• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.670-673
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• 2010

무기저 손상 진단 기법은 능동센서를 이용하여 과거의 기저자료와 현재 상태에서 취득한 유도파의 정보를 비교하지 않고, 구조물의 현재 상태에서 취득한 신호만을 분석함으로써 구조물의 상태를 진단하는 기법이다. 온도 변화 및 하중 변화 등의 외부 환경의 변화에 민감한 유도파의 특성으로 인하여 기저자료를 이용하는 과거의 방법론은 현실적용성이 떨어질 우려가 있다. 본 무기저 손상 진단 기법은 외부 환경적 영향을 최소화함으로써 구조물의 상태를 효율적으로 진단할 수 있다. 최초, 본 연구진에서 제안하였던 무기저 기법은 두 쌍의 능동센서를 구조물에 양면 대칭으로 배치시켜 능동센서의 극성을 이용한 방법이었다. 하지만 실제 구조물의 양면에 완벽한 대칭성을 유지하며 능동센서를 배치시키는 것은 사실상 불가능하다. 이와 같은 한계점을 극복하기 위해 신개념의 듀얼 능동센서를 활용한 무기저 손상 진단 기법이 제안되었고, 수치해석 및 연구실 환경에서 제한적으로 그 실용성이 검증되었다. 본 논문에서는 무기저 손상 진단 기법의 실 구조물에의 적용성을 폐교량을 대상으로 검토하였다. 특히, 보강재를 포함하는 영역에서 본 기법을 적용함으로써 실제 구조물에 적용 가능성을 검증하였다.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.2
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• pp.132-143
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• 2008

The sloshing phenomena in a two-dimensional rectangular tank are investigated using a level set method based on finite volume method. The code validations are performed by comparing between the present results and previous numerical results, which gives a good agreement. We present the streamlines pattern, free surface shape, maximum free surface elevation and pressure fluctuation patterns in the tank under the pitch and surge motions with various frequencies. These two different motions cause the different flow structures in the tank. The time variations of surface elevation and pressure at the different locations in the tank strongly depend on the exciting frequency of tank moving.

• Genomics & Informatics
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• v.13 no.2
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• pp.60-67
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• 2015

The leading cause of cancer mortality globally amongst the women is due to human papillomavirus (HPV) infection. There is need to explore anti-cancerous drugs against this life-threatening infection. Traditionally, different natural compounds such as withaferin A, artemisinin, ursolic acid, ferulic acid, (-)-epigallocatechin-3-gallate, berberin, resveratrol, jaceosidin, curcumin, gingerol, indol-3-carbinol, and silymarin have been used as hopeful source of cancer treatment. These natural inhibitors have been shown to block HPV infection by different researchers. In the present study, we explored these natural compounds against E6 oncoprotein of high risk HPV18, which is known to inactivate tumor suppressor p53 protein. E6, a high throughput protein model of HPV18, was predicted to anticipate the interaction mechanism of E6 oncoprotein with these natural inhibitors using structure-based drug designing approach. Docking analysis showed the interaction of these natural inhibitors with p53 binding site of E6 protein residues 108-117 (CQKPLNPAEK) and help reinstatement of normal p53 functioning. Further, docking analysis besides helping in silico validations of natural compounds also helped elucidating the molecular mechanism of inhibition of HPV oncoproteins.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.1
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• pp.78-88
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• 2007

In the present study a detailed examination of various porous media models for predicting filtration efficiency and pressure drop of diesel particulate filter (DPF), such as sphere-in-cell and constricted tube models, are attempted. In order for demonstrating their validities of correct estimation on permeability, geometry of property configurations common in commercial cordierite DPFs are correlated to the porous media flow models, and validations of predicted filtration efficiencies due to the use of different unit collectors are made with experiments. The result shows that the porosity, pore size and permeability of cordierite DPF can be successfully correlated by Kuwabara flow field with correction factor of 0.6. The unit collector efficiency predicted by sphere-in-cell model agrees very well with measurements in accumulation mode, whereas that by constricted tube model with significant prediction error.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.757-767
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• 2010

This study employs the KED method using the correlations between probability rainfall and topographical factors as single auxiliary variable for assessing the effectiveness of external variables to improve the reliability in the estimation of spatial distribution of probability rainfall. As a result, the KED method gives similar results compared with deterministic spatial interpolation methods and kriging methods in the estimation of rainfall spatial distribution and mean areal rainfall, and as a result of the cross-validations of KED and kriging methods, the KED method using terrain elevation as auxiliary variable gives the best results, which are not significantly different in comparisons with other methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.793-798
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• 2012

In this paper, we explored the new method for extracting feature from the electroencephalography (EEG) signal based on linear regression technique with the orthonormal polynomial bases. At first, EEG signals from electrodes around motor cortex were selected and were filtered in both spatial and temporal filter using band pass filter for alpha and beta rhymic band which considered related to the synchronization and desynchonization of firing neurons population during motor imagery task. Signal from epoch length 1s were fitted into linear regression with Legendre polynomials bases and extract the linear regression weight as final features. We compared our feature to the state of art feature, power band feature in binary classification using support vector machine (SVM) with 5-fold cross validations for comparing the classification accuracy. The result showed that our proposed method improved the classification accuracy 5.44% in average of all subject over power band features in individual subject study and 84.5% of classification accuracy with forward feature selection improvement.

