"The capacity of contrastive analysis to successfully predict the errors of second language learners - a case study"

The aim of this dissertation is to show the power of contrastive analysis in successfully predicting the errors a language learner will make by means of a concrete case study. First, there is a description of what language transfer is and why it is important in the matter of second language acquisition. Second, a brief explanation of the history and development of contrastive analysis will be offered. Third, the focus of the thesis will move to an analysis of errors usually made by language learners. To conclude, the dissertation will focus on the concrete case study of a Russian learner of English: after an analysis of the errors the student is likely to make, a recorded conversation will be examined.

Target Tracking in UWB Multistatic Radars

Detection, localization and tracking of non-collaborative objects moving inside an area is of great interest to many surveillance applications. An ultra- wideband (UWB) multistatic radar is considered as a good infrastructure for such anti-intruder systems, due to the high range resolution provided by the UWB impulse-radio and the spatial diversity achieved with a multistatic configuration. Detection of targets, which are typically human beings, is a challenging task due to reflections from unwanted objects in the area, shadowing, antenna cross-talks, low transmit power, and the blind zones arised from intrinsic peculiarities of UWB multistatic radars. Hence, we propose more effective detection, localization, as well as clutter removal techniques for these systems. However, the majority of the thesis effort is devoted to the tracking phase, which is an essential part for improving the localization accuracy, predicting the target position and filling out the missed detections. Since UWB radars are not linear Gaussian systems, the widely used tracking filters, such as the Kalman filter, are not expected to provide a satisfactory performance. Thus, we propose the Bayesian filter as an appropriate candidate for UWB radars. In particular, we develop tracking algorithms based on particle filtering, which is the most common approximation of Bayesian filtering, for both single and multiple target scenarios. Also, we propose some effective detection and tracking algorithms based on image processing tools. We evaluate the performance of our proposed approaches by numerical simulations. Moreover, we provide experimental results by channel measurements for tracking a person walking in an indoor area, with the presence of a significant clutter. We discuss the existing practical issues and address them by proposing more robust algorithms.

Scene Reconstruction And Understanding By RGB-D Sensors

This thesis investigates interactive scene reconstruction and understanding using RGB-D data only. Indeed, we believe that depth cameras will still be in the near future a cheap and low-power 3D sensing alternative suitable for mobile devices too. Therefore, our contributions build on top of state-of-the-art approaches to achieve advances in three main challenging scenarios, namely mobile mapping, large scale surface reconstruction and semantic modeling. First, we will describe an effective approach dealing with Simultaneous Localization And Mapping (SLAM) on platforms with limited resources, such as a tablet device. Unlike previous methods, dense reconstruction is achieved by reprojection of RGB-D frames, while local consistency is maintained by deploying relative bundle adjustment principles. We will show quantitative results comparing our technique to the state-of-the-art as well as detailed reconstruction of various environments ranging from rooms to small apartments. Then, we will address large scale surface modeling from depth maps exploiting parallel GPU computing. We will develop a real-time camera tracking method based on the popular KinectFusion system and an online surface alignment technique capable of counteracting drift errors and closing small loops. We will show very high quality meshes outperforming existing methods on publicly available datasets as well as on data recorded with our RGB-D camera even in complete darkness. Finally, we will move to our Semantic Bundle Adjustment framework to effectively combine object detection and SLAM in a unified system. Though the mathematical framework we will describe does not restrict to a particular sensing technology, in the experimental section we will refer, again, only to RGB-D sensing. We will discuss successful implementations of our algorithm showing the benefit of a joint object detection, camera tracking and environment mapping.

Wavetrack, implementazione ottimizzata di un algoritmo di pitch tracking basato su wavelet

WaveTrack é un'implementazione ottimizzata di un algoritmo di pitch tracking basato su wavelet, nello specifico viene usata la trasformata Fast Lifting Wavelet Transform con la wavelet di Haar. La libreria è stata scritta nel linguaggio C e tra le sue peculiarità può vantare tempi di latenza molto bassi, un'ottima accuratezza e una buona flessibilità d'uso grazie ad alcuni parametri configurabili.

