Vision-Based Production of Personalized Video

In this paper we present a novel vision-based system for the automated production of personalised video souvenirs for visitors in leisure and cultural heritage venues. Visitors are visually identified and tracked through a camera network. The system produces a personalized DVD souvenir at the end of a visitor’s stay allowing visitors to relive their experiences. We analyze how we identify visitors by fusing facial and body features, how we track visitors, how the tracker recovers from failures due to occlusions, as well as how we annotate and compile the final product. Our experiments demonstrate the feasibility of the proposed approach

Neural network-based colonoscopic diagnosis using on-line learning and differential evolution

In this paper, on-line training of neural networks is investigated in the context of computer-assisted colonoscopic diagnosis. A memory-based adaptation of the learning rate for the on-line back-propagation (BP) is proposed and used to seed an on-line evolution process that applies a differential evolution (DE) strategy to (re-) adapt the neural network to modified environmental conditions. Our approach looks at on-line training from the perspective of tracking the changing location of an approximate solution of a pattern-based, and thus, dynamically changing, error function. The proposed hybrid strategy is compared with other standard training methods that have traditionally been used for training neural networks off-line. Results in interpreting colonoscopy images and frames of video sequences are promising and suggest that networks trained with this strategy detect malignant regions of interest with accuracy

HARMONIA: strategy of an integrated resilience assessment platform (IRAP) with available tools and geospatial services

The huge amount of the available data nowadays has raised some major challenges which are related to the storage, fusion, structure, streaming and processing of these data. In this paper, we present the development of a holistic framework, entitled HARMONIA, that encompasses State-of-The-Art solutions for the emerging issues related to Climate Change, natural and/or man-made hazards and urban/peri-urban risks. The Horizon 2020 HARMONIA project is developing an Integrated Resilience Assessment Platform (IRAP) which plans to provide targeted services for different groups of end-users. In particular, it will actively support urban decision-makers in strategic decisions and planning and citizens in facing daily effects and risks of Climate Change. Additionally, the platform will be a place to interconnect cities which end up facing similar Climate Change effects. HARMONIA IRAP leverages cuttingedge technologies (i.e., explainable Artificial Intelligence, Data Mining, multi-criteria analysis, dynamic programming) and services (ie., Virtual Machines, Containers) in order to provide solutions considering the complexity and diversity of extreme earth and non-earth data. In addition, this platform includes a Decision Support System providing early-warning feedback and recommendations to the end-users. In this way the HARMONIA IRAP design tends to address these challenges by offering the corresponding dynamic, scalable and robust mechanisms with the aim to provide useful integrated tools for the related users. Datacubes architecture, which is a major part of the IRAP, offers the opportunity to investigate more sophisticated correlations among the data and provide a more tangible representation of the extracted information

An evaluation study of clustering algorithms in the scope of user communities assessment

AbstractIn this paper, we provide the results of ongoing work in Magnet Beyond project, regarding social networking services. We introduce an integrated social networking framework through the definition or the appropriate notions and metrics. This allows one to run an evaluation study of three widely used clustering methods (k-means, hierarchical and spectral clustering) in the scope of social groups assessment and in regard to the cardinality of the profile used to assess users’ preferences. Such an evaluation study is performed in the context of our service requirements (i.e. on the basis of equal-sized group formation and of maximization of interests’ commonalities between users within each social group). The experimental results indicate that spectral clustering, due to the optimization it offers in terms of normalized cut minimization, is applicable within the context of Magnet Beyond socialization services. Regarding profile’s cardinality impact on the system performance, this is shown to be highly dependent on the underlying distribution that characterizes the frequency of user preferences appearance. Our work also incorporates the introduction of a heuristic algorithm that assigns new users that join the service into appropriate social groups, once the service has been initialized and the groups have been assessed using spectral clustering. The results clearly show that our approach is able to adhere to the service requirements as new users join the system, without the need of an iterative spectral clustering application that is computationally demanding

Exercise as a mean to reverse the detrimental effect of high-fat diet on bone’s fracture characteristics

