基于二阶广义全变差的多帧图像超分辨率重建

图像超分辨率重建是图像处理领域的重要问题.本文将二阶广义全变差用于基于正则化的多帧图像超分辨率重建问题,构建了基于二阶广义全变差正则项的图像超分辨率模型.为了更好地保持重建图像的边缘和细节,采用图像空域自适应正则化参数,并针对该重建模型的非光滑性,给出了基于半二次正则化和交替方向法的求解算法.实验结果表明该模型和数值算法能够较好地提高图像的分辨率,同时可以较好地保持图像的细节信息.     

一种面向高斯差分图的压缩感知目标跟踪算法

传统的压缩感知目标跟踪在目标纹理改变、比例缩放、光照变化剧烈时鲁棒性不足,本文提出一种面向高斯差分图的压缩感知目标跟踪算法。首先,构建原始图像的多尺度空间及其对应的图像高斯差分图,实现高斯差分图的特征提取并获取压缩感知的输入信号;然后,通过压缩降维,目标邻域遍历,参数更新等过程,计算出面向高斯差分图的后续帧的目标最优跟踪窗;最后,将跟踪窗投影到对应的原始图像上,完成面向视频流的目标跟踪。实验证明,高斯差分图像是单通道灰度图,相比较原始视频流的三通道彩色图,具有灰度取值范围小,数值低,结构简单,维数少等特点,增强了特征对纹理改变、比例缩放和光照变化的稳健性,且继承了原始算法的实时性。因此,与传统的压缩感知算法相比,本文算法能快速准确地实现复杂环境下的移动目标跟踪任务,具有更强的鲁棒性。     

一种基于多传感器的红外图像正则化超分辨率算法

提出一种红外图像多传感器超分辨率重建算法。 算法存在两个关键点:一是有效利用两类图像的相关性;二是针对红外图像的特点利用其自 身信息 构造正则化模型。采用相位一致性算法提取可见光图像边缘,利用此边缘信息对正则化模型 加权,以 充分利用可见光和红外图像的相关性;将一阶梯度锐化算子引入总广义变分模型,构成针对 红外 图像特点的正则化模型;最后采用一阶主-对偶优化算法求得加权后模型的最优解。实验表 明,本文算法可获得边缘清晰的重建结果,并且有效抑制噪声,在主观视觉效果和客观评价 指标方面均优于其他算法。     

基于近红外体散射数据的气溶胶尺度谱正则化反演方法

基于0.86 um 波段气溶胶的体散射数据,提出了一种新的尺度谱反演方法。根据大气气溶胶尺度谱特征,将尺度谱函数n(r)分解为趋势变化函数H(r)和细节变化函数(r),并构造了一组新的基函数对(r) 进行参数化逼近,然后严格照Mie 散射理论,采用Tikhonov 正则化对尺度谱函数进行了反演。采用城市型、乡村型和海洋型气溶胶的尺度谱实测数据进行反演仿真,结果表明,在粒径0.2~10 um 区间、噪声不大于50%的条件下,实际与反演的尺度谱曲线相关系数高于0.98,表现出良好的抗噪声能力;针对小尺寸段(r0.2 um)反演结果的不稳定性,提出了小尺寸段的荣格分布修正法与细模态参数补偿法,模拟结果表明,两种方法对尺度谱修正效果较理想,在0.1~10 um 区间,实际与反演尺度谱曲线相关系数大于0.97。与基于遗传算法的尺度谱反演方法相比,该方法效率高,耗时短,且对尺度谱函数细节变化特征反演较好。     

换热型节能技术在基站中的应用研究

换热型节能技术虽在基站中得到了大量应用,但由于应用场景至今还没有科学客观定量评估规定,使工程实施处于一种无章可循的尴尬局面,阻碍了换热型节能技术的进一步推广和应用。深入研究分析了基站内各类设备工作环境温湿度、空气清洁度和换热型节能设备能效比等技术指标,对比了不同标准中相关技术指标,指出了不同标准相关技术指标差别和部分标准存在的问题,并结合大气空气质量和环境温度等因素,提出了换热型节能技术应用场景和新风系统工程设计方法。     

