43,078 research outputs found

    Quantifying the causal effects of 20 mph zones on road casualties in London via doubly robust estimation

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    © 2016 Elsevier Ltd. All rights reserved.This paper estimates the causal effect of 20 mph zones on road casualties in London. Potential confounders in the key relationship of interest are included within outcome regression and propensity score models, and the models are then combined to form a doubly robust estimator. A total of 234 treated zones and 2844 potential control zones are included in the data sample. The propensity score model is used to select a viable control group which has common support in the covariate distributions. We compare the doubly robust estimates with those obtained using three other methods: inverse probability weighting, regression adjustment, and propensity score matching. The results indicate that 20 mph zones have had a significant causal impact on road casualty reduction in both absolute and proportional terms

    Cooperative output regulation of multi-agent systems coupled by dynamic edges

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    This paper investigates a new class of linear multi-agent systems, in which nodes are coupled by dynamic edges in the sense that each edge has a dynamic system attached. The outputs of the edge dynamic systems combine to form the external input of the node dynamic system, which is called neighboring input; while the outputs of the node dynamic systems are inputs of the edge dynamic systems that therefore cannot be directly controlled. Distributed controllers for nodes are presented to realize output synchronization and output cooperation. Output cooperation makes the outputs of nodes realize some cooperation that here is specified as making the neighboring input track a predefined trajectory. The controllers depending on local state and neighboring inputs are designed by combining the feedback passivity theory and the internal model principle. A simulation example on the cooperated current control of an electrical network illustrates the potential applications of the analytic results.preprin

    Factors determining the magnitude of grain-size strengthening in polycrystalline metals

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    Grain-size strengthening of polycrystalline metals, the Hall-Petch effect, has been described for the past sixty years as a dependence of the strength of polycrystalline metals on the inverse square-root of grain size, d. The value of the coefficient of the dependence has been the subject of discussion throughout. Here, we find what known factors in the experiments may determine its value, by meta-analysis using maximum-likelihood methods of the literature values of the coefficient in sixty-one datasets. No dependence of the coefficient is found on plastic strain, and a strong dependence is found on the average grain size of each study. Combining these and other factors accounts for the reported values of about 80% of the sixty-one coefficients. The grain-size dependence of the Hall-Petch coefficient is an artefact arising from fitting the data to an incorrect expression. An alternative grain-size effect described by a lnd/d function is consistent with the theory of dislocations dynamics and generation. The corresponding analysis of the coefficients of fits based on this theory shows that none of the factors investigated are statistically significant, confirming the correctness of this approach

    Safety effects of the London cycle superhighways on cycle collisions

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    This paper evaluates the effects of the London Cycle Superhighways (CS) on cycle collisions. A total of 45 CS segments and 375 control segments are observed for a period of 8 years in London. Variables such as road characteristics, crash history and socio-economic in formation are included in the data set. Traffic characteristics Including traffic volume, cycle volume and traffic speed are obtained from Department for Transport. We first estimate the safety effects on the CS routes using Empirical Bayes methods. Then propensity score matching methods are also applied for comparison. The introduction of cycle superhighways caused cycling traffic volumes to increase dramatically along CS routes with no significant impacts on collision rates. Our models find that the increase in traffic was associated with a rise in annual total cycle collisions of around 2.6 per km (38% in percentage). However, when we re-estimate the effects based on cycle collision rates rather than levels, our results also show that the CS routes are not more dangerous or safer than the control roads. Among the four CS routes, CS3 performs the best in protecting cyclists with a large proportion of segregated lanes whilst the cyclists have to share the lanes with motorists on other routes. It is recommended that consistent safety designs should be applied on all CS routes for a safer cycling environment

    A New Methodology for Generalizing Unweighted Network Measures

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    Several important complex network measures that helped discovering common patterns across real-world networks ignore edge weights, an important information in real-world networks. We propose a new methodology for generalizing measures of unweighted networks through a generalization of the cardinality concept of a set of weights. The key observation here is that many measures of unweighted networks use the cardinality (the size) of some subset of edges in their computation. For example, the node degree is the number of edges incident to a node. We define the effective cardinality, a new metric that quantifies how many edges are effectively being used, assuming that an edge's weight reflects the amount of interaction across that edge. We prove that a generalized measure, using our method, reduces to the original unweighted measure if there is no disparity between weights, which ensures that the laws that govern the original unweighted measure will also govern the generalized measure when the weights are equal. We also prove that our generalization ensures a partial ordering (among sets of weighted edges) that is consistent with the original unweighted measure, unlike previously developed generalizations. We illustrate the applicability of our method by generalizing four unweighted network measures. As a case study, we analyze four real-world weighted networks using our generalized degree and clustering coefficient. The analysis shows that the generalized degree distribution is consistent with the power-law hypothesis but with steeper decline and that there is a common pattern governing the ratio between the generalized degree and the traditional degree. The analysis also shows that nodes with more uniform weights tend to cluster with nodes that also have more uniform weights among themselves.Comment: 23 pages, 10 figure

    Delay Aware Intelligent Transient Stability Assessment System

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    Transient stability assessment is a critical tool for power system design and operation. With the emerging advanced synchrophasor measurement techniques, machine learning methods are playing an increasingly important role in power system stability assessment. However, most existing research makes a strong assumption that the measurement data transmission delay is negligible. In this paper, we focus on investigating the influence of communication delay on synchrophasor-based transient stability assessment. In particular, we develop a delay aware intelligent system to address this issue. By utilizing an ensemble of multiple long short-term memory networks, the proposed system can make early assessments to achieve a much shorter response time by utilizing incomplete system variable measurements. Compared with existing work, our system is able to make accurate assessments with a significantly improved efficiency. We perform numerous case studies to demonstrate the superiority of the proposed intelligent system, in which accurate assessments can be developed with time one third less than state-of-the-art methodologies. Moreover, the simulations indicate that noise in the measurements has trivial impact on the assessment performance, demonstrating the robustness of the proposed system.published_or_final_versio

    Are multiple speed cameras more effective than a single one? Causal analysis of the safety impacts of multiple speed cameras

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    Most previous studies investigate the safety effects of a single speed camera, ignoring the potential impacts from adjacent speed cameras. The mutual influence between two or even more adjacent speed cameras is a relevant attribute worth taking into account when evaluating the safety impacts of speed cameras. This paper investigates the safety effects of two or more speed cameras observed within a specific radius which are defined as multiple speed cameras. A total of 464 speed cameras at treated sites and 3119 control sites are observed and related to road traffic accident data from 1999 to 2007. The effects of multiple speed cameras are evaluated using pairwise comparisons between treatment units with different doses based on the propensity score methods. The spatial effect of multiple speed cameras is investigated by testing various radii. There are two major findings in this study. First, sites with multiple speed cameras perform better in reducing the absolute number of road accidents than those with a single camera. Second, speed camera sites are found to be most effective with a radius of 200 m. For a radius of 200 m and 300 m, the reduction in the personal injury collisions by multiple speed cameras are 21.4 % and 13.2 % more than a single camera. Our results also suggest that multiple speed cameras are effective within a small radius (200 m and 300 m)
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