الصفحة 15
الصفحة 15
Ambient intelligence : A novel paradigm
Ambient Intelligence (AmI) is an integrating technology for supporting a pervasive and transparent infrastructure for implementing smart environments. Such technology is used to enable environments for detecting events and behaviors of people and for responding in a contextually relevant fashion. AmI proposes a multi-disciplinary approach for enhancing human machine interaction. The authors start with a description of the iDorm as an example of a smart environment conforming to the AmI paradigm, and introduces computer vision as an important component of the system. Other computer vision examples describe visual monitoring for the elderly, classic and novel surveillance techniques using clusters of cameras installed in indoor and outdoor application domains, and the monitoring of public spaces. Face and speech recognition systems are also covered as well as enhanced LEGO blocks for novel educational purposes. The book closes with a provocative chapter on how a cybernetic system can be designed as the backbone of a human machine interaction.
Algorithms on Trees and Graphs : With Python Code
Introduces graph algorithms on an intuitive basis followed by a detailed exposition using structured pseudocode, with correctness proofs as well as worst-case analyses. Centered around the fundamental issue of graph isomorphism, the content goes beyond classical graph problems of shortest paths, spanning trees, flows in networks, and matchings in bipartite graphs. Advanced algorithmic results and techniques of practical relevance are presented in a coherent and consolidated way. Numerous illustrations, examples, problems, exercises, and a comprehensive bibliography support students and professionals in using the book as a text and source of reference. Furthermore, Python code for all algorithms presented is given in an appendix. Topics and features: Algorithms are first presented on an intuitive basis, followed by a detailed exposition using structured pseudocode / Correctness proofs are given, together with a worst-case analysis of the algorithms / Full implementation of all the algorithms in Python / An extensive chapter is devoted to the algorithmic techniques used in the book / Solutions to all the problems
Algorithms in Bioinformatics : Theory and Implementation
Explores a comprehensive and insightful treatment of the practical application of bioinformatic algorithms in a variety of fields. Delivers a fulsome treatment of some of the main algorithms used to explain biological functions and relationships. It introduces readers to the art of algorithms in a practical manner which is linked with biological theory and interpretation. The book covers many key areas of bioinformatics, including global and local sequence alignment, forced alignment, detection of motifs, Sequence logos, Markov chains or information entropy. Other novel approaches are also described, such as Self-Sequence alignment, Objective Digital Stains (ODSs) or Spectral Forecast and the Discrete Probability Detector (DPD) algorithm. Readers will also benefit from the inclusion of: A detailed presentation of new methods, such as Self-sequence alignment, Objective Digital Stains and Spectral Forecast ; A treatment of sequence alignment, including local sequence alignment, global sequence alignment and forced sequence alignment with full implementations ; Discussions of position-specific weight matrices, including the count, weight, relative frequencies, and log-likelihoods matrices ; A detailed presentation of the methods related to Markov Chains as well as a description of their implementation in Bioinformatics and adjacent fields ; An examination of information and entropy, including sequence logos and explanations related to their meaning ; A chapter on philosophical transactions that allows the reader a broader view of the prediction process ; Extensive worked examples with detailed case studies that point out the meaning of different results
Algorithms for Sensor and Ad Hoc Networks : Advanced Lectures
Thousands of mini computers (comparable to a stick of chewing gum in size), equipped with sensors, are deployed in some terrain or other. After activation the sensors form a self-organized network and provide data, for example about a forthcoming earthquake. The trend towards wireless communication increasingly affects electronic devices in almost every sphere of life. Conventional wireless networks rely on infrastructure such as base stations; mobile devices interact with these base stations in a client/server fashion. In contrast, current research is focusing on networks that are completely unstructured, but are nevertheless able to communicate (via several hops) with each other, despite the low coverage of their antennas. Such systems are called sensor or ad hoc networks, depending on the point of view and the application. Wireless ad hoc and sensor networks have gained an incredible research momentum. Computer scientists and engineers of all flavors are embracing the area. Sensor networks have been adopted by researchers in many fields: from hardware technology to operating systems, from antenna design to databases, from information theory to networking, from graph theory to computational geometry.
Algorithms and data structures for massive datasets
Learn: Probabilistic sketching data structures for practical problems Choosing the right database engine for your application Evaluating and designing efficient on-disk data structures and algorithms Understanding the algorithmic trade-offs involved in massive-scale systems Deriving basic statistics from streaming data Correctly sampling streaming data Computing percentiles with limited space resources Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You'll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects--and there's no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you'll find the sweet spot of saving space without sacrificing your data's accuracy. About the Technology Standard algorithms and data structures may become slow--or fail altogether--when applied to large distributed datasets. Choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost.
