• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.1
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• pp.39-48
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• 2010

Recreation forests are in the spotlight as the place for personality development, mind and body comfort, companionship, and environment education in forests and valleys. Visitors to recreation forests have been on the increase along with booming in recreation forest building since 1988. Recreation forests are being categorized according to some features such as regional and environmental condition. Recreation forests, however, have not met the expectations of some visitors who want to take a rest with calmness due to the influence of the 5-day-work-week system, increasing interest in rest, leisure, and well-being, and users converge during weekends, summer, and the tourist season. In order to improve visitors' satisfaction efficiently, this study surveyed the level of satisfaction in each cluster based on the precedent study which had classified 85 national or public recreation forests in Korea into clusters. Questionnaires were distributed properly to each cluster and, of the 1,132 questionnaires collected, 1,015 were valid and used for analysis. Reliability of questionnaires and statistical validity of the model were verified. As a result, there are meaningful differences in the ranking of independent variables which affect the level of satisfaction according to clusters. Variables in rest and fatigue recovery have the strongest influence on the level of satisfaction in the clusters of potential factor, internal activation factor, and mixed potential capacity factor. In the use performance and visiting condition factor cluster, appropriateness of visit cost is most influential and, in the education cluster, connectivity with tourist attractions around it is most affective. These results can provide priority in services and maintenance of recreation forests for improving the level of satisfaction and differentiate the distribution of resources according to clusters.

• Journal of agricultural medicine and community health
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• v.26 no.1
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• pp.37-56
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• 2001

This study was conducted to analyze the degree of changes in knowledge and attitude toward smoking and to examine the factors affecting knowledge and attitude for smoking after providing a smoking prevention program based on social influence model for a year to middle school students. Study population consists of 665 subjects of middle school students(aged 14 years) in Gumi city in Kyeongsangbukdo Province. Among them three-hundred sixty-seven students(intervention group) were educated to a smoking prevention program for 1 year from April 1999 to April 2000. School-based four-class program to prevent smoking was developed. The program provides instruction about short and long-term negative physiologic and social consequences of smoking and also discussed the health hazards of smoking, social pressure to smoke, peer norms regarding tobacco use, and refusal skill. A 45-item self-administered structured questionnaire was designed to evaluate the change of knowledge, attitude, smoking rate and the amount of smoking. The instrument was comprised of 11 knowledge items, thirteen attitude item and demographic items. Each scales were created by summing responses to each items within each scales and high scores on the knowledge, attitude, and smoking behavioral intention scales indicated positive responses. Based on the changes before and after the implementation of smoking prevention program between intervention and control group, the change of scores on knowledge were significantly different between the control group and the intervention group(p<0.05) and the change of scores on the attitude toward smoking was significantly different between intervention and control group. The change of smoking rate were not showing a significant difference between two groups but the amount of smoking were significantly reduced in intervention group than control group. In multiple regression analysis on changes of knowledge about smoking, the variables of smoking prevention program education, previous knowledge on smoking and students' school performance were selected the significant variables. In multiple regression to analysis of the factors influencing changes in attitude toward smoking, the variables of smoking prevention program education, previous knowledge on smoking were shown to be significant. The smoking prevention program was effective on change of knowledge and attitude of middle school students. In considering that the policy should be needed to extent of implementation of school-based health education curricula based on social influence model and it would contribute to reduce smoking of students.

• The Journal of Korean Society for Radiation Therapy
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• v.22 no.2
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• pp.97-103
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• 2010

