• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.2
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• pp.86-91
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• 2014

This paper compare with SNR performance of coherent integration and non-coherent integration in radar system. This paper to prevent distortion of transmit signal and radar return in radar system is used to pulsed waveform. This paper to estimate target detection range and to compare with SNR performance used to coherent integration performed before the envelope detector and non-coherent integration processed after the envelope detector. Through simulation, SNR performance of coherent integration and non-coherent integration were comparatively analyzed. SNR performance of coherent integration is good proof higher than non-coherent integration.

• ETRI Journal
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• v.42 no.2
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• pp.217-229
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• 2020

Long-term electroencephalography (EEG) monitoring is time-consuming, and requires experts to interpret EEG signals to detect seizures in patients. In this paper, we propose a novel automated method called adaptive slope of wavelet coefficient counts over various thresholds (ASCOT) to classify patient episodes as seizure waveforms. ASCOT involves extracting the feature matrix by calculating the mean slope of wavelet coefficient counts over various thresholds in each frequency subband. We validated our method using our own database and a public database to avoid overtuning. The experimental results show that the proposed method achieved a reliable and promising accuracy in both our own database (98.93%) and the public database (99.78%). Finally, we evaluated the performance of the method considering various window sizes. In conclusion, the proposed method achieved a reliable seizure detection performance with a short-term window size. Therefore, our method can be utilized to interpret long-term EEG results and detect momentary seizure waveforms in diagnostic systems.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.4
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• pp.327-334
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• 2010

This paper deals with a single-phase dynamic voltage restorer(DVR) with a quasi Z-source topology. The proposed system based on a single-phase quasi Z-source PWM ac-ac converter which have features such as the input voltage and output voltage are sharing ground, and input current operates in continuous current mode(CCM). For the detection of voltage sag-swell, peak voltage detection method is applied. Also, the circuit principles of the proposed system are described. During the 60% severe voltage sag and 30% voltage swell, the proposed system controls the adding or missing voltage and maintains the rated voltage of sinusoidal waveform at the terminals of the critical loads. Finally, PSIM simulation and experimental results are presented to verify the proposed concept and theoretical analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.476-483
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• 2009

Tracking and detecting targets by the microwave seeker is affected by the clutter reflecting from the earth's surface. In order to detect retreating targets in look-down scenario, which appear in the sidelobe clutter (SLC) region, in the microwave seeker of high pulse repetition frequency (HPRF) mode, it is necessary to understand statistical characteristics of the surface SLC. Statistical analysis of SLC has been conducted for several kinds of the surface using data obtained by the captive flight test of the microwave seeker in the HPRF mode. The probability density function (PDF) fitting is conducted for several kinds and conditions of the surface. PDFs and PDF parameters, which best describe statistical distribution of the SLC power, are estimated. By using the estimated PDFs and PDF parameters, analyses for setting the target-detection thresholds, which give a desired level of target-detection false alarm probability, are made. These analysis materials for statistical characteristics of SLC power and the target-detection threshold can be used in various fields, such as development of a target-detection method, the constant false alarm rate processing.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.395-401
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• 2023

Sound Event Detection (SED) aims to identify not only sound category but also time interval for target sounds in an audio waveform. It is a critical technique in field of acoustic surveillance system and monitoring system. Recently, various models have introduced through Detection and Classification of Acoustic Scenes and Events (DCASE) Task 4. This paper explored how to design optimal parameters of DenseNet based model, which has led to outstanding performance in other recognition system. In experiment, DenseRNN as an SED model consists of DensNet-BC and bi-directional Gated Recurrent Units (GRU). This model is trained with Mean teacher model. With an event-based f-score, evaluation is performed depending on parameters, related to model architecture as well as model training, under the assessment protocol of DCASE task4. Experimental result shows that the performance goes up and has been saturated to near the best. Also, DenseRNN would be trained more effectively without dropout technique.

