• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.1-12
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• 2022

Traditional methods of measuring corneal ulcers were difficult to present objective basis for diagnosis because of the subjective judgment of the medical staff through photographs taken with special equipment. In this paper, we propose a method to detect the ulcer area on a pixel basis in corneal ulcer images using a semantic segmentation model. In order to solve this problem, we performed the experiment to detect the ulcer area based on the DeepLab model which has the highest performance in semantic segmentation model. For the experiment, the training and test data were selected and the backbone network of DeepLab model which set as Xception and ResNet, respectively were evaluated and compared the performances. We used Dice similarity coefficient and IoU value as an indicator to evaluate the performances. Experimental results show that when 'crop & resized' images are added to the dataset, it segment the ulcer area with an average accuracy about 93% of Dice similarity coefficient on the DeepLab model with ResNet101 as the backbone network. This study shows that the semantic segmentation model used for object detection also has an ability to make significant results when classifying objects with irregular shapes such as corneal ulcers. Ultimately, we will perform the extension of datasets and experiment with adaptive learning methods through future studies so that they can be implemented in real medical diagnosis environment.

• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.435-446
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• 2019

The purpose of this study was to investigate the effect of strength exercise program(60 minutes/day, 3 times/week) on health-related fitness and the factor of metabolic syndrome in the older at senior care facilities during 12 weeks. Twenty-seven volunteers were recruited for the study and divided into two groups: 15 persons(82.6yrs) undertook a continuous 12 weeks strength exercise program(EG), and 12 persons(78.9yrs) served as a control group(CG). The data process of this study calculated as mean(M) and standard Deviation(SD) of all measured value, used repeated measure ANOVA, and paired t-test. The significant level of hypothesis verification is set-up as α=.05. After 12 weeks in EG, health-related fitness increased by an average of 15.2% for right grip strength(p<.05), 26.9% for left grip strength(p<.05), 32.7% for chair stand(p<.05), 92.5% for one leg stand(p<.05), 29.6% for sit and reach(p<.05), and 34.5% for TUG(p<.05); CG showed no difference between pre and post. In the factor of metabolic syndrome, Systolic BP(3.1mmHg) and fasting blood glucose(7.4mg/dl) decreased in the EG group(p<.05). In summary, the strength exercise program leads to a genuine increase in health-related fitness and decrease in the factor of metabolic syndrome in the older adults. The well planned strength exercise seems to be an important intervention to improve function fitness in this population.

• Journal of Industrial Convergence
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• v.22 no.2
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• pp.33-43
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• 2024

This study aims to test the relationship between brand embeddedness and cross-selling intention, as well as how customer satisfaction affects as mediator its relationship. The data set includes 258 consumers using a specific smartphone brand and we gather the data by conducting a survey. We use structural equation modeling to verify hypotheses and do nonparametric bootstrap approach for additional analysis of the mediating role of customer satisfaction. The results of analysis are as follows. First, it has been shown that barnd embeddedness positively affects customer satisfaction and cross-buying intention. Second, customer satisfaction is found to have a positive effect on cross-buying. By combining these results and additional analysis, we confirm that the direct effect of brand embeddedness is more effective for cross-buying intention than the indirect effect of customer satisfaction. The results of this empirical analysis show the academic value that brand embeddedness as social capital can be a antecedent for cross-buying intention. In addition, this study suggests the need for brand practitioners to increase the embeddedness of customers related to the brand and consider the mediating role of customer satisfaction together in order to increase cross-buying.

• Journal of Preventive Medicine and Public Health
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• v.57 no.3
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• pp.288-297
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• 2024

