Yilan, Taiwan

Fo Guang University

Yilan, Taiwan

Fo Guang University is a private university in Jiaoxi Township, Yilan County, Taiwan. It was founded by the Mahayana Buddhist Fo Guang Shan monastic order in 2000 and as such represents the culmination of education efforts of the order that started in 1963 with establishing Chinese Buddhist Research Institute at Fo Guang Shan.A gradual approach was adopted in developing the campus as a part of a plan for the overall area. The Ministry of Education granted approval on July 20, 2000, and the school formally opened in September that year. The Schools of Humanities and Sociology were the first to be founded during the initial phase of establishment. By introducing the undergraduate and postgraduate level of education, Fo Guang University is gradually developing into a full-rounded university. Currently, it comprises the College of Arts and Humanities, College of Social science and Management, College of Technology, and College of Buddhist Studies. All programs are taught in Chinese Mandarin, with the exception of the MA program in Buddhism Studies, which has both Chinese and English tracks. A new Center for Buddhist Studies will open in early 2013. As of 2012-2013 academic year, its total enrollment is 3,400 students, including undergraduate and graduate students. The university library holds more than 253,000 volumes. Wikipedia.

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Lai C.-F.,Fo Guang University
International Journal of Energy Economics and Policy | Year: 2016

This paper constructed a two-period overlapping generations (OLG) model to investigate the effects of the energy tax on environmental quality (the first dividend) and output level (the second dividend) to review the double dividend effect of the energy tax. According to the results of comparative static analysis, we found that the energy tax can improve environmental quality but cannot affect the output level. This suggests that the double effect of the energy tax is not supported in the OLG model. This is because an agent can only survive two periods, and need to give consideration to the consumption level of two-generation and the environmental quality of second-generation for pursuing the maximization of lifetime utility, therefore, the agent must maintain consumption (output) stability, and the double dividend effect does not exist. © 2016, Econjournals. All right reserved.

Hsu M.-J.,Fo Guang University
Publishing Research Quarterly | Year: 2014

The main objective of this study was to understand the critically essential competences for digital publishing editors in digital era. The study firstly established a draft of the framework based on the literature review and document analysis in competences required for digital publishing editors, the draft in turn was used as the basis and merged with experts' opinions to establish the final Competence Framework. The study further designed the Delphi Technique Questionnaires according to the Competence Framework to obtain various competences deemed essential for digital publishing editors. The results of Delphi Technique Questionnaire Survey were 30 critically essential competences. © 2013 Springer Science+Business Media New York.

Wang S.-W.,Fo Guang University
Telecommunication Systems | Year: 2013

In all-optical WDM networks, splitters at branch nodes are used to realize multicast trees. The problem of selecting a subset of nodes to place the splitters such that certain performance measure is optimized is called the splitter placement problem. This paper studies the splitter placement problem in all-optical WDM networks in which a light-forest is used to realize a multicast connection. The goal is to place a given number of splitters in the network such that the average per link wavelength resource usage of multicast connections is minimized. An upper bound and a lower bound on the per link average wavelength resource usage are derived. Two splitter placement methods are proposed for this problem. The proposed splitter methods are shown to yield significant lower average wavelength resource usage than the random placement method. One of the methods is shown to produce near minimum average wavelength resource usage. © 2011 Springer Science+Business Media, LLC.

Suryani E.,National Taiwan University of Science and Technology | Chou S.-Y.,National Taiwan University of Science and Technology | Chen C.-H.,Fo Guang University
Expert Systems with Applications | Year: 2010

This paper deals with how to develop a model to forecast air passenger demand and to evaluate some policy scenarios related with runway and passenger terminal capacity expansion to meet the future demand. System dynamics frameworks can be used to model, to analyze and to generate scenario to increase the system performance because of its capability of representing physical and information flows, based on information feedback control that are continuously converted into decisions and actions. We found that airfare impact, level of service impact, GDP, population, number of flights per day and dwell time play an important roles in determining the air passenger volume, runway utilization and total additional area needed for passenger terminal capacity expansion. © 2009 Elsevier Ltd. All rights reserved.

This paper proposes a new dynamic-alternate routing algorithm and its corresponding converter placement algorithm in order to reduce the connection blocking probability for all-optical WDM networks. The main idea in the proposed dynamic-alternate routing algorithm is to try to route the traffics according to a predefined optimal probability distribution. The problem for finding the optimal probability distribution was shown as a convex optimization problem. The problem can be solved by flow deviation method or other standard optimization techniques. Simulation results show that the proposed routing algorithm yields lower connection blocking probabilities than the previous works. The proposed routing algorithm produces similar traffic pattern as the optimal traffic pattern. The similarity between the traffic pattern produced by the proposed dynamic-alternate routing algorithm and the optimal traffic pattern can be further employed for solving other network designing problems such as converter placement problem. Since the optimal traffic pattern can be easily predicted, the optimal traffic pattern which minimizes the blocked traffic intensity is utilized for finding the locations of wavelength converters. The key idea is to place the wavelength converters at the nodes where they are needed most. Simulations have been performed to study the performance of the proposed wavelength converter placement method. The simulation results have shown that the proposed placement method combined with the proposed probability based dynamic-alternate routing algorithm yields smaller connection blocking probability than the two converter placement methods with their corresponding alternate routing algorithms. © 2012 Elsevier B.V. All rights reserved.

