63,286 research outputs found
Participatory Patterns in an International Air Quality Monitoring Initiative
The issue of sustainability is at the top of the political and societal
agenda, being considered of extreme importance and urgency. Human individual
action impacts the environment both locally (e.g., local air/water quality,
noise disturbance) and globally (e.g., climate change, resource use). Urban
environments represent a crucial example, with an increasing realization that
the most effective way of producing a change is involving the citizens
themselves in monitoring campaigns (a citizen science bottom-up approach). This
is possible by developing novel technologies and IT infrastructures enabling
large citizen participation. Here, in the wider framework of one of the first
such projects, we show results from an international competition where citizens
were involved in mobile air pollution monitoring using low cost sensing
devices, combined with a web-based game to monitor perceived levels of
pollution. Measures of shift in perceptions over the course of the campaign are
provided, together with insights into participatory patterns emerging from this
study. Interesting effects related to inertia and to direct involvement in
measurement activities rather than indirect information exposure are also
highlighted, indicating that direct involvement can enhance learning and
environmental awareness. In the future, this could result in better adoption of
policies towards decreasing pollution.Comment: 17 pages, 6 figures, 1 supplementary fil
Asymmetric evolutionary games
Evolutionary game theory is a powerful framework for studying evolution in
populations of interacting individuals. A common assumption in evolutionary
game theory is that interactions are symmetric, which means that the players
are distinguished by only their strategies. In nature, however, the microscopic
interactions between players are nearly always asymmetric due to environmental
effects, differing baseline characteristics, and other possible sources of
heterogeneity. To model these phenomena, we introduce into evolutionary game
theory two broad classes of asymmetric interactions: ecological and genotypic.
Ecological asymmetry results from variation in the environments of the players,
while genotypic asymmetry is a consequence of the players having differing
baseline genotypes. We develop a theory of these forms of asymmetry for games
in structured populations and use the classical social dilemmas, the Prisoner's
Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric
games reveal essential differences between models of genetic evolution based on
reproduction and models of cultural evolution based on imitation that are not
apparent in symmetric games.Comment: accepted for publication in PLOS Comp. Bio
Virtual Reality Rhythm Game
Virtual reality headsets such as the HTC Vive and Oculus Rift bring robust virtual reality technology in the hands of consumers. However, virtual reality technology is still a very new and unexplored domain with a dearth of compelling software that takes advantage of what virtual reality has to offer. Current rhythm games on the virtual reality platform lack a sense of immersion for the player. These games also require players to remain stationary during gameplay. Our solution is a game where players have to hit musical notes that appear in a trail around them. The trail will move in different directions and players have to move and turn around accordingly in order to hit every note and pass a song
Exploratory Study of the Privacy Extension for System Theoretic Process Analysis (STPA-Priv) to elicit Privacy Risks in eHealth
Context: System Theoretic Process Analysis for Privacy (STPA-Priv) is a novel
privacy risk elicitation method using a top down approach. It has not gotten
very much attention but may offer a convenient structured approach and
generation of additional artifacts compared to other methods. Aim: The aim of
this exploratory study is to find out what benefits the privacy risk
elicitation method STPA-Priv has and to explain how the method can be used.
Method: Therefore we apply STPA-Priv to a real world health scenario that
involves a smart glucose measurement device used by children. Different kinds
of data from the smart device including location data should be shared with the
parents, physicians, and urban planners. This makes it a sociotechnical system
that offers adequate and complex privacy risks to be found. Results: We find
out that STPA-Priv is a structured method for privacy analysis and finds
complex privacy risks. The method is supported by a tool called XSTAMPP which
makes the analysis and its results more profound. Additionally, we learn that
an iterative application of the steps might be necessary to find more privacy
risks when more information about the system is available later. Conclusions:
STPA-Priv helps to identify complex privacy risks that are derived from
sociotechnical interactions in a system. It also outputs privacy constraints
that are to be enforced by the system to ensure privacy.Comment: author's post-prin
Optimal configuration of active and backup servers for augmented reality cooperative games
Interactive applications as online games and mobile devices have become more and more popular in recent years. From their combination, new and interesting cooperative services could be generated. For instance, gamers endowed with Augmented Reality (AR) visors connected as wireless nodes in an ad-hoc network, can interact with each other while immersed in the game. To enable this vision, we discuss here a hybrid architecture enabling game play in ad-hoc mode instead of the traditional client-server setting. In our architecture, one of the player nodes also acts as the server of the game, whereas other backup server nodes are ready to become active servers in case of disconnection of the network i.e. due to low energy level of the currently active server. This allows to have a longer gaming session before incurring in disconnections or energy exhaustion. In this context, the server election strategy with the aim of maximizing network lifetime is not so straightforward. To this end, we have hence analyzed this issue through a Mixed Integer Linear Programming (MILP) model and both numerical and simulation-based analysis shows that the backup servers solution fulfills its design objective
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Location-based and contextual mobile learning. A STELLAR Small-Scale Study
This study starts from several inputs that the partners have collected from previous and current running research projects and a workshop organised at the STELLAR Alpine Rendevous 2010. In the study, several steps have been taken, firstly a literature review and analysis of existing systems; secondly, mobile learning experts have been involved in a concept mapping study to identify the main challenges that can be solved via mobile learning; and thirdly, an identification of educational patterns based on these examples has been done.
Out of this study the partners aim to develop an educational framework for contextual learning as a unifying approach in the field. Therefore one of our central research questions is: how can we investigate, theorise, model and support contextual learning
Hedonic Coalition Formation for Distributed Task Allocation among Wireless Agents
Autonomous wireless agents such as unmanned aerial vehicles or mobile base
stations present a great potential for deployment in next-generation wireless
networks. While current literature has been mainly focused on the use of agents
within robotics or software applications, we propose a novel usage model for
self-organizing agents suited to wireless networks. In the proposed model, a
number of agents are required to collect data from several arbitrarily located
tasks. Each task represents a queue of packets that require collection and
subsequent wireless transmission by the agents to a central receiver. The
problem is modeled as a hedonic coalition formation game between the agents and
the tasks that interact in order to form disjoint coalitions. Each formed
coalition is modeled as a polling system consisting of a number of agents which
move between the different tasks present in the coalition, collect and transmit
the packets. Within each coalition, some agents can also take the role of a
relay for improving the packet success rate of the transmission. The proposed
algorithm allows the tasks and the agents to take distributed decisions to join
or leave a coalition, based on the achieved benefit in terms of effective
throughput, and the cost in terms of delay. As a result of these decisions, the
agents and tasks structure themselves into independent disjoint coalitions
which constitute a Nash-stable network partition. Moreover, the proposed
algorithm allows the agents and tasks to adapt the topology to environmental
changes such as the arrival/removal of tasks or the mobility of the tasks.
Simulation results show how the proposed algorithm improves the performance, in
terms of average player (agent or task) payoff, of at least 30.26% (for a
network of 5 agents with up to 25 tasks) relatively to a scheme that allocates
nearby tasks equally among agents.Comment: to appear, IEEE Transactions on Mobile Computin
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