Suppression of sidelobe levels for guided-wave acousto-optic tunable filters using weighted coupling

An analysis of guided-wave acousto-optic tunable filters (AOTFs) that employ simple acousto-optic (AO) weighted coupling techniques for sidelobe reduction and the calculated and experimental results from a specific example that involves only variation of the width of a surface acoustic wave (SAW) slot waveguide are presented. The calculations on single- and multi-stage AOTFs consisting of an optical channel waveguide and a SAW slot waveguide in LiNbO(3) substrate show that waveguide width weighting using generalized Hamming functions would provide significant improvement in sidelobe suppression. Calculated results together with the design, fabrication, and measured performance characteristics of a single-stage AOTF that utilizes a weighted-aperture SAW slot waveguide in YX-LiNbO(3) substrate at the optical wavelength of 1.55 mum and the acoustic center frequency of 175 MHz are reported. The measured sidelobe level is -13.6 dB and the measured FWHM bandwidth is 26 A, as compared to the theoretical values of -15.0 dB and 15 A, respectively. The RF drive power was measured to be 1.0 W at a mode-conversion efficiency of 100%     

On the optimal design of fuzzy neural networks with robust learningfor function approximation

A novel robust learning algorithm for optimizing fuzzy neural networks is proposed to address two important issues: how to reduce the outlier effects and how to optimize fuzzy neural networks, in the function approximation. This algorithm is able to reduce the outlier effects by cooperating with a conventional robust approach, and then to optimize fuzzy neural networks by determining the optimal learning rates which can minimize the next-step mean error at each iteration of our algorithm.     

Multi-layer thermoelectric-temperature-mapping microbial incubator designed for geo-biochemistry applications

We demonstrate a novel, vertical temperature-mapping incubator utilizing eight layers of thermoelectric (TE) modules mounted around a test tube. The temperature at each layer of the TE module is individually controlled to simulate the vertical temperature profile of geo-temperature variations with depth. Owing to the constraint of non-intrusion to the filled geo-samples, the temperature on the tube wall is adopted for measurement feedback. The design considerations for the incubator include spatial arrangement of the energy transfer mechanism, heating capacity of the TE modules, minimum required sample amount for follow-up instrumental or chemical analysis, and the constraint of non-intrusion to the geo-samples during incubation. The performance of the incubator is experimentally evaluated with two tube conditions and under four preset temperature profiles. Test tubes are either empty or filled with quartz sand, which has comparable thermal properties to the materials in the geo-environment. The applied temperature profiles include uniform, constant temperature gradient, monotonic-increasing parabolic, and parabolic. The temperature on the tube wall can be controlled between 20 °C and 90 °C with an averaged root mean squared error of 1 °C.     

Interactive augmented reality system for enhancing library instruction in elementary schools

Due to limited budgets and manpower, most elementary schools in Taiwan do not plan or provide library instruction for students. Although students can use libraries, they typically lack the knowledge needed to use library resources effectively. Consequently, students have difficulty finding the books they need and can easily become overwhelmed by the massive amount of information in libraries. Computer-assisted instruction for teaching basic library skills to large numbers of students is an appealing method. Particularly, developing augmented reality (AR) technologies for learning have garnered considerable attention in education research. Many researchers and scholars believe that integrating teaching and AR enhances student learning performance and motivation. This work develops an educational AR system based on situated learning theory, and applies innovative augmented reality interactive technology to a library’s learning environment. Student library knowledge can be enhanced via the proposed augmented reality library instruction system (ARLIS). Experimental results demonstrate that student learning performance is improved significantly by using the proposed ARLIS. Moreover, this work demonstrates that using the proposed ARLIS for library instruction results in the same learning performance as conventional librarian instruction and there is no gender difference on learning performance between the proposed ARLIS and conventional librarian instruction. Moreover, the proposed library instruction system overcomes shortcomings of personal teaching skills of librarians that may adversely affect student learning performance by conveying the same learning content to all students. Additionally, the proposed system results in better learning performance for learners with the field-dependent cognitive style than learners with the field-independent cognitive style. Further, the proposed system provides more benefits in terms of library skills of application and comprehension than conventional librarian instruction. Moreover, the learning performance of students is not affected by their gaming skills. Therefore, student gaming skills do not need to be considered when adopting the proposed system in library instruction programs.     

