• Journal of the Korean Data and Information Science Society
• /
• 제24권4호
• /
• pp.701-712
• /
• 2013

이러닝 (e-learning)산업통계는 이러닝산업 전반에 걸친 수요와 공급을 망라한 실태조사통계로 2004년 이후 정보통신산업진흥원에 의해 매년 발표되고 있다. 한국표준산업분류가 2008년 개정 (제9차)됨에 따라, 이러닝 수요부문의 사업체조사에 사용해온 표본설계 (종사자규모 산업분류별 층화추출)에 대한 개선이 필요하게 되었다. 본 논문은 사업체조사의 목표모집단을 개정된 한국표준산업분류에 따라 종사자규모 산업분류별로 층화하고, 각 층에 부여된 목표변동계수값을 만족시키는 멱배분법의 승수를 모의실험으로 찾아서 층화별로 표본의 크기를 결정하였다. 이와 더불어 본 연구에서 고려한 표본가중치 계산, 그리고 가중치를 반영한 모수추정량과 추정오차는 기존의 조사에서 사용된 기술 통계적 분석을 벗어나 업종별과 종사자 규모별 추정과 추정의 정도에 대한 평가를 가능하게 하였다.

• Nutrition Research and Practice
• /
• 제14권2호
• /
• pp.160-166
• /
• 2020

BACKGROUND/OBJECTIVES: The obese population is rapidly increasing because of reduced physical activity and a Westernized diet; consequently, various chronic diseases are more prevalent. With the increasing interest in body shape and appearance, research on body shape perceptions and accompanying weight control behaviors are needed for healthy weight management. SUBJECTS/METHODS: A cross-sectional survey was conducted on randomly selected 536 (209 men and 327 women) aged 20 to 65 years. Body mass index (BMI), body-shape perception, weight control behavior, quality of sleep, and place of residence were collected using self-reported questionnaires. Multivariable logistic regression analysis was conducted using complex design in each groups. Collected data were analyzed using the SAS 9.4 statistical package, and the significance level was set at P < 0.05. RESULTS: When these two variables were divided into four groups, they were found to influence dieting attempts. People with abnormal weights who were dissatisfied with their body shapes attempted dieting 5.23 times more than those with healthy weights and satisfaction with their body shapes. Further, those with normal weights but dissatisfaction with their bodies attempted dieting 4.45 times more than those who were satisfied with their shapes. Subjects in their 20s attempted dieting 2.53 times more than those in their 30s and 40s, and female subjects attempted dieting 2.24 times more than male subjects. CONCLUSIONS: A correct perception of one's shape can be an important factor for dietary behavior, as body shape perceptions and dieting attempts are strongly related. Additionally, healthy weight management and nutrition education are important elements to incorporate into a weight control program aimed at preventing excessive weight control behaviors and promoting correct perceptions of body shape.

• KIEAE Journal
• /
• 제9권3호
• /
• pp.21-27
• /
• 2009

The goal of this paper is to determine the suitability evaluation indices of a riverside reservoir space planning by classifying major indicators and calculating AHP(Analytical Hierarchy Process) based weights of them. The major indicators were set up based on literature review and questionnaire survey to experts. Four indicator categories were developed: location, environment, resource availability and economical efficiency. And they were divided into 12 sub-categories for calculating AHP-based weights. First, as for the major indicator categories, the calculation shows that the weighted index of environment is the most important at 0.458, followed by location at 0.128, economical efficiency at 0.170 and resource availability at 0.154. This suggests that environment is getting more public attention and the reservoir is regarded as a facility that is connected to a river. Those weight values were considered in calculating final weights for each of 12 sub-categories. Among them water quality and ecological environment take top ranks at 0.190 and 0.186, respectively. The lower ranks include access 0.112, resource availability of site 0.082, tourism resource 0.078, users 0.076, available land 0.052, area of site 0.031, shape of site and deterioration level 0.030 and percentage of private land 0.030 - which represents general considerations in other space planning. The difference of the top rank (water quality, 0.190) and the last one (percentage of private land, 0.027) is 0.163. The above result shows that users regard environmental aspect and resource availability more important than easiness of construction.

