• Journal of Industrial Convergence
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• v.20 no.10
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• pp.79-86
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• 2022

The purpose of this study was to identify suicidal ideation and related factors of elderly people with diabetes mellitus living alone in rural area. A descriptive study design was used. The participants were 466 elderly people, aged 65 years and over, and diagnosed with diabetes mellitus living at O province in South Korea. Collected data were analyzed using descriptive statistics, t-test, χ²-test, and logistic regression analysis with SPSS statistics 26.0 program. The results of the analysis showed that the suicidal ideation rate of the subjects was 27.3%, and the subjects showed significant differences in suicidal ideation as Cognitive function was lower (t=-4.23, p<.001), Depression(t=9.56, p<.001) and Loneliness (t=4.88, p<.001) were higher. Related Factors of suicidal ideation were Cognitive function (OR=0.86, p<.001), Depression (OR=1.18, p<.001) and Loneliness (OR=1.17, p=.001). These variables explained 32.2% of suicidal ideation. Therefore, in order to reduce suicide ideation of the elderly with diabetes mellitus living alone in rural areas, intervention that can improve Cognitive function, Depression, and Loneliness is needed.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.445-459
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• 2014

As a certain job is repeatedly done by a worker, the outcome comparative to the effort to complete the job gets more remarkable. The outcome may be the time required and fraction defective. This phenomenon is referred to a learning-curve effect. We focus on the parametric modeling of the learning-curve effects on count data using a logistic cumulative distribution function and some probability mass functions such as a Poisson and negative binomial. We conduct various simulation scenarios to clarify the characteristics of the proposed model. We also consider a real application to compare the two discrete-type distribution functions.

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.211-222
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• 2013

We consider the problem of nonparametrically estimating the conditional quantile function from censored data and propose new estimators here. They are based on local logistic regression technique of Lee et al. (2006) and "double-kernel" technique of Yu and Jones (1998) respectively, which are modified versions under random censoring. We compare those with two existing estimators based on a local linear fits using the check function approach. The comparison is done by a simulation study.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.242-244
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• 1992

Conventionally in the industrial control, PlD controller has been used because of its robustness, and nonlinear characteristic of a system under control. Although the PlD controller produce suitable parameter of the each system and also variable of PlD controller should be changed according to environment, disturbance, load. In this paper, the convergence and learning accuracy of the back-propagation(BP) method in neural network are investigated by analyzing the reason for decelerating the convergence of BP method. and examining the rapid deceleration of the convergence when the learning is executed on the part of sigmoid activation function with the very small first derivative. The modified logistic activation function it proposed by defining the convergence factor based on the analysis and applied to the position and speed control of a DC-servo motor. This paper revealed for experimental, a neural network and a PD controller combined off-line system using developed the position and speed characteristics of a DC-servo motor.

• Journal of Korean Public Health Nursing
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• v.27 no.1
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• pp.5-15
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• 2013

Purpose: The purpose of this study was to determine factors related to regular walking exercise in the elderly using KNHNES data. Method: The study subjects, a total of 1437 adults over age 65, were classified into two groups based on their type of walking exercise: regular walking exercise group or irregular walking exercise group. The study variables were measured using scale physiological function, mental health status, chronic disease and quality of life. Results: The data was analyzed by $x^2$-test, t-test, and logistic regression using the SPSS 18.0 program. The factors related to regular walking exercise were male (OR=0.628, 95%CI=0.503-0.783), subjective health state (OR=0.832, 95%CI=0.751-0.921), thoughts of suicide (OR=0.753, 95%CI=0.586-0.967), hypoHDL-cholesterolemia (OR=0.742, 95%CI=0.591-0.930), and stroke (OR=0.604, 95%CI=0.366-0.997). Conclusion: The findings indicate that regular walking exercise in the elderly is related to physiological function, mental health status, and chronic disease. Therefore, providing for the education and awareness of health promotion for the elderly will may improve the quality of life in old age.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.1005-1012
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• 2009

The area under the curve(AUC) is commonly used as a measure of the receiver operating characteristic(ROC) curve which displays the performance of a set of binary classifiers for all feasible ratios of the costs associated with true positive rate(TPR) and false positive rate(FPR). In the bipartite ranking problem where one has to compare two different observations and decide which one is "better", the AUC measures the quantity that ranking score of a randomly chosen sample in one class is larger than that of a randomly chosen sample in the other class and hence, the function which maximizes an AUC of bipartite ranking problem is different to the function which maximizes (minimizes) accuracy (misclassification error rate) of binary classification problem. In this paper, we develop a way to construct the unified framework for AUC maximizer including support vector machines based on maximizing large margin and logistic regression based on estimating posterior probability. Moreover, we develop an efficient algorithm for the proposed unified framework. Numerical results show that the propose unified framework can treat various methodologies successfully.

