On-road and simulated driving: concurrent and discriminant validation

Introduction

A converging pair of studies investigated the validity of a simulator for measuring driving performance/skill.

Study 1

A concurrent validity study compared novice driver performance during an on-road driving test with their performance on a comparable simulated driving test.

Results

Results showed a reasonable degree of concordance in terms of the distribution of driving errors on-road and errors on the simulator. Moreover, there was a significant relationship between the two when driver performance was rank ordered according to errors, further establishing the relative validity of the simulator. However, specific driving errors on the two tasks were not closely related suggesting that absolute validity could not be established and that overall performance is needed to establish the level of skill.

Study 2

A discriminant validity study compared driving performance on the simulator across three groups of drivers who differ in their level of experience - a group of true beginners who had no driving experience, a group of novice drivers who had completed driver education and had a learner's permit, and a group of fully licensed, experienced drivers.

Results

The findings showed significant differences among the groups in the expected direction -- the various measures of driving errors showed that beginners performed worse than novice drivers and that experienced drivers had the fewest errors. Collectively, the results of the concurrent and discriminant validity studies support the use of the simulator as a valid measure of driving performance for research purposes.

Impact on industry

These findings support the use of a driving simulator as a valid measure of driving performance for research purposes. Future research should continue to examine validity between on-road driving performance and performance on a driving simulator and the use of simulated driving tests in the evaluation of driver education/training programs.     

Effects of experimental protocol on global vegetation model accuracy: A comparison of simulated and observed vegetation patterns for Asia

Prognostic vegetation models have been widely used to study the interactions between environmental change and biological systems. This study examines the sensitivity of vegetation model simulations to: (i) the selection of input climatologies representing different time periods and their associated atmospheric CO₂ concentrations, (ii) the choice of observed vegetation data for evaluating the model results, and (iii) the methods used to compare simulated and observed vegetation. We use vegetation simulated for Asia by the equilibrium vegetation model BIOME4 as a typical example of vegetation model output. BIOME4 was run using 19 different climatologies and their associated atmospheric CO₂ concentrations. The Kappa statistic, Fuzzy Kappa statistic and a newly developed map-comparison method, the Nomad index, were used to quantify the agreement between the biomes simulated under each scenario and the observed vegetation from three different global land- and tree-cover data sets: the global Potential Natural Vegetation data set (PNV), the Global Land Cover Characteristics data set (GLCC), and the Global Land Cover Facility data set (GLCF). The results indicate that the 30-year mean climatology (and its associated atmospheric CO₂ concentration) for the time period immediately preceding the collection date of the observed vegetation data produce the most accurate vegetation simulations when compared with all three observed vegetation data sets. The study also indicates that the BIOME4-simulated vegetation for Asia more closely matches the PNV data than the other two observed vegetation data sets. Given the same observed data, the accuracy assessments of the BIOME4 simulations made using the Kappa, Fuzzy Kappa and Nomad index map-comparison methods agree well when the compared vegetation types consist of a large number of spatially continuous grid cells. The results of this analysis can assist model users in designing experimental protocols for simulating vegetation.     

Evaluation of ecological network analysis: Validation of output

Ecological network analysis (ENA) is a modeling approach increasingly being used to evaluate food webs and provide an ecosystem-based approach to resource management. Unfortunately, validation of ENA output is rarely performed. This study represents part of a larger effort to critically evaluate ENA. Here we validate ENA output using stable isotope analysis (SIA), and where validation is not met, determine the effects of modifying trophic networks to reflect validation.     

Determination of Water-soluble Atmospheric Aerosols Using Ion Chromatography

A field study was established to investigate the chemical composition of atmospheric aerosols in Chicago, IL. One goal of this study was to determine the influence of precursor trace gases and local meteorology on concentrations of secondary aerosol ionic species. This paper describes the method details, shows the method is analytically valid, and reports overall as well as some specific results found during the field study. Two particulate air samples were collected per day onto quartz fiber filters at the Loyola University Chicago Air Station during the summer months in 2002–2004. In parallel, mixing ratios of ozone and nitrogen oxides were monitored and weather parameters were recorded. Particulates were extracted from the filter substrates and the subsequent solutions were analyzed by ion chromatography for anions, including low molecular weight organic acids, and cations. A washing procedure was implemented to reduce the high background values of the quartz fiber filters. Method validation showed that the collection method was efficient for all ions with exception of nitrate, whose efficiency of 70% indicated losses caused by volatilization. The extraction method also proved efficient for both field and laboratory samples, and the repeatability of the method was high with relative standard deviations less than 10% for all ions. Reproducibility of the results was determined by comparison of sulfate to sulfur analyzed by total reflection X-ray fluorescence spectrometry and proved to be high as well. Concentrations differed significantly between the three summer studies due to varying levels of precursor species as a consequence of distinct temperatures and wind direction profiles.     

