04 Contributo in atti di convegno

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04.01 Contributo in atti di convegno 13500
04.02 Abstract in Atti di convegno 2012
04.03 Poster 667

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Augmentation Techniques for Balancing Spatial Datasets in Machine and Deep Learning Applications

Thanks to the availability of a huge amount of spatial data, many new machine and deep learning (ML/DL) applications have emerged that are able to deal with such kind of information. In particular, new cost models have been developed with the aim of predicting the cost of spatial operations carefully. For obtaining good ML/DL models, the training activity is usually performed with synthetically generated datasets that capture as many spatial distributions as possible and as many combinations ...

VARADE: a Variational-based AutoRegressive model for Anomaly Detection on the Edge

Detecting complex anomalies on massive amounts of data is a crucial task in Industry 4.0, best addressed by deep learning. However, available solutions are computationally demanding, requiring cloud architectures prone to latency and bandwidth issues. This work presents VARADE, a novel solution implementing a light autoregressive framework based on variational inference, which is best suited for real-time execution on the edge. The proposed approach was validated on a robotic arm, part of a p...

Functional Neuroplasticity in Acute Diverticulitis: Differential Regulation of Colonic Excitatory Nerve Pathways By Cyclooxygenase Isoforms

Introduction. Prostanoids generated by cyclooxygenase isoforms (COX-1, COX-2) contribute to regulate intestinal motor functions. However, the role played by these pathways in human intestinal motility during inflammation is unknown. Objectives. This study examines the effects of COX inhibitors on excitatory neuromuscular activity of colonic tissues dissected from patients with acute diverticulitis (AD). Methods. Longitudinal muscle preparations were obtained from distal colon of patients und...

Who Should Pay for the Returns Product? The Effect of Transparency on Consumers’ Decision-making across the Reverse Supply Chain

The increasing volumes of consumer returns present a growing challenge for retailers, significantly impacting sustainability across all three dimensions of the triple bottom line: environmental, social, and economic. Concurrently, consumers are expressing increasing concerns about the environmental impact of returns. Given these concerns and the increasing involvement of consumers in logistics and supply chain management processes, it becomes imperative for retailers to consider empowering co...

AI for discovering the role of cognitive and brain reserves in Parkinson's Disease classification

This study explores the combined impact of cognitive and brain reserves with resting-state functional magnetic resonance imaging (rs-fMRI) based functional connectivity on Parkinson’s Disease (PD) classification. A machine learning pipeline is presented aimed at discriminating between 52 healthy controls and 43 subjects with PD using a support vector machine (SVM) classifier trained using a 5-fold cross-validation approach. Augmenting our approach with an eXplainable artificial intelligence (...

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