• Journal of Preventive Medicine and Public Health
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• v.20 no.1 s.21
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• pp.67-83
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• 1987

This study relates to the problems of organizational performance in the Christian hospitals. In this study, quality of working life (QOWL), which harmonizes individual as well as organizational goals, was used as an indicator of organizational performance from the open systems view. In order to identify the behavioral factors influencing QOWL in hospitals, self-administered questionnaires were distributed to 1,926 employees who were randomly selected from fifteen Christian hospitals from August 1 to August 30, 1986. The following results were obtained: 1) All correlation coefficients between QOWL and behavioral variables were statistically significant even though their magnitude varied according to hospital size. 2) Using factor analysis, 32 variables were parsimoniously grouped into four factors: individual conflicts, group behavior, organizational characteristics and situation, and job characteristics. The proportion of variance explained by these factors ranged from 33.5% to 38.6% according to hospital size. 3) The overall effects of the four factors in the multiple logistic models ranged from 0.85 to 3.12 according to hospital size. Among three hospital models, the model for small hospitals showed the best statistical fit. 4) The most influential factor was organizational characteristics and situation with an odds ratio ranging from 1.99 to 3.02. Again, the odds ratio was the highest for small hospitals. 5) For large hospitals, the two main factor effects were statistically significant: organizational characteristics and situation, and job characteristics. For medium hospitals, all main factor effects except job characteristics were statistically significant. For small hospitals, all main factor effects except group behavior were statistically significant. However, a factor interaction effect was shown only for large hospitals where it was statistically significant. 6) To examine whether the four factors influence financial performance, the four factor scores from the two financial performance groups were compared using Mann-Whitney test. The test results showed that the organizational characteristics and situation factor score was significantly different only for small hospitals.

• Journal of the Korean Geosynthetics Society
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• v.15 no.2
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• pp.13-24
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• 2016

The safety factor of an infinite slope tends to be analyzed as lower when the effects of root cohesion are not considered into the equation. Thus, it is essential to consider regional characteristics such as root cohesion and crown density in order to obtain a reasonable safety factor value. In this study, The safety factor of the landslide model, both before and after considering crown density and root cohesion, was calculated and a comparative analysis was carried out. The safety factor is increased by the effect of roots cohesion of the analysis results, the amount of increase in safety factor along the inclination of the slope angle has been analyzed with various things, the effect of reinforcing the roots cohesion, slope of the lower angle it was found that the higher the safety factor increase.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.6
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• pp.44-49
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• 2008

Contract power conversion factor which is applied to estimate contract power of industrial customers is an important standard to caculate transformer capacity. This paper shows a reasonable contract power conversion factor, that was made by the systematic and statistical way considering actual conditions, such as investigated contact power and peak power for the last 5 years of each customer for 349 industrial customers as to AMR. In this dissertation, it is necessary to analyze the key features and general trend from the investigated data. It made an analysis of the feature parameters, such as average, standard deviation, median, maximum, minimun and thus it was carried by the linear and nonlinear regression analysis. Therefore, this paper compared characteristics for a contract power conversion factor which is a lied to calculate contract power with characteristics for a regression model for customers which maximum utilization factor of transformer is more than 60(%).

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.5
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• pp.80-85
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• 2008

Contract power conversion factor which is applied to estimate contract power of general customers is an important standard to caculate transformer capacity. This paper shows a reasonable contract power conversion factor, that was made by the systematic and statistical way considering actual conditions, such as investigated contract power and peak power for the last 5 years of each customer for 461 general customers as to AMR. In this dissertation, it is necessary to analyze the key features and general trend from the investigated data It made an analysis of the feature parameters, such as average, standard deviation, median, maximum, minimun and thus it was carried by the linear and nonlinear regression analysis. Therefore, this paper compared characteristics for a contract power conversion factor which is applied to estimate contract power with characteristics for a regression model for customers which maximum utilization factor of transformer is more than 60[%].

• Journal of Korean Society of Rural Planning
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• v.27 no.3
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• pp.35-46
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• 2021

Ecosystem services play a role in promoting sustainable development by contributing to human welfare. For sustainable development, a balance between supply and demand for ecosystem services must be made. In this regard, in this study, factor analysis was performed using the results of measuring ecosystem services for the supply of ecosystem services and national statistical data representing socio-economic factors for demand for ecosystem services The results of analysis for Gyeong-gi Province are as follows. The service supply based on the result of ecosystem services was divided into the mixed service provisioning as factor1, the food provisioning as factor2, and the P retention service provisioning area as factor3. As for the demand for services based on socio-economic factors, factor1 is divided into urbanized areas, factor2 is forest development area, and factor3 is agricultural activity development area. Local governments that maintain balance were evaluated as Pocheon, Yangpyeong, Icheon, Pyeongtaek, Goyang, Suwon, Gwangmyeong, and Osan, and imbalanced local governments appeared in Gimpo, Uiwang, Anseong, and Yeoju. A management plan to maintain the balance between supply and demand of ecosystem services was suggested. The analysis method and results of this study are expected to be applicable to various local governments through regional expansion.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.17-24
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• 2008