Objectives: This study explored the prevalence and predictors of alcohol and cannabis co-use among 9263 Filipino adolescents, using data from the 2019 Global School-based Student Health Survey (GSHS). Methods: We conducted a cross-sectional secondary analysis of the GSHS, targeting adolescents aged 13-17 years and excluding cases with incomplete data on alcohol and cannabis use. Our analysis employed the bivariate chi-square test of independence and multivariable logistic regression using Stata version 18 to identify significant predictors of co-use, with a p-value threshold set at 0.05. Results: The weighted prevalence of co-users was 4.2% (95% confidence interval [CI], 3.4 to 5.3). Significant predictors included male sex (adjusted odds ratio [aOR], 4.50; 95% CI, 3.31 to 6.10; p<0.001) and being in a lower academic year, specifically grade 7 (aOR, 4.08; 95% CI, 2.39 to 6.99; p<0.001) and grade 8 (aOR, 2.20; 95% CI, 1.30 to 3.72; p=0.003). Poor sleep quality was also a significant predictor (aOR, 1.77; 95% CI, 1.29 to 2.44; p<0.001), as was a history of attempted suicide (aOR, 5.31; 95% CI, 4.00 to 7.06; p<0.001). Physical inactivity was associated with lower odds of co-use (aOR, 0.45; 95% CI, 0.33 to 0.62; p<0.001). Additionally, non-attendance of physical education classes (aOR, 1.48; 95% CI, 1.06 to 2.05; p=0.021), infrequent unapproved parental checks (aOR, 1.37; 95% CI, 1.04 to 1.80; p=0.024), and lower parental awareness of free-time activities (aOR, 0.63; 95% CI, 0.45 to 0.87; p=0.005) were associated with higher odds of co-use. Factors not significantly linked to co-use included age group, being in grade 9, always feeling lonely, having no close friends, being bullied outside school, and whether a parent or guardian understood the adolescent's worries. Conclusions: The findings highlight the critical need for comprehensive interventions in the Philippines, addressing not only physical inactivity and parental monitoring but also focusing on sex, academic grade, participation in physical education classes, sleep quality, and suicide attempt history, to effectively reduce alcohol and cannabis co-use among adolescents.

• Korean Journal of Radiology
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• v.20 no.8
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• pp.1275-1284
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• 2019

Objective: To develop algorithms using convolutional neural networks (CNNs) for automatic segmentation of acute ischemic lesions on diffusion-weighted imaging (DWI) and compare them with conventional algorithms, including a thresholding-based segmentation. Materials and Methods: Between September 2005 and August 2015, 429 patients presenting with acute cerebral ischemia (training:validation:test set = 246:89:94) were retrospectively enrolled in this study, which was performed under Institutional Review Board approval. Ground truth segmentations for acute ischemic lesions on DWI were manually drawn under the consensus of two expert radiologists. CNN algorithms were developed using two-dimensional U-Net with squeeze-and-excitation blocks (U-Net) and a DenseNet with squeeze-and-excitation blocks (DenseNet) with squeeze-and-excitation operations for automatic segmentation of acute ischemic lesions on DWI. The CNN algorithms were compared with conventional algorithms based on DWI and the apparent diffusion coefficient (ADC) signal intensity. The performances of the algorithms were assessed using the Dice index with 5-fold cross-validation. The Dice indices were analyzed according to infarct volumes (< 10 mL, ≥ 10 mL), number of infarcts (≤ 5, 6-10, ≥ 11), and b-value of 1000 (b1000) signal intensities (< 50, 50-100, > 100), time intervals to DWI, and DWI protocols. Results: The CNN algorithms were significantly superior to conventional algorithms (p < 0.001). Dice indices for the CNN algorithms were 0.85 for U-Net and DenseNet and 0.86 for an ensemble of U-Net and DenseNet, while the indices were 0.58 for ADC-b1000 and b1000-ADC and 0.52 for the commercial ADC algorithm. The Dice indices for small and large lesions, respectively, were 0.81 and 0.88 with U-Net, 0.80 and 0.88 with DenseNet, and 0.82 and 0.89 with the ensemble of U-Net and DenseNet. The CNN algorithms showed significant differences in Dice indices according to infarct volumes (p < 0.001). Conclusion: The CNN algorithm for automatic segmentation of acute ischemic lesions on DWI achieved Dice indices greater than or equal to 0.85 and showed superior performance to conventional algorithms.

• 한국초등상담교육학회:학술대회논문집
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• 2004.01a
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• pp.223-245
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• 2004