• Journal of Korea Multimedia Society
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• v.16 no.10
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• pp.1147-1155
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• 2013

In this study, we designed and implemented a step detection analyzer that can compare and analyze the step detection rates and results among the step detection algorithms. The step detection analyzer converts 3-axes accelerometer data into continuous energy stream through SVM operation, shows the horizontal comparison among the step detection results for each step detection algorithms, and can make elemental detection analyses. For these processes, the step detection analyzer presents the continuous energy stream as energy waveform, checks the peak values and time location of the detected steps with step detection algorithms, and gives visual interface to get some possible causes in cases of step detection miss. It can also give the threshold graph for each algorithm to check the threshold value on missed cases directly and can help to get more appropriate threshold values or other adjustable parameters in step detection algorithm. This step detection analyzer can be applied efficiently on performance enhancement of step detection algorithm, on deciding an appropriate algorithm for a specific step counter system in the various step counter filed operations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.245-254
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• 2013

In oriental medicine, it is possible to classify and treat many diseases using the pulse wave detection system. Other problems may arise. As it is a very subjective way to analyze the pulse wave. One problem of the conventional pulse wave detection system is that the arterial pulse sensor is not located correctly at the radial artery. Threrefore measurement results can differ depending on the measurement position and the measurement procedure. This is mostly due to it's sensitivity to high reproducibility. In order to solve this problem this paper proposes an algorithm to analyze the weak pulse wave symptom and strong pulse wave symptom. It uses the portable pulse wave detection system which includes a Hall Sensor. As a final result, it analyzed the weak pulse wave symptom and strong pulse wave symptom by the SPSS statistics technique. It proves that N time (notch point time) and S Amp (rise waveform size) mean values are significantly different in 95% confidence interval.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.5
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• pp.485-492
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• 2009

The thermal fatigue crack(TFC) is one of the life-limiting mechanisms at the nuclear power plant operating conditions. In order to evaluate the structural integrity, various non-destructive test methods such as radiographic test, ultrasonic test and eddy current are used in the industrial field. However, these methods have restrictions that defect detection is possible after the crack growth. For this reason, acoustic emission testing(AET) is becoming one of powerful inspection methods, because AET has an advantage that possible to monitor the structure continuously. Generally, every mechanism that affects the integrity of the structure or equipment is a source of acoustic emission signal. Therefore the noise filtering is one of the major works to the almost AET researchers. In this study, acoustic emission signal was collected from the pipes which were in the successive thermal fatigue cycles. The data were filtered based on the results from previous experiments. Through the data analysis, the signal characteristics to distinguish the effective signal from the noises for the TFC were proven as the waveform difference. The experiment results provide preliminary information for the acoustic emission technique to the continuous monitoring of the structure failure detection.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.36 no.3
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• pp.186-194
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• 2000

bottom as a reference basis, some theoretical elements which form bottom echoes during acoustic survey of demersal fish were considered. A stable bottom detection method based on maximum voltage difference, which was not influenced by variable levels and waveform transformation. The method has been shown to be effective using in-situ bottom echo waveforms and computer simulation data. A comparison between near-bottom SV profiles acquired in Funka Bay, Hokkaido, of Japan, the East China Sea and the Yellow Sea, of Korea, with the threshold method and maximum differential voltage method, shows that the SV obtained with the maximum differential voltage method is 4-6 dB higher than those with threshold method within 2m from the bottom.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.3
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• pp.349-356
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• 2015

Remote monitoring partial discharge sensor, equipping with hybrid filter combining optical and electrical noise reduction capabilities and with signal integrating function to calculate total arc energy, was investigated. Hybrid filter showed insensitivity to fluorescent and incandescent lamps under simulated distribution panel condition. Signal integrating function showed selective detection capability corresponding to different arc energy levels, while convention arc sensor had difficulty to discriminate arc energy level due to bursty arc waveform and peak level detection characteristics. The sensor showed possibility for application to remote monitoring partial discharge sensor, since it detected arc energy level corresponding to normal open and close discharge in low voltage 100A MCCB at 2m distance.