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Hsinchu, Taiwan

Hsuan Chuang University is a private Buddhist university in Hsinchu, Taiwan. Founded in 1997 by the Ven. Liao Zhong , and named for the Tang Dynasty monk Xuanzang, the school was promoted to university status in 2004. It offers bachelors and masters degrees, mainly in humanities subjects. Wikipedia.

Huang J.-Y.,Hsuan Chuang University
Journal of Forensic Psychiatry and Psychology | Year: 2016

Rape committed during adolescence is a vital indicator for predicting the propensity of committing rape in adulthood. Moreover, although numerous studies related juvenile rape have been proposed in Western countries, most of these studies have focused on the impact of personal factors, and have neglected to examine the impact of rape myths. Therefore, in the present study, we investigated the relationship between rape myths and male juvenile rape. This study used an anonymous self-report questionnaire to collect data. Participants included 466 male middle- and high-school students in Taiwan. The results showed that rape myths are associated with juvenile rape. Furthermore, rape victim myths were the myth category relating to juvenile rape, rather than rape perpetrator myths. Among the rape victim myths, the dimension, women secretly wish to be raped, had the strongest association. Discussions pertaining to implications, applications, limitations, and future research are included in the present study. © 2016 Informa UK Limited, trading as Taylor & Francis Group.

Chiang C.I.,Hsuan Chuang University | Hwang M.J.,National Chiao Tung University | Liu Y.H.,University of Nebraska at Omaha
Mathematical and Computer Modelling | Year: 2011

A separation method to be used for locating a set of weights, also known as a common set of weights (CSW), in the Data Envelopment Analysis (DEA) is proposed in this work. To analyze the methods of finding the CSW, it is necessary to solve a particular form of a multiple objectives fractional linear programming problem (MOFP). One of the characteristics of this particular MOFP is that the decision variables can be separated into two parts; one part of variables present in the numerator and the other part of variables present in the denominator. Based on this characteristic, this research utilized an auxiliary vector to convert the MOFP to a single objective linear programming to obtain a CSW for calculating the DMU's efficiency ratio. Finally, the developed method is applied to analyze the data of the last Beijing Olympic Games. © 2011 Elsevier Ltd.

Tsai Y.-H.,Hsuan Chuang University
International Journal of Innovative Computing, Information and Control | Year: 2010

Image thresholding is one of the most powerful techniques for image segmentation, but it is not always satisfactory in applications under uneven illuminations. Adaptive image thresholding is used to find the optimal window for solving the illumination problem. In this paper, a novel window selection method for adaptive local thresholding is proposed. Based on simulated annealing, the proposed algorithm searches the optimal window among partitioned subimages on the quadtree data structure from bottom up. It can be applied to other existing methods to improve the performance of image thresholding. Experimental results show the efficiency of the proposed method. © 2010 ISSN 1349-4198.

Chang K.-L.,Hsuan Chuang University
British Food Journal | Year: 2013

Purpose: The aim of this paper is to integrate the analytic network process (ANP) and a technique for order preference by similarity to the ideal solution (TOPSIS) to help Taiwanese managers in century-old food industry firms make better decisions for new product development (NPD) project selection. Design/methodology/approach: The balanced scorecard (BSC) which links financial and non-financial, tangible and intangible, inward and outward factors can provide an integrated viewpoint for decision makers in selecting optimal NPD projects. Considering the interrelated perspectives and criteria of BSC, ANP is used to obtain the weights of the criteria. TOPSIS is used for simplifying ANP to rank the alternatives. After reviewing the literature on BSC, the study collected criteria for selecting optimal NPD projects. Likert nine-point scale questionnaires based on the BSC criteria were received from 34 senior executives to obtain the importance of criteria. Findings: Based on the geometric mean values, the top 12 criteria are: Capabilities, Well-being, Satisfaction, Lead-time, Risk, Facility, Reputation, Loyalty, New customer, Market, Profitability and New market to structure the hierarchy for century-old Taiwanese food business NPD project selection. Practical implications: Using the hierarchy based on four perspectives and 12 important criteria, century-old Taiwanese food businesses may select the optimal NPD projects more effectively. Moreover, the practical application of the proposed approach illustrated is generic and also suitable for century-old Taiwanese food businesses. Originality/value: In 2008, Taiwan External Trade Development Council (TAITRA) established an association to help century-old businesses to maintain growth and competitive advantage. To maintain continuous competitive advantage, developing new products is necessary. However, NPD is a risky process. The vital issue in NPD is how to select the optimal projects for new products. The majority of century-old Taiwanese businesses are in the food industry. This paper contributes to a more effective selection of optimal NPD projects for century-old Taiwanese food firms. © Emerald Group Publishing Limited.

Chiang C.-H.,Hsuan Chuang University
Lecture Notes in Electrical Engineering | Year: 2013

The well-known ANFIS (adaptive-network-based fuzzy inference system) has demonstrated good performance and applicability. This chapter presents a quantum version of ANFIS model, namely, qANFIS, whose network structure is similar to ANFIS but it is with quantum membership functions (qMF). A hybrid learning procedure is proposed to update the parameters. First, we develop a genetic algorithm with trimming operator to determine the number of quantum levels in qMF. Second, the least squares estimate method is applied to update the consequent parameters. Finally, we introduce two methods to update the qMF parameters, the gradient descent and the quantum-inspired particle swarm optimization methods, and one of them is selected for training purpose. The simulation results of path planning had demonstrated that the proposed method could reach satisfactory performance and smaller error measure as compared with ANFIS. © 2013 Springer Science+Business Media New York.

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