新时代背景下电力精准扶贫模式研究及建议

发挥电力行业优势特点,开展电力精准扶贫,对打赢脱贫攻坚战具有十分重要的作用,并能够助推脱贫攻坚与乡村振兴战略有效衔接.本文从电力扶贫在脱贫攻坚的重要作用出发,以“三聚焦”“三优先”“三模式”“三保障”为指引,详尽梳理并总结了电力精准扶贫主要模式和经验.在此基础上,深刻剖析了当前电力扶贫面临的困难及问题,提出电力精准扶贫的策略,以期为下一步开展电力精准扶贫提供参考与借鉴.     

Elastic instabilities,microstructure transformations,and pattern formations in soft materials

Large deformations of soft materials can give rise to the development of various elastic instabilities. The phenomenon is associated with a sudden and dramatic change in structure morphologies. The underlying mechanism is crucial for the formation of complex morphologies in biology. Moreover, the concept of instability-induced pattern transformations is promising for designing novel materials with switchable functions and properties. In this paper, we review the state of the art in elastic instability phenomena in soft materials. We start by considering the classical buckling in beam-based structure lattice designs. Then, we discuss the instability-induced microstructure transformations in soft porous materials, and heterogeneous multiphase and fiber composites. Next, the mechanisms – often involving the post-buckling consideration – leading to the wrinkling and folding, creasing, fringe, and fingering are discussed.     

加权信息熵与增强局部二值模式结合的人脸识别

针对人脸识别因光照、姿态、表情、遮挡及噪声等多种因素的影响而导致的识别率不高的问题，提出一种加权信息熵（IEw）与自适应阈值环形局部二值模式（ATRLBP）算子相结合的人脸识别方法（IE （w） ATR-LBP）。首先，从原始人脸图像分块提取信息熵，得到每个子块的IEw；然后，利用ATRLBP算子分别对每个人脸子块提取特征从而得到概率直方图；最后，将各个块的IEw与概率直方图相乘，再串联成为原始人脸图像最后的特征直方图，并利用支持向量机（SVM）对人脸进行识别。在AR人脸库的表情、光照、遮挡A和遮挡B四个数据集上，IE （w） ATR-LBP方法分别取得了98.37%、94.17%、98.20%和99.34%的识别率。在ORL人脸库上，IE （w） ATR-LBP方法的最大识别率为99.85%；而且在ORL人脸库5次不同训练样本的实验中，与无噪声时相比，加入高斯和椒盐噪声后的平均识别率分别下降了14.04和2.95个百分点。实验结果表明，IE （w） ATR-LBP方法能够有效提高人脸在受光照、姿态、遮挡等影响时的识别率，尤其是存在表情变化及脉冲类噪声干扰时的识别率。     

杭州文化创意产业区的空间发展格局及空间影响

在我国城市化发展转型的大环境下,随着城市新区的开发以及城市中心区传统产业的外迁和置换,文化创意产业区建设正日益受到城市决策者和研究者的关注。本文以杭州为例,在分析目前城市文化创意产业区建设现状的基础上,探讨了其在城市宏观层面的空间发展格局与发展的基本模式。     

A new reverse reduce-error ensemble pruning algorithm

Although greedy algorithms possess high efficiency, they often receive suboptimal solutions of the ensemble pruning problem, since their exploration areas are limited in large extent. And another marked defect of almost all the currently existing ensemble pruning algorithms, including greedy ones, consists in: they simply abandon all of the classifiers which fail in the competition of ensemble selection, causing a considerable waste of useful resources and information. Inspired by these observations, an interesting greedy Reverse Reduce-Error (RRE) pruning algorithm incorporated with the operation of subtraction is proposed in this work. The RRE algorithm makes the best of the defeated candidate networks in a way that, the Worst Single Model (WSM) is chosen, and then, its votes are subtracted from the votes made by those selected components within the pruned ensemble. The reason is because, for most cases, the WSM might make mistakes in its estimation for the test samples. And, different from the classical RE, the near-optimal solution is produced based on the pruned error of all the available sequential subensembles. Besides, the backfitting step of RE algorithm is replaced with the selection step of a WSM in RRE. Moreover, the problem of ties might be solved more naturally with RRE. Finally, soft voting approach is employed in the testing to RRE algorithm. The performances of RE and RRE algorithms, and two baseline methods, i.e., the method which selects the Best Single Model (BSM) in the initial ensemble, and the method which retains all member networks of the initial ensemble (ALL), are evaluated on seven benchmark classification tasks under different initial ensemble setups. The results of the empirical investigation show the superiority of RRE over the other three ensemble pruning algorithms.     