Software tools and efficient algorithms for the feature detection, feature tracking, event localization, and visualization of large sets of atmospheric data

Data sets describing the state of the earth's atmosphere are of great importance in the atmospheric sciences. Over the last decades, the quality and sheer amount of the available data increased significantly, resulting in a rising demand for new tools capable of handling and analysing these large, multidimensional sets of atmospheric data. The interdisciplinary work presented in this thesis covers the development and the application of practical software tools and efficient algorithms from the field of computer science, aiming at the goal of enabling atmospheric scientists to analyse and to gain new insights from these large data sets. For this purpose, our tools combine novel techniques with well-established methods from different areas such as scientific visualization and data segmentation. In this thesis, three practical tools are presented. Two of these tools are software systems (Insight and IWAL) for different types of processing and interactive visualization of data, the third tool is an efficient algorithm for data segmentation implemented as part of Insight.Insight is a toolkit for the interactive, three-dimensional visualization and processing of large sets of atmospheric data, originally developed as a testing environment for the novel segmentation algorithm. It provides a dynamic system for combining at runtime data from different sources, a variety of different data processing algorithms, and several visualization techniques. Its modular architecture and flexible scripting support led to additional applications of the software, from which two examples are presented: the usage of Insight as a WMS (web map service) server, and the automatic production of a sequence of images for the visualization of cyclone simulations. The core application of Insight is the provision of the novel segmentation algorithm for the efficient detection and tracking of 3D features in large sets of atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. Data segmentation usually leads to a significant reduction of the size of the considered data. This enables a practical visualization of the data, statistical analyses of the features and their events, and the manual or automatic detection of interesting situations for subsequent detailed investigation. The concepts of the novel algorithm, its technical realization, and several extensions for avoiding under- and over-segmentation are discussed. As example applications, this thesis covers the setup and the results of the segmentation of upper-tropospheric jet streams and cyclones as full 3D objects. Finally, IWAL is presented, which is a web application for providing an easy interactive access to meteorological data visualizations, primarily aimed at students. As a web application, the needs to retrieve all input data sets and to install and handle complex visualization tools on a local machine are avoided. The main challenge in the provision of customizable visualizations to large numbers of simultaneous users was to find an acceptable trade-off between the available visualization options and the performance of the application. Besides the implementational details, benchmarks and the results of a user survey are presented.

Effiziente und robuste, feature-basierte Wiedererkennung langer Zeitreihen in großen Datenbanken

Die Materialverfolgung gewinnt in der Metallindustrie immer mehr an Bedeutung:rnEs ist notwendig, dass ein Metallband im Fertigungsprozess ein festgelegtes Programm durchläuft - erst dann ist die Qualität des Endprodukts garantiert. Die bisherige Praxis besteht darin, jedem Metallband eine Nummer zuzuordnen, mit der dieses Band beschriftet wird. Bei einer tagelangen Lagerung der Bänder zwischen zwei Produktionsschritten erweist sich diese Methode als fehleranfällig: Die Beschriftungen können z.B. verloren gehen, verwechselt, falsch ausgelesen oder unleserlich werden. 2007 meldete die iba AG das Patent zur Identifikation der Metallbänder anhand ihres Dickenprofils an (Anhaus [3]) - damit kann die Identität des Metallbandes zweifelsfrei nachgewiesen werden, eine zuverlässige Materialverfolgung wurde möglich.Es stellte sich jedoch heraus, dass die messfehlerbehafteten Dickenprofile, die als lange Zeitreihen aufgefasst werden können, mit Hilfe von bisherigen Verfahren (z.B. L2-Abstandsminimierung oder Dynamic Time Warping) nicht erfolgreich verglichen werden können.Diese Arbeit stellt einen effizienten feature-basierten Algorithmus zum Vergleichrnzweier Zeitreihen vor. Er ist sowohl robust gegenüber Rauschen und Messausfällen als auch invariant gegenüber solchen Koordinatentransformationen der Zeitreihen wie Skalierung und Translation. Des Weiteren sind auch Vergleiche mit Teilzeitreihen möglich. Unser Framework zeichnet sich sowohl durch seine hohe Genauigkeit als auch durch seine hohe Geschwindigkeit aus: Mehr als 99.5% der Anfragen an unsere aus realen Profilen bestehende Testdatenbank werden richtig beantwortet. Mit mehreren hundert Zeitreihen-Vergleichen pro Sekunde ist es etwa um den Faktor 10 schneller als die auf dem Gebiet der Zeitreihenanalyse etablierten Verfahren, die jedoch nicht im Stande sind, mehr als 90% der Anfragen korrekt zu verarbeiten. Der Algorithmus hat sich als industrietauglich erwiesen. Die iba AG setzt ihn in einem weltweit einzigartigen dickenprofilbasierten Überwachungssystemrnzur Materialverfolgung ein, das in ersten Stahl- und Aluminiumwalzwerkenrnbereits erfolgreich zum Einsatz kommt.

