Structure learning of graphical models for task-oriented robot grasping

In the collective imaginaries a robot is a human like machine as any androids in science fiction. However the type of robots that you will encounter most frequently are machinery that do work that is too dangerous, boring or onerous. Most of the robots in the world are of this type. They can be found in auto, medical, manufacturing and space industries. Therefore a robot is a system that contains sensors, control systems, manipulators, power supplies and software all working together to perform a task. The development and use of such a system is an active area of research and one of the main problems is the development of interaction skills with the surrounding environment, which include the ability to grasp objects. To perform this task the robot needs to sense the environment and acquire the object informations, physical attributes that may influence a grasp. Humans can solve this grasping problem easily due to their past experiences, that is why many researchers are approaching it from a machine learning perspective finding grasp of an object using information of already known objects. But humans can select the best grasp amongst a vast repertoire not only considering the physical attributes of the object to grasp but even to obtain a certain effect. This is why in our case the study in the area of robot manipulation is focused on grasping and integrating symbolic tasks with data gained through sensors. The learning model is based on Bayesian Network to encode the statistical dependencies between the data collected by the sensors and the symbolic task. This data representation has several advantages. It allows to take into account the uncertainty of the real world, allowing to deal with sensor noise, encodes notion of causality and provides an unified network for learning. Since the network is actually implemented and based on the human expert knowledge, it is very interesting to implement an automated method to learn the structure as in the future more tasks and object features can be introduced and a complex network design based only on human expert knowledge can become unreliable. Since structure learning algorithms presents some weaknesses, the goal of this thesis is to analyze real data used in the network modeled by the human expert, implement a feasible structure learning approach and compare the results with the network designed by the expert in order to possibly enhance it.

"Offshore tower or platform foundations: numerical analysis of a laterally loaded single pile or pile group in soft clay and analysis of actions on a jacket structure"

Laterally loaded piles are a typical situation for a large number of cases in which deep foundations are used. Dissertation herein reported, is a focus upon the numerical simulation of laterally loaded piles. In the first chapter the best model settings are largely discussed, so a clear idea about the effects of interface adoption, model dimension, refinement cluster and mesh coarseness is reached. At a second stage, there are three distinct parametric analyses, in which the model response sensibility is studied for variation of interface reduction factor, Eps50 and tensile cut-off. In addition, the adoption of an advanced soil model is analysed (NGI-ADP). This was done in order to use the complex behaviour (different undrained shear strengths are involved) that governs the resisting process of clay under short time static loads. Once set a definitive model, a series of analyses has been carried out with the objective of defining the resistance-deflection (P-y) curves for Plaxis3D (2013) data. Major results of a large number of comparisons made with curves from API (America Petroleum Institute) recommendation are that the empirical curves have almost the same ultimate resistance but a bigger initial stiffness. In the second part of the thesis a simplified structural preliminary design of a jacket structure has been carried out to evaluate the environmental forces that act on it and on its piles foundation. Finally, pile lateral response is studied using the empirical curves.

Inference of Raja miraletus population structure using mitochondrial and nuclear DNA: comparing the resolution power of molecular markers in exploring species and population boundaries

This study focused on the role of oceanographic discontinuities and the presence of transitional areas in shaping the population structure and the phylogeography of the Raja miraletus species complex, coupled with the test of the effective occurrence of past speciation events. The comparisons between the Atlantic African and the North-Eastern Atlantic-Mediterranean geographic populations were unravelled using both Cytochrome Oxidase I and eight microsatellite loci. This approach guaranteed a robust dataset for the identification of a speciation event between the Atlantic African clade, corresponding to the ex Raja ocellifera nominal species, and the NE Atlantic-Mediterranean R. miraletus clade. As a matter of fact, the origin of the Atlantic Africa and the NE Atlantic-Mediterranean deep split dated about 11.74MYA and was likely due to the synergic influence currents and two upwelling areas crossing the Western African Waters. Within the Mediterranean Sea, particular attention was also paid to the transitional area represented by Adventura and Maltese Bank, that might have contributed in sustaining the connectivity of the Western and the Eastern Mediterranean geographical populations. Furthermore, the geology of the easternmost part of Sicily and the geo-morphological depression of the Calabrian Arc could have driven the differentiation of the Eastern Mediterranean Sea. Although bathymetric and oceanographic discontinuity could represent barriers to dispersal and migration between Eastern and Western Mediterranean samples, a clear and complete genetic separation among them was not detected. Results produced by this work identified a speciation event defining Raja ocellifera and R. miraletus as two different species, and describing the R. miraletus species complex as the most ancient cryptic speciation event in the family Rajidae, representing another example of how strictly connected the environment, the behavioural habits and the evolutionary and ecologic drivers are.

Aviation English: Structure and Importance of an International Airborne Language

In today’s globalized world, air travel is one of the fastest growing markets. Millions of aircrafts take off and then touch down all around the world each day. This well-synchronized symphony, however, is much more complex than it seems, and communication – language - plays a crucial role during a plane’s journey. Misunderstandings and miscommunications can have disastrous effects, so the adoption of a standard phraseology to be used during flight is a means to overcome language barriers, avoid ambiguous expressions and guarantee a safe and effective operation of an aircraft. Little is known about the interaction that goes on between pilots and air traffic controllers (ATCOs), and even though the language of aviation is English, cockpit communication can be hard to understand for people who are not familiar with this specific language. The scope of this thesis is to examine the origins of this uncommon language, the characteristics and peculiarities of air communication and to shed a little light on this mystery called Aviation English.