• 한국노년학
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• v.29 no.2
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• pp.761-779
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• 2009

The purpose of this study is to analyze the factors affecting the quality of life of elderly people from the ecological perspective. Specifically, this study attempts to compare the relative contributions of the variables from the individual system, microsystem, mesosystem, and macrosystem on the quality of life of the elderly people. The subjects for this study consisted of 443 elderly over 60 years old in Daegu city, Gyeongsang-do, and Chungchung-do areas. The data were collected randomly by interviews with a structured questionnaire, and analyzed by frequencies, means, ANOVA, and hierarchial regression method. The major-findings of this study were as follows: 1. The quality of life of the elderly consisted of four factors; physical, economic, psychological, and social factors. The highest satisfaction score for the quality of life was found in psychological factors, The global satisfaction score for the quality of life was found to be relatively high. 2. Out of the individual factors influencing the quality of life of the elderly, the economic status of the respondent was found to be the most important. Out of the microsystemic factors, the most important factors were found to be the intimacy with the spouse and with the children. Out of the mesosysystemic factors, the degree of the social participation of the elderly was found to be the most significant. However, none of the macrosystemic factors were found to be important in influencing the quality of life of the elderly people. 3. The relative significances of the variables contributing to the quality of life of the elderly were analyzed using a hierarchical regression technique. It was found that there was no significant factor in social background and mesosystemic variables. On the other hand, the degree of the self-efficacy and the level of the economic status from the individual factors, and the intimacy with the spouse and the children from microsystemic factors were found to be very significant in contributing the quality of life of the elderly.

• Korean Journal of School Psychology
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• v.8 no.2
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• pp.133-152
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• 2011

This is a short-term longitudinal study investigating the relationships between changes in mental health and academic burnout among Korean middle school students. Study sample consisted of 409 middle school students in Seoul provision, with 161 male, 216 female, and 32 unidentified. Both Symptom Check List(SCL-47) and Maslach Burnout Inventory-Student Survey(MBI-SS) were used. In order to examine the pattern of changes in mental health and academic burnout among students, standardized residuals were calculated using regression equations which were then put into canonical correlation analysis. The results of this study are as follows. First, according to Function 1, among sub-factors of mental health, decreases in depression, compulsion, anxiety, and hostility were particularly associated with decreases in exhaustion and cynicism among academic burnout. Put in another way, students who showed increases in depression, compulsion, anxiety, and hostility experienced more academic exhaustion and cynicism. Second, according to Function 2, increases in phobic anxiety, compulsion with decreases in anxiety, depression were associated with decrease in academic exhaustion and increase in cynicism. Considering Russell's dimensional theory of emotion, Function 1 showed that mental health symptoms including both aroused and non-aroused affects were related with increases in exhaustion and cynicism while Function 2 showed that mental health symptoms including only aroused aspects were related with decrease in exhaustion and increase in cynicism. Thus, a conclusive intervention program seems to be required to deal with both aroused and non-aroused affects of students who are experiencing increased exhaustion and cynicism. On the other hand, an intervention program focused on aroused affects seems appropriate to students who are experiencing decreased exhaustion and increased cynicism. This study has its value in that it has enhanced understanding of students in school and counseling settings by revealing the relationships between mental health and academic burnout among adolescents and suggested differentiated intervention strategies based on patterns of students' academic burnout.

• Food Engineering Progress
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• v.23 no.1
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• pp.7-15
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• 2019

The impregnation of solid foods into the surrounding hypotonic or hypertonic solution was explored as a method to infuse NaCl in pork loin cube without altering its matrix. Mass transfer kinetics using a diffusive model as the mathematical model for moisture gain/loss and salt gain and the resulting textural properties were studied for the surrounding solutions of NaCl 2.5, 5.0, 10.0 and 15% (w/w). It was possible to access the effects of brine concentration on the direction of the resulting water flow, quantify water and salt transfer, and confirm tenderization effect by salt infusion. For brine concentrations up to 10% it was verified that meat samples gained water, while for processes with 15% concentration, pork loin cubes lost water. The effective diffusion coefficients of salt ranged from 2.43×10^-9 to 3.53×10^-9 m²/s, while for the values of water ranged from 1.22×10^-9 to 1.88×10^-9 m²/s. The diffusive model was able to represent well salt gain rates using a single parameter, i.e. an effective diffusion coefficient of salt through the meat. However, it was not possible to find a characteristic effective diffusion coefficient for water transfer. Within the range of experimental conditions studied, salt-impregnated samples by 5% (w/w) brine were shown with minimum hardness, chewiness and shear force.

