视觉对比度机制小目标增强与背景抑制综述北大核心CSCD

复杂背景中的红外弱小目标因亮度低、尺寸小、可用特征少而难以检测。如何在检测中抑制背景杂波、提高目标信噪比成为该领域的研究热点与难点。本文对基于人类视觉系统对比度机制的小目标增强与背景抑制技术的演进和性能进行了归纳与分析。局部对比度测度窗口由单尺度向多尺度,乃至动态或自适应尺度的发展,满足应用中对未知尺寸小目标同步快速检测的需要;局部对比度测度计算方法由简单到复杂、依据低阶信息到采用高阶信息的变化,有利于更全面地抑制复杂背景、进一步增强目标。因此,将成为未来人类视觉对比度机制小目标检测算法的发展方向。     

区块链技术在多元融合高弹性电网中的应用初探

多元融合高弹性电网通过构建源网荷储全向交互机制,显著提升了电网的互动与自愈能力。区块链技术采用去中心化理念和分布式记账模式,保障数据可信,打破信任壁垒,为电网多端友好互动提供了核心技术支撑。基于现有理论研究与工程实践,区块链的技术特征与高弹性电网的形态架构具有较强的理念契合性和技术互补性,区块链有潜力成为多元融合高弹性电网的重要赋能技术。面向多元融合高弹性电网的建设目标,刻画了区块链技术与高弹性电网深度融合的应用场景,梳理了建设高弹性电网过程中的关键痛点,阐明了区块链之于高弹性电网的技术赋能要素及匹配关系。面向高弹性电网的建设需求,提出了区块链系统的设计原则、评价指标以及设计流程,并以需求响应为例进行系统设计与性能测试,为区块链技术在高弹性电网中的应用提供理论支撑。     

Weakly supervised temporal action localization with proxy metric modeling

Temporal localization is crucial for action video recognition. Since the manual annotations are expensive and time-consuming in videos, temporal localization with weak video-level labels is challenging but indispensable. In this paper, we propose a weakly-supervised temporal action localization approach in untrimmed videos. To settle this issue, we train the model based on the proxies of each action class. The proxies are used to measure the distances between action segments and different original action features. We use a proxy-based metric to cluster the same actions together and separate actions from backgrounds. Compared with state-of-the-art methods, our method achieved competitive results on the THUMOS14 and ActivityNet1.2 datasets.     

Exploring the tidal effect of urban business district with large-scale human mobility data

Business districts are urban areas that have various functions for gathering people, such as work, consumption, leisure and entertainment. Due to the dynamic nature of business activities, there exists significant tidal effect on the boundary and functionality of business districts. Indeed, effectively analyzing the tidal patterns of business districts can benefit the economic and social development of a city. However, with the implicit and complex nature of business district evolution, it is non-trivial for existing works to support the fine-grained and timely analysis on the tidal effect of business districts. To this end, we propose a data-driven and multi-dimensional framework for dynamic business district analysis. Specifically, we use the large-scale human trajectory data in urban areas to dynamically detect and forecast the boundary changes of business districts in different time periods. Then, we detect and forecast the functional changes in business districts. Experimental results on real-world trajectory data clearly demonstrate the effectiveness of our framework on detecting and predicting the boundary and functionality change of business districts. Moreover, the analysis on practical business districts shows that our method can discover meaningful patterns and provide interesting insights into the dynamics of business districts. For example, the major functions of business districts will significantly change in different time periods in a day and the rate and magnitude of boundaries varies with the functional distribution of business districts.     

Label distribution learning for scene text detection

Recently, segmentation-based scene text detection has drawn a wide research interest due to its flexibility in describing scene text instance of arbitrary shapes such as curved texts. However, existing methods usually need complex post-processing stages to process ambiguous labels, i.e., the labels of the pixels near the text boundary, which may belong to the text or background. In this paper, we present a framework for segmentation-based scene text detection by learning from ambiguous labels. We use the label distribution learning method to process the label ambiguity of text annotation, which achieves a good performance without using additional post-processing stage. Experiments on benchmark datasets demonstrate that our method produces better results than state-of-the-art methods for segmentation-based scene text detection.     

