Monica Mordonini

• University of Parma

Background: Management of operating rooms is a critical point in health care organizations because surgical departments represent a significant cost in hospital budgets. Therefore, it is increasingly important that there is effective planning of elective, emergency, and day surgery and optimization of both the human and physical resources availabl...

BACKGROUND Management of operating rooms is a critical point in health care organizations because surgical departments represent a significant cost in hospital budgets. Therefore, it is increasingly important that there is effective planning of elective, emergency, and day surgery and optimization of both the human and physical resources available,...

During the pandemic, a consortium of libraries in the Milan area (Italy) interviewed the community and applied sentiment analysis to quickly understand the community’s feelings toward online services. The model compares both sentiment analysis and topic detection using algorithms that identify sentiments and topics. The results highlight the prefer...

Detecting anomalous data within time series is a very relevant task in pattern recognition and machine learning, with many possible applications that range from disease prevention in medicine, e.g., detecting early alterations of the health status before it can clearly be defined as "illness" up to monitoring industrial plants. Regarding this latte...

Background Risk stratification plays a central role in anesthetic evaluation. The use of Big Data and machine learning (ML) offers considerable advantages for collection and evaluation of large amounts of complex health-care data. We conducted a systematic review to understand the role of ML in the development of predictive post-surgical outcome mo...

Operating rooms management is a critical point in healthcare organizations; inefficient scheduling and allocation of human and physical resources are often present. This study aims to automatically collect data from a real surgical scenario to develop an integrated technological-organizational model that optimizes the operating block resources.Each...

The General Data Protection Regulation (GDPR) has allowed EU citizens and residents to have more control over their personal data, simplifying the regulatory environment affecting international business and unifying and homogenising privacy legislation within the EU. This regulation affects all companies that process data of European residents rega...

Social networking systems can be considered one of the most important social phenomena because they succeeded in involving billions of people all around the world and in attracting users from several social groups, regardless of age, gender, education, or nationality. Social networking systems blur the distinction between the private and working sp...

Why and how more and more people get involved and use social networking systems are critical topics in social network analysis (SNA). As a matter of fact, social networking systems bring online a growing number of acquaintances, for many different purposes. Both business interests and personal recreational goals are motivations for using online soc...

Modeling and forecasting the spread of COVID-19 remains an open problem for several reasons. One of these concerns the difficulty to model a complex system at a high resolution (fine-grained) level at which the spread can be simulated by taking into account individual features such as the social structure, the effects of the governments' policies,...

In the knowledge discovery field of the Big Data domain the analysis of geographic positioning and mobility information plays a key role. At the same time, in the Natural Language Processing (NLP) domain pre-trained models such as BERT and word embedding algorithms such as Word2Vec enabled a rich encoding of words that allows mapping textual data i...

This paper proposes a literature review about the usage of simulation-based optimization tools in hospital environment and, more precisely, for operating rooms management. The usage of simulation, in its various forms, is gaining increasing attention in healthcare management because of its capability of describing the system in a high degree of det...

This work proposes the development and testing of three machine learning technique for demand forecasting in the automotive industry: Artificial Neural Network (ANN) and two types of Ensemble Learning models, i.e. AdaBoost and Gradient Boost. These models demonstrate the great potential that machine learning has over traditional demand forecasting...

A complex system can be composed of inherent dynamical structures, i.e., relevant subsets of variables interacting tightly with one another and loosely with other subsets. In the literature, some effective methods to identify such relevant sets rely on the so-called Relevance Indexes (RIs), measuring subset relevance based on information theory pri...

This article describes the current landscape in the fields of social media and socio-technical systems. In particular, it analyzes the different ways in which social media are adopted in organizations, workplaces, educational and smart environments. One interesting aspect of this integration, is the use of social media for members’ participation an...

The phenomenon of “trolling” in social networks is becoming a very serious threat to the online presence of people and companies, since it may affect ordinary people, public profiles of brands, as well as popular characters. In this paper, we present a novel method to preprocess the temporal data describing the activity of possible troll profiles o...

