• Nuclear Medicine and Molecular Imaging
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• v.43 no.5
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• pp.369-385
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• 2009

In this paper, the authors intended to summarize briefly the features of lymphoma with regard to $^{18}F$-FDG PET for assessment of tumor response to therapy, to describe why assessment of treatment response should be performed, to review what method so far has been used in monitoring treatment response, to discuss what limitations of morphologic imaging criteria for assessing tumor response are, in compared with $^{18}F$-FDG PET, and to introduce recently proposed criteria for assessing tumor response in malignant lymphoma. And also the authors emphasize the need to understand the characteristics of diagnostic performance of $^{18}F$-FDG PET in several clinical settings in order to interpret $^{18}F$-FDG PET results appropriately, and to encourage the use of interval likelihood ratio to enhance clinical implications of test results which, in turns, allows referring physicians to understand the meaning of interpretation with easy. Until recently, treatment response has been assessed according to the morphologic criteria. Metabolic imaging with $^{18}F$-FDG PET was adopted to have important role for treatment assessment in IWC+PET criteria proposed recently by IHP. To accomplish this role, we should perform and interpret $^{18}F$-FDG PET according to IWC+PET criteria. It is important for referring physicians to understand the various limitations of $^{18}F$-FDG PET and pitfalls in PET interpretation, and to understand that clinical information are needed by nuclear medicine physicians to optimize the interpretation of $^{18}F$-FDG PET.

• Journal of Korean Society for Quality Management
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• v.34 no.1
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• pp.54-72
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• 2006

In recent years, the widespread application of quality management and measurement reliability has put increasing emphasis on procedures for periodic instrument calibration. By optimizing calibration intervals, unnecessary calibrations can be minimized, thereby reducing costs. Moreover, optimizing intervals will improve compliance with regulatory directives while ensuring maximal compliance with reliability targets. In this paper, we present Calibration Interval Analysis Program developed using several establishment methodologies of calibration interval for measurement quality and reliability improvement. Also, we perform calibration interval analysis for some measurement instruments and analyse its results.

• Journal of Applied Reliability
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• v.2 no.2
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• pp.113-119
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• 2002

The estimation of mean lifetimes in presence of interval censoring with replacement procedure are examined when the distributions of lifetimes are exponential. It is assumed that, due to physical restrictions and/or economic constraints, the number of failures is investigated only at several inspection times during the lifetime test. The maximum likelihood estimator is found in an implicit form. The Cramer-Rao lower bounds of the estimates are found in places of variances and by simulations the properties of the estimates are examined.

• Journal of Korean Society for Quality Management
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• v.25 no.4
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• pp.79-87
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• 1997

In this paper, we obtain maximum likelihood estimator(MLE) of a parallel system reliability for the Marshall and Olkin's bivariate exponential model with birariate type 1 consored data. The asymptotic normal distribution of the estimator is obtained. Also we construct an a, pp.oximate confidence interval for the reliability based on MLE. We present a numerical study for obtaining MLE and a, pp.oximate confidence interval of the reliability.

• Journal of Information Technology Applications and Management
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• v.24 no.1
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• pp.25-32
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• 2017

For repairable software systems, the Mean Time Between Failure (MTBF) is used as a measure of software system stability. Therefore, the evaluation of software reliability requirements or reliability characteristics can be applied MTBF. In this paper, we want to compare MTBF in terms of parameter estimation using Makeham life distribution. The parameter estimates used the least square method which is regression analyzer method and the maximum likelihood method. As a result, the MTBF using the least square method shows a non-decreased pattern and case of the maximum likelihood method shows a non-increased form as the failure time increases. In comparison with the observed MTBF, MTBF using the maximum likelihood estimation is smallerd about difference of interval than the least square estimation which is regression analyzer method. Thus, In terms of MTBF, the maximum likelihood estimation has efficient than the regression analyzer method. In terms of coefficient of determination, the mean square error and mean error of prediction, the maximum likelihood method can be judged as an efficient method.

• Journal of Integrative Natural Science
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• v.5 no.3
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• pp.151-156
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• 2012

Because of the equivalence between control chart procedures and hypothesis testing, we propose to use likelihood ratio test (LRT) statistic $Z_i^2$ as the multivariate control statistic for simultaneous monitoring means of the multivariate normal process. Properties and comparisons of the proposed control charts are explored and conducted for matched fixed sampling interval (FSI) and variable sampling interval (VSI) with two sampling interval charts. The result of numerical comparisons shows that EWMA chart with two sampling interval procedure is more efficient than the corresponding FSI chart for small or moderate changes. When large shift of the process has occurred, we also found that Shewhart chart is more efficient than EWMA chart.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.12
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• pp.1669-1674
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• 2005

Maximum likelihood methodology was applied to analyze the efficiency and statistical power of interval mapping by using a threshold model. The factors that affect QTL detection efficiency (e.g. QTL effect, heritability and incidence of categories) were simulated in our study. Daughter design with multiple families was applied, and the size of segregating population is 500. The results showed that the threshold model has a great advantage in parameters estimation and power of QTL mapping, and has nice efficiency and accuracy for discrete traits. In addition, the accuracy and power of QTL mapping depended on the effect of putative quantitative trait loci, the value of heritability and incidence directly. With the increase of QTL effect, heritability and incidence of categories, the accuracy and power of QTL mapping improved correspondingly.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.825-833
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• 2003

Knowing the time of the process change could lead to quicker identification of the responsible special cause and less process down time, and it could help to reduce the probability of incorrectly identifying the special cause. In this paper, we propose a maximum likelihood estimator of the process change point when a Shewhart $\bar{X}$ chart with variable sample size (VSS) scheme signals a change in the process mean. Also we build a confidence interval for the process change point by using the likelihood function.

• Journal of information and communication convergence engineering
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• v.13 no.3
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• pp.152-158
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• 2015

We consider the problem of designing independently operating local quantizers at nodes in distributed estimation systems, where many spatially distributed sensor nodes measure a parameter of interest, quantize these measurements, and send the quantized data to a fusion node, which conducts the parameter estimation. Motivated by the discussion that the estimation accuracy can be improved by using the quantized data with a high probability of occurrence, we propose an iterative algorithm with a simple design rule that produces quantizers by searching boundary values with an increased likelihood. We prove that this design rule generates a considerably reduced interval for finding the next boundary values, yielding a low design complexity. We demonstrate through extensive simulations that the proposed algorithm achieves a significant performance gain with respect to traditional quantizer designs. A comparison with the recently published novel algorithms further illustrates the benefit of the proposed technique in terms of performance and design complexity.

• Communications for Statistical Applications and Methods
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• v.21 no.2
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• pp.193-200
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• 2014

It was recognized by some researchers that the disturbance variance in a censored regression model is frequently underestimated by the maximum likelihood method. This underestimation has implications for the estimation of marginal effects and asymptotic standard errors. For instance, the actual coverage probability of the confidence interval based on a maximum likelihood estimate can be significantly smaller than the nominal confidence level; consequently, a Bayesian estimation is considered to overcome this difficulty. The behaviors of the maximum likelihood and Bayesian estimators of disturbance variance are examined in a fixed effects panel regression model with a limited dependent variable, which is known to have the incidental parameter problem. Behavior under random effect assumption is also investigated.