• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.227-244
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• 2015

Synthetic Aperture Radar is able to provide images of wide coverage in day, night, and all-weather conditions. Recently, as the SAR image resolution improves up to the sub-meter level, their applications are rapidly expanding accordingly. Especially there is a growing interest in the use of geographic information of high resolution SAR images and the change detection will be one of the most important technique for their applications. In this paper, an automatic threshold tracking and change detection algorithm is proposed applicable to high-resolution SAR images. To detect changes within SAR image, a reference image is generated using log-ratio operator and its amplitude distribution is estimated through K-S test. Assuming SAR image has a non-gaussian amplitude distribution, a generalized thresholding technique is applied using Kittler and Illingworth minimum-error estimation. Also, MoLC parametric estimation method is adopted to improve the algorithm performance on rough ground target. The implemented algorithm is tested and verified on the simulated SAR raw data. Then, it is applied to the spaceborne high-resolution SAR images taken by Cosmo-Skymed and KOMPSAT-5 and the performances are analyzed and compared.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.884-891
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• 2018

In this paper, we propose an automatic earthquake P-wave detection algorithm based on the variations of the impact momentum derived from the seismic acceleration signals. The amount of change in the impact momentum induced by the acceleration refers to the influence of buildings or facilities on the earthquake, The proposed algorithm can effectively detect the seismic P-wave by simultaneously considering the amplitude and the frequency change of the seismic wave when the earthquake occurs. Computer simulations using the observed seismic signals were performed to evaluate the validity of the induced impact momentum variation and the superiority of the proposed algorithm.

• 한국기계연구소 소보
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• s.19
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• pp.61-68
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• 1989

As the system monitoring technology become required in order to improve the system performance and the productivity, we’ve studied to the detection for the tool wear and the tool breakage using AE sensors that is able to detection of generated high frequency stress pulse at cutting. The detection system is consist of a sensing part, a amplifier part, a signal processing part, and a analysis & output part. The moment (a rms and a kurtosis) of statistical method is used for analysis of AE singnal. The experiment are carried out in a CNC lathe. In this study, we achieved that the amplitude level of the AE signal and statistical moments was largely changed as the tool failure. The change rate of Kurtosis was especially large, but the change rate of the rms was small.

• Journal of Biomedical Engineering Research
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• v.28 no.5
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• pp.665-675
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• 2007

The morphological change of ECG is the important diagnostic parameter to finding the malfunction of a heart. Generally ST segment deviation is concerned with myocardial abnormality. The aim of this study is to detect the change of ST in shape using a polynomial approximation method and the reference ST type. The developed algorithm consists of feature point detection, ST level detection and ST shape classification. The detection of QRS complex is accomplished using it's the morphological characteristics such as the steep slope and high amplitude. The developed algorithm detects the ST level change, and then classifies the ST shape type using the polynomial approximation. The algorithm finds the least squares curve for the data between S wave and T wave in ECG. This curve is used for the classification of the ST shapes. ST type is classified by comparing the slopes of the specified points between the reference ST set and the least square curve. Through the result from the developed algorithm, we can know when the ST level change occurs and what the ST shape type is.

• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.320-326
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• 2009

This paper proposed a new magnetic field detection algorithm to detect metal pieces in food producing processes. This algorithm can detect mixed metal pieces by sensing magnetic field. Some metal pieces are passed through an over-current circuit to magnetize them. The magnetic field sensor can detect the change in the magnetic field on theconveyor belt caused by the flow of the metal pieces in the food product. However, such a method detects the output of signals that change their amplitude and phase according to the movement of the conveyor belt with the food product, in which the equilibrium of the positive signal that is created in the receiver coil loses its balance due to the magnetized material. This includes not only the signal elements resulting from the effect of the alternating magnetic fields of the mixed metals, but also the signal elements resulting from the effect of the alternating magnetic fields of the examined object itself.

• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.351-360
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• 2013

Harmonic analysis enables to characterize patterns of variation in MODIS NDVI time series data and track changes in ground vegetation cover. In harmonic analysis, a periodic phenomenon of time series data is decomposed into the sum of a series of sinusoidal waves and an additive term. Each wave is defined by an amplitude and a phase angle and accounts for the portion of variance of complex curve. In this study, harmonic analysis was explored to tract ground vegetation variation through time for land-cover vegetation change detection. The process also enables to reconstruct observed time series data including various noise components. Harmonic model was tested with simulation data to validate its performance. Then, the suggested change detection method was applied to MODIS NDVI time series data over the study period (2006-2012) for a selected test area located in the northern plateau of Korean peninsula. The results show that the proposed approach is potentially an effective way to understand the pattern of NDVI variation and detect the change for long-term monitoring of land cover.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.387-390
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• 1997

Electrogastrography(EGG), the cutaneous recording of the myoelectrical activity of the stomach using surface electrodes, is attractive due to its non-invasiveness. We propose feasible methods to detect tile gastric contraction by vector analysis of the surface EGG signals obtained from three paired electrodes. The amplitude and direction of the calculated EGG vector were analyzed and compared with the gastric contraction signals such as the strain gauge signal from the gastric serosa in dog. From the vector analysis of the EGG signal, we found a typical change of the amplitude and direction of the EGG vector, which can indicate occurrences of the gastric contraction.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1999.11a
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• pp.233-239
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• 1999

The feasibility of an ultrasonic technique using a pulse-echo method of normal-incident compressional waves was evaluated for its sensitivity to the worn surface and near surface damage due to wear. Worn surfaces were generated at various oscillation frequency under a given load and amplitude and these surface were in situ monitored using a ultrasonic wave detection system. Analysis of the ultrasonic waves received from the worn surface revealed a close relationship between the surface and near-surface damage and the maximum echo-amplitude of the compressional waves. The ultrasonic technique was successful in assessing the level of severity of the worn surface in real time during the wear process. It is also shown that the wear depth can be easily measured by the calculation of change of the specimen thickness based on the wave speed measured for the specimen medium.

• Tribology and Lubricants
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• v.16 no.5
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• pp.351-356
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• 2000

The feasibility of an ultrasonic technique using a pulse-echo method of normal-incident compressional waves was evaluated for its sensitivity to the worn surface and near surface damage due to wear. Worn surfaces were generated at various oscillation frequency under a given load and amplitude and these surface were in situ monitored using a ultrasonic wave detection system. Analysis of the ultrasonic waves received from the worn surface revealed a close relationship between the surface and near-surface damage and the maximum echo-amplitude of the compressional waves. The ultrasonic technique was successful in assessing the level of severity of the worn surface in real time during the wear process. It is also shown that the wear depth can be easily measured by the calculation of change of the specimen thickness based on the wave speed measured for the specimen medium.

• Journal of IKEEE
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• v.25 no.4
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• pp.689-696
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• 2021

In this paper, in order to apply Prognostics and Health Management(PHM) to an electronic system or circuit, a circuit capable of detecting and predicting defect characteristics inside the system or circuit is implemented, and the results are described. In the previous study, we demonstrated that the frequency of the amplitude of S-parameter changed as the circuit defect progressed. These characteristics were measured by network analyser. but in this study, even if the same defect detection method is used, a circuit is proposed to check the progress of the defect, the remaining time, and the occurrence of the defect without large measurement devices. The circuit is designed to detect the change in impedance that generates changes of S-parameter, and it is verified through simulation using the measurement results of Bond-wires.