When developing a software engineering project, selecting the most appropriate programming language is a crucial step. Most often, feeling at ease with the possible options becomes almost as relevant as the technical features of the language. Therefore, it appears to be worth analyzing the role that the emotional component plays in this process. In...

A troll is usually defined as somebody who provokes and offends people to make them angry, who wants to dominate any discussion or who tries to manipulate people’s opinions. The problems caused by such persons have increased with the diffusion of social media. Therefore, on the one hand, press bodies and magazines have begun to address the issue an...

We conducted a systematic review of literature to better understand the role of new technologies in the perioperative period; in particular we focus on the administrative and managerial Operating Room (OR) perspective. Studies conducted on adult (≥ 18 years) patients between 2015 and February 2019 were deemed eligible. A total of 19 papers were inc...

The so-called Relevance Index (RI) metrics are a set of recently-introduced indicators based on information theory principles that can be used to analyze complex systems by detecting the main interacting structures within them. Such structures can be described as subsets of the variables which describe the system status that are strongly statistica...

Human Activity Recognition (HAR) is currently recognized as a key element of a more general framework designed to perform continuous monitoring of human behaviors in the area of Ambient Assisted Living (AAL), well-being management, medical diagnosis, elderly care, rehabilitation, entertainment and surveillance in smart home environments. In this pa...

We present an improvement of a method that aims at detecting important dynamical structures in complex systems, by identifying subsets of elements that show tight and coordinated interactions among themselves, while interplaying much more loosely with the rest of the system. Such subsets are estimated by means of a Relevance Index (RI), which is no...

ActoDatA (Actor Data Analysis) is an actor-based software library for the development of distributed data mining applications. It provides a multi-agent architecture with a set of predefined and configurable agents performing the typical tasks of data mining applications. In particular, its architecture can manage different users’ applications; it...

Hidradenitis Suppurativa (HS), also known as Acne Inversa, is a chronic, underdiagnosed, often debilitating and painful disease that affects the folds of the skin. It has a considerable negative impact on the quality of life and on the emotional well-being. In this paper we discuss some results obtained by applying automatic Emotion Detection and S...

In the last few years the amount of electronic data in high schools has grown tremendously, also as a consequence of the introduction of electronic logbooks, where teachers store data about their students’ activities: school attendance, marks obtained in individual test trials and the typology of these tests. However, all this data is often spread...

This work presents the results of some summer stages for high school students, for the first introduction to computational thinking and programming. Differently from other approaches, our experiences are characterized by: (i) a full week of lessons and exercises, for gradually developing a small but complete and original project, (ii) an objects-ea...

Social networking systems are usually huge centralized systems owned by a single company. However, this solution has many drawbacks (e.g., lack of privacy, lack of anonymity, risks of censorship, and operating costs). This chapter proposes a novel P2P system that leverages existing, widespread, and stable technologies such as DHTs and BitTorrent. I...

Social networking systems can be considered one of the most important social phenomena because they succeeded in involving billions of people all around the world and in attracting users from several social groups, regardless of age, gender, education, or nationality. Social networking systems blur the distinction between the private and working sp...

In the last few years, the impact of information spread through online social networks has continuously grown. For this reason, understanding the trustworthiness of news has become one of the most important challenges for an Internet user, especially during crisis events or in political, health and social issues. As part of a more comprehensive pro...

We present a comprehensive framework for managing reports sent to the local government by citizens through well-known instant messaging apps. It leverages a combined use of Web systems and automated bots, based on Machine Learning techniques. This project has been developed in collaboration with the local administration of Montecchio Emilia (Italy)...

Methods based on information theory, such as the Relevance Index (RI), have been employed to study complex systems for their ability to detect significant groups of variables, well integrated among one another and well separated from the others, which provide a functional block description of the system under analysis. The integration (or zI in its...

