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.

On the Typical Statistic Features for Image Blind Steganalysis

Abstract: Multimedia content is a suitable carrier for secret communication. This paper focuses on the steganalysis technique which aims to get the forensic of secrecy existing in multimedia carriers. A key concern for designing a blind steganalysis algorithm is the selection of statistic features. The Probability Density Function (PDF) moment and Characteristic Function (CF) moment are two typical kinds of statistic features commonly used in blind steganalysis. And generally, the features are computed from the subbands of transform domains, such as the wavelet coefficient subbands, the prediction subbands of wavelet coefficients, the prediction error subbands of wavelet coefficients, the wavelet coefficient subbands of image noise, and the log prediction error subbands of wavelet coefficients. To decide which feature is more sensitive to message embedding and useful for steganalysis is important and urgent. Till now, few works have focused on this topic, and they can only give some experimental results without theoretical analysis. Additionally, few frequency subbands have been investigated. To solve this problem, this paper reviews existing feature computing algorithms, compares the two kinds of features, the PDF moments and the CF moments, by analyzing the change trends of the statistic distribution parameters of various frequency subbands before and after message embedding, and so that provides a theoretical basis for the steganalysis feature selection and extraction. These theoretical results are further confirmed by experimental results. This is the first work to provide thorough theoretical analysis on so many feature computing algorithms. It is expected to provide valuable information to researchers or engineers working in the field of steganography forensics or steganalysis.

Space invaders; biological invasions in marine conservation planning

Abstract: Aim Biological invasions are major contributors to global change and native biodiversity decline. However, they are overlooked in marine conservation plans. Here, we examine for the first time the extent to which marine conservation planning research has addressed (or ignored) biological invasions. Furthermore, we explore the change of spatial priorities in conservation plans when different approaches are used to incorporate the presence and impacts of invasive species. Location Global analysis with a focus on the Mediterranean Sea region. Methods We conducted a systematic literature review consisting of three steps: (1) article selection using a search engine, (2) abstract screening and (3) review of pertinent articles, which were identified in the second step. The information extracted included the scale and geographical location of each case study as well as the approach followed regarding invasive species. We also applied the software Marxan to produce and compare conservation plans for the Mediterranean Sea that either protect, or avoid areas impacted by invasives, or ignore the issue. One case study focused on the protection of critical habitats, and the other on endemic fish species. Results We found that of 119 papers on marine spatial plans in specific biogeographic regions, only three (2.5%) explicitly took into account invasive species. When comparing the different conservation plans for each case study, we found that the majority of selected sites for protection (ca. 80%) changed in the critical habitat case study, while this proportion was lower but substantial (27%) in the endemic fish species case study. Main conclusions Biological invasions are being widely disregarded when planning for conservation in the marine environment across local to global scales. More explicit consideration of biological invasions can significantly alter spatial conservation priorities. Future conservation plans should explicitly account for biological invasions to optimize the selection of marine protected areas.

Search for new non-resonant phenomena in high-mass dilepton final states with the ATLAS detector

Abstract: A search for new physics with non-resonant signals in dielectron and dimuon final states in the mass range above 2 TeV is presented. This is the first search for non-resonant signals in dilepton fi ...

Characterization of digital medical images utilizing support vector machines.

Abstract: In this paper we discuss an efficient methodology for the image analysis and characterization of digital images containing skin lesions using Support Vector Machines and present the results of a preliminary study. The methodology is based on the support vector machines algorithm for data classification and it has been applied to the problem of the recognition of malignant melanoma versus dysplastic naevus. Border and colour based features were extracted from digital images of skin lesions acquired under reproducible conditions, using basic image processing techniques. Two alternative classification methods, the statistical discriminant analysis and the application of neural networks were also applied to the same problem and the results are compared. The SVM (Support Vector Machines) algorithm performed quite well achieving 94.1% correct classification, which is better than the performance of the other two classification methodologies. The method of discriminant analysis classified correctly 88% of cases (71% of Malignant Melanoma and 100% of Dysplastic Naevi), while the neural networks performed approximately the same. The use of a computer-based system, like the one described in this paper, is intended to avoid human subjectivity and to perform specific tasks according to a number of criteria. However the presence of an expert dermatologist is considered necessary for the overall visual assessment of the skin lesion and the final diagnosis.

Extraction of Antioxidant Phenolics from Agri-Food Waste Biomass Using a Newly Designed Glycerol-Based Natural Low-Transition Temperature Mixture: A Comparison with Conventional Eco-Friendly Solvents

Abstract: A novel natural low transition temperature mixture (LTTM), composed of glycerol and ammonium acetate (molar ratio 3:1), was tested for its efficacy as a solvent in recovering phenolics from chlorogenate-rich agri-food solid wastes, including potato peels (PPs), eggplant peels (EPPs), and spent filter coffee (SFC). The efficacy of this solvent was compared with other eco-friendly solvents, including aqueous glycerol, aqueous ethanol, and water. The LTTM was demonstrated to be by far the most efficient in extracting chlorogenates and superior or equally efficient with the other solvents in recovering flavonoids. LTTM extracts produced from waste were also more potent radical scavengers, but results on the reducing power were inconclusive. Liquid chromatography-diode array-mass spectrometry analysis showed that the polyphenolic profiles of all waste extracts obtained with the LTTM were rich in caffeoylquinic and p-coumaroylquinic acid conjugates.