• Journal of Life Science
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• v.26 no.8
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• pp.904-910
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• 2016

Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The gene network analysis has been performed by diverse types of methods such as gene co-expression, gene regulatory relationships, protein-protein interaction (PPI) and genetic networks. Moreover, the network-based methods were described for predicting gene functions such as graph theoretic method, neighborhood counting based methods and weighted function. However, there are a limited number of researches in livestock. The present study systemically analyzed genes associated with 102 types of economic traits based on the Animal Trait Ontology (ATO) and identified their relationships based on the gene co-expression network and PPI network in cattle. Then, we constructed the two types of gene network databases and network visualization system (http://www.nabc.go.kr/cg). We used a gene co-expression network analysis from the bovine expression value of bovine genes to generate gene co-expression network. PPI network was constructed from Human protein reference database based on the orthologous relationship between human and cattle. Finally, candidate genes and their network relationships were identified in each trait. They were typologically centered with large degree and betweenness centrality (BC) value in the gene network. The ontle program was applied to generate the database and to visualize the gene network results. This information would serve as valuable resources for exploiting genomic functions that influence economically and agriculturally important traits in cattle.

• Journal of Korean Home Economics Education Association
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• v.18 no.2 s.40
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• pp.63-77
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• 2006

The Purpose of this study is to provide the basic data for the improvement or the contents or clothing curriculum in the 7th technology home economics of middle school. The standard of satisfaction of students' according to the detail domains and the standard of necessity and practical use and learners' patterns of activity task suggested in textbooks were evaluated. The ninth grade 169 boy students and 336 girl students in the national capital region were participated in this survey. According to the survey results, firstly, a dress domain got the highest relative importance(28.56%) while a clothes material domain took the lowest relative importance(8.07%) among various detail domains. Secondly, the standard of satisfaction according to each detail domain fell below the average. Generally girls' satisfaction for teaching was higher than boys'. Thirdly, a clothes material domain showed the lowest necessity for textbook contents according to detail domain and other domains showed above the average. The necessity for textbook contents appeared high for boy students rather than girl students. In addition, boy and girl students did not have interest in content relevance in textbook. Especially, they could not do well and understand experiments and practices in clothing section. Finally, The degree of utilization of the activity task ill textbooks was very low. Among various activity tasks, the learning by discovering and exploring were more utilized than cooperating learning.

• The Journal of the Korean bone and joint tumor society
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• v.15 no.1
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• pp.34-43
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• 2009

Purpose: Glomus tumors are rare benign vascular tumors, usually located in the skin or soft tissue of extremities. Approximately 30-50% of glomus tumors occur in subungal area, but glomus tumors have been described in every location even where glomus bodies are not or rarely present. The purpose of this study was to identify clinical, histologic and MRI characteristics of soft tissue glomus tumor. Materials and Methods: Between 1993 and 2008, eight patients underwent surgery of soft tissue Glomus tumor at our institution. Exclusion criteria were patients with Glomus tumors in digits, stomach, trachea and glomus tympanicum. We analyzed medical records, interviews, physical examinations, MR findings and histolocial types retrospectively. Results: There were four men and four women. The mean age was fourty-seven years. The mean prevalence time was eight-point-nine years. In the classic triad of symptoms, all eight patients had pain and tenderness. Two patients complained of cold sensitivity. Two showed skin color changes. After surgery, two showed symptom improvement (VAS $9^{\circ}{\rightarrow}8$, $8^{\circ}{\rightarrow}5$) and?six showed complete disappearance of symptoms. Slightly symptom improvemented (VAS $9^{\circ}{\rightarrow}8$) one had additional surgery two times after first surgery due to relapse/remaining Glomus tumor. The mean size was 13.9 mm. In histology, six were 'solid glomus tumor', one was a mixture of 'solid glomus tumor' and 'lomangioma' and one was 'malignant glomus tumor'. MR findings showed isointense signal on T1 image, high signal on T2 image and strong enhancement on the Gadolinium enhanced image. Conclusion: Glomus tumor has low recurrence rate and malignant change, rapid diagnosis and surgical excision is critical in treatment to prevent unnecessary pain of patient.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.28 no.3
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• pp.131-143
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• 2010

