Estimation of crowd density from UAVs images based on corner detection procedures and clustering analysis

With rapid developments in platforms and sensors technology in terms of digital cameras and video recordings, crowd monitoring has taken a considerable attentions in many disciplines such as psychology, sociology, engineering, and computer vision. This is due to the fact that, monitoring of the crowd is necessary to enhance safety and controllable movements to minimize the risk particularly in highly crowded incidents (e.g. sports). One of the platforms that have been extensively employed in crowd monitoring is unmanned aerial vehicles (UAVs), because UAVs have the capability to acquiring fast, low costs, high-resolution and real-time images over crowd areas. In addition, geo-referenced images can also be provided through integration of on-board positioning sensors (e.g. GPS/IMU) with vision sensors (digital cameras and laser scanner). In this paper, a new testing procedure based on feature from accelerated segment test (FAST) algorithms is introduced to detect the crowd features from UAV images taken from different camera orientations and positions. The proposed test started with converting a circle of 16 pixels surrounding the center pixel into a vector and sorting it in ascending/descending order. A single pixel which takes the ranking number 9 (for FAST-9) or 12 (for FAST-12) was then compared with the center pixel. Accuracy assessment in terms of completeness and correctness was used to assess the performance of the new testing procedure before and after filtering the crowd features. The results show that the proposed algorithms are able to extract crowd features from different UAV images. Overall, the values of Completeness range from 55 to 70 % whereas the range of correctness values was 91 to 94 %.     

长江口徐六泾悬浮细颗粒泥沙絮凝体特性

2003年6月14日-22日, 利用现场激光粒度仪LISST-100在不扰动颗粒物的情况下, 于长江口徐六泾定点连续观测了洪季大、小潮表层粘性悬浮细颗粒泥沙絮凝体的实有粒径、体积浓度, 配合OBS-3A现场测量的悬沙浓度计算了现场絮凝体的有效密度和静水沉速.观测结果显示, 徐六泾大、小潮表层絮凝体体积浓度、粒径、有效密度和静水沉速的平均值分别为98.0 μl/L、39.8 μm、1173 kg/m^3、1.14 mm/s和70.8 μl/L、64.4 μm、919 kg/m^3、2.32 mm/s.研究表明： ①长江口徐六泾表层絮凝体体积浓度主要受水流流速影响, 再悬浮现象明显, 体积浓度过程线滞后流速过程线, 落潮期间滞后10-30 min, 涨潮则滞后30-50 min; ②小于一定流速时絮凝体平均粒径随流速增大而增大, 大于一定流速时絮凝体平均粒径则随流速增大而减小, 徐六泾大、小潮表层絮凝体在50 cm/s的垂线平均流速时出现平均粒径与垂线平均流速关系的转折; ③徐六泾大、小潮表层絮凝体平均粒径在体积浓度75 μl/L时出现平均粒径与体积浓度关系的转折, 体积浓度小于75 μl/L时粒径随体积浓度增加而增大, 超过75 μl/L时粒径随体积浓度的增加变化不明显; ④絮凝体有效密度由粒径大小控制, 粒径大, 有效密度小, 反之亦然, 粒径和有效密度共同决定絮凝体静水沉速, 有效密度和沉速与平均粒径之间均存在良好的幂指数关系.     

Distribution patterns of interstitial polychaetes in sandy beaches of southern Brazil

This study describes the distribution patterns of interstitial polychaetes along morphodynamic gradients on six exposed sandy beaches in Santa Catarina and Paraná (South Brazil). Three random transects were sampled at two points on each beach, one at the swash and another at the surf zone, in winter and summer conditions. Six sediment replicates were collected at each sampling point using a corer of 4.6 cm internal diameter that removed 10 cm into the sediment. Abundance and composition of interstitial polychaete were correlated to wave height, slope, grain size, CaCO₃, chlorophyll a , omega indexes, temperature and relative tide range using a canonical correspondence analysis (CCA). A factorial ANOVA showed that taxa richness, mean density and Shannon's diversity were significantly higher at the reflective beaches, but average values differ significantly between transects and these differences change according to the beach zones on both sampling dates. PERMANOVA showed that polychaete associations differ among transects according to the beach zones. The composition of interstitial polychaete associations was significantly correlated to beach morphodynamics and features (P < 0.01). Polychaete associations of reflective beaches were more diverse than in other morphodynamic states. Intermediate beaches may also sustain diverse associations due to temporal variability of the morphodynamic patterns. Beaches presenting extreme dissipative morphodynamics and compacted sediments appear to be unfavourable for the occurrence of interstitial polychaetes.     

