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。     

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。     

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。     

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.     

一种基于固件的云系统策略文件完整性安全机制

针对云系统服务器之间共享策略文件所面临的完整性安全威胁,提出一种新的基于固件的策略安全机制。该机制可在云系统服务器平台之间安全且快速地进行共享策略文件交互,并可对共享策略文件进行完整性校验,进而提高协同工作的服务器所共享策略文件的安全性。实验结果表明,该机制有效实现了云系统环境下共享策略文件的完整性安全,同时提高了云系统管理员的管理效率。     

连续冶炼冶金焦工艺初探──（Ⅰ）现状分析和连续混热式焦炉的结构

本文论述了炼焦工艺的现状和发展方向，分析了存在的问题，提出了一种全新的连续型混热式冶金焦炉结构及其工艺流程，为焦化工业的发展探讨了一条新的途径。     

Efficient multilevel image segmentation through fuzzy entropy maximization and graph cut optimization

The fuzzy c-partition entropy has been widely adopted as a global optimization technique for finding the optimized thresholds for multilevel image segmentation. However, it involves expensive computation as the number of thresholds increases and often yields noisy segmentation results since spatial coherence is not enforced. In this paper, an iterative calculation scheme is presented for reducing redundant computations in entropy evaluation. The efficiency of threshold selection is further improved through utilizing the artificial bee colony algorithm as the optimization technique. Finally, instead of performing thresholding for each pixel independently, the presented algorithm oversegments the input image into small regions and uses the probabilities of fuzzy events to define the costs of different label assignments for each region. The final segmentation results is computed using graph cut, which produces smooth segmentation results. The experimental results demonstrate the presented iterative calculation scheme can greatly reduce the running time and keep it stable as the number of required thresholds increases. Quantitative evaluations over 20 classic images also show that the presented algorithm outperforms existing multilevel segmentation approaches.     

Detecting changes of the Yellow River Estuary via SAR images based on a local fit-search model and kernel-induced graph cuts

The Yellow River Estuary area of China is under great pressure from both human intervention and natural processes. For analysis of the changes in this area, this article presents a novel change-detection method based on a local fit-search model and kernel-induced graph cuts in multitemporal synthetic aperture radar images. Change detection involves assigning a label to every pixel. This task is naturally formulated in terms of energy minimization, which can be effectively solved by graph cuts. The difference image is transformed implicitly by a kernel function so that an alternative to complex modelling of the original data makes the piecewise constant model become applicable for graph cuts formulation. An issue is that graph cuts are sensitive to the initial estimate. The local fit-search model is proposed to approximate to the local histogram while selecting an optimal threshold for the initial labelling, which leads to an effective constraint for graph cuts and computational benefits as well. Visual and quantitative analyses obtained on the Yellow River Estuary data set confirm the effectiveness of the proposed method and that it outperforms the other state-of-the-art methods of change detection.     

基于SVM模型的妫水河叶绿素a浓度的遥感反演

以北京市妫水河为研究区,基于2011年9月25日和2012年9月30日的两期叶绿素a浓度实测数据和准同步的环境一号卫星(HJ-1A)多光谱数据,分别构建一元线性和多元支持向量机模型(SVMM),通过决定系数R²和平均相对误差对模型的精度进行检验,用模型进行水体叶绿素a浓度的反演,并分析其时空分布特征。研究表明:在样本数较少的情况下,SVM具有很强的非线性映射能力,能够取得较好的预测结果,更适用于反演叶绿素a浓度。时间分布上,研究区叶绿素a浓度呈增加趋势,均值上升了6.86 μg/L;空间分布上,深水区叶绿素a浓度值低于浅水区,上游高于下游。国产HJ-1A CCD2多光谱数据以其4 d的时间分辨率,在水质动态变化监测方面具有优势。