• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.3
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• pp.173-184
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• 2023

Presently, the general seismic fragility evaluation method for a bridge system composed of member elements with different nonlinear behaviors against strong earthquakes has been to evaluate at the element-level. This study aims to develop a system-level seismic fragility evaluation method that represents a structural system. Because the seismic behavior of bridges is generally divided into transverse and longitudinal directions, this study evaluated the system-level seismic fragility in both directions separately. The element-level seismic fragility evaluation in the longitudinal direction was performed for piers, bridge bearings, pounding, abutments, and unseating. Because pounding, abutment, and unseating do not affect the transverse directional damages, the element-level seismic fragility evaluation was limited to piers and bridge bearings. Seismic analysis using nonlinear models of various structural members was performed using the OpenSEES program. System-level seismic fragility was evaluated assuming that damage between element-levels was serially connected. Pier damage was identified to have a dominant effect on system-level seismic fragility than other element-level damages. In other words, the most vulnerable element-level seismic fragility has the most dominant effect on the system-level seismic fragility.

• Journal of Biomedical Engineering Research
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• v.19 no.5
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• pp.455-468
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• 1998

For the objective interpretation of cerebral metabolic patterns in epilepsy patients, we developed computer-aided classifier using artificial neural network. We studied interictal brain FDG PET scans of 257 epilepsy patients who were diagnosed as normal(n=64), L TLE (n=112), or R TLE (n=81) by visual interpretation. Automatically segmented volume of interest (VOI) was used to reliably extract the features representing patterns of cerebral metabolism. All images were spatially normalized to MNI standard PET template and smoothed with 16mm FWHM Gaussian kernel using SPM96. Mean count in cerebral region was normalized. The VOls for 34 cerebral regions were previously defined on the standard template and 17 different counts of mirrored regions to hemispheric midline were extracted from spatially normalized images. A three-layer feed-forward error back-propagation neural network classifier with 7 input nodes and 3 output nodes was used. The network was trained to interpret metabolic patterns and produce identical diagnoses with those of expert viewers. The performance of the neural network was optimized by testing with 5~40 nodes in hidden layer. Randomly selected 40 images from each group were used to train the network and the remainders were used to test the learned network. The optimized neural network gave a maximum agreement rate of 80.3% with expert viewers. It used 20 hidden nodes and was trained for 1508 epochs. Also, neural network gave agreement rates of 75~80% with 10 or 30 nodes in hidden layer. We conclude that artificial neural network performed as well as human experts and could be potentially useful as clinical decision support tool for the localization of epileptogenic zones.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.599-609
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• 2021

A novel grounding system, which is presented in IEC 60364, has been adopted since 2021. A safety evaluation for the human body on the grounding system is required due to the various characteristics of the touch voltage and current passing when the human body experiences an electric shock. The Korea Electrical Safety Corporation (KESCO) and Korea Electric Association (KEA) have been conducting a safety technical education on the grounding system. On the other hand, it is difficult to instruct the electrical safety manager because of a lack of safety evaluations for the test equipment on the grounding system. Therefore, this paper modeled and implemented a test device for a safety evaluation depending on the grounding system of IEC 60364. Namely, this paper presents the modeling of the test device for a safety evaluation using PSCAD/EMTDC S/W, which is composed of an AC grid section, s test device section on the grounding system, and a sub-device section. This paper implemented a test device for safety evaluation, which consisted of an AC grid section, TT grounding system section, TN-S grounding system section, and monitoring section. From the simulation and test results with the safety characteristics of the human body in the TT and TN-S grounding system, when the fault impedances are 0[Ω], 10[Ω], and 100[Ω], the currents passing through the human body in the TT grounding system are 104[mA], 87.4[mA], and 35.5[mA], respectively. The corresponding currents in the TN-S grounding system are 54.9[mA], 4.1[mA], and 0.4[mA], respectively. Based on the results, the protection performance for an electric shock to the human body in the TN-S system is better than the TT system. This can be improved when the existing grounding system is changed from the TT system to the TN-S system.