• Spatial Information Research
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• v.8 no.1
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• pp.141-153
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• 2000

The purpose of this study is to develop and apply spatial landslide information system using Geographic information system (GIS) in concerned with spatial data. Landslide locations detected from interpretation of aerial photo and field survey, and topographic , soil , forest , and geological maps of the study area, Yongin were collected and constructed into spatial database using GIS. As landslide occurrence factors, slope, aspect and curvature of topography were calculated from the topographic database. Texture, material, drainage and effective thickness of soil were extracted from the soil database, and type, age, diameter and density of wood were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the Landsat TM satellite image. In addition, landslide damageable objects such as building, road, rail and other facility were extracted from the topographic database. Landslide susceptibility was analyzed using the landslide occurrence factors by probability, logistic regression and neural network methods. The spatial landslide information system was developed to retrieve the constructed GIS database and landslide susceptibility . The system was developed using Arc View script language(Avenue), and consisted of pull-down and icon menus for easy use. Also, the constructed database can be retrieved through Internet World Wide Web (WWW) using Internet GIS technology.

• Korean Journal of Construction Engineering and Management
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• v.11 no.6
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• pp.100-110
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• 2010

The main roots of CM service contracts include existing customer repurchases and those made by new customers by existing ones. The study on customers and loyalty can be factors to strengthen CM's competitiveness. However, there have been little attempt to study customer satisfaction and customer loyalty. Construction Management (CM), the advanced construction management method, was introduced 15 years ago in the mid 1990's in the domestic market. The aim of this research is to build a model that can predict customer loyalty based on how much customers are satisfied with CM service. To measure customer satisfaction and loyalty, this research surveyed 135 decision-makers who have experienced CM services. Customer satisfaction was tested and analyzed according to different phases: planning, designing, procurement, construction, and post construction. Referral intention was tested based on NPS theory. Customer types were divided into detractors, passively satisfied and promoters according to the tested measurement and multinomial logistic regression between the satisfaction by construction phases and customer types. This research resulted to a model that can predict customer types: detractors, passively satisfied and promoters, which were determined according to satisfaction level. The initial planning phase also revealed which factor is most influential for a customer to become promoter. These results can be used to acquire customer loyalty by managing the satisfaction of customers through a project under an Internet-based environment. Such can provide the needed information in quickly exploring positive and negative word-of-mouth feedbacks.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.249-258
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• 2004

오늘날 활발하게 이루어지고 있는 유비쿼터스 컴퓨팅 관련 기술 연구는 사용자가 시간과 장소에 구애받지 않고 네트워크에 접근해 다양한 컴퓨터 관련 서비스를 제공 받을 수 있는 방법에 초점을 맞추고 있다. 이 처럼 시간과 공간의 한계를 뛰어 넘은 네트워크로의 자유로운 접근은 일상 생활의 패러다임을 바꾸어 놓게 될 것이다. 유비쿼터스 컴퓨팅 기술을 통해 가장 큰 변화가 일어나는 분야는 일반 가정환경에서 일어나는 인텔리전트 홈 네트워크 (Intelligent Home Network) 라고 할 수 있다. 집에 들어오면, 자동으로 문을 열어주고, 불을 켜주며, 놓쳤던 TV 프로그램을 자동으로 녹화해 놓았다가 원하는 시간에 보여주고, 적당한 시간에 목욕물을 미리 받아준다. 또한 집밖으로 나가기 전, 일기예보에 따라 우산을 챙겨주고, 일정을 확인시켜주며 입고 나갈 옷을 골라줄 수도 있다. 이 모든 일들이 유비쿼터스 컴퓨팅 기술이 가져올 인텔리전트 홈 네트워크의 모습이다. 그러나, 모든 사용자에게 효과적인 서비스를 제공하기 위해서는 홈 네트워크 상의 자원 관리에서 일어날 수 있는 에이전트들간의 자원 접근 권한 충돌을 효율적으로 방지할 수 있는 기술이 필요하다. 유비쿼터스 컴퓨팅 환경에서 자원관리 특성은 점유의 연속성, 자원 사이의 연관성, 그리고 자원과 사용자 사 사이의 연계성의 3 가지 특성을 지니고 있다. 본 논문에서는 유비쿼터스 컴퓨팅 환경에서 일어날 수 있는 자원 충돌 상황을 효율적으로 처리하기 위한 자원 협상 방법을 제안한다. 본 방법은 자원 관리 특성을 바탕으로 시간논리에 기반을 둔 자원 선점과 분배 규칙으로 구성된다.트 시스템은 b-Cart를 기반으로 할 것으로 예측할 수 있다.타났다. 또한, 스네이크의 초기 제어점을 얼굴은 44개, 눈은 16개, 입은 24개로 지정하여 MER추출에 성공한 영상에 대해 스네이크 알고리즘을 수행한 결과, 추출된 영역의 오차율은 각각 2.2%, 2.6%, 2.5%로 나타났다.해서 Template-based reasoning 예를 보인다 본 방법론은 검색노력을 줄이고, 검색에 있어 Feasibility와 Admissibility를 보장한다.매김할 수 있는 중요한 계기가 될 것이다.재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data b

