• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.103-108
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• 1999

The aim of the work described in this paper is to develop a complex underground acoustic system which detects and localizes the origin of an underground hammering sound using an array of hydrophones located about loom underground. Three different methods for the sound localization will be presented, a time-delay method, a power-attenuation method and a hybrid method. In the time-delay method, the cross correlation of the signals received from the array of sensors is used to calculate the time delays between those signals. In the power-attenuation method, the powers of the received signals provide a measure of the distances of the source from the sensors. In the hybrid method, both informations of time-delays and power-ratios are coupled together to produce better performance of position estimation. A new acoustic imaging technique has been developed for improving the hybrid method. This new acoustic imaging method shows the multi-dimensional distribution of the normalized cost function, so as to indicate the trend of the minimizing direction toward the source location. For each method the sound localization is carried out in three dimensions underground. The distance between the true and estimated origins of the source is 28m for a search area of radius 250m.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.5
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• pp.277-285
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• 2016

Moving object detection system has been an emerging research field in various advanced driver assistance systems (ADAS) and surveillance system. In this paper, we propose two optical flow based moving object detection methods at dynamic scenes. Both proposed methods consist of three successive steps; pre-processing, foreground segmentation, and post-processing steps. Two proposed methods have the same pre-processing and post-processing steps, but different foreground segmentation step. Pre-processing calculates mainly optical flow map of which each pixel has the amplitude of motion vector. Dense optical flows are estimated by using Farneback technique, and the amplitude of the motion normalized into the range from 0 to 255 is assigned to each pixel of optical flow map. In the foreground segmentation step, moving object and background are classified by using the optical flow map. Here, we proposed two algorithms. One is Gaussian mixture model (GMM) based background subtraction, which is applied on optical map. Another is adaptive thresholding based foreground segmentation, which classifies each pixel into object and background by updating threshold value column by column. Through the simulations, we show that both optical flow based methods can achieve good enough object detection performances in dynamic scenes.

• Bulletin of the Korean Chemical Society
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• v.24 no.2
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• pp.205-208
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• 2003

Laser-induced Raman spectroscopy has been utilized to demonstrate its feasibility for studying the kinetics of imine formation in chloroform solvent. The imine formation, by the nucleophilic addition of primary amine to the carbonyl group of ketone, has been monitored at ten minute intervals for eight hours. The intensity of the C=O stretching mode at 1684 $cm^{-1}$ was measured to determine the rate constant of the reaction. In order to correct the sample-to-sample fluctuations in Raman peak area, this peak was normalized to the C-Cl bending peak at 666 $cm^{-1}$. By the peak area change during the course of reaction, the second order rates at three different temperatures have been determined. The substituent effects on the π conjugations of imine product have also been investigated. On the basis of Raman frequency shifts, the delocalization properties of the aromatic system modified by substitution of a hydrogen atom with -Cl and $-CH_3O$ groups could be clearly understood.

• Journal of Oriental Neuropsychiatry
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• v.13 no.2
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• pp.107-119
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• 2002

This study was performed to evaluate the effects of Koamsimsinwhan (without Cinnabarite) on depression in CMS-treated rats. Rats of trial groups were exposured to chronic mild unpredictable stress for 4 weeks. These CMS-treated rats were stratified into Koamsimsinwhan(without Cinnabarite) group and vehicle(non-drug) group. And there were control rats excluding both CMS and Koamsimsinwhan(without Cinnabarite). Forced swimming test, general activity test and immunohistochemical test(measuring the level of manifestation of c-Fos in PVN) were executed to evaluate the effects of Koamsimsinwhan(without Cinnabarite) on depression after 4 weeks of CMS treatment. The results were as follows 1. In FST, depression was induced from CMS treatment and was supressed with Koamsimsinwhan(without Cinnabarite). 2. The increased activity of nerve cell in PVN, which refers to stress, was induced from CMS treatment and normalized with Koamsimsinwhan (without Cinnabarite).

