Huafan University is an institute of higher education founded by members of the Buddhist community in Shiding District, New Taipei, Taiwan. The university consists of 4 colleges, 12 departments, 12 graduate institutes, and 5 research centers. Wikipedia.
Lin S.-W.,Chang Gung University |
Lee Z.-J.,Huafan University |
Ying K.-C.,National Taipei University of Technology |
Lu C.-C.,National Taipei University of Technology
Computers and Operations Research | Year: 2011
In this paper, we consider an identical parallel machine scheduling problem with sequence-dependent setup times and job release dates. An improved iterated greedy heuristic with a sinking temperature is presented to minimize the maximum lateness. To verify the developed heuristic, computational experiments are conducted on a well-known benchmark problem data set. The experimental results show that the proposed heuristic outperforms the basic iterated greedy heuristic and the state-of-art algorithms on the same benchmark problem data set. It is believed that this improved approach will also be helpful for other applications. © 2010 Elsevier Ltd.
Yan M.-T.,Huafan University |
Lin S.-S.,Huafan University
International Journal of Advanced Manufacturing Technology | Year: 2011
This paper presents a novel multi-cut process planning method and a new electrode wear compensation method based on a machine vision system for threedimensional (3D) micro-electrical discharge machining (micro-EDM). Front wear and corner wear of tool electrode can be measured and compensated in a direct manner by the vision system's image processing software capabilities. Experiments have shown that corner wear ratio (defined as a ratio between the length of corner wear and electrode diameter) is linearly proportional to machining length under a fixed machining depth condition. Track overlapping between the two adjoining paths is designed appropriately according to the corner wear ratio. Experimental results not only indicate that the proposed multi-cut process planning and electrode wear compensation methods can significantly improve machining accuracy and reduce machining time for the micro-EDM process, they also demonstrate that the X-Y dimensional errors of micro-structures can be controlled within 10 μm.
Wang Y.-C.,Huafan University |
Chien C.-J.,Huafan University
International Journal of Fuzzy Systems | Year: 2013
In this paper, a fuzzy neural network (FNN) based discrete adaptive iterative learning controller (AILC) is proposed for a class of discrete-time uncertain nonlinear plants which can repeat a given task over a finite time sequence. Compared with the existing discrete AILC schemes, the proposed strategy can be applied to the discrete-time uncertain nonlinear plants with not only initial resetting errors and iteration-varying desired trajectory, but also random bounded disturbances and unknown non-Lipschitz plant nonlinearities. Two FNNs are used as approximators to compensate for the unknown plant nonlinearities. To overcome the function approximation error and possibly large random bounded disturbance, a time-varying boundary layer is introduced to design an auxiliary error function. The auxiliary error function is then utilized to derive the adaptive laws since the optimal FNN parameters for a good function approximation and the optimal width of time-varying boundary layer are unavailable. By using a Lyapunov like analysis, we show that the closed-loop is stable in the sense that the adjustable parameters and internal signals are bounded for all the iterations. Furthermore, learning performance is guaranteed in the sense that the norm of output tracking error vector will asymptotically converge to a residual set which is bounded by the width of boundary layer. © 2013 TFSA.
Chen J.-C.,Huafan University
Environmental Earth Sciences | Year: 2011
This study investigates the variations in the critical conditions for debris-flow occurrence before and after the Chi-Chi earthquake in the Chen-Yu-Lan watershed, Taiwan. Topographical and rainfall parameters such as the gully gradient, drainage area, rainfall intensity, cumulative rainfall, and rainfall duration in the Chen-Yu-Lan watershed were used to analyze the conditions of debris-flow occurrence over the past 25 years. A recovery equation was proposed on the basis of rainfall parameters and used to determine the variations in the critical line of rainfall that trigger debris flow after the earthquake and to evaluate the recovery period required for the rainfall threshold of debris-flow occurrence after the earthquake to return to that before the earthquake in the watershed. The critical line for the runoff parameter versus gully gradient in the watershed was also presented. © 2011 Springer-Verlag.
Lee C.-Y.,National Ilan University |
Lee Z.-J.,Huafan University
Applied Soft Computing Journal | Year: 2012
Unbalanced data that are minority classes with few samples presented in many fields. The mean of unbalanced data is difficult to formalize so that traditional algorithms are limited in solving unbalanced data. In this paper, a novel algorithm based on analysis of variance (ANOVA), fuzzy C-means (FCM) and bacterial foraging optimization (BFO) is proposed to classify unbalanced data. ANOVA can measure the difference between the means of two or more groups in which the observed variance is partitioned into components due to various explanatory variables. FCM is a method of fuzzy clustering algorithm that allows one piece of data to belong to two or more clusters. Natural selection tends to eliminate animals with poor foraging strategies and favors the propagation of genes of those animals that have successful foraging strategies. BFO can model the mechanism of natural selection and solve many application problems. The proposed algorithm combines the advantages of ANOVA, FCM and BFO. ANOVA has the ability to select beneficial feature subsets. FCM has the ability to identify data into clusters with certain membership degrees, and BFO has the fast ability to converge to global optima. In this paper, microarray data of ovarian cancer and zoo dataset are used to test the performance for the proposed algorithm. The performance of the proposed algorithm is supported by simulation results. From simulation results, the classification accuracy of the proposed algorithm outperforms other existing approaches. © 2012 Elsevier B.V.
