• Asian-Australasian Journal of Animal Sciences
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• v.12 no.6
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• pp.846-849
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• 1999

Angus postweaning daily gain (PWDG) were analyzed to investigate heterogeneous variance by sex. A set of data (16,239 records) was divided into six sub-data sets according to level of environment. REML estimation was conducted by a multitrait model, where PWDG in each sex was treated as a separate trait. Estimates showed diversity among environmental levels, where the heritability for heifers was high in good environment but low in poor environment. The bull's estimates varied among environmental levels. The largest heterogeneity of phenotypic variance between sexes was estimated in a data set of the poor environment level. The genetic correlations between the heifer's PWDG and the bull's PWDG were high in the good environment and low in the poor environment (-0.17). The results suggest existence of genotype by sex interaction in the poor environment.

• Journal of the Speleological Society of Korea
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• no.85
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• pp.38-40
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• 2008

With regard to Jeju Special Self-governing Province's natural-spa tourist spot development project, this paper has investigated the natural environment of Sehwa-Songdang Lave Region. According to this study, the cave consists of many small caverns with poor cave formations. Due to unfavorable climate conditions in the cave, in addition, hydrological environment is also very poor. In terms of vegetation, the cave shows the general vegetation environment of Jeju.

• Journal of IKEEE
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• v.18 no.4
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• pp.485-494
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• 2014

Traffic Sign Recognition(TSR) is an important element in an Advanced Driver Assistance System(ADAS). However, many studies related to TSR approaches only in normal daytime environment because a sign's unique color doesn't appear in poor environment such as night time, snow, rain or fog. In this paper, we propose a new TSR algorithm based on machine learning for daytime as well as poor environment. In poor environment, traditional methods which use RGB color region doesn't show good performance. So we extracted sign characteristics using HoG extraction, and detected signs using a Support Vector Machine(SVM). The detected sign is recognized by a decision tree based on 25 reference points in a Normalized RGB system. The detection rate of the proposed system is 96.4% and the recognition rate is 94% when applied in poor environment. The testing was performed on an Intel i5 processor at 3.4 GHz using Full HD resolution images. As a result, the proposed algorithm shows that machine learning based detection and recognition methods can efficiently be used for TSR algorithm even in poor driving environment.

• Korean Journal of Rural Living Science
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• v.6 no.2
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• pp.151-161
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• 1995

The objective of this study is to analyse consumption problems of the rural poor households. This is a succeeding work to the previous report on economic resource problems. Data from 154 rural poor house holds and 290 rural non-poor households were analysed to comprehend their consumption practices, financial management ability, consumer competence of homemakers, and market environments. The major findings and conclusions are as follows : 1. The rural poor households had deficit of 30, 000 won per month. They perceived relative importance of the educational expenses and food expenses and heavier pressure of educational expenses and light and water expenses than other items. 2. The rural poor households evaluated their financial management ability average like non-poor households but their level of consumer competence was lower than other households. This means their consumer efficiency is relatively low. 3. The rural poor households had similar grade of market environments to non-poor households. This is significantly different from urban households.

• Journal of the Korean housing association
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• v.21 no.1
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• pp.1-9
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• 2010

Housing problems in city have being caused social contradiction that contains social discord and conflict between poor and rich. And they have raised one of social problems including a disequilibrium of demand and supply, a housing trouble, and a poor residential environment. Therefore, the purpose of this study is to suggest to the improvement of social housing that exposes to a poor environment for social integration. For this, this study is to extract environmental-friendly design factors for each building phase by in-depth evaluation of experts, and to analyze the problems of domestic social housing and environment-friendly design factors considered prior literature. The results as follow. It might be considered highly phase of schematic design, The building construction, and performance management having factors. Specially, it analyzed to 'Living Environment', 'Economic Efficiency', and 'renewable Energy Systems' should be considered highly. Ultimately, this study would be reconsidered the improvement of social housing proposed by the Government for the social outcast.

• Korean Journal of Occupational Health Nursing
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• v.25 no.4
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• pp.300-310
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• 2016

Purpose: Few studies have considered the psychosocial work environment factors in relation to employee health. This study explored the relationship between psychosocial work characteristics and self-rated health among Korean employees. Methods: The study population of 21,476 employees was derived from the 2014 Korean Work Environment Survey (KWES). Psychosocial work environment was measured by Copenhagen psychosocial questionnaire scales. Results: Among employees at workplaces (n=21,476), 23.3% rated their health as poor. Among 12 indicators of psychosocial work environment characteristics, 'higher emotional demand', 'demands for hiding emotions', 'work-family conflict', and 'social community at work' were independently associated with risk of poor self-rated health of Korean employees after adjustment of all sociodemographics, work condition characteristics and physical work environment exposure. In addition, higher 'possibilities for development' and 'social support from supervisor' were more likely to decrease the risk of poor health. Conclusion: We suggest that psychosocial work environment is an important determinant of employees' health. The study results provide a good starting point for developing intervention and strategies for health improvement.

