• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.165-166
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• 2023

물환경정보시스템에서 하천의 수질을 측정한 자료를 대상으로 DMS(Digital Mosquito Monitoring System)가 설치된 위치와 수질 측정지 위치가 가까운 4개 지점에 대한 수질 측정 성분과 모기지수의 연관성을 분석하였다. 수질 기준 외 측정 성분과 모기지수의 상관관계는 총질소(T-N), 용존총질소(TDN), 인산염인이 연관성이 높은 것으로 나타났다. 이 중에서 인산염인은 모기지수와 양적 선형관계를 이루는데, 인산염은 수중에 부영양화를 일으키는 성분 중 하나다. 수질 측정지는 비료의 영향보다는 오수의 유입으로 인산염이 과잉공급되는 것으로 보였다. 따라서 매년 바뀌는 모기지수 산출식의 지연일자 데이터에 부영양화 지수를 넣음으로써 모기지수의 정확도를 보완할 수 있을 것으로 판단된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.315-325
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• 2016

Due to the expansion of data and technical progress in the military industry, it is important to extract meaningful information for assuring quality and making policies. The analysis of trends and decision making based on big data is helpful for increasing productivity in business and finding new business opportunities. We propose an application to collect reliable quality information for munitions and build a big data platform for using the accumulated information and numerical data. We verified the proposed platform using the Test Report Information Service (TRIS) system and suggest a method that utilizes unstructured and semi-structured data accumulated by TRIS. Thus, we expect that the proposed platform will help in building infrastructure for military data, making efficient strategies, and analyzing trends for assuring munitions quality.

• Journal of Information Management
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• v.32 no.1
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• pp.108-119
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• 2001

Creating digital document by scanning paper or using a digital camera or using a computer is a daily task at every office. Digital document is increasing at high pace. The quantity of digital document is almost beyond the maximum capacity of the online storage and is destroying searching efficiency. To solve these problems, we developed a document management system(ChronoStar) by integrating various searching methods(Picture, Full-Text Related), 3D graphic and a DVD changer.

• The Journal of Society for e-Business Studies
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• v.22 no.4
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• pp.71-101
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• 2017

Since late 2016, protectionism has been a major trend in world trade with the Great Britain exiting the European Union and the United States electing Donald Trump as the 45th president. Consequently, there has been a huge public outcry regarding the negative prospects of heavy industry firms in Korea, which are highly dependent upon international trade with Western countries including the United States. In light of such trend and concerns, we have tried to predict business performance of heavy industry firms in Korea with data regarding trade policy of the United States. United States International Trade Commission (USITC) levies countervailing duties and anti-dumping duties to firms that violate its fair-trade regulations. In this study, we have performed data analysis with past records of countervailing duties and anti-dumping duties. With results from clustering analysis, it could be concluded that trade policy trends of the Unites States significantly affects the business performance of heavy industry firms in Korea. Furthermore, we have attempted to quantify such effects by employing long short-term memory (LSTM), a popular neural networks model that is well-suited to deal with sequential data. Our major contribution is that we have succeeded in empirically validating the intuitive argument and also predicting the future trend with rigorous data mining techniques. With some improvements, our results are expected to be highly relevant to designing regulations regarding heavy industry in Korea.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.2
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• pp.33-58
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• 2006

This article deals with the information poverty issue of Korean residents in Japan. In details, it introduces the substantial examples of information poverty which the Korean residents in Japan have experienced in their daily lives, and analyzes the factors causing such information poverty. The focus is on identifying the 'relative' information-poor groups in the Korean community. Finally suggested is a strategic method to improve both the poor information literacy of Korean residents and the poor information environment of Korean community in Japan. The data needed for discussion were collected by two methods a full-scale survey with 532 Korean residents and an in-depth interviews with 24 samples drawn from the survey participants.

