A graph-based algorithm for extracting units and loops from architectural floor plans for a building evacuation model

This article presents the development of an automatic process in transforming computer-drawn architectural plans into a building fire evacuation simulator—spatial-grid evacuation model (SGEM). The SGEM has been developed to model the dynamic positions of each occupant of a building at every time point under an evacuation process. The presented process, termed automatic unit generator (AUG), is developed on the basis of a graph-based approach. It captures the architectural information originally produced by architects/building designers in CAD plans and rebuilds the units and their topological relationships, as well as determines the evacuation direction at every portal. As limited pre-defined information is needed, this proposed process could be employed at any stage of the design process. It makes the SGEM capable of integrating into CAD system to set up a smooth architectural design workflow.     

基于菲茨定律的虚拟现实任意形状选择模型

为了评估虚拟现实（VR）交互界面不同图形设计的点击效率，基于概率菲茨定律提出一种针对虚拟现实情境下指向性任务完成时间的预测方法，并构建了VR任意形状选择模型。首先，根据VR界面设计的实际需求，加入形状对指向性任务完成时间的影响，构建命中概率与任务难度指数的关系函数，将目标质心设为待积分函数的中心点，完成虚拟情境下概率菲茨模型定义。然后，设计实验一以获取改进概率菲茨模型中概率函数的常数项值；在此基础上设计实验二计算改进概率菲茨模型中预测函数的常数项，完成改进概率菲茨模型的构建。最后，以某VR烟草分拣系统实际点击任务对模型进行验证与评估，实验结果表明该模型能够在虚拟情境下对任务完成时间进行良好预测。     

基于菲茨定律的虚拟现实任意形状选择模型

为了评估虚拟现实（VR）交互界面不同图形设计的点击效率,基于概率菲茨定律提出一种针对虚拟现实情境下指向性任务完成时间的预测方法,并构建了VR任意形状选择模型。首先,根据VR界面设计的实际需求,加入形状对指向性任务完成时间的影响,构建命中概率与任务难度指数的关系函数,将目标质心设为待积分函数的中心点,完成虚拟情境下概率菲茨模型定义。然后,设计实验一以获取改进概率菲茨模型中概率函数的常数项值;在此基础上设计实验二计算改进概率菲茨模型中预测函数的常数项,完成改进概率菲茨模型的构建。最后,以某VR烟草分拣系统实际点击任务对模型进行验证与评估,实验结果表明该模型能够在虚拟情境下对任务完成时间进行良好预测。     

What do we know about ageing at work? Evidence-based fitness for duty and health in fire fighters

This study sought to collect evidence on age and workability in fire fighters, using systematic international literature searches, interviews, and secondary analyses from Dutch fire fighter studies. Recent decades have witnessed growing demands on fire fighters, who face peak task demands during duty. Older Dutch fire fighters experience greater emotional and mental demands than their younger colleagues. Huge inter-individual variation emerged in task performance with over six-fold differences in time-on-tasks and the percentage heart rate reserve between and within age groups. However, no age-effect was observed in lifting capacity during simulations. Compared to their youngest colleagues, older Dutch fire fighters face a six-fold increase in the risk of health complaints. The international literature lacks psychological age effects studies. Semi-functional tests, (e.g. exercise stress testing or push-ups) do not predict workability. Regular screening of fire fighters, using multi-modal functional tests that closely simulate real job activities, is recommended.     

A reinforcement learning approach to fail-safe design for multiple space robots—cooperation mechanism without communication and negotiation schemes

This paper explores a fail-safe design for multiple space robots, which enables robots to complete given tasks even when they can no longer be controlled due to a communication accident or negotiation problem. As the first step towards this goal, we propose new reinforcement learning methods that help robots avoid deadlock situations in addition to improving the degree of task completion without communications via ground stations or negotiations with other robots. Through intensive simulations on a truss construction task, we found that our reinforcement learning methods have great potential to contribute towards fail-safe design for multiple space robots in the above case. Furthermore, the simulations revealed the following detailed implications: (i) the first several planned behaviors must not be reinforced with negative rewards even in deadlock situations in order to derive cooperation among multiple robots, (ii) a certain amount of positive rewards added into negative rewards in deadlock situations contributes to reducing the computational cost of finding behavior plans for task completion, and (iii) an appropriate balance between positive and negative rewards in deadlock situations is indispensable for finding good behavior plans at a small computational cost.     

