• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• (The)Study of the Eastern Classic
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• no.69
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• pp.83-114
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• 2017

The purpose of this article is to analyze the standings of working-level officials belonging to Jongbusi (Court of the Royal Clan) holding the rank of "jeong" and below between the 18th and mid-19th Century. Jongbusi, which was headed by a Grade-3 official, was in charge of the compilation of royal genealogy and supervision of royal relatives. During the late Joseon Period, its officials were composed of its chief, jeong, jubu (Grade-6 official), and jikjang (Grade-7 official). By 1864, it was incorporated into Jongchinbu (Office of the Royal Relatives). Jongbusi nangcheong seonsaengan (Register of Staff Officials at the Court of the Royal Clan), which is preserved at the Jangseogak Archives of the Academy of Korean Studies, lists the officials who served at the office between 1794 and its incorporation into Jongchinbu in 1864. The register also includes the officials' ranks, names, DOBs, family clans, their ranks in the offices they were transferred from, their ranks in the office they were transferred to, etc. Those interested view it as a precious relic that provides valuable information on the officialdom of the dynasty. A majority of the officials who served at Jongbusi were those who passed the higher civil service examination. Many of them at the level of jikjang were those who passed the licentiate examination. Their designation as an official was part of the "muneum" system, which granted official posts to descendants of those who accomplished a distinguished service for the country or served as a high-ranking official. They were those transferred from equal or lower positions in another office. Many of jubu-level officials of Jongbusi were those transferred from honorable and important posts of other offices or local administrative offices. Many of jikjang-level officials of Jongbusi were those who previously served as dosa (assistant officials) at Uigeumbu (Bureau of Crime Investigation) headed by a Grade-1 official. The officials' transfer to an office with a lower position like Jongbusi appears to have been for the provision of placing them in working-level positions rather than letting them remain in positions only carrying an honorary title. As for the transfer of officials of Jongbusi to other offices, many of those with the rank of jeong were transferred to lower positions. Supposedly it was because not many Grade-3 positions were vacant. Many of them were transferred to honorable and important posts. Some of them were also transferred to positions at local government offices, supposedly to avoid an excess of personnel at the central government. Those at the level of jubu or jikjang of Jongbusi were transferred to equal or higher posts in other offices. Particularly, most of those holding the position of jikjang (Grade-7) were transferred to higher posts. The family clan that produced the largest number (10%) of Jongbusi officials was the Jeonju Yi Clan, which produced the largest number of those who passed the higher civil service examination. It was also found that the top 20 family clans produced about half of the entirety of Jongbusi officials. According to the aforesaid Jongbusi nangcheong seonsaengan, about 90% of the cases of promotion of Jongbusi officials occurred after the revision of Seonwon boryak (Royal Genealogy of the Joseon Dynasty). It is speculated that the supervision of royal family members, one of the two leading functions assigned to Jongbusi, was suspended in the late Joseon Period. The relevant function does not appear even in chronicles pertaining to the Joseon Dynasty. The reason being had something to do with the sharp decrease in the number of royal family members during the reign of King Injo (r. 1623-1649). Their number was decreased to the extent that royal ceremonies could not be adequately carried out. Naturally, the meaning of supervising royal family members faded. Witnessing such a sorry state of the royal family, Heungseon Daewongun, King Gojong's father who served as the regent, incorporated Jongbusi into Jongchinbu in an effort to enhance the status and authority of the royal family.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.

