• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.201-208
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• 2013

In this paper, we studied on improvement for radiated EMI of USB power line of cable. it is made by using wireless video access point system for confirming the phenomenon of radiated EMI from cable. then, we make sure that the limit exceed through the initial measurement of radiated EMI limit criteria in comparison to about 3 [dBuV/m]~15 [dBuV/m]. after that we confirmed the resonance in power line of cable through measurement of s-parameters. so, we confirmed the relation radiated EMI and power line of cable resonance and we reduced radiated EMI in power line of cable through a capacitor and low pass-band filter using the technique of power networks management. in conclusion, we suggested how to reduce power line of cable resonance applied for the improved method. and we confirmed that suggested reduction method is suitable through testing radiated EMI. the result of radiated EMI reduction limit criteria 40[dBuV/m]~47[dBuV/m] in comparison to about 3 [dBuV/m]~20 [dBuV/m].

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.21-31
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• 2021

As the COVID-19 pandemic rapidly changes healthcare around the globe, the need for smart healthcare that allows for remote diagnosis is increasing. The current classification of respiratory diseases cost high and requires a face-to-face visit with a skilled medical professional, thus the pandemic significantly hinders monitoring and early diagnosis. Therefore, the ability to accurately classify and diagnose respiratory sound using deep learning-based AI models is essential to modern medicine as a remote alternative to the current stethoscope. In this study, we propose a deep learning-based respiratory sound classification model using data collected from medical experts. The sound data were preprocessed with BandPassFilter, and the relevant respiratory audio features were extracted with Log-Mel Spectrogram and Mel Frequency Cepstral Coefficient (MFCC). Subsequently, a Parallel CNN network model was trained on these two inputs using stacking ensemble techniques combined with various machine learning classifiers to efficiently classify and detect abnormal respiratory sounds with high accuracy. The model proposed in this paper classified abnormal respiratory sounds with an accuracy of 96.9%, which is approximately 6.1% higher than the classification accuracy of baseline model.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.5
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• pp.27-37
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• 1999

A CMOS ReadOut Integrated Circuit (ROlC) for InfraRed Focal Plane Array (IRFPA) detector is presented, which is a key component in uncooled thermal imaging systems. The ROIC reads out signals from $64\times64$ Barium Strontium Titanate (BST) infrared detector array, then outputs pixel signals sequentially after amplifying and noise filtering. Various design requirements and constraints have been considered including impedance matching, low noise, low power dissipation and small detector pitch. For impedance matching between detector and pre~amplifier, a new circuit based on MOS diode structure is devised, which can be easily implemented using standard CMOS process. Also, tunable low pass filter with single~pole is used to suppress high frequency noise. In additions, a clamping circuit is adopted to enhance the signal~to-noise ratio of the readout output signals. The $64\times64$ IRFPA ROIC is designed using $0.65-\mu\textrm{m}$ 2P3M (double poly, tripple metal) N~Well CMOS process. The core part of the chip contains 62,000 devices including transistors, capacitors and resistors on an area of about $6.3-mm\times6.7-mm$.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.7-16
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• 2015

The transmitter of quadrature multiplexed GMSK (QM-GMSK) is composed of two quadrature multiplexed GMSK modulators. QM-GMSK has a slightly increased spectrum main lobe compared with $Q^2PSK$ or QMSK, but it has highly suppressed side lobes. As a result, practical spectrum efficiency of QM-GMSK is achieved. By replacing the baseband elementary pulses of QM-GMSK with their approximate, the squared sinusoid of half-period, offset-$Q^2PSK$($OQ^2PSK$) is obtained. The $OQ^2PSK$ signal has similar spectral properties to QM-GMSK. The transmitter of $OQ^2PSK$ can be simply implemented without the Gaussian lowpass filter, which is required in QM-GMSK transmitter. In this paper, we propose an overlapped pulse shaping in $OQ^2PSK$ with RC(raised-cosine) or SRC(squared raised-cosine) pulses of length longer than the symbol period. Power spectrum of the proposed modulation scheme exhibits further suppressed side lobes, hence enhanced spectrum efficiency is obtained. Simulation results indicate that BER performance of the proposed scheme is comparable to that of $OQ^2PSK$.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.251-260
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• 1998

The Holter monitoring system is a widely used noninvasive diagnostic tool for ambulatory patient who may be at risk from latent life-threatening cardiac abnormalities. In this paper, we design a high performance intelligent holter monitoring system which is characterized by the small-sized and the low-power consumption. The system hardware consists of one-chip microcontroller(68HC11E9), ECG preprocessing circuit, and flash memory card. ECG preprocessing circuit is made of ECG preamplifier with gain of 250, 500 and 1000, the bandpass filter with bandwidth of 0.05-100Hz, the auto-balancing circuit and the saturation-calibrating circuit to eliminate baseline wandering, ECG signal sampled at 240 samples/sec is converted to the digital signal. We use a linear recursive filter and preprocessing algorithm to detect the ECG parameters which are QRS complex, and Q-R-T points, ST-level, HR, QT interval. The long-term acquired ECG signals and diagnostic parameters are compressed by the MFan(Modified Fan) and the delta modulation method. To easily interface with the PC based analyzer program which is operated in DOS and Windows, the compressed data, that are compatible to FFS(flash file system) format, are stored at the flash memory card with SBF(symmetric block format).

