Predicting vehicular travel times by modeling heterogeneous influences between arterial roads

Predicting travel times of vehicles in urban settings is a useful and tangible quantity of interest in the context of intelligent transportation systems. We address the problem of travel time prediction in arterial roads using data sampled from probe vehicles. There is only a limited literature on methods using data input from probe vehicles. The spatio-temporal dependencies captured by existing data driven approaches are either too detailed or very simplistic. We strike a balance of the existing data driven approaches to account for varying degrees of influence a given road may experience from its neighbors, while controlling the number of parameters to be learnt. Specifically, we use a NoisyOR conditional probability distribution (CPD) in conjunction with a dynamic bayesian network (DBN) to model state transitions of various roads. We propose an efficient algorithm to learn model parameters. We propose an algorithm for predicting travel times on trips of arbitrary durations. Using synthetic and real world data traces we demonstrate the superior performance of the proposed method under different traffic conditions.Comment: 13 pages, conferenc

Reporting and dealing with missing quality of life data in RCTs : has the picture changed in the last decade?

Peer reviewedPublisher PD

LAPSES: A Recipe for High-Performance Adaptive Router Design

Earlier research has shown that adaptive routing can help in improving network performance. However, it has not received adequate attention in commercial routers mainly due to the additional hardware complexity, and the perceived cost and performance degradation that may result from this complexity. These concerns can be mitigated if one can design a cost-effective router that can support adaptive routing. This paper proposes a three step recipe — Look-Ahead routing, intelligent Path Selection, and an Economic Storage implementation, called the LAPSES approach — for cost-effective high performance pipelined adaptive router design. The first step, look-ahead routing, reduces a pipeline stage in the router by making table lookup and arbitration concurrent. Next, three new traffic-sensitive path selection heuristics (LRU, LFU and MAX-CREDIT) are proposed to select one of the available alternate paths. Finally, two techniques for reducing routing table size of the adaptive router are presented. These are called meta-table routing and economical storage. The proposed economical storage needs a routing table with only 9 and 27 entries for two and three dimensional meshes, respectively. All these design ideas are evaluated on a (16 16) mesh network via simulation. A fully adaptive algorithm and various traffic patterns are used to examine the performance benefits. Performance results show that the look-ahead design as well as the path selection heuristics boost network performance, while the economical storage approach turns out to be an ideal choice in comparison to full-table and meta-table options. We believe the router resulting from these three design enhancements can make adaptive routing a viable choice for interconnects.

Are Essay Mills committing fraud? An analysis of their behaviours vs the 2006 Fraud Act (UK)

Many strategies have been proposed to address the use of Essay Mills and other ‘contract cheating’ services by students. These services generally offer bespoke custom-written essays or other assignments to students in exchange for a fee. There have been calls for the use of legal approaches to tackle the problem. Here we determine whether the UK Fraud Act (2006) might be used to tackle some of the activities of companies providing these services in the UK, by comparing their common practises, and their Terms and Conditions, with the Act. We found that all the sites examined have disclaimers regarding the use of their products but there are some obvious contradictions in the activities of the sites which undermine these disclaimers, for example all sites offer plagiarism-free guarantees for the work and at least eight have advertising which appears to contradict their terms and conditions. We identify possible areas in which the Act could be used to pursue a legal case but overall conclude that such an approach is unlikely to be effective. We call for a new offence to be created in UK law which specifically targets the undesirable behaviours of these companies in the UK, although the principles could be applied elsewhere. We also highlight other UK legal approaches that may be more successful

A double-edged sword: the merits and the policy implications of Google Translate in higher education

Machine translation, specifically Google Translate is freely available on a number of devices, and is improving in its ability to provide grammatically accurate translations. This development has the potential to provoke a major transformation in the internationalisation process at universities, since students may be, in the future, able to use technology to circumvent traditional language learning processes. While this is a potentially empowering move that may facilitate academic exchange and the diversification of the learner and researcher community at an international level, it is also a potentially problematic issue in two main respects. Firstly, the technology is at present unable to align to the socio-linguistic aspects of university level writing and may be misunderstood as a remedy to lack of writer language proficiency – a role it is not able to fulfil. Secondly, it introduces a new dimension to the production of academic work that may clash with Higher Education policy and, thus, requires legislation, in particular in light issues such as plagiarism and academic misconduct. This paper considers these issues against the background of English as a Global Lingua Franca, and argues two points. First of these is that HEIs need to develop an understanding and code of practice for the use of this technology. Secondly, three strands of potential future research will be presente