974 resultados para Adjusting computing methods
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This study evaluates two methods for estimating a soilís hydraulic conductivity: in-situ infiltration tests and grain-size analyses. There are numerous formulas in the literature that relate hydraulic conductivity to various parameters of the infiltrating medium, but studies have shown that these formulas do not perform well when applied to depositional environments that differ from those used to derive the formulas. Thus, there exists a need to specialize infiltration tests and related grain-size analyses for the Vashon advance outwash in the Puget Lowland. I evaluated 134 infiltration tests and 119 soil samples to find a correlation between grain-size parameters and hydraulic conductivity. This work shows that a constant-head borehole infiltration test that accounts for capillarity with alpha approximately 5m^-1 is an effective method for calculating hydraulic conductivity from our flow tests. Then, by conducting grain-size analysis and applying a multiple linear regression, I show that the hydraulic conductivity can also be estimated by log(K) = 1.906 + 0.102D_10 + 0.039D_60 - 0.034D_90 - 7.952F_fines. This result predicts the infiltration rate with a 95% confidence interval of 20 ft/day. The results of study are for application in the Puget Lowland.
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A variety of current and future wired and wireless networking technologies can be transformed into a seamless communication environments through application of context-based vertical handovers. Such seamless communication environments are needed for future pervasive/ubiquitous systems. Pervasive systems are context aware and need to adapt to context changes, including network disconnections and changes in network Quality of Service (QoS). Vertical handover is one of many possible adaptation methods. It allows users to roam freely between heterogeneous networks while maintaining the continuity of their applications. This paper proposes a vertical handover mechanism suitable for multimedia applications in pervasive systems. The paper focuses on the handover decision making process which uses context information regarding user devices, user location, network environment and requested QoS. (C) 2004 Elsevier B.V. All rights reserved.
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This paper gives a review of recent progress in the design of numerical methods for computing the trajectories (sample paths) of solutions to stochastic differential equations. We give a brief survey of the area focusing on a number of application areas where approximations to strong solutions are important, with a particular focus on computational biology applications, and give the necessary analytical tools for understanding some of the important concepts associated with stochastic processes. We present the stochastic Taylor series expansion as the fundamental mechanism for constructing effective numerical methods, give general results that relate local and global order of convergence and mention the Magnus expansion as a mechanism for designing methods that preserve the underlying structure of the problem. We also present various classes of explicit and implicit methods for strong solutions, based on the underlying structure of the problem. Finally, we discuss implementation issues relating to maintaining the Brownian path, efficient simulation of stochastic integrals and variable-step-size implementations based on various types of control.
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What is the computational power of a quantum computer? We show that determining the output of a quantum computation is equivalent to counting the number of solutions to an easily computed set of polynomials defined over the finite field Z(2). This connection allows simple proofs to be given for two known relationships between quantum and classical complexity classes, namely BQP subset of P-#P and BQP subset of PP.
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Systems biology is based on computational modelling and simulation of large networks of interacting components. Models may be intended to capture processes, mechanisms, components and interactions at different levels of fidelity. Input data are often large and geographically disperse, and may require the computation to be moved to the data, not vice versa. In addition, complex system-level problems require collaboration across institutions and disciplines. Grid computing can offer robust, scaleable solutions for distributed data, compute and expertise. We illustrate some of the range of computational and data requirements in systems biology with three case studies: one requiring large computation but small data (orthologue mapping in comparative genomics), a second involving complex terabyte data (the Visible Cell project) and a third that is both computationally and data-intensive (simulations at multiple temporal and spatial scales). Authentication, authorisation and audit systems are currently not well scalable and may present bottlenecks for distributed collaboration particularly where outcomes may be commercialised. Challenges remain in providing lightweight standards to facilitate the penetration of robust, scalable grid-type computing into diverse user communities to meet the evolving demands of systems biology.
