• 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.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.202-204
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• 2005

상품 온톨로지는 온톨로지 (Ontology) 구성요소인 개념 (Concept) 과 속성 (Property)이 상품 도메인에 특화된 온틀로지이다. 본 논문에서는 대용량을 특징으로 하는 상품 온톨로지를 표현함에 적용되어 질 수 있는 Hyperbolic Tree, Cluster Map, 그래프 비주얼라이제이션을 살펴보고, 계층을 갖는 개념을 표현하는 데 좋은 Hyperbolic과, 속성을 잘 표현 할 수 있는 Cluster Map을 상품 온톨로지에 유리한 비주얼라이제이션으로서 제안한다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.2
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• pp.212-219
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• 2012

This study focus on what methods of MOT are needed and utilized to solve a technical problem in the MOT leading company. We first classified the MOT methods by project life cycle and R&D job quality based on the several discussion with working group. In order to study, the survey was carried out by 168 experts working on MOT practices. Our main research findings are as follows. The level of utilized MOT methods was above average because MOT sector was beginning to represent an increasing share of total R&D business. But the satisfaction level on the MOT majors was below average. The more utilized MOT methods in practices were 'environment analysis and opportunity research,' 'business feasibility,' 'roadmapping,' 'portfolio,' 'technology tree,' 'scheduling,' 'risk management,' 'six sigma,' 'design of experiment,' 'quality control,' 'cost analysis' etc. And the subjects of product realization process were also needed to MOT practice such as 'design for reliability,' 'design for cost,' 'design for performance,' 'design for safety' deeply involved to product quality. Finally, the capability requested to University students were 'problem define and solving,' 'technology planning and strategy,' 'creative thinking.'

• Clean Technology
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• v.26 no.1
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• pp.79-87
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• 2020

The bio-oil produced from the fast pyrolysis of lignocellulosic biomass contains a high amount of oxygenates, causing variation in the properties of bio-oil, such as instability, high acidity, and low heating value, reducing the quality of the bio-oil. Consequently, an upgrading process should be recommended ensuring that these bio-oils are widely used as fuel sources. Catalytic fast pyrolysis has attracted a great deal of attention as a promising method for producing upgraded bio-oil from biomass feedstock. In this study, the fast pyrolysis of tulip tree was performed in a bubbling fluidized-bed reactor under different reaction temperatures, with and without catalysts, to investigate the effects of pyrolysis temperature and catalysts on product yield and bio-oil quality. The system used silica sand, ferric oxides (Fe₂O₃ and Fe₃O₄), and H-ZSM-5 as the fluidized-bed material and nitrogen as the fluidizing medium. The liquid yield reached the highest value of 49.96 wt% at 450 ℃, using Fe₂O₃ catalyst, compared to 48.45 wt% for H-ZSM-5, 47.57 wt% for Fe₃O₄ and 49.03 wt% with sand. Catalysts rejected oxygen mostly as water and produced a lower amount of CO and CO₂, but a higher amount of H₂ and hydrocarbon gases. The catalytic fast pyrolysis showed a high ratio of H₂/CO than sand as a bed material.

• Korean Journal of Food Science and Technology
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• v.31 no.5
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• pp.1153-1158
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• 1999

Propolis is a resinous bee-hive product that honeybees collect from plant exudates, flower and leaves. Flavor characteristics of two varieties of propolis collected from different plant origins, falseacacia(Robinia psedoacacia L.) and chestnut tree(Castanea crenata), were analyzed using Aroma Scan and GC/MS. Two varieties of propolis were grouped with quite different aroma profiles by Aroma Scan. Fifty five flavor compounds were identified by GC/MS, of which 44 compounds were found from the propolis of falseacacia and 47 compounds from chestnut tree. Five aldehydes, eight alcohols. five ketones, three esters, one fatty acid, twenty seven hydrocarbons. two terpenes and four phenolic derivatives were identified. Thirty six compounds including benzaldehyde, cinnamyl alcohol, eudesmol and benzyl benzoate were detected in both propolis, eight compounds including geraniol and n-undecane only in propolis of falseacacia and eleven compounds including piperitenone and valencene only in chestnut tree.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.56-65
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• 2016

