• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1044-1049
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• 2001

Classical deconvolution methods for source identification following linear filtering can only be used if the transfer function of the system is known. For many practical situations, however, this information is not accessible and/or is time varying. The problem addressed here is that of reconstruction of the original input from only the measured signal. This is known as 'blind deconvolution'. By using Higher Order Statistics (HOS), the restoration of the input signal is established through the maximisation of higher order moments (cumulants) with respect to the characteristics of the signals concerned. This restoration is achieved by constructing an inverse filter considering the choice of the initial inverse filter type. As a practical application, an experimental verification is carried out for the restoration of our impacting signal arising in the response of a cantilever beam with an end stop when randomly excited.

• Genomics & Informatics
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• v.17 no.1
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• pp.2.1-2.12
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• 2019

Chronic obstructive pulmonary disease (COPD) is a type of progressive lung disease, featured by airflow obstruction. Recently, a comprehensive analysis of the transcriptome in lung tissue of COPD patients was performed, but the heterogeneity of the sample was not seriously considered in characterizing the mechanistic dysregulation of COPD. Here, we established a new transcriptome analysis pipeline using a deconvolution process to reduce the heterogeneity and clearly identified that these transcriptome data originated from the mild or moderate stage of COPD patients. Differentially expressed or co-expressed genes in the protein interaction subnetworks were linked with mitochondrial dysfunction and the immune response, as expected. Computational protein localization prediction revealed that 19 proteins showing changes in subcellular localization were mostly related to mitochondria, suggesting that mislocalization of mitochondria-targeting proteins plays an important role in COPD pathology. Our extensive evaluation of COPD transcriptome data could provide guidelines for analyzing heterogeneous gene expression profiles and classifying potential candidate genes that are responsible for the pathogenesis of COPD.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.98-108
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• 2023

This paper is an attempt to design segmentation method based on fully convolutional networks (FCN) and attention mechanism. The first five layers of the Visual Geometry Group (VGG) 16 network serve as the coding part in the semantic segmentation network structure with the convolutional layer used to replace pooling to reduce loss of image feature extraction information. The up-sampling and deconvolution unit of the FCN is then used as the decoding part in the semantic segmentation network. In the deconvolution process, the skip structure is used to fuse different levels of information and the attention mechanism is incorporated to reduce accuracy loss. Finally, the segmentation results are obtained through pixel layer classification. The results show that our method outperforms the comparison methods in mean pixel accuracy (MPA) and mean intersection over union (MIOU).

• Proceedings of the KSMRM Conference
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• 2000.11a
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• pp.33-33
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• 2000

• The Journal of the Acoustical Society of Korea
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• v.36 no.6
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• pp.378-386
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• 2017

Accurate distance measurement between maneuver target in underwater and measuring devices is required to perform quantitative test evaluation in marine weapons system R&D process. In general, the target distance is measured using a one-way ToA (Time of Arrival) method that calculates the time difference between transmitted and received signals from the two accurately synchronized devices. However, the distance estimation performance is degraded because of the multi-path environments. In this paper, the time-variant transfer function of complex underwater environment is estimated from each received data frame using RBD (Ray-based Blind Deconvolution), and the estimated time-variant transfer function is then used to get rid of the effect about complex underwater environment and to recover the data signal using PTRM (Passive Time Reversal Mirror). The result from the simulation and experimental data show that the suggested method improve the distance estimation performance when comparing with the conventional ToA method.

• The Journal of the Acoustical Society of Korea
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• v.35 no.5
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• pp.375-382
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• 2016

This paper presents the results for the performance improvement of underwater communication in a passive time reversal mirror (PTRM) using ray-based blind deconvolution (RBD). In conventional PTRM, the signal to be recovered is found from matched-filtering the received probe signal. However, the communication performance is degraded because the time-varying impulse response for each data frame is not reflected in the received probe signal. In this study, the time-variant transfer function is estimated from each received data frame using RBD, and the estimated time-variant transfer function is then used to recover the data signal using PTRM. The results from the experimental data show that the suggested method improves the communication performance when comparing with the conventional PTRM.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.09a
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• pp.574-578
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• 2003

