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.     

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?     

弹道导弹的雷达探测系统仿真

该文根据弹道理论建立了雷则弹道导弹的仿真模型,并对雷达跟踪的导弹弹道数据进行了处理,预报了它的落点范围,并与理论落点进行比较,给出了落点精度。仿真结果表明：雷达对导弹的探测数据经过一数据处理,所得到的落点比较精确。     

用水信用与风险管理系统

系统采用Oracle数据库作为开发平台,VB.net为开发工具研制而成。系统借鉴银行和电力企业信用等级评价的规则,结合水司水费收缴的历史纪录及各客户的实际情况,运用自动采集程序,从原有的营销系统和财务系统自动录入数据,再通过优化的模糊概率、神经网络程序,对用户进行交纳水费信用等级评定,建立客户交纳水费风险预警机制。     

基于GIS的矿井自然灾害隐患识别、预警模型研究

以煤矿地理中间数据一体化管理的数据模型和数据结构为基础,文章提出了一种基于GIS的煤矿自然灾害隐患识别单体评判预警模型、区域评判预警模型以及两者综合的煤矿自然灾害隐患识别区域与单体联合评判预警模型,并详细研究了模型的数据要求和模型的实现流程等关键问题。     

旱情预警几个主要技术问题的探讨

旱灾是我国主要的自然灾害之一。近年来,我国干旱灾害发生频繁,对经济社会造成的影响不断加剧。加强旱情监测,提高旱情综合评判能力,探索旱情预警方法等,显得十分必要和紧迫。目前,我国旱情监测工作相对薄弱,旱情预测预报起步较晚,旱情预警尚处于研究和探索阶段。本文结合吉林省旱情预警模型研究的有关成果,探讨预警指标、预测模型、预警综合指数等主要技术问题的创建思路,为旱情预警系统研究提供借鉴和参考作用。