Browsing by Author "Shih, C. W."

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Extremely High Mobility Ultra-Thin Metal-Oxide with ns(2)np(2) Configuration
(2015)
Shih, C. W.
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Chin, Albert
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Lu, Chun-Fu
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Yi, S. H.
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電子工程學系及電子研究所
To increase the transistor\'s current (I-ON) and decrease the off-state leakage (I-OFF), high-mobility, wide-bandgap and ultra-thin body channel materials are crucial for display, sub-10 nm MOSFET, and brain-mimicking 3D IC. The wide-bandgap ultra-thin-film SnO2 nMOSFET has achieved a high I-ON/I-OFF of > 10(7), and high mobility of >0.5X SiO2/Si device value operated at 1 MV/cm. The high mobility TFT is due to the overlapped orbitals.
Magnetocaloric Properties of Melt-Spun Fe-Ni-Mn-Ga Ribbons
(2014-01-01)
Shih, C. W.
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Zhao, X. G.
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Chang, H. W.
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Tseng, Y. C.
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Chang, W. C.
The effects of Ni substitution for Fe on phase constitutions, Curie temperature T-C, and magnetocaloric properties of melt-spun Fe50-xNixMn25Ga25 (x =0, 1, 3, 5 and 7) ribbons have been investigated. X-ray diffraction results show that the main phase in the Fe50-xNixMn25Ga25 (x = 0-7) alloy changed with the increase of Ni content from FCC structure for x = 0 into B2 structure for x = 1-7. Besides, the magnetic phase exhibits phase transition of ferromagnetic into paramagnetic state with increasing temperature for the samples with B2-type structure. The Curie temperature T-C of these ribbons varies in the temperature range of 232-257 K. The peak values of the maximal magnetic entropy change, -Delta S-M(max), are about 1.4-1.6 Jkg/K for Ni-substituted ribbons at a maximum applied field of 30 kOe. On the other hand, the relatively broader temperature range at the half maximum of Delta S-M peak (similar to 90 K), low-cost and nontoxic elements make Fe-Ni-Mn-Ga-based ribbons the promising candidates for magnetic refrigeration applications close to room temperature.
Mining association rules through integration of clustering analysis and ant colony system for health insurance database in Taiwan
(2007-10-01)
Kuo, R. J.
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Lin, S. Y.
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Shih, C. W.
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工業工程與管理學系
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Department of Industrial Engineering and Management
In addition to sharing and applying the knowledge in the community, knowledge discovery has become an important issue in the knowledge economic era. Data mining plays an important role of knowledge discovery. Therefore, this study intends to propose a novel framework of data mining which clusters the data first and then followed by association rules mining. The first stage employs the ant system-based clustering algorithm (ASCA) and ant K-means (AK) to cluster the database, while the ant colony system-based association rules mining algorithm is applied to discover the useful rules for each group. The medical database provided by the National Health Insurance Bureau of Taiwan Government is used to verify the proposed method. The evaluation results showed that the proposed method not only is able to extract the rules much faster, but also can discover more important rules. (c) 2006 Published by Elsevier Ltd.