经食道心房调搏的放射性核素心血管造影

本文应用反符合电路剔除调搏脉冲干扰的方法,制成经食道心房调搏心电心音门电路触发装置,用于经食道心房调搏的核素心血管造影。参考Tzivoni标准,当逐级增加调搏心率至140次/min或亚极量心率后发现:冠心病人有调搏后EF降低;急性心肌梗塞病人EF减低更为明显,并呈室壁反向运动。因此,心房调搏核素心血管造影有助于冠心病,特别是心肌梗塞的诊断。     

浅析Cookies认证机制及其安全性

Web服务器生成Cookies并作为文本存贮于用户计算机硬盘或内存中,是实现Web应用认证的主要手段。本文分析了Cookie认证机制的实现过程与特点,并且论述了该认证机制易遭受的安全威胁以及安全需求,并给出实现安全Cookie认证的方法与措施。     

铝阳极氧化膜颜色的检验和观察法

介绍铝及铝合金阳极氧化膜颜色的概念和描写,对颜色的儿种测量方法进行了比较,重点分析观察法及其在各国标准中的异同。在此基础上,提出了GB8013中的对颜色进行观察的条件和理论根据。     

粗糙集理论及其在图像处理中的应用*

首先描述了粗糙集理论的基本概念,包括粗糙集知识表示方法和粗糙集约简理论;叙述了粗糙集理论及其与其他非线性理论相结合在图像处理中的应用情况;最后指出了粗糙集理论应用于图像处理的基本思路,并指出将粗糙集理论与其他非线性理论相结合应用于图像处理,将会产生更加有效的结果.     

8-羟基喹啉-N-氧化物和5,7-二硝基-8-羟基喹啉-N-氧化物与Au(Ⅲ)、Pd(Ⅱ)的配合物之合成

合成4种标题配合物,用元素分析、红外和紫外光谱、摩尔电导、核磁共振氢谱、荧光光谱及X射线粉末衍射物相分析研究了它们的组成和性质及其结构。按结构将配合物分为两类,一是含氢键的离子缔合物;一是含金属—氧键的螯环型配合物。     

The role of the surface free energy in the selection of a suitable excipient in the course of a wet-granulation method

Pellets containing metronidazole were produced in a centrifugal granulator, with hydroxypropylcellulose (Klucel LF®) as binding agent, and corn starch, microcrystalline cellulose (Vivapur 101®) and lactose as excipients. The wettability of the pharmaceutical powders was assessed by means of contact angle measurements, and the dispersive and polar surface energies were determined. The spreading coefficients, the work of adhesion and the work of cohesion were calculated and correlated with the pellet properties (friability, bulk and tapped density, and porosity). The aim was to investigate the role of the surface free energy of one- and two-component powder compositions in pellet production. The interactions between the particles were found to be connected with the measured pellet parameters. It was concluded that, in the course of the growth of the pellets, the particle sizes of the pharmaceutical powders and the interactions between them are important. If the work of cohesion of the binder is lower than the work of cohesion of the substrate and the work of adhesion, then the optimal amount of the binding agent is that which coats the particles uniformly in minimal quantity and in continuous layer.     

基于Flash的关键变量容错存储技术研究

嵌入式系统中往往需要保存少量复位或掉电后依赖的关键变量,利用处理器片内Flash存储参数已经成为常规选择,但与常规Flash存储器件相比,片内Flash擦除次数更为有限,难以满足系统生命周期要求。研究了如何延长微处理器片内Flash使用寿命以及关键系统变量容错存储技术,针对典型嵌入式系统应用,分析Flash擦写管理机制,基于写磨损均衡算法进行改良,进一步提升系统容错能力。该技术在基于STM32单片机硬件平台进行了测试验证。     

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.     

Stability-based preference selection in affinity propagation

Recently, as one of the most popular exemplar-based clustering algorithms, affinity propagation has attracted a great amount of attention in various fields. The advantages of affinity propagation include the efficiency, insensitivity to cluster initialization and capability of finding clusters with less error. However, one shortcoming of the affinity propagation algorithm is that, the clustering results generated by affinity propagation strongly depend on the selection of exemplar preferences, which is a challenging model selection task. To tackle this problem, this paper investigates the clustering stability of affinity propagation for automatically selecting appropriate exemplar preferences. The basic idea is to define a novel stability measure for affinity propagation, based on which we can select exemplar preferences that generate the most stable clustering results. Consequently, the proposed approach is termed stability-based affinity propagation (SAP). Experimental results conducted on extensive real-world datasets have validated the effectiveness of the proposed SAP algorithm.     

基于全网能量均衡的WirelessHART图路由算法

如何均衡使用网络节点能量并生成高可靠路由是WirelessHART网络研究的一个难题,为此提出了一种GRAEB（graph routing algorithm based on energy balancing）图路由算法。首先,网络被初始化为连通的图结构,能够提高丰富的冗余路径。网络管理器根据全网节点剩余能量、通信周期、链路分布等因子生成节点鲁棒系数矩阵,节点通过比较邻居的鲁棒系数来选择最优路径。另外,规定了邻居节点数的上限阈值,每次路由更新只保留鲁棒系数最优的邻居。仿真结果表明GRAEB不仅提高了网络可靠性,而且延长了网络寿命。