• Fibers and Polymers
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• v.2 no.2
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• pp.81-85
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• 2001

The effects of rate of phase separation to ester interchange reactions and the repulsive pair interaction energy on the phase behavior in a phase-separated immiscible polyester blend are investigated using a Monte Carlo simulation method. The time evolution of structure factor and the degree of randomness are monitored as a function of homogenization time. When the phase separation is dominant over ester interchange reactions, the domain size slowly increases with homogenization time. However, when the pair interaction becomes less repulsive, the domain size does not significantly change with homogenization time. On the other hand, when ester interchange reactions are dominant over the phase separation, the homogenization proceeds without a change in the domain size. The higher the extent of phase separation, the lower the increasing rate of the DR. However, when the phase separation is sufficiently dominant, the effect of the extent of phase separation on the increasing rate of the degree of randomness become less significant.

• The Korean Journal of Ceramics
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• v.6 no.3
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• pp.262-266
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• 2000

We investigated the effect of the grain size on the photovoltaic current in (Pb$_{1-x}$La$_x$)TiO$_3$ceramics, and the photoinduced domain switching in (Pb$_{0.85}$La$_{0.15}$)TiO$_3$and BaTiO$_3$ceramics. These behaviors in ferroelectric ceramics were attributed to the grain boundary at which photoexcited electrons were trapped. As the charged grain boundary acted as an electro-potential barrier which impeded the movement of electrons, the photovoltaic current showed a peak at a critical grain size. The space charge field built by the electrons trapped at the grain bound-aries was accounted for the photoinduced domain switching, and AE experimental results support well this account.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.519-528
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• 2016

In order to achieve fast computational speed with good visual quality of output video, we propose a frequency domain based new fractal video compression scheme. Normalized cross correlation is used to find the structural self similar domain block for the input range block. To increase the searching speed, cross correlation is implemented in the frequency domain using FFT with one computational operation for all the domain blocks instead of individual block wise calculations. The encoding time is further minimized by applying rotation and reflection DFT properties to the IFFT of zero padded range blocks. The energy of overlap small size domain blocks is pre-computed for the entire reference frame and retaining the energies of the overlapped search window portion of previous adjacent block. Quadtree decompositions are obtained by using domain block motion compensated prediction error as a threshold to control the further partitions of the block. It provides a better level of adaption to the scene contents than fixed block size approach. The result shows that, on average, the proposed method can raise the encoding speed by 48.8 % and 90 % higher than NHEXS and CPM/NCIM algorithms respectively. The compression ratio and PSNR of the proposed method is increased by 15.41 and 0.89 dB higher than that of NHEXS on average. For low bit rate videos, the proposed algorithm achieve the high compression ratio above 120 with more than 31 dB PSNR.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.84-93
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• 2023

The supervised learning-based deep-learning seismic inversion techniques have demonstrated successful performance in synthetic data examples targeting small-scale areas. The supervised learning-based deep-learning seismic inversion uses time-domain wavefields as input and subsurface velocity models as output. Because the time-domain wavefields contain various types of wave information, the data size is considerably large. Therefore, research applying supervised learning-based deep-learning seismic inversion trained with a significant amount of field-scale data has not yet been conducted. In this study, we predict subsurface velocity models using Laplace-domain wavefields as input instead of time-domain wavefields to apply a supervised learning-based deep-learning seismic inversion technique to field-scale data. Using Laplace-domain wavefields instead of time-domain wavefields significantly reduces the size of the input data, thereby accelerating the neural network training, although the resolution of the results is reduced. Additionally, a large grid interval can be used to efficiently predict the velocity model of the field data size, and the results obtained can be used as the initial model for subsequent inversions. The neural network is trained using only synthetic data by generating a massive synthetic velocity model and Laplace-domain wavefields of the same size as the field-scale data. In addition, we adopt a towed-streamer acquisition geometry to simulate a marine seismic survey. Testing the trained network on numerical examples using the test data and a benchmark model yielded appropriate background velocity models.