• Journal of the Daesoon Academy of Sciences
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• v.21
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• pp.157-195
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• 2013

대순진리회는 '구천응원뇌성보화천존강성상제(이하 '구천상제')'를 주신(主神)으로 신앙하는 종교단체이다. 그렇다면 대순진리회의 '구천상제'와 중국 도교에서 모셔지는 '구천응원뇌성보화천존'(이하 '보화천존')은 어떤 연관성이 있는 것인가? 이런 질문을 토대로 본 글에서는 이 신들의 기원과 칭호, 도세법문(度世法門 : 세상을 제도하고자 펼친 법도) 등의 관점에서 그 차이점과 공통점을 하나씩 비교해 보았다. 먼저 기원이라는 측면에서 '구천상제'와 '보화천존'을 비교해보면, '구천상제'는 천지인 삼계의 최고신으로서 강씨 가문을 선택하여 인간의 육신으로 태어났다. 강씨 성은 상고 신농씨에서 시작되었는데, 고대 문헌에 근거하면 신농씨는 태양신, 남쪽, 불(火) 등으로 상징화된다. 이런 상징들은 '구천상제'가 인간으로 태어날 때 나타난 "하늘이 남북으로 갈라지다", "큰 불덩이가 몸을 덮치다", "천지가 밝아지는도다" 등의 현상들에서 찾아볼 수 있다. 도교의 '보화천존'은 뇌신의 특징을 가지면서 일신(日神), 월신(月神)과 관계를 맺고 있는데, 이런 면들은 신농씨로부터 분석한 '구천상제'의 신적 기원과 일치하고 있다. 또한 도교에서는 신농씨가 다스리던 세상을 중국 상고시대의 가장 이상적인 사회형태로 보고 있는데, 이것을 '구천상제'가 건설하려는 후천선경과 연관 지어 생각해보면 '구천상제'가 신농씨의 후손인 강씨 종가에서 태어난 배경을 이해할 수 있다. 도교의 '보화천존' 역시 중생의 이익을 도모하고, 조화로운 인간세상을 만드는 것을 목표로 삼고 있으며, 이것은 대순진리회 '구천상제'가 행한 대순의 목적과 거의 비슷하다고 볼 수 있다. 다음으로 '구천상제'와 '보화천존'은 칭호에서도 공통점과 차이점을 살펴볼 수 있다. 단적으로 말하자면, '구천상제'에는 '보화천존'에 비해 '강성상제'라는 칭호가 추가되어 있다는 것이다. 또한 도교에서는 '보화천존'을 최고신으로 모시지 않으며, '구천상제' 신앙에서는 '보화천존' 신앙에서와 달리 뇌신과의 관계에 대한 설명을 찾아볼 수 없다. 마지막으로 '구천상제'와 '보화천존'의 도세법문을 비교해보면 첫째, 구천상제는 세상이 혼란, 불공평, 죄악에 빠졌기에 육신으로 인간 세상에 강림한 후 대순진리를 선포하였다. 이와 유사하게 보화천존도 천하와 인간세상을 순시하여 죄악과 겁액을 없앤다는 '순시천하(巡視天下)' 사상이 있다. 물론 여기에는 차이점이 존재하는데, 그 중 하나는 '보화천존'은 순시할 때 인간의 육신으로 화하지 않았다는 점이다. 또 다른 하나는 '보화천존'이 인간 세상에 창교의 방법을 통하여 선경을 건설하고자 하는 목표를 전해주지 않았다는 점이다. '보화천존'은 교리를 가르치거나 신통을 발휘하는 데에만 중점을 두고 있다. 둘째, '구천상제'가 내린 가르침인 해원상생은 후천선경을 건설하기 위한 수단과 과정이다. 도교의 '보화천존'도 인간이 지은 많은 죄악과 겁액은 세상 사람들이 맺은 원한과 관계가 있으므로, 이런 겁액과 죄를 해소하려면 해원부터 해야 한다는 것을 수차례에 걸쳐 언급하고 있다. 도교에서 말하는 '해원'의 구체적인 내용은 주로 인간의 시비, 질병, 겁액에 관한 것이며, 그 해결 방법으로는 주로 마음속으로 『옥추보경』을 읽는 것이다. 이를 '구천상제'의 '해원상생' 가르침과 비교하면 그 사상의 폭이나 깊이, 중요성, 이론적 측면 등에서 비교적 간단한 형태로서 체계적인 면모로까지 나아가지는 못하였다. 셋째, '구천상제' 는 곤경에 처한 사람이 신명의 호칭을 부르면 그에 상응하는 신명이 달려와서 구원해준다는 '소리감응' 방법을 사용하고 있는데, 이 방법은 도교의 '보화천존' 역시 사용하고 있는 것이다. 넷째, '구천상제'는 과오를 범한 사람이 자신의 과오를 뉘우치면, 그 다음에 상제의 용서를 받음으로써 그 원한이 풀리게 된다는 참법(懺法 : 懺悔法)을 세인(世人) 교화에 자주 사용하였다. 물론 이것은 해원상생의 구체적인 적용이라 할 수 있다. 기능면에서 보면 이 방법은 『구천응원뇌성보화천존옥추보참(九天應元雷聲普化天尊玉樞寶懺)』의 참의(懺儀)와 공통되는 점이 있다. 참의는 수도자 스스로 자신의 잘못을 뉘우치고, 수도에 정진하며, 사회의 안정을 도모하고, 포덕에 힘쓰고, 악을 물리치고 선을 널리 펼친다는 것인데, 이런 의미에서 양자는 일치한다고 생각된다. 필자가 생각하건대, 대순진리회의 '구천응원뇌성보화천존강성상제'와 도교의 '구천응원뇌성보화천존' 사이에는 공통점이 아주 많지만 동시에 차이점 또한 적지 않다. 만약 더욱 다양한 자료들을 수집하여 더욱 깊고 광범위한 연구를 진행한다면 한국 대순진리회와 중국 도교, 특히 도교의 뇌법종파(雷法宗派)와의 상관관계를 해석하는 데 큰 도움이 될 것이라 생각한다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.398-403
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• 2023

