• 한국지진공학회논문집
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• 제19권5호
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• pp.229-238
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• 2015

For small-size reinforce-concrete buildings, Midas Gen, OpenSees, and Perform-3D, which are structural analysis programs that are most popularly used at present, were applied for nonlinear static pushover analysis, and then difference between those programs was analyzed. Example buildings were limited to 2-story frames with irregular shaped walls. Analysis result showed that there were more differences than for frames only and frames with rectangular walls, but it was not so significant. Nevertheless, the capacity curve were different in some buildings, which is attributed to shape and location of walls, and feature of the analysis program. Especially, selection of automatic or manual input in Midas Gen, or nonlinear wall elements in Perform3D can affect the capacity curve and performance of the buildings. Therefore, the program users should understand the feature of the program well, and then conduct performance assessment. The result of this study is limited to low-story buildings so that it should be noted that it is possible to get different results for mid- to high-rise buildings.

• 한국해양공학회지
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• 제32권4호
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• pp.253-260
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• 2018

Recently, the application of non-steel materials in ships and offshore plants is increasing because of the development of various nonlinear materials and the improvement of performance. Especially, hyper-elastic materials, which have a nonlinear stress-strain relationship, are used mainly in marine plant structures or ships where impact relaxation, vibration suppression, and elasticity are required, while elasticity must be maintained, even under high strain conditions. In order to simulate and evaluate the behavior of the hyperelastic material, it is very important to select an appropriate material model according to the strain of the material. This study focused on the selection of material models for hyperelastic materials, such as rubber used in the marine and offshore fields. Tension and compression tests and finite element simulations were conducted to compare the accuracy of the nonlinear material models due to variations in the stretch ratio of hyper-elastic material. Material coefficients of nonlinear material models are determined based on the curve fitting of experimental data. The results of this study can be used to improve the reliability of nonlinear material models according to stretch ratio variation.

• Asian Pacific Journal of Cancer Prevention
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• 제17권1호
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• pp.347-352
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• 2016

Background: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) adenosquamous carcinoma data to identify predictive models and potential disparities in outcome. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for adenosquamous carcinoma. For the risk modeling, each factor was fitted by a generalized linear model to predict the cause specific survival. An area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. Results: A total of 20,712 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 54.2 (78.4) months. Some 2/3 of the patients were female. The mean (S.D.) age was 63 (13.8) years. SEER stage was the most predictive factor of outcome (ROC area of 0.71). 13.9% of the patients were un-staged and had risk of cause specific death of 61.3% that was higher than the 45.3% risk for the regional disease and lower than the 70.3% for metastatic disease. Sex, site, radiotherapy, and surgery had ROC areas of about 0.55-0.65. Rural residence and race contributed to socioeconomic disparity for treatment outcome. Radiotherapy was underused even with localized and regional stages when the intent was curative. This under use was most pronounced in older patients. Conclusions: Anatomic stage was predictive and useful in treatment selection. Under-staging may have contributed to poor outcome.

• 수산해양기술연구
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• 제55권4호
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• pp.285-293
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• 2019

The mesh selectivity of hairtail (Trichiurus lepturus) caught by coastal drift gill net was examined in field experiments with three different mesh sizes (45, 50 and 55 mm) from October to November, 2013 in the coastal areas of south-west of Jeju province. The mesh selectivity tests were conducted with the experimental net to be set middle part of conventional driftnets. The mesh selectivity tests were carried out the total of four times. The selectivity curve was estimated by the Kitahara's and Fujimori's method. In the results, the catch number of hairtail was 653 (125.8 kg) and occupied 34.8% in total catches weight. The optimal mesh size for 50% selection on the minimum landing size (180 mm, AL) and the first maturity size (260 mm, AL) of hairtail were estimated as 47.2 mm and 64.5 mm by master selectivity curves, respectively.

• 한국농공학회논문집
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• 제54권5호
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• pp.129-139
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• 2012

Accurate modeling rainfall induced landslide and slope stability requires a detailed knowledge of the distribution of material strength characteristics and suction distribution. However, material properties obtained from the drying cycle are still used for infiltration analysis in many cases, even though material properties of wetting cycle are quite different from those of drying cycle due to hydraulic hysteresis and air occlusion. Therefore, the selection of proper material properties such as soil-water retention curve (SWRC) and the hydraulic conductivity function (HCF) reflecting characteristics of wetting cycle and air occlusion is an essential prerequisite in order to simulate the infiltration phenomena and to predict the suction and water content distribution in unsaturated soils. It is concluded that the simulation of infiltration with material properties from the drying cycle did not reasonably match with experimental outputs. Further discussion is made on how to describe the material properties considering air occlusion during wetting cycle over the entire suction range in order to simulate infiltration phenomena.

• 한국지열·수열에너지학회논문집
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• 제17권2호
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• pp.20-29
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• 2021

In this study, it is proposed that an analysis method using charatersistics curve of PICV in the CFD simulation for hydronic system. From the results, the pressure drop characteristics appeared in the region of PICV at a specified flow rate. And the CFD results are in good agreement with the experimental results. Proposed analysis method is proved that the characteristics of PICV applied to the hydronic system were properly applied in the flow analysis. This result can be applied to PICV in the complex hydronic systems. Therefore, the optimal selection of PICV in hydronic system contribute the building energy saving.

