• Proceedings of the Korea Society for Industrial Systems Conference
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• 2007.02a
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• pp.163-167
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• 2007

We propose an XML document storage system, called XDMS (XML Document Management System), by using an object-relational DBMS. XDMS generates object database schema from XML Schema and stores the XML documents in an object-relational database. SAX parser is used for understanding the structure of the XML documents, and XDMS transforms the documents into objects in the database. Experiment shows that object-relational databases provide more efficient storage and query model compared with relational databases.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.849-855
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• 2008

The Diagnostic Unit of CLINAID can infer working diagnoses for general diseases from the information provided by a user. This user-provided information in the form of signs and symptoms, however, is usually not sufficient to make a final decision on a working diagnosis. In order for the Diagnostic Unit to reach a diagnostic conclusion, it needs to select suitable clinical investigations for the patients. Because different investigations can be selected for the same patient, we need a process that can optimize the selection procedure employed by the Diagnostic Unit. This process, called a selection algorithm, must work with the fuzzy relational method because CLINAID uses fuzzy relational structures extensively for its knowledge bases and inference mechanism. In this paper we present steps of the selection algorithm along with simulation results on this algorithm using fuzzy relational products, both harsh product and mean product. The computation results of applying several different fuzzy implication operators are compared and analyzed.

• Korean Journal of Remote Sensing
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• v.3 no.2
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• pp.115-119
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• 1987

After the introduction of the topologically structured geographic information system(GIS) with relational DBMS, the attribute data can be handled without considering locational data. By utilzing of the characteristic of the relational DBMS, it can be used as an expert system building tool in GIS. The relational DBMS of the GIS furnishes the data needed to perform deductive functions of the expert system, and the rule based approach provides the decision rules. Therefore, rule based approach with the expert judgement can be easily combined with relational DBMS.

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.265-272
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• 2022

The most effective method to improve information system capabilities is to enable instant access to several relational database sources and transform data with a logical structure into multiple target relational databases. There are numerous data transformation tools available; however, they typically contain fixed procedures that cannot be changed by the user, making it impossible to fulfill the near-real-time data transformation requirements. Furthermore, some tools cannot build object references or alter attribute constraints. There are various situations in which tool changes in data type cause conflicts and difficulties with data quality while transforming between the two systems. The R-programming language was extensively used throughout this study, and several different relational database structures were utilized to complete the proposed study. Experiments showed that the developed study can improve the performance of information systems by interacting with and exchanging data with various relational databases. The study addresses data quality issues, particularly the completeness and integrity dimensions of the data transformation processes.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.240-245
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• 1998

Fuzzy information retrieval which uses the concept of fuzzy relation is able to retrieve documents in the way based on not morphology but semantics, dissimilar to traditional information retrieval theories. Fuzzy information retrieval logically consists of three sets : the set of documents, the set of terms and the set of queries. It maintains a fuzzy relational matrix which describes the relationship between documents and terms and creates a thesaurus with fuzzy relational product. It also provides the user with documents which are relevant to his query. However, there are some problems on building a thesaurus with fuzzy relational product such that it has big time complexity and it uses fuzzy values to be processed with flating-point. Actually, fuzzy values have to be expressed and processed with floating-point. However, floating-point operations have complex logics and make the system be slow. If it is possible to exchange fuzzy values with binary values, we could expect sp eding up building the thesaurus. In addition, binary value expressions require just a bit of memory space, but floating -point expression needs couple of bytes. In this study, we suggest a new method of building a thesaurus, which accelerates the operation of the system by pre-applying an ${\alpha}$-cut. The experiments show the improvement of performance and reliability of the system.

• Journal of the Korean Home Economics Association
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• v.47 no.1
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• pp.105-113
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• 2009

The purpose of this study was to explore differences in social information processing according to children's sex and types of aggression in response to instrumental and relational provocation factors. Two hundred and fifty-one 4, 5, and 6 graders were selected from an elementary school in Seoul. To evaluate their social information processing, the Intent Attributions and Feelings of Distress(Crick, 1995; Fitzgerald & Asher, 1987) and Response Decision Instrument(Crick & Werner, 1998) were revised and analyzed. A peer-nomination measure(Crick, 1995; Crick & Grotpeter, 1995) was used to select aggressive groups. Data were subjected to descriptive statistical analysis and multivariate [2(sex: M, F)${\times}$3(type of aggression: overt, relational, overt and relational aggression)] analysis of variance. Findings revealed that children's social information processing patterns were different according to sex and type of aggression. Also aggressive children responded differently in their social information processing according to instrumental and relational provocation factors. Implications of these findings for the role of gender, aggression type, and provocation type are discussed in order to better understanding of children's social information processing.

• The Journal of Society for e-Business Studies
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• v.8 no.1
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• pp.85-102
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• 2003

Nowadays an information exchange on XML such as B2B electronic commerce is spreading. Therefore the systematic and stable management mechanism for storing the exchanged information is needed. For this goal there are many research activities for connection between XML application and relational database. But because XML data have hierarchical structures and relational database can store only flat-structured data, we need to make the conversion rule which changes the hierarchical architecture to 2-dimensional information. Accordingly the modeling methodology for storing each structured information in relational database is needed. In this paper, we introduce a XML modeling methodology to design W3C XML schema using UML and we propose a unified design methodology for relational database schema to store XML data efficiently in relational databases. In the second place, in order to verify objectivity of a unified design methodology. By the way of Ronald Bourret, First we introduce the method of the transformation from XML schema to object model and second we translate object model into relational database schema. Therefore we show the mutual consistency between those consequence, and so can verify a unified design methodology.

• The Journal of Information Technology and Database
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• v.1 no.1
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• pp.9-30
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• 1994

The objective of this paper is to give a brief review of relational design methodology, and show how a relational schema can be converted into an object-relational schema. We first introduce relational terminology and describe the relational design process along with its limitations. Next we show how the relational model can be extended to overcome these limitations : these extensions form the core of an object-relational data model ; we use the UniSQL/X data model as an example. We illustrate the process or converting a relational schema into an object-relational schema, and show the benefits of this conversion with respect to queries. The conversion process is then summarized as a set of guidelines. Finally, we make our conclusions.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.149-156
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• 2020

This study investigated the key factors affecting online relational intimacy in the context of SNS. Based on the use and gratification theory, self-presentation, relationship formation and information searching were identified as the main needs of SNS usage. These needs were expected to influence online relational intimacy through user satisfaction, subjective well-being, and disclosing information behaviors. The theoretical framework was validated by a longitudinal method. Hypotheses were tested by using the partial least squares to data from 199 Facebook users. Self-presentation and information searching had a significant impact on both user satisfaction and subjective well-being. However, relationship formation did not significantly affect both user satisfaction and subjective well-being. User satisfaction had a significant direct effect only on online relational intimacy. Subjective well-beings played a significant role in enhancing both disclosing information behaviors and online relational intimacy. Finally, it has been found that disclosing information behaviors are a key factor in enhancing online relational intimacy. The results of this study are expected to provide academic and practical implications for the key antecedents of online relational intimacy.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.128-133
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• 1998

This paper aims to present some ideas for implementation of Uncertain Relational Databases (URD) which are extensions of classical relational databases. Our system firstly is based on possibility distribution and probability theory to represent and manipulate fuzzy and probabilistic information, secondly adopts flexible mechanisms that allow the management of uncertain data through the resources provided by both available relational database management systems and front-end interfaces, and lastly chooses dynamic SQL to enhance versatility and adjustability of systems.