• ETRI Journal
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• v.41 no.1
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• pp.117-123
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• 2019

This paper presents a tri-wideband bandpass filter (TWB-BPF) with compact size, high band-to-band isolation, and multiple transmission zeros (TZs). The proposed TWB-BPF is based on a multiple-mode resonator (MMR), which is interpreted by the method of the even- and odd-mode analysis technique. The MMR can excite 11 resonant modes, where the first two modes comprise the first passband, the next four modes form the second passband, and the last five modes are used to generate the third passband. In addition, 10 TZs are yielded to obtain high band-to-band isolation and wide stopband suppression characteristics up to $14.95f_{c1}$ ($f_{c1}$ is the center frequency of the first passband). To verify the proposed filter, a TWB-BPF with 3-dB fractional bandwidths (FBWs) of 37.4%, 43.5%, and 40.4% is designed, fabricated, and measured.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.133-138
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• 2019

The indoor navigation system using smart phone is a very important infrastructure technology for users' location based services in large indoor facilities. For this purpose, if the user can estimate the movement distance and direction by using the acceleration sensor and the gyro sensor built in the smartphone, the additional external environment is not necessary, which is a very useful technique. This paper deals with indoor navigation system technology that uses Pedestrian Dead Reckoning (PDR) technology and Kalman filter on a general smartphone and allows the user to trace the position while moving the smartphone in front of his chest. In particular, an extended Kalman filter was designed to estimate the direction of movement, and its performance was verified when walking at a constant speed.

• Wind and Structures
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• v.36 no.4
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• pp.221-236
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• 2023

The lateral component of turbulence and the vortices shed in the wake of a structure result in introducing dynamic wind load in the acrosswind direction and the resulting level of motion is typically larger than the corresponding alongwind motion for a dynamically sensitive structure. The underlying source mechanisms of the acrosswind load may be classified into motion-induced, buffeting, and Strouhal components. This study proposes a frequency domain framework to decompose the overall load into these components based on output-only measurements from wind tunnel experiments or full-scale measurements. First, the total acrosswind load is identified based on measured acceleration response by solving the inverse problem using the Kalman filter technique. The decomposition of the combined load is then performed by modeling each load component in terms of a Bayesian filtering scheme. More specifically, the decomposition and the estimation of the model parameters are accomplished using the unscented Kalman filter in the frequency domain. An aeroelastic wind tunnel experiment involving a tall circular cylinder was carried out for the validation of the proposed framework. The contribution of each load component to the acrosswind response is assessed by re-analyzing the system with the decomposed components. Through comparison of the measured and the re-analyzed response, it is demonstrated that the proposed framework effectively decomposes the total acrosswind load into components and sheds light on the overall underlying mechanism of the acrosswind load and attendant structural response. The delineation of these load components and their subsequent modeling and control may become increasingly important as tall slender buildings of the prismatic cross-section that are highly sensitive to the acrosswind load effects are increasingly being built in major metropolises.

• Journal of the Earthquake Engineering Society of Korea
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• v.28 no.4
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• pp.183-191
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• 2024

Accurate seismic vulnerability assessment requires high quality and large amounts of ground motion data. Ground motion data generated from time series contains not only the seismic waves but also the background noise. Therefore, it is crucial to determine the high-pass cut-off frequency to reduce the background noise. Traditional methods for determining the high-pass filter frequency are based on human inspection, such as comparing the noise and the signal Fourier Amplitude Spectrum (FAS), f² trend line fitting, and inspection of the displacement curve after filtering. However, these methods are subject to human error and unsuitable for automating the process. This study used a deep learning approach to determine the high-pass filter frequency. We used the Mel-spectrogram for feature extraction and mixup technique to overcome the lack of data. We selected convolutional neural network (CNN) models such as ResNet, DenseNet, and EfficientNet for transfer learning. Additionally, we chose ViT and DeiT for transformer-based models. The results showed that ResNet had the highest performance with R² (the coefficient of determination) at 0.977 and the lowest mean absolute error (MAE) and RMSE (root mean square error) at 0.006 and 0.074, respectively. When applied to a seismic event and compared to the traditional methods, the determination of the high-pass filter frequency through the deep learning method showed a difference of 0.1 Hz, which demonstrates that it can be used as a replacement for traditional methods. We anticipate that this study will pave the way for automating ground motion processing, which could be applied to the system to handle large amounts of data efficiently.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.3
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• pp.307-314
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• 2017

