• Journal of Intelligence and Information Systems
• /
• v.16 no.3
• /
• pp.181-199
• /
• 2010

As rapid progress of population aging and strong interest in health, the demand for new healthcare service is increasing. Until now healthcare service has provided post treatment by face-to-face manner. But according to related researches, proactive treatment is resulted to be more effective for preventing diseases. Particularly, the existing healthcare services have limitations in preventing and managing metabolic syndrome such a lifestyle disease, because the cause of metabolic syndrome is related to life habit. As the advent of ubiquitous technology, patients with the metabolic syndrome can improve life habit such as poor eating habits and physical inactivity without the constraints of time and space through u-healthcare service. Therefore, lots of researches for u-healthcare service focus on providing the personalized healthcare service for preventing and managing metabolic syndrome. For example, Kim et al.(2010) have proposed a healthcare model for providing the customized calories and rates of nutrition factors by analyzing the user's preference in foods. Lee et al.(2010) have suggested the customized diet recommendation service considering the basic information, vital signs, family history of diseases and food preferences to prevent and manage coronary heart disease. And, Kim and Han(2004) have demonstrated that the web-based nutrition counseling has effects on food intake and lipids of patients with hyperlipidemia. However, the existing researches for u-healthcare service focus on providing the predefined one-way u-healthcare service. Thus, users have a tendency to easily lose interest in improving life habit. To solve such a problem of u-healthcare service, this research suggests a u-healthcare recommender system which is based on collaborative filtering principle and social network. This research follows the principle of collaborative filtering, but preserves local networks (consisting of small group of similar neighbors) for target users to recommend context aware healthcare services. Our research is consisted of the following five steps. In the first step, user profile is created using the usage history data for improvement in life habit. And then, a set of users known as neighbors is formed by the degree of similarity between the users, which is calculated by Pearson correlation coefficient. In the second step, the target user obtains service information from his/her neighbors. In the third step, recommendation list of top-N service is generated for the target user. Making the list, we use the multi-filtering based on user's psychological context information and body mass index (BMI) information for the detailed recommendation. In the fourth step, the personal information, which is the history of the usage service, is updated when the target user uses the recommended service. In the final step, a social network is reformed to continually provide qualified recommendation. For example, the neighbors may be excluded from the social network if the target user doesn't like the recommendation list received from them. That is, this step updates each user's neighbors locally, so maintains the updated local neighbors always to give context aware recommendation in real time. The characteristics of our research as follows. First, we develop the u-healthcare recommender system for improving life habit such as poor eating habits and physical inactivity. Second, the proposed recommender system uses autonomous collaboration, which enables users to prevent dropping and not to lose user's interest in improving life habit. Third, the reformation of the social network is automated to maintain the quality of recommendation. Finally, this research has implemented a mobile prototype system using JAVA and Microsoft Access2007 to recommend the prescribed foods and exercises for chronic disease prevention, which are provided by A university medical center. This research intends to prevent diseases such as chronic illnesses and to improve user's lifestyle through providing context aware and personalized food and exercise services with the help of similar users'experience and knowledge. We expect that the user of this system can improve their life habit with the help of handheld mobile smart phone, because it uses autonomous collaboration to arouse interest in healthcare.

• Journal of Nutrition and Health
• /
• v.51 no.6
• /
• pp.556-566
• /
• 2018

Purpose: This study was designed to determine the relationship between health behaviors and high levels of low-density lipoprotein-cholesterol (LDL-cholesterol) according to cardiovascular risk factors among Korean adults. Methods: This cross-sectional study was based on the sixth Korea national health and nutrition examination survey (KNHANES VI). Participants were 13,841 adults aged 19 years and older. Cardiovascular risk factors were stroke, myocardial infarction or angina, diabetes mellitus, smoking, hypertension, aging, high density lipoprotein-cholesterol (HDL-cholesterol) under 40 mg/dL and HDL-cholesterol over 60 mg/dL. Cardiovascular risk groups were classified as very high risk (stroke, myocardial infarction or angina), high risk (diabetes mellitus), moderate risk (over 2 risk factors), and low risk (below 1 risk factor). The prevalence of high LDL-cholesterol was calculated using the LDL-cholesterol target level according to cardiovascular risk group. Results: The prevalence of high LDL-cholesterol was 25.5% in males and 21.7% in females. Complex sample cross tabulation demonstrated that the high LDL-cholesterol and normal groups differed significantly according to age, education, body mass index, percentage of energy from carbohydrate, fat, saturated fat and n-6 in males and females. These two groups were also significantly different according to smoking in males and the percentage of energy from n-3 in females. Complex sample multiple logistic regression analysis adjusted for multiple confounding factors demonstrated that the probability of high LDL-cholesterol was significantly associated with current smoking (OR: 1.66, 95% CI: 1.40-1.99), obesity (OR: 1.95, 95% CI: 1.64-2.31) in males, and current smoking (OR: 1.73, 95% CI: 1.19-2.52), obesity (OR: 1.63, 95% CI: 1.39-1.90), percentage of energy from n-3 (quartile 1 vs. quartile 2; OR: 0.77, 95% CI: 0.62-0.96; quartile 1 vs. quartile 3; OR: 0.73, 95% CI: 0.56-0.94; quartile 1 vs. quartile 4: OR: 0.67, 95% CI: 0.51-0.87) in females. Conclusion: This study reveals the impact of smoking, obesity, energy percentage of nutrient intake on LDL-cholesterol.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.4
• /
• pp.198-221
• /
• 2021

