University of the Aegean

About: University of the Aegean is a education organization based out in Mytilene, Greece. It is known for research contribution in the topics: Population & Context (language use). The organization has 2818 authors who have published 8100 publications receiving 179275 citations. The organization is also known as: UAEG.

Incentivized vehicle relocation in vehicle sharing systems

Abstract: The asymmetric demand-offer problem represents a major challenge for one-way vehicle sharing systems (VSS) affecting their economic viability as it necessitates the engagement of considerable human (and financial) resources in relocating vehicles to satisfy customer demand. In this paper, we propose a novel approach which involves user-based vehicle relocations to address supply-and-demand mismatches; in our approach, VSS users are offered price incentives so as to accept picking up their vehicle from an oversupplied station and/or to drop it off to an under-supplied station. The system incentivizes users based on the priorities of vehicle relocations among stations, taking into account the fluctuating demand for vehicles and parking places at different stations over time. A graph-theoretic approach is employed for modeling the problem of allocating vehicles to users in a way that maximizes the profit of the system taking into account the budget the VSS can afford to spend for rewarding users, as well as the users’ strategic behavior. We present two different schemes for incentivizing users to act in favour of the system. Both schemes consider budget constraints and are truthful and budget-feasible. We have extensively evaluated our approach through simulations which demonstrated significant gain with respect to the number of completed trips and system revenue. We have also validated our approach through pilot trials conducted in a free-floating e-motorbike sharing system in the framework of an EU-funded research project.

Learning to recognize webpage genres

Abstract: Webpages are mainly distinguished by their topic (eg, politics, sports etc) and genre (eg, blogs, homepages, e-shops, etc) Automatic detection of webpage genre could considerably enhance the ability of modern search engines to focus on the requirements of the user's information need In this paper, we present an approach to webpage genre detection based on a fully-automated extraction of the feature set that represents the style of webpages The features we propose (character n-grams of variable length and HTML tags) are language-independent and easily-extracted while they can be adapted to the properties of the still evolving web genres and the noisy environment of the web Experiments based on two publicly-available corpora show that the performance of the proposed approach is superior in comparison to previously reported results It is also shown that character n-grams are better features than words when the dimensionality increases while the binary representation is more effective than the term-frequency representation for both feature types Moreover, we perform a series of cross-check experiments (eg, training using a genre palette and testing using a different genre palette as well as using the features extracted from one corpus to discriminate the genres of the other corpus) to illustrate the robustness of our approach and its ability to capture the general stylistic properties of genre categories even when the feature set is not optimized for the given corpus

Hybrid trust and reputation management for sensor networks

Abstract: Wireless sensor networks are characterised by the distributed nature of their operation and the resource constraints on the nodes. Trust management schemes that are targeted at sensor networks need to be lightweight in terms of computational and communication requirements, yet powerful in terms of flexibility in managing trust between nodes of heterogeneous deployments. In this paper, we propose a trust management model that can uniformly support the needs of nodes with highly diverse network roles and capabilities, by exploiting the pre-deployment knowledge on the network topology and the information flows, and by allowing for flexibility in the trust establishment process. The model is hybrid, combining aspects from certificate-based and behaviour-based approaches on trust establishment on common evaluation processes and metrics. It enables controlled trust evolution based on network pre-configuration, and controlled trust revocation through the propagation of behaviour evaluation results made available by supervision networks. The proposed model and trust metrics have been validated through simulation. The results and analysis demonstrate its effectiveness in managing the trust relationships between nodes and clusters, while distributing the computational cost of trust evaluation operations.

Production of Added-Value Chemical Compounds through Bioconversions of Olive-Mill Wastewaters Blended with Crude Glycerol by a Yarrowia lipolytica Strain

Abstract: Olive mill wastewaters (OMW) are the major effluent deriving from olive oil production and are considered as one of the most challenging agro-industrial wastes to treat. Crude glycerol is the main by-product of alcoholic beverage and oleochemical production activities including biodiesel production. The tremendous quantities of glycerol produced worldwide represent a serious environmental challenge. The aim of this study was to assess the ability of Yarrowia lipolytica strain ACA-DC 5029 to grow on nitrogen-limited submerged shake-flask cultures, in crude glycerol and OMW blends as well as in media with high initial glycerol concentration and produce biomass, cellular lipids, citric acid and polyols. The rationale of using such blends was the dilution of concentrated glycerol by OMW to (partially or fully) replace process tap water with a wastewater stream. The strain presented satisfactory growth in blends; citric acid production was not affected by OMW addition (Citmax~37.0 g/L, YCit/Glol~0.55 g/g) and microbial oil accumulation raised proportionally to OMW addition (Lmax~2.0 g/L, YL/X~20% w/w). Partial removal of color (~30%) and phenolic compounds (~10% w/w) of the blended media occurred. In media with high glycerol concentration, a shift towards erythritol production was noted (Erymax~66.0 g/L, YEry/Glol~0.39 g/g) simultaneously with high amounts of produced citric acid (Citmax~79.0 g/L, YCit/Glol~0.46 g/g). Fatty acid analysis of microbial lipids demonstrated that OMW addition in blended media and in excess carbon media with high glycerol concentration favored oleic acid production.