An experimental and three-dimensional numerical study of natural convection heat transfer between two horizontal parallel plates

In this study, experimental and three-dimensional numerical studies were performed to investigate the effects of plate spacing and temperature difference on natural convection between isothermally heated upward-facing lower horizontal plate and externally insulated horizontal upper plate. Air is used as the heat transfer medium. Rayleigh number varied in the 1108–2.339 × 10⁵ range. Several numerical simulations for three-dimensional steady laminar and turbulent flows heat transfer were carried out using a commercial CFD code Fluent 6.2. Results have shown that there is a good agreement between the numerical and present experimental results as well as with available data in literature.     

视知觉特性对网页设计的影响因素分析

本文从视知觉的角度分析了用户对网页的视知觉需求。并通过对用户视知觉过程的分析,结合心理学理论,提出了符合用户视知觉特性的七个"适当",即适当的知觉形式、适当的位置、适当的信息、适当的时刻、适当的信息量、适当的时长、适当的环境条件,同时结合现有优秀网页设计案例,阐述了七个"适当"对网页设计的影响因素。     

含三维内裂纹透明类岩石材料破坏红外热像试验研究

由于目前针对含三维内裂纹的岩石破坏红外热像特征的研究较少,本文基于预埋浇注法制作含内裂纹类岩石试件,开展了单轴压缩块体试验和巴西圆盘劈拉试验,得到含内裂纹的岩石破坏过程,监测内裂纹扩展及试件破坏过程中的红外热像特征,得到以下结论:(1)含三维内裂纹的块体试件在单轴压缩下,在预制内裂纹面上发生剪切破坏;(2)块体试件在单轴压缩作用下红外热像特征明显,在破坏时,在预制内裂纹面处急剧升温;(3)含三维内裂纹巴西圆盘试件在预制内裂纹尖端发生翼型裂纹扩展,边缘带有针刺状Ⅲ型裂纹参与特征,最终翼型裂纹与上下表面贯穿;(4)巴西圆盘试验的红外热像特征与块体单轴压缩不同,在断裂面处未发生明显变化。研究结果为研究三维内裂纹的扩展规律及内裂纹扩展破裂的红外热像规律可提供一定的试验参考。     

Deep neural network-based fusion model for emotion recognition using visual data

The Journal of Supercomputing - In this study, we present a fusion model for emotion recognition based on visual data. The proposed model uses video information as its input and generates emotion...     

Multi-verse optimization algorithm- and salp swarm optimization algorithm-based optimization of multilevel inverters

Neural Computing and Applications - Renewable energy sources are installed into both distribution and transmission grids more and more with the introduction of smart grid concept. Hence, efficient...     

Creativity in non‐routine jobs: The role of transformational leadership and organizational identification

An increasing number of individuals work in jobs with little standardization and repetition, that is, with high levels of job non‐routinization. At the same time, demands for creativity are high, which raises the question of how employees can use job non‐routinization to develop creativity. Acknowledging the importance of social processes for creativity, we propose that transformational leaders raise feelings of organizational identification in followers and that this form of identification then helps individuals to develop creativity in jobs with little routinization. This is because organizational members evaluate and promote those ideas as more creative, which are in line with a shared understanding of creativity within the organization. To investigate these relationships, we calculated a mediated moderation model with 173 leader–follower dyads from China. Results confirm our hypotheses that transformational leadership moderates the relationship between job non‐routinization on employee creativity through organizational identification. We conclude that raising feelings of social identity is a key task for leaders today, especially when working in uncertain and fast developing environments with little repetition and the constant need to develop creative ideas.     

CFAR processing with switching exponential smoothers for nonhomogeneous environments

Conventional constant false alarm rate (CFAR) methods use a fixed number of cells to estimate the background variance. For homogeneous environments, it is desirable to increase the number of cells, at the cost of increased computation and memory requirements, in order to improve the estimation performance. For nonhomogeneous environments, it is desirable to use less number of cells in order to reduce the number of false alarms around the clutter edges. In this work, we present a solution with two exponential smoothers (first order IIR filters) having different time-constants to leverage the conflicting requirements of homogeneous and nonhomogeneous environments. The system is designed to use the filter having the large time-constant in homogeneous environments and to promptly switch to the filter having the small time constant once a clutter edge is encountered. The main advantages of proposed Switching IIR CFAR method are computational simplicity, small memory requirement (in comparison to windowing based methods) and its good performance in homogeneous environments (due to the large time-constant smoother) and rapid adaptation to clutter edges (due to the small time-constant smoother).     

Exploring brain connectivity with two-dimensional neural maps

We introduce two-dimensional neural maps for exploring connectivity in the brain. For this, we create standard streamtube models from diffusion-weighted brain imaging data sets along with neural paths hierarchically projected into the plane. These planar neural maps combine desirable properties of low-dimensional representations, such as visual clarity and ease of tract-of-interest selection, with the anatomical familiarity of 3D brain models and planar sectional views. We distribute this type of visualization both in a traditional stand-alone interactive application and as a novel, lightweight web-accessible system. The web interface integrates precomputed neural-path representations into a geographical digital-maps framework with associated labels, metrics, statistics, and linkouts. Anecdotal and quantitative comparisons of the present method with a recently proposed 2D point representation suggest that our representation is more intuitive and easier to use and learn. Similarly, users are faster and more accurate in selecting bundles using the 2D path representation than the 2D point representation. Finally, expert feedback on the web interface suggests that it can be useful for collaboration as well as quick exploration of data.