• 한국노년학
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• v.39 no.3
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• pp.467-484
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• 2019

The purpose of this study is to explore latent classes of longitudinal medical expenses of older people and to analyze its predictors and its effects on subjective health. Among participants of the Korean Health Panel, the sample of this study includes 1,119 people who is 65-year-old or older and reported their medical expenses for nine consecutive years. The analyses were conducted in three steps. First, Growth Mixture Model (GMM) was applied to find distinct subgroups showing similar patterns in medical expenses. The results showed four groups which were classified as high medical expenditure maintenance group, medical expenditure increase group, low medical expenditure maintenance group, and medical expenditure reduction group. Second, the multinominal logistic regression found that the presence of spouse, economic participation, the number of chronic diseases, and the type of health insurance were significant predictors of latent classes in medical expenses. In particular, the greater the number of chronic diseases, the higher the likelihood of belonging to the high medical expenditure maintenance group. In addition, medical benefit recipients are more likely to belong to the low medical cost maintenance and medical cost reduction groups. Third, multiple regression analysis revealed that the older people in the groups with low or reducing expenses reported better subjective health than people with higher expenses. This study has its meanings in exploring the heterogeneity in longitudinal medical expenses among older people and its predictors and its associations with health outcome. The results of this research provide background information in establishing public health policy for older people.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.49-65
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• 2014

Word of Mouth (WOM) is a behavior used by consumers to transfer or communicate their product or service experience to other consumers. Due to the popularity of social media such as Facebook, Twitter, blogs, and online communities, electronic WOM (e-WOM) has become important to the success of products or services. As a result, most enterprises pay close attention to e-WOM for their products or services. This is especially important for movies, as these are experiential products. This paper aims to identify the network factors of an online movie community that impact box office revenue using social network analysis. In addition to traditional WOM factors (volume and valence of WOM), network centrality measures of the online community are included as influential factors in box office revenue. Based on previous research results, we develop five hypotheses on the relationships between potential influential factors (WOM volume, WOM valence, degree centrality, betweenness centrality, closeness centrality) and box office revenue. The first hypothesis is that the accumulated volume of WOM in online product communities is positively related to the total revenue of movies. The second hypothesis is that the accumulated valence of WOM in online product communities is positively related to the total revenue of movies. The third hypothesis is that the average of degree centralities of reviewers in online product communities is positively related to the total revenue of movies. The fourth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. The fifth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. To verify our research model, we collect movie review data from the Internet Movie Database (IMDb), which is a representative online movie community, and movie revenue data from the Box-Office-Mojo website. The movies in this analysis include weekly top-10 movies from September 1, 2012, to September 1, 2013, with in total. We collect movie metadata such as screening periods and user ratings; and community data in IMDb including reviewer identification, review content, review times, responder identification, reply content, reply times, and reply relationships. For the same period, the revenue data from Box-Office-Mojo is collected on a weekly basis. Movie community networks are constructed based on reply relationships between reviewers. Using a social network analysis tool, NodeXL, we calculate the averages of three centralities including degree, betweenness, and closeness centrality for each movie. Correlation analysis of focal variables and the dependent variable (final revenue) shows that three centrality measures are highly correlated, prompting us to perform multiple regressions separately with each centrality measure. Consistent with previous research results, our regression analysis results show that the volume and valence of WOM are positively related to the final box office revenue of movies. Moreover, the averages of betweenness centralities from initial community networks impact the final movie revenues. However, both of the averages of degree centralities and closeness centralities do not influence final movie performance. Based on the regression results, three hypotheses, 1, 2, and 4, are accepted, and two hypotheses, 3 and 5, are rejected. This study tries to link the network structure of e-WOM on online product communities with the product's performance. Based on the analysis of a real online movie community, the results show that online community network structures can work as a predictor of movie performance. The results show that the betweenness centralities of the reviewer community are critical for the prediction of movie performance. However, degree centralities and closeness centralities do not influence movie performance. As future research topics, similar analyses are required for other product categories such as electronic goods and online content to generalize the study results.

