• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1167-1181
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• 2021

In relation to the algae bloom, four types of blue-green algae that emit toxic substances are designated and managed as harmful Cyanobacteria, and prediction information using a physical model is being also published. However, as algae are living organisms, it is difficult to predict according to physical dynamics, and not easy to consider the effects of numerous factors such as weather, hydraulic, hydrology, and water quality. Therefore, a lot of researches on algal bloom prediction using machine learning have been recently conducted. In this study, the characteristic importance of water quality factors affecting the occurrence of Cyanobacteria harmful algal blooms (CyanoHABs) were analyzed using the random forest (RF) model for Bohyeonsan Dam and Yeongcheon Dam located in Yeongcheon-si, Gyeongsangbuk-do and also predicted the occurrence of harmful blue-green algae using the machine learning and deep learning models and evaluated their accuracy. The water temperature and total nitrogen (T-N) were found to be high in common, and the occurrence prediction of CyanoHABs using artificial neural network (ANN) also predicted the actual values closely, confirming that it can be used for the reservoirs that require the prediction of harmful cyanobacteria for algal management in the future.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.107-114
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• 2022

In this paper, availabilities of student-evaluations of team activities in the computer science basic classes were analysed. For the purpose, correlation analysis was conducted to investigate the relationships among peer-evaluation, self-evaluation, and academic achievement, and it was found that there was a statistically significant positive correlation among them. Moreover, the gap between peer-evaluation scores and self-evaluation scores was analyzed. When a one-sample t-test was performed, it was found that the gap was very significant. However, the size of the gap was not different between the two classes. That is, regardless of grade level, the students' self-evaluation scores tended to be on average higher than the evaluation scores received from peers. Finally, when analyzing the relationship between the gap in peer-evaluation and self-evaluation scores and academic achievement, there was no significant correlation between the gap in scores and academic achievement. In other words, there was no difference in the tendency of evaluation for students with high or low academic achievement. The results of the analysis shows the availability of student-evaluations of team activities in the evaluation of team-based instruction. The high correlation between self-evaluation and peer-evaluation indicates the objectivity of student-evaluation. Although it is clear that the self-evaluation score is higher on average than the score received from peers, it is more useful in terms of objectivity because it does not vary according to grade, subject, or academic achievement.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.315-324
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• 2022

In this paper, we propose KoEPT, a Transformer-based generative model for automatic math word problems solving. A math word problem written in human language which describes everyday situations in a mathematical form. Math word problem solving requires an artificial intelligence model to understand the implied logic within the problem. Therefore, it is being studied variously across the world to improve the language understanding ability of artificial intelligence. In the case of the Korean language, studies so far have mainly attempted to solve problems by classifying them into templates, but there is a limitation in that these techniques are difficult to apply to datasets with high classification difficulty. To solve this problem, this paper used the KoEPT model which uses 'expression' tokens and pointer networks. To measure the performance of this model, the classification difficulty scores of IL, CC, and ALG514, which are existing Korean mathematical sentence problem datasets, were measured, and then the performance of KoEPT was evaluated using 5-fold cross-validation. For the Korean datasets used for evaluation, KoEPT obtained the state-of-the-art(SOTA) performance with 99.1% in CC, which is comparable to the existing SOTA performance, and 89.3% and 80.5% in IL and ALG514, respectively. In addition, as a result of evaluation, KoEPT showed a relatively improved performance for datasets with high classification difficulty. Through an ablation study, we uncovered that the use of the 'expression' tokens and pointer networks contributed to KoEPT's state of being less affected by classification difficulty while obtaining good performance.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.111-122
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• 2023

The purpose of this study is to verify the factors affecting survival time by estimating survival rate and survival time using non-financial information of social enterprises using credit guarantee in credit guarantee institutions, and provide information to stakeholders to improve survival rate and employ to contribute to maintaining and expanding the As a research method, survival analysis was performed using a non-parametric analysis method, Kaplan-Meier Analysis. As a sample, 621 companies (577 normal companies, 44 insolvent companies) established between 2009 and 2018 were selected as the target companies. As a result of examining the factors affecting survival time by classifying social enterprise representative information and corporate information, representative credit rating, representative home ownership, credit transaction period, and corporate credit rating were derived as significant variables affecting survival time. In the future, financial institutions will be able to induce corporate soundness by reflecting factors that affect survival when examining loans for social enterprises, contributing to job retention and reduction of social costs. Supporting organizations such as the government and private organizations will be able to use it in various ways, such as policy establishment and education and training for the growth and sustainability of social enterprises. With this study as an opportunity, I hope that research will continue with more interest in the factors influencing social enterprise performance as well as corporate insolvency.

