Variational PCA fusion for resolution Pan-sharpening very high imagery

The Pan-sharpening approach based on principle component analysis （PCA） is affected by severe spectral distortion. To address this problem, a new pan-sharpening model based on PCA and variational technique is proposed to construct the substitute image of the first principal component （PC1）. The energy functional consists of three terms. The first term injects PC1 with the geometric structure of the panchromatic （Pan） image. The second term preserves the spectral pattern of the multi-spectral image in the merged result. And the third term guarantees the smoothness of the functional optimization solution. The fusion result is given by the minimum of the energy functional, which is computed with the gradient descend flow. The experiments on QuickBird and IKONOS datasets validate the effectiveness of the proposed model. Compared with the state- of-the-art pan-sharpening approaches, this model exhibits a better trade-off between improving spatial quality and preserving spectral signature of the MS image.     

基于高精度流线生成的交互流场可视化

高效准确的流线绘制一直是流场可视化的重要研究内容,流线可以对流场的重要特征进行有效的稀疏表示,但流线需要长期的粒子追踪过程及大量的积分计算,在面向大规模流场可视化时时间效率较低,需要高性能计算设备进行辅助计算.本文通过设计一种基于深度学习的高精度流线生成算法,将初始的低精度流线快速映射为稠密的高精度流线,可以在较短的时间内快速生成可靠的流线可视化结果,并在此基础上设计了交互式实时流场可视化系统,涵盖了流场的特征检测,属性关联分析,信息论分析等,帮助用户快速了解流场数据,找到自己感兴趣的区域进行后续进一步深度分析,避免了获取过多冗余数据,同时优化了分析工作的效率,满足用户对于流场结构,特征属性等多维度进行关联分析的需求.     

A real-time vehicle detection and a novel vehicle tracking systems for estimating and monitoring traffic flow on highways

Real-time highway traffic monitoring systems play a vital role in road traffic management, planning, and preventing frequent traffic jams, traffic rule violations, and fatal road accidents. These systems rely entirely on online traffic flow info estimated from time-dependent vehicle trajectories. Vehicle trajectories are extracted from vehicle detection and tracking data obtained by processing road-side camera images. General-purpose object detectors including Yolo, SSD, EfficientNet have been utilized extensively for real-time object detection task, but, in principle, Yolo is preferred because it provides a high frame per second (FPS) performance and robust object localization functionality. However, this algorithm’s average vehicle classification accuracy is below 57%, which is insufficient for traffic flow monitoring. This study proposes improving the vehicle classification accuracy of Yolo, and developing a novel bounding box (Bbox)-based vehicle tracking algorithm. For this purpose, a new vehicle dataset is prepared by annotating 7216 images with 123831 object patterns collected from highway videos. Nine machine learning-based classifiers and a CNN-based classifier were selected. Next, the classifiers were trained via the dataset. One out of ten classifiers with the highest accuracy was selected to combine to Yolo. This way, the classification accuracy of the Yolo-based vehicle detector was increased from 57% to 95.45%. Vehicle detector 1 (Yolo) and vehicle detector 2 (Yolo + best classifier), and the Kalman filter-based tracking as vehicle tracker 1 and the Bbox-based tracking as vehicle tracker 2 were applied to the categorical/total vehicle counting tasks on 4 highway videos. The vehicle counting results show that the vehicle counting accuracy of the developed approach (vehicle detector 2 + vehicle tracker 2) was improved by 13.25% and this method performed better than the other 3 vehicle counting systems implemented in this study.     

基于国产处理器增量式实时交通流预测算法及实现

针对城市交通难以处理大量数据且实时性差等问题,提出了根据增量式城市交通流数据预测拥堵情况的一种基于国产处理器的L-BFGS(limited-memory BFGS)算法。该算法通过存储向量序列计算Hessian矩阵,改进Two-Loop算法求下降方向,在Spark集群中并行处理时收敛速度快,适用于实时性要求强的城市交通场景。实验结果证明,L-BFGS预测算法完全可以在国产平台上对大规模的实时交通数据流进行快速建模、预测,在改善城市交通管理水平提供有效支撑的同时也丰富了国产芯片的应用领域。     

面向交通流量预测的时空超关系图卷积网络

交通流量预测是智能交通系统中的重要研究课题,然而,交通对象（如站点、传感器）之间存在的复杂局部时空关系使得这项研究颇具挑战。尽管以往的一些研究将流量预测问题转化为一个时空图预测问题从而取得了较大的进展,但是它们忽略了交通对象们跨时空维度的直接关联性。目前仍缺乏一种全面建模局部时空关系的方法。针对这一问题,首先提出一种新颖的时空超图建模方案,通过构造一种时空超关系来全面地建模复杂的局部时空关系;然后提出一种时空超关系图卷积网络（STHGCN）预测模型来捕获这些关系用于交通流量预测。在四个公开交通数据集上进行了大量对比实验,结果表明,相比ASTGCN、时空同步图卷积网络（STSGCN）等时空预测模型,STHGCN在均方根误差（RMSE）、平均绝对误差（MAE）、平均绝对百分比误差（MAPE）这三个评价指标上均取得了更优的结果,不同模型运行时间的对比结果也表明,STHGCN有着更高的推理速度。     

