Jincheng, Taiwan
Jincheng, Taiwan

National Quemoy University is a national university, located in Jinning Township, Kinmen, Fujian, Republic of China. NQU offers a variety of academic programs. They are divided into three categories: 1. undergraduate program, 2. graduate program, and 3. continuing education program. Wikipedia.


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Monitoring and measuring the maximum power of solar modules in real time is essential for evaluating the performance of a solar electric system. In order to monitor the rapidly fluctuating output power of high-concentration photovoltaic (HCPV) modules, a simplified maximum power point (MPP) estimation and measuring system is presented in this paper. The fractional open-circuit voltage (FOCV) technique and a controllable electronic load circuit were proposed to estimate and measure the MPP. The feasibility of using the FOCV technique on HCPV modules was evaluated, the results of which demonstrate the maximum voltage and power estimation accuracy of the experimental modules. The main advantages of this simplified HCPV MPP measurement system are rapid response time, low complexity, and ease of implementation. © 2014 IEEE.


Feng H.-M.,National Quemoy University | Liao K.-L.,National Quemoy University
Information Sciences | Year: 2014

This study develops a hybrid evolutionary fuzzy learning algorithm that automatically determines the near optimal traveling path in large-scale traveling salesman problems (LSTSPs). Identifying solutions for LSTSPs is one of the most complicated topics in the field of global combinatorial optimization problems. The proposed hybrid evolutionary fuzzy learning scheme combines the advantages of the adaptive fuzzy C-means (FCM), simple MAX-MIN merging concept, simulated annealing (SA) learning algorithm and an efficient table transform-based particle swarm optimization (TPSO). This study uses the proposed method to deal with the large-size TSP routing system. The evolutionary TPSO learning algorithm is applied to optimize the traveling table, which in turn extracts the appropriate traveling table sequence codes for approaching the shorter traveling path. The SA local optimal learning algorithm works after the TPSO learning scheme, using three operators to acquire the optimal traveling solution, inversion, translation and switching. The other considerable notation is to divide the large-scale cities into suitable subgroup cities to improve the efficiency of training machine. The popular FCM algorithm is a valid unsupervised clustering method that identifies the relational grades of a given traveling city dataset, separating them into popular categories. Based on the critical issue in maximal city number to break the city nodes of the traveling loop, and reconnect suitable nodes again with the minimal distance searching procedure, the proposed simple but powerful MAX-MIN merging algorithm to rebuild the new traveling path. Various sizes of TSP testing instances reveal that the developed hybrid evolutionary fuzzy learning algorithm achieves better results than other learning methods in both the quality of routing and computing time. © 2014 Elsevier Inc. All rights reserved.


Tsai T.-H.,National Quemoy University
Transportation Research Part C: Emerging Technologies | Year: 2014

Accurate short-term arrival forecasting is essential information for railway operators to conduct daily operations such as demand management strategies. Conventional time series methods apply historical arrival data which is the accumulation of reservations to project future arrivals. This study aims to utilize reservation data directly and proposes a novel advanced booking model by using the framework of case-based reasoning. The proposed model contains four modules with distinctive functions for similarity evaluation, instance selection, arrival projection, and parameter search. We have the constructed model tested on fourteen daily arrival series and compared its out-of-sample accuracy with that of four traditional benchmarks. The empirical results show that in average the proposed self-learning model may reduce at least 11% of mean square errors (MSE). Moreover, the learning scheme in the model may achieve significant reduction of MSE comparing with performance of other naïve versions. © 2013 Elsevier Ltd.


Ke C.-H.,National Quemoy University
KSII Transactions on Internet and Information Systems | Year: 2012

The ever-increasing demand for H.264 scalable video coding (H.264/SVC) distribution motivates researchers to devise ways to enhance the quality of video delivered on the Internet. Furthermore, researchers and practitioners in general depend on computer simulators to analyze or evaluate their designed network architecture or proposed protocols. Therefore, a complete toolset, which is called myEvalSVC, for evaluating the delivered quality of H.264/SVC transmissions in a simulated environment is proposed to help the network and video coding research communities. The toolset is based on the H.264 Scalable Video coding streaming Evaluation Framework (SVEF) and extended to connect to the NS2 simulator. With this combination, people who work on video coding can simulate the effects of a more realistic network on video sequences resulting from their coding schemes, while people who work on network technology can evaluate the impact of real video streams on the proposed network architecture or protocols. To demonstrate the usefulness of the proposed new toolset, examples of H.264/SVC transmissions over 802.11 and 802.11e are provided. © 2012 KSII.


Chen R.-S.,National Quemoy University | Liu I.-F.,Oriental Institute of Technology
Computers and Education | Year: 2013

To strengthen the information technology skills of students living in remote areas, the Ministry of Education of Taiwan advocated the 2008 Country Development Plan to diminish the gap between urban and rural education development. This study proposes a hypothetical model to evaluate the effectiveness of the government policy in decreasing the Rural-Urban Knowledge Divide in higher education. There were 427 participants in this study. From the research results, we found that the government policy had a significant impact on reducing the Rural-Urban Knowledge Divide in higher education, and it demonstrated that most hypotheses were supported. Finally, as a virtual teacher or classroom for students living in rural areas, this research provides several suggestions as strategies in building up prospective resources for a Digital Opportunity Center or e-learning environment beneficial for both rural and urban students.© 2013 Elsevier Ltd. All rights reserved.


