• Korean Security Journal
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• no.48
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• pp.177-206
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• 2016

The purpose of this study is to verify the factors that affect the fear of crime by applying the risk interpretation model. Especially, whereas previous studies have not proven micro individual factor that the risk interpretation model had presented, This study includes micro individual elements such as neighborhood factor, perceived risk of crime, fears of crime as main variables. This study utilized secondary data of the National Crime Victimization Survey 2012, conducted by the Korean Institute of Criminology. In this study, multiple regression analysis of two stages and Sobel Test were conducted for verifying the individual influence of each independent variables and identifying the causal relationship between the variables set out in the risk analysis model. As the result, it appeared that the higher level of perceived risk of crime, neighborhood factor, crime experience, education, income cause the higher degree of the fear of crime. On the other hand, the lower degree of age was found to induce the higher level of the fear of crime. In addition, female showed the higher degree of the fear of crime than man. The causal relationship between the variables set out in the risk interpretation model was presented significantly in all variables, except for education.

• Genomics & Informatics
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• v.8 no.1
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• pp.28-33
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• 2010

Increased exposure of human to RF fields has raised concerns for its potential adverse effects on our health. To address the biological effects of RF radiation, we used genome wide gene expression as the indicator. We exposed normal WI-38 human fibroblast cells to 1763 MHz mobile phone RF radiation at a specific absorption rate (SAR) of 60 W/kg with an operating cooling system for 24 h. There were no alterations in cell numbers or morphology after RF exposure. Through microarray analysis, we identified no differentially expressed genes (DEGs) at the 0.05 significance level after controlling for multiple testing errors with the Benjaminiochberg false discovery rate (BH FDR) method. Meanwhile, 82 genes were differentially expressed between RF-exposed cells and controls when the significance level was set at 0.01 without correction for multiple comparisons. We found that 24 genes (0.08% of the total genes examined) were changed by more than 1.5-fold on RF exposure. However, significant enrichment of any gene set or pathway was not observed from the functional annotation analysis. From these results, we did not find any evidence that non-thermal RF radiation at a 60-W/kg SAR significantly affects cell proliferation or gene expression in WI-38 cells.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.9
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• pp.35-44
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• 2014

This study was to secure the safety of poor appearance distribution concrete poles effectively and to reduce the replacement costs of them by developing a soundness evaluation index. The researcher of this study investigated poor appearance types of concrete pole, collected 53 of test samples, and tested pole strength. As a result of strength test, only 17 percent of poor appearance concrete poles were below 2.0 of safety factor spec. As results of multiple regression analysis, it is verified that surface air void, horizontal crack, net-shaped crack, elapsed year, vertical crack, and deterioration in concrete compressive strength have statistically negative effects on safety factor of concrete poles in a significant level. The researcher set up a soundness evaluation index by using multiple regression equation, and suggested that poor appearance concrete poles should be replaced or reinforced only in case of soundness evaluation score of 150 or above.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.24-27
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• 1996

The storage function method(SFM) is one of hydrologic flood routings which has been used most widely in Korea and Japan. This paper presents a storage function method using multiple model adaptive estimation(MMAE), in which a model set is generated by partitioning storage parameters over feasible range, and each storage function model is estimated, and then the weighted average of them is calculated. Finally, the future runoff is predicted in real time by means of observed data of water level at dam and rainfall. Simulation results applied to actual data show that the proposed method has much better performance than that of conventional SFM.

• Journal of Wellness
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• v.6 no.2
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• pp.139-147
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• 2011

The purpose of this study was to examine the relationship between stress and leisure satisfaction of college student athletes. The participants comprised 140 of the college student athletes. The measures were composed of stress inventory and leisure satisfaction scale. The data were analyzed by SPSS 17.0 Version frequency analysis, reliability analysis, confirmatory factor analysis, independent sample t-test, one-way ANOVA, and multiple regression analysis were performed. The level of significance was set up .05. The results were as follows: First, according to college, there was significant difference in economic burden, environmental condition, and course factor. Second, in regard with multiple regression analysis on relationships between the stress and leisure satisfaction of the college student athletes, discriminative evaluation, environmental condition, and course factor had positive effect on leisure satisfaction.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.521-526
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• 2003

In this paper, we propose a geometric active contour model based on intensity information and curve evolution for detecting region boundaries. We put boundary extraction problem as the minimization of the difference between the average intensity of the region and the intensity of the expanding closed curves. We used level set theory to implement the curve evolution for optimal solution. It offered much more freedom in the initial curve position than a general active contour model. Our methods could detect regions whose boundaries are not necessarily defiened by gradient compared to general edge based methods and detect multiple boundaries at the same time. We could improve the result by using anisotropic diffusion filter in image preprocessing. The performance of our model was demonstrated on several data sets like CT and MRI medical images.

