Implementation of network entropy algorithms on hpc machines, with application to high-dimensional experimental data

Network Theory is a prolific and lively field, especially when it approaches Biology. New concepts from this theory find application in areas where extensive datasets are already available for analysis, without the need to invest money to collect them. The only tools that are necessary to accomplish an analysis are easily accessible: a computing machine and a good algorithm. As these two tools progress, thanks to technology advancement and human efforts, wider and wider datasets can be analysed. The aim of this paper is twofold. Firstly, to provide an overview of one of these concepts, which originates at the meeting point between Network Theory and Statistical Mechanics: the entropy of a network ensemble. This quantity has been described from different angles in the literature. Our approach tries to be a synthesis of the different points of view. The second part of the work is devoted to presenting a parallel algorithm that can evaluate this quantity over an extensive dataset. Eventually, the algorithm will also be used to analyse high-throughput data coming from biology.

Feedback control of underactuated cable-driven parallel robots

In this work an Underactuated Cable-Driven Parallel Robot (UACDPR) that operates in the three dimensional Euclidean space is considered. The End-Effector has 6 degrees of freedom and is actuated by 4 cables, therefore from a mechanical point of view the robot is defined underconstrained. However, considering only three controlled pose variables, the degree of redundancy for the control theory can be considered one. The aim of this thesis is to design a feedback controller for a point-to-point motion that satisfies the transient requirements, and is capable of reducing oscillations that derive from the reduced number of constraints. A force control is chosen for the positioning of the End-Effector, and error with respect to the reference is computed through data measure of several sensors (load cells, encoders and inclinometers) such as cable lengths, tension and orientation of the platform. In order to express the relation between pose and cable tension, the inverse model is derived from the kinematic and dynamic model of the parallel robot. The intrinsic non-linear nature of UACDPRs systems introduces an additional level of complexity in the development of the controller, as a result the control law is composed by a partial feedback linearization, and damping injection to reduce orientation instability. The fourth cable allows to satisfy a further tension distribution constraint, ensuring positive tension during all the instants of motion. Then simulations with different initial conditions are presented in order to optimize control parameters, and lastly an experimental validation of the model is carried out, the results are analysed and limits of the presented approach are defined.

A parallel community detection algorithm

Complex networks analysis is a very popular topic in computer science. Unfortunately this networks, extracted from different contexts, are usually very large and the analysis may be very complicated: computation of metrics on these structures could be very complex. Among all metrics we analyse the extraction of subnetworks called communities: they are groups of nodes that probably play the same role within the whole structure. Communities extraction is an interesting operation in many different fields (biology, economics,...). In this work we present a parallel community detection algorithm that can operate on networks with huge number of nodes and edges. After an introduction to graph theory and high performance computing, we will explain our design strategies and our implementation. Then, we will show some performance evaluation made on a distributed memory architectures i.e. the supercomputer IBM-BlueGene/Q "Fermi" at the CINECA supercomputing center, Italy, and we will comment our results.

Vending Machines avanzate basate su principi di Physical Web e Internet of Things

La costante evoluzione tecnologica sta portando alla luce nuove possibilità, che un tempo non erano nemmeno immaginabili. Uno dei settori che si è rivoluzionato maggiormente negli ultimi anni è quello delle telecomunicazioni e questo ha portato sia a una riduzione dei costi per le connessioni a Internet, sia ad un aumento delle loro capacità e prestazioni; di conseguenza queste connessioni sono diventate più accessibili e affidabili permettendo alle persone e alle cose di accedere a Internet quasi ininterrottamente. Questo sviluppo sta portando innumerevoli benefici, ma come ciascuna innovazione tecnologica, tuttavia, i benefici si accompagnano a nuove sfide. In questo elaborato viene dapprima analizzato lo stato dell’arte, i benefici, le problematiche e gli attuali interessi da parte di alcuni dei maggiori player verso l’Internet of Things. Vengono poi prese in considerazione due problematiche: l'individuazione e l'interazione con gli oggetti connessi a Internet, portando come esempio l'utilizzo e la ricerca di una vending machine, un distributore automatico. Proponendo una soluzione, in primo luogo è stato effettuato lo sviluppo di un ecosistema che sfrutta le potenzialità del Physical Web, implementando ad hoc ogni componente, dall'emissione del beacon Eddystone-URL alla visualizzazione della pagina ad esso associata. In secondo luogo questa è stata creata un'applicazione Android che sfrutta l'altro tipo di frame offerto dalla piattaforma beacon di Google, l'Eddystone-UID. Queste due applicazioni vengono quindi analizzate e messe a confronto, per individuare i punti forti e le mancanze delle rispettive piattaforme.