An Image Recognition Software for Identification of Vehicle Homologation Tags

In recent years, we have witnessed great changes in the industrial environment as a result of the innovations introduced by Industry 4.0, especially in the integration of Internet of Things, Automation and Robotics in the manufacturing field. The project presented in this thesis lies within this innovation context and describes the implementation of an Image Recognition application focused on the automotive field. The project aims at helping the supply chain operator to perform an effective and efficient check of the homologation tags present on vehicles. The user contribution consists in taking a picture of the tag and the application will automatically, exploiting Amazon Web Services, return the result of the control about the correctness of the tag, the correct positioning within the vehicle and the presence of faults or defects on the tag. To implement this application we ombined two IoT platforms widely used in industrial field: Amazon Web Services(AWS) and ThingWorx. AWS exploits Convolutional Neural Networks to perform Text Detection and Image Recognition, while PTC ThingWorx manages the user interface and the data manipulation.

Edilizia sociale e prestazioni energetiche in un caso di studio a queimados all'interno del programa minha casa, minha vida: Analisi e proposte di miglioramento

Social Housing and energy performance in a study case in Queimados within the Programa Minha Casa Minha Vida: analysis and proposals for improvement. The thesis in based on a personal experience lived in Brazil, working with a firm that deals with the construction of housing, for the population with incomes between 1.600 R$ and 3.100 R$ per month, in the Programa Minha Casa Minha Vida. Thanks to the construction site and contact with the local people, it was possible to attend to the construction phases and to understand the pros and cons of this Program. Working with the company made also possible to know the costs of the construction and to see that they reached the limit budget imposed by the Program (160.000 R$). Between the critical aspects of the program there is the fact that it doesn’t deal with the energy consumptions of buildings. For that reason it was interesting to calculate the energy requirements for cooling- using the software EnergyPlus and Legacy Opens Studio plug-in for Google Sketchup- and, later, to try to propose ideas for improving performances and reduce energy consumption introducing: increase in the wall mass, frame windows and patio doors, exterior blinds, wall shading on the west side. From the analysis of these simulations, considering the decrease of energy requirements for cooling, the decrease of operative and mean radiant temperatures and costs, the most convenient proposal was the exterior curtain. As all these assumptions were too expensive for the program it was analyzed how the behavior of the inhabitants influence energy consumption. Thinking of an intelligent ventilation –opening windows while the outside temperature is lower than the inside one- the reduction of energy requirements is about 27%. These result is really important, if you consider that it is obtained without spending more money.

Robotic grasping: State of the art and modular real-world implementation

Robotic Grasping is an important research topic in robotics since for robots to attain more general-purpose utility, grasping is a necessary skill, but very challenging to master. In general the robots may use their perception abilities like an image from a camera to identify grasps for a given object usually unknown. A grasp describes how a robotic end-effector need to be positioned to securely grab an object and successfully lift it without lost it, at the moment state of the arts solutions are still far behind humans. In the last 5–10 years, deep learning methods take the scene to overcome classical problem like the arduous and time-consuming approach to form a task-specific algorithm analytically. In this thesis are present the progress and the approaches in the robotic grasping field and the potential of the deep learning methods in robotic grasping. Based on that, an implementation of a Convolutional Neural Network (CNN) as a starting point for generation of a grasp pose from camera view has been implemented inside a ROS environment. The developed technologies have been integrated into a pick-and-place application for a Panda robot from Franka Emika. The application includes various features related to object detection and selection. Additionally, the features have been kept as generic as possible to allow for easy replacement or removal if needed, without losing time for improvement or new testing.

Classificazione di oggetti in immagini attraverso il modello Bag of Visual Words

Generic object recognition is an important function of the human visual system and everybody finds it highly useful in their everyday life. For an artificial vision system it is a really hard, complex and challenging task because instances of the same object category can generate very different images, depending of different variables such as illumination conditions, the pose of an object, the viewpoint of the camera, partial occlusions, and unrelated background clutter. The purpose of this thesis is to develop a system that is able to classify objects in 2D images based on the context, and identify to which category the object belongs to. Given an image, the system can classify it and decide the correct categorie of the object. Furthermore the objective of this thesis is also to test the performance and the precision of different supervised Machine Learning algorithms in this specific task of object image categorization. Through different experiments the implemented application reveals good categorization performances despite the difficulty of the problem. However this project is open to future improvement; it is possible to implement new algorithms that has not been invented yet or using other techniques to extract features to make the system more reliable. This application can be installed inside an embedded system and after trained (performed outside the system), so it can become able to classify objects in a real-time. The information given from a 3D stereocamera, developed inside the department of Computer Engineering of the University of Bologna, can be used to improve the accuracy of the classification task. The idea is to segment a single object in a scene using the depth given from a stereocamera and in this way make the classification more accurate.

