• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.151-159
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• 2010

Currently, by using the Internet, We can do varius things such as Web surfing, email, on-line shopping, stock trading on your home or office. However, as being out of the concept of security from the beginning, it is the big social issues that malicious user intrudes into the system through the network, on purpose to steal personal information or to paralyze system. In addition, network intrusion by ordinary people using network attack tools is bringing about big worries, so that the need for effective and powerful intrusion detection system becomes very important issue in our Internet environment. However, it is very difficult to prevent this attack perfectly. In this paper we proposed the algorithm for the detection of DoS attacks, and developed attack detection tools. Through learning in a normal state on Step 1, we calculate thresholds, the number of packets that are coming to each port, the median and the average utilization of each port on Step 2. And we propose values to determine how to attack detection on Step 3. By programing proposed attack detection algorithm and by testing the results, we can see that the difference between the median of packet mounts for unit interval and the average utilization of each port number is effective in detecting attacks. Also, without the need to look into the network data, we can easily be implemented by only using the number of packets to detect attacks.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.21-30
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• 2023

The study proposes a model that utilizes Python-based deep learning text classification techniques to detect the legality of illegal financial advertising posts on the internet. These posts aim to promote unlawful financial activities, including the trading of bank accounts, credit card fraud, cashing out through mobile payments, and the sale of personal credit information. Despite the efforts of financial regulatory authorities, the prevalence of illegal financial activities persists. By applying this proposed model, the intention is to aid in identifying and detecting illicit content in internet-based illegal financial advertisining, thus contributing to the ongoing efforts to combat such activities. The study utilizes convolutional neural networks(CNN) and recurrent neural networks(RNN, LSTM, GRU), which are commonly used text classification techniques. The raw data for the model is based on manually confirmed regulatory judgments. By adjusting the hyperparameters of the Korean natural language processing and deep learning models, the study has achieved an optimized model with the best performance. This research holds significant meaning as it presents a deep learning model for discerning internet illegal financial advertising, which has not been previously explored. Additionally, with an accuracy range of 91.3% to 93.4% in a deep learning model, there is a hopeful anticipation for the practical application of this model in the task of detecting illicit financial advertisements, ultimately contributing to the eradication of such unlawful financial advertisements.

• Korea Trade Review
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• v.41 no.5
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• pp.235-254
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• 2016

Recently, enterprise information management activities have been applied to promote electronic trade, while changing the paradigm of cross-border trade and overall trade business processes. L/C, which facilitates payment from the trade transaction in a company, has been able to eliminate the high cost and inefficient element of the trade process by utilizing the electronic letter of credit (e-L/C). This study examines the influential relationship among the e-trade utilizing factor (such as the perceived ease of use and the volition of CEO), the e-L/C and corporate performance, and the study aimed to verify the moderating effect of customer service level by organizations utilizing e-trade. For the purpose of the research, we conducted a survey implementing the e-L/C and analyzed the 338 data collected. The results of this research are as follows. First, the perceived ease of use and volition of CEO have positive impact on the e-L/C. Second, the e-L/C has positive impact on the business performance. Third, a moderating effect shows on the customer expectation level. The main implication of this study is that the perceived ease of use is to be considered preferentially than the volition of CEO in order to utilize electronic trading, and the volition of CEO shows synergy effect with customer service level by organization utilizing e-trade.

• Journal of Korean Home Economics Education Association
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• v.35 no.3
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• pp.169-190
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• 2023

Uzbekistan, one of the top five cotton-producing countries in the world, primarily focuses its textile and fashion industry on raw cotton exports and the sewing industry. For Uzbekistan to achieve high added value, it is essential for the textile and fashion industry, which is currently at the CMT(cut, make, and trim) stage, to upgrade to OEM (original equipment manufacturing), ODM (original design manufacturing), and OBM (original brand manufacturing). South Korea recognizes Uzbekistan as a potential manufacturing base and trading partner and has invested Official Development Assistance (ODA) funds for the development of Uzbekistan's textiles and apparel sector. This study aims to evaluate Uzbekistan's fashion higher education in the context of global competitiveness and measure the need and prospects for education ODA from the Korean government in this field. Comprehensive investigations, including surveys of academics, industry experts, and government officials, in-depth interviews, and focus group interviews, were conducted to understand Uzbekistan's current fashion education environment. According to the research results, despite the textile and fashion sectors playing a pivotal role in the Uzbek economy, there is room for improvement in the curricula and teaching and learning methods of the fashion higher education programs. This study holds significance as foundational data for establishing education ODA strategies.

