Superior Tribological Properties of Particulate Aluminum Matrix Nano Composites

Aluminum is the best metal for producing metal matrix composites which are known as one of the most useful and high-tech composites in our world. Combining aluminum and nano Al₂O₃ particles will yield a material with high mechanical properties. Characterization of tribological properties revealed that the presence of nano particles significantly increased wear resistance of the composite. In case of unreinforced Al alloy, the depth of penetration is governed by the hardness of the specimen surface and applied load. But, in case of Al matrix composite, the depth of penetration of the harder asperities of hardened steel disk is primarily governed by the protruded hard ceramic reinforcement. The hard Al₂O₃ particles act as a protrusion over the matrix, carries a major portion of the applied load and protect the abrasives from penetration into the specimen surface.     

A hybrid lithium‐ion battery model for system‐level analyses

We describe an advanced lithium‐ion battery model for system‐level analyses such as electric vehicle fleet simulation or distributed energy storage applications. The model combines an empirical multi‐parameter model and an artificial neural network with particular emphasis on thermal effects such as battery internal heating. The model is fast and can accurately describe constant current charging and discharging of a battery cell at a variety of ambient temperatures. Comparison to a commonly used linear kilowatt‐hour counter battery model indicates that a linear model overestimates the usable capacity of a battery at low temperatures. We highlight the importance of including internal heating in a battery model at low temperatures, as more capacity is available when internal heating is taken into account. Copyright © 2016 John Wiley & Sons, Ltd.     

Cognitive and affective causes of interest and liking.

In this study, I investigated some of the cognitive and affective causes of interest and liking. In Experiment 1, 240 undergraduates read stories with endings that varied in the degree of surprise, outcome valence (i.e., goodness or badness of outcome), and incongruity resolution. The results did not support the hypothesis that degree of surprise per se causes interest (Schank, 1979). Instead, as suggested by Kintsch (1980), subjects rated high-surprise story endings as more interesting than low-surprise story endings for those conditions in which the postsurprise incongruity was resolved (p?p?     

Periodic unsteady flows of a non-Newtonian fluid

Summary Exact analytic solutions for the flow of non-Newtonian fluid generated by periodic oscillations of a rigid plate are discussed. Some interesting flows caused by certain special oscillations are also obtained.     

An efficient deep learning technique for facial emotion recognition

Emotion recognition from facial images is considered as a challenging task due to the varying nature of facial expressions. The prior studies on emotion classification from facial images using deep learning models have focused on emotion recognition from facial images but face the issue of performance degradation due to poor selection of layers in the convolutional neural network model.To address this issue, we propose an efficient deep learning technique using a convolutional neural network model for classifying emotions from facial images and detecting age and gender from the facial expressions efficiently. Experimental results show that the proposed model outperformed baseline works by achieving an accuracy of 95.65% for emotion recognition, 98.5% for age recognition, and 99.14% for gender recognition.

     

Embedding cycles and paths on solid grid graphs

Despite many algorithms for embedding graphs on unbounded grids, only a few results on embedding graphs on restricted grids have been published. In this paper, we study the problem of embedding paths and cycles on solid grid graphs. We show that a cycle of length k is unit-length embeddable on a solid grid graph G if k is an even integer between four and the length of the longest cycle of G. In addition, our result shows that a path of length k is unit-length embeddable on G, between its two given vertices s and t, if \(k\le L\) and \(k\equiv L (\mathrm{mod}\ 2)\), in which L is the length of the longest path between s and t. Our presented two algorithms show that such embeddings can be found in linear time for cycles and quadratic time for paths, with respect to the size of graph G. In the case of rectangular grid graphs, the running time of the algorithms can be improved to O(k) and O\((k^2)\), respectively. In addition, we extend our results to \(m\times n\times o\) 3D grids. A application of our result is in the interconnection network mapping in parallel processing.