Systems that exhibit complex behaviours often contain inherent dynamical structures which evolve over time in a coordinated way. In this paper, we present a methodology based on the Relevance Index method aimed at revealing the dynamical structures hidden in complex systems. The method iterates two basic steps: detection of relevant variable sets b...

Various techniques based on artificial intelligence have been proposed for the automatic detection of online anti-social behaviors, both in existing systems and in the scientific literature. In this article, we describe TrollPacifier, a holistic system for troll detection, which analyses many different features of trolls and legitimate users on the...

Why and how more and more people get involved and use social networking systems are critical topics in social network analysis (SNA). As a matter of fact, social networking systems bring online a growing number of acquaintances, for many different purposes. Both business interests and personal recreational goals are motivations for using online soc...

Many complex systems, both natural and artificial, may be represented by networks of interacting nodes. Nevertheless, it is often difficult to find meaningful correspondences between the dynamics expressed by these systems and the topological description of their networks. In contrast, many of these systems may be well described in terms of coordin...

The Relevance Index (RI) is an information theory-based measure that was originally defined to detect groups of functionally similar neurons, based on their dynamic behavior. More in general, considering the dynamical analysis of a generic complex system, the larger the RI value associated with a subset of variables, the more those variables are st...

Identifying Relevant Sets, i.e., variable subsets that exhibit a coordinated behavior, in complex systems is a very relevant research topic. Systems that exhibit complex dynamics are, for example, social networks, which are characterized by complex and dynamic relationships among users. A challenging topic within this context regards the identifica...

Within the field of sentiment analysis and emotion detection applied to tweets, one of the main problems related to the construction of an automatic classifier is the lack of suitable training sets. Considering the tediousness of manually annotating a training set, and the noise present in data collected directly from the social web, in this paper...

In Facebook, the set of pages liked by some users represents an important knowledge about their real life tastes. However, the process of classification, which is already hard when dealing with dozens of classes and genres, is made even more difficult by the very coarse information of Facebook pages. Our work originates from a large dataset of page...

Scopus is a well known repository of metadata about scientific research articles. In this work, we gather data from this repositiory to create a social graph of scientific authors, starting from citations among their articles. Moreover, using data mining techniques, we infer some relevant research topics for each author, from the textual analysis o...

Building centralized social networking systems has many drawbacks, e.g., lack of privacy, lack of anonymity, risks of censorship, and operating costs. As it is discussed in this article, an alternative approach is possible. A prototype system, named Blogracy, has been realized as a micro-blogging social networking system, based on well-known P2P te...

A balanced diet is the key to a healthy lifestyle and is crucial for preventing or dealing with many chronic diseases such as diabetes and obesity. Therefore, monitoring diet can be an effective way of improving people’s health. However, manual reporting of food intake has been shown to be inaccurate and often impractical. This paper presents a new...

Social media analysis is rapidly becoming awidespread tool for various applications. Motivations for interestrange from commercial marketing to the monitoring of socialtrends and political opinions. This work presents an actor-based platform, augmented with machine learning algorithms.To evaluate its possible application for the continuous analysis...

Mainly as a consequence of societal changes, the traditional approach to provide cares and social services in hospitals and institutional centres is being paralleled with a growing tendency to provide cares in the community, directly. Information and communication technologies play an important role in enabling and supporting this tendency. However...

Various methods have been proposed to identify emergent dynamical structures in complex systems. In this paper, we focus on the Dynamical Cluster Index (DCI), a measure based on information theory which allows one to detect relevant sets, i.e. sets of variables that behave in a coherent and coordinated way while loosely interacting with the rest of...

The AAL Systems have been devised to monitor the life of persons in their home, in order to infer information on their state of health and to support their wellbeing. The achievement of this purpose is possible by means of various technologies and systems (such as, for instance, home environment sensors, personal sensors and clinical devices). This...

BOOK WEBSITE: http://www.igi-global.com/book/social-media-performance-evaluation-success/169445 There are many different social media platforms that provide a wide array of services. Exploring the results yielded by these platforms can enhance their usefulness and impact on society’s advancement. Social Media Performance Evaluation and Success Me...

