• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.26-35
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• 2011

In these days, internet environment are very quickly development as well on-line service have been using a online for the mission critical business around the world. As the amount of information to be processed by computers has recently been increased there has been cluster computing systems developed by connecting workstations server using high speed networks for high availability. but cluster computing technology are limited for a lot of IT resources. So, grid computing is an expanded technology of distributed computing technology to use low-cost and high-performance computing power in various fields. Although the purpose of Grid computing focuses on large-scale resource sharing, innovative applications, and in some case, high-performance orientation, it has been used as conventional distributed computing environment like clustered computer until now because grid middleware does not have common sharable information system. In order to use grid computing environment efficiently which consists of various grid middleware, it is necessary to have application-independent information system which can share information description and services, and expand them easily. This paper proposed new database architecture and load balancing for high availability through Grid technology.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1593-1601
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• 2017

In a big data platform, association rule mining applications could bring some benefits. For instance, in a agricultural big data platform, the association rule mining application could recommend specific products for farmers to grow, which could increase income. The key process of the association rule mining is the frequent itemsets mining, which finds sets of products accompanying together frequently. Former researches about this issue, e.g. Apriori, are not satisfying enough because huge possible sets can cause memory to be overloaded. In order to deal with it, SON algorithm has been proposed, which divides the considered set into many smaller ones and handles them sequently. But in a single machine, SON algorithm cause heavy time consuming. In this paper, we present a method to find association rules in our Hadoop based big data platform, by parallelling SON algorithm. The entire process of association rule mining including pre-processing, SON algorithm based frequent itemset mining, and association rule finding is implemented on Hadoop based big data platform. Through the experiment with real dataset, it is conformed that the proposed method outperforms a brute force method.

• Journal of Information Management
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• v.41 no.4
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• pp.227-249
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• 2010

Scholarly information has increased tremendously according to the development of IT, especially the Internet. However, simultaneously, people have to spend more time and exert more effort because of information overload. There have been many research efforts in the field of expert systems, data mining, and information retrieval, concerning a system that recommends user-expected information items through presumption. Recently, the hybrid system combining a content-based recommendation system and collaborative filtering or combining recommendation systems in other domains has been developed. In this paper we resolved the problem of the current recommendation system and suggested a new system combining collaborative filtering and Naive Bayes Classification. In this way, we resolved the over-specialization problem through collaborative filtering and lack of assessment information or recommendation of new contents through Naive Bayes Classification. For verification, we applied the new model in NDSL's paper service of KISTI, especially papers from journals about Sitology and Electronics, and witnessed high satisfaction from 4 experimental participants.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.456-467
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• 2018

This study analyzed the repeated causes of policy failure focusing on Yangyang International Airport cases. Yangyang International Airport, which opened in 2002, was built with about 360 billion won, but it is considered as a representative example of policy failure of local airports. According to the policy failure theory, the failure factors of Yangyang International Airport are anlyzed by rationalistic, political, and environmental complexity viewpoint. The results are as follows. First, from a rationalist point of view, Yangyang Airport failed to achieve the policy goal of securing passengers and revitalizing local economy, This is due to the pressure of politics and the lack of geographical infrastructure. Second, the failure of the stakeholders to resolve conflicts in the flow of politics can be seen as the conflict between the airline and the airport, and the failure to reconcile conflicts between the government and the airports on the low cost airline permits and subsidies. Third, from the viewpoint of environmental complexity, Yangyang International Airport can be regarded as a failure to adapt to environmental changes such as the opening of nearby expressways and railway lines, and the sharp decline of Chinese tourists. This study sugeests the establishment of an independent organization that can prevent unreasonable business promotion by politics in the case of large scale national projects, the linkage with the surrounding infrastructure and related businesses in the case of transportation facilities such as airports and railways, and institutionalization of cooperative governance for coordinating conflict among stakeholders.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.121-129
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• 2021

In this study, we try to minimize the tariff risk by constructing a hazardous cargo screening model by applying Association Rule Mining, one of the data mining techniques. For this, the risk level between supply chains is calculated using the Apriori Algorithm, which is an association analysis algorithm, using the big data of the import declaration form of the Korea Customs Service(KCS). We perform data preprocessing and association rule mining to generate a model to be used in screening the supply chain. In the preprocessing process, we extract the attributes required for rule generation from the import declaration data after the error removing process. Then, we generate the rules by using the extracted attributes as inputs to the Apriori algorithm. The generated association rule model is loaded in the KCS screening system. When the import declaration which should be checked is received, the screening system refers to the model and returns the confidence value based on the supply chain information on the import declaration data. The result will be used to determine whether to check the import case. The 5-fold cross-validation of 16.6% precision and 33.8% recall showed that import declaration data for 2 years and 6 months were divided into learning data and test data. This is a result that is about 3.4 times higher in precision and 1.5 times higher in recall than frequency-based methods. This confirms that the proposed method is an effective way to reduce tariff risks.

