On the nature of over-dispersion in motor vehicle crash prediction models

Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites

Gas boosted solar water heaters : Queensland case studies of installation practices in new homes

Because of the greenhouse gas emissions implications of the market dominating electric hot water systems, governments in Australia have implemented policies and programs to encourage the uptake of solar water heaters (SWHs) in the residential market as part of climate change adaptation and mitigation strategies. The cost-benefit analysis that usually accompanies all government policy and program design could be simplistically reduced to the ratio of expected greenhouse gas reductions of SWH to the cost of a SWH. The national Register of Solar Water Heaters specifies how many renewable energy certificates (RECs) are allocated to complying SWHs according to their expected performance, and hence greenhouse gas reductions, in different climates. Neither REC allocations nor rebates are tied to actual performance of systems. This paper examines the performance of instantaneous gas-boosted solar water heaters installed in new residences in a housing estate in south-east Queensland in the period 2007 – 2010. The evidence indicates systemic failures in installation practices, resulting in zero solar performance or dramatic underperformance (estimated average 43% solar contribution). The paper will detail the faults identified, and how these faults were eventually diagnosed and corrected. The impacts of these system failures on end-use consumers are discussed before concluding with a brief overview of areas where further research is required in order to more fully understand whole of supply chain implications.

Trajectory design for autonomous underwater vehicles based on ocean model predictions for feature tracking

Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection. We consider the use of ocean model predictions to determine the locations to be visited by an AUV, which then provides near-real time, in situ measurements back to the model to increase the skill of future predictions. The motion planning problem of steering the vehicle between the computed waypoints is not considered here. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks. We design a sampling plan and present experimental results with AUV retasking in the Southern California Bight (SCB) off the coast of Los Angeles.

Critical Factors for Sustainable Post Natural Disaster Reconstruction : Chinese Data

While scientists continue to explore the level of climate change impact to new weather patterns and our environment in general, there have been some devastating natural disasters worldwide in the last two decades. Indeed natural disasters are becoming a major concern in our society. Yet in many previous examples, our reconstruction efforts only focused on providing short-term necessities. How to develop resilience in the long run is now a highlight for research and industry practice. This paper introduces a research project aimed at exploring the relationship between resilience building and sustainability in order to identify key factors during reconstruction efforts. From extensive literature study, the authors considered the inherent linkage between the two issues as evidenced from past research. They found that sustainability considerations can improve the level of resilience but are not currently given due attention. Reconstruction efforts need to focus on resilience factors but as part of urban development, they must also respond to the sustainability challenge. Sustainability issues in reconstruction projects need to be amplified, identified, processed, and managed properly. On-going research through empirical study aims to establish critical factors (CFs) for stakeholders in disaster prone areas to plan for and develop new building infrastructure through holistic considerations and balanced approaches to sustainability. A questionnaire survey examined a range of potential factors and the subsequent data analysis revealed six critical factors for sustainable Post Natural Disaster Reconstruction that include: considerable building materials and construction methods, good governance, multilateral coordination, appropriate land-use planning and policies, consideration of different social needs, and balanced combination of long-term and short-term needs. Findings from this study should have an influence on policy development towards Post Natural Disaster Reconstruction and help with the achievement of sustainable objectives.

Brca2 is involved in meiosis in Arabidopsis thaliana as suggested by its interaction with Dmc1

Two BRCA2-like sequences are present in the Arabidopsis genome. Both genes are expressed in flower buds and encode nearly identical proteins, which contain four BRC motifs. In a yeast two-hybrid assay, the Arabidopsis Brca2 proteins interact with Rad51 and Dmc1. RNAi constructs aimed at silencing the BRCA2 genes at meiosis triggered a reproducible sterility phenotype, which was associated with dramatic meiosis alterations. We obtained the same phenotype upon introduction of RNAi constructs aimed at silencing the RAD51 gene at meiosis in dmc1 mutant plants. The meiotic figures we observed strongly suggest that homologous recombination is highly disturbed in these meiotic cells, leaving aberrant recombination events to repair the meiotic double-strand breaks. The 'brca2' meiotic phenotype was eliminated in spo11 mutant plants. Our experiments point to an essential role of Brca2 at meiosis in Arabidopsis. We also propose a role for Rad51 in the dmc1 context.

A tag-based personalized item recommendation system using tensor modeling and topic model approaches

This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment , should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.

Media futures: A review essay on'The Future of Reputation','TV Futures', and'The Future of the Internet and How to Stop It'

In his 1987 book, The Media Lab: Inventing the Future at MIT, Stewart Brand provides an insight into the visions of the future of the media in the 1970s and 1980s. 1 He notes that Nicolas Negroponte made a compelling case for the foundation of a media laboratory at MIT with diagrams detailing the convergence of three sectors of the media—the broadcast and motion picture industry; the print and publishing industry; and the computer industry. Stewart Brand commented: ‘If Negroponte was right and communications technologies really are converging, you would look for signs that technological homogenisation was dissolving old boundaries out of existence, and you would expect an explosion of new media where those boundaries used to be’. Two decades later, technology developers, media analysts and lawyers have become excited about the latest phase of media convergence. In 2006, the faddish Time Magazine heralded the arrival of various Web 2.0 social networking services: You can learn more about how Americans live just by looking at the backgrounds of YouTube videos—those rumpled bedrooms and toy‐strewn basement rec rooms—than you could from 1,000 hours of network television. And we didn’t just watch, we also worked. Like crazy. We made Facebook profiles and Second Life avatars and reviewed books at Amazon and recorded podcasts. We blogged about our candidates losing and wrote songs about getting dumped. We camcordered bombing runs and built open‐source software. America loves its solitary geniuses—its Einsteins, its Edisons, its Jobses—but those lonely dreamers may have to learn to play with others. Car companies are running open design contests. Reuters is carrying blog postings alongside its regular news feed. Microsoft is working overtime to fend off user‐created Linux. We’re looking at an explosion of productivity and innovation, and it’s just getting started, as millions of minds that would otherwise have drowned in obscurity get backhauled into the global intellectual economy. The magazine announced that Time’s Person of the Year was ‘You’, the everyman and everywoman consumer ‘for seizing the reins of the global media, for founding and framing the new digital democracy, for working for nothing and beating the pros at their own game’. This review essay considers three recent books, which have explored the legal dimensions of new media. In contrast to the unbridled exuberance of Time Magazine, this series of legal works displays an anxious trepidation about the legal ramifications associated with the rise of social networking services. In his tour de force, The Future of Reputation: Gossip, Rumor, and Privacy on the Internet, Daniel Solove considers the implications of social networking services, such as Facebook and YouTube, for the legal protection of reputation under privacy law and defamation law. Andrew Kenyon’s edited collection, TV Futures: Digital Television Policy in Australia, explores the intersection between media law and copyright law in the regulation of digital television and Internet videos. In The Future of the Internet and How to Stop It, Jonathan Zittrain explores the impact of ‘generative’ technologies and ‘tethered applications’—considering everything from the Apple Mac and the iPhone to the One Laptop per Child programme.