Process-based K-cabbage model is based on physiological processes such as photosynthesis and phenology, making it possible to predict crop growth under different climate conditions that have never been experienced before. Current first-stage process-based models can be used to assess climate impact through yield prediction based on climate change scenarios, but no comparison has been performed between big data obtained from the main production area and model prediction so far. The aim of this study was to find out the direction of model improvement when using the current model for yield prediction. For this purpose, model performance evaluation was conducted based on data collected from farmers growing 'Chungwang' cabbage in Taebaek and Samcheok, the main producing areas of Chinese cabbage in highland region. The farms surveyed in this study had different cultivation methods in terms of planting date and soil water and nutrient management. The results showed that the potential biomass estimated using the K-cabbage model exceeded the observed values in all cases. Although predictions and observations at the time of harvest did not show a complete positive correlation due to limitations caused by the use of fresh weight in the model evaluation process (R²=0.74, RMSE=866.4), when fitting the model based on the values 2 weeks before harvest, the growth suitability index was different for each farm. These results are suggested to be due to differences in soil properties and management practices between farms. Therefore, to predict attainable yields taking into account differences in soil and management practices between farms, it is necessary to integrate dynamic soil nutrient and moisture modules into crop models, rather than using arbitrary growth suitability indices in current K-cabbage model.

