• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.519-531
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• 2020

Global warming is accelerating as greenhouse gas emissions increase owing to the increase in population and urbanization rates worldwide. As an alternative to this solution, smart cities are being promoted. The purpose of this paper is to suggest a plan for developing energy service modules for the Sejong 5-1 living area, which has been selected as a test-bed for smart cities in Korea. Based on the smart city plans announced by the government for this study, a survey questionnaire on 12 energy services was composed by collecting the opinions of experts. The survey was conducted with 1,000 citizens, the degree of necessity of energy service that citizens think of was identified. Principal Component Analysis and Association Rule Mining were conducted to describe 12 energy service items in a reduced manner and analyze the correlation and relationship of each energy service. Finally, three modules were suggested using the analyzed results so that 12 energy services could be implemented in an efficient platform. These results are expected to contribute to the realization of a smart city to make them easily accessible for those who want to promote platform services in the energy field and envision energy service items.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.420-426
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• 2018

The purpose of this paper is to examine the business cycle in the Jeju region and what differences exist in relation to the nation as a whole, to calculate the relative importance between the random walk stochastic trend and cyclical factor, and to find out its causes and implications. Results of empirical analysis found that the characteristics of the business cycle in the Jeju region were as follows: First, the Jeju region, which is likely to have a growth component of the economy such as technological development and the accumulation of capital, was projected to have a possibility of high growth due to a greater proportion of the stochastic trend factor(46.8%) than the entire country(27.8%). Secondly, employment fluctuation in Jeju, which varies from 0.007 to 0.058 depending on the model, was lowest compared to the fluctuation of other indicators. The employment market in Jeju remained firm, showing that it is not smooth enough to create new jobs despite the production growth in industry. Third, the tourism industry was acting as a stabilizing factor, whereas the mining and manufacturing production was the opposite of tourism industry. This implies that the mining and manufacturing production was based on a weak foundation.

• Geophysics and Geophysical Exploration
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• v.5 no.4
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• pp.299-308
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• 2002

We have derived an analytical expression for the sensitivity of the frequency domain small-loop electromagnetic (EM) surveys over a two-layer earth in order to estimate the depth of investigation with an instrument having the source-receiver separation of about 2 m. We analyzed the sensitivities to the lower layer normalized by those to the upper half-space and estimated the depth of investigation from the sensitivity analyses and the mutual impedance ratio. The computational results showed that the in-phase components of the sensitivity to the lower layer dominates those to the upper layer when the thickness of the upper layer is less than 20 m, while the quadrature components are not sensitive to the lower layer over the entire frequency range. Hence we confirmed that the accurate measurement of the in-phase component is essential to increase the depth of investigation in the multi-frequency small-loop EM survey. When conductive basement of 10 ohm-m underlies the upper layer of 100 ohm-m, an accurate measurement of the in-phase components ensures the depth of the investigation more than 10 m even accounting a noise effect, from which we conclude that the small-loop EM survey is quite effective in imaging the conductive plume down to a considerable depth. On the other hand, in the presence of the resistive basement of 1,000 ohm-m, the depth of investigation may not exceed 5 m considering the instrumental accuracy, which implies that the application of the small-loop EM survey is not recommended over the resistive environment other than detecting the buried conductor.

• Korean Journal of Clinical Pharmacy
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• v.24 no.1
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• pp.39-44
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• 2014

Purpose: To investigate adverse drug reactions (ADR) and causative drugs in the elderly 65 years of age or older, using Korean spontaneous reporting adverse events reporting database from June 2009 to December 2010. Methods: We estimated the association between ADRs and implicated medications by calculating a proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC). We reexamined the most frequently implicated medications and ADRs, and the seriousness of ADRs. Then, we assessed reports and concordant rate of ADRs due to medications designated as "high-risk" in elderly by 2012 healthcare effectiveness data and information set (HEDIS) or "potentially inappropriate" by 2012 American Geriatrics Society updated Beers criteria for potentially inappropriate medications (PIMs). Results: Among 15,484 elderly reports, data-mining analysis by PRR, ROR and IC showed that 421 drug-ADR pairs were detected as signals (3,189). The most frequently reported ADR and causative drug were urticaria (470) and contrast media agents (647), respectively. One hundred eighty nine ADR cases were graded as serious. Twenty-two kinds of high-risk medications were shown to be implicated in only 0.9% of ADRs. Only thirty-nine cases were consistent with 2012 Beers criteria or HEDIS. Conclusion: These results suggest that management of the other medications including contrast media agents as well as close monitoring of PIMs are necessary for reducing ADRs in the elderly.