Design methods and geometric modelling of scaffolds for bone tissue engineering

Every year, thousand of surgical treatments are performed in order to fix up or completely substitute, where possible, organs or tissues affected by degenerative diseases. Patients with these kind of illnesses stay long times waiting for a donor that could replace, in a short time, the damaged organ or the tissue. The lack of biological alternates, related to conventional surgical treatments as autografts, allografts, e xenografts, led the researchers belonging to different areas to collaborate to find out innovative solutions. This research brought to a new discipline able to merge molecular biology, biomaterial, engineering, biomechanics and, recently, design and architecture knowledges. This discipline is named Tissue Engineering (TE) and it represents a step forward towards the substitutive or regenerative medicine. One of the major challenge of the TE is to design and develop, using a biomimetic approach, an artificial 3D anatomy scaffold, suitable for cells adhesion that are able to proliferate and differentiate themselves as consequence of the biological and biophysical stimulus offered by the specific tissue to be replaced. Nowadays, powerful instruments allow to perform analysis day by day more accurateand defined on patients that need more precise diagnosis and treatments.Starting from patient specific information provided by TC (Computed Tomography) microCT and MRI(Magnetic Resonance Imaging), an image-based approach can be performed in order to reconstruct the site to be replaced. With the aid of the recent Additive Manufacturing techniques that allow to print tridimensional objects with sub millimetric precision, it is now possible to practice an almost complete control of the parametrical characteristics of the scaffold: this is the way to achieve a correct cellular regeneration. In this work, we focalize the attention on a branch of TE known as Bone TE, whose the bone is main subject. Bone TE combines osteoconductive and morphological aspects of the scaffold, whose main properties are pore diameter, structure porosity and interconnectivity. The realization of the ideal values of these parameters represents the main goal of this work: here we'll a create simple and interactive biomimetic design process based on 3D CAD modeling and generative algorithmsthat provide a way to control the main properties and to create a structure morphologically similar to the cancellous bone. Two different typologies of scaffold will be compared: the first is based on Triply Periodic MinimalSurface (T.P.M.S.) whose basic crystalline geometries are nowadays used for Bone TE scaffolding; the second is based on using Voronoi's diagrams and they are more often used in the design of decorations and jewellery for their capacity to decompose and tasselate a volumetric space using an heterogeneous spatial distribution (often frequent in nature). In this work, we will show how to manipulate the main properties (pore diameter, structure porosity and interconnectivity) of the design TE oriented scaffolding using the implementation of generative algorithms: "bringing back the nature to the nature".

Struttura di età di nasello (Merluccius merluccius, Linnaeus, 1758) in alto-medio Adriatico mediante analisi degli otoliti e frequenza di taglia

The aim of present study is to define the general framework of Merluccius merluccius population structure, to estimate the growth rate and to assess the recruitment dynamics of juveniles from Northern and Central Adriatic, through otoliths analysis. The otoliths of hake specimens collected during the MedITS trawl survey in the 2012 in GSA 17, were cleaned and 102 otoliths out of 506 were embedded, sectioned, grindined and polished to obtain frontal and sagittal sections. The whole sample were analysed under stereomicroscope and optical microscope, with camera and connected to PC provided of an image analyses program. The frequency analysis of size classes and age revealed that the species is dominated by hake with >200mm TL and > one year old. The fish average size of M. merluccius at the end of the first year of life is about 199 mm TL. Allometrics analyses between fish TL and Feret (major axis), MiniFeret (minor axis), Area, Perimeter, showed a direct proportionality among lengths. Among the 88 otoliths sections analysed, the number of daily increments read ranged from 86 to 206, within 55 and 175mm TL range. The age estimate ranged from about 2-3 to 9 months and the growth rate from 20.99 to 27.15mm TL. The hatch-date distribution, obtained by back calculation, showed that the hatching occurs in November-March. In conclusion, strong preventive measures are needed for hake adults because the success of this species seems to be linked to deep water ecosystem protection where big spawners dwell.