顶部定常吸气对高层建筑模型气动力的影响

为减少高层建筑受到的风荷载,提高高层建筑抗风性能,提出一种顶部吸气的主动控制方法。在一高宽比为H/d=5的正方形截面柱体的高层建筑模型上,通过在其顶部前边缘开设狭缝进行吸气来实现流动控制。通过风洞试验研究了顶部吸气对气动力与顶部分离流的影响.利用流动可视化与流场测试结果揭示了顶部狭缝吸气的控制机理.实验对比了不同吸气系数Q(=U/U_∞,U为狭缝吸气速度)对气动力控制效果的影响,并对Q=0,1和3的三种工况下风压分布与顶部剪切流进行了详细对比.研究发现狭缝吸气改变了顶部分离流特性,并对模型所有高度上的气动力均有显著影响.Q=1时控制效果最佳,脉动阻力与脉动升力分别减小17.8%和45.5%.此时顶面分离流被削弱并伴随有再附现象且湍流强度较大,最有利于顶部剪切流与尾流间的动量交换,从而削弱柱体展向涡脱落与脉动气动力.     

Probabilistic and interval reliability design of the composite pressure vessel

Considering the randomness or interval character of physical parameters and applied loads of composite pressure vessels (COPV), the COPV reliability-analyzing model is built. And then the computational expressions for the mean value, standard deviation and deviation of fiber stress are deduced by the random factor method. The probabilistic and interval reliability designs on COPV are implemented by utilizing the probabilistic method and interval method combined with the improved particle swarm optimization (PSO) algorithm, respectively. The influence of fluctuation of structure uncertain parameters on COPV design thickness is inspected. Finally, examples are given to demonstrate that both probabilistic and interval reliability methods can satisfy the safety requirement and both are of higher rationality than the traditional safety factor method. And probabilistic method has a lower relative error but a higher computational complexity contrasted with the interval method.     

A customised approach to determining the geomorphic effectiveness of small flood events in a regulated river

The construction of dams significantly alters flow and sediment regimes with subsequent deleterious effects on the morphological and ecological character of rivers. Effective experimental floods can ameliorate the downstream geomorphic impacts of dams. The traditional view is that large floods are required to perform effective geomorphic work, and the geomorphic outcomes of small floods are often overlooked. Many river restoration frameworks do not consider small floods. Yet, there is evidence that the hydrological characteristics that ameliorate specific geomorphic impacts in a river are unique to each river, and a customised approach to setting the right mix of floods (including small experimental floods) is needed. In this study, we modify an existing flood effectiveness model developed for large floods, for determining the geomorphic effectiveness of small floods in a highly regulated Australian river. Two flood classes were added to the model (medium peak stream power and moderate total energy expenditure), and the flood power characteristics were rescaled to reflect the relative difference in the magnitude of the small floods and the magnitude of the geomorphic work performed. Using a step‐wise approach, this customised model determined the geomorphic effectiveness of small floods. The best flood for ameliorating the geomorphic impacts of flow regulation had medium to long duration (10 to 51 days), high peak unit stream power (77 to 123 Wm^?2) and moderate to large total energy expenditure (78,600 to 342,320 × 10³ J). This approach to determining flood effectiveness for small floods is applicable to other geomorphically impacted river channels downstream of dams and can be used to inform experimental flood releases for geomorphic outcomes.     

Dynamic buffering performance of the honeycomb paperboard filled with polyurethane

A new kind of composite buffering material was made by filling the voids of honeycomb paperboard with polyurethane. Drop tests were performed to evaluate the dynamic energy absorption capacity of the material. Based on the tests results, we analyzed the mechanical behaviors of the material under different conditions and obtained the inherent influencing laws of some factors on the material＇s dynamic buffering performance. It was shown that the dynamic buffering performance varied directly with impact velocity, and inversely with the void diameter, thickness and buffeting area of the composite material.     

基于表面反应和扩散迁移控制的灰岩单裂隙渗流—溶解模型及其数值模拟

针对碳酸盐类可溶岩地区水电站坝址流场、化学场以及固相介质属性等随时间发生改变,从而对工程安全运行造成不利影响等问题,研究了灰岩地区地下水运移过程中各物理场间的相互作用,分析了影响灰岩溶解速率的两个因素,即表面反应控制和扩散迁移控制。在此基础上,建立了单裂隙中的渗流—溶解耦合模型,并进行数值求解。模拟结果表明,在垂直裂隙延伸方向,其溶蚀锋面为非齐整平面,而是呈似“虫洞”状非均一变化,而沿裂隙延伸方向即自上游侧向下游方向溶蚀程度逐渐减轻;而通过裂隙的流量呈现随时间逐渐增大的趋势,但变幅不大;根据流量求得的等效水力隙宽,其增幅和增长速率均小于实际平均隙宽;同时,化学场中Ca2+浓度的分布与裂隙开度变化具有相似性,不同时刻下上游侧反应速率R均大于下游侧。就反应机制而言,在初期均受表面反应控制,而随反应进行,位于上游补给区部位转为受扩散迁移控制,但在下游位置仍受表面反应控制。