• Journal of Yeungnam Medical Science
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• v.8 no.1
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• pp.63-71
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• 1991

Noninvasive techniques for antenatal detection of the fetal development and well-being such as biophysical profile, non-stress and stress test remain major challenges in modem obstetric practice. To obtain and analyze umbilical artery velocity waveform by pulsed-wave doppler ultrasound, a total of 160 determinations were carried out on 157 normal pregnant women between 16th to 41st week gestation. The ratio of peak systolic to end-diastolic flow velocity(S/D ratio), pulsatility index and resistance index were measured as indices of the resistance in feto-placental circulation. The results were as follows : As gestation advances, the, mean values for peak systolic and end-diastolic velocities raised progressively. As gestation advances, the mean values for the S/D ratio declined progressively, exhibiting high diastolic flow velocity caused by low resistance. Pulsatility index, and resistance index were also declined progressively, as gestation advances. The analysis of umbilical artery blood flow velocity waveforms provides a new noninvasive technique to evaluate fetal development and well-being, and may be expected a reliable method for assessment of fetal life.

• Journal of the Korea Society for Simulation
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• v.27 no.4
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• pp.61-68
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• 2018

This paper deals with ground clutter model for FOD (foreign object debris) surveillance FMCW (frequency modulated continuous waveform) radar. In the FOD surveillance radar, it has received not only the signals reflected by FOD, but also the clutters of the surface of the runway and the grassland simultaneously. However, to detect the FOD, the clutter rejection algorithm is necessary because the RCS (radar cross section) of FOD is nearly same to RCS of the grassland. In addition, it is difficult to apply the MTI (moving target indicator) algorithm as the clutter rejection algorithm because both the FOD and the clutter coexist stationarily. Hence, to remove the stationary clutter, it is crucial to accurately generate clutter map considering the surface of road. In this paper, in order to generate the clutter map, the respective beat signal at every range bin is generated in the case of only the surface without FOD, and then the beat signal accumulated 100 times. And also, Weibull distribution is applied to the RCS value to take the scattering distribution of clutter into consideration. The simulation results show that FOD can be well detected by applying the generated clutter map to the FOD FMCW radar.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.335-342
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• 2004

This paper describes a trans-admittance scanner for breast cancer detection. A FPGA-based sinusoidal waveform generator produces a constant voltage. The voltage is applied between a hand-held electrode and a scan probe placed on the breast. The scan probe contains an 8x8 array of electrodes that are kept at the ground potential. Multi-channel precision digital ammeters using the phase-sensitive demodulation technique were developed to measure the exit current from each electrode in the array. Different regions of the breast are scanned by moving the probe on the breast. We could get trans-admittance images of resistor and saline phantoms with an anomaly inside. The images provided the information on the depth and location of the anomaly. In future studies, we need to improve the accuracy through a better calibration method. We plan to test the scanner's ability to detect a cancer lesion inside the human breast.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.5
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• pp.8-14
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• 2009

In the research field of speech recognition, pinpointing the endpoints of speech utterance even with the presence of background noise is of great importance. These noise present during recording introduce disturbances which complicates matters since what we just want is to get the stationary parameters corresponding to each speech section. One major cause of error in automatic recognition of isolated words is the inaccurate detection of the beginning and end boundaries of the test and reference templates, thus the necessity to find an effective method in removing the unnecessary regions of a speech signal. The conventional methods for speech endpoint detection are based on two linear time-domain measurements: the short-time energy, and short-time zero-crossing rate. They perform well for clean speech but their precision is not guaranteed if there is noise present, since the high energy and zero-crossing rate of the noise is mistaken as a part of the speech uttered. This paper proposes a novel approach in finding an apparent threshold between noise and speech based on Lyapunov Exponents (LEs). This proposed method adopts the nonlinear features to analyze the chaos characteristics of the speech signal instead of depending on the unreliable factor-energy. The excellent performance of this approach compared with the conventional methods lies in the fact that it detects the endpoints as a nonlinearity of speech signal, which we believe is an important characteristic and has been neglected by the conventional methods. The proposed method extracts the features based only on the time-domain waveform of the speech signal illustrating its low complexity. Simulations done showed the effective performance of the Proposed method in a noisy environment with an average recognition rate of up 92.85% for unspecified person.

• Journal of the Korean Society of Radiology
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• v.10 no.1
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• pp.1-6
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• 2016

Recently, the various digital X-ray imaging devices using CCD and TFT LCD-based flat panel digital X-ray sensor are being used. In particular, a number of studies on photon counting sensor technique have been reported. In this study, the incident X-rays fluence on the photon counting sensor material was measured to estimate photon detection efficiency which is the quantitative performance evaluation factor of photon counting sensor. The result of measuring the photon fluence by using RQA-M2 Radiation beam quality of IEC 61223-1-2 recommendations, the incident photon fluence could be defined as about $4 photons/(0.01mm)^2{\cdot}{\mu}Gy$ within $10{\mu}m$ pin-hole area, and about $50photons/(0.03mm)^2{\cdot}{\mu}Gy$ within $30{\mu}m$ pin-hole area, and about $698photons/(0.1mm)^2{\cdot}{\mu}Gy$ within $100{\mu}m$ pin-hole area. Consequently, with the previously setup of the incident fluence, the measuring of actual photon counting efficiency by observing the output waveform of the photon counting sensor material was considered possible.

