• Information Systems Review
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• v.23 no.1
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• pp.69-91
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• 2021

Credit Bureaus in Korea commonly use financial transaction information of the past and present time for calculating an individual's credit scores. Compared to other rating factors, the repayment history information accounts for a larger weights on credit scores. Accordingly, despite full redemption of overdue payments, late payment history is reflected negatively for the assessment of credit scores for certain period of the time. An individual with debt delinquency can be classified into two groups; (1) the individuals who have faithfully paid off theirs overdue debts(Normal Repayment), and (2) those who have not and as differences of creditworthiness between these two groups do exist, it needs to grant relatively higher credit scores to the former individuals with normal repayment. This study is designed to analyze the factors of normal repayment of Korean financial debt delinquents based on credit information of personal loan, overdue payments, redemption from Korea Credit Information Services. As a result of the analysis, the number of overdue and the type of personal loan and delinquency were identified as significant variables affecting normal repayment and among applied methodologies, neural network models suggested the highest classification accuracy. The findings of this study are expected to improve the performance of individual credit scoring model by identifying the factors affecting normal repayment of a financial debt delinquent.

• Journal of Industrial Convergence
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• v.22 no.4
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• pp.21-29
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• 2024

This study analyzed the difficulty of scoring in different match situations in relation to which competitor scored first. The study analyzed the data from the 2022 Guadalajara World Taekwondo Championships. The analysis was performed for two separate weight classes: lightweight and heavyweight. Four game content variables were used: whether the athlete scored first, attack type, attack area, and game situation. Descriptive statistics, the Rasch model, and discrimination function questions were applied for data processing. SPSS and Winsteps were used for the statistical analysis, and the statistical significance level was set at 0.05. Consequently, in the lightweight class, the scoring frequency of the first scorer was high for all the game variables. In the heavyweight class, the scoring frequency for the first scorer was high for the attack type and attack area. By contrast, those who did not score first were more frequently found to be in a loss situation. By analyzing the scoring difficulties in different match situations based on whether the competitor scored first, the athletes who scored first in attack type most easily scored first. In losing situations, the athletes who scored first in attack area scored most easily, whereas those who did not score first scored most easily in body and match situations. For the heavyweight class, those who scored first in terms of attack type, counter-attack, and attack area scored the most easily while winning in body and match situations.

• Advances in nano research
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• v.16 no.4
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• pp.325-340
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• 2024

There are several novel uses for dispersing many nanoparticles into a conventional fluid, including dynamic sealing, damping, heat dissipation, microfluidics, and more. Therefore, melting heat and mass transfer characteristics of a 3-D MHD Hybrid Nanofluid flow over a rotating disc with presenting dufour and soret effects are assessed numerically in this study. In this instance, we investigated both ferric sulfate and molybdenum disulfide as nanoparticles suspended within base fluid water. The governing partial differential equations are transformed into linked higher-order non-linear ordinary differential equations by the local similarity transformation. The collection of these deduced equations is then resolved using a Chebyshev spectral collocation-based algorithm built into the Mathematica software. To demonstrate how different instances of hybrid/ nanofluid are impacted by changes in temperature, velocity, and the distribution of nanoparticle concentration, examples of graphical and numerical data are given. For many values of the material parameters, the computational findings are shown. Simulations conducted for different physical parameters in the model show that adding hybrid nanoparticle to the fluid mixture increases heat transfer in comparison to simple nanofluids. It has been identified that hybrid nanoparticles, as opposed to single-type nanoparticles, need to be taken into consideration to create an effective thermal system. Furthermore, porosity lowers the velocities of simple and hybrid nanofluids in both cases. Additionally, results show that the drag force from skin friction causes the nanoparticle fluid to travel more slowly than the hybrid nanoparticle fluid. The findings also demonstrate that suction factors like magnetic and porosity parameters, as well as nanoparticles, raise the skin friction coefficient. Furthermore, It indicates that the outcomes from different flow scenarios correlate and are in strong agreement with the findings from the published literature. Bar chart depictions are altered by changes in flow rates. Moreover, the results confirm doctors' views to prescribe hybrid nanoparticle and particle nanoparticle contents for achalasia patients and also those who suffer from esophageal stricture and tumors. The results of this study can also be applied to the energy generated by the melting disc surface, which has a variety of industrial uses. These include, but are not limited to, the preparation of semiconductor materials, the solidification of magma, the melting of permafrost, and the refreezing of frozen land.

