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Hsinchu, Taiwan

Chung Hua University is a private university located in Xiangshan District, Hsinchu City, Taiwan. It was formerly known as Chung Hua Polytechnic Institute founded in 1990 by three local Hsinchu entrepreneurs, Ron-Chang Wang, Zau-Juang Tsai and Lin Junq-tzer. It was upgraded to university status and renamed as "Chung Hua University" in 1997. There are six colleges with 25 departments offering undergraduate courses as well as 16 master programs and 3 PH.D. programs. Wikipedia.


Hsu C.-F.,Chung Hua University
Expert Systems with Applications | Year: 2011

Chaotic system is a nonlinear deterministic system that displays complex, noisy-like and unpredictable behavior, so how to synchronize chaotic system become a great deal in engineering community. In this paper, an adaptive fuzzy wavelet neural synchronization controller (AFWNSC) is proposed to synchronize two nonlinear identical chaotic gyros. The proposed AFWNSC system is composed of a neural controller and a fuzzy compensator. The neural controller uses a fuzzy wavelet neural network to online approximate an ideal controller and the fuzzy compensator is used to guarantee system stable without chattering phenomena. All the parameter learning algorithms of the proposed AFWNSC scheme are derived in the Lyapunov stability sense. Finally, some simulation results verify the chaotic behavior of two nonlinear identical chaotic gyros can be synchronized by the proposed AFWNSC scheme after learning of the controller parameters. Moreover, the convergence of the tracking error and control parameters can be accelerated by the developed proportional-integral type adaptation learning algorithm. © 2011 Published by Elsevier Ltd. Source


Sheu L.J.,Chung Hua University
Transport in Porous Media | Year: 2011

The onset of convection in a horizontal layer of a porous medium saturated with a viscoelastic nanofluid was studied in this article. The modified Darcy model was applied to simulate the momentum equation in porous media. An Oldroyd-B type constitutive equation was used to describe the rheological behavior of viscoelastic nanofluids. The model used for the viscoelastic nanofluid incorporates the effects of Brownian motion and thermophoresis. The onset criterion for stationary and oscillatory convection was analytically derived. The effects of the concentration Rayleigh number, Prandtl number, Lewis number, capacity ratio, relaxation, and retardation parameters on the stability of the system were investigated. Oscillatory instability is possible in both bottom- and top-heavy nanoparticle distributions. Results indicated that there is competition among the processes of thermophoresis, Brownian diffusion, and viscoelasticity that causes the convection to set in through oscillatory rather than stationary modes. Regimes of stationary and oscillatory convection for various parameters were derived and are discussed in detail. © 2011 Springer Science+Business Media B.V. Source


In this paper, a self-organizing Takagi-Sugeno-Kang (TSK) type fuzzy neural network (STFNN) is proposed. The self-organizing approach demonstrates the property of automatically generating and pruning the fuzzy rules of STFNN without the preliminary knowledge. The learning algorithms not only extract the fuzzy rule of STFNN but also adjust the parameters of STFNN. Then, an adaptive self-organizing TSK-type fuzzy network controller (ASTFNC) system which is composed of a neural controller and a robust compensator is proposed. The neural controller uses an STFNN to approximate an ideal controller, and the robust compensator is designed to eliminate the approximation error in the Lyapunov stability sense without occurring chattering phenomena. Moreover, a proportional-integral (PI) type parameter tuning mechanism is derived to speed up the convergence rates of the tracking error. Finally, the proposed ASTFNC system is applied to a DC motor driver on a field-programmable gate array chip for low-cost and high-performance industrial applications. The experimental results verify the system stabilization and favorable tracking performance, and no chattering phenomena can be achieved by the proposed ASTFNC scheme. © 2011 Springer Science+Business Media B.V. Source


Luoh L.,Chung Hua University
Soft Computing | Year: 2014

Nowadays positioning system is no longer only for military purpose, while it has been widely applied to various livelihood purposes such as biological information, emergency rescue, public facilities and individual safety. While the most frequently used to identify the coordinates of users is global positioning system (GPS), however, it tends to be interfered by indoor buildings such that it cannot be effectively used in indoor environment. Recently, wireless sensor network has become a trendy research topic, the positioning service of indoor positioning system can be achieved by the measurements of received signal strength (RSS) or link quality indicator (LQI). In this paper, the average RSS is first adopted for reducing the noise interference of LQI, and then the object to be detected will be trained by radial basis function network (RBFN) with the capability of identifying the environment of location. ZigBee module will then be integrated to realize a set of convenient wireless indoor positioning system with low cost. In addition, multiple similar artificial neural networks within the same region will be adopted to further improve the positioning accuracy. Experiments shown that this study is capable of effective enhancement of existing IPS accuracy with the average error of indoor positioning at 2.8 meters 100 % comparing with other approaches. © 2013 Springer-Verlag Berlin Heidelberg. Source


Wang H.-Y.,Chung Hua University
International Journal of Hospitality Management | Year: 2011

In recent years gastronomy blogs providing an important channel for electronic word-of-mouth (eWOM) to take place are quickly becoming a popular new source of reading material for blog readers. However, little is published to understand what factors from gastronomy blogs play critical roles in predicting readers' intention to taste local food and beverages. Based on reviewing previous studies, this study developed a research model containing three main categories of variables: (1) inspiring taste desire (i.e., experiencing appeal and generating empathy), (2) forming taste awareness (i.e., providing image, delivering knowledge and presenting guides) and (3) facilitating interpersonal interaction (i.e., social influence and cybercommunity influence), and suggested that these potential variables can influence readers' behavioral intention to taste directly. Data collected from 329 respondents in Taiwan were tested against the research model using the structural equation modeling approach. The results indicated that excluding delivering knowledge, all the other proposed variables (i.e., experiencing appeal, generating empathy, providing image, presenting guides, social influence and cybercommunity influence) were the critical components significantly influencing online readers' intention to taste, and the proposed model accounted for 70% of the variance. The findings of this study will not only help hospitality and tourism practitioners in understanding the perceptions of potential customers, but also provide insights into research on technology's influence on hospitality and gastronomy. © 2010 Elsevier Ltd. Source

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