• Korean Journal of Radiology
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• v.23 no.8
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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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.69-77
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• 2022

The 3D spatial model is an analysis framework for solving urban problems and is used in various fields such as urban planning, environment, land and housing management, and disaster simulation. The utilization of drones that can capture 3D images in a short time at a low cost is increasing for the construction of 3D spatial model. In terms of building a virtual city and utilizing simulation modules, high location accuracy of aerial survey and precision of 3D spatial model function as important factors, so a method to increase the accuracy has been proposed. This study analyzed location accuracy of aerial survey and precision of 3D spatial model by each condition of aerial survey for urban areas where buildings are densely located. We selected Daerim 2-dong, Yeongdeungpo-gu, Seoul as a target area and applied shooting angle, shooting altitude, and overlap rate as conditions for the aerial survey. In this study, we calculated the location accuracy of aerial survey by analyzing the difference between an actual survey value of CPs and a predicted value of 3D spatial Model. Also, We calculated the precision of 3D spatial Model by analyzing the difference between the position of Point cloud and the 3D spatial Model (3D Mesh). As a result of this study, the location accuracy tended to be high at a relatively high rate of overlap, but the higher the rate of overlap, the lower the precision of 3D spatial model and the higher the shooting angle, the higher precision. Also, there was no significant relationship with precision. In terms of baseline-height ratio, the precision tended to be improved as the baseline-height ratio increased.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1139-1158
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• 2015

This paper proposes an efficient system identification method for modeling nonlinear behavior of civil structures. This method is developed by integrating three different methodologies: principal component analysis (PCA), artificial neural networks, and fuzzy logic theory, hence named PANFIS (PCA-based adaptive neuro-fuzzy inference system). To evaluate this model, a 3-story building equipped with a magnetorheological (MR) damper subjected to a variety of earthquakes is investigated. To train the input-output function of the PANFIS model, an artificial earthquake is generated that contains a variety of characteristics of recorded earthquakes. The trained model is also validated using the1940 El-Centro, Kobe, Northridge, and Hachinohe earthquakes. The adaptive neuro-fuzzy inference system (ANFIS) is used as a baseline. It is demonstrated from the training and validation processes that the proposed PANFIS model is effective in modeling complex behavior of the smart building. It is also shown that the proposed PANFIS produces similar performance with the benchmark ANFIS model with significant reduction of computational loads.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.1
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• pp.139-146
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• 2013

A process diagnosis method for membrane water treatment plant was developed using a constant flux membrane fouling model. This diagnosis method can be applied to a real-field membrane-based water treatment plant as an early alarming system for membrane fouling. The constant flux membrane fouling model was based on the simplest equation form to describe change in trans-membrane pressure (TMP) during the filtration cycle from a literature. The model was verified using a pilot-scale microfiltraton (MF) plant with two commercial MF membrane modules (72 m2 of membrane area). The predicted TMP data were produced using the model, where the modeling parameters were obtained by the least square method using the early plant data and modeling equations. The diagnosis was carried out by comparing the predicted TMP data (as baseline) and real plant data. As a result of the case study, the diagnsis method worked pretty well to predict the early points where fouling started to occur.

• Journal of Korea Water Resources Association
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• v.42 no.10
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• pp.877-889
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• 2009

This study is to assess the future potential impact of climate change on stream water quality for a 6,581.1 km$^2$ dam watershed using SWAT (Soil and Water Assessment Tool) model. The ECHAM5-OM climate data of IPCC (The Intergovernmental Panel on Climate Change) A2, A1B, and B1 emission scenarios were adopted and the future data (2007-2099) were corrected using 30 years (1977-2006, baseline period) weather data and downscaled by Change Factor (CF) method. After model calibration and validation using 6 years (1998-2003) observed daily streamflow and monthly water quality (SS, T-N, and T-P) data, the future (2020s, 2050s and 2080s) hydrological behavior and stream water quality were projected.

• Journal of Korean Society of Steel Construction
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• v.22 no.4
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• pp.377-388
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• 2010

The flexural behavior of composite HSB600 and HSB800 I-girders under a positive moment was investigated using the material non-linear moment-curvature analysis method. Three representative composite sections with different ductility properties were selected as the baseline sections in this study. Using these baseline sections, the moment-curvature program was verified by comparing the flexural strength and the moment-curvature curve obtained from the program with those obtained using the non-linear FE analysis of ABAQUS. In the FE analysis, the composite girders were modeled three-dimensionally with flanges, the web, and the concrete slab as thin shell elements, and initial imperfections and residual stresses were imposed on the FE model. In the moment-curvature and FE analyses, the 28-day compressive strength of the concrete slab was assumed to be 30-50 MPa, and the HSB600 and HSB800 steels were modeled as elasto-plastic strain-hardening materials, with the concrete as the CEB-FIP model. The effects of the ductility ratio of the composite girder, the type of steel, the compressive strength of the concrete deck, and the location of the plastic neutral axis on the flexural characteristics were analyzed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.5
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• pp.404-414
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• 2013