• Journal of Digital Contents Society
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• v.18 no.5
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• pp.933-942
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• 2017

In this paper, we propose a web crawler service method for collecting information efficiently about college students and job-seeker's external activities, competition, and scholarship. The proposed web crawler service uses Jsoup tree analysis and Json format data transmission method to avoid problems of duplicated crawling while crawling at high speed. After collecting relevant information for 24 hours, we were able to confirm that the web crawler service is running with an accuracy of 100%. It is expected that the web crawler service can be applied to various web sites in the future to improve the web crawler service.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.907-910
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• 2019

본 연구에서는 X-ray 영상에서 비산란 그리드 장치의 영향으로 인한 아티팩트를 제거하기 위하여 이산코사인변환(DCT: discrete cosine transform) 기반의 주파수 분석 기법과 딥러닝 네트워크의 학습 기법을 상호 보완적으로 결합하는 방법론을 제안한다. 피사체의 특성에 따라 다양하게 나타나는 그리드 라인의 억제 기능을 학습하기 위하여 서로 다른 특성을 반영하는 3 종류의 학습데이터를 생성한다. 학습에 사용되는 그리드 라인 영상의 타겟 데이터를 산출하기 위하여 DCT 기반의 밴드스톱 필터링 기법을 사용하였으며 학습데이터의 양적인 부족을 해결하기 위하여 패치 기반의 학습 방법을 적용하였다. 제안된 방법에 대해 기존의 방법과 비교하여 피사체 경계선 영역에서 발생하는 성능저하 현상, 분할의 가장자리에서 발생하는 블로킹 현상, 배경 영상에서의 성능저하 현상 등을 상대적으로 개선할 수 있음을 실험적으로 평가하였다.

• Database Research
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• v.34 no.3
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• pp.159-169
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• 2018

Discretization of continuous variables intended to improve the performance of various algorithms such as data mining by transforming quantitative variables into qualitative variables. If we use appropriate discretization techniques for data, we can expect not only better performance of classification algorithms, but also accurate and concise interpretation of results and speed improvements. Various discretization techniques have been studied up to now, and however there is still demand of research on discretization studies. In this paper, we propose a new discretization technique to set the cut-point using Wasserstein distance with considering the distribution of continuous variable values with classes of data. We show the superiority of the proposed method through the performance comparison between the proposed method and the existing proven methods.

• The KIPS Transactions:PartD
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• v.14D no.1 s.111
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• pp.35-44
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• 2007

Recently, an increasing in quantity of multimedia data have brought a new problem that expected data should be retrieved fast and exactly. The adequate representation for the multimedia data is the key element for efficient retrieval. For this reason, MPEG-7 standard was established for description of multimedia data. In this paper, we propose a new approach to metadata production. The user can decompose a given content into units and easily annotate each unit by adding basic Information such as time, place, etc. as well as classification information such as event, relationship, etc. according to the MPEG-7 standard. The objective is to build automatically a pure semantic description; the nodes are the events and the links are the graphs which describe the relationships among the events. Finally, we have implemented an annotation tool(SMAT) for semantic description based on proposed technique and assess some of the experiment results. In conclusion, we ran say that the proposod annotation tool is characterized by two important proprieties : reusability and extendibility.

• The Journal of the Korea Contents Association
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• v.12 no.1
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• pp.17-29
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• 2012

In recent years, Linked Data that is published under an open license shows increased growth rate and comes into the spotlight due to its interoperability and openness especially in government of developed countries. However there are relatively few out-links compared with its entire number of links and most of links refer a few hub dataset. These occur because of absence of technology that identifies entities in Linked data. In this paper, we present an improved author entity resolution method that using representative properties. To solve problems of previous methods that utilizes relation with other entities(owl:sameAs, owl:differentFrom and so on) or depends on Curation, we design and evaluate an automated realtime resolution process based on multi-ontologies that respects entity's type and its logical characteristics so as to verify entities consistency. The evaluation of author entity resolution shows positive results (The average of K measuring result is 0.8533.) with 29 author information that has obtained confirmation.