一种基于自适应扁平搜索模板的改进ARPS算法

针对ARPS算法中初始预测运动矢量不够精确并且ARPS算法针对不同宏块采用相同搜索策略的问题,在深入研究ARPS算法原理的基础上,提出一种基于自适应扁平搜索模板的新的快速运动估计算法.本文在算法的初始预测运动矢量、算法提前终止准则等方面提出了新的观点和方法,同时针对物体的不同运动趋势采用不同的搜索模板.实验证明,本文提出的改进算法在不影响图像编码效率的前提下较大地降低了计算复杂度.     

Classifying species of individual trees by intensity and structure features derived from airborne laser scanner data

The objective of this study was to identify candidate features derived from airborne laser scanner (ALS) data suitable to discriminate between coniferous and deciduous tree species. Both features related to structure and intensity were considered. The study was conducted on 197 Norway spruce and 180 birch trees (leaves on conditions) in a boreal forest reserve in Norway. The ALS sensor used was capable of recording multiple echoes. The point density was 6.6 m^− 2. Laser echoes located within the vertical projection of the tree crowns, which were assumed to be circular and defined according to field measurements, were attributed to three categories: “first echoes of many”, “single echoes”, or “last echoes of many echoes”. They were denoted FIRST, SINGLE, and LAST, respectively. In tree species classification using ALS data features should be independent of tree heights. We found that many features were dependent on tree height and that this dependency influenced selection of candidate features. When we accounted for this dependency, it was revealed that FIRST and SINGLE echoes were located higher and LAST echoes lower in the birch crowns than in spruce crowns. The intensity features of the FIRST echoes differed more between species than corresponding features of the other echo categories. For the FIRST echoes the intensity values tended to be higher for birch than spruce. When using the various features for species classification, maximum overall classification accuracies of 77% and 73% were obtained for structural and intensity features, respectively. Combining candidate features related to structure and intensity resulted in an overall classification accuracy of 88%.     

基于车辆自组网络的分布式自主导航系统

针对交通拥堵和道路安全问题,在车载自组网路由协议改进和实现的基础上,提出一种基于车辆自组网络的分布式智能交通服务系统,实现邻域动态路况展示、突发交通事故预警和交通图片视频信息分发等自主交通导航服务。与传统后台计算动态交通服务实现方式相比,车辆自组网能较好地发挥其在车辆问直接交互交通、安全、娱乐等实时信息的优势。     

基于传感器的汽车主动安全设计

从汽车主动安全方面进行研究,通过对车辆道路行驶时关键要素的危险状态识别,实现完善汽车主动安全性能.本设计采取自动控制方法,通过研究汽车防碰撞检测和预防以及偏离车道报警,为汽车安全系统提供信息支持,实现车辆主动避免碰撞危险,减少或避免交通事故发生,大大提高汽车行驶主动安全性.所设计汽车主动安全防撞系统主要包括激光防撞测距、激光车道检测、报警警示系统等.     

The impact of false warnings on partial and full lane departure warnings effectiveness and acceptance in car driving

In the past, lane departure warnings (LDWs) were demonstrated to improve driving behaviours during lane departures but little is known about the effects of unreliable warnings. This experiment focused on the influence of false warnings alone or in combination with missed warnings and warning onset on assistance effectiveness and acceptance. Two assistance unreliability levels (33 and 17%) and two warning onsets (partial and full lane departure) were manipulated in order to investigate interaction. Results showed that assistance, regardless unreliability levels and warning onsets, improved driving behaviours during lane departure episodes and outside of these episodes by favouring better lane-keeping performances. Full lane departure and highly unreliable warnings, however, reduced assistance efficiency. Drivers’ assistance acceptance was better for the most reliable warnings and for the subsequent warnings. The data indicate that imperfect LDWs (false warnings or false and missed warnings) further improve driving behaviours compared to no assistance.

