• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.

• 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.

• Journal of Digital Convergence
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• v.13 no.8
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• pp.69-82
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• 2015

This article critically examines the backgrounds and meanings of National Competency Standards (NCS) that is employed by Korean colleges for managing performance-based, competency-based curriculum. Findings are as follows: 1) the NCS-based curriculum was primarily adopted to enhance students' business competency for their successes in a competitive job market. 2) NCS is questioned its efficacy to resolve Korean employment issues in a serious economic structure in which a growing number of jobless youth and aged employees and education discrimination are involved. 3) NCS, with its emphasis on the Tyler Rationale and principles of scientific curriculum development, has many criticisms due to its technical approaches to educational processes and needs to be replaced with an alternative paradigm. 4) This article suggests that administrators, policy makers, and educators seek ways to resolve NCS issues considering contextual features of Korean job market and rethinking NCS ideology in the education process. A need for curriculum reconceptualisation is discussed.

• Management & Information Systems Review
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• v.39 no.2
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• pp.1-15
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• 2020

Using information and communication technologies, many firms have increased their productivity. In resource based view, practical use of information and communication technologies is a process of increasing competitive advantage in uncertain environment. However, use of new information and communication technologies does not surely improve the productivity and work efficiency, but sometimes could be a factor to hinder firm performance. Technostress means adverse effect occurring in which the user of new information and communication technologies does not adapt to environment of new technologies. That is, Technostress is a negative impact resulted from using information and communication technologies. This study investigated the effect of technostress on counter-productivity. Unlike the previous studies, this study was made with the survey for firm employees of Daegu region, and both counter-productive work behavior and innovation resistance were used in this study. The empirical result means that technostress positively affects both counter-productive work behavior and innovation resistance. Because technostress increases both counter-productive work behavior and innovation resistance, systematic management for firm employees is needed in time adopting information and communication technologies.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.2
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• pp.97-109
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• 2020

Drought is one of the most influential disasters in sustainable agriculture and food security of nations. In order to preemptively respond to agricultural droughts, vulnerability assessments were conducted to predict the possibility of drought in the region, the degree of direct or indirect damage, and the ability to cope with the damage. Information on agricultural drought vulnerability status of different regions is extremely useful for implementation of long term drought management measures. The purpose of this study is to develop and implement a quantitative approach for measuring agricultural drought vulnerability at sub-district level based on agricultural water and reservoirs. To assess the vulnerability in a quantitative manner and also to deal with different physical and socioeconomic data on the occurrence of agricultural drought, we selected the appropriate factors for the assessment of agricultural drought vulnerability through preceding studies, and analyzed the meteorological and agricultural reservoir data from 2015 to 2018. Each item was weighted using AHP (Analytic Hierarchy Process) analysis and evaluated through the agricultural drought vulnerability estimation. The entire national vulnerability assessments showed that Ganghwa, Naju, and Damyang were the most vulnerable to agricultural droughts. As a result of analyzing spatial expression, Gyeongsang-do is relatively more vulnerable to drought than Gangwon-do and Gyeonggi-do. The results revealed that the methodology and evaluation items achieved good performance in drought response. In addition, vulnerability assessments based on agricultural reservoir are expected to contribute supporting effective drought decisions in the field of agricultural water management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.228-237
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• 2018

The purpose of this study is to develop an index to measure regional creativity factors from previous research, as well as to empirically analyze the relationship between regional creativity and regional growth. We conduct panel analysis on the balanced panel data of regional creativity in fifteen Korean cities and provinces during 2008-2012. The result of hypothesis testing are as follows: First, amongst factors of regional creativity, sub-factors such as creative personnel and intangible asset (of the basic asset factor), creative enterprise (of the economic agent factor), and convergence and creative industries (of the core industry factor) showed significant influential relationships with GRDP (Gross Regional Domestic Product) as positive. Concerning the systemization factor, all sub-factors showed no significant relationship with GRDP. Second, amongst the factors, creative personnel (of the basic asset factor), start-up and entrepreneurship (of the systemization factor), creative enterprise (of the economic agent factor), the regional space factor, and convergence industry (of the core industry factor) showed significant positive relationships with employment rate. However, tangible and intangible creative asset (of the basic asset factor), convergence management and administration (of the systemization factor), Large/middle/small enterprises and central government/municipalities (of the economic agent factor), and creative industry (of the core industry factor) showed no significant relationship with employment rate. The results of this study will provide insight into the current situation for regional creativity, and review the process and short and long term performance. In addition, it will be a basic means to lead the central government's policy of strengthening local autonomy and decentralization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.5
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• pp.1460-1466
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• 2008