• Journal of Technology Innovation
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• v.24 no.4
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• pp.277-307
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• 2016

Since 2011, DCF(Discounted Cash Flow) method has been used initiatively for valuating R&D technology assets in the agricultural food industry and recently technology valuation based on royalties comparison among technology transfer transactions has been also carried out in parallel when evaluating the technology assets such as new seed development technologies. Since the DCF method which has been known until now has many input variables to be estimated, sophisticated estimation has been demanded at the time of technology valuation. In addition, considering more similar trading cases when applying sales transaction comparison or industry norm method based on information of technology transfer royalty, it is an important issue that should be taken into account in the same way in the Agri-Food industry. The main input variables used for technology valuation in the Agri-Food industry are life cycle of technology asset, the financial information related to the Agri-Food industry, discount rate, and technology contribution rate. The latest infrastructure building and data updating related to technology valuation has been carried out on a regular basis in the evaluation organization of the Agri-Food segment. This study verifies the key variables that give the most important impact on the results for the existing technology valuation in the Agri-Food industry and clarifies the difference between the existing valuation result and the outcome by referring the support information that is derived through the latest input information applied in DCF method. In addition, while presenting the scheme to complement fragment information which the latest input data just influence result of technology valuation, we tried to perform comparative analysis between the existing valuation results and the evaluated outcome after the latest of reference data for making a decision the input values to be estimated in DCF. To perform these analyzes, it was first selected the representative cases evaluated past in the Agri-Food industry, applied a sensitivity analysis for input variables based on these selected cases, and then executed a simulation analysis utilizing the key input variables derived from sensitivity analysis. The results of this study is to provide the information which there are the need for modernization of the data related to the input variables that are utilized during valuating technology assets in the Agri-Food sector and for building the infrastructure of the key input variables in DCF. Therefore it is expected to provide more fruitful information about the results of valuation.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• KDI Journal of Economic Policy
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• v.32 no.2
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• pp.93-143
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• 2010