Chuang C.-C.,National Ilan University |
Lee Z.-J.,Huafan University
Applied Soft Computing Journal | Year: 2011
In this study, a hybrid robust support vector machine for regression is proposed to deal with training data sets with outliers. The proposed approach consists of two stages of strategies. The first stage is for data preprocessing and a support vector machine for regression is used to filter out outliers in the training data set. Since the outliers in the training data set are removed, the concept of robust statistic is not needed for reducing the outliers' effects in the later stage. Then, the training data set except for outliers, called as the reduced training data set, is directly used in training the non-robust least squares support vector machines for regression (LS-SVMR) or the non-robust support vector regression networks (SVRNs) in the second stage. Consequently, the learning mechanism of the proposed approach is much easier than that of the robust support vector regression networks (RSVRNs) approach and of the weighted LS-SVMR approach. Based on the simulation results, the performance of the proposed approach with non-robust LS-SVMR is superior to the weighted LS-SVMR approach when the outliers exist. Moreover, the performance of the proposed approach with non-robust SVRNs is also superior to the RSVRNs approach. © 2010 Elsevier B.V. All rights reserved.
Li H.-Y.,Huafan University |
Chiang M.-H.,Huafan University
International Journal of Heat and Mass Transfer | Year: 2011
This work investigates the effects of a shield on the thermal and hydraulic characteristics of plate-fin vapor chamber heat sinks under cross flow cooling. The surface temperature distributions of the vapor chamber heat sinks are measured using infrared thermography. The thermal-fluid performance of vapor chamber heat sinks with a shield is determined by varying the fin width, the fin height, the fin number and the Reynolds number. The experimental data thus obtained are compared with those without a shield. Experimental results indicate that the maximum surface temperature of the vapor chamber heat sink is effectively reduced by adding the shield, which forces more cooling fluid into the inter-fin channel to exchange heat with the heat sink. However, using the shield increases the pressure drop across the heat sink. The experimental data also show that the enhancement of the heat transfer increases with the Reynolds number, but the improvement declines as the Reynolds number increases. When the pumping power and heat transfer are simultaneously considered, vapor chamber heat sinks with thinner, higher or more fins exhibit better thermal-hydraulic performance. © 2010 Elsevier Ltd. All rights reserved.
Huafan University | Date: 2011-10-20
An operation circuit and an operation method thereof are revealed. The operation circuit includes an extreme value processing unit, a curve processing module, and a component unit. The extreme value processing unit receives and processes a plurality of input data to get maximum values and minimum values. The curve processing module constructs a first matrix and a second matrix according to the maximum and minimum values and then decomposes the first matrix and the second matrix into first submatrices and second submatrices respectively. According to these submatrices, the curve processing module gets at least one mean value function corresponding to the maximum and the minimum values. The computation of a single matrix is reduced by matrix decomposition and operations of the operation circuit. Compared with conventional Gauss matrix manipulations that run by computer systems, the present invention can be applied to simpler circuits by simplifying matrix operation processes.
Huafan University | Date: 2015-05-11
The present invention provides a portable sensing and operational device, which uses a sensing module to receive the sensing signal transmitted by the sensor and produce a sensing datum correspondingly. Then an operational circuit operates a first matrix and a second matrix according to the sensing datum. The first matrix corresponds to a plurality of maximum values; the second matrix corresponds to a plurality of minimum values. The operational circuit operates to generate at least a component by decomposing the first matrix and the second matrix. The component is provided to an output circuit for outputting the component to an electronic device.
Jeng C.-J.,Huafan University |
Lin T.-A.,Huafan University
Soils and Foundations | Year: 2011
Huafan University is located on the slope of the Ta-Lun Mountain area. The slope surface in this area is a colluvium soil cover layer with loose non-uniform particles, with high permeability. Because it is situated above a rapidly changing water table, the pore water pressure varies dynamically, depending on the weather conditions. In the dry season, most of the topsoil behaves in the unsaturated condition such that the matrix suction in the soil increases its shearing strength. In contrast, when heavy rainfall occurs, the seepage by precipitation tends to destroy the existing matrix suction. This reduction in soil strength frequently results in slope failure. This study, focuses on the variation of matrix suction of the colluvium soil in different precipitation conditions with varying vegetation at the campus of Huafan University. The analysis of the in-situ monitoring results and the laboratory test results for the undisturbed specimens taken from the field, with shearing strength and matrix suction taken into account. It is expected the results to be a useful reference for disaster protection on slopes.