密度权稳健估计

利用观测量分布函数作为权函数的计算公式,分析了密度权法的抗差性和收敛速率,证实了用密度权法处理含粗差数据是行之有效的。     

On the use of iterative re-weighting least-squares and outlier detection for empirically modelling rates of vertical displacement

The proper identification and removal of outliers in the combination of rates of vertical displacements derived from GPS, tide gauges/satellite altimetry, and GRACE observations is presented. Outlier detection is a necessary pre-screening procedure in order to ensure reliable estimates of stochastic properties of the observations in the combined least-squares adjustment (via rescaling of covariance matrices) and to ensure that the final vertical motion model is not corrupted and/or distorted by erroneous data. Results from this study indicate that typical data snooping methods are inadequate in dealing with these heterogeneous data sets and their stochastic properties. Using simulated vertical displacement rates, it is demonstrated that a large variety of outliers (random scattered and adjacent, as well as jointly influential) can be dealt with if an iterative re-weighting least-squares adjustment is combined with a robust median estimator. Moreover, robust estimators are efficient in areas weakly constrained by the data, where even high quality observations may appear to be erroneous if their estimates are largely influenced by outliers. Four combined models for the vertical motion in the region of the Great Lakes are presented. The computed vertical displacements vary between  − 2 mm/year (subsidence) along the southern shores and 3 mm/year (uplift) along the northern shores. The derived models provide reliable empirical constraints and error bounds for postglacial rebound models in the region.     

Application of probabilistic neural network to design breakwater armor blocks

This study presents a probabilistic neural network (PNN) technique for predicting the stability number of armor blocks of breakwaters. The PNN is prepared using the experimental data of Van der Meer. The predicted stability numbers of the PNN are compared with those of previous studies, i.e. by an empirical formula and a previous neural network model. The agreement index between the measured and predicted stability numbers by PNN are better than those by the previous studies. The PNN offers a way to interpret the network's structure in the form of a probability density function and it is easy to implement. Therefore, it can be an effective tool for designers of rubble mound breakwaters.     

南海北部海区软骨鱼类种类组成和资源密度分布

根据2006～2007年南海北部海区4季的调查资料,分析该海区软骨鱼类的种类组成和资源密度的分布．结果表明,软骨鱼类有32种,分隶于9目17科,优势种为斑鳐、曾氏兔银鲛、褐黄扁缸、橙黄鲨;渔获率D断面最高（10．19kg／h）,B断面最低（4．52kg／h）;渔获率有明显的季节变动,夏季最高（12．16kg／h）,秋季最低（3．71kg／h）,平均渔获率为7．05kg／h;密集分布于180m和140m水深处;其年均资源密度为94．00kg／km^2．文中并讨论合理利用和保护该类群的措施．     

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耿达短水准异常与汶川8.0级地震

结合龙门山断裂带其他跨断层资料,对耿达短水准在汶川8.0级地震前后的观测资料进行了重新分析,发现耿达短水准在汶川地震前后的异常为当地居民修建生活小区所致,不应视为地震前兆异常。     

能效渔业状态下津市西湖生态因子与浮游植物密度的灰关联模型{GM(I,N)}

利用灰色系统理论,于2004—2008年5—8月份对能效渔业状态下津市西湖水质状况进行了实时采样研究,并计算了浮游植物密度与透明度、水温、水深、溶解氧、pH、NH4-N、NO3-N、NO2-N、PO4-P、TP、TN、NH4-N/PO4-P、TN/TP和浮游动物共14个生态因子的关联度、关联序。结果表明,透明度、水温、水深、溶解氧、pH和浮游动物(毛里湖)或TN(西湖)是影响浮游植物增殖态势的最重要的环境变量。提取如上变量和浮游植物密度作为建模要素,构建了津市西湖生态因子与浮游植物密度的灰关联模型{GM(I,N)},经作图分析表明,模型值和实测值具有较好的对应峰,表明模型的有效性及在预测上有较高的参考价值。P元素在西湖的营养限制性基本得到消除,水体N/P比被调控到了较好状态。