Marco Simonetti

Marco Simonetti
University of Florence | UNIFI · Dipartimento di Matematica e Informatica "Ulisse Dini"

About

38
Publications
3,770
Reads
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157
Citations
Introduction
Graduated in Electronic Engineering from the University of Bologna, with a thesis on transmission systems with a chaotic carrier. He worked in the Clinical Engineering sector and participated with a work team in the creation of automated systems for Health Administrations. He works as a high school teacher of Mathematics and is currently a PhD student in Computer Science at the University of Florence. His interests include Deep Learning , Neural Networks, Quantum Computing and Didactics of Math
Skills and Expertise
Additional affiliations
November 2019 - present
Università degli Studi di Perugia
Position
  • PhD Student

Publications

Publications (38)
Chapter
The Visual Snow Syndrome is a neurological condition that causes flickering dots to appear across a person’s entire field of vision. Those who suffer from this syndrome report seeing an unending stream of flickering dots throughout their visual field. Although patients often experience concurrent migraines, Visual Snow Syndrome appears to be a dist...
Chapter
The topic of quantum computing is one that is expanding quickly and has the potential to completely change how some difficult problems can be resolved. In recent years, there has been considerable advancement in the research and application of quantum computing technologies. The use of this technology to address challenging or impractical tasks for...
Chapter
The metaverse is an increasingly popular social interaction, gaming, and education platform. In recent years there has been a growing interest in the Metaverse by various commercial firms in order to promote economic transactions and the development of applications in the world of digital and virtual interaction. With the widespread adoption of the...
Article
Full-text available
The computing world is rapidly evolving and advancing, with new ground-breaking technologies emerging. Quantum Computing and Quantum Machine Learning have opened up new possibilities, providing unprecedented computational power and problem-solving capabilities while offering a deeper understanding of complex systems. Our research proposes new varia...
Preprint
Full-text available
We implemented a system able to locate people indoor, with the purpose of providing assistive services. Such approach is particularly important for the Art, for providing information on exhibitions, art galleries and museums, and to allow the access to the cultural heritage patrimony to people with disabilities. The system may provide also very imp...
Preprint
Full-text available
The experience of the COVID-19 pandemic, which has accelerated many chaotic processes in modern society, has highlighted in a very serious and urgent way the need to understand complex processes in order to achieve the common well-being. Modern High performance computing technologies, Quantum Computing, Computational Intelligence are shown to be ex...
Preprint
Full-text available
This paper introduces a deep learning system based on a quantum neural network for the binary classification of points of a specific geometric pattern (Two-Moons Classification problem) on a plane. We believe that the use of hybrid deep learning systems (classical + quantum) can reasonably bring benefits, not only in terms of computational accelera...
Chapter
Full-text available
Visual Snow Syndrome is a neurological disease that causes flashing dots to appear throughout the visual field. Patients claim to see an endless stream of flashing dots throughout their visual area. Although patients frequently experience concurrent migraine, visual snow appears to be a distinct phenomenon from prolonged migraine aura. VSS has been...
Chapter
Full-text available
The COVID-19 pandemic caused despair, poverty and, above all, pain and death across the planet. Nevertheless, there is no doubt that it has also given a strong global impetus to the digital world, asserting its importance, sustainability and richness of perspectives. With our work we intend to establish a set of best practices aimed at defining met...
Chapter
This paper introduces a deep learning system based on a quantum neural network for the binary classification of points of a specific geometric pattern (Two-Moons Classification problem) on a plane. We believe that the use of hybrid deep learning systems (classical + quantum) can reasonably bring benefits, not only in terms of computational accelera...
Article
Full-text available
The telerehabilitation of patients with neurological lesions has recently assumed significant importance due to the COVID-19 pandemic, which has reduced the possibility of access to healthcare facilities by patients. Therefore, the possibility of exercise for these patients safely in their own homes has emerged as an essential need. Our efforts aim...
Preprint
The use of games for non-ludic purposes, the serious games, is an interesting branch of science that has shown important results. With the advent of the pandemic that has made access to rehabilitation centres more problematic for patients with cognitive rehabilitation needs, the importance of being able to exercise these patients safely in their ow...
Article
Full-text available
This study analyses some of the leading technologies for the construction and configuration of IT infrastructures to provide services to users. For modern applications, guaranteeing service continuity even in very high computational load or network problems is essential. Our configuration has among the main objectives of being highly available (HA)...
Article
Full-text available
The pandemic has accelerated the process of digitization in many fields, highlighting some critical issues that have slowed the development of digital technologies in many areas. One of these is undoubtedly that of skills assessment, which on a digital platform is a more streamlined, reliable and faster process and allows some individuals from disa...
Chapter
The experience of the COVID-19 pandemic, which has accelerated many chaotic processes in modern society, has highlighted in a very serious and urgent way the need to understand complex processes in order to achieve the common well-being. Modern high performance computing technologies, quantum computing, computational intelligence are shown to be ex...
Preprint
This study analyses some of the leading technologies for the construction and configuration of IT infrastructures to provide services to users. For modern applications, guaranteeing service continuity even in very high computational load or network problems is essential. Our configuration has among the main objectives of being highly available (HA)...
Article
Full-text available
This paper provides a methodology for the production of synthetic images for training neural networks to recognise shapes and objects. There are many scenarios in which it is difficult, expensive and even dangerous to produce a set of images that is satisfactory for the training of a neural network. The development of 3D modelling software has nowa...
Preprint
