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Variable Methods (variable + methods)

Distribution by Scientific Domains

Engineering	50%

Selected Abstracts

Systematic review: secondary prevention with band ligation, pharmacotherapy or combination therapy after bleeding from oesophageal varices

ALIMENTARY PHARMACOLOGY & THERAPEUTICS, Issue 6 2009
J. CHEUNG
Summary Background, Variable methods are available for secondary prevention after oesophageal variceal bleeding (EVB). Aim, To compare band ligation (BL), pharmacotherapy (PT) and BL+PT for EVB secondary prevention. Methods, A systematic search of databases, references and meeting abstracts was conducted for randomized trials of BL, PT or BL+PT. The outcomes were mortality, rebleeding and adverse events. A random-effects model was used for meta-analyses. Results, Twelve trials were included (6 BL vs. PT, 4 BL+PT vs. BL, 2 BL+PT vs. PT). All trials used beta-blockers ± isosorbide mononitrate (ISMN) as PT. Mortality was not significantly different among trials. Rebleeding was not significantly different for BL vs. PT (RR 1.00, 95% CI 0.73,1.37). BL reduced rebleeding compared with PT for trials with mean beta-blocker dose <80 mg/day (RR 0.67, 95% CI 0.49,0.91). There were nonsignificant differences in rebleeding for BL+PT vs. BL (RR 0.57, 95% CI 0.31,1.08) and BL+PT vs. PT (RR 0.76, 95% CI 0.56,1.03). There was no difference in adverse events between BL vs. PT, but was higher with BL+PT vs. BL. Conclusion, Band ligation and PT alone are comparable for secondary prevention of rebleeding after EVB. Further trials with adequate PT dosing are required to determine the efficacy of combination BL+PT therapy. [source]

Parallel multipole implementation of the generalized Helmholtz decomposition for solving viscous flow problems

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 11 2003
Mary J. Brown
Abstract The evaluation of a domain integral is the dominant bottleneck in the numerical solution of viscous flow problems by vorticity methods, which otherwise demonstrate distinct advantages over primitive variable methods. By applying a Barnes,Hut multipole acceleration technique, the operation count for the integration is reduced from O(N2) to O(NlogN), while the memory requirements are reduced from O(N2) to O(N). The algorithmic parameters that are necessary to achieve such scaling are described. The parallelization of the algorithm is crucial if the method is to be applied to realistic problems. A parallelization procedure which achieves almost perfect scaling is shown. Finally, numerical experiments on a driven cavity benchmark problem are performed. The actual increase in performance and reduction in storage requirements match theoretical predictions well, and the scalability of the procedure is very good. Copyright © 2003 John Wiley Sons, Ltd. [source]

Application of latent variable methods to process control and multivariate statistical process control in industry

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 4 2005
Theodora Kourti
Abstract Multivariate monitoring and control schemes based on latent variable methods have been receiving increasing attention by industrial practitioners in the last 15 years. Several companies have enthusiastically adopted the methods and have reported many success stories. Applications have been reported where multivariate statistical process control, fault detection and diagnosis is achieved by utilizing the latent variable space, for continuous and batch processes, as well as, for process transitions as for example start ups and re-starts. This paper gives an overview of the latest developments in multivariate statistical process control (MSPC) and its application for fault detection and isolation (FDI) in industrial processes. It provides a critical review of the methodology and describes how it is transferred to the industrial environment. Recent applications of latent variable methods to process control as well as to image analysis for monitoring and feedback control are discussed. Finally it is emphasized that the multivariate nature of the data should be preserved when data compression and data preprocessing is applied. It is shown that univariate data compression and reconstruction may hinder the validity of multivariate analysis by introducing spurious correlations. Copyright © 2005 John Wiley & Sons, Ltd. [source]

Analysis of a finite-buffer bulk-service queue with discrete-Markovian arrival process: D-MAP/Ga,b/1/N

NAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 4 2003
M.L. Chaudhry
Abstract Discrete-time queues with D-MAP arrival process are more useful in modeling and performance analysis of telecommunication networks based on the ATM environment. This paper analyzes a finite-buffer discrete-time queue with general bulk-service rule, wherein the arrival process is D-MAP and service times are arbitrarily and independently distributed. The distributions of buffer contents at various epochs (departure, random, and prearrival) have been obtained using imbedded Markov chain and supplementary variable methods. Finally, some performance measures such as loss probability and average delay are discussed. Numerical results are also presented in some cases. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 345,363, 2003. [source]

Applications of Taxometric Methods to Problems of Comorbidity: Perspectives and Challenges

CLINICAL PSYCHOLOGY: SCIENCE AND PRACTICE, Issue 4 2001
Irwin D. Waldman
We share Meehl's view that taxometric procedures hold considerable promise for elucidating questions regarding psychiatric comorbidity. Drawing on examples from the domain of childhood disruptive disorders, we discuss why the issues raised by Meehl are scientifically and pragmatically important and outline several profitable applications of taxometric methods to questions of comorbidity (e.g., estimating the statistical relations between latent taxa). We explain why taxometric methods and other sophisticated latent variable methods are needed to answer such questions and provide examples of how certain statistical methods have been used to make erroneous inferences regarding taxonicity. Several important unresolved issues bearing on the use of taxometric procedures and their application to questions of comorbidity are delineated, including (a) the distributional assumptions of taxometric methods, (b) the construct validation of provisional taxa identified by taxometric analyses, (c) the relation of taxometric methods to other latent variable techniques (e.g., latent class analysis), (d) the potential existence of spurious taxa, (e) the question of "fuzzy taxonicity," and (f) "configural taxa." We conclude with a discussion of analytic methods for characterizing and understanding the covariation between latent dimensions as opposed to taxa. [source]