计及可靠性收益的配电网柔性多状态开关及分布式电源综合优化配置

柔性多状态开关(flexible multi-state switch,FMS)是支撑新型电力系统背景下配电网运行控制能力提升和可再生能源接入渗透率改善的重要技术装备,针对现有配电网中FMS的规划并未详细考虑FMS与分布式电源(distributed generation,DG)的协调配置,以及对于FMS接入带来的可靠性提升考虑不足的问题。文章在规划配置阶段详细考虑了含FMS和DG的协同优化运行,并充分计及FMS接入带来的可靠性收益,构建了基于嵌套优化的FMS和DG选址定容双层优化配置模型。针对双层嵌套规划模型求解的复杂性,提出了基于改进粒子群算法和GAMS(general algebraic modeling language)算法相结合的模型求解策略,以改造后的IEEE 33节点算例系统为例,对所提出模型和方法的有效性进行了验证,结果表明提出的方法相比传统单一FMS规划具有更好的经济性,能最大程度地降低配电网年综合费用,同时减少用户因停电带来的损失。     

基于钛相变边缘传感器的超导单光子探测器特性

研究了基于钛TES的超导单光子探测器的特性,器件尺寸范围为5 μm×5 μm到20 μm×20 μm,集成光学腔体后在1 550 nm波长实测的系统探测效率最高达到72%,最佳能量分辨率为0.26 eV。在此基础上,采用二流体模型提取了基于钛TES的超导单光子探测器的特性参数（包括温度灵敏度、电流灵敏度、热容等）,并模拟计算了基于钛TES的超导单光子探测器的响应时间和能量分辨率,与实验结果完全吻合。结果表明优化探测器尺寸和临界温度,可以同时达到高探测效率和高能量分辨率,实现光子数可分辨的高性能单光子探测器。     

互联网时代用户参与制的产品设计研究

目的研究互联网时代不同行业用户参与制的产品设计方式。方法以互联网技术和网络平台为基础,建立互联网交流平台,打破不同行业、不同专业用户之间的专业知识壁垒,另外将用户散乱的创意和要求聚拢在一起,为产品的创新设计提供素材来源。结论通过对不同行业人员及用户利用互联网资源对产品设计的分析与研究,结合案例得出人人都可以参与产品设计的论证,同时打破了传统产品设计的规则性制约,使得产品设计不再是产品设计行业人士的专利,极大地降低了传统设计中的设计师研发成本。     

坑道内爆炸冲击波相似律问题探讨

为研究坑道内爆炸冲击波相似律问题,进行了不同药量坑道堵口爆炸实验,并利用ANSYS/LSDYNA软件对原型坑道与模型坑道爆炸冲击波进行数值计算。结果表明:与自由大气中不同,同一坑道内不同药量爆炸产生的冲击波不符合爆炸相似律;若原型坑道与模型坑道几何相似,装药量之比为几何相似比的三次方,则原型坑道与模型坑道内爆炸冲击波符合爆炸相似律;坑道内爆炸冲击波数值模拟时,若原型坑道与模型坑道网格尺寸符合相应的几何相似比,则冲击波计算结果满足相似律,当坑道截面网格密度为1675~2977时可以达到计算精度要求。     

固溶处理对TC11钛合金棒材组织和性能的影响

通过场发射扫描电镜及拉伸性能测试,研究了TC11钛合金棒材3种固溶处理时间和2种固溶方式对显微组织及力学性能的影响。结果表明:TC11钛合金在经过3 h的固溶后,组织中局部的亚稳定β晶体位相发生偏转,β转变组织中的次生α相变的粗大,经过后续时效后的β转变基体发生更为充分的分解和析出,在片层的β边界出现连续的更细小的次生α相。由于固溶时间延长,发生了过固溶,析出的次生相逐渐细小,导致裂纹扩展阻力降低,引起屈服强度的降低,分开各1 h的固溶时效性能低于连续2 h的固溶时效性能。