4,076 research outputs found

    Stable determination of an immersed body in a stationary Stokes fluid

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    We consider the inverse problem of the detection of a single body, immersed in a bounded container filled with a fluid which obeys the Stokes equations, from a single measurement of force and velocity on a portion of the boundary. We obtain an estimate of stability of log-log type.Comment: 30 page

    Improving the predictability of take-off times with Machine Learning : a case study for the Maastricht upper area control centre area of responsibility

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    The uncertainty of the take-off time is a major contribution to the loss of trajectory predictability. At present, the Estimated Take-Off Time (ETOT) for each individual flight is extracted from the Enhanced Traffic Flow Management System (ETFMS) messages, which are sent each time there is an event triggering a recalculation of the flight data by the Network Man- ager Operations Centre. However, aircraft do not always take- off at the ETOTs reported by the ETFMS due to several factors, including congestion and bad weather conditions at the departure airport, reactionary delays and air traffic flow management slot improvements. This paper presents two machine learning models that take into account several of these factors to improve the take- off time prediction of individual flights one hour before their estimated off-block time. Predictions performed by the model trained on three years of historical flight and weather data show a reduction on the take-off time prediction error of about 30% as compared to the ETOTs reported by the ETFMS.Peer ReviewedPostprint (published version

    Determining interaction rules in animal swarms

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    In this paper we introduce a method for determining local interaction rules in animal swarms. The method is based on the assumption that the behavior of individuals in a swarm can be treated as a set of mechanistic rules. The principal idea behind the technique is to vary parameters that define a set of hypothetical interactions to minimize the deviation between the forces estimated from observed animal trajectories and the forces resulting from the assumed rule set. We demonstrate the method by reconstructing the interaction rules from the trajectories produced by a computer simulation.Comment: v3: text revisions to make the article more comprehensibl

    Metacognition in schizophrenia disorders: Comparisons with community controls and bipolar disorder: Replication with a Spanish language Chilean sample

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    Metacognition refers to the activities which allow for the availability of a sense of oneself and others in the moment. Research mostly in North America with English-speaking samples has suggested that metacognitive deficits are present in schizophrenia and are closely tied to negative symptoms. Thus, replication is needed in other cultures and groups. The present study accordingly sought to replicate these findings in a Spanish speaking sample from Chile. Metacognition and symptoms were assessed among 26 patients with schizophrenia, 26 with bipolar disorder and 36 community members without serious mental illness. ANCOVA controlling for age and education revealed that the schizophrenia group had greater levels of metacognitive deficits than the bipolar disorder and community control groups. Differences in metacognition between the clinical groups persisted after controlling for symptom levels. Spearman correlations revealed a unique pattern of associations of metacognition with negative and cognitive symptoms. Results largely support previous findings and provide added evidence of the metacognitive deficits present in schizophrenia and the link to outcome cross culturally. Implications for developing metacognitively oriented interventions are discussed

    GP-Unet: Lesion Detection from Weak Labels with a 3D Regression Network

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    We propose a novel convolutional neural network for lesion detection from weak labels. Only a single, global label per image - the lesion count - is needed for training. We train a regression network with a fully convolutional architecture combined with a global pooling layer to aggregate the 3D output into a scalar indicating the lesion count. When testing on unseen images, we first run the network to estimate the number of lesions. Then we remove the global pooling layer to compute localization maps of the size of the input image. We evaluate the proposed network on the detection of enlarged perivascular spaces in the basal ganglia in MRI. Our method achieves a sensitivity of 62% with on average 1.5 false positives per image. Compared with four other approaches based on intensity thresholding, saliency and class maps, our method has a 20% higher sensitivity.Comment: Article published in MICCAI 2017. We corrected a few errors from the first version: padding, loss, typos and update of the DOI numbe

    Landing together: how flocks arrive at a coherent action in time and space in the presence of perturbations

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    Collective motion is abundant in nature, producing a vast amount of phenomena which have been studied in recent years, including the landing of flocks of birds. We investigate the collective decision making scenario where a flock of birds decides the optimal time of landing in the absence of a global leader. We introduce a simple phenomenological model in the spirit of the statistical mechanics-based self-propelled particles (SPP-s) approach to interpret this process. We expect that our model is applicable to a larger class of spatiotemporal decision making situations than just the landing of flocks (which process is used as a paradigmatic case). In the model birds are only influenced by observable variables, like position and velocity. Heterogeneity is introduced in the flock in terms of a depletion time after which a bird feels increasing bias to move towards the ground. Our model demonstrates a possible mechanism by which animals in a large group can arrive at an egalitarian decision about the time of switching from one activity to another in the absence of a leader. In particular, we show the existence of a paradoxical effect where noise enhances the coherence of the landing process.Comment: 15 pages, 7 figure
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