Practitioner Summary: This study revealed that imperfect lane departure warnings are able to significantly improve driving performances and that warning onset is a key element for assistance effectiveness and acceptance. The conclusion may be of particular interest for lane departure warning designers.     

An integrated package for drought monitoring,prediction and analysis to aid drought modeling and assessment

Due to severe drought events and disastrous impacts in recent decades, substantial efforts have been devoted recently to drought monitoring, prediction and risk analysis for aiding drought preparedness plans and mitigation measures. Providing an overview of these aspects of drought research, this study presents an integrated R package and illustrates a wide range of its applications for drought modeling and assessment based on univariate and multivariate drought indices for both operational and research purposes. The package also includes statistical prediction of drought in a probabilistic manner based on multiple drought indicators, which serves as a baseline for drought prediction. The univariate and multivariate drought risk analysis of drought properties and indices is also presented. Finally, potential extensions of this package are also discussed. The package is provided freely to public to aid drought early warning and management.     

基于传感网与GIS的智慧排水管网系统

针对城市排水设施复杂,监控监管、规划及社会服务缺乏高效的管理手段的问题,本文提出了基于传感网与GIS技术设计的排水防涝智慧管网系统的设计方案,实现对排水管网的管理、规划、监控,实时动态掌握管网管线的运行状态,实现对排水管网“动态管理、预警预防、智慧决策”的最终目标,提高排水防涝管理的效率、质量和水平.     

Integrating airborne multispectral imagery and airborne LiDAR data for enhanced lithological mapping in vegetated terrain

Practical and financial constraints associated with traditional field-based lithological mapping are often responsible for the generation of maps with insufficient detail and inaccurately located contacts. In arid areas with well exposed rocks and soils, high-resolution multi- and hyperspectral imagery is a valuable mapping aid as lithological units can be readily discriminated and mapped by automatically matching image pixel spectra to a set of reference spectra. However, the use of spectral imagery in all but the most barren terrain is problematic because just small amounts of vegetation cover can obscure or mask the spectra of underlying geological substrates. The use of ancillary information may help to improve lithological discrimination, especially where geobotanical relationships are absent or where distinct lithologies exhibit inherent spectral similarity. This study assesses the efficacy of airborne multispectral imagery for detailed lithological mapping in a vegetated section of the Troodos ophiolite (Cyprus), and investigates whether the mapping performance can be enhanced through the integration of LiDAR-derived topographic data. In each case, a number of algorithms involving different combinations of input variables and classification routine were employed to maximise the mapping performance. Despite the potential problems posed by vegetation cover, geobotanical associations aided the generation of a lithological map - with a satisfactory overall accuracy of 65.5% and Kappa of 0.54 - using only spectral information. Moreover, owing to the correlation between topography and lithology in the study area, the integration of LiDAR-derived topographic variables led to significant improvements of up to 22.5% in the overall mapping accuracy compared to spectral-only approaches. The improvements were found to be considerably greater for algorithms involving classification with an artificial neural network (the Kohonen Self-Organizing Map) than the parametric Maximum Likelihood Classifier. The results of this study demonstrate the enhanced capability of data integration for detailed lithological mapping in areas where spectral discrimination is complicated by the presence of vegetation or inherent spectral similarities.     

Parents,pre‐schoolers and learning with technology at home: some implications for policy

Schemes that seek to ensure that children have access to technology at home have, so far, been aimed at children over the age of 8. However, there is likely to be an increasing policy interest in extending similar schemes to pre‐school children given widespread commitment to the value of early intervention in children's education and family life. We draw on three research studies conducted by the authors to discuss the range of technologies that children encounter at home, the different forms their learning takes and family support for learning. We use these findings to provide starting points for considering the implementation of similar schemes for pre‐school children and their parents in the future, identifying several questions to consider when developing policy on home access to technology for pre‐schoolers: which technologies are most appropriate? Will access to technology at home lead to increased use? What roles do parents play in supporting learning? Which forms of learning are most likely to be promoted?