• Korean Journal of Psychosomatic Medicine
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• v.24 no.1
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• pp.66-73
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• 2016

Objectives : The purpose of this study was to investigate the characteristics of psychosocial factors related to functional dyspepsia(FD) and their effects on quality of life(QOL) in firefighters. Methods : This study examined data collected from 1,217 firefighters. We measured psychological symptoms by Patient Health Questionnaire-9(PHQ-9), Generalized Anxiety Disorder questionnaire(GAD-7), Korean Occupational Stress Scale(KOSS), Ways of Coping checklist(WCCL), Rosenberg's Self-Esteem Scale(RSES) and World Health Organization Quality of Life Scale abbreviated version(WHOQOL-BREF). Chi-square test, independent t-test, Pearson's correlation test, logistic regression analysis, and hierarchical regression analysis were used as statistical analysis methods. Results : For the group with FD, the male participants showed significantly higher frequency(p=0.006) compared to the female participants. The group with FD had higher scores for depressive symptoms(p<.001), anxiety (p<.001), and occupational stress(p<.001), and did lower scores for self-esteem(p=.008), quality of life(p<.001) than those without FD. The FD risk was higher in the following KOSS subcategories: job demand(OR 1.94, 95% CI : 1.29-2.93), lack of reward(OR 2.47, 95% CI : 1.61-3.81), and occupational climate(OR 1.51, 95% CI : 1.01-2.24). In the hierarchical regression analysis, QOL was best predicted by depressive symptoms, self-esteem, and occupational stress. Three predictive variables above accounts for 42.0% variance explained of total variance. Conclusions : The psychosocial factors showed significant effects on FD, and predictive variables for QOL were identified based on regression analysis. The results suggest that the psychiatric approach should be accompanied with medical approach in future FD assessment.

• Korean Journal of Breeding Science
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• v.43 no.4
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• pp.233-240
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• 2011

Food security has been a main global issue due to climate changes and growing world population expected to 9 billion by 2050. While biodiversity is becoming more highlight, breeders are confronting shortage of various genetic materials needed for new variety to tackle food shortage challenge. Though biotechnology is still under debate on potential risk to human and environment, it is considered as one of alternative tools to address food supply issue for its potential to create a number of variations in genetic resource. The new technology, phenomics, is developing to improve efficiency of crop improvement. Phenomics is concerned with the measurement of phenomes which are the physical, morphological, physiological and/or biochemical traits of organisms as they change in response to genetic mutation and environmental influences. It can be served to provide better understanding of phenotypes at whole plant. For last decades, high-throughput screening (HTS) systems have been developed to measure phenomes, rapidly and quantitatively. Imaging technology such as thermal and chlorophyll fluorescence imaging systems is an area of HTS which has been used in agriculture. In this article, we review the current statues of high-throughput screening system in phenomics and its application for crop improvement.

• Korean Journal of Environmental Agriculture
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• v.37 no.4
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• pp.268-276
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• 2018

BACKGROUND: In the month of January 2018, fine dust alerts and warnings were issued 36 times for $PM_{10}$ and 81 times for PM2.5. Air quality is becoming a serious issue nation-wide. Although interest in air-purifying plants is growing due to the controversy over the risk of chemical substances of regular air-purifying solutions, industrial spread of the plants has been limited due to their efficiency in air-conditioning perspective. METHODS AND RESULTS: This study aims to propose a vegetation-based bio-filter system that can assure total indoor air volume for the efficient application of air-purifying plants. In order to evaluate the quantitative performance of the system, time-series analysis was conducted on air-conditioning performance, indoor air quality, and comfort index improvement effects in a lecture room-style laboratory with 16 persons present in the room. The system provided 4.24 ACH ventilation rate and reduced indoor temperature by $1.6^{\circ}C$ and black bulb temperature by $1.0^{\circ}C$. Relative humidity increased by 24.4% and deteriorated comfort index. However, this seemed to be offset by turbulent flow created from the operation of air blowers. While $PM_{10}$ was reduced by 39.5% to $22.11{\mu}g/m^3$, $CO_2$ increased up to 1,329ppm. It is interpreted that released $CO_2$ could not be processed because light compensation point was not reached. As for the indoor comfort index, PMV was reduced by 83.6 % and PPD was reduced by 47.0% on average, indicating that indoor space in a comfort range could be created by operating vegetation-based bio-filters. CONCLUSION: The study confirmed that the vegetation-based bio-filter system is effective in lowering indoor temperature and $PM_{10}$ and has positive effects on creating comfortable indoor space in terms of PMV and PPD.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.2
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• pp.127-136
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• 2019