• International Area Studies Review
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• v.22 no.3
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• pp.293-317
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• 2018

In the era of glocalization, the role of the state is gradually being reduced and the roles of cities and regions are becoming more critical, especially for the everyday life of residents. Many attempts have been made to secure regional competitiveness based on local identity, to differentiate it from other cities and regions, and to search for methods of sustainable development. The importance of place, which affects human life-world, is getting to garner more attention whereas the large-scale development-centered approach has becoming less prominent. The objective of the study is to investigate the concept of place-making and to apply for the East Asian regions, which seems to be differentiated from urban cultural frameworks of the West. The paper employs comparative methodology for the placemaking strategies of the three case locations, say Mok-dong in Seoul, Koganecho in Yokohama and red town in Shanghai. By through examining the three stages of place-making for each three place, it reveals that cultural identity is quintessential in the East-Asian region. In conclusion, it suggests a sustainable place-making strategies for urban areas in East-Asian regional setting.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.531-540
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• 2021

As cyber attacks and crimes increase exponentially and hacking attacks become more intelligent and advanced, hacking attack methods and routes are evolving unpredictably and in real time. In order to reinforce the enemy's responsiveness, this study aims to propose a method for developing an artificial intelligence-based security control platform by building a next-generation security system using artificial intelligence to respond by self-learning, monitoring abnormal signs and blocking attacks.The artificial intelligence-based security control platform should be developed as the basis for data collection, data analysis, next-generation security system operation, and security system management. Big data base and control system, data collection step through external threat information, data analysis step of pre-processing and formalizing the collected data to perform positive/false detection and abnormal behavior analysis through deep learning-based algorithm, and analyzed data Through the operation of a security system of prevention, control, response, analysis, and organic circulation structure, the next generation security system to increase the scope and speed of handling new threats and to reinforce the identification of normal and abnormal behaviors, and management of the security threat response system, Harmful IP management, detection policy management, security business legal system management. Through this, we are trying to find a way to comprehensively analyze vast amounts of data and to respond preemptively in a short time.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.567-575
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• 2021

Residents in Dangjin, South Chungcheong Province, in which large-scale emissions facilities such as coal-fired power plants and steel mills are concentrated, are very much concerned about their health despite the local government's aggressive efforts to improve air quality and reduce greenhouse gases. To understand the impact of coal-fired power plants and external factors on local air pollution, the origins of local pollutants were investigated using stable carbon isotopes that are generally used as tracers of the provenance of fine or ultrafine dust. The origins of the pollutants were analyzed with the data library, built using the seasonally measured data for the two separate locations selected considering the distance from the coal-fired power plant and the analysis of previous studies, and with the back trajectory analysis. As a result of analyzing stable isotope ratios, the tendency of high concentration was found in the order of winter > spring > fall > summer. According to the data matching with the library, the mobile pollutants and open-air incineration had a relatively higher impact on the local air pollution. It is believed that this study, as a pilot study, should focus on securing the reliability of the study results through continuous monitoring and data accumulation.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.147-161
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• 2021

Through photogrammetry techniques, what current researches can achieve at present is rough 3D mesh and color map of objects, rather than usable photo-realistic 3D assets. This research aims to propose a new method to create photo-realistic 3D assets that can be used in the field of visualization applications. The new method combines photogrammetry with computer graphics modeling. Through the description of the production process of three objects in the real world - "Bullet Box", "Gun" and "Metal Beverage Bottle," it introduces in details the concept, functions, operating skills and software packages used in the steps including the photograph object, white balance, reconstruction, cleanup reconstruction, retopology, UV unwrapping, projection, texture baking, De-Lighting and Create Material Maps. In order to increase the flexibility of the method, alternatives to the software packages are also recommended for each step. In this research, 3D assets are produced that are accurate in shape, correct in color, easy to render and can be physically interacted with dynamic lighting in texture. The new method can obtain more realistic visual effects at a faster speed. It does not require large-scale teams, expensive equipment and software packages, therefore it is suitable for small studios and independent artists and educational institutions.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.81-88
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• 2022

This study is to investigate the perception of domestic appraisers about the possibility of using artificial intelligence (AI) and related risks from the use of AI in the appraisal industry. We conducted a mobile survey of evaluators from February 10 to 18, 2022. We collected survey data from 193 respondents. Frequency analysis and multiple response analysis were performed for basic analysis. When AI is used in the appraisal industry, factor analysis was used to analyze various types of risks. Although appraisers have a positive perception of AI introduction in the appraisal industry, they considered collateral, consulting, and taxation, mainly in areas where AI is likely to be used and replaced, mainly negative effects related to job losses and job replacement. They were more aware of the alternative risks caused by AI in the field of human labor. I was very aware of responsibilities, privacy and security, and the risk of technical errors. However, fairness, transparency, and reliability risks were generally perceived as low risk issues. Existing studies have mainly studied analysis methods that apply AI to mass evaluation models, but this study focused on the use and risk of AI. Understanding industry experts' perceptions of AI utilization will help minimize potential risks when AI is introduced on a large scale.