• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.147-150
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• 1996

A homing torpedo's performance can be expressed a function of many variables, i.e. technical and tactical variables. When designing a homing torpedo, these variables have to be decided upon. The system effectiveness of a homing torpedo can be determined by analyzing of these variables. This paper describes a procedure of simulation metamodelling using a Factor Analysis methodology. A simulation model was used in order to obtain the data base for analyzing detection probability of torpedo. By analyzing the main and interaction effects these variables on the analysis of detection probability, we will show the importance of certain variables, of a homing torpedo.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.19-30
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• 2012

Based on the internet-based infrastructures such as various information devices, social network systems and cloud computing environments, distributed and sharable data are growing explosively. Recently, as a data analysis and mining technique for extracting, analyzing and classifying the inherent and useful knowledge and information, Formal Concept Analysis on binary or many-valued data has been successfully applied in many diverse fields. However, in formal concept analysis, there has been little research conducted on analyzing interval data whose attributes have some interval values. In this paper, we propose a new approach for classification of interval data based on the formal concept analysis. We present the development of a supporting tool(iFCA) that provides the proposed approach for the binarization of interval data table, concept extraction and construction of concept hierarchies. Finally, with some experiments over real-world data sets, we demonstrate that our approach provides some useful and effective ways for analyzing and mining interval data.

• Journal of Information Management
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• v.42 no.4
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• pp.39-58
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• 2011

This paper presents a meta-tag expanded from scholarly service types of OpenURL written in Key/Encoded-Value format, after analyzing new scholarly service types and DataCite metadata elements which are for research data publishing and services. So far, OpenURL Z39.88 standard, KEVFormat: Sch-Svc, supporting six scholarly service type only, the expansion of this standard is needed for a research data circulation. New eight scholarly service types were extracted, after analyzing and comparing with the Scopus, Web of Science, and NDSL services. And nine representative attributes were extracted, after analyzing intensively the DataCite's elements.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.1-8
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• 2020

The use of text data in big data analytics has been increased. So, much research on methods for text data analysis has been performed. In this paper, we study Bayesian learning based on conjugate prior for analyzing keyword data extracted from text big data. Bayesian statistics provides learning process for updating parameters when new data is added to existing data. This is an efficient process in big data environment, because a large amount of data is created and added over time in big data platform. In order to show the performance and applicability of proposed method, we carry out a case study by analyzing the keyword data from real patent document data.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.119-129
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• 2016

With the development of web, amount of information are generated in social web. Then many researchers are focused on the extracting and analyzing social issues from various social data. The proposed approach performed gathering the science data and analyzing with LDA algorithm. It generated the clusters which represent the social topics related to 'health'. As a result, we could deduce the relationship between science data and social issues.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.25 no.2
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• pp.25-38
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• 2017

Current limitation of Aviation airworthiness manage system and text based Aviation safety report data, lack of Data Manage system for aviation parts failure and lack of continuing airworthiness related to task linking system for Inspection/Report/Improvement(AD ; Airworthiness Directive) have been apprehended to suggest direction of realizing improved operating system by applying aviation airworthiness manage system by using standardization and safety performance index based managing and safety performance index based data analyzing.

• IE interfaces
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• v.15 no.2
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• pp.209-217
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• 2002

Quality of Service(QoS) in the telecommunications can be evaluated by analyzing the opinion data which result from the surveyed opinions of respondents and quantify subjective satisfaction on the QoS from the customers' viewpoints. For analyzing the opinion data, MOS(mean opinion score) method and Cumulative Probability Curve method are often used. The methods are based on the scoring method, and therefore, have the intrinsic deficiency due to the assignment of arbitrary scores. In this paper, we propose an analysis method of the opinion data using logit models which can be used to analyze the ordinal categorical data without assigning arbitrary scores to customers' opinion, and develop an analysis procedure considering the usage of procedures provided by SAS(Statistical Analysis System) statistical package. By the proposed method, we can estimate the relationship between customer satisfaction and network performance parameters, and provide guidelines for network planning. In addition, the proposed method is compared with Cumulative Probability Curve method with respect to prediction errors.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.1-9
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• 2010

This paper suggests a mixed-effects model for analyzing split-plot data when there is a repeated measures factor that affects on the response variable. Covariance structures are discussed among the observations because of the assumption of a repeated measures factor as one of explanatory variables. As a plausible covariance structure, compound symmetric covariance structure is assumed for analyzing data. The restricted maximum likelihood (REML)method is used for estimating fixed effects in the model.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.47 no.3
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• pp.222-233
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• 2011

This study is for the multi-dimensional analysis of diverse data sets for artificial reefs off the coast of Shimonoseki, Yamaguchi prefecture, Japan. Various data sets recorded in artificial reefs ground were integrated in new GIS software: to reveal the relationships between water temperature and fish schools; to visualize the quantitative connection between the reefs and the fish schools; and to compare the seabed types derived from two different data sources. The results obtained suggest that the application of GIS in analyzing multi-dimensional data is a better way to understand the characteristics of fish schools and environmental information around artificial reefs and particularly in the evaluation of the effectiveness of artificial reefs.

• Korean Journal of Oriental Medicine
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• v.14 no.3
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• pp.81-87
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• 2008

Sasanag Contitution Medicine(SCM) is the traditional medicine theory based on constitutional medicine in Korea. It is most import ant that a personal SCM type is determined accurately ahead of applying any Sasang treatments. For this, many researches have been studied to diagnose the SCM type using constitutional clinical data. The decision tree is a tree-structured data-mining methodology. Recently, in the Korean traditional medicine society, there have been several efforts to find diagnosing tools using the decision tree method. So, we developed a decision tree program based on web for analyzing constitutional clinical information. It can use various clinical data as input data, offer filtering function to select clinical data to be used. We can find useful factor to be influential on SCM types using this program.