The aim of this study is to investigate whether exercise can reverse some of the adverse effects of high-fat-diet-induced obesity on lipid metabolism and bone biomechanical properties. A total of 26 adult male C57bl/6J mice were randomly assigned into three groups: (A) Control group (n=6), (B) High-fat diet group (n=10), (C) High-fat diet and exercise group (n=10). Body mass and relevant biochemical parameters were measured for the duration of the experimental protocol (37 weeks). Mechanical strength of both femurs of each animal was assessed in-vitro based on three point bending tests. It was revealed that exposure to high-fat diet led to significant increase of body mass and cholesterol levels and also to substantial changes in bone morphology and strength. Ultimate stress for the animals exposed to high-fat diet and those exposed to high-fat-diet and exercise was 25% and 24% lower compared to control, respectively. Exercise increased bone thickness by 15% compared to animals that were not exposed to exercise. It was concluded that high-fat-diet appears to have a detrimental effect on bone biomechanics and strength. Exercise reversed the reduction in bone thickness that appears to be induced by high-fat diet. However no statistically significant increase in bone strength was observed

Correlation between mesenteric fat thickness and serum apolipoproteins in patients with peripheral arterial occlusive disease

BACKGROUND: Visceral fat possesses the most detrimental potential for cardiovascular morbidity through the release of adipokines, as well as metabolic and proinflammatory mediators, which adversely affect metabolic and vascular homeostasis. Among the different types of visceral adipose tissue, mesenteric fat is considered particularly detrimental, due to its close proximity to the portal circulation, affecting directly the liver, which is the main regulator of body metabolic homeostasis. Mesenteric fat can be reliably estimated using abdominal ultrasonography, the only available imaging method able to depict individual mesenteric leaves. Aim of the present study was to investigate the correlation of mesenteric fat thickness (MFT) with serum apolipoprotein levels in patients undergoing digital subtraction angiography in a single center. METHODS: 35 male patients with peripheral arterial disease were examined. After careful examination of the periumbilical area, the mesenteric leaves were identified. The maximal distance between each pair of sequential leaves was measured, and the mean value of the three thickest leaves was determined as the mesenteric fat thickness. Six apolipoprotein fasting serum concentrations were measured using a Luminex proteomics platform (xMAP Multiplex immunoassay): apolipoprotein A-I (apoAI), apolipoprotein A-II (apoAII), apolipoprotein B (apoB), apolipoprotein C-II (apoCII), apolipoprotein C-III (apoCIII) and apolipoprotein E (apoE). RESULTS: MFT correlated with apoAII and apoB serum concentrations. The correlations with apoAII and apoB remained significant following correction for BMI. No correlations were noted between MFT and serum apoAI, apoCII, apoCIII or apoE levels before or after adjustment for BMI. CONCLUSIONS: Our study indicates that MFT is significantly correlated with the concentration of atherogenic low density lipoproteins particles, as well as with apoAII, a determinant of free fatty acids levels. No correlation was observed between mesenteric fat thickness and very low density lipoprotein or chylomicron particles concentration

STAMINA: Bioinformatics Platform for Monitoring and Mitigating Pandemic Outbreaks

Data Availability Statement: All data driven applications used the our world in data COVID-19 datasets, complimented by proprietary datasets share by the STAMINA consortium.Copyright © 2022 by the authors. This paper presents the components and integrated outcome of a system that aims to achieve early detection, monitoring and mitigation of pandemic outbreaks. The architecture of the platform aims at providing a number of pandemic-response-related services, on a modular basis, that allows for the easy customization of the platform to address user’s needs per case. This customization is achieved through its ability to deploy only the necessary, loosely coupled services and tools for each case, and by providing a common authentication, data storage and data exchange infrastructure. This way, the platform can provide the necessary services without the burden of additional services that are not of use in the current deployment (e.g., predictive models for pathogens that are not endemic to the deployment area). All the decisions taken for the communication and integration of the tools that compose the platform adhere to this basic principle. The tools presented here as well as their integration is part of the project STAMINA.The paper presented is based on research undertaken as part of the European Commission-funded project STAMINA (Grant Agreement 883441)