基于数据质量评价的目标估计

针对目标估计过程需要大量人工参与、自动化程度低的问题，提出了基于数据质量评价的目标估计方法。利用目标数据质量评价方法，对不同传感器得到的目标数据质量进行科学、有效的测度和评价，并根据质量得分动态调整各数据源在目标估计过程中所占的权重，从而减少人工干预，提高目标估计效能。仿真试验结果证明了该方法的有效性。     

学情调查和数据驱动专业基础课教学探索

文章以“数字电子技术基础”课程为对象,设计了基于教学数据和问卷调查的教学框架。通过学生情况调查和雨课堂教学数据掌握学习状态和学习能力,针对性设计了个性化作业布置、拓展延伸、疫情线上自学跟学双通道等特色教学方式。结课问卷表明教学设计得到了良好评价和认可。     

An analytical model for gas leakage through contact interface in proton exchange membrane fuel cells

Sealing performance between two contacting surfaces is of significant importance to stable operation of proton exchange membrane (PEM) fuel cells. In this work, an analytical micro-scale approach is first established to predict the gas leakage in fuel cells. Gas pressure and uneven pressure distribution at the interface are also included in the model. At first, the micro tortuous leakage path at the interface is constructed by introducing contact modelling and fractal porous structure theory. In order to obtain the leakage at the entire surface, contact pressure distribution is predicted based on bonded elastic layer model. The gas leakage through the discontinuous interface can be obtained with consideration of convection and diffusion. Then, experiments are conducted to validate the numerical model, and good agreement is obtained between them. Finally, influences of surface topology, gasket compression and gasket width on leakage are studied based on the model. The results show that gas leakage would be greatly amplified when the asperity standard deviation of surface roughness exceeds 1.0 μm. Gaskets with larger width and smaller thickness are beneficial to sealing performance. The model is helpful to understand the gas leakage behavior at the interface and guide the gasket design of fuel cells.     

A numerical study on nonlinear DPL model for analyzing heat transfer in tissue during thermal therapy

In the present paper, therapeutic treatment of infected tumorous cells has been studied through mathematical modeling and simulation of heat transfer in tissues by using a nonlinear dual-phase lag bioheat transfer model with Dirichlet boundary condition. The components of volumetric heat source in this model such as blood perfusion and metabolism are assumed experimentally validated temperature-dependent function, which gives more accurate temperature distribution in tissues through this model. We have used the finite difference and RK (4, 5) techniques of numerical methods to solve the proposed problem and obtained the exact solution in a particular case. After comparison, we got a good agreement between them. We have used dimensionless quantities throughout this paper. The effect of relaxation and thermalization time with respect to dimensionless temperature distribution has been analyzed in the treatment process.     

A numerical model to predict the powder–binder separation during micro-powder injection molding

The micro-powder injection molding (micro-PIM) process has the potential to bridge the gap between the design and manufacturing of micro-components that are often used in small and handy devices. Numerical modeling helps to analyze and overcome various difficulties of micro-PIM. In the present work, a numerical model is developed to predict the powder–binder separation (a common defect in PIM and especially severe in micro-PIM) during the injection of an alumina feedstock. A powder–binder separation criterion is proposed dealing with applied injection pressure and friction force between the powder and binder. An indirect comparison of feedstock travel time between two locations is used to validate the model. The predicted segregation from the simulated result is supported by a qualitative experimental measurement. The developed model can be used to optimize injection parameters to get a defect-free product.     

基于Hadoop的气象数据分布式存储技术研究

针对目前气象数据存储所面临的海量扩张、高并发读写、结构化和非结构化数据并存以及长时间序列和大数据集检索效率低下等问题,提出了以Hadoop开源框架为基础的气象数据分布式存储方案。通过对气象数据自身属性和特点进行分析,得出了气象数据在经过充分优化的基础上,在分布式存储框架中具有很强的适应性和规模化应用的潜力;并在HBase数据库中的Row Key设计和小文件合并策略方面做了创新。最后针对气象数据中广泛存在的结构化和非结构化这两种主要数据类型,以自动气象站数据和雷达产品数据为具体实例,给出了详细的设计思路和实现方法。     

