• Proceedings of the Korea Database Society Conference
• /
• 1994.09a
• /
• pp.213-234
• /
• 1994

고도 정보화 사회로 발전해 감에 따라 사회 전반에서 발생하는 정보들을 컴퓨터에 저장하여 관리하는 정보 관리 시스템들이 많이 개발되고 있다. 특히 컴퓨터 기술의 발달과 통신의 발달은 서로 떨어져 있는 정보 시스템끼리의 정보 교환을 보다 효율적으로 할 수 있게 되어 시스템 통합 환경으로 선도하고 있다. 이에 본 논문에서는 시스템 통합 환경에서 공유 데이타 저장소를 기반으로 하여 지역 데이타베이스를 구축할 수 있는 데이타 모델인 ESR 데이타 모델을 제안하고, 그에 따른 데이타 모델링 방법론을 제안하였다. 또한 공유데이타 저장소를 기반으로 하여 ESR 데이타 모델링을 통한 데이터베이스를 설계할 수 있는 지원도구를 설계하였다.

• Journal of KIISE:Software and Applications
• /
• v.26 no.9
• /
• pp.1052-1060
• /
• 1999

이제까지 비디오 데이타베이스를 모델링하기 위한 많은 연구들이 수행되었지만 그 모든 모델들에서 다루는 비디오 데이타는 사용자의 개입이 없을 때 항상 미리 정의된 순서로 보여진다는 점에서 정적 데이타 모델로 간주될 수 있다. 주문형 뉴스 서비스, 주문형 비디오 서비스, 디지털 도서관, 인터넷 쇼핑 등과 같이 최신 비디오 정보 서비스를 제공하는 비디오 데이타베이스 응용들에서는 빈번한 비디오 편집이 요구되는데 실시간 처리가 바람직하다. 이를 위해서 기존의 비디오 데이타 내용이 변경되거나 새로운 비디오 데이타가 생성되어야 하지만 이제까지의 비디오 데이타 모델에서는 이러한 비디오 편집 작업이 일일이 수작업으로 수행되어야만 했다. 본 논문에서는 비디오 편집에 드는 노력을 줄이기 위해서 객체지향 데이타 모델에 기반하여 DVID(Dynamic Video Object Data Model)라는 동적 비디오 객체 데이타 모델을 제안한다. DVID는 기존의 정적 비디오 객체뿐만 아니라 사용자의 개입없이도 비디오의 내용을 비디오 데이타베이스로부터 동적으로 결정하여 보여주는 동적 비디오 객체도 함께 제공한다.Abstract A lot of research has been done on modeling video databases, but all of them can be considered as the static video data model from the viewpoint that all video data on those models are always presented according to the predefined sequences if there is no user interaction. For some video database applications which provides with up-to-date video information services such as news-on-demand, video-on-demand, digital library, internet shopping, etc., video editing is requested frequently, preferably in real time. To do this, the contents of the existing video data should be changed or new video data should be created, but on the traditional video data models such video editing works should be done manually. In order to save trouble in video editing work, this paper proposes the dynamic video object data model named DVID based on object oriented data model. DVID allows not only the static video object but also the dynamic video object whose contents are dynamically determined from video databases in real time even without user interaction.

• Proceedings of the Korea Database Society Conference
• /
• 1997.10a
• /
• pp.463-471
• /
• 1997

비디오 데이타는 다양하고 방대한 양의 의미를 포함하고 있어 효율적인 내용기반 검색을 지원하기 위해서는 비디오 데이타를 기술하는 구조적이고 체계화된 형태의 메타데이타가 요구된다. 이러한 메타데이타는 검색 시 색인과 같은 역할을 수행하게 되므로 내용 기반검색의 가장 기본적이고 필수적인 데이타이다. 본 논문에서는 뉴스 응용 분야(News On Demand：NOD)를 적용한 비디오 데이터베이스 시스템의 효율적인 내용 기반 검색을 위한 메타데이타를 분류하고, Rambaugh의 OMT기법을 이용하여 메타데이타를 모델링한 후 질의 유형에 따라 모델의 접근 경로를 검사하여 모델을 검증하였다.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
• /
• 1992.11a
• /
• pp.191-200
• /
• 1992

위성망은 정보의 유출이 쉬운 전송로를 가질 뿐만 아니라 다자간에 이루어지는 통신망이므로 정보보호가 요구된다. 본 논문에서는 위성망의 정보 보호모델을 제안하고, 관련된 보호서비스를 제시한다. 본 위성망 보호모델에서는 OSI 참조모델 계층 2에 해당하는 MAC와 LLC부계층들 사이에 SDE 부계층을 두어 데이타의 안전한 교환이 이루어지도록 하며, SDE 부계층에서 제공하는 보호서비스들로는 데이타 비밀보장, 비접속 데이타 무결성, 데이타 발신처 확인, 그리고 접근제어 서비스이다.

