• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.61-71
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• 2009

The server redirection system replicates contents on replica servers in the distributed network environment. When users make a request for contents, the system can provide the contents much faster than the client-server network system. In the server redirection system, it is the most important to select the optimal replica server with user's information because many replica servers are geographically distributed. And, the system can serve contents to users flexibly if a redirector is well constructed. In this paper, the redirector makes a list of candidates suitable for user conditions by the decision tree method and calculates the availability of each replica server. And, the redirector selects the replica server with the highest availability. This paper also proposes an availability-based server redirection system that predicts the availability of each replica server in order to reduce the workload of replica servers and the repetitive communication messages between a redirector and replica servers. If a user accesses the network path for the replica server selected and noticed by the proposed system, the user can get contents effectively and efficiently.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.

• Journal of Arbitration Studies
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• v.17 no.2
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• pp.101-124
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• 2007

The legal systems and open-door policies to foreign affairs in North Korea have been followed by those of China. Whereas an arbitration system of South Korea accepted most parts of UNCITRAL Model Law, North Korea has succeeded to an arbitration system of a socialist country. China, under the arbitration system of socialist country, enacted an arbitration act reflected from UNCITRAL Model Law for keeping face with international trends. We have used these three arbitration system as a tool for analyzing an arbitration system in North Korea. With an open-door policy, North Korea and China enacted an arbitration act to provide a legal security. Therefore, the core parts of arbitration system in North Korea and China are based on a socialist system while those of South Korea is on liberalism. So, North Korea and China enacted an arbitration act on the basis of institutional arbitration, on the other side, South Korea is based on ad-hoc arbitration. Because of these characters, in terms of party autonomy, it is recognized with the order as South Korea, China and North Korea. Also North Korea enacted separate 'Foreign Economic Arbitration Act' to resolve disputes arising out of foreign economies including commercial things and investments. There are differences in arbitration procedures and appointment of arbitrators : South Korea recognizes parties' autonomy, however parties should follow the arbitration rules of arbitration institutes in North Korea and China. According to an appointment of arbitrators, if parties fail to appoint co-arbitrators or chief arbitrators by a mutual agreement, the court has the right to appoint them. In case of following KCAB's rules, KCAB secretariats take a scoring system by providing a list of candidates. A party has to appoint arbitrators out of the lists provided by arbitration board(or committee) in North Korea. If a party may fail to appoint a chief arbitrator, President of International Trade Arbitration Board(or Committee) may appoint it. In China, if parties fail to appoint a co-arbitrator or a chief arbitrator by a mutual agreement, Secretary general will decide it. If a arbitral tribunal fails to give a final award by a majority decision, a chief arbitrator has the right for a final decision making. These arbitration systems in North Korea and China are one of concerns that our companies take into account in conducting arbitration procedures inside China. It is only possible for a party to enforce a final arbitral award when he applies an arbitration inside North Korea according to International Trade Arbitration Act because North Korea has not joined the New York Convention. It's doubtful that a party might be treated very fairly in arbitration procedures in North Korea because International Trade Promotion Commission controls(or exercises its rights against) International Trade Arbitration Commission(or Board).

• Information Systems Review
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• v.25 no.1
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• pp.189-212
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• 2023

This study uses various methods, including media analysis, expert interviews, and large-scale surveys, to derive notable digital business trends in 2023. Most trend studies have yet to deal with digital business trends in Korea. They also often have limitations in the objectivity of the results using unclear methods. On the other hand, this study emphasizes the validity of the results by collecting opinions from Korean digital business experts in various fields. First, Korean IT news articles were collected and analyzed through topic modeling analysis. Then, based on the results, interviews were conducted with 13 academic and industrial experts to derive 16 IT business trend candidates. Then, a survey was conducted on 210 experts to finalize the list of Korean IT business trends. Finally, to compare overseas and domestic views, we conducted an additional survey using the items developed by the Society for Information Management, SIM. This study is meaningful in that it drew prospects for digital business trends in consideration of the domestic business environment by scientifically converging various opinions of Korean digital business leaders. Our study contributes to developing strategies for IT technology and IT service business markets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.692-700
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• 2016

The study proposed a strategy for supporting North Korea's SOC construction in the future by reviewing domestic and foreign cases. According to the literatureanalysis, we developed a candidate list of technology for SOC of North Korea in terms of Construction Management / economy sectors. The category is North Korea SOC construction support, and the sub-category is North Korea SOC construction support program. The implementation procedures included the following six steps: Preparation, Support for Establishing Construction Industry Base, Support for Establishing Business Management Base, Support for HR Management Base, Business Model Establishment/Expansion, and Monitoring of Management Result. Lastly, we developed twenty-five candidates of detailed technology. In the future, it is necessary to decide a methodology for project implementation by each scenario after selecting a study area, and to develop a more specified scenario.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.1
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• pp.43-59
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• 2022

Electronic public records are classified simultaneously as production, a preservation period is granted, and after a certain period, they are transferred to an archive and preserved. This study intends to find a way to improve the efficiency in classifying transferred records and maintain consistent standards. To this end, the current record classification work process carried out by the National Archives of Korea was analyzed, and problems were identified. As a way to minimize the manual work of record classification by converging the required improvement, the process of identifying outlier candidates based on a list consisting of classified information of the transferred records was proposed and systemized. Furthermore, the proposed outlier discrimination process was applied to the actual records transferred to the National Archives of Korea. The results were standardized and constructed as a training data format that can be used for machine learning in the future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.108-126
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• 2013