This paper investigates the history, policy and status of the conservation of historic gardens in the National Trust in England and its implications for Korea. It was conducted in three phases as follows: First, related literature data was collected to understand the National Trust and its role in the conservation of historic gardens. Second, The National Trust Policy Papers: Gardens and Landscape Parks in 1996 was reviewed and analyzed into eight categories with a review of 216 gardens and interviews with gardener-in-charge via e-mail. Finally an understanding of the policy for the conservation of historic gardens was formed from the results of the previous phases, and implications were drawn from the integrated analysis guidelines of the policy and status. The key feature of the conservation of the National Trust's historic gardens is that the conservation process has been conducted systematically through acquisition, management, upkeep, advice and so on. Furthermore, the conservation principles are defined in a concise and accessible form. According to their practical conservation process and principles, the results of the National Trust activities are to appreciate the significance of the gardens and act with accountability; integration; managing change; access and participation; and training gardener and partnership. According to the results of its activities under the premise that the purpose of the conservation and the meaning of a garden do not differ significantly among nations, implications for Korea can be primarily suggested by three points as follows: First of all, a flexible approach to change in historic gardens should be managed. In response to inevitable and desirable change, anything that is added or transferred should be recorded for the future as much as possible. Therefore, everything must be recorded and any change should be managed. Second, is to provide sustainable access for the benefit for the people and visitors. The aim of conserving the gardens is for human's to eventually understand that the present generation just borrows the historic gardens before they are passed down. The ensuing implication is that people may enjoy the gardens educationally, aesthetically, and physically, and children can be continuously interested in historic gardens as apart of educating the future generation. Finally, the National Trust educates apprentice gardeners who will maintain the historic gardens and continuously keep the current garden staff up to date with workshops. This is in contrast to the day laborers who work for historic gardens in Korea. In practice, the maintenance of historic gardens is not a simple process. The gardener must understand the past, reflect the present, and prepare for the future. Therefore, gardeners deliver culture from generation to generation.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.28 no.3
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• pp.122-130
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• 2010

The Study takes the rivers in Zhouzhuang - traditional Chinese Kangnam watery landscape as the object. The purpose of this study is to grasp the relationships between visual characteristics and the preference. The following is the research process: Firstly, the theoretical study of Zhouzhuang, the traditional Kangnam region in China, is conducted, the watery landscape is taken pictures, and 22 photos are selected. Secondly, in order to grasp the visual preference and landscape characteristics of the watery landscape in Zhouzhuang, 22 pictures and 25 pairs of adjectives are adopted for the questionnaire survey. Thirdly, in order to have a better understanding on the physical properties and effects of physical quantity on the preference, the occupation ratios of buildings and sculptures, natural elements, footpaths, bank revetments and other landscape elements are calculated, and the mean analysis, dispersion analysis and regression analysis are conducted. In order to grasp the landscape characteristics and preference factors, 25 pairs of adjectives are used to conduct the factor analysis. In order to grasp the effects of characteristics of visual factors on the preference, the dispersion analysis and regression analysis are carried out. The results are as follows: From the results of the landscape preference analysis, in the No.22 photo with the top preference, 11 pairs of adjectives, namely, "harmonious-disharmonious", "beautiful-ugly", "rural-urban", "soft-rough", "stable-instable", "romantic-realistic", "cheerful-gloomy", "brilliant-simple", "natural-artificial", "familiar-strange", and "clean-dirty" have positive effects on watery landscape. It can be viewed as the relatively important factor in the visual preference. In terms of the results of visual physical quantity analysis of traditional Chinese Kangnam watery landscape, the landscape with high occupation ratio of buildings and sculptures has positive effects on visual preference. The results of analysis of visual physical quantity and preference show that the preference degree increases as the occupation ratio of footpath area increases. The analysis results of visual characteristics of traditional Chinese Kangnam watery landscape identify four factors, namely psychological factor, cultural factor, condition factor and physical factor. It can be concluded from the results of analysis of the relationships between visual preference and visual characteristics that the return coefficient B of the psychological factor is +0.936. It can significantly affect the watery landscape, so it can be identified as the most important factor among the visual preference factors of Chinese Kangnam watery landscape.