• Atmosphere
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• v.33 no.2
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• pp.275-295
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• 2023

In Korea, there are four institutions related to atmospheric science: the university's atmospheric science-related department, the Korea Meteorological Administration (KMA), the ROK Air Force Weather Group, and the Meteorological Industry Association. These four institutions have developed while maintaining a deep cooperative relationship with the Korea Meteorological Society (KMS) for the past 60 years. At the university, 6,986 bachelors, 1,595 masters, and 505 doctors, who are experts in meteorology and climate, have been accredited by 2022 at 7 universities related to atmospheric science. The KMA is carrying out national meteorological tasks to protect people's lives and property and foster the meteorological industry. The ROK Air Force Weather Group is in charge of military meteorological work, and is building an artificial intelligence and space weather support system through cooperation with universities, the KMA, and the KMS. Although the Meteorological Industry Association has a short history, its members, sales, and the number of employees are steadily increasing. The KMS greatly contributed to raising the national meteorological service to the level of advanced countries by supporting the development of universities, the KMA, the Air Force Meteorological Agency, and the Meteorological Industry Association.

• Journal of the Korean Society of Food Culture
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• v.22 no.6
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• pp.721-741
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• 2007

1. For the types of boiled rice, there were 1 type of bap, 1 type of jebap cooked with glutinous rice, 13 types of boiled rice cooked by mixing grains and nuts such as daemakban, somakban, jobap, cheongryangmiban, jobap, gijangbap, yulmubap, hyeonmibap, boribap and patmulbap as well as patbap, congbap, byeolbap and bambap etc as ogokbap. Also, there were 12 types of bap cooked by mixing herb medicinal ingredients such as cheongjeong, oban, boksungabap, gumeunsaekbap, hwanggukgamchobap, yeongeunbap, okjeongbap, gogumabap, dububap, samssibap, dorajibap, gamjabap, songibap and jukshilbap. There were 7 types bap cooked as unique one bowl dish at the present as bapby mixing fish, meat, shellfish and milk as ingredients are hwangtang, gyejanggukbap, janggukbap, gulbap, kimchibap, chusaban and bibimbap, etc and the types of bap that have been analyzed are 34 total. 2. For the food ingredients used in bap types 23 types of miscellaneous grains, 5 types of nuts and 11 types of meat, 6 types of fish, 35 types of vegetables, 2 types of fruit including pears or peaches were used. Garlic wasn't used perhaps because of it being boiled rice 3. Types of Sap by Cooking Methods. (1) The ssalbap was cooked by first boiling water, putting in rice grains and boiling hard to be cooked as overcooked bap (rice). (2) The japgokbap (boiled cereals) has used buckwheat, barley job's tear, etc to be boiled down by soaking the ones with large grains (beans) first in advance to be boiled down or cooked by crushing into fine pieces. The red bean, etc was boiled down in advance or placed at the bottom of pot by cutting into two pieces while jujube or nut was cut into three pieces to cook the bap by pouring a lot of water and mixing other ingredients. (3) The gukbap (soup boiled rice), etc were cooked by squeezing out the yellow chrysanthemum that has dried chrysanthemum to cook the boiled rice by putting in rice and gukbap, meat or bones, etc were boiled down for a long time and decorated with meat or wild greens by mixing the bap in the meat juice. For gulbap (oyster boiled rice), etc, it was cooked as ingredients were stir fried in advance or washed and put in when the bap was about half cooked. (4) For bibimbap (mixed boiled rice), after the bap was overcooked first with rice, the wild greens were mixed lightly with bap beforehand, then the wild greens, decorations and garnishings were laid above rice and red pepper powder was sprinkled. (5) Namchok leaves, etc were boiled to cook the boiled rice with rice after being cooled while namchok stem and leaves were pounded to make juice and cooked the bap with rice. The peach, lotus root and yams were cut into fine pieces to be put in together when rice was about half done. The bellflower was soaked in water to be boiled down for a long time while potatoes and pine mushrooms, etc were cut into fine pieces to cook the bap (boiled rice) with rice.