Terrain referenced navigation(TRN) system is an attractive method for obtaining position based on terrain measurements and a terrain map. We focus on TRN systems based on the point mass filter(PMF) which is one of the recursive Bayesian method. In this paper, we propose two kinds of performance index for Bayesian filter. The proposed indices are based on entropy and mutual information from information theory. The first index measures roughness of terrain based on entropy of likelihood. The second index named by information gain, which is the mutual information between priori and posteriori distribution, is a quantity of information gained by updating measurement at each step. The proposed two indices are used to determine whether the solution from TRN is adequate for TRN/INS integration or not, and this scheme gives the performance improvement. Simulation result shows that the proposed indices are meaningful and the proposed algorithm performs better than normal TRN algorithm.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.1
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• pp.114-124
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• 2004

In this paper, we present an automatic C source code generation system for DirectShow based multimedia application programming. In this system, C source code is automatically synthesized from the filter connection graph edited with GraphEdit, a utility tool provided with DirectShow SDK package from Microsoft. In traditional DirectShow programming environments, program design and brief testing steps are usually done with GraphEdit tool just by inserting filters and connecting them properly, while actual implementation of the program should be done separately. The filter connection graph information from GraphEdit is used just as a reference in such the implementation step. Therefore, our system which automatically generates C source code directly from the filter connection graph of GraphEdit seems very useful and many programmers can develop DirectShow based multimedia application programs more effectively and quickly using our system. In addition, our system supports more various media stream control functions for the generated application programs than the existing system such as Wizard which supports limited and fixed number of media control functions only. This feature allows more flexibility in the user interface of the generated source program and makes our system more practical for DirectShow based programming.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.22-27
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• 2014

Blocking and ringing artifacts continue to be the most serious defects that occur in images and video streams compressed to low bit rates using block-based discrete cosine transform(DCT) compression standards. These artifacts contain the high frequency components near the block and the edge boundaries. Usually the lowpass filter can remove them. However, simple lowpass filter results into blur by removing important information such as edges at the same time. To overcome these problems, we propose a novel postfiltering algorithm that calculate the weight value based on the intensity similarity in the neighboring pixels and multiply this weight to the Gaussian lowpass filter coefficient. Experimental results show that the proposed technique provides satisfactory performance in both objective and subjective image quality.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.60-70
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• 2018

A software defined storage (SDS) is being deployed in cloud environment to allow multiple users to virtualize physical servers, but a solution for optimizing space efficiency with limited physical resources is needed. In the conventional data deduplication system, it is difficult to deduplicate redundant data uploaded to distributed storages. In this paper, we propose a distributed deduplication method using similarity-based clustering and multi-layer bloom filter. Rabin hash is applied to determine the degree of similarity between virtual machine servers and cluster similar virtual machines. Therefore, it improves the performance compared to deduplication efficiency for individual storage nodes. In addition, a multi-layer bloom filter incorporated into the deduplication process to shorten processing time by reducing the number of the false positives. Experimental results show that the proposed method improves the deduplication ratio by 9% compared to deduplication method using IP address based clusters without any difference in processing time.

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.4
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• pp.335-342
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• 2000

A new control method for a single-phase active power filter, based on a load current estimation using a DC capacitor voltage of active power filter without sensing nonlinear load current, is proposed in this paper. Because the method proposed can remove the load current sensor in comparison with a conventional method sensing the load current and DC capacitor voltage together, it can make the active power filter easy installation, low cost, small size with no performance detriment. In addition, sample-hold technique and proportional control method is adopted to control the DC capacitor voltage and as no delay element such as LPF or PI control in the conventional method is used, the transient response is fast and good. Operation of a single-phase active power filter which consist of eight mode is explained according to utility voltage, compensation current and switch state, and compensation characteristics of active power filter using proposed method is verified by experiment.

• Journal of Magnetics
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• v.22 no.1
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• pp.55-59
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• 2017

The purpose of this study was to quantitatively evaluate image quality using intensity profile, coefficient of variation (COV), and peak signal to noise ratio (PSNR) with respect to noise reduction techniques in the ultrasound images. For that purpose, we compared with the median filter, Rudin-Osher-Fatemi (ROF), Anscombe and proposed patch group prior based denoising (PGPD) techniques. To evaluate image quality, the Shepp-Logan phantom and the ultrasound image were acquired using simulation and experiment, respectively. According to the results, the difference of intensity profile using PGPD technique is lowest compared with original Shepp-Logan phantom. In simulation, the measured COV was 0.249, 0.198, 0.198, 0.177, and 0.080 using noisy, median, ROF, Anscombe and PGPD technique, respectively. Also, in experimental image, the measured COV was 0.245, 0.230, 0.231, 0.242 and 0.187 using noisy, median, ROF, Anscombe and PGPD technique, respectively. Especially, when we used PGPD technique, the PSNR has highest value in both simulation and experiment. In this study, we performed simulation and experiment study to compare various denoising techniques in the ultrasound image. We can expect the PGPD technique to improve in medical diagnosis with excellent noise reduction.