• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5C
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• pp.393-402
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• 2012

In this study, we propose a signal processing algorithm to measure the arousal level of a human subject using a PPG(Photoplethysmography) sensor. From the measured PPG signals, the arousal level is determined by PPI(Pulse to Pulse Interval) and discrete-time signal processing. We ran psychophysical experiments displaying visual stimuli on TV display while measuring PPG signal from a finger, where the nature landscape scenes were used for restorative effect, and the urban environments were used to stimulate the stress. However, the measured PPG signals may include noise due to subject movement and measurement error, which results in incorrect detections. In this paper, to mitigate the noise impact on stimulus detection, we propose a detecting algorithm using digital signal processing methods and statistics of measured signals. A filter is adopted to remove a high frequency noise and adaptively designed taking into account the statistics of the measured PPG signals. Moreover we employ a hysteresis method to reduce the distortion of PPI in decision of emotional. Via experiment, we show that the proposed scheme reduces signal noise and improves stimulus detection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.995-1006
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• 2003

It is well know that in the wireless communication systems the transmitted signals can suffer from multipath fading due to the wave propagation characteristics and the obstacles over the paths, resulting in serious reduction in the power of the received signals. However, it is possible to take advantage of the inherent diversity imposed in the multipath reception if the underlying channel can be properly estimated. One of the diversity reception methods in this case is Rake processing. In this paper we study the Rake receivers for the direct-sequence spread-spectrum communication systems utilizing PN (pseudo noise) sequences to achieve spread spectrum. A conventional Rake receiver can use the finite-duration impulse (FIR) filter followed by the PN sequence demodulator, where the FIR filter coefficients are the reverse-ordered complex conjugate values of the fading channel impulse response estimates. Here, we propose a new Rake processing method by replacing the aforementioned PN code sequence with a new set of optimum demodulator coefficients. More specifically, the concept of the new optimum Rake processing is first introduced and then the optimum demodulator coefficients are theoretically derived. The performance obtained using the new optimum Rake processing is also calculated. The analytical results are verified by computer simulation. As a result, it is shown that the new optimum Rake processing method improves the MSE performance more than 10 dB over the conventional one using the fixed PN sequence demodulator. It is also shown that the new optimum Rake processing method improves the MSE performance about 10 dB over the Adaptive Correlator that performs the combining of the multipath components and PN demodulation concurrently. And finally, the MSE performance of the optimum Rake demodulator is very close to the MSE performance of OPSK demodulator under the AWGN channel.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.326-334
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• 2022

In this paper, we propose speech enhancement algorithm as a pre-processing for robust speech recognition in noisy environments. Auxiliary-function-based Independent Vector Analysis (AuxIVA) is performed with weighted covariance matrix using time-varying variances with scaling factor from target masks representing time-frequency contributions of target speech. The mask estimates can be obtained using Neural Network (NN) pre-trained for speech extraction or diffuseness using Coherence-to-Diffuse power Ratio (CDR) to find the direct sounds component of a target speech. In addition, outputs for omni-directional noise are closely chained by sharing the time-varying variances similarly to independent subspace analysis or IVA. The speech extraction method based on AuxIVA is also performed in Independent Low-Rank Matrix Analysis (ILRMA) framework by extending the Non-negative Matrix Factorization (NMF) for noise outputs to Non-negative Tensor Factorization (NTF) to maintain the inter-channel dependency in noise output channels. Experimental results on the CHiME-4 datasets demonstrate the effectiveness of the presented algorithms.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.11
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• pp.2047-2058
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• 2000

The effects of operating parameters on performance of upflow anaerobic sludge blanket(UASB). anaerobic filter(AF), and two-stage anaerobic sludge bed filter (ASBF) bioreactors in treating swine wastewater were evaluated by operating the lab-scale bioreactors upto hydraulic retention time(HRT) of 1 day and organic loading rate (OLR) of $5.1kg-COD/m^3{\cdot}d$ for 200 days. Swine wastewaters of which characteristics were affected by types of hog raising and seasons contained high concentrations of COD, SS, and ammonia. Inoculation of the bioreactors with waste sludge from anaerobic treatment facility of local municipal wastewater treatment plant was effective in developing biomass in the bioreactors. Acclimation period of the bioreactors with swine wastewaters required approximately 40 days, but that for AF and two-stage ASBF, which were filled with media, was faster than VASB. The bioreactors showed high and stable COD removal efficiency of 77~91% at influent T-N concentrations of 370~800mg/L but low and unstable COD removal efficiency of 24~94% at influent T-N concentrations of 760~1,310mg/L. It is essential to remove ammonia prior to anaerobic treatment since the concentrations of ammonia in swine wastewaters showed toxic effects to methanogenic bacteria. The bioreactors were effective in treating swine wastewaters with COD removal efficiency of 78.9~81.5% and biogas generation rate of $0.39{\sim}0.59m^3/kg-COD_r$ at OLR of $1.1{\sim}2.2kg-COD/m^3{\cdot}d$: however, an increase of OLR by reducing HRT and increasing influent COD caused decrease of COD removal efficiency. The extent of decrease in COD removal efficiency was higher in UASB than AF and two-stage ASBF. AF and two-stage ASBF anaerobic bioreactors were effective in treating varing characteristics of swine wastewaters since they showed high and stable COD removal efficiency at high OLR due to effective retention of biomass by media and staging.

