Riccardo Pecori

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• PhD
• Associate Professor of Computer Engineering at Università degli Studi eCampus

See CfP below.

Artificial Intelligence (AI) has become an integral part of our lives, and Explainable Artificial Intelligence (XAI) is becoming more essential to ensure trustworthiness and comply with regulations. XAI methodologies help to explain the automatic processing behind data analysis. This paper provides an overview of the use of XAI in the educational d...

Cardiopathy has become one of the predominant global causes of death. The timely identification of different types of heart diseases significantly diminishes mortality risk and enhances the efficacy of treatment. However, fast and efficient recognition necessitates continuous monitoring, encompassing not only specific clinical conditions but also d...

In the context of the Internet of Things (IoT), particularly within medical facilities, the detection and categorization of Internet traffic remain significant challenges. While conventional methods for IoT traffic analysis can be applied, obtaining suitable medical traffic data is challenging due to the stringent privacy constraints associated wit...

Remote hybrid work risk assessment is an obligation for the employer according to Occupational Safety and Health (OSH) regulations. Risk management requires the cooperation of the worker, who is now responsible for recognizing and managing hazards, necessitating specific technical training. Generative Artificial Intelligence (AI) technologies can s...

PeRConAI will focus on solutions contributing towards the advancement of truly pervasive and liquid AI enabling edge devices, regardless of their available resources, to accomplish both training and inference under full, weak or no supervision. The PeRConAI workshop aims at fostering the development and circulation of new ideas and research directi...

Research on identification methods for the Coronavirus Disease 2019 (COVID-19) has increased in the last years and the need for automated detection methods has surged as well. Computed Tomography scan images have demonstrated to contain useful and sufficient information to detect COVID-19 by using machine learning and computational intelligence tec...

The use of artificial intelligence approaches in health-care systems has grown rapidly over the last few years. In this context, early detection of diseases is the most common area of application. In this scenario, thyroid diseases are an example of illnesses that can be effectively faced if discovered quite early. Detecting thyroid diseases is cru...

Artificial Intelligence-based methods have been thoroughly applied in various fields over the years and the educational scenario is not an exception. However, the usage of the so-called explainable Artificial Intelligence, even if desirable, is still limited, especially whenever we consider educational datasets. Moreover, the time dimension is not...

Virtual Learning Environments (VLEs) are online educational platforms that combine static educational content with interactive tools to support the learning process. Click-based data, reporting the students' interactions with the VLE, are continuously collected, so automated methods able to manage big, non-stationary, and changing data are necessar...

Water stress and in particular drought are some of the most significant factors affecting plant growth, food production, and thus food security. Furthermore, the possibility to predict and shape irrigation on real plant demands is priceless. The objective of this study is to characterize, classify, and forecast water stress in tomato plants by mean...

Anomaly detection in network traffic is a hot and ongoing research theme especially when concerning IoT devices, which are quickly spreading throughout various situations of people’s life and, at the same time, prone to be attacked through different weak points. In this paper, we tackle the emerging anomaly detection problem in IoT, by integrating...

Research on Coronavirus Disease 2019 (COVID-19) detection methods has increased in the last months as more accurate automated toolkits are required. Recent studies show that CT scan images contain useful information to detect the COVID-19 disease. However, the scarcity of large and well balanced datasets limits the possibility of using detection ap...

In this paper, we report the scientific experience of HELMeTO 2020, the second edition of the International Workshop on Higher Education Learning Methodologies and Technologies Online, held virtually in Bari (Italy) in September 2020 because of the COVID-19 pandemic. The call received 59 proposals from nine countries, 39 papers were accepted to the...

During the last years, several studies have been proposed about user identification by means of keystroke analysis. Keystroke dynamics has a lower cost when compared to other biometric-based methods since such a system does not require any additional specific sensor, apart from a traditional keyboard, and it allows the continuous identification of...

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...

The constant spread of smart devices in many aspects of our daily life goes hand in hand with the ever-increasing demand for appropriate mechanisms to ensure they are resistant against various types of threats and attacks in the Internet of Things (IoT) environment. In this context, Deep Learning (DL) is emerging as one of the most successful and s...

Data stream mining has recently grown in popularity, thanks to an increasing number of applications which need continuous and fast analysis of streaming data. Such data are generally produced in application domains that require immediate reactions with strict temporal constraints. These particular characteristics make problematic the use of classic...

Featured Application The communications scenario analyzed in this paper is typical of environments affected by strong electromagnetic interference (EMI), such as, e.g., power line communications or power substations. The transmission of random correlated samples with continuous values, which we analyze, can be seen both as a rough model for multica...

Impulsive noise is the main limiting factor for transmission over channels affected by electromagnetic interference. We study the estimation of (correlated) Gaussian signals in an impulsive noise scenarios. In this work, we analyze some of the existing as well as some novel estimation algorithms. Their performance is compared, for the first time, f...

Internet traffic detection and classification has been thoroughly studied in the last decade, but this is still a hot topic as regards the Internet of Things (IoT), a communication paradigm that is going to involve different aspects of our daily life. As a consequence, researchers started applying traditional methods for traffic classification also...

Parkinson's disease is a degenerative movement disorder causing considerable disability. However, the early detection of this syndrome and of its progression rates may be decisive for the identification of appropriate therapies. For this reason, the adoption of Neural Networks to detect this disease on the base of walking information is gaining mor...

