334 research outputs found

    OceanNETs Data Management Plan

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    This is the data management plan for the research project OceanNETs. It compiles OceanNETs research data output and describes the data handling during and after the projects duration with the aim to make OceanNETs research data FAIR – sustainably available for the scientific community. This data management plan is a living document; it will be continously developed in close cooperation with the consortium members throughout the project duration

    Counterfactual Building and Evaluation via eXplainable Support Vector Data Description

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    Increasingly in recent times, the mere prediction of a machine learning algorithm is considered insufficient to gain complete control over the event being predicted. A machine learning algorithm should be considered reliable in the way it allows to extract more knowledge and information than just having a prediction at hand. In this perspective, the counterfactual theory plays a central role. By definition, a counterfactual is the smallest variation of the input such that it changes the predicted behaviour. The paper addresses counterfactuals through Support Vector Data Description (SVDD), empowered by explainability and metric for assessing the counterfactual quality. After showing the specific case in which an analytical solution may be found (under Euclidean distance and linear kernel), an optimisation problem is posed for any type of distances and kernels. The vehicle platooning application is the use case considered to demonstrate how the outlined methodology may offer support to safety-critical applications as well as how explanation may shed new light into the control of the system at hand

    Long-term maintenance of the sea urchin Paracentrotus lividus in culture

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    Abstract The common sea urchin Paracentrotus lividus (Lamarck, 1816) is an important commercial species in the Mediterranean Sea for the consumption of its gonads (roe). This species has also long been used as an animal model in developmental biology and as an indicator in the assessment of environmental quality. In recent decades, the exploitation of this marine resource has become increasingly intensive, causing the depletion of wild stocks. The ripple effect observed in the laboratory use of this species has been the growing difficulty in finding valiant mature animals in the wild. We focused on the long-term maintenance of wild P. lividus and on the essential question of diet to maintain the animals and improve gonad development. The use of practical ration blocks which are nutrient-rich and show stability, easy storage and handling, resulted reduction in labor requirement and time for feeding streamlining the feeding practice. A significantly higher gonad production and a prolonged period of reproduction were obtained compared to wild caught individuals over the same period of time

    Dual-View Single-Shot Multibox Detector at Urban Intersections: Settings and Performance Evaluation

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    The explosion of artificial intelligence methods has paved the way for more sophisticated smart mobility solutions. In this work, we present a multi-camera video content analysis (VCA) system that exploits a single-shot multibox detector (SSD) network to detect vehicles, riders, and pedestrians and triggers alerts to drivers of public transportation vehicles approaching the surveilled area. The evaluation of the VCA system will address both detection and alert generation performance by combining visual and quantitative approaches. Starting from a SSD model trained for a single camera, we added a second one, under a different field of view (FOV) to improve the accuracy and reliability of the system. Due to real-time constraints, the complexity of the VCA system must be limited, thus calling for a simple multi-view fusion method. According to the experimental test-bed, the use of two cameras achieves a better balance between precision (68%) and recall (84%) with respect to the use of a single camera (i.e., 62% precision and 86% recall). In addition, a system evaluation in temporal terms is provided, showing that missed alerts (false negatives) and wrong alerts (false positives) are typically transitory events. Therefore, adding spatial and temporal redundancyincreases the overall reliability of the VCA system

    Research Data Management

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    Data Management Services

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    XNAT-PIC: Extending XNAT to Preclinical Imaging Centers

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    Molecular imaging generates large volumes of heterogeneous biomedical imagery with an impelling need of guidelines for handling image data. Although several successful solutions have been implemented for human epidemiologic studies, few and limited approaches have been proposed for animal population studies. Preclinical imaging research deals with a variety of machinery yielding tons of raw data but the current practices to store and distribute image data are inadequate. Therefore, standard tools for the analysis of large image datasets need to be established. In this paper, we present an extension of XNAT for Preclinical Imaging Centers (XNAT-PIC). XNAT is a worldwide used, open-source platform for securely hosting, sharing, and processing of clinical imaging studies. Despite its success, neither tools for importing large, multimodal preclinical image datasets nor pipelines for processing whole imaging studies are yet available in XNAT. In order to overcome these limitations, we have developed several tools to expand the XNAT core functionalities for supporting preclinical imaging facilities. Our aim is to streamline the management and exchange of image data within the preclinical imaging community, thereby enhancing the reproducibility of the results of image processing and promoting open science practices
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