• Journal of the Korean earth science society
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• v.22 no.5
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• pp.388-404
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• 2001

In order to examine the relative accuracy of satellite observations and model reanalyses about lower stratospheric temperature trends, two satellite-observed Microwave Sounding Unit (MSU) channel 4 (Ch 4) brightness temperature data and two GCM (ECMWF and GEOS) reanalyses during 1981${\sim}$1993 have been intercompared with the regression analysis of time series. The satellite data for the period of 1980${\sim}$1999 are MSU4 at nadir direction and SC4 at multiple scans, respectively, derived in this study and Spencer and Christy (1993). The MSU4 temperature over the globe during the above period shows the cooling trend of -0.35 K/decade, and the cooling over the global ocean is 1.2 times as much as that over the land. Lower stratospheric temperatures during the common period (1981${\sim}$1993) globally show the cooling in MSU4 (-0.14 K/decade), SC4 (-0.42 K/decade) and GEOS (-0.15 K/decade) which have strong annual cycles. However, ECMWF shows a little warming and weak annual cycle. The 95% confidence intervals of the lower stratospheric temperature trends are greater than those of midtropospheric (channel 2) trends, indicating less confidence in Ch 4. The lapse rate in the trend between the above two atmospheric layers is largest over the northern hemispheric land. MSU4 has low correlation with ECMWF over the globe, and high value with GEOS near the Korean peninsula. Lower correlations (r < 0.6) between MSU4 and SC4 (or ECMWF) occur over $30^{\circ}$N latitude belt, where subtropical jet stream passes. Temporal correlation among them over the globe is generally high (r > 0.6). Four kinds of lower stratospheric temperature data near the Korean peninsula commonly show cooling trends, of which the SC4 values (-0.82 K/decade) is the largest.

• Journal of the Korean Applied Science and Technology
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• v.36 no.4
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• pp.1472-1484
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• 2019

This study aimed to verify the effects of nutritional status, K-ADL, K-IADL, and social network on the life satisfaction of the elderly in home. Total 213 research subjects participated in this study, and their average age was 71.38±5.59. As the methods of analysis, using the SPSS 21.0, this study examined the differences between variables in accordance with the general characteristics, and then verified the correlations between independent variables of nutritional status, K-ADL, K-IADL, social network(family networks, friends networks), and life satisfaction. In order to verify the factors having effects on the life satisfaction of the elderly in home, the stepwise multiple regression analysis was conducted. In the results of this study, in the general characteristics, the life satisfaction showed statistically significant differences in accordance with education(F=5.280, p=.002), economic condition(F=22.407, p<.001), monthly income(F=3.181, p=.015), and subjective health status(F=14.933, p<.001). In the results of verifying the correlation between independent variables, the life satisfaction showed positive correlations with family networks(r=268, p<.001) and friends networks(r=.286, p<.001) while the nutritional status(r=-.222, p=.001), K-IADL(r=-.235, p=.001), and interdependent social support(r=-.283, p<.001) showed negative correlations. The predictive factors on the life satisfaction of the elderly in home included the economic condition(β=.358, p<.001), subjective health status(β=.245, p<.001), interdependent social support(β=-.158, p=.009), and K-IADL(β=-.153, p=.012), and the explanatory power was 30.1%. The regression model was statistically significant(F=23.778, p<.001). Based on such results of this study, it would be necessary to develop programs that could maintain and improve the health of the elderly, and also provide financial support to the elderly suffering from economic hardship, in order to improve the life satisfaction of the elderly in home. Moreover, there should be the concrete measures for vitalizing the community-connected activities for interdependent social support.

• Journal of dental hygiene science
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• v.16 no.3
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• pp.242-248
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• 2016

