Luca Oneto

Università degli Studi di Genova | UNIGE · Dipartimento di Informatica, Bioingegneria, Robotica e Ingegneria dei Sistemi (DIBRIS)

For propeller-driven vessels, cavitation is the most dominant noise source producing both structure-borne and radiated noise impacting wildlife, passenger comfort, and underwater warfare. Physically plausible and accurate predictions of the underwater radiated noise at design stage, i.e., for previously untested geometries and operating conditions,...

Applying computational statistics or machine learning methods to data is a key component of many scientific studies, in any field, but alone might not be sufficient to generate robust and reliable outcomes and results. Before applying any discovery method, preprocessing steps are necessary to prepare the data to the computational analysis. In this...

Demand upon the future Air Traffic Management (ATM) systems is expected to grow to possibly exceed available system capacity, pushing forward the need for automation and digitisation to maintain safety while increasing efficiency. This work focuses on a manifestation of ATM safety, the Loss of Separation (LoS), exploiting safety reports and ATM-sys...

A Track Circuit (TC) System enables automatic train detection and protection functions. A typical TC failure is the False Occupancy (FO), i.e., a TC results occupied for a certain period of time when there is no train on it. FO can be resolved by manually driving a train on the faulty TC with a waste of time and resources. After a FO, operators, ba...

The potential impact of underwater radiated noise from maritime operations on marine fauna has become an important issue. The most dominant noise source on a propeller-driven vessel is propeller cavitation, producing both structure-borne and radiated noise, with a broad spectrum that covers a wide range of frequencies. To ensure acceptable noise le...

Answer Set Programming (ASP) is a well-established declarative AI formalism for knowledge representation and reasoning. ASP systems were successfully applied to both industrial and academic problems. Nonetheless, their performance can be improved by embedding domain-specific heuristics into their solving process. However, the development of domain-...

Emotions have always played a crucial role in human evolution, improving not only social contact but also their ability to adapt and react to a changing environment. In the field of social robotics, providing robots with the ability to recognize human emotions through the interpretation of non-verbal signals may represent the key to more effective...

Ultimate limit state (ULS) assessment examines the maximum load-carrying capacity of structures considering inelastic buckling failure. Contrary to the traditional allowable stress principle which is mainly based on experiences , the ULS assessment focuses on explicitly evaluating the structural safety margin and thus enables a consistent level of...

The potential impact of ships underwater radiated noise (URN) on marine fauna has become an important issue. The most dominant noise source on a propeller-driven vessel is propeller cavitation, and the accurate prediction of its noise signature is fundamental for the design process. In this work, we investigate the potential of using Machine Learni...

Recent research has shown that models induced by machine learning, and in particular by deep learning, can be easily fooled by an adversary who carefully crafts imperceptible, at least from the human perspective, or physically plausible modifications of the input data. This discovery gave birth to a new field of research, the adversarial machine le...

Movement dataset reviews exist but are limited in coverage, both in terms of size and research discipline. While topic-specific reviews clearly have their merit, it is critical to have a comprehensive overview based on a systematic survey across disciplines. This enables higher visibility of datasets available to the research communities and can fo...

The increasing digitization and datification of all aspects of people’s daily life, and the consequent growth in the use of personal data, are increasingly challenging the current development and adoption of Machine Learning (ML). First, the sheer complexity and amount of data available in these applications strongly demands for ML algorithms that...

Monitoring and evaluating the biofouling state and its effects on the vessel's hull and propeller performance is a crucial problem that attracts the attention of both academy and industry. Effective and reliable tools to address this would allow a timely cleaning procedure able to trade off costs, efficiency, and environmental impacts. In this pape...

Background: The air traffic management (ATM) system has historically coped with a global increase in traffic demand ultimately leading to increased operational complexity. When dealing with the impact of this increasing complexity on system safety it is crucial to automatically analyse the losses of separation (LoSs) using tools able to extract mea...

