• Journal of the Korea Safety Management & Science
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• v.6 no.2
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• pp.177-186
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• 2004

Decision analysis has becomes an important technique for decision making in the face of uncertainty. It is characterized by enumerating all the available courses of action, identifying the payoffs for all possible outcomes, and quantifying the subjective probabilities for the all possible random events. When the data are available, decision analysis becomes a powerful tool for determining an optimal course of action. We study the multi-attribute decision making in a compensatory models. In this paper, we use the entropy methods in weights calculating. For the purpose of making optimal decision, the data of five different car models are used. For computing, we used Visual Numerica Version 1.0 software package.

• Journal of Korean Library and Information Science Society
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• v.39 no.4
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• pp.331-352
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• 2008

The person information is a database given free most lively. This study investigates the construction of the domestic person information database and the service present situation. And I compare a search item and a search method with problems for the biographical database construction process and analyze it. I analyze the problems of the person information database and show the person idea who can solve this. I use term relations and the attribute data of the person which used thesaurus by biographical database construction with this purpose.

• Journal of Korean Society of Transportation
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• v.4 no.1
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• pp.12-27
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• 1986

This study examined user preferences toward transportation modes in Seoul. Two multidimensional scaling models, the ideal point and vector models, were applied to data on mode preferences of 114 adults in the metropolitan area. While both models produced fairly similar results, the vector model performed slightly better than the other in terms of interpretability of the results. The transport attributes elicited are comfort, flexibility, travel cost, travel time, privacy, and safety; among which comfort is salient most. The comfort variable is a multi-faceted attribute in nature. The variations of attribute preferences are most significant between the gender groups as well as worker/nonworker groups. In particular, male workers, female workers and female nonworkers form three distinctive market segments. An unidimensional scaling of the preference data reveals that subway, auto-driver, and subscription bus modes are preferred most, whereas motorcycle and bicycle least. The other modes of express bus, taxt, auto-passenger, bus and walk rank intermediately. An examination of how preference orders vary among modal groups hints that users align their stated attitudes to their choice in order to reduce cognitive dissonance.

• KSCI Review
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• v.14 no.2
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• pp.177-183
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• 2006

Today, corporation's business support system is intending web environment. However difficulty by elements of tool that Hyeoneop can support web program development efficiently standing be and is. Specially, is suffering difficulty relation data base system and development of wormed web connection program. Because using candidate key attribute of database at web program development in this research hereupon, wish to computerize web development process, and present algorithm that can develop web program efficiently.

• Journal of Internet Computing and Services
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• v.3 no.3
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• pp.31-38
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• 2002

A method of DID generating step is suggested for applying the XML technology to the information data extracted from the Legacy databases. The IDREF-ID attribute reference modeling is used for representing the complex relationship between tables and excluding the prearranged step of ID insertion. ID Insertion procedure is performed in parallel with investigating the relationship between the tables and the frequent search direction between the table data. As a result, ID insertion procedure can be performed simultaneously with understanding of the IDREF-ID relationship between tables, and DID are also generated.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.7-10
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• 1998

The conventional relational databases have difficulties to efficiently represent various of data because an attribute of a tuple should have only one elementary value. In order to represent ambiguous and imprecious information, fuzzy set and rough set have been gaining acceptance, especially as a tool for knowledge discovery in databases. One of former researches applies only one fuzzy membership value to a tuple. We suggest a more advanced model for data representation by way of applying many membership values to a tuple, i.e. one membership value to each attribute of a tuple.

• Journal of the Korea Safety Management & Science
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• v.9 no.2
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• pp.215-233
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• 2007

Even though the ad hoc Shewhart methods remain controversial due to various mathematical flaws, there is little disagreement among researchers and practitioners when a set of process data has a skewness distribution. In the context and language of process control, the error related to the process data shows that time to signal increases when a control parameter shifts to a skewness direction. In real-world industrial settings, however, quality practitioners often need to consider a skewness distribution. To address this situation, we developed an enhanced design method to utilize advantages of the traditional attribute control chart and to overcome its associated shortcomings. The proposed design method minimizes bias, i.e., an average time to signal for the shift of process from the target value (ATS) curve, as well as it applies a variable sampling interval (VSI) method to an attribute control chart for detecting a process shift efficiently. The results of the factorial experiment obtained by various parameter circumstances show that the VSI c control chart using nearly unbiased ATS design provides the smallest decreasing rate in ATS among other charts for all experimental cases.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.545-547
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• 2003

본 논문에서는 Edge-Labeled Graph에 기반하여 XML 인스턴스들을 관계형 데이터베이스(RDB)로 저장하는 모델을 제안하고 구현한다. 저장되는 XML 인스턴스들은 Edge-Libeled Graph에 기반 한 Data Graph로 표현되고 이를 이용하여 데이터 경로(Data Path), 요소(Element), 속성(Attribute), 테이블 인덱스(Table Index) 테이블에 정의된 값들이 추출된 후 Napper를 이용하여 데이터베이스 스키마를 정의하고 추출된 값들을 저장한다. 그리고, RDB 저장 모델은 질의를 지원하기 위해, XPATH를 따르는 질의 언어로 사용되는 XQL을 SQL로 변환하는 변환기를 제공하며, 또한 저장된 XML 인스턴스를 복원하는 DBtoXML 처리기를 갖도록 하였다. 구현 결과, XML 인스턴스들과 RDB 구조로의 저장 관계가 그래프(Graph) 기반의 경로(Path)를 이용한 표현으로 가능했으며, 동시에, 특정 요소 (Element) 또는 속성(Attribute)들의 정보들을 쉽게 검색할 수 있는 가능성을 보였다.

• Journal of Biosystems Engineering
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• v.27 no.2
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• pp.161-172
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• 2002

Database as a supporting system for decision-making is one of essential parts for realizing precision farming. Application models on constructing a database for precision farming, including collection of spatial and attribute data, were suggested using a GPS, DXF files, AutoCAD, a Java application program and PostgreSQL DBMS in this study. The constructed spatial database based on the schema design of spatial and attribute data table was evaluated as a supporting system for decision-making by a simulation of a virtual variable-rate chemical applicator. The applicator could extract the values of soil property at its consecutive location in the tested field in communication with the constructed database, and prescribe the corresponding variable-rate of chemicals. The results of the study suggested the possibility that the constructed database can function a supporting system for decision-making for precision farming.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1260-1272
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• 2024

This paper tackles the prevalent challenges faced by existing tourism route recommendation methods, including data sparsity, cold start, and low accuracy. To address these issues, a novel intelligent tourism route recommendation method based on collaborative filtering is introduced. The proposed method incorporates a series of key steps. Firstly, it calculates the interest level of users by analyzing the item attribute rating values. By leveraging this information, the method can effectively capture the preferences and interests of users. Additionally, a user attribute rating matrix is constructed by extracting implicit user behavior preferences, providing a comprehensive understanding of user preferences. Recognizing that user interests can evolve over time, a weight function is introduced to account for the possibility of interest shifting during product use. This weight function enhances the accuracy of recommendations by adapting to the changing preferences of users, improving the overall quality of the suggested tourism routes. The results demonstrate the significant advantages of the approach. Specifically, the proposed method successfully alleviates the problem of data sparsity, enhances neighbor selection, and generates tourism route recommendations that exhibit higher accuracy compared to existing methods.