• Journal of the Korean Geotechnical Society
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• v.29 no.11
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• pp.99-106
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• 2013

In this study, the correlation of evaluation items and safety rating for 104 of large-scale slopes along the general national road was analyzed. And, we proposed the regression model to predict the safety rating using the multiple regressions analysis. As the result, it is shown that the evaluation items of slope angle, rainfall and groundwater have a low correlation with safety rating. Also, the regression model suggested by multiple regression analysis shows high predictive value, and it would be possible to apply if the evaluation items of excavation condition and groundwater (rainfall) are not clear.

• Journal of the Korean Geographical Society
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• v.41 no.3 s.114
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• pp.319-330
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• 2006

The objective of this research is to achieve an objectivity of site decision after extracting site decision factors on a large-scale discount store(LSDS) and utilize any hidden information using the association rules mining through huge database. To catch this objective, we collect a census, economic, and environmental dataset related with locating of LSDS. And then, we construct a spatial data on the research area. These data is used for the extraction of a spatial association rules. To verify whether the extracted rules are suitability or not, we use the sales of some LSDS. As the result of test, the more sales, the more factors of the extracted rules relate with the sales it coincides. Consequently, the spatial association rules mining is efficient method which support the ideal site decision of LSDS.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.145-149
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• 2023

High-resolution images of surfaces provide detailed information on pores or shapes with specific sizes ranging from nano sizes to micrometers. However, it is not yet clear to determine an efficient association for pores or shapes from high-resolution images of surfaces. For the efficient association of pores and shapes, the surface characteristics of the device were considered as fractal dimensions by taking SEM photographs and binarizing the images. The fractal program was directly coded for surface analysis of the device. The device surface characteristics and electrical characteristics are thought to be related to the fractal dimension. The fractal dimension decreased with an increase in internal pores. The density and grain boundary of particles, which are structural characteristics of the device surface, were related to the fractal dimension. The particle size decreased with an increase in the fractal dimension and was uniformly formed. When the particles were uniformly formed, fewer pores were present and the fractal dimension increased.

• Journal of Nutrition and Health
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• v.52 no.3
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• pp.268-276
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• 2019

Purpose: Metabolic syndrome causes diabetes and increases the risk of cardiovascular disease. This study examined the correlation between metabolic syndrome, nutrition intake, and triglyceride (TG)/high-density lipoprotein (HDL) cholesterol ratio. Methods: Using the data from the $7^{th}$ KNHANES (2016), this study was conducted on healthy adults aged 19 and older. The components and existence of metabolic syndrome and nutrition intake were independent variables and the TG/HDLcholesterol ratio was a dependent variable. A complex sample logistic progress test was used with age, sex, smoking, and drinking frequency corrected. Results: The TG/HDLcholesterol ratio of people with metabolic syndrome was as high as 1.314 on average, compared to people without metabolic syndrome (p < 0.0001). Among each component of metabolic syndrome, the TG/HDL cholesterol ratio had a significant association with fasting blood glucose, TG, HDL cholesterol, and waist circumference (p < 0.05). Only energy and carbohydrate intake were significantly related to the TG/HDLcholesterol ratio (p < 0.05). Conclusion: The TG/HDLcholesterol ratio is associated with each component of metabolic syndrome, but in particular, it is positively correlated with the presence of metabolic syndrome. Lower energy intakehad a positive correlation with the TG/HDLcholesterol ratio. These results show that metabolic syndrome can be predicted using the TG/HDLcholesterol ratio, and a diet strategy through nutrition and health education is necessary to prevent metabolic syndrome.