Tracking di oggetti mediante la libreria opencv

Tracking di oggetti mediante la libreria opencv

Sviluppo e validazione sperimentale di un software di acquisizione ed elaborazione dati provenienti da un sistema di eye tracking per lo studio dei movimenti oculari

L'argomento del seguente lavoro di tesi è lo sviluppo di un software per acquisire e elaborare i dati provenienti da un sistema di eye tracking, per lo studio dei movimenti oculari.

Sicurezza stradale: Proposta di traduzione di un estratto del research report "The Nature of Errors Made by Drivers"

The aim of this dissertation is to provide a translation from English into Italian of an extract from the research report “The Nature of Errors Made by Drivers”. The research was conducted by the MUARC (the Monash University Accident Research Centre) and published in June 2011 by Austroads, the association of Australasian road transport and traffic agencies. The excerpt chosen for translation is the third chapter, which provides an overview of the on-road pilot study conducted to analyse why drivers make mistakes during their everyday drive, including the methodology employed and the results obtained. This work is divided into six sections. It opens with an introduction on the topic and the formal structure of the report, followed by the first chapter, which provides an overview of the main features of the languages for special purposes and the specialised texts, an analysis of the text type and a presentation of the extract chosen for translation. In the second chapter the linguistic and extralinguistic resources available to specialised translators are presented, focussing on the ones used to translate the text. The third chapter is dedicated to the source text and its translation, while the fourth one provides an analysis of the strategies chosen to translate the text and a comment on the solutions to problematic passages. Finally, the last section – the conclusion – provides a comment on the entire work and on the professional activity of translators. The work closes with an appendix, which contains a glossary of the terms extracted from the translated text.

Tecniche di ottimizzazione dell'advertising online tramite eye-tracking: un modello sperimentale

La tesi analizza l'attuale offerta dell'advertising online, ne individua alcune problematiche e valuta una possibile soluzione, tramite l'elaborazione di un nuovo modello di costo. Tale modello è basato sul tempo di persistenza dello sguardo rilevato tramite dispositivo di eye-tracking. L'obiettivo della tesi è quindi la creazione di un tool per raccogliere i dati dal dispositivo e, infine, restituire i risultati grafici e testuali generati dalla funzione di costo.

Online advertising: analisi attraverso eye tracking della percezione di un banner in una pagina web commerce

La mia tesi è formata da tre capitoli. Il primo capito è composto da due parti: -Nella prima parte ho descritto l'online advertising dalla sua nascita fino alle diverse categorie attualmente presenti sul mercato. -Nella seconda parte ho descritto i processi cognitivi della mente umana, più nello specifico, i fattori che influenzano le scelte degli utilizzatori del web. Il secondo capitolo comprende un'unica parte dove ho descritto il funzionamento e i principali settori di utilizzo del dispositivo di remote tracker che ho utilizzato nel terzo ed ultimo capitolo, contenente la parte di sperimentazione. Il terzo capitolo è la parte sperimentale, dove ho eseguito una scrupolosa analisi finalizzata alla stipulazione di fondate ipotesi su efficaci strategie di posizionano di banner pubblicitari in una pagina web.

