• Journal of Korean Institute of Industrial Engineers
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• v.24 no.2
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• pp.175-183
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• 1998

When a product is designed, tolerances must be given to the product so that required functions are guaranteed and production costs are minimized. In this research, a model is suggested which allocates tolerances to components optimally according to the STA(Statistical Tolerance Allocation) method. Taking into account the concept that dimensional errors have characteristics of statistical distributions, this model presents the discrete pseudo-boolean approach for the tolerance optimization by minimizing the tolerance cost and the quality loss cost. In this approach, two methods are proposed for the reduction of the problem scale; 1) a method for converting the minimization model for casts into the maximization model for cost savings, and 2) procedures to reduce the number of constraints and variables.

• IE interfaces
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• v.16 no.3
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• pp.344-351
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• 2003

Critical dimension is one of the most important characteristics of up-to-date integrated circuit devices. Hence, critical dimension control in a semiconductor wafer fabrication process is inevitable in order to achieve optimum device yield as well as electrically specified functions. Currently, in complex semiconductor wafer fabrication processes, statistical methodologies such as Shewhart-type control charts become crucial tools for practitioners. Meanwhile, given a critical dimension sampling plan, the analysis of variance technique can be more effective to investigating critical dimension variation, especially for on-chip and on-wafer variation. In this paper, relating to a typical sampling plan, linear statistical models are presented for the analysis of critical dimension variation. A case study is illustrated regarding a semiconductor wafer fabrication process.

• Journal for History of Mathematics
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• v.26 no.4
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• pp.277-299
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• 2013

It was not until the early twentieth century that statistics emerged as an independent academic discipline. The developments of statistical theory and methods would not have been possible without heated controversies among founding fathers. One of them, controversy on the statistical test between R. A. Fisher and J. Neyman, E. S. Pearson had been very fierce and long-lasting. On the other hand it was in the early twentieth century that psychologists began to utilize statistical test which was a hybrid of tests developed by Fisher and Neyman-Pearson. By considering the history of fields such as psychology, we can see distinctive characteristics specific to the history of statistics.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.07b
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• pp.927-930
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• 2002

The HFPD measurement method is a technique to analyze aging state of high voltage insulation materials and detect higher frequency signals than conventional PD measurement method therefore it takes less noise effect and could execute active line measurement. It is possible to analyze main discharge phenomena and obtain access to aging progress occurred in insulation materials through accumulation of HFPD signals during determined interval and expression of fractal dimension using statistical process of accumulated signals. In this study, the statistical parameters (skewness & kurtosis) and fractal dimensions are changed by discharge patterns that is shown up different characteristics with applied voltages and times.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.519-533
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• 2004

In this paper, we suggest quasi-likelihood estimation (QLE) method and its robust version in estimating spatial dependence modelled through variogram used for spatial data modelling. We compare the statistical characteristics of the estimators with other popular least squares estimators of parameters for variogram model by simulation study. The QLE method for estimating spatial dependence has the advantages that it does not need the concept of lags commonly required for least squares estimation methods as well as its statistical superiority. The QLE method also shows the statistical superiority to the other methods for the tested Gaussian and non-Gaussian spatial processes.

• Journal of the Korean Society of Safety
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• v.13 no.1
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• pp.104-111
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• 1998

Statistical analyses of occupational accidents associated with construction work were carried out to explore the basic statistical characteristics of their damage consequences. Emphasis was placed upon the probabilistic and statistical analyses to clarify, in particular, the relationship between frequency of labour accidents and their damage consequences. Damage consequences were classified into two categories such as the number of workdays lost due to accidents and the number of injured workers involved in one accident. Two types of accident data were collected for the analyses. From the analyses, it was found that the relation between damage due to accidents and their frequencies can be represented by a simple power function which indicates a log-log linear relation. By making use of this relationship, various probabilistic evaluations such as the estimation of the mean time periods between accidents, expected damage consequences, and expected damage ratio between different mean time period of accidents were conducted.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.2
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• pp.99-105
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• 2007

According to the automated manufacturing processes followed by the development of computer manufacturing technologies, products or quality characteristics produced on the processes have measured and recorded automatically. Much amount of data daily produced on the processes may not be efficiently analyzed by current statistical methodologies (i.e., statistical quality control and statistical process control methodologies) because of the dimensionality associated with many input and response variables. Although a number of statistical methods to handle this situation, there is room for improvement. In order to overcome this limitation, we integrated data mining and robust design approach in this research. We find efficiently the significant input variables that connected with the interesting response variables by using the data mining technique. And we find the optimum operating condition of process by using RSM and robust design approach.

