Temperature Effect on Light Concentration Silicon Solar Cell’s Operating Point and Conversion Efficiency

It is well known that temperature acts negatively on practically all the parameters of photovoltaic solar cells. Also, the solar cells which are subjected to particularly very high temperatures are the light concentration solar cells and are used in light concentration photovoltaic systems (CPV). In fact, the significant heating of these solar cells is due to the concentration of the solar flux which arrives on them. Light concentration solar cells appear as solar cells under strong influences of heating and temperature. It is therefore necessary to take into account temperature effect on light concentration solar cells performances in order to obtain realistic results. This one-dimensional study of a crystalline silicon solar cell under light concentration takes into account electrons concentration gradient electric field in the determination of the continuity equation of minority carriers in the base. To determine excess minority carrier’s density, the effects of temperature on the diffusion and mobility of electrons and holes, on the intrinsic concentration of electrons, on carrier’s generation rate as well as on width of band gap have also been taken into account. The results show that an increase of temperature improves diffusion parameters and leads to an increase of the short-circuit photocurrent density. However, an increase of temperature leads to a significant decrease in open-circuit photovoltage, maximum electric power and conversion efficiency. The results also show that the operating point and the maximum power point (MPP) moves to the open circuit when the cell temperature increases.

Research on color image matching method based on feature point compensation in dark light environment

Image matching refers to the process of matching two or more images obtained at different time,different sensors or different conditions through a large number of feature points in the image.At present,image matching is widely used in target recognition and tracking,indoor positioning and navigation.Local features missing,however,often occurs in color images taken in dark light,making the extracted feature points greatly reduced in number,so as to affect image matching and even fail the target recognition.An unsharp masking(USM)based denoising model is established and a local adaptive enhancement algorithm is proposed to achieve feature point compensation by strengthening local features of the dark image in order to increase amount of image information effectively.Fast library for approximate nearest neighbors(FLANN)and random sample consensus(RANSAC)are image matching algorithms.Experimental results show that the number of effective feature points obtained by the proposed algorithm from images in dark light environment is increased,and the accuracy of image matching can be improved obviously.

Synthesis of Polyfluorene-Polytriarylamine Block Copolymer with Emitting Part at Junction Point for Light Emitting Applications

A block copolymer consisting of polyfluorene (PF) and polytriarylamine (PTAA) functionalized with green emitting phenoxazine moiety at the junction point of two blocks was designed and prepared for electroluminescent application. PF homopolymer was synthesized by Suzuki coupling polymerization, and was reacted with brominated phenoxazine. In the presence of the resulting PF functionalized with phenoxazine, C-N coupling polymerization of 4-(4’-bromophenyl)-4’’-butyldiphenylamine was carried out to afford a triblock copolymer, PTAA-phenoxazine-PF-phenoxazine-PTAA (PF-Ph-PTAA). Two types of random copolymers were also synthesized with fluorene and phenoxazine (PF2) by Suzuki coupling polymerization for comparison. All the polymers were soluble in common organic solvents and readily formed thin films by a solution processing. Prepared polymers exhibited similar UV absorption and PL emission in chloroform solutions. In a film state, the existence of phenoxazine unit drastically changed PL spectra. Although the content of phenoxazine unit in PF-Ph-PTAA was relatively high (13 mol%), it showed similar PL spectrum to that of PF2(phenoxazine content, 0.2 mol%) indicating that phenoxazine unit is isolated in single polymer chain nevertheless the high content. EL device based on PF-Ph-PTAA showed green-emission, suggesting that emission sites predominantly located in the vicinity of phenoxazine moiety because of its shallow HOMO level.