• Korean Journal of Agricultural Science
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• v.9 no.2
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• pp.546-555
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• 1982

To evaluate the digestibility and absorbability of proteins, and the rates of energy and nitrogen(N) metabolism of the Korean native goats, studies were carried out with open type respiration apparatus based on the nitrogen-carbon method. The results on the nitrogen retention and the metabolic rate of energy, which was obtained with one male (10-month-old) and one female (24-month-old) goats, both weighing ${\simeq}20kg$, are summarized as follows. 1. When the goats were fed ad libitum the medium quality orchard grass hay, they consumed hay about 0.66 to 0.92% of body weight per day. The hay intake was remained the same even when high quality hay was provided. This amount of hay intake was relatively lower than that of dairy goat and sheep. It was believed to be partly due to the change in feeding enviroment. When fed with hay and soybean meal together, the goats ate hay about 1.06% and soybean meal about 0.60% of body weight, corresponding to 1.66% of body weight as fed basis. 2. The $CO_2$ gas produced from the goat in the open type respiration chamber and absorbed with KOH solution was estimated to be 99~117g/day. The difference in feed intake did not influence the $CO_2$ production; however, these seems to be a linea relationship between body weight and $CO_2$ production. 3. When fed orchard grass hay only, the goats showed protein digestibility of 24~41%. The protein digestibility incresed to 58.2% when fed hay and soybean meal together. A negative nitrogen balance(-0.16g N/day) was observed with goats fed 11.53g N originated from 212g hay and 150g soybean meal. Converting that nitrogen ingested to a crude protein, the amount of crude protein intake by the goats per day was 77.9g compared to 40~45g N known to be required in a day by goat weighing 20kg, indicating that the extra protein ingested was metabolized to provide energy. 4. When the male and female goats comsumed 624 kcal gross energy and 824 kcal gross energy by consuming 158g and 213g of hay, respectively, the digestible energy intake was calculated to be 260kcal for the male and 199kcal for the female goat. The daily heat production of male and female goats were 338kcal and 334kcal, respectively, when fed hay only. However, the female goat fed 212g hay and 150g soybean meal produced about 591kcal per day. Consequently, the energy requirment of the Korean native goats weighing ${\simeq}20kg$ was concluded to be $${\geq_-}$$600kcal net energy per day. 5. The fasting heat product ion of a male goat weighing 27.7kg was 412kcal per day when fasted for 2~3 days. When fasted for 3~4 days, the value decresed to 240kcal. The enviromental temperatures during the expreimental period were ranged from 19 to $34.5^{\circ}C$. The goats seemed to be panting when the chamber temperature rose to $32^{\circ}C$ or above. 6. When fed low levels of dietary protein, serum protein levels of the goats were decresed slightly ($${\leq_-}$$10%); however, urea content in the serum was observed to decrese to a great extent (3X).

• KOREAN JOURNAL OF CROP SCIENCE
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• v.4 no.1
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• pp.115-124
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• 1968

