• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.116-119
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• 2005

As to the synthetical estimation of land covering parameters or the compounded land covering classification for multi-resolution satellite data, former researches mainly adopted linear or nonlinear regression models to describe the regression relationship of land covering parameters caused by the degradation of spatial resolution, in order to improve the retrieval accuracy of global land covering parameters based on 1;he lower resolution satellite data. However, these methods can't authentically represent the complementary characteristics of spatial resolutions among different satellite data at arithmetic level. To resolve the problem above, a new compounded land covering classification method at arithmetic level for multi-resolution satellite data is proposed in this .paper. Firstly, on the basis of unsupervised clustering analysis of the higher resolution satellite data, the likelihood distribution scatterplot of each cover type is obtained according to multiple-to-single spatial correspondence between the higher and lower resolution satellite data in some local test regions, then Parzen window approach is adopted to derive the real likelihood functions from the scatterplots, and finally the likelihood functions are extended from the local test regions to the full covering area of the lower resolution satellite data and the global covering area of the lower resolution satellite is classified under the maximum likelihood rule. Some experimental results indicate that this proposed compounded method can improve the classification accuracy of large-scale lower resolution satellite data with the support of some local-area higher resolution satellite data.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.609-620
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• 2008

There may be several parallel equipments having the same function in a multi-stage manufacturing process, which affect the product quality differently and have significant differences in defect rate. The product quality may depend on what equipments it has been processed as well as what process variable values it has. Applying one model ignoring the presence of different equipments may distort the prediction of defect rate and the identification of important quality variables affecting the defect rate. We propose a procedure for data segmentation when constructing models for predicting the defect rate or for identifying major process variables influencing product quality. The proposed procedure is based on the principal component analysis and the analysis of variance, which demonstrates a better performance in predicting defect rate through a case study with a PDP manufacturing process.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.4
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• pp.94-101
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• 2003

Recently, miniaturization and weight reduction is getting more attention due to various benefits in automotive components design. It is a trend that the design of experiment(DOE) and statical design method are frequently used for optimization. In this research, the safety of lower control arm is evaluated according to its material change form S45C to A16061 for the reduction of arm's weight. The variance analysis on the basis of structure analysis and DOE is applied to the lower control m. We have proposed a statistical design model to evaluate the effect of structural modification by performing the practical multi-objective optimization considering mass, stress and deflection.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.4
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• pp.40-45
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• 2016

Interrupted cutting has different cutting characteristics compared with continuous cutting. In interrupted cutting, the workpiece has a groove that regularly impacts the cutting tool and workpiece. Therefore, tool damage occurs rapidly, and this increases the cutting force and surface roughness. In this study, we performed interrupted cutting of carbon steel for machine structure (SM45C) using a coated carbide tool (TT7100). To predict the cutting force, we analyzed the experimental results with a regression analysis. The results were as follows: We confirmed that the factors affecting the principal force and radial force were cutting speed, depth of cut, and feed rate. From the multi-regression analysis, we deduced regression equations, and their coefficients of determination were 89.6, 89.27, and 28.27 for the principal, radial, and feed forces, respectively. This means that the regression equations were significant for the principal and radial forces but not for the feed force.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.4
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• pp.118-124
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• 2012

In this study, we turning mold steel (SKD61) using whisker reinforced ceramic tool (WA1) to get affected factor to surface roughness and regression equation. For this study, we adapt system of experiments. Results are follows; From the analysis of variance, it was found that affected factor to surface roughness was feed rate, cutting speed, depth of cut in order. From multi-regression analysis, we calculated regression equation and the coefficient of determination($R^2$). $R^2$ was 0.978 and It means regression equation is significant. Regression equation means if feed rate increase 0.039mm/rev, surface roughness will increase $0.8391{\mu}m$, if cutting speed increase 50m/min, surface roughness will decrease $0.034{\mu}m$, if depth of cut increase 0.1mm, surface roughness will increase $0.0203{\mu}m$. From the experimental verification, it was confirmed that surface roughness was predictable by system of experiments.

