.- New CBC-MAC Forgery Attacks.- Cryptanalysis of a Public Key Cryptosystem Proposed at ACISP 2000.- Improved Cryptanalysis of the Self-Shrinking Generator.- Attacks Based on Small Factors in Various Group Structures.- On Classifying Conference Key Distribution Protocols.- Pseudorandomness of MISTY-Type Transformations and the Block Cipher KASUMI.- New Public-Key Cryptosystem Using Divisor Class Groups.- First Implementation of Cryptographic Protocols Based on Algebraic Number Fields.- Practical Key Recovery Schemes.- Non-deterministic Processors.- Personal Secure Booting.- Evaluation of Tamper-Resistant Software Deviating from Structured Programming Rules.- A Strategy for MLS Workflow.- Condition-Driven Integration of Security Services.- SKETHIC: Secure Kernel Extension against Trojan Horses with Informat ion-Carrying Codes.- Secure and Private Distribution of Online Video and Some Related Cryptographic Issues.- Private Information Retrieval Based on the Subgroup Membership Problem.
Informatics in the Future ; Proceedings of the 11th European Computer Science Summit (ECSS 2015), Vienna, October 2015
This volume discusses the prospects and evolution of informatics (or computer science), which has become the operating system of our world, and is today seen as the science of the information society. Its artifacts change the world and its methods have an impact on how we think about and perceive the world. Classical computer science is built on the notion of an “abstract” machine, which can be instantiated by software to any concrete problem-solving machine, changing its behavior in response to external and internal states, allowing for self-reflective and “intelligent” behavior. However, current phenomena such as the Web, cyber physical systems or the Internet of Things show us that we might already have gone beyond this idea, exemplifying a metamorphosis from a stand-alone calculator to the global operating system of our society.
Heavy-Tailed Time Series
This book aims to present a comprehensive, self-contained, and concise overview of extreme value theory for time series, incorporating the latest research trends alongside classical methodology.Additionally, the book incorporates complete proofs and exercises with solutions as well as substantive reference lists and appendices, featuring a novel commentary on the theory of vague convergence.
Fuzzy Equational Logic
The book deals with similarity relations defined on a set with functions. The functions are required to map similar elements to similar ones. The book presents basic mathematical properties of structures consisting of similarity-preserving functions and logics for reasoning about similarities. The presented text is self-contained. The notions and results are demonstrated through examples which are graphically illustrated. The book is useful for researchers, but it can also be used as a graduate text.
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.
Fundamentals and Methods of Machine and Deep Learning : Algorithms, Tools, and Applications
provides a practical approach by explaining the concepts of machine learning and deep learning algorithms, evaluation of methodology advances, and algorithm demonstrations with applications. In recent research studies, they are regarded as one of the disruptive technologies that will transform our future life, business, and the global economy. The recent explosion of digital data in a wide variety of domains, including science, engineering, Internet of Things, biomedical, healthcare, and many business sectors, has declared the era of big data, which cannot be analysed by classical statistics but by the more modern, robust machine learning and deep learning techniques. Since machine learning learns from data rather than by programming hard-coded decision rules, an attempt is being made to use machine learning to make computers that are able to solve problems like human experts in the field.
Fundamental approaches to software engineering ; 25th International Conference, FASE 2022, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022, Munich, Germany, April 2–7, 2022, Proceedings
The papers deal with the foundations on which software engineering is built, including topics like software engineering as an engineering discipline, requirements engineering, software architectures, software quality, model-driven development, software processes, software evolution, AI-based software engineering, and the specification, design, and implementation of particular classes of systems, such as (self-)adaptive, collaborative, AI, embedded, distributed, mobile, pervasive, cyber-physical, or service-oriented applications.
Fractal Dimensions of Networks
The goal of the book is to provide a unified treatment of fractal dimensions of sets and networks. Since almost all of the major concepts in fractal dimensions originated in the study of sets, the book achieves this goal by first clearly presenting, with an abundance of examples and illustrations, the theory and algorithms for sets, and then showing how the theory and algorithms have been applied to networks. For example, the book presents the classical theory and algorithms for the box counting dimension for sets, and then presents the box counting dimension for networks. All the major fractal dimensions are studied, e.g., the correlation dimension, the information dimension, the Hausdorff dimension, the multifractal spectrum, as well as many lesser known dimensions. Algorithm descriptions are accompanied by worked examples, with many applications of the methods presented.
Foundations of learning classifier systems
This volume brings together recent theoretical work in Learning Classifier Systems (LCS), which is a Machine Learning technique combining Genetic Algorithms and Reinforcement Learning. It includes self-contained background chapters on related fields (reinforcement learning and evolutionary computation) tailored for a classifier systems audience and written by acknowledged authorities in their area - as well as a relevant historical original work by John Holland.
Foundation models for natural language processing : pre-trained language models integrating media
Covers basic natural language processing models, pre-trained language models BERT, GPT, and sequence-to-sequence converters, as well as the concepts of self-attention and context-sensitive embedding. Various approaches to improving these models are then discussed, such as expanding the pre-training parameters, increasing the length of input texts, or incorporating additional knowledge. An overview of the best performing models is then provided for about twenty application areas, e.g., question answering, translation, story generation, dialogue systems, image generation from text, etc. For each application area, the strengths and weaknesses of existing models are discussed, and an overview of further developments is provided. In addition, links to freely available code are provided. The concluding chapter summarizes the economic opportunities, risk mitigation, and potential developments of AI.
