Player Rating Systems for Balancing Human Computation Games : Testing the Effect of Bipartiteness

Human Computation Games (HCGs) aim to engage volunteers to solve information tasks, yet suffer from low sustained engagement themselves. One potential reason for this is limited difficulty balance, as tasks difficulty is unknown and they cannot be freely changed. In this paper, we introduce the use of player rating systems for selecting and sequencing tasks as an approach to difficulty balancing in HCGs and game genres facing similar challenges. We identify the bipartite structure of user-task graphs as a potential issue of our approach: users never directly match users, tasks never match tasks. We therefore test how well common rating systems predict outcomes in bipartite versus non-bipartite chess data sets and log data of the HCG Paradox. Results indicate that bipartiteness does not negatively impact prediction accuracy: common rating systems outperform baseline predictions in HCG data, supporting our approach’s viability. We outline limitations of our approach and future work

Smart data-harnessing for financial value in short-term hire electric car schemes

In the developed world, two distinct trends are emerging to shake-up the current dominance of privately-owned, combustion motor car transport. The first is the emergence of the electric powertrain for vehicles as an affordable and massmarketed means of transport. This carries with it the potential to address many of the immediate shortcomings of the current paradigm, especially CO2 emissions, air and noise pollution. The second is the rise of new hire models of car ownership - the concept of paying for the use of a car as and when you need it. This carries with it the potential to address many of the existing issues: outlay-induced car use, residential parking and social division. On a similar timescale, we are witnessing the rise of smart technologies and smart cities, concepts that use data about the state of a system or elements of it to create value. There have been relatively few examples of schemes that have combined the electric and hire-model concepts, despite the huge potential for synergy. Indeed, the majority is against them on both counts -- cars are predominantly privately-owned and driven by internal combustion engines. Nevertheless, there is significant potential for this to change over the coming years

Neutrino flavor mixing with moments

The successful transition from core-collapse supernova simulations using classical neutrino transport to simulations using quantum neutrino transport will require the development of methods for calculating neutrino flavor transformations that mitigate the computational expense. One potential approach is the use of angular moments of the neutrino field, which has the added appeal that there already exist simulation codes which make use of moments for classical neutrino transport. Evolution equations for quantum moments based on the quantum kinetic equations can be straightforwardly generalized from the evolution of classical moments based on the Boltzmann equation. We present an efficient implementation of neutrino transformation using quantum angular moments in the free streaming, spherically symmetric bulb model. We compare the results against analytic solutions and the results from more exact multi-angle neutrino flavor evolution calculations. We find that our moment-based methods employing scalar closures predict, with good accuracy, the onset of collective flavor transformations seen in the multi-angle results. However in some situations they overestimate the coherence of neutrinos traveling along different trajectories. More sophisticated quantum closures may improve the agreement between the inexpensive moment-based methods and the multi-angle approach.Comment: Accepted in Physical Review

Whole-Life Environmental Impacts of ICT Use

In this paper we apply a whole-life assessment approach to estimate the environmental impact of the use of ICT of an individual within the UK over a one-year period. By estimating the energy and data consumption of an average user's use of a typical device, and estimating the associated energy usage (and thus CO2 produced) of each stage in the data chain, we are able to calculate the summed CO2 value for embodied carbon of an average device. Overall, device energy is seen to dominate; within device, desktops dominate, both due to their high energy use for a given task, but also their high standby power, which is the most significant point of behaviour-driven waste. Geographical, behavioural and chronological factors are all evaluated to be highly significant to the impact of a user's ICT use, along with a number of secondary factors. Finally, we present policy recommendations to further the understanding of the factors affecting the environmental impact of ICT, particularly focusing on sustainability, resource efficiency and the social implications of ICT in a low-carbon transformation