Enhanced 3D Point Cloud Reconstruction for Light Field Microscopy Using U-Net-Based Convolutional Neural Networks

This article describes a novel approach for enhancing the three-dimensional(3D)point cloud reconstruction for light field microscopy(LFM)using U-net architecture-based fully convolutional neural network(CNN).Since the directional view of the LFM is limited,noise and artifacts make it difficult to reconstruct the exact shape of 3D point clouds.The existing methods suffer from these problems due to the self-occlusion of the model.This manuscript proposes a deep fusion learning(DL)method that combines a 3D CNN with a U-Net-based model as a feature extractor.The sub-aperture images obtained from the light field microscopy are aligned to form a light field data cube for preprocessing.A multi-stream 3D CNNs and U-net architecture are applied to obtain the depth feature fromthe directional sub-aperture LF data cube.For the enhancement of the depthmap,dual iteration-based weighted median filtering(WMF)is used to reduce surface noise and enhance the accuracy of the reconstruction.Generating a 3D point cloud involves combining two key elements:the enhanced depth map and the central view of the light field image.The proposed method is validated using synthesized Heidelberg Collaboratory for Image Processing(HCI)and real-world LFM datasets.The results are compared with different state-of-the-art methods.The structural similarity index(SSIM)gain for boxes,cotton,pillow,and pens are 0.9760,0.9806,0.9940,and 0.9907,respectively.Moreover,the discrete entropy(DE)value for LFM depth maps exhibited better performance than other existing methods.

Development of vehicle-recognition method on water surfaces using LiDAR data:SPD^(2)(spherically stratified point projection with diameter and distance)

Swarm robot systems are an important application of autonomous unmanned surface vehicles on water surfaces.For monitoring natural environments and conducting security activities within a certain range using a surface vehicle,the swarm robot system is more efficient than the operation of a single object as the former can reduce cost and save time.It is necessary to detect adjacent surface obstacles robustly to operate a cluster of unmanned surface vehicles.For this purpose,a LiDAR(light detection and ranging)sensor is used as it can simultaneously obtain 3D information for all directions,relatively robustly and accurately,irrespective of the surrounding environmental conditions.Although the GPS(global-positioning-system)error range exists,obtaining measurements of the surface-vessel position can still ensure stability during platoon maneuvering.In this study,a three-layer convolutional neural network is applied to classify types of surface vehicles.The aim of this approach is to redefine the sparse 3D point cloud data as 2D image data with a connotative meaning and subsequently utilize this transformed data for object classification purposes.Hence,we have proposed a descriptor that converts the 3D point cloud data into 2D image data.To use this descriptor effectively,it is necessary to perform a clustering operation that separates the point clouds for each object.We developed voxel-based clustering for the point cloud clustering.Furthermore,using the descriptor,3D point cloud data can be converted into a 2D feature image,and the converted 2D image is provided as an input value to the network.We intend to verify the validity of the proposed 3D point cloud feature descriptor by using experimental data in the simulator.Furthermore,we explore the feasibility of real-time object classification within this framework.

The Role of Social Change Factors in the Criminal Saturation Law

In the crime saturation law,the crime rate of a country depends on the specific time and space conditions of the country,and its distribution and size are limited to the“saturation”of social conditions.Therefore,the process of social change is the process of the criminial rate change.First,based on the regression analysis of the longitudinal crime rate data and relevant social development data in China from 1981 to 2015,this paper searches for the cointegration relationship between the variable sequences.Second,by the Quandt-Andrews breakpoint test,this paper finds the potential structural breakpoints within the sample interval.Finally,based on the structural breakpoints,this paper compares and analyzes the regression results between the sub regions,the sub intervals and overall sample intervals.The study finds that the increase of per capita GDP level,the widening income gap between urban and rural areas,the decline of social education level and the increase of unemployment rate all contribute to the growth of crime rate.China’s relevant departments should implement measures to maintain stability in the period of rapid economic growth,pay attention to social equity problems,increase investment in education,and reduce social unemployment rate.