Sweet sorghum (Sorghum bicolor L. Moench), compared to traditional crops, has been evaluated as a useful crop with high adaptability to the environment and various uses, but cultivation has not expanded owing to a lack of related research and information in Korea. This study was conducted to estimate heading date in 'Chorong' sweet sorghum based on climate data of the last 30 years (1989 - 2018) from six regions (Jeonju, Buan, Jeongup, Imsil, Namwon, and Jangsu) in Jellabuk Province. In addition, we compared the growth and quality factors by sowing date (April 10, April 25, May 10, May 25, June 10, June 25, and July 10) in 2018. Days from sowing to heading (DSH) increased to 107, 96, 83, 70, 59, 64, and 65 days in order of the sowing dates, respectively, and the average was 77.7 days. The effective accumulated temperature for heading date was $1,120.3^{\circ}C$. The mean annual temperature was the highest in Jeonju, followed in descending order by Jeongup, Buan, Namwon, Imsil, and Jangsu. The DSH based on effective accumulated temperature gradually decreased in all sowing date treatments in the six regions during the last 30 years. DSH of the six regions showed a negative relationship with mean temperature (sowing date to heading date) and predicted DSH ($R^2=0.9987**$) calculated by mean temperature was explained with a probability of 89% of observed DSH in 2017 and 2018. At harvest, fresh stem weight and soluble solids content were higher in the April and July sowings, but sugar content was higher in the May 10 ($3.4Mg{\cdot}ha^{-1}$) and May 25 ($3.1Mg{\cdot}ha^{-1}$) sowings. Overall, the April and July sowings were of low quality and yield, and there is a risk of frost damage; thus, we found May sowings to be the most effective. Additionally, sowing dates must be considered in terms of proper harvest stage, harvesting target (juice or grain), cultivation altitude, and microclimate.

• Korean journal of applied entomology
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• v.57 no.4
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• pp.261-269
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• 2018

The cowpea aphid Aphis craccivora Koch (Hemiptera: Aphididae) is a polyphagous species with a worldwide distribution. We investigated the temperature effects on development periods of nymphs, and the longevity and fecundity of apterous female of A. craccivora. The study was conducted at six constant temperatures of 10.0, 15.0, 20.0, 25, 30.0, and $32.5^{\circ}C$. A. craccivora developed successfully from nymph to adult stage at all temperatures subjected. The developmental rate of A. craccivora increased as temperature increased. The lower developmental threshold (LT) and thermal constant (K) of A. craccivora nymph stage were estimated by linear regression as $5.3^{\circ}C$ and 128.4 degree-days (DD), respectively. Lower and higher threshold temperatures (TL, TH and TH-TL, respectively) were calculated by the Sharpe_Schoolfield_Ikemoto (SSI) model as $17.0^{\circ}C$, $34.6^{\circ}C$ and $17.5^{\circ}C$. Developmental completion of nymph stages was described using a three-parameter Weibull function. Life table parameters were estimated. The intrinsic rate of increase was highest at $25^{\circ}C$, while the net reproductive rate was highest at $20^{\circ}C$. Biological characteristics of A. craccivora populations from different geographic areas were discussed.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.287-316
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• 2023

