Improving Target Detection Ability Based on Time Invariant and Dot-Shape Beamforming in TMRC-FDA-MIMO Radar

Epilepsy is a severe neurological disease which is diagnosed by analyzing Electroencephalogram. The epileptic seizure detection technique based on multiscale entropies and complete ensemble empirical mode decomposition (CEEMD) is proposed in this paper. CEEMD is used for the estimation of sub-bands and two multiscale entropies; multiscale dispersion entropy (MDE) and refined composite MDE are extracted from the sub-bands. The feature selection method, configured by hybridizing the filter based and wrapper based method, is used to select relevant multiscale entropies. The hybrid method has not only reduced features but also improved classification performance. An artificial neural network is trained with relevant features and performance is measured using classification accuracy, sensitivity and specificity. Five clinically relevant classification problems are used to assess the proposed technique. The performance is also compared with the state of the art techniques. The proposed technique has shown an improvement in detection of seizures and can be used to build the clinical system for epileptic seizure detection.

     

面向移动内容分发网络环境的移动视频预取技术研究进展

随着移动互联网的发展和视频应用的普及,移动内容分发网络(MCDN)应运而生。预取技术是内容分发的关键技术之一,它通过预测用户未来的请求,提前将预测的内容预取至网络边缘,从而减少数据的获取时延、提升用户体验质量(QoE)。为深入阐述移动视频预取技术的发展现状,从用户移动行为感知、内容属性感知、网络资源感知等角度分析梳理了移动视频预取技术的最新研究成果,同时分析了各类预取方案的性能及其主要优缺点,最后指出未来可以进一步研究的方向。     

基于区块链的云数据匿名确定性删除方法

现有确定性删除方案忽略了用户数据与用户身份的关联性,使用户的删除行为暴露给攻击者或云服务提供商。为解决此问题,提出一种基于区块链的云数据匿名确定性删除方法。该方法改进了可链接环签名方案,使用户可以通过控制签名中的链接标记在匿名情况下实现确定性删除;同时,它利用区块链记录删除行为,使其具有不可抵赖性。理论分析和实验表明:该方法不仅能满足用户数据的确定性删除要求,而且具有匿名性可以切断用户数据与其身份的关联,从而有效避免攻击者或云服务提供商对用户行为的追踪分析。     

激光选区熔化工艺晶格支撑结构快速建模

针对激光选区熔化成型工艺中的支撑结构,提出一种晶格单元自动填充生成支撑 的快速建模方法。首先,分别对两种典型晶格支撑结构--杆架结构和孔隙结构的组成单元实 现参数化造型,并建立支撑结构数字化模型;其次,设计实现杆件单元和孔隙单元的造型算法; 最后,提出一种单元自然生长算法,实现对支撑空间快速填充。实例结果表明,晶格结构可以 对不同类型金属产品结构实现有效稳定支撑;相比实体材料,平均可以节省 72%的材料用量, 具有重要的工程意义。     

Pulmonary nodule diagnosis using dual‐modal supervised autoencoder based on extreme learning machine

In recent years, deep learning techniques have been applied to the diagnosis of pulmonary nodules. In order to improve the pulmonary nodule diagnostic performance effectively, we propose a novel pulmonary nodule diagnosis method using dual‐modal deep supervised autoencoder based on extreme learning machine for which discriminative features are automatically learnt from the input data. The network is fed with nodule images in pairs obtained from computed tomography and positron emission tomography respectively. For each pair image, the high‐level discriminative features of nodules in computed tomography and positron emission tomography are extracted from stacked supervised autoencoder layers. The outputs of the proposed architecture are combined using an ideal fusion method to get the final classification. In the experiments, 5‐fold cross‐validation method is used to validate the proposed method on 1,600 pulmonary nodule images and our method reaches high‐classification sensitivities of 91.75% at 1.58 false positives per scan. Meanwhile, compared with other deep learning diagnosis methods, our method achieves better discriminative results and is highly suited to be used for pulmonary nodule diagnosis.     

Hybrid followee recommendation in microblogging systems

Bug reports are widely employed to facilitate software tasks in software maintenance. Since bug reports are contributed by people, the authorship characteristics of contributors may heavily impact the perfor-mance of resolving software tasks. Poorly written bug reports may delay developers when fixing bugs. However, no in-depth investigation has been conducted over the authorship characteristics. In this study, we first leverage byte-level N-grams to model the authorship characteristics and employ Normalized Simplified Profile Intersection (NSPI) to identify the similarity of the authorship characteristics. Then, we investigate a series of properties related to contributors’ authorship characteristics, including the evolvement over time and the variation among distinct products in open source projects. Moreover, we show how to leverage the authorship characteristics to facilitate a well-known task in software maintenance, namely Bug Report Summarization (BRS). Experiments on open source projects validate that incorporating the authorship characteristics can effectively improve a state-of-the-art method in BRS. Our findings suggest that contributors should retain stable authorship characteristics and the authorship characteristics can assist in resolving software tasks.

     

超滤膜孔径及其分布的测定方法──Ⅰ．常用测定方法讨论

讨论了超滤膜孔径的物理意义，指出其与固体表面吸附体系中孔径概念的区别，讨论了现行各种测定方法的原理及在超滤膜孔径测定中的适用性。     

一种改进的Hilbert-Huang变换方法及其应用

针对希尔伯特-黄变换方法中存在的端点效应和虚假模态分量等问题,通过对上述问题产生原因的分析,提出一种基于边界极值均值延拓的端点效应抑制方法与虚假模态分量剔除算法相结合的改进方法。该方法首先根据信号两侧端点和其临近极值点的特性,对包络线在信号两端点处的位置进行约束,从而改善包络线拟合结果,在一定程度上抑制端点效应问题的产生。然后,依据各模态分量间的正交性原理,通过虚假模态分量剔除算法,选取能够反映信号特征的敏感模态分量,以保证分析的准确性。通过数值仿真,验证了所提方法的有效性。最后,应用于发动机异响故障诊断中,诊断结果表明该方法有效抑制了传统希尔伯特-黄变化方法的端点效应和虚假模态问题,可有效提取发动机异响信号的故障特征。     

Effect of annealing on the structure and properties of polyvinylidene fluoride hollow fiber by melt‐spinning

Polyvinylidene fluoride hollow fibers were prepared by melt‐spinning technique under three spinning temperatures. The effects of annealing treatment on the structure and properties of hollow fiber were studied by differential scanning calorimetry (DSC), wide‐angle X‐ray diffraction (WAXD), tensile test, and scanning electron microscopy (SEM) measurements. DSC and WAXD results indicated that the annealing not only produced secondary crystallization but also perfected primary crystallization, and spinning and annealing temperature influenced the crystallinity of hollow fiber: the crystallinity decreased with the increase of spinning temperature; 140°C annealing increased the crystallinity, and hardly influenced the orientation of hollow fiber; above 150°C annealing increased the crystallinity as well, and furthermore had a comparative effect on the orientation. The tensile tests showed that the annealed samples, which did not present the obvious yield point, exhibited characteristics of hard elasticity, and all the hollow fiber had no neck phenomenon. Compared with the annealed sample, the precursor presented a clear yield point. In addition, the annealed samples had a higher break strength and initial modulus by contrast with the precursor, and the 140°C annealed sample showed the smallest break elongation. SEM demonstrated the micro‐fiber structure appeared in surface of drawn sample. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 935–941, 2007