• Journal of Adhesion and Interface
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• v.25 no.1
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• pp.157-161
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• 2024

Amphiphilic gold nanoparticles, synthesized by the simultaneous binding of hydrophilic and hydrophobic ligands on their surfaces, find diverse applications in energy, bio, optical, electronic technologies, and various other fields. Particularly, these amphiphilic gold nanoparticles possess both hydrophilic and hydrophobic characteristics, enabling them to activate interface at the interface of immiscible fluids and form organized structures. The surface properties of gold nanoparticles play a crucial role in influencing the behaviors of amphiphilic gold nanoparticles at the interface of two fluids. Therefore, this study investigated the adsorption behaviors of gold nanoparticles at the organic solvent-water interface based on the surface characteristics of amphiphilic gold nanoparticles and the type of organic solvents. It was observed that the amount of adsorbed gold nanoparticles at the interface increased with the length of hydrocarbon chains in hydrophobic ligands and increased with shorter hydrocarbon chains in the organic solvent. Furthermore, using the Langmuir isotherm model, the study confirmed the formation of a monolayer by amphiphilic gold nanoparticles and obtained significant thermodynamic parameters simultaneously.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.1985-1995
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• 2021

Objective: Although the liver-to-spleen volume ratio (LSVR) based on CT reflects portal hypertension, its prognostic role in cirrhotic patients has not been proven. We evaluated the utility of LSVR, automatically measured from CT images using a deep learning algorithm, as a predictor of hepatic decompensation and transplantation-free survival in patients with hepatitis B viral (HBV)-compensated cirrhosis. Materials and Methods: A deep learning algorithm was used to measure the LSVR in a cohort of 1027 consecutive patients (mean age, 50.5 years; 675 male and 352 female) with HBV-compensated cirrhosis who underwent liver CT (2007-2010). Associations of LSVR with hepatic decompensation and transplantation-free survival were evaluated using multivariable Cox proportional hazards and competing risk analyses, accounting for either the Child-Pugh score (CPS) or Model for End Stage Liver Disease (MELD) score and other variables. The risk of the liver-related events was estimated using Kaplan-Meier analysis and the Aalen-Johansen estimator. Results: After adjustment for either CPS or MELD and other variables, LSVR was identified as a significant independent predictor of hepatic decompensation (hazard ratio for LSVR increase by 1, 0.71 and 0.68 for CPS and MELD models, respectively; p < 0.001) and transplantation-free survival (hazard ratio for LSVR increase by 1, 0.8 and 0.77, respectively; p < 0.001). Patients with an LSVR of < 2.9 (n = 381) had significantly higher 3-year risks of hepatic decompensation (16.7% vs. 2.5%, p < 0.001) and liver-related death or transplantation (10.0% vs. 1.1%, p < 0.001) than those with an LSVR ≥ 2.9 (n = 646). When patients were stratified according to CPS (Child-Pugh A vs. B-C) and MELD (< 10 vs. ≥ 10), an LSVR of < 2.9 was still associated with a higher risk of liver-related events than an LSVR of ≥ 2.9 for all Child-Pugh (p ≤ 0.045) and MELD (p ≤ 0.009) stratifications. Conclusion: The LSVR measured on CT can predict hepatic decompensation and transplantation-free survival in patients with HBV-compensated cirrhosis.

• Korean Journal of Radiology
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• v.22 no.11
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• pp.1850-1857
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• 2021

Objective: The purpose of this study was to assess whether a deep learning (DL) algorithm could enable simultaneous noise reduction and edge sharpening in low-dose lumbar spine CT. Materials and Methods: This retrospective study included 52 patients (26 male and 26 female; median age, 60.5 years) who had undergone CT-guided lumbar bone biopsy between October 2015 and April 2020. Initial 100-mAs survey images and 50-mAs intraprocedural images were reconstructed by filtered back projection. Denoising was performed using a vendor-agnostic DL model (ClariCT.AI^TM, ClariPI) for the 50-mAS images, and the 50-mAs, denoised 50-mAs, and 100-mAs CT images were compared. Noise, signal-to-noise ratio (SNR), and edge rise distance (ERD) for image sharpness were measured. The data were summarized as the mean ± standard deviation for these parameters. Two musculoskeletal radiologists assessed the visibility of the normal anatomical structures. Results: Noise was lower in the denoised 50-mAs images (36.38 ± 7.03 Hounsfield unit [HU]) than the 50-mAs (93.33 ± 25.36 HU) and 100-mAs (63.33 ± 16.09 HU) images (p < 0.001). The SNRs for the images in descending order were as follows: denoised 50-mAs (1.46 ± 0.54), 100-mAs (0.99 ± 0.34), and 50-mAs (0.58 ± 0.18) images (p < 0.001). The denoised 50-mAs images had better edge sharpness than the 100-mAs images at the vertebral body (ERD; 0.94 ± 0.2 mm vs. 1.05 ± 0.24 mm, p = 0.036) and the psoas (ERD; 0.42 ± 0.09 mm vs. 0.50 ± 0.12 mm, p = 0.002). The denoised 50-mAs images significantly improved the visualization of the normal anatomical structures (p < 0.001). Conclusion: DL-based reconstruction may enable simultaneous noise reduction and improvement in image quality with the preservation of edge sharpness on low-dose lumbar spine CT. Investigations on further radiation dose reduction and the clinical applicability of this technique are warranted.

