山东栖霞—大柳行地区金矿找矿靶区地质评价及优选

栖霞—大柳行地区位于胶东中部栖霞—蓬莱金矿成矿带内，是胶东重要的金成矿区，成矿条件优越。为了对圈定靶区进行优选分类，通过对该区地质背景、找矿靶区评价、找矿靶区优选方面展开综合研究，并结合勘查工作程度和矿业权设置情况，划分出3类预测区，选定了5个靶区为今后优先部署勘查工作的方向。     

建筑师和城市的背景建筑

城市背景建筑的质量决定着城市空间的整体品质，中国城市背景建筑的质量有待提高，这取决于建筑师的城市整体意识、建构意识、过程意识和大众意识的提高。     

多边形坡屋顶屋脊线的递归算法

坡屋顶是比较常见的一种屋面构造形式。在建筑结构CAD辅助设计软件中,自动生成坡屋顶是一项必要的功能。坡屋顶尽管有多种形式,但其基础算法却大同小异。本文探讨的是最有代表性的一类坡屋顶的屋脊线算法问题。坡屋顶的底边可为简单规则的四边形、六边形,但也可能为任意的复杂多边形。根据坡屋顶的底边及坡屋面的倾角求坡屋顶的屋脊线是相对较复杂的几何问题。经过尝试,本文针对这个问题找到了一种非常简明有效的递归算法,该算法主要基于试探性的解题路线和屋脊线无交叉的有效性判断准则,很适于在计算机上编程实现。坡屋顶的屋脊线算法已有不止一种,本文的新意在于算法的简练。若把这种思路在类似问题中加以扩展,也很容易应用在其它一些建筑几何问题的算法处理上。     

基于区域的边坡稳定性分析地层建模方法

目前大部分边坡稳定性分析软件的地层建模采用基于线条的建模方法,这种建模方法手算工作量大,建模繁琐且不直观。本文基于拓扑理论和多边形图的性质,提出了基于区域的二维边坡地层建模方法。在确定边坡计算域多边形后,用户可以任意绘制地层折线,程序自动进行折线求交运算并截除边坡计算域外的部分,然后运用左转搜索算法将计算域分割成一个个地层多边形区域,可以包含复杂内岛等情况,以模拟工程地质剖面中的透镜体及人工处理的区域等。本文的地层建模方法具有多边形区域自动识别功能,减少手工计算量,可以明显地提高边坡稳定性分析软件的建模效率和可视化程度。     

Application of nonparametric regression methods to study the relationship between NO2 concentrations and local wind direction and speed at background sites

Background concentrations of nitrogen dioxide (NO₂) are not constant but vary temporally and spatially. The current paper presents a powerful tool for the quantification of the effects of wind direction and wind speed on background NO₂ concentrations, particularly in cases where monitoring data are limited. In contrast to previous studies which applied similar methods to sites directly affected by local pollution sources, the current study focuses on background sites with the aim of improving methods for predicting background concentrations adopted in air quality modelling studies. The relationship between measured NO₂ concentration in air at three such sites in Ireland and locally measured wind direction has been quantified using nonparametric regression methods. The major aim was to analyse a method for quantifying the effects of local wind direction on background levels of NO₂ in Ireland. The method was expanded to include wind speed as an added predictor variable. A Gaussian kernel function is used in the analysis and circular statistics employed for the wind direction variable. Wind direction and wind speed were both found to have a statistically significant effect on background levels of NO₂ at all three sites. Frequently environmental impact assessments are based on short term baseline monitoring producing a limited dataset. The presented non-parametric regression methods, in contrast to the frequently used methods such as binning of the data, allow concentrations for missing data pairs to be estimated and distinction between spurious and true peaks in concentrations to be made. The methods were found to provide a realistic estimation of long term concentration variation with wind direction and speed, even for cases where the data set is limited. Accurate identification of the actual variation at each location and causative factors could be made, thus supporting the improved definition of background concentrations for use in air quality modelling studies.     

射线法判断平面中的点在多边形内外的算法

介绍了射线法的基本思想,对该算法的具体实现进行了探讨,并且在程序设计时用判断和二分法进行了优化,从而避免了求交点运算的麻烦,减少了判断运算所需时间,并列举了具体的应用实例,验证了该算法的可行性。     

Robust visual tracking via CAMShift and structural local sparse appearance model

This paper addresses issues in visual tracking where videos contain object intersections, pose changes, occlusions, illumination changes, motion blur, and similar color distributed background. We apply the structural local sparse representation method to analyze the background region around the target. After that, we reduce the probability of prominent features in the background and add new information to the target model. In addition, a weighted search method is proposed to search the best candidate target region. To a certain extent, the weighted search method solves the local optimization problem. The proposed scheme, designed to track single human through complex scenarios from videos, has been tested on some video sequences. Several existing tracking methods are applied to the same videos and the corresponding results are compared. Experimental results show that the proposed tracking scheme demonstrates a very promising performance in terms of robustness to occlusions, appearance changes, and similar color distributed background.     

Robust techniques for abandoned and removed object detection based on Markov random field

This paper presents a novel framework for detecting abandoned objects by introducing a fully-automatic GrabCut object segmentation. GrabCut seed initialization is treated as a background (BG) modelling problem that focuses only on unhanded objects and objects that become immobile. The BG distribution is constructed with dual Gaussian mixtures that are comprised of high and low learning rate models. We propose a primitive BG model-based removed object validation and Haar feature-based cascade classifier for still-people detection once a candidate for a released object has been detected. Our system can obtain more robust and accurate results for real environments based on evaluations of realistic scenes from CAVIAR, PETS2006, CDnet 2014, and our own datasets.     

New trends on moving object detection in video images captured by a moving camera: A survey

This paper presents a survey on the latest methods of moving object detection in video sequences captured by a moving camera. Although many researches and excellent works have reviewed the methods of object detection and background subtraction for a fixed camera, there is no survey which presents a complete review of the existing different methods in the case of moving camera. Most methods in this field can be classified into four categories; modeling based background subtraction, trajectory classification, low rank and sparse matrix decomposition, and object tracking. We discuss in details each category and present the main methods which proposed improvements in the general concept of the techniques. We also present challenges and main concerns in this field as well as performance metrics and some benchmark databases available to evaluate the performance of different moving object detection algorithms.