• 정보처리학회논문지B
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• 제18B권2호
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• pp.51-56
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• 2011

흑체의 온도 변화에 대한 영상의 색차를 줄이는 본질 영상은 단일 불변 방향을 검출하고 백색 장면 조명체를 기반으로 하기 때문에 실영상에 존재하는 다수의 불변 방향과 유색 장면 조명체에 취약하다. 이러한 문제를 해결하기 위해 본 논문에서는 ${\chi}$-색도 공간에서 ROI의 전방향프로젝션과 백색패치의 평행이동을 통해 불변 방향을 검출하는 본질 영상 획득 기법을 제안한다. 3차원 RGB 공간 분석의 어려움으로 인하여, 본 논문 또한 밝기가 고려되지 않은 ${\chi}$-색도 공간을 사용한다. 이 공간에서 유색 조명체의 효과는 백색패치의 평행이동을 통해 감소시키고, 색차에 따라 가상의 선분으로 나타나는 불변 방향은 ROI의 전방향 프로젝션을 통해 검출한다. 다수의 불변 방향을 고려하여 ROI 선택은 3D 히스토그램에서 빈도수에 의해 결정한다. 검출 후, 본질 영상은 불변 방향의 직교 방향으로의 프로젝션과 RGB영상으로의 역변환 과정을 통해 획득된다. 실험에서 Ebner가 제안한 데이터집합을 실험 영상으로 이용하였고, 불변 방향의 표준편차와 색항등성 측도를 평가 측도로 사용하였다. 제안한 기법의 실험 결과는 엔트로피 기법보다 불변 방향의 표준 편차가 낮았으며, 기존의 기법에 비해 색항등성이 2배 이상 높았다.

• 산업경영시스템학회지
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• 제10권16호
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• pp.101-106
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• 1987

Statistical control charts are useful tools to monitor and control the manufacturing processes and are widely used in most Korean industries. Many Korean companies, however, do not always obtain desired results from the traditional control charts by Shewhart such as the $\bar{X}$-chart, $\bar{X}$-chart, $\bar{X}$-chart, etc. This is partly because the quality charterstics of the process are not distributed normally but are skewed due to the intermittent production, small lot size, etc. In Shewhart $\bar{X}$-chart. which is the most widely used one in Kora, such skewed distributions make the plots to be inclined below or above the central line or outside the control limits although no assignable causes can be found. To overcome such shortcomings in nonnormally distributed processes, a distribution-free type of confidence interval can be used, which should be based on order statistics. This thesis is concerned with the design of control chart based on a sample median which is easy to use in practical situation and therefore properties for nonnormal distributions may be easily analyzed. Control limits and central lines are given for the more famous nonnormal distributions, such as Gamma, Beta, Lognormal, Weibull, Pareto, Truncated-normal distributions. Robustness of the proposed median control chart is compared with that of the $\bar{X}$-chart; the former tends to be superior to the latter as the probability distribution of the process becomes more skewed. The average run length to detect the assignable cause is also compared when the process has a Normal or a Gamma distribution for which the properties of X are easy to verify, the proposed chart is slightly worse than the $\bar{X}$-chart for the normally distributed product but much better for Gamma-distributed products. Average Run Lengths of the other distributions are also computed. To use the proposed control chart, the probability distribution of the process should be known or estimated. If it is not possible, the results of comparison of the robustness force us to use the proposed median control chart based oh a normal distribution. To estimate the distribution of the process, Sturge's formula is used to graph the histogram and the method of probability plotting, $\chi$$^2$-goodness of fit test and Kolmogorov-Smirnov test, are discussed with real case examples. A comparison of the proposed median chart and the $\bar{X}$ chart was also performed with these examples and the median chart turned out to be superior to the $\bar{X}$-chart.

• 품질경영학회지
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• 제5권2호
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• pp.59-120
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• 1977

An antibiotic 'P', which is one of the products of the Gist Brocades N. V. is being tested by its research department as fungicide on seed-potatoes. For this testing they designed experiments, with two control groups, one competitor's product, eight formulations of the antibiotic to be tested in different concentrations and one mercury treatment which can not be used in practice. The treated potatoes were planted in three different regions, where bifferent conditions prevail. After several months the harvested potatoes are divided in groups according to their diameter, potato illness is analysed and counted. These data were summarised in percentage and given to us for Analysis. We approached and analysed the data by following methods: a. Computation of the mean and standard deviation of the percenage of good results in each size group and treatment. b. Computation of the experimental errors by substraction of each treatment mean from observed data. c. Description of the frequency table, plotting of a histogram and a normal curve on same graph to check normality. d. Test of normality paper and chi-sqeare test to check the goodness of fit to a normal curve. e. Test for homogeneity of variance in each treatment with the Cochran's test and Hartley's test. f. Analysis of Variance for testing the means by one way classifications. g. Drawing of graphs with upper and lower confidence limits to show the effect of different treatments. h. T-test and F-test to two Control mean and variance for making one control of Dunnett's test. i. Dunnett's Test and calculations for numerical comarision of different treatments wth one control. In region R, where the potatoes were planted, it was this year very dry and rather bad conditions to grow potatoes prevailed during the experimental period. The results of this investigation show us that treatment No.2, 3 and 4 are significantly different from other treatments and control groups (none treated, just like natural state). Treatment no.2 is the useless mercury formulation. So only No. 3 and 4, which have high concentrations of antibiotic 'P', gave a good effect to the potatoes. As well as the competitors product, middle and low concentrated formulations are not significantly different from control gro-ups of every size. In region w, where the potatoes got the same treatments as in region R, prevailed better weather conditions and was enough water obtainable from the lake. The results in this region showed that treatment No. 2, 3, 4, and 5 are Significantly different from other treatments and the control groups. Again No.2 is the mercury treatmentin this investigation. Not only high concentrated formulation of antibiotic 'P', but also the competitor's poroduct gave good results. But, the effect of 'P', was better than the competitors porduct. In region G, where the potatoes got the same treatments as in the regions R and w. and the climate conditions were equal to region R, the results showed that most of the treatments are not significantly different from the control groups. Only treatment no. 3 was a little bit different from the others. but not Significantly different. It seems to us that the difference between the results in the three regions was caused by certain conditions like, the nature of the soil the degres of moisture and hours of sunshine, but we are not sure of that. As a conclusion, we can say that antibiotic 'P' has a good effect on potatoes, but in most investigations a rather high concentration of 'P' was required in formulations.