• KCID journal
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• v.18 no.2
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• pp.33-42
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• 2011

Climate change has impacts on not only the average temperature rise but also the intensity and frequency of extreme events such as flood and drought. It is also expected that the damages on agricultural infrastructure will be increased resulting from increased rainfall intensity and frequency caused by climate change. To strengthen the climate change adaptation capacity, it is necessary to identify the vulnerability of a given society's physical infrastructures and to develop appropriate adaptation strategies with infrastructure management because generally facilities related to human settlements are vulnerable to climate changes and establishing an adaptive public infrastructure would reduce the damages and the repair cost. Therefore, development of mitigation strategies for agricultural infrastructure against climatic hazard is very important, but there are few studies on agricultural infrastructure vulnerability assessment and adaptation strategies. The concept of vulnerability, however, is difficult to functionally define due to the fact that vulnerability itself includes many aspects (biological, socioeconomic, etc.) in various sectors. As such, much research on vulnerability has used indicators which are useful for standardization and aggregation. In this study, for the vulnerability assessment for agricultural infrastructure, 3 categories of climate exposure, sensitivity, and adaptation capacity were defined which are composed of 16 sub-categories and 49 proxy variables. Database for each proxy variables was established based on local administrative province. Future studies are required to define the weighting factor and standardization method to calculate the vulnerability indicator for agricultural infrastructure against climate change.

• Journal of Environmental Impact Assessment
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• v.22 no.6
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• pp.677-693
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• 2013

IPCC showed that calculation of climate vulnerability index requires standardization process of various proxy variables for the estimation of climate exposure, sensitivity, and adaptive capacity. In this study, four different methodologies of standardization methods: Z-score, Rescaling, Ranking, and Distance to the reference country, are employed to evaluate climate vulnerability-VRI (Vulnerability-Resilience Indicator) over Korean peninsula, and the error ranges of VRI, arising from employing the different standardization are estimated. All of proxy variables are provided by CCGIS (Climate Change adaptation toolkit based on GIS) which hosts information on both past and current socio-economic data and climate and environmental IPCC SRES (A2, B1, A1B, A1T, A1FI, and A1 scenarios) climate data for the decades of 2000s, 2020s, 2050s, and 2100s. The results showed that Z-score and Rescaling methods showed statistically undistinguishable results with minor differences of spatial distribution, while Ranking and Distance to the reference country methods showed some possibility to lead the different ranking of VRI among South Korean provinces, depending on the local characteristics and reference province. The resultant VRIs calculated from different standardization methods showed Cronbach's alpha of more than 0.84, indicating that all of different methodologies were overall consistent. Similar horizontal distributions were shown with the same trends: VRI increases as province is close to the coastal region and/or it close toward lower latitude, and decreases as it is close to urbanization area. Other characteristics of the four different standardization are discussed in this study.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.665-676
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• 2013

The present study analyzed the KOCCA's Game Immersion data to explore the relationship between psychological traits and game immersion. Psychological traits were classified into four categories; emotional stability, self-esteem, willpower, and happiness. These were put into the multiple regression analysis as the dependent variables with age, sex (dummy), economic status of the homes, variety of leisure activities, friend and family relationship, and time to play games. Four types of immersion (psychological unstability, bad relationship, interrupted daily lives, and failure to control game time and desire) were put into the multiple regression analysis as the independent variables. The multiple regression analysis indicated that the dependent variables predicted the game immersion. Among the psychological traits emotional stability was the strongest factor (negative) that influences the game immersion. Next powerful indicator (negative) among the psychological traits was self-esteem. Based on the findings, measures to alleviate the problems of game immersion and ideas for further research were suggested.

• Journal of Korean Academy of Nursing
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• v.31 no.2
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• pp.315-327
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• 2001

