• 한국군사과학기술학회지
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• 제10권1호
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• pp.94-100
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• 2007

MVRS's measuring principles are based on the Doppler principle. It measures the velocities near the muzzle using the doppler signal output from the antenna and then predicts the velocity of the bullet leaving the muzzle by performing the regression analysis on previous measured velocities. There are a number of error sources when calculating the muzzle velocity. Antenna has long term frequency stability error and the doppler signal from the antenna has noise. These two error sources influence the accuracy of estimated velocities from the doppler signal. Estimated velocity errors result in the random error of data statistics. And when performing a regression analysis these random error components are transferred to the fitting error component. This study also analyzed the error components according to the hardware limitations of MVRS-700 and the signal processing method, and presented the calculated uncertainty of muzzle velocity.

• 한국의류학회지
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• 제24권3호
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• pp.313-322
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• 2000

The purpose of this study was to investigate the characteristic and image of oriental costume designs which represented among three countries, Korea, China and Japan. The specific objectives were: 1) to find out the positioning of oriental costume design. 2) to find out relation to oriental costume image and preference. The stimulus were 75 costume designs of contemporary costume which represented the traditional images of three countries Korea, China and Japan. The main survey of questionary consisted of their evaluation of the oriental costume image by 26 semantic differential bi-polar scales and the subjects were 99 female students majoring in clothing and textile. The data were analyzed by Multidimensional Scaling Method and Regression Analysis. The specific objective were as follows: 1. According to image positioning. The oriental costume design was classified by simple-decorative, soft-hard. 2. As result of regression analysis. The preference of oriental costume image was related to attractive factor.

• 한국농공학회지
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• 제32권1호
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• pp.103-109
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• 1990

The application of the Log-Pearson Type m distribution recommended by Water Resources Council, U. S. A. for flood frequency analysis requires the estimation of the regionalized skew coefficient. In this study, regionalized skew coefficients are estimated using a weighted regression model which relates at-site skews based on logarithms of observed annual flood peak series to both basin characteristics and precipitation data in the Han river and the Nakdong river basin. The model is developed with weighted least squares method in which the weights are determined by separating residual variance into that due to model error and due to sampling error. As the result of analysis, regionalized skews are estimated as - 0.732 and - 0.575 in the Han river and the Nakdong river basin, respectively.

• 대한간호학회지
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• 제34권3호
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• pp.576-585
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• 2004

Purpose: The purpose of this study was to identify the relationship between eating disorders, physical symptoms, depression and health locus of control. Method: The research design was a descriptive study done by using a constructive self-report questionnaire. A total of 464 elementary school girls were measured. The instrument was a constructive questionnaire that consisted 136 items. The subjects were divided into 4 groups according to the Body Mass Index (BMI). Data analysis was done by SPSS/WIN Programs using frequency, percentage, mean, SD, ANOVA, Pearson correlation coefficient, and stepwise multiple regression. Result: The score of eating disorders differed significantly by BMI : the score was highest in the group of obese students(F=4.208, P=.015). Stepwise multiple regression analysis revealed that the most powerful predictor of eating disorders was BMI. Conclusion: These results indicate that Korean elementary school girls need more education and counseling on diet. Also, we should take systematic efforts to reestablish the social standard of beauty to promote normal growth development.

• 한국군사과학기술학회지
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• 제12권4호
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• pp.491-499
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• 2009

The determination of response characteristics for pressure sensors is routinely limited to static calibration against a deadweight pressure standard. The strength of this method is that the deadweight device is a primary standard used to generate precise pressure. Its weakness lies in the assumption that the static and dynamic responses of the sensor in question are equivalent. Differences in sensor response to static and dynamic events, however, can lead to serious measurement errors. Dynamic techniques are required to calibrate pressure sensors measuring dynamic events in milliseconds. In this paper, a dynamic calibration using negative going dynamic pressure is proposed to determine dynamic pressure response for piezoelectric sensors. Sensitivity and linearity of sensor by the dynamic calibration were compared with those by the static calibration. The uncertainty of calibration results and the goodness of fit test of linear regression analysis were presented. The results show that the dynamic calibration is applicable to determine dynamic pressure response for piezoelectric sensors.

• Journal of the Korean Data and Information Science Society
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• 제26권3호
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• pp.773-779
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• 2015

We study a statistical analysis about the fifth wave data of the Korea National Health and Nutrition Examination Survey based on linear regression models with measurement errors. The data is obtained from a national population-based complex survey. To demonstrate the availability of measurement error models, two results between the general linear regression model and measurement error model are compared based on the model selection criteria which are Akaike information criterion and Bayesian information criterion. For our study, we use the simulation extrapolation algorithm for measurement error model and the jackknife method for the estimation of standard errors.

• 한국기계가공학회지
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• 제6권4호
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• pp.15-21
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• 2007

The effect of manufacturing parameters on friction characteristics of motorcycle break system was studied using a disk-on-pad type friction tester. Such parameters conditions have an effect on the frictional factor such as number of ventilated disk hole, applied load, sliding speed, and sliding distance. However, it is difficult to know the mutual relation of these factors. In this study, the friction characteristics using design of experiment containing 4 elements were investigated for an optimal condition for the best motorcycle break system employing regression analysis method. From this study, the result was shown that the applied load in frictional factors was the most important, next to sliding speed, number of ventilated disk hole.

• Asia pacific journal of information systems
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• 제15권2호
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• pp.51-63
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• 2005

There has been substantial research into the bankruptcy prediction. Many researchers used the statistical method in the problem until the early 1980s. Since the late 1980s, Artificial Intelligence(AI) has been employed in bankruptcy prediction. And many studies have shown that artificial neural network(ANN) achieved better performance than traditional statistical methods. However, despite ANN's superior performance, it has some problems such as overfitting and poor explanatory power. To overcome these limitations, this paper suggests a relatively new machine learning technique, support vector machine(SVM), to bankruptcy prediction. SVM is simple enough to be analyzed mathematically, and leads to high performances in practical applications. The objective of this paper is to examine the feasibility of SVM in bankruptcy prediction by comparing it with ANN, logistic regression, and multivariate discriminant analysis. The experimental results show that SVM provides a promising alternative to bankruptcy prediction.

• 한국공작기계학회논문집
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• 제10권2호
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• pp.89-94
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• 2001

This paper presents a study of surface roughness prediction model by orthogonal design in turning operation. Regression analysis technique has been used to study the effects of the cutting parameters such as cutting speed, feed depth of cut, and nose radius on surface roughness. An effect of interaction between two parameters on surface roughness has also been investigated. The experiment has been conducted using coated tungsten carbide inserts without cutting fluid. The reliability of the surface roughness model as a function of the cutting parameters has been estimated. The results show that the experimental design used in turning process is a method to estimate the effects of cutting parameters on sur-face roughness.

• 제어로봇시스템학회논문지
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• 제13권2호
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• pp.173-178
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• 2007

This paper is to establish an appropriate model for predicting the temperature decreases in the batch transferred from the refining process to the caster in steel-making companies. Mathematical modeling of the temperature decreases between the processes is difficult, since the reaction mechanism by which the temperature changes in a molten steel batch is dynamic, uncertain and complex. Three soft computing techniques are examined using the same data, namely the multiple regression, fuzzy regression, and neural net (NN) models. To compare the accuracy of these three models, a limited number of input variables are selected from those variables significantly affecting the temperature decrease. The results show that the difference in accuracy between the three models is not statistically significant. Nonetheless, the NN model is recommended because of its adaptive ability and robustness. The method presented in this paper allows the temperature decrease to be predicted without requiring any precise metallurgical knowledge.