Multiscale analysis of stiffness and fracture of nanoparticle-reinforced composites using micromechanics and global–local finite element models

A combined micromechanics analysis and global–local finite element method is proposed to study the interaction of particles and matrix at the nano-scale near a crack tip. An analytical model is used to obtain the effective elastic modulus of nanoparticle-reinforced composites, then a global–local multi-scale finite element model with effective homogeneous material properties is used to study the fracture of a compact tension sample. For SiO₂ particle-reinforced epoxy composites with various volume fractions, the simulation results for effective elastic modulus, fracture toughness, and critical strain energy release rate show good agreement with previously published experimental data. It is demonstrated that the proposed parametric multi-scale model can be used to efficiently study the toughness mechanisms at both the macro and nano-scale.     

Experimental evaluation of the seismic performance of steel MRFs with compressed elastomer dampers using large-scale real-time hybrid simulation

Real-time hybrid simulation combines experimental testing and numerical simulation, and thus is a viable experimental technique for evaluating the effectiveness of supplemental damping devices for seismic hazard mitigation. This paper presents an experimental program based on the use of the real-time hybrid simulation method to verify the performance-based seismic design of a two story, four-bay steel moment resisting frame (MRF) equipped with compressed elastomer dampers. The laboratory specimens, referred to as experimental substructures, are two individual compressed elastomer dampers with the remainder of the building modeled as an analytical substructure. The proposed experimental technique enables an ensemble of ground motions to be applied to the building, resulting in various levels of damage, without the need to repair the experimental substructures, since the damage will be within the analytical substructure. Statistical experimental response results incorporating the ground motion variability show that a steel MRF with compressed elastomer dampers can be designed to perform better than conventional steel special moment resisting frames (SMRFs), even when the MRF with dampers is significantly lighter in weight than the conventional MRF.     

结合颜色和MGD特征及MRF模型的场景文本分割

针对场景文本受到光照、复杂背景等因素影响而难以进行有效分割的问题,提出了一种融合颜色和最大梯度差(MGD,maximum gradient difference)特征及马尔科夫随机场(MRF,Markov random field)的场景文本分割方法。首先提取能够有效表达文本纹理特性的MGD特征,通过概率框架将其和颜色特征结合起来对观测图像进行建模;然后结合空间关系和邻域像素属性差异对传统势函数进行改进;最后建立场景文本分割的MRF模型,利用图割(graph cut)算法快速地求解该模型。实验结果表明,采用颜色和MGD特征相结合以及改进的势函数对分割结果具有较大地改善,尤其在光照不均匀及背景复杂情况下相比其他算法取得了较好的性能。     

DF100A型发射机宽频带放大器工作原理及故障分析

主要针对DF100A型发射机200 W宽频带放大器的工作原理,故障现象分析和处理方法。对于宽频带放大器的未来发展方向提供一种新的思路,从根本上解决宽频带放大器的故障率较高的问题。     

On the choice of spatial and categorical scale in remote sensing land cover classification

Our interest in this paper is on the choice of spatial and categorical scale, and their interaction, in creating classifications of land cover from remotely sensed measurements. We note that in discussing categorical scale, the concept of spatial scale naturally arises, and in discussing spatial scale, the issue of aggregation of measurements must be considered. Therefore, and working towards an ultimate goal of producing multiscale, multigranular characterizations of land cover, we address here successively and in a cumulative fashion the topics of (1) aggregation of measurements across multiple scales, (2) adaptive choice of spatial scale, and (3) adaptive choice of categorical scale jointly with spatial scale. We show that the use of statistical finite mixture models with groups of original pixel-scale measurements, at successive spatial scales, offers improved pixel-wise classification accuracy as compared to the commonly used technique of label aggregation. We then show how a statistical model selection strategy may be used with the finite mixture models to provide a data-adaptive choice of spatial scale, varying by location (i.e., multiscale), from which classifications at least as accurate as those of any single spatial scale may be achieved. Finally, we extend this paradigm to allow for jointly adaptive selection of spatial and categorical scale. Our emphasis throughout is on the empirical quantification of the role of the various elements above, and a comparison of their performance with standard methods, using various artificial landscapes. The methods proposed in this paper should be useful for a variety of scale-related land cover classification tasks.     

马尔可夫随机场在SAR图像处理中的应用

马尔可夫随机场（MRF）可以很好地描述空间连续性，选择适当的邻域系统，能对图像的结构特征建模。利用以能量函数表示的联合概率分布，可以使用优化算法进行参数估计。高斯MRF能够准确、简洁地表示图像的纹理，而且具有线性特性，计算方便。本文回顾了在SAR图像处理中使用的MRF模型，详细说明了其中2种在图像复原及分割中的应用。     

多尺度分析用于图像边缘的精确检测

图像中边缘往往存在于一个较宽的尺度范围内，边缘的定位精确性是衡量一个边缘检测算法性能的重要依据。众多算法中，引起较大关注的是M—H的二阶导数过零点检测和Canny的一阶导数最大值检测，但都存在各自的不足。本文提出将线性权重函数(LWF)作为平滑函数，并利用小波理论的多尺度分析方法，对图像边缘进行检测，其在定位精确性、噪声抑制能力方面均有较好性能。     

基于各向异性MRF建模的多帧图像 变分超分辨率重建

 本文首先研究设计出结构自适应的各向异性数字滤波器,同时导出广义各向异性MRF(Markov Random Field)图像模型.它继承了各向异性数字滤波器的滤波性能,是对双边全变差模型以及经典 MRF模型的有效改进.随后,提出各向异性模型驱动的联合估计亚像素运动和高分辨率图像的变分超分辨率重建算法.实验结果显示,本文算法具有更优的噪声抑制和边缘保持性能.     

应用分层MRF/GRF模型的立体图像视差估计及分割

视差估计与分割是立体图像编码及立体视觉匹配的核心问题,本文提出一种基于分层MRF/GRF模型和交叠块匹配(HMOM)视差估计算法以及结合主动轮廓模型的视差分割提取算法.该混合视差估计方法,可得到光滑准确,且具有清晰边缘的视差场;并便于用主动轮廓模型提取感兴趣对象(OOI)的视差轮廓.与通常的变尺寸块匹配(VSBM)相比,本算法得到的视差补偿图像的峰值信噪比可提高2.5dB左右.本文得到的视差场及对应的轮廓可进一步用于立体图像编码以及视频对象分割.     

基于MRF24J40的IEEE802．15．4无线收发电路设计

采用MRF24J40构成的IEEE802.15.4无线收发器电路,为IEEE802.5.15.4MAC和PHY物理层提供硬件层,支持MiWiTM、ZigBee协议和其他协议,工作在2.405~2.48 GHz ISM频段,接收灵敏度为-91 dBm,发射输出功率为 0 dBm,发射功率控制范围为38.75 dB,电源电压范围为2.4~3.6 V,睡眠模式电流消耗为2μA。采用4线式SPI与微控制器接口,适合家居自动化、工业自动化等低数据速率传输的应用。