• Investigative Magnetic Resonance Imaging
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• v.13 no.2
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• pp.137-145
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• 2009

Purpose : To compare 12 and 32-element surface coil arrays for highly accelerated coronary magnetic resonance angiography (MRA) using parallel imaging. Materials and Methods : Steady state free precession coronary MRA was performed in 5 healthy volunteers at 1.5 T whole body MR scanner using both 12 and 32-element surface coil arrays. Left anterior descending and right coronary artery data sets were acquired for each volunteer. Data sets were sub-sampled for parallel imaging using reduction factors from 1 to 6. Mean geometry factor (g-factor), maximum g-factor, and artifact level were calculated for each of the two coil arrays. Results : Over all reduction factors, the mean and maximum g-factors and artifact level were significantly reduced using the 32-element array compared to the 12element array (P << 0.1). The mean g-factor was sensitive to the imaging orientations of coronary arteries while the maximum g-factor and artifact level were independent of orientation. Conclusion : The 32-element surface coil array significantly improves artifact and noise suppression for highly accelerated coronary MRA using parallel imaging. The increased acceleration factors made feasible with the 32-element array offer the potential to enhance spatial resolution or increase volumetric coverage for 3D coronary MRA.

• Journal of the Earthquake Engineering Society of Korea
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• v.14 no.1
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• pp.25-34
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• 2010

A method is presented for evaluating the seismic failure probability of bridge structures which show a nonlinear hysteretic dynamic behavior. Bridge structures are modeled as a bilinear dynamic system with a single degree of freedom. We regarded that the failure of bridges will occur when the displacement response of a deck level firstly crosses the predefined limit state during a duration of strong motion. For the estimation of the first-crossing probability of a nonlinear structural system excited by earthquake motion, we computed the average frequency of crossings of the limit state. We presented the non-Gaussian closure method for the approximation of the joint probability density function of response and its derivative, which is required for the estimation of the average frequency of crossings. The failure probabilities are estimated according to the various artificial earthquake acceleration sets representing specific seismic characteristics. For the verification of the accuracy and efficiency of presented method, we compared the estimated failure probabilities with the results evaluated from previous methods and the exact values estimated with the crude Monte-Carlo simulation method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.111-116
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• 2018

This research examines the drop impact of an external cooling unit package of an air conditioner system. The packaging is composed of a shock-absorbing material, which protects the package contents by absorbing the impact energy and other parts for fixture. Accurate quantification of the impact acceleration experienced by the package contents is necessary to design an effective packaging with minimal volume and sufficient shock absorbing capacity. Explicit time integration was used for the drop impact analyses. A finite element model of the package was constructed, material testing and material model selection were carried out, and sensors for data acquisition were modeled to obtain accurate simulation results. The results were compared with real physical test data. Due to imprecise modeling of the damping, the acceleration and strain values predicted by the simulation were larger than those from physical test. However, the trend of the history data and the peak deceleration value in the direction of impact showed good agreements. Thus, the analysis model and scheme are suitable for the design of an air conditioner cooling unit package.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.82-89
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• 2012

This paper presents the intelligent tracking algorithm for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. Fuzzy c-mean clustering and predicted impact point are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by fuzzy c-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. The filtering process in a series of the algorithm which estimates the target value recognize the nonlinear maneuvering target as linear one because the filter recognize only remained noise by extracting acceleration from the positional error. After filtering process, we get the estimates target by compensating extracted acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. To maximize the effectiveness of the proposed system, we construct the multiple model structure. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

• Journal of Korean Society of Steel Construction
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• v.20 no.1
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• pp.151-163
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• 2008

A formulation of three-dimensional model of articulated train-b ridge dynamic interaction has been made for the Korean eXpress Train (KTX). Semi-periodic profiles of rail irregularities consisting of elevation, alignment, cross and gauge irregularities have also been proposed using FRA maximum tolerable rail deviations. The effects of rail joints and sleeper step were also included. The resulting system matrices of train and bridge are very spare, and thus, are stored in one-dimensional arrays, yielding a time-efficient solution. A numerical algorithm for computing bridge-train response including an iterative scheme is also formulated. A program simulating train-bridge interaction and solving this problem using the new algorithm is implemented as new modules for the f inite element analysis software named XFINAS. Computed results using the new program are then checked by that of the validated 2-D bridge-train interaction model. This new 3D analysis provides more detailed train responses such as swaying, bouncing, rolling, pitching and yawing accelerations, which are useful inevaluating passenger riding comfort. Train operation safety and derailment could also be directly investigated by relative wheel displacements computed from this program.