Purpose: Treating same region with different modalities there is a limit to evaluate the total absorbed dose of normal tissues. The reason is that it does not support to communication each modalities yet. In this article, it evaluates absorbed dose of the patients who had been treated same region by a tomotherapy and a linear accelerator. Materials and Methods: After reconstructing anatomic structure with a anthropomorphic phantom, administrate 45 Gy to a tumor in linac plan system as well as prescribe 15 Gy in tomotherapy plan system for make an ideal treatment plan. After the plan which made by tomoplan system transfers to the oncentra plan system for reproduce plan under the same condition and realize total treatment plan with summation 45 Gy linac treatment plan. To evaluate the absorbed dose of two different modalities, do a comparative study both a simple summation dose values and integration dose values. Then compare and analyze absorbed dose of normal tissues and a tumor with the patients who had been exposured radiation by above two differents modalities. Results: The result of compared data, in case of minimum dose, there are big different dose values in spleen (12.4%). On the other hand, in case of the maximum dose, it reports big different in a small bowel (10.2%) and a cord (5.8%) in head & neck cancer patients, there presents that oral (20.3%), right lens (7.7%) in minimum dose value. About maximum dose, it represents that spinal (22.5), brain stem (12%), optic chiasm (8.9%), Rt lens (11.5%), mandible (8.1%), pituitary gland (6.2%). In case of Rt abdominal cancer patients, there represents big different minimum dose as Lt kidney (20.3%), stomach (8.1%) about pelvic cancer patients, it reports there are big different in minimum dose as a bladder (15.2%) as well as big different value in maximum dose as a small bowel (5.6%), a bladder (5.5%) in addition, making treatment plan it is able us to get. Conclusion: In case of comparing both simple summation absorbed dose and integration absorbed dose, the minimum dose are represented higher as well as the maximum dose come out lower and the average dose are revealed similar with our expected values data. It is able to evaluate tumor & normal tissue absorbed dose which could had been not realized by treatment plan system. The DVH of interesting region are prescribed lower dose than expected. From now on, it needs to develop the new modality which are able to realize exact dose distribution as well as integration absorbed dose evaluation in same treatment region with different modalities.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.3
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• pp.543-560
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• 2018

With the increased development in downtown underground space facilities that vertically cross under a railway at a shallow depth, the demand for non-open cut method is increasing. However, most construction sites still adopt the pipe roof method, where medium and large diameter steel pipes are pressed in to form a roof, enabling excavation of the inside space. Among the many factors that influence the loosening region and loads that occur while pressing in steel pipes, the size of the pipe has the largest impact, and this factor may correspond to the magnitude of load applied to the underground structure inside the steel pipe roof. The super equilibrium method (SEM) has been developed to minimize ground disturbance and loosening load, and uses small diameter pipes of approximately 114 mm instead of conventional medium and large diameter pipes. This small diameter steel pipe is called an SEM pile. After SEM piles are pressed in and the grouting reinforcement is constructed, a crossing structure is pressed in by using a hydraulic jack without ground subsidence or heaving. The SEM pile, which plays the role of timbering, is a fore-poling pile of approximately 5 m length that prevents ground collapse and supports surface load during excavation of toe part. The loosening region should be adequately calculated to estimate the spacing and construction length of the piles and stiffness of members. In this paper, we conducted a comparative analysis of calculations of loosening load that occurs during the press-in of SEM pile to obtain an optimal design of SEM. We analyzed the influence of factors in main theoretical and empirical formulas applied for calculating loosening regions, and carried out FEM analysis to see an appropriate loosening load to the SEM pile. In order to estimate the soil loosening caused by actual SEM-pile indentation and excavation, a steel pipe indentation reduction model test was conducted. Soil subsidence and soil loosening were investigated quantitatively according to soil/steel pipe (H/D).

• Journal of the Korean Society of Radiology
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• v.17 no.2
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• pp.257-265
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• 2023

The purpose of this study was to vaccinate every year according to the general characteristics of COVID-19, whether to vaccinate every year according to the vaccination experience, whether to vaccinate every year according to knowledge/attitude about vaccination, and negative responses to the vaccinate every year In order to understand the factors affecting the vaccination physician every year by identifying the factors of Statistical analysis is based on general characteristics, variables based on vaccination experience, and knowledge/attitudes related to vaccination. The doctor calculates the frequency and percentage, A square test (-test) was performed, and if the chi-square test was significant but the expected frequency was less than 5 for 25% or more, a ratio difference test was performed with Fisher's exact test. Through multiple logistic regression analysis using variables that were significant in simple analysis, a predictive model for future vaccination and the effect size of each independent variable were estimated. As statistical analysis software, SAS 9.4 (SAS Institute Inc., Cary, NC, USA) was used, and because the sample size was not large, the significance level was set at 10%, and when the p-value was less than 0.10, it was interpreted as statistically significant. In the simple logistic regression analysis, the reason why they answered that they would not be vaccinated every year was that they answered 'to prevent infection of family and hospital guests' rather than 'to prevent my infection' as the reason for the vaccination. It was 11.0 times higher and 3.67 times higher in the case of 'for the formation of collective immunity of the local community and the country'. The adverse reactions experienced after the 1st and 2nd vaccination were 8.42 times higher in those who did not experience pain at the injection site than those who did not, 4.00 times higher in those who experienced swelling or redness, and 5.69 times higher in those who experienced joint pain. There was a 5.57 times higher rate of absenteeism annually than those who did not. In addition, the more anxious they felt about vaccination, the more likely they were to not get the vaccine every year by 2.94 times.