Forecasting and Assessing Risk of Individual Electricity Peaks
The overarching aim of this open access book is to present self-contained theory and algorithms for investigation and prediction of electric demand peaks. A cross-section of popular demand forecasting algorithms from statistics, machine learning and mathematics is presented, followed by extreme value theory techniques with examples.
Focused Access to XML Documents ; 6th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2007 Dagstuhl Castle, Germany, December 17-19, 2007. Selected Papers
This book constitutes the thoroughly refereed post-conference proceedings of the 6th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2007, held at Dagstuhl Castle, Germany, in December 2007.The 37 revised full papers presented were carefully reviewed and selected for presentation at the workshop from 50 initial submissions. The papers are organized in an ad hoc track and 6 topical sections on book search, XML-mining, entity ranking, interactive, link-the-wiki, and multimedia.
First course on fuzzy theory and applications
This basic textbook gives an easily accessible introduction to Fuzzy theory and its applications. It provides basic and concrete concepts of the field in a self-contained, condensed and understandable style. This "First Course on Fuzzy Theory and Applications" includes numerous examples, descriptive illustrations and figures of the basic concepts, as well as exercises at the end of each chapter. The author has long time experience in teaching on fuzzy theory and its applications and continuously developed and summarized his didactic lecture notes into this book. This book can be used in introductory graduate and undergraduate courses in Fuzziness and Soft Computing and is recommendable to students, scientists, engineers, or professionals in the field for self-study.
Fault Diagnosis of Analog Integrated Circuits
Fault Diagnosis of Analog Integrated Circuits is a textbook for advanced undergraduate and graduate level students as well as practicing engineers. The objective of this book is to study the testing and fault diagnosis of analog and analog part of mixed signal circuits. A background in analog integrated circuit, artificial neural network is desirable but not essential.
Essential discrete mathematics for computer science
An ideal introductory textbook for standard undergraduate courses, and is also suitable for high school courses, distance education for adult learners, and self-study. The essential introduction to discrete mathematics / Features thirty-one short chapters, each suitable for a single class lesson / Includes more than 300 exercises / Almost every formula and theorem proved in full / Breadth of content makes the book adaptable to a variety of courses / Each chapter includes a concise summary
Error-Correction Coding and Decoding : Bounds, Codes, Decoders, Analysis and Applications
This book discusses both the theory and practical applications of self-correcting data, commonly known as error-correcting codes. The applications included demonstrate the importance of these codes in a wide range of everyday technologies, from smartphones to secure communications and transactions. Written in a readily understandable style,This book is a valuable resource for anyone interested in error-correcting codes and their applications, ranging from non-experts to professionals at the forefront of research in their field.
Engineering self-organising systems Vol. 3910 ; 3rd International Workshop, ESOA 2005, Utrecht, The Netherlands, July 25, 2005, Revised Selected Papers
This book contains recent work from a broad range of areas with the common theme of utilising self-organisation productively. As distributed information infrastructures continue to spread (such as the Internet, wireless and mobile systems), new challenges have arisen demanding robust and scalable solutions. In these new challenging environments the - signers and engineers of global applications and services can seldom rely on centralised control or management, high reliability of devices, or secure en- ronments. At the other end of the scale, ad-hoc sensor networks and ubiquitous computing devices are making it possible to embed millions of smart computing agents into the local environment.
Engineering self-organising systems ; Vol. 3464 : Methodologies and applications
Self-organisation, self-regulation, self-repair, and self-maintenance are promising conceptual approaches to deal with the ever increasing complexity of distributed interacting software and information handling systems. Self-organising applications are able to dynamically change their functionality and structure without direct user intervention to respond to changes in requirements and the environment. This book comprises revised and extended papers presented at the International Workshop on Engineering Self-Organising Applications, ESOA 2004, held in New York, NY, USA in July 2004 at AAMAS as well as invited papers from leading researchers. The papers are organized in topical sections on state of the art, synthesis and design methods, self-assembly and robots, stigmergy and related topics, and industrial applications.
Engineering self-organising systems ; 4th International Workshop, ESOA 2006, Hakodate, Japan, May 9, 2006, Revised and Invited Papers
This book discusses a broad variety of topics in an effort to allow room for new ideas and discussion, and eventually a better understanding of the important directions and techniques of Engineering Self-Organizing.This book raises the important question of whether there are underlying statistical mechanics-like principles that apply to emergent multi-agent systems. Answering this question will in the long run provide an important part of the underlying theory of emergent distributed systems.
Engineering Environment-Mediated Multi-Agent Systems ; International Workshop, EEMMAS 2007, Dresden, Germany, October 5, 2007. Selected Revised and Invited Papers
This book constitutes the thoroughly refereed proceedings of the International Workshop on Engineering Environment-Mediated Multi-Agent Systems, held in Dresden,The volume includes 16 thoroughly revised papers, selected from the lectures given at the workshop, together with 2 papers resulting from invited talks by prominent researchers in the field. The papers are organized in sections on engineering self-organizing applications, stigmergic interaction, modeling and structuring mediating environments, and environment-based support for context and organizations.
