Investigating the feasibility of vehicle telemetry data as a means of predicting driver workload

Driving is a safety critical task that requires a high level of attention and workload from the driver. Despite this, people often also perform secondary tasks such as eating or using a mobile phone, which increase workload levels and divert cognitive and physical attention from the primary task of driving. If a vehicle is aware that the driver is currently under high workload, the vehicle functionality can be changed in order to minimize any further demand. Traditionally, workload measurements have been performed using intrusive means such as physiological sensors. Another approach may be to use vehicle telemetry data as a performance measure for workload. In this paper, we present the Warwick-JLR Driver Monitoring Dataset (DMD) and analyse it to investigate the feasibility of using vehicle telemetry data for determining the driver workload. We perform a statistical analysis of subjective ratings, physiological data, and vehicle telemetry data collected during a track study. A data mining methodology is then presented to build predictive models using this data, for the driver workload monitoring problem

Dual viewpoint passenger state classification using 3D CNNs

The rise of intelligent vehicle systems will lead to more human-machine interactions and so there is a need to create a bridge between the system and the actions and behaviours of the people inside the vehicle. In this paper, we propose a dual camera setup to monitor the actions and behaviour of vehicle passengers and a deep learning architecture which can utilise video data to classify a range of actions. The method incorporates two different views as input to a 3D convolutional network and uses transfer learning from other action recognition data. The performance of this method is evaluated using an in-vehicle dataset, which contains video recordings of people performing a range of common in-vehicle actions. We show that the combination of transfer learning and using dual viewpoints in a 3D action recognition network offers an increase in classification accuracy of action classes with distinct poses, e.g. mobile phone use and sleeping, whilst it does not apply as well for classifying those actions with small movements, such as talking and eating

Data mining for vehicle telemetry

This paper presents a data mining methodology for driving condition monitoring via CAN-bus data that is based on the general data mining process. The approach is applicable to many driving condition problems and the example of road type classification without the use of location information is investigated. Location information from Global Positioning Satellites and related map data are often not available (for business reasons), or cannot represent the full dynamics of road conditions. In this work, Controller Area Network (CAN)-bus signals are used instead as inputs to models produced by machine learning algorithms. Road type classification is formulated as two related labelling problems: Road Type (A, B, C and Motorway) and Carriageway Type (Single or Dual). An investigation is presented into preprocessing steps required prior to applying machine learning algorithms, namely, signal selection, feature extraction, and feature selection. The selection methods used include Principal Components Analysis (PCA) and Mutual Information (MI), which are used to determine the relevance and redundancy of extracted features, and are performed in various combinations. Finally, as there is an inherent bias towards certain road and carriageway labellings, the issue of class imbalance in classification is explained and investigated. A system is produced, which is demonstrated to successfully ascertain road type from CAN-bus data, and it is shown that the classification correlates well with input signals such as vehicle speed, steering wheel angle, and suspension heigh

Why do those out of work because of sickness or disability have a high mortality risk? Evidence from a Scottish cohort

<b>Background:</b> Existing evidence on the association between being out of work because of sickness or disability and high mortality risk suggests that most of the association cannot be explained by controlling for health, health behaviour or socio-economic position. However, studies are often based on administrative data that lack explanatory factors. Here, we investigate this high mortality risk using detailed information from a cohort study.<p></p> <b>Methods:</b> Data from the West of Scotland Twenty-07 prospective cohort study were used to follow those (average age 56 years) employed, unemployed and out of work in 1988 to death or end of follow-up in 2011. Using a parametric survival model, mean survival was calculated for each employment group after adjustment for health behaviours, health and socio-economic position.<p></p> <b>Results:</b> The difference in survival between those sick or disabled (30% survival at end of follow-up), and those unemployed (49%) or employed (61%) was mostly accounted for by adjusting for the higher levels of poor heath at baseline in the former group (49, 46 and 56%, respectively, after adjustment). After controlling for all variables, the difference between those sick or disabled (51%) and those employed (56%) was further attenuated slightly.<p></p> <b>Conclusion:</b> Our results suggest that the present health of those out of work and sick or disabled should be taken seriously, as their long-term survival prospects are considerably poorer than other employment groups.<p></p&gt

Why do those out of work because of sickness or disability have a high mortality risk? Evidence from a Scottish cohort

<b>Background:</b> Existing evidence on the association between being out of work because of sickness or disability and high mortality risk suggests that most of the association cannot be explained by controlling for health, health behaviour or socio-economic position. However, studies are often based on administrative data that lack explanatory factors. Here, we investigate this high mortality risk using detailed information from a cohort study.<p></p> <b>Methods:</b> Data from the West of Scotland Twenty-07 prospective cohort study were used to follow those (average age 56 years) employed, unemployed and out of work in 1988 to death or end of follow-up in 2011. Using a parametric survival model, mean survival was calculated for each employment group after adjustment for health behaviours, health and socio-economic position.<p></p> <b>Results:</b> The difference in survival between those sick or disabled (30% survival at end of follow-up), and those unemployed (49%) or employed (61%) was mostly accounted for by adjusting for the higher levels of poor heath at baseline in the former group (49, 46 and 56%, respectively, after adjustment). After controlling for all variables, the difference between those sick or disabled (51%) and those employed (56%) was further attenuated slightly.<p></p> <b>Conclusion:</b> Our results suggest that the present health of those out of work and sick or disabled should be taken seriously, as their long-term survival prospects are considerably poorer than other employment groups.<p></p&gt