It was shown that the most desirable characters for kenaf are high-fiber weight and moderately early maturity. Therefore, the objectives of this research on this crop is to find varieties possessing these characteristics. The experiments covered in this report provided new information relative to segregation, mode of inheritance, estimate of the number of genes involved in fiber weight and their response to short day length of 10 hours and the qualitative characters, such as, color of stem, capsule, petiole and shape of leaves. The associations which exist among these characters are also indicated. Fiber weight per plant, days to flowering, Stem color, Petiole color, Capsule color, and shape of leaves were studied in parental, $F_1$.$F_2$and backcross populations of a cross between Dashkent, a low-fiber weight but early maturing kenaf variety, and G 38 F-1, a high-fiber weight but late maturing kenaf variety. Crosses were made using the varieties, Dashkent and G 38 F-1 as parents. The Dashkent parent had the following characteristics: green stems, capsules and petioles and lobed shaped leaves; 105.8234 mean-days to flowering in the field, and 106.9222 mean-days under 10 hours short day treatment. The other parent, G 38 F-1 had red stems yellow capsules and red petioles and unlobed shaped leaves; 149.8921 mean-days to flowering in the field, and 62.3684 mean-days under 10 hours short day treatment. Both of the parents, $F_1$, $F_2$, $BC_1$ ($F_1$ X Dashkent, ) and $BC_2$($F_1$ ${\times}$ G38F-1) of the kenaf cross were grown at the Crops Experiment Station, Suwon, Korea in 1965. Color of stems, petioles and capsules, and shape of leaves were noted to be simply inherited as a single factor. Red stem color was dominant over green stem color, red petiole color was dominant over green petiole, lobed shaped leaves were dominant over unlobed shaped leaves and yellow capsules were dominant over green capsule. It was, also, noted that the factor for color of petiole was linked with the factor for shape of leaf with a 11.9587 percent recombination value, however no interaction or linkage were found among the color of stem and capsule color. Using Powers partitioning method, theoretical means and frequency distributions for each population, the days to flowering were calculated with the assumption that two gene pairs were involved. The values obtained fitted the theoretical values. In general this would indicate that Dashkent and G 38 F -1 were differentiated by two gene pairs. Heritability values were calculated as the percent of additive genetic variance. Heritability value of days to flowering, 89.5% in the broad sense and 79.91% in the narrow sense, indicated that the selection for this character would be effective in relatively early generations. Particularly, high positive correlations were found between days to flowering and the color of petioles and shape of leaves. However, there was no relation between days to flowering and capsule color nor between these and stem color. On the basis of the results of this experiment there is evidence that the hereditary factor for shape of leaves and the color of petioles is linked with an effective factor or factors for the characters of days to flowering. The association was sufficiently close to offer a possible simple and efficient means of selection for moderately early mat. uring plants by leaf shape and petiole color selection. Again using Powers partitioning method the frequency distribution for each population to the fiber weight were calculated with the assumption that two gene pairs, AaBb, were involved. Both phenotypic and genotypic dominance were complete. The obtained value did not agree with the theoretical value for $F_2$ and $BC_1$ ($F_1$ ${\times}$ Dashkent.) It seems that Dashkent and G 38 F-1 were differentiated by two major gene pairs but some the other minor genes are necessary. It is certain that the hereditary factor for shape of leaves and color of petioles is linked with an effective factor or factors for fiber weight. Also, high. yielding plants with moderately early maturity were found in the $F_2$ population. Thus, simultaneous selection for high-fiber yield and moderately early maturing plants should be possible in these populations. Phenotypic and genotypic correlation coefficients between fiber weight per plant and days to flowering, stem height and stem diameter were calculated. In general, genotypic correlations are higher than the phenotypic correlation. The highest correlation is found between stem height and fiber weight per plant (0.7852 in genotypic and 0.4103 in phenotypic) and between days to flowering and fiber weight per plant (0.7398 in genotypic and 0.3983 in phenotypic.) It was also expected that the selection of high stem height and moderately early maturing plants were given the efficient means of selection for high fiber weight.

• Korean Journal of Environmental Biology
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• v.39 no.1
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• pp.119-135
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• 2021