• Journal of the Korea Society of Computer and Information
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• v.5 no.4
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• pp.41-47
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• 2000

In modern dynamic management environment, there is growing recognition that information & knowledge management systems are essential for CEO's efficient/effective decision making. As a key component to cope with this current, we suggest the management performance data-mining system based on IT(Information Technology). This system measures management performance that is considered with both VA(Value-Added), which represents stakeholder's point of view and EVA(Economic Value-Added), which represents shareholder's point of view. The relationship between management performance and 85 financial ratios is analyzed, and then important financial ratios are drawn out. In analyzing the relationship, we applied the explanation-based Gas(Genetic Algorithms) that consider predictability, understanability (lucidity) and reasonability factors simultaneously. To demonstrate the performance of the system, we conducted a case study using financial data over the 16-years from 1981 to 1996 of Korean automobile industry which is taken from database of KISFAS(Korea Investors Services Financial Analysis System).

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.69-90
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• 2023

The purpose of this study is to evaluate the service attributes and consumer reactions of telemedicine apps in South Korea and visualize their differentiation by constructing positioning maps. We crawled 23,219 user reviews of 6 major telemedicine apps in Korea from the Google Play store. Topics were derived by BERTopic modeling, and sentiment scores for each topic were calculated through KoBERT sentiment analysis. As a result, five service characteristics in the application attribute category and three in the medical service category were derived. Based on this, a two-dimensional positioning map was constructed through principal component analysis. This study proposes an objective service evaluation method based on text mining, which has implications. In sum, this study combines empirical statistical methods and text mining techniques based on user review texts of telemedicine apps. It presents a system of service attribute elicitation, sentiment analysis, and product positioning. This can serve as an effective way to objectively diagnose the service quality and consumer responses of telemedicine applications.

• Spatial Information Research
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• v.20 no.4
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• pp.17-27
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• 2012

This study was performed to evaluate the spatial distribution of heavy metals using principal component analysis and Ordinary Kriging technique in the Gangwon Mine site. In the soils from the sub soil, the contents of Zn and Ni in the PC1 were gradually dispersed from south to north direction, while the components of Cd and Hg in the PC2 showed an increase significantly from middle-south area in the Gangwon Mine site. According to the cluster analysis, pollutant metals of As and Cu were presented a strong spatial autocorrelation structure in cluster D. The concentration of As was 0.83mg/kg and shown to increase from the south to north direction. The spatial distribution maps of the soil components using geostatistical method might be important in future soil remediation studies and help decision-makers assess the potential health risk affects of the abandoned mining sites.

• The Journal of Korean Academic Society of Nursing Education
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• v.23 no.3
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• pp.279-289
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• 2017

Purpose: The purpose of this study is to investigate the learning experience, self-directed learning ability and self-efficacy of Japanese nursing students undergoing portfolio-based clinical practicums. Methods: The self-directed learning ability and self-efficacy of nursing students were examined using two scales. And using a text-mining approach, we constructed correspondence analysis followed by cluster analysis of open-ended responses forms. Results: The mean score of the self-directed learning ability was $60.89{\pm}5.28$ and the generalized self-efficacy was $68.37{\pm}11.56$. Moreover, the scores in the self-directed learning ability were positively correlated with scores in the generalized self-efficacy. In correspondence analysis, the distribution of extracted words showed that record was located on the negative side of the third quadrant, to the first principal component and that patient was located on the positive side of the first quadrant, contributing greatly to the second principal component. Conclusion: The results of this study contribute to approaching to "confidence, pride, stability," "growth and intention to development'' offers a key in developing self-directed learning ability. Students record what they see and learn the importance of visualizing it in learning portfolios. "Expression in detail of the learned contents" and "concerning to which objective evaluation is suggested" are important to the students.

• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.877-885
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• 2004

In this paper, we propose an enhancement shot change detection method using the neural net and the robust feature selection out of multiple features. The previous shot change detection methods usually used single feature and fixed threshold between consecutive frames. However, contents such as color, shape, background, and texture change simultaneously at shot change points in a video sequence. Therefore, in this paper, we detect the shot changes effectively using robust features, which are supplementary each other, rather than using single feature. In this paper, we use the typical CART (classification and regression tree) of data mining method to select the robust features, and the backpropagation neural net to determine the threshold of the each selected features. And to evaluation the performance of the robust feature selection, we compare the proposed method to the PCA(principal component analysis) method of the typical feature selection. According to the experimental result. it was revealed that the performance of our method had better that than the PCA method.

• The Korean Journal of Applied Statistics
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• v.32 no.6
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• pp.837-849
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• 2019

Latent class models (LCM) are useful tools to draw hidden information from categorical data. This model can also be interpreted as a mixture model with multinomial component distributions. In some cases, however, an available dataset may contain both categorical and count or continuous data. For such cases, we can extend the LCM to a mixture model with both multinomial and other component distributions such as normal and Poisson distributions. In this paper, we consider a LCM for the data containing categorical and count data to analyze the Drug Review dataset which contains categorical responses and text review. From this data analysis, we show that we can obtain more specific hidden inforamtion than those from the LCM only with categorical responses.