• The Korean Journal of Applied Statistics
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• v.33 no.3
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• pp.297-308
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• 2020

We focus on the functional autoregressive conditional heteroscedasticity (fARCH) modelling to analyze intraday volatilities based on high frequency financial time series. Multivariate volatility models are investigated to approximate fARCH(1). A formula of multi-step ahead volatilities for fARCH(1) model is derived. As an application, in implementing fARCH(1), a choice of appropriate time interval for the intraday return is discussed. High frequency KOSPI data analysis is conducted to illustrate the main contributions of the article.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.12
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• pp.84-90
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• 2010

In order to level electric power of the photovoltaic and wind-turbine system and ensure fast response of the fuel-cell and micro-turbine, the energy storage is required in the microgrid system. In this paper, a simplified simulation model of the battery energy storage for charging method with IUIa is developed using PSCAD/EMTDC. The model consists of e.m.f.(electromotive force), internal resistor and overvoltage capacitor. A method for deciding parameters of the model on a case-by-case basis is proposed. The developed model can be used in the simulation of a complicated system such as a microgrid system.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.1-10
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• 2024

In the era of big data, the growth of e-commerce transactions brings forth both opportunities and risks, including the threat of data theft and fraud. To address these challenges, an automated real-time fraud detection system leveraging machine learning was developed. Four algorithms (Decision Tree, Naïve Bayes, XGBoost, and Neural Network) underwent comparison using a dataset from a clothing website that encompassed both legitimate and fraudulent transactions. The dataset exhibited an imbalance, with 9.3% representing fraud and 90.07% legitimate transactions. Performance evaluation metrics, including Recall, Precision, F1 Score, and AUC ROC, were employed to assess the effectiveness of each algorithm. XGBoost emerged as the top-performing model, achieving an impressive accuracy score of 95.85%. The proposed system proves to be a robust defense mechanism against fraudulent activities in e-commerce, thereby enhancing security and instilling trust in online transactions.

• Geomechanics and Engineering
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• v.14 no.5
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• pp.479-489
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• 2018

In this paper, a comparative study of the effects of soil modelling on the interaction between tunnelling in soft soil and adjacent piled structure is presented. Several three-dimensional finite element analyses are performed to study the deformation of pile caps and piles as well as tunnel internal forces during the construction of an underground tunnel. The soil is modelled by two material models: the simple, yet approximate Mohr Coulomb (MC) yield criterion; and the complex, but reasonable hardening soil (HS) model with hyperbolic relation between stress and strain. For the former model, two different values of the soil stiffness modulus ($E_{50}$ or $E_{ur}$) as well as two profiles of stiffness variation with depth (constant and linearly increasing) were used in attempts to improve its prediction. As these four attempts did not succeed, a hybrid representation in which the hardening soil is used for soil located at the highly-strained zones while the Mohr Coulomb model is utilized elsewhere was investigated. This hybrid representation, which is a compromise between rigorous and simple solutions yielded results that compare well with those of the hardening soil model. The compared results include pile cap movements, pile deformation, and tunnel internal forces. Problem symmetry is utilized and, therefore, one symmetric half of the soil medium, the tunnel boring machine, the face pressure, the final tunnel lining, the pile caps, and the piles are modelled in several construction phases.

• Wind and Structures
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• v.7 no.2
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• pp.89-106
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• 2004

The response of tall buildings to gust buffeting is usually evaluated assuming that the structural damping is of a viscous nature. In addition, when dampers are incorporated in the design to mitigate the response, their effect is allowed for increasing the building modal damping ratios by a quantity corresponding to the additional energy dissipation arising from the presence of the devices. Even though straightforward, this procedure has some degree of inaccuracy due to the existence of a memory effect, associated with the damping mechanism, which is neglected by a viscous model. In this paper a more realistic viscoelastic model is used to evaluate the response to gust buffeting of tall buildings provided with energy dissipation devices. Both cases of viscous and hysteretic inherent damping are considered, while for the dampers a generic viscoelastic behaviour is assumed. The Laguerre Polynomial Approximation is used to write the equations of motion and find the frequency response functions. The procedure is applied to a 25-story building to quantify the memory effects, and the inaccuracy arising when the latter is neglected.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.885-887
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• 2003

부양용해 기술은 티타늄등 용해 및 주조에 어려움이 있는 기능성 금속의 용해 시 소재의 오염이나 고가의 도가니 없이 용해할 수 있는 기술로써 기계 부품 경량화 및 고강도를 위한 기술 및 신수요 창출을 위한 기반을 제공할 수 있다. 본 논문은 실기용 부양용해 cold crucible의 설계 및 제작에 앞서 모사 cold crucible에 대한 기초 자료를 바탕으로 컴퓨터 시뮬레이션을 위한 3차원 전자기장 해석 model을 구축하여, 모사 모델과의 측정값과 전자장 해석결과를 비교하여, 실제 cold crucible 설계 제작시 다양한 형태로 활용될 수 있는 기본자료를 확보하는데 그 목적이 있다.

