A Quantitative Critical Thinking (QCT) software tool was developed in this study to facilitate students’ learning of quantitative critical thinking via repeated practice by chemical engineering students reading a core module called fluid-solid systems. The software tool generated detailed calculation steps to typical engineering design problems encountered in this module that contained weaknesses, flaws or even errors. Students utilized the software tool to practice identifying these weaknesses, flaws or errors in the design solutions and then present a better or correct design by applying the concepts and knowledge acquired in the module. Since the QCT software tool was built upon an existing design software tool that was able to generate the correct, detailed design calculation steps to design problems, students were able to check their own design calculations against those presented by the software tool during this second learning step, thereby engaging in and learning quantitative critical thinking via a repeated practice approach. The software tool was successful in enhancing the performance of second-year undergraduate students in solving a question that required quantitative critical thinking in the final examination of the module. The average percentage scores achieved by students for the question who reported higher frequencies of usage of the software were generally higher than those who reported lower frequencies of usage or did not utilize the software tool throughout the semester. 相似文献
To investigate the nonstoichiometric effect of (Bi0.5Na0.5)TiO3 (BNT) ceramics on their properties, we propose a novel chemical expression, (Bi0.5+xNa0.5−3x)TiO3. The nonstoichiometric effect of BNT can be explored in compounds with this composition without being hampered by the charge imbalance problem. With x ranging from −0.02 to 0.02, we find that the morphological, dielectric, ferroelectric, and electrostrain properties differ considerably between Na-rich and Bi-rich ceramic samples. The average grain size (AGS) increased significantly in Na-rich samples compared to that in stoichiometric BNT, while it decreased slightly in Bi-rich samples. The dielectric characteristics measured from 30 °C to 500 °C indicate that conductivity is activated in Na-rich nonstoichiometric samples but is effectively suppressed in Bi-rich nonstoichiometric samples. The ferroelectric properties also show the same trend. In Na-rich samples, elliptical polarization against electric field (P-E) hysteresis loops were detected, indicating a conductive character induced by high electric field loading. However, saturated P-E loops are observed in Bi-rich samples with well-inhibited conductivity. Furthermore, compared to stoichiometric BNT and nonstoichiometric x = 0.02 Bi-rich samples, (Bi0.5+xNa0.5−3x)TiO3 samples with x = 0.01 exhibit higher electrostrain from 30 °C to 150 °C. Based on the assumption of charge balance, our findings indicated that the presence of 1 mol% excess Bi would facilitate significant improvement in the dielectric, ferroelectric, and electrostrain properties of BNT and BNT-based systems. 相似文献
In recent days, the manufacture of automotive vehicles is dramatically enhanced worldwide. Most vehicle crashes are due to the drive distraction on the real highway roads and traffic-density. In this proposed method, a novel collision detection and avoidance algorithm are coined for Midvehicle Collision Detection and Avoidance System (MCDAS), addressing two scenarios, namely, (a) A rear-end collision avoidance with host vehicle under no front-end vehicle condition and (b) offset-based curvilinear motion under critical conditions, while, suitable parallel parking manoeuvring also addressed using offset-based curvilinear motion. The Monte Carlo analysis of the proposed MCDAS is demonstrated using the Constant Velocity (CV) manoeuvring strategy and simulated with real-time data using the NGSIM database.
MiE is a facial involuntary reaction that reflects the real emotion and thoughts of a human being. It is very difficult for a normal human to detect a Micro-Expression (MiE), since it is a very fast and local face reaction with low intensity. As a consequence, it is a challenging task for researchers to build an automatic system for MiE recognition. Previous works for MiE recognition have attempted to use the whole face, yet a facial MiE appears in a small region of the face, which makes the extraction of relevant features a hard task. In this paper, we propose a novel deep learning approach that leverages the locality aspect of MiEs by learning spatio-temporal features from local facial regions using a composite architecture of Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM). The proposed solution succeeds to extract relevant local features for MiEs recognition. Experimental results on benchmark datasets demonstrate the highest recognition accuracy of our solution with respect to state-of-the-art methods. 相似文献
The widespread demand for clean energy stimulates great interest to hydrogen energy with high energy density and conversion efficiency. Separation technologies by membranes are increasingly applied for hydrogen separation because of its excellent performance and low consumption. In this work, density functional theory simulations is used to study hydrogen separation of Pd–Au–Ag membrane, and the performance of Pd–Au alloy is also compared and discussed. The results indicate that Pd–Au alloy shows superior selectivity to H2 gas over CO, N2, CH4, CO2 and H2S gases, which is in line with experimental results. In particular, the separation selectivity of Pd–Au–Ag to H2 is significantly greater than those for Pd–Au alloy and several currently reported materials. Moreover, the permeability of H2 in Pd–Au–Ag exceeds the limits for industrial production at deferent temperatures. Our calculations demonstrate that Pd–Au–Ag alloy present excellent performance as a promising membrane for hydrogen separation. 相似文献
Journal of Materials Science: Materials in Electronics - The main weakness of polymer gas sensors is its stability. Here, we report stability enhancement of a 100 nm polypyrrole (PPy) thin... 相似文献
PEMFC system is a complex new clean power system. Based on MATLAB/Simulink, this paper develops a system-level dynamic model of PEMFC, including the gas supply system, hydrogen supply system, hydrothermal management system, and electric stack. The neural network fits the electric stack model to the simulation data. The effects of different operating conditions on the PEMFC stack power and system efficiency are analyzed. Combining the power of the reactor and the system efficiency to define the integrated performance index, the particle swarm optimization (PSO) algorithm is introduced to optimize the power density and system efficiency of the PEMFC with multiple objectives. The final optimal operating point increases the power density and system efficiency by 1.33% and 12.8%, respectively, which maximizes the output performance and reduces the parasitic power. 相似文献