• The Journal of the Acoustical Society of Korea
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• v.21 no.3
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• pp.323-329
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• 2002

This paper proposes a frame reliability weighting method to compensate for a time-selective noise that occurs at random positions of speech signal contaminating certain parts of the speech signal. Speech frames have different degrees of reliability and the reliability is proportional to SNR (signal-to noise ratio). While it is feasible to estimate frame Sl? by using the noise information from non-speech interval under a stationary noisy situation, it is difficult to obtain noise spectrum for a time-selective noise. Therefore, we used statistical models of clean speech for the estimation of the frame reliability. The proposed MFR (model-based frame reliability) approximates frame SNR values using filterbank energy vectors that are obtained by the inverse transformation of input MFCC (mal-frequency cepstral coefficient) vectors and mean vectors of a reference model. Experiments on various burnt noises revealed that the proposed method could represent the frame reliability effectively. We could improve the recognition performance by using MFR values as weighting factors at the likelihood calculation step.

• Earthquakes and Structures
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• v.25 no.3
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• pp.177-186
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• 2023

Reinforced concrete frames with a masonry infill panel is a structural typology frequently used worldwide. In seismic cases, the interaction between the masonry infill and the RC frames constitutes one of the most complex subjects in earthquake engineering. In this work, an enhancement of an existing numerical model is proposed to improve the estimation of lateral strength and stiffness of masonry-infilled frame structures and predict their probable failure modes. The proposed improvement is based on attributing corrective coefficients to the shear strength of each diagonal shear spring of the macro element, which simulates the masonry infill. The improved numerical model is validated by comparing the results with those of the original numerical model and with experimental results available in the literature. The enhanced macro element model can be used as a powerful, accessible tool for assessing the capacity and stiffness of masonry-infilled frame structures and predicting their probable failure modes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5459-5473
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• 2017

Recently, a tracking algorithm called the spatial-temporal context model has been proposed to locate a target by using the contextual information around the target. This model has achieved excellent results when the target undergoes slight occlusion and appearance changes. However, the target location in the current frame is based on the location in the previous frame, which will lead to failure in the presence of fast motion because of the lack of a prediction mechanism. In addition, the spatial context model is updated frame by frame, which will undoubtedly result in drift once the target is occluded continuously. This paper proposes two improvements to solve the above two problems: First, four possible positions of the target in the current frame are predicted based on the displacement between the previous two frames, and then, we calculate four confidence maps at these four positions; the target position is located at the position that corresponds to the maximum value. Second, we propose a target reliability criterion and design an adaptive threshold to regulate the updating speed of the model. Specifically, we stop updating the model when the reliability is lower than the threshold. Experimental results show that the proposed algorithm achieves better tracking results than traditional STC and other algorithms.

• Steel and Composite Structures
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• v.50 no.3
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• pp.337-345
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• 2024

This research proposed a particle swarm optimization (PSO) based seismic retrofit design of moment frame structures using a steel frame assembly. Two full scale specimens of the steel frame assembly with different corner details were attached to one-story RC frames for seismic retrofit, and the lateral load resisting capacities of the retrofitted frames subjected to cyclic loads were compared with those of a bare RC frame. The open source software framework Opensees was used to develop an analytical model for validating the experimental results. The developed analytical model and the optimization scheme were applied to a case study structure for economic seismic retrofit design, and its seismic performance was assessed before and after the retrofit. The results show that the developed steel frame assembly was effective in increasing seismic load resisting capability of the structure, and the PSO algorithm could be applied as convenient optimization tool for seismic retrofit design of structures.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2104-2107
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• 2003

In this paper, we propose the method Model based Non-Rigid Moving Object Tracking. Motion based method becomes difficult to predict precisely when motion gets larger, so that we can solve such difficultly with regarding the moving object as a model. In the model based method, it should be concerned about setting initial model and updating its model in each frame. We used SNAKE in a way to set the initial model, and also proposed a modified SNAKE to handle the previous SNAKE problems. Moreover, with the elliptical setting, we made the initializing process automatically which is highly subject to change in measuring the performance of SNAKE. We used the Hausdorff distance to identify models in each frame. Through our experiments, our Proposed algorithm does effective work in Non-Rigid Moving Object Tracking.