The purpose of this study was to investigate the differences in depression, irrational faith and the school adaptation of elementary school students by their sex and region, to provide basic materials to teach children with the likelihood to be depressed by analyzing the correlation of depression, irrational faith and school adaptation, and help them to have healthy emotion and behaviors. To achieve these goals, following agenda were set. First, what are the differences in the depression, the irrational faith and the school adaptation of elementary school students by their sex and region? Second, what is the relationship between the depression characteristics and the irrational faith of elementary school students? Third, what is the relationship between the irrational faith and the school adaptation of elementary school students? Fourth, what is the relationship between the depression characteristics and school adaptation of elementary school students? : To resolve these agenda, the subjects were selected from Grade 6 students from the elementary schools locatec in Suwon and Hwaseong. The jubjects were selected from the two schools in Suwon and three schools in Hwaseong which were randomly chosen. The subjects were 670 in total. 70 insincere answers were excluded from the analysis. Therefore the subjects used in the analysis were 600 in total(150 male and female students in city respectively and 150 male and female students in rural area respectively). The tools used for this study were Children's Depression Inventory (CDI), Irrational Faith Test (over-self-reliance, dichotomy, determinism, over-concern, evasive faith, over dependent faith), School Adaptation Test (Attitudes to teachers and school environments, hobbies and specialties, academic achievements, peer relationship). Materials were processed with the SPSS program for ANOVA and correlation analysis. All the statistical values were verified at .05 level. The followings are the results of the analysis of the collected data. First, in the analysis of depression, there was significant difference between male and female students (F=4.75, p<.05). Female students (X =56.93) showed a little higher value than male students (X =53.83). There was significant difference between regions (F=13.02, p<.001), too. Rural area students (X =57.93) showed higher value than city area students (X =52.82). When analyzing irrational faith, there was significant difference between male and female students (F=S.60, p<.05). Female students (X =81.32) showed a little higher value than male students (X =77.72). There was no significant difference according to regions. When analyzing the school adaptation, there was no significant difference according to either sex or region. Second, depression and irrational faith showed highly positive correlations in all areas. In particular, over concern and evasive faith showed the highest correlation with depression inclination (r=.68, p<.001). When looking into the results by sex and by region, female students (r=.70, p<.001) and the rural area students (r=.69, p<.001) showed higher correlation between depression and irrational faith than male students and city area students (r=.63, p<.001). Additionally, in all areas including by sex and by region, a positive correlation was shown. In all variables such as male students (r=.63, p<.001), female students (r=.72, p<.001), city area students (r=.66, p<.001), and rural area students (r=.69, p<.001), over concern and evasive faith showed the highest correlation with depression inclinations. Third, irrational faith (overall) and its sub factors such as over-self-reliance, dichotomy, determinism, over-concern and evasive faith had significant negative correlations with school adaptation (overall) and its sub factors in the scope of $r=-.27{\sim}-.52$. Determinism out of the sub factors of the irrational faith had the highest negative correlation with school adaptation (overall) and sub factors at the scope of $r=-.37{\sim}-.51$. However, over-self-reliance showed the negative correlation with school adaptation (overall) and its sub factors only partially. When looking into the results by gender, both genders showed significant negative correlation between irrational faith (overall) and its sub factors with school adaptation. Male students showed highly negative correlations with school adaptation (overall) and its sub factors in determinism ($r=-.35{\sim}-52$) and over-concern and evasive faith($r=-.31{\sim}-.51$), and fern ale students showed in over-self-reliance ($r=-.27{\sim}-.45$). However over-self-reliance showed negative correlation with school adaptation and its sub factors only partially. When looking into by region, both city and rural areas showed significant negative correlation between irrational faith (overall) and it sub factors, and school adaptation. Rural areas showed higher negative correlation in irrational faith (overall) ($r=-.39{\sim}-.53$) and over-self-reliance ($r=-.32{\sim}-.44$) and dichotomy ($r=-.28{\sim}-.39$) than city areas. However over-self-reliance showed negative correlation with school adaptation and its sub factors only partially. Fourth, depression and school adaptation showed the negative correlation in all areas. In particular, academic achievements and peer relationship showed the highest negative correlation with depression (r=-.53 p<.001). When looking into the results by sex and by region, female students (r=-.62, p<.001) and rural area students (r=-.61, p<.001) showed higher negative correlation with depression and school adaptation than female students (r=-.56, p<.001) and city area students (r=-.57, p<.001). Although there was negative correlation in all areas by sex and by region, male students (r=-.52, p<.001) and rural area students (r=-.56, p<.001) showed the highest negative correlation in peer relationship and female students (r=-.57, p<.001) and city area students (r=-.56, p<.001) showed the highest negative correlation in academic records. Based on the results of the study, it is proposed to provide elementary school students sho are likely to be depressed very easily with careful counselling and teaching based on the attention and love in school fields so that they can adapt themselves to home, school and society with positive and reasonable thinking.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.123-139
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• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• Journal of the Korean Society of Radiology
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• v.10 no.8
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• pp.619-627
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• 2016