群智协同任务分配研究综述

任务分配是群智协同计算和众包中的核心问题之一,即通过设计合理的任务分配策略,在满足任务约束条件下,将群智任务分配给合适的工作者,以提高群智任务的完成效率和结果质量。分析了目前任务分配方法存在的问题,总结并提出了一个通用的任务分配框架,并分别从工作者模型、任务模型、任务分配算法三个方面对国内外相关研究工作进行了分析、归纳和总结。提出了群智协同任务分配研究中的关键问题与今后的研究趋势。     

Training in virtual environments: transfer to real world tasks and equivalence to real task training

Virtual environments (VEs) are extensively used in training but there have been few rigorous scientific investigations of whether and how skills learned in a VE are transferred to the real world. This research aimed to measure and evaluate what is transferring from training a simple sensorimotor task in a VE to real world performance. In experiment 1, real world performances after virtual training, real training and no training were compared. Virtual and real training resulted in equivalent levels of post-training performance, both of which significantly exceeded task performance without training. Experiments 2 and 3 investigated whether virtual and real trained real world performances differed in their susceptibility to cognitive and motor interfering tasks (experiment 2) and in terms of spare attentional capacity to respond to stimuli and instructions which were not directly related to the task (experiment 3). The only significant difference found was that real task performance after training in a VE was less affected by concurrently performed interference tasks than was real task performance after training on the real task. This finding is discussed in terms of the cognitive load characteristics of virtual training. Virtual training therefore resulted in equivalent or even better real world performance than real training in this simple sensorimotor task, but this finding may not apply to other training tasks. Future research should be directed towards establishing a comprehensive knowledge of what is being transferred to real world performance in other tasks currently being trained in VEs and investigating the equivalence of virtual and real trained performances in these situations.     

Training in virtual environments: transfer to real world tasks and equivalence to real task training

Virtual environments (VEs) are extensively used in training but there have been few rigorous scientific investigations of whether and how skills learned in a VE are transferred to the real world. This research aimed to measure and evaluate what is transferring from training a simple sensorimotor task in a VE to real world performance. In experiment 1, real world performances after virtual training, real training and no training were compared. Virtual and real training resulted in equivalent levels of post-training performance, both of which significantly exceeded task performance without training. Experiments 2 and 3 investigated whether virtual and real trained real world performances differed in their susceptibility to cognitive and motor interfering tasks (experiment 2) and in terms of spare attentional capacity to respond to stimuli and instructions which were not directly related to the task (experiment 3). The only significant difference found was that real task performance after training in a VE was less affected by concurrently performed interference tasks than was real task performance after training on the real task. This finding is discussed in terms of the cognitive load characteristics of virtual training. Virtual training therefore resulted in equivalent or even better real world performance than real training in this simple sensorimotor task, but this finding may not apply to other training tasks. Future research should be directed towards establishing a comprehensive knowledge of what is being transferred to real world performance in other tasks currently being trained in VEs and investigating the equivalence of virtual and real trained performances in these situations.     

On the interaction between plan recognition and intelligent interfaces

Plan recognition is an active research area in automatic reasoning, as well as a promising approach to engineering interfaces that can exploit models of user's plans and goals. Much research in the field has focused on the development of plan recognition algorithms to support particular user/system interactions, such as found in naturally occurring dialogues. However, two questions have typically remained unexamined: 1) exactly what kind of interface tasks can knowledge of a user's plans be used to support across communication modalities, and 2) how can such tasks in turn constrain development of plan recognition algorithms? In this paper we present a concrete exploration of these issues. In particular, we provide an assessment of plan recognition, with respect to the use of plan recognition in enhancing user interfaces. We clarify how use of a user model containing plans makes interfaces more intelligent and interactive (by providing an intelligent assistant that supports such tasks as advice generation, task completion, context-sensitive responses, error detection and recovery). We then show how interface tasks in turn provide constraints that must be satisfied in order for any plan recognizer to construct and represent a plan in ways that efficiently support these tasks. Finally, we survey how interfaces are fundamentally limited by current plan recognition approaches, and use these limitations to identify and motivate current research. Our research is developed in the context of CHECS, a plan-based design interface.     