• Progress in Medical Physics
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• v.23 no.1
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• pp.62-69
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• 2012

The dose re-calculation process using Megavoltage cone-beam CT images is inevitable process to perform the Adaptive Radiation Therapy (ART). The purpose of this study is to improve dose re-calculation accuracy using MVCBCT images by applying intensity calibration method and three dimensional rigid body transform and filtering process. The three dimensional rigid body transform and Gaussian smoothing filtering process to MVCBCT Rando phantom images was applied to reduce image orientation error and the noise of the MVCBCT images. Then, to obtain the predefined modification level for intensity calibration, the cheese phantom images from kilo-voltage CT (kV CT), MVCBCT was acquired. From these cheese phantom images, the calibration table for MVCBCT images was defined from the relationship between Hounsfield Units (HUs) of kV CT and MVCBCT images at the same electron density plugs. The intensity of MVCBCT images from Rando phantom was calibrated using the predefined modification level as discussed above to have the intensity of the kV CT images to make the two images have the same intensity range as if they were obtained from the same modality. Finally, the dose calculation using kV CT, MVCBCT with/without intensity calibration was applied using radiation treatment planning system. As a result, the percentage difference of dose distributions between dose calculation based on kVCT and MVCBCT with intensity calibration was reduced comparing to the percentage difference of dose distribution between dose calculation based on kVCT and MVCBCT without intensity calibration. For head and neck, lung images, the percentage difference between kV CT and non-calibrated MVCBCT images was 1.08%, 2.44%, respectively. In summary, our method has quantitatively improved the accuracy of dose calculation and could be a useful solution to enhance the dose calculation accuracy using MVCBCT images.

• Progress in Medical Physics
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• v.22 no.1
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• pp.28-34
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• 2011

To perform the Adaptive Radiation Therapy (ART), a high degree of deformable registration accuracy is essential. The purpose of this study is to identify whether the change of MV CBCT intensity can improve registration accuracy using predefined modification level and filtering process. To obtain modification level, the cheese phantom images was acquired from both kilovoltage CT (kV CT), megavoltage cone-beam CT (MV CBCT). From the cheese phantom images, the modification level of MV CBCT was defined from the relationship between Hounsfield Units (HUs) of kV CT and MV CBCT images. 'Gaussian smoothing filter' was added to reduce the noise of the MV CBCT images. The intensity of MV CBCT image was changed to the intensity of the kV CT image to make the two images have the same intensity range as if they were obtained from the same modality. The demon deformable registration which was efficient and easy to perform the deformable registration was applied. The deformable lung phantom which was intentionally created in the laboratory to imitate the changes of the breathing period was acquired from kV CT and MV CBCT. And then the deformable lung phantom images were applied to the proposed method. As a result of deformable image registration, the similarity of the correlation coefficient was used for a quantitative evaluation of the result was increased by 6.07% in the cheese phantom, and 18% in the deformable lung phantom. For the additional evaluation of the registration of the deformable lung phantom, the centric coordinates of the mark which was inserted into the inner part of the phantom were measured to calculate the vector difference. The vector differences from the result were 2.23, 1.39 mm with/without modification of intensity of MV CBCT images, respectively. In summary, our method has quantitatively improved the accuracy of deformable registration and could be a useful solution to improve the image registration accuracy. A further study was also suggested in this paper.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.1-18
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• 2014

Over the past years RFID/SN has been an elementary technology in a diversity of applications for the ubiquitous environments, especially for Internet of Things. However, one of obstacles for widespread deployment of RFID technology is the inherent unreliability of the RFID data streams by tag readers. In particular, the problem of false readings such as lost readings and mistaken readings needs to be treated by RFID middleware systems because false readings ultimately degrade the quality of application services due to the dirty data delivered by middleware systems. As a result, for the higher quality of services, an RFID middleware system is responsible for intelligently dealing with false readings for the delivery of clean data to the applications in accordance with the tag reading environment. One of popular techniques used to compensate false readings is a sliding window filter. In a sliding window scheme, it is evident that determining optimal window size intelligently is a nontrivial important task in RFID middleware systems in order to reduce false readings, especially in mobile environments. In this paper, for the purpose of reducing false readings by intelligent window adaption, we propose a new adaptive RFID data cleaning scheme based on window sliding for a single tag. Unlike previous works based on a binomial sampling model, we introduce the weight averaging. Our insight starts from the need to differentiate the past readings and the current readings, since the more recent readings may indicate the more accurate tag transitions. Owing to weight averaging, our scheme is expected to dynamically adapt the window size in an efficient manner even for non-homogeneous reading patterns in mobile environments. In addition, we analyze reading patterns in the window and effects of decreased window so that a more accurate and efficient decision on window adaption can be made. With our scheme, we can expect to obtain the ultimate goal that RFID middleware systems can provide applications with more clean data so that they can ensure high quality of intended services.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.4
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• pp.479-488
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• 2002

In recent years the amount of digital video used has risen dramatically to keep pace with the increasing use of the Internet and consequently an automated method is needed for indexing digital video databases. Textual information, both superimposed and embedded scene texts, appearing in a digital video can be a crucial clue for helping the video indexing. In this paper, a new method is presented to extract both superimposed and embedded scene texts in a freeze-frame of news video. The algorithm is summarized in the following three steps. For the first step, a color image is converted into a gray-level image and applies contrast stretching to enhance the contrast of the input image. Then, a modified local adaptive thresholding is applied to the contrast-stretched image. The second step is divided into three processes: eliminating text-like components by applying erosion, dilation, and (OpenClose+CloseOpen)/2 morphological operations, maintaining text components using (OpenClose+CloseOpen)/2 operation with a new Geo-correction method, and subtracting two result images for eliminating false-positive components further. In the third filtering step, the characteristics of each component such as the ratio of the number of pixels in each candidate component to the number of its boundary pixels and the ratio of the minor to the major axis of each bounding box are used. Acceptable results have been obtained using the proposed method on 300 news images with a recognition rate of 93.6%. Also, my method indicates a good performance on all the various kinds of images by adjusting the size of the structuring element.