• Nuclear Engineering and Technology
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• v.49 no.3
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• pp.466-475
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• 2017

Coolant mixing under natural circulation flow regime constitutes a key parameter that may play a role in the course of an accidental transient in a nuclear pressurized water reactor. This issue has motivated some experimental investigations carried out within the OECD/NEA PKL projects. The aim was to assess the coolant mixing phenomenon in the reactor pressure vessel downcomer and the core lower plenum under several asymmetric steady and unsteady flow conditions, and to provide experimental data for code validations. Former studies addressed the mixing phenomenon using, on the one hand, one-dimensional computational approaches with cross flows that are not fully validated under transient conditions and, on the other hand, expensive computational fluid dynamic tools that are not always justified for large-scale macroscopic phenomena. In the current framework, an unsteady coolant mixing experiment carried out in the Rossendorf coolant mixing test facility is simulated using the three-dimensional porous media capabilities of the thermal-hydraulic system CATHARE code. The current study allows highlighting the current capabilities of these codes and their suitability for reproducing the main phenomena occurring during asymmetric transient natural circulation mixing conditions.

• Steel and Composite Structures
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• v.38 no.5
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• pp.599-615
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• 2021

The ultimate strength behaviour of sandwich composite beams with J-hooks and normal weight concrete (SCSSBJNs) are studied through two-point loading tests on ten full-scale SCSSBJNs. The test results show that the SCSSBJN with different parameters under two-point loads exhibits three types of failure modes, i.e., flexure, shear, and combined shear and flexure mode. SCSSBJN failed in different failure modes exhibits different load-deflection behaviours, and the main difference of these three types of behaviours exist in their last working stages. The influences of thickness of steel faceplate, shear span ratio, concrete core strength, and spacing of J-hooks on structural behaviours of SCSSBJN are discussed and analysed. These test results show that the failure mode of SCSSBJN was sensitive to the thickness of steel faceplate, shear span ratio, and concrete core strength. Theoretical models are developed to estimate the cracking, yielding, and ultimate bending resistance of SCSSBJN as well as its transverse cross-sectional shear resistance. The validations of predictions by these theoretical models proved that they are capable of estimating strengths of novel SCSSBJNs.

• Journal of Multimedia Information System
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• v.9 no.1
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• pp.21-32
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• 2022

Early-stage diagnosis of Alzheimer's Disease (AD) from Cognitively Normal (CN) patients is crucial because treatment at an early stage of AD can prevent further progress in the AD's severity in the future. Recently, computer-aided diagnosis using magnetic resonance image (MRI) has shown better performance in the classification of AD. However, these methods use a traditional machine learning algorithm that requires supervision and uses a combination of many complicated processes. In recent research, the performance of deep neural networks has outperformed the traditional machine learning algorithms. The ability to learn from the data and extract features on its own makes the neural networks less prone to errors. In this paper, a dense neural network is designed for binary classification of Alzheimer's disease. To create a classifier with better results, we studied result of different activation functions in the prediction. We obtained results from 5-folds validations with combinations of different activation functions and compared with each other, and the one with the best validation score is used to classify the test data. In this experiment, features used to train the model are obtained from the ADNI database after processing them using FreeSurfer software. For 5-folds validation, two groups: AD and CN are classified. The proposed DNN obtained better accuracy than the traditional machine learning algorithms and the compared previous studies for AD vs. CN, AD vs. Mild Cognitive Impairment (MCI), and MCI vs. CN classifications, respectively. This neural network is robust and better.

• Structural Engineering and Mechanics
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• v.83 no.2
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• pp.245-257
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• 2022

As the main lateral load resisting system in high-rise reinforced concrete structures, the mechanical performance of shear wall has a significant impact on the structure, especially for high-rise buildings. Steel corrosion has been recognized as an important factor affecting the mechanical performance and durability of the reinforced concrete structures. To investigate the effect on the seismic behaviour of corroded reinforced concrete shear wall induced by corrosion, analytical investigations and simulations were done to observe the effect of corrosion on the ultimate seismic capacity and drift capacity of shear walls. To ensure the accuracy of the simulation software, several validations were made using both non-corroded and corroded reinforced concrete shear walls based on some test results in previous literature. Thereafter, a parametric study, including 200 FE models, was done to study the influence of some critical parameters on corroded structural shear walls with boundary element. These parameters include corrosion levels, axial force ratio, aspect ratio, and concrete compressive strength. The results obtained would then be used to propose equations to predict the seismic resistance and drift capacity of shear walls with various corrosion levels.