• Physical Therapy Rehabilitation Science
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• 제11권2호
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• pp.154-164
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• 2022

Objective: The purpose of this study is to select a cognitive training game that can evaluate five cognitive domains and to study their validity with existing cognitive evaluation tools. Design: Methods: Delphi survey was conducted through the 2nd questionnaire for 30 experts to select games suitable for training 5 cognitive domains. Five cognitive training games and Mini Mental State Examination - Korea(MMSE-K), and cognitive impairment screening test(CIST) were conducted for 82 elderly in the community. Pearson correlation analysis was performed to find out the correlation of the three tests. The ROC curve was used to calculate the selection criteria for the game results for the screening evaluation of the presence or absence of mild cognitive impairment. Results: The coefficient of variation to evaluate the stability of the Delphi survey was less than 0.50 in most game items. The 'correct answers' and 'level' of the five final selected game items showed a statistically significant positive correlation with the CIST and MMSE-K scores. CIST score and 'time' of all game items except 'number making_time' showed a statistically significant negative correlation. Conclusions: The validity of the cognitive training program using smart devices was evaluated, and the criteria for classifying the cognitive domain and distinguishing the presence or absence of cognitive impairment were confirmed.

• Current Optics and Photonics
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• 제8권3호
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• pp.282-299
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• 2024

Target detection (TD) is a research hotspot in the field of hyperspectral imaging (HSI). Traditional TD methods often mine targets from HSIs under a single imaging condition, without considering the influence of imaging conditions. In fact, the spectra of ground objects in HSIs are uncertain and affected by the imaging conditions (weather, atmospheric, light, time, and other angle conditions including zenith angle). Hyperspectral data changes under different imaging conditions. Therefore, the detection result for a single imaging condition cannot accurately reflect the effectiveness of the detection method used. It is necessary to analyze the performance of various detection methods under different imaging conditions, to find a more applicable detection method. In this paper, we study the performance of TD methods under various land-based imaging conditions. We first summarize classical TD methods and evaluation methods. Then, the detection effects under various imaging conditions are analyzed. Finally, the concepts of the stability coefficient (SC) and effective area under the curve (EAUC) are proposed to comprehensively evaluate the applicability of detection methods under land-based imaging conditions, in terms of both detection accuracy and stability. This is conducive to our selection of detection methods with better applicability in land-based contexts, to improve detection accuracy and stability.

• 대한임상검사과학회지
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• 제38권3호
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• pp.166-172
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• 2006

Metallo-${\beta}$-lactamase (MBL) can hydrolyze all ${\beta}$-lactams except monobactams and frequently coexists with various antibiotic resistance genes such as aminoglycoside resistance, sulfonamide resistance gene, etc. Therefore, the effective antibiotics against infections by these bacteria are markedly limited or can't even be found. We tried to search in-vitro antimicrobial combinations with synergistic effects for a VIM-2 type MBL producing Pseudomonas aeruginosa, isolated from clinical specimen. On the selection of antibiotic combinations with synergistic effects, we performed a one disk synergy test, modified Pestel's method, in agar without aztreonam (AZT). The bacteriostatic synergistic effects of this tests were scored as $S_1$ (by susceptibility pattern in agar without antibiotics), $S_2$ (by the change of susceptibility in agar with or without antibiotics) and $S_3$ ($S_1$ + $S_2$) and was classified into weak (1 point), moderate (2 points) and strong (3 points) by $S_3$ score. Subsequently, we carried out the time-killing curve for the antibiotic combinations with the strong synergistic bacteriostatic effect. One VIM-2 type MBL producing P. aeruginosa confirmed by the PCR showed all resistance against all ${\beta}$-lactams except AZT, aminoglycoside and ciprofloxacin. In the one disk synergy test, this isolate showed a strong bacteriostatic synergistic effect for the antibiotic combination of AZT and piperacillin-tazobactam (PIP-TZP) or AZT and amikacin (AN). On the time-killing curve after six hours of incubation, the colony forming units (CFUs/mL) of this bacteria in the medium broth with both combination antibiotics were decreased to 1/18.7, 1/17.1 of the least CFUs of each single antibiotics. The triple antibiotic combination therapy including AZT, PIP-TZP and AN was shown to be significantly synergistic after 8 hrs of exposure. In a VIM-2 MBL producing P. aeruginosa with susceptibility for AZT, the triple antibiotic combination therapy including AZT, PIP-TZP and AN may be considered as an alternative antibiotics modality against the infection by some MBL type. But the antimicrobial combination therapy for many more MBL producing isolates is essential to know as soon as possible for the selection of effective treatment against the infection by this bacteria.

• Korean Journal of Radiology
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• 제23권8호
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• pp.811-820
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• 2022

Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses. Results: Age, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825-0.910) in the training cohort and 0.890 (0.844-0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness. Conclusion: The clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcomes.