• Journal of Ecology and Environment
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• v.32 no.4
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• pp.229-236
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• 2009

A habitat model was developed to delineate potential habitat of the leopard cat (Prionailurus bengalensis) in a mountainous region of Kangwon Province, Korea. Between 1997 and 2005, 224 leopard cat presence sites were recorded in the province in the Nationwide Survey on Natural Environments. Fifty percent of the sites were used to develop a habitat model, and the remaining sites were used to test the model. Fourteen environmental variables related to topographic features, water resources, vegetation and human disturbance were quantified for 112 of the leopard cat presence sites and an equal number of randomly selected sites. Statistical analyses (e.g., t-tests, and Pearson correlation analysis) showed that elevation, ridges, plains, % water cover, distance to water source, vegetated area, deciduous forest, coniferous forest, and distance to paved road differed significantly (P < 0.01) between presence and random sites. Stepwise logistic regression was used to develop a habitat model. Landform type (e.g., ridges vs. plains) is the major topographic factor affecting leopard cat presence. The species also appears to prefer deciduous forests and areas far from paved roads. The habitat map derived from the model correctly classified 93.75% of data from an independent sample of leopard cat presence sites, and the map at a regional scale showed that the cat's habitats are highly fragmented. Protection and restoration of connectivity of critical habitats should be implemented to preserve the leopard cat in mountainous regions of Korea.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.8 s.101
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• pp.945-953
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• 2005

The purpose of this paper is to develop a linear regression model for the sound quality index of vehicle Interior noise. For this, objective measurement data of the vehicles driving in acceleration was measured. On the basis of analysis, psychoacoustic parameters were extracted and subjective evaluation was performed by noise and vibration expert evaluators. For the subjective evaluation, the paired comparisons and the semantic differential methods were used to evaluate sound quality of vehicle interior noise. By the paired comparison which evaluate two pairs of vehicle interior noise, the preference was estimated. With the semantic differential and the factor analysis, it was evaluated words of two pairs which expressed appropriately the sense of evaluator about noise source. Therefore the characteristics of the sound qualify for the vehicle were differentiated. From the results of both the correlation analysis and the multiple factor regression analysis, the sound quality evaluation model for the sense of human hearing was derived and indexed.

• Journal of Nutrition and Health
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• v.31 no.3
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• pp.354-362
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• 1998

The purposes of this study were to develop standardized indices of staffing needs in each school, foodservice system through work sampling methodology . Conventional school foodservices were classified into 5 groups depending on size of meals served. Commissary school foodservices were also classified into 5 groups by cluster analysis using number of meals served, number of satellite schools, and time for transportation of food. Work measurement through work sampling methodology was conducted in 15 conventional and 21 commissary foodservices during 3 consecutive days from September to October in 1995. Statistical data analysis was completed using the SAS programs for descriptive analysis, cluster analysis, and simple linear regression. The results were as follows : Average points of leveling factors of conventional and commissary foodservices were 1.066 and 1.061 , respectively. Mean labor hours per work force was 328 minutes and 366 minutes in conventional and commissary foodservice , respectively. Standardized work time was calculated using leveling factor, ILO allowance rate (175) , and observational work time. The model for standardized indices of staffing needs was developed based on simple linear regression in each school foodservice system. In conventional school foodservice systems(for 100-1,900 meals per day) standardized staffing needs=3.2497 +0.005267$\times$number of meals served (F=273.1, R-square 0.9750, p<0.001). In commissary school foodservice systems (for 200-1,600 meals per day ) Standardized staffing needs=3.393384 +0.0063$\times$number of meals served (F=30.78, R-square 0.6580, p<0.001).

• Journal of the Korea Fashion and Costume Design Association
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• v.14 no.2
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• pp.63-74
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• 2012

The purpose of this study was to find factors affecting satisfaction and intention to re-purchase fashion goods through social commerce. A questionnaire method was applied for 123 women aged from twenties to thirties, with buying experience in fashion goods through social commerce. Independent variables were service quality, fashion shopping orientation, and demographics. Factor analyses and multiple regression methods were used to analyze data. Factor analyses resulted in two factors for service quality and resulted in four factors for fashion shopping orientation. The results of multiple regression analyses showed that convenience & benefits and site layout factors of the service quality had significant impacts on satisfaction in fashion social commerce. Those two service quality factors, demographics like job, and satisfaction were shown significantly important to predict intention to re-purchase fashion goods on social commerce service. Intention to re-purchase was best explained in the model with satisfaction as an independent variable. Meanwhile, shopping orientation factors were not important in any model.

• Korean Journal of Environment and Ecology
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• v.22 no.2
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• pp.113-118
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• 2008

This study was carried out with the aim to provide basic data for efficient park management by analyzing satisfaction factors and estimated regression model through questionnaire survey method for the visitors to Bukhansan National Park in Korea. As a result of analysis, it was found that visitors are satisfied with such variables as 'illegal camping', 'cooking act' and 'padded bills' but extremely unsatisfied with 'waste problem', 'congestion', 'damage of visiting trails' and 'lack of cultural facilities'. In the result of satisfaction factors, it was revealed that 'facility management factor' was found to have the greatest effect on satisfaction degree. In the estimated model by Multiple Regression Analysis, 'damage of natural resources' and 'damage of cultural and historic resources', and 'lack of traffic facilities' were found to affect visitors' satisfaction.

• Journal of the Korea Institute of Building Construction
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• v.19 no.5
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• pp.439-448
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• 2019

There are various factors affecting the success and failure of an apartment building project. However, after the unit sale price has been determined and the sale has started, the most important factor affecting on the project is the initial sales ratio for one month after the sale. Generally, developers predict an initial sales ratio by various data such as economic situation, the trend of the housing market, and the house price near the business place. However, it is very difficult for these factors to be calculated quantitatively in connection with the initial sales ratio. Therefore, the purpose of this study is to develop a regression model for forecasting the initial sales ratio of apartment building projects. For this study, pre-sales data collection, correlation analysis between influencing factors, and regression model development are performed sequentially. The results of this study are used as basic data for predicting the initial sales ratio in the feasibility analysis of apartment building projects and are used as key data for the development of the risk management model.

• Journal of Digital Convergence
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• v.9 no.1
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• pp.51-59
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• 2011

The objective of this paper is to identify factors influencing intention to use ubiquitous banking service focusing on potential users using a regression model. Through this, providers of ubiquitous banking services can get an idea of future development, including marketing strategy through the results of this analysis. This paper proposes that perceived usefulness is the most important factor influencing the uptake of ubiquitous service. Also in addition, ANOVA test shows that higher education level of the user can lead to the higher intention to use an ubiquitous banking service. In this study, we set up a model by using the most basic factor among influential factors presented in previous studies as an independent variable. However, other research variables which affect acceptance of ubiquitous service should be considered by thinking more diversely.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.1
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• pp.47-51
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• 2018

This paper is concerned with an optimization design of Incremental Granular Model(IGM) based Genetic Algorithm (GA) as an evolutionary approach. The performance of IGM has been successfully demonstrated to various examples. However, the problem of IGM is that the same number of cluster in each context is determined. Also, fuzzification factor is set as typical value. In order to solve these problems, we develop a design method for optimizing the IGM to optimize the number of cluster centers in each context and the fuzzification factor. We perform energy analysis using 12 different building shapes simulated in Ecotect. The experimental results on energy efficiency data set of building revealed that the proposed GA-based IGM showed good performance in comparison with LR and IGM.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.359-364
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• 1999

Providing the reasonable construction cost at the initial stage of the rural development project, is a kety factor of the each step of project , such as propriety analysis , cost planning , design, and planning the progress of work. The explainable construction cost can be estimated at the early stage using the actual cost data by statistical analysis. In this study, the influence factors are extracted by factor analysis with the actual cost data of rural development project, object cost model is developed by multiple regression analysis, and verify the developed cost model by Monte-Carlo simulation .

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1253-1262
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• 2014

Regression tree is a tree-structured solution in which a simple regression model is fitted to the data in each node made by recursive partitioning of predictor space. There have been many efforts to apply tree algorithms to various regression problems like logistic regression and quantile regression. Recently, algorithms have been expanded to the panel data analysis such as RE-EM algorithm by Sela and Simonoff (2012), and extension of GUIDE by Loh and Zheng (2013). The algorithms are briefly introduced and prediction accuracy of three methods are compared in this paper. In general, RE-EM shows good prediction accuracy with least MSE's in the simulation study. A RE-EM tree fitted to business survey index (BSI) panel data shows that sales BSI is the main factor which affects business entrepreneurs' economic sentiment. The economic sentiment BSI of non-manufacturing industries is higher than that of manufacturing ones among the relatively high sales group.