• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3C
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• pp.187-196
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• 2008

An earthquake of magnitude 5.0 occurred at Ssang-gye-sa, a Buddhist temple in Jirisan, located near the southern border of the Korean peninsula on 4 July 1936. It resulted in severe damage of several buildings and structures in Ssang-gye-sa. Particularly, the top component of a five-story stone pagoda in the temple was tipped over and fell down during the earthquake. This earthquake damage case would be usefully applied to estimating the intensity of ground motion in the Korean peninsula, a moderate seismicity region, where strong motion has never been recorded with the exception of historic seismic events. In order to estimate the local site effects and the corresponding ground motion at Ssang-gye-sa site, intensive site investigations including borehole drilling and in-situ seismic tests such as crosshole and SASW tests were performed in the temple area. Based on the site characteristics, site-specific seismic response analyses using various input motions were conducted for a representative Ssang-gye-sa site by means of both one-dimensional equivalent-linear and nonlinear methods with six input rock outcrop acceleration levels ranging from 0.044g to 0.220g. The resultant site-specific seismic responses indicated the amplified ground motions in the short-period range near the site period of Ssang-gye-sa. Furthermore, the intensity on rock outcrop of the 1936 Jirisan earthquake was estimated by making a comparison between the site responses analysis results in this study and the full-scaled seismic test of pagoda model in the prior study.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.1-8
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• 2023

If there is a defect in the wheel bearing, which is a major part of the car, it can cause problems such as traffic accidents. In order to solve this problem, big data is collected and monitoring is conducted to provide early information on the presence or absence of wheel bearing failure and type of failure through predictive diagnosis and management technology. System development is needed. In this paper, to implement such an intelligent wheel hub bearing maintenance system, we develop an embedded system equipped with sensors for monitoring reliability and soundness and algorithms for predictive diagnosis. The algorithm used acquires vibration signals from acceleration sensors installed in wheel bearings and can predict and diagnose failures through big data technology through signal processing techniques, fault frequency analysis, and health characteristic parameter definition. The implemented algorithm applies a stable signal extraction algorithm that can minimize vibration frequency components and maximize vibration components occurring in wheel bearings. In noise removal using a filter, an artificial intelligence-based soundness extraction algorithm is applied, and FFT is applied. The fault frequency was analyzed and the fault was diagnosed by extracting fault characteristic factors. The performance target of this system was over 12,800 ODR, and the target was met through test results.

• The Journal of the Acoustical Society of Korea
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• v.35 no.3
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• pp.192-201
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• 2016

Condition Monitoring System (CMS) has been used to detect unexpected faults of wind turbine caused by the abrupt change of circumstances or the aging of its mechanical part. In fact, it is a very hard work to do regular inspection for its maintenance because wind turbine is located on the mountaintop or sea. The purpose of this study is to find out distribution patterns of vibration signals measured from the main mechanical parts of wind turbine according to its operation condition. To this end, acceleration signals of main bearing, gearbox, generator, wind speed, rotational speed, etc were measured through the long period more than 2 years and trend analyses on each signal were conducted as a function of the rotational speed. In addition, correlation analysis among the signals was done to grasp the relation between mechanical parts. As a result, the vibrations were dependent on the rotational speed of main shaft and whether power was generated or not, and their distributions at a specific rotational speed could be approximated to Weibull distribution. It was also investigated that the vibration at main bearing was correlated with vibration at gearbox each other, whereas vibration at generator should be dealt with individually because of generating mechanism. These results can be used for improving performance of CMS that early detects the mechanical abnormality of wind turbine.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.1
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• pp.141-152
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• 2015

The objective of this study is to estimate shear wave velocity of rockfill materials by making practical use of the micro-earthquake records which are ordinarily obtained at a domestic rockfill dam and to verify its applicability. Micro-earthquake records were obtained at the site of Heongseong dam and Soyanggang dam, which are the existing multi-purpose dams in Korea. In the previous study, the fundamental periods of each dam were already evaluated by analyzing the response spectrum of the observed records. In this study, numerical analyses varying shear moduli of rockfill zone were carried out using the acceleration histories measured at the abutment as input ground motions. From comparison between the fundamental periods calculated by numerical analyses and measured records, the shear wave velocities with depth were estimated. It is found that the effect of different earthquake events on shear wave velocity estimation for the target dam materials is negligible and the shear wave velocity can be consistently evaluated. Furthermore, comparing the shear wave velocity with the previous researchers' empirical relationships and field test results, applicability of suggested method is verified. Therefore, in case that it is impossible to conduct field tests and estimation is preliminary, the suggested method can be practically used.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.12
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• pp.1106-1113
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• 2013