• Korean Journal of Radiology
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• v.21 no.7
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• pp.869-879
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• 2020

Objective: To evaluate the performance of a convolutional neural network (CNN) model that can automatically detect and classify rib fractures, and output structured reports from computed tomography (CT) images. Materials and Methods: This study included 1079 patients (median age, 55 years; men, 718) from three hospitals, between January 2011 and January 2019, who were divided into a monocentric training set (n = 876; median age, 55 years; men, 582), five multicenter/multiparameter validation sets (n = 173; median age, 59 years; men, 118) with different slice thicknesses and image pixels, and a normal control set (n = 30; median age, 53 years; men, 18). Three classifications (fresh, healing, and old fracture) combined with fracture location (corresponding CT layers) were detected automatically and delivered in a structured report. Precision, recall, and F1-score were selected as metrics to measure the optimum CNN model. Detection/diagnosis time, precision, and sensitivity were employed to compare the diagnostic efficiency of the structured report and that of experienced radiologists. Results: A total of 25054 annotations (fresh fracture, 10089; healing fracture, 10922; old fracture, 4043) were labelled for training (18584) and validation (6470). The detection efficiency was higher for fresh fractures and healing fractures than for old fractures (F1-scores, 0.849, 0.856, 0.770, respectively, p = 0.023 for each), and the robustness of the model was good in the five multicenter/multiparameter validation sets (all mean F1-scores > 0.8 except validation set 5 [512 x 512 pixels; F1-score = 0.757]). The precision of the five radiologists improved from 80.3% to 91.1%, and the sensitivity increased from 62.4% to 86.3% with artificial intelligence-assisted diagnosis. On average, the diagnosis time of the radiologists was reduced by 73.9 seconds. Conclusion: Our CNN model for automatic rib fracture detection could assist radiologists in improving diagnostic efficiency, reducing diagnosis time and radiologists' workload.

• Journal of the Korean Magnetic Resonance Society
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• v.8 no.2
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• pp.77-85
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• 2004

$^1$H-detected $^{15}$N NMR was employed to investigated the effect of mutation (Y14F) on the dynamic properties of catalytic residues in ${\Delta}^5$-3- ketosteroid isomerase (KSI) from Conamonas testosteroni. In particular, the backbone dynamics of the catalytic residues have been studied in free enzyme and its complex with a steroid ligand, 19-nortestosterone hemisuccinate, by $^{15}$N relaxation measurements. The relaxation data were analyzed using the model-free formalism to extract the model-free parameters (S$^2$, ${\tau}_e$, and R$_{ex}$). The results show that the mutation causes a significant decrease in the order parameter (S$^2$) for the catalytic residues of free Y14F KSI, presumably due to breakdown of the hydrogen bond network by mutation. In addition, the order parameters of Phe-14 and Asp-99 increased slightly upon ligand binding, indicating a slight restriction of the high-frequency (pico- to nanosecond) internal motions of the residues in the complexed Y14F KSI, while the order parameter of Tyr-55 decreased significantly upon ligand binding.

• Korean Journal of Clinical Pharmacy
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• v.27 no.4
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• pp.258-266
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• 2017

Objective: To develop a population pharmacokinetics (PK)/pharmacodynamics (PD) model for alcohol in healthy volunteers and to elucidate individual characteristics to affects alcohol's PK or PD including dissolved oxygen. Methods: Following multiple intakes of total 540 mL alcohol (19.42 v/v%) to healthy volunteer, blood alcohol concentration was measured using a Breathe alcohol analyser (Lion SD-400 $Alcolmeter^{(R)}$). A sequential population PK/PD modeling was performed using NONMEM (ver 7.3). Results: Eighteen healthy volunteer were included in the study. PK model of alcohol was well explained by one-compartment model with first-order absorption and Michaelis-Menten elimination kinetics. $K_a$, V/F, $V_{max}$, $K_m$ is $8.1hr^{-1}$, 73.7 L, 9.65 g/hr, 0.041 g/L, respectively. Covariate analysis revealed that gender significantly influenced $V_{max}$ (Male vs Female, 9.65 g/hr vs 7.38 g/hr). PD model of temporary systolic blood pressure decreasing effect of alcohol was explained by biophase model with inhibitory $E_{max}$ model. $K_{e0}$, $I_{max}$, $E_0$, $IC_{50}$ were $0.23hr^{-1}$, 44.9 mmHg, 138 mmHg, 0.693 g/L, respectively. Conclusion: Model evaluation results suggested that this PK/PD model was robust and has good precision.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.2
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• pp.220-227
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• 2002

This paper describes an integrated approach process to carry out pre-test, model correlation and updating analysis on the sub-frame of a vehicle. In this study, it was found that the modal test could be more efficient when the exciting point was selected on the area with high driving point residue. Such area could be located with the aid of finite element modal analysis. The model correlation was appraised in conjunction with the modal parameters between modal test and finite elements analysis. Also, the finite element model updating was obtained the good resultant using the iteration method based on sensitivity analysis results that carried out the variation of natural frequencies and MAC for the material properties. Finally, optimization of vehicle subframe was carried out the analysis of core location and physical properties by tow steps.