• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1992년도 춘계학술대회
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• pp.121-122
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• 1992

We present a new EEG waveform detection method, based on the search of distinctive line-segments. The method is based on the assumption that EEG waveform morphology is characterized by a sequence of its distinctive line-segments and their structural features. In this method, the distinctive line segments are first searched for, and the structural feature analysis is performed on the found line-segment sequence. Experiments of detecting epileptic spikes are performed on four different subjects.

• 대한의용생체공학회:의공학회지
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• 제39권2호
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• pp.69-79
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• 2018

The present study proposes an algorithm that can discriminate between normal subjects and paroxysmal atrial fibrillation (PAF) patients, which is conducted using electrocardiogram (ECG) without PAF events. For this, time-domain features and random forest classifier are used. Time-domain features are obtained from Poincare plot, Lorenz plot of ${\delta}RR$ interval, and morphology analysis. Afterward, three features are selected in total through feature selection. PAF patients and normal subjects are classified using random forest. The classification result showed that sensitivity and specificity were 81.82% and 95.24% respectively, the positive predictive value and negative predictive value were 96.43% and 76.92% respectively, and accuracy was 87.04%. The proposed algorithm had an advantage in terms of the computation requirement compared to existing algorithm, so it has suggested applicability in the more efficient prediction of PAF.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.736-739
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• 2006

While hyperspectral data are very rich in information, their processing poses several challenges such as computational requirements, noise removal and relevant information extraction. In this paper, the application of advanced scale-space filtering to selected hyperspectral bands was investigated. In particular, a pre-processing tool, consisting of anisotropic diffusion and morphological leveling filtering, has been developed, aiming to an edge-preserving smoothing and simplification of hyperspectral data, procedures which are of fundamental importance during feature extraction and object detection. Two scale space parameters define the extent of image smoothing (anisotropic diffusion iterations) and image simplification (scale of morphological levelings). Experimental results demonstrated the effectiveness of the developed scale space filtering for the enhancement and smoothing of hyperspectral remote sensing data and their advantage against watershed over-segmentation problems and edge detection.

• 천문학회지
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• 제42권3호
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• pp.33-37
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• 2009

We propose a diagnostic that can resolve the planet/binary degeneracy of central perturbations in caustic-crossing high-magnification microlensing events. The diagnostic is based on the difference in the morphology of perturbation inside the central caustics induced by a planet and a wide-separation binary companion. We find that the contours of excess exhibit a concentric circular pattern around the caustic center for the binary-lensing case, while the contours are elongated or off-centered for the planetary case. This difference results in the distinctive features of the individual lens populations in the residual of the trough region between the two peaks of the caustic crossings, where the shape of the residual is symmetric for binary lensing while it tends to be asymmetric for planetary lensing. We determine the ranges of the planetary parameters for which the proposed diagnostic can be used. The diagnostic is complementary to previously proposed diagnostics in the sense that it is applicable to caustic-crossing events with small finite-source effect.

• 천문학회지
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• 제40권3호
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• pp.61-65
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• 2007

The 2-1 and 5-4 transitions of SiO have been observed toward the Sgr B2 region, including the Principal Cloud(the GMC containing Sgr B2(M)) and its surroundings. The morphology and velocity structure of the SiO emission show a close resemblance with the HNCO Ring feature, identified by Minh & Irvine(2006), of about 10 pc in diameter, which may be expanding and colliding with the Principal Cloud. Three SiO clumps have been found around the Ring, with total column densities $N_{SiO}{\sim}1{\times}10^{14}cm^{-2}$ at the peak positions of these clumps. The fractional SiO abundance relative to $H_2$ has been estimated to be ${\sim}(0.5-1){\times}10^{-9}$, which is about two orders of magnitude larger than the quiet dense cloud values. Our SiO observational result supports the existence of an expanding ring, which may be triggering active star formations in the Principal Cloud.

• 대한전자공학회논문지
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• 제25권7호
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• pp.759-766
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• 1988

the effect of heat treatment in oxygen ambient on the nucleation and growth of oxidation induced stacking faults(OSF) in n-type(100)silicon wafer has been investigated. The growth of OSF is determind as a function of oxygen concentration in silicon wafer, heat treatment time and temperature, and the activation energy for the growth of OSF can be obtained from the growth kinetics. The activation energies are respectively 2.66 eV for dry oxidation and 2.37 eV for wet oxidation. In this paper, we have also studied the structural feature of OSF with the comparison of optical microscopic morphology and crystalline structure.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1997년도 제26회 추계학술대회
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• pp.135-144
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• 1997

This wear debris can be harvested from the lubricants of operating machinery and its morphology is directly related to the damage to the interacting surfaces from which the particles originated. The morphologies of the wear particles are therefore directly indica- rive of wear processes occuring in machinery and their severity. The neural network was applied to identify wear debris generated from the lubricated moving system. The four parameter(50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction condition of five values(material 3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameter learned. The three kinds of the wear debris had a different pattern characteristic and recognized the friction condition and materials very well by neural network. We dicuss how the network determines difference in wear debris feature, and this approach can be applied to condition diagnosis of the lubricated moving system.

• 한국생산제조학회지
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• 제7권5호
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• pp.92-97
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• 1998

The morpholgies of the wear particles are directly indicative of wear processes occuring in machinery and their severity. The neural network was applied to identify wear debris generated from the machine driving system. The four parameters(50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction condition of five values(material 3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameters learned. The three kinds of the wear debris had a different patter characteristic and recognized the friction condition and materials very well by artificial neural network. We discussed how the network determines differencee in wear debris feature, and this approach can be applied to foreseeability and decisio for moving condition of the Machine driving system.

• 소성∙가공
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• 제19권5호
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• pp.320-324
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• 2010

Multi-Layer Ceramic Circuit(MLCC) in the face of thousands of fine pitch multi hole is processed. However, the fine pitch multi hole has a size of only a few micrometers. Therefore, in order to curtail the measurement time and reduce error, the image processing measurement method is required. So, we proposed an image processing measurement algorithm which is required to accurately measure the fine pitch multi hole. The proposed algorithm gets image of the fine pitch multi hole, extracts object from the image by morphological process, and extracts the parameters of its position and feature by edge detecting process. In addition, we have used the sub-pixel algorithm to improve accuracy. As a result, the proposed algorithm shows 97% test-retest measurement reliability within 2 ${\mu}m$. We found that the algorithm was wellsuited for measuring the fine pitch multi hole.

• Macromolecular Research
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• 제10권1호
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• pp.44-48
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• 2002

The supermolecular structures of poly(ethylene terephthalate) (PET), poly(ethylene 2,6-naphthalate) (PEN), and their blend were investigated with optical microscopy and small angle light scattering. With increasing the crystallization temperature, incomplete spherulitic texture was developed for the PET samples. At a high crystallization temperature of 220 $^{\circ}C$, the light scattering pattern represented a random collection of uncorrelated lamellae. The general morphological appearances for the PEN samples were similar to that of the PET. A notable feature was that the spherulites of the PEN formed at 200 $^{\circ}C$ showed regular concentric bands arising from a regular twist in the radiating lamellae. The spherulitic morphology of the PET/PEN blend was largely influenced by the changes of the sequence distribution in polymer chains determined by the level of transesterifcation. The increased sequential irregularity in the polymer chains via transesterification caused a morphological transition from a regular folded crystallite to a tilted lamellar crystallite.