• Journal of Korean society of Dental Hygiene
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• v.18 no.1
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• pp.93-101
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• 2018

Objectives: The purpose of this study was to investigate the relationship between consumption of nutrition and periodontal diseases in the Korean menopausal women. Methods: The data used for analysis were obtained from the sixth Korean National Health and Nutrition Examination Survey (2013). Subjects were 1,407 women aged over 35 years old. Data were analyzed by chi-square and t-test. Multiple regression analysis was also performed to assess the association between nutrition and periodontal diseases. Statistical significance level was set at p<0.05. Results: Using multiple logistic regression analysis after adjustment of age, education level, and BMI, we found significant relationship between intake of protein (OR: 0.31, 95%CI: 0.14-0.65), carbohydrate (OR:3.31, 95%CI 1.90-5.77) and risk for periodontitis. Conclusions: dequate intake of protein and decreased intake of carbohydrate may be recommended for prevention of periodontal diseases in the menopausal women.

• Health Policy and Management
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• v.15 no.3
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• pp.94-113
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• 2005

The purpose of this study was to determine the level of appropriateness in hospital stays and factors influencing inappropriate hospital stays. The study was conducted at fifteen general care units in a tertiary university hospital. Appropriateness of hospital stay was assessed using Appropriateness Evaluation Protocol by trained head nurses. The total of 447 patient records were reviewed. Among them, 352 patient data were included in the final data set. A unit of observation was patient day. A rate of appropriate hospital stay was calculated per patient as a unit of analysis. Multiple regression analysis was performed to determine the factors affecting inappropriate hospital stay. The eighty-three percent (2030/2651) of hospital stays were evaluated as appropriate. There were significant differences in appropriateness of hospital stay according to patient's age, type of health insurance, medical specialty, and length of stay(p<0.05). In the multiple regression analysis, medical speciality was the most significant factor to predict the inappropriate hospital stay. The study showed a substantial proportion of hospital stay was found to inappropriate. Level of appropriateness was significantly different from medical specialty. Interdepartmental approach should be required to coordinate and improve appropriate resource utilization.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.3
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• pp.190-198
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• 2023

This study was conducted to calculate the damage of Italian ryegrass (IRG) by abnormal climate using machine learning and present the damage through the map. The IRG data collected 1,384. The climate data was collected from the Korea Meteorological Administration Meteorological data open portal.The machine learning model called xDeepFM was used to detect IRG damage. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The calculation of damage was the difference between the Dry matter yield (DMY)_normal and DMY_abnormal. The normal climate was set as the 40-year of climate data according to the year of IRG data (1986~2020). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization (WMO) standard. The DMY_normal was ranged from 5,678 to 15,188 kg/ha. The damage of IRG differed according to region and level of abnormal climate with abnormal temperature, precipitation, and wind speed from -1,380 to 1,176, -3 to 2,465, and -830 to 962 kg/ha, respectively. The maximum damage was 1,176 kg/ha when the abnormal temperature was -2 level (+1.04℃), 2,465 kg/ha when the abnormal precipitation was all level and 962 kg/ha when the abnormal wind speed was -2 level (+1.60 ㎧). The damage calculated through the WMO method was presented as an map using QGIS. There was some blank area because there was no climate data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

• Journal of the Korean Home Economics Association
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• v.35 no.1
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• pp.429-442
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• 1997

This study present s and tests a casual model of cohesion adaptability the level of stress recognition coping starategies and quality of life for employed wives and unemployed wives. For the data set 205 employed wives and 200 unemployed wives living in Pusan were chosen. The data were analyzed using M, SD, t-test multiple regression and path analysis. The findings of this study are as follows; First There level of stress recognition and quality of life are higher for employes wives than unemployed wives. Cohesion is higher for employed wives. Whereas adaptability is higher for unemployed wives than employed wives. Employes wives are greater use of coping starategies than unemployed wives. Second For employes wives adaptability the level of stress recognition and coping starategies have significant direct effect on quality of life. Besides wife's level of education age of the youngest child working hours employment motivation and cohesion have significant indirect effect on quality of life. For unemployed wives cohesion adaptability and level of stress recognition have signficant direct effect on quality of life. Besides wife's level of education number of children religion and husband's housework participation are indirectly associated with quality of life. From these results the proposed model is generally supported by the data.