An SOFC anode model using TPB-based kinetics

Fundamental studies focusing on the electrode kinetics are essential in understanding the fuel cell operation and optimizing the electrode designs. In this study, we determined the triple-phase boundary (TPB)-based kinetics of hydrogen electrochemical oxidation using nickel patterned electrode experimental data and the Butler-Volmer formalism of the oxidation process. The same kinetics are then incorporated in a cermet electrode electrochemical model to estimate the effective TPB density of the nickel/yittrium-stabilized zirconia cermet anode. The kinetics are found to be of the same order of magnitude as previously determined by the microstructure reconstruction of cermet anode. Simulation results further revealed that the effective TPB density is several orders of magnitude lower than the typically reported physical densities of the cermet anode that possibly suggests that only a minor fraction of the physical TPB is actually required or available to produce the cell current at given cell voltage. The effect of various operating conditions on the anode activation overpotential is also investigated and discussed in this study.     

基于多颜色分量CLBP提取的浮选泡沫状态识别

针对不同状态的浮选泡沫图像之间纹理结构相似、颜色差异不明显的问题，提出一种基于色调、饱和度和亮度（HSV）颜色空间的完全局部二进制模式（CLBP）纹理提取的浮选泡沫状态识别方法。首先使用双域去噪在保留纹理细节的同时滤除图像噪声，然后转换为HSV图像，在H、S和V颜色分量上分别提取三个尺度的CLBP纹理特征。将提取的纹理特征归一化后线性排列，建立高维度的纹理分类模型。最后通过一对一模式的支持向量机分类器对四类泡沫状态的样本集进行纹理提取后的分类训练与测试。结果表明，该方法对不同浮选泡沫状态的分类正确率较高，优于其他纹理描述方法，适用于浮选泡沫状态的识别。     

工程教育认证背景下设计模式课程教学研究

工程教育是我国高等教育的重要组成部分,工程教育认证已成为中国高校新的风向标,也成为高考生选择报考专业的一项重要指标。设计模式是计算机科学与技术专业的一门核心课程,包含了面向对象的精髓,是软件体系结构的基础,在工程教育认证所评估的课程设置中起着承上启下的关键作用。本文基于工程教育专业认证理念,以及山东农业大学申请认证所用的《计算机科学与技术专业培养方案》,从教学内容、教学方式、课程目标与毕业要求对应关系、解决复杂工程问题能力、教学进度安排等方面,对设计模式课程开展了教学研究,并将该教学方案应用于本科教学。     

基于宜兴彩陶山水图案的女式针织衫设计

对宜兴彩陶装饰艺术中典型的山水图案进行分析,阐述宜兴彩陶山水图案的文化内涵。分析宜兴彩陶山水图案的审美特征,包括浓淡有序的色彩层次、抽象凝练的造型肌理、形饰一体的结构布局。以各类针织纱线为原料,采用岛精电脑横机,对女式针织衫进行款式、图案及组织结构设计。详细介绍基于宜兴彩陶山水图案元素的女式针织衫色彩、款式、图案和肌理设计应用实例。该研究为女式针织衫的设计提供了新的思路,为中国传统装饰艺术元素在服饰品中的跨界设计提供了理论与实践参考。