• Journal of KIISE:Databases
• /
• v.30 no.6
• /
• pp.573-584
• /
• 2003

Recent massive data generation by genomics and proteomics requires bioinformatic tools to extract the biological meaning from the massive results. Here we introduce ROSPath, a database system to deal with information on reactive oxygen species (ROS)-mediated cell signaling pathways. It provides a structured repository for handling pathway related data and tools for querying, displaying, and analyzing pathways. ROSPath data model provides the extensibility for representing incomplete knowledge and the accessibility for linking the existing biochemical databases via the Internet. For flexibility and efficient retrieval, hierarchically structured data model is defined by using the object-oriented model. There are two major data types in ROSPath data model: ‘bio entity’ and ‘interaction’. Bio entity represents a single biochemical entity: a protein or protein state involved in ROS cell-signaling pathways. Interaction, characterized by a list of inputs and outputs, describes various types of relationship among bio entities. Typical interactions are protein state transitions, chemical reactions, and protein-protein interactions. A complex network can be constructed from ROSPath data model and thus provides a foundation for describing and analyzing various biochemical processes.

• Journal of KIISE:Software and Applications
• /
• v.34 no.7
• /
• pp.667-680
• /
• 2007

The bio-data processing is used for a suitable purpose with bio-signals, which are obtained from human individuals. Recently, there is increasing demand that the bio-data has been widely applied to various applications. However, it is often that the number of data within each class is limited and the number of classes is large due to the property of problem domain. Therefore, the conventional pattern recognition systems and classification methods are suffering form low generalization performance because the system using the lack of data is influenced by noises of that. To solve this problem, we propose a modified additive factor model for bio-data generation, with two factors; the class factor which affects properties of each individuals and the environment factor such as noises which affects all classes. We then develop a classification system through defining a new similarity function using the proposed model. The proposed method maximizes to use an information of the class classification. So, we can expect to obtain good generalization performances with robust noises from small number of datas for bio-data. Experimental results show that proposed method outperforms significantly conventional method with real bio-data.

• Journal of KIISE:Databases
• /
• v.33 no.5
• /
• pp.526-537
• /
• 2006

The most representative approach for efficient storing of XML data is to store XML data in relational databases. The merit of this approach is that it can easily accept the realistic status that most data are still stored in relational databases. This approach needs to convert XML data into relational data or relational data into XML data. The most important issue in the translation is to reflect structural and semantic relations of RDB to XML schema model exactly. Many studies have been done to resolve the issue, but those methods have several problems: Not cover structural semantics or just support explicit referential integrity relations. In this paper, we propose an algorithm for extracting implicit referential integrities automatically. We also design and implement the suggested algorithm, and execute comparative evaluations using translated XML documents. The proposed algorithm provides several good points such as improving semantic information extraction and conversion, securing sufficient referential integrity of the target databases, and so on. By using the suggested algorithm, we can guarantee not only explicit referential integrities but also implicit referential integrities of the initial relational schema model completely. That is, we can create more exact XML schema model through the suggested algorithm.

• The Journal of Natural Sciences
• /
• v.5 no.2
• /
• pp.25-32
• /
• 1992

Statistical database(SDB) are large database primarily collected for purpose of statistical analysis. Commerical database management systems have not been widely used for SDB because of the efficiency problem of storage and access of those systems for SDB. In this paper, we propose SDB management method to use a front-end system to a Relatianal Datebase Management System (RDBMS). We do the design of SM-F system (Stasticical database Management as Front-end system) as a front-end system to a RDBMS. In the system, we use GROS model specially proposed for SDB, and store and manage summary database and meta database to support statistical analysis and to provide users with statistical summary information.

• Journal of KIISE:Software and Applications
• /
• v.34 no.11
• /
• pp.1001-1010
• /
• 2007

HMM tends to output high probability for not only the proper class data but confusable class data, since the modeling power increases as the number of parameters increases. Thus it may not be helpful for discrimination to simply increase the number of parameters of HMM. We proposed two methods in this paper. One is a CMC(Confusion Likelihood Model Selection Criterion) using confusion class data probability, the other is a new recognition method, RCM(Recognition Using Confusion Models). In the proposed recognition method, confusion models are constructed using confusable class data, then confusion models are used to depress misrecognition by confusion likelihood is subtracted from the corresponding standard model probability. We found that CMC showed better results using fewer number of parameters compared with ML, ALC2, and BIC. RCM recorded 93.08% recognition rate, which is 1.5% higher result by reducing 17.4% of errors than using standard model only.

• Journal of KIISE:Databases
• /
• v.34 no.3
• /
• pp.232-243
• /
• 2007

Metadata IR model has high precision and low recall because the query in Metadata IR model is strict that is, the query can express user information need exactly, while Full-text IR model has low precision and high recall because the query in Full-text IR model is a kind of simple keyword query which expresses user information need roughly. If user can translate one's information need into structured query well, the retrieval result will be improved. However, it is little possible to make relevant query without understanding characteristics of metadata. Unfortunately, most users do not interested in metadata, then they cannot construct well-made structured query. Amount of information contained in metadata is less than text information. In this paper, we suggest hybrid IR model using metadata and text which can provide users with lots of relevant documents by retrieving from metadata field and text field complementarily.