• Journal of Biomedical Engineering Research
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• v.17 no.4
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• pp.433-442
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• 1996

Since one texture property(i.e coarseness, orientation, regularity, granularity) for ultrasound liver ages was not sufficient enough to classify the characteristics of livers, we used multi texture vectors tracted from ultrasound liver images and a statistical classifier. Multi texture vectors are selected among the feature vectors of the normal liver, fat liver and cirrhosis images which have a good separability in those ultrasound liver images. The statistical classifier uses multi texture vectors as input vectors and classifies ultrasound liver images for each multi texture vector by the Bayes decision rule. Then the decision of the liver disease is made by choosing the maximum value from the averages of a posteriori probability for each multi texture vector In our simulation, we obtained higtler correct ratio than that of other methods using single feature vector, for the test set the correct ratio is 94% in the normal liver, 84% in the fat liver and 86% in the cirrhosis liver.

• Korean Journal of Applied Biomechanics
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• v.26 no.4
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• pp.343-351
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• 2016

Objective: The purpose of this study was to help improve game performance and provide preliminary data to enhance the efficiency of the kick and stability of the support foot by comparing the kinematic characteristics of the repeated side kick (geodeupyeopchagi) in poomsaeKoryo between expert and non-expert groups. Method: The subjects were divided into 2 groups according to proficiency in Taekwondo, an expert group and a non-expert group (n = 7 in each group), to observe the repeated side-kick technique. Four video cameras were set at a speed of 60 frames/sec and exposure time of 1/500 sec to measure the kinematic factors of the 2 groups. The Kwon3D XPprogramas used to collect and analyze three-dimensional spatial coordinates. Ground reaction force data were obtained through a force plate with a 1.200-Hz frequency. An independent samplesttest was performed, and statistical significance was defined as .05. The SPSS 18.0 software was used to calculate the mean and standard deviation of the kinematic factors and to identify the difference between the experts and non-experts. Results: The angular displacement of the hip joint in both the expert and non-expert groups showed statistical significance on E1 and E4 of the left support foot and E5 of the right foot (p<.05). The angle displacement of the knee joint in both groups showed statistical significance on E4 of the left support foot, and E1 and E2 of the right foot (p<.05). The angular velocity of the lower leg in both groups showed no statistical significance on the left support foot but showed statistical significance on E2 and E6 of the right foot (p<.05). The angular velocity of the foot in both groups showed no statistical significance on the left support foot but showed statistical significance on E2 of the right foot (p<.05). The vertical ground reaction force in both groups showed statistical significance on E2 (p<.05). The center of pressure in all directions in both groups showed statistical significance (p<.5). Conclusion: While performing the repeated side kick (geodeupyeopchagi), the experts maintainedconsistency and stability of the angle of the support leg while the kick foot moved high and fast. On the other hand, the angle of the support foot of non-experts appeared inconsistent, and the kick foot was raised, relying on the support leg, resulting in unstable and inaccurate movement.

• Atmosphere
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• v.25 no.1
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• pp.19-30
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• 2015

The Ka-band cloud radar (KCR) has been operated by the National Institute of Meteorological Research (NIMR) of Korea Meteorological Administration (KMA) at Boseong National Center for Intensive Observation of severe weather since 2013. Evaluation of data quality is an essential process to further analyze cloud information. In this study, we estimate the measurement error and the sampling uncertainty to evaluate data quality. By using vertically pointing data, the statistical uncertainty is obtained by calculating the standard deviation of each radar parameter. The statistical uncertainties decrease as functions of sampling number. The statistical uncertainties of horizontal and vertical reflectivities are identical (0.28 dB). On the other hand, the statistical uncertainties of Doppler velocity (spectrum width) are 2.2 times (1.6 times) larger at the vertical channel. The reflectivity calibration of KCR is also performed using X-band vertically pointing radar (VertiX) and 2-dimensional video disdrometer (2DVD). Since the monitoring of calibration values is useful to evaluate radar condition, the variation of calibration is monitored for five rain events. The average of calibration bias is 10.77 dBZ and standard deviation is 3.69 dB. Finally, the statistical characteristics of cloud properties have been investigated during two months in autumn using calibrated reflectivity. The percentage of clouds is about 26% and 16% on September to October. However, further analyses are required to derive general characteristics of autumn cloud in Korea.