Automated Fault Tolerance Augmentation in Model-Driven Engineering for CPS

Cyber-Physical Systems are usually subject to dependability requirements such as safety and reliability constraints. Over the last 50 years, a body of efficient fault-tolerance mechanisms has been devised to handle faults occurring at run-time. However, properly implementing those mechanisms is a time-consuming task that requires a great deal of know-how. In this paper, we propose a general framework which allows system designers to decouple functional and non-functional concerns, and express non- functional properties at design time using domain-specific languages. In the spirit of generative programming, functional models are then automatically “augmented” with dependability mechanisms. Importantly, the real-time behavior of the initial models in terms of sampling times and meeting deadlines is preserved. The practicality of the approach is demonstrated with the automated implementation of one prominent software fault-tolerance pattern, namely N-Version Programming, in the CPAL model-driven engineering workflow

Evolutionary history of clathrin-mediated endocytosis and the eisosome

Endocytosis is both an ancient and a diverse feature of the eukaryotic cell. Studying how it evolved can provide insight into the nature of the last common eukaryotic ancestor, and the diversification of eukaryotes into the known extant lineages. In this thesis, I present two studies on the evolution of endocytosis. In the first part of the thesis I report results from a large-scale, phylogenetic and comparative genomic study of clathrin-mediated endocytosis (CME). The CME pathway has been studied to a great level of detail in yeast to mammal model organisms. Several protein families have now been identified as part of the complex set of protein-protein and protein-lipid interactions which mediate endocytosis. To investigate how such complexity evolved, first, I defined the modular nature of the CME interactome (CME-I) by literature review, and then I carried out a systematic phylogenetic and protein domain architecture analysis of the proteins involved. These data were used to construct a model of the evolution of the CME-I network, and to map the expansion of the network's complexity to the eukaryotic tree of life. In the second part of the thesis, I present results from evolutionary and functional studies of the eisosome, a protein complex which has been proposed to regulate the spatial distribution of endocytosis in S. cerevisiae. The phylogeny of eisosomes components Pil1 and Lsp1 reported here, suggests that eisosomes are likely to have originated at the base of the fungi, and then diversified significantly via multiple gene duplications. I thus studied the localisation and function of Pil1 and Lsp1 homologues in Magnaporthe oryzae to investigate the role of eisosomes in filamentous fungi. Results suggests that eisosomes are linked with septal formation and integrity in M. oryzae, and that the septal specific Pil2 paralogue was lost in budding yeasts. Together, the data presented in this thesis describe the evolutionary history of a complex biological system, but also highlights the problem of asymmetry in the understanding of endocytic diversity in the eukaryotes.BBSR

Explainable AI for Machine Fault Diagnosis: Understanding Features' Contribution in Machine Learning Models for Industrial Condition Monitoring

Although the effectiveness of machine learning (ML) for machine diagnosis has been widely established, the interpretation of the diagnosis outcomes is still an open issue. Machine learning models behave as black boxes; therefore, the contribution given by each of the selected features to the diagnosis is not transparent to the user. This work is aimed at investigating the capabilities of the SHapley Additive exPlanation (SHAP) to identify the most important features for fault detection and classification in condition monitoring programs for rotating machinery. The authors analyse the case of medium-sized bearings of industrial interest. Namely, vibration data were collected for different health states from the test rig for industrial bearings available at the Mechanical Engineering Laboratory of Politecnico di Torino. The Support Vector Machine (SVM) and k-Nearest Neighbour (kNN) diagnosis models are explained by means of the SHAP. Accuracies higher than 98.5% are achieved for both the models using the SHAP as a criterion for feature selection. It is found that the skewness and the shape factor of the vibration signal have the greatest impact on the models’ outcomes

On a non-convex hyperbolic differential inclusion

We prove the existence of a solution u(.,.;a,/?) of the Darboux problem uxfeF(x,y,u), u(x,0) = a(x), u(0,y) = P(y), which is continuous with respect to (a,/?). We assume that F is Lipschitzean with respect to u but not necessarily convex valued

DESIGN OF A PROTOTYPE UNMANNED LIGHTER-THAN-AIR PLATFORM FOR REMOTE SENSING: CONTROL, ALIMENTATION, AND PROPULSION SYSTEMS

This work presents several aspects related to the design of a new concept for a Remotely Piloted Aircraft System (RPAS), specifically, a Lighter-Than-Air (LTA) platform for the remote sensing of medium-sized rural and urban areas. The airship’s payload is intended to carry an array of sensors ranging from high-definition video cameras to hyperspectral sensors, a thermographic camera, and a LiDAR system, which all require power alimentation during low-speed surveying for fine mapping. Here, a fuel cell design solution, combined with supercapacitors, is proposed. The system is designed to provide energy for both the onboard sensors and the propulsion and thrust vector control system. In this regard, the design and optimization of the propeller blades, using Blade Element Momentum Theory (BEMT), is discussed as well, in a multidisciplinary optimisation fashion. A twin paper describes the other structural aspects of the airship design