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Miaoli, Taiwan

Lu C.-W.,Jen Teh Junior College | Chen J.-C.,National Central University
Crystal Research and Technology | Year: 2010

The thermal and flow transport in an inductively heated Czochralski crystal growth furnace during a crystal growth process is investigated numerically. The temperature and flow fields inside the furnace, coupled with the heat generation in the iridium crucible induced by the electromagnetic field generated by the RF coil, are computed. The results indicate that for an RF coil fixed in position during the growth process, although the maximum value of the magnetic, temperature and velocity fields decrease, the convexity of the crystal-melt interface increases for longer crystal growth lengths. The convexity of the crystal-melt interface and the power consumption can be reduced by adjusting the relative position between the crucible and the induction coil during growth. © 2010 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. Source


Chen C.-H.,National Central University | Chen J.-C.,National Central University | Lu C.-W.,Jen Teh Junior College | Liu C.-M.,Industrial Technology Research Institute of Taiwan
Journal of Crystal Growth | Year: 2011

Numerical computation has been performed to investigate temperature and velocity distributions for different stages of the Kyropoulos sapphire single crystal-growth process. The finite-element method is employed to solve the governing equations with proper boundary conditions. In the power history considered here, a vortex appears in the melt during growth, and its strength decreases as the input power is reduced. Isotherms in the melt are distorted by flow motion. The crystalmelt interface is always convex towards the melt and in early stages the convexity increases as the input power decreases. When the crystalmelt interface is close to the bottom of the crucible, this interface is flat near the apex because of reduction in growth rate near the upper region caused by input heat from the bottom of the crucible. Therefore, convexity of the crystalmelt interface decreases the input power decreases. The crystal shape predicted by the present simulation is similar to that of crystals grown in the industry. © 2010 Elsevier B.V. Source


Chen C.-H.,National Central University | Chen J.-C.,National Central University | Lu C.-W.,Jen Teh Junior College | Liu C.-M.,Industrial Technology Research Institute of Taiwan
Journal of Crystal Growth | Year: 2012

The Kyropoulos (KY) method is commonly used to grow large sized sapphire single crystals. The shape of the sapphire crystal thus grown is determined by the heater arrangement and the power reduction history in the Kyropoulos furnace. In order to grow high-quality sapphire single crystal, the heater arrangement should allow different power inputs in different sections in order to control the thermal field in the melt during the growth process. In this study, a numerical computation is performed to investigate the effects of the heater arrangement on the thermal and flow transport, the shape of the crystal-melt interface, and the power requirements during the Kyropoulos sapphire crystal growth process in a resistance heated furnace. Four different power ratio arrangements in a three-zone heater are considered. The results show that for the power arrangements considered herein, the temperature gradients along the crystallization front do not exceed 0.05 K/mm, and that, after the growth of the crown, the crystal maintains an almost constant diameter. The remelting phenomenon may occur during growth when the input power of the upper side of the heater is higher than that of the lower side of the heater. © 2012 Elsevier B.V. Source


Yin K.-C.,Feng Chia University | Yin K.-C.,Jen Teh Junior College | Hsieh Y.-L.,Feng Chia University | Yang D.-L.,Feng Chia University
Proceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010 | Year: 2010

In this paper, we propose a new approach of mining temporal association rules. In conventional association rule mining algorithms, if the value of minimum support is set too high, we may lose lots of valuable rules. But if it is set too low, many trivial rules will be mined, and it is hard to distinguish which ones are valuable. When taking temporal factors into consideration, an itemset may not be frequent over the entire database but may be frequent in some specific intervals. Here, we propose a temporal association rule mining algorithm for interval frequent patterns, called GLFMiner, which can automatically generate all of the intervals without using any domain knowledge. In our algorithm, we consider not only global frequent patterns but also local frequent patterns. Then, with the same value of minimum support, we can find plenty of valuable temporal rules and don't lose any rule that conventional association rule mining algorithm can find. The experimental results show that our algorithm can mine more temporal frequent patterns than theconventional association rule mining algorithm. © 2010 IEEE. Source


Chen F.-L.,National Tsing Hua University | Li F.-C.,National Tsing Hua University | Li F.-C.,Jen Teh Junior College
Expert Systems with Applications | Year: 2010

The credit scoring has been regarded as a critical topic and its related departments make efforts to collect huge amount of data to avoid wrong decision. An effective classificatory model will objectively help managers instead of intuitive experience. This study proposes four approaches combining with the SVM (support vector machine) classifier for features selection that retains sufficient information for classification purpose. Different credit scoring models are constructed by selecting attributes with four approaches. Two UCI (University of California, Irvine) data sets are chosen to evaluate the accuracy of various hybrid-SVM models. SVM classifier combines with conventional statistical LDA, Decision tree, Rough sets and F-score approaches as features pre-processing step to optimize feature space by removing both irrelevant and redundant features. In this paper, the procedure of the proposed approaches will be described and then evaluated by their performances. The results are compared in combination with SVM classifier and nonparametric Wilcoxon signed rank test will be held to show if there is any significant difference between these models. The result in this study suggests that hybrid credit scoring approach is mostly robust and effective in finding optimal subsets and is a promising method to the fields of data mining. © 2009 Elsevier Ltd. All rights reserved. Source

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