• Child Health Nursing Research
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• v.9 no.3
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• pp.301-308
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• 2003

The Purpose of this study was to identify factors that influence the self-esteem of the schooler of families in poverty. A descriptive, correlational, and cross-sectional study design was used. The data were collected from February to March, 2001. Convenient sampling was done from 194 subjects living in Jeju Do, but 167 subjects among these were used for the study analysis. Hierarchical Stepwise Regression was used to identify significant factors. The results of this study were as follows: In general, self-esteem status of the schooler in poor families was relatively poor. In stepwise regression analysis, self-esteem status was significantly influenced by emotional home environment, duration of poverty and frequency of parent-child tactics. These variables explained 26.8％ of the variance of schooler's self-esteem. Conclusively, it is recommended that nursing intervention programs for schooler in poor family should be a focus to enhance the economic context as well as family effect.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.5-25
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• 2016

The purpose of this study develops the methodology to extract the poor deprived districts using the data from the national spatial data infrastructure portal. Particularly this study tries to select more acute indicators and to test the operability of such indicators. Also this study is focused on the versatile methodology that can be adjusted to incorporate alternative indicators that might be appropriate according to the hierarchy of the spatial unit. The indicator sets are composed of three dimensions: the poor class, the poor old housing, and poor residential neighborhood environment. Each representative indicator is selected based on the characteristics of the poor deprived districts. As a result, at the level of administrative Dong, key indicators for extracting the poor deprived districts are number of recipients of national basic living security per thousand persons and ratio of households living at old detached house. At the level of the national based zip code district, the ratio of buildings built on parcels located at roads below 4m in width, the ratio of small parcels below $60m^2$ and the ratio of poor old buildings are very important indicators. The result of grid analysis by overlaying the coverage of multiple indicators shows that relatively more vulnerable and deprived districts can be extracted at the small sub-district level. This study suggests the possibility to create the high value-added information, using the data from the national spatial data infrastructure portal. This methodology enables policymakers to select the priority target districts of poor deprived district more effectively.

• Human Ecology Research
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• v.56 no.2
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• pp.175-193
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• 2018

This study identified the rate of income poverty and multidimensional poverty, correlation between income poverty and multidimensional poverty, and adjusted multidimensional poverty rate. We also analyzed the factors that affected the number of poverty dimension and the probability of belonging to the poor or not in 3,159 elderly households including 474 poor households and 2,685 middle class households. First, in poor households, the employment poverty rate was the highest and the housing poverty rate was the lowest. In middle class households, the relation poverty rate was the highest and the employment poverty rate was the lowest. Second, in poor households, correlation between asset poverty and relation poverty had the highest coefficient of .205 and asset poverty and housing poverty had the lowest coefficient of .149. In middle class households, the correlation between income poverty and relation poverty had highest coefficient of -.290 and employment poverty and relation poverty had the lowest coefficient of .038. Third, in poor households, the number of average poverty dimension was 4.30, but the number of average poverty dimensions of middle class households was 2.310. Fourth, the variable affecting the number of poverty dimensions in poor households were gender, age, level of education, marital status; however, the significant variables were gender, education level, marital status, income poverty in the middle class households. The variable that affected the probability of belonging to the poor or not in poor households was age. However, the significant variables were gender, education level, marital status, residence, and income poverty in middle class households.

• Journal of Korean Public Health Nursing
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• v.29 no.3
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• pp.528-539
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• 2015

Purpose: The aim of this study is to provide baseline data on the housing environment of a vulnerable population. Methods: This study provides a descriptive survey on the housing environment of a vulnerable population of a city in Gyeong-gi province. A total of 9,061 households were selected as research participants. Data were collected through face-to-face interviews by visiting nurses from February 2014 to March 2014. Results: Interviewees answered "poor" on items including cold drafts, illumination, daylight penetration, inflow of polluted air, house odor, stairs safety, noise, mold, pests, and ventilation. The score for housing environment problems showed a significant group difference due to gender, age, economic status, family type, type of housing, and type of ownership. Conclusion: These results indicate that the vulnerable population is exposed to a poor housing environment. Thus, there is an urgent need to improve the housing environment for the vulnerable population. Based on this study, linking a visiting health care service program and housing environment improvement projects from relevant administrative agencies might be recommended in order to effectively improve the housing environment.