• Korean Journal of Radiology
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• v.25 no.2
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• pp.189-198
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• 2024

Objective: To investigate the prognostic utility of radiomics features extracted from ¹⁸F-fluorodeoxyglucose (FDG) PET/CT combined with clinical factors and metabolic parameters in predicting progression-free survival (PFS) and overall survival (OS) in individuals diagnosed with extranodal nasal-type NK/T cell lymphoma (ENKTCL). Materials and Methods: A total of 126 adults with ENKTCL who underwent ¹⁸F-FDG PET/CT examination before treatment were retrospectively included and randomly divided into training (n = 88) and validation cohorts (n = 38) at a ratio of 7:3. Least absolute shrinkage and selection operation Cox regression analysis was used to select the best radiomics features and calculate each patient's radiomics scores (RadPFS and RadOS). Kaplan-Meier curve and Log-rank test were used to compare survival between patient groups risk-stratified by the radiomics scores. Various models to predict PFS and OS were constructed, including clinical, metabolic, clinical + metabolic, and clinical + metabolic + radiomics models. The discriminative ability of each model was evaluated using Harrell's C index. The performance of each model in predicting PFS and OS for 1-, 3-, and 5-years was evaluated using the time-dependent receiver operating characteristic (ROC) curve. Results: Kaplan-Meier curve analysis demonstrated that the radiomics scores effectively identified high- and low-risk patients (all P < 0.05). Multivariable Cox analysis showed that the Ann Arbor stage, maximum standardized uptake value (SUVmax), and RadPFS were independent risk factors associated with PFS. Further, β2-microglobulin, Eastern Cooperative Oncology Group performance status score, SUVmax, and RadOS were independent risk factors for OS. The clinical + metabolic + radiomics model exhibited the greatest discriminative ability for both PFS (Harrell's C-index: 0.805 in the validation cohort) and OS (Harrell's C-index: 0.833 in the validation cohort). The time-dependent ROC analysis indicated that the clinical + metabolic + radiomics model had the best predictive performance. Conclusion: The PET/CT-based clinical + metabolic + radiomics model can enhance prognostication among patients with ENKTCL and may be a non-invasive and efficient risk stratification tool for clinical practice.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1314-1319
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• 2008

Fatigue reliability problems are nowadays actively considered in the design of mechanical components. Recently, Dimension Reduction Method using Kriging approximation (KDRM) was proposed by the authors to efficiently calculate statistical moments of the response function. This method, which is more tractable for its sensitivity-free nature and providing the response PDF in a few number of analyses, is adopted in this study for the reliability analysis. Before applying this method to the practical fatigue problems, accuracies are studied in terms of parameters of the KDRM through a number of numerical examples, from which best set of parameters are suggested. In the fatigue reliability problems, good number of experimental data are necessary to get the statistical distribution of the S-N parameters. The information, however, are not always available due to the limited expense and time. In this case, a family of curves with prediction interval, called P-S-N curve, is constructed from regression analysis. Using the KDRM, once a set of responses are available at the sample points at the mean, all the reliability analyses for each P-S-N curve can be efficiently studied without additional response evaluations. The method is applied to a spring design problem as an illustration of practical applications, in which reliability-based design optimization (RBDO) is conducted by employing stochastic response surface method which includes probabilistic constraints in itself. Resulting information is of great practical value and will be very helpful for making trade-off decision during the fatigue design.

• Korean Journal of Community Nutrition
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• v.23 no.4
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• pp.277-288
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• 2018

Objectives: This study was performed to verify the validity and judgment criteria setting of a health status assessment tool based on dietary patterns for middle-aged women. Methods: A total of 474 middle-aged women who visited the Comprehensive Medical Examination Center at Hanmaeum Hospital in Changwon were enrolled (IRB 2013-0005). The validity was verified using clinical indicators for the diagnosis of metabolic syndrome (MS), and it was used to set the criteria for the tool. A logistic regression analysis was performed for validation. The area under-receiver operation (AUC), sensitivity, specificity, and Youden Index were calculated through ROC curve analysis. Statistical analysis was performed by SPSS 21, and p value <0.05 was considered to be statistically significant. Results: The mean score of the group with no MS (73.3 points) was significantly higher compared to the group with MS (65.7 points) (p<0.001). An analysis of the association between the tool scores and risk of MS showed a 0.15-fold reduction in the risk of MS every time the tool's score increased by one point. As the result of the ROC curve analysis, the assessment reference point was set to 71 points, indicating 77.0% sensitivity and 61.0% specificity. Risk of MS was significantly higher in the group with a score of less than 71.0 than a group with more than 71 points (OR=5.28, p<0.001). Conclusions: This study was the first attempt to develop a health status assessment tool based on the dietary patterns for middle-aged women, and this tool has proven its usefulness as an MS assessment tool through the application of middle-aged women in the field of health screening.