As global energy crisis and the COVID-19 pandemic have emerged as social issues, there is a growing demand for companies to move away from profit-centric business models and embrace sustainable management that balances environmental, social, and governance (ESG) factors. ESG activities of companies vary across industries, and industry-specific weights are applied in ESG evaluations. Therefore, it is important to develop strategic management approaches that reflect the characteristics of each industry and the importance of each ESG factor. Additionally, with the stance of strengthened focus on ESG disclosures, specific guidelines are needed to identify and report on sustainable management activities of domestic companies. To understand corporate sustainability strategies, analyzing ESG reports and news articles by industry can help identify strategic characteristics in specific industries. However, each company has its own unique strategies and report structures, making it difficult to grasp detailed trends or action items. In our study, we analyzed ESG reports (2019-2021) and news articles (2019-2022) of six companies in the 'Finance,' 'Manufacturing,' and 'IT' sectors to examine the sustainability strategies of leading domestic ESG companies. Text mining techniques such as keyword frequency analysis and topic modeling were applied to identify industry-specific, ESG element-specific management strategies and issues. The analysis revealed that in the 'Finance' sector, customer-centric management strategies and efforts to promote an inclusive culture within and outside the company were prominent. Strategies addressing climate change, such as carbon neutrality and expanding green finance, were also emphasized. In the 'Manufacturing' sector, the focus was on creating sustainable communities through occupational health and safety issues, sustainable supply chain management, low-carbon technology development, and eco-friendly investments to achieve carbon neutrality. In the 'IT' sector, there was a tendency to focus on technological innovation and digital responsibility to enhance social value through technology. Furthermore, the key issues identified in the ESG factors were as follows: under the 'Environmental' element, issues such as greenhouse gas and carbon emission management, industry-specific eco-friendly activities, and green partnerships were identified. Under the 'Social' element, key issues included social contribution activities through stakeholder engagement, supporting the growth and coexistence of members and partner companies, and enhancing customer value through stable service provision. Under the 'Governance' element, key issues were identified as strengthening board independence through the appointment of outside directors, risk management and communication for sustainable growth, and establishing transparent governance structures. The exploration of the relationship between ESG disclosures in reports and ESG issues in news articles revealed that the sustainability strategies disclosed in reports were aligned with the issues related to ESG disclosed in news articles. However, there was a tendency to strengthen ESG activities for prevention and improvement after negative media coverage that could have a negative impact on corporate image. Additionally, environmental issues were mentioned more frequently in news articles compared to ESG reports, with environmental-related keywords being emphasized in the 'Finance' sector in the reports. Thus, ESG reports and news articles shared some similarities in content due to the sharing of information sources. However, the impact of media coverage influenced the emphasis on specific sustainability strategies, and the extent of mentioning environmental issues varied across documents. Based on our study, the following contributions were derived. From a practical perspective, companies need to consider their characteristics and establish sustainability strategies that align with their capabilities and situations. From an academic perspective, unlike previous studies on ESG strategies, we present a subdivided methodology through analysis considering the industry-specific characteristics of companies.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.261-272
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• 2023

In recent years, natural disasters such as heavy rainfall and typhoons have occurred more frequently, and their severity has increased due to climate change. The Korea Meteorological Administration (KMA) currently uses the same criteria for all regions in Korea for watch and warning based on the maximum cumulative rainfall with durations of 3-hour and 12-hour to reduce damage. However, KMA's criteria do not consider the regional characteristics of damages caused by heavy rainfall and typhoon events. In this regard, it is necessary to develop new criteria considering regional characteristics of damage and cumulative rainfalls in durations, establishing four stages: blue, yellow, orange, and red. A classification model, called DSCM (Disaster Severity Classification Model), for the four-stage disaster severity was developed using four machine learning models (Decision Tree, Support Vector Machine, Random Forest, and XGBoost). This study applied DSCM to local governments of Seoul, Incheon, and Gyeonggi Province province. To develop DSCM, we used data on rainfall, cumulative rainfall, maximum rainfalls for durations of 3-hour and 12-hour, and antecedent rainfall as independent variables, and a 4-class damage scale for heavy rain damage and typhoon damage for each local government as dependent variables. As a result, the Decision Tree model had the highest accuracy with an F1-Score of 0.56. We believe that this developed DSCM can help identify disaster risk at each stage and contribute to reducing damage through efficient disaster management for local governments based on specific events.