The number of installed floating offshore wind turbines (FOWTs) has doubled since 2017, quadrupling the total installed capacity, and is expected to increase significantly over the next decade. Consequently, there is a growing consideration towards the main challenges for FOWT projects: monitoring the system’s integrity, extending the lifespan of t...

After a brief opening to the microprocessors’ world, this chapter will gradually introduce the idea of building a digital programmable network able to solve different problems. The reader will be led through the basics of microprocessors, introducing step by step the microcomputer architecture’s cornerstones. Several concepts, such as sequencer, AL...

In this chapter, we will learn how to interface the microcomputer with external devices and how to transfer data between different systems. First, we will introduce the concept of “handshake”. Then we will present techniques such as “polling”, “interrupts” and the use of “timers”, which allow convenient management of the communication. Each concept...

In this chapter, after a brief and general introduction to the programming language and their compilers, the DMC8 assembly language is presented. The different sections will describe the processor’s addressing modes, categorize the instructions available, and provide examples to illustrate their functionality. Particular attention will be given to...

In this chapter, we introduce the DMC8 microprocessor through the study of a microcomputer based on it. In particular we will present the organization of its bus, its architecture, and how it carries out instructions. Then we will start to detail the behavior over time of the processor’s bus signals. Consequently we will present how memory and inpu...

In this chapter, we will learn what a Field Programmable Gate Array (FPGA) device is and how we can use it to physically implement what we have just simulated until now. In fact, Deeds supports both the simulation and deployment on FPGA of the microprocessor-based systems. After a brief introduction to the FPGA, we will present a few examples of FP...

Accurate, reliable, and computationally inexpensive models of the dynamic state of combustion engines are a fundamental tool to investigate new engine designs, develop optimal control strategies, and monitor their performance. The use of those models would allow to improve the engine cost-efficiency trade-off, operational robustness, and environmen...

This book is intended for a first course on microprocessor-based systems design for engineering and computer science students. It starts with an introduction of the fundamental concepts, followed by a practical path that guides readers to developing a basic microprocessor example, using a step-by-step problem-solving approach. Then, a second microp...

In recent years, the railway system has been facing the various challenges of the “digital age”. To increase its attractiveness, capacity, sustainability, and security, it needs to improve its’ everyday operational and planning process. This can be enabled using new generation digitised and automated Traffic Management Systems (TMS). Nowadays, rail...

The purpose of this chapter is to provide an overview of the state-of-the-art and future perspectives of Data Science and Advanced Analytics for Shipping Energy Systems. Specifically, we will start by listing the different static and dynamic data sources and knowledge base available in this particular context. Then we will review the Data Science a...

Chronic kidney disease (CKD) describes a long-term decline in kidney function and has many causes. It affects hundreds of millions of people worldwide every year. It can have a strong negative impact on patients, especially when combined with cardiovascular disease (CVD): patients with both conditions have lower survival chances. In this context, c...

Background: The air traffic management (ATM) system has historically coped with a global increase in traffic demand ultimately leading to increased operational complexity. When dealing with the impact of this increasing complexity on system safety it is crucial to automatically analyse the loss of separation (LoS) using tools able to extract meanin...

The number of installed Floating Offshore Wind Turbines (FOWTs) has doubled since 2017, quadrupling the total installed capacity, and is expected to increase significantly over the next decade. Consequently, there is a growing consideration towards the main challenges for FOWT projects: monitoring the system's integrity, extending the lifespan of t...

Diesel engines will remain a fundamental component of propulsion systems due to their maturity, reliability, and power density. Building Digital Twins of the propulsion system is one feasible solution to pursue the optimal propulsions system operation, estimating system states and efficiency. This work will investigate a modelling approach that com...

Learning to play and perform violin is a complex task, that requires a high conscious control and coordination for the player. In this paper, our aim is to understand which technology and which motion features can be used to efficiently and effectively distinguish a professional performance from a student one trading off intrusiveness and accuracy....

In many decision-making scenarios, ranging from recreational activities to healthcare and policing, the use of artificial intelligence coupled with the ability to learn from historical data is becoming ubiquitous. This widespread adoption of automated systems is accompanied by the increasing concerns regarding their ethical implications. Fundamenta...

