• Journal of Korean Society of Forest Science
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• v.87 no.4
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• pp.519-527
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• 1998

An economic study of vegetation control to increase production of Songyi (Korean name far pine mushroom, matsutake, Tracholoma matsutake (S. Ito & Imai) Sing.) in red pine (Panes densiflora) stands in Korea was undertaken. In Korea, Songyi grows only in red pine stands. Harvest of this mushroom provides a significant income source to rural people in Korea yielding exports of US$20 million to US$80 million per year. However, hypogeous Songyi colonies and the mushroom production are declining, partly because shade tolerant species are succeeding the shade intolerant red pine. Past research says that it is possible to deep Songyi production increasing by controlling under-story vegetation. But few people are wilting to invest in the necessary control. Our analysis found that the economics of vegetation control appear to be quite favorable, showing an internal rate of return (IRR) of 20.7 percent in 15 years. However, positive returns do not occur for at least eight years and even then, the returns may not appear to the landowner to be a result of vegetation control efforts only because the mushroom production has been greatly variable depending on weather conditions. In a sensitivity analysis, it was found that the number of circular mushroom colonies was critically important for the cash flow. Results of this analysis are also sensitive to assumptions about annual growth length(0.16m radial growth=1.0m/circular length growth) of Songyi colony. However, the primary goal of vegetation control should be to keep the young colonies growing. Further research in the behavior of hypogeous Songyi colonies after vegetation control would help to improve our confidence in the results.

• The korean journal of orthodontics
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• v.34 no.5 s.106
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• pp.371-379
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• 2004

The purpose of this study was to investigate the changes and types of statistical methods used in the Korean Journal of Orthodontics (KJO) and the American Journal of Orthodontics and Dentofacial Orthopedics (AJODO) from )999 to 2003. The frequency of use, transitions, assumption check of statistical methods and types of advanced statistical methods were examined from each journal. The study consisted of 247 articles published in the KJO and randomly chosen 50 articles per year which were original articles and used statistical methods T-test, analysis of variance(ANOVA), correlation analysis, nonparametric analysis. regression analysis chi-square test. factor analysis, were the order of statistical methods most frequently used in the KJO, while t-test. ANOVA, nonparametric analysis, correlation analysis, regression analysis, chi-square test. factor analysis. were the order of statistical methods used in the AJODO The changes of statistical methods observed in the KJO were not significant $(X^2=17.4\;p=0.5881)$ but the changes observed in the AJODO was seen to be significant $(x^2=42.4,\;p=0.0397)$ Some of the studies examined had overlooked the assumptions of the statistical methods employed. Data investigation such as outlier should be performed before analysis and alternative statistical approaches are applied for a small sample size. Types of advanced statistical methods were factor analysis and discriminant analysis in the KJO and Intention-To-Treat (ITT) analysis in clinical trials through multi-center, survival analysis and Generalized Estimating Equations (GEE) in the AJODO. Appropriate analysis approaches and interpretations should be applied for the correlated and repeated measurements of the orthodontic data set.

• Education of Primary School Mathematics
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• v.16 no.2
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• pp.123-145
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• 2013

This study was expected to yield the meaningful conclusions from the experimental group who took lessons based on inductive activities using GeoGebra at the beginning of proof learning and the comparison one who took traditional expository lessons based on deductive activities. The purpose of this study is to give some helpful suggestions for teaching proof to mathematically gifted elementary students. To attain the purpose, two research questions are established as follows. 1. Is there a significant difference in proof abilities between the experimental group who took inductive lessons using GeoGebra and comparison one who took traditional expository lessons? 2. Is there a significant difference in proof attitudes between the experimental group who took inductive lessons using GeoGebra and comparison one who took traditional expository lessons? To solve the above two research questions, they were divided into two groups, an experimental group of 10 students and a comparison group of 10 students, considering the results of gift and aptitude test, and the computer literacy among 20 elementary students that took lessons at some education institute for the gifted students located in K province after being selected in the mathematics. Special lesson based on the researcher's own lesson plan was treated to the experimental group while explanation-centered class based on the usual 8th grader's textbook was put into the comparison one. Four kinds of tests were used such as previous proof ability test, previous proof attitude test, subsequent proof ability test, and subsequent proof attitude test. One questionnaire survey was used only for experimental group. In the case of attitude toward proof test, the score of questions was calculated by 5-point Likert scale, and in the case of proof ability test was calculated by proper rating standard. The analysis of materials were performed with t-test using the SPSS V.18 statistical program. The following results have been drawn. First, experimental group who took proof lessons of inductive activities using GeoGebra as precedent activity before proving had better achievement in proof ability than the comparison group who took traditional proof lessons. Second, experimental group who took proof lessons of inductive activities using GeoGebra as precedent activity before proving had better achievement in the belief and attitude toward proof than the comparison group who took traditional proof lessons. Third, the survey about 'the effect of inductive activities using GeoGebra on the proof' shows that 100% of the students said that the activities were helpful for proof learning and that 60% of the reasons were 'because GeoGebra can help verify processes visually'. That means it gives positive effects on proof learning that students research constant character and make proposition by themselves justifying assumption and conclusion by changing figures through the function of estimation and drag in investigative software GeoGebra. In conclusion, this study may provide helpful suggestions in improving geometry education, through leading students to learn positive and active proof, connecting the learning processes such as induction based on activity using GeoGebra, simple deduction from induction(i.e. creating a proposition to distinguish between assumptions and conclusions), and formal deduction(i.e. proving).

