854 resultados para Recall interval
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There has been a resurgence of interest in the mean trace length estimator of Pahl for window sampling of traces. The estimator has been dealt with by Mauldon and Zhang and Einstein in recent publications. The estimator is a very useful one in that it is non-parametric. However, despite some discussion regarding the statistical distribution of the estimator, none of the recent works or the original work by Pahl provide a rigorous basis for the determination a confidence interval for the estimator or a confidence region for the estimator and the corresponding estimator of trace spatial intensity in the sampling window. This paper shows, by consideration of a simplified version of the problem but without loss of generality, that the estimator is in fact the maximum likelihood estimator (MLE) and that it can be considered essentially unbiased. As the MLE, it possesses the least variance of all estimators and confidence intervals or regions should therefore be available through application of classical ML theory. It is shown that valid confidence intervals can in fact be determined. The results of the work and the calculations of the confidence intervals are illustrated by example. (C) 2003 Elsevier Science Ltd. All rights reserved.
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The Timed Interval Calculus, a timed-trace formalism based on set theory, is introduced. It is extended with an induction law and a unit for concatenation, which facilitates the proof of properties over trace histories. The effectiveness of the extended Timed Interval Calculus is demonstrated via a benchmark case study, the mine pump. Specifically, a safety property relating to the operation of a mine shaft is proved, based on an implementation of the mine pump and assumptions about the environment of the mine. (C) 2002 Elsevier Science B.V. All rights reserved.
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This article is is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Attribution-NonCommercial (CC BY-NC) license lets others remix, tweak, and build upon work non-commercially, and although the new works must also acknowledge & be non-commercial.
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This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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We derived a framework in integer programming, based on the properties of a linear ordering of the vertices in interval graphs, that acts as an edge completion model for obtaining interval graphs. This model can be applied to problems of sequencing cutting patterns, namely the minimization of open stacks problem (MOSP). By making small modifications in the objective function and using only some of the inequalities, the MOSP model is applied to another pattern sequencing problem that aims to minimize, not only the number of stacks, but also the order spread (the minimization of the stack occupation problem), and the model is tested.
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The minimum interval graph completion problem consists of, given a graph G = ( V, E ), finding a supergraph H = ( V, E ∪ F ) that is an interval graph, while adding the least number of edges |F| . We present an integer programming formulation for solving the minimum interval graph completion problem recurring to a characteri- zation of interval graphs that produces a linear ordering of the maximal cliques of the solution graph.
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In this paper we address an order processing optimization problem known as the Minimization of Open Stacks Problem (MOSP). This problem consists in finding the best sequence for manufacturing the different products required by costumers, in a setting where only one product can be made at a time. The objective is to minimize the maximum number of incomplete orders from costumers that are being processed simultaneously. We present an integer programming model, based on the existence of a perfect elimination order in interval graphs, which finds an optimal sequence for the costumers orders. Among other economic advantages, manufacturing the products in this optimal sequence reduces the amount of space needed to store incomplete orders.
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The problem addressed here originates in the industry of flat glass cutting and wood panel sawing, where smaller items are cut from larger items accordingly to predefined cutting patterns. In this type of industry the smaller pieces that are cut from the patterns are piled around the machine in stacks according to the size of the pieces, which are moved to the warehouse only when all items of the same size have been cut. If the cutting machine can process only one pattern at a time, and the workspace is limited, it is desirable to set the sequence in which the cutting patterns are processed in a way to minimize the maximum number of open stacks around the machine. This problem is known in literature as the minimization of open stacks (MOSP). To find the best sequence of the cutting patterns, we propose an integer programming model, based on interval graphs, that searches for an appropriate edge completion of the given graph of the problem, while defining a suitable coloring of its vertices.
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In this paper we address an order processing optimization problem known as minimization of open stacks (MOSP). We present an integer pro gramming model, based on the existence of a perfect elimination scheme in interval graphs, which finds an optimal sequence for the costumers orders.
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The Symbol Digit Modalities Test (SDMT) is a widely used instrument to assess information processing speed, attention, visual scanning, and tracking. Considering that repeated evaluations are a common need in neuropsychological assessment routines, we explored test–retest reliability and practice effects of two alternate SDMT forms with a short inter-assessment interval. A total of 123 university students completed the written SDMT version in two different time points separated by a 150-min interval. Half of the participants accomplished the same form in both occasions, while the other half filled different forms. Overall, reasonable test–retest reliabilities were found (r = .70), and the subjects that completed the same form revealed significant practice effects (p < .001, dz = 1.61), which were almost non-existent in those filling different forms. These forms were found to be moderately reliable and to elicit a similar performance across participants, suggesting their utility in repeated cognitive assessments when brief inter-assessment intervals are required.
