• 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.

• Geomechanics and Engineering
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• v.18 no.5
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• pp.515-525
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• 2019

A karst collapse, as a natural hazard, is totally different to a normal collapse. In recent years, karst collapses have caused substantial economic losses and even threatened human safety. A risk assessment model for karst collapse was developed based on the fuzzy analytic hierarchy process (FAHP) and grey relational analysis (GRA), which is a simple and effective mathematical algorithm. An evaluation index played an important role in the process of completing the risk assessment model. In this study, the proposed model was applied to Jiaobai village in southwest China. First, the main controlling factors were summarized as an evaluation index of the model based on an investigation and statistical analysis of the natural formation law of karst collapse. Second, the FAHP was used to determine the relative weights and GRA was used to calculate the grey relational coefficient among the indices. Finally, the relational sequence of evaluation objects was established by calculating the grey weighted relational degree. According to the maximum relational rule, the greater the relational degree the better the relational degree with the hierarchy set. The results showed that the model accurately simulated the field condition. It is also demonstrated the contribution of various control factors to the process of karst collapse and the degree of collapse in the study area.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.1-18
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• 2015

This paper proposes relational capability as a main driver of constructing inter-organizational collaboration networks. Based on social network theory and relational view literature, three components of relational capability are constructed and implemented by an agent-based model. The components include organizational capability, structural capability, and trust between a partner and a focal firm. These three components are updated by two micro mechanisms: structural mechanism and relational mechanism. Structural mechanism is a feedback loop in which the relational capability increases structural capability and vice versa. Relational mechanism is a learning-by-doing process in which a focal firm experiences success or failure of collaboration and the experience increases or decreases cumulative trust in a partner firm. Result of agent-based simulation shows that a collaboration network emerges through interactions of firm's relational capabilities and the characteristics of emerged networks vary with the contribution of structural capability and trust to relational capability. Specifically, in case structural capability contributes more to relational capability, the average degree centrality and collaboration proportion increases as time passes and enters into an equilibrium state. In that case, almost every firms participated in the network collaborates each other so that the emerged network becomes highly cohesive. In case trust contributes more to relational capability, the results are reversed. In an equilibrium state, the balance of contribution between structural capability and trust makes an emerged network larger and maximizes average degree centrality of the network.

• Journal of Families and Better Life
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• v.30 no.2
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• pp.189-196
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• 2012

The purpose of this study was to investigate trajectories of relational aggression in preschool children. The latent growth curve model was used to examine relational aggression in 3 to 5 year olds. The participants were 3-year-old children recruited from preschools and daycare centers. The children's verbal ability was assessed by interview and teachers completed measurements of negative emotionality and relational aggression. The findings suggest that relational aggression decreased during the preschool years. Gender, language ability, and negative emotionality showed positive effects on the initial level of relational aggression. Moreover, gender and negative emotionality had negative effects, however, language ability had positive effects on the change rate of relational aggression.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.859-868
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• 2012

Due to a rapidly aging society, the future Korea mortality rate is important for planning national financial strategies and social security policies. Old age mortality statistics are very limited in their ability to project a future mortality rate; therefore, it is essential to accurately estimate the old age mortality rate. In this paper, we show that the CK model with a Relational model as a base model provides accurate estimates of old age mortality rates.

• The Journal of Society for e-Business Studies
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• v.8 no.1
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• pp.103-111
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• 2003

Nowadays XML is used for exchanging information in e-Commerce, especially B2B. Necessity of XML DBMS has being increased to efficiently process XML data. So a lots of database products for supporting XML are rapidly appeared in the market. In this paper, we made an XML DBMS system based on Generic Data Model. First we developed XML Adaptor based on Generic Data Model and added it on relational DBMS for developing XML DBMS. XML Adaptor is composed of Query Convertor and XML Repository System. The Query Convertor parse commands that are for XML data manipulation and then call the relevant component of XML Repository System for relational database operation. The XML Repository System handles relational database operations such as create, delete, store, and etc. In this way we can use a relational DBMS for manipulation XML data. Therefor we can build more economically XML DBMS.

• Journal of the Korea Society for Simulation
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• v.11 no.2
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• pp.55-66
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• 2002

VHDL has been. widely used in modeling and simulation of hardware designs. However, complex relationship between components of the designs makes the VHDL modeling problem very difficult. Furthermore, after the initial creation of VHDL models, they evolve into many versions over their lifetime. To cope with such difficulties, this paper proposes a new methodology for the management of VHDL models supporting versions. Its conceptual bases are system entity structure and relational database. Within the methodology, a family of hierarchical structures of a design is organized in the form of VHDL model structure. It is, in turn, represented in the form of relational tables. Once the model structure is built in such a way, a specific simulation model which meets design objective is pruned from the model structure. The details of VHDL codes are systematically synthesized by combining it with the primitive models in a model base. These algorithms are also defined in terms of relational algebraic operations.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.301-305
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• 2007

Mapping of EXPRESS, which is object-favored language to represent IFC model, to Relational Database is not straightforward. Model size can be much bigger and data can be missed through process. However mapping to the object concept added database, such as Object Oriented Database or Object Relational Database, may be simpler and have lots of advantages. This study investigates previous IFC mapping studies, concept of Relational Database and Object Oriented Database, and mapping methodology to Object Relational Database using object.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.11a
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• pp.71-76
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• 2005

XML is rapidly becoming one of the most widely adopted technologies for information exchange and representation on the World Wide Web. However, the large part of data is still stored in a relational database. Hence, we need to convert relational data into XML documents. The most important point of the conversion is to reflect referential integrities In relational schema model to XML schema model exactly. Until now, FT, NeT and CoT are suggested as existing approaches for conversion from the relational schema model to the XML schema model but these approaches only reflect referential integrities which are defined explicitly for conversion. In this paper, we suggest an algorithm for automatic extraction of implicit referential integrities such as foreign key constraints which is not defined explicitly in the initial relational schema model. We present translated XML documents by existing algorithms and suggested algorithms as comparison evaluation. We also compare suggested algorithm and conventional algorithms by simluation in accuracy part.

• Journal of KIISE:Software and Applications
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• v.37 no.5
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• pp.363-369
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• 2010

Demonstration-based learning has the advantage that a user can easily teach his/her robot new task knowledge just by demonstrating directly how to perform the task. However, many previous demonstration-based learning techniques used a kind of attribute-value vector model to represent their state spaces and policies. Due to the limitation of this model, they suffered from both low efficiency of the learning process and low reusability of the learned policy. In this paper, we present a new demonstration-based learning method, in which the relational model is adopted in place of the attribute-value model. Applying the relational instance-based learning to the training examples extracted from the records of the user demonstrations, the method derives a relational instance-based policy which can be easily utilized for other similar tasks in the same domain. A relational policy maps a context, represented as a pair of (state, goal), to a corresponding action to be executed. In this paper, we give a detail explanation of our demonstration-based relational policy learning method, and then analyze the effectiveness of our learning method through some experiments using a robot simulator.