Reliability of variable message signs information: A field experiment study in Chongqing

A variable message sign (VMS), which is a key component of intelligent transportation systems, has been frequently used in the management of urban roads and motorways to provide drivers with real-time traffic condition information about a road section or area. Nevertheless, there is a lack of unified regulations for VMS design, which makes it difficult to accurately determine the understandability and legibility of VMS information. In practice, inappropriate designs of VMSs are common, such as overload of VMS information and excessive number of phases, particularly on the urban roads of China. Building on our earlier findings obtained by surveys, in this study, field tests were conducted to assess the reliability of VMS information in terms of the visual perception characteristics of drivers. For a full visual perception, the information displayed on a VMS must be reliable, i.e., it should be easy for drivers to detect, obtain, and understand the messages they require. Two basic theories—information theory and visual perception theory—were introduced to build a quantification model of VMS information, select evaluation indices, and design the experimental process. A total of 24 drivers participated in the field experiments and questionnaires. Five indices—information obtainment rate, periodic validity, driver subjective scoring and the corresponding UI (represents information intelligibility), and CE (represents information legibility)—were analyzed to evaluate their relationships to VMS information reliability. The results confirmed that the amount of information, and the scrolling period considering redundant distance, significantly affect the reliability of VMSs information. For static VMSs, the information obtainment rate and the subjective scoring decrease with increasing amount of information. The recollection accuracy of the drivers significantly declines when the amount of information shown increases to 90 bits, corresponding to an information obtainment rate of less than 0.8 and UI equal to 0. For dynamic VMSs, the information reliability deteriorates as the scrolling period shortens and the number of phases increases. Unreasonable reliability is found when the periodic validity is less than 0.9, i.e., the actual scrolling period is more than 10% less than the calculated one, corresponding to CE equal to 0. The reliability of information was evaluated by combining the subjective scoring of the drivers and a data-based statistical analysis and considering driving safety. Accordingly, it was recommended that 90 bit is the maximum amount of information to be shown on a VMS and that the preferred scrolling period of each phase of a dynamic VMS is 5 s. The results of this study support the objective of providing reliable information to drivers by addressing the problems related to the amount of information and presentation time for VMSs. These findings provide a basis for determining the thresholds for VMS information to promote practical and user-friendly designs of VMSs on urban roads.     

基于网络理论的物质成瘾新视角

物质成瘾是一种涉及生理、心理和环境等多因素的复杂现象, 但是当前基于生物还原论的解释对物质成瘾现象整体性的理解和康复研究造成了阻碍。网络理论聚焦于心理障碍变量之间相互作用形成的反馈环路, 从整体视角为研究物质成瘾提供了新的理论框架。将网络理论应用于物质成瘾的研究中将有利于:(1)理解症状之间的相互关系和影响; (2)理解症状网络的整体性和系统性动态变化过程; 以及(3)将多层次和多水平因素整合到统一的理论框架中。从网络理论视角来理解物质成瘾, 也将对未来的干预和治疗提供了理论支持。目前, 网络理论仍处于言语模型阶段, 未来需要进一步提出更具体、可验证的统计模型, 以完善对于物质成瘾机制的了解, 更加有效地推进物质成瘾的治疗与恢复。     

动作视频游戏对发展性阅读障碍者阅读技能的影响及其内在机制

发展性阅读障碍是一种在获得阅读技能方面的特殊困难, 这种障碍会严重影响个体的发展, 如何帮助发展性阅读障碍者改善其阅读技能是近年来研究的焦点。传统的干预方法主要针对发展性阅读障碍者的语音缺陷, 这类方法存在一些问题, 如费时费力、给阅读障碍者带来阅读压力等。近年来, 大部分研究表明通过趣味性的动作视频游戏训练可以显著地提高发展性阅读障碍者的阅读技能, 但是其背后的机制尚不明确。基于大细胞通路缺陷理论框架, 从视觉空间注意、注意跨通道转换、视觉运动加工等方面来梳理动作视频游戏与阅读之间的关系, 揭示了动作视频游戏训练对阅读效率影响的可能内在机制。未来的研究可以在大细胞通路缺陷理论的框架下, 深入分析动作视频游戏改善阅读的神经机制, 并尝试开发更适合发展性阅读障碍者的干预程序。     

