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 & Tourism. The organization has 2818 authors who have published 8100 publications receiving 179275 citations. The organization is also known as: UAEG.

Towards a global participatory platform: Democratising open data, complexity science and collective intelligence

Abstract: The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted government, scientific or corporate elites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project’s own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of self-organization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed.

Cross-sectoral interactions of adaptation and mitigation measures

Abstract: Adaptation and mitigation are complementary strategies for addressing the impacts of climate change, yet are often considered separately. This paper examines the literature for evidence of the interactions of adaptation and mitigation measures across the agriculture, biodiversity, coasts, forests, urban and water sectors, focusing on Europe. It found that often adaptation and mitigation synergies and conflicts were not explicitly mentioned within a sector, let alone between sectors. Most measures, however, were found to have an effect on another sector, resulting in neutral, positive (synergies) or negative (conflicts) interactions within and between sectors. Many positive cross-sectoral interactions involved biodiversity or water and thus these could represent good starting places for the implementation of integrated, cross-sectoral strategies. Previous studies suggest that adaptation and mitigation are undertaken on different time and geographical scales; this study found many local scale measures which could facilitate integration between both adaptation and mitigation. It is important that cross-sectoral interaction of adaptation and mitigation measures are explicitly recognised if they are to be mainstreamed into policy, so that positive outcomes are enhanced and unintended consequences avoided.

Incorporating Social Interaction into Hybrid Choice Models

Abstract: The aim of this paper is to develop a methodological framework for the incorporation of social interaction effects into choice models. The developed method provides insights for modeling the effect of social interaction on the formation of psychological factors (latent variables) and on the decision-making process. The assumption is based on the fact that the way the decision maker anticipates and processes the information regarding the behavior and the choices exhibited in her/his social environment, affects her/his attitudes and perceptions, which in turn affect her/his choices. The proposed method integrates choice models with decision makers’ psychological factors and latent social interaction. The model structure is simultaneously estimated providing an improvement over sequential methods as it provides consistent and efficient estimates of the parameters. The methodology is tested within the context of a household aiming to identify the social interaction effects between teenagers and their parents regarding walking-loving behavior and then the effect of this on mode to school choice behavior. The sample consists of 9,714 participants aged from 12 to 18 years old, representing 21% of the adolescent population of Cyprus. The findings from the case study indicate that if the teenagers anticipate that their parents are walking lovers, then this increases the probability of teenagers to be walking-lovers too and in turn to choose walking to school. Generally, the findings from the application result in: a) improvements in the explanatory power of choice models, b) latent variables that are statistically significant, and c) a real-world behavioral representation that includes the social interaction effect.

A critical review of 13 years of mobile game-based learning

Abstract: With the increasing popularity of smartphones and tablets, game-based learning (GBL) is undergoing a rapid shift to mobile platforms. This transformation is driven by mobility, wireless interfaces, and built-in sensors that these smart devices offer in order to enable blended and context-sensitive mobile learning (m-Learning) activities. Thus, m-Learning is becoming more independent and ubiquitous (u-Learning). In order to identify and analyze the main trends and the future challenging issues involved in designing mGBL learning strategies, as well as to bring to the foreground important issues pertaining to mobile and context-aware ubiquitous GBL, the work at hand conducts a comprehensive survey of this particular area. Specifically, it introduces and applies a six-dimensional framework consisted of Spatio-temporal, Collaboration/Social, Session, Personalization, Data security & privacy, and Pedagogy, with the aim of scrutinizing the contributions in the field of mGBL published from 2004 to 2016. It was found that the transition to mGBL presents several difficulties, and therefore cannot be conceived as a simple and quick modification of existing GBL solutions. In this respect, this work is anticipated to foster the development of well-designed solutions that are intensive not only in their technological aspect, but in pedagogical qualities as well.

Influence of landscape context on the abundance and diversity of bees in Mediterranean olive groves

Abstract: The diversity and abundance of wild bees ensures the delivery of pollination services and the maintenance of ecosystem diversity. As previous studies carried out in Central Europe and the US have shown, bee diversity and abundance is influenced by the structure and the composition of the surrounding landscape. Comparable studies have so far not been carried out in the Mediterranean region. The present study examines the influence of Mediterranean landscape context on the diversity and abundance of wild bees. To do this, we sampled bees in 13 sites in olive groves on Lesvos Island, Greece. Bees were assigned to five categories consisting of three body size groups (small, medium and large bees), the single most abundant bee species (Lasioglossum marginatum) and all species combined. The influence of the landscape context on bee abundance and species richness was assessed at five radii (250, 500, 750, 1000 and 1250 m) from the centre of each site. We found that the abundance within bee groups was influenced differently by different landscape parameters and land covers, whereas species richness was unaffected. Generally, smaller bees’ abundance was impacted by landscape parameters at smaller scales and larger bees at larger scales. The land cover that influenced bee abundance positively was olive grove, while phrygana, conifer forest, broad-leaved forest, cultivated land, rock, urban areas and sea had mostly negative or no impact. We stress the need for a holistic approach, including all land covers, when assessing the effects of landscape context on bee diversity and abundance in the Mediterranean.