Classification of metabolic and respiratory demands in fire fighting activity with extreme workloads

Fire fighting work comprises work tasks requiring an energy yield at maximal or close to maximal levels of the individual. Due to the very nature of fire fighting more complex physiological variables are difficult to measure. We measured metabolic and respiratory responses in 15 male, professional fire fighters during simulated work tasks on a test ground. Work time was on the average 22 min with individual components of work tasks lasting 2-4 min. The mean oxygen consumption for the whole exercise (22 min) was 2.75+/-0.29 l/min. The most demanding work task demanded an oxygen uptake of 3.55+/-0.27 l/min. Corresponding values for respiratory minute volumes were 82+/-14 and 102+/-14l/min, respectively. Heart rates averaged 168+/-12 for the whole test and 179+/-13 beats/min for the heaviest work task. Two new classes for classification of intensive and exhausting, short term physical work are proposed for inclusion in ISO8996 and values for relevant parameters are proposed.     

基于效益博弈的云计算资源动态可协调分配策略研究

在对用户的任务进行计算资源分配时,为了有效提高计算资源的利用效率,减少任务执行所需要的成本,提出了一种基于效益博弈的云计算资源动态可协调分配机制。该机制采用时间矩阵和费用矩阵作为任务效益的衡量指标,提出效益博弈模型,通过该模型的效益计算方程来得到最好的资源分配策略。为了使得计算资源能够合理地按需进行分配,提出了动态可协调分配机制,在合理地分配资源,满足所有任务正常执行时所需资源的同时,最大化任务的执行效益。实验仿真及对比结果表明,在任务完成时间、任务执行的平均成本、任务完成成功率上,本文算法都取得了较好的效果。     

Advanced modeling of selection and steering data: beyond Fitts' law

Human performance in selection tasks is frequently described by Fitts' law, which states that the average time needed to move to a target and select it is linearly related to the index of difficulty for the task, which is the logarithm of the task characteristic C=A/W, where A is the target distance and W is the target width. The coefficients in this linear relationship can vary across interaction conditions, such as when using distinct interaction devices, and can for instance be used to define throughput, which is a standardized measure to compare interaction conditions. Although Fitts' law has proven very useful in the field of human–computer interaction (HCI) over the past 50 years, there are several issues with Fitts' law that argue in favor of more advanced statistical modeling of experimental data. More specifically, we propose two generalizations of Fitts' law. The first generalization is not to limit the data analysis to average movement times, but to consider the distributions of the observed times instead. The second generalization is to extend Fitts' law to a more general relationship between task characteristics and index of difficulty and to use this generalized model to come up with additional measures that can be used alongside throughput.We use data from an experiment with both selection and tracing tasks to illustrate the proposed analysis method. The primary goal of the experiment is to compare the task performance in four experimental conditions, corresponding to all combinations of interaction device (mouse or pen) and target orientation (horzizontal/vertical versus oblique movements). First, we show that non-linear transformations on the measured task completion times are indeed advised to resolve problems with the normality and homoscedasticity of the data, especially in case of the tracing task. Second, we show that in case of the selection task the data supports a linear relationship between the logarithm of the task characteristic C and the logarithm of the movement time, which corresponds to a power-law between movement time and task characteristic, an alternative to Fitts' law that has previously been proposed by several authors. In case of the tracing task, the data supports a power-law function in between a linear and a logarithmic function. We conclude by demonstrating how multiple performance measures can be used simultaneously when comparing interaction conditions.     

城区建筑物3D景观模型建立

为了在2D GIS基础上实现城市建筑物的3D显示,提出了一种建立建筑物3D模型的方法,该方法首先采用最大包围盒法将建筑物3D模型与2．5D DEM集成在一起,然后采用了Meier关系数据结构的表示城区建筑物几何模型中的拓扑信息和属性信息,并通过VRML浏览器业实现城市景观的交互显示,从而实现了利用常规2D GIS数据建立建筑物3D景观虚拟模型,实验结果表明,该方法能在VRML浏览器中以各种视角,在各个位置和按各种缩放比例,对建筑物模型进行动态观察,并在计算机屏幕上实现立体显示,根据实验结果和分析可见,随着2D GIS的发展成熟,利用常规2D GIS数据来建立建筑物3D景观模型的条件已经具备。     

