• Journal of Institute of Control, Robotics and Systems
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• v.7 no.4
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• pp.304-308
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• 2001

The increase of video data makes the demand of efficient retrieval, storing, and browsing technologies necessary. In this paper, a video segmentation method (scene change detection method, or shot boundary detection method) for the development of such systems is proposed. For abrupt cut detection, inter-frame similarities are computed using luminance and edge histograms and a cut is declared when the similarities are under th predetermined threshold values. A gradual scene change detection is based on the similarities between the current frame and the previous shot boundary frame. A correlation method is used to obtain universal threshold values, which are applied to various video data. Experimental results show that propose method provides 90% precision and 98% recall rates for abrupt cut, and 59% precision and 79% recall rates for gradual change.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3050-3065
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• 2016

Neural networks (NNs) are extensively used in applications requiring signal classification and regression analysis. In this paper, a NN based threshold selection algorithm for 60 GHz millimeter wave (MMW) time of arrival (TOA) estimation using an energy detector (ED) is proposed which is based on the skewness, kurtosis, and curl of the received energy block values. The best normalized threshold for a given signal-to-noise ratio (SNR) is determined, and the influence of the integration period and channel on the performance is investigated. Results are presented which show that the proposed NN based algorithm provides superior precision and better robustness than other ED based algorithms over a wide range of SNR values. Further, it is independent of the integration period and channel model.

• Proceedings of the Korean Nuclear Society Conference
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• 2004.05a
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• pp.157-157
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• 2004

• Proceedings of the Korean Nuclear Society Conference
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• 2003.10a
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• pp.135.2-135.2
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• 2003

• Journal of the Korean Society of Physical Medicine
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• v.12 no.4
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• pp.39-46
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• 2017

PURPOSE: The effectiveness of the stretching to increase the range of motion of the joint, reduce the risk of injury, enhance athletic performance or decrease post exercise muscle soreness. This study was to compare the effect of the stretching method applied on the shortened hamstring muscle for flexibility, strength, pressure pain threshold value and muscle tone. METHODS: This study is a two-group pretest- posttest design. Fifty-four healthy young adults were randomly assigned to a vibration-assisted stretching group (VASG, n=27) or a static stretching group (SSG, n=27). Participants performed each stretch in 4 sets of 30 seconds each. A 30-second break time was provided between the sets. The range of motion, strength, pressure pain threshold values and muscle tone of the hamstring muscle were measured to compare the effects of the stretching methods. RESULTS: Both the VASG and the SSG participants showed significant improvement in the range of motion and strength (p<.05); however, the increase in the VASG was significantly higher than that in the SSG (p<.05). The pressure pain threshold values and muscle tone were significantly decreased only in the VASG (p<.05). CONCLUSION: These findings indicate that vibration-supported stretching is an effective intervention for people with hamstring shortening, with high pain level and muscle tone decrease.

• Journal of Korean Ophthalmic Optics Society
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• v.2 no.1
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• pp.1-8
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• 1997

When a ferroelastic domain of ${\beta}-Tb_2(MoO_4)_3$ single crystal is switched from $S_k$ state to $S_p$ state by external force, the formulae that can calculate relativistic displacement of the lattice point and distribution of ferroelastic switching force were derived by this study. The formulae that can calculate threshold switching force in any direction were derived from the conservation law of enthalpy and measured value of threshold switching force in specific direction. Theoretical values of threshold switching force were in accord with measured values at (${\theta}=90^{\circ}$, ${\phi}=15^{\circ}$), (${\theta}=90^{\circ}$, ${\phi}=30^{\circ}$), (${\theta}=90^{\circ}$, ${\phi}=45^{\circ}$), (${\theta}=90^{\circ}$, ${\phi}=60^{\circ}$), (${\theta}=90^{\circ}$, ${\phi}=75^{\circ}$).

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.297-302
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• 2004

In this paper, the 3-D shape description for the objects with the cone ridge and valley surfaces, and the corresponding threshold value selection for surface classification are considered. The existing method based on the mean and Gaussian curvatures(H and K) of differential geometries cannot properly describe cone primitives, which are some of the most common objects in the real world. Also the existing method for surface classification based on the sign values of H and K has Problems in practical applications. For this, cone surface shapes are classified cone ridges and cone valleys are derived from surfaces using the fact that H values are constant case of cylinder surfaces and variable for cone surfaces, respectively. Also threshold value selection for surface classification from a statistical point of view is proposed. The effectiveness of the proposed methods are verified through experiments.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.835-844
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• 2010

Tools for statistical analysis of extreme values include the classical annual maximum method, the modern threshold method and variants improving the second one. While the annual maximum method is to t th generalized extreme value distribution to the annual maxima of a time series, the threshold method is to the generalized Pareto distribution to the excesses over a high threshold from the series. In this paper we deal with the Poisson-GPD method, a variant of the threshold method with a further assumption that the total number of exceedances follows the Poisson distribution, and apply it to the daily percentage increases and decreases computed from the spot prices of West Texas Intermediate, which were collected from January 4th, 1988 until December 31st, 2009. According to this analysis, the distribution of daily percentage increases as well as decreases turns out to have a heavy tail, unlike the normal distribution, which coincides well with the general phenomenon appearing in the analysis of lots of nowaday nancial data.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.9
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• pp.1407-1414
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• 2018

Objective: The aim of this study was to estimate (co) variance components and genetic parameters for categorical carcass traits using Bayesian inference via mixed linear and threshold animal models in Anglonubian goats. Methods: Data were obtained from Anglonubian goats reared in the Brazilian Mid-North region. The traits in study were body condition score, marbling in the rib eye, ribeye area, fat thickness of the sternum, hip height, leg perimeter, and body weight. The numerator relationship matrix contained information from 793 animals. The single- and two-trait analyses were performed to estimate (co) variance components and genetic parameters via linear and threshold animal models. For estimation of genetic parameters, chains with 2 and 4 million cycles were tested. An 1,000,000-cycle initial burn-in was considered with values taken every 250 cycles, in a total of 4,000 samples. Convergence was monitored by Geweke criteria and Monte Carlo error chain. Results: Threshold model best fits categorical data since it is more efficient to detect genetic variability. In two-trait analysis the contribution of the increase in information and the correlations between traits contributed to increase the estimated values for (co) variance components and heritability, in comparison to single-trait analysis. Heritability estimates for the study traits were from low to moderate magnitude. Conclusion: Direct selection of the continuous distribution of traits such as thickness sternal fat and hip height allows obtaining the indirect selection for marbling of ribeye.

• Journal of the Korean Geophysical Society
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• v.2 no.2
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• pp.143-152
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• 1999

We have studied a denoising technique involving wavelet transform for improving the quality of geophysical data during the preprocessing stage. To assess the effectiveness of this technique, we have made synthetic data contaminated by random noises and compared the results of denoising with those obtained by conventional low-pass filtering. The low-pass filtering of the sinusoidal signal having a sharp discontinuity between the first and last sample values shows apparent errors related to Gibbs' phenomena. For the case of bump signal, the low-pass filtering induces maximum errors on peak values by removing some high-frequency components of signal itself. The wavelet transform technique, however, denoises these signals with much less adverse effects owing to its pertinent properties on locality of wavelet and easy discrimination of noise and signal in the wavelet domain. The field data of gravity tide are denoised by using soft threshold, which shrinked all the wavelet coefficients toward the origin, and the G-factor is determined by comparing the denoised data and theoretical data.