The most recent advances in artificial intelligence, as concerns both software and hardware, are fostering a multitude of smart devices capable to recognize and to react to music, images, as well as to other "stimuli". These autonomous things, from robots to cameras to healthcare devices, could exploit recent advances in Internet of Things and reso...

In the emerging Industrial Internet of Things (IIoT) scenario machine-to-machine communication is a key technology to set up environments wherein sensors, actuators, and controllers can exchange information autonomously. However, many current communication frameworks do not provide enough dynamic interoperability and security. Therefore, we propose...

Fairness, Accountability, Transparency and Explainability have become strong requirements in most practical applications of Artificial Intelligence (AI). Fuzzy sets and systems are recognized world-wide because of their outstanding contribution to model AI systems with a good interpretability-accuracy tradeoff. Accordingly, fuzzy sets and systems a...

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...

In this paper, smartphones and exergame controllers are proposed as BYOD (Bring Your Own Device) solutions for carrying out the interactive learning activities of an online sport and exercise sciences university program. Such devices can be used as sources of kinematic and physiological data during the execution of some selected physical activities...

We present a model, based on Fog Computing, to access contents of a Virtual Learning Environment. This model will help bringing learning contents and applications closer to students by means of smart nodes located at the edge of the access networks used by the students themselves. It features optimized bandwidth usage that significantly reduces lat...

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...

Evaluating novel applications and protocols in realistic scenarios has always been a very important task for all stakeholders working in the networking field. Network emulation, being a trade-off between actual deployment and simulations, represents a very powerful solution to this issue, providing a working network platform without requiring the a...

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...

Purpose Managing efficiently educational Big Data, produced by Virtual Learning Environments, is becoming a compelling necessity, especially for those universities providing distance learning. This paper aims to propose a possible framework to compute efficiently key performance indicators, summarizing the trends of students’ academic careers, by...

This book constitutes the thoroughly refereed post-conference proceedings of the First International Workshop on Higher Education Learning Methodologies and Technologies Online, HELMeTO 2019, held in Novedrate, Italy, in June 2019. The 15 revised full papers and 2 short papers presented were carefully reviewed and selected from a total of 39 subm...

Security in the Internet of Things is a current hot topic and it may comprise different aspects such as confidentiality and integrity of personal data, as well as the authentication and the authorization to access smart objects that are spreading more and more in our every-day lives. In this work we focus on MQTT (Message Queue Telemetry Transport)...

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...

A Sybil attack is one of the main challenges to be addressed when securing peer-to-peer networks, especially those based on Distributed Hash Tables (DHTs). Tampering routing tables by means of multiple fake identities can make routing, storing, and retrieving operations significantly more difficult and time-consuming. Countermeasures based on trust...

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...

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...

In recent years, virtual learning environments are gaining more and more momentum, considering both the technologies deployed in their support and the sheer number of terminals directly or indirectly interacting with them. This essentially means that every day, more and more smart devices play an active role in this exemplary Web of Things scenario...

Mining and analyzing the valuable knowledge hidden behind the amount of data available in social media is becoming a fundamental prerequisite for any effective and successful strategic marketing campaign. Anyway, to the best of our knowledge, a systematic analysis and review of the very recent literature according to a marketing framework is still...

The growing development of virtual learning platforms is boosting a new type of Big Data and of Big Data Stream, those ones that can be labeled as e-learning Big Data. These data, coming from different sources of Virtual Learning Environments, such as communications between students and instructors as well as pupils tests, require accurate analysis...

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...

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...

Peer-to-peer architectures have become very popular in the last years for a variety of services and applications they support, such as collaborative computing, streaming and VoIP applications. The security of the protocols involved in such operations is, however, a fundamental prerequisite for a widespread diffusion of such a technology. In this pa...

Peer-to-peer architectures have become very popular in the last years for a variety of services and applications such as collaborative computing, streaming and VoIP applications. The security and integrity of the overlay involved in such networks is a fundamental prerequisite for deploying such a technology. Withstanding multiple false identities i...

Withstanding multiple false identities, also known as a Sybil attack, is one of the main challenges in securing structured peer-to-peer networks. Poisoning routing tables through these identities may make the routing process, needed for storing and retrieving resources within a DHT (Distributed Hash Table), extremely difficult and time consuming. W...

The increasing demand of network security, access control, and service differentiation over IP networks drives Internet Service Providers and network administrators to deploy ever more sophisticated and faster traffic recognition mechanisms. Unfortunately this is complicated by the continuous development of new application protocols, increasing net...

The security of the protocols involved in peer-to-peer communications is becoming a fundamental prerequisite for their widespread diffusion. In this paper, we propose a new protocol for establishing a security association between two peers willing to set up a VoIP or multimedia communication through the standard SIP protocol. Our proposal is based...

Voice over IP (VoIP) and multimedia real-time communications between two or more parties are widely used over the Internet. The Session Initiation Protocol (SIP) is the current signaling standard for such applications and allows users to establish and negotiate any end-to-end multimedia session. Unfortunately current SIP-based platforms use a centr...

A crucial aspect when establishing a secure peer-to-peer communication channel is the negotiation of the security parameters used to protect the successive data communications, including the various encryption and authentication keys. There are different secure protocol (such as IPSec, TLS, SSH, etc.) currently defined with their own negotiation me...