According to current definitions, health can not be merely intended as the absence of disease or infirmity. In this sense, for maintaining health, the coordination and collaboration among social and health systems is becoming essential, and it can happen only though the harmonization of existing and new integrated information systems. In this study...

Food intake and eating habits have a significant impact on people's health. Widespread diseases, such as diabetes and obesity, are directly related to eating habits. Therefore, monitoring diet can be a substantial base for developing methods and services to promote healthy lifestyle and improve personal and national health economy. Studies have dem...

The most important technological trend of the last years has been the rise of socialnetworking systems to social phenomena involving hundreds of millions of people,attracting users from several social groups. Social networking systems blur thedistinction between the private and working spheres, and users use such systemsboth at home and in the work...

Social media are more and more frequently used by people to express their feelings in the form of short messages. This has raised interest in emotion detection, with a wide range of applications among which the assessment of users’ moods in a community is perhaps the most relevant. This paper proposes a comparison between two approaches to emotion...

In a previous work, Villani et al. introduced a method to identify candidate emergent dynamical structures in complex systems. Such a method detects subsets (clusters) of the system elements which behave in a coherent and coordinated way while loosely interacting with the remainder of the system. Such clusters are assessed in terms of an index that...

We evaluated the effectiveness in classifying food images of a deep-learning approach based on the specifications of Google's image recognition architecture Inception. The architecture is a deep convolutional neural network (DCNN) having a depth of 54 layers. In this study, we fine-tuned this architecture for classifying food images from three well...

The popularity of mobile devices has fostered the emergence of plenty of new services most of which rely on the use of their camera. Among these, diet monitoring, based on computer vision, can be of particular interest. However, estimation of the amount of food portrayed in an image requires a size reference. A small checkerboard is a simple patter...

Monitoring diet is crucial for preventing or dealing with many chronic diseases. Therefore, plenty of different methods have been developed to serve this purpose. Among these, automatic diet monitoring based on mobile devices are of particular interest. An automatic system is supposed to be able to detect type and amount of food intake. This work s...

This work focuses on the design and the implementation of an ontology devised to extract knowledge from an Ambient Assisted Living environment, equipped with an Home Automation System. In particular, the design of the ontology is been carried out taking as reference the experience of the FOOD project [1], funded in the framework of the European AAL...

Microblogging platforms like Twitter can convey short messages to direct contacts, but also to other potentially interested users. They are actively exploited either by individual users or whole organizations and companies. This paper describes some results we obtained from the Social Network and Sentiment Analysis of a Twitter channel, related to...

Twitter is a platform which may contain opinions, thoughts, facts and other information. Within it, many and various communities are originated by users with common interests, or with similar ways to feel part of the community. This paper presents a possible combined approach between Social Network Analysis and Sentiment Analysis. In particular, we...

This paper describes a novel system for detecting and classifying human activities based on a multi-sensor approach. The aim of this research is to create a loosely structured environment, where activity is constantly monitored and automatically classified, transparently to the subjects who are observed. The system uses four calibrated cameras inst...

Particle swarm optimization (PSO) is an efficient population-based optimization technique. Niching is introduced into PSO to deal with multimodal problems, and converge onto the largest possible number of minima. In this paper, a niching PSO algorithm is described, which targets the imaging domain; our niching PSO enhances the fitness of a particle...

In this paper we propose a variant of particle swarm optimisation (PSO), oriented at image analysis applications, that is suitable for implementation on hardware chips. The new variant, called HPSO (Hardware PSO), can be mapped easily to field-programmable gate arrays (FPGAs). The modularity of our new architecture permits to take full advantage of...

This paper describes an innovative video fall detector which can be implemented in hardware The goal was to design a very economic embedded video sensor, based on a computationally light algorithm Such a sensor can be placed in an environment equipped with an 'ambient intelligence system', to produce a robust detection of fall events, using a data-...