The purposes of this study were to investigate the factors affection the Oral Impacts on Daily Performances for Children (C-OIDP) in elementary and middle school students, and identify the association between oral health-related behaviors, oral health condition and C-OIDP. A cross-sectional study was conducted in three schools in Incheon, Asan, Korea. A total of 175 selected children were interviewed by a trained examiner using a questionnaire. Oral Health Related Quality of Life was assessed by the Korean version of C-OIDP. Socio-economic characteristics, oral health-related behaviors, oral health condition and C-OIDP were verified using the questionnaire. ANOVA analysis was performed to determine the oral health and C-OIDP, and multiple regression analysis was performed to determine the factors affecting the C-OIDP. The activities with the greatest effect were eating (28.0%), cleaning teeth (22.9%), and smiling (18.9%). In the logistic regression model, the high item score of C-OIDP was associated with experiencing dental caries and gum pain in the past month. The more the C-OIDP prevalence item, the more the fillng deciduous tooth surface (fs) (p=0.024), caries experienced deciduous tooth surface (dfs) (p=0.049), total caries tooth surface (ds+DS) (p=0.021), and total caries experienced tooth surface (dfs+DMFS) (p=0.047). It can be concluded that the factors affecting C-OIDP are fs, dfs, dfs+DMFS, and gingival pain. Based on these results, we can improve C-OIDP to advance preventive practice.

• Journal of dental hygiene science
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• v.17 no.2
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• pp.134-141
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• 2017

This study examined 191 pregnant women before delivery in an obstetrics and gynecology clinic in North Gyeongsang Province from May to September 2016 by using a questionnaire after obtaining informed consent for voluntary participation in the study. The study was performed to investigate the association of depression with sociodemographic characteristics, pregnancy-related characteristics, social support, sleep quality and Oral Health Impact Profile (OHIP) in pregnant women. The prevalence of depression among the pregnant women was 25.1% in the healthy group and 74.9% in the depression group. The depression level was significantly higher in women in the depression group who were unsatisfied with their marriage life, had no occupation, had lower social support, had poor sleep quality and had higher OHIP scores. The results of the logistic regression analysis indicated that, the risk ratio for more severe depression was significantly higher in the group with no experience of miscarriage and induced childbirth than in the group with childbirth experience. Conversely, the risk ratio for more severe depression was significantly lower in the group with high social support than in the group with low social support. Depression in the respondents significantly positively correlated with sleep quality and OHIP score but significantly negatively correlated with social support. The multiple regression analysis revealed that the depression level was significantly higher by 22.3% among pregnant women with lower marital satisfaction, no childbirth experience, lower social support and higher OHIP scores. In summary, depression was related to marital satisfaction, childbirth experience, social support, and OHIP score, among others, in pregnant women in this study. Therefore, further investigation is warranted to construct programs and measures that will help build positive thinking by designing and verifying a three-dimensional study model by taking into consideration various variables to reduce the incidence of depression in pregnant women.

• Korean Journal of Environment and Ecology
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• v.34 no.5
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• pp.446-453
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• 2020

This study built a model to predict the daily number of visitors to 18 trails in the Taebaeksan National Park using the auto-counter system data to analyze the factors affecting the daily number of visitors to each trail and classified the trails by visitors' behaviors. Results of the multiple regression models with the daily number of visitors of the 18 trails indicated that the events, such as the National Foundation Day celebration of Snow Festival, affected the number of visitors of all of the 18 trails and were the most critical factor that determined the daily number of visitors to the Taebaeksan National Park. The long-holidays of three days or longer and other national holidays also affected the daily number of visitors to the trails. Precipitation had a negative impact on the number of visitors of trails where the intention of most visitors was for sightseeing or camping instead of hiking, whereas had no significant impacts on the number of visitors of trails where many visitors intended for hiking. It indicated that visitors who intended for hiking went ahead hiking even if the weather was poor. The effects of temperature had a positive effect on the number of visitors who intended for hiking but a negative effect on the number of visitor to the trails near Danggol Plaza where the Snow Festival was held in each winter, suggesting that the impact of the Snow Festival was the deterministic factor for trail management. Results of K-mean clustering showed that the 18 trails of the Taekbaeksan National Park could be classified into three types: those affected by the Snow Festival (type 1), those that have sightseeing points and so were visited mostly by non-hikers (type 2), and those visited mostly by hikers (type 3). Since visitor behaviors and illegal actions differ according to the trail type, this study's results can be used to prepare a trail management plan based on the trail characteristics.

