Proposta di traduzione di "Cette fille a du style" di Marie-Sophie Vermot

Il presente elaborato si pone l'obiettivo di fornire una proposta di traduzione del romanzo per ragazzi "Cette fille a du style". Il primo capitolo presenta una panoramica dell'evoluzione dei personaggi femminili nella letteratura per ragazzi in Italia e in Francia, sicuramente breve e non esaustiva ma volta a mostrare come i libri abbiano accompagnato le ragazze e come le ragazze siano cambiate con loro. A questa segue la presentazione dell'autrice del libro, della casa editrice e infine del romanzo in questione attraverso un'analisi tematica e stilistica, con particolare attenzione alla questione della serialità. Il secondo capitolo è costituito dalla proposta di traduzione del romanzo, che sarà commentata nel capitolo successivo. L'ultimo capitolo affronta la questione della traduzione dal punto di vista del genere, inizialmente riferita all'intera produzione letteraria e in seguito approfondita per il romanzo oggetto di questa tesi. La sezione successiva ha come scopo quello di fornire una breve panoramica del linguaggio della moda, dalla sua nascita fino alle sue più recenti evoluzioni, cui fa seguito un’analisi mirata degli aspetti traduttivi risultati particolarmente ostici e le relative soluzioni. Infine, si è ipotizzato un possibile inserimento della traduzione di "Cette fille a du style" all’interno del panorama editoriale italiano, confrontando le opere della stessa autrice già tradotte nel nostro Paese.

Conceptualization of an Electric Compact SUV for the American and Italian Market using the IDeS Method

Electric cars are increasingly popular due to a transition of mobility towards more sustainable forms. From an increasingly green and pollution reduction perspective, there are more and more incentives that encourage customers to invest in electric cars. Using the Industrial Design and Structure (IDeS) research method, this project has the aim to design a new electric compact SUV suitable for all people who live in the city, and for people who move outside urban areas. In order to achieve the goal of developing a new car in the industrial automotive environment, the compact SUV segment was chosen because it is a vehicle very requested by the costumers and it is successful in the market due to its versatility. IDeS is a combination of innovative and advanced systematic approaches used to set up a new industrial project. The IDeS methodology is sequentially composed of Quality Function Deployment (QFD), Benchmarking (BM), Top-Flop analysis (TFA), Stylistic Design Engineering (SDE), Design for X, Prototyping, Testing, Budgeting, and Planning. The work is based on a series of steps and the sequence of these must be meticulously scheduled, imposing deadlines along the work. Starting from an analysis of the market and competitors, the study of the best and worst existing parameters in the competitor’s market is done, arriving at the idea of a better product in terms of numbers and innovation. After identifying the characteristics that the new car should have, the other step is the styling part, with the definition of the style and the design of the machine on a 3D CAD. Finally, it switches to the prototyping and testing phase to see if the product is able to work. Ultimately, intending to place the car on the market, it is essential to estimate the necessary budget for a possible investment in this project.

Deep learning based style transfer for low altitude aerial imagery

Unmanned Aerial Vehicle (UAVs) equipped with cameras have been fast deployed to a wide range of applications, such as smart cities, agriculture or search and rescue applications. Even though UAV datasets exist, the amount of open and quality UAV datasets is limited. So far, we want to overcome this lack of high quality annotation data by developing a simulation framework for a parametric generation of synthetic data. The framework accepts input via a serializable format. The input specifies which environment preset is used, the objects to be placed in the environment along with their position and orientation as well as additional information such as object color and size. The result is an environment that is able to produce UAV typical data: RGB image from the UAVs camera, altitude, roll, pitch and yawn of the UAV. Beyond the image generation process, we improve the resulting image data photorealism by using Synthetic-To-Real transfer learning methods. Transfer learning focuses on storing knowledge gained while solving one problem and applying it to a different - although related - problem. This approach has been widely researched in other affine fields and results demonstrate it to be an interesing area to investigate. Since simulated images are easy to create and synthetic-to-real translation has shown good quality results, we are able to generate pseudo-realistic images. Furthermore, object labels are inherently given, so we are capable of extending the already existing UAV datasets with realistic quality images and high resolution meta-data. During the development of this thesis we have been able to produce a result of 68.4% on UAVid. This can be considered a new state-of-art result on this dataset.