• KOREAN JOURNAL OF CROP SCIENCE
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• v.61 no.2
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• pp.79-86
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• 2016

The late-maturing black rice cultivar Shinnongheugchal from Jeollabuk-do Agricultural Research and Extension Service was used as the plant material for estimating growth characters, quality and yield from the vegetation period to harvest age. This study was performed to select an optimum combination of nitrogen level and planting density for the maximum yield of Shinnongheugchal. The plant height, number of tillers, and SPAD index were higher when the combination of 70 hills per $3.3m^2$ and 13 kg/10 a nitrogen level was used at 30 days after transplanting. The heading date for the combination of 70 hills per $3.3m^2$ and 15 kg/10 a nitrogen level, and 80 hills per $3.3m^2$ and 15 kg/10 a nitrogen level was August 22. The heading date for the other combinations was August 21. The combination of 70 hills per $3.3m^2$ and 13 kg/10 a nitrogen level yielded the highest number of tillers at 40 days after flowering. Even though the lodging index was increased with increasing nitrogen levels, field lodging did not occur until harvest time. Seed nitrogen concentration in the combination of 70 hills per $3.3m^2$ and 13 kg/10 a nitrogen level showed a significant difference when compared with the other combinations. The black rice yield varied significantly, and the highest yield was observed in the combination of 70 hills per $3.3m^2$ and 13 kg/10 a nitrogen level. The yield was significantly correlated with seed nitrogen concentration. The maximum yield was estimated to be 14.67 kg/10 a nitrogen level by using the regression equation. On average, the coloring degree of the black rice was higher at planting density of 70 hills per $3.3m^2$ than at 80 hills per $3.3m^2$. The highest yield of perfect black rice was obtained using the combination of 70 hills per $3.3m^2$ and 13 kg/10 a nitrogen level. Our findings demonstrate that a nitrogen level of 13-14 kg/10 a can be used to obtain the maximum yield from Shinnongheugchal with yield, cyanidin 3-glucoside content, and perfect black rice yield as the standard.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.62 no.4
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• pp.275-284
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• 2017

Rice quality should be considered as a primary consumer requirement. Regarding marketing, characteristics such as appearance, physicochemical properties, and palatability of brand rice are of high economic importance. Therefore, this study was conducted to select the optimal rice cultivars representing the commercial rice brands of Gyeongsangbuk-do province in Korea. Various rice grain quality components, grain appearance, several physicochemical properties of rice grain, and texture or palatability of cooked rice grains of ten cultivars (namely 'top quality rice') cultivated at three different locations, such as inland mountainous and southern plain areas of Gyeongsangbuk-do province in 2013~2014, were evaluated, and the obtained data was analyzed. 'Hiami' showed slightly higher protein contents and lower palatability of cooked rice than the other rice cultivars. Rice production and head rice yield produced at Gumi were the highest. The protein content of milled rice produced at Andong, an inland mountainous region, was approximately 0.3% point lower than that from other locations, whereas the amylose content of milled rice was approximately 1% point higher than those from the other plain regions, Daegu and Gumi. We evaluated the texture, Glossiness value determined using a Toyo teste meter and palatability of cooked rice of ten cultivars. The hardness of cooked rice produced in Andong was slightly lower than that produced in Daegu and Gumi, and additionally, the palatability of cooked rice produced in Andong was the best, followed by that producted in Gumi and Daegu. Considering rice yield and grain quality in the major rice cultivation areas of Gyeongsangbuk-do province, the rice cultivars that may be suitable for each region could be recommended mid-late maturation: 'Younghojinmi' and 'Mipum' in Daegu, 'Daebo', 'Samgwang', Chilbo' and 'Younghojinmi' in Gumi, 'Samgwang', 'Jinsumi' and 'Sukwang' in Andong. These results obtained in this study imply that the selected cultivars with high yield and quality could be recommended with high priority to rice farmers in the regions.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.299-310
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• 2019

The eating quality of rice is one of the main concerns of rice breeding programs in many countries, especially in japonica rice cultivation areas. To select new resources with high eating quality from Korean native japonica rice, we evaluated a total of 76 varieties, including 47 native rice resources (26 landraces + 21 weedy rice) of Korea. In this study, all eating quality traits varied widely among the native resources, and some of the native resources revealed a high evaluation score in the palatability, expected eating quality, and physicochemical traits among the tested whole-plant materials. From the results, we selected two landraces (Sangdo and Waebyeo) and three weedy rice varieties (Hoengseongaengmi3, Namjejuaengmi6, and Wandoaengmi6) as promising resources for improvement of rice eating quality. Specifically, Wandoaengmi6 presented potential as a key breeding material for improving the eating quality of Korean rice cultivars, having the best evaluation results in palatability score (PS 0.83) from the sensory test and glossiness value (GV 81.8) from the Toyo taste meter of cooked rice. Given the urgent need to overcome the constraint of the narrow genetic background of Korean japonica rice, the results could be a practical solution for exploring new opportunities for improving rice eating quality through the expansion of genetic resources.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.414-421
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• 2019

