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강원,경북지역 낙엽송 지위지수 적합성 평가에 관한 연구
이대성 ( Dae Sung Lee ),이의섭 ( Eui Sub Lee ),최종현 ( Jong Hyun Choi ),서영완 ( Yeong Wan Seo ),최정기 ( Jung Kee Choi1 ) 한국임학회 2014 산림과학 공동학술대회 논문집 Vol.2014 No.-
본 연구는 강원 및 경북지역의 낙엽송 지위지수의 적합도를 평가하기 위해 실시되었다. 연구자료는 강원 및 경북지역의 45개 낙엽송 인공림 표준지 조사로부터 우세목 1본을 선발하여 수간석 해를 통해 분석되었다. 산림청에서 개발된 지위지수표에 의거하여 본 연구대상지의 지위지수를 산정한 결과, 지위지수가 18 이하로 낮은 지역은 8곳(18%)이었으며, 지위지수가 20 이상으로 우수한 지역이 37곳(82%)으로서 대부분 지역에서 지위지수가 우세하였다. 지위지수곡선의 적합도를 평가하기위해 수간석해목의 과거에서 현재까지의 수고생장에 따른 지위지수의 변화를 도시한 결과, 초기 임령 때 지위지수와 차이가 없는 곳은 단지 8지역(18%)이었으며, 지위지수가 2∼4 m 차이가 발생한 지역이 19곳(42%), 6 m 이상 발생한 지역이 18곳(40%)으로 나타났다. This study was performed to evaluate the compatibility of site index for Larix kaempferi in Gangwon and Kyeongbuk regions. The data were collected and analyzed from stem alalysis of one dominant tree at each of 45 permanent plots installed in the regions. The result of site index estimation following the site index table developed by Korean Forest Service (KFS) showed that 8 plots (18%) were less than site index 18 and 37 plot (82%) greater than site index 20. Height growth changes of stemmed trees until present were illustrated in a graphic form to evaluate the compatibility of site index curve. The result showed that only 8 plots (18%) did not show any change of site index as trees age, 19 plots (42%) fluctuated in 2∼4m and 18 plots (40%) over 6m.
최종현(Jong-Hyun Choi),정두원(DooWon Jeong),이상진(Sangjin Lee) 한국정보보호학회 2013 정보보호학회논문지 Vol.23 No.5
기업의 정보는 대부분 데이터베이스에 보관된다. 따라서 기업의 범죄 행위를 조사하기 위해서는 데이터베이스에 대한 포렌식 분석이 중요하며 삭제 레코드 복구 기술을 개발할 필요가 있다. 이에 본 논문은 전 세계적으로 가장 많이 쓰이는 Oracle 데이터베이스의 테이블스페이스 파일 구조와 테이블정보를 저장하고 있는 시스템 테이블에 대해 분석하고, 이를 통해 Oracle 테이블스페이스에서 삭제된 레코드를 복구할 수 있는 방법을 제시한다. Most of the enterprise information is stored in the database. Therefore, in order to investigate the company’s criminal behavior, forensic analysis is important for the database and delete record is a need to develop recovery techniques. This paper is explained structure of the oracle database tablespace file and analyzed system tables that stored table information. Further, we suggests a method of recovery for deleted record in oracle tablespace.
최종현(Jong Hyun Choi),최성후(Sung Hoo Choi),윤종필(Jong Pil Yun),구근휘(Keunhwi Koo),김상우(Sang Woo Kim) 대한전기학회 2009 전기학회논문지 Vol.58 No.5
In steel making production line, steel slabs are given a unique identification number. This identification number, Slab management number (SMN), gives information about the use of the slab. Identification of SMN has been done by humans for several years, but this is expensive and not accurate and it has been a heavy burden on the workers. Consequently, to improve efficiency, automatic recognition system is desirable. Generally, a recognition system consists of text localization, text extraction, character segmentation, and character recognition. For exact SMN identification, all the stage of the recognition system must be successful. In particular, the text localization is great important stage and difficult to process. However, because of many text-like patterns in a complex background and high fuzziness between the slab and background, directly extracting text region is difficult to process. If the slab region including SMN can be detected precisely, text localization algorithm will be able to be developed on the more simple method and the processing time of the overall recognition system will be reduced. This paper describes about the slab region localization using SIFT (Scale Invariant Feature Transform) features in the image. First, SIFT algorithm is applied the captured background and slab image, then features of two images are matched by Nearest Neighbor (NN) algorithm. However, correct matching rate can be low when two images are matched. Thus, to remove incorrect match between the features of two images, geometric locations of the matched two feature points are used. Finally, search rectangle method is performed in correct matching features, and then the top boundary and side boundaries of the slab region are determined. For this processes, we can reduce search region for extraction of SMN from the slab image. Most cases, to extract text region, search region is heuristically fixed [1][2]. However, the proposed algorithm is more analytic than other algorithms, because the search region is not fixed and the slab region is searched in the whole image. Experimental results show that the proposed algorithm has a good performance.