• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.76-87
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• 2017

This study examined the role of safety climate, organizational trust, job satisfaction, and organizational commitment. In addition, the study verified the mediating effect of organizational trust between safety climate, and job satisfaction and organizational commitment. Targeting population were the workers in the manufacturing sector. First, it was figured out that employees' recognition of organizations' safety climate has an effect positively on both job satisfaction and organizational commitment. Second, it turns out that individuals' safety awareness has a positive effect on the both job satisfaction and organizational commitment. Third, it was figured out that organizational trust plays a role as mediation when employees' recognition of organizations' safety climate has an effect positively on both job satisfaction and organizational commitment. Fourth, the result revealed that foreign investment company moderated the relationship between safety climate and organizational climate. Fifth, organizational trust mediates the relationship that the individuals' safety awareness are positively affected on the both job satisfaction and organizational commitment. Finally, The results of four hypotheses using intermediary variable in which organizational trust mediates the relationship between the safety climate and "work attitude" such as job satisfaction and organization commitment demonstrate significance of trust in organization in connecting safety climate and work attitude. Therefore, when trust in organization is enhanced, work attitude such as job satisfaction and organizational commitment could be improved.

• Journal of the Korean Society of Safety
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• v.21 no.4 s.76
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• pp.127-133
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• 2006

The major purpose of this paper to identify safety climate practices, and to find the affecting variables that influence to the difference in the level of safety climate between plants and employees. And this paper attempted to find the interventions for improving safety climate in the chemical plants. The questionnaires were developed from literature review, especially made by HSE(Health and Safety Executive) in the UK and distributed to managers and workers. The frequency analysis was applied for identifying the level of safety climate. The affecting variables(plant size, accident occurrence, accident experience, injury experience and severity, and length of employment) are tested through analysis of variance(ANOVA). The results of frequency analysis showed that both managers and workers recorded generally high level of safety climate, and the major underlying problems are inadequate H&S procedures/rules, pressure for production, and rule breaking. According to the outcomes of ANOVA, the variable 'length of employment' is the only variable which makes the level of safety climate different. From the survey of safety climate practice, this study finds the level of safety climate and three major underlying problems in safety climate factors of the responded plants, and presents two interventions for improving safety performance. Despite of these outcomes, the applied factors are remained questionable for reflecting as the best ones for identifying safety climate in the chemical industry. In addition, the bias caused by self-report exist in the reliability of the response, and the equivalent size of respondents.

• Journal of Korean Society of Rural Planning
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• v.23 no.4
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• pp.153-168
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• 2017

The main objective of this study was to assess reference evapotranspiration based on multiple GCMs (General Circulation Models) and estimation methods. In this study, 10 GCMs based on the RCP (Representative Concentration Pathway) 4.5 scenario were used to estimate reference evapotranspiration. 54 ASOS (Automated Synoptic Observing System) data were constructed by statistical downscaling techniques. The meteorological variables of precipitation, maximum temperature and minimum temperature, relative humidity, wind speed, and solar radiation were produced using GCMs. For the past and future periods, we estimated reference evapotranspiration by GCMs and analyzed the statistical characteristics and analyzed its uncertainty. Five methods (BC: Blaney-Criddle, HS: Hargreaves-Samani, MK: Makkink, MS: Matt-Shuttleworth, and PM: Penman-Monteith) were selected to analyze the uncertainty by reference evapotranspiration estimation methods. We compared the uncertainty of reference evapotranspiration method by the variable expansion and analyzed which variables greatly influence reference evapotranspiration estimation. The posterior probabilities of five methods were estimated as BC: 0.1792, HS: 0.1775, MK: 0.2361, MS: 0.2054, and PM: 0.2018. The posterior probability indicated how well reference evapotranspiration estimated with 10 GCMs for five methods reflected the estimated reference evapotranspiration using the observed data. Through this study, we analyzed the overall characteristics of reference evapotranspiration according to GCMs and reference evapotranspiration estimation methods The results of this study might be used as a basic data for preparing the standard method of reference evapotranspiration to derive the water management method under climate change.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.10
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• pp.29-35
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• 2021

The current study's objective isto determine the impact of organizational climate on organizational reputation in the context of organizational health as a mediating variable, in a case study of textile enterprises in Jordan that are listed on the Industrial Qualified zones. The study population contains (12) companies, according to the industrial qualified zones, with 317 employees who are working at CEO, deputy CEO, and supervisor positions chosen through convenience sampling. While the final sample of the current study consists of 174. Furthermore, to test the current study's hypotheses, the Smart Partial Least Square (PLS) technique was applied. Additionally, the current study concludes that there is a positive impact of organizational climate on organizational reputation. The current study shows that organizational climate has a positive impact on organizational health and organizational health has a positive impact on organizational reputation. Moreover, there is the mediation impact of organizational health on the relationship between organizational climate and organizational reputation. Based on the results of the current study, the study proposes that the level of organizational climate, organizational health, and organizational reputation in the examined companies be enhanced and increased.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.47-47
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• 2023