Korea has stepped up efforts to investigate and catalog its flora and fauna to conserve the biodiversity of the Korean Peninsula and secure biological resources since the ratification of the Convention on Biological Diversity (CBD) in 1992 and the Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits (ABS) in 2010. Thus, after its establishment in 2007, the National Institute of Biological Resources (NIBR) of the Ministry of Environment of Korea initiated a project called the Korean Indigenous Species Investigation Project to investigate indigenous species on the Korean Peninsula. For 15 years since its beginning in 2006, this project has been carried out in five phases, Phase 1 from 2006-2008, Phase 2 from 2009-2011, Phase 3 from 2012-2014, Phase 4 from 2015-2017, and Phase 5 from 2018-2020. Before this project, in 2006, the number of indigenous species surveyed was 29,916. The figure was cumulatively aggregated at the end of each phase as 33,253 species for Phase 1 (2008), 38,011 species for Phase 2 (2011), 42,756 species for Phase 3 (2014), 49,027 species for Phase 4 (2017), and 54,428 species for Phase 5(2020). The number of indigenous species surveyed grew rapidly, showing an approximately 1.8-fold increase as the project progressed. These statistics showed an annual average of 2,320 newly recorded species during the project period. Among the recorded species, a total of 5,242 new species were reported in scientific publications, a great scientific achievement. During this project period, newly recorded species on the Korean Peninsula were identified using the recent taxonomic classifications as follows: 4,440 insect species (including 988 new species), 4,333 invertebrate species except for insects (including 1,492 new species), 98 vertebrate species (fish) (including nine new species), 309 plant species (including 176 vascular plant species, 133 bryophyte species, and 39 new species), 1,916 algae species (including 178 new species), 1,716 fungi and lichen species(including 309 new species), and 4,812 prokaryotic species (including 2,226 new species). The number of collected biological specimens in each phase was aggregated as follows: 247,226 for Phase 1 (2008), 207,827 for Phase 2 (2011), 287,133 for Phase 3 (2014), 244,920 for Phase 4(2017), and 144,333 for Phase 5(2020). A total of 1,131,439 specimens were obtained with an annual average of 75,429. More specifically, 281,054 insect specimens, 194,667 invertebrate specimens (except for insects), 40,100 fish specimens, 378,251 plant specimens, 140,490 algae specimens, 61,695 fungi specimens, and 35,182 prokaryotic specimens were collected. The cumulative number of researchers, which were nearly all professional taxonomists and graduate students majoring in taxonomy across the country, involved in this project was around 5,000, with an annual average of 395. The number of researchers/assistant researchers or mainly graduate students participating in Phase 1 was 597/268; 522/191 in Phase 2; 939/292 in Phase 3; 575/852 in Phase 4; and 601/1,097 in Phase 5. During this project period, 3,488 papers were published in major scientific journals. Of these, 2,320 papers were published in domestic journals and 1,168 papers were published in Science Citation Index(SCI) journals. During the project period, a total of 83.3 billion won (annual average of 5.5 billion won) or approximately US $75 million (annual average of US $5 million) was invested in investigating indigenous species and collecting specimens. This project was a large-scale research study led by the Korean government. It is considered to be a successful example of Korea's compressed development as it attracted almost all of the taxonomists in Korea and made remarkable achievements with a massive budget in a short time. The results from this project led to the National List of Species of Korea, where all species were organized by taxonomic classification. Information regarding the National List of Species of Korea is available to experts, students, and the general public (https://species.nibr.go.kr/index.do). The information, including descriptions, DNA sequences, habitats, distributions, ecological aspects, images, and multimedia, has been digitized, making contributions to scientific advancement in research fields such as phylogenetics and evolution. The species information also serves as a basis for projects aimed at species distribution and biological monitoring such as climate-sensitive biological indicator species. Moreover, the species information helps bio-industries search for useful biological resources. The most meaningful achievement of this project can be in providing support for nurturing young taxonomists like graduate students. This project has continued for the past 15 years and is still ongoing. Efforts to address issues, including species misidentification and invalid synonyms, still have to be made to enhance taxonomic research. Research needs to be conducted to investigate another 50,000 species out of the estimated 100,000 indigenous species on the Korean Peninsula.

• Journal of Korean Society of Forest Science
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• v.29 no.1
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• pp.54-101
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• 1976