混合情绪能促进心理健康吗？

摘 要 积极和消极情绪的同时体验,即混合情绪,是生活中常见的情绪状态。健康应对的共激活模型、情绪动态模型和积极比模型一致认为混合情绪与心理健康之间呈现非线性的关系,适当的混合情绪有利于个体在困境中全面加工和整合信息,寻求意义,获得控制感,进而实现健康应对和心理症状改善,获得幸福感。未来研究应关注对非线性关系的精确描述;低压力或非压力情境下混合情绪的意义;进一步研究混合情绪促进心理健康的内部机制和影响因素。     

Termination of information evaluation in auditing

A screening decision is about whether a candidate fails to meet a decision maker's criteria and must be rejected, or whether it meets the criteria and can be accepted. Image theory contends that screening decisions are based on a simple, noncompensatory process that focuses solely upon the candidate's negative attributes. This contention has received empirical support in a job screening context in which students role-played a hypothetical person seeking a job. But how robust is image theory's prediction? The present work was done in the context of professional auditors screening prospective clients. The client screening context is a particularly interesting setting to test the implications of image theory. If auditors reject clients with negative attributes, as predicted by image theory, this will indicate that some clients are being denied access to a socially useful service. Further, auditors can accept prospective clients with negative attributes and simply adjust the audit plan and fees to compensate for the client's riskiness. Thus, it is not clear that the preliminary findings obtained in a job screening context will generalize to the audit context. On the other hand, results consistent with the image theory prediction would suggest a robust theory. Even in the client screening context, where auditors used their own criteria to screen prospective clients, we found overwhelming support for image theory's view of screening. The results indicate the potential payoffs of image theory as a robust framework to address audit and other substantive problems. Implications of a noncompensatory, negative oriented, client screening strategy are discussed.     

Selecting a new technology strategy using multiattribute,multilevel decision trees

Research indicates that selecting a strategy to best exploit a new technology is a complex decision-making process. The task involves making a series of decisions with multiple alternatives, each to be evaluated by multiple criteria whose values have high levels of uncertainty. This paper presents a methodology for modelling a new technology decision using decision trees and an optimizing algorithm. A problem of a mining company considering the adoption of new technology is used to illustrate the decision-making task and modelling methodology. A numerical solution to the case demonstrates the potential of the optimizing technique in strategy selection.     

Preference structures and threshold models

Preferences are often represented in terms of a function, in the deterministic case as well as in the probabilistic case. In the present paper we develop a new numerical representation of preference structures for which the strict preference relation (P) is without circuit but not necessarily transitive. Moreover, we investigate the consequences of the representation for the usual preference structures. In particular, we propose new formulations for the numerical representation of the interval order structure.     

Decomposition of multivariate utility functions in non-additive expected utility theory

In expected utility many results have been derived that give necessary and/or sufficient conditions for a multivariate utility function to be decomposable into lower-dimensional functions. In particular, multilinear, multiplicative and additive decompositions have been widely discussed. These utility functions can be more easily assessed in practical situations. In this paper we present a theory of decomposition in the context of nonadditive expected utility such as anticipated utility or Choquet expected utility. We show that many of the results used in conventional expected utility carry over to these more general frameworks. If preferences over lotteries depend only on the marginal probability distributions, then in expected utility the utility function is additively decomposable. We show that in anticipated utility the marginality condition implies not only that the utility function is additively decomposable but also that the distortion function is the identity function. We further demonstrate that a decision maker who is bivariate risk neutral has a utility function that is additively decomposable and a distortion function q for which q(½) = ½.