Algorithmic Aspects of Bioinformatics
Advances in bioinformatics and systems biology require improved computational methods for analyzing data, while progress in molecular biology is in turn influencing the development of computer science methods. This book introduces some key problems in bioinformatics, discusses the models used to formally describe these problems, and analyzes the algorithmic approaches used to solve them. After introducing the basics of molecular biology and algorithmics, Part I explains string algorithms and alignments; Part II details the field of physical mapping and DNA sequencing; and Part III examines the application of algorithmics to the analysis of biological data. Exciting application examples include predicting the spatial structure of proteins, and computing haplotypes from genotype data. This book describes topics in detail and presents formal models in a mathematically precise, yet intuitive manner, with many figures and chapter summaries, detailed derivations, and examples. It is well suited as an introduction into the field of bioinformatics, and will benefit students and lecturers in bioinformatics and algorithmics, while also offering practitioners an update on current research topics.
Algebraic Methodology and Software Technology ; 11th International Conference, AMAST 2006, Kuressaare, Estonia, July 5-8, 2006, Proceedings
This is the proceedings of the 11th edition of the Algebraic Methodology and Software Technology (AMAST) conference series. The rst conference was held in the USA in 1989, and since then AMAST conferences have been held on (or near) fve diferent continents and have been hosted by many of the most prominent people and organizations in the ?eld. The AMAST initiative has always sought to have practical efects by dev- oping the science of software and basing it on a ?rm mathematical foundation. AMAST hasinterpretedsoftwaretechnologybroadly,andhas, for example, held AMAST workshops in areas as diverse as real-time systems and (natural) l- guage processing. Similarly, algebraic methodology is interpreted broadly and includes abstract algebra, category theory, logic, and a range of other ma- ematical subdisciplines.
AI in banking : Practical applications and case studies
Delves into the application of AI from theory to practice, offering detailed insights into AI project design and code implementation across eleven business scenarios in four major sectors: retail banking, e-banking, bank credit, and tech operations. it provides hands-on examples of various technologies, including automatic machine learning, integrated learning, graph computation, recommendation systems, causal inference, generative adversarial networks, supervised learning, unsupervised learning, computer vision, reinforcement learning, fuzzy control, automatic control, speech recognition, semantic understanding, bayesian networks, edge computing, and more. this book stands as a rare and practical guide to AI projects in the banking industry.
AI and UX : Why artificial intelligence needs user experience
Great effort has been put forth to continuously make AI “smarter.” But, will smarter always equal more successful AI? It is not just about getting a product to market, but about getting the product into a user’s hands in a form that will be embraced. This demands examining the product from the perspective of the user. Authors Gavin Lew and Robert Schumacher have written AI and UX to examine just how product managers and designers can best strike this balance. From exploring the history of the parallel journeys of AI and UX, to investigating past product examples and failures, to practical expert knowledge on how to best execute a positive user experience, AI and UX examines all angles of how AI can best be developed within a UX framework.
Agile Development with the ICONIX Process : People, Process, and Pragmatism
Describes how to apply ICONIX Process (a minimal, use case-driven modeling process) in an agile software project. It's full of practical advice for avoiding common agile pitfalls. Further, the book defines a core agile subset so those of you who want to get agile need not spend years learning to do it. Instead, you can simply read this book and apply the core subset of techniques. The book follows a real-life .NET/C# project from inception and UML modeling, to working code through several iterations. You can then go on-line to compare the finished product with the initial set of use cases. The book also introduces several extensions to the core ICONIX Process, including combining test-driven development (TDD) with up-front design to maximize both approaches (with examples using Java and JUnit). And the book incorporates persona analysis to drive the projects goals and reduce requirements churn.
Agent Technology from a Formal Perspective
The field of agent & multi-agent systems is experiencing tremendous growth. At the same time the field of formal methods is blossoming and has proven its importance in industrial and government applications. The FAABS (Formal Approaches to Agent-Based Systems) workshops, merging the concerns of the two fields, provided a timely and compelling platform on which the growing concerns and requirement of agent-based systems users that systems should be accompanied by behavioral assurances, could be discussed. This book has arisen from the overwhelming response to FAABS ’00, ’02 & ’04 and all chapters are updated or represent new research, and are designed to provide a more in-depth treatment of the topic. Examples of how others have applied formal methods to agent-based systems are included, plus formal method tools & techniques that readers can apply to their own systems.
Advances in neural networks -- ISNN 2007 ; 4th International symposium on neutral networks, ISNN 2007 Nanjing, China, June 3-7, 2007. Proceedings, Part II
An eural network is an information processing structure inspired by biological nervous systems, such as the brain. It consists of a large number of highly int- connected processing elements, called neurons. It has the capability of learning from example.
