• Journal of agricultural medicine and community health
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• v.26 no.2
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• pp.97-109
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• 2001

To investigate the total cholesterol level and its related factors in the rural and sea-board, 2,840 adults who participated voluntarily were examined during the study period December 1999 to February 2000. The height, weight, and fasting serum total cholesterol were measured. Body mass index was calculated. Information on age, gender, smoking, alcohol, and menopausal status in women were collected using a questionnaire by interviewing method. The mean value of total cholesterol was 191.6mg/ dl in sea- board and 173.6mg/ dl in rural men, respectively, and 206.9mg/ dl and 186.9mg/ dl in sea-board and in rural women. By simple analysis, in men, area, BMI and smoking were significant risk factors(p<0.01). Area(p<0.01), age(p<0.01), BMI(p<0.01), smoking(p<0.05), and menopausal status (p<0.01) were significant. In multiple linear regression analysis, the significant factors for total cholesterol in men were area(sea-board versus rural area; p<0.01), body mass index(the more obese; p<0.01), and smoking (non-smoker versus smoker ; p<0.05). Those in women were area(sea-board versus rural area; p<0.01), body mass index(the more obese; p<0.01), and menopausal status(menopause versus normal; p<0.01). Thus, in both gender, the significant factors related with total cholesterol were area and body mass index, and in addition to those, menopausal status was proved as a significant risk factor in women.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.11
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• pp.1554-1558
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• 2012

Method development and validation of ellagic acid for the standardization of Gochang Bokbunja as a functional ingredient and health food were accomplished. A Symmetry$^{(R)}$ (C18, $4.6{\times}250mm$, $5.0{\mu}m$) column was used with a gradient elution system of 1% formic acid in water and acetonitrile. This method was validated according to specificity, linearity, accuracy, precision test, and recovery test. Specificity was confirmed with identical retention time, and calibration curves of ellagic acid showed good linear regression ($R^2$ >0.9996). Relative standard deviations (RSD) of data from the intra- and inter-day experiments were less than 2.28% and 2.84%, except in the low limit of quality control (LLOQ, $1{\mu}g/mL$) sample. The results of the recovery test were from 89.17% to 97.92% with RSD values from 0.05 to 0.14%. Therefore, we performed analysis of ellagic acid as a marker compound in Gochang Bokbunja extracts. The amount of ellagic acid in Gochang Bukbunja was about $1.918{\mu}g/mg$ (0.192%) in the three times analysis, and RSD was less than 2.36% by the validated method. These results suggest that the developed HPLC method is simple, efficient, and could contribute to the quality control of Gochang Bokbunja extract as a functional ingredient.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.1
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• pp.117-120
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• 2011

Purpose: There are 3 warnings for Glucagon tests. First, EDTA tubes that already contain Aprotinin must be used for plasma collection. Second, for freezer storage of centrifuged plasma, glass tubes must be used. Last, glass tubes must be used for testing procedure. So we compared the glucagon results of next 3 situation to those of control group. First, We compared to results by tubes without Aprotinin and with aprotinin. Second, we compared to results by tubes(plastic vs glass) for plasma storage. Third, we compared to results by tubes(plastic vs glass) for testing. We tried to evaluate the results of the 3 different condition. Materials and Methods: 40 healthy adults were studied with normal results on the general medical check up and laboratory tests. We compared the results of 3 different condition belows: Blood were collected in EDTA tube containing aprotinin and plasma was stored in the glass tube for 3 days in a freezer and results were obtained by tests in the glass tubes. Results from EDTA plasma without aprotinin, results from platic tubes for freezer stroage, results from plastic tube when testing. Simple linear regression analysis and paired t-test using SPSS were done for statistical analysis. Commercial glucagon kit(RIA-method)which made by Siemens company were used. Results: Correlation coefficient between results of EDTA tubes with Aprotinin vs without Aprotinin was r=0.783 (p=0.064). Result of specimen in plastic tubes stored 3 days in a freezer showed lower value compared to those in glass tube(r=0.979, p=0.005). Also, results of testing in plastic tubes showed lower values than those testing in glass tubes. (r=0.754, p<0.001). Conclusion: It is recommended for glucagon determination to use EDTA tube with Aprotinin which is a inhibitor of protein breakdown enzyme. Results of plastic tube when storage and testing showed lower value than those of glass tubes, so it is recommended to store and test in glass tubes.

