2DPCA-SIFT:一种有效的局部特征描述方法

PCA-SIFT （Principal component analysis—scale invariant feature transform）方法通过对归一化梯度向量进行PCA降维,在保留特征不变性的同时,有效地降低了特征矢量的维数,从而提高了局部特征的匹配速度. 但PCA-SIFT中对本征向量空间的求解非常耗时,极大地限制了PCA-SIFT的灵活性与应用范围. 本文提出采用2DPCA对梯度向量块进行降维的特征描述方法. 该方法相比于PCA-SIFT,可以快速地求解本征空间. 实验结果表明:2DPCA-SIFT在多种图像变换匹配和图像检索实验中可以实现与PCA-SIFT相当的性能,并且从计算效率上看,2DPCA-SIFT具有更好的扩展性.     

基于局部重要性采样的SAR图像纹理特征提取方法

合成孔径雷达（Synthetic aperture radar,SAR）图像因为相干斑现象和目标响应的空间变化呈现出一种纹理特性,局部二进编码等局部图像特征 在光学纹理描述中获得较好的结果,但光学纹理特征在描述SAR图像纹理特性中因为相干成像特性往往失效. 本文 在前期工作纹理特征框架的基础上,提出了一种局部重要性采样二进编码的SAR图像纹理特征（Feature extraction based on local important sampling binary,LISBF）描述方法:首先,利用样本图像对局部采样位 置进行随机自适应采样,基于重要性采样（Important sample,IS）方法输出递归学习位置结果;然后,利用学习出的纹理重要采样点对进 行二进特征编码;最后,通过映射和统计生成描述算子. 该特征较固定位置采样能够获取更大范围信息,同时能通 过采样避免特征维数的急剧增大;通过自适应学习重要性关键点较随机采样 更容易捕捉纹理固有信息;较好地适应了SAR图像极低信噪比和斑点现象的纹理. 本文将该特征用于真实图像和标准纹理库的分类研究,实验结果证明了该特征的有效性.     

Learning Kernels for Unsupervised Domain Adaptation with Applications to Visual Object Recognition

Domain adaptation aims to correct the mismatch in statistical properties between the source domain on which a classifier is trained and the target domain to which the classifier is to be applied. In this paper, we address the challenging scenario of unsupervised domain adaptation, where the target domain does not provide any annotated data to assist in adapting the classifier. Our strategy is to learn robust features which are resilient to the mismatch across domains and then use them to construct classifiers that will perform well on the target domain. To this end, we propose novel kernel learning approaches to infer such features for adaptation. Concretely, we explore two closely related directions. In the first direction, we propose unsupervised learning of a geodesic flow kernel (GFK). The GFK summarizes the inner products in an infinite sequence of feature subspaces that smoothly interpolates between the source and target domains. In the second direction, we propose supervised learning of a kernel that discriminatively combines multiple base GFKs. Those base kernels model the source and the target domains at fine-grained granularities. In particular, each base kernel pivots on a different set of landmarks—the most useful data instances that reveal the similarity between the source and the target domains, thus bridging them to achieve adaptation. Our approaches are computationally convenient, automatically infer important hyper-parameters, and are capable of learning features and classifiers discriminatively without demanding labeled data from the target domain. In extensive empirical studies on standard benchmark recognition datasets, our appraches yield state-of-the-art results compared to a variety of competing methods.     

Bifurcation analysis of a two-dimensional simplified Hodgkin–Huxley model exposed to external electric fields

In this paper, the dynamical behaviors of a two-dimensional simplified Hodgkin–Huxley (H–H) model exposed to external electric fields are investigated through qualitative analysis and numerical simulation. A necessary and sufficient condition is proposed for the existence of the Hopf bifurcation. Saddle-node bifurcations and canards of the simplified model with the coefficients of different linear forms are also discussed. Finally, the bifurcation curves with the coefficients of different linear forms are shown. The numerical results demonstrate that some linear forms can retain the bifurcation characteristics of the original model, which is of great use to simplify the H–H model for the real-world applications.     

