• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2627-2647
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• 2016

With the rapid growth of microblog, expert identification on microblog has been playing a crucial role in many applications. While most previous expert identification studies only assess global authoritativeness of a user, there is no way to differentiate the authoritativeness in a particular aspect of topics. In this paper, we propose a novel model, which jointly models text and following relationship in the same generative process. Furthermore, we integrate a similarity-based weight scheme into the model to address the popular bias problem, and use followee topic distribution as prior information to make user's topic distribution more precisely. Our empirical study on two large real-world datasets shows that our proposed model produces significantly higher quality results than the prior arts.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.4 s.175
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• pp.1047-1054
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• 2000

A numerical simulation was made to delineate the re-distribution of tonal noise generated from the equally-spaced blade passing frequency (BPF). A pressure-wave model was employed to analyze the tonal noise. An optimal solution for diversifying the tonal peak noise was obtained by rearranging the unequally-spaced blade angles. This was based on the fact that the noise energy is transferred from BPF to the neighboring frequency band. A limit condition for the minimum blade angle spacing was imposed. The unbalancing problem was also considered to avoid the weight bias.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.07a
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• pp.855-858
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• 2001

The stress induced leakage currents of thin silicon oxides is investigated in the VLSI implementation of a self learning neural network integrated circuits using a linearity synapse transistor. The channel current for the thickness dependence of stress current, transient current, and stress induced leakage currents has been measured in oxides with thicknesses between 41 ${\AA}$, 86${\AA}$, which have the channel width ${\times}$ length 10 ${\times}$1${\mu}$m, 10 ${\times}$0.3${\mu}$m respectively. The stress induced leakage currents will affect data retention in synapse transistors and the stress current, transient current is used to estimate to fundamental limitations on oxide thicknesses. The synapse transistor made by thin silicon oxides has represented the neural states and the manipulation which gaves unipolar weights. The weight value of synapse transistor was caused by the bias conditions. Excitatory state and inhitory state according to weighted values affected the channel current. The stress induced leakage currents affected excitatory state and inhitory state.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.155-159
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• 2003

최근 들어 SVM(support vector machines)은 기계학습의 분야에서 많은 응용이 이루어지고 있으며 특히 분류(classification)나 회귀(regression)분석의 영역에서 많은 연구가 진행중이다. 본 논문에서는 SVM을 이용하여 입력영상자료(image data)를 분류하고자 한다. RGB 컬러 영상자료가 입력되면 이미지 크기에 관계없이 이미지 자체를 입력패턴으로 인식하고 SVM을 통한 훈련(training)을 거친 결과(weight 들과 bias 추정치)를 이용하여 입력영상자료가 사람인가를 분류할 수 있는 문제를 다룬다. 제안된 방법의 타당성은 152개의 영상자료에 적용하여 분석되었다.

• Macromolecular Research
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• v.15 no.6
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• pp.491-497
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• 2007

NPT Monte Carlo simulations were performed to calculate the molecular properties of syndiotactic poly(vinyl chloride) (PVC) and syndiotactic poly(vinyl alcohol) (PVA) melts using the configurational bias Monte Carlo move, concerted rotation, reptation, and volume fluctuation. The density, mean square backbone end-to-end distance, mean square radius of gyration, fractional free-volume distribution, distribution of torsional angles, small molecule solubility constant, and radial distribution function of PVC at 0.1 MPa and above the glass transition temperature were calculated/measured, and those of PVA were calculated. The calculated results were compared with the corresponding experimental data and discussed. The calculated densities of PVC and PVA were smaller than the experimental values, probably due to the very low molecular weight of the model polymer used in the simulation. The fractional free-volume distribution and radial distribution function for PVC and PVA were nearly independent of temperature.