煤矿井下采掘工作场景非均质图像去雾与增强技术

【目的】针对煤矿井下采掘作业中采煤和除尘活动引发尘雾分布不均及复杂光照条件,导致视频图像模糊不清、信息量和细节丢失等问题,提出了一种井下采掘工作场景非均质图像去雾与增强技术。【方法】首先对雾图进行区域分割,计算不同亮度区域的全局暗通道环境光均值,并与通过自适应伽马矫正和多尺度高斯滤波得到的局部亮通道环境光进行加权融合,以获得精确的环境光估计。为了保证图像细节的同时实现自然去雾效果,采用多尺度融合矫正技术处理透射图,并利用联合双边滤波得到精细化的透射图,结合大气散射模型,实现尘雾图像的清晰化。针对去雾后的图像整体较暗且对比度不足,进一步采用修正白平衡处理,将图像转换到HSV空间,提出自适应饱和度矫正和改进对比度增强算法,并结合拉普拉斯锐化提升图像的细节和对比度。【结果和结论】通过选取DCP、MRP、OSFD、MF-LIME、CEEF 5种算法处理真实典型的场景图像,并采用多项指标与本研究算法处理结果进行对比实验,结果表明:与新颖优秀算法的最优指标对比,提出算法相比CEEF在平均梯度的平均提升约为两倍,提升了图像的清晰度;相比MRP的信息熵平均降低约为1%,保留了更多图像信息;相比OSFD的标准差平均提升约为6%,改善了图像对比度;相比CEEF的FADE平均降低约为23%,能更有效地降低尘雾密度且运行速度较快,表现出更优越的性能。提出的算法能够有效提高煤矿井下采掘工作场景中模糊图像的视觉效果和图像质量,增强了其在工程应用中的实用性。

Impacts of bird abundance, activity height and light intensity on the number of birds captured by mist netting

To understand better the impact on mist net capture rates of the activity height of birds, light intensity, bird richness and abundance, we compared data from mist nets and point counts at the Jianfengling Forest Area, Hainan Island. Mist-nets were operated for a total of 7135 net-hours. A total of 587 individuals of 45 bird species were captured. The total mean capture rate was 8.6 ± 10.4 per 100 net-hours. A total of 4932 individuals of 107 bird species were recorded by visual observation alone and 7616 individuals of 120 species were recorded in a visual and aural combination. The Grey-cheeked Fulvetta (Alcippe morrisonia) was the most abundant species, accounting for 38.7% of total captures, 27.9% of visual observations and 22.2% of visual + aural observations. The capture number was correlated with the number observed. Thirty-one species were more likely to be captured than observed. Canopy species, such as members of the Corvidae and Dicruridae, were seldom captured. For all ground feeding species, the capture number was greater than that of observation. Some cryptic species, such as the Lesser Wren Babbler (Napothera epilepidota), Spotnecked Babbler (Stachyris striolata) and Cuckoo Owl (Glaucidium cuculoides) also had a higher relative capture rate than that of observations. There was a significant relationship between light intensity and the number of birds captured.

28例轻嵴帽的Null Point临床特征分析

目的:分析轻嵴帽患者眼震消失平面(NP)的临床特征。方法:纳入仰卧滚转试验表现为持续性向地性变向性位置性眼震且有NP的患者28例;在眼震视图下行观察其动态位置性眼震特征,并寻找NP进行定侧诊断;给予手法复位,并于首次复位后1周及1个月随访,观察患者的转归。结果:28例轻嵴帽患者中,11例(39.3%)有自发眼震;10例(35.7%)有NP1,28例(100%)有NP2和NP3,且患者对NP2检测时的耐受性较好;首次复位有效率为7.1%,1周随访有效率为14.3%,1月随访有效率100%。结论:NP2检测是轻嵴帽诊断及定侧诊断的简便、可行的方法;轻嵴帽患者复位效果差,但病程多呈自限性。

基于运动约束的无人机编队一致性优化算法

针对无人机运动约束下的编队任务研究标准二阶一致性控制算法的优化问题。首先,结合编队信息,基于虚拟结构法思想,设计含虚拟参考点的二阶一致性编队控制算法,使得编队收敛于指定队形,解决标准二阶一致性控制算法的收敛状态与各无人机初值有关以及收敛位置趋于一致的问题,得到编队渐近收敛的条件。其次,引入饱和函数得到运动约束条件下的渐近收敛的二阶一致性编队控制算法,设计无人机编队高度、航向、速度通道控制器。最后,设计无人机编队队形集结仿真实验,对比相同饱和函数不同一致性方法的编队控制算法、相同一致性方法不同饱和函数的编队控制算法,验证了优化算法的有效性和快速性。