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A precise estimation of the postmortem interval (PMI) is one of the most important topics in forensic pathology. However, the PMI estimation is based mainly on the visual observation of cadaverous pheno- mena (e.g. algor, livor and rigor mortis) and on alternative methods such as thanatochemistry that remain relatively imprecise. The aim of this in vitro study was to evaluate the kinetic alterations of several bio- chemical parameters (i.e. proteins, enzymes, substrates, electrolytes and lipids) during putrefaction of human blood. For this purpose, we performed kinetic biochemical analysis during a 264 hour period. The results showed a significant linear correlation between total and direct bilirubin, urea, uric acid, transferrin, immunoglobulin M (IgM), creatine kinase (CK), aspartate transaminase (AST), calcium and iron with the time of blood putrefaction. These parameters allowed us to develop two mathematical models that may have predictive values and become important complementary tools of traditional methods to achieve a more accurate PMI estimation
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OBJECTIVE: To determine in arrhythmogenic right ventricular cardiomyopathy the value of QT interval dispersion for identifying the induction of sustained ventricular tachycardia in the electrophysiological study or the risk of sudden cardiac death. METHODS: We assessed QT interval dispersion in the 12-lead electrocardiogram of 26 patients with arrhythmogenic right ventricular cardiomyopathy. We analyzed its association with sustained ventricular tachycardia and sudden cardiac death, and in 16 controls similar in age and sex. RESULTS: (mean ± SD). QT interval dispersion: patients = 53.8±14.1ms; control group = 35.0±10.6ms, p=0.001. Patients with induction of ventricular tachycardia: 52.5±13.8ms; without induction of ventricular tachycardia: 57.5±12.8ms, p=0.420. In a mean follow-up period of 41±11 months, five sudden cardiac deaths occurred. QT interval dispersion in this group was 62.0±17.8, and in the others it was 51.9±12.8ms, p=0.852. Using a cutoff > or = 60ms to define an increase in the degree of the QT interval dispersion, we were able to identify patients at risk of sudden cardiac death with a sensitivity of 60%, a specificity of 57%, and positive and negative predictive values of 25% and 85%, respectively. CONCLUSION: Patients with arrhythmogenic right ventricular cardiomyopathy have a significant increase in the degree of QT interval dispersion when compared with the healthy population. However it, did not identify patients with induction of ventricular tachycardia in the electrophysiological study, showing a very low predictive value for defining the risk of sudden cardiac death in the population studied.
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OBJECTIVE: Parasympathetic dysfunction is an independent risk factor in individuals with coronary artery disease, and cholinergic stimulation is a potential therapeutical option. We determined the effects of pyridostigmine bromide, a reversible anticholinesterase agent, on electrocardiographic variables of healthy individuals. METHODS: We carried out a cross-sectional, double blind, randomized, placebo-controlled study. We obtained electrocardiographic tracings in 12 simultaneous leads of 10 healthy young individuals at rest before and after oral administration of 45 mg of pyridostigmine or placebo. RESULTS: Pyridostigmine increased RR intervals (before: 886±27 ms vs after: 1054±37 ms) and decreased QTc dispersion (before: 72±9ms vs after: 45±3ms), without changing other electrocardiographic variables (PR segment, QT interval, QTc, and QT dispersion). CONCLUSION: Bradycardia and the reduction in QTc dispersion induced by pyridostigmine may effectively represent a protective mechanism if these results can be reproduced in individuals with cardiovascular diseases.
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Background: Although exercise training is known to promote post-exercise hypotension, there is currently no consistent argument about the effects of manipulating its various components (intensity, duration, rest periods, types of exercise, training methods) on the magnitude and duration of hypotensive response. Objective: To compare the effect of continuous and interval exercises on hypotensive response magnitude and duration in hypertensive patients by using ambulatory blood pressure monitoring (ABPM). Methods: The sample consisted of 20 elderly hypertensives. Each participant underwent three ABPM sessions: one control ABPM, without exercise; one ABPM after continuous exercise; and one ABPM after interval exercise. Systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), heart rate (HR) and double product (DP) were monitored to check post-exercise hypotension and for comparison between each ABPM. Results: ABPM after continuous exercise and after interval exercise showed post-exercise hypotension and a significant reduction (p < 0.05) in SBP, DBP, MAP and DP for 20 hours as compared with control ABPM. Comparing ABPM after continuous and ABPM after interval exercise, a significant reduction (p < 0.05) in SBP, DBP, MAP and DP was observed in the latter. Conclusion: Continuous and interval exercise trainings promote post-exercise hypotension with reduction in SBP, DBP, MAP and DP in the 20 hours following exercise. Interval exercise training causes greater post-exercise hypotension and lower cardiovascular overload as compared with continuous exercise.