• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.113-130
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• 2011

Due to the development of information and communication technology, the global influence on politics, economics, society, and culture has grown. A major example of this impact on the economic sector is the growth of e-commerce, which increases both the speed and efficiency of businesses. In light of these new developments, businesses need to shift away from the misconception that information overwhelms to embrace the enhanced competitiveness that e-commerce provides. However, concern about fraudulent transactions through e-commerce is pertinent because of the loss in both critical revenue and consumer confidence in open markets. Current solutions for fraudulent transactions include real-time monitoring and processing, payment pending, and confirmation through SMS, E-mail, and other wired means. Our research focuses on the management of Fraud Detection Systems (FDS) to safeguard online electronic payment systems. With effective implementation of our research we hope to foster an honorable online trading culture and protect consumers. Future comparative research in domestic and abroad markets would provide further insight into preventing fraudulent transactions.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.851-858
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• 2021

Due to the increase in renewable energy and distributed resources, not only traditional data but also various energy-related data are being generated in the new energy industry. In other words, there are various renewable energy facilities and power generation data, system operation data, metering and rate-related data, as well as weather and energy efficiency data necessary for new services and analysis. Energy big data processing technology can systematically analyze and diagnose data generated in the first half of the power production and consumption infrastructure, including distributed resources, systems, and AMI. Through this, it will be a technology that supports the creation of new businesses in convergence between the ICT industry and the energy industry. To this end, research on the data analysis system, such as itemized characteristic analysis of the collected data, correlation sampling, categorization of each feature, and element definition, is needed. In addition, research on data purification technology for data loss and abnormal state processing should be conducted. In addition, it is necessary to develop and structure NIFI, Spark, and HDFS systems so that energy data can be stored and managed in real time. In this study, the overall energy data processing technology and system for various power transactions as described above were proposed.

• 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 Arbitration Studies
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• v.12 no.1
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• pp.271-321
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• 2002

Every year, many million of business transactions take place. Ocassionally, disagreements develop over these business transactions. Many of these disputes are resolved by mediation, arbitration and out-of-court settlement options. The American Arbitration Association(AAA) helps resolve a wide range of disputes through mediation, arbitration, elections and other out-of-court settlement procedures. The AAA offers a broad range of dispute resolution services to business executives, attorneys, individuals, trade associations, unions, management, consumers, families, communities, and all level of governments. The 198,491 cases composed of the 194,303 arbitration cases and the 4,188 mediation cases, were filed with the AAA in 2000. These case filings represent a full range of matters, including commercial finance, construction, labor and employment, environmental, health care, insurance, real state, securities, and technology disputes. The Korean Commercial Arbitration Board (KCAB) does more than render arbitration services. It helps facilitate settlements and guarantee implementation thereof between trading partners at home and abroad involving disputes related to such areas as the sale of commodities, construction, joint venture agreements, technical assistance, agency agreements, and maritime transport. The 643 cases composed of the the 197 arbitration cases and the 446 mediation cases, were filed with the KCAB in 2001. There are some differences between the AAA and the KCAB regarding the number and the area of mediation and arbitration case filings, the breath of service offerings, the scope of alternative dispute resolution, and the education and training. In order to apply to the proceedings of the commercial mediation and arbitration, the AAA has the Commercial Mediation Rules, the Commercial Arbitration Rules, the Expedited Procedures, the Optional Procedures for Large, Complex Commerical Dispute, and the Optional Rules for Emergency Measures of Protection as amended and effective on September 1, 2000. In order to apply to the proceedings of commercial arbitration, the KCAB has the Arbitration Rules as amended by the Supreme Court on April 27, 2000, which have been changed to incorporate the revisions of the Arbitration Act that went into effect on December 31, 1999. There are some differences between the AAA's commercial Arbitration Rules and the KCAB's Arbitration Rules regarding the clauses of jurisdiction and administrative conference, number of arbitrators, communication with arbitrator, vacancies, preliminary hearing, exchange of information, oaths, evidence by affidavit and posthearing filing of documents or others, interim measures, serving of notice, form of award, scope of award, delivery of award to parties, modification of award, release of liability, administrative fees, neutral arbitrator's compensation, and expedited procedures. In conclusion, for the vitalization of KCAB and its ADR system, the following measures should be taken : the effective case management, the development of on0-line ADR, the establishment of ADR system of electronic commerce disputes, and the variety of dispute resolution rules in each expert field.

