Sara Manzoni

Università degli Studi di Milano-Bicocca | UNIMIB · Department of Computer Science, Systems and Communications

Infrared spectroscopy has proved to be a powerful tool for solving organic chemistry problems and finds a widening field in many industries. Infrared absorption and its relation to the molecular structure of organic material are discussed to give the essential background for detailed descriptions of techniques adopted in this work. Existing spectra...

Learning and training processes are starting to be affected by the diffusion of Artificial Intelligence (AI) techniques and methods. AI can be variously exploited for supporting education, though especially deep learning (DL) models are normally suffering from some degree of opacity and lack of interpretability. Explainable AI (XAI) is aimed at cre...

Advances in Near-infrared (NIR) spectroscopy technology led to an increase of interest in its applications in various industries due to its powerful non-destructive quantization tool. In this work, we used a one-dimensional CNN to determine simultaneously quantities of organic materials in a mixture using their NIR infrared spectra. The coefficient...

As the worldwide population gets increasingly aged, in-home telemedicine and mobile-health solutions represent promising services to promote active and independent aging and to contribute to a paradigm shift towards patient-centric healthcare. In this work, we present ACTA (Advanced Cognitive Training for Aging), a prototype mobile-health solution...

Objective: To evaluate the impact on Electroencephalography (EEG) classification of different kinds of attention mechanisms in Deep Learning (DL) models. Methods: We compared three attention-enhanced DL models, the brand-new InstaGATs, an LSTM with attention and a CNN with attention. We used these models to classify normal and abnormal (i.e., artif...

Conscious and functional use of online social spaces can support the elderly with mind cognitive impairment (MCI) in their daily routine, not only for systematic monitoring, but to achieve effective targeted engagement. In this sense, although social involvement can be obtained when elder’s experiences, interests, and goals are shared and accepted...

Emerging studies in the deep learning community focus on techniques aimed to identify which part of a graph can be suitable for making better decisions and best contributes to an accurate inference. These researches (i.e., “attentional mechanisms” for graphs) can be applied effectively in all those situations in which it is not trivial to capture d...

Recent studies in the context of machine learning have shown the effectiveness of deep attentional mechanisms for identifying important communities and relationships within a given input network. These studies can be effectively applied in those contexts where capturing specific dependencies, while downloading useless content, is essential to take...

[This corrects the article DOI: 10.3389/fnins.2019.00807.].

Mind Cognitive Impairment is one of the most common clinical manifestations affecting the elderly. In this paper, we report the work in progress (in the frame of our SENIOR project) to provide elderly with new Nudge theory driven advices for influencing their interest to a conscious and functional participation to “targeted” social communities wher...

Patients who survive brain injuries may develop Disorders of Consciousness (DOC) such as Coma, Vegetative State (VS) or Minimally Conscious State (MCS). Unfortunately, the rate of misdiagnosis between VS and MCS due to clinical judgment is high. Therefore, diagnostic decision support systems aiming to correct any differentiation between VS and MCS...

The identification of cohesive communities (dense subgraphs) is a typical task applied to the analysis of social and biological networks. Different definitions of communities have been adopted for particular occurrences. One of these, the 2-club (dense subgraphs with diameter value at most of length 2) has been revealed of interest for applications...

The paper presents an ongoing research within a multidisciplinary collaboration aiming at improving information and tools to prepare local authorities, volunteers and citizens (at a municipal and/or inter-municipal level) to anticipate, cope with, resist against and recover from the impacts of hydro-geological hazards. In particular, the paper aims...

The paper presents a Multi Agent Systems (MAS) approach to crowd modelling, based on the Situated Cellular Agents (SCA) model. This is a special class of Multilayered Multi Agent Situated System (MMASS), rooted on Cellular Automata, providing an explicit spatial representation and the definition of adjacency geometries. The model also defines a con...