For patients who have senile mental disorder such as dementia, quantity of excercise and amount of sunlight are important clue for dose and the treatment. Therefore, monitoring health information of daily life is necessary for patients' safety and healthy life. Portable & wearable sensor device and server configuration monitoring data are needed to provide these services for patients. Watch-type device(smart watch) which patients wear and server system are developed in this paper. Smart watch developed includes GPS, accelerometer and illumination sensor, and can obtain real time health information by measuring the position of patients, quantity of exercise and amount of sunlight. Server system includes the sensor data analysis algorithm and web server that doctor and protector can monitor through sensor data acquired from smart watch. The proposed data analysis algorithm acquires quantity of exercise information and detects step count in patients' motion acquired from acceleration sensor and to verify this, the three cases with fast pace, slow pace, and walking pace show 96% of the experimental result. If developed u-Healthcare System for dementia patients is applied, more high-quality medical service can be provided to patients.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.1
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• pp.71-80
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• 2013

According to design specifications for structural safety, a bridge in initial design step has been modelled to have larger self-weight, external loads and less stiffness than those of real one in service. Thereby measured buffeting responses of existing bridge show different distributions from those of the design model in design step. In order to obtain accurate buffeting responses of the in-site bridge, the analysis model needs to be modified by considering the measured natural frequencies. Until now, a Manual Tuning Method (MTM) has been widely used to obtain the Measurement-based Model(MBM) that has equal natural frequencies to the real bridge. However, since state variables can be selected randomly and its result is not apt to converge exact rapidly, MTM takes a lot of effort and elapsed time. This study presents Buffeting Response Correction Method (BRCM) to obtain more exact buffeting response above MTM. The BRCM is based on the idea the commonly used frequency domain buffeting analysis does not need all structural properties except mode shapes, natural frequencies and damping ratio. BRCM is used to improve each modal buffeting responses of the design model by substituting measured natural frequencies. The measured natural frequencies are determined from acceleration time-history in ordinary vibration of the real bridge. As illustrated examples, simple beam is applied to compare the results of BRCM with those of a assumed MBM by numerical simulation. Buffeting responses of BRCM are shown to be appropriate for those of in-site bridge and the difference is less than 3% between the responses of BRCM and MTM. Therefore, BRCM can calculate easily and conveniently the buffeting responses and improve effectively maintenance and management of in-site bridge than MTM.

• Korean Journal of Applied Biomechanics
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• v.18 no.1
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• pp.137-146
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• 2008

The purpose of this study is to examine the causes of errors from EGR posture on the balance beam, which is bending flick-flack salto backward stretched national team players through kinematic analysis, and present training methods for them so as to provide scientifically useful information to coaches and athlete. Findings from this study are summarized below. The most important factors that affect the errors in boyd center position and speed change were the speed change of left and right body centers and the horizontal and vertical speed changes. The left and right acceleration changes were greater in failed posture than in successful posture. The horizontal and vertical accelerations in E3 and E5 were the key factors that affected the backward somersault and landing. The angular speed changes which varied between success and failure were notable in head and shoulder joints. In individual results. The section when the angular speeds of head and shoulder joint must be the greatest was E4. In this section, when the body is extending instantly in a bent posture, increasing the angular speeds of head, shoulder and hip joints can improve the duration of staying in the air and the rotation radius of a somersault.