• Journal of Environmental Science International
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• v.25 no.12
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• pp.1653-1660
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• 2016

Drought is a reoccurring worldwide natural hazard that affects not only food production but also economics, health, and infrastructure. Drought monitoring is usually performed with precipitation-based indices without consideration of the actual state and amount of the land surface properties. A drought index based on the actual evapotranspiration can overcome these shortcomings. The severity of a drought can be quantified by making a spatial map. The procedure for estimating actual evapotranspiration is costly and complicated, and requires land surface information. The possibility of utilizing drone-driven remotely sensed data for actual evapotranspiration estimation was analyzed in this study. A drone collected data was used to calculate the normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI). The spatial resolution was 10 m with a grid of $404{\times}395$. The collected data were applied and parameterized to an actual evapotranspiration estimation. The result shows that drone-based data is useful for estimating actual evapotranspiration and the corresponding drought indices.

• Structural Engineering and Mechanics
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• v.30 no.2
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• pp.177-190
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• 2008

Material failure behavior is generally dependent on loading rate. Especially in brittle and quasi-brittle materials, rate dependent material behavior can be significant. Empirical formulations are often used to predict the rate dependency, but such methods depend on extensive experimental works and are limited by practical constraints of physical testing. Numerical simulation can be an effective means for extracting knowledge about rate dependent behavior and for complementing the results obtained by testing. In this paper, the failure behavior of a brittle material under different loading rates is simulated by molecular dynamics analysis. A notched specimen is modeled by sub-million particles with a normalization scheme. Lennard-Jones potential is used to describe the interparticle force. Numerical simulations are performed with six different loading rates in a direct tensile test, where the loading velocity is normalized to the ratio of the pseudo-sonic speed. As a consequence, dynamic features are achieved from the numerical experiments. Remarkable failure characteristics, such as crack surface interaction/crack arrest, branching, and void nucleation, vary in case of the six loading cases. These characteristics are interpreted by the energy concept approach. This study provides insight into the change in dynamic failure mechanism under different loading rates.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.55-60
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• 2000

Constant ${\Delta}K$ fatigue crack growth tests were performed applying an intermediate multiple overload for SM45C steel. The purpose of the present study is to investigate the effects of specimen thickness at various baseline stress intensity levels$({\Delta}K_b)$, overload application frequency(a/W) and overload application frequency$(OL_{HZ})$ on fatigue crack growth retardation behavior. The principal results are summarized as follows. The amount of retardation for a given ${\Delta}K_b$ level is increased with increasing the baseline stress intensity level in all specimen thickness. The normalized minimum crack growth rate is increased with increasing the specimen thickness, except for ${\Delta}K=45MPa \sqrt m$. The retardation cycle is decreased with increasing the overload application position and increased with the overload application frequency.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.736-746
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• 2016

In this paper, we propose an automatic prostate cancer detection method using position, signal intensity and texture feature based on SVM in multi-parametric MR images. First, to align the prostate on DWI and ADC map to T2wMR, the transformation parameters of DWI are estimated by normalized mutual information-based rigid registration. Then, to normalize the signal intensity range among inter-patient images, histogram stretching is performed. Second, to detect prostate cancer areas in T2wMR, SVM classification with position, signal intensity and texture features was performed on T2wMR, DWI and ADC map. Our feature classification using multi-parametric MR imaging can improve the prostate cancer detection rate on T2wMR.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.611-614
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• 2012

Space-Time Block Code (STBC) is a simple transmit diversity scheme mitigating detrimental effects of fading channel. However, STBC receivers require channel knowledge and suffer from inaccurate channel estimation. Differential Space-Time Modulation (DSTM) renders the receiver a choice of coherent detection or non-coherent detection, depending on the availability of the channel information. Based on the simulated BER performances of these two schemes over various normalized Doppler frequency scenarios using LTE-like parameters, a benefit of adaptively switching the receiver type is investigated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.385-388
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• 2013

In this paper, we show the weakness of the image matching method by using MPEG-7 EHD(Edge Histogram Descriptor) and suggest how to improve this weakness by using image normalization. EHD algorithm is an image matching technique that collects edge's slope of distribution and same distribution. However, the EHD error rate is high because EHD is sensitive for changes of object distortion and rotation that will be matched. We improve matching performance by accurately extract edge information in image by using normalization. We compare and analyze the normalized EHD algorithm by using distortion and rotation and it shows robustness for changes of the size and rotation.