Refine Results
Sort By
From
To
Page 17
Page 17
Component-Based Software Development for Embedded Systems : An Overview of Current Research Trends
Embedded systems are ubiquitous. They appear in cell phones, microwave ovens, refrigerators, consumer electronics, cars, and jets. Some of these embedded s- tems are safety- or security-critical such as in medical equipment, nuclear plants, and X-by-wire control systems in naval, ground and aerospace transportation - hicles. With the continuing shift from hardware to software, embedded systems are increasingly dominated by embedded software. Embedded software is complex. Its engineering inherently involves a mul- disciplinary interplay with the physics of the embedding system or environment. Embedded software also comes in ever larger quantity and diversity. The next generation of premium automobiles will carry around one gigabyte of binary code. The proposed US DDX submarine is e?ectively a ?oating embedded so- ware system, comprising 30 billion lines of code written in over 100 programming languages. Embedded software is expensive. Cost estimates are quoted at around US$15– 30 per line (from commencement to shipping). In the defense realm, costs can range up to $100, while for highly critical applications, such as the Space Shuttle, the cost per line approximates $1,000. In view of the exponential increase in complexity, the projected costs of future embedded software are staggering.
Complexity Theory : Exploring the Limits of Efficient Algorithms
Complexity theory is the theory of determining the necessary resources for the solution of algorithmic problems and, therefore, the limits of what is possible with the available resources. An understanding of these limits prevents the search for non-existing efficient algorithms. This textbook considers randomization as a key concept and emphasizes the interplay between theory and practice: New branches of complexity theory continue to arise in response to new algorithmic concepts, and its results - such as the theory of NP-completeness - have influenced the development of all areas of computer science. The topics selected have implications for concrete applications, and the significance of complexity theory for today's computer science is stressed throughout.
Classification and Modeling with Linguistic Information Granules : Advanced Approaches to Linguistic Data Mining
Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod els. Computer systems can easily handle mathematical models even when they are complicated and nonlinear (e.g., neural networks). On the other hand, it is not always easy for human users to intuitively understand mathe matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com puter systems are designed to handle symbolic and numerical information. A large part of our daily communication is based on words. We learn from various media such as books, newspapers, magazines, TV, and the Inter net through words. We also communicate with others through words. While words play a central role in human information processing, linguistic models are not often used in the fields of classification and modeling. If there is no goal other than the maximization of accuracy in classification and modeling, mathematical models may always be preferred to linguistic models. On the other hand, linguistic models may be chosen if emphasis is placed on interpretability.
Chaos and fractals : New frontiers of science
Covers the central ideas and concepts of chaos and fractals as well as many related topics including: the Mandelbrot set, Julia sets, cellular automata, L-systems, percolation and strange attractors.
Case-Based Approximate Reasoning
Case-based reasoning (CBR) has received a great deal of attention in recent years and has established itself as a core methodology in the field of artificial intelligence. The key idea of CBR is to tackle new problems by referring to similar problems that have already been solved in the past. More precisely, CBR proceeds from individual experiences in the form of cases. The generalization beyond these experiences typically relies on a kind of regularity assumption demanding that 'similar problems have similar solutions'. Making use of different frameworks of approximate reasoning and reasoning under uncertainty, notably probabilistic and fuzzy set-based techniques, this book develops formal models of the above inference principle, which is fundamental to CBR. The case-based approximate reasoning methods thus obtained especially emphasize the heuristic nature of case-based inference and aspects of uncertainty in CBR. This way, the book contributes to a solid foundation of CBR which is grounded on formal concepts and techniques from the aforementioned fields. Besides, it establishes interesting relationships between CBR and approximate reasoning, which not only cast new light on existing methods but also enhance the development of novel approaches and hybrid systems.
Biometrics, Computer Security Systems and Artificial Intelligence Applications
This book presents the most recent achievements in some fascinating and rapidly developing fields within Computer Science. The scientific works presented in this book have been partitioned into three topical groups: Image Analysis and Biometrics, Computer Security Systems, and Artificial Intelligence and Applications. Image Analysis and Biometrics is the branch of Computer Science dealing with the very difficult task of artificial, visual perception of objects and surroundings, as well as the problems connected with it. Computer Security and Safety is at present a very important and intensively investigated branch of Computer Science because of the menacing activity of hackers and computer viruses.