• Clinical and Experimental Pediatrics
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• v.50 no.6
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• pp.549-555
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• 2007

Purpose : Pulse wave velocity (PWV) and ankle brachial index (ABI) are simple, non-invasive methods to assess arterial stiffness. These parameters are also known to be closely related to cardiovascular risk factors and diseases. The purposes of this study were to measure blood pressure, PWV, ABI in healthy Korean adolescents, set up their normal values and assess their correlations. Methods : Three hundred ninety two healthy adolescents (213 boys and 179 girls) underwent measurement of brachial ankle pulse wave velocity (baPWV), ABI, body mass index(BMI) and blood pressure from four extremities. Linear regression analysis was performed to reveal the correlations between PWV, ABI and independent variables. Results : Blood pressure and PWV were significantly higher in all extremities in males compared to females. Blood pressure of both brachial and ankle showed positive correlation with body weight, height, and BMI, whereas ABI showed no correlation with any of these indices. Conclusion : Blood pressure increases as body weight, height and BMI increases. PWV shows positive correlation with blood pressure. It will be helpful to predict the risks of cardiovascular diseases in adolescents.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.95-108
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• 2011

TThis is a study of the personalization method that intelligently adapts the level of clustering considering purchasing index of a customer. In the e-biz era, many companies gather customers' demographic and transactional information such as age, gender, purchasing date and product category. They use this information to predict customer's preferences or purchasing patterns so that they can provide more customized services to their customers. The previous Customer-Segmentation method provides customized services for each customer group. This method clusters a whole customer set into different groups based on their similarity and builds predictive models for the resulting groups. Thus, it can manage the number of predictive models and also provide more data for the customers who do not have enough data to build a good predictive model by using the data of other similar customers. However, this method often fails to provide highly personalized services to each customer, which is especially important to VIP customers. Furthermore, it clusters the customers who already have a considerable amount of data as well as the customers who only have small amount of data, which causes to increase computational cost unnecessarily without significant performance improvement. The other conventional method called 1-to-1 method provides more customized services than the Customer-Segmentation method for each individual customer since the predictive model are built using only the data for the individual customer. This method not only provides highly personalized services but also builds a relatively simple and less costly model that satisfies with each customer. However, the 1-to-1 method has a limitation that it does not produce a good predictive model when a customer has only a few numbers of data. In other words, if a customer has insufficient number of transactional data then the performance rate of this method deteriorate. In order to overcome the limitations of these two conventional methods, we suggested the new method called Intelligent Customer Segmentation method that provides adaptive personalized services according to the customer's purchasing index. The suggested method clusters customers according to their purchasing index, so that the prediction for the less purchasing customers are based on the data in more intensively clustered groups, and for the VIP customers, who already have a considerable amount of data, clustered to a much lesser extent or not clustered at all. The main idea of this method is that applying clustering technique when the number of transactional data of the target customer is less than the predefined criterion data size. In order to find this criterion number, we suggest the algorithm called sliding window correlation analysis in this study. The algorithm purposes to find the transactional data size that the performance of the 1-to-1 method is radically decreased due to the data sparity. After finding this criterion data size, we apply the conventional 1-to-1 method for the customers who have more data than the criterion and apply clustering technique who have less than this amount until they can use at least the predefined criterion amount of data for model building processes. We apply the two conventional methods and the newly suggested method to Neilsen's beverage purchasing data to predict the purchasing amounts of the customers and the purchasing categories. We use two data mining techniques (Support Vector Machine and Linear Regression) and two types of performance measures (MAE and RMSE) in order to predict two dependent variables as aforementioned. The results show that the suggested Intelligent Customer Segmentation method can outperform the conventional 1-to-1 method in many cases and produces the same level of performances compare with the Customer-Segmentation method spending much less computational cost.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.1-9
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• 2022

The effect of sediments in a waste dumping area on marine organisms was evaluated using sediment toxicity tests with a benthic amphipod (Monocorophium acherusicum) and bioluminescent bacterium (Vibrio fischeri) in accordance with the Korean Standard Method for Marine Wastes (KSMMW). Nine sites in the East Sea-Byeong, East Sea-Jeong, and Yellow Sea-Byeong areas were sampled from 2016 to 2019. The test results showed that the relative average survival rate (benthic amphipods) and relative luminescence inhibition rate (luminescent bacteria) were below 30%, which were judged to be "non-toxic." However, in the t-test, a total of 12 benthic amphipod samples (6, 1, 1, and 4 in 2016, 2017, 2018, and 2019, respectively) were significantly different (p<0.05) from the control samples. To identify the source of toxicity on benthic amphipods, a simple linear regression analysis was performed between the levels of eight heavy metals (Cr, As, Ni, Cd, Cu, Pb, Zn, and Hg) in sediments and the relative average survival rate. The results indicated that Cr had the highest contribution to the toxicity of benthic amphipods (p = 0.000, R2 = 0.355). In addition, Cr was detected at the highest concentration at the DB-85 station and exceeded the Marine Environment Standards every year. Although the sediments were determined as "not toxic" according to the ecotoxicity criteria of the KSMMW, the results of the statistical significance tests and toxicity identification evaluation indicated that the toxic effect was not acceptable. Therefore, revising the criteria for determining the toxic effect by deriving a reference value through quantitative risk assessment using species sensitivity distribution curves is necessary in the future.