In-station train dispatching is the problem of optimising the effective utilisation of available railway infrastructures for mitigating incidents and delays. In this paper, we describe an approach for dealing with the in-station dispatching problem by means of automated planning techniques.

The central goal of algorithmic fairness is to develop AI-based systems which do not discriminate subgroups in the population with respect to one or multiple notions of inequity, knowing that data is often humanly biased. Researchers are racing to develop AI-based systems able to reach superior performance in terms of accuracy, increasing the risk...

In-station train dispatching is the problem of optimising the effective utilisation of available railway infrastructures for mitigating incidents and delays. This is a fundamental problem for the whole railway network efficiency, and in turn for the transportation of goods and passengers, given that stations are among the most critical points in ne...

The potential impact of ships underwater radiated noise (URN) on marine fauna has become an important issue. The most dominant noise source on a propeller-driven vessel is propeller cavitation, and the accurate prediction of its noise signature is fundamental for the design process. In this work, we investigate the potential of using low-computatio...

In railway networks, stations are probably the most critical points for interconnecting trains' routes: in a restricted geographical area, a potentially large number of trains have to stop according to an official timetable, with the concrete risk of accumulating delays that can then have a knockout effect on the rest of the network. In this contex...

Fast diesel engine models for real-time prediction in dynamic conditions are required to predict engine performance parameters, to identify emerging failures early on and to establish trends in performance reduction. In order to address these issues, two main alternatives exist: one is to exploit the physical knowledge of the problem, the other one...

The present study deals with the development of a zero-dimensional model for marine diesel engines of the four-stroke type, as well as a methodology to automate its calibration process. The modelling and calibration approach is validated using experimental and operational data from a Wärtsilä engine, covering several model input and outputs. Valida...

The hydromechanics analysis of floating offshore wind turbines is a fundamental and time consuming part of the design process, traditionally analysed with methods of computational fluid dynamics. In this work, an alternative computational framework is suggested, able to significantly accelerate the design process with minimal accuracy loss. Through...

In offshore maritime operations, automated systems capable of maintaining the vessel’s position and heading using its own propellers and thrusters to compensate exogenous disturbances, like wind, waves, and currents, are referred to as marine dynamic positioning (DP) systems. DP systems play a central role in several marine operations, such as dril...

Background Maritime transportation accounts for around 80% of the world freight movements, remarkably contributing to the global environmental footprint. Dual fuel engines, running on both gaseous and liquid fuels, represent a viable way toward the reduction of emissions at the cost of additional complexity in monitoring activities. Motivation Dat...

Background Sepsis is a life-threatening clinical condition that happens when the patient’s body has an excessive reaction to an infection, and should be treated in one hour. Due to the urgency of sepsis, doctors and physicians often do not have enough time to perform laboratory tests and analyses to help them forecast the consequences of the sepsis...

In this paper, we deal with the classical Statistical Learning Theory’s problem of bounding, with high probability, the true risk R(h) of a hypothesis h chosen from a set H of m hypotheses. The Union Bound (UB) allows one to state that PLR^(h),δqh≤R(h)≤UR^(h),δph≥1−δ where R^(h) is the empirical errors, if it is possible to prove that P{R(h)≥L(R^(h...

In questo capitolo, dopo un breve accenno ai linguaggi di programmazione e ai relativi traduttori, viene introdotto il linguaggio assembly del DMC8. In particolare, sono descritti i metodi di indirizzamento del processore e la classificazione per categoria delle istruzioni disponibili, corredate di esempi esplicativi. Ampio spazio è dedicato ai sal...

In questo capitolo affronteremo il tema delle “interruzioni”, spesso necessarie per gestire al meglio lo scambio di dati tra il processore e le periferiche. Come già accennato nei capitoli precedenti, il processore possiede delle linee che permettono di interrompere l’esecuzione del programma in corso, in favore di un altro programma appositamente...