Complementarity determining region residues aspartic acid at H55, serine at H95 and tyrosines at H97 and L96 play important roles in the B72.3 antibody-TAG72 antigen interaction

Structural analysis derived from the crystallographic studyof the chimeric B72.3 antibody illustrated some major atomicinteractions between complementarity determining region (CDR)residues. For example, hydrogen bonds are formed between H35/H95,L50/H97, H53/H55 and H96/L96 respectively. These CDR residuesmay play important roles in the B72.3–TAG72 (antibody-antigen)interaction either by direct interaction with the TAG72 antigenor by maintaining a CDR loop conformation through atomic interactionsbetween CDR residues. In order to confirm these assumptions,we altered these CDR residues by site-directed mutagenesis anddetermined binding affinities of these mutant chimeric antibodiesfor the TAG72 antigen in a solid-phase radioimmunoassay. Wefound that H55, H95, H97 and L96 are important CDR residuesfor the B72.3–TAG72 interaction. Single amino acid substitutionsof aspartic acid and serine by alanine at H55 of CDR2 and atH95 of CDR3 respectively and of tyrosine by phenylalanine atH97 and L96 of CDR3, significantly reduced the binding affinityfor the TAG72 antigen by 20-, 8-, 16- and 45-fold respectively.Therefore, this study reveals some of the requirements for maintainingthe integrity of the B72.3 antibody combining sites.     

硫酸工艺和设备选择中的节能问题

介绍了硫酸生产中能量利用及我国硫酸工业能源利用状况。分析了硫酸工艺和设备选择中的节能降耗问题,做好投资费用与能耗的技术经济评估及塔设备、干吸塔除雾器、主鼓风机等主要耗能设备的设计与选型,合理地选择工艺、设备及其参数,提高能量利用率,实现投资最小化和节能最大化,构筑“节能型”硫酸工业。     

处理硝基苯类废水的Fenton催化氧化技术研究现状

硝基苯类化合物是高毒性物质,难以生物降解且对生化反应有抑制和毒害作用.因此,硝基苯对环境的污染问题越来越受到科学研究者的关注.目前,采用Fenton氧化技术降解硝基苯类化合物的机理和工艺研究越来越活跃.作者就近几年来国内外Fenton催化氧化技术降解硝基苯类废水的研究现状进行了综述.     

无线传感器网络中的改进数据聚集调度算法

针对现有聚集数据调度近似算法具有较高延时上界的问题,提出一种改进的聚集数据调度近似算法。建立一棵根在中心结点的广度优先搜索树,分层构造一个最大独立集(MIS),使MIS中相邻的2个结点相距两跳。将MIS中的结点连接起来,形成一棵根在中心结点的数据聚集调度树,使结点按数据聚集调度树进行分层数据调度。在数据聚集调度树的构造过程中,对于任意支配点,以最小的结点连接其相距两跳的支配点。对于2个相邻支配点的公共邻居支配点,通过在距中心点最近的支配点加入数据聚集树,使其在数据调度过程中将数据发送给距中心点最近的支配点,从而降低数据的聚集延时。实验结果表明,与SAS算法、Guo’s算法和IAS算法相比,该算法的数据聚集延时更低,其延时上界为14R+△?10。     

江苏省地震前方指挥车应急数据信息通信方式的实现

前方指挥车是在有地震灾害事件发生时,能够立即响应,并快速到达地震震中所在地,立即开展现场信息汇集与共享、地震灾情动态评估和修正、辅助决策建议及时生成、现场资源调度和管理,实现前方指挥部与现场工作人员、国家指挥部、区域指挥部的不同应用系统之间的数据信息的共享和传递.本文主要介绍前方指挥车两种不同应急通信方式,并讨论各自的优缺点.     

IPV6技术在数字化校园建设中安全防范研究

随着校园网的日益发展,IPv6网络在我国数字化校园网中广泛部署,其安全问题也日益突出。基于我院数字化校园网庞大的实验环境,该文从分析IPV6数字化校园网的安全特点入手,对IPV6技术在我院数字化校园建设中体现的安全问题进行了分析,阐述了保证IPv6对解决我院数字化校园网安全实现的一些策略。