• Journal of Korean Society of Steel Construction
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• v.17 no.1 s.74
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• pp.1-11
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• 2005

A bi-level damage detection algorithm that utilizes the dynamic responses of the structure as input and neural network (NN) as pattern classifier is presented. Signal anomaly index (SAI) is proposed to express the amount of changes in the shape of frequency response functions (FRF) or strain frequency response function (SFRF). SAI is calculated using the acceleration and dynamic strain responses acquired from intact and damaged states of the structure. In a bi-level damage identification algorithm, the presence of damage is first identified from the magnitude of the SAI value, then the location of the damage is identified using the pattern recognition capability of NN. The proposed algorithm is applied to an experimental model bridge to demonstrate the feasibility of the algorithm. Numerically simulated signals are used for training the NN, and experimentally-acquired signals are used to test the NN. The results of this example application suggest that the SAI-based pattern recognition approach may be applied to the structural health monitoring system for a real bridge.

• Polymer(Korea)
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• v.36 no.6
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• pp.712-720
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• 2012

Thermal degradation for glass fiber-reinforced polyamide 66 composite (PA 66) with respect of thermal exposure time has been investigated using optical microscopy, scanning electron microscopy and Fourier transform infrared spectroscopy. As the thermal exposure time was prolonged, a slight increase in tensile strength for only initial stage and afterward, a proportional decrease of tensile strength was observed. These results can be explained by the increase of crystallinity, followed by the increase of crosslinking density, chain scission and the decrease in chain mobility, due to thermal oxidation with the exposure time. Fourier transform infrared spectroscopy results showed the increase of ketone peak and silica peak on the surface of thermally exposed PA 66. In addition, the thermal decomposition kinetics of PA 66 was analyzed using thermogravimetric analysis at three different heating rates. The relationship between activation energy and lifetime-prediction of PA 66 was investigated by several methodologies, such as statistical tool, UL 746B, Ozawa and Kissinger. The activation energy determined by thermogravimetric analysis had a relatively large value compared with that from the accelerated test. This may result in over-estimating the lifetime of PA 66. In this study, a master curve of exponential fitting has been developed to extrapolate the activation energy at various service temperatures.

• Journal of the Earthquake Engineering Society of Korea
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• v.16 no.3
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• pp.35-42
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• 2012

We propose a probabilistic method to evaluate the uniform hazard spectra (UHS) of the soil of nuclear power plant(NPP) sites corresponding to that of a bedrock site. To do this, amplification factors on the surface of soil sites were estimated through site response analysis while considering the uncertainty in the earthquake ground motion and soil deposit characteristics. The amplification factors were calculated by regression analysis with spectral acceleration because these two factors are mostly correlated. The proposed method was applied to the evaluation of UHS for the KNGR (Korean Next Generation Reactor) and the APR1400 (Advanced Power Reactor 1400) nuclear power plant sites of B1, B4, C1 and C3. The most dominant frequency range with respect to the annual frequency of earthquakes was evaluated from the UHS analysis. It can be expected that the proposed method will improve the results of integrated risk assessments of NPPs rationally. We expect also that the proposed method will be applied to the evaluation of the UHS and of many other kinds of soil sites.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1166-1174
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• 2004

In this paper, a design of RISC-based transmission wrapper processor for TCP/IP protocol stack is described. The processor consists of input and output buffer memory with dual bank structure, 32-bit RISC microprocessor core, DMA unit with on-the-fly checksum capability, and memory module. To handle the various modes of TCP/IP protocol, hardware-software codesign approach based on RISC processor is used rather than the conventional state machine design. To eliminate large delay time due to sequential executions of data transfer and checksum operation, DMA module which can execute the checksum operation along with data transfer operation is adopted. The designed processor exclusive of variable-size input/output buffer consists of about 23,700 gates and its maximum operating frequency is about 167MHz under 0.35${\mu}m$ CMOS technology.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.341-350
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• 2022

In this paper, we propose a deep learning based on-device augmented reality (AR) system in which multiple input images are used to implement the correct occlusion in a real environment. The proposed system is composed of three technical steps; camera pose estimation, depth estimation, and object augmentation. Each step employs various mobile frameworks to optimize the processing on the on-device environment. Firstly, in the camera pose estimation stage, the massive computation involved in feature extraction is parallelized using OpenCL which is the GPU parallelization framework. Next, in depth estimation, monocular and multiple image-based depth image inference is accelerated using the mobile deep learning framework, i.e. TensorFlow Lite. Finally, object augmentation and occlusion handling are performed on the OpenGL ES mobile graphics framework. The proposed augmented reality system is implemented as an application in the Android environment. We evaluate the performance of the proposed system in terms of augmentation accuracy and the processing time in the mobile as well as PC environments.