Biometric User Authentication for IT Security : From Fundamentals to Handwriting
Biometric User Authentication for IT Security: From Fundamentals to Handwriting conveys general principals of passive (physiological trait like fingerprint, iris, face) and active (learned and trained behavior like voice, handwriting and gait) biometric recognition techniques to the reader. This professional book, unlike other publications in this area which concentrate on passive schemes, reflects a more comprehensive analysis of one particular active biometric technique: handwriting. Aspects which are thoroughly discussed include sensor characteristic dependency, attack scenarios, and the generation of cryptographic keys from handwriting.
Biomedical data mining for information retrieval : Methodologies, techniques, and applications
Discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally.
Biologically Inspired Algorithms for Financial Modelling
Then Part I provides a thorough guide to the various bioinspired methodologies – neural networks, evolutionary computing (particularly genetic algorithms and grammatical evolution), particle swarm and ant colony optimization, and immune systems. Part II brings the reader through the development of market trading systems. Finally, Part III examines real-world case studies where BIA methodologies are employed to construct trading systems in equity and foreign exchange markets, and for the prediction of corporate bond ratings and corporate failures.
Biological and artificial intelligence environments
The book reports the proceedings of the 15th Italian workshop on neural networks issued by the Italian Society on Neural Networks SIREN. The longevity recipe of this conference stands in three main points that normally renders the reading of these proceedings so interesting as appealing. 1. The topics of the neural networks is considered an attraction pole for a set of researches centered on the inherent paradigm of the neural networks, rather than on a specific tool exclusively. Thus, the subsymbolic management of the data information content constitutes the key feature of papers in various fields such as Pattern Recognition, Stochastic Optimization, Learning, Granular Computing, and so on, with a special bias toward bioinformatics operational applications. An excerpt of all these matters may be found in the book. 2. Though managed at domestic level, the conference attracts contributions from foreign researchers as well, so that in the book the reader may capture the flavor of the state of the art in the international community. 3. The conference is a meeting of friends as well. Thus the papers generally reflect a relaxed atmosphere where researchers meet to generously exchange their thought and explain their actual results in view of a common cultural growing of the community.
Bioinformatics research and development ; 2nd International Conference, BIRD 2008 Vienna, Austria, July 7-9, 2008 Proceedings
This book constitutes the refereed proceedings of the Second International Bioinformatics Research and Development Conference, BIRD 2008, held in Vienna, Austria in July 2008.
Bioinformatics
In this textbook present mathematical models in bioinformatics and they describe the biological problems that inspire the computer science tools used to handle the enormous data sets involved. The first part of the book covers the mathematical and computational methods, while the practical applications are presented in the second part. The mathematical presentation is descriptive and avoids unnecessary formalism, and yet remains clear and precise. Emphasis is laid on motivation through biological problems and cross applications. Each of the four chapters in the first part is accompanied by exercises and problems to support an understanding of the techniques presented. Each of the six chapters of the second part is devoted to some specific application domain: sequence alignment, molecular phylogenetics and coalescence theory, genomics, proteomics, RNA, and DNA microarrays. Each chapter concludes with a problems and projects section, to deepen the reader's understanding and to allow for the design of derived methods. Many of the projects involve publicly available software and/or Web-based bioinformatics depositories. Finally, the book closes with a thorough bibliography, reaching from classic research results to very recent findings, providing many pointers for future research.Overall, this volume is ideally suited for a senior undergraduate or graduate course on bioinformatics, with a strong focus on its mathematical and computer science background.
Big data-enabled internet of things
Covers analytical techniques for handling the huge amount of data generated by the Internet of Things, from architectures and platforms to security and privacy issues, applications, and challenges as well as future directions. The fields of Big Data and the Internet of Things (IoT) have seen tremendous advances, developments, and growth in recent years. The IoT is the inter-networking of connected smart devices, buildings, vehicles and other items which are embedded with electronics, software, sensors and actuators, and network connectivity that enable these objects to collect and exchange data. The IoT produces a lot of data. Big data describes very large and complex data sets that traditional data processing application software is inadequate to deal with, and the use of analytical methods to extract value from data. This edited book covers analytical techniques for handling the huge amount of data generated by the Internet of Things, from architectures and platforms to security and privacy issues, applications, and challenges as well as future directions.