This study was conducted on the major factors affecting soil erosion and surface run-off. In order to investigate the processes and mechanisms of soil erosion on denuded forest-land in Korea, and to systematize the magnitudes of influences and interactions between individual factors, the five major factors adopted in these experiments are soil textures (coarse sand and clay loam), slope steepness ($10^{\circ}$, $20^{\circ}$, $30^{\circ}$ and $40^{\circ}$), rainfall intensities (50, 75 and 100mm/hr), slope mulching methods (bare, coarse straw-mat mulching, grass mulching and anti-erosion liquid mulching) and vegetation densities (sparse, moderate and dense). The processes and mechanisms of soil erosion, and the effects of mulchings on soil erosion as well as surface run-off rates were studied algebraically with four parts of laboratory experiments under the simulated rainfall and another part of field experiment under the natural rainfall. The results in this study are summarized as follows: 1. Experiment factors and surface run-off rates The surface run-off rates under the natural rainfall were resulted about 24.7~28.7% from the bare slopes, about 14.0~16.4% from the straw-mat mulched slopes, about 7.9~9.1% from the liquid mulched slopes, and about 5.6~7.2% from the grass mulched slopes respectively. The surface run-off rates under the simulated rainfall differed greatly according to the rainfall intensity and the mulching method. 2. Magnitudes of influences and interactions of the individual factor on the surface run-off rates. The experimental analyses on the major factors(soils, slopes, rainfalls, mulchings and vegetations) affecting the rates of surface run-off, show that the mean differences of surface run-off rate are significant at 5% level between the soil texture factors, among the slope steepness factors, among the rainfall intensity factors, among the mulching method factors, and among the vegetation density factors respectively. The interactions among the individual factor have a great influence(significant at 1% level) upon the rate of surface run-off, except for the interactions of the factors between soils and slopes; between slopes and vegetations; among soils, slopes and rainfalls; and among soils, slopes and mulchings respectively. On the bare slopes under the simulated rainfall, the magnitude of influences of three factors(soils, slopes and rainfalls) affecting the rate of surface run-off is in the order of the factor of rainfalls, soils and slopes. The magnitude of influences of three factors (soils, rainfalls and mulchings) affecting the rate of surface run-off, on the mulched slopes under the simulated rainfall is in the order of the factor of mulchings, rainfalls and soils and that of influences of the factor of soils, slopes and mulchings is in the order of the factor of mulchings, soils and slopes. On the vegetation growing slopes under the simulated rainfall, the magnitude of influences of three factors (soils, slopes and vegetations) affecting the rate of surface run-off is in the order of the factor of vegetations, soils and slopes. In the same condition of treatments on the field experiment under the natural rainfall, the order of magnitude of influences affecting the rate of surface run-off is the factor of mulchings, soils and slopes. 3. Experiment factors and soil losses The soil losses of the experiment plots differed according to the factors of soil texture, slope steepness, rainfall intensity and mulching method. The soil losses from the coarse soil were increased about 1.1~1.3 times as compared with that of fine soil under the natural rainfall, while the soil losses from the fine soil were increased about 1.2~1.3 times compared with that of coarse soil under the simulated rainfall. The equation of $E=aS^b$ (a, b are constant) between the slope steepness (log S) and soil losses (log E) under the simulated rainfall were developed. The equation of $E=aI^b$ (a, b are constant) between the rainfall intensity (log I) and soil losses (log E) were developed, and b values have a decreasing tendency according to the increase of the slope steepness and rainfall intensity. The soil losses under the natural rainfall were appeared about 38~41% from the coarse straw-mat mulched slopes, about 20~22% from the liquid mulched slopes, about 14~15% from the grass mulched slopes as compared with that of the bare slopes respectively. The soil loss from the vegetation plots showed about 7.1~16.4 times from the sparse plot, about 10.0~17.9 times from the moderate plot and about 11.1~28.1 times from the dense plot as compared with that of the bare slopes. 4. Magnitudes of influences and interactions of the individual factor on the soil erosion. The experimental analyses on the major factors(soils, slopes, rainfalls, mulchings and vegetations) affecting the soil erosion, show that the mean differences of soil losses are highly significant between the soil texture factors, among the slope steepness factors, among the rainfall intensity factors, among the mulching method factors and among the vegetation density factors respectively. The interactions among the individual factor have mostly great influences upon the soil erosion. The magnitude of influences of three factors (soils, slopes and rainfalls) affecting the soil erosion on the bare slopes under the simulated rainfall is in order of the factor of rainfalls, soils and slopes. On the mulched slopes under the simulated rainfall, the magnitude order of influences of three factors(soils, rainfalls and mulchings) affecting the soil erosion is the factor of mulchings, rainfalls and soils, and the order of influences of factor of soils, slopes and mulchings is the factor of mulchings, soils and slopes. On the vegetation growing slopes under the simulated rainfall, the magnitude of influences of three factors (soils, slopes and vegetations) affecting the soil erosion is in the order of the factor of slopes. vegetations and soils. In the same condition of treatments on the field experiment under the natural rainfall, the order of magnitude of influences of three factors (soils, slopes and mulchings) affecting the soil erosion is the factor of mulchings, of slopes and of soils.