• 자원환경지질
• /
• 제35권1호
• /
• pp.67-74
• /
• 2002

본 연구의 목적은 산사태 취약성 분석을 위하여 인공신경망을 이용하여 산사태 요인의 가중치를 결정하는 것이다. 산사태 발생 지역은 항공사진, 현장조사와 지형도 등으로부터 위치를 파악하였다. 용인 지역에 대해서 산사태에 영향을 주는 지형경사, 지형곡률, 토양배수, 토양 유효심도, 토양 종류, 식생 경급과 영급 등의 자료가 사용되었다. 이들 자료를 이용하여 인공신경망의 층간 가중치가 역전파 트레이닝 알고리즘에 의해 계산되었으며, 이는 산사태 요인의 가중치를 결정하는데 사용되었다. 죽, 트레이닝 후 층간 가중치를 해석하여 분류에 미치는 영향을 고려함으로서 각 산사태 요인의 가중치가 결정되게 된다. 가장 높은 값은 지형경사로서 5.33의 값을 나타냈으며 지형 곡률과 토질은 각각 1과 1.17로 낮은 값을 나타냈다. 역전파 알고리즘을 이용한 가중치 결정 방법은 분석에 중요하지 않은 요인을 제거함으로 계산시간을 단축시킬 수 있어 GIS를 이용한 중첩 분석 연구에 활용되 수 있다.

• 한국지반공학회:학술대회논문집
• /
• 한국지반공학회 2002년도 가을 학술발표회 논문집
• /
• pp.499-506
• /
• 2002

The purpose of this study is to develop landslide susceptibility analysis techniques using artificial neural networks and to apply the newly developed techniques for assessment of landslide susceptibility to the study area of Yongin in Korea. Landslide locations were identified in the study area from interpretation of aerial Photographs and field survey data, and a spatial database of the topography, soil type and timber cover were constructed. The landslide-related factors such as topographic slope, topographic curvature, soil texture, soil drainage, soil effective thickness, timber age, and timber diameter were extracted from the spatial database. Using those factors, landslide susceptibility and weights of each factor were analyzed by two artificial neural network methods. In the first method, the landslide susceptibility index was calculated by the back propagation method, which is a type of artificial neural network method. Then, the susceptibility map was made with a GIS program. The results of the landslide susceptibility analysis were verified using landslide location data. The verification results show satisfactory agreement between the susceptibility index and existing landslide location data. In the second method, weights of each factor were determinated. The weights, relative importance of each factor, were calculated using importance-free characteristics method of artificial neural networks.

• 인간식물환경학회지
• /
• 제24권6호
• /
• pp.663-672
• /
• 2021

Background and objective: As the 'Healing Agriculture Research and Development and Promotion Act' came into effect on March 25, 2021, social interest in agro-healing has been increasing exponentially. This study was conducted to analyze the priorities of agro-healing classification system and to provide basic data to inform policy directions and related research for the development and activation of agro-healing. Methods: The survey data collected from 18 experts were analyzed using the analytic hierarchy process (AHP) method in determine the relative weights of the main and sub-criteria for the classification system. There were three main criteria identified: agro-healing input industry, agro-healing service industry, and agro-healing-related/derived industry. There were also 11 sub-criteria. Results: The top three sub-criteria with the highest complex weights include "community service," "social rehabilitation" and "treatment and rehabilitation," all of which correspond to the main criterion "agro-healing service industry". In addition, the complex weights of the sub-criteria corresponding to the main criterion "agro-healing related/derived industry" are as follows: "other agro-healing support service," which ranked 4th, and "training and education institutions for agro-healing experts," which ranked 5th when prioritizing the criteria. Conclusion: The results of this study suggest that the main criterion to be considered first in establishing a classification system is "agro-healing service industry". Therefore, it is necessary to continue research on detailed service classifications and systems with verified validity to ensure expertise in human resources, and organization related to social purpose services in agro-healing.