• Journal of Service Research and Studies
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• v.10 no.4
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• pp.57-70
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• 2020

Globally, cloud service is a core infrastructure that improves industrial productivity and accelerates innovation through convergence and integration with various industries, and it is expected to continuously expand the market size and spread to all industries. In particular, due to the global pandemic caused by COVID-19, the introduction of cloud services was an opportunity to be recognized as a core infrastructure to cope with the untact era. However, it is still at the preliminary stage for market expansion of cloud service in Korea. This paper aims to empirically analyze how cloud services can be accepted by users by each industry through extended Technology Acceptance Model(TAM), and what factors influence the acceptance and avoidance of cloud services to users. For this purpose, the impact and factors on the acceptance intention of cloud services were analyzed through the hypothesis test through the proposed extended technology acceptance model. The industrial sector selected four industrial sectors of education, finance, manufacturing and health care and derived factors by examining the parameters of TAM, key characteristics of the cloud and other factors. As a result of the empirical analysis, differences were found in the factors that influence the intention to accept cloud services for each of the four industry sectors, which means that there is a difference in perception of the introduction or use of cloud services by industry sector. Eventually it is expected that this study will not only help to understand the intention of using cloud services by industry, but also help cloud service providers expand and provide cloud services to each industry.

• Journal of Aerospace System Engineering
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• v.17 no.4
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• pp.34-42
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• 2023

This study aims to analyze safety reports received through the recently added SMS safety self-report in the Air Force's "integrated air control management" system, identify hazards, present improvements by region (base), and lay the foundation for future data-based safety management. To identify risk factors, it was first classified by base based on data classified into 16 groups in the autonomous reporting system, and second classified in detail based on the type and description. Risk factors were analyzed for the most reported control cooperation (306) items, and improvements were derived by dividing risk factors into information sharing, regulations, procedures, education, training, and equipment items based on the analysis results. It was confirmed that risk factors and specific improvements vary by base (12), which is important data that can present statistical analysis and the direction of safety management in the flight control field by base (region). In addition, since there is no data-based risk factor analysis study for each specific base (region), it can be used in the future as basic research data for data-oriented safety management.

• Journal of Environmental Impact Assessment
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• v.32 no.4
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• pp.203-213
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• 2023

The AERMOD model was the most used, accounting for 89.0%, based on the analysis of the environmental impact assessment reports published in the Environmental Impact Assessment Information Support System (EIASS) between 2021 and 2022. The mismatch of versions between AERMET and AERMOD was found to be 25.3%. There was the operational time discrepancy of 50.6% from industrial complexes, urban development projects between used in the model and applied in estimating pollutant emissions. The results of applying various versions of the AERMET and AERMOD models to both area sources and point sources in both simple and complex terrain in the Gunsan area showed similar values after AERMOD version 12 (15181). Emissions are assessed as 24-hour operation, and the predicted concentration in both simple and complex terrain when using the variable emission coefficient option that applies an 8-hour daytime operation in the model is lowered by 37.42% ~ 74.27% for area sources and by 32.06% ~ 54.45% for point sources. Therefore, to prevent the error in using the variable emission coefficient, it is required to clearly present the emission calculation process and provide a detailed explanation of the composition of modeling input data in the environmental impact assessment reports. Also, thorough reviews by special institutions are essential.