In questo capitolo è esaminata dapprima la struttura hardware di un sistema basato sul microprocessore DMC8, a partire dall’organizzazione del bus, dell’architettura del microprocessore e del modo in cui esegue le istruzioni. Poi si scenderà più in dettaglio, considerando il comportamento nel tempo dei segnali del bus del processore. Tutte queste i...

In questo capitolo, dopo una breve introduzione ai microprocessori, nella quale vengono definiti alcuni termini e criteri generali, sono introdotti gradualmente i concetti alla base delle architetture dei microcalcolatori. Si inizia da un semplice esempio di problema da risolvere e via via individueremo gli elementi architetturali di un sistema di...

Il libro di testo è concepito per studenti di un primo corso sullo sviluppo di sistemi a microprocessore, nelle Facoltà di Ingegneria e di Scienze. Adattabile a diverse esigenze didattiche, non richiede conoscenze preliminari sui microprocessori e fornisce una solida introduzione all’argomento. L’apprendimento della teoria è facilitato da numerosi...

Liver cancer kills approximately 800 thousand people annually worldwide, and its most common subtype is hepatocellular carcinoma (HCC), which usually affects people with cirrhosis. Predicting survival of patients with HCC remains an important challenge, especially because technologies needed for this scope are not available in all hospitals. In thi...

Machine learning based systems are reaching society at large and in many aspects of everyday life. This phenomenon has been accompanied by concerns about the ethical issues that may arise from the adoption of these technologies. ML fairness is a recently established area of machine learning that studies how to ensure that biases in the data and mod...

Myocardial infarctions and heart failure are the cause of more than 17 million deaths annually worldwide. ST-segment elevation myocardial infarctions (STEMI) require timely treatment, because delays of minutes have serious clinical impacts. Machine learning can provide alternative ways to predict heart failure and identify genes invovled in heart f...

Learning to play and perform a music instrument is a complex cognitive task, requiring high conscious control and coordination of an impressive number of cognitive and sensorimotor skills. For professional violinists, there exists a physical connection with the instrument allowing the player to continuously manage the sound through sophisticated bo...

Machine learning based systems and products are reaching society at large in many aspects of everyday life, including financial lending, online advertising, pretrial and immigration detention, child maltreatment screening, health care, social services, and education. This phenomenon has been accompanied by an increase in concern about the ethical i...

Marine accidents are complex processes in which many factors are involved and contribute to accident development. For this reason, effectively analyse what combination of factors lead an accident event is a complex problem, especially when human factors are involved. State-of-the-art methods such as Human Factor Analysis and Classification System,...

Reducing the noise impact of ships on the marine environment is one of the objectives of new propellers designs, since they represent the dominant source of underwater radiated noise, especially when cavitation occurs. Consequently, ship designers require new predictive tools able to verify the compliance with noise requirements and to compare the...

Innovation capability (IC) is a fundamental firms’ strategic asset to sustain competitive advantage. In this article, relying on patent data, patents forward citations are used as proxy of IC and the main patents numerical and categorical variables are considered as proxy of IC determinants. The main purpose of this article is to understand which p...

We study the problem of learning a real-valued function that satisfies the Demographic Parity constraint. It demands the distribution of the predicted output to be independent of the sensitive attribute. We consider the case that the sensitive attribute is available for prediction. We establish a connection between fair regression and optimal trans...

The importance of reducing the noise impact of ships is being recognised worldwide. Consequently, the inclusion of this principle among the objectives and constraints of new designs is becoming a standard. For this reason, considerable attention is given to the propeller being often the dominant source of underwater radiated noise, especially when...

Machine learning based systems are reaching society at large and in many aspects of everyday life. This phenomenon has been accompanied by concerns about the ethical issues that may arise from the adoption of these technologies. ML fairness is a recently established area of machine learning that studies how to ensure that biases in the data and mod...

We address the problem of randomized learning and generalization of fair and private classifiers. From one side we want to ensure that sensitive information does not unfairly influence the outcome of a classifier. From the other side we have to learn from data while preserving the privacy of individual observations. We initially face this issue in...