Roberto Colella

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Feature selection becomes a central task when 'signature' profiles specific to a pathological status have to be extracted from high dimensional gene expression or proteomic data. In the present paper, we propose a feature selection method based on Singular Value Decomposition (SVD) and apply it to SELDI-TOF/MS proteomic data from a cohort of Type 2(More)
In the last few decades, sensor networks have received significant attention in the field of ambient intelligence (AmI) for surveillance and assisted living applications, as they provide a powerful tool to capture relevant information about environments and human activities. Mobile robots hold promise for enhancing the potential of sensor networks toward(More)
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