الصفحة 65
الصفحة 65
Bio-inspired modeling of cognitive tasks ; 2nd International Work-conference on the interplay between natural and artificial computation, IWINAC 2007, La Manga del Mar Menor, Spain, June 18-21, 2007, Proceedings, Part I
This volume includes all the contributions mainly related with theoretical, conceptual and methodological aspects linking AI and knowledge engineering with neurophysiology, clinics and cognition.
Bio-inspired credit risk analysis : Computational intelligence with support vector machines
Credit risk analysis is one of the most important topics in the field of financial risk management. Due to recent financial crises and regulatory concern of Basel II, credit risk analysis has been the major focus of financial and banking industry. Especially for some credit-granting institutions such as commercial banks and credit companies, the ability to discriminate good customers from bad ones is crucial. The need for reliable quantitative models that predict defaults accurately is imperative so that the interested parties can take either preventive or corrective action. Hence credit risk analysis becomes very important for sustainability and profit of enterprises. In such backgrounds, this book tries to integrate recent emerging support vector machines and other computational intelligence techniques that replicate the principles of bio-inspired information processing to create some innovative methodologies for credit risk analysis and to provide decision support information for interested parties.
Bio-inspired computing and communication ; 1st Workshop on Bio-inspired design of networks, BIOWIRE 2007 Cambridge, UK, April 2-5, 2007 Revised Selected Papers
The book constitutes the thoroughly refereed post-workshop proceedings of the First Workshop on Bio-Inspired Design of Networks, BIOWIRE 2007, held in Cambridge, UK, in April 2007.
Bio-inspired computational intelligence and applications ; International conference on life system modeling, and simulation, LSMS 2007, Shanghai, China, September 14-17, 2007. Proceedings
It covers both micro and macro c- ponents ranging from cells, tissues and organs across to organisms and ecologic niches. These interact and evolve to produce an overall complex system whose beh- ior is difficult to comprehend and predict.The arrival of the 21st century has been marked by a resurgence of research interest both in arriving at a systems-level und- standing of biology and in applying such knowledge in complex real-world appli- tions. Consequently, computational methods and intelligence in systems, biology, as well as bio-inspired computational intelligence, have emerged as key drivers for new computational methods. For this reason papers dealing with theory, techniques and real-world applications relating to these two themes were especially solicited.
Bioinformatics of genome regulation and structure II
The conference was organized by the Laboratory of Theoretical Genetics, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia. The material covers the most recent topics in bioinformatics, including (i) regulatory genomic sequences: databases, knowledge bases, computer analysis, modeling, and recognition; (ii) large-scale genome analysis and functional annotation; (iii) gene structure detection and prediction; (iv) comparative and evolutionary genomics; (v) computer analysis of genome polymorphism and evolution; computer analysis and modeling of transcription, splicing, and translation; structural computational biology: structure- function organization of genomic DNA, RNA, and proteins; (vi) gene networks, signal transduction pathways, and genetically controlled metabolic pathways: databases, knowledge bases, computer analysis, and modeling; principles of organization, operation, and evolution; (vii) data warehousing, knowledge discovery and data mining; and (viii) analysis of basic patterns of genome operation, organization, and evolution.
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.
Bioeconomic modelling and valuation of exploited marine ecosystems
This book offers an environmental-economic analysis of exploited ecosystems with a clear policy orientation. The study tries to move beyond traditional economic fishery analysis in two respects. First, several theoretical and numerical models are offered that combine economic and ecological descriptions of fisheries. These models give special attention to spatial processes as well as to combining exploitation and conservation objectives. Second, valuation and stakeholder concerns are addressed in empirical analyses employing both qualitative and quantitative approaches. The latter is done by using advanced methods of monetary valuation. In addition, the first part of the book presents short, introductory overviews of integrated assessment, economic modeling of fishery management, and incorporating uncertainty in fisheries analysis.
Bioactive Heterocycles IV
This volume contains nine more contributions from expert researchers of the?eld, providing readers with in depth and current research results regarding therespective topics. In the?rst chapter, Flemming et al. review the chemistry, biosynthesis, metabolism and biological activities of tetrahydrocannabinol and its deri- tives. Hansch and Verma contribute to the quantitative structure-activity re- tionship (QSAR) analysis of heterocyclic topoisomerase I and II inhibitors. These inhibitors, knowntoinhibit either enzyme, actasantitumoragentsand are currently used in chemotherapy and in clinicaltrials. In the third chapter, Khan reviews some aspects of molecular modeling studies on biologically active alkaloids.
