Experimental Evaluation of A New Developed Algorithm for An Autonomous Surface Vehicle and Comparison with Simulink Results

China Ocean Engineering - Performing repeatable duties automatically was the dreams of human being for centuries. Although full autonomy has long been dreamed of by visionaries, many researches...     

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 %.     

On the D́ust content of nearby galaxies

By inspection of photographs of the Hubble Atlas of Galaxies the frequency distribution of the sizes of dark cloud complexes in the four nearby galaxies NGC 3031, 5128, 5194 and 5457 is derived and the total amount of dust in these systems is estimated. The frequency distribution of the clouds is nearly the same in all the considered galaxies and may be approximated by n(R) ∼ e^−kR, k ≈︂ 0.050 pc⁻¹. The total amount of dust yields to roughly 10⁶M⊙.     

古尔班通古特沙漠地表辐射收支特征

古尔班通古特沙漠是中国最大的固定、半固定沙漠.利用2017年该沙漠克拉美丽站辐射资料,分析了古尔班通古特沙漠不同时间尺度和不同天气条件下的地表辐射变化特征.结果表明:(1)不同月份沙漠辐射收支各分量月平均日变化均呈单峰型,但极值大小及出现时间存在差异.各分量曝辐量季节变化明显:太阳总辐射表现为生长期(4-9月)＞积雪期...     

3D Static Modeling and Petrographic Aspects of the Albian/Cenomanian Reservoir,Komombo Basin,Upper Egypt

Natural Resources Research - The Albian/Cenomanian reservoir is one of the two main reservoirs composing the petroleum system in the Komombo Basin. However, these reservoirs have not previously...     

Detecting Land Subsidence Due to Groundwater Withdrawal in Aliabad Plain,Iran, Using ESA Sentinel-1 Satellite Data

Natural Resources Research - In the present study, ground subsidence in the Aliabad plain (central Iran) was investigated using differential synthetic aperture radar interferometry. The data used...     

Curie Point Depth Estimations for Northwest Iran Through Spectral Analysis of Aeromagnetic Data for Geothermal Resources Exploration

Natural Resources Research - The northwest of Iran is considered as a promising geothermal zone owing to its geographical properties, tectonic features, and thermal activities, particularly in...     

3D Structural,Facies and Petrophysical Modeling of C Member of Six Hills Formation,Komombo Basin,Upper Egypt

Natural Resources Research - Two main reservoirs are producing in Komombo Basin: the first one belongs to the C Member of the Six Hills Formation, and the second belongs to the Albian/Cenomanian...     

Compressive and rarefactive double layers in non-uniform plasma with $$-nonextensive distributed electrons

Electrostatic solitary waves and double layers (DLs) formed by the coupled ion acoustic (IA) and drift waves have been investigated in non-uniform plasma using \(q\)-nonextensive distribution function for the electrons and assuming ions to be cold \(T_{i}< T_{e}\). It is found that both compressive and rarefactive nonlinear structures (solitary waves and DLs) are possible in such a system. The steeper gradients are supportive for compressive solitary (and double layers) and destructive for rarefactive ones. The \(q\)-nonextensivity parameter \(q\) and the magnitudes of gradient scale lengths of density and temperature have significant effects on the amplitude of the double layers (and double layers) as well as on the speed of these structures. This theoretical model is general which has been applied here to the \(F\)-region ionosphere for illustration.     

Prediction of riverine suspended sediment discharge using fuzzy logic algorithms, and some implications for estuarine settings

The ability of fuzzy logic algorithms to model relationships between stream flow and suspended sediment discharge was investigated using daily measurements of stream flow and suspended sediment discharge for the Escanaba River mouth station, situated on the shore of Lake Michigan and operated by the US Geological Survey. Three different configurations of inputs were applied, whereby the inputs were fuzzified into fuzzy subsets of variables by means of triangular membership functions. The relationships between inputs and suspended sediment discharge (output) were represented by a set of fuzzy rule expressed in IF–THEN format. The weighted average method served for defuzzification. The commonly used sediment rating curve was also applied to the data, and its performance compared with that of the three models by means of statistical analyses. For all three models, suspended sediment discharge predicted by the fuzzy logic algorithm was in satisfactory agreement with observations. Furthermore, the fuzzy logic algorithms performed better than the sediment rating curve, particularly at higher rates of suspended sediment discharge (in this study, more than 50  × 10⁶ g/day). Considered collectively, the use of fuzzy logic algorithms is suggested as a simple and effective approach for better prediction of suspended sediment discharge, also for estuaries.