• Asian-Australasian Journal of Animal Sciences
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• v.15 no.7
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• pp.925-931
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• 2002

Gibbs sampling algorithms were implemented to the multi-trait threshold animal models with any combinations of multiple binary, ordered categorical, and linear traits and investigate the amount of bias on these models with two kinds of parameterization and algorithms for generating underlying liabilities. Statistical models which included additive genetic and residual effects as random and contemporary group effects as fixed were considered on the models using simulated data. The fully conditional posterior means of heritabilities and genetic (residual) correlations were calculated from 1,000 samples retained every 10th samples after 15,000 samples discarded as "burn-in" period. Under the models considered, several combinations of three traits with binary, multiple ordered categories, and continuous were analyzed. Five replicates were carried out. Estimates for heritabilities and genetic (residual) correlations as the posterior means were unbiased when underlying liabilities for a categorical trait were generated given by underlying liabilities of the other traits and threshold estimates were rescaled. Otherwise, when parameterizing threshold of zero and residual variance of one for binary traits, heritability estimates were inflated 7-10% upward. Genetic correlation estimates were biased upward if positively correlated and downward if negatively correlated when underling liabilities were generated without accounting for correlated traits on prior information. Residual correlation estimates were, consequently, much biased downward if positively correlated and upward if negatively correlated in that case. The more categorical trait had categories, the better mixing rate was shown.

• Journal of the Korean Chemical Society
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• v.66 no.4
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• pp.278-283
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• 2022

Using the Kirkwood's method, the free energy of a binary lattice solution consisting of two identical interpenetrating sublattices, such as a simple cubic lattice or a body-centered cubic lattice, was calculated up to the tenth order of the reciprocal of absolute temperature. Using this, liquid-liquid coexistence curves and critical solution temperatures for the binary lattice solutions were calculated to quantitatively investigate the effect of non-random mixing of molecules. And it was shown that the coexistence curve of the simple cubic lattice solution was in good agreement with the Monte-Carlo computer simulation result.

• ETRI Journal
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• v.24 no.5
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• pp.373-380
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• 2002

This paper presents a new method for a visual cryptography scheme that uses phase masks and an interferometer. To encrypt a binary image, we divided it into an arbitrary number of slides and encrypted them using an XOR process with a random key or keys. The phase mask for each encrypted image was fabricated nuder the proposed phase-assignment rule. For decryption, phase masks were placed on any path of the Mach-Zehnder interferometer. Through optical experiments, we confirmed that a secret binary image that was sliced could be recovered by the proposed method.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.63-66
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• 2001

In this paper a binary image encryption technique and decryption system based on a joint transform correlator (JTC) are Proposed. In this method, a Fourier transform of the encrypted image is used as the encrypted data and a Fourier transform of the random phase is used as the key code. The original binary image can be reconstructed on a square law device, such as a CCD camera after the joint input is inverse Fourier transformed. The proposed encryption technique does not suffer from strong auto-correlation terms appearing in the output plane. Based on computer simulations, the proposed encryption technique and decoding system were demonstrated as adequate for optical security applications.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.250-254
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• 2010

As the number of input and fuzzy set of a fuzzy system increase, the size of the rule base increases exponentially and becomes unmanageable (curse of dimensionality). In this paper, tree architectures of fuzzy controller (TAFC) is proposed to overcome the curse of dimensionality problem occurring in the design of fuzzy controller. TAFC is constructed with the aid of AND and OR fuzzy neurons. TAFC can guarantee reduced size of rule base with reasonable performance. For the development of TAFC, genetic algorithm constructs the binary tree structure by optimally selecting the nodes and leaves, and then random signal-based learning further refines the binary connections (two-step optimization). An inverted pendulum system is considered to verify the effectiveness of the proposed method by simulation.

• Journal of Biomedical Engineering Research
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• v.26 no.3
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• pp.171-176
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• 2005

This paper proposes an automatic liver segmentation method using improved partial histogram threshold (PHT) algorithms. This method removes neighboring abdominal organs regardless of random pixel variation of contrast enhanced CT images. Adaptive multi-modal threshold is first performed to extract a region of interest (ROI). A left PHT (LPHT) algorithm is processed to remove the pancreas, spleen, and left kidney. Then a right PHT (RPHT) algorithm is performed for eliminating the right kidney from the ROI. Finally, binary morphological filtering is processed for removing of unnecessary objects and smoothing of the ROI boundary. Ten CT slices of six patients (60 slices) were selected to evaluate the proposed method. As evaluation measures, an average normalized area and area error rate were used. From the experimental results, the proposed automatic liver segmentation method has strong similarity performance as the MSM by medical Doctor.

• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.121-128
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• 2017

In this paper, we propose a multi-label classification method in which multi-label classification estimation techniques are applied to resolving location prediction problem. Most of previous studies related to location prediction have focused on the use of single-label classification by using contextual information such as user's movement paths, demographic information, etc. However, in this paper, we focused on the case where users are free to visit multiple locations, forcing decision-makers to use multi-labeled dataset. By using 2373 contextual dataset which was compiled from college students, we have obtained the best results with classifiers such as bagging, random subspace, and decision tree with the multi-label classification estimation methods like binary relevance(BR), binary pairwise classification (PW).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.468-475
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• 2003

In this Paper, we design an optimal binary phase computer generated hologram for Pattern generation using combined genetic algorithm and simulated annealing algorithm together. To design an optimal binary phase computer generated hologram, in searching process of the proposed method, the simple genetic algorithm is used to get an initial random transmittance function of simulated annealing algorithm. Computer simulation shows that the proposed algorithm has better performance than the genetic algorithm or simulated annealing algorithm of terms of diffraction efficiency

• Korean Chemical Engineering Research
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• v.57 no.1
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• pp.73-77
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• 2019

Isothermal (vapor + liquid) equilibrium data measurements were undertaken for the binary mixtures of (propylene oxide + 1-pentanol) system at three different temperatures (303.15, 318.15, and 333.15) K. The Peng-Robinson-Stryjek-Vera equation of state (PRSV EOS) was used to correlate the experimental data. The van der Waals one-fluid mixing rule was used for the vapor phase and the Wong-Sandler mixing rule, which incorporates the non-random two liquid (NRTL) model, the universal quasi-chemical (UNIQUAC) model and the Wilson model, was used for the liquid phase. The experimental data were in good agreement with the correlation results.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.175-177
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• 2018

This paper proposes an algorithm to speed up block structure partition of quad tree plus binary tree (QTBT) in Joint Exploration Test Model (JEM) encoder. The proposed fast encoding of QTBT block partition employs three spatially neighbor coded blocks, such as left, top-left, and top of current block, to early terminate QTBT block structure pruning. The propose algorithm is organized based on statistical similarity of those spatially neighboring blocks, such as block depths and coded block types, which are coded with overlapped block motion compensation (OBMC) and adaptive multi transform (AMT). The experimental results demonstrate about 30% encoding time reduction with 1.3% BD-rate loss on average compared to the anchor JEM-7.1 software under random access configuration.