干扰条件下的“北斗”信号解扩重构DOA估计

在干扰条件下，卫星导航抗干扰波束形成算法往往需要卫星信号波达方向（Direction-of-Arrival，DOA）的先验信息。但当存在低信噪比信号或主动干扰源时，常规的DOA估计算法性能急剧下降甚至失效。针对此问题，提出了一种被干扰信号压制的低信噪比“北斗”信号的DOA估计算法。该算法首先通过对接收信号进行子空间投影抑制干扰信号，然后对抑制干扰后的信号进行解扩重构处理，最后通过多重信号分类算法完成对“北斗”信号的DOA估计。仿真结果表明，在干扰信号干信比80 dB条件下，“北斗”信号DOA估计误差在5°以内，为下一步进行波束形成计算提供了高精度的入射角信息。     

基于信号增强的缓慢泄漏检测方法

目前管道泄漏检测方法可有效检测突发泄漏，对于缓慢泄漏则存在检测灵敏度低、定位不准确等问题。基于此，提出了一种基于信号增强的缓慢泄漏检测方法。通过信号压缩（抽取及移位）克服缓慢泄漏压力信号下降平缓的缺点；根据声波信号具有波形尖锐突出、对突发泄漏敏感的优点，通过建立以压力为输入、虚拟声波为输出的声波信号变送器模型，将压力信号转换为声波信号，克服了泄漏压力信号容易被淹没在管道压力波动及背景噪声中的缺点，实现了缓慢泄漏信号的增强；利用临近插值方法重构虚拟声波信号，基于延时互相关分析实现了缓慢泄漏的准确定位。实验结果表明，该方法具有显著的信号增强效果和定位精度，实现了缓慢泄漏的准确检测。     

Nonlinear dynamic behaviors and control based on simulation of high-purity heat integrated air separation column

In this paper, the dynamic behaviors on the basis of simulation for high-purity heat integrated air separation column (HIASC) are studied. A nonlinear generic model control (GMC) scheme is proposed based on the nonlinear behavior analyses of a HIASC process, and an adaptive generic model control (AGMC) scheme is further presented to correct the model parameters online. Related internal model control (IMC) scheme and multi-loop PID (M-PID) scheme are also developed as the comparative base. The comparative researches are carried out among these linear and nonlinear control schemes in detail. The simulation research results show that the proposed AGMC schemes present advantages in both servo control and regulatory control for the high-purity HIASC.     

面部运动单元检测研究综述

面部运动单元检测旨在让计算机从给定的人脸图像或视频中自动检测需要关注的运动单元目标。经过二十多年的研究，尤其是近年来越来越多的面部运动单元数据库的建立和深度学习的兴起，面部运动单元检测技术发展迅速。首先，阐述了面部运动单元的基本概念，介绍了已有的常用面部运动单元检测数据库，概括了包括预处理、特征提取、分类器学习等步骤在内的传统检测方法；然后针对区域学习、面部运动单元关联学习、弱监督学习等几个关键研究方向进行了系统性的回顾梳理与分析；最后讨论了目前面部运动单元检测研究存在的不足以及未来潜在的发展方向。     

弱相互作用调控表面活性剂自组装(Ⅱ)——表面活性剂的结构与设计

介绍了表面活性剂的结构、性质以及分类,综述了阴离子表面活性剂、阳离子表面活性剂、两性离子表面活性剂、非离子表面活性剂的分子间弱相互作用。另外,简述了低聚型表面活性剂和其他新型表面活性剂的结构及应用。     

Revisiting the Parallel Strategy for DOACROSS Loops

Journal of Computer Science and Technology - DOACROSS loops are significant parts in many important scientific and engineering applications, which are generally exploited pipeline/wave-front...     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.     

应用膨胀算法提取目标的直接定位算法

为了解决被动雷达系统中的多发射源定位问题，提出了一种基于多重信号分类(MUSIC)算法和图像膨胀(IE)算法的直接定位方法。该方法结合了谱分析中的MUSIC思想，通过对接收量测协方差矩阵进行特征分析求解目标的位置。首先，在目标个数未知的前提下，利用Akaike信息准则(AIC)来确定模型阶数；然后，推导了基于MUSIC的定位代价函数；之后，利用图像膨胀算法处理得到的代价函数平面；最后，膨胀处理后的输出为目标个数及目标位置的估计值。提出的算法有效地解决了目标检测及提取的问题，能够确定多个目标的位置坐标，为后续的定位性能分析提供可能性，也保证了算法的完整性。进一步地分析了多个临近目标情况下影响目标提取性能的主要因素。     

Weak Delocalization in Graphene on a Ferromagnetic Insulating Film

Graphene has been predicted to develop a magnetic moment by proximity effect when placed on a ferromagnetic film, a promise that could open exciting possibilities in the fields of spintronics and magnetic data recording. In this work, the interplay between the magnetoresistance of graphene and the magnetization of an underlying ferromagnetic insulating film is studied in detail. A clear correlation between both magnitudes is observed but through a careful modeling of the magnetization and the weak localization measurements, that such correspondence can be explained by the effects of the magnetic stray fields arising from the ferromagnetic insulator is found. The results emphasize the complexity arising at the interface between magnetic and 2D materials.     

A Mobile Cloud-Based eHealth Scheme

Mobile cloud computing is an emerging field that is gaining popularity across borders at a rapid pace. Similarly, the field of health informatics is also considered as an extremely important field. This work observes the collaboration between these two fields to solve the traditional problem of extracting Electrocardiogram signals from trace reports and then performing analysis. The developed system has two front ends, the first dedicated for the user to perform the photographing of the trace report. Once the photographing is complete, mobile computing is used to extract the signal. Once the signal is extracted, it is uploaded into the server and further analysis is performed on the signal in the cloud. Once this is done, the second interface, intended for the use of the physician, can download and view the trace from the cloud. The data is securely held using a password-based authentication method. The system presented here is one of the first attempts at delivering the total solution, and after further upgrades, it will be possible to deploy the system in a commercial setting.