Vegetation Change in Great Lakes Coastal Wetlands: Deviation from the Historical Cycle

Water-level change is integral to the structure and function of Great Lakes coastal wetlands, and many studies document predictable relationships between vegetation and water level. However, anthropogenic stressors, such as invasive species, land-use change, and water-level stabilization, interact to shift the historical cycle (of native vegetation migration up- and down-slope) toward dominance by invasive Typha species. Knowing from earlier studies that water-level stabilization alters the historical vegetation cycle, we asked if similar shifts can occur where water levels are not stabilized. Using historical aerial photographs of three coastal wetlands (in Lake Michigan's Green Bay, Wisconsin), we determined that habitat dominated by Typha species has expanded to eliminate wet meadow habitat. Between 1974 and 1992, linear regressions showed strong, significant relationships of both meadow area (R² ≥ 0.894; p < 0.02) and marsh area (R² ≥ 0.784; p < 0.05) to water level in all three wetlands. In 2000, meadow area was below that predicted by the historical pattern due to the landward advance of marsh habitat during a year of decreasing water levels. In the same period, land use in the wetland watersheds converted from agriculture to urban. Urbanization and the replacement of native Typha latifolia by the invasive hybrid Typha xglauca may have overwhelmed the beneficial impact of water-level fluctuation. The documentation of vegetation shifts, as herein, is an essential step in the process of preserving and restoring ecological integrity.     

Introducing autonomous aerial robots in industrial manufacturing

Although ground robots have been successfully used for many years in manufacturing, the capability of aerial robots to agilely navigate in the often sparse and static upper part of factories makes them suitable for performing tasks of interest in many industrial sectors. This paper presents the design, development, and validation of a fully autonomous aerial robotic system for manufacturing industries. It includes modules for accurate pose estimation without using a Global Navigation Satellite System (GNSS), autonomous navigation, radio-based localization, and obstacle avoidance, among others, providing a fully onboard solution capable of autonomously performing complex tasks in dynamic indoor environments in which all necessary sensors, electronics, and processing are on the robot. It was developed to fulfill two use cases relevant in many industries: light object logistics and missing tool search. The presented robotic system, functionalities, and use cases have been extensively validated with Technology Readiness Level 7 (TRL-7) in the Centro Bahía de Cádiz (CBC) Airbus D&S factory in fully working conditions.     

Do the Kallikaks look "menacing" or "retarded?"

To extend R. E. Fancher's (see record 1987-31600-001) review of claims that photographs of the Kallikak family in H. H. Goddard's (1912) study had been retouched to make them look more menacing and retarded, 29 Ss (aged 18–69 yrs) were surveyed for their impressions of the photographs. Overall, Ss were strongly inclined to view the photographed individuals as "kind" and "very bright." (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

More on Goddard and the Kallikak family photographs.

Discusses retouching of the Kallikak family photographs in H. H. Goddard's (1912) study of mental retardation and heredity, with reference to analyses by R. E. Fancher (see record 1987-31600-001) and S. J. Gould (1981), and concurs with Fancher that the retouching was probably not done for deceitful purposes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

近程防御系统中多空中目标威胁度分析

研究近程防御系统,快速打击威胁目标的控制是整个系统的主要问题。针对敌方空中目标批次较多、运动状态复杂,而我方防御火力有限,对目标进行有效、精确拦截,需要对目标威胁度排序,依次进行打击。为了正确识别对整个目标过程,进行定性和定量的分析判断,提出了一种行之有效的灰色关联分析的变权威胁度分析方法;进行仿真,生成空中多组动态飞行目标,采用上述算法对空中目标有效识别,并对威胁度进行排序,进行打击。实验结果与专家评估后的结果完全一致,并能够准确而快速的在战场做出决策。     

中继协同无人机辅助的认知无线电网络安全通信

针对中继协同无人机（UAV）辅助的无线通信网络,提出一种基于认知无线电网络（CRN）的物理层安全通信方案。利用二次发射机协同解码转发中继向目的接收机发送机密消息,将UAV用作移动干扰器发送干扰噪声,以降低窃听者的解码能力。在不影响主用户通信的前提下,通过联合优化UAV的飞行轨迹和发射功率提高系统的平均保密率,采用基于连续凸逼近的算法求解近似凸规划的保密率最大化问题。仿真结果表明,相较于优化功率和优化轨迹这两种传统方案,该方案能够进一步提高CRN系统通信的安全性。     

无人机航拍图像中裸露地表的识别

电力输电线路下方或附近的无覆盖物的裸露地表,是引起输电线路事故的主要隐患之一;从无人机电力巡检航拍图像中识别裸露地表可以预防类似事故的发生;由于Mask RCNN识别无人机电力巡检航拍图像中裸露地表的精度较低,提出一种图像特征融合的方法,即人工提取HOG和LBP两种不同的图像特征,经过不同权重的融合共同表征图像中裸露地表区域的特征,再对SVM进行训练并用于识别;实验结果表明,采用该方法识别率可以达到80％以上,识别时间少于60 ms;HOG和LBP两种特征在进行融合时,当两种特征的数量级相当时,得到的识别率最高;可见,该方法在具有较高识别率的同时,具有比较好的实时性,适合于无人机机载平台对航拍图像的初筛,且训练时间较少,权重参数规模小,为无人机航拍图像中目标物的识别提供一种新思路.     

航空材料的两种激光表面处理技术

针对航空材料的表面强化问题,分析了激光表面处理技术在航空材料上应用的发展现状.论述了两种类型激光表面处理技术的基本原理和国内外研究现状.分析了激光表面处理技术在航空材料上应用的发展方向.     

用于UAV视觉导航的跑道检测与跟踪

跑道检测与跟踪是UAV视觉导航研究的重点内容.针对UAV着陆过程中跑道变化情况,提出一种新的方法,利用单目视觉信息,基于距离跑道的远近不同采用不同的策略实现跑道检测与跟踪,帮助UAV自主降落在安全区域.当距离较远时,利用地平线检测和模板匹配的方法对跑道进行定位;结合模板更新策略实现跑道跟踪;当距离较近时,在融合远距离跑道方位信息的基础上利用改进型Canny算子和Hough变换对跑道边缘进行更精确的描述.实验结果表明,利用该方法可以有效地对跑道进行检测和跟踪,并且具有较快的处理速度.     

孪生网络框架下融合显著性和干扰在线学习的航拍目标跟踪算法

针对一般跟踪算法不能很好地解决航拍视频下目标分辨率低、视场大、视角变化多等特殊难点,该文提出一种融合目标显著性和在线学习干扰因子的无人机(UAV)跟踪算法.通用模型预训练的深层特征无法有效地识别航拍目标,该文跟踪算法能根据反向传播梯度识别每个卷积滤波器的重要性来更好地选择目标显著性特征,以此凸显航拍目标特性.另外充分利用连续视频丰富的上下文信息,通过引导目标外观模型与当前帧尽可能相似地来在线学习动态目标的干扰因子,从而实现可靠的自适应匹配跟踪.实验证明:该算法在跟踪难点更多的UAV123数据集上跟踪成功率和准确率分别比孪生网络基准算法高5.3%和3.6%,同时速度达到平均28.7帧/s,基本满足航拍目标跟踪准确性和实时性需求.