• Journal of Preventive Medicine and Public Health
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• v.28 no.4 s.51
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• pp.783-794
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• 1995

This study was conducted to clarify the relationship of body fat percent with serum lipid level and blood pressure in adults. The study subjects were 472 men and 189 women who visited Multiphasic Health Screening Center of Yeungnam University Hospital in Taegu from May 20 to September 30, 1994. The relationship of serum lipid and blood pressure with BMI, Katsura index, atherogenic index, which calculated from the health screening data and body fat percent measured by impedance fat meter(model SIF-819) were analyzed. Three groups were classified as Group I (men : body fat Percent $\geq$ 20, women : body fat percent $\geq$ 25), Group II (men : 15 $\leq$ body fat percent< 20, women : 20 $\leq$ body fat percent< 25), Group III(men : body fat percent < 15, women body fat percent <20). In this study, Group I accounted for 3.2% in men, 3.7% in women. Weight was significantly different among three groups in both sexes(p<0.01) and height was not significantly different among three groups. In men, serum total cholesterol, triglyceride, high density lipoprotein, low density lipoprotein, atherogenic index were significantly different(p<0.01). In women, serum total cholesterol and low density lipoprotein were significantly different(p<0.05) but there was no differences in triglyceride and high density lipoprotein among three groups. BMI and Katsura index were significantly different among three groups in both sexes(p<0.01). In men, body fat percent was positively correlated with weight, BMI, Katsura index, total cholesterol, triglyceride, low density lipoprotein, atherogenic index and systolic and diastolic blood pressures, and negatively correlated with high density lipoprotein. In women, body fat percent was positively correlated with age, height, weight, BMI, Katsura index, total cholesterol, triglyceride, low density lipoprotein and atherogenic index, and negatively correlated with high density lipoprotein. But there was no significant correlation between body fat percent and blood pressure in women. In multiple regression analysis for total cholesterol, fat percent, age and BMI were significant independent variables in men$(p<0.05,\;R^2=0.1286)$, and body fat percent and age in women$(p<0.05,\;R^2=0.3399)$. In case of LDL/HDL ratio, only BMI was a significant independent variable in menu$(p<0.01,\;R^2=0.0954)$, and body fat percent, age and BMI in women$(p<0.05,\;R^2=0.3164)$. In multiple regression analysis, age, low density lipoprotein and total cholesterol were significant independent variables on systolic blood pressure in men$(p<0.05,\;R^2=0.1297)$, age and total cholesterol in women$(p<0.05,\;R^2=0.1705)$. On diastolic blood pressure, only age was a significantly independent variable in men$(p<0.01,\;R^2=0.0972)$ and women$(p<0.01,\;R^2=0.1218)$. From the result of this study, it could concluded that body fat percent was significantly associated with other obesity indices and serum lipid, but had no significant association with blood pressure. To establish the relationship of body fat percent with blood pressure, further study which consider other variables that may have an effect on blood pressure should be performed.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.441-448
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• 2015

Lack of agricultural information for food supply and demand in Democratic People's republic Korea(DPRK) make people sometimes confused for right and timely decision for policy support. We carried out a study to estimate paddy rice yield in DPRK using MODIS NDVI reflecting rice growth and climate data. Mean of MODIS $NDVI_{max}$ in paddy rice over the country acquired and processed from 2002 to 2014 and accumulated rainfall collected from 27 weather stations in September from 2002 to 2014 were used to estimated paddy rice yield in DPRK. Coefficient of determination of the multiple regression model was 0.44 and Root Mean Square Error(RMSE) was 0.27 ton/ha. Two-way analysis of variance resulted in 3.0983 of F ratio and 0.1008 of p value. Estimated milled rice yield showed the lowest value as 2.71 ton/ha in 2007, which was consistent with RDA rice yield statistics and the highest value as 3.54 ton/ha in 2006, which was not consistent with the statistics. Scatter plot of estimated rice yield and the rice yield statistics implied that estimated rice yield was higher when the rice yield statistics was less than 3.3 ton/ha and lower when the rice yield statistics was greater than 3.3 ton/ha. Limitation of rice yield model was due to lower quality of climate and statistics data, possible cloud contamination of time-series NDVI data, and crop mask for rice paddy, and coarse spatial resolution of MODIS satellite data. Selection of representative areas for paddy rice consisting of homogeneous pixels and utilization of satellite-based weather information can improve the input parameters for rice yield model in DPRK in the future.