This was a descriptive study clarifying the factors affecting family caregivers' sense of well-being. This study was conducted with 131 caregivers using structured self-reporting questionnaires and directly interviewing adult patients who had been under treatment in two general hospitals. The hospitals were located in M city from Aug. 10, 2000 until Sep. 2, 2000. The collected data were analyzed using SAS PC+ program, and the data were tested using descriptive statistics, t-tests, ANOVA, Pearson's Correlation Coefficient, and Stepwise Multiple Regression. The results of this study are as follows; 1) The variables affecting the caregivers' sense of burden were age (F=3.76, p=.0063), education level (F=4.67, p=.0015), monthly income (F=2.49, p=.0466), amount of assistance provided (F=4.19, p=.0037), and the relationship with patient before disease (F=9.49, p=.0001). 2) The variables affecting caregivers' sense of well-being were age (F=9.54, p=.0001), residing with patient (t=11.38, p=.0010), the period of caregiving (F=10.52, p= .0001), education level (F= 2.79, p=.0290), monthly income (F=3.04, p=.0196), and relationship with patient before disease (F= 10.51, p=.0001). Also, all of the variables which showed statistical significance. 3) In viewing the relationship between activities of daily living (ADL) and the senses of burden and well-being, a negative relation- ship between activities of daily living (ADL) and a sense of burden was found (r=-.640, p=.000). However, the relationship between activities of daily living (ADL) and a sense of well-being had a positive correlation (r= .232, p=.008). Also the relationship between the sense of burden and the sense of well-being was revealed to have a negative correlation (r=-.614, p=.000). 4) A sense of burden was the most important indicator to the well-being of the caregivers who took care of stroke patients (R2 =.36). In addition to this, living with the patient (45%), activities of daily living (51%), relationship with patient before disease (53%), and the family's monthly income accounted for 56% of the sense of well-being of the caregivers.

• Journal of Animal Science and Technology
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• v.63 no.3
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• pp.651-661
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• 2021

This study aimed to investigate whether breed, sex, and age affected temperament differently (more or less neophobic) in mature horses during a novel object test. The study included Jeju crossbred (n = 12, age = 9.42 ± 4.57 y), Thoroughbred (n = 15, age = 10.73 ± 3.09 y), and Warmblood horses (n = 12, age = 13.08 ± 3.55 y) with the females (n = 22, age = 11.36 ± 4.24 y) and geldings (n = 17, age = 10.65 ± 3.66 y). Jeju crossbreds (Jeju horse × Thoroughbred) are valuable considering their popular usage in Korea, but limited studies have explored temperament of Jeju crossbred horses. A trained experimenter touched the left side of the neck with a white plastic bag (novel object). The test ended when the horse stopped escape response and heart rate (HR) dropped to baseline. Behavioral score and escape duration were measured as behavioral variables. Multiple variables related to HR and heart rate variability (HRV) were measured to reflect emotional state. These included basal HR (BHR), maximum HR (MHR), delay to reach maximum heart rate (Time to MHR), standard deviation of beat-to-beat intervals (SDNN), root mean square of successive differences (RMSSD), and ratio of low to high frequency components of a continuous series of heartbeats (LF/HF). Statistics revealed that Thoroughbreds had significantly higher behavioral scores, and lower RMSSD than Jeju crossbreds (p < 0.05), suggesting greater excitement and fear to the novel object in Thoroughbreds. None of the behavioral or cardiac parameters exhibited sex differences (p < 0.05). Age was negatively correlated with SDNN and RMSSD (p < 0.05), indicating that older horses felt more anxiety to the novelty than younger horses. Thoroughbreds and females had distinct correlations between behavioral and HRV variables in comparison with other groups (p < 0.05), implying that escape duration might be a good indicator of stress, especially in these two groups. These results are expected to improve equine welfare, safety and utility, by providing insights into the temperament of particular horse groups, to better match reactivity levels with specific functions.

• Journal of the Korean Geosynthetics Society
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• v.21 no.2
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• pp.21-30
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• 2022

Shear strength is the most important indicator in the evaluation of rock slope stability. It is generally estimated by comparing the results of existing literature data, back analysis, experiments and etc. There are additional variables related to the state of discontinuity to consider in the shear strength of the rock slope. It is difficult to determine whether these variables exist through drilling, and it is also difficult to find an exact relationship with shear strength. In this study, the data calculated through back analysis were used. The relationship between previously considered variables was applied to deep learning and the possibility for estimating shear strength of rock slope was explored. For comparison, an existing simple linear regression model and a deep learning algorithm, a deep neural network(DNN) model, were used. Although each analysis model derived similar prediction results, the explanatory power of DNN was improved with a small differences.

• Journal of Korea Trade
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• v.26 no.7
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• pp.127-144
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• 2022

Purpose - This study aimed to analyze the dynamic effects of progress in globalization on firm performance by employing individual companies' financial statement datasets. Design/methodology - The analysis leveraged the variables of operating revenue (OPRE) and pre-tax profit and loss (PLBT) as measurement variables for firm performance over 2011-2019. As a proxy variable for globalization, the trade index, a subordinate indicator of the KOF Globalization Index, was used. Through panel regression analysis, the relationship among those variables was ascertained, and the local projection (LP) method was subsequently utilized to identify dynamic effects. A subsample analysis was further performed by classifying companies based on their sizes and industries to determine the differential effects of globalization on each group. Findings - The panel regression analysis derived positive effects of an increasing degree of globalization on OPRE of Korea maritime and fishery firms. However, the impulse response functions, obtained from the LP, showed that in the short run, globalization affects PLBT negatively but in the long run, it gradually converted into a positive effect. In addition, according to the subsample analysis based on company size, the effects of globalization on OPRE became greater as each company became larger. Moreover, the industry-based analysis showed heterogeneous effects, depending on the industries in which the maritime and fishery companies operated. Originality/value - The analysis of the dynamic effects of globalization on firm performance, which revealed that the effects vary depending on the time points, is the important contribution of this study. The results also suggest that the effects of globalization vary depending on the company size and industry.