• Investigative Magnetic Resonance Imaging
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• v.21 no.2
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• pp.71-81
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• 2017

Purpose: To compare three, motion-resistant, T1-weighted MR sequences on the hepatobiliary phase for gadoxetic acid-enhanced MR imaging of the liver. Materials and Methods: In this retrospective study, 79 patients underwent gadoxetic acid-enhanced, 3T liver MR imaging. Fifty-nine were examined using a standard protocol, and 20 were examined using a motion-resistant protocol. During the hepatocyte-specific phase, three MR sequences were acquired: 1) gradient recalled echo (GRE) with controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA); 2) radial GRE with the interleaved angle-bisection scheme (ILAB); and 3) radial GRE with golden-angle scheme (GA). Two readers independently assessed images with motion artifacts, streaking artifacts, liver-edge sharpness, hepatic vessel clarity, lesion conspicuity, and overall image quality, using a 5-point scale. The images were assessed by measurement of liver signal-to-noise ratio (SNR), and tumor-to-liver contrast-to-noise ratio (CNR). The results were compared, using repeated post-hoc, paired t-tests with Bonferroni correction and the Wilcoxon signed rank test with Bonferroni correction. Results: In the qualitative analysis of cooperative patients, the results for CAIPIRINHA had significantly higher ratings for streak artifacts, liver-edge sharpness, hepatic vessel clarity, and overall image quality as compared to, radial GRE, (P < 0.016). In the imaging of uncooperative patients, higher scores were recorded for ILAB and GA with respect to all of the qualitative assessments, except for streak artifact, compared with CAIPIRINHA (P < 0.016). However, no significant differences were found between ILAB and GA. For quantitative analysis in uncooperative patients, the mean liver SNR and lesion-to-liver CNR with radial GRE were significantly higher than those of CAIPIRINHA (P < 0.016). Conclusion: In uncooperative patients, the use of the radial GRE sequence can improve the image quality compared to GRE imaging with CAIPIRINHA, despite the data acquisition methods used. The GRE imaging with CAIPIRINHA is applicable for patients without breath-holding difficulties.

• Journal of Korean Society of Steel Construction
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• v.22 no.6
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• pp.553-561
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• 2010

The purpose of this paper is to analytically find the approximate supplement damping ratio of the viscous damper installed in self-centering (SC) single-degree-of-freedom (SDOF) systems with maximum displacements that are similar to those of elasto-plastic (EP) SDOF systems. The behavior of an SC SDOF system under harmonic cyclic loading was first described. Then an analytical model that can capture the behavior of the viscously damped SC SDOF system was introduced. Analysis parameters that characterize the hysteresis of the EP and SC SDOF systems were chosen, and nonlinear time-history analyses were performed using 20 historical accelerograms. Most of the SC SDOF systems with viscous dampers with approximately 10-15% damping ratios presented mean maximum displacement values that were similar to those of the EP SDOF systems. To investigate in detail the seismic performance of both systems, three EP SDOF systems and six corresponding SC SDOF systems were selected. The analyses showed that all the SC SDOF systems eliminated the residual displacements after the end of their shaking, and that the SC SDOF systems with 15% damping ratios performed better than the EP SDOF systems in terms of maximum displacement and acceleration response.

• Journal of KIISE:Software and Applications
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• v.34 no.12
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• pp.1045-1055
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• 2007

Latent topic models are statistical models which automatically captures salient patterns or correlation among features underlying a data collection in a probabilistic way. They are gaining an increased popularity as an effective tool in the application of automatic semantic feature extraction from text corpus, multimedia data analysis including image data, and bioinformatics. Among the important issues for the effectiveness in the application of latent topic models to the massive data set is the efficient learning of the model. The paper proposes an accelerated learning technique for PLSA model, one of the popular latent topic models, by an incremental EM algorithm instead of conventional EM algorithm. The incremental EM algorithm can be characterized by the employment of a series of partial E-steps that are performed on the corresponding subsets of the entire data collection, unlike in the conventional EM algorithm where one batch E-step is done for the whole data set. By the replacement of a single batch E-M step with a series of partial E-steps and M-steps, the inference result for the previous data subset can be directly reflected to the next inference process, which can enhance the learning speed for the entire data set. The algorithm is advantageous also in that it is guaranteed to converge to a local maximum solution and can be easily implemented just with slight modification of the existing algorithm based on the conventional EM. We present the basic application of the incremental EM algorithm to the learning of PLSA and empirically evaluate the acceleration performance with several possible data partitioning methods for the practical application. The experimental results on a real-world news data set show that the proposed approach can accomplish a meaningful enhancement of the convergence rate in the learning of latent topic model. Additionally, we present an interesting result which supports a possible synergistic effect of the combination of incremental EM algorithm with parallel computing.