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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 technologies
Solving modern biological problems requires advanced computational methods. Bioinformatics evolved from the active interaction of two fast-developing disciplines, biology and information technology. The central issue of this emerging field is the transformation of often distributed and unstructured biological data into meaningful information. This book describes the application of well-established concepts and techniques from areas like data mining, machine learning, database technologies, and visualization techniques to problems like protein data analysis, genome analysis and sequence databases. Chen has collected contributions from leading researchers in each area. The chapters can be read independently, as each offers a complete overview of its specific area, or, combined, this monograph is a comprehensive treatment that will appeal to students, researchers, and R&D professionals in industry who need a state-of-the-art introduction into this challenging and exciting young field.
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 : 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.
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.
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 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
Beginning Java Data Structures and Algorithms : Sharpen your problem solving skills by learning core computer science concepts in a pain-free manner
Teaches you tools that you can use to build efficient applications. It starts with an introduction to algorithms and big O notation, later explains bubble, merge, quicksort, and other popular programming patterns. You’ll also learn about data structures such as binary trees, hash tables, and graphs. The book progresses to advanced concepts, such as algorithm design paradigms and graph theory. By the end of the book, you will know how to correctly implement common algorithms and data structures within your applications.
Beginning Java 17 Fundamentals : Object-Oriented Programming in Java 17
Learn the fundamentals of the Java 17 LTS or Java Standard Edition version 17 Long Term Support release, including basic programming concepts and the object-oriented fundamentals necessary at all levels of Java development. You will: Write your first Java programs with emphasis on learning object-oriented programming / How to work with switch expressions, value types (records), local variable type inference, pattern matching switch and more from Java 17 / Handle exceptions, assertions, strings and dates, and object formatting / Learn about how to define and use modules / Dive in depth into classes, interfaces, and inheritance in Java / Use regular expressions / Take advantage of the JShell REPL tool
Bayesian Networks and Decision Graphs
Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. As modeling languages they allow a natural specification of problem domains with inherent uncertainty, and from a computational perspective they support efficient algorithms for automatic construction and query answering. This includes belief updating, finding the most probable explanation for the observed evidence, detecting conflicts in the evidence entered into the network, determining optimal strategies, analyzing for relevance, and performing sensitivity analysis. The book introduces probabilistic graphical models and decision graphs, including Bayesian networks and influence diagrams.It contians two parts. The first part focuses on probabilistic graphical models. Compared with the previous book, the new edition also includes a thorough description of recent extensions to the Bayesian network modeling language, advances in exact and approximate belief updating algorithms, and methods for learning both the structure and the parameters of a Bayesian network. The second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision processes and partially ordered decision problems.
Bayesian Methods in the Search for MH370
This book demonstrates how nonlinear/non-Gaussian Bayesian time series estimation methods were used to produce a probability distribution of potential MH370 flight paths. It provides details of how the probabilistic models of aircraft flight dynamics, satellite communication system measurements, environmental effects and radar data were constructed and calibrated. The probability distribution was used to define the search zone in the southern Indian Ocean. The book describes particle-filter based numerical calculation of the aircraft flight-path probability distribution and validates the method using data from several of the involved aircraft’s previous flights. Finally it is shown how the Reunion Island flaperon debris find affects the search probability distribution.
Balanced Website Design : Optimising Aesthetics, Usability and Purpose
Balanced Website Design (BWD) is a new methodology that fuses the strengths of traditional structured, stepped, and iterative approaches with a sharp focus on defining and achieving the desired characteristics of purpose, usability and aesthetics – absolutely essential requirements for any website. The book includes discussions of new perspectives on usability and aesthetics in the special context of website design. BWD is suitable for all types of websites, for individual and/or team projects, and should prove to be of significant value for even the most experienced of website designers. BWD provides guidance, structure and detailed documentation/process support for the activity of designing and implementing your next website – helping you to maximise its effectiveness and relevance.