大尹格庄金矿深部采场稳定性分析与参数优化

以大尹格庄金矿-616m水平8204采场为工程依托,对采场进行稳定性分析及结构参数优化。为此,对8204采场进行工程地质调查、矿岩力学性质试验,并应用Q系统和RMR分级法对采场岩体质量进行评价。基于Mathews稳定性图表法、临界跨度图表法和数值模拟,对采场尺寸和最大跨度进行优化。分析认为,8204采场的最佳跨度为12m,并将其结果应用于现场。结果表明,采用采场暴露面尺寸为12m×100m的结构参数进行回采,采场顶板及围岩并未发生垮落及剥落现象,采场稳定性良好。     

Spatial analyses of wildlife contact networks

Datasets from which wildlife contact networks of epidemiological importance can be inferred are becoming increasingly common. A largely unexplored facet of these data is finding evidence of spatial constraints on who has contact with whom, despite theoretical epidemiologists having long realized spatial constraints can play a critical role in infectious disease dynamics. A graph dissimilarity measure is proposed to quantify how close an observed contact network is to being purely spatial whereby its edges are completely determined by the spatial arrangement of its nodes. Statistical techniques are also used to fit a series of mechanistic models for contact rates between individuals to the binary edge data representing presence or absence of observed contact. These are the basis for a second measure that quantifies the extent to which contacts are being mediated by distance. We apply these methods to a set of 128 contact networks of field voles (Microtus agrestis) inferred from mark–recapture data collected over 7 years and from four sites. Large fluctuations in vole abundance allow us to demonstrate that the networks become increasingly similar to spatial proximity graphs as vole density increases. The average number of contacts, , was (i) positively correlated with vole density across the range of observed densities and (ii) for two of the four sites a saturating function of density. The implications for pathogen persistence in wildlife may be that persistence is relatively unaffected by fluctuations in host density because at low density is low but hosts move more freely, and at high density is high but transmission is hampered by local build-up of infected or recovered animals.     

Network morphospace

The structure of complex networks has attracted much attention in recent years. It has been noted that many real-world examples of networked systems share a set of common architectural features. This raises important questions about their origin, for example whether such network attributes reflect common design principles or constraints imposed by selectional forces that have shaped the evolution of network topology. Is it possible to place the many patterns and forms of complex networks into a common space that reveals their relations, and what are the main rules and driving forces that determine which positions in such a space are occupied by systems that have actually evolved? We suggest that these questions can be addressed by combining concepts from two currently relatively unconnected fields. One is theoretical morphology, which has conceptualized the relations between morphological traits defined by mathematical models of biological form. The second is network science, which provides numerous quantitative tools to measure and classify different patterns of local and global network architecture across disparate types of systems. Here, we explore a new theoretical concept that lies at the intersection between both fields, the ‘network morphospace’. Defined by axes that represent specific network traits, each point within such a space represents a location occupied by networks that share a set of common ‘morphological’ characteristics related to aspects of their connectivity. Mapping a network morphospace reveals the extent to which the space is filled by existing networks, thus allowing a distinction between actual and impossible designs and highlighting the generative potential of rules and constraints that pervade the evolution of complex systems.     

面向社交网络分析的差分隐私保护研究综述

阐述了数据的差分隐私保护概念,给出了差分隐私保护模型,从理论上描述了其噪声机制和组合性质,着重进述了差分隐私保护模型在社交网络发布数据隐私保护上的应用及发展,给出了差分隐私保护应用于度分布查询、子图计数、聚类系数计算、边权重计算等社交网络分析技术的实验结果。分析发现,研究差分隐私保护应重点考虑隐私预算和噪声机制,隐私预算决定了隐私保护强度,噪声机制决定了查询准确性;探讨差分隐私保护在社交网络领域的应用,是一个重要的研究方向。