• International Commerce and Information Review
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• v.3 no.2
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• pp.1-16
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• 2001

This study discusses some theoretical implications for efficient utilization of the global E-commerce in a world of uncertainty by beginning with measures of risk and return for the global E-commerce, and by moving to risk and return for a efficient transaction portfolio of many risky methods of transaction. Decision rules are developed to show how individuals choose optimal transaction portfolios that maximize their expected utility of wealth. First, the individuals will generally want to allocate positive amount to the global E-commerce, which requires that the expected marginal utility of wealth equals zero. Secondly, the optimal transaction portfolio will be determined by finding the point of tangency between the efficient trading line and the hightest indifference curve in the mean-variance plane. Thirdly, if the global E-commerce is positively correlated with wealth, it must have an expected return that is higher than the risk-free transaction methods in order to compensate for its risk. Fourthly, on the other hand, if the global E-commerce is negatively correlated with wealth, it will have an expected return that is less than the risk-free transaction methods. Finally, the valuation of global E-commerce depends on the degree of individual's risk aversion and the covariance between the expected return of total wealth and the return of global E-commerce.

• Information Systems Review
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• v.4 no.2
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• pp.191-208
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• 2002

In the area of new millennium of twenty first century, one of the urgent and critical research issues in commerce area is the regenerating of new business opportunities from the high value added perspectives. With this motivation, in this paper, we create new on-line e-businesses with the speed of lightning their affiliated supply, finance and business communities - which are involved in more and more tightly connected, open trading - we find that we need to deal with hundreds of business collaborative partners, millions of buyers and sellers while we have to face incompatible IT systems. Challenges of new business opportunities linking multi-enterprise data and processes cost effectively, reliably and securely in real time remains an open area in e-business. This challenge we shall describe as the problem of synchronization of multiple enterprise collaborative e-business opportunities (production related), value (finance related), business (operations related) in new business opportunity and infrastructure integrated all together over the off-line and online basis. It brings a new e-commerce opportunities infrastructure into this profitable challenge: by extracting and tracking new business information, new trends in the events of e-business processes. The transformation of the traditional commerce into this type of electronic based commerce can be interpreted as new Cultural Revolution. The revolution will be a new paradigm crossing over the geographical, and organizational zone, restructuring enterprise business process infrastructure.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.204-208
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• 2018

In this paper, we proposed and evaluated the time series deep learning prediction model for learning fluctuation pattern of stock price. Recurrent neural networks, which can store previous information in the hidden layer, are suitable for the stock price prediction model, which is time series data. In order to maintain the long - term dependency by solving the gradient vanish problem in the recurrent neural network, we use LSTM with small memory inside the recurrent neural network. Furthermore, we proposed the stock price prediction model using bidirectional LSTM recurrent neural network in which the hidden layer is added in the reverse direction of the data flow for solving the limitation of the tendency of learning only based on the immediately preceding pattern of the recurrent neural network. In this experiment, we used the Tensorflow to learn the proposed stock price prediction model with stock price and trading volume input. In order to evaluate the performance of the stock price prediction, the mean square root error between the real stock price and the predicted stock price was obtained. As a result, the stock price prediction model using bidirectional LSTM recurrent neural network has improved prediction accuracy compared with unidirectional LSTM recurrent neural network.

