Efforts to realize video streaming over Mobile Ad hoc Networks (MANETs) meet many challenges, which are addressed by different techniques. In the highly dynamic and unpredictable environment of MANETs, cross-layer mechanisms seem to be the most suitable for optimising video streaming. This paper presents a survey of 44 studied papers on the area, comparing tools, parameters and metrics used for their evaluation. It also indicatively describes in more detail some of these proposals.
Health care domain have attracted considerable amount of research fields. One of the field that has a drastic focus on health care domain is data mining. Mainly health care system focuses on some data mining theories like classification, clustering etc.
Malignant melanoma represents the most dangerous type of skin cancer. In this study we present an ensemble classification scheme, employing the mutual information, the cross-correlation and the clustering based on proximity of image features methods, for early stage assessment of melanomas on plain photography images. The proposed scheme performs two main operations. First, it retrieves the most similar, to the unknown case, image samples from an available image database with verified benign moles and malignant melanoma cases. Second, it provides an automated estimation regarding the nature of the unknown image sample based on the majority of the most similar images retrieved from the available database. Clinical material comprised 75 melanoma and 75 benign plain photography images collected from publicly available dermatological atlases. Results showed that the ensemble scheme outperformed all other methods tested in terms of accuracy with 94.9 ± 1.5%, following an external cross-validation evaluation methodology. The proposed scheme may benefit patients by providing a second opinion consultation during the self-skin examination process and the physician by providing a second opinion estimation regarding the nature of suspicious moles that may assist towards decision making especially for ambiguous cases, safeguarding, in this way from potential diagnostic misinterpretations.
Most industries worldwide have entered a period of reaping the benefits and opportunities cloud offers. At the same time, many efforts are made to address engineering challenges for the secure development of cloud systems and software. With the majority of software engineering projects today relying on the cloud, the task to structure end-to-end secure-by-design cloud systems becomes challenging but at the same time mandatory. The PaaSword project has been commissioned to address security and data privacy in a holistic way by proposing a context-aware security-by-design framework to support software developers in constructing secure applications for the cloud. This chapter presents an overview of the PaaSword project results, including the scientific achievements as well as the description of the technical solution. The benefits offered by the framework are validated through two pilot implementations and conclusions are drawn based on the future research challenges which are discussed in a research agenda.
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