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.2
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• pp.23-32
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• 2020

The compression sensing technology, CAFB, was developed to obtain the raw signal of the target structure by compressing it into a signal of the intended frequency range. At this point, for compression sensing, the CAFB can be optimized for various reference signals depending on the desired frequency range of the target structure. In addition, optimized CAFB should be able to efficiently compress the effective structural answers of the target structure even in sudden/dangerous conditions such as earthquakes. In this paper, the targeted frequency range for efficient structural integrity monitoring of relatively flexible structures was set below 10Hz, and the optimization method of CAFB for this purpose and the seismic response performance of CAFB in seismic conditions were evaluated experimentally. To this end, in this paper, CAFB was first optimized using Kobe seismic waveform, and embedded it in its own wireless IDAQ system. In addition, seismic response tests were conducted on two span bridges using Kobe seismic waveform. Finally, using an IDAQ system with built-in CAFB, the seismic response of the two-span bridge was wirelessly obtained, and the compression signal obtained was cross-referenced with the raw signal. From the results of the experiment, the compression signal showed excellent response performance and data compression effects in relation to the raw signal, and CAFB was able to effectively compress and sensitize the effective structural response of the structure even in seismic situations. Finally, in this paper, the optimization method of CAFB was presented to suit the intended frequency range (less than 10Hz), and CAFB proved to be an economical and efficient data compression sensing technology for instrumentation-monitoring of seismic conditions.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.3
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• pp.58-65
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• 2002

In order to reduce blocking artifacts in inter-frame coded images, we propose a new image restoration algorithm, which directly processes differential images before reconstruction. We note that blocking artifact in inter-frame coded images is caused by both 8$\times$8 DCT and 16$\times$16 macroblock based motion compensation, while that of intra-coded images is caused by 8$\times$8 DCT only. According to the observation, we Propose a new degradation model for differential images and the corresponding restoration algorithm that utilizes additional constraints and convex sets for discontinuity inside blocks. The proposed restoration algorithm is a modified version of standard regularization that incorporate!; spatially adaptive lowpass filtering with consideration of edge directions by utilizing a part of DCT coefficients. Most of video coding standard adopt a hybrid structure of block-based motion compensation and block discrete cosine transform (BDCT). By this reason, blocking artifacts are occurred on both block boundary and block interior For more complete removal of both kinds of blocking artifacts, the restored differential image must satisfy two constraints, such as, directional discontinuities on block boundary and block interior Those constraints have been used for defining convex sets for restoring differential images.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.5 s.305
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• pp.27-34
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• 2005

Ventricular fibrillation(VF) is generally caused by chaotic behavior of electrical propagation in heart and may result in sudden cardiac death. In this study, we proposed a ventricular fibrillation detection algorithm based on support vector machine classifier, which could offer benefits to reduce the teaming costs as well as good classification performance. Before the extraction of input features, raw ECG signal was applied to preprocessing procedures, as like wavelet transform based bandpass filtering, R peak detection and segment assignment for feature extraction. We selected input features which of some are related to the rhythm information and of others are related to wavelet coefficients that could describe the morphology of ventricular fibrillation well. Parameters for SVM classifier, C and ${\alpha}$, were chosen as 10 and 1 respectively by trial and error experiments. Each average performance for normal sinus rhythm ventricular tachycardia and VF, was 98.39%, 96.92% and 99.88%. And, when the VF detection performance of SVM classifier was compared to that of multi-layer perceptron and fuzzy inference methods, it showed similar or higher values. Consequently, we could find that the proposed input features and SVM classifier would one of the most useful algorithm for VF detection.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.1
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• pp.85-95
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• 2012

In this thesis, we develop a spectral analysis scheme to eliminate the spurious peaks generated in HRR Millimeterwave Seeker based on FMICW system. In contrast to FMCW system, FMICW system generates spurious peaks in the spectrum of its IF signal, caused by the periodic discontinuity of the signal. These peaks make the accuracy of the system depend on the previously estimated range if a band pass filter is utilized to eliminate them and noise floor go to high level if random interrupted sequence is utilized and in case of using staggering process, we must transmit several waveforms to obtain overlapped information. Using the spectral analysis one of the schemes such as IAA(Iterative Adaptive Approach) and SPICE(SemiParametric Iterative Covariance-based Estimation method) which were introduced recently, the spurious peaks can be eliminated effectively. In order to utilize IAA and SPICE, since we must distinguish between reliable data and unreliable data and only use reliable data, STFT(Short Time Fourier Transform) is applied to the distinguishment process.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.2
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• pp.99-107
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• 2006

Magnetic nondestructive testing is very useful far detecting a crack on the surface or near of the surface of the ferromagnetic materials. The distribution of the magnetic flux leakage (DMFL) on a specimen has to be obtained quantitatively to evaluate the crack. The magnetic camera is proposed to obtain the DMFL at the large lift-off. The magnetic camera consists of a magnetic source, magnetic lens, analog to digital converters (ADCs), interface, and computer. The magnetic leakage fields or the distorted magnetic fields from the object, which are concentrated on the magnetic lens, are converted to analog electrical signals tv arrayed small magnetic sensors. These analog signals are converted to digital signals by the ADCs, and are stored, imaged, and processed by the interface and computer. However the magnetic camera has limitations with respect to converting and switching speed, full range and resolution, direct memory access (DMA), temporary storage speed and volume because common ADCs were used. Improved techniques, such as those that introduce the operational amplifier (OP-Amp), amplify the signal, reduce the connection line, and use the low pass filter (LPF) to increase the signal to noise ratio are necessary. This paper proposes the exclusive embedded ADC including OP-Amp, LPF, microprocessor and DMA circuit for the magnetic camera to satisfy the conditions mentioned above.