• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.1-6
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• 2005

In this paper we propose how to simultaneously optimize multiple responses for robust design when data are collected from a combined array. The proposed method is based on the quadratic loss function. An example is illustrated to show the proposed method.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.291-300
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• 2006

In this research, the performance of widely used Bayesian estimators such as Bayes estimator, empirical Bayes estimator, constrained Bayes estimator and constrained empirical Bayes estimator are compared by means of a measurement under balanced loss function for the typical normal-normal situation. The proposed measurement is a weighted sum of the precisions of first and second moments. As a result, one can gets the criterion according to the size of prior variance against the population variance.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.255-261
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• 2005

Many designed experiments require the simultaneous optimization of multiple responses. In this paper, we propose how to simultaneously optimize multiple responses for robust design when data are collected from a combined array. The proposed method is based on the quadratic loss function. An example is illustrated to show the proposed method.

• Proceedings of the Safety Management and Science Conference
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• 2003.05a
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• pp.1-5
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• 2003

We purpose a decision model to select the optimal facilities for the Decision Making problems with multiple characteristics(nominal-is-best characteristics, larger-is -better characteristics, smaller- is -better characteristics). Using this model, concept of the loss function is used in this comprehensive method of for select the optimal preferred facilities. To solve the issue on the optimal preferred facilities for multiple characteristics, this study propose the loss function with cross-product terms among the characteristics and derived range of the coefficients of the terms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.165-172
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• 2017

Machines are physically or chemically degenerated by continuous usage. One of the results of this degeneration is the process mean shift. Under the process mean shift, production cost, failure cost and quality loss function cost are increasing continuously. Therefore a periodic preventive resetting the process is necessary. We suppose that the wear level is observable. In this case, process mean shift problem has similar characteristics to the maintenance policy model. In the previous studies, process mean shift problem has been studied in several fields such as 'Tool wear limit', 'Canning Process' and 'Quality Loss Function' separately or partially integrated form. This paper proposes an integrated cost model which involves production cost by the material, failure cost by the nonconforming items, quality loss function cost by the deviation between the quality characteristics from the target value and resetting the process cost. We expand this process mean shift problem a little more by dealing the process variance as a function, not a constant value. We suggested a multiplier function model to the process variance according to the analysis result with practical data. We adopted two-side specification to our model. The initial process mean is generally set somewhat above the lower specification. The objective function is total integrated costs per unit wear and independent variables are wear limit and initial setting process mean. The optimum is derived from numerical analysis because the integral form of the objective function is not possible. A numerical example is presented.

• Journal of Korean Society for Quality Management
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• v.20 no.1
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• pp.80-90
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• 1992

In industries, the capability indices $C_p$ and $C_{pk}$ can be used to provide measures of process potential capability and performance, respectively. The new approach advocated by Taguchi in quality control overcomes some problems in other approaches preventive management activities. Taguchi introduces the emphasis on loss function to improve quality of products on the side of customer. The proceeding concept of capability indices is not rational for the measurement of quality if the process mean is not equal to target value. The Taguchi approach is said to be more reasonable than the others in quality evaluation because of his loss function. However, the capability indices $C_{pm}{^+}$ and $C_{pn}$ using Taguchi's loss function only consider, acceptance cost for deviation from target value within specification limits. In other words, they do not include rejection cost for nonconformings that are failed to fall on the specification limits.

• Proceedings of the ESK Conference
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• 1995.10a
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• pp.268-279
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• 1995

The purpose of this study is to suggest a brassiere sizing chart for elderly women. It is found that there is no direct linear relationship between cup size and under bust girth from the analsis of breast measurements. These 2 factors(under bust girth and cup size) were chosen as 2 axes of brassiere size chart. A loss function was used to determined intervals of bust girth and cup size of size chart, because the loss function introduces the concept of frequency to size chart for better customer's satisfaction. From the dual distribution table whose intervals had been determinde by a loss function. The 15 sizes, which had more than 2% of appearance were suggested for brassiere size chart. The suggested brassierc sizes covened 87.6% of all subjects. Considering that KS brassiere size thart consisting of 32 sizes covers 88.5%, the suggested brassiere size chart would be considered quite feasible. Also is suggested supply reference measurement chart relevant to brassiere manufacturing for 10 most frequent sizes.

• Journal of the Ergonomics Society of Korea
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• v.15 no.2
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• pp.1-13
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• 1996

The purpose of this study is to suggest a brassiere sizing chart for elderly women. 2 control dimensions(under bust girth and cup size) were chosen as 2 axes of brassiere size chart. A loss function was used to determined intervals of under bust girth and cup size of size chart, because the loss function introduces the concept of frequency to size chart for better customer's satisfaction. From the dual distribution table whose intervals had been determined by a loss function. The 15 sizs, which had more than 2% of appearance were suggested for brassiere size chart. The suggested brassiere sizes covered 87.6% of all subjects. Considering that KS brassiere size chart consisting of 32 sizes covers 88.5%, the suggested brassiere size chart would be considered quite feasible. Also it is suggested supply reference measurement chart relevant to brassiere manufacturing for 10 most frequent sizes.

• Communications for Statistical Applications and Methods
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• v.27 no.4
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• pp.469-486
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• 2020

Entropy is an important term in statistical mechanics that was originally defined in the second law of thermodynamics. In this paper, we consider the maximum likelihood estimation (MLE), maximum product spacings estimation (MPSE) and Bayesian estimation of the entropy of an inverse Weibull distribution (InW) under a generalized type I progressive hybrid censoring scheme (GePH). The MLE and MPSE of the entropy cannot be obtained in closed form; therefore, we propose using the Newton-Raphson algorithm to solve it. Further, the Bayesian estimators for the entropy of InW based on squared error loss function (SqL), precautionary loss function (PrL), general entropy loss function (GeL) and linex loss function (LiL) are derived. In addition, we derive the Lindley's approximate method (LiA) of the Bayesian estimates. Monte Carlo simulations are conducted to compare the results among MLE, MPSE, and Bayesian estimators. A real data set based on the GePH is also analyzed for illustrative purposes.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1319-1325
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• 2021

It is important to remove fog for accurate object recognition and detection during preprocessing because images taken in foggy adverse weather suffer from poor quality of images due to scattering and absorption of light, resulting in poor performance of various vision-based applications. This paper proposes an end-to-end deep learning-based single image de-fogging method using U-Net architecture. The loss function used in the algorithm is a loss function based on Mahalanobis distance with fog features, which solves the problem of domain shifts, and demonstrates superior performance by comparing qualitative and quantitative numerical evaluations with conventional methods. We also design it to generate fog through the VGG19 loss function and use it as the next training dataset.