Jen Teh Junior College

Miaoli, Taiwan

Jen Teh Junior College

Miaoli, Taiwan
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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.


Teng Y.-Y.,Chung Shan Institute of Science and Technology | Chen J.-C.,National Central University | Huang C.-C.,National Central University | Lu C.-W.,Jen Teh Junior College | And 2 more authors.
Journal of Crystal Growth | Year: 2012

In this study, a numerical simulation is performed to investigate the effect of the shape of the heat shield on the oxygen concentration in the melt. The results show that the oxygen concentration in the melt can be significantly decreased by increasing the speed of the argon gas near the crucible wall. This can be achieved by enlarging the horizontal length of the heat shield. The oxygen concentration at the melt-crystal interface varies with the length of the crystal growth. In the initial stage, there is a significant decrease in the oxygen concentration as the growth length increases. There is also a significant reduction in the emission of oxygen from the crucible wall due to the lower melt depth and crucible temperature. The transportation of oxygen impurity towards the melt-crystal interface is suppressed by the vortex motion in the melt. When the crystal exceeds a certain length, the oxygen concentration in the melt-crystal interface starts to increase with increasing crystal length, due to the drop in vortex motion in the melt. © 2012 Elsevier B.V.


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.


Li F.,Jen Teh Junior College | Lung T.,Jen Teh Junior College | Yeh C.,Takming University of Science and Technology
Proceedings - 2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010 | Year: 2010

Hybrid classification model is currently an active research area and successfully solves classification problems in credit scoring. Finding effective classificatory models is important. Classification in credit scoring has been regarded as a critical topic, with its related departments collecting huge amounts of data to avoid making the wrong decision. Filter feature selection model is important in credit scoring and in the field of data mining. This study proposes three filter approaches which combine with Random Vector Functional-Link net (RVFL) classifier, to find the suitable classification models. Filter approach retains sufficient information for classification purposes. Different credit scoring combinations are constructed by selecting features with three approaches. Two credit data sets from University of California, Irvine (UCI) are chosen to evaluate the accuracy of various filter selection models. RVFL classifiers combine with Grey relation analysis (GRA), conventional statistical linear discriminate analysis (LDA), and F-score approaches as preprocessing step to optimize features space. In this research, the procedures are described and then evaluated by their performances. The results are compared by nonparametric Wilcoxon signed rank test and performed to show if there is any significant difference between these filters. Our results suggest that the performances of the F-score approach combined with RVFL classifier are brilliant among the two data sets. The hybrid model is more effective and higher accuracy than the original feature space and is a promising method in the field of data mining. ©2010 IEEE.


Lu C.-W.,Jen Teh Junior College | Chen J.-C.,National Central University | Chen C.-H.,National Central University | Hsu W.-C.,Industrial Technology Research Institute of Taiwan | Liu C.-M.,Industrial Technology Research Institute of Taiwan
Journal of Crystal Growth | Year: 2010

The effect of the RF coil position during the stages of sapphire crystal growth process in an inductively heated Czochralski crystal growth furnace on the thermal and flow transport, the shape of the crystal-melt interface shape, and the power requirements is investigated numerically. The results show that although the maximum values of temperature and velocity decrease, the convexity of the crystal-melt interface increases as the crystal length grows. It is found that the least input power is required if the central position of the RF coil is maintained below the central position of the melt during the crystal growth process. Under such crystal growth conditions, the temperature gradients along the crystalline front are small. © 2009 Elsevier B.V. All rights reserved.


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.


Liu Y.C.,University of Management and Technology | Lin C.,Curtin University Australia | Feng-Chia L.,Jen Teh Junior College
Proceedings of the 4th International Conference on Ubiquitous Information Management and Communication ICUIMC 10 | Year: 2010

Few studies have formulated how individuals contribute to the team process and bring the success of virtual teams. The researcher attempted to integrate Technology-Task fit (TTF), Self-disclosure and Social Networks to build a framework to formulate how individual efforts are transited to the outcome of virtual teams. This framework was validated by an experiment which was engaged in a Wiki system. The results revealed that virtual team members interact by computer-mediated communication (CMC), the social relations were formed and gradually the team was tied together as a group. The efforts of each member are integrated by social ties in order to accomplish the goals. Three suggestions were proposed: (a) an appropriate technology which fits to the tasks should be provided; (b) an adequate training of operating the technology and disclose is needed to help members convey social cues and information to accomplish the tasks; (c) a mechanism to ensure the social ties go on the right track is crucial such as the frequency of communication and the way of solving conflicts. © 2010 ACM.


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.


Wang P.-K.,Hwa Hsia University of Technology | Yeh L.-L.,National Tsing Hua University | Li F.-C.,Jen Teh Junior College
IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management | Year: 2010

Recently, both the non-uniform sampling scheme and economic statistical design approaches have been successfully applied to determine three parameters of X- control charts (including sample size, sampling interval between successive samples, and the control limits) for monitoring a manufacturing process with increasing hazard functions. Nevertheless, a primary assumption for these cost models is that measurements within a sample are independent. However, the conventional supposition may underestimate significantly the type I error probability for an X- control chart. Hence, in this investigation, we develop a cost model that combine Rahim and Banerjee's cost model with Yang and Hancock's multivariate normal distribution model under maximum probability of type I error and minimum value of power to search the optimal parameters of non-uniform sampling interval X- control charts for the measurements within a sample being correlated. In addition, an industrial example is applied to indicate the solution procedure. Meanwhile, a genetic algorithm is adopted. ©2010 IEEE.


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.

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