• IE interfaces
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• v.14 no.3
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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.

• Proceedings of the KSRS Conference
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• 2005.10a
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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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• v.2 no.2
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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.

• Proceedings of the KSRS Conference
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• 2004.10a
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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.

• Proceedings of the KSRS Conference
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• v.2
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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.

• Korean Journal of Remote Sensing
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• v.22 no.5
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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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• v.4 no.4
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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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• v.3 no.3
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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.

• Journal of KIISE:Databases
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• v.31 no.3
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• pp.243-251
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• 2004

Most programs of bioinformatics provide biochemists and biologists retrieve and analysis services of gene and protein database. As these services retrieve database for each arrival of user's request, it takes a long time and increases server's load and response time. In this paper. by utilizing database retrieval patterns of sequence alignment programs in bioinformatics, grouping method is proposed to share database retrieval between many requests. Carpool method is also proposed to reduce response time as well as to increase system expandability by combining new arriving requests with the previous on going requests. The performance of our two proposed schemes is verified by mathematic analysis and simulation.

• The Journal of the Korea Contents Association
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• v.13 no.9
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• pp.410-417
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• 2013

Long-term behavior analysis considering construction sequence should be performed in the design and the actual construction of reinforced tall buildings. Most of the analytical studies on this subject, however, has not been applied directly to the structural design and the construction caused by the simple approach. As the axial force redistribution of shores and columns is time-dependent, the actual construction sequence with the placement of concrete, form removal, reshoring, shore removal, and the additional load application is very important. Object-oriented analysis program considering construction sequence, especially time-dependent deformation in early days, is developed. This system is composed of input module, database module, database store module, analysis module, and result generation module. Linkage interface between the central database and each of the related module is implemented by the visual c# concept. Graphic user interface and the relational database table are supported for user's convenience.