• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.11-14
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• 2000

We present an image retrieval method that improves retrieval rate by using the fusion of histogram and wavelet moment features. The key idea is that images similar to a query image are selected in DB by using the wavelet moment features. Then the result images are retrieved from the selected images by using histogram method. In order to evaluate the performance of the proposed method, we use Brodatz texture database, MPEG-7 T1 database and Corel Draw photo. Experimental result shows that the proposed method is better than each of histogram method and wavelet moment method.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
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• pp.211-214
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• 2000

In this paper, we propose a regular-texture image retrieval approach relating In curvature. Maximum curvature and minimum curvature are computed from the query and each regular-texture image in the database. Seven features are computed from curvature characterizing statistical properties of the corresponding image. Each regular-texture image in the database is then represented as the seven CM (curvature measurement)-features. Query comparison and matching can be done using the corresponding CM-features. Experimental results on Brodatz texture show that the proposed approach is effective.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 2005년도 추계학술대회 발표 논문집
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• pp.443-454
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• 2005

The purpose of this study is to show the operations and implementations of ASP web database which uses open-source web site packages called bighitonline video shop. Some literature reviews have been done to reveal robust theoretical background for this research And also, some basic experiments as Preparatory Processes have also been made by using some softwares such as Windows XP professional, IIS, MS SQL Server and others. The main purpose of these experiments is to show strong theoretical and practical backgrounds. These experimental results in the micro-level showed to be successful to understand the Interrelations of web components and web-site architectures.

• 반도체디스플레이기술학회지
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• 제10권3호
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• pp.89-94
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• 2011

The image identification methodology associates an image with a unique identifiable representation. Whenever the methodology regenerates an identifier for the same image, moreover, the newly created identifier needs to be consistent in terms of representation value. In this paper, we discuss a methodology for image identifier generation utilizing luminance correlation. We furthermore propose a method for performance enhancement of the image identifier generation. We also demonstrate the experimental evaluations for uniqueness and similarity analysis and performance improvement that have shown favorable results.

• 정보보호학회논문지
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• 제26권1호
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• pp.125-134
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• 2016

MySQL 데이터베이스는 현재 데이터베이스 시장에서 높은 점유율을 보이며 많은 사용자들이 사용한다. MyISAM 스토리지 엔진의 경우, 이전에 디폴트 엔진으로 사용되었음에도 불구하고 실질적인 레코드 복구 방법이 존재하지 않았다. 삭제된 레코드에는 데이터베이스 수사 시 중요한 증거로 쓰일 수 있는 정보가 존재할 가능성이 높으며, 수사관이 방대한 양의 데이터베이스를 직접 조사하여 일일이 정보를 판별하는 것은 거의 불가능하다. 본 논문에서는 MySQL MyISAM 데이터베이스 구조를 분석하여 삭제된 레코드의 복구 기법을 제안하며 이를 도구로 구현하여 실험한 결과를 제시한다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.627-630
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.

• 대한원격탐사학회지
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• 제22권5호
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• pp.457-462
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.

• Computers and Concrete
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• 제28권5호
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• pp.441-450
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• 2021

This study presents the first analysis system and fast-access cloud database for shrinkage and creep of concrete in the world, named "shrinkage and creep database in Taiwan", SCDT. SCDT not only has the most comprehensive experimental data, including NU, JSCE, Europe, and TW databases, but provides a design tool for researchers and engineers. It can further facilitate the development of prediction models for localized concrete. Users can obtain the shrinkage and creep curves based on their selected prediction models in SCDT. Comparisons of the predicted results of selected models and test results in the chosen database can be generated in seconds. One example of the development of basic creep prediction model in Taiwan based on model B4 by using SCDT to reflect concrete characteristics in Taiwan is also presented in this study. Users anywhere in the world can easily access SCDT to browse and upload data, receive predictive results, or develop predictive models.

• 정보처리학회논문지D
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• 제8D권1호
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• pp.24-31
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• 2001

본 논문에서는 다단계 보안 데이터베이스에서 동시성 정도를 향상시키고, 보안 요구사항을 만족하는 향상된 트랜잭션 스케쥴링 프로토콜을 제안한다. 전통적인 직렬성 표기를 가진 두단계 잠금 기법을 다단계 보안 데이터베이스에 적용했다. 이타적 잠금기법은 기부라는 사상을 사용하여 트랜잭션이 더 잇아 그 객체를 요구하지 않을 때 다른 트랜잭션들이 그 객체를 로크할 수 있도록 미리 객체에 대한 로크를 해제함으로써 트랜잭션들의 대기시간을 줄이기 위해서 제안된 것이다. 확장형 이타적 잠금기법은 처음에 기부되지 않은 객체까지도 처리하는 좀 더 완화된 기법이다. 본 논문에서는 다단계 보안 데이터베이스에서 단기 트랜잭션의 기아현상을 최소화하도록 하였다. 본 프로토콜은 확장형 잠금 기법(XAL/MLS)을 기초로 하였으나, 새로운 방법인 다단계 보안 데이터베이스를 위한 양방향 기부 잠금 규약(2DL/MLS)으로 보안 여구와 동시성 제어를 동시에 만족한다. 제안된 프로토콜의 효율성은 실험의 결과로 확인되었다.

• 정보관리연구
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• 제23권1호
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• pp.1-21
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• 1992

컴퓨터 및 정보통신망(情報通信網)의 발전에 따라 데이터베이스의 구축(構築) 및 활용(活用)이 중요해지고 있다. 과학기술분야(科學技術分野)에서 선진국(先進國)은 문헌(文獻)데이터베이스 뿐만 아니라 수치데이터베이스도 구축하여 왔다. 국내(國內)에서는 문헌(文獻)데이터베이스의 구축 및 활용은 정착되는 단계(段階)이나 수치데이터베이스에 대한 연구(硏究)는 매우 미약하였다. 선진국의 지적소유권(知的所有權)에 대응하기 위해서는 우리 고유의 수치데이터베이스를 구축한 다음에 이를 바탕으로 교환사용(交換使用)을 추진하는 것이 가장 적절한 대응책이며, 따라서 수치데이터베이스의 구축은 우리가 선진국(先進國)과 어깨를 나란히 하려면 필수적으로 요구되는 연구분야(硏究分野)이다. 본 연구(硏究)에서는 재료강도(材料强度) 데이터 중에서 고온특성(高溫特性)에 해당하는 크리프강도에 대한 수치데이터베이스를 구축하였다. 대상물질(對象物質)을 25종으로 하였으며, 국내(國內)에서 생산(生産)된 데이터베이스를 대상으로 하였다.