• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.5
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• pp.483-488
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• 2016

Plug-In Digital Framework is a system response analysis tool that is employed when system components are composed of black-box modules. Generally, the dynamic characteristics of joints between the system components significantly affect system responses, and they lead to displacement- and frequency-dependent stiffness and loss factor. Thus, the sensitivity of each joint parameters should be estimated from a global perspective. In this study, we introduce a global sensitivity analysis procedure under the Plug-In Digital Framework. To efficiently calculate the system responses, we introduce the frequency response function (FRF)-based substructuring method. Using the random balance designs (RBD), we generate the system responses and estimate the global first-order sensitivities for each joint stiffness. We apply the proposed global sensitivity analysis method to an interior noise problem of a passenger car, and we evaluate the efficiency of the global sensitivity analysis method.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.7
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• pp.287-294
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• 2001

The identification of connection stiffnesses of bolted structures is presented using FRT-based substructural sensitivity analysis. The substructural design sensitivity formula is derived and plugged into the optimization module of MATLAB to identify connection stiffnesses of an air-conditioner compressor or passenger Car. The air-conditioner composed of a compressor and a bracket, is analysed by using the FRT-based substructural(FBS) method to obtain FTRs an FE model is generated for the bracket, and the impact hammer test is performed for the compressor, Obtained FRTs are combined to calculate the reaction force at the connection point and the system response. By minimizing the difference between a target FRT and calculated one the connection element properties of the air-conditioner syste are identified It is shown that the proposed identification method is effective for a real problem.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.813-816
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• 2018

X-ray 진단에서 그리드 하드웨어의 사용은 산란선에 의한 영상의 왜곡을 보정할 수 있는 장점이 있는 반면, 반복되는 라인 형태의 그리드 아티팩트를 발생시키는 부작용을 수반한다. 본 논문에서는 이러한 그리드 라인을 제거하는 방법론으로서 이산코사인변환(DCT: discrete cosine transform)을 사용 하는 기법을 제안한다. X-ray 영상에서 그리드 라인의 특성은 피사체의 형태와 영상의 영역에 따라 서로 다른 특성을 갖는다. 이에 본 연구에서는 동적으로 재구성되는 분할 구조를 기반으로 DCT 변환을 적용하고 개별 영역별로 필터전달함수를 최적화하는 방법을 채택하였다. 추출된 주파수 영역 데이터에 대하여 그리드 라인의 대역을 검출하는 알고리즘을 제안하였으며, 필터전달함수로 Kaiser윈도우와 Butterworth 필터를 조합한 형태의 밴드스톱필러(BSF: band stop filter)를 구현하였다. 또한 블로킹 현상을 개선하기 위하여 다중 영상으로부터 경계선 부분의 픽셀값을 결정하는 방법론을 제안하였다. 제안된 이론에 대하여 실제 영상을 사용한 실험결과로부터 그 타당성을 평가하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.786-792
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• 2001

In this paper, the identification of connections for a vibration system has been presented using FRF-based substructural sensitivity analysis. The substructural design sensitivity formula is derived and plugged into a commercial optimization program, MATLAB, to identify connection stiffness of an air-conditioner system of passenger car. The air-conditioner system, composed of a compressor and a bracket is analyzed by using FRF-based substructural(FBS) method. To obtain the FRFs, FE model is built for the bracket, and the impact hammer test is performed for the compressor. Obtained FRFs are combined to calculate the reaction force at the connection point and the system response. Connection element properties are determined by minimizing the difference between a target FRF and calculated one. It is shown that the proposed identification method is effective even for a real problem.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.5 s.45
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• pp.21-28
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• 2005

This paper proposes a shaking table test considering the dynamic soil strcuture interaction (SSI) by using the accelerations measured from superstructure and shaking table. The proposed method based on the substructure method is that only superstructure is used as an experimental model and dynamic soil stiffness is reflected on the controller of shaking table for soil model. At the moment, an experimental superstructure is excited by a shaking table with the motion required to emulate the dynamic behavior of total SSI system. First, the validity of the proposed method is verified by the verification model of numerical simulation, which is derived from the equation of motion of SSI system under consideration. Also, the applicability of the proposed method to shaking table test is numerically verified from the simulation model incorporating the transfer function of shaking table.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1117-1128
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• 2016

In genetic association studies with high-dimensional genomic data, regularization procedures based on penalized likelihood are often applied to identify genes or genetic regions associated with diseases or traits. A network-based regularization procedure can utilize biological network information (such as genetic pathways and signaling pathways in genetic association studies) with an outstanding selection performance over other regularization procedures such as lasso and elastic-net. However, network-based regularization has a limitation because cannot be applied to high-dimension genomic data with a group structure. In this article, we propose to combine data dimension reduction techniques such as principal component analysis and a partial least square into network-based regularization for the analysis of high-dimensional genomic data with a group structure. The selection performance of the proposed method was evaluated by extensive simulation studies. The proposed method was also applied to real DNA methylation data generated from Illumina Innium HumanMethylation27K BeadChip, where methylation beta values of around 20,000 CpG sites over 12,770 genes were compared between 123 ovarian cancer patients and 152 healthy controls. This analysis was also able to indicate a few cancer-related genes.