• The Korean Journal of Pesticide Science
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• v.15 no.4
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• pp.545-572
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• 2011

The genetic diagnosis methods by RT-PCR and Virion capture (VC)/RT-PCR against Rice stripe virus (RSV) were developed. Three diagnosis methods of seedling test, ELISA and RT-PCR were compared in virus detection sensitivity (VDS) for RSV. The VDS of ELISA for RSV viruliferous small brown plant hopper (SBPH) was higher with 40.5% than that of seedling test. The VDS of RT-PCR was higher with 21% than that of ELISA. The VDS of ELISA and VC/RT-PCR was same with 9.2% in average on the SBPH collected from fields at the areas of Gimpo, Pyungtaeg and Sihueng, Gyeonggi province in 2009. The specific primers of RSV for SBPH and rice plant were developed for the diagnosis by Real time PCR. The RQ value of Real time PCR for the viruliferous and non viruliferous SBPH was 1 for 50 heads of non viruliferous SBPH, 96.5 for 50 heads of viruliferous SBPH, 23.1 for 10 heads of viruliferous SBPH + 40 heads of non viruliferous SBPH, and 75.6 for 30 heads of viruliferous SBPH + 20 heads of non viruliferous SBPH. The RQ value was increased positively by the ratio of viruliferous SBPH. Full sequences of 4 genomes of RSV RNA1, RNA2, RNA3 and RNA4 were analysed for the 13 RSV isolates from rice plants collected from different areas. Genetic relationships among the RSV isolates of Korea, Japan and China were classified as China + Korea, and China + Korea + Japan by phylogenetic analysis for RSV RNA1 and RNA2. In case of RNA3 involved in pathogenicity, genetic relationship of RSV among the three countries was grouped into 3 as China, China + Korea, and Korea + Japan. According to the genetic relationships in RSV RNA4, RSV isolates were grouped into 4 as China, Korea, China + Korea + Japan, and Korea + Japan. Viruliferous insect rate (VIR) of RSV in average increased in each year from 2008 to 2010, and the rates were 4.3%, 6.1%, and 7.2%, respectively, at the 28 major rice production areas in 7 provinces including Gyeonggido. The highest VIR in each year was 11.3% of Gyeonggido in 2008, 20.1% of Jellanamdo in 2009 and 14.2% of Chungcheongbukdo in 2010. The highest VIR depending upon the investigated areas was 22.1% at Buan of Jellabukdo in 2008, 36% at Wando and Jindo of Jellanamdo in 2009, and 30.0% at Boeun of Chungcheongbukdo in 2010. Average population density (APD) of overwintered SBPH was 13.1 heads in 2008, 13.9 heads in 2009 and 5.6 heads in 2010. The highest APD was 39.1 and 60.4 heads at Buan of Jellabukdo in 2008 and 2009, respectively, and 14.0 heads at Pyungtaeg of Gyeonggido. The acreage of RSV occurred fields was 869 ha in the western and southern parts, mainly at Jindo and Wando areas, of Jellanamdo in 2008. In 2009, RSV occurred in the acreage of 21,541 ha covered whole country, especially, partial and whole plant death were occurred with infection rate of 55.2% at 3,025 plots in 53 Li, 39 Eup/Myun, 19 Si/Gun of Gyeonggido, Incheonsi, Chungcheongnamdo, Jeollabukdo and Jeollanamdo. Seasonal development of overwintered SBPH was investigated at Buan, Jeollabukdo, and Jindo, Jeollanamdo for 3 years from 2008. Most SBPH developed to the 3rd and 4th instar on the periods of May 20 to June 10, and they developed to the adult stage for the 1st generation on Mid and Late June. In 2009, all SBPH trapped by sky net trap were adult on May 31 to June 1 at Mid-western aeas of Taean, Seosan and Buan, and South-western areas of Sinan and Jindo. The