• Journal of Nutrition and Health
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• v.56 no.6
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• pp.702-713
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• 2023

Purpose: Depression is a prevalent mental health concern globally including South Korea. Given the growing interest in the relationship between diet and mental health, this study aimed to investigate the association between seafood consumption and depression among Korean adults. Methods: A cross-sectional analysis was conducted using data from the Korea National Health and Nutrition Examination Survey (KNHANES, 2014-2020). The study included 18,149 participants (7,541 men and 10,608 women) aged 19 years and older who completed the Patient Health Questionnaire (PHQ-9). Seafood intake levels were assessed using a oneday 24-hour dietary recall, and participants were categorized into three tertiles by gender. Depression status was determined using the PHQ-9 scores and the self-report of the doctor's diagnosis and treatment. Multivariable logistic regression analysis was performed to assess the association between seafood consumption and depression in both genders. Results: Participants with a higher seafood intake had a significantly lower nutritional density of total fat, while the nutritional density of omega-3 polyunsaturated fatty acids was significantly higher. The prevalence of depression was significantly lower in the highest tertile of seafood consumption compared to the lowest tertile in both men (p < 0.001) and women (p < 0.001). After adjusting for confounding factors, the highest tertile of seafood consumption demonstrated a decreased risk of depression compared to the lowest tertile in men (odds ratio [OR], 0.71; 95% confidence interval [CI], 0.51-0.99; p-trend = 0.020) and women (OR, 0.73; 95% CI, 0.59-0.91; p-trend = 0.004). Conclusion: The findings of this study suggest that consuming seafood rich in omega-3 fatty acids may potentially reduce the risk of depression in the adult population.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.523-541
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• 2023

As accessibility to 3D printers increases, there is a growing frequency of exposure to chemicals associated with 3D printing. However, research on the toxicity and harmfulness of chemicals generated by 3D printing is insufficient, and the performance of toxicity prediction using in silico techniques is limited due to missing molecular structure data. In this study, quantitative structure-activity relationship (QSAR) model based on data-centric AI approach was developed to predict the toxicity of new 3D printing materials by imputing missing values in molecular descriptors. First, MissForest algorithm was utilized to impute missing values in molecular descriptors of hazardous 3D printing materials. Then, based on four different machine learning models (decision tree, random forest, XGBoost, SVM), a machine learning (ML)-based QSAR model was developed to predict the bioconcentration factor (Log BCF), octanol-air partition coefficient (Log Koa), and partition coefficient (Log P). Furthermore, the reliability of the data-centric QSAR model was validated through the Tree-SHAP (SHapley Additive exPlanations) method, which is one of explainable artificial intelligence (XAI) techniques. The proposed imputation method based on the MissForest enlarged approximately 2.5 times more molecular structure data compared to the existing data. Based on the imputed dataset of molecular descriptor, the developed data-centric QSAR model achieved approximately 73%, 76% and 92% of prediction performance for Log BCF, Log Koa, and Log P, respectively. Lastly, Tree-SHAP analysis demonstrated that the data-centric-based QSAR model achieved high prediction performance for toxicity information by identifying key molecular descriptors highly correlated with toxicity indices. Therefore, the proposed QSAR model based on the data-centric XAI approach can be extended to predict the toxicity of potential pollutants in emerging printing chemicals, chemical process, semiconductor or display process.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.14 no.4
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• pp.213-228
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• 2009