• Geomechanics and Engineering
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• v.32 no.1
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• pp.69-84
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• 2023

This paper proposes a novel frame element on Winkler-Pasternak foundation for analysis of a non-ductile reinforced concrete (RC) member resting on foundation. These structural members represent flexural-shear critical members, which are commonly found in existing buildings designed and constructed with the old seismic design standards (inadequately detailed transverse reinforcement). As a result, these structures always experience shear failure or flexure-shear failure under seismic loading. To predict the characteristics of these non-ductile structures, efficient numerical models are required. Therefore, the novel frame element on Winkler-Pasternak foundation with inclusion of the shear-flexure interaction effect is developed in this study. The proposed model is derived within the framework of a displacement-based formulation and fiber section model under Timoshenko beam theory. Uniaxial nonlinear material constitutive models are employed to represent the characteristics of non-ductile RC frame and the underlying foundation. The shear-flexure interaction effect is expressed within the shear constitutive model based on the UCSD shear-strength model as demonstrated in this paper. From several features of the presented model, the proposed model is simple but able to capture several salient characteristics of the non-ductile RC frame resting on foundation, such as failure behavior, soil-structure interaction, and shear-flexure interaction. This confirms through two numerical simulations.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.4
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• pp.47-53
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• 2011

Firstly, FEM model for the body frame of a fuel cell vehicle was built up and design optimization results based on different schemes were exhibited. One scheme was to minimize weight while maintaining the normal mode frequencies and the other was to increase the frequencies without weight change. Next, for a rear frame model, shape parameter study on collapse characteristics such as peak resistance load and absorbed energy was carried out. Also, the stiffness of frame mounting brackets was predicted using inertance calculation and the durability of those mounting brackets for vehicle system loads was evaluated. Finally, for a representative mounting model, the influence on durability due to thickness change was analyzed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.503-510
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• 2004

One of the methods improving the seismic behavior of a structure is the frame with reduced beam section (RBS) which cuts a segment of flanges of the beam near the beam-to-column connection so that the section with reduced flanges has smaller flexural strength than the beam end. It is difficult to analyze the RBS frame because RBS portion has circular-cut type flange. And inelastic response of the steel frame with the RBS is very sensitive to the RBS model. In this paper, the analytical models of RBS portion are investigated and the results of the inelastic analysis for RBS analytical models are compared and then the analytical model for RBS is determined based on the results of inelastic analysis. Inelastic behavior of the RBS frame and its dynamic characteristics are investigated for selected analytical model of RBS.

• The Journal of the Acoustical Society of Korea
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• v.31 no.2
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• pp.93-99
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• 2012

For speech coding, a vocal tract is modeled using Linear Predictive Coding (LPC) coefficients. The LPC coefficients are typically transformed to Line Spectral Frequency (LSF) parameters which are advantageous for linear interpolation and quantization. If multidimensional LSF data are quantized directly using Vector-Quantization (VQ), high rate-distortion performance can be obtained by fully utilizing intra-frame correlation. In practice, since this direct VQ system cannot be used due to high computational complexity and memory requirement, Split VQ (SVQ) is used where a multidimensional vector is split into multilple sub-vectors for quantization. The LSF parameters also have high inter-frame correlation, and thus Predictive SVQ (PSVQ) is utilized. PSVQ provides better rate-distortion performance than SVQ. In this paper, to implement the optimal predictors in PSVQ for voice storage devices, we propose Multi-Frame AR-model based SVQ (MF-AR-SVQ) that considers the inter-frame correlations with multiple previous frames. Compared with conventional PSVQ, the proposed MF-AR-SVQ provides 1 bit gain in terms of spectral distortion without significant increase in complexity and memory requirement.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.4
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• pp.595-604
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• 2013

Currently, registered number of imported vehicles is increasing rapidly over the years. Accordingly, environment improvements of vehicle maintenance company for maintenance of luxury vehicle such as imported vehicle are continuously being made. In this paper, we propose a key frame extraction method based on HSV color model for smart vehicle management system implementation to offer for customer reliability of maintenance vehicle. After automatically recognize the license plates of the vehicle using vehicle license plate recognition system when the vehicle come in the car center, we check the repair history and request of the vehicle based on it. We implement mobile services which provide extracted key frame images to the user after extract key frames from vehicle repair video. In addition, we verify the superiority of key frame extraction method by applying a smart vehicle management system. Finally, we convert the RGB color to HSV color to improve the performance of proposed key frame extraction scheme. As a result, we confirmed that our scheme is more excellence about 30% in terms of recall than RGB color model from the performance evaluations.