الصفحة 107
الصفحة 107
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 research and development ; 1st International Conference, BIRD 2007, Berlin, Germany, March 12-14, 2007, Proceedings
This volume covers a wide range of topics related to bioinformatics like microarray data, genomics, single nucleotide polymorphism, sequence analysis, systems biology, medical applications, proteomics, information systems.
Bioinformatics research and applications ; 3rd International Symposium,ISBRA 2007, Atlanta, GA, USA, May 7-10, 2007, Proceedings
This book including clustering and classification, gene expression analysis, gene networks, genome analysis, motif finding, pathways, protein structure prediction, protein domain interactions, phylogenetics, and software tools.
Bioinformatics research and applications : 4th International Symposium, ISBRA 2008, Atlanta, GA, USA, May 6-9, 2008. Proceedings
This book constitutes the refereed proceedings of the Fourth International Symposium on Bioinformatics Research and Applications, ISBRA 2008, held in Atlanta, GA, USA in May 2008.
Bioinformatics and Computational Biology Solutions Using R and Bioconductor
Bioconductor is a widely used open source and open development software project for the analysis and comprehension of data arising from high-throughput experimentation in genomics and molecular biology. Bioconductor is rooted in the open source statistical computing environment R. This volume's coverage is broad and ranges across most of the key capabilities of the Bioconductor project, including: Importation and preprocessing of high-throughput data from microarray, proteomic, and flow cytometry platforms / Curation and delivery of biological metadata for use in statistical modeling and interpretation. / Statistical analysis of high-throughput data, including machine learning and visualization,modeling and visualization of graphs and networks. This book is a dynamic document. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.
Bioinformatics : Problem Solving Paradigms
This book highlights basic paradigms of problem analysis and algorithm design in the context of core bioinformatics problems. Mathematically demanding themes are put across to the reader by properly chosen representations with the aid of lots of illustrations.
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 Recommender Systems ; Vol.1 : Algorithms, Architectures, Big Data, Security and Trust
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.
Big data analysis of nanoscience bibliometrics, patent, and funding data (2000-2019)
Presents an evaluation of nanotechnologies outputs (academic outputs and patents) and their impact from 2000-2019. The evaluation uses Elsevier’s Scopus (the largest abstract and citation database of peer-reviewed literature), SciVal (a scientific research analysis platform), Funding Institutional (a funding database), and PatentSight (a patent analysis platform). It covers four key topics regarding nanoscience research, including: 1) An overview of nano-related scholarly output, 2) Nanoscience and its contribution to basic science, 3) Nanoscience and its impact on and collaboration with industry partners, and 4) Key factors that promote the development of nanoscience.
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 – BigData 2020; 9th International Conference, Held as Part of the Services Conference Federation, SCF 2020, Honolulu, HI, USA, September 18-20, 2020, Proceedings
Constitutes the proceedings of the 9th International Conference on Big Data, BigData 2020, held as part of SCF 2020, during September 18-20, 2020. The conference was planned to take place in Honolulu, HI, USA and was changed to a virtual format due to the COVID-19 pandemic. The 16 full and 3 short papers presented were carefully reviewed and selected from 52 submissions. The topics covered are Big Data Architecture, Big Data Modeling, Big Data As A Service, Big Data for Vertical Industries (Government, Healthcare, etc.), Big Data Analytics, Big Data Toolkits, Big Data Open Platforms, Economic Analysis, Big Data for Enterprise Transformation, Big Data in Business Performance Management, Big Data for Business Model Innovations and Analytics, Big Data in Enterprise Management Models and Practices, Big Data in Government Management Models and Practices, and Big Data in Smart Planet Solutions.
Bidding Strategies in Agent-Based Continuous Double Auctions
Presents a new bidding strategy for agents to adopt in CDAs and propose tools to enhance the performance of existing bidding strategies in CDAs. The superior performance of the new bidding strategy as well as the tools presented in this book are illustrated through extensive experiments.
Bézier and Splines in image processing and machine vision
Digital image processing and machine vision have grown considerably during the last few decades. Of the various techniques, developed so far splines play a positive and significant role in many of them. This book deals with various image processing and machine vision problems efficiently with splines.
Beyond the Worst-Case Analysis of Algorithms
There are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve every computational problem. Nor are there silver bullets in algorithm analysis, as the most enlightening method for analyzing an algorithm often depends on the problem and the application. However, typical algorithms courses rely almost entirely on a single analysis framework, that of worst-case analysis, wherein an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which can be taught in lectures to beginning graduate students in theoretical computer science and machine learning.
Beyond knowledge : The legacy of competence : Meaningful computer-based learning environments
The edited and peer reviewed volume presents selected papers of the conference "Beyond knowlegde: the legacy of competence" It reflects the current state-of-the-art work of scholars worldwide within the area of learning and instruction with computers. Mainly, areas of computer-based learning environments supporting competence-focused knowledge acquisition but also foundational scientific work are addressed. More specific, contents cover cognitive processes in hypermedia and multimedia learning, social issues in computer-supported collaborative learning, motivation and emotion in Blended Learning and e-Learning.
Best practices in software measurement : How to use metrics to improve project and process performance
Not everything that counts can be counted. Not everything that is counted counts. Albert Einstein This is a book about software measurement from the practitioner’s point of view and it is a book for practitioners. Software measurement needs a lot of practical guidance to build upon experiences and to avoid repeating errors. This book t- gets exactly this need, namely to share experiences in a constructive way that can be followed. It tries to summarize experiences and knowledge about software measurement so that it is applicable and repeatable. It extracts experiences and lessons learned from the narrow context of the specific industrial situation, thus facilitating transfer to other contexts. Software measurement is not at a standstill. With the speed software engine- ing is evolving, software measurement has to keep pace. While the underlying theory and basic principles remain invariant in the true sense (after all, they are not specific to software engineering), the application of measurement to specific contexts and situations is continuously extended. The book thus serves as a ref- ence on these invariant principles as well as a practical guidance on how to make software measurement a success.
Beginning Visual C# 2005 Express ed. : From novice to professional
Wright took the same approach with this book that he did with the VB titles, and inside you'll find a fast–paced guide to the essentials to get you programming fast. You'll learn the C# language and the tools Visual C# 2005 Express provides. He covers everything from simple console programs to code that talks to the Internet, and even how to write your own database programs. Whatever your reasons for wanting to learn to program with C#, this book will get you where you want to be quickly, and hopefully with a smile on your face. So dive in and change the way you use computers forever.
Beginning Scala 3 : A functional and Object-Oriented Java Language
Introduces you to the Scala programming language, its object-oriented and functional programming characteristics, and then guides you through Scala constructs and libraries that allow you to assemble small components into high-performance, scalable systems. You will understand why Scala is judiciously used for critical business applications by leading companies such as Twitter, LinkedIn, Foursquare, the Guardian, Morgan Stanley, Credit Suisse, UBS, and HSBC – and you will be able to use it in your own projects. You will: Get started with Scala 3 or Scala language programming in general / Understand how to utilitze OOP in Scala / Perform functional programming in Scala / Master the use of Scala collections, traits and implicits / Leverage Java and Scala interopability / Employ Scala for DSL programming / Use patterns and best practices in Scala