This study was conducted to investigate spatio-temporal changes in macrobenthic community structure and benthic environmental conditions in Geoje-Hansa Bay, which is the greatest oyster producing site in Korea. Field survey for benthic environment and macrobenthos was seasonally carried out at 15 stations covering oyster farming sites and non-farming sites from February to November, 2008. The grain size of surface sediments was dominated by very fine silt with the mean phi of about $9\;{\Phi}$ and TOC was 1.9% on average. Mean dissolved oxygen content was 8.1 mg/L and lowest in August corresponding to the 2nd degree in seawater quality criteria. Total species number was 351 and mean density was $3,675\;ind./m^2$, both of which were dominated by polychaete worms. Spatio-temporal variation in above two biological variables was great with higher values seasonally in spring and spatially in channels rather than inner bay. Dominant species were Lumbrineris longifolia (21.3%), Aphelochaeta monilaris (17.8%) and Ericthonius pugnax(6.1%), all of which are typical species of organically enriched area. From the multivariate analyses, the whole macrobenthic community was distinguished into two groups of channel and inner bay group. Spatio-temporal changes of macrobenthic community in Geoje-Hansan Bay were related to those of TOC and acid volatile sulfide (AVS). Our results showed that Geoje-Hansan Bay should be intermediately affected by organic pollution, and that such organic enrichment was more remarkable at farming stations in the inner bay.

• Journal of Environmental Impact Assessment
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• v.33 no.1
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• pp.1-8
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• 2024

Amphibians are a taxonomic group that ecologically connects terrestrial ecosystems and aquatic ecosystems. They play a very important role in the food chain of the ecosystem. It is known that there are about 5,948 species distributed all over the world, but after the Industrial Revolution, due to industrialization and urbanization, there has been a decrease in species and populations. In particular, it is becoming a factor in exacerbating habitat fragmentation or fragmentation due to artificial canals. In orderto improve the survivalrate of wild animals in artificial canals, escape facilities are installed to reduce it. This study analyzed the slope, height of the escape facility, escape rate, and travel distance in the operating facility for Bombina orientalis, which mainly inhabits near forests. The slope of the escape facility showed a relatively similar escape success rate regardless of height at 50° and 60°, while at 70°, it showed a relatively high escape success rate at only 40cm in height. The success rate of escape from the waterway escape facility in operation was 14.71%, showing a very low utilization rate, and the recognition rate of the artificial canal escape facility was found to be very low as it moved along the side wall of the artificial canal. Therefore, in the case of a waterway escape facility for Bombina orientalis, it is possible to construct it at an angle of 60°, and if the side walls of the artificial canals are built within 60°, Bombina orientalis can move freely in both directions, overcoming the low utilization rate of existing waterway escape facilities. It is expected to minimize the impact of movement and death of artificial canals. In addition, if the spacing between escape facilities is narrowed from the installation standard of 30m and ramps are constructed in both directions upstream and downstream, the escape success rate of amphibians,reptiles, and small mammals otherthan lady frogs is expected to improve.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.35-44
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• 2024

Research in dam inflow prediction has actively explored the utilization of data-driven machine learning and deep learning (ML&DL) tools across diverse domains. Enhancing not just the inherent model performance but also accounting for model characteristics and preprocessing data are crucial elements for precise dam inflow prediction. Particularly, existing rainfall data, derived from snowfall amounts through heating facilities, introduces distortions in the correlation between snow accumulation and rainfall, especially in dam basins influenced by snow accumulation, such as Soyang Dam. This study focuses on the preprocessing of rainfall data essential for the application of ML&DL models in predicting dam inflow in basins affected by snow accumulation. This is vital to address phenomena like reduced outflow during winter due to low snowfall and increased outflow during spring despite minimal or no rain, both of which are physical occurrences. Three machine learning models (SVM, RF, LGBM) and two deep learning models (LSTM, TCN) were built by combining rainfall and inflow series. With optimal hyperparameter tuning, the appropriate model was selected, resulting in a high level of predictive performance with NSE ranging from 0.842 to 0.894. Moreover, to generate rainfall correction data considering snow accumulation, a simulated snow accumulation algorithm was developed. Applying this correction to machine learning and deep learning models yielded NSE values ranging from 0.841 to 0.896, indicating a similarly high level of predictive performance compared to the pre-snow accumulation application. Notably, during the snow accumulation period, adjusting rainfall during the training phase was observed to lead to a more accurate simulation of observed inflow when predicted. This underscores the importance of thoughtful data preprocessing, taking into account physical factors such as snowfall and snowmelt, in constructing data models.