• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.5 no.2
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• pp.37-48
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• 1991

This paper shows the characteristics of sparkover discharge in flowing air ranging from O(Reynolds number, Re) to $10.52{\times}10^4$(Re). Also, we investigated changes of discharge pattern for constant input power by adjustment of the Reynolds number. Flowing air duct of this investigation is a circular tube. The flow at the experimented positions' section is described as fully development laminar flow. The important results obtained from this study are as follows. The sparkover discharge path of flowing air can be analyzed by the theories of flow field for air. The sparkover voltage shows nearly the maximum value when the Reynolds number of flowing air ranges $3{\times}10^4$ to $4{\times}10^4$The maximum sparkover voltages of flowing air are about 6.3[kV] higher than those of static air. The discharge pattern can be controlled by adjustment of the Reynolds number.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.12
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• pp.46-53
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• 2003

This paper describes a new linear operational transconductance amplifier (OTA) and its application to the 9th-order Bessel filter. To improve the linearity of the OTA, we employ a mobility compensation technique. The combination of the triode and the subthreshold region transistors can compensate the mobility reduction effect and make the OTA with a good linearity. The proposed OTA shows $\pm$0.32% Gm variation over the input range of $\pm$0.8-V. The total harmonic distortion (THD) was lower than -60-㏈. The 9th-order Bessel filter has been designed using a 0.35-${\mu}{\textrm}{m}$ n-well CMOS process under 3.3-V supply voltage. It shows the cutoff frequency of 8-MHz and the power consumption of 65-mW.

• Journal of Biomedical Engineering Research
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• v.40 no.2
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• pp.62-67
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• 2019

The purpose of this study was to evaluate the performance of deep neural network model in order to determine whether there is a risk factor for coronary artery disease based on the cardiac variation parameter. The study used unidentifiable 297 data to evaluate the performance of the model. Input data consists of heart rate parameters, which are SDNN (standard deviation of the N-N intervals), PSI (physical stress index), TP (total power), VLF (very low frequency), LF (low frequency), HF (high frequency), RMSSD (root mean square of successive difference) APEN (approximate entropy) and SRD (successive R-R interval difference), the age group and sex. Output data are divided into normal and patient groups, and the patient group consists of those diagnosed with diabetes, high blood pressure, and hyperlipidemia among the various risk factors that can cause coronary artery disease. Based on this, a binary classification model was applied using Deep Neural Network of deep learning techniques to classify normal and patient groups efficiently. To evaluate the effectiveness of the model used in this study, Kernel SVM (support vector machine), one of the classification models in machine learning, was compared and evaluated using same data. The results showed that the accuracy of the proposed deep neural network was train set 91.79% and test set 85.56% and the specificity was 87.04% and the sensitivity was 83.33% from the point of diagnosis. These results suggest that deep learning is more efficient when classifying these medical data because the train set accuracy in the deep neural network was 7.73% higher than the comparative model Kernel SVM.

• Design & Manufacturing
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• v.16 no.4
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• pp.52-59
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• 2022

Currently, Korea is an aging society and is expected to become a super-aged society in about four years. X-ray devices are widely used for early diagnosis in hospitals, and many X-ray technologies are being developed. The development of X-ray device technology is important, but it is also important to increase the reliability of the device through accurate data management. Sensor nodes such as temperature, voltage, and current of the diagnosis device may malfunction or transmit inaccurate data due to various causes such as failure or power outage. Therefore, in this study, the temperature, tube voltage, and tube current data related to each sensor and detection circuit of the diagnostic X-ray imaging device were measured and analyzed. Based on QC data, device failure prediction and diagnosis algorithms were designed and performed. The fault diagnosis algorithm can configure a simulator capable of setting user parameter values, displaying sensor output graphs, and displaying signs of sensor abnormalities, and can check the detection results when each sensor is operating normally and when the sensor is abnormal. It is judged that efficient device management and diagnosis is possible because it monitors abnormal data values (temperature, voltage, current) in real time and automatically diagnoses failures by feeding back the abnormal values detected at each stage. Although this algorithm cannot predict all failures related to temperature, voltage, and current of diagnostic X-ray imaging devices, it can detect temperature rise, bouncing values, device physical limits, input/output values, and radiation-related anomalies. exposure. If a value exceeding the maximum variation value of each data occurs, it is judged that it will be possible to check and respond in preparation for device failure. If a device's sensor fails, unexpected accidents may occur, increasing costs and risks, and regular maintenance cannot cope with all errors or failures. Therefore, since real-time maintenance through continuous data monitoring is possible, reliability improvement, maintenance cost reduction, and efficient management of equipment are expected to be possible.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2317-2325
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• 2016