• Journal of the Korean Geographical Society
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• v.50 no.6
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• pp.571-605
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• 2015

This research revealed that 'Yipjiamlyu' in the Mukedeng's map is geographically 'a beginning point of underf low,' whose location is on the Heishigou's riverbed(E.L. 1,840m) in the NNE side of Daegakbong peak, and that 'Tomungangweon'(Heishigou) is one of the upstream reach of the Sungari River, which, according to historical documents and my fieldwork, Mukedeng also knew at the time of Yimjin(1712) Boundary Making and Demarcation(YBMD). These findings suggest the need to reinterpret the processes of YBMD. Mukedeng set up the Baekdusanjeonggyeobi on the mistaken assumptions on the linkage of 'Yipjiamlyu' and Tumen River. It should have been set up on the Daeyeonjibong peak. Mukedeng found the 'Yipjiamlyu' on the riverbed of 'Tomungangweon'(Heishigou), went downstream, and realized that this river did not flow into the Tumen River. During the search for the source of Tumen River, he found a water stream, and regarded it as the source of Tumen River. He speculated that the water at the 'Yipjiamlyu' flows through the underground to reappear at the his 'identified' source of Tumen River. Consequently, he adjured the construction of demarcation from Baekdusanjeonggyeobi through 'Yipjiamlyu' to the his 'identified' source of Tumen River. The water stream pointed as the source of Tumen River, however, was not part of the upstream reach of Tumen River. Actually, Korean officials, who were in charge of establishing boundary features, set up the demarcation from Baekdusanjeonggyeobi through Huanghuasongdianzi to the true source of Tumen River identified by themselves, which Mukedeng had not intended. The ambiguity of the location of 'Yipjiamlyu' caused a difference between Mukedeng's original request and Korean officials' implementation in the boundary demarcation. Throughout the whole processes of YBMD, Korea(Joseon) and China(Qing) both mistook the real geography of the river system. Their understanding on Yalu River system was correct. But the identification of the spring source of the Tumen River by Korean participants was the only geographically correct result related on this river system in YBMD.

• KSBB Journal
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• v.23 no.6
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• pp.519-524
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• 2008

Monacolin-K is a strong anti-hypercholesterolemic agent produced by Monascus sp. via polyketide pathway. High-yielding mutants of monacolin-K were developed through rational screening strategies adopted based on understanding of monacolin-K biosynthetic pathway. Through the experiments for investigating various amino acids as putative precursors for the monacolin-K biosynthesis, it was found that production level of monacolin-K was remarkably increased when optimum amount of cysteine was supplemented into the production medium. We suggested that these phenomena might be related to the special roles of SAM (S-adenosyl methionine), a putative methyl group donor in the biosynthetic pathway of monacolin-K, demonstrating close interrelationship between SAM-synthesizing primary metabolism and monacolin-K synthesizing secondary metabolism. Namely, increase in the intracellular amount of SAM derived from the putative precursor, cysteine which was extracellularly supplemented into the production medium might contribute to the significant enhancement in the monacolin-K biosynthetic capability of the highly mutated producers. On the basis of these assumptions derived from the above fermentation results, we decided to construct efficient expression vectors harboring SAM synthetase gene (metK) cloned from A. nidulans, with the hope that increased intracellular level of SAM could lead to further enhancement in the monacolin-K production through overcoming a rate-limiting step associated with monacolin-K biosynthesis. Hence, in order to overcome the plausible rate-limiting step associated with monacolin-K biosynthesis by increasing intracellular level of SAM, we transformed the producer mutants with an efficient expression vector harboring gpdA promoter of the producer microorganism, and metK gene. Notably, from the resulting various transformants, we were able to screen a very high-yielding transformant which showed approximately 3.3 fold higher monacolin-K productivity than the parallel nontransformed mutants in shake flask cultures performed under the identical fermentation conditions.

• KDI Journal of Economic Policy
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• v.12 no.2
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• pp.51-79
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• 1990