Chen J.-D.,National Quemoy University
Microelectronics Journal | Year: 2011

This paper presents a wideband mixer chip covering the frequency range from 3.4 to 6.8 GHz using TSMC 0.18 μm CMOS technology. The linearity can be improved using multiple-gated-transistors (MGTR) topology. The measured 3-dB RF frequency bandwidth is from 3.1 to 6.8 GHz with an IF of 10 MHz. The measured results of the proposed mixer achieve 7.2-4.3 dB power conversion gain and 2-3 dBm input third-order intercept point (IIP3), and the total dc power consumption of this mixer including output buffers is 2.9 mW from a 1 V supply voltage. The current output buffer is about 2.17 mW, and the excellent LO-RF isolation achieved up to 54 dB at 5 GHz. The paper presents a mixer topology that is very suitable for low-power in ultra-wideband system applications. © 2010 Elsevier Ltd. All rights reserved.


Feng H.-M.,National Quemoy University | Chou H.-C.,National Quemoy University
Expert Systems with Applications | Year: 2011

An artificial neural prediction system is automatically developed with the combinations of step wise regression analysis (SRA), dynamic learning and recursive-based particle swarm optimization (RPSO) learning algorithms. In the first stage, the SRA can be considered like a data filtering machine to choose two primary factors from 20 channel technical indexes as input variables of the RBFNs system. Then, an efficient dynamic learning algorithm is applied to sequentially generate RBFs functions from training data set, where it can efficiently determine the proper number of RBFs' centers and their associated positions. It can be exploited to forecast appropriate behaviors of the wanted identified financial time series data. While characteristics of training data set are automatically mined and generated by the proposed dynamic learning algorithm, architecture of the RBFNs prediction system is initially represented with collected information. Moreover, the RPSO learning scheme with the hybrid particle swarm optimization (PSO) and recursive least-squares (RLS) learning methods are applied to extract those appropriate parameters of the RBFNs prediction system. The RBFNs prediction systems are implemented in data analysis, module generation and price trend of the financial time series data. It not only automatically determines proper RBFs number but also fast approach the desired target in actual trading of Taiwan stock index (TAIEX). Computer simulations in training and testing phases of historic TAIEX are compared with other learning methods, which illustrate our great performance not only increases the accuracy of the stock price prediction but also improves the win rate in the trend of TAIEX. © 2011 Elsevier Ltd. All rights reserved.


Weng K.-W.,National Quemoy University | Huang Y.-P.,National Quemoy University
Surface and Coatings Technology | Year: 2013

High concentration photovoltaic (HCPV) systems improve their long-term stability in terms of sunlight concentration by using silicone-on-glass (SOG) composite optic lenses with glasses. Due to dust pollution, reflectance of the concentrator glasses significantly decreases the output power efficiency of a solar power system. Titanium dioxide (TiO2) films are known for their hydrophilic and photocatalytic characteristics. This study investigates the effects of introducing third elements in a-TiO2 films by implantation, to enhance the photocatalytic and hydrophilicity properties, as well as widen the wavelength sensitization range. TiO2-based hydrophilic and photocatalytic films on glass for self-cleaning purposes were prepared. The implant elements are Fe, Cr, and V. The samples are prepared by a hybrid system consisting of physical vapor deposition (PVD) and metal plasma ion implantation (MPII). High quality TiO2 films are first fabricated by r.f. magnetron sputtering system, followed by metal plasma ion implantation of Fe. Experimental results indicate that the hybrid processing method significantly increases the activation and sunlight absorption rate of TiO2 thin films with the addition of third elements. Moreover, the proposed TiO2-Fe thin film exhibits superior hydrophilicity properties with a contact angle of 9.95° and reduces the optical bandgap to 3.33eV. © 2012 Elsevier B.V.


The military landscape of Kinmen is an historical treasure left behind following the threat of war. Kinmen used to be a key military location of high strategic value, and witnessed some decisive victories battles. However, owing to rapid developments in the worldwide landscape and changes in cross-strait relations, Kinmen has been transformed from a high-alert military fortification to a famous group of islands that attract many tourists. In the last few years, the issue of climate change has increased the public's environmental awareness. In dedication to this issue, Kinmen is aggressively pursuing the construction of an energy-efficiency management network. As the current overall power supply for the Kinmen mainly from thermal power, Kinmen is hoping that by developing greener sources of energy it can play a role in the worldwide campaign to address the problems of global warming. In order to achieve the goal, the first focus should be on the best method of making good use of the natural resources of the islands - solar and wind power - and the integration of these natural resources with the unique resource of the islands - military installations. Kinmen needs to rethink the application and management of the regeneration of the abandoned military installations. By applying the approach proposed in this paper, Kinmen could develop a renewable energy scheme with distributed power systems to replace the centralized power plants. In addition to the unique characteristics of Kinmen's existing ecology and cultural history, the feasible development of renewable energy sources by integration with surplus military installations will convert Kinmen into an area with the unique combined characteristics of environmental education and tourism. © 2011 Elsevier Ltd.


Patent
National Quemoy University | Date: 2014-02-25

The present invention discloses a smart photographing apparatus, comprising a casing, a first photographing module, a second photographing module, and a control module. The first photographing module comprises a sensing lens installed on one side of the casing to capture eye motion images when a photographer is blinking. The second photographing module comprises a photographing lens installed on the other side of the casing to execute an image capturing function of shooting an image of a target. The control module is connected to the first photographing module and the second photographing module, and the control module generates an image capturing instruction upon receiving the eye motion images and controls the second photographing module to execute the image capturing function according to the image capturing instruction.

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