• 대한토목학회논문집
• /
• 제12권4호
• /
• pp.107-116
• /
• 1992

도로교의 안전수준에 영향을 미치는 것은 주로 과적중차량이다. 계속 증가하는 과적중차량의 문제는 오래전 부터 매우 심각한 상태인 것으로 지적되어오고 있다. 따라서 여러나라에서 차량하중의 특성에 관한 연구가 활발히 이루어지고 있으며, 일부에서는 이러한 변화를 반영하기 위하여 도로교 설계활하중을 개선하였다. 본 연구에서는 차량하중 및 통행특성의 자료를 수집하여 차량형식, 차량총중량, 축중분배, 차종혼입율, 연행특성 등을 분석하고 합리적인 모형을 제시하였다. 또한 차량하중이 도로교에 미치는 하중효과를 교량형식에 따라 분석하여 현행 도로교 설계관련 규정들이 내포하고 있는 안전수준에 대한 분석을 실시하였다.

• Journal of Construction Engineering and Project Management
• /
• 제6권3호
• /
• pp.1-7
• /
• 2016

The purpose of this paper is to develop a model for selecting the best contractor in the Gaza Strip using the Artificial Neural Network (ANN). The contractor's selection methods and criteria were identified using a field survey. Fifty four engineers were asked to fill a questionnaire that covers factors related to the selection criteria of contractors practiced in Gaza Strip. The results shows that the dominant part of respondents (91%) confirmed that the current awarding method "the lowest bid price" is considered one of the major problems of the construction sector, "award the bid to the highest weight after combination of the technical and financial scores" represented 50% of the respondents. The criteria weights were determined based on Relative Importance Index (RII. Ninety-one tenders(13 projects) were used to train and test the ANN model after re-evaluating the contractors depend on the weights of factors to select the best contractor who achieves the highest score. Neurosolution software was used to train the models. The results of the trained models indicated that neural network reasonably succeeded in selection the best contractor with 95.96% accuracy. The performed sensitivity analysis showed that the profitability and capital of company are the most influential parameters in selection contractors. This model gives chance to the owner to be more accurate in selecting the most appropriate contractor.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
• /
• pp.294-297
• /
• 2004

The purpose of this study was to develop landslide susceptibility analysis techniques using artificial neural networks and then to apply these to the selected study area of Janghung in Korea. We aimed to verify the effect of data selection on training sites. Landslide locations were identified from interpretation of satellite images and field survey data, and a spatial database of the topography, soil, forest, and land use was constructed. Thirteen landslide-related factors were extracted from the spatial database. Using these factors, landslide susceptibility was analyzed using an artificial neural network. The weights of each factor were determined by the back-propagation training method. Five different training datasets were applied to analyze and verify the effect of training. Then, the landslide susceptibility indices were calculated using the trained back-propagation weights and susceptibility maps were constructed from Geographic Information System (GIS) data for the five cases. The results of the landslide susceptibility maps were verified and compared using landslide location data. GIS data were used to efficiently analyze the large volume of data, and the artificial neural network proved to be an effective tool to analyze landslide susceptibility.

• 대한가정학회지
• /
• 제23권4호
• /
• pp.33-54
• /
• 1985

The purpose of this study is to establish the suitable wearing standard under environmental thermal conditions in Pusan. The data is obtained from 50 girl students from April, 1984 to March, 1985. Items of the research are as follows : Environmental conditioni, clothing weight, contents of wearing, clothing climate, wearing order etc. RESULTS : 1. The upper clothing wights are varied considerably with temperature, while the lower are not. 2. The outdoor temperature and the total clothing weights show the high negative correlation of r=-.97 wth regression equation of Y=-37.64X+1692.66. 3. The clothing weight per clo is 390g/$m^2$. 4. Mostly, subjects were 2~7kinds of the upper and 3~5kinds of the lower clothing. 5. The clothing weights on the upper part of the body are heavier than those on the lower part of it. 6. The standard deviation of the obver clothing is larger than that of the under clothing. 7. The clothing shape of comfort-sensation reporter changes with variation of temperature. 8. The clothing climate of the inner layer is 32.26$\pm$$0.5^{\circ}C$ in temperature, 43.6$\pm$7% in humidity at four seasons. 9. It is represented that total subjects and comfort-sensation reporter control the wearing contents suitably for temperature. 10. The standard of wearing in Pusan is established as Fig. 6.