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Effect of Mung Bean Ethanol Extract on Pro-inflammtory Cytokines in LPS Stimulated Macrophages
이석준,Ji Hye Lee,임지영,Han-Hyung Lee,전태훈,Seul Lee,김세헌 한국식품과학회 2011 Food Science and Biotechnology Vol.20 No.2
The anti-inflammatory effect of mung bean ethanol extract on lipopolysaccharide (LPS) stimulated macrophages (J774) was evaluated. The mung bean extract was separated into 5 fractions by normal phase silica gel column chromatography and the mRNA expressions of pro-inflammatory cytokines were examined after incubation with each fraction in LPS stimulated macrophages. All pro-inflammatory cytokines including interleukin (IL)-1β,IL-6, IL-12β, tumor necrosis factor (TNF)-α, and inducible NO synthase (iNOS) were remarkably decreased in the cells treated with 3.7 mg/mL of F3 fraction. The active F3fraction did not show any cytotoxcity according to propidium iodide staining and no inhibitory effects on J774cell proliferation were observed by MTT assay. The active fraction contained gallic acid, vitexin, and isovitexin as major components.
이석준,Lee, Seog-Jun 한국경영정보학회 2003 Asia Pacific Journal of Information Systems Vol.13 No.2
This study was conducted to analyze Korean companie's perception in IT investment cost-benefit analysis(CBA), and to see if various user group's perception is different. Literature was reviewed to classify and define variables in IT CBA, and questionnaire was distributed to CEOs, CIOs, IT managers, and general managers in Korean companies. Respondent's priority ranking in IT CBA was shown to be tangible benefit, direct cost/intangible benefit, and indirect cost/risk. Data analysis showed that Korean companie's actual practice in CBA was generally aligned with their perception. User group's(Executives vs. mangers, and IT managers vs. general managers) perception was not shown to be statistically different. Survey result also showed that IT CBA was not well practiced in the companies although respondents perceive the analysis very important. These findings suggest that more education and practical experience is needed for Korean companies to perform IT CBA.
Syslog 데이터의 의미론적 검색을 위한 XML 기반의 모델링
이석준,신동천,박세권,Lee Seok-Joon,Shin Dong-Cheon,Park Sei-Kwon 한국정보처리학회 2006 정보처리학회논문지D Vol.13 No.2
Event logging plays increasingly an important role in system and network management, and syslog is a de-facto standard for logging system events. However, due to the semi-structured features of Common Log Format data most studies on log analysis focus on the frequent patterns. The extensible Markup Language can provide a nice representation scheme for structure and search of formatted data found in syslog messages. However, previous XML-formatted schemes and applications for system logging are not suitable for semantic approach such as ranking based search or similarity measurement for log data. In this paper, based on ranked keyword search techniques over XML document, we propose an XML tree structure through a new data modeling approach for syslog data. Finally, we show suitability of proposed structure for semantic retrieval. 이벤트 로깅은 시스템 및 네트워크 관리에 있어 그 역할이 증대되고 있으며, syslog는 해당 분야에 있어 사실상의 표준으로 사용되고 있다. 그러나 대부분의 로그 분석은 반구조적 특징을 보이는 로그 형식으로 인하여 빈번히 출현하는 패턴에만 집중하고 있다. XML은 syslog 데이터를 구조화하는 데 있어 유용한 방식을 제공하고 정보 탐색을 용이하게 해 준다. 하지만 이전의 XML 형식들 및 어플리케이션들은 로그 데이터를 위한 순위 기반 검색이나 유사도 측정 등과 같은 의미론적 접근에 적합하지 않다. 본 논문에서는 XML 기반의 순위 키워드 검색 기법을 기초로, 새로운 로그 데이터 모델링을 통해 syslog 데이터를 위한 XML 트리 구조를 제안한다. 그리고 기존의 XML 구조보다 의미론적 검색에 적합함을 보인다.
이석준,HEE CHOON LEE,정영준 한국전산응용수학회 2010 Journal of applied mathematics & informatics Vol.28 No.1
In this paper, we propose a new idea to evaluate the prediction accuracy of user's preference generated by memory-based collaborative filtering algorithm before prediction process in the recommender system. Our analysis results show the possibility of a pre-evaluation before the prediction process of users' preference of item's transaction on the web. Classification functions proposed in this study generate a user's rating pattern under certain conditions. In this research, we test whether classification functions select users who have lower prediction or higher prediction performance under collaborative filtering recommendation approach. The statistical test results will be based on the differences of the prediction accuracy of each user group which are classified by classification functions using the generative probability of specific rating. The characteristics of rating patterns of classified users will also be presented.
선물시장의 시스템트레이딩에서 동적시간와핑 알고리즘을 이용한 최적매매빈도의 탐색 및 거래전략의 개발
이석준,오경주,Lee, Suk-Jun,Oh, Kyong-Joo 한국데이터정보과학회 2011 한국데이터정보과학회지 Vol.22 No.2
국내 정치적 사회적 경제적 요인 및 국제 정치 상황, 해외 경제 동향 등의 요인들을 비롯한 IMF이후의 금융시장 개방에 따른 외국투자자본의 유출입으로 인하여 한국 금융시장의 불확실성은 더욱 증가되었다. 특히 투자자들은 의사결정에 더 많은 혼돈을 겪게 되었고 투자 시 도움을 줄 수 있는 보다 유용한 도구들을 필요로 하게 되었다. 본 연구는 시스템 트레이딩을 이용하여 선물시장에서 거래 할 때 최적의 매매 타이밍을 알아보고 이에 적합한 전략을 알아보는 것이 목적이다. 패턴인식 알고리즘인 동적 시간 와핑 (DTW; Dynamic Time Warping) 알고리즘을 이용하여 빈도별 (10분, 30분, 60분, 일 별) 유사 패턴을 찾아내고 최적의 매매 타이밍을 분석한다. 이를 위해 주식시장의 대표적인 패턴들을 알아보고, 유사한 패턴을 보이는 기간을 DTW를 이용하여 빈도별로 분석한다. 유사한 패턴들의 검증을 위해 기술적 지표들의 개별 전략을 적용한 거래 시뮬레이션을 실시한다. 시뮬레이션 결과 대부분 30분 데이터에 적용된 전략들이 높은 수익률을 가져왔다. The aim of this study is to utilize system trading for making investment decisions and use technical analysis and Dynamic Time Warping (DTW) to determine similar patterns in the frequency of stock data and ascertain the optimal timing for trade. The study will examine some of the most common patterns in the futures market and use DTW in terms of their frequency (10, 30, 60 minutes, and daily) to discover similar patterns. The recognized similar patterns were verified by executing trade simulation after applying specific strategies to the technical indicators. The most profitable strategies among the set of strategies applied to common patterns were again applied to the similar patterns and the results from DTW pattern recognition were examined. The outcome produced useful information on determining the optimal timing for trade by using DTW pattern recognition through system trading, and by applying distinct strategies depending on data frequency.