• Journal of Industrial Convergence
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• v.21 no.2
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• pp.73-77
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• 2023

This study investigated the level of knowledge about changes in the oral environment according to the presence or absence of smoking in adults in their 20s and 40s. It was conducted to use as basic data for the relationship between periodontal disease and smoking and the importance of concurrent education on smoking cessation during oral health education for adults.In subjective oral condition analysis, 65.4% of non-smokers and 59.0% of smokers thought that it was very good or good. Also, in both the non-smokers and smokers groups, the most common answer was that they thought the cleanliness of non-smokers would be higher. To the question of whether they had ever received anti-smoking education, 63.9% of non-smokers and 76.1% of smokers answered 'yes'. In the education that 'the oral environment changes depending on whether or not there is smoking', the non-smoker group showed 'no' and the smoker group showed 'yes' respectively. As a result, oral health education related to smoking and prevention It is thought that specific and active educational methods should be accompanied for this.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.881-888
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• 2005

As the internet continues to grow, the quantity of information on the Web increases beyond measure. The internet users' abilities and requirements to use information also become varied and complicated. Ontology can describe correct meaning of web resource and relationships between web resources. And it can extract conformable information that a user wants. Accordingly, we need the ontology to represent knowledge. W3C announced OWL(Web Ontology Language), a meaning description technology for such web resources. But, the development of a professional use of tools that can compose and edit effectively is not yet developed adequately. In this paper, we design and implement an Ontology editor which generates and edits OWL documents through intuitional interface, with a OWL parser, a Internal DataModel, and a Serializer.

• Journal of KIISE:Information Networking
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• v.35 no.2
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• pp.139-148
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• 2008

Many types of sensor data exhibit strong correlation in both space and time. Suppression, both temporal and spatial, provides opportunities for reducing the energy cost of sensor data collection. Unfortunately, existing clustering algorithms are difficult to utilize the spatial or temporal opportunities, because they just organize clusters based on the distribution of sensor nodes or the network topology but not correlation of sensor data. In this paper, we propose a novel clustering algorithm with suppression techniques. To guarantee independent communication among clusters, we allocate multiple channels based on sensor data. Also, we propose a spatio-temporal suppression technique to reduce the network traffic. In order to show the superiority of our clustering algorithm, we compare it with the existing suppression algorithms in terms of the lifetime of the sensor network and the site of data which have been collected in the base-station. As a result, our experimental results show that the size of data was reduced by $4{\sim}40%$, and whole network lifetime was prolonged by $20{\sim}30%$.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.75-77
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• 2021

A variety of search engines are currently in use. The search engine supports the retrieval of data required by users through three stages: crawling, index generation, and output of search results based on meta-tag information. However, a large number of documents obtained by searching for keywords are often unrelated or scarce. Because of these problems, it takes time and effort to grasp the content from the search results and classify the accuracy. The index of search engines is updated periodically, but the criteria for weighted values and update periods are different from one search engine to another. Therefore, this paper uses the LSTM model, which extracts the relationship between keywords entered by the user and documents instead of the existing search engine, and improves the relationship between keywords and documents by entering keywords that the user wants to find.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.391-397
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• 2008

This paper analyzes the spatial patterns of population distribution in Seoul Metropolitan Area in terms of spatial association using spatial statistics and spatial exploratory technique. Our empirical analysis based on global index shows that, in Seoul Metropolitan Area, the population had been distributed with strong positive spatial association over the period of 1980-2005. It implies that the population of each region is affected by the population distribution of adjacent regions. In addition, the analysis using local index was conducted for detecting the local patterns of spatial association, and the result shows that the clusters of population had been moved in the direction of West(Incheon and Bucheon) and South(Anyang and Seongnam) of Seoul where a large scale of lands or towns were developed over the period. These results will be the preliminary data for establishing management and development plans of Seoul Metropolitan Area.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.837-848
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• 2021

Evaluating or predicting the effectiveness of economic policies is an important issue, but it is difficult to find an economic variable which causes a significant result because there are numerous variables that cannot be taken into account. A randomized controlled experiment is the best way to investigate causality, but it is not realistically possible to control through randomization and intervention in time series data such as macroeconomic data. Although some analysis methods have been proposed to find causality, the methods such as Granger causality method and Chow test are insufficient to explain causality. Recently, Pfister et al. (2019) proposed invariant causal prediction methods which can be applicable in time series data. In this paper, we introduce the method of Pfister et al. (2019) and use the method to find macroeconomic variables invariantly affecting the won-dollar exchange rate.