• Journal of Power Electronics
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• 제11권6호
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• pp.856-863
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• 2011

In this paper a novel method of the Ant Colony Optimization algorithm for rotor position estimation in Switched Reluctance Motors is presented. The data provided by the initial assumptions is one of the important aspects used to solve the problems relative to an Ant Colony algorithm. Considering the nature of a real ant colony, it was found that the ants have no primary data for deducing which is the shortest path in their initial iteration. They also do not have the ability to see the food sources at a distance. According to this point of view, a novel method is presented in which the rotor pole position relative to the corresponding stator pole in a switched reluctance motor is estimated with high accuracy using the active and inactive phase parameters. This new method gives acceptable results such as a desirable convergence together with an optimized and stable response. To the best knowledge of the authors, such an analysis has not been carried out previously.

• International Journal of Reliability and Applications
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• 제7권2호
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• pp.177-186
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• 2006

Typical confidence intervals for a mean or mean residual life (MRL) are centered about the mean or mean residual life. We discuss novel confidence intervals that produce statements like "we are 95% confident that the MRL function, e(t), is greater than a prespecified $\mu_o$ for all t in the interval [0, $\hat{\theta})$)" where $\hat{\theta}$ is determined from the sample data, confidence level, and $\mu_o$. Also, we can have statements like 'we are 95% confident that the MRL of population 1, namely $e_1$(t), is greater than the MRL of population 2, $e_2$(t), for all t in the interval [0, $\hat{\theta}$)" where $\hat{\theta}$ is determined from the sample data and confidence level. We illustrate these one and two sample confidence intervals on internal bonds (tensile strengths) for an important modem engineered wood product, called medium density fiberboard (MDF), used internationally.

• Natural Product Sciences
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• 제10권2호
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• pp.59-62
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• 2004

A novel chlorinated diterpene quinone methide; chlorosmaridione (7-chloro-11-hydroxy-abeita-7,9(11),13-triene-6,12-diode) was isolated from petroleum ether extract of the stems of Rosemarinus officinalis L. growing in Egypt. In addition, ${\beta}-sitosterol$, stigmasterol, lupeol acetate, ${\alpha}-amyrin,\;{\beta}-amyrin$, lupeol, acetyloleanolic acid, acetylursolic acid taxodione, horminone, and cryptotanshinone were also identified. Chemical structures of the isolated compounds have been elucidated on the bases of physical, chemical, and spectral data including IR, UV, MS, 1D-and 2D-NMR spectra.

• 전기학회논문지
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• 제56권1호
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• pp.197-205
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• 2007

We have proposed a novel line detection method based on the estimated probability density function of gradient directions of edges. By estimating peaks of the density function, we determine groups of edges that have the same gradient direction. For edges in the same groups, we detect lines that correspond to peaks of the connectivity weighted distribution of the distances from the origin. In the experiments using the Data Matrix barcode images and LCD images, the proposed method showed better performance than conventional Methods in terms of the processing speed and accuracy.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2000년도 제1회 학술대회 논문집
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• pp.13-14
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• 2000

21.6" a-Si:H TFT array for direct conversion X-ray detector with 2480 by 3072 pixel is successfully developed. To obtain good X-ray image quality, novel structure, storage on BCB structure, is proposed. The structure reduces the parasitic capacitance of data line, one of the main sources of signal noise. Also, the structure shows higher failure resistance against defects than that of the old design.

• Computers and Concrete
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• 제15권1호
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• pp.55-71
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• 2015

This paper presents a novel harmony search (HS)-based data-driven single input rule modules (SIRMs)-connected fuzzy inference system (FIS) for the prediction of stress in externally prestressed tendon. The proposed method attempts to extract causal relationship of a system from an input-output pairs of data even without knowing the complete physical knowledge of the system. The monotonicity property is then exploited as an additional qualitative information to obtain a meaningful SIRMs-connected FIS model. This method is then validated using results from test data of the literature. Several parameters, such as initial tendon depth to beam ratio; deviators spacing to the initial tendon depth ratio; and distance of a concentrated load from the nearest support to the effective beam span are considered. A computer simulation for estimating the stress increase in externally prestressed tendon, ${\Delta}f_{ps}$, is then reported. The contributions of this paper is two folds; (i) it contributes towards a new monotonicity-preserving data-driven FIS model in fuzzy modeling and (ii) it provides a novel solution for estimating the ${\Delta}f_{ps}$ even without a complete physical knowledge of unbonded tendons.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권3호
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• pp.813-829
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• 2022

In multi-view subspace clustering, how to integrate the complementary information between perspectives to construct a unified representation is a critical problem. In the existing works, the unified representation is usually constructed in the original data space. However, when the data representation in each view is very diverse, the unified representation derived directly in the original data domain may lead to a huge information loss. To address this issue, different to the existing works, inspired by the latest revelation that the data across all perspectives have a very similar or close spectral block structure, we try to construct the unified representation in the spectral embedding domain. In this way, the complementary information across all perspectives can be fused into a unified representation with little information loss, since the spectral block structure from all views shares high consistency. In addition, to capture the global structure of data on each view with high accuracy and robustness both, we propose a novel low-rank approximation via the tight lower bound on the rank function. Finally, experimental results prove that, the proposed method has the effectiveness and robustness at the same time, compared with the state-of-art approaches.

• Structural Engineering and Mechanics
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• 제87권1호
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• pp.1-18
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• 2023

The paper presents a Bayesian Finite element (FE) model updating methodology by utilizing modal data. The dynamic condensation technique is adopted in this work to reduce the full system model to a smaller model version such that the degrees of freedom (DOFs) in the reduced model correspond to the observed DOFs, which facilitates the model updating procedure without any mode-matching. The present work considers both the MPV and the covariance matrix of the modal parameters as the modal data. Besides, the modal data identified from multiple setups is considered for the model updating procedure, keeping in view of the realistic scenario of inability of limited number of sensors to measure the response of all the interested DOFs of a large structure. A relationship is established between the modal data and structural parameters based on the eigensystem equation through the introduction of additional uncertain parameters in the form of modal frequencies and partial mode shapes. A novel sampling strategy known as the Metropolis-within-Gibbs (MWG) sampler is proposed to sample from the posterior Probability Density Function (PDF). The effectiveness of the proposed approach is demonstrated by considering both simulated and experimental examples.

• Journal of the Korean Statistical Society
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• 제30권2호
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• pp.327-345
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• 2001

New statistical methods are ended to analyzed data in a multi-scale way. Some multi-scale extensions of stand methods, including novel visualization using dynamic graphics are proposed. These tools are used to explore non-standard structure in internet traffic data.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2000년도 International Symposium on Bioinformatics
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• pp.41-44
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• 2000

With the advent of DNA microarray and "chip" technologies, gene expression in an organism can be monitored on a genomic scale, allowing the transcription levels of many genes to be measured simultaneously. Functional interpretation of massive expression data and linking such data to DNA sequences have become the new challenges to bioinformatics. I will us yeast cell cycle expression data analysis as an example to demonstrate how special database and computational methods may be used for extracting functional information, I will also briefly describe a novel clustering algorithm which has been applied to the cell cycle data.