This paper estimates the impact of Japan's economic sanction on DPRK trade in the 2000s. It conceptualizes the effects of sanction on DPRK trade, econometrically tests whether such effects exist in case of Japan's sanction using currently available DPRK trade statistics, and measures the size of the effects by correcting and reconfiguring the deficiencies of the currently available DPRK trade statistics. The main findings of the paper are as follows. First, Japan's sanction can have two different effects on DPRK trade: 'Sanction Country Effect' and "Third Country Effect.' The former means that the sanction diminishes DPRK trade with Japan while the latter refers to the effects on DPRK trade with other countries as well. The third country effect can arise not simply because the DPRK changes its trade routes to circumvent the sanction, but because the sanction forces the DPRK to readjust its major trade items and patterns. Second, currently no official DPRK trade statistics are available. Thus, the so-called mirror data referring to DPRK trading partners' statistics should be employed for the analysis of the sanction effects. However, all currently available mirror data suffer from three fundamental problems: 1) they may omit the real trade partners of the DPRK; 2) they may confuse ROK trade with DPRK trade; 3) they cannot distinguish non-commercial trade from commercial trade, whereas only the latter concerns Japan's sanction. Considering those problems, we have to adopt the following method in order to reach a reasonable conclusion about the sanction effect. That is, we should repeat the same analysis using all different mirror data currently available, which include KOTRA, IMF and UN Commodity Trade Statistics, and then discuss only the common results from them. Third, currently available mirror data make the following points. 1) DPRK trade is well explained by the gravity model. 2) Japan's sanction has not only the sanction country effect but also the third country effect on DPRK trade. 3) The third country effect occurs differently on DPRK export and import. In case of export, the mirror statistics reveal positive (+) third country effects on all of the major trade partners of the DPRK, including South Korea, China and Thailand. However, on DPRK import, such third country effects are not statistically significant even for South Korea and China. 4) This suggests that Japan's sanction has greater effects on DPRK import rather than its export. Fourth, as far as DPRK export is concerned, it is possible to resolve the abovementioned fundamental problems of mirror data and thus reconstruct more accurate statistics on DPRK trade. Those reconstructed statistics lead us to following conclusions. 1) Japan's economic sanction diminished DPRK's export to Japan from 2004 to 2006 by 103 million dollars on annual average (Sanction Country Effect). It comprises around 60 percent of DPRK's export to Japan in 2003. 2) However, for the same period, the DPRK diverted its exports to other countries to cope up with Japan's sanction, and as a result its export to other countries increased by 85 million dollars on annual average (Third Country Effect). 3) This means that more than 80 per cent of the sanction country effect was made up for by the third country effect. And the actual size of impact that Japan's sanction made on DPRK export in total was merely 30 million dollars on annual average. 4) The third country effect occurred mostly in inter-Korean trade. In fact, Japan's sanction increased DPRK export to the ROK by 72 million dollars on annual average. In contrast, there was no statistically significant increase in DPRK export to China caused by Japan's sanction. 5) It means that the DPRK confronted Japan's sanction and mitigated its impact primarily by using inter-Korean trade and thus the ROK. Fifth, two things should be noted concerning the fourth results above. 1) The results capture the third country effect caused only by trade transfer. Facing Japan's sanction, the DPRK could transfer its existing trade with Japan to other countries. Also it could change its main export items and increase the export of those new items to other countries as mentioned in the first result. However, the fourth results above reflect only the former, not the latter. 2) Although Japan's sanction did not make a huge impact on DPRK export, it might not be necessarily true for DPRK import. Indeed the currently available mirror statistics suggest that Japan's sanction has greater effects on DPRK import. Hence it would not be wise to argue that Japan's sanction did not have much impact on DPRK trade in general, simply using the fourth result above.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.19
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• pp.224-242
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• 2003

The author believes that the main task of study in international trade usage and practice is the management of transactional risks involved in international sale of goods. They are foreign exchange risks, transportation risks, credit risk, risk of miscommunication, etc. In most cases, these risks are more serious and enormous than those involved in domestic sales. Historically, the merchant adventurers organized the voyage abroad, secured trade finance, and went around the ocean with their own or consigned cargo until around the $mid-19^{th}$ century. They did business faceto-face at the trade fair or the open port where they maintained the local offices, so-called "Trading House"(商館). Thererfore, the transactional risks might have been one-sided either with the seller or the buyer. The bottomry seemed a typical arrangement for risk sharing among the interested parties to the adventure. In this way, such organizational arrangements coped with or bore the transactional risks. With the advent of ocean liner services and wireless communication across the national border in the $19^{th}$ century, the business of merchant adventurers developed toward the clear division of labor; sales by mercantile agents, and ocean transportation by the steam ship companies. The international banking helped the process to be accelerated. Then, bills of lading backed up by the statute made it possible to conduct documentary sales with a foreign partner in different country. Thus, FOB terms including ocean freight and CIF terms emerged gradually as standard trade terms in which transactional risks were allocated through negotiation between the seller and the buyer located in different countries. Both of them did not have to go abroad with their cargo. Instead, documentation in compliance with the terms of the contract(plus an L/C in some cases) must by 'strictly' fulfilled. In other words, the set of contractual documents must be tendered in advance of the arrival of the goods at port of discharge. Trust or reliance is placed on such contractual paper documents. However, the container transport services introduced as international intermodal transport since the late 1960s frequently caused the earlier arrival of the goods at the destination before the presentation of the set of paper documents, which may take 5 to 10% of the amount of transaction. In addition, the size of the container vessel required the speedy transport documentation before sailing from the port of loading. In these circumstances, computerized processing of transport related documents became essential for inexpensive transaction cost and uninterrupted distribution of the goods. Such computerization does not stop at the phase of transportation but extends to cover the whole process of international trade, transforming the documentary sales into less-paper trade and further into paperless trade, i.e., EDI or E-Commerce. Now we face the other side of the coin, which is data security and paperless transfer of legal rights and obligations. Unfortunately, these issues are not effectively covered by a set of contracts only. Obviously, EDI or E-Commerce is based on the common business process and harmonized system of various data codes as well as the standard message formats. This essential feature of E-Commerce needs effective coordination of different divisions of business and tight control over credit arrangements in addition to the standard contract of sales. In a few word, information does not alway invite "trust". Credit flows from people, or close organizational tie-ups. It is our common understanding that, without well-orchestrated organizational arrangements made by leading companies, E-Commerce does not work well for paperless trade. With such arrangements well in place, participating E-business members do not need to seriously care for credit risk. Finally, it is also clear that E-International Commerce must be linked up with a set of government EDIs such as NACCS, Port EDI, JETRAS, etc, in Japan. Therefore, there is still a long way before us to go for E-Commerce in practice, not on the top of information manager's desk.