• Electrical & Electronic Materials
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• v.10 no.8
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• pp.783-793
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• 1997

A VLSI implementation of a self-learning neural network integrated circuits using a linearity synapse transistor is investigated. The thickness dependence of oxide current density stress current transient current and channel current has been measured in oxides with thicknesses between 41 and 112 $\AA$, which have the channel width $\times$ length 10 $\times$1${\mu}{\textrm}{m}$, 10 $\times$ 0.3${\mu}{\textrm}{m}$ respectively. The transient current will affect data retention in synapse transistors and the stress current is used to estimate to fundamental limitations on oxide thicknesses. The synapse transistor has represented the neural states and the manipulation which gaves unipolar weights. The weight value of synapse transistor was caused by the bias conditions. Excitatory state and inhitory state according to weighted values affected the drain source current.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.07a
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• pp.59-62
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• 2000

A VLSI implementation of a self-learning neural network integrated circuits using a linearity synapse transistor is investigated. The thickness dependence of oxide current density, stress current, transient current and channel current has been measured in oxides with thicknesses between 41 and 112 $\AA$, which have the channel width$\times$length 10$\times$1${\mu}{\textrm}{m}$ respectively. The transient current will affect data retention in synapse transistors and the stress current is used to estimate to fundamental limitations on oxide thicknesses. The synapse transistor has represented the neural states and the manipulation which gave unipolar weights. The weight value of synapse transistor was caused by the bias conditions. Excitatory state and inhitory state according to weighted values affected the drain source current.

• Proceedings of the IEEK Conference
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• summer
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• pp.209-212
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• 2004

In this paper, The stress induced leakage currents of thin silicon oxides is investigated in the nano scale structure implementation for Soc. The stress and transient currents associated with the on and off time of applied voltage were used to measure the distribution of high voltage stress induced traps in thin silicon oxide films. The stress and transient currents were due to the charging and discharging of traps generated by high stress voltage in the silicon oxides. The channel current for the thickness dependence of stress current, transient current, and stress induced leakage currents has been measured in oxides with thicknesses between $41\square\;and\;113.4\square,$ which have the channel width x length 10x1um, respectively. The stress induced leakage currents will affect data retention and the stress current, transient current is used to estimate to fundamental limitations on oxide thicknesses. The weight value of synapse transistor was caused by the bias conditions. Excitatory state and inhitory state according to weighted values affected the channel current. The stress induced leakage currents affected excitatory state and inhitory state.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.816-839
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• 2023

In a random vector functional link (RVFL) network, shortcomings such as local optimal stagnation and decreased convergence performance cause a reduction in the accuracy of illumination correction by only inputting the weights and biases of hidden neurons. In this study, we proposed an improved regularized random vector functional link (RRVFL) network algorithm with an optimized grey wolf optimizer (GWO). Herein, we first proposed the moth-flame optimization (MFO) algorithm to provide a set of excellent initial populations to improve the convergence rate of GWO. Thereafter, the MFO-GWO algorithm simultaneously optimized the input feature, input weight, hidden node and bias of RRVFL, thereby avoiding local optimal stagnation. Finally, the MFO-GWO-RRVFL algorithm was applied to ameliorate the performance of illumination correction of various test images. The experimental results revealed that the MFO-GWO-RRVFL algorithm was stable, compatible, and exhibited a fast convergence rate.

• Fashion & Textile Research Journal
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• v.13 no.3
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• pp.418-424
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• 2011

The purpose of this study was to reveal the effects of the seam type on the fabric drape to provide the basic knowledge for proper seam type according to the design of sewing products. Seven kinds of specimens were constructed with seam (no seam, welt seam with over-edged finish, welt seam with bias bound finish, plain seam with over-edged finish, plain seam with bias bound finish, french seam, and flat fell seam) in wrap direction of the fabric. Using a drape measurement system involving two 18 cm diameter supporting disks, and a digital camera, the images of draped specimens were captured and processed. Drape behavior was evaluated in terms of drape coefficient, node number, and drape profile. Significant differences were found in drape coefficient by the seam types. The specimens with french seam and flat fell seam showed higher drape coefficients compared to those with welt seam and plain seam. Node numbers in the drape profiles showed positive correlation with the weight of the specimens, however, no significant differences were observed in node numbers by the seam types. Significant differences were found in the length of the seamed part by the seam types. The specimens with french seam and flat fell seam showed longer length of the seamed part compared to those with welt seam and plain seam. The ratio of the maximum length in the seam direction to the maximum length perpendicular to the seam direction showed significant differences by the seam types.