基于IFC 与gbXML 标准的建筑信息模型与绿色建筑分析软件互操作性测试与评估

绿色建筑和建筑节能是建筑行业可持续发展的重要因素,然而建筑信息模型(BIM) 软件种类繁多、数据标准各异、软件之间的数据传递经常丢失信息。为解决不同软件之间的“信 息孤岛”问题和互操作性问题,分析了基于工业基础类标准(IFC)和gbXML 标准的绿色建筑模型 的结构框架,选取BIM 建模软件ArchiCAD 和绿色建筑性能分析软件Ecotec,对基于IFC 和 gbXML 标准的软件之间的互操作性进行了测试和评估,确定了建筑信息模型在交互过程中的问 题。针对相关问题本文提出了减少IFC 标准中的信息冗余、提高IFC 标准领域层对绿色建筑信 息的支持、提高资源层对相关信息定义的针对性等建议。     

Influence of age and proximity warning devices on collision avoidance in simulated driving

OBJECTIVE: We conducted a set of experiments to examine the utility of several different uni- and multimodal collision avoidance systems (CASs) on driving performance of young and older adult drivers in a high-fidelity simulator. BACKGROUND: Although previous research has examined the efficacy of different CASs on collision avoidance, there has been a dearth of studies that have examined such devices in different driving situations with different populations of drivers. METHOD: Several different CAS warnings were examined in varying traffic and collision configurations both without (Experiment 1a) and with (Experiment 2) a distracting in-vehicle task. RESULTS: Overall, collision avoidance performance for both potential forward and side object collisions was best for an auditory/visual CAS, which alerted drivers using both modalities. Interestingly, older drivers (60-82 years of age) benefited as much as younger drivers from the CAS, and sometimes they benefited more. CONCLUSION: These data suggest that CASs can be beneficial across a number of different driving scenarios, types of collisions, and driver populations. APPLICATION: These results have important implications for the design and implementation of CASs for different driver populations and driving conditions.     

Efficient Update of Indexes for Dynamically Changing Web Documents

Recent work on incremental crawling has enabled the indexed document collection of a search engine to be more synchronized with the changing World Wide Web. However, this synchronized collection is not immediately searchable, because the keyword index is rebuilt from scratch less frequently than the collection can be refreshed. An inverted index is usually used to index documents crawled from the web. Complete index rebuild at high frequency is expensive. Previous work on incremental inverted index updates have been restricted to adding and removing documents. Updating the inverted index for previously indexed documents that have changed has not been addressed. In this paper, we propose an efficient method to update the inverted index for previously indexed documents whose contents have changed. Our method uses the idea of landmarks together with the diff algorithm to significantly reduce the number of postings in the inverted index that need to be updated. Our experiments verify that our landmark-diff method results in significant savings in the number of update operations on the inverted index.     

Simulating Ramsey-Type Fringes in a Pulsed Microwave-Driven Classical Josephson Junction

We present evidence for a close analogy between the nonlinear behaviour of a pulsed microwave-driven Josephson junction at low temperature and the experimentally observed behaviour of Josephson systems operated below the quantum transition temperature under similar conditions. We specifically address observations of Ramsey-type fringe oscillations, which can be understood in classical nonlinear dynamics as results of slow transient oscillations in a pulsed microwave environment. Simulations are conducted to mimic experimental measurements by recording the statistics of microwave-induced escape events from the anharmonic potential well of a zero-voltage state. Observations consistent with experimentally obtained Ramsey-type oscillations are found in the classical model. An erratum to this article can be found at     

How users perceive and respond to security messages: a NeuroIS research agenda and empirical study

Users are vital to the information security of organizations. In spite of technical safeguards, users make many critical security decisions. An example is users’ responses to security messages – discrete communication designed to persuade users to either impair or improve their security status. Research shows that although users are highly susceptible to malicious messages (e.g., phishing attacks), they are highly resistant to protective messages such as security warnings. Research is therefore needed to better understand how users perceive and respond to security messages. In this article, we argue for the potential of NeuroIS – cognitive neuroscience applied to Information Systems – to shed new light on users’ reception of security messages in the areas of (1) habituation, (2) stress, (3) fear, and (4) dual-task interference. We present an illustrative study that shows the value of using NeuroIS to investigate one of our research questions. This example uses eye tracking to gain unique insight into how habituation occurs when people repeatedly view security messages, allowing us to design more effective security messages. Our results indicate that the eye movement-based memory (EMM) effect is a cause of habituation to security messages – a phenomenon in which people unconsciously scrutinize stimuli that they have previously seen less than other stimuli. We show that after only a few exposures to a warning, this neural aspect of habituation sets in rapidly, and continues with further repetitions. We also created a polymorphic warning that continually updates its appearance and found that it is effective in substantially reducing the rate of habituation as measured by the EMM effect. Our research agenda and empirical example demonstrate the promise of using NeuroIS to gain novel insight into users’ responses to security messages that will encourage more secure user behaviors and facilitate more effective security message designs.     

灰色二层多目标线性规划问题及其解法

针对二层多目标线性规划问题,结合灰色系统的特性,提出了一般灰色二层多目标线性规划问题,并给出了模型的相关定义和定理.针对漂移型灰色二层多目标线性规划问题,提出一种具有全局收敛性质的求解算法.首先通过线性加权模理想点法把多目标转化为单目标;然后当可行域为非空紧集时,利用库恩塔克条件把双层转化为单层,再利用粒子群算法搜索单目标单层线性规划即可得到原问题的解;最后通过算例表明了该算法的有效性.     

非等间隔GM(1, 1, ????) 幂次时间项模型及其应用

GM(1, 1, ??^??) 幂次时间项模型是灰色GM(1, 1) 模型的推广. 在灰色GM(1, 1) 模型和等间隔GM(1, 1, ??^??) 幂次时间项模型的基础上提出非等间隔GM(1, 1, ??^??) 幂次时间项模型, 并对模型进行求解. 讨论了GM(1, 1, ????) 幂次时间项模型的曲线形状、发展系数以及幂指数间的关系, 研究了非等间隔GM(1, 1, ??^??) 幂次时间项模型的参数空间. 将平均相对误差看成幂指数的函数, 根据序列形状判断幂指数的范围, 并利用粒子群算法求解幂指数. 实际应用验证了所提出模型的有效性.