850 resultados para Adjusted Average Time to Signal


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A Fortran computer program is given for the computation of the adjusted average time to signal, or AATS, for adaptive (X) over bar charts with one, two, or all three design parameters variable: the sample size, n, the sampling interval, h, and the factor k used in determining the width of the action limits. The program calculates the threshold limit to switch the adaptive design parameters and also provides the in-control average time to signal, or ATS.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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A Fortran computer program is given for the computation of the adjusted average time to signal, or AATS, for adaptive X̄ charts with one, two, or all three design parameters variable: the sample size, n, the sampling interval, h, and the factor k used in determining the width of the action limits. The program calculates the threshold limit to switch the adaptive design parameters and also provides the in-control average time to signal, or ATS.

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Recent studies have shown that the X̄ chart with variable sampling intervals (VSI) and/or with variable sample sizes (VSS) detects process shifts faster than the traditional X̄ chart. This article extends these studies for processes that are monitored by both the X̄ and R charts. A Markov chain model is used to determine the properties of the joint X and R charts with variable sample sizes and sampling intervals (VSSI). The VSSI scheme improves the joint X̄ and R control chart performance in terms of the speed with which shifts in the process mean and/or variance are detected.

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Varying the parameters of the X̄ chart has been explored extensively in recent years. In this paper, we extend the study of the X̄ chart with variable parameters to include variable action limits. The action limits establish whether the control should be relaxed or not. When the X̄ falls near the target, the control is relaxed so that there will be more time before the next sample and/or the next sample will be smaller than usual. When the X̄ falls far from the target but not in the action region, the control is tightened so that there is less time before the next sample and/or the next sample will be larger than usual. The goal is to draw the action limits wider than usual when the control is relaxed and narrower than usual when the control is tightened. This new feature then makes the X̄ chart more powerful than the CUSUM scheme in detecting shifts in the process mean.

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Research has shown that applying the T-2 control chart by using a variable parameters (VP) scheme yields rapid detection of out-of-control states. In this paper, the problem of economic statistical design of the VP T-2 control chart is considered as a double-objective minimization problem with the statistical objective being the adjusted average time to signal and the economic objective being expected cost per hour. We then find the Pareto-optimal designs in which the two objectives are met simultaneously by using a multi-objective genetic algorithm. Through an illustrative example, we show that relatively large benefits can be achieved by applying the VP scheme when compared with usual schemes, and in addition, the multi-objective approach provides the user with designs that are flexible and adaptive.

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In this article, we consider the synthetic control chart with two-stage sampling (SyTS chart) to control the process mean and variance. During the first stage, one item of the sample is inspected; if its value X, is close to the target value of the process mean, then the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and the statistic T = Sigma [x(i) - mu(0) + xi sigma(0)](2) is computed taking into account all items of the sample. The design parameter is function of X-1. When the statistic T is larger than a specified value, the sample is classified as nonconforming. According to the synthetic procedure, the signal is based on Conforming Run Length (CRL). The CRL is the number of samples taken from the process since the previous nonconforming sample until the occurrence of the next nonconforming sample. If the CRL is sufficiently small, then a signal is generated. A comparative study shows that the SyTS chart and the joint X and S charts with double sampling are very similar in performance. However, from the practical viewpoint, the SyTS chart is more convenient to administer than the joint charts.

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A standard (X) over bar chart for controlling the process mean takes samples of size no at specified, equally-spaced, fixed-time points. This article proposes a modification of the standard (X) over bar chart that allows one to take additional samples, bigger than no, between these fixed times. The additional samples are taken from the process when there is evidence that the process mean moved from target. Following the notation proposed by Reynolds (1996a) and Costs (1997) we shortly call the proposed (X) over bar chart as VSSIFT (X) over bar chart: where VSSIFT means variable sample size and sampling intervals with fixed times. The (X) over bar chart with the VSSIFT feature is easier to be administered than a standard VSSI (X) over bar chart that is not constrained to sample at the specified fixed times. The performances of the charts in detecting process mean shifts are comparable.

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Recent theoretical studies have shown that the X̄ chart with variable sampling intervals (VSI) and the X̄ chart with variable sample size (VSS) are quicker than the traditional X̄ chart in detecting shifts in the process. This article considers the X̄ chart with variable sample size and sampling intervals (VSSI). It is assumed that the amount of time the process remains in control has exponential distribution. The properties of the VSSI X̄ chart are obtained using Markov chains. The VSSI X̄ chart is even quicker than the VSI or VSS X̄ charts in detecting moderate shifts in the process.