In this paper, in order to reduce the delay and area of the partial product accumulation (PPA) of the parallel decimal multiplier, a tree architecture that composed by multi-operand decimal CSAs and improved CLA is proposed. The proposed tree using multi-operand CSAs reduces the partial product quickly. Since the input range of the recoder of CSA is limited, CSA can get the simplest logic. In addition, using the multi-operand decimal CSAs to add decimal numbers that have limited range in specific locations of the specific architecture can reduce the partial products efficiently. Also, final BCD result can be received faster by improving the logic of the decimal CLA. In order to evaluate the performance of the proposed partial product accumulation, synthesis is implemented by using Design Complier with 180 nm COMS technology library. Synthesis results show the delay of the proposed partial product accumulation is reduced by 15.6% and area is reduced by 16.2% comparing with which uses general method. Also, the total delay and area are still reduced despite the delay and area of the CLA are increased.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1021-1026
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• 2015

Increasing of damage by phishing, government and organization response more rapidly. So phishing use malware and vulnerability for attack. Recently attack that use patch analysis is increased when Microsoft announce patches. Cause of that, researcher for security on defense need technology of patch analysis. But most patch analysis are develop for Microsoft's product. Increasing of mobile environment, necessary of patch analysis on mobile is increased. But ordinary patch analysis can not use mobile environment that there is many file and small size. So we suggest this research that use code filtering instead of Control Flow Graph and Abstract Syntax Tree.

• Journal of the Korea Safety Management & Science
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• v.6 no.3
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• pp.237-247
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• 2004

The condition of the manufacturing process in a factory should be diagnosed and maintained efficiently because any unexpected disorder in the process will be reason to decrease the efficiency of the overall system. However, if an expert experienced in this system leaves, there will be a problem for the efficient process diagnosis and maintenance, because disorder diagnosis within the process is normally dependent on the expert's experience. This paper suggests a process diagnosis using data mining based on the collected data from the coil-spring manufacturing process. The rules are generated for the relations between the attributes of the process and the output class of the product using a decision tree after selecting the effective attributes. Using the generated rules from decision tree, the condition of the current process is diagnosed and the possible maintenance actions are identified to correct any abnormal condition. Then, the appropriate maintenance action is recommended using the decision network.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.12
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• pp.20-35
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• 2016

In this paper, in order to reduce the delay and area of the partial product accumulation (PPA) of the parallel decimal multiplier, a tree architecture that composed by multi-operand decimal CSAs and improved CLA is proposed. The proposed tree using multi-operand CSAs reduces the partial product quickly. Since the input range of the recoder of CSA is limited, CSA can get the simplest logic. In addition, using the multi-operand decimal CSAs to add decimal numbers that have limited range in specific locations of the specific architecture can reduce the partial products efficiently. Also, final BCD result can be received faster by improving the logic of the decimal CLA. In order to evaluate the performance of the proposed partial product accumulation, synthesis is implemented by using Design Complier with 180 nm COMS technology library. Synthesis results show the delay of the proposed partial product accumulation is reduced by 15.6% and area is reduced by 16.2% comparing with which uses general method. Also, the total delay and area are still reduced despite the delay and area of the CLA are increased.

• KSBB Journal
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• v.32 no.2
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• pp.117-123
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• 2017

Maple tree is a useful medical plant for obtaining bioactive materials such as pharmaceutics, cosmetics, food additive, etc., and there are 16 species of native maple trees in Korea. In this study, we evaluated the antioxidant activity of sap and crude extracts of Acer mono Max, a representative maple species. The crude extracts were obtained by solvent extraction (water, ethanol, and ethyl acetate) from its branches (bark and xylem). The phenolic contents and radical scavenging capacities of the extracts and the sap were evaluated in terms of half maximal effective concentration ($EC_{50}$) and kinetics by 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. The ethanol extracts showed the highest extraction yield, phenolic contents and antioxidant activity, and bark extracts showed better antioxidant activity than xylem extracts. The antioxidant activity of the sap was very low, but the $EC_{50}$ of ethanol and ethyl acetate extracts ranged from 68 to $79{\mu}g/mL$, similar to that ($60{\mu}g/mL$) of the control, butylated hydroxytoluene (BHT). The DPPH radical scavenging rate ($220{\sim}760{\mu}M/min$) and the second-order reaction rate constant ($6.48{\sim}7.04L/g{\cdot}min$) of these extracts were better than those of BHT ($55{\sim}370{\mu}M/min$ and $3.60L/g{\cdot}min$). These results suggest that A. mono Max. is one of the useful bioresources for obtaining antioxidant biologically active substances, and it is possible to obtain physiologically active substances from by-product of its pruning while minimizing the effect on the growth of the tree.