基于LightGBM的乘客候车路段推荐方法

目前城市出租车服务系统中出租车的营运效率普遍不高,一方面出租车有较高的空载率,另一方面由于乘客盲目选择打车地点而造成打车难的问题。针对上述问题,提出了一种基于LightGBM的乘客候车路段推荐方法。该方法从城市出租车的历史轨迹信息中提取影响空载的时空特征,利用LightGBM框架预测各个路段出租车的空载数量,并以此计算各个路段在未来一个时隙内成功打到空车的概率,最终根据乘客所处位置将其附近成功打车概率最高的路段推荐给乘客。仿真实验利用了西安市出租车数据对模型进行训练和验证,并将实验效果与SVR、GBDT等方法进行了对比。实验结果表明,所提方法的RMSE、MAE、MAPE等指标均优于其他方法,该模型对解决出租车与乘客人车矛盾有一定实用价值。

轮对廓形采集装置的自适应对中研究

该文针对检修车间内测量轮对全廓形的需求,综合环境、工况、成本和需求等因素,在现有镟前轮对测量设备的基础上,增加补充激光传感法测量的轮对廓形采集装置。考虑轮对测量机测量时会由于轮对车轴抬升高度的不同,导致廓形采集位置不过轴心会对廓形测量数据造成误差的这一问题,该文提出一种基于图像的轮对廓采集装置的自适应对中方法,算法体现对物体表面纹理变化的鲁棒性,大大增加激光这种小目标检测的准确性,检测时间平均每张1.01 s,满足对实时性的要求。实现在不同光照条件影响下,廓形采集装置的快速、精确的自适应调节,提升廓形检测精度的同时为轮对镟修计划编排提供基础。

基于模型匹配的机器人焊缝自适应校正打磨系统开发与应用

针对目前机器人焊缝打磨过程中,由于工件制造误差、定位装夹误差等导致机器人打磨轨迹偏离实际工件焊缝,造成打磨质量一致性差问题,研发了一种基于点云模型特征匹配的机器人焊缝打磨轨迹自适应校正系统。该系统利用双目面结构光相机扫描工件特征区域,获取工件真实形貌,与标准点云模板进行匹配,得到实际工件坐标系的偏差转换矩阵,应用到机器人主程序实现焊缝打磨初始点的快速引导以及打磨轨迹的在线自适应校正。最后,以高铁转向架为对象开展了实验研究,实验结果表明该系统具有良好的焊缝打磨轨迹自动校正性能和稳定性。

车载可见光视距通信系统块误码率的研究

为了提高车载通信质量和可靠性,通过分析基础设施与车辆间信道传输模型和道路基础设施参数的影响,引入车载可见光通信技术。根据基础设施与车辆间的视距信道进行建模,分析信号传输中的通信损耗;利用视距通信误码率(BER)、停机概率及块误码率(BLER)推导系统性能的闭式解析式;分析复合指向误差对视距通信系统的误码率、停机概率以及块误码率的影响。试验结果表明:在无衰落和视距传输条件下,增加路灯高度可以降低误码率,通信链路距离增加将增大误码率;提高停机阈值,视距链路的停机概率降低;增加发送比特块数量有助于改善块误码率性能;考虑指向误差后,误码率、停机概率以及块误码率均增加,表明指向误差对系统通信有衰弱作用。

富水地质条件下地铁车站深基坑轻型井点降水施工技术研究

为保证地下工程基坑的稳定性,先进的降水施工技术十分关键。该文提出了富水地质条件下地铁车站深基坑轻型井点降水施工技术。首先进行基坑轻型降水井点的平面布置,并计算相关参数;接着进行轻型井点的降水管布置和降水点的安插;最后启动轻型井点降水点。实例测试结果显示,施工后基坑内的渗水量明显减少,深基坑的渗水量接近于0,从而增强了基坑的稳定性,为后续施工提供了可靠的保障。