In the conceptual design phase of jet fighters, the trade study is performed repeatedly for a selection of the baseline configuration. The automation of repeated trade study makes possible to select efficiently the baseline configuration. In this study, the performance analysis code was developed for the automation of trade study. The code was consists of the module of shape generation, the module of weight estimation, the module of mission performance analysis. 3D CAD Model can be generated by the module of shape generation and Weight can be estimated by using the empirical equation in the module of weight estimation. The module of mission performance analysis was able to calculate the mission performance about the arbitrary mission profile. In addition, the optimal mission performance can be calculated by using optimization method. By performing the validation, the code was confirmed to be able to apply to the conceptual design phase.

• KIEAE Journal
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• v.16 no.5
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• pp.39-45
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• 2016

Purpose: The purpose of this study is to analyze the energy saving and cost benefit analysis of the Low-income Energy Efficiency Treatment Program supported by KOREF(Korea Energy Foundation). This program was launched in 2007 and performs building energy retrofit for the low-income and energy poverty houses. Method: Energy simulation and cost benefit analysis were accomplished for the low-income detached houses. The structure of detached house was a lot og block structure, wood frame (single glass) and concrete roof. Baseline model of the low-income detached houses was proposed. Result: Annual heating energy consumptions were decreased by about 3.2% with the window system replacement(Case 1), 9.3% with reinforcement of insulation(Case2), and 12.5% with both(Case 3) compared to those of baseline model. The construction cost will be recouped within 5 years for the Case 1, 3 years for the Case 2, and 3 years for the Case 3. Case 3 was the most cost beneficient construction method in the analyzed cases in this study.

• Journal of Ocean Engineering and Technology
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• v.31 no.4
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• pp.315-323
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• 2017

This paper presents an integrated navigation system that combines ultra-short baseline (USBL), Doppler velocity log (DVL), and heading measurements for a deep-sea remotely operated vehicle, Hemire. A navigation model is introduced based on the kinematic relation of the position and velocity. The system states are predicted using the navigation model and corrected with the USBL, DVL, and heading measurements using the Kalman filter. The performance of the navigation system was confirmed through re-navigation simulations with the measured data at the Southern Mariana Arc submarine volcanoes. Based on the characteristics of the measurements, the design process for the parameters of the system modeling error covariance, measurement error covariance, and initial error covariance are presented. This paper reviews the influence of the outliers and blackout of the USBL and DVL measurements, and proposes an outlier rejection algorithm that is robust to USBL blackout. The effectiveness of the method is demonstrated with re-navigation for the data that includes USBL blackouts.

• Nutrition Research and Practice
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• v.15 no.6
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• pp.789-797
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• 2021

BACKGROUD/OBJECTIVES: Registered dietitian nutritionists (RDN) are providers of medical nutrition therapy (MNT) to address health and chronic disease. Traditionally, RDNs have provided care in healthcare facilities including hospitals and private care facilities. The purpose of this study was to determine how RDN individualized MNT in the home impacted nutrition, physical activity, and food security. SUBJECTS/METHODS: This is a secondary data analysis. The mean age of the participants (n = 1,007) was 51.6 years old with a mean body mass index (BMI) of 34.1 kg/m². Individualized MNT visits were delivered by an RDN in the home setting from January to December 2019. Participants were referred by healthcare professionals or self-referred. Participants had MNT benefits covered by their health insurance plan (43.3% Medicaid; 39.8% private insurance; 7.9% Medicare, 9% other). Health outcomes related to nutrition care were measured. Outcomes included self-reported consumption of nutrition factors and physical activity. Our secondary outcome focused on food security. The changes in weight, BMI, physical activity, and nutrition factors were analyzed by a linear regression model or linear mixed model, adjusting for age, sex, baseline value, and number of appointments. Food security was summarized in a 2 by 2 contingency table. RESULTS: Baseline values had significantly negative impacts for all changes and number of appointments was significant in the changes for weight and BMI. Increases in physical activity were significant for both female and male participants, 10.4 and 12.6 minutes per day, respectively, while the changes in weight and BMI were not. Regarding dietary factors, the consumption total servings per day of vegetables (0.13) and water (3.35) significantly increased, while the consumption of total servings of whole grain (-0.27), fruit (-0.32), dairy (-0.80) and fish (-0.81) significantly decreased. About 24% (of overall population) and 45% (of Medicaid population) reported improvements in food security. CONCLUSIONS: This study found that home visits were a useful setting for MNT delivered by RDNs. There is a strong need for individualized counseling to meet the participants' needs and personal goals.