• Journal of Digital Convergence
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• v.17 no.3
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• pp.107-117
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• 2019

In the era of SNS, many people relies on it to express their emotions about various kinds of products and services. Therefore, for the companies eagerly seeking to investigate how their products and services are perceived in the market, emotion mining tasks using dataset from SNSs become important much more than ever. Basically, emotion mining is a branch of sentiment analysis which is based on BOW (bag-of-words) and TF-IDF. However, there are few studies on the emotion mining which adopt feature selection (FS) methods to look for optimal set of features ensuring better results. In this sense, this study aims to propose FS methods to conduct emotion mining tasks more effectively with better outcomes. This study uses Twitter and SemEval2007 dataset for the sake of emotion mining experiments. We applied three FS methods such as CFS (Correlation based FS), IG (Information Gain), and ReliefF. Emotion mining results were obtained from applying the selected features to nine classifiers. When applying DT (decision tree) to Tweet dataset, accuracy increases with CFS, IG, and ReliefF methods. When applying LR (logistic regression) to SemEval2007 dataset, accuracy increases with ReliefF method.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.350-362
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• 2019

The purpose of this study was to examine the effects of job characteristics and health on accident experience by analyzing the data of transportation workers according to age. The analysis used data from 'the fourth Korean Working Conditions Survey(KWCS)'. A total of 1,997 transport workers data were finally analyzed, and correlation analysis, crossover analysis and logistic regression analysis were performed. It was confirmed that there was no correlation between the age of the transport workers and the accident experience. In the relationship between the characteristics of transportation workers and the experience of the accident, it was found that, in the case of older workers, there was a significant effect in the order of 'at mistake someone else hurt', 'musculoskeletal problem', 'cardiovascular problem' and 'repetitive movements of hands or arms', the model explaining power was 56.9%(p <.01). In the case of non-older workers, it was found that 'depression and anxiety disorder', 'relationship between job and safety', 'at mistake someone else hurt' and 'labor union', the model explaining power was 21.8%(p <.01). Therefore, in order to promote prevent accidents of transportation workers in future, it is necessary to consider various variables such as health and job characteristics besides age.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.42-52
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• 2021

This study was conducted to identify the influence of the discrimination experienced in daily life and social isolation on depression among older adults living in the community. This study was a secondary analysis of the data of 2017 Living Profiles of Older Adults Survey. The participants was a representative sample among the older adults 65 years and older. Data from 10,041 older adults were analyzed for this study. Hierarchical logistic regression analyses were used. When the discrimination experiences was added in model 1, the likelihood of being depressed was 1.95(1.60-2.36) times higher for those who experienced discrimination comparing with those who didn't experienced discrimination. When the social isolation was added in model 2, the likelihood of being depressed was 1.89(1.55-2.30) times higher in those who experienced discrimination. In addition, as the number of close friends, neighbors, and acquaintances decreased by one, the likelihood of being depressed increased by 1.14 times. Those who were isolated from family, friends, neighbors and acquaintances were 3.90 times more likely to be depressed. Therefore, social efforts are needed to reduce the experience of discrimination. Maintaining a social network or creating a new network will contribute to lowering the level of depression in older adults who have experienced discrimination.

• Information Systems Review
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• v.22 no.3
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• pp.143-156
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• 2020

Price promotion is one of the most frequently marketing strategies with a long history. According to various studies, the effect of price promotion is controversial. Some studies have argued that price promotion has a positive effect, while others have found that it has no effect or rather has a negative effect. This study aims to examine the effect of price promotion in a subscription-based service. First, we check the effect of price promotion on the repurchase of the consumer. And we investigate how this effect varies depending on the characteristics of the consumer. Using the data from one of the music streaming service in South Korea, the effect of consumers' price promotion experience, demographic characteristics, and behavioral characteristics on their repurchase is analyzed through logistic regression analysis. As a result of the study, it is found that consumers' experience of price promotion has a positive effect on repurchase. In addition, the positive effect of price promotion is relatively greater in younger and female consumers. This study has implications in that it not only confirmed the positive effect of price promotion in a subscription-based environment but also empirically confirmed that the characteristics of consumers should be considered when performing price promotion.