• International Area Studies Review
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• v.15 no.3
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• pp.393-405
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• 2011

Three different models have been consecutively employed with the U.S. yield curve and the Korean composite stock price index, firstly to see the coupling between the economies of the U.S. and Korea, secondly to find out the time consumed completing the coupling, and lastly to figure out the impact of the recent U.S. financial crisis on this coupling. This study has, first of all, produced an empirical research outcome which proved the existence of coupling between two countries' economies. The direction of this coupling was consistent with the general expectation that when the yield spread between the U.S. 10-year Treasury Note and the U.S. 3-month Treasury Bill increased which often occurred with better prospects of U.S. economy, the asset price of emerging economies including Korea also rose reflecting the accompanying change in investment atmosphere in favor of risk. It has also found out that the degree of the coupling was maximized with a lag of one week. And finally the recent US financial crisis has been revealed to reduce the degree of the coupling by as much as half in a regression model with a dummy variable.

• Clinical and Experimental Pediatrics
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• v.62 no.7
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• pp.261-268
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• 2019

Purpose: This study aimed to evaluate the time trends of waist circumference (WC) and waist-height ratio (WHR), and to present WC and WHR distributions with optimal WHR cutoff for abdominal obesity in Korean children and adolescents. Methods: We performed a retrospective cross-sectional analysis of data from 13,257 children and adolescents (6,987 boys and 6,270 girls) aged 6-18 years who were included in the third to sixth Korea National Health and Nutrition Examination Survey (KNHANES, 2005-2015). Linear regression analyses were used to identify secular changes in WC and WHR by age, sex, and KNHANES waves. A receiver operating characteristic curve analysis was used to determine the optimal WHR cutoff values for abdominal obesity and cardiometabolic risk factors. Results: The mean WC and WHR distributions from 2005 to 2015 showed no significant secular changes between the KNHANES 4 waves (P for trend ${\geq}0.05$ in all ages and both sexes). The mean WCs in the present study were lower than those in the 2007 Korean National Growth Charts. The mean WHR at ages <13 years was statistically higher in the boys than in the girls, but did not significantly differ between the sexes among those aged 13 to 18 years. The optimal WHR cutoff for abdominal obesity was 0.48 (area under the curve, 0.985; 95% confidence interval, 0.985-0.985) in the 13- to 18-year-old adolescents. Conclusion: WC and WHR showed no secular changes over 10 years. The optimal WHR cutoff for abdominal obesity of 0.48 is useful for diagnosing and managing obesity and thus preventing obesity-related cardiometabolic complications in 13- to 18-year-old Korean adolescents.

• Journal of Korea Water Resources Association
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• v.35 no.6
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• pp.715-727
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• 2002

The travel time of a flood through a river reach can be estimated by dividing the river length by the mean velocity with which the flood passes downstream. It is closely related to storage constant for the watershed routing of a flood. There are so many empirical formulas available for the estimation of travel time but the results computed generally show great different depending on individual formulas. In the present study, the mean velocity data computed in the process of water surface profile computation for a probability flood through more than 100 different river reaches were collected along with the mean river bed slope of each river reach. And then, a regression analysis is made between the mean river bed slope and the mean velocity, which showed a wide scatter along the mean regression curve, which appears to be due to the different in the magnitude of probability rainfall and size of watershed area. Therefore, methods have been developed to remove the effect of these factors and generalized empirical equation is proposed to relate the mean velocity to mean river bed slope of a reach. Hence, if the mean river bed slope of a river reach is estimated from the longitudinal river profile, the mean velocity can be computed by the generalized equation along with the probability rainfall and watershed area of the river reach under consideration, which leads to the estimation of travel time through a river reach.

