Browsing by Author "Chang, J. Y."

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Characterization of 380 nm UV-LEDs grown on free-standing GaN by atmospheric-pressure metal-organic chemical vapor deposition
(2014-01-01)
Shieh, C. Y.
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Li, Z. Y.
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Kuo, H. C.
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Chang, J. Y.
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Chi, G. C.
We reported the defects and optical characterizations of the ultraviolet light-emitting diodes grown on free-standing GaN substrate (FS-GaN) and sapphire. Cross-sectional transmission electron microscopy (TEM) images showed that the total defect densities of grown UV LEDs on FS-GaN and sapphire including edge, screw and mixed type were 3.6x10(6) cm(-2) and 5.5x10(8) cm(-2). When substrate of UV LEDs was changed from sapphire to FS-GaN, it can be clearly found that the crystallography of GaN epilayers was drastically different from that GaN epilayers on sapphire. Besides, the microstructures or indium clustering can be not observed at UV LEDs on FS-GaN from TEM measurement. The internal quantum efficiency of UVLEDs on FS-GaN and sapphire were 34.8 % and 39.4 % respectively, which attributed to indium clustering in multi-layers quantum wells (MQWs) of UV LEDs on sapphire. The relationship between indium-clustering and efficiency droop were investigated by temperature-dependent electroluminescence (TDEL) measurements.
Crystal structure of aminoacylpeptidase dipeptidase from Vibrio alginolyticus, a metallopeptidase with dinuclear center
(2009-07-01)
Wu, T. K.
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Chang, J. Y.
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交大名義發表
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National Chiao Tung University
Deep Learning Based AOI System with Equivalent Convolutional Layers Transformed from Fully Connected Layers
(2019-01-01)
Tsai, Y. H.
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Lyu, N. Y.
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Jung, S. Y.
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Chang, K. H.
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Chang, J. Y.
The rise of deep learning, especially in the realm of computer vision, paves ways of leveraging automatic optical inspection systems to a higher level. Convolutional neural networks and its derivatives might be the most widely used architectures for defect inspection tasks. In real cases the amount of collected data is often not large, so transferring learning and data augmentation are necessary. In this paper, we explain some details how we implement the deep learning based AOI system where fully connected layers are replaced by convolutional layers, then a classification heat map is output after post-processing. We examine the performance of our model with two data sets collected in industrial manufacturing cases. We further propose an idea to transfer models pretrained on augmented data of different sizes cropped from original image to the present classification task for possible improvements of the performance.
Growth of gamma-In2Se3 films on Si substrates by metal-organic chemical vapor deposition with different temperatures
(2008-04-01)
Huang, Yen-Chin
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Li, Zhen-Yu
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Uen, Wu-Yih
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Lan, Shan-Ming
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Chang, K. J.
In2Se3 films were deposited on the p(+)-Si(1 1 1) substrates by metal-organic chemical vapor deposition (MOCVD) for the first time at temperatures higher than 500 degrees C. Trimethyl indium (TMI) and H2Se were used as the source reactants with the flow ratio of [H2Se]/[TMI] being maintained at 6.7. The growth temperature was varied from 350 to 650 degrees C. Powder X-ray diffraction analyses revealed that the In2Se3 film grown is polycrystalline and has a wurtzite structure when the growth temperature is below 450 degrees C. Instead, a rhombohedral structure began to appear when the growth temperature is above 450 degrees C. Besides, SEM observations indicated a surface morphology of columnar structure for all films grown. Optical properties were examined by photoluminescence (PL) measurements. It was found that by conducting the growth at 550 degrees C a strong PL emission at around 2.14 eV was observed at 20 K. The luminescence mechanism was found to be dominated by the free excitons based on the temperature-dependent PL spectra from 20 to 120 K. However, bound exciton emissions were also observed or even became the dominant band when the films were grown at temperatures lower than 500 degrees C. Otherwise, the intensity of the 2.14 eV peak reduced greatly when the growth temperature was higher than 5 50 degrees C. Power-dependent PL measurements with excitation power varying from 0.1 to 100 mW confirm the luminescent mechanism and the material quality of the film grown at 550 degrees C. It is concluded that single-phase gamma-In2Se3 films can be achieved at temperatures lower than 450 degrees C; however, good-quality In2Se3 films with the simultaneous appearance of gamma- and beta-phase structures can be grown at around 550 degrees C. (C) 2007 Elsevier B.V. All rights reserved.
Takagi-Sugeno-Kang Type Collaborative Fuzzy Rule Based System
(2014)
Chou, K. P.
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Prasad, M.
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Lin, Y. Y.
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Joshi, S.
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Lin, C. T.
In this paper, a Takagi-Sugeno-Kang (TSK) type collaborative fuzzy rule based system is proposed with the help of knowledge learning ability of collaborative fuzzy clustering (CFC). The proposed method split a huge dataset into several small datasets and applying collaborative mechanism to interact each other and this process could be helpful to solve the big data issue. The proposed method applies the collective knowledge of CFC as input variables and the consequent part is a linear combination of the input variables. Through the intensive experimental tests on prediction problem, the performance of the proposed method is as higher as other methods. The proposed method only uses one half information of given dataset for training process and provide an accurate modeling platform while other methods use whole information of given dataset for training.