Big Data Recommender Systems ; Vol.2 : Application Paradigms
Combines experimental and theoretical research on big data recommender systems to help computer scientists develop new concepts and methodologies for complex applications. It includes original scientific contributions in the form of theoretical foundations, comparative analysis, surveys, case studies, techniques and tools. First designed to generate personalized recommendations to users in the 90s, recommender systems apply knowledge discovery techniques to users’ data to suggest information, products, and services that best match their preferences. In recent decades, we have seen an exponential increase in the volumes of data, which has introduced many new challenges. recommender systems. Volume 2 covers a broad range of application paradigms for recommender systems over 22 chapters
Big Data : Conceptual Analysis and Applications
The book is devoted to the analysis of big data in order to extract from these data hidden patterns necessary for making decisions about the rational behavior of complex systems with the different nature that generate this data. To solve these problems, a group of new methods and tools is used, based on the self-organization of computational processes, the use of crisp and fuzzy cluster analysis methods, hybrid neural-fuzzy networks, and others. The book solves various practical problems. In particular, for the tasks of 3D image recognition and automatic speech recognition large-scale neural networks with applications for Deep Learning systems were used.
Big Data : An Art of Decision Making
Manipulating and processing masses of digital data is never a purely technical activity. It requires an interpretative and exploratory outlook - already well known in the social sciences and the humanities - to convey intelligible results from data analysis algorithms and create new knowledge. Big Data is based on an inquiry of several years within Proxem, a software publisher specializing in big data processing. The book examines how data scientists explore, interpret and visualize our digital traces to make sense of them, and to produce new knowledge. Grounded in epistemology and science and technology studies, Big Data offers a reflection on data in general, and on how they help us to better understand reality and decide on our daily actions.
Beginning XSLT 2.0 : From novice to professional
This followup to Jeni Tennison's Beginning XSLT has been updated to accomodate the revised XSLT standard. Part one of this book introduces XML and XSLT at a comfortable pace, and gradually demonstrates techniques for generating HTML (plus other formats), from XML. In part two, Tennison applies theory to real-life XSLT capabilities—including generating graphics. Each chapter includes step-by-step examples (with code available online), plus review questions at the end, to help you grasp the discussed features. In fact, all of the examples and exercises revolve around an interesting common theme: making TV listings available online. This book lives up to its name, and will definitely take you from a novice to a professional, in no time!
Beginning Web Development, Silverlight, and ASP.NET AJAX : From novice to professional
Beginning Web Development, Silverlight, and ASP.NET AJAX: From Novice to Professional aims to give you the skills you need to start building web applications with Microsoft's next–generation technology as quickly as possible. Whether you're interested in ASP.NET AJAX, Silverlight, or the technologies that support them (WPF, WCF, WF, etc.), this book is the starting point that you need. It adopts a “zero to hero” approach that concentrates on achieving practical results you can use in real projects rather than presenting a deep academic treatment that can't be immediately applied.
Beginning Ubuntu Linux
Beginning Ubuntu Linux, the award–winning and best–selling Ubuntu book for beginners, is now in its third edition, presenting readers with an up–to–the–minute introduction to the world of Linux and the open source community. A detailed overview of Ubuntu's installation and configuration process encourages you to take the plunge and switch to Linux, and from there you'll learn how to wield total control over your newly installed operating system. Guided through the most commonly desired tasks such as printer configuration, listening to audio CDs and MP3s, watching movies, performing office and Internet–related tasks, as well as general system maintenance matters, authors Keir Thomas and Jaime Sicam will soon have you using and enjoying Ubuntu Linux and never looking back.
Beginning SQL Queries : From novice to professional
Clare Churcher's Beginning SQL Queries is your guide to mastering the lingua franca of the database industry: the SQL language. Good knowledge of SQL is crucial to anyone working with databases, because it is with SQL that you retrieve data, manipulate data, and generate business results. Knowing how to write good queries is the foundation for all work done in SQL, and it is a foundation that Clare lays well in her book.