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A standard X̄ chart for controlling the process mean takes samples of size n0 at specified, equally-spaced, fixed-time points. This article proposes a modification of the standard X chart that allows one to take additional samples, bigger than n0, between these fixed times. The additional samples are taken from the process when there is evidence that the process mean moved from target. Following the notation proposed by Reynolds (1996a) and Costa (1997) we shortly call the proposed X chart as VSSIFT X chart where VSSIFT means variable sample size and sampling intervals with fixed times. The X chart with the VSSIFT feature is easier to be administered than a standard VSSI X chart that is not constrained to sample at the specified fixed times. The performances of the charts in detecting process mean shifts are comparable. Copyright © 1998 by Marcel Dekker, Inc.

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This work investigates the performance of cardiorespiratory analysis detecting periodic breathing (PB) in chest wall recordings in mountaineers climbing to extreme altitude. The breathing patterns of 34 mountaineers were monitored unobtrusively by inductance plethysmography, ECG and pulse oximetry using a portable recorder during climbs at altitudes between 4497 and 7546 m on Mt. Muztagh Ata. The minute ventilation (VE) and heart rate (HR) signals were studied, to identify visually scored PB, applying time-varying spectral, coherence and entropy analysis. In 411 climbing periods, 30-120 min in duration, high values of mean power (MP(VE)) and slope (MSlope(VE)) of the modulation frequency band of VE, accurately identified PB, with an area under the ROC curve of 88 and 89%, respectively. Prolonged stay at altitude was associated with an increase in PB. During PB episodes, higher peak power of ventilatory (MP(VE)) and cardiac (MP(LF)(HR) ) oscillations and cardiorespiratory coherence (MP(LF)(Coher)), but reduced ventilation entropy (SampEn(VE)), was observed. Therefore, the characterization of cardiorespiratory dynamics by the analysis of VE and HR signals accurately identifies PB and effects of altitude acclimatization, providing promising tools for investigating physiologic effects of environmental exposures and diseases.

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Measures of transit accessibility are important in evaluating transit services, planning for future services and investment on land use development. Existing tools measure transit accessibility using averaged walking distance or walking time to public transit. Although the mode captivity may have significant implications on one’s willingness to walk to use public transit, this has not been addressed in the literature to date. Failed to distinguish transit captive users may lead to overestimated ridership and spatial coverage of transit services. The aim of this research is to integrate the concept of transit captivity into the analysis of walking access to public transit. The conventional way of defining “captive” and “choice” transit users showed no significant difference in their walking times according to a preliminary analysis. A cluster analysis technique is used to further divide “choice” users by three main factors, namely age group, labour force status and personal income. After eliminating “true captive” users, defined as those without driver’s licence or without a car in respective household, “non-true captive” users were classified into a total of eight groups having similar socio-economic characteristics. The analysis revealed significant differences in the walking times and patterns by their level of captivity to public transit. This paper challenges the rule-of-thumb of 400m walking distance to bus stops. In average, people’s willingness to walk dropped drastically at 268m and continued to drop constantly until it reached the mark of 670m, where there was another drastic drop of 17%, which left with only 10% of the total bus riders willing to walk 670m or more. This research found that mothers working part time were the ones with lowest transit captivity and thus most sensitive to the walking time, followed by high-income earners and the elderly. The level of captivity increases when public transit users earned lesser income, such as students and students working part time.

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Fifty four purse-seine boats at Mangalore landing centre were observed during different stages of unloading fish catch. It was found that a boat takes 75% of the berthing time to unload an average quantity of 2.4 tons of fish. Further, unloading period and catch were found to be directly related where it was estimated that 5 to 7 minutes are spent in unloading about half a ton of fish to a nearby tempo by employing 9 ± 2 laborers.

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This article uses feminist scholarship to investigate ‘the elderly mystique’ – which contends that the potential of old age is masked by a set of false beliefs about ageing (i.e. ageism) which permeate social, economic and political life (Cohen, 1988).
The article presents a theoretical model which explores the extent to which institutionalised ageism shapes the trajectory of life after 60. The hypothesis under-pinning the model is simple: The challenge for ageing societies is not the average age of a given population but, rather, how age is used to structure economic, social and political life. An inter-disciplinary framework is used to examine how biological facts about ageing are used to segregate older from younger people, giving older people the status of “other”; economically through retirement, politically through assumptions about ‘the grey vote’ and socially through ageist stereotyping in the media and through denial and ridicule of the sexuality of older people. Each domain is informed by the achievements of feminist theory and research on sexism and how its successes and failures can inform critical investigations of ageism.
The paper recognises the role of ageism in de-politicising the lived experience of ageing. The paper concludes that feminist scholarship, particularly work by feminists in their seventies, eighties and nineties has much to offer in terms of re-framing gerontology as an emancipatory project for current and future cohorts of older people.