• Korea Journal of Hospital Management
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• v.27 no.2
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• pp.44-52
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• 2022

Purposes: This study tried to extract variables affecting patient-experience satisfaction level in hospital situation, using a multiple-regression analysis and ISA(Revised Importance-Satisfaction Analysis), and to explore variables needed to be improved. Methodology: A mobile-based online patient-experience survey was conducted in eleven general hospitals in A city. To test the validity of this test, this data was compared with the data from Health-Insturance Review and Assessment Service. Then, the standardized regression coefficients extracted from a multiple-regression analysis were used as the importance scale to be used in ISA. Finding: Taken together, the areas with the highest contribution for the in-hospital patient-experience satisfaction level were medication and treatment process and hospital environment. In conclusion, the revised ISA which can show satisfaction and importance both with simultaneously and multi-axis way would be useful in hospital improvement activities. Practical Implications: This study tried to develop a mobile-based patient-experience survey, and to extract the major variables affecting patient-satisfaction level and to identify variables need to be improved. Finally, this should help hostipals to prepare the assessment process with various improvement activities.

• Journal of the Korean Home Economics Association
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• v.47 no.9
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• pp.27-36
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• 2009

The purpose of this study to gather information on demographic statistics, children’s attachment to their mothers, and daily stress variants in order to assess their effects on child’s self-concept and depression within multi-ethnic familiy settings. A questionnaire survey was used to targeted 3rd, 4th, 5th and 6th graders in elementary schools in Jeonnam. A total of 158 children were surveyed. SPSS for Windows 12.0 was used to carry out descriptive, and comparative statistical analysis such as Cronbach's $\alpha$, correlations analysis, and a hierarchical regression analysis. Result showed that the most significant variant affecting self-concept among children from multi-ethnic families was attachment to their mothers. Other related individual variants were in order of importance, communication skills, feelings of alienation, and mothers’ nationalities. The variant most responsible for having an affect on depression among children from multi-entnic families was the attachment to their mothers. Other related individual variants were in order of importance, feelings of alienation, stress from peer relationships, mothers’ nationalities, and stress from economic and physical environments.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.571-579
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• 2022

This research empirically analyzed the factors associated with the energy consumption of tourism hotels in Busan, Ulsan, and the Kyoungnam region of Korea based on their individual and locational characteristics. The study adopted a comprehensive modeling approach involving multi-level regression analyses that allowed for improved accuracy by considering the hierarchical structures of the hotels and their locational characteristics. The results indicated that the majority of energy consumption can be explained by the hotels'individual characteristics, including the size of building structure and the services, while their effects vary by region with statistical significance. Furthermore, the proximity to central commercial districts and hotel clusters had a significant influence on the variability in their energy consumption, indicating that locational factors are also important determinants. The findings here suggest the need for regional energy policies and solutions at various urban scales along with conventional energy policies at the building level and highlight regional responsibilities when attempting to create sustainable tourism industries.

• Journal of the Korean Institute of Landscape Architecture
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• v.35 no.1 s.120
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• pp.28-35
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• 2007

The purpose of this study is to evaluate the visual preference factors for river scenery, which can vary according to changes in water levels, to estimate the optimal ratio of water surface/river width. Five locations on the Youngsan and Sumjin Rivers were selected as representative samples and field survey data such as channel geometry with water levels were prepared to develop the slide of river scenery, To estimate the level of satisfaction in river scenery, slides of 4 different water levels at each of the representative locations were developed through questionnaire. To analyse the correlation between the visual preference for river scenery and preference factors, a multi regression analysis method was adopted in this study. According to the results of the multi regression analysis, Factor B(Aesthetic factors) have the greatest affect on visual preferences and Factor A(A Feeling of Open space and Physical factors) affect significantly to visual preferences for river scenery. The results of analysis shows that the most preferred W/B ratio varies from 0.5 to 0.7 and this result indicates that many people prefer high levels river flow to maintain a natural and harmonious view of rivers. The results of this study will contribute to the field of river landscape design and river restoration projects in order to maximize the human being's satisfaction as a part of nature.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2000.09a
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• pp.147-154
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• 2000

The influence of the mined-out caves on the stability of the high speed railway tunnel was investigated with a series of geological logging and in-situ tests on the one hand, and with the rock mass classification using the multiple regression analysis on the other hand. The rock mass in this area can be classified as 'fair', and the condition of the discontinuities plays the most important role in the classification of the rock mass. The results of the analysis obtained by the FLAC showed that the western part of the tunnel locating at 50m above the mine cavities could be affected by subsidence associated with a considerable deformation, the magnitude of which might depend on the properties of the rock mass. Key word : multi regression analysis, subsidence, mine cavities