Research on technical efficiency, an important dimension of market performance, had received little attention until recently by most industrial organization empiricists, the reason being that traditional microeconomic theory simply assumed away any form of inefficiency in production. Recently, however, an increasing number of research efforts have been conducted to answer questions such as: To what extent do technical ineffciencies exist in the production activities of firms and plants? What are the factors accounting for the level of inefficiency found and those explaining the interindustry difference in technical inefficiency? Are there any significant international differences in the levels of technical efficiency and, if so, how can we reconcile these results with the observed pattern of international trade, etc? As the first in a series of studies on the technical efficiency of Korea's manufacturing industries, this paper attempts to answer some of these questions. Since the estimation of technical efficiency requires the use of plant-level data for each of the five-digit KSIC industries available from the Census of Manufactures, one may consture the findings of this paper as empirical evidence of technical efficiency in Korea's manufacturing industries at the most disaggregated level. We start by clarifying the relationship among the various concepts of efficiency-allocative effciency, factor-price efficiency, technical efficiency, Leibenstein's X-efficiency, and scale efficiency. It then becomes clear that unless certain ceteris paribus assumptions are satisfied, our estimates of technical inefficiency are in fact related to factor price inefficiency as well. The empirical model employed is, what is called, a stochastic frontier production function which divides the stochastic term into two different components-one with a symmetric distribution for pure white noise and the other for technical inefficiency with an asymmetric distribution. A translog production function is assumed for the functional relationship between inputs and output, and was estimated by the corrected ordinary least squares method. The second and third sample moments of the regression residuals are then used to yield estimates of four different types of measures for technical (in) efficiency. The entire range of manufacturing industries can be divided into two groups, depending on whether or not the distribution of estimated regression residuals allows a successful estimation of technical efficiency. The regression equation employing value added as the dependent variable gives a greater number of "successful" industries than the one using gross output. The correlation among estimates of the different measures of efficiency appears to be high, while the estimates of efficiency based on different regression equations seem almost uncorrelated. Thus, in the subsequent analysis of the determinants of interindustry variations in technical efficiency, the choice of the regression equation in the previous stage will affect the outcome significantly.

• The Korean Journal of Pesticide Science
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• v.9 no.4
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• pp.347-353
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• 2005

Pesticide risk assessment for pesticide operators as well as for consumers has become one of the pesticide regulatory tools to reduce any unreasonable adverse health effects from pesticide use. The risk for pesticide operators can be quantified by comparing the acceptable operator exposure level(AOEL) with exposure level during pesticide application. This study is to evaluate the risk of benzimidazole fungicides application worker. The exposure level of pesticide applicators were calculated using Japanese operator exposure study tested with EPN 45% EC. The AOELs for pesticides were obtained dividing relevant lowest no observed abuse effect levels(NOAELs) for the exposure scenario into uncertainty factor, 100. For the non-cancer and cancer occupational risk assessment, $Q_1^*$ produced by US/EPA and life time average daily dose(LADD) calculated from average daily dose(ADD), treatment days per year, worked years for life time were used. Operator exposure for benzimidazole fungicides application were benomyl 0.2, carbendazim 0.36 and thiophanate-methyl 0.42 mg/kg/day. Short-term AOELs for benomyl, carbendazim and thiophanate-methyl were 0.3, 0.1, and 0.2 mg/kg/day, and long-term AOEL were 0.025, 0.025, 0.08 mg/kg/day, respectively. LADDs were benomyl 0.0038, carbendazim 0.0067, thiophanate-methyl 0.0081 mg/kg/day. The ratios of exposure to AOEL were $0.28{\sim}1.5$ for short-term and $3.73{\sim}9.88$ for long-term. Cancer risk for operator were $9.12{\times}10^{-6}$ for benomyl, $1.61{\times}10^{-5}$ for carbendazim and $1.13{\times}10^{-4}$ for thiophanate-methyl by the standard application scenario. The result showed 3 fungicides exceed the risk criteria, $1.0{\times}10^{-6}$. The above risk assessments were based upon conservative assumptions and therefore are believed to be protective of the applicator. To refine the risk at the more actual conditions, further risk assessment with more realistic data would be needed.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• 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.

• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.113-132
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• 2003

Using nonradial data envelopment analysis(DEA) under assumptions of strong disposability and variable returns scale, this paper annually estimates productive. technical and allocative efficiencies of three publicly-owned rail transit properties which are different in terms of organizational type: Seoul Subway Corporation(SSC, local public corporation), the Seoul Metropolitan Electrified Railways sector (SMESRS) of Korea National Railroad(the national railway operator controlled by the Ministry of Construction and Transportation(MOCT)), and Busan Urban Transit Authority (BUTA, the national authority controlled by MOCT). Using the estimation results of Tobit regression analysis. the paper next computes their true productive, true technical and true allocative efficiencies, which reflect only the impacts of internal factors such as production activity by removing the impacts of external factors such as an organizational type and a track utilization rate. And the paper also computes an organizational efficiency and annually gross efficiencies for each property. The paper then conceptualized that the property produces a single output(car-kilometers) using four inputs(labor, electricity, car & maintenance and track) and uses unbalanced panel data consisted of annual observations on SSC, SMESRS and BUTA. The results obtained from DEA show that, on an average, SSC is the most efficient property on the productive and allocative sides, while SMESRS is the most technically-efficient one. On the other hand. BUTA is the most efficient one on the truly-productive and allocative sides, while SMESRS on the truly-technical side. Another important result is that the differences in true efficiency estimates among the three properties are considerably smaller than those in efficiency estimates. Besides. the most cost-efficient organizational type appears to be a local public corporation represented by SSC, which is also the most grossly-efficient property. These results suggest that a measure to sort out the impacts of external factors on the efficiency of rail transit properties is required to assess fairly it, and that a measure to restructure (establish) an existing(a new) rail transit property into a local public corporation(or authority) is required to improve its cost efficiency.