• Journal of Korean Academy of Nursing
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• v.44 no.1
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• pp.21-30
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• 2014

Purpose: This study was conducted to explore the impact of registered nurse/nurses' aid (RN/NA) staffing and turnover rate on inpatient health outcomes in long term care hospitals. Methods: A secondary analysis was done of national data from the Health Insurance Review and Assessment Services including evaluation of long term care hospitals in October-December 2010 and hospital general characteristics in July-September 2010. Final analysis of data from 610 hospitals included RN/NA staffing, turnover rate of nursing staff and 5 patient health outcome indicators. Results: Finding showed that, when variables of organization and community level were controlled, patients per RN was a significant indicator of decline in ADL for patients with dementia, and new pressure ulcer development in the high risk group and worsening of pressure ulcers. Patients per NA was a significant indicator for new pressure ulcer development in the low risk group. Turnover rate was not significant for any variable. Conclusion: To maintain and improve patient health outcomes of ADL and pressure ulcers, policies should be developed to increase the staffing level of RN. Studies are also needed to examine causal relation of NA staffing level, RN staffing level and patient health outcomes with consideration of the details of nursing practice.

• Bulletin of the Korean Chemical Society
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• v.31 no.7
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• pp.1907-1914
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• 2010

A novel catalytic kinetic method is proposed for the determination of Se(IV), Se(VI) and total inorganic selenium in water based on the catalytic effect of Se(IV) on the reduction of bromate by p-nitrophenylhydrazine at pH 3.0. The generated bromine, $Br_2$ or $Cl_2$ plus $Br_2$ in 0.1 M NaCl (or NaBr) environment efficiently decolorized Calmagite and the reaction was monitored spectrophotometrically at 523 nm as a function of time. In this indicator reaction, bromide acted as an activator for the catalysis of selenium (IV) and a reducing agent for selenium (VI) at pH 3.0, which allowed the determination of total selenium. The fixed time method was adopted for the determination and speciation of inorganic selenium. Under the optimum conditions, the calibration graph are linear in the range 1 - 35 ${\mu}gL^{-1}$ of Se(IV) for the fixed time method at $25^{\circ}C$. The detection limit based on statistical $3S_{blank}$/m-criterion was 0.215 ${\mu}gL^{-1}$ for the fixed time method (7 min). All of the variables that affect the sensitivity at 523 nm were investigated, and the optimum conditions were established. The interference effect of various cations and anions on the Se (IV) determination was also studied. The selectivity of the selenium determination was greatly improved with the use of the strongly cation exchange resin such as Amberlite IR120 plus. The proposed kinetic method was validated statistically and through recovery studies in natural water samples. The RSDs for ten replicate measurements of 5, 15 and 25 ${\mu}gL^{-1}$ of Se(IV) and Se(VI) was changed between 2.1 - 4.85%. Analyses of a certified standard reference material (NIST SRM 1643e) for selenium using the fixed-time method showed that the proposed kinetic method has good accuracy. Se(IV), Se(VI) and total inorganic selenium in environmental water samples have been successfully determined by this method after selective reduction of Se(VI) to Se(IV).

• Journal of the Economic Geographical Society of Korea
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• v.14 no.3
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• pp.377-393
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• 2011

This study aims to indicate the spatial characteristics of the changes in the Korean farm land. In particular, we analyze the spatial diffusion patterns of organic farms increasing rapidly with the growth in the agricultural product markets as well as the demand for safe food and sustainable growth. For the purpose, we examine the changes in the distribution patterns of organic farms between year 2000 and 2005. We analyze the agglomeration pattern by Location Quotient (LQ) and Local indicator of spatial association (LISA). Organic farms have been spread out from the outscuirts of Seoul, the capital city, to the traditional agriculture spetilized area in the southern parts of the nation. In order to analyze the relationships between organic farm distribution and the geographical variables affecting the organic farming, we develop multivariate regression models. Our findings indicate that organic farming is related with the number of agriculture-based business and information technique adaptation as well as the level of education and farmers age.