Localizzazione e tracking tramite filtri statistici in sistemi multi antenna

Uno dei temi più recenti nel campo delle telecomunicazioni è l'IoT. Tale termine viene utilizzato per rappresentare uno scenario nel quale non solo le persone, con i propri dispositivi personali, ma anche gli oggetti che le circondano saranno connessi alla rete con lo scopo di scambiarsi informazioni di diversa natura. Il numero sempre più crescente di dispositivi connessi in rete, porterà ad una richiesta maggiore in termini di capacità di canale e velocità di trasmissione. La risposta tecnologica a tali esigenze sarà data dall’avvento del 5G, le cui tecnologie chiave saranno: massive MIMO, small cells e l'utilizzo di onde millimetriche. Nel corso del tempo la crescita delle vendite di smartphone e di dispositivi mobili in grado di sfruttare la localizzazione per ottenere servizi, ha fatto sì che la ricerca in questo campo aumentasse esponenzialmente. L'informazione sulla posizione viene utilizzata infatti in differenti ambiti, si passa dalla tradizionale navigazione verso la meta desiderata al geomarketing, dai servizi legati alle chiamate di emergenza a quelli di logistica indoor per industrie. Data quindi l'importanza del processo di positioning, l'obiettivo di questa tesi è quello di ottenere la stima sulla posizione e sulla traiettoria percorsa da un utente che si muove in un ambiente indoor, sfruttando l'infrastruttura dedicata alla comunicazione che verrà a crearsi con l'avvento del 5G, permettendo quindi un abbattimento dei costi. Per fare ciò è stato implementato un algoritmo basato sui filtri EKF, nel quale il sistema analizzato presenta in ricezione un array di antenne, mentre in trasmissione è stato effettuato un confronto tra due casi: singola antenna ed array. Lo studio di entrambe le situazioni permette di evidenziare, quindi, i vantaggi ottenuti dall’utilizzo di sistemi multi antenna. Inoltre sono stati analizzati altri elementi chiave che determinano la precisione, quali geometria del sistema, posizionamento del ricevitore e frequenza operativa.

Analisi sperimentale sull'utilizzo del Microsoft Kinect One come sistema di Body Tracking per la realta virtuale in riabilitazione

In questo progetto di tesi sarà innanzitutto presentato il Kinect One e sarà fatta una panoramica sull’uso della realtà virtuale in ambito riabilitativo. In seguito sarà analizzato l’algoritmo di Body tracking, valutandone il comportamento in diverse situazioni pratiche e poi stimandone la precisione in statica. Sarà presentato un filtraggio per limitare il rumore in tempo reale e valutarne i pro ed i contro in funzione delle caratteristiche impostabili. Saranno presentate inoltre le metodologie con cui gli algoritmi integrati del Kinect permettono di ricavare una stima dell’orientamento delle parti anatomiche nello spazio ed alcune considerazioni circa le implicazioni pratiche di tali metodologie, anche in base alle osservazioni sul campo ottenute durante i mesi di realizzazione di questo progetto. Lo scopo è determinare se e come sia possibile utilizzare il Microsoft Kinect One come unico sistema di motion tracking del paziente in applicazioni cliniche di riabilitazione, quali limiti ci sono nel suo utilizzo e quali categorie di scenari e prove potrebbe supportare.

Why do humans make antisaccade errors?

Antisaccade errors are attributed to failure to inhibit the habitual prosaccade. We investigated whether the amount of information about the required response the patient has before the trial begins also contributes to error rate. Participants performed antisaccades in five conditions. The traditional design had two goals on the left and right horizontal meridians. In the second condition, stimulus-goal confusability between trials was eliminated by displacing one goal upward. In the third, hemifield uncertainty was eliminated by placing both goals in the same hemifield. In the fourth, goal uncertainty was eliminated by having only one goal, but interspersed with no-go trials. The fifth condition eliminated all uncertainty by having the same goal on every trial. Antisaccade error rate increased by 2% with each additional source of uncertainty, with the main effect being hemifield information, and a trend for stimulus-goal confusability. A control experiment for the effects of increasing angular separation between targets without changing these types of prior response information showed no effects on latency or error rate. We conclude that other factors besides prosaccade inhibition contribute to antisaccade error rates in traditional designs, possibly by modulating the strength of goal activation.