Traffic accident forecasting model has been developed steadily to understand factors affecting traffic accidents and to reduce them. In Korea, the length of highways is over 3,000km, and it is within the top ten in the world. However, the number of accidents-per-one kilometer highway is higher than any other countries. The rapid increase of travel demand and transportation infrastructures since 1980's may influence on the high rates of traffic accident. Accident severity is one of the important indices as well as the rate of accident and factors such as road geometric conditions, driver characteristics and type of vehicles may be related to traffic accident severity. However, since all these factors are interacted complicatedly, the interactions are not easily identified. A structural equations model is adopted to capture the complex relationships among variables. In the model estimation, we use 2,880 accident data on highways in Korea. The SEM with several factors mentioned above as endogenous and exogenous variables shows that they have complex and strong relationships.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.487-496
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• 2000

In this paper, the Multi-FNN(Fuzzy-Neural Networks) model is identified and optimized using HCM(Hard C-Means) clustering method and genetic algorithms. The proposed Multi-FNN is based on Yamakawa's FNN and uses simplified inference as fuzzy inference method and error back propagation algorithm as learning rules. We use a HCM clustering and Genetic Algorithms(GAs) to identify both the structure and the parameters of a Multi-FNN model. Here, HCM clustering method, which is carried out for the process data preprocessing of system modeling, is utilized to determine the structure of Multi-FNN according to the divisions of input-output space using I/O process data. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. The aggregate performance index stands for an aggregate objective function with a weighting factor to consider a mutual balance and dependency between approximation and predictive abilities. According to the selection and adjustment of a weighting factor of this aggregate abjective function which depends on the number of data and a certain degree of nonlinearity, we show that it is available and effective to design an optimal Multi-FNN model. To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.

• Journal of the Korea Institute of Building Construction
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• v.18 no.5
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• pp.489-498
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• 2018

The purpose of this study was to propose a decision support model for selecting a lifting method of large spatial roof construction. First, we deducted influential factors consist of 6 factors and 19 sub-factors through literature reviews and expert's advices. Second, the relative importance of each factor was calculated by Analytic Hierarchy Process. As a result, 'site condition(0.237)' among 6 factors and 'available space of the site(0.118)' among 19 sub-factors were identified as the most important factor for selecting lifting method. In addition, methods and procedures were established for evaluating alternatives of lifting methods for each influential factor. A decision support model was completed by providing the Site Suitability Index(SSI) of each lifting method. Finally, we got advices form experts who were actually in charge of the works for large spatial construction project to validate the model. The model proposed in this study was analyzed to be useful in selecting the lifting method. The findings of this study are expected to support the decision making of on-site managers when they select the lifting method on the beginning of the project.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.343-350
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• 2000

In this paper, we propose the Multi-FPNN(Fuzzy Polynomial Neural Networks) model based on FNN and PNN(Polyomial Neural Networks) for optimal system identifacation. Here FNN structure is designed using fuzzy input space divided by each separated input variable, and urilized both in order to get better output performace. Each node of PNN structure based on GMDH(Group Method of Data handing) method uses two types of high-order polynomials such as linearane and quadratic, and the input of that node uses three kinds of multi-variable inputs such as linear and quadratic, and the input of that node and Genetic Algorithms(GAs) to identify both the structure and the prepocessing of parameters of a Multi-FPNN model. Here, HCM clustering method, which is carried out for data preproessing of process system, is utilized to determine the structure method, which is carried out for data preprocessing of process system, is utilized to determance index with a weighting factor is used to according to the divisions of input-output space. A aggregate performance inddex with a wegihting factor is used to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of this aggregate abjective function which it is acailable and effective to design to design and optimal Multi-FPNN model. The study is illustrated with the aid of two representative numerical examples and the aggregate performance index related to the approximation and generalization abilities of the model is evaluated and discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.5
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• pp.741-749
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• 2018

The purpose of this study is to propose a rational and scientific damage calculation model in relation to damages caused by bid rigging in construction projects. Previous studies and precedents in relation to calculating damages from bid rigging suggest that the main issue was the lack of consideration in standards for deciding successful bids, selection of inadequate standard comparative markets, insufficiency in analyzing the appropriateness of competitive bid price influence factors, and absence of calculation model verification. In order to improve on these issues, a damage calculation method on alternative tenders for construction projects was proposed. For this calculation model, first, a standard market adequate to the successful bid selection standards was determined, second, an appropriate factor was selected by analyzing the correlation between competitive bid price influence factors, and third, a regression analysis was conducted on the selected factor. Lastly, this was demonstrated through verification of appropriateness, significance & normality of the proposed model and application of actual bid rigging cases. Through the proposed calculation model, this study seeks to serve as a base to prevent opportunity damages for parties involved in related court cases by early resolution of disputes and relief from issues of unfair damage burdens on a particular party.