“半翻转”教学模式下评价指标体系研究与实践

研究基于“半翻转”教学模式的线上教学评价指标体系,包括课前活动开展、课中教学活动设计、课后任务以及基于此过程中的评价指标体系设计。最后通过层次分析法设计评价指标权重,设计评价算法得到动态评价结果。该评价指标体系应用在本专业“数据结构与算法”课程中,并得到良好的应用效果。     

Adaptive reversible data hiding for JPEG images with multiple two-dimensional histograms

Joint photographic experts group (JPEG) can provide good quality with small file size but also eliminate extensively the redundancies of images. Therefore, hiding data into JPEG images in terms of maintaining high visual quality at small file sizes has been a great challenge for researchers. In this paper, an adaptive reversible data hiding method for JPEG images containing multiple two-dimensional (2D) histograms is proposed. Adaptability is mainly reflected in three aspects. The first one is to preferentially select sharper histograms for data embedding after $K$ histograms are established by constructing the $k$th ($k\in \{1,2,\dots ,K\}$) histogram using the $k$th non-zero alternating current (AC) coefficient of all the quantized discrete cosine transform blocks. On the other hand, to fully exploit the strong correlation between coefficients of one histogram, the smoothness of each coefficient is estimated by a block smoothness estimator so that a sharply-distributed 2D-histogram is constructed by combining two coefficients with similar smoothness into a pair. The pair corresponding to low complexity is selected priorly for data embedding, leading to high embedding performance while maintaining low file size. Besides, we design multiple embedding strategies to adaptively select the embedding strategy for each 2D histogram. Experimental results demonstrate that the proposed method can achieve higher rate–distortion performance which maintaining lower file storage space, compared with previous studies.     

Flow distribution and mass removal in floating treatment wetlands arranged in series and spanning the channel width

Floating treatment wetlands (FTWs) use plants’ roots for water quality improvement. The plants are supported by a buoyant structure deployed at the water surface. The roots form a porous zone beneath the structure and remove pollutants carried in suspension through filtering, absorption and uptake. This paper used CFD simulation to model FTWs arranged in series and spanning the channel width and to study the effects of root length and spacing between FTWs on flow distribution and mass removal. The root zone was modelled as a porous media, and removal was computed using first-order decay, for which a range of removal constants was tested. Longer roots increased the reactive volume of the root zone, which increased the fraction of pollutant inflow entering the FTWs. Increasing the distance between FTWs allowed greater mixing between water that went through and beneath the upstream FTW. This increased the concentration entering each FTW, which enhanced mass removal per FTW. However, a larger distance between FTWs reduced the number of FTWs in the channel, reducing the reactive volume. In the tradeoff between mixing and reactive volume, the reactive volume was more important, such that total removal in the channel increased with longer roots and more units of FTW (shorter gap distance). However, removing the gap entirely was detrimental, as FTWs in series removed more mass than a continuous FTW of same volume. This study points to two design recommendations for FTWs in series. First, if resources for building FTWs are not limiting, but the channel length is, it is preferable to prioritize higher reactive volume (shorter gap distance) to achieve maximum removal per channel length. Second, if resources for FTWs are limiting, but channel length is not, it is better to place the FTWs with a longer gap distance, preferably along enough to allow mixing over the full depth between FTWs, as this will achieve maximum removal per FTW.     

基于双时间点检测的毫米波雷达人流量监测方法

针对现有基于视频监控的人流量统计方案成本高、算法复杂且不利于个人隐私保护的局限性，利用毫米波雷达体积小、成本低、分辨率高的特点，提出了一种基于双时间点检测的人流量监测方法。该方法先获取人体目标散射点位置和多普勒频移信息来构成点云数据，然后根据多普勒频移正负来判断人体的运动方向，并筛选具有高多普勒频移值的点云数据以降低干扰点对聚类结果的影响；在双时间点对特定区域内人员数量进行统计，并根据双时间点之间所获取的点云数据聚类结果对所统计人员数据进行修正。实验结果表明，该方法能够用匿名的方式以较高的正确率统计人员进出。