• Journal of Environmental Science International
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• v.28 no.12
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• pp.1101-1110
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• 2019

This study investigated Post-Occupancy Evaluation (POE) of cherry blossom trails 'Cherry Road' in Daegu Catholic Univ. campus, at Gyeonsan-city, Korea. The evaluation focused on image preference and satisfaction of users i.e., students, using questionnaire surveys. A total 201 questionnaire samples were analyzed and most of the respondents were in the age group of 20. Frequency analysis was conducted on demographics, use behavior, reliability, and means. Factor analysis and multiple regression analysis were conducted for user satisfaction and image preference. Over 80% of visitors came with companions during daytime. The most common motives for use were strolling and walking, event and meeting, passing. For user satisfaction the mean scores were highest for landscape beauty (4.22), image improvement (4.14), campus image (4.08). Night lighting facility received the lowest score (3.32). Factor analysis concerning user satisfaction was categorized into environment-human behavior and physical factors. Multiple regression analysis showed that the overall satisfaction of user was significantly influenced by five independent variables: 'harmonious' (β=.214), 'night lighting facility' (β=.173), 'landscape beauty' (β=.208), 'lawn care' (β=.154), and 'walking trails' (β=.123). The mean scores of image variables were highest for 'beautiful' (5.81), 'bright' (5.67), and 'open' (5.64). The lowest scores was for 'quiet' (4.47). Exploratory factor analysis led to three factors being categorized: aesthetics, comforts, and simplicity. Result of multiple regression analysis indicated that the preference of space image was significantly influenced by five variables: 'bright' (β=.397), 'refreshing' (β=.211), 'cool' (β=.219), 'clean' (β=.182), and 'natural' (β=.-142). Hence, Cherry Road has a high level of user satisfaction and image evaluation, which is interpreted as having various cultural events and value for students on campus. To improve the satisfaction of Cherry Road in the future, it is necessary to secure night lighting, to manage trash cans, and to secure rest space.

• Mass Spectrometry Letters
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• v.13 no.1
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• pp.11-19
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• 2022

Although translational research is referred to clinical chemistry measures, correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm have not been carefully considered in bioanalytical assays yet. The objective of this study was to identify steroidogenic roles in preeclampsia and verify accuracy of quantitative results by comparing two different linear regression models with weighting factor of 1 and 1/x². A liquid chromatography-mass spectrometry (LC-MS)-based adrenal steroid assay was conducted to reveal metabolic signatures of preeclampsia in both serum and placenta samples obtained 15 preeclamptic patients and 17 age-matched control pregnant women (33.9 ± 4.2 vs. 32.8 ± 5.6 yr, respectively) at 34~36 gestational weeks. Percent biases in the unweighted model (w_i = 1) were inversely proportional to concentrations (-739.4 ~ 852.9%) while those of weighted regression (w_i = 1/x²) were < 18% for all variables. The optimized LC-MS combined with the weighted linear regression resulted in significantly increased maternal serum levels of pregnenolone, 21-deoxycortisol, and tetrahydrocortisone (P < 0.05 for all) in preeclampsia. Serum metabolic ratio of (tetrahydrocortisol + allo-tetrahydrocortisol) / tetrahydrocortisone indicating 11β-hydroxysteroid dehydrogenase type 2 was decreased (P < 0.005) in patients. In placenta, local concentrations of androstenedione were changed while its metabolic ratio to 17α-hydroxyprogesterone responsible for 17,20-lyase activity was significantly decreased in patients (P = 0.002). The current bioanalytical LC-MS assay with corrected weighting factor of 1/x² may provide reliable and accurate quantitative outcomes, suggesting altered steroidogenesis in preeclampsia patients at late gestational weeks in the third trimester.

• KIEAE Journal
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• v.9 no.1
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• pp.107-113
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• 2009

The energy cost is resulted from the energy use. Its sources are divided into some types and depended on the building use or energy-use type. The energy cost should be affected by the amount of the energy use. The cost could be calculated to consider various factors such as the insulation, heating type, building shape and others. But it can not consider all of the affect factors to the energy cost and need to categorize the factors to the condition for estimating the cost. In this paper, it aimed at providing the estimation model in linear equation and multiple linear regression, utilizing the building exterior condition and management characteristics in apartment housing. Its survey are conducted in two parts of management characteristics and building exterior condition. The correlation analysis is conducted to get rid of the multicolinearity among the inputted factors. The number of linear equation model is 11 and includes the 1st, 2nd and 3rd equation function, power function and others. Among these, it suggested the 2nd and 3rd function and power function in terms of the statistics. In multiple linear regression model, the building volume and management area are inputted to the estimation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.253-263
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• 2021

Traffic data collected using advanced equipment are highly valuable for traffic planning and efficient road operation. However, there is a problem regarding the reliability of the analysis results due to equipment defects, errors in the data aggregation process, and missing data. Unlike other detectors installed for each vehicle lane, radar detectors can yield different error types because they detect all traffic volume in multilane two-way roads via a single installation external to the roadway. For the traffic data of a radar detector to be representative of reliable data, the error factors of the radar detector must be analyzed. This study presents a field survey of variables that may cause errors in traffic volume collection by targeting the points where radar detectors are installed. Video traffic data are used to determine the errors in traffic measured by a radar detector. This study establishes three types of radar detector traffic errors, i.e., artificial, mechanical, and complex errors. Among these types, it is difficult to determine the cause of the errors due to several complex factors. To solve this problem, this study developed a radar detector traffic volume error analysis model using a multiple linear regression model. The results indicate that the characteristics of the detector, road facilities, geometry, and other traffic environment factors affect errors in traffic volume detection.