The purpose of this study is to investigate the effect of CT contrast agent and MRI contrast agent on the area dose in the body when using automatic exposure control system in general radiography. After making rectangular holes in the center of the abdominal thickness paraffin phantom, CT contrast agent and MRI contrast agent were respectively diluted with physiological saline solution for contrast medium dilution ratio of 10:0, 9:1, 8:2, 7:3, 6:4, 5:5, 4:6, 3:7, 2:8, 1:9, 0:10%. Each experiment was set to 78 kVp, 320 mA, which is the proper condition for KUB photography, and thereafter a total of 30 inspections were made for each dilution ratio using an automatic exposure control device, and the area dose corresponding to the dilution ratio of each contrast agent, Average comparison and correlation analysis were performed on the exposure index. As a result, the CT contrast agent and the MRI contrast agent appeared different in area dose according to the dilution ratio(p<0.05), and as the dilution ratio increased, the area dose increased for CT contrast agent and MRI contrast agent(P<0.05). In each test, the exposure index showed the manufacturer's recommendation of 200-800 EI value, and the exposure index and area dose increased as the area dose increased(p<0.05). In conclusion, CT contrast agent and MRI contrast agent confirmed to increase the area dose by general imaging test using all automatic exposure control device. Therefore, it is considered that it is necessary to perform it after the contrast medium has been excreted sufficiently when using usual imaging test after using the contrast agent in CT and MRI examination.

• Geophysics and Geophysical Exploration
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• v.15 no.4
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• pp.209-218
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• 2012

Repeatability and reproducibility in solid weight and effective porosity measurements have been discussed using 8 core samples with different diameters, lengths, rock types, and effective porosities. Further, the effect of temperature on the effective porosity measurement has been discussed as well. Effective porosity of each sample has been measured 7 times with vacuum saturation method with vacuum pressure of 1 torr and vacuum time of 80 minutes. Firstly, effective porosity of each sample is measured one by one, so that it can provide a reference value. Then for reproducibility check, effective porosity measurements with vacuum saturation of 2, 4, and 8 samples simultaneously have been performed. And finally, repeated measurements for 3 times for each sample are made for repeatability check. Average deviation from the reference set in solid weight showed 0.00 $g/cm^3$, which means perfect repeatability and reproducibility. For effective porosity, average deviations are less than 0.07% and 0.05% in repeatability and reproducibility test sets, respectively, which are in good agreement too. Most of porosities measured in reproducibility test lies within the deviation range in repeatability test sets. Thus, simultaneous vacuum saturation of several samples has little impact on the effective porosity measurement when high vacuum pressure of 1 torr is used. Air temperature can cause errors on submerged weight read and even effective porosity, because it is closely related to the temperature, density, and buoyancy of water. Consequently, for accurate measurement of effective porosity in a laboratory, efforts for maintaining air or water temperature constant during the experiment, or a temperature correction from other information are needed.

• Applied Biological Chemistry
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• v.50 no.4
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• pp.245-252
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• 2007

FTA (fault tree analysis), an analytical method for system failure management, was employed in the management of faults in running PCR analysis. PCR is executed through several processes, in which the process of PCR machine operation was selected for the analysis by FTA. The reason for choosing the simplest process in the PCR analysis was to adopt it as a first trial to test a feasibility of the FTA approach. First, fault events-top event, intermediate event, basic events-were identified by survey on expert knowledge of PCR. Then those events were correlated deductively to build a fault tree in hierarchical structure. The fault tree was evaluated qualitatively and quantitatively, yielding minimal cut sets, structural importance, common cause vulnerability, simulation of probability of occurrence of top event, cut set importance, item importance and sensitivity. The top event was 'errors in the step of PCR machine operation in running PCR analysis'. The major intermediate events were 'failures in instrument' and 'errors in actions in experiment'. The basic events were four events, one event and one event based on human errors, instrument failure and energy source failure, respectively. Those events were combined with Boolean logic gates-AND or OR, constructing a fault tree. In the qualitative evaluation of the tree, the basic events-'errors in preparing the reaction mixture', 'errors in setting temperature and time of PCR machine', 'failure of electrical power during running PCR machine', 'errors in selecting adequate PCR machine'-proved the most critical in the occurrence of the fault of the top event. In the quantitative evaluation, the list of the critical events were not the same as that from the qualitative evaluation. It was because the probability value of PCR machine failure, not on the list above though, increased with used time, and the probability of the events of electricity failure and defective of PCR machine were given zero due to rare likelihood of the events in general. It was concluded that this feasibility study is worth being a means to introduce the novel technique, FTA, to the management of faults in running PCR analysis.