Student Perspectives on Reflective Writing, Improvisation, and Cooperative and Peer Learning in a Collegiate Aural Skills Course

Student-centered instructional approaches that directly engage the learner in problem-solving activities and emphasize social interaction in the construction of knowledge are known to be much more effective than traditional teaching methods. While music educators also claim to espouse these views, these strategies have yet to infiltrate the area of aural skills pedagogy, where the mode of instruction often remains limited to traditional repetition and drill. In an effort to update and improve the Ear Training and Sight Singing (ETSS) curriculum at Linfield, reflective writing, improvisation, and cooperative and peer-learning activities were integrated into the course for the 2012-2013 academic year. This study examined the efficacy of these new approaches by comparing students’ experiences, progress, and assessments to those of previous years. Though a comparison of final exam scores did not reveal a statistically significant difference in achievement, results suggest reflective writing was particularly effective for students in increasing self-awareness, organizing and reinforcing learning, increasing retention of course material, and providing opportunities for self-assessment. Data revealed a mixed effectiveness for cooperative and peer-learning activities that is often dependent on a variety of factors including the nature and goals of the activity or assignment and the level of disparity in abilities between partners. Benefits include increased accountability, motivation and practice

A Case Study: Influence of Circuit Impedance on the Performance of Class-E² Resonant Power Converter for Capacitive Wireless Power Transfer

The evolution of power electronics led to rapid development in wireless charging technology; as a result, a single active switch topology was introduced. The present market utilizes inductive wireless power transfer (IPT); because of the disadvantages of cost, size, and safety concerns, research on wireless power transfer was diverted towards capacitive wireless power transfer (CPT). This paper studies the optimal impedance tracking of the capacitive wireless power transfer system for maximum power transfer. Compared to prior methods developed for maximum power point tracking in power control, this paper proposes a new approach by means of finding impedance characteristics of the CPT system for a certain range of frequencies. Considering the drone battery as an application, a single active switch Class-E2 resonant converter with circular coupling plates is utilized. Impedance characteristics are identified with the help of equations related to the input and resonant impedance. The impedance tracking is laid out for various resonant inductors, and the difference in current peak is observed for each case. Simulations verify and provide additional information on the reactive type. Additionally, hardware tests provide the variation of input current and output voltage for a range of frequencies from 70 kHz to 300 kHz. Efficiency at the optimal impedance points for a resonant inductor with 50 μH and 100 μH are tested and analyzed. It is noted that the efficiency for a resonant inductor with 50 μH is 8% higher compared to the CPT with a 100 μH resonant inductor. Further hardware tests were performed to investigate the impact of frequency and duty cycle variation. Zero-voltage-switching (ZVS) limits have been discussed with respect to both frequency and duty cycle

ASDN: A Deep Convolutional Network for Arbitrary Scale Image Super-Resolution

Deep convolutional neural networks have significantly improved the peak signal-to-noise ratio of SuperResolution (SR). However, image viewer applications commonly allow users to zoom the images to arbitrary magnification scales, thus far imposing a large number of required training scales at a tremendous computational cost. To obtain a more computationally efficient model for arbitrary scale SR, this paper employs a Laplacian pyramid method to reconstruct any-scale high-resolution (HR) images using the high-frequency image details in a Laplacian Frequency Representation. For SR of small-scales (between 1 and 2), images are constructed by interpolation from a sparse set of precalculated Laplacian pyramid levels. SR of larger scales is computed by recursion from small scales, which significantly reduces the computational cost. For a full comparison, fixed- and any-scale experiments are conducted using various benchmarks. At fixed scales, ASDN outperforms predefined upsampling methods (e.g., SRCNN, VDSR, DRRN) by about 1 dB in PSNR. At any-scale, ASDN generally exceeds Meta-SR on many scales

A New Method of Detecting and Interrupting High Impedance Faults by Specifying the Z-Source Breaker in DC Power Networks

High impedance faults (HIFs) that cause a relatively smaller current magnitude compared to the traditional low impedance faults are not easily detectable but can cause an extreme threat to electric apparatus and system operation. This paper introduces a new method of detecting and interrupting HIFs in DC power networks by specifying Z-source circuit breakers (ZCBs). The ZCB is a protective device for high power DC branches, with the capabilities of protecting bidirectional power flow and automatic/controllable turnoff function. In this new method, the operational mode of ZCB (i.e., either the detection mode or interruption mode) can be specified. Beyond previous research, the theoretical analysis has been performed on this method and the mathematical relationship between the maximum HIF resistance and required Z-source capacitance has been derived and verified. It has been found that the ZCB can respond to a HIF accordingly when its capacitances are properly adjusted in the ZCB circuit. With the adjustment of these Z-source capacitances, the ZCB can be specified to detect and report a HIF status to power system operators, or cut off the HIF branch and protect the rest of the DC system directly. The new method can detect/interrupt a HIF that is as small as 2 times of its nominal rated current and the effectiveness and general usage of the derived equation have been verified by both low power experiments in lab and high power simulation tests

A Mathematical Method to Assess the Yin-Yang Balance of Commercial Complexes’ Entrances

Shopping malls are important landmarks of modern and sustainable cities as they are substantial business and investment by themselves, and as they also facilitate the social activities of communities. Entrances to shopping malls provide a first impression to customers, thus affecting the business performance of the malls. This paper presents a method to assess the entrances of modern shopping malls by applying traditionally qualitative Feng shui practices quantitatively with an innovative mathematical model. The assessment is based on the manipulation of the yin-and-yang concept applied to the layout of Ming tang (bright court) as the focus of consideration. By applying this novel approach to three shopping malls in Guangzhou, China as a pilot study to match their commercial performance, our hypothesis appears workable. The ideology of balancing yin and yang may be practically meaningful to urban planning and the successful measurement of such balance could shed light on future studies

Integrating experts’ weights generated dynamically into the consensus reaching process and its applications in managing non-cooperative behaviors

This work was supported in part by the NSF of China under grants 71171160 and 71571124, in part by the SSEM Key Research Center at Sichuan Province under grant xq15b01, in part by the FEDER funds under grant TIN2013-40658-P, and in part by Andalusian Excellence Project under grant TIC-5991.The consensus reaching process (CRP) is a dynamic and iterative process for improving the consensus level among experts in group decision making. A large number of non-cooperative behaviors exist in the CRP. For example, some experts will express their opinions dishonestly or refuse to change their opinions to further their own interests. In this study, we propose a novel consensus framework for managing non-cooperative behaviors. In the proposed framework, a self-management mechanism to generate experts' weights dynamically is presented and then integrated into the CRP. This self-management mechanism is based on multi-attribute mutual evaluation matrices (MMEMs). During the CRP, the experts can provide and update their MMEMs regarding the experts' performances (e.g., professional skill, cooperation, and fairness), and the experts' weights are dynamically derived from the MMEMs. Detailed simulation experiments and comparison analysis are presented to justify the validity of the proposed consensus framework in managing the non-cooperative behaviors.National Natural Science Foundation of China 71171160 71571124SSEM Key Research Center at Sichuan Province xq15b01European Union (EU) TIN2013-40658-PAndalusian Excellence Project TIC-599