population density of adult SBPH was 963 heads at Taean, 919 at Seocheon and 819 at Sinan area. The origin of these higher population of adult SBPH were verified from the population of non-overwintered SBPH but immigrant SBPH. From Mid May to Mid June in 2010, adult SBPH could not be counted as immigrant insects by sky net trap. The variation of RSV VIR was high with 2.1% to 9.5% for immigrant adult SBPH trapped by sky net trap at Hongsung of Chungcheongbukdo, Buan of Jeollabukdo and so forth in 2009. The highest VIR for the immigrant adult SBPH was 9.5% at Boryung of Chungcheongnamdo, followed by 7.9% at Hongsung of Chungcheongnamdo, 6.5% at Younggwang of Jeollanamdo, and 6.4% at Taean of Cheongcheongnamdo. The infection rate of RSV on rice plants induced by the immigrant adult SBPH cultivated near sky net trap after about 10 days from immigration on June 12 in 2009 was 84.6% at Taean, 65.4% at Buan and 92.9% at Jindo, and 81% in average through genetic diagnosis of RT-PCR. Barley known as a overwintering host plant of RSV had very low infection rate of 0.2% from 530 specimens collected at 10 areas covering whole country including Pyungtaeg of Gyeonggido. Twenty nine plant species were newly recorded as natural hosts of RSV. In winter annual plant species, 11 plants including Vulpia myuros showed RSV infection rate of 24.9%. The plant species in summer annual ecotype were 13 including Digitaria ciliaris with 44.9%, Echinochloa crusgalli var. echinata with 95.2% and Setaria faberi with 65.5% in infection rate of RSV. Five perennial plants including Miscanths sacchariflorus with infection rate of 33.3% were recorded as hosts of RSV. Rice cultivars, 8 susceptible cultivars including Donggin1 and 17 resistant ones including Samgwang, were screened in field conditions at 3 different areas of Buan, Iksan and Ginje in 2009. All the susceptible cultivars were showed typical symptom of mosaic and wilt. In 17 genetic resistant cultivar, 12 cultivars were susceptible, however, 5 cultivars were field-resistant plus genetic resistant to RSV as non symptom expression. When RSV was artificially inoculated at seedling stage to 4 cultivars known as genetic resistant and 3 cultivars known as genetic susceptible, the symptom expression in resistant cultivars was lower as 19.3% in average than that of 53.3% in susceptible ones. In comparison of symptom expression rate and viral infection rate using resistant Nampyung and susceptible Heugnam cultivars by artificial inoculation of RSV at seedling stage, the symptom expression of Heugnam was higher as 28% than 12% of Nampyung. However, virion infection of resistant Nampyung cultivar was higher as 12% reversely than 85% of susceptible Heugnam. Yield loss of rice was investigated by the artificial inoculation of RSV at the seedling stage of resistant cultivars of Nampyung and Onnuri, and susceptible cultivars of Donggin1 and Ungwang for 3 years from 2008. The average yield per plant was 7.8 g, 8.5 g and 13.8 g on rice plants inoculated at seedling stage, tillering stage and maximum tillering stage, respectively. The yield loss rate was increased by earlier infection of RSV with 51% at seedling stage, 46% at tillering stage and 13% at maximum tillering stage. In resistant rice cultivars, there was no statistically significant relation between infection time and yield loss. In natural fields on susceptible rice cultivar of Ungwang at Taean and Jindo areas in 2009, the yield loss rate was increased with same tendency to the infection hill rate having the corelation coefficient of 0.94 when the viral infection was over 23.4%.