The purpose of this study is to verify how the accounting information of a bankrupt firm which is defined as a dishonor, an impaired total capital, a poor financial performance of a business, a rejection of auditor's opinion and an incongruity of auditor's opinion differs from that of a healthy firm on the basis of the index of financial affairs if the accounting information released by KOSDAQ is valuable. The sampling firms consists of 45 KOSDAQ firms that went bankrupt from 2000 to 2007 and 45 healthy firms which are selected in accordance with the sizes of assets. It has also selected the 30 sampling firms for the confirmation of the model in the same way. According to the result of the in-depth analysis, the variables related to security among the 17 indexes of financial affairs that have been used in this study for 5 years show a noticeable difference between a bankrupt firm and a healthy one. The accuracy of failed firms using this model for confirmation demonstrates 76.7% in 5 years before the bankruptcy, 76.7% in 4 years before that, 65.0% in 3 years before it, 76.7% in 2 years, 88.3% in 1 year. This data shows that the process from a healthy firm to a bankrupt one has progressed gradually and confirms the value of the index of financial affairs, exhibiting the accuracy with 83.8% of a presuming sample and 76.7% of a confirming sample for 5 years.

• Journal of the Korean Regional Science Association
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• v.34 no.3
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• pp.3-11
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• 2018

Urban regeneration is a worldwide challenging project, showing a great interest in the sector. In order for Korea's urban regeneration to be settled successfully in the early stage, it is necessary to analyze and review the opinions and business performance of the urban regeneration areas. The purpose of this study is to evaluate the urban regeneration planning factors affecting urban regeneration on the satisfaction of citizens, public administration and region. This study surveyed the residents and experts of the Yeongju city, Gyeongsangbuk-do, where urban regeneration is actively doing with active participation of residents and local government. Based on the data of the survey, this paper performed frequency analysis, correlation analysis and multiple regression analysis as a analytic methods. The results revealed that 'community factor' was the most important factor to the satisfaction of residents in the urban regeneration project in progress. In the final stage(at present), both 'community factor' (0.387) and 'physical factor'(0.454) were found to have a significant effect on satisfaction. While the satisfaction from 'the economic factor'(0.111) has slowed but it has increased with 'the physical factors' in the process of regeneration project, 'the social factors'(-0.007) shows a downward trend. If the role of social factors and community factors are supported at the beginning step of the urban regeneration project, the physical factors and economic factors are continued to lead a sustainable urban regeneration in the long term.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.1978-1990
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• 2010

This study, centered on public institutions that introduced and are using Knowledge Management System(KMS), is a study of affecting influence factors for utilization and satisfaction. In case of public institutions, they introduced in earnest knowledge management system starting second half of 1999 and most branches of the government such as Department of Defence, Ministry of Government Administration and Home Affairs and Ministry of Planning and Budget have laid the foundation and been managing the system. As a result understanding convenience and need of knowledge management system and awareness for importance of knowledge asset are proliferating. But there is a lot of difference in utilization of KMS by work unit and also can find that the difference exists among users in terms of satisfaction. This is expected as having influence from chief officer's concern, support of exclusively responsible personnel factor, whether education training was given, KM process support etc. for KMS. Therefore this study draws subordinate factors of organization characteristic, knowledge information characteristic, strategy characteristic as influence factors to KMS and analyzes how these subordinate factors influence utilization and satisfaction of KMS to suggest a way to catalyze knowledge management system in the future.

• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.83-91
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• 2018

Purpose - The purpose of this study is to explore the introduction and activation of smart training for the effective training of vocational ability development of companies in the 4th industrial revolution era, we analyze the present status of smart training introduction and related difficulties and propose concrete activation plan. Research design, data, and methodology - Through the online survey, we tried to confirm the recognition of corporate about smart training. Questionnaires include what are the benefits, expectations, and difficulties of smart training, etc. The survey was conducted from August 21, 2017 to September 4, 2017. A total of 69 companies participated in the questionnaire. The questionnaire results were analyzed through frequency analysis and contents analysis. Based on the results of the questionnaire, we found out the cause of inhibition of smart training activation and suggested activation strategies. Results - The main reason for the provision of smart training is the expectation of the training performance and the recognition that it is possible to provide training in a flexible manner. The effectiveness of smart training operation was evaluated as a high level of contribution to the development of creative training course and the capacity of training institute. As a result of checking factors that hinders the activation of smart training, the most important reason is that the time and cost burden of the training institutes is excessive. The lack of expertise in the design of smart training courses and the burden of employers and trainees. Conclusions - In order to activate smart training, it is necessary to find solutions to the obstacles at the internal or external level of training institutions. The internal barriers to the training organization are lack of internal competence for preparation and course management. In this regard, we need to consider providing consulting, best practices or guidance in the process of designing and operating smart training. On the other hand, as an external obstacle factor, it is necessary to provide incentives to participate in smart training. In addition, further research is needed on strategies that can lead to participation in smart training from the viewpoint of employers and learners.