• Journal of the Korean Geotechnical Society
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• v.40 no.3
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• pp.77-84
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• 2024

Aging and damaged underground utilities cause cavity and ground subsidence under roads, which can cause economic losses and risk user safety. This study used infrared cameras to assess the thermal characteristics of such cavities and evaluate their reliability using a CNN algorithm. PVC pipes were embedded at various depths in a test site measuring 400 cm × 50 cm × 40 cm. Concrete blocks were used to simulate road surfaces, and measurements were taken from 4 PM to noon the following day. The initial temperatures measured by the infrared camera were 43.7℃, 43.8℃, and 41.9℃, reflecting atmospheric temperature changes during the measurement period. The RP algorithm generates images in four resolutions, i.e., 10,000 × 10,000, 2,000 × 2,000, 1,000 × 1,000, and 100 × 100 pixels. The accuracy of the CNN model using RP images as input was 99%, 97%, 98%, and 96%, respectively. These results represent a considerable improvement over the 73% accuracy obtained using time-series images, with an improvement greater than 20% when using the RP algorithm-based inputs.

• Journal of Korean Society of Forest Science
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• v.113 no.2
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• pp.170-186
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• 2024

This study was conducted to identify the usage characteristics of the DMZ Punchbowl Trail (DPT) as a national forest trail (NFT) and to estimate its ripple effects on the local economy. The objective of this study is to provide policy implications for sustainable operational management. Out of the 500 questionnaires distributed, 215 respondents provided their complete travel itineraries and expenditures. The respondents, mainly aged 50 and above and residing in the Seoul Metropolitan Area, spend 3.5 hours of travel time to the DPT. Together with their families, the respondents typically spend approximately 4 hours for leisurely activities, primarily appreciation of scenic views and relaxation by visiting the "O-yubatgil." Furthermore, they extend their travels to other parts of Gangwon Province, where the DPT is situated. Within Gangwon Province, Yanggu County is the most visited destination. The respondents reported a notably higher average expenditure per visitor compared with the typical local walking tourists. Estimates show that the DPT generates an annual average of KRW 2.1 billion in direct expenditure (based on an average of 10,000 visitors for over five years), KRW 2.8 billion in production, and KRW 1.3 billion in added value, and it has created 40 jobs in Gangwon Province. The results of this study lies in empirically determining the specific economic scale and ripple effects of DPT as an NFT in the major sector, which occupies a significant portion of the Gangwon Province's local economy. The results will be instrumental in validating NFT policies and informing policy making for sustainable forest utilization.

• Korean Journal of Radiology
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• v.22 no.2
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• pp.213-224
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• 2021

Objective: Clinical outcomes of patients who undergo transarterial chemoembolization (TACE) for single small hepatocellular carcinoma (HCC) are not consistent, and may differ based on certain imaging findings. This retrospective study was aimed at determining the efficacy of pre-TACE CT or MR imaging findings in predicting survival outcomes in patients with small HCC upon being treated with TACE. Besides, the study proposed to build a risk prediction model for these patients. Materials and Methods: Altogether, 750 patients with functionally good hepatic reserve who received TACE as the first-line treatment for single small HCC between 2004 and 2014 were included in the study. These patients were randomly assigned into training (n = 525) and validation (n = 225) sets. Results: According to the results of a multivariable Cox analysis, three pre-TACE imaging findings (tumor margin, tumor location, enhancement pattern) and two clinical factors (age, serum albumin level) were selected and scored to create predictive models for overall, local tumor progression (LTP)-free, and progression-free survival in the training set. The median overall survival time in the validation set were 137.5 months, 76.1 months, and 44.0 months for low-, intermediate-, and high-risk groups, respectively (p < 0.001). Time-dependent receiver operating characteristic curves of the predictive models for overall, LTP-free, and progression-free survival applied to the validation cohort showed acceptable areas under the curve values (0.734, 0.802, and 0.775 for overall survival; 0.738, 0.789, and 0.791 for LTP-free survival; and 0.671, 0.733, and 0.694 for progression-free survival at 3, 5, and 10 years, respectively). Conclusion: Pre-TACE CT or MR imaging findings could predict survival outcomes in patients with small HCC upon treatment with TACE. Our predictive models including three imaging predictors could be helpful in prognostication, identification, and selection of suitable candidates for TACE in patients with single small HCC.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.11 no.2
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• pp.82-91
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• 2006

We investigated the possibility of using effluents from a municipal sewage treatment plant (STP) as tracers a tracer for hydrologic studies of rivers. The possibility was checked in a 12-km long reach downstream of Jeonju Municipal Sewage Treatment Plant (JSTP). Time-series monitoring of the water chemistry reveals that chemical compositions of the effluent from the JSTP are fluctuating within a relatively wide range during the sampling period. In addition, the signals from the plant were observed at the downstream stations consecutively with increasing time lags, especially in concentrations of the conservative chemical parameters (concentrations f3r chloride and sulfate, total concentration of major cations, and electric conductivity). Based on this observation, we could estimate the stream flow (Q), velocity (v), and dispersion coefficient (D). A 1-D nonreactive solute-transport model with automated optimization schemes was used for this study. The values of Q, v, and D estimated from this study varied from 6.4 to $9.0m^3/sec$ (at the downstream end of the reach), from 0.06 to 0.10 m/sec, and from 0.7 to $6.4m^2/sec$, respectively. The results show that the effluent from a large-scaled municipal STP frequently provides good, multiple natural tracers far hydrologic studies.