After large-scale reforestation in the 1960s and 1970s, forests in Korea have gradually been aging. Net ecosystem CO₂ exchange of old-growth forests is theoretically near zero; however, it can be a CO₂ sink or source depending on the intervention of disturbance or management. In this study, we report the CO₂ budget dynamics of the Gwangneung deciduous old-growth forest (GDK) in Korea and examined the following two questions: (1) is the preserved GDK indeed CO₂ neutral as theoretically known? and (2) can we explain the dynamics of CO₂ budget by the common mechanisms reported in the literature? To answer, we analyzed the 15-year long CO₂ flux data measured by eddy covariance technique along with other biometeorological data at the KoFlux GDK site from 2006 to 2020. The results showed that (1) GDK switched back-and-forth between sink and source of CO₂ but averaged to be a week CO₂ source (and turning to a moderate CO₂ source for the recent five years) and (2) the interannual variability of solar radiation, growing season length, and leaf area index showed a positive correlation with that of gross primary production (GPP) (R²=0.32~0.45); whereas the interannual variability of both air and surface temperature was not significantly correlated with that of ecosystem respiration (RE). Furthermore, the machine learning-based model trained using the dataset of early monitoring period (first 10 years) failed to reproduce the observed interannual variations of GPP and RE for the recent five years. Biomass data analysis suggests that carbon emissions from coarse woody debris may have contributed partly to the conversion to a moderate CO₂ source. To properly understand and interpret the long-term CO₂ budget dynamics of GDK, new framework of analysis and modeling based on complex systems science is needed. Also, it is important to maintain the flux monitoring and data quality along with the monitoring of coarse woody debris and disturbances.

• 한국체육학회지인문사회과학편
• /
• v.51 no.3
• /
• pp.373-382
• /
• 2012

The purpose of this study is to predict VO₂max with body index and submaximal metabolic responses. The subjects are consisted of 250 male aging from 18 to 34 and we separated them into two groups randomly; 179 for a sample, 71 for a cross-validation group. They went through maximal exercise testing with Bruce protocol, and we measured the metabolic responses in the end of the first(3 minute) and second stage(6 minute). To predict VO₂max, we applied multiple regression analysis to the sample with stepwise method. Model 1's variables are weight, 6 minute HR and 6 minute VO₂(R=0.64, SEE=4.74, CV=11.7%, p<.01), and the equation is VO₂max(ml/kg/min)= 72.256-0.340(Weight)-0.220(6minHR)+0.013(6minVO₂). Model 2's variables are weight, 6 minute HR, 6 minute VO₂, and 6 minute VCO₂(R=0.67, SEE=4.59, CV=11.3%, p<.01), and the equation is VO₂max(ml/kg/min)= 68.699-0.277(Weight) -0.206(6minHR)+0.020(6minVO₂)-0.009(6minVCO₂). And the result did not show multicolinearity for both models. Model 2 demonstrated more correlation compared to Model 1. However, when we conducted cross-validation of those models with 71 men, measured VO₂max and estimated VO₂ Max had statistical significance with correlation (R=0.53, 0.56, P<.01). Although both models are functional with validity considering their simplicity and utility, Model 2 has more accuracy.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
• /
• v.7 no.1
• /
• pp.5-28
• /
• 2001

Objectives: The objective of this study was to investigate analysis of bone mineral density according to Women with low back pain women. Methods: The data were collected from women who visited Physical Examination Center of a Catholic university hospital located in Daegu. Questionnaires were completed by 50 women during the period from July 20, 2000 to January 12, 2001. The sample was divided into three groups(the normal group of 16 cases and the osteopenia group of 12cases and the osteoporosis group of 22 cases). Bone mineral density(BMD) of lumbar spine was measured using energy absorptiometry. Results: The bone mineral density of the lumbar spine decreased with aging. The bone mineral density of the lumbar spine decreased with the serum Calcium and Phosphorus and Alkaline phosphatase increased. The mean bone mineral density of the lumbar spine of healthy women in age(50~59) was 0.87g/$cm^2$, the lumbar spine of women with low back pain in age(50~59) was 0.77g/$cm^2$. In the multiple regression of risk factors to bone mineral density(BMD) of lumbar spine were correlated with age, marriage existence, exercise time, the loving food of taste, calcium, bone mineral density standard T scores(p<0.05). The experience for LBP increased as weight increased(Odds ratio=999.000). The experience for LBP increased as number of Exercise decreased(Odds ratio=999.000). The experience for LBP increased as menopause existence increased(Odds ratio=999.000). The experience for LBP increased as serum Calcium and Phosphorus increased (Odds ratio=999.000). however all four variables had significant no relationship. The correlation in variables in relation to low back pain and bone mineral density, age showed contra-correlation with low back pain existence, Alkaline phosphatase(p<0.01). Weight showed contra-correlation with body mass index(BMI)(p<0.01). Exercise time showed correlation with number of exercise(p<0.01). The loving food of taste showed contra-correlation with Alkaline phosphatase(p<0.05). Bone mineral density showed correlation with menopause existence(p<0.05). Conclusions: Results from this study indicated that a statistically significant association between bone mineral density of the lumbar spin and age, marriage existence, exercise time, the loving food of taste, calcium, bone mineral density standard T scores. In logistic regression test, there were no related variables. The combination of bone mineral density measurement and assessment of the bone turnover rate by measuring biochemical would be helpful for the treatment of patients with risks of osteoporosis. The more precise study for risk factors to osteoporosis is essential.