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Institution

University of the Aegean

EducationMytilene, Greece
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.


Papers
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Journal ArticleDOI
TL;DR: A survey undertaken in Northern Greece has shown that organochlorine pesticides are present in the surface waters, including the isomers of hexachlorocyclohexane, aldrin, dieldrin and endosulfan sulfate.

165 citations

Journal ArticleDOI
TL;DR: The potential for one plant species to influence another indirectly via shared pollinators was greater for plants whose resources were more abundant (higher floral unit number and nectar sugar content) and more accessible.
Abstract: Co-flowering plant species commonly share flower visitors, and thus have the potential to influence each other's pollination. In this study we analysed 750 quantitative plant-pollinator networks from 28 studies representing diverse biomes worldwide. We show that the potential for one plant species to influence another indirectly via shared pollinators was greater for plants whose resources were more abundant (higher floral unit number and nectar sugar content) and more accessible. The potential indirect influence was also stronger between phylogenetically closer plant species and was independent of plant geographic origin (native vs. non-native). The positive effect of nectar sugar content and phylogenetic proximity was much more accentuated for bees than for other groups. Consequently, the impact of these factors depends on the pollination mode of plants, e.g. bee or fly pollinated. Our findings may help predict which plant species have the greatest importance in the functioning of plant-pollination networks.

165 citations

Journal ArticleDOI
TL;DR: This paper proposes a Support Vector Machines based classifier in comparison with Bayesian classifiers and Artificial Neural Networks for the prognosis and diagnosis of breast cancer disease and provides the implementation details along with the corresponding results.
Abstract: In recent years, computational diagnostic tools and artificial intelligence techniques provide automated procedures for objective judgments by making use of quantitative measures and machine learning techniques. In this paper we propose a Support Vector Machines (SVMs) based classifier in comparison with Bayesian classifiers and Artificial Neural Networks for the prognosis and diagnosis of breast cancer disease. The paper provides the implementation details along with the corresponding results for all the assessed classifiers. Several comparative studies have been carried out concerning both the prognosis and diagnosis problem demonstrating the superiority of the proposed SVM algorithm in terms of sensitivity, specificity and accuracy.

165 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present a conceptual framework that integrates various relevant port performance components in a way that can be used for a comprehensive port evaluation and adjustment of existing port governance models.
Abstract: This paper develops a conceptual framework that integrates various relevant port performance components in a way that can be used for a comprehensive port evaluation and adjustment of existing port governance models. The paper presents a synthesis of the literature on port governance models and port performance, arguing that the process of change is a dynamic one, and that the performance outcome of a reform process influences the next round of reforms. It also explores the potential for decomposing performance into two different, although related, port performances components, namely efficiency and effectiveness. Bringing into the analysis concepts like the need to integrate users’ satisfaction in port performance assessment, the paper explores the content of each of these components and their relationship. This discussion, along with empirical evidence provided by port authorities, leads to the conclusion that governance decisions, both at firm and government levels, are largely based on a very limited ...

164 citations

Journal ArticleDOI
TL;DR: A classification of the various methods of 3D mesh segmentation based on their corresponding underlying fundamental methodology concept as well as on the distinct criteria and features used in the segmentation process is given.
Abstract: D mesh segmentation is a fundamental process for Digital Shape Reconstruction in a variety of applications including Reverse Engineering, Medical Imaging, etc. It is used to provide a high level representation of the raw 3D data which is required for CAD, CAM and CAE. In this paper, we present an exhaustive overview of 3D mesh segmentation methodologies examining their suitability for CAD models. In particular, a classification of the various methods is given based on their corresponding underlying fundamental methodology concept as well as on the distinct criteria and features used in the segmentation process.

164 citations


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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202345
202292
2021479
2020493
2019543
2018447