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This paper describes methods used to support collaboration and communication between practitioners, designers and engineers when designing ubiquitous computing systems. We tested methods such as “Wizard of Oz” and design games in a real domain, the dental surgery, in an attempt to create a system that is: affordable; minimally disruptive of the natural flow of work; and improves human-computer interaction. In doing so we found that such activities allowed the practitioners to be on a ‘level playing ground’ with designers and engineers. The findings we present suggest that dentists are willing to engage in detailed exploration and constructive critique of technical design possibilities if the design ideas and prototypes are presented in the context of their work practice and are of a resolution and relevance that allow them to jointly explore and question with the design time. This paper is an extension of a short paper submitted to the Participatory Design Conference, 2004.
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Many variables that are of interest in social science research are nominal variables with two or more categories, such as employment status, occupation, political preference, or self-reported health status. With longitudinal survey data it is possible to analyse the transitions of individuals between different employment states or occupations (for example). In the statistical literature, models for analysing categorical dependent variables with repeated observations belong to the family of models known as generalized linear mixed models (GLMMs). The specific GLMM for a dependent variable with three or more categories is the multinomial logit random effects model. For these models, the marginal distribution of the response does not have a closed form solution and hence numerical integration must be used to obtain maximum likelihood estimates for the model parameters. Techniques for implementing the numerical integration are available but are computationally intensive requiring a large amount of computer processing time that increases with the number of clusters (or individuals) in the data and are not always readily accessible to the practitioner in standard software. For the purposes of analysing categorical response data from a longitudinal social survey, there is clearly a need to evaluate the existing procedures for estimating multinomial logit random effects model in terms of accuracy, efficiency and computing time. The computational time will have significant implications as to the preferred approach by researchers. In this paper we evaluate statistical software procedures that utilise adaptive Gaussian quadrature and MCMC methods, with specific application to modeling employment status of women using a GLMM, over three waves of the HILDA survey.
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Pervasive systems need to be context aware and need to adapt to context changes, including network disconnections and changes in network Quality of Service (QoS). Vertical handover (handover between heterogeneous networks) is one of possible adaptation methods. It allows users to roam freely between heterogeneous networks while maintaining continuity of their applications. This paper proposes a vertical handover approach suitable for multimedia applications in pervasive systems. It describes the adaptability decision making process which uses vertical handovers to support users mobility and provision of QoS suitable for users’ applications. The process evaluates context information regarding user devices, User location, network environment, and user perceived QoS of applications.
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While developments in distributed object computing environments, such as the Common Object Request Broker Architecture (CORBA) [17] and the Telecommunication Intelligent Network Architecture (TINA) [16], have enabled interoperability between domains in large open distributed systems, managing the resources within such systems has become an increasingly complex task. This challenge has been considered for several years within the distributed systems management research community and policy-based management has recently emerged as a promising solution. Large evolving enterprises present a significant challenge for policy-based management partly due to the requirement to support both mutual transparency and individual autonomy between domains [2], but also because the fluidity and complexity of interactions occurring within such environments requires an ability to cope with the coexistence of multiple, potentially inconsistent policies. This paper discusses the need of providing both dynamic (run-time) and static (compile-time) conflict detection and resolution for policies in such systems and builds on our earlier conflict detection work [7, 8] to introduce the methods for conflict resolution in large open distributed systems.
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In this thesis various mathematical methods of studying the transient and dynamic stabiIity of practical power systems are presented. Certain long established methods are reviewed and refinements of some proposed. New methods are presented which remove some of the difficulties encountered in applying the powerful stability theories based on the concepts of Liapunov. Chapter 1 is concerned with numerical solution of the transient stability problem. Following a review and comparison of synchronous machine models the superiority of a particular model from the point of view of combined computing time and accuracy is demonstrated. A digital computer program incorporating all the synchronous machine models discussed, and an induction machine model, is described and results of a practical multi-machine transient stability study are presented. Chapter 2 reviews certain concepts and theorems due to Liapunov. In Chapter 3 transient stability regions of single, two and multi~machine systems are investigated through the use of energy type Liapunov functions. The treatment removes several mathematical difficulties encountered in earlier applications of the method. In Chapter 4 a simple criterion for the steady state stability of a multi-machine system is developed and compared with established criteria and a state space approach. In Chapters 5, 6 and 7 dynamic stability and small signal dynamic response are studied through a state space representation of the system. In Chapter 5 the state space equations are derived for single machine systems. An example is provided in which the dynamic stability limit curves are plotted for various synchronous machine representations. In Chapter 6 the state space approach is extended to multi~machine systems. To draw conclusions concerning dynamic stability or dynamic response the system eigenvalues must be properly interpreted, and a discussion concerning correct interpretation is included. Chapter 7 presents a discussion of the optimisation of power system small sjgnal performance through the use of Liapunov functions.