There are so many methods to estimate the groundwater recharge. These methods can be categorized into four groups. First groupis related to the water balance analysis, second group is concerned with baseflow/springflow recession, and third group is interested in some types of tracers; environmental tracers and/or temperature profile. The limitation of these types of methods is that the estimated results of recharge are presented in the form of an average over some time period. Forth group has a little different approach. They use the time series data of hydraulic head and specific yield evaluated from field test, and the results of estimation are described in the sequential form. But their approach has a serious problem. The estimated results in forth typeof methods are generally underestimated because they cannot consider the discharge phase of water table fluctuation coupled with the recharge phase. Ketchum el. at. (2000) proposed calibrated method, considering recharge- and discharge-coupled water table fluctuation. But the dischargeis considered just as the areal average with discharge rate. On the other hand, there are many methods to estimate the source wavelet with observed data set in geophysics/signal processing and geophysical methods are rarely applied to the estimation of groundwater recharge. The purpose this study is the evaluation of the applicability of one of the geophysical method in the estimation of sequential recharge rate. The applied geophysical method is called minimum entropy deconvolution (MED). For this purpose, numerical modeling with linearized Boussinesq equation was applied. Using the synthesized hydraulic head through the numerical modeling, the relative sequenceof recharge is calculated inversely. Estimated results are very concordant with the applied recharge sequence. Cross-correlations between applied recharge sequence and the estimated results are above 0.985 in all study cases. Through the numerical test, the availability of MED in the estimation of the recharge sequence to groundwater was investigated

• Progress in Medical Physics
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• v.7 no.1
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• pp.9-17
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• 1996

The response function of ionization chambers are measured in the narrow radiation field Nominal photon energies are 4MV, 6MV and 15MV. the Radii of the chambers are 0.5cm～3.05cm and the field size is 0.2$\times$20$\textrm{cm}^2$. The measurements are taken in the water phantom at 10cm depth. The beam kernel (radiation distribution profile) for narrow radiation field in the phantom are obtained from Monte Carlo simulation (EGS4, Electron Gamma Shower 4). The beam kernel components in the measured chamber response function are deconvolved in order to get the ideal chamber response function of the $\delta$-shaped function radiation field. The chamber response functions have energy dependent tendency before deconvolution, while they show energy invariant properties, after the components of beam kernels are removed by deconvolution method.

• Radiation Oncology Journal
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• v.16 no.1
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• pp.81-86
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• 1998

Purpose : To generate the axial, coronal and sagittal images from conventional simulation images, as a preliminary study of broad-beam simulator CT. Methods and Materials : Volumetric filtered back-projection was performed using 90 sheets of films from conventional simulator for every $4^{\circ}$ gantry angle. Two mAs exposure condition for 120kvp beam qualify at SFD 140cm was given to each film. Outside the silhouette portion was removed and scatter component was deconvolved before back-projection. Results : The axial, the sagittal and the coronal images with same spatial resolutions over all direction could be obtained. But image quality was very poor. Conclusion : CT images could be obtained using broad-beam. Scatter deconvolution technique was effective for this reconstruction. The fact that same spatial resolutions over all direction tells us the possibility of application of this technique to DRR or Simulator-CT. But the quality of image should be improved for clinical application practically.

• Fire Science and Engineering
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• v.31 no.4
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• pp.20-25
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• 2017

In the present study, the temperature distribution of droplet diffusion flames was predicted from the measurements of radiative emissions of soot particles formed. In order to predict the temperature distributions, the radiative emissions from soot particles filtered at both 700 nm and 900 nm were measured using CCD cameras and local emission distributions within the flame deconvoluted with Abel transformation were plugged into a two color method. The experimental results obtained from the present study demonstrate that the two color method as tool for temperature measurements is feasible but can introduce approximately 2% maturement errors in a deconvolution process depending on intervals for the line of sight. The estimated error in temperature measurements was found to be within 18 K at 2000 K.