BIM for design firms : Data rich architecture at small and medium scales
Expands on Building Information Modeling, showing its applicability to a range of design-oriented projects. It emphasizes the full impact that a data modeling tool has on design processes, systems, and the high level of collaboration required across the design team. It also explains the quantitative analysis opportunities that BIM affords for sustainable design and for balancing competing design agendas, while highlighting the benefits BIM offers to designing in 3D for construction. The book concludes with a deep look at the possible future of BIM and digitally-enhanced design.
Big Data in Energy Economics
Combines energy economics and big data modeling analysis in energy conversion and management and comprehensively introduces the relevant theories, key technologies, and application examples of the smart energy economy. With the help of time series big data modeling results, energy economy managers develop reasonable and feasible pricing mechanisms of electricity price and improve the absorption capacity of the power grid. In addition, they also carry out scientific power equipment scheduling and cost–benefit analysis according to the results of data mining, so as to avoid the loss caused by accidental damage of equipment. Energy users adjust their power consumption behavior through the modeling results provided and achieve the effect of energy saving and emission reduction while reasonably reducing the electricity expenditure.
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.
Bifurcations, Instabilities, Degradation in Geomechanics
Leading international researchers and practitioners of bifurcations and instabilities in geomechanics debate the developments and applications which have occurred over the last few decades. The topics covered include modeling of bifurcation, structural failure of geomaterials and geostructures, advanced analytical, numerical and experimental techniques, and application and development of generalised continuum models etc. In addition analytical solutions, numerical methods, experimental techniques, and case histories are presented. Beside fundamental research findings, applications in geotechnical, petroleum, mining, and bulk materials engineering are emphasised.
Biased technical change and economic conservation laws
Makes use of Lie groups to shed new light on the analysis of economic conservation laws. Economic conservation laws are not simply abstract concepts; this book shows that they are tools of empirical analysis that can be applied to such topics as analyses of macro performance and corporate efficiency.
Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series
This book discusses the statistical methods most often applied for such adjustments, ranging from ad hoc procedures to regression-based models. The latter are emphasized, because of their clarity, ease of application, and superior results. Each topic is illustrated with many real case examples. In order to facilitate understanding of their properties and limitations of the methods discussed, a real data example, the Canada Total Retail Trade Series, is followed throughout the book.This book brings together the scattered literature on these topics and presents them using a consistent notation and a unifying view.
Beginning relational data modeling
Data storage design, and awareness of how data needs to be utilized within an organization, is of prime importance in ensuring that company data systems work efficiently. 'Beginning Data Modeling' leads readers you step by step through the process of developing an effective logical data model for a relational database model.
Beginning Object-Oriented Programming with VB 2005 : From novice to professional
Beginning Object-Oriented Programming with VB 2005 is a comprehensive resource of correct coding procedures. Author Daniel Clark takes you through all the stages of a programming project, including analysis, modeling, and development, all using object-oriented programming techniques and Visual Basic .NET. Clark explores the structure of classes and their hierarchies, as well as inheritance and interfaces. He also introduces the .NET Framework and the Visual Studio integrated development environment, or IDE. A real-world case study walks you through the design of a solution. You can then transform the design into a functional VB .NET application. The application includes a graphical user interface (GUI), a business logic class library, and integration with a back-end database. Throughout the book, you'll explore the fundamentals of software design, object-oriented programming, Visual Basic .NET 2.0, and the Unified Modeling Language (UML).
Beginning Java Objects : From concepts to code
Learning to design objects effectively with Java is the goal of Beginning Java Objects: From Concepts to Code, Second Edition. Plenty of titles dig into the Java language in massive detail, but this one takes the unique approach of stepping back and looking at fundamental object concepts first. Mastery of Java—from understanding the basic language features to building complete industrial-strength Java applications—emerges only after a thorough tour of thinking in objects. The first edition of Beginning Java Objects has been a bestseller; this second edition includes material on the key features of J2SE 5, conceptual introductions to JDBC and J2EE, and an in-depth treatment of the critical design principles of model-data layer separation and model-view separation.
Bayesian networks and Influence diagrams : A guide to construction and analysis
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification, troubleshooting, and data mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty.
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 core : A practical approach to computational Bayesian statistics
This Bayesian modeling book provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical justifications. Special attention is paid to the derivation of prior distributions in each case and specific reference solutions are given for each of the models.