This paper presents a 10 bit successive approximation register (SAR) analog-to-digital converter (ADC) with a reference driver. The proposed SAR ADC consists of a capacitive digital-to-analog converter (CDAC), a comparator, a SAR logic, and a reference driver which improves the immunity to the power supply noise. The reference driver generates the reference voltages of 0.45 V and 1.35 V for the SAR ADC with an input voltage range of ${\pm}0.9V$. The SAR ADC is implemented using a $0.18-{\mu}m$ CMOS technology with a 1.8-V supply. The proposed SAR ADC including the reference driver almost maintains an input voltage range to be ${\pm}0.9V$ although the variation of supply voltage is +/- 200 mV. It consumes 5.32 mW at a sampling rate of 10 MS/s. The measured ENOB, DNL, and INL of the ADC are 9.11 bit, +0.60/-0.74 LSB, and +0.69/-0.65 LSB, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.230-235
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• 2005

In this paper, we propose an algorithm that improves a tone quality of a noisy audio signal in order to enhance a performance of perceptual filter using intelligent estimation of noise pattern from a band degraded by additive noise. The proposed method doesn't use the estimated noise which is obtained from silent range. Instead new estimated noise according to the power of signal and effect of noise variation is considered for each frame. So the noisy audio signal is enhanced by the method which controls a estimation of noise Pattern effectively in a noise corruption band. To show the performance of the proposed algorithm, various input signals which had a different signal-to-noise ratio(SNR) such as $5\cal{dB},\;10\cal{dB},\;15\cal{dB}\;and\;20\cal{dB}$ were used to test the proposed algorithm. we carry out SSNR and NMR of objective measurement and MOS test of subjective measurement. An approximate improvement of $7.4\cal{dB},\;6.8\cal{dB},\;5.7\cal{dB},\;5.1\cal{dB}$ in SSNR and $15.7\cal{dB},\;15.5\cal{dB},\;15.2\cal{dB},\;14.8\cal{dB}$ in NMR is achieved with the input signals, respectively. And we confirm the enhancement of tone quality in terms of mean opinion score(MOS) test which is result of subjective measurement.

• The Journal of the Acoustical Society of Korea
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• v.23 no.6
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• pp.446-453
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• 2004

In this paper, a new adaptive perceptual filter using variable threshold to enhance audio signals degraded by additively nonstationary noise is proposed. The adaptive perceptual filter updates variable threshold each time according to the power of signal and the effect of noise variation. So the noisy audio signal is enhanced by the method which controls a residual noise effectively. The proposed algorithm uses the perceptual filter which transforms a time domain signal into frequency domain and calculates an intensity energy and an excitation energy in bark domain. In this method. the stage updated the response of filter is decided by threshold. The proposed algorithm using vairable threshold effectively controls a residual noise using the energy difference of audio signals degraded by the additive nonstationary noise. The proposed method is tested with the noisy audio signals degraded by nonstationary noise at various signal -to-noise ratios (SNR). We carry out NMR and MOS test when the input SNR is 15dB. 20dB. 25dB and 30dB. An approximate improvement of 17.4dB. 15.3dB, 12.8dB. 9.8dB in NMR and enhancement of 2.9, 2.5, 2.3, 1.7 in MOS test is achieved with the input signals. respectively.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.1
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• pp.59-67
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• 2016

A novel instrumentation amplifier (IA) using fully-differential linear operational transconductance amplifier (FLOTA) for electronic measurement systems with low cost, wideband, and gain control with wide range is designed. The IA consists of a FLOTA, two resistor, and an operational amplifier(op-amp). The principal of the operating is that the difference of two input voltages applied into FLOTA converts into two same difference currents, and then these current drive resistor of (+) terminal and feedback resistor of op-amp to obtain output voltage. To verify operating principal of the IA, we designed the FLOTA and realized the IA used commercial op-amp LF356. Simulation results show that the FLOTA has linearity error of 0.1% and offset current of 2.1uA at input dynamic range ${\pm}3.0V$. The IA had wide gain range from -20dB to 60dB by variation of only one resistor and -3dB frequency for the 60dB was 10MHz. The proposed IA also has merits without matching of external resistor and controllable offset voltage using the other resistor. The power dissipation of the IA is 105mW at supply voltage of ${\pm}5V$.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.953-966
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• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.11
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• pp.1104-1112
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• 2013

This paper presents a wideband Colpitts voltage controlled oscillator(VCO) with nanosecond startup time and a center frequency of 8.35 GHz for a new bubble-type motion detector that has a bubble-layer detection zone at the specific distance from itself. The VCO circuit consists of two parts; one is a negative resistance part with a HEMT device and Colpitts feedback structure and the other is a resonator part with a varactor diode and shorted shunt microstrip line. The shorted shunt microstrip line and series capacitor are utilized to compensate for the input reactance of the packaged HEMT that changes from capacitive values to inductive values at 8.1 GHz due to parasitic package inductance. By tuning the feedback capacitors which determine negative resistance values, this paper also investigates startup time improvement with the negative resistance variation and tuning bandwidth improvement with the reactance slope variation of the negative resistance part. The VCO measurement shows the tuning bandwidth of 2.3 GHz(28 %), the output power of 4.1~7.5 dBm and the startup time of less than 2 nsec.