Pod shattering during the maturing stage causes a serious yield loss in soybean. It is the main limiting factor of soybean cultivation and mechanization. It is important to develop varieties suitable for mechanical harvesting and to develop energy-efficient agricultural machinery to save labor and costs. 'Daewonkong,' developed by the National Institute of Crop Science (NICS) in 1997, is an elite cultivar that occupies more than 80% of the soybean cultivation area in Korea because of its strong tolerance to pod shattering. The objectives of this study were to investigate the variation in pod shattering degree in a RIL population developed from a 'Daewonkong' parent and to select promising lines with pod shattering tolerance. 'Daewonkong' demonstrated a high level of tolerance to pod shattering compared to the 'Tawonkong' and 'Saeolkong' varieties, with no shattered pods after 72 hours of drying. Screening of pod shattering showed a clear distinction between the tolerant and susceptible varieties. Also, the distribution of shattering pod ratio in the two populations showed a similar pattern for three years. The promising lines with pod shattering tolerance included 27 lines in the 'Daewonkong'×'Tawonkong' population and 21 lines in the 'Daewonkong'×'Saeolkong' population. The promising lines are expected to be widely used as breeding parents for creating soybean cultivars with pod shattering tolerance.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.10
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• pp.916-927
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• 2010

In general water treatment process, the disinfection process by chlorine is used to prevent water borne disease and microbial regrowth in water distribution system. Because chlorines were reacted with organic matter, carcinogens such as disinfection by-products (DBPs) were produced in drinking water. Therefore, a suitable injection of chlorine is need to decrease DBPs. Rechlorination in water pipelines or reservoirs are recently increased to secure the residual chlorine in the end of water pipelines. EPANET 2.0 developed by the U.S. Environmental Protection Agency (EPA) is used to compute the optimal chlorine injection in water treatment plant and to predict the dosage of rechlorination into water distribution system. The bulk decay constant ($k_{bulk}$) was drawn by bottle test and the wall decay constant ($k_{wall}$) was derived from using systermatic analysis method for water quality modeling in target region. In order to predict water quality based on hydraulic analysis model, residual chlorine concentration was forecasted in water distribution system. The formation of DBPs such as trihalomethanes (THMs) was verified with chlorine dosage in lab-scale test. The bulk decay constant ($k_{bulk}$) was rapidly decreased with increasing temperature in the early time. In the case of 25 degrees celsius, the bulk decay constant ($k_{bulk}$) decreased over half after 25 hours later. In this study, there were able to calculate about optimal rechlorine dosage and select on profitable sites in the network map.

• Analytical Science and Technology
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• v.11 no.1
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• pp.62-72
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• 1998

This study was performed to characterize the trace organic pollutants in the industrial wastewater and to establish the database of the trace organic pollutants. The four manufacturing industries, which are refined petroleum, industrial chemicals, rubber & plastics and fabricated metals, were surveyed. The wastewater and discharging water of these 30 factories are analyzed to characterize the trace organic pollutants. In industrial chemicals, the kinds of products and organic pollutants are very various. Therefore to select the characteristic organic pollutants in this categories are also very difficult. In industrial chemicals, the gas chromatograpic peak patterns of wastewater are represented the various type according to their products, therefore the typical patterns of the characteristic organic pollutants could not be obtained because the kinds of manufactured goods and organic pollutants are very various. In refined petroleum, the effluent is discharged in the distillatory process of atmosphere pressure and contained the saturated hydrocarbons, phenol compounds, benzene compounds and naphtalene compounds. The saturated hydrocarbons peaks from $C_{15}$ to $C_{35}$ are represented the typical oil patterns by the uniform intervals therefore the peak can be easily distinguished. In rubber & plastics, the wastewater is discharged in the washing process which contains the additives. The problem of wastewater is not serious because the manufacturing process is not produced the effluent or the produced cooling water is recycled in that process.