Lo J.-H.,Fo Guang University
Proceedings of the International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2011 | Year: 2011

For more than three decades, Box and Jenkins' Auto-Regressive Integrated Moving Average (ARIMA) technique has been one of the most widely used linear models in time series forecasting. However, it is well documented that many software failure observations are nonlinear and ARIMA is a general univariate model developed based on the assumption that the time series data being predicted are linear. Therefore, in this study, the utilization of Support Vector Machine (SVM) as a nonlinear model and ARIMA as a linear model are integrated in software reliability forecasting. Experiments on real-world data set validate the effectiveness of the hybrid model. These results also show that the proposed methodology can be a more effective way in order to combine linear and nonlinear models together than traditional methodologies. Therefore, it can significantly improve the prediction performance and can be applied as an appropriate alternative approach for software reliability forecasting field, especially when higher prediction performance is needed. © 2011 IEEE.

Deng G.-F.,National Chengchi University | Lin W.-T.,National Chengchi University | Lo C.-C.,Fo Guang University
Expert Systems with Applications | Year: 2012

This work presents particle swarm optimization (PSO), a collaborative population-based meta-heuristic algorithm for solving the Cardinality Constraints Markowitz Portfolio Optimization problem (CCMPO problem). To our knowledge, an efficient algorithmic solution for this nonlinear mixed quadratic programming problem has not been proposed until now. Using heuristic algorithms in this case is imperative. To solve the CCMPO problem, the proposed improved PSO increases exploration in the initial search steps and improves convergence speed in the final search steps. Numerical solutions are obtained for five analyses of weekly price data for the following indices for the period March, 1992 to September, 1997: Hang Seng 31 in Hong Kong, DAX 100 in Germany, FTSE 100 in UK, S&P 100 in USA and Nikkei 225 in Japan. The test results indicate that the proposed PSO is much more robust and effective than existing PSO algorithms, especially for low-risk investment portfolios. In most cases, the PSO outperformed genetic algorithm (GA), simulated annealing (SA), and tabu search (TS). © 2011 Elsevier Ltd. All rights reserved.

Lo J.-H.,Fo Guang University
2nd International Conference on Computer Research and Development, ICCRD 2010 | Year: 2010

Support vector machine (SVM) is a new method based on statistical learning theory. It has been successfully used to solve nonlinear regression and time series problems. However, SVM has rarely been applied to software reliability prediction. In this study, an SVM-based model for software reliability forecasting is proposed. In addition, the parameters of SVM are determined by Genetic Algorithm (GA). Empirical results show that the proposed model is more precise in its reliability prediction and is less dependent on the size of failure data comparing with the other forecasting models. © 2010 IEEE.

Lo J.-H.,Fo Guang University
Proceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010 | Year: 2010

With recent strong emphasis on rapid development of information technology, the decisions made on the basis of early software reliability estimation can have greatest impact on schedules and cost of software projects. Software reliability prediction models is very helpful for developers and testers to know the phase in which corrective action need to be performed in order to achieve target reliability estimate. In this paper, an SVM-based model for software reliability forecasting is proposed. It is also demonstrated that only recent failure data is enough for model training. Two types of model input data selection in the literature are employed to illustrate the performances of various prediction models. © 2010 IEEE.

Fang K.Y.,Fo Guang University
Proceedings - 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016 | Year: 2016

Jiaoxi hot springs are unique geographical resources known to Ilan County. It has been over a century since the development of hot spring hotels for commercial use during the Japanese Colonial Period. This study covers the analysis of the impact of endogenous development on the industrial tourism of hot springs through FeiXiaotong's theory of regional development. The micro-film "Temperature Record" used the hot spring industry as a starting point. Through university students' knowledge and exploration of regional terroir, the idea of hot spring agriculture not only promotes regional industrial development, but also enhances regional economic power. However, the hot spring season is unable to construct the connotation of the Jiaoxi hot spring culture. Through "Temperature Record," relative issues such as reflections on hot spring resources and sustainable regional development were put forth, in cooperation with the travel industry in this study who were traveling APP Hot springs depth design and testing. © 2016 IEEE.

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