• The Mathematical Education
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• v.55 no.3
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• pp.357-382
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• 2016

The purpose of this study was to report the effects of self-directed and self-regulated learning programs on elementary, middle, and high school students through meta-analysis of previous studies. For this research, 22 of previous studies were selected which were all conducted in the country, and calculated the effect size of 'standardized change of the mean difference' for many factors included in each research. The findings were as follows: first, the overall effect sizes of self-directed and self-regulated learning programs on elementary, middle, and high school students were .665 and .702 in the affective and cognitive domain, respectively, meaning that the self-directed and self-regulated learning programs had average or greater effects on elementary, middle, and high school students and exerted somewhat greater effects in the cognitive domain. Second, when the areas of moderating effects were divided into self-directed and self-regulated learning, the former and latter had more influences on the cognitive and affective domains, respectively. Third, the elementary school level recorded a larger effect size both in the affective and cognitive domains than the secondary school level. Fourth, the findings show that the characteristics of affective domain, "reflective thinking" and "self-confidence," recorded a very large effect size both at the elementary and secondary school levels. Finally, the programs were more effective when the application period was one to four weeks in the affective domain and more than four weeks in the cognitive domain. And, Significance and implications of this research were discussed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.21-27
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• 2019

The video compression standard required a processing technique for a high resoluion image and increased the coding size to increase the resolution of the image. Accurate motion estimation and increased coding size provide high accuracy and compression rate, but there is a problem of increased computational complexity. In this paper, we use DCT - based motion estimation in the frequency domain to reduce complexity. However, we found that the DCT and quantization process used in a general video encoder are applied to the frequency domain encoder, resulting in problems caused by the scaling process. Therfore, in this paper, we extract the scaling matrix that can be applied in the DCT step and resolve the, and improve the performance of motion estimation using increased coding size.

• Journal of the Korean Magnetics Society
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• v.6 no.3
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• pp.165-169
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• 1996

The relationship between grain size and number of magnetic domain walls for tertiary recrystallized ultra thin 3 % Si-Fe strips was investigated. It was found that the strips with different grain size can be produced by controlling the inserting speed of sample in annealing furnace. Though grain size of the stirip became smaller than 1mm, $B_{8}$ of high value above 1.95T was obtained. But $H_{c}$ increased with decaying the grain size. The magnetic domains and losses of the ultra thin grain oriented silicon steel with smaller grian size were observed. The eddy current losses of the strips were decreased with decreasing the grain size in high frequency range because strips with smaller grain have narrower magnetic domain wall spacings. But Hysteresis losses of the strips with smaller grain have high value in low frequency range. Therefore the iron loss of ultra thin grain oriented silicon steel could be controlled by the grain size. It was clarified that the minumum tatal loses depended on the exciting frequency and grain size.

• Journal of the Korea Convergence Society
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• v.7 no.5
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• pp.145-153
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• 2016

The purpose of this study was using a meta-analysis to estimate effect size ACT intervention program. Using a statistical method, meta-analysis has advantages that prove intervention's amount and direction. Meta-analysis facilitates comprehensive analysis. Through the data collection, 43studies were selected and 183 effect size were calculated as analysis objects. Using a 183 effect size, the overall effect size, Effect Size of categorical Factor, meta-regression result were suggested. The overall effect size of ACT program was 0.704. In the effect area of ACT, the affective domain had the largest effect size. Next were the cognitive domain, the behavioral domain. Analysis on gender of participant, mixed group had the largest effect size. Next were the female grouop, male group. Analysis on age of participant, adult group had the largest effect size. Next were the undergraduate grouop, adolescent group. Based on the findings, implications for future study were discussed.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.25-33
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• 2017

The purpose of this study was using a meta-analysis to estimate effect size of emotional intelligence program. Using a statistical method, meta-analysis has advantages that prove intervention's amount and direction. Meta-analysis facilitates comprehensive analysis. Through the data collection, 33studies were selected and 92 effect size were calculated as analysis objects. The overall effect size of emotional intelligence program was 0.839. Depend on subordinate scope, the emotional cognition had the largest effect size. Next were the understanding domain, application domain, the regulation domain and the expression domain. Analysis on age of participant, adult group had the largest effect size. Next were the elementary students group and the adolescent group. Based on the findings, implications for future study were discussed.

• Korean Journal of Mathematics
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• v.13 no.1
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• pp.113-122
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• 2005

We consider the iterative schemes for the large sparse linear system to solve partial differential equations. Using spectral radius of iteration matrices, the optimal relaxation parameters and good parameters can be obtained. With those parameters we compare the effectiveness of the SOR and SSOR algorithms. Applying Crank-Nicolson approximation, we observe the error distribution according to domain decomposition. The number of processors due to domain decomposition affects time and error. Numerical experiments show that effectiveness of SOR and SSOR can be reversed as time size varies, which is not the usual case. Finally, these phenomena suggest conjectures about equilibrium time grid for SOR and SSOR.