Recently, it becomes essential for firms or nations to forecast the future and identify emerging technologies in order to improve R&D efficiency and gain a competitive advantage. Particularly, the mobile communications industry is characterized by rapid advance and wide application of its technology and thus identifying emerging technologies is more important in the industry than in others. Nevertheless, few attempts have been made to explore its emerging technologies. Therefore, this research aims to develop a methodology to identify the future and emerging technologies especially for the industry and applied it to list top ten emerging technologies for 2020 in the industry. For this purpose, firstly, we focused the key issues in the future targeting 2020 and identified user needs relating to them. Then, candidates of emerging technologies were defined from a set of technologies to meet the needs, for which technological and economic feasibility is assessed to determine their priorities. Finally, the top ten most important technologies were selected and verified. This research is distinct from the previous studies in that it takes a market-pull approach instead of a technology-push approach. The research results are expected to provide valuable information to support strategy- and policy-makings in the mobile communications industry.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

• Korean Journal of Heritage: History & Science
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• v.49 no.1
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• pp.22-43
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• 2016

State Ownership of Excavated Cultural Heritage System was originated from the legislations concerning cultural objects during the Japanese colonial period (1910~1945) and was succeeded by the present Buried Cultural Properties Act enacted in 2011. Despite the importance of the system that completes the outcomes of excavations and determines the state-owned cultural properties, the foundation of national heritage, it has been limitedly regarded as administrative area and neglected by the academic scholars or policy researchers. Recently the traditional culture has drawn increasing domestic interest and awareness that the cultural heritage contributes to building cultural identity and vitalizing tourism has led to increasing the demand of a local government's role in management of the state-designated cultural heritage and even fighting for hegemony in securing the cultural objects between the central and local governments. Despite the continuing efforts for improving the selection process of cultural heritage and its management institution, establishment of an advanced objective system has been requested. This paper is intended to suggest the policy direction through demonstrating the problem and assignment caused in the process of implementing the Buried Cultural Properties Act and reviews the State Ownership of Excavated Cultural Heritage System from the legal point of view accordingly. First, I suggest improving the selection process of the state-owned cultural properties. Even though current law states that Administrator of Cultural Heritage Administration reviews the research reports and selects the possible candidates for the state-owned cultural properties almost all the cultural objects listed on the reports are practically selected. In this regard, two possible resolutions can be made; newly establishing a separate process for selecting the state-owned cultural properties after publishing the report or adding the selection process of the state-owned cultural properties during the heritage selection meeting. Either way should contribute to strengthening the impartiality and objectivity of the policy. My second suggestion is improving the operating system of the heritage selection meeting in which the cultural properties to be listed on the reports are determined. Given the present extensive assessment criteria, there is much room for certain experts' subjective opinions. Therefore, in order to enhance the fairness and credibility of the heritage selection meeting, specifying the assessment criteria and advance review of the expert list are necessary. Third, this paper suggests increasing the local government's role in management of the state-owned cultural heritage and diversifying the heritage management institution. Development of a local self-governing system has led to the increased demand for delegating the authority of the state-owned heritage management to the local governments. Along with this, the gradual improvements of public museum management raises the need for expanding the cultural benefits through increasing the local government's role in management of the state-owned heritage. Considering the fact that overall majority of the art collections housed at national or public museums is owned by the central government, developing a variety of heritage contents and vitalizing the heritage tourism are crucial. The true meaning and value of the state-owned cultural heritage hidden at the storage of a museum can be found when they are shared together with the public.

• Journal of Life Science
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• v.30 no.9
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• pp.804-812
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• 2020

The giant mealworm beetle, Zophobas atratus (Coleoptera: Tenebrionidae) has been used as a protein source for small pets and mammals. Recently, it was temporarily registered in the list of the Food Code. We previously performed an in silico analysis of the Zophobas atratus transcriptome to identify putative antimicrobial peptides and identified several antimicrobial peptide candidates. Among them, we assessed the antimicrobial and anti-inflammatory activities of zophobacin 1 that was selected bio-informatically based on its physicochemical properties against microorganisms and mouse macrophage Raw264.7 cells. Zophobacin 1 showed antimicrobial activities against microorganisms without inducing hemolysis and decreased the nitric oxide production of the lipopolysaccharide-induced Raw264.7 cells. Moreover, ELISA and Western blot analysis revealed that zophobacin 1 reduced expression levels of pro-inflammatory enzymes such as inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2). We also investigated expression of pro-inflammatory cytokines (interleukin-6 and interleukin-1β) production through quantitative real time-PCR and ELISA. Zophobacin 1 markedly reduced the expression level of cytokines through the regulation of mitogen-activated protein kinases (MAPKs) and nuclear factor kappa B (NF-κB) signaling. We confirmed that zophobacin 1 bound to bacterial cell membranes via a specific interaction with lipopolysaccharides. These data suggest that zophobacin 1 could be promising molecules for development as antimicrobial and anti-inflammatory therapeutic agents.