An intelligent hot-desking model harnessing the power of occupancy sensing

Purpose The purpose of this paper is to develop a model to harness occupancy sensing in a commercial hot-desking environment. Hot-desking is a method of office resource management designed to reduce the real estate costs of professional practices. However, the shortcoming is often in the suitability and appropriateness of allocated work environments. The Internet of Things could produce new data sets in the office at a resolution, speed and validity of which that they could be factored into desk-allocation, distributing seats based on appropriate noise levels, stay length, equipment requirements, previous presence and proximity to others working on the same project, among many others. Design/methodology/approach The study utilises primary data from a commercial office environment in Central London (numerical building system data and semi-structured interviews) to feed a discrete events simulator. To test the hypothesis, the authors look at the potential for intelligent hot-desking to use “work type” data to improve the distribution of individuals in the office, increasing productivity through the creation of positive “work type environments” – where those working on specific tasks perform better when grouped with others doing the same task. The simulation runs for a typical work day, and the authors compare the intelligent hot-desking arrangement to a base case. Findings The study shows that sensor data can be used for desk allocation in a hot-desking environment utilising activity-based working, with results that outweigh the costs of occupancy detection. The authors are not only able to optimise desk utilisation based on quality occupancy data but also demonstrate how overall productivity increases as individuals are allocated desks of their preference as much as possible among other enabling optimisations that can be applied. Moreover, the authors explore how an increase in occupancy data collection in the private sector could have key advantages for the business as an organization and the city as a whole. Research limitations/implications The research explores only one possible incarnation of intelligent hot-desking, and the authors presume that all data have already been collected, and while not insurmountable, they do not discuss the technical or cultural difficulties to this end. Furthermore, final examination of the productivity benefit – because of the difficulty in defining and measuring the concept – is exploratory rather than definitive. This research suggests that not only human-centric smart building research should be prioritised over energy or space-based themes but also large-scale private sector collection of occupancy data may be imminent, and its potential should be examined. Practical implications Findings strongly suggest that the hot-desking may cost more in lost productivity than it gains in reduced rental costs and as such many commercial offices should revaluate the transition, particularly with a view to facilitate intelligent hot-desking. Companies should begin to think strategically about the wider benefits of collecting occupancy data across their real estate portfolio, rather than reviewing use cases in silos. Finally, cities should consider scenarios of widespread collection of occupancy data in the private sector, examining the value these data have to city systems such as transport, and how the city might procure it for these ends. Social implications This paper raises positive and negative social concerns. The value in occupancy data suggested herein, bringing with it the implication it should be collected en mass, has a noted concern that this brings privacy concerns. As such, policy and regulation should heed that current standards should be reviewed to ensure they are sufficient to protect those in offices from being unfairly discriminated, spied or exploited through occupancy data. However, the improved use of occupancy data improving workplaces could indeed make them more enjoyable places to work, and have the potential to become a staple in company’s corporate social responsibility policies. Originality/value This paper fulfils an identified need for better understanding the specific uses of occupancy data in the smart building mantra. Several sources suggest the current research focus on energy and rental costs is misguided when the holistic cost of an office is considered, and concepts related to staff – although less understood – may have an order of magnitude bigger impact. This research supports this hypothesis through the example of intelligent hot-desking. The value of this paper lies in redirecting industry and research towards the considering occupancy data in smart building uses cases including – but not limited to– intelligent hot-desking. </jats:sec

Electric Vehicle Mobility-as-a-Service: Exploring the “Tri-Opt” of Novel Private Transport Business Models

Three distinct trends have emerged that have disrupted the dominance of privately- owned, combustion-powered car transport in the UK. First, the electric powertrain has emerged as an affordable means of transport; the second is the development of new hire models of car ownership: third, the growth of `smart city thinking' emphasises capitalising on increased connectivity and data availability to create value. We define the combination of these three trends as the 'tri-opt' of private transport -- three disruptors that should not be considered in isolation but as interacting -- an inflection of the`Energy Trilemma'."br/"In this paper, we apply systems thinking and a mixed methodology of workshops, interviews and systems modelling to the UK city of Bristol's Smart EV Transport Hub project to identify concepts that positively combine two or more of these three `Opts'. We demonstrate that there are many synergistic overlaps and that combinations potentially create significant value. Our data highlights that of the greatest value are those use cases that the current literature base has explored the least, and can be characterised as requiring significant public and private sector collaboration. Document type: Articl