On the selection of stimulus for the auditory variant of the detection response task method for driving experiments

Objectives: The detection response task (DRT) is a method for measuring attentional effects of secondary tasks on a driver's cognitive load by measuring response times and hit rates to different types of stimuli as indirect indicators of increased cognitive load. ISO 17488 (International Organization for Standardization 2016) only provides guidelines for the technical implementation and measurement methods for the visual and tactile versions (use of visual and tactile stimuli) of the DRT method. This article presents a study with the goal of finding the most appropriate auditory stimulus for the implementation of an auditory version of the DRT method.

Methods: This article presents the results of an experiment in which responses to 7 different auditory DRT stimuli—varying in frequency—were compared while inducing users' cognitive load with a modified n-back task. The experiment was conducted in a surrogate driving environment and in a within-subject design. Response times, hit rates, and secondary task performances were observed as indicators of increased cognitive load.

Results: Significantly shorter response times were found for the white noise signal compared to single-frequency signals. However, the largest differences in response times, for trials without and with a cognitive task, were found for 4- and 8-kHz single-frequency signals. No significant differences were found for hit rates and secondary task performances between the different stimuli.

Conclusions: Consistent significant differences in response times for all tested stimuli prove that the auditory DRT variant is also sensitive to changes in cognitive load. The mean increase in response times of more than 25% for 4- and 8-kHz signals for trials with a cognitive task compared to trials without one indicates that one of these signals could be used as a potential auditory stimulus for the auditory DRT variant.     

基于大数据分析与认知技术的空气质量预报预警平台

为深入认识区域大气污染现象规律,完善并提高城市空气质量预报预警能力,提高大气污染治理决策支持能力,开展城市污染成因分析与空气质量预报预警研究是十分必要的。本文针对环境大数据时代下的城市空气质量预报,提出了一种基于大数据分析与认知技术的专业先进的大气环境业务应用系统体系。该体系基于底层统一的数据资源中心,融合各类不同类型的空气质量监测、不同预报系统的产品数据以及基础辅助数据,建立数据汇交、共享、质控管理机制,通过上层预报预警、综合分析、案例分析、应急决策支持四大子系统,从多模式集合预报结合专家调优支撑高性能预报会商应用,从大数据融合时空关联分析深度挖掘大气复合污染特征与污染成因,从多维度历史污染过程和天气形势全自动化认知分析支撑重污染过程研判,从业务化仿真情景方案与污染溯源助力专业应急决策。最后,通过在北京市环境保护监测中心的系统实现证明体系的高性能、稳定性和实用性。     

认知过程中交通标志视认有效性影响因素分析

应用认知心理学的理论及方法,对驾驶员感知交通标志的心理过程进行分析,提出一种将驾驶员的直觉、分析和推理三者相结合的驾驶员信息处理模型。从标志和驾驶员特征出发对影响标志视认性的因素给出基于心理感知的理论分析。该分析结果为驾驶员认知过程研究、标志视认有效性的评价指标选取和相关系统开发设计提供了依据。     

夜间动态环境中空间距离驾驶员判识变化

为研究驾驶员在夜间地面动态环境中距离判识变化的规律,改进行车安全.选取32名驾驶员进行实际道路试验.被试在自车行进方向不同的深度距离、车速下,判识前方障碍物的绝对距离和相对距离.统计距离判识值,得出夜间距离判识值数据分布,取得距离判识特征值.回归分析判识距离与速度的关系,建立障碍物判识变化的数学模型.比较昼夜距离判识差异,分析其对夜间行车安伞的影响.结果表明:在车辆行驶深度方向,夜间距离判识值随速度增加而不断下降,两者之间呈负指数关系;在相同深度距离和速度下,夜间判识距离大于昼间;夜间行车时,需适当降低车速,确保有效的安伞距离.     

利益、价值与认知视域下的环境冲突及其伦理调适

从利益、价值与认知三维视域出发,分析了环境冲突的形成原因,考察了环境伦理对环境冲突的调适机理.环境冲突是社会主体利益、价值、认知多元化背景下多种因素综合的结果.从彼此间独断性的对立和冲突转向建设性的生态与互动,是化解环境冲突的根本路径.对此,环境伦理学具有其独特的价值和意义.环境伦理通过对环境价值的辩护,将自然拉进道德关注的视野,塑造和影响人们的利益、价值和认知结构,调适人类社会中工业文明以来不断制度化的生态缺失,从而作为一种积极的要素,推进各主体的利益、价值和认知由对立和冲突走向彼此共存的生态互动.     

流动人口空间结构分析

在人本主义地理学框架下，对城市社会空间结构的分类研究成为必然。以流动人口空间结构为主题，总结了城市化一空间的二元分析框架。在此基础上重点构建了流动人口空间结构体系，对流动人口区位空间、行为空间和感应空间的涵义、特征、功能等进行解析。认为流动人口空间是在城市空间基底上叠加的具有流动人口特质的空间形态，是一种再造的空间。提出流动人口收入水平及行为活动的多少是影响流动人口空间关系的主要因素。     

Black swans,cognition, and the power of learning from failure

Failure carries undeniable stigma and is difficult to confront for individuals, teams, and organizations. Disciplines such as commercial and military aviation, medicine, and business have long histories of grappling with it, beginning with the recognition that failure is inevitable in every human endeavor. Although conservation may arguably be more complex, conservation professionals can draw on the research and experience of these other disciplines to institutionalize activities and attitudes that foster learning from failure, whether they are minor setbacks or major disasters. Understanding the role of individual cognitive biases, team psychological safety, and organizational willingness to support critical self‐examination all contribute to creating a cultural shift in conservation to one that is open to the learning opportunity that failure provides. This new approach to managing failure is a necessary next step in the evolution of conservation effectiveness.     

Making sense of organizational change: Is hindsight really 20/20?

This qualitative study explores the conceptual links between 2 different approaches to managerial cognition, sensemaking and cognitive bias, in the context of organizational change. A longitudinal case study utilizing both real‐time assessments and retrospective sensemaking data from interviews with 26 hospital employees at 3 points in time was undertaken. Patterns related to individuals' retrospective accounts and real‐time assessments were identified and used to construct 4 prototypical narratives. Data analysis revealed that organizational change was not a markedly negative experience for most informants, which is contrary to the prevailing theme in the literature. This and other findings are discussed in terms of sensemaking and cognitive bias. This study makes 2 contributions to our understanding of how individual's experience and make sense of organizational change over time as (a) little is known about how the process of change unfolds over time at the individual level and (b) extant research has not investigated the extent to which individuals' retrospective sensemaking about organizational change reflects or diverges from their real‐time assessments over the course of the change. More broadly, the study provides insights and focused advice for management researchers regarding the use of retrospective data to understand individuals' perceptions of situations that have already occurred.     

数字化核电站SGTR事故操纵员认知分析

核电站主控室数字化后的人因特征包括数字化规程、警报系统、操作班组信息共享、界面管理任务,它们对操纵员认知可靠性都有重要影响。IDA认知模型把操纵员认知过程分为信息(Information)、诊断(Diagnosis)/决策(Decision)、执行(Action)3个阶段。按IDA模型把数字化核电站主控室操纵员SGTR事故认知过程分为3个阶段,对每个阶段进行操作分析,找到操纵员在SGTR事故认知过程各阶段最容易发生的失误和主要失误。操纵员认知失误发生的原因在于界面管理任务增大了认知难度以及数字化后缺乏情景意识等。