• Knowledge Management Research
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• v.21 no.3
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• pp.45-65
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• 2020

It is desirable to invest in wine that increases its value, but wine investment itself is unfamiliar in Korea. Also, the process itself is unreasonable, and information is often forged, because pricing in the wine market is done by a small number of people. With the right solution, however, the wine market can be a desirable investment destination in that the longer one invests, the higher one can expect. Also, it is expected that the domestic wine consumption market will expand through the steady increase in domestic wine imports. This study presents the consortium block chain framework for revitalizing the wine market and enhancing transparency as the "right solution" of the nation's wine investment market. Blockchain governance can compensate for the shortcomings of the wine market because it guarantees desirable decision-making rights and accountability. Because the data stored in the block chain can be checked by consumers, it reduces the likelihood of counterfeit wine appearing and complements the process of unreasonably priced. In addition, digitization of assets resolves low cash liquidity and saves money and time throughout the supply chain through smart contracts, lowering entry barriers to wine investment. In particular, if the governance of the block chain is composed of 'chateau-distributor-investor' through consortium blockchains, it can create a desirable wine market. The production process is stored in the block chain to secure production costs, set a reasonable launch price, and efficiently operate the distribution system by storing the distribution process in the block chain, and forecast the amount of orders for futures trading. Finally, investors make rational decisions by viewing all of these data. The study presented a new perspective on alternative investment in that ownership can be treated like a share. We also look forward to the simplification of food import procedures and the formation of trust within the wine industry by presenting a framework for wine-owned sales. In future studies, we would like to expand the framework to study the areas to be applied.

• Journal of Climate Change Research
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• v.4 no.4
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• pp.409-416
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• 2013

Recently, the property damage has been increasing due to climate change in South Korea. While the general public has become more aware of the environmental issues, but the environmental education system has not been able to meet up with the demands of the public. The purpose of this study is to suggest preliminary data which is needed for developing a environmental textbook. A survey was conducted to meet the following requirements. Respondent's level of interest in problems or situations concerning the following eight themes: fundamental science, health and medicine, aerospace engineering, life science, electrical electronics, telecommunication, mineral and energy resources, environment. The data was collected from 139 students in Seoul and Gyeonggi province. The results showed that health and medicine issues interest students the most (49.6%), followed by environment (46.8%). We asked the respondents who were very interested in each question for their reasons, and they answered that environmental issue is related to the improvement of their life quality (53.8%) than their curiosity (38.5%). Students were very interested in the other issues because of just curiosity. Most students (90.6%) said seasonal change was not same each year. 18.0% of respondents replied that they and their friends had experienced climate change. The majority of students (94.2%) thought that they will experience natural disaster blamed on climate change during their life. In other words, climate change is already the day-to-day events of their lives. The majority of their opinions, more then three than ten students(30.9%) said the South Korean government should conduct an energy saving campaign to climate change problems followed by expanding new renewable energy (24.5%), conducting adaptation policies of climate change(22.3 %), introducing of a system as like $CO_2$ emissions trading(20.9%) and so on. There are more Stu- dents (69.1%) who know of new renewable energy than students who don't know it; however, respondents who know the meaning very well were just 18.7% showing that most students dimly know the meaning of new renewable energy.