Advances in Neural Networks -- ISNN 2007 ; 4th International Symposium on Neutral Networks, ISNN 2007 Nanjing, China, June 3-7, 2007. Proceedings, Part I
An eural network is an information processing structure inspired by biological nervous systems, such as the brain. It consists of a large number of highly int- connected processing elements, called neurons. It has the capability of learning from example.
Advances in Neural Networks -- ISNN 2007 ; 4th International symposium on neural networks, ISNN 2007 Nanjing, China, June 3-7, 2007. Proceedings, Part III
An eural network is an information processing structure inspired by biological nervous systems, such as the brain. It consists of a large number of highly int- connected processing elements, called neurons. It has the capability of learning from example.
Advances in Intelligent Data Analysis VII ; 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, Proceedings
There su- ing oral presentations were then scheduled in a single-track, two-and-a-half-day conference program, summarized in the book that you have before you. In accordance with the stated IDA goal of "bringing together researchers from diverse disciplines," we believe we have achieved an excellent balance of presentationsfromthemoretheoretical-both statistical and machine learning- to the more application-oriented areas that illustrate how these techniques can beusedinpractice. Forexample, the proceeding sinclude papers withth eoretical contributions dealing with statistical approaches to sequence alignment as well as papers addressing practical problems in the areas of text classification and medical data analysis. It is reassuring to see that IDA continues to bring such diverse areas together, thus helping to cross-fertilize these fields
Advances in information system development : New methods and practice for the networked society ; Vol. 2
These volume on Information Systems Development examine the exchange of ideas between academia and industry and aims to explore new solutions. The field of Information Systems Development (ISD) progresses rapidly, continually creating new challenges for the professionals involved. New concepts, approaches and techniques of systems development emerge constantly in this field.
Advances in information system development : New methods and practice for the networked society ; Vol. 1
Advances in Information Systems Development: Bridging the Gap between Academia and Industry, Volumes 1 and 2, are the collected proceedings of the Fourteenth International Conference on Information Systems Development. These latest volumes on Information Systems Development examine the exchange of ideas between academia and industry and aims to explore new solutions.
Advances in Digital Forensics III ; IFIP International Conference on Digital Forensics, National Center for Forensic Science, Orlando Florida, January 28-January 31, 2007
Digital forensics deals with the acquisition, preservation, examination, analysis and presentation of electronic evidence. Networked computing, wireless communications and portable electronic devices have expanded the role of digital forensics beyond traditional computer crime investigations. Practically every crime now involves some aspect of digital evidence; digital forensics provides the techniques and tools to articulate this evidence. Digital forensics also has myriad intelligence applications. Furthermore, it has a vital role in information assurance -- investigations of security breaches yield valuable information that can be used to design more secure systems.it describes original research results and innovative applications in the emerging discipline of digital forensics. In addition, it highlights some of the major technical and legal issues related to digital evidence and electronic crime investigations.
Advances in digital forensics ; IFIP International Conference on digital forensics, National Center for Forensic Science, Orlando, Florida, February 13-16, 2005
Digital forensics deals with the acquisition, preservation, examination, analysis and presentation of electronic evidence. Networked computing, wireless communications and portable electronic devices have expanded the role of digital forensics beyond traditional computer crime investigations. Practically every crime now involves some aspect of digital evidence; digital forensics provides the techniques and tools to articulate this evidence. Digital forensics also has myriad intelligence applications. Furthermore, it has a vital role in information assurance – investigations of security breaches yield valuable information that can be used to design more secure systems. Advances in Digital Forensics describes original research results and innovative applications in the emerging discipline of digital forensics. In addition, it highlights some of the major technical and legal issues related to digital evidence and electronic crime investigations.
Advances in cryptology - CRYPTO -87 ; Conference on the theory and applications of cryptographic techniques : Proceedings
Zero-knowledge interactive proofsystems are a new technique which can be used as a cryptographic tool for designing provably secure protocols. Goldwasser, Micali, and Rackoff originally suggested this technique for controlling the knowledge released in an interactive proof of membership in a language, and for classification of languages. In this approach, knowledge is defined in terms of complexity to convey knowledge if it gives a computational advantage to the receiver, theory, and a message is said for example by giving him the result of an intractable computation. The formal model of interacting machines is described in. A proof-system (for a language L) is an interactive protocol by which one user, the prover, attempts to convince another user, the verifier, that a given input x is in L. We assume that the verifier is a probabilistic machine which is limited to expected polynomial-time computation, while the prover is an unlimited probabilistic machine.