Drought occurs due to lack of water resources over an extended period and its intensity has been magnified globally by climate change. In recent years, drought over South Korea has also been intensed, and the prediction was inevitable for the water resource management and water industry. Therefore, drought forecasting over South Korea was performed in the current study with the following procedure. First, accumulated spring precipitation(ASP) driven by the 93 weather stations in South Korea was taken with their median. Then, correlation analysis was followed between ASP and Df4m, the differences of two pair of the global winter MSLP. The 37 Df4m variables with high correlations over 0.55 was chosen and sorted into three regions. The selected Df4m variables in the same region showed high similarity, leading the multicollinearity problem. To avoid this problem, a model that performs variable selection and model fitting at once, least absolute shrinkage and selection operator(LASSO) was applied. The LASSO model selected 5 variables which showed a good agreement of the predicted with the observed value, R²=0.72. Other models such as multiple linear regression model and ElasticNet were also performed, but did not present a performance as good as LASSO. Therefore, LASSO model can be an appropriate model to forecast spring drought over South Korea and can be used to mange water resources efficiently.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.109-128
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• 2020

A climate-impact projection usually consists of several stages, and the uncertainty of the projection is known to be quite large. It is necessary to assess how much each stage contributed to the uncertainty. We call an uncertainty quantification method in which relative contribution of each stage can be evaluated as uncertainty decomposition. We propose a new Bayesian model for uncertainty decomposition in climate change impact assessments. The proposed Bayesian model can incorporate uncertainty of natural variability and utilize data in control period. We provide a simple and efficient Gibbs sampling algorithm using the auxiliary variable technique. We compare the proposed method with other existing uncertainty decomposition methods by analyzing streamflow data for Yongdam Dam basin located at Geum River in South Korea.

• Journal of Korean Society of Water and Wastewater
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• v.30 no.1
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• pp.51-58
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• 2016

On account of the increase in water demand and climate change, droughts are in great concern for water resources planning and management. In this study, rainfall characteristics with stationary and non-stationary perspectives were analyzed using Weibull distribution model with 40-year records of annual minimum rainfall depth collected in major cities of Korea. As a result, the non-stationary minimum probable rainfall was expected to decrease, compared with the stationary probable rainfall. The reliability of ${\xi}_1$, a variable reflecting the decrease of the minimum rainfall depth due to climate change, in Wonju, Daegu, and Busan was over 90%, indicating the probability that the minimal rainfall depths in those city decrease is high.

• Journal of Korean Society of Water and Wastewater
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• v.26 no.2
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• pp.321-329
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• 2012

In this study, statistical analysis under both stationary and non-stationary climate was conducted for rainfall data measured in Seoul. Generalised Extreme Value (GEV) distribution and Gumbel distribution were used for the analysis. Rainfall changes under the non-stationary climate were estimated by applying time variable (t) to location parameter (${\xi}$). Rainfall depths calculated in non-stationary climate increased by 1.1 to 6.2mm and 1.0 to 4.6mm for the GEV distribution and gumbel distribution respectively from those stationary forms. Changes in annual maximum rainfall were estimated with rate of change in the location parameter (${\xi}1{\cdot}t$), and temporal changes of return period were predicted. This was also available for re-evaluating the current sewer design return period. Design criteria of sewer system was newly suggested considering life expectance of the system as well as temporal changes in the return period.

• Korean Journal of Agricultural Science
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• v.38 no.2
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• pp.219-225
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• 2011

Changes in biota, species distribution range shift and catastrophic climate influence due to recent global warming have been observed during the last century. Since global warming affects various sectors, such as agriculture and vegetation, it is important to predict more accurate impact of future climate change. The purpose of this study is to examine the observed distribution of Abeliophyllum distichum in the Korean peninsula. For this purpose, two period (present and future) climate data were used. Mean data between 1950 and 2000, were used as the present value and the year 2050 and 2080 data from A1B senario in IPCC SRES were used for the future value. Potential habitation is analyzed by MaxEnt(Maximum Entropy model), and Abeliophyllum distichum's coordinates data were used as a dependent variable and independent variables are composed of environmental data such as BioClim, altitude, aspect and slope. The result of six types GCM mean calculation, the potential habitability decreased by 40-60% of the average existing distribution. The methodogies and results of this research can be applicable to the climate changing adaptation stratiegies for the biodiversity conservation.

• Journal of the Korean Society of Safety
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• v.28 no.1
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• pp.102-108
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• 2013

This study aimed to examine the impact of workers' perceptions of the safety climate on job satisfaction and intention to turnover in the manufacturing industry. Data was collected from employees(n=143) working in the manufacturing industry. The perceived safety climate included perceptions of the safety commitment of the management, safety leadership of the immediate supervisor, and safety policy. Hierarchical regressions were conducted to identify the significance of the relation between the sub-variable of the perceived safety climate and job satisfaction, and intention to turnover. The results show that safety commitment and safety policy are significant predictors of job satisfaction. The immediate supervisor's safety leadership was significantly correlated with intention to turnover. These results indicated that the perceived safety climate of workers in the manufacturing industry might influence job satisfaction and intention to turnover. Therefore, organizations in the manufacturing industry should focus on improving safety climates to enhance job satisfaction and prevent employee turnover.