Data extraction, retrieval and visualization are some of the key points in Digital Humanities, and together they cover most of the challenges of this field of study, requiring multidisciplinary knowledge. The fruition by users is still today compromised by limited user experiences, problems of...
04b Atto di convegno in volume
-
-
Recent years witnessed a growing interest in the employment of intelligent techniques for the management of manufacturing processes in smart manufacturing. These processes may include tens of resources distributed among several different companies composing the supply chain. The status of the...
-
In recent years, there has been an increase interest in using intelligent methods to control manufacturing processes. Tens of resources to be modeled and offered as services through Industrial APIs, may be used in these processes and orchestrated throughout the various supply chain companies. The...
-
Behavioural Cloning is a Machine Learning method concerning how a machine attempts to autonomously mimic the actions of a human, or in general a complex controller, performing a given task. This work innovatively exploits Behavioural Cloning in support of Pediatric Neurorehabilitation. In...
-
In this work we consider the solution of large scale (possibly nonconvex) unconstrained optimization problems. We focus on Truncated Newton methods which represent one of the commonest methods to tackle such problems. In particular, we follow the approach detailed in Caliciotti et al. (Comput Optim...
-
This extended abstract summarizes our recent work in which we study a dynamic Controlled Query Evaluation method over Description Logic ontologies.
-
Analysing visitors’ behaviour in museums and cultural sites is a key element to manage spaces and artworks arrangement. Museum stakeholders and curators may benefit from technology to improve the visit experience. This paper presents the preliminary results of the ARTEMISIA project, which aims to...
-
One major limitation to the applicability of Reinforcement Learning (RL) to many practical domains is the large number of samples required to learn an optimal policy. To address this problem and improve learning efficiency, we consider a linear hierarchy of abstraction layers of the Markov Decision...
-
Brain-Computer Interfaces based on Motor Imagery (MI-BCI) have been validated as promising systems to support rehabilitative protocols for the post-stroke motor recovery of the upper limb. To date, the long-term effects of MI-BCI training in post-stroke patients need to be clarified. In order to...
-
Group level characterization of brain networks still represents an open issue in modern neuroscience. Investigating the functional mechanisms underlying the complexity of the human brain requires an analytical way to efficiently integrate information from multiple subjects, while properly handling...