• Journal of Environmental Impact Assessment
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• v.28 no.6
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• pp.568-579
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• 2019

The present study aims to identify the effect of land cover categories on particulate matter (PM) concentrations by analyzing the correlation between monthly PM concentrations in Seoul's air quality monitoring network and the percentages of land cover categories by buffers around air quality monitoring stations. According to a monthly correlation analysis between land cover categories and PM concentrations, in the buffer 3km, PM₁₀ showed a better correlation than PM_2.5, there was a clear negative correlation with the forest area, the grassland and the urbanized area had some positive correlation with PM₁₀, and the barren land and the urbanized area had some positive correlation with PM_2.5. According to a monthly correlation analysis of dominant land cover sub-categories and sub-sub-categories within the buffer 3km, PM₁₀ showed a clear negative correlation with the broad-leaved forest, and some positive correlation with the road was dominant. PM_2.5 showed partly negative correlation with the broad-leaved forest and partly positive correlation with the commercial area. There was a very low or no correlation with other grassland and bare land subcategories. A monthly stepwise regression analysis on noticeable land cover sub-categories and sub-sub-categories with positive or negative correlations revealed that an increasing percentage of the broad-leaved forest had a clear effect on reducing PM₁₀ concentrations, and the road was excluded from the selected variables. Although an increasing percentage of the commercial area had some effect on increasing monthly PM_2.5 concentrations and an increasing percentage of the broad-leaved forest had an effect on decreasing the PM_2.5 concentrations, their effect size was smaller than that on PM₁₀. The forest area around the city center had the largest and clearest effect on reducing PM concentrations. The urbanized area's sub-categories and sub-sub-categories were also confirmed to have some effect on increasing PM concentrations.

• Journal of Nutrition and Health
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• v.49 no.5
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• pp.277-287
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• 2016

Purpose: This study was performed to compare total phenolic contents, in vitro antioxidant capacity, and reduction effect of Korean food groups on ex vivo DNA damage in human cells and analyze correlations between each indicator. Methods: Vegetable foods in the Korean diet based the results of the KNHANES V-2 (2011) were classified into 10 food groups: cereals, fruits, vegetables, nuts, kimchi, seaweeds, potatoes, mushrooms, legumes, and oils. Eighty-four foods constituted more than 1% of the total intake in each food group and finally designated as vegetable foods in the Korean diet. Total phenolic content of each food group was measured. Further, in vitro antioxidant capacity was measured based on DPPH radical scavenging assay, TEAC assay, and $ORAC_{ROO{\cdot}}$ assay. Ex vivo DNA damage in human lymphocytes was assessed using comet assay. Results: Total phenolic contents of food groups of the Korean diet increased in the order of mushrooms, fruits, vegetables, seaweeds, and kimchi. Meanwhile, antioxidant rankings of food groups as mean values from the three in vitro test methods increased in the order of mushrooms, seaweeds, vegetables, kimchi, and fruits. Protection against ex vivo DNA damage in human lymphocytes was highest in mushrooms, followed by vegetables, fruits, seaweeds, and kimchi. The rankings of the food groups for total phenolic content, in vitro DAC, and ex vivo DNA protection activity were similar, and correlations between each indicator were significantly high. Conclusion: Mushrooms, fruits, vegetables, and seaweeds among the tested food groups in the Korean diet showed high total phenolic contents, in vitro antioxidant capacities, and protection against DNA damage. Correlations between each indicator in terms of total phenolic content, in vitro antioxidant capacity, and ex vivo DNA protection between each food group were found to be particularly high.

• Applied Biological Chemistry
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• v.43 no.3
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• pp.218-224
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• 2000

The efforts were made to optimite ethanol extraction from persimmon leaf with the time of extraction$(1.5{\sim}2.5\;hrs)$, the temperature of extraction$(70{\sim}90^{\circ}C)$, and the concentration of ethanol$(0{\sim}40%)$ as three primary variables together with several functional characteristics of persimmon leaf as reaction variables. The conditions of extraction was best fitted by using response surface methodology through the center synthesis plan, and the optimal conditions of extraction were established. The contents of soluble solid and soluble tannin went up as the concentration of ethanol went up and the temperature of extraction went down, and the turbidity went down as the concentration of ethanol went down. Electron donation ability was hardly affected by the extraction temperature and had the tendency to go up as the concentration of ethanol went up. The inhibitory activity of xanthine oxidase(XOase) had the tendency to go up as both the concentration of ethanol and the temperature of extraction went up. The inhibitory activity of angiotensin converting enzyme(ACE), the significance of which still was not recognized, showed the maximum when the concentration of ethanol was 27%. In result, the optimal conditions of extraction was the extraction time of two hours, the extraction temperature of $75{\sim}81^{\circ}C$, and the ethanol concentration of $33{\sim}35%$.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.