• The Korean Journal of Pesticide Science
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• v.4 no.3
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• pp.19-26
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• 2000

In order to select potent bioactive isolates, 70 Fusarium isolates obtained from soil and 21 plant species were screened by antifungal, insecticidal, herbicidal, and duckweed bioassays after culturing in potato dextrose broth and rice solid media. Eight (11.4%) of the 70 liquid broth cultures showed disease-controlling activities more than 80% against at least one of the 6 plant diseases tested. Fusarium sp. FO-68 isolate exhibited the most potent antifungal activity; it controlled rice blast, wheat leaf rust, and barley powdery mildew with control values more than 95%. Out of 70 solid cultures, 21 (30.0%) controlled at least one plant disease more than 80% and F. equiseti FO-68 isolate showed disease-controlling activities more than 95% against 3 plant diseases such as rice blast, tomato late blight, and wheat leaf rust. As for tile insecticidal activities, 2 liquid and 1 solid cultures showed potent insecticidal activities against pest insects more than 80%, Liquid cultures of F. oxysporum FO-61 and Fusarium sp. FO-80 isolates exhibited insecticidal activities more than 80% against green peach aphid and diamondback moth, respectively. The solid culture of Fusarium sp. FO-510 isolate had 80% insecticidal activity against green peach aphid. However, none of liquid and solid cultures of the 70 Fusarium isolates showed potent herbicidal activities against 10 upland weeds. As the results of duckweed assay, 3 liquid cultures showed 70% growth inhibitory activity at concentrations less than 1.25% of culture supernatants and 9 solid cultures had a potent inhibitory activity against duckweed growth. On the other hand, there was a significant correlation between antifungal activities and herbicidal activities against duckweed of both liquid and solid cultures of tile 70 Fusarium isolates.

• The Korean Journal of Pesticide Science
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• v.4 no.3
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• pp.40-46
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• 2000

To select the effective fungicides for the control of leaf spot disease of jujube tree (Zizyphus jujuba) caused by Phoma sp., inhibitory effects of 26 fungicides for mycelial growth were investigated at $250{\mu}g\;a.i./m{\ell}$. In the test, eight fungicides were selected and minimum inhibitory concentration (MIC) for mycelial growth and an inhibitory effect for spore germination were investigated. Among the fungicides, myclobutanil, hexaconazole, and triflumizole were excluded in control effect tests because of their relatively high MICs. MICs were ranged $10-50{\mu}g\;a.i./m{\ell}$ for benomyl, carbendazim + kasugamycin (CK), and thiophanate-methyl. triflumizole (TT), and $50-250{\mu}g\;a.i./m{\ell}$ for iprodione + propineb (IT) and iminoctadine-triacelate (IT). However, benomyl and IP showed very low inhibitory effect on conidial germination. When the fungicides were sprayed on the seedlings before the leaves were inoculated with conidial suspension of Phoma sp., the protective values of CK and TT were around 70% at 1,000 ppm and around 90% at 2,000 ppm. The protective values were around 70% at 2,000 ppm (benomyl), 4,000 ppm (IP), and 8,000 ppm (IT). When the fungicides were sprayed after inoculation, benomyl showed the highest curative values of over 90% at 1,000 ppm and the values of CK and TT ranged $70{\sim}80%$ at 1,000 ppm. However, IP and IT had little or no effect on therapy of the disease. IT caused necrotic phytotoxicity on the leaves of jujube seedlings. As results, the best fungicides for the protection of jujube trees from leaf spot disease were CK (2,000 ppm) and TT (2,000 ppm) and for the remedy of the tree, benomyl (1,000 ppm) was the best. Therefore, alternate application of benomyl and CK or TT will be effective in the disease control.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.65-82
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• 2015

Recently, there has been a surge of interest in finding core issues and analyzing emerging trends for the future. This represents efforts to devise national strategies and policies based on the selection of promising areas that can create economic and social added value. The existing studies, including those dedicated to the discovery of future promising fields, have mostly been dependent on qualitative research methods such as literature review and expert judgement. Deriving results from large amounts of information under this approach is both costly and time consuming. Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research. There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The change is to ensure objective and practical emerging trend analysis results based on large amounts of data. However, even such studies have had shortcoming related to their dependence on simple keywords for analysis, which makes it difficult to derive meaning from data. Besides, no study has been carried out so far to develop core issues and analyze emerging trends in special domains like the aviation industry. The change used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and emerging trends from overall research papers pertaining to aviation through text mining, which is one of the big data analysis techniques. In this manner, the promising future areas for the air transport industry are selected based on objective data from aviation-related research papers. In order to compensate for the difficulties in grasping the meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future. Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results. On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.