• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.3
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• pp.45-58
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• 2016

Data are important in an organization because they are used in making decisions and obtaining insights. Furthermore, given the increasing importance of data in modern society, data governance should be requested to increase an organization's competitive power. However, data governance concepts have caused confusion because of the myriad of guidelines proposed by related institutions and researchers. In this study, we re-established the concept of ambiguous data governance and derived the top-level components by analyzing previous research. This study identified the components of data governance and quantitatively analyzed the relation between these components by using DEMATEL and context analysis techniques that are often used to solve complex problems. Three higher components (data compliance management, data quality management, and data organization management) and 13 lower components are derived as data governance components. Furthermore, importance analysis shows that data quality management, data compliance management, and data organization management are the top components of data governance in order of priority. This study can be used as a basis for presenting standards or establishing concepts of data governance.

• Journal of the Korean Society of Industry Convergence
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• v.13 no.4
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• pp.211-217
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• 2010

As the vehicle components are various, we confront unexpected problems in the development and application of them. also warranty expenses occur in the result of unconfirmed warranty.in this paper, to solve the problems of disconnection of damper Strut cable, we applied the optimum conditions through taguchi method for improvement of durability. and we made standard of reliability by weibull analysis of the field data. we acquired reliability standard by correlation with lab data and confirmed improved components satisfying the target of reliability. The analysis of reliability by field data is very useful and we need to apply this method to other components, the correlation between field data and Lab Test has influence on satisfying the target of reliability.this method would be utilized for current mass production components and upcoming developed components. the reliability of durability should be continuously used in the basis of primary technique in cope with competitive automotive companies.

• Journal of Environmental Science International
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• v.11 no.1
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• pp.63-68
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• 2002

In this study, we examined statistical analysis between sewage plant operations parameters and effluent quality We got six components from principle component analysis of the operation parameters and secondary effluent quality. 91.8% of the total variance was explained by the six components. The components were identified in the following order : 1) organic matter removal by aeration basin microbe, 2) settleability on secondary clarifier load, 3) removal of nutrients, 4) microbial number increasement and species diversity, 5) microbial activity in aeration basin, 6) oxidation in aeration basin.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.496-498
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• 2003

Signal is composed of the independent components that can describe itself. These components can distinguish itself from any other signals and be extracted by analysis itself. This algorithm is called Independent Component Analysis (ICA) and image signal is considered as linear combination of independent components and features that is the weighted vector of independent component. This algorithm is already used in order to extract the good feature for image classification and very effective In this paper, we'll explain the method of stereo matching using independent component analysis and show the experimental result.

• Journal of the Korean Mathematical Society
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• v.57 no.2
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• pp.401-414
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• 2020

It is computationally expensive to compute principal components from scratch at every update or downdate when new data arrive and existing data are truncated from the data matrix frequently. To overcome this limitations, incremental principal component analysis is considered. Specifically, we present a sliding window based efficient incremental principal component computation from a covariance matrix which comprises of two procedures; simultaneous update and downdate of principal components, followed by the rank-one matrix update. Additionally we track the accurate decomposition error and the adaptive numerical rank. Experiments show that the proposed algorithm enables a faster execution speed and no-meaningful decomposition error differences compared to typical incremental principal component analysis algorithms, thereby maintaining a good approximation for the principal components.

• Culinary science and hospitality research
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• v.14 no.2
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• pp.128-137
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• 2008

The importance of brand and brand equity has greatly increased not only in the professional perspectives but also in academic viewpoints. Especially, lots of related studies have been focused on the components of brand equity itself. However, this study concentrates on the relationships of brand equity components for understanding consumers' attitudes toward the brands of the food-service businesses. The basic research model consists of 4 brand equity components: brand awareness, perceived quality, brand image, and brand preference. Research data are gathered through survey questions responded by university students. For statistical analysis, correlation analysis, factor analysis, and covariance structure analysis are carried out. The result of this study are summed up as follows. Among the brand equity components, brand awareness had a great effect on perceived quality(path coefficient; 0.476). Brand image highly influenced brand preference(path coefficient; 0.439).

• Journal of the Earthquake Engineering Society of Korea
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• v.24 no.6
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• pp.267-275
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• 2020

In the event of an earthquake, non-structural components require seismic performance to ensure evacuation routes and to protect lives from falling non-structural components. Accordingly, the seismic design code proposes horizontal force for the design and evaluation of non-structural components. Ground motion observed on each floor is affected by a building's eigen vibration mode. Therefore, the earthquake damage of non-structural components is determined by the characteristics of the non-structural component system and the vibration characteristics of the building. Floor response spectra in the seismic design code are estimated through time history analysis using seismic waves. However, it is difficult to use floor response spectra as a design criterion because of user-specific uncertainties of time history analysis. In addition, considering the response characteristics of high-rise buildings to long-period ground motions, the safety factor of the proposed horizontal force may be low. Therefore, this study carried out the horizontal force review proposed in the seismic design code through dynamic analysis and evaluated the floor response of seismic waves considering buildings and predominant periods of seismic waves.

• Journal of the Korean Society of Tobacco Science
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• v.27 no.1 s.53
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• pp.141-152
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• 2005

This study focused on the relationships among leaf and smoke components and sensory properties following tobacco leaf blending. A completely randomized experimental design was used to evaluate components of leaf and smoke and sensory properties for sample cigarettes with four mixtures of flue cured and burley tobacco (40:60, 60:40, 80:20 and 100:0). Eleven leaf components, six smoke components, and eight sensory properties of smoking taste were analyzed. A sensory evaluation method known as quantitative descriptive analysis was used to evaluate perceptual strength on a fifteen score scale. Raw data from ten trained panelists were obtained and statistically analyzed. Based on the MANOVA, clustering analysis, correlation matrix and partial least square (PLS) method were applied to find out which smoke component most affected sensory properties. The PLS method was used to remove the influence between explanatory variables in the leaf, smoke components derived from the results. High correlations (p<0.0l) were found among ten specific leaf and smoke components and sensory attributes. Total nitrogen, ammonia, total volatile base, and nitrate in the leaf were significantly correlated (p<0.05) with impact, bitterness, tobacco taste, irritation, smoke volume, and smoke pungency. From the results of PLS analysis, influence variables are used to explain about the correlation. In terms of bitterness, with only two explanatory variables, Leaf $NO_3$ and Leaf crude fiber were enough for guessing their correlation. In the distance weighted least square fitting analysis, carbon monoxide highly influenced bitterness, hay like taste, and smoke volume.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2004.04a
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• pp.311-314
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• 2004

To identify the effect of geology and land use, the hydrogeochemical and multivariate statitstical analysis were executed for stream water collected in headwater region of Daecheong reservoir. Hydrogeochemical analysis was showed the effect of weathering process such as dissolution of calc-silicate minerals to hydrochemistry of stream water with contrasting geology. Cluster and principal components analysis can also help to identify the source of dissolved components in stream water.

• Korean Journal of Mathematics
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• v.14 no.1
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• pp.47-55
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• 2006

This paper presents an image analysis technique using connected components by applying SPA (shortest path algorithm) from graph theory. Software implementation of Floyd-Warshall transitive matrix labelling method is discussed. Results are also presented.