• Journal of Biosystems Engineering
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• v.25 no.5
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• pp.391-398
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• 2000

This study was performed to analyze the holding pace and decision factors of tractor in Korea and Japan, which probably should be used for making master plan of agricultural mechanization. The logistic function is used for holding pace estimation of tractor, and log-log function for analysis of decision factors. The results of this study are as follows: First, the increasing rate of the total amount of holding tractor power in Korea has been over that in Japan during 1980∼、94 which is now, however, under Japan. So, it could be forecasted that the per tractor holding power in Japan will increase continuously, and will be over 30PS in the short run. Second, the most important one of decision factors to support tractor demand is agricultural income in Korea, but on the other hand Non-Agricultural Income in Japan. From these, the fast increase of total amount of holding power of tractor in Korea could not expected, because Korea Agriculture has some difficulties to increase Agricultural Income. There are differences on the holding pace and decision factors of tractor between Korea and Japan, therefore, the plan of agricultural mechanization should be made in accordance with self-features.

• Korean Chemical Engineering Research
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• v.62 no.1
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• pp.53-69
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• 2024

The solubility of Cloxacillin sodium in ethanol, 1-propanol, isopropanol, and acetone solutions was measured at different temperatures. The melting property was also tested by using a differential scanning calorimeter (DSC). Then, the solubility data were fitted using Apelblat equation and λh equation, respectively. The Wilson model and NRTL model were not utilized to correlate the test data, since Cloxacillin sodium will decompose directly after melting. For comparison purposes, the four empirical models, i.e., Apelblat equation, λh equation, Wilson model and NRTL Model, were evaluated by using 1155 solubility curves of 103 solutes tested under different monosolvents and temperatures. The comparison results indicate that the Apelblat equation is superior to the others. Furthermore, a new method (named the calculation method) for determining the Apelblat equation using only three data points was proposed to solve the problem that there may not be enough solute in the determination of solubility. The log-logistic distribution function was used to further capture the trend of the correlation and to make better quantitative comparison between predicted data and the experimental ones for the Apelblat equation determined by different methods (fitting method or calculation method). It is found that the proposed calculation method not only greatly reduces the number of test data points, but also has satisfactory prediction accuracy.

• Journal of East-West Nursing Research
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• v.30 no.1
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• pp.31-41
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• 2024

Purpose: This study aimed to identify factors affecting subjective cognitive decline (SCD) in men and women. Methods: This study was conducted based on data from the 2021 Korea Community Health Survey, and targeted a total of 80,026 men and 98,753 women aged 40 or older who responded to the SCD assessment. Multivariate logistic regression analysis using a complex sample was performed to identify factors influencing SCD. Results: Of the participants, 19,438 (22.7%) men and 30,826 (29.9%) women in the community reported SCD. Significant factors that influence SCD in both groups were age, education level, subjective health status, and depressive symptoms, and the strongest risk factor was depressive symptoms. Compared to women, men's monthly income, flexibility exercise, hypertension, and diabetes mellitus were found to be significant factors on SCD and Healthcare services affected SCD only in women. Medical services affected SCD only in women. Conclusions: When planning and providing intervention programs for cognitive function, it is necessary to reflect differences in factors associated with SCD according to sex.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.609-620
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• 2008

There may be several parallel equipments having the same function in a multi-stage manufacturing process, which affect the product quality differently and have significant differences in defect rate. The product quality may depend on what equipments it has been processed as well as what process variable values it has. Applying one model ignoring the presence of different equipments may distort the prediction of defect rate and the identification of important quality variables affecting the defect rate. We propose a procedure for data segmentation when constructing models for predicting the defect rate or for identifying major process variables influencing product quality. The proposed procedure is based on the principal component analysis and the analysis of variance, which demonstrates a better performance in predicting defect rate through a case study with a PDP manufacturing process.