University of Piraeus

About: University of Piraeus is a education organization based out in Piraeus, Attiki, Greece. It is known for research contribution in the topics: Context (language use) & Computer science. The organization has 1731 authors who have published 6209 publications receiving 106699 citations.

User recruitment for mobile crowdsensing over opportunistic networks

Abstract: We look into the realization of mobile crowdsensing campaigns that draw on the opportunistic networking paradigm, as practised in delay-tolerant networks but also in the emerging device-to-device communication mode in cellular networks. In particular, we ask how mobile users can be optimally selected in order to generate the required space-time paths across the network for collecting data from a set of fixed locations. The users hold different roles in these paths, from collecting data with their sensing-enabled devices to relaying them across the network and uploading them to data collection points with Internet connectivity. We first consider scenarios with deterministic node mobility and formulate the selection of users as a minimum-cost set cover problem with a submodular objective function. We then generalize to more realistic settings with uncertainty about the user mobility. A methodology is devised for translating the statistics of individual user mobility to statistics of spacetime path formation and feeding them to the set cover problem formulation. We describe practical greedy heuristics for the resulting NP-hard problems and compute their approximation ratios. Our experimentation with real mobility datasets (a) illustrates the multiple tradeoffs between the campaign cost and duration, the bound on the hopcount of space-time paths, and the number of collection points; and (b) provides evidence that in realistic problem instances the heuristics perform much better than what their pessimistic worst-case bounds suggest.

Cross-Country Effects in Herding Behaviour: Evidence from Four South European Markets

Abstract: This study provides comprehensive evidence testing for the existence of herding effects in the Portuguese, Italian, Spanish and Greek market, constructing a survivor-bias-free dataset of daily stock returns during the period January 1998 - December 2008. Moreover, it examines the potential asymmetries of herding effects with respect to the sign of the market return, trading activity and volatility. A novel feature of this study, with implications for financial stability in the Eurozone and international portfolio diversification, is to examine whether the cross-sectional dispersion of returns in one market is affected by the cross-sectional dispersion of returns in the rest three markets. Finally, it tests whether herding effects became more intense during the recent global financial crisis of 2007-2008.

The impact of internet use on air pollution: Evidence from emerging countries.

Abstract: The goal of this study is to analyze the impact of Internet use, employed as a proxy for information and communications technologies (ICTs), on CO2 emissions. Using a panel of 20 emerging economies spanning the period 1990 to 2015, this paper finds that increased Internet access results in lower levels of air pollution. Moreover, panel causality test results highlight a unidirectional causality running from Internet use to CO2 emissions. This result also has crucial policy implications for the governments in emerging markets. For instance, increased investment in the ICT sector could be a plausible channel to reduce air pollution level.

Person identification based on parametric processing of the EEG

Abstract: Person identification based on parametric spectral analysis of the EEG signal is addressed in this work-a problem that has not yet been seen in a signal-processing framework, to the best of our knowledge. AR parameters are estimated from a signal containing only the alpha, rhythm activity of the EEG. These parameters are used as features in the classification step, which employs a learning vector quantizer network. The proposed method was applied on a set of real EEG recordings made on healthy individuals, in an attempt to experimentally investigate the connection between a person's EEG and genetically-specific information. Correct classification scores at the range of 72% to 84% show the potential of our approach for person classification/identification and are in agreement with previous research showing evidence that the EEG carries genetic information.