Political geographies of the object

This paper examines the role of objects in the constitution and exercise of state power, drawing on a close reading of the acclaimed HBO television series The Wire, an unconventional crime drama set and shot in Baltimore, Maryland. While political geography increasingly recognizes the prosaic and intimate practices of stateness, we argue that objects themselves are central to the production, organization, and performance of state power. Specifically, we analyze how three prominent objects on The Wire—wiretaps, cameras, and standardized tests—arrange and produce the conditions we understand as ‘stateness’. Drawing on object-oriented philosophy, we offer a methodology of power that suggests it is generalized force relations rather than specifically social relations that police a population—without, of course, ever being able to fully capture it. We conclude by suggesting The Wire itself is an object of force, and explore the implications of an object-oriented approach for understanding the nature of power, and for political geography more broadly

Phenoloxidase activity acts as a mosquito innate immune response against infection with semliki forest virus

Several components of the mosquito immune system including the RNA interference (RNAi), JAK/STAT, Toll and IMD pathways have previously been implicated in controlling arbovirus infections. In contrast, the role of the phenoloxidase (PO) cascade in mosquito antiviral immunity is unknown. Here we show that conditioned medium from the Aedes albopictus-derived U4.4 cell line contains a functional PO cascade, which is activated by the bacterium Escherichia coli and the arbovirus Semliki Forest virus (SFV) (Togaviridae; Alphavirus). Production of recombinant SFV expressing the PO cascade inhibitor Egf1.0 blocked PO activity in U4.4 cell- conditioned medium, which resulted in enhanced spread of SFV. Infection of adult female Aedes aegypti by feeding mosquitoes a bloodmeal containing Egf1.0-expressing SFV increased virus replication and mosquito mortality. Collectively, these results suggest the PO cascade of mosquitoes plays an important role in immune defence against arboviruses

A First Search for coincident Gravitational Waves and High Energy Neutrinos using LIGO, Virgo and ANTARES data from 2007

We present the results of the first search for gravitational wave bursts associated with high energy neutrinos. Together, these messengers could reveal new, hidden sources that are not observed by conventional photon astronomy, particularly at high energy. Our search uses neutrinos detected by the underwater neutrino telescope ANTARES in its 5 line configuration during the period January - September 2007, which coincided with the fifth and first science runs of LIGO and Virgo, respectively. The LIGO-Virgo data were analysed for candidate gravitational-wave signals coincident in time and direction with the neutrino events. No significant coincident events were observed. We place limits on the density of joint high energy neutrino - gravitational wave emission events in the local universe, and compare them with densities of merger and core-collapse events.Comment: 19 pages, 8 figures, science summary page at http://www.ligo.org/science/Publication-S5LV_ANTARES/index.php. Public access area to figures, tables at https://dcc.ligo.org/cgi-bin/DocDB/ShowDocument?docid=p120000

Protocol for a mixed-methods longitudinal study to identify factors influencing return to work in the over 50s participating in the UK Work Programme: Supporting Older People into Employment (SOPIE)

Introduction Increasing employment among older workers is a policy priority given the increase in life expectancy and the drop in labour force participation after the age of 50. Reasons for this drop are complex but include poor health, age discrimination, inadequate skills/qualifications and caring roles; however, limited evidence exists on how best to support this group back to work. The Work Programme is the UK Government's flagship policy to facilitate return to work (RTW) among those at risk of long-term unemployment. ‘Supporting Older People Into Employment’ (SOPIE) is a mixed-methods longitudinal study involving a collaboration between academics and a major Work Programme provider (Ingeus). The study will investigate the relationship between health, worklessness and the RTW process for the over 50s. Methods and analysis There are three main study components. Embedded fieldwork will document the data routinely collected by Ingeus and the key interventions/activities delivered. The quantitative study investigates approximately 14 000 individuals (aged 16–64 years, with 20% aged over 50) who entered the Ingeus Work Programme (referred to as ‘clients’) in a 16-month period in Scotland and were followed up for 2 years. Employment outcomes (including progression towards work) and how they differ by client characteristics (including health), intervention components received and external factors will be investigated. The qualitative component will explore the experiences of clients and Ingeus staff, to better understand the interactions between health and (un)employment, Work Programme delivery, and how employment services can be better tailored to the needs of the over 50s. Ethics and dissemination Ethical approval was received from the University of Glasgow College of Social Sciences Research Ethics Committee (application number 400140186). Results Results will be disseminated through journal articles, national and international conferences. Findings will inform current and future welfare-to-work and job retention initiatives to extend healthy working lives