• Korean Journal of Heritage: History & Science
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• v.56 no.2
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• pp.264-279
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• 2023

The 50th anniversary of the UNESCO World Heritage Convention was in 2022. In order to reflect on the present and future of the meaning of World Heritage, this paper examines the development and changes of the UNESCO World Heritage system. After promulgating the convention in 1972, the UNESCO World Heritage system prioritized the protection of heritage sites in the world that were at risk due to armed conflicts and natural disasters to bequeath heritage to the next generation. In addition, the UNESCO World Heritage's emphasis on Outstanding Universal Value represents the particular culture of human beings formed during a certain period of time, and acts as a significant source of soft power in public diplomacy. The UNESCO World Heritage might be perceived as a shared heritage that has not only become a channel to understand various national values, but also an effective medium to convey one of UNESCO's main principles, that is, peacebuilding. However, the UNESCO World Heritage is now at the center of conflicts of heritage interpretation between many stakeholders related to invisible wars, such as cultural wars, memory wars, and history wars as the social, political, and cultural contexts concerning World Heritage have dramatically shifted with the passing of time. Paying attention to such changing contexts, this paper seeks to understand the main developments in UNESCO World Heritage's discourse concerning changes to the World Heritage Operation Guidelines and heritage experts' meetings by dividing its 50-year history into five phases. Next, this paper analyzes the main shifts in keywords related to UNESCO World Heritage through UNESDOC, which is a platform on which all UNESCO publications are available. Finally, this paper discusses three main changes of UNESCO World Heritage: 1) changes in focus in World Heritage inscriptions, 2) changes in perception of World Heritage protection, and 3) changes of view on the role of the stakeholders in World Heritage. It suggests new emerging issues regarding heritage interpretation and ethics, climate change, and human rights.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.981-992
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• 2023

Due to recent global climate change, the scale of flood damage is increasing as rainfall is concentrated and its intensity increases. Rain on a scale that has not been observed in the past may fall, and long-term rainy seasons that have not been recorded may occur. These damages are also concentrated in ASEAN countries, and many people in ASEAN countries are affected, along with frequent occurrences of flooding due to typhoons and torrential rains. In particular, the Bandung region which is located in the Upper Chitarum River basin in Indonesia has topographical characteristics in the form of a basin, making it very vulnerable to flooding. Accordingly, through the Official Development Assistance (ODA), a flood forecasting and warning system was established for the Upper Citarium River basin in 2017 and is currently in operation. Nevertheless, the Upper Citarium River basin is still exposed to the risk of human and property damage in the event of a flood, so efforts to reduce damage through fast and accurate flood forecasting are continuously needed. Therefore, in this study an artificial intelligence-based river flood water level forecasting model for Dayeu Kolot as a target station was developed by using 10-minute hydrological data from 4 rainfall stations and 1 water level station. Using 10-minute hydrological observation data from 6 stations from January 2017 to January 2021, learning, verification, and testing were performed for lead time such as 0.5, 1, 2, 3, 4, 5 and 6 hour and LSTM was applied as an artificial intelligence algorithm. As a result of the study, good results were shown in model fit and error for all lead times, and as a result of reviewing the prediction accuracy according to the learning dataset conditions, it is expected to be used to build an efficient artificial intelligence-based model as it secures prediction accuracy similar to that of using all observation stations even when there are few reference stations.