Lin J.-C.,Taipei Chengshih University of Science and Technology
Composite Structures | Year: 2010
The objective of this paper is to study the vibration characteristic for a sandwich beam with silica/polymer blend as principal material, and pure polymer matrix as surface laminate. It is anticipated that high stiffness and structure damping of viscoelastic layer can be obtained by taking advantage of fascinating network of densely packed between silica and polymer matrix. Spherical particles of size 12-235 nm at various filler fraction (10-50 wt.%) and three different polymer matrices, polyacrylate, polyimide and polypropylene, were selected as the matrix materials. The mechanical damping and stiffness of the sandwich cantilever beam are recorded by using a Dynamic Mechanical Thermal Analyzer (DMTA). The silica's small particle size feature and strain difference between principal and surface layers could highly enhance the energy dissipation ability of the beam structure. A numerical model is then developed and validated for the vibration of a symmetric elastic-viscoelastic sandwich beam. Experimental results show that the structure deformation for these sandwich beams with contiguous and constraining layers are in reasonable agreement with the prediction of the model. Both higher resonant vibrations are well damped in accordance with the symmetric motion of the elastic layers and relative little motion of the constraining layer. © 2009 Elsevier Ltd. All rights reserved.
Lee C.-N.,Taipei Chengshih University of Science and Technology
Circuits, Systems, and Signal Processing | Year: 2010
Two new multiple-mode (including voltage, current, transconductance, and transresistance modes) OTA-C universal biquad filters are proposed. The first proposed circuit uses only four operational transconductance amplifiers (OTAs) and two grounded capacitors. The second proposed circuit uses five OTAs and two grounded capacitors. Both the proposed circuits can realize voltage, current, transconductance, and transresistance mode universal filtering responses (low-pass, high-pass, band-pass, notch, and all-pass) from the same topology. The first proposed circuit uses the least number of components. This represents an attractive feature from a chip area and power consumption point of view. The second proposed circuit has no need of extra inverting and non-inverting amplifiers for special input signals. Moreover, both the proposed biquads still have (i) the employment of two grounded capacitors, (ii) cascadable connection of the former voltage-mode stage and the latter current-mode stage, and (iii) low sensitivity performance. H-SPICE simulation results confirm the theoretical analysis. © Springer Science+Business Media, LLC 2009.
Lee C.-N.,Taipei Chengshih University of Science and Technology
Journal of Circuits, Systems and Computers | Year: 2011
A fully cascadable (i.e., low/high input impedance for current/voltage input signals and high/low output impedance for current/voltage output signals) mixed-mode (input and output signals can be voltage or current) universal filter biquad by using three differential difference current conveyors (DDCCs), three grounded resistors, and two grounded capacitors is presented in this paper. The proposed biquad can realize the inverting, non-inverting, and differential types universal filtering responses (lowpass, highpass, bandpass, notch, and allpass) from the voltage and current output terminals without changing the filter topology. The proposed circuit is suitable for cascading in all the four possible modes (i.e., voltage, current, transresistance, and transconductance modes). Moreover, the proposed mixed-mode biquad still enjoys (i) using only grounded passive components, (ii) no need of extra inverting and non-inverting amplifiers for special input signals, and (iii) low active and passive sensitivities. This paper also shows how analytical synthesis can be used to produce the proposed mixed-mode filter circuit. H-Spice simulation results confirm the theory. © 2011 World Scientific Publishing Company.
Chiu Y.-J.,Taipei Chengshih University of Science and Technology
Renewable Energy | Year: 2010
In a fuel cell of low temperature, especially a direct methanol fuel cell (DMFC), fuel crossover phenomenon plays a significant role not only in its performance evaluation and analysis, but also in the optimum control under various operating conditions. A quantitative prediction of the fuel crossover flux thus becomes essential. Generally speaking, the theoretical approaches to the issue will be dramatically complex and less practical. On the other hand, experimental schemes are time-consuming and less capable of further analysis and applications. Consequently, a semi-empirical model that incorporates dominant physical parameters and operating variables is proposed in this paper to adequately evaluate the phenomenon of fuel crossover fluxes. It is stated analytically in the form of an algebraic function, in which the fuel concentration, the current density, and the temperature of the fuel cell are considered. It is therefore more suitable for a variety of in-situ applications. In the proposed model, the methanol concentration gradient in the anode backing layer, the anode catalyst layer, and the membrane are analyzed. The transfer behavior of methanol is modeled on the basis of diffusion and electro-osmosis mechanisms. By means of the proposed model, one can obtain a better prediction and a clearer picture of the effects of operating variables and physical parameters on methanol crossover fluxes.
Hung L.-P.,Taipei Chengshih University of Science and Technology
Expert Systems with Applications | Year: 2010
This study focuses on predicting whether a credit applicant can be categorized as good, bad or borderline from information initially supplied. This is essentially a classification task for credit scoring. Given its importance, many researchers have recently worked on an ensemble of classifiers. However, to the best of our knowledge, unrepresentative samples drastically reduce the accuracy of the deployment classifier. Few have attempted to preprocess the input samples into more homogeneous cluster groups and then fit the ensemble classifier accordingly. For this reason, we introduce the concept of class-wise classification as a preprocessing step in order to obtain an efficient ensemble classifier. This strategy would work better than a direct ensemble of classifiers without the preprocessing step. The proposed ensemble classifier is constructed by incorporating several data mining techniques, mainly involving optimal associate binning to discretize continuous values; neural network, support vector machine, and Bayesian network are used to augment the ensemble classifier. In particular, the Markov blanket concept of Bayesian network allows for a natural form of feature selection, which provides a basis for mining association rules. The learned knowledge is represented in multiple forms, including causal diagram and constrained association rules. The data driven nature of the proposed system distinguishes it from existing hybrid/ensemble credit scoring systems. © 2009 Elsevier Ltd. All rights reserved.