• Journal of Practical Agriculture & Fisheries Research
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• v.12 no.1
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• pp.137-150
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• 2010

Traditionally, like many people in mountain region of the Himalaya, the Lwang communities depend on mix of subsistence agriculture, animal husbandry, and seasonal migrant labor for their livelihoods. These traditional systems are characterized by low productivity, diverse use of available natural resources (largely for home consumption), limited markets, and some aversion for innovation. The potential to generate wealth through commerce has largely been untapped by these mountain residents and thus is undervalued in local and national economies. Introduction of organic tea farming is a part of Lwang community's several initiatives to break the vicious poverty cycle Annapurna Conservation Area Project (ACAP) played facilitating roles in all their efforts since beginning. In five years, the tea plantation emerged as a new means for secured a livelihood. This study aims to analyze the current practices in tea farming both in terms of farm management and soil nutrient status(technical) and the prosperity of the tea farmers (social). The technical aspect covers the soil and tea leaf analysis of various nutrients contents in the soil and tea leaf. Originally, the technical aspect of the study was not planned but later during the consultation with the advisor it was taken into consideration which added value to the research study. The sample were collected from different locations and analyzed on the field itself. The other part of the study i.e. the social aspect was done through questionnaire survey and focus group discussion. the tea farming provided them not only a new opportunity but also earned an identity in the region. This initiative was undertaken as a piloting measure. Now that the tea is in production with processing unit established locally, more serious consideration has to be given for better yield and economic prosperity. This research finding will help the community to analyze their efforts and make correction measures in tea garden management and application of fertilizer. It is also expected to fill up the gaps of knowledge and information required to reduce economic stresses and enhance capacity of farmers to make the tea farming a sustainable and beneficial business. The findings are expected to Sustainability of organic tea farming has direct impacts on biodiversity conservation compared to the other traditional farming practices that are more resource intensive. The study will also contribute to identify key action points required for reducing poverty while conserving environment and enhancing livelihoods

• Journal of Practical Agriculture & Fisheries Research
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• v.10 no.1
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• pp.77-90
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• 2008

This study was conducted to investigate the influence of chilling temperature and duration at different seeding stages on yield, fruit characteristics and growth of cucumber in a greenhouse. When 20-day-old cucumber were exposed to 0 and 3℃ for 10 hours, 25 and 30% reduction in the main stem elongation rate and 34 and 37% reduction in total leaf area per plant were observed. The reduction in stem elongation and total leaf area was apparently associated with the increases in chilling duration. Exposure of seedlings to 6℃ failed to causes any significant differences in growth as compared to the unchilled plants. Repeated exposure of seedlings to 3℃ chilling for 10 hours per day increased the chilling injury significantly. The seedlings exposed to low temperature for 3 consecutive days exhibited severe injury as compared to the seedlings exposed to chilling treatment only once or twice. Fruit elongation rate was inhibited by approximately 10%, such as 0.59~2.26cm/day, with chilling of 15 hours at 0℃ as compare to 0.61~2.60cm/day in the non-chilled plants. Chilling treatment at 0~3℃ for 10 hours reduced the percentage of marketable fruits by 25~26%. while it increased the percentage of severely bent fruits significantly. Total fruits yield was reduced by 15~25% in cucumber plants when the chilling treatment was given to 20-day-old seedlings and by 22~37% in 30-day-old seedlings. This shows that, Larger seedlings were more sensitive to chilling. Total yield was also influenced by the duration of chilling. Definitely, at 0℃, 5-hour chilling treatment caused 18% of reduction, 10-hour caused 30%, and 15-hour caused 36%, respectively.

• Journal of Practical Agriculture & Fisheries Research
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• v.10 no.1
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• pp.67-75
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• 2008

Tartary buckwheat is one of specialized plants in Pyeongchang county, Korea and contains rutin much more than common buckwheat. Rutin is a kind of flavonoid (polyphenol compound) that has effects on blood vascular disease, strengthen capillary, and anti-inflammatory effect. This study was conducted to determine the possibility of development of beverage extracted from sugar-treated plants and sprouts of tartary buckwheat. By using two types of undiluted solution extracted from plant and sprouts of tartary buckwheat, we analyzed their nutrition components and did experiment on mice to find out pharmaceutical effects. In an experiment on mice, we administered various concentration of buckwheat to induced diabetic mellitus mice for 1 weeks. As a result, the buckwheat effected finely on lowering blood sugar and decreased LDL-cholesterol and total lipid level but increased HDL-cholesterol level.