A new trend in modern assistive technologies implies making extensive use of ICT to develop efficient and reliable "ambient intelligence" applications dedicated to disabled, elderly or frail people. In this paper we describe two fall detectors, based on bio-inspired algorithms. Such devices can either operate independently or be part of a modular a...

Particle Swarm Optimization (PSO) is a simple but powerful optimization algorithm, introduced by Kennedy and Eberhart (Kennedy 1995). Its search for function optima is inspired by the behavior of flocks of birds looking for food. Similarly to birds, a set (swarm) of agents (particles) fly over the search space, which is coincident with the function...

Spherical reprojection was introduced in omnidirectional vision mainly to simplify the projection model for single-viewpoint catadioptric sensors. It was then extended to omni-stereo systems to perform 3D information recovery and disparity map estimation. Although the same rectification technique has already been exploited also to the classical ste...

In this paper we propose a simplified, hardware-oriented algorithm for object detection, based on particle swarm optimization. Starting from an algorithm coded in a high-level language which has shown to perform well, both in terms of accuracy and of computation efficiency, the simplified version can be implemented on an FPGA. After describing the...

Many of the known visual systems in nature are characterized by a wide field of view allowing animals to keep the whole surrounding environment under control. In this sense, dragonflies are one of the best examples: their compound eyes are made up of thousands of separate light-sensing organs arranged to give nearly a 360° field of vision. However,...

Biological vision processes are usually characterized by the following different phases: • Awareness: natural or artificial agents operating in dynamic environments can benefit from a, possibly rough, global description of the surroundings. In human this is referred to as peripheral vision, since it derives from stimuli coming from the edge of the...

Peer-to-peer (P2P) and mobile technologies enable the integration between face-to-face and virtual communities, allowing users to experiment new models of learning and to contextualize them to their physical space or time. In this work we describe our view of a P2P e-learning community (PEC), and propose a taxonomy for context-aware e-learning serv...

Many of the known visual systems in nature are characterized by a wide field of view allowing animals to keep the whole surrounding environment under control. In this sense, dragonflies are one of the best examples: their compound eyes are made up of thousands of separate light-sensing organs arranged to give nearly a 360° field of vision. However,...

Particle Swarm Optimization (PSO) is a simple but powerful optimization algorithm, introduced by Kennedy and Eberhart (Kennedy 1995). Its search for function optima is inspired by the behavior of flocks of birds looking for food. Similarly to birds, a set (swarm) of agents (particles) fly over the search space, which is coincident with the function...

In this paper, we present a compact hybrid video sensor that combines perspective and omnidirectional vision to achieve a 360deg field of view, as well as high-resolution images. Those characteristics, in association with 3D metric reconstruction capabilities, are suitable for vision tasks such as surveillance and obstacle detection for autonomous...

M-learning mainly addresses informal learning aiming at the creation of knowledge outside curricula or courses. In this paper we present an investigation into whether and how a formal structure like a university can promote and guide informal learning. A mobile infrastructure allows learners to overcome space/time difficulties and to enter in a vir...

In this paper we describe results of a modified Particle Swarm Optimization (PSO) algorithm which has been applied to two image analysis tasks. In the former, accurate region-based segmentation is obtained by analyzing the cumulative results of several runs of the algorithm. In the latter, the fast-convergence properties of the algorithm are used t...

In this chapter we discuss some issues on mobile robot perception from the point of view of the structure of vision systems. Through some experiences and results from research projects we will approach the problem from the point of view of purposive vision, with particular regard to less conventional sensors and systems, such as omnidirectional and...

This paper describes two versions of a novel approach to developing binary classifiers, based on two evolutionary computation paradigms: cellular programming and genetic programming. Such an approach achieves high computation efficiency both during evolution and at runtime. Evolution speed is optimized by allowing multiple solutions to be computed...

Ontology may be used in the context of e-learning to capture knowledge about learning activities and subjects. We present a system that supports an automatic speech recognition and generation between users and an agent based application on the basis these ontologies. The system is realized taking advantage of the JADE agent development framework an...