Revealing perceptual–cognitive expertise in law enforcement: an iterative approach using verbal-report,temporal-occlusion,and option-generation methods

Despite the attention garnered in the media about police use of force, there have been relatively few investigations of perceptual–cognitive skill in law enforcement using the naturalistic-decision-making approach. In this paper, we provide an overview of a series of four studies in which we investigated experience-based differences in police officer decision making in complex, rapidly unfolding, and uncertain situations. In these naturalistic situations, decision makers must first generate—for themselves—at least one option before intervening or taking action. We sought to test hypotheses about option-generation processes derived from apparently competing theories of skilled decision making and expert sensemaking. These two theories can be considered as representing two phases of decision making: skilled decision making focuses on selecting an appropriate course of action, while expert sensemaking addresses situational assessment and diagnosis. In the studies, we employed a variety of cognitive task analysis techniques, including experiments using option-generation and temporal-occlusion methods and process tracing measures (e.g., retrospective verbal reports, video-stimulated recall). Based on the data, we conclude that the two theoretical approaches—skilled decision making and expert sensemaking—appear to be complementary rather than competing. When the situation is relatively familiar, officers can quickly recognize the situation and identify an appropriate response. However, when situations are less familiar, more complex, and/or more uncertain, officers may need to engage in rapid sensemaking or situational diagnosis so that they can quickly comprehend the situation. We discuss implications for law enforcement officers and for law enforcement training.     

一种基于预测的资源匹配算法

网格任务调度过程中的资源匹配是根据任务要求从网格资源信息服务（GRIS）中查找出合适资源的过程。GRIS中记录的往往是资源的静态信息，由于本地负载的动态变化使得基于资源静态信息来确定的候选资源集中一些资源并不能满足任务的QoS需求。基于相关资源动态信息预测资源未来状态，给出了网格任务平均完成时间及完成时间的分布函数，并根据任务QoS需求，兼顾考虑资源当前及未来状态，提出了一种资源匹配模型与匹配算法。通过实验表明，该算法能有效减少候选资源数目，从而降低调度时间复杂度。     

VRML应用在远程教育中的探讨

VRML是一种建模语言,用来在Web环境中描述三维物体及其行为,从而在网络环境中构建虚拟场景（Virtual World）,作为构建虚拟现实应用的基本框架,具有包括分布式、三维、动态交互、多媒体集成、境界逼真等特征。VRML的特征对于远程教育有很高的应用价值。本文讨论了VRML的网络特性,归纳了在远程教育中的关键技术和应用。该研究服务于VRML在远程教育领域更深入的应用,并为该领域的未来发展把握方向。     

信息论课程在网络安全与执法专业建设中的重要性研究

网络安全与执法专业融合信息通信工程、信息安全和计算机科学与技术专业学科知识,旨在培养信息时代的优秀网络安全执法人员。信息论作为现代通信的理论基础,涵盖信源编码、信道传输和密码学等多学科理论。作为通信类专业的主干课程,信息论同样应该成为网络安全与执法专业的重要课程之一。在网络安全与执法专业开设信息论课程,通过教授基础信息理论、结合当前技术发展前沿,讲授信息网络通信理论体系,对完善网络安全与执法专业建设具有重要意义。文章论述信息论课程对网络安全与执法专业建设的重要性并得出结论：信息论课程建设是网络安全与执法专业建设的重要工作。因此,在网络安全与执法专业建设中,应当开始相应信息论课程。     

VRML应用在远程教育中的探讨

VRML是一种建模语言,用来在Web环境中描述三维物体及其行为,从而在网络环境中构建虚拟场景(Virtual World),作为构建虚拟现实应用的基本框架,具有包括分布式、三维、动态交互、多媒体集成、境界逼真等特征。VRML的特征对于远程教育有很高的应用价值。本文讨论了VRML的网络特性,归纳了在远程教育中的关键技术和应用。该研究服务于VRML在远程教育领域更深入的应用,并为该领域的未来发展把握方向。     

VRML在远程教育中的应用

在某些以实验为基础的专业领域,远程教育中有必要对场景进行模拟,VRML则是建构这种虚拟学习环境的利器,用3DS MAX实现几何形体的三维建模,得到虚拟场景的对象,并用VRML及脚本创建虚拟的场景,可以生动地实现虚拟的实验活动。