活性污泥法简化数学模型的研究与进展

介绍几种简化数学模型 (如ROM、SPM、SLM等 )的结构与特点。模型的验证结果表明 ,简化模型能够较好的模拟系统的运行 ,产生较为准确的模拟结果     

Comparison of Evapotranspiration Simulation Performance by APEX Model in Dryland and Irrigated Cropping Systems

Accurate estimation of evapotranspiration (ET) is essential to improve water use efficiency of crop production systems managed under different water regimes. The Agricultural Policy/Environmental eXtender (APEX) model was used to simulate ET using four potential ET (ET_p) methods. The objectives were to determine sensitive ET parameters in dryland and irrigated cropping systems and compare ET simulation in the two systems using multiple performance criteria. Measured ET and crop yield data from lysimeter fields located in the United States Department of Agriculture‐Agricultural Research Service Bushland, Texas were used for evaluation. The number of sensitive parameters was higher for dryland (11–14) than irrigated cropping systems (6–8). Only four input parameters: soil evaporation plant cover factor, root growth soil strength, maximum rain intercept, and rain intercept coefficient were sensitive in both cropping systems. Overall, it is possible to find a set of robust parameter values to simulate ET accurately in APEX in both cropping systems using any ET_p method. However, more computation time is required for dryland than irrigated cropping system due to a relatively larger number of sensitive input parameters. When all inputs are available, the Penman–Monteith method takes the shortest computation time to obtain one model run with robust parameter values in both cropping systems. However, in areas with limited datasets, one can still obtain reasonable ET simulations using either Priestley–Taylor or Hargreaves. Editor's note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

典型区土壤重金属空间插值方法与污染评价

选择最优的空间插值方法对土壤重金属空间分布特征的反映和污染评价具有重要的意义.以湖北省恩施市典型区表层土壤重金属As和Cd为例,选取常用的反距离权重法(IDW)、径向基函数法(RBF)、局部多项式法(LPI)和普通克里格法(OK)进行空间插值,对比分析了不同插值方法的插值精度及结果差异.同时采用地累积指数和指示克里格法(IK)评价了土壤重金属污染状况.结果表明,不同插值方法对于同一种元素的预测误差相差较小,但对土壤重金属含量的空间分布特征存在明显差异,其中LPI法表现出明显的平滑效应,OK法次之,而IDW法和RBF法极大地保留了元素含量的极值信息,插值结果较详尽.为准确了解局部高背景区土壤重金属的空间分布状况,应优选IDW法或RBF法进行插值.以湖北省深层土壤重金属含量算术均值作为背景值,地累积指数污染评价结果显示:As和Cd的超标样点分别占5.5%和99.0%,研究区Cd污染程度较高.IK法污染评价显示:Cd中度-强污染以上的高概率污染区域主要位于研究区的中部,应重视土壤Cd污染分布,并对其有效治理与修复.     

基于OMI数据的中国中东部城市近地面臭氧时空分布特征研究

利用OMI卫星反演数据分析了2005—2014年中国中东部地区对流层臭氧变化趋势.结果表明,近10年来对流层臭氧总柱浓度混合比例较稳定,但近地面浓度明显增加,特别是在冬季臭氧上升速度达40%.同时分析了京津冀、长三角、珠三角地区10个重点城市的臭氧数据,发现京津冀地区的臭氧涨幅超过其他两个地区,其中,长三角地区臭氧混合比例最高,而珠三角地区相对较稳定.利用臭氧激光雷达和地面臭氧监测数据对卫星反演结果进行比较显示了较好的一致性,证明使用卫星反演的数据来研究长时间范围内近地层的臭氧变化是一种可行的方法.     

Validation of I ecological transfer models and thyroid dose assessments using Chernobyl fallout data from the Plavsk district, Russia

Within the project “Environmental Modelling for Radiation Safety” (EMRAS) organized by the IAEA in 2003 experimental data of ¹³¹I measurements following the Chernobyl accident in the Plavsk district of Tula region, Russia were used to validate the calculations of some radioecological transfer models. Nine models participated in the inter-comparison. Levels of ¹³⁷Cs soil contamination in all the settlements and ¹³¹I/¹³⁷Cs isotopic ratios in the depositions in some locations were used as the main input information. 370 measurements of ¹³¹I content in thyroid of townspeople and villagers, and 90 measurements of ¹³¹I concentration in milk were used for validation of the model predictions.A remarkable improvement in models performance comparing with previous inter-comparison exercise was demonstrated. Predictions of the various models were within a factor of three relative to the observations, discrepancies between the estimates of average doses to thyroid produced by most participant not exceeded a factor of ten.     

方法标准验证实验数据中离群值的识别

对方法标准验证实验中测量数据进行合格性审核,对于后续方法精密度计算是一个重要环节。文献中识别离群值的Grubbs法、Dixon法等经典方法有时不能满足要求。探讨了用稳健统计法识别离群值的可行性。基于2套文献数据和XRF方法标准验证实验精密度测量数据,对Grubbs法、Dixon法、Mandel h检验法、质控指标法和稳健统计法(四分位法、迭代法、合格数据范围判定法)进行了比较。结果表明:稳健统计法可有效识别离群值。但四分位法存在过度"检出"现象。综合考虑多种方法识别结果有利于提高离群值判定结论的可靠性。对于个别难以判断的情形,可借助质控指标、技术要求以及数据是否剔除对实验室间标准偏差的影响进行取舍。