• Journal of the Korea Institute of Construction Safety
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• v.2 no.1
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• pp.36-44
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• 2019

$21^{st}$ century is digitally civilized era. Technologies such as AI, Iot, Big Data, Mobile and etc makes this era digitally advanced. These advancement of the technology greatly impacted detection range of the radar. Human's eye sight can see about 20Km and hear 20 ~ 20000 Hz. These limitations can be overcome using radar. This radar technology is used in military, aircraft, ship, vehicle and etc. to replace human eye. However, radar technology is capable of making False Alarm Rate. This document will propose the fix of these problems. Radar's distortion includes beam refraction, diffraction and reflection. These inaccurate data result in deterioration of human judgements and my cause various casualties and damages. Radar goes through annual testing to test how many false alarm is being produced. Normal radar usually makes 10 to 20 False alarms. In emergency situation, if operator were to follow this false alarm, this might result in following false object or take 12 more seconds to follow the right object. This problem can be overcome by using different radar data from different places and angles. This helps reduces False Alarm rate and track the object twice as fast.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.701-709
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• 2019

Recently, heart rate signal, which is one of biological signals, have been used in various fields related to healthcare. Conventionally, most of the proposed heart rate signal detection methods are contact type methods, but there is a problem of discomfort that the subject have to contact with the device. In order to solve the problem, detection study by non-contact method has been progressed recently. The detected heart rate signal can be used for finger vein liveness detection and various application using heart rate. In this paper, we propose a method to obtain heart rate signal by using finger vein imaging system. The proposed method detected the signal from the changes of the brightness value in the time domain of the infrared finger vein images and converted it into the frequency domain using the image processing algorithm. After the conversion, we removed the noise not related to the heart rate signal through band-pass filtering. In order to evaluate the accuracy of the signal, we analyzed the correlation with the signal obtained simultaneously with the finger vein acquisition device and contact type PPG sensor approved by KFDA. As a result, it was possible to confirm that the heart rate signal detected in non-contact method through the finger vein image coincides with the waveform of actual heart rate signal.

• Progress in Medical Physics
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• v.14 no.4
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• pp.211-217
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• 2003

The Principal component analysis (PCA) is a well-known data analysis method that is useful in linear feature extraction and data compression. The PCA is a linear transformation that applies an orthogonal rotation to the original data, so as to maximize the retained variance. PCA is a classical technique for obtaining an optimal overall mapping of linearly dependent patterns of correlation between variables (e.g. neurons). PCA provides, in the mean-squared error sense, an optimal linear mapping of the signals which are spread across a group of variables. These signals are concentrated into the first few components, while the noise, i.e. variance which is uncorrelated across variables, is sequestered in the remaining components. PCA has been used extensively to resolve temporal patterns in neurophysiological recordings. Because the retinal signal is stochastic process, PCA can be used to identify the retinal spikes. With excised rabbit eye, retina was isolated. A piece of retina was attached with the ganglion cell side to the surface of the microelectrode array (MEA). The MEA consisted of glass plate with 60 substrate integrated and insulated golden connection lanes terminating in an 8${\times}$8 array (spacing 200 $\mu$m, electrode diameter 30 $\mu$m) in the center of the plate. The MEA 60 system was used for the recording of retinal ganglion cell activity. The action potentials of each channel were sorted by off­line analysis tool. Spikes were detected with a threshold criterion and sorted according to their principal component composition. The first (PC1) and second principal component values (PC2) were calculated using all the waveforms of the each channel and all n time points in the waveform, where several clusters could be separated clearly in two dimension. We verified that PCA-based waveform detection was effective as an initial approach for spike sorting method.

• The Journal of the Acoustical Society of Korea
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• v.36 no.5
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• pp.293-299
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• 2017

Small unmanned platforms maneuvering underwater are the key naval future forces, utilized as the asymmetric power in war. As a method of detecting and identifying such platforms, we introduce a property estimation technique based on an iterative numerical analysis. The property estimation technique can estimate not only the position of a target but also its physical properties. Moreover, it will have a potential in detecting and classifying still target or multiple targets. In this study, we have conducted the property estimation of an small underwater target using the data acquired from the lake experiment. As a result, it shows that the properties of a small platform may be roughly estimated from the in site data even using one channel.

• Publications of The Korean Astronomical Society
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• v.22 no.2
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• pp.43-54
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• 2007

Many gravitational wave detectors are now being built or under operation throughout the world. In particular, LIGO has taken scientific data several times, although current sensitivity is not sufficient to detect the weak signals routinely. However, the sensitivities have been improving steadily over past years so that the real detection will take place in the near future. Data analysis is another important area in detecting the gravitational wave signal. We have carried out the basic research in order to implement data analysis software in Korea@home environment. We first studied the LIGO Science Collaboration Algorithm Library(LAL) software package, and extracted the module that can generate the virtual data of gravitational wave detector. Since burst sources such as merging binaries of neutron stars and black holes are likely to be detected first, we have concentrated on the simulation of such signals. This module can generate pure gravitational wave forms, noise suitable for LIGO, and combination of the signal and noise. In order to detect the gravitational signal embedded in the noisy data, we have written a simple program that employs 'matched filtering' method which is very effective in detecting the signal with known waveform. We found that this method works extremely well.