• 산업공학
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• 제14권3호
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• pp.247-254
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• 2001

As current postal automation is limited to dispatch and arrival sorting, delivery sequence sorting is performed manually by each postman. It not only acts as a bottleneck process in the overall mailing process but is expensive operation. To cope with this problem effectively, delivery sequence sorting automation is required. The important components of delivery sequence sorting automation system are sequence sorter and Hangul OCR which function is to extract the address of delivery point. DSI database will be interfaced to both Hangul OCR and sequence sorter for finding the accurate delivery sequence number and stacker number. The objectives of this research are to develop DSI(Delivery Sequence Information) database prototype and client application for managing information effectively. For database requirements collection and analysis, we draw all possible sorting plans, and apply the AHP(Analytic Hierarchy Process) method to determine the optimal one. And then, we design DSI database schema based on the optimal one and implement it using Oracle RDBMS. In addition, as address information in DIS database consist of hierarchical structure which has its correspondence sequence number, so it is important to reorganize sequence information accurately when address information is inserted, deleted or updated. To increase delivery accuracy, we reflect this point in writing application.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.770-773
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• 2005

In most biological laboratory, sequences from sequence machine are stored into file disks as simple files. It will be hard work to store and manage the sequence data with consistency and integrity such as storing redundant files. It is required needed to develop a system which integrated and managed genome data with consistency and integrity for accurate sequence analysis. There fore, in this paper, we not only store gene and protein sequence data through sequencing but also manage them. We also make a integrate schema for transforming the file formats and design database system using it. As integrated schema is designed as a BSML, it is possible to apply a style language of XSL. From this, we can transfer among heterogeneous sequence formats.

• Bioinformatics and Biosystems
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• 제2권2호
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• pp.46-51
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• 2007

In the proteomics research using mass spectrometry, the protein database search gives the protein information from the peptide sequences that show the best match with the tandem mass spectra. The protein sequence database has been a powerful knowledgebase for this protein identification. However, as we accumulate the protein sequence information in the database, the database size gets to be huge. Now it becomes hard to consider all the protein sequences in the database search because it consumes much computing time. For the high-throughput analysis of the proteome, usually we have used the non-redundant refined database such as IPI human database of European Bioinformatics Institute. While the non-redundant database can supply the search result in high speed, it misses the variation of the protein sequences. In this study, we have concerned the proteomics data in the point of protein similarities and used the network analysis tool to build a new analysis method. This method will be able to save the computing time for the database search and keep the sequence variation to catch the modified peptides.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.99-102
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• 2004

Recently according to developing of bioinformatics techniques, there are a lot of researches about large amount of biological data. And a variety of files and databases are being used to manage these data efficiently. However, because of the deficiency of standardization there are a lot of problems to manage the data and transform one into the other among heterogeneous formats. We are interested in integrating. saving, and managing gene and protein sequence data generated through sequencing. Accordingly, in this paper the goal of our research is to implement the system to manage sequence data and transform a sequence file format into other format. To satisfy these requirements, we adopt BSML (Bioinformatics Sequence Markup Language) as the standard to manage the bioinformatics data. And then we integrate and store the heterogeneous 리at file formats using BSML schema based DTD. And we developed the system to apply the characteristics of object-oriented database and to process XPath query, one of the efficient structural query. that saves and manages XML documents easily.

• 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.

• Genomics & Informatics
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• 제4권4호
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• pp.173-181
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• 2006

Pattern finding is one of the important tasks in a protein or DNA sequence analysis. Alignment is the widely used technique for finding patterns in sequence analysis. BLAST (Basic Local Alignment Search Tool) is one of the most popularly used tools in bio-informatics to explore available DNA or protein sequence databases. BLAST may generate a huge output for a large sequence data that contains various sequence patterns. However, BLAST does not provide a tool to summarize and analyze the patterns or matched alignments in the BLAST output file. BLAST lacks of general and robust parsing tools to extract the essential information out from its output. This paper presents a pattern summary system which is a powerful and comprehensive tool for discovering pattern structures in huge amount of sequence data in the BLAST. The pattern summary system can identify clusters of patterns, extract the cluster pattern sequences from the subject database of BLAST, and display the clusters graphically to show the distribution of clusters in the subject database.

• Genomics & Informatics
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• 제3권3호
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• pp.94-97
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• 2005

We have built a database server called Patome which contains the annotation information for patented bio-sequences from the Korean Intellectual Property Office (KIPO). The aims of the Patome are to annotate Korean patent bio-sequences and to provide information on patent relationship of public database entries. The patent sequences were annotated with Reference Sequence (RefSeq) or NCBI's nr database. The raw patent data and the annotated data were stored in the database. Annotation information can be used to determine whether a particular RefSeq ID or NCBI's nr ID is related to Korean patent. Patome infrastructure consists of three components­the database itself, a sequence data loader, and an online database query interface. The database can be queried using submission number, organism, title, applicant name, or accession number. Patome can be accessed at http://www.patome.net. The information will be updated every two months.

• 한국정보과학회논문지:데이타베이스
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• 제31권3호
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• pp.243-251
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• 2004

대부분의 생물정보학의 프로그램들은 데이타베이스로부터 유전자 등의 데이타를 검색하고 처리하여 생화학자와 생물학자에게 서비스를 제공한다. 이때 각각 클라이언트의 요청마다 데이타베이스의 검색을 수행한다면 많은 디스크 접근 시간이 소요된다. 또한 서버에 과부하를 초래하여 응답시간이 길어질 수 있다. 본 논문에서는 생물정보학에서 서열 검색 프로그램의 데이타베이스 사용 패턴을 이용하여 많은 데이타베이스 요청에 대하여 데이타베이스의 검색을 위한 디스크 접근을 공유하는 그룹핑 기법을 제안한다. 또한, 사용자 요청을 대기 시간 없이 처리중인 작업과 동시에 데이타베이스의 검색을 위한 디스크 접근을 공유하여 시스템 처리율을 높이고 빠른 응답시간을 가지는 카플 방식을 제안한다. 제안된 기법은 수학적 분석과 시뮬레이션을 통하여 성능을 검증하였다.

• 한국콘텐츠학회논문지
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• 제13권9호
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• pp.410-417
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• 2013

시공단계에 따른 철근콘크리트 구조물의 장기변형 해석은 설계 및 시공에 있어서 매우 중요한 요소이다. 하지만 기존의 많은 해석적 연구들은 그 적용기법의 단순화로 인하여 실제 구조설계 및 시공에 대부분 반영되지 못하고 있다. 동바리와 기둥에서는 축력 재분배가 시간에 따라 계속적으로 변화되기 때문에 콘크리트 타설, 거푸집 제거, 동바리 재설치, 동바리 제거 및 이에 따른 추가하중의 작용과 같은 전반적인 시공단계를 그대로 적용하여 해석하는 것은 매우 중요한 요소이다. 따라서 본 논문에서는 이와 같은 시간에 따른 시공단계별 해석을 객체지향 알고리즘으로 개발하였다. 본 시스템에서는 입력모듈, DB 모듈, DB저장 모듈, 해석모듈 및 결과분석모듈로 구분하였으며, 각 모듈간의 연계는 visual c# 루틴으로 처리하였다. 또한 그래픽 인터페이스와 DB 테이블은 사용자 편의성을 고려하여 개발하였다.