• Journal of Industrial Convergence
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• v.22 no.6
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• pp.107-120
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• 2024

This study aimed to identify factors associated with metabolic abnormalities in non-obese and obese postmenopausal women based on biopsychosocial model. Secondary data analysis was conducted using data from 5,335 postmenopausal women who participated in the Korean National Health and Nutrition Examination Survey (2015-2021). According to logistic analysis with applying a complex simple analysis in SPSS 26.0, biomedical (increased age; a family history of hypertension, type 2 diabetes, dyslipidemia, and cardiovascular diseases) and biosocial factors (low educational level) were associated with 1-2 metabolic abnormalities and metabolic syndrome, regardless of adiposity. Additionally, low familial socioeconomic status and prolonged sedentary behaviors were the biosocial and psychosocial factors associated with metabolic syndrome regardless of adiposity. Finally, insufficient physical activity was associated with metabolic syndrome in obese postmenopausal women. Based on these results, tailored strategies should be developed considering the significant factors associated with metabolic abnormalities and adiposity in postmenopausal women.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.53-62
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• 2013

Land-use/cover changes not only amplify or alleviate influence of climate changes but also they are representative factors to affect environmental change along with climate changes. Thus, the use of land-use/cover changes scenario, consistent climate change scenario is very important to evaluate reliable influences by climate change. The purpose for this study is to predict and analyze the future urban growth considering social and economic scenario from RCP scenario suggested by the 5th evaluation report of IPCC. This study sets land-use/cover changes scenario based on storyline from RCP 4.5 and 8.5 scenario. Urban growth rate for each scenario is calculated by urban area per person and GDP for the last 25 years and regression formula based on double logarithmic model. In addition, the urban demand is predicted by the future population and GDP suggested by the government. This predicted demand is spatially distributed by the urban growth probability map made by logistic regression. As a result, the accuracy of urban growth probability map is appeared to be 89.3~90.3% high and the prediction accuracy for RCP 4.5 showed higher value than that of RCP 8.5. Urban areas from 2020 to 2050 showed consistent growth while the rate of increasing urban areas for RCP 8.5 scenario showed higher value than that of RCP 4.5 scenario. Increase of urban areas is predicted by the fact that famlands are damaged. Especially RCP 8.5 scenario indicated more increase not only farmland but also forest than RCP 4.5 scenario. In addition, the decrease of farmland and forest showed higher level from metropolitan cities than province cities. The results of this study is believed to be used for basic data to clarify complex two-way effects quantitatively for future climate change, land-use/cover changes.

• Korean Journal of Psychosomatic Medicine
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• v.24 no.1
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• pp.66-73
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• 2016

Objectives : The purpose of this study was to investigate the characteristics of psychosocial factors related to functional dyspepsia(FD) and their effects on quality of life(QOL) in firefighters. Methods : This study examined data collected from 1,217 firefighters. We measured psychological symptoms by Patient Health Questionnaire-9(PHQ-9), Generalized Anxiety Disorder questionnaire(GAD-7), Korean Occupational Stress Scale(KOSS), Ways of Coping checklist(WCCL), Rosenberg's Self-Esteem Scale(RSES) and World Health Organization Quality of Life Scale abbreviated version(WHOQOL-BREF). Chi-square test, independent t-test, Pearson's correlation test, logistic regression analysis, and hierarchical regression analysis were used as statistical analysis methods. Results : For the group with FD, the male participants showed significantly higher frequency(p=0.006) compared to the female participants. The group with FD had higher scores for depressive symptoms(p<.001), anxiety (p<.001), and occupational stress(p<.001), and did lower scores for self-esteem(p=.008), quality of life(p<.001) than those without FD. The FD risk was higher in the following KOSS subcategories: job demand(OR 1.94, 95% CI : 1.29-2.93), lack of reward(OR 2.47, 95% CI : 1.61-3.81), and occupational climate(OR 1.51, 95% CI : 1.01-2.24). In the hierarchical regression analysis, QOL was best predicted by depressive symptoms, self-esteem, and occupational stress. Three predictive variables above accounts for 42.0% variance explained of total variance. Conclusions : The psychosocial factors showed significant effects on FD, and predictive variables for QOL were identified based on regression analysis. The results suggest that the psychiatric approach should be accompanied with medical approach in future FD assessment.