• Journal of Information Technology Services
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• v.19 no.1
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• pp.103-112
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• 2020

Job seekers are making various efforts to find a good company and companies attempt to recruit good people. Job search activities through self-introduction essay are nowadays one of the most active processes. Companies spend time and cost to reviewing all of the numerous self-introduction essays of job seekers. Job seekers are also worried about the possibility of acceptance of their self-introduction essays by companies. This research builds a classification model and conducted an experiments to classify self-introduction essays into pass or fail using deep learning and decision tree techniques. Real world data were classified using stratified sampling to alleviate the data imbalance problem between passed self-introduction essays and failed essays. Documents were embedded using Doc2Vec method developed from existing Word2Vec, and they were classified using logistic regression analysis. The decision tree model was chosen as a benchmark model, and K-fold cross-validation was conducted for the performance evaluation. As a result of several experiments, the area under curve (AUC) value of PV-DM results better than that of other models of Doc2Vec, i.e., PV-DBOW and Concatenate. Furthmore PV-DM classifies passed essays as well as failed essays, while PV_DBOW can not classify passed essays even though it classifies well failed essays. In addition, the classification performance of the logistic regression model embedded using the PV-DM model is better than the decision tree-based classification model. The implication of the experimental results is that company can reduce the cost of recruiting good d job seekers. In addition, our suggested model can help job candidates for pre-evaluating their self-introduction essays.

• Research in Community and Public Health Nursing
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• v.30 no.4
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• pp.449-459
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• 2019

Purpose: The aim of this study is to explore different types of self-rated health trajectories among one-person households in Korea. Methods: We used five time-point data derived from Korea Health Panel (2011~2015). A latent growth curve modeling was used to assess the overall feature of self-rated health trajectory in one-person households, and a latent class growth modeling was used to determine the number and shape of trajectories. We then applied multinomial logistic regression on each class to explore the predicting variables. Results: We found that the overall slope of self-rated health in one-person households decreases. In addition, latent class analysis demonstrated three classes: 1) High-Decreasing class (i.e., high intercept, significantly decreasing slope), 2) Moderate-Decreasing class (i.e., average intercept, significantly decreasing slope), and 3) Low-Stable class (i.e., low intercept, flat and nonsignificant slope). The multinomial logistic regression analysis showed that the predictors of each class were different. Especially, one-person households with poor health condition early were at greater risk of being Low-Stable class compared with High-Decreasing class group. Conclusion: The findings of this study demonstrate that more attentions to one-person households are needed to promote their health status. Policymakers may develop different health and welfare programs depending on different characteristics of one-person household trajectory groups in Korea.

• Korean Journal of Food Science and Technology
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• v.19 no.2
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• pp.171-175
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• 1987

An objective method for the evaluation of eating quality of cooked noodle was established by using a specially designed shear extrusion cell of Rheometer. From the force-distance curve, the maximum force, initial force, extrusion work, and the slope were determined. In a test with Korean dried noodles made from 17 types of Australian wheat flour, the maximum and initial forces and extrusion work could represent the firm-soft and chewy character, which govern mostly the preference of cooked noodle. On the other hand, the slope could distinguish the textural changes of cooked noodle during the storage after cooking. The parameters showed significant correlation with the protein content, water absorption, development time and extensibility of flour, but no correlation was obtained with the maximum viscosity of viscogram. For the estimation of textural preference, the correlation coefficient obtained from a multiple regression analysis using the maximum viscosity of viscogram and the maximum force of shear extrusion test as the two independent variables was not significantly higher than the coefficient obtained from a simple regression with the maximum force only.

• Applied Biological Chemistry
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• v.40 no.3
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• pp.225-231
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• 1997

Optimization theory was applied to a native and two imported soybeans. Failure stress and stress relaxation curve was measured with rheometer, and color was measured by colorimeter. The effects of each soybean upon the tofu texture were expressed through a non-linear canonical regression model and trace plot. Compared to the other imported soybeans, native soybean produced a higher strength in tofu texture, and showed the positive increase in viscoelastic properties such as instantaneous stress, equilibrium stress and relaxation time, whereas it had no effect on whiteness from reference blend, represented that native soy-bean showed the individual strength upon the selected rheological texture properties. Higher soaking ability in native soybean was selected as a new response for the optimization mixture process, and it contributed positively to the rheological properties of tofu. New soaking process control system during processing and desirability for the mathematical model should be applied for a better mixture design in varieties of soybeans.