• Journal of the Korean association of regional geographers
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• v.4 no.1
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• pp.57-76
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• 1998

Yanji(延吉) city is the district seat of the Yanbian(延邊) Korean Autonomous District where is located in the Jilin(吉林) Province in China, and also the largest city with a population of three hundred sixty thousand, Since the mid-1980s, the inter-exchange and cooperation between Yanbian District and South Korea has been increased rapidly. That draw many scholars' attention to studying Yanbian District and Korean Chinese as a research theme for area studies. Unfortunately they neglect the study of the commerce and service industry in Yanbian city, which has indicated its rapid growth by the market economic policy of China, and an inter-exchange between Korean Chinese and Korean. The purpose of this study is to provide an information to many Korean potential investors for an investment strategy of the commerce and service industry in Yanji city. In order to do so, this study consists of three major steps. First of all. we analyzed the regional structure and locational characteristics of the commerce and service industry in Yanji City. Secondly, we investigated the characteristics of consumers behavior toward purchasing goods and service facilities. Finally, we supplied the proper businesses and location information for investment to Korean firms according to the results that identified above. In conclusion, we suggest that the proper businesses to invest are department store, retail clothing store, shoes store, cosmetics store, electronics and home appliances store, oversea branch offices of trading companies, Korean-style restaurant, hotel, nightclubs, Korean-style music room(Noraebang), travel agencies, beauty parlors, video rooms, electronic games, and so on. We also suggest that the proper locational areas to invest those businesses are the core area of the commerce and service industry in Yanji, where are Xinxing(新興) 3-zone and Jinxue(進學) 2-zone expressed in the Yanji city figure.

• Information Systems Review
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• v.22 no.1
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• pp.59-72
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• 2020

Artificial Intelligence is establishing itself as a familiar tool from an intractable concept. In this trend, financial sector is also looking to improve the problem of existing system which includes Fraud Detection System (FDS). It is being difficult to detect sophisticated cyber financial fraud using original rule-based FDS. This is because diversification of payment environment and increasing number of electronic financial transactions has been emerged. In order to overcome present FDS, this paper suggests 3 types of artificial intelligence models, Generative Adversarial Network (GAN), Deep Neural Network (DNN), and Convolutional Neural Network (CNN). GAN proves how data imbalance problem can be developed while DNN and CNN show how abnormal financial trading patterns can be precisely detected. In conclusion, among the experiments on this paper, WGAN has the highest improvement effects on data imbalance problem. DNN model reflects more effects on fraud classification comparatively.

• International Commerce and Information Review
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• v.13 no.4
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• pp.51-79
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• 2011

Korea has accomplished the establishment of the National Single Window for Paperless Trade. Since 1991, it has developed Trade Automation Service System based on EDI technology. In 2003, Korean government and private sectors jointly began to set up National Paperless Trade Service( e-Trade Service) as one of the e-government projects. In 2008, they commenced the uTradeHub Service which was equipped with Internet based e-B/L and e-Nego service systems for the first time in the world To facilitate the service Korea amended its e-Trade facilitation Act and Law by 2007. At the end of 2011, Korea historically recorded its trade volume of 1 trillion US dollars and joined '$1 trillion trade club' as the 9the member country since the country had started international trade less than five decades ago. A rolling out of the e-B/L and e-Nego service will 'ally reduce the transaction costs of trading businesses and accelerate the activation e-trade services. The purposes of the study are to examine 'e-B/L Korea' service and its facilitation strategies as well as identify obstacles to utilize the 'e-B/L Korea' service. The paper reviewed and analyzed Korea's Paperless trade system and distinctive characteristics of the 'e-B/L Korea Service. Parts of the fOWld distinctive characteristics of the Korea's e-B/L service are as follows; It is well equiped with IT and legal system. It also has more that 30,000 potential users who are already uTradeHub service users. The paper indicated several weaknesses of the current system such as global KPI issues, circulation of the electronic documents not only in the domestic market but also among economies, development of the electronic Bill of Exchange. As resolution measures, the paper recommended the introduction of mutual recognition system of PKI among trade partner counties, setting up e-trade solution for small and medium companies, and special attention to raise users' awareness of the e-B/L service.