Preliminary cost estimates for thin-film transistor liquid–crystal display inspection and repair equipment: A hybrid hierarchical approach

The thin-film transistor liquid–crystal display (TFT-LCD) industry has developed rapidly in recent years. Because TFT-LCD manufacturing is highly complex and requires different tools for different products, accurately estimating the cost of manufacturing TFT-LCD equipment is essential. Conventional cost estimation models include linear regression (LR), artificial neural networks (ANNs), and support vector regression (SVR). Nevertheless, in accordance with recent evidence that a hierarchical structure outperforms a flat structure, this study proposes a hierarchical classification and regression (HCR) approach for improving the accuracy of cost predictions for TFT-LCD inspection and repair equipment. Specifically, first-level analyses by HCR classify new unknown cases into specific classes. The cases are then inputted into the corresponding prediction models for the final output. In this study, experimental results based on a real world dataset containing data for TFT-LCD equipment development projects performed by a leading Taiwan provider show that three prediction models based on HCR approach are generally comparable or better than three conventional flat models (LR, ANN, and SVR) in terms of prediction accuracy. In particular, the 4-class and 5-class support vector machines in the first-level HCR combined with individual SVR obtain the lowest root mean square error (RMSE) and mean average percentage error (MAPE) rates, respectively.     

Optimal expansion of competence sets with multilevel skills

The purpose of competence set expansion is to find an optimal expansion process at the minimal cost and then obtain the required competence set from the acquired competence set to solve a problem. Several models have been proposed to address the competence set expansion problem of only a single decision maker or multiple decision makers without considering multilevel skills. However, a practical competence set expansion model should involve multiple decision makers and multilevel skills. This study discusses an optimal expansion model of incorporating competence sets of group decision makers with multilevel skills. The proposed method not only obtains the optimal competence set expansion of all decision makers with the maximal total benefit but finds all optimal alternatives of the competence set expansion model. A cooperative alliance problem is solved to illustrate the usefulness of the proposed method.     

The effect of moderator’s facilitative strategies on online synchronous discussions

Moderators play an important role within a computer supported collaborative learning environment, and thus facilitative strategies and communication technology are nowadays used to enhance students’ learning. This study proposed facilitative strategies as a guide for students’ learning, and explored the influence of these strategies on the students’ online synchronous discussion. A total of 331 senior high school students from eight computer classes in northern Taiwan were recruited to participate in this study. They were randomly assigned into an experimental condition, with the moderators’ facilitation to complete online learning tasks, and the control condition without moderators’ support. To fulfill the goal of the research, four strategies—helping students focus on the main topic, facilitating students’ making argumentation, giving students positive feedback, and helping students sustain threaded discussion—were adopted to facilitate the online synchronous discussion in the experimental condition. According to the results of the content analysis, four group discussion patterns were revealed, including collaboration, centralization, partial contribution, and non-interaction. The findings suggest that the moderator helped enhance the collaboration pattern and increase the online participation rate. In addition, it was found that the strategies of helping students focus on the main topic and giving students positive feedback were frequently employed.     

From immediate agreement to eventual agreement: early stopping agreement protocol for dynamic networks with malicious faulty processors

With the rapid advancement of wireless networking technology, networks have evolved from static to dynamic. Reliability of dynamic networks has virtually become an important issue. Fortunately, a solution to the above issue can be derived from solutions to the Byzantine Agreement (BA) problem. BA problem can be solved by protocols that make processors reach an agreement through message exchange. Protocols used to solve the problem can be divided into Immediate Byzantine Agreement (IBA) protocols and Eventual Byzantine Agreement (EBA) protocols. In IBA protocols, the number of rounds of message exchange is determined by the total number of processors in the network. Even if no faulty processor is present in the network, IBA protocols still require a fixed number of rounds of message exchange, causing a waste of time. In contrast, EBA protocols dynamically adjust the number of rounds of message exchange according to the interference of faulty processors. In terms of efficiency, EBA protocols certainly outperform IBA protocols. Due to the fact that the existing EBA protocols have been designed for static networks, they cannot work on dynamic networks. In this paper, we revisit the EBA problem in dynamic networks to increase the reliability of dynamic networks. Simulations will be conducted to validate that the proposed protocol requires the minimum rounds of message exchange and can tolerate the maximum number of malicious faulty processors compared to other existing protocols.