• Korean Business Review
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• v.17
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• pp.1-26
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• 2004

After IMF crisis in late 1997, the environment of banking industry has become competitive. To survive in this circumstance, the Local Nong-Hyup is needed to understand the customer's needs and improve the service quality. To achive the purpose, two methods were employed in this study. The first corvered the review of related literature on service. The second adopted field survey approach for data. The study model was developed using Venkatakrishnan & Jagannathan's "An Enhanced Model for Measuring Service Quality" model and details of study as follows. 1. What is the determination factors of service quality for Local Nong-Hyup. 2. Are there differences between "service perception" and "service expectation" for Local Nong-Hyup. 3. Does banking service determination factor of Local Nong-hyup affects customer's satisfaction. 4. Does banking service determination factor of Local Nong-hyup affects customer's repurchase. 5. Does customer's satisfaction for Local Nong-hyup relates repurchase. The samples of this study were extracted at random from the customers of Local Nong-hyup. The results of the questionnaire were analyzed to do frequency analysis, factor analysis, t-test, regression analysis, cross sectional analysis using SPSS Win 10. The results are as follows, First, as determination factors of service quality for Local Nong-Hyup "Reliability, Empathy, Tangibles, Convenience" were extracted by factor analysis. Secondly, using t-test, it was found that there are factor's gap between service anticipation and service perception. Thirdly, using regression analysis, it was found that except Convenience factor, Reliability, Empathy and Tangibles factors affect customer's satisfaction. Forthly, using regression analysis, it was found that all the factors affect repurchase. Finally, using cross sectional analysis, it was found that customer's satisfaction and customer's repurchase correlate.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1215-1224
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• 2016

Climate information of the high resolution grid units is an important factor to explain the phenomenon in a variety of research field. Statistical linear interpolation models are computationally inexpensive and applicable to any climate data compared to the dynamic simulation method at regional scales. In this paper, we considered four different linear-based statistical interpolation models: general linear model, generalized additive model, spatial linear regression model, and Bayesian spatial linear regression model. The climate variable of interest was the daily mean temperature, where the spatial variability was explained using geographic terrain information: latitude, longitude, elevation. The data were collected by weather stations in January from 2003 and 2012. In the sense of RMSE and correlation coefficient, Bayesian spatial linear regression model showed better performance in reflecting the spatial pattern compared to the other models.

• Journal of Industrial Convergence
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• v.1 no.2
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• pp.107-124
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• 2003

With rapid growth and competition of electronic commerce through internet, various buying types and business models are being appeared. In this paper, we studied group buying which is new business model to consumer and factors affecting on trust and participation of group buying. The followings are the regression result of this study. First, familiarity factor, customer service factor, seal of security and product value factor made a significant effect on trust. Second, familiarity factor, perceived reputation factor, customer service factor, seal of security and product value factor made a significant effect on participation of group buying. Third, trust of group buying made a significant effect on participation of group buying. In this study, modeling and empirical test were implemented about structure of trust and participation of group buying. We can know where our group buying strategies should focus and which factor we should improve.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.3
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• pp.107-114
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• 2014

The purpose of this study is to explore a correlation model of traffic safety and personality in elderly and non-elderly people. The correlation model is constructed by a factor regression analysis with latent factors and items related to traffic safety consciousness. As a result, it is found that non-elderly people with positive, active, perfectionistic, and unforgiving personality are likely to speed, have a high chance to be involved in traffic accidents, and tend to give low scores to traffic conditions. However, elderly people who are highly educated are likely to give high scores to traffic conditions and do not speed. Instead, elderly people become more likely to be involved in traffic accidents when they are engaged in more social activities. The results could contribute to developing traffic safety education and policy that is better customized to the specific needs of different groups of road users.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.330-332
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• 2002

There are a lot errors and little accuracy when calculating the grounding resistance with the transposition methods in the equivalent surface of hemisphere electrode. Therefore we should calculate the grounding resistance by using the mesh factor. In this paper, we would estimated the grounding value of mesh electrode with water tank model & estimation method using the reduced scale ratio of mesh electrode based on the theory of model electrode & proportional factor according to the reduced scale ratio. And also we have confirmed the accuracy of the empirical formula of model electrode by using by regression analysis.

• Proceedings of the KIEE Conference
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• 2002.06a
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• pp.29-33
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• 2002

There are a lot of errors and little accuracy when calculating the grounding resistance with the transposition methods in the equivalent surface of hemisphere electrode. Therefore we should calculate the grounding resistance by using the mesh factor, In this paper, we would estimate the grounding value of mesh electrode with water tank model & estimation method using the reduced scale ratio of mesh electrode based on the theory of model electrode & proportional factor according to the reduced scale ratio. And also we have confirmed the accuracy of the empirical formula of model electrode by using the regression analysis.