This paper provides a methodology for the production of synthetic images for training neural networks to recognise shapes and objects. There are many scenarios in which it is difficult, expensive and even dangerous to produce a set of images that is satisfactory for the training of a neural network. The development of 3D modelling software has nowa...
Preprint
Full-text available
We present a sample implementation of a Virtual and Augmented Reality immersive environment based on Free and Libre Open Source Hardware and Software and the HTC Vive system, used to enhance the immersive experience of the user and to track her/his movements. The sense of immersion has increased and stimulated using a footplate and a Tibetan bridge...
Preprint
Full-text available
In this article we look at the potential of cloud containers and we provide some guidelines for companies and organisations that are starting to look at how to migrate their legacy infrastructure to something modern, reliable and scalable. We propose an architecture that has an excellent relationship between the cost of implementation and the benef...
Preprint
Full-text available
In this work we set out to find a method to classify protein structures using a Deep Learning methodology. Our Artificial Intelligence has been trained to recognize complex biomolecule structures extrapolated from the Protein Data Bank (PDB) database and reprocessed as images; for this purpose various tests have been conducted with pre-trained Conv...
Preprint
Full-text available
In the present work we intend to introduce a system based on VR (Virtual Reality) for examining analytical-geometric structures that occur in the study of mathematics and physics concepts in the last high school classes. In our opinion, an immersive study environment has several advantages over traditional two-dimensional environments (such as a bo...
Preprint
Full-text available
In this work we present a system based on a Deep Learning approach, by using a Convolutional Neural Network, capable of classifying protein chains of amino acids based on the protein description contained in the Protein Data Bank. Each protein is fully described in its chemical-physical-geometric properties in a file in XML format. The aim of the w...
Preprint
Full-text available
Medical data classification is typically a challenging task due to imbalance between classes. In this paper, we propose an approach to classify dermatoscopic images from HAM10000 (Human Against Machine with 10000 training images) dataset, consisting of seven imbalanced types of skin lesions, with good precision and low resources requirements. Class...
Preprint
Full-text available
The unexpected historical period we are living has abruptly pushed us to loosen any sort of interaction between individuals, gradually forcing us to deal with new ways to allow compliance with safety distances; indeed the present situation has demonstrated more than ever how critical it is to be able to properly organize our travel plans, put peopl...
Chapter
The unexpected historical period we are living has abruptly pushed us to loosen any sort of interaction between individuals, gradually forcing us to deal with new ways to allow compliance with safety distances; indeed the present situation has demonstrated more than ever how critical it is to be able to properly organize our travel plans, put peopl...
Chapter
In this work we set out to find a method to classify protein structures using a Deep Learning methodology. Our Artificial Intelligence has been trained to recognize complex biomolecule structures extrapolated from the Protein Data Bank (PDB) database and reprocessed as images; for this purpose various tests have been conducted with pre-trained Conv...
Chapter
In this article we look at the potential of cloud containers and we provide some guidelines for companies and organisations that are starting to look at how to migrate their legacy infrastructure to something modern, reliable and scalable. We propose an architecture that has an excellent relationship between the cost of implementation and the benef...
Chapter
Full-text available
In this work we introduce a learning system based on Virtual Reality and Augmented Reality for studying analytical-geometric structures that are part of the curriculum in mathematics and physics in high school classes. We believe that an immersive study environment has several advantages with respect to traditional two-dimensional environments (suc...
Article
Full-text available
In recent years, the need to contain healthcare costs due to the growing public debt of many countries, combined with the need to reduce costly travel by patients unable to move autonomously, have captured the attention of public administrators towards tele-rehabilitation. This trend has been consolidated overwhelmingly following the Covid-19 pande...
Preprint
Full-text available
In recent years, the need to contain healthcare costs due to the growing public debt of many countries, combined with the need to reduce costly travel by patients unable to move autonomously, have captured the attention of public administrators towards tele-rehabilitation. This trend has been consolidated overwhelmingly following the Covid-19 pande...
Chapter
Medical data classification is typically a challenging task due to imbalance between classes. In this paper, we propose an approach to classify dermatoscopic images from HAM10000 (Human Against Machine with 10000 training images) dataset, consisting of seven imbalanced types of skin lesions, with good precision and low resources requirements. Class...
Chapter
In this work we present a system based on a Deep Learning approach, by using a Convolutional Neural Network, capable of classifying protein chains of amino acids based on the protein description contained in the Protein Data Bank. Each protein is fully described in its chemical-physical-geometric properties in a file in XML format. The aim of the w...
Chapter
In this work we introduce a learning system based on VR (Virtual Reality) for studying analytical-geometric structures that are part of the curriculum in mathematics and physics high school classes. We believe that an immersive study environment has several advantages over traditional two-dimensional environments (such as a book or the simple scree...
Chapter
We present a sample implementation of a Virtual and Augmented Reality immersive environment based on Free and Libre Open Source Hardware and Software and the HTC Vive system, used to enhance the immersive experience of the user and to track her/his movements. The sense of immersion has increased and stimulated using a footplate and a Tibetan bridge...
Chapter
We implemented a system able to locate people indoor, with the purpose of providing assistive services. Such approach is particularly important for the Art, for providing information on exhibitions, art galleries and museums, and to allow the access to the cultural heritage patrimony to people with disabilities.
Chapter
NLP technologies and components have an increasing diffusion in mass analysis of text based dialogues, such as classifiers for sentiment polarity, trends clustering of online messages and hate speech detection. In this work we present the design and the implementation an automatic classification tool for the evaluation of the complexity of Italian...

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