基于Silverlight网页游戏的寻径优化算法

为了解决A*路径搜索算法在Silverlight网页游戏中的搜索费时和路径曲折等问题,在结合光线跨越算法和引入父结点指针的二叉堆存储开启列表的A*算法的基础上,提出了一种基于Silverlight网页游戏的寻径优化算法。该算法在现有研究的基础上使用光线跨越算法减小A*算法搜索规模,同时将动态关键点技术与光线跨越算法结合来优化算法返回的路径。将该算法在游戏所使用的网格地图中进行实验,实验结果表明,该算法能够有效地根据系统设定的通行条件寻找出一条最优的实际可行的路径,同时缩短寻路的时间消耗和所寻的路径长度,提高游戏的可玩性。

Method for Detecting Weld Feature Size Based on Line Structured Light

With the rapid development of the machining and manufacturing industry,welding has been widely used in forming connections of structural parts.At present,manual methods are often used for welding and quality inspection,with low efficiency and unstable product quality.Due to the requirements of visual inspection of weld feature size,a visual inspection system for weld feature size based on line structured light(LSL)is designed and built in this paper.An adaptive light stripe sub-pixel center extraction algorithm and a feature point extraction algorithm for welding light stripe are proposed.The experiment results show that the detection error of the weld width is 0.216 mm,the detection error of the remaining height is 0.035 mm,the single measurement costs 109 ms,and the inspection stability and repeatability of the system is 1%.Our approach can meet the online detection requirements of practical applications.

Novel empirical correlations for estimation of bubble point pressure,saturated viscosity and gas solubility of crude oils

Knowledge of petroleum fluid properties is crucial for the study of reservoirs and their development. Estimation of reserves in an oil reservoir or determination of its performance and economics requires a good knowledge of the fluid physical properties. Bubble point pressure, gas solubility and viscosity of oils are the most important parameters in use for petroleum and chemical engineers. In this study a simple-to-use, straight-forward mathematical model was correlated on a set of 94 crude oil data. Three correlations were achieved based on an exponential regression, which were different from conventional empirical correlations, and were evaluated against 12 laboratory data other than those used for the regression. It is concluded that the new exponential equation is of higher precision and accuracy than the conventional correlations and is a more convenient mathematical formulation.

Study on the Effect of Monochromatic Light on the Growth of the Red Tide Diatom <i>Skeletonema Costatum</i>

Effects of light intensity and quality of three kinds of LED monochromatic lights (blue, green, and red) on the growth of Skeletonema costatum are investigated in batch culture conditions. Seven light intensities (20, 30, 40, 45, 50, 60 and 80 μmol·m-2·s-1) are used to evaluate the specific growth rate, spectrum absorption coefficient and saturated light intensity of LED monochromatic light. Results show that the growth rates of Skeletonema costatum increase with the enhanced light intensity;however, the light level beyond the saturation light intensity inhibited the growth of Skeletonema costatum. Compared with red and green light, the growth rate of Skeletonema costatum under blue light is higher within saturated light intensity, and saturated light intensity of LED monochromatic light is lower under blue light and higher under green light. It is concluded that under different monochromatic light, the saturated light intensity decreases and the growth rate increases with the increasing of spectrum absorption coefficient.

Optical Design and Stray Light Analysis of the Space Infrared Optical System

This article describes a novel configuration design for a re-imaging off-axis catadioptric space infrared optical system,and in order to satisfy the signal noise ratio requirements of the system,the stray light of the system is necessary to analyze and restrain. The optical system with a focal length of 1 200 mm,an entrance pupil diameter of 600 mm,an F-number of 2,a field of view of 3°× 0. 15°,a working wave band of 8 μm-10 μm,and the image quality of the optical system almost approach to diffraction limits in all field of view.Then the mathematical models of stray light are built,and the suppressive structure is established to eliminate the effect of stray light. Finally,TraceP ro is used to analyze and simulate stray light with and without the suppressive structure,and also get the results of the PST curves. The results indicate that appropriate optical system and suppressive structure can highly reduce the stray light of the space infrared optical system.