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This thesis describes research on End-User Computing (EUC) in small business in an environment where no Information System (IS) support and expertise are available. The research aims to identify the factors that contribute to EUC Sophistication and understand the extent small firms are capable of developing their own applications. The intention is to assist small firms to adopt EUC, encourage better utilisation of their IT resources and gain the benefits associated with computerisation. The factors examined are derived inductively from previous studies where a model is developed to map these factors with the degree of sophistication associated with IT and EUC. This study attempts to combine the predictive power of quantitative research through surveys with the explanatory power of qualitative research through action-oriented case study. Following critical examination of the literature, a survey of IT Adoption and EUC was conducted. Instruments were then developed to measure EUC and IT Sophistication indexes based on sophistication constructs adapted from previous studies using data from the survey. This is followed by an in-depth action case study involving two small firms to investigate the EUC phenomenon in its real life context. The accumulated findings from these mixed research strategies are used to form the final model of EUC Sophistication in small business. Results of the study suggest both EUC Sophistication and the Presence of EUC in small business are affected by Management Support and Behaviour towards EUC. Additionally EUC Sophistication is also affected by the presence of an EUC Champion. Results are also consistent with respect to the independence between IT Sophistication and EUC Sophistication. The main research contributions include an accumulated knowledge of EUC in small business, the Model of EUC Sophistication, an instrument to measure EUC Sophistication Index for small firms, and a contribution to research methods in IS.
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The study here highlights the potential that analytical methods based on Knowledge Discovery in Databases (KDD) methodologies have to aid both the resolution of unstructured marketing/business problems and the process of scholarly knowledge discovery. The authors present and discuss the application of KDD in these situations prior to the presentation of an analytical method based on fuzzy logic and evolutionary algorithms, developed to analyze marketing databases and uncover relationships among variables. A detailed implementation on a pre-existing data set illustrates the method. © 2012 Published by Elsevier Inc.
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The evolution of cognitive neuroscience has been spurred by the development of increasingly sophisticated investigative techniques to study human cognition. In Methods in Mind, experts examine the wide variety of tools available to cognitive neuroscientists, paying particular attention to the ways in which different methods can be integrated to strengthen empirical findings and how innovative uses for established techniques can be developed. The book will be a uniquely valuable resource for the researcher seeking to expand his or her repertoire of investigative techniques. Each chapter explores a different approach. These include transcranial magnetic stimulation, cognitive neuropsychiatry, lesion studies in nonhuman primates, computational modeling, psychophysiology, single neurons and primate behavior, grid computing, eye movements, fMRI, electroencephalography, imaging genetics, magnetoencephalography, neuropharmacology, and neuroendocrinology. As mandated, authors focus on convergence and innovation in their fields; chapters highlight such cross-method innovations as the use of the fMRI signal to constrain magnetoencephalography, the use of electroencephalography (EEG) to guide rapid transcranial magnetic stimulation at a specific frequency, and the successful integration of neuroimaging and genetic analysis. Computational approaches depend on increased computing power, and one chapter describes the use of distributed or grid computing to analyze massive datasets in cyberspace. Each chapter author is a leading authority in the technique discussed.
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This paper is partially supported by project ISM-4 of Department for Scientific Research, “Paisii Hilendarski” University of Plovdiv.