Simultaneous localization and mapping (SLAM) is the problem of mapping your surroundings while simultaneously localizing yourself in the map. It is an important and active area of research for robotics. In this master thesis two approaches are attempted to reduce the drift which appears over time in SLAM algorithms. The first approach tries 3 different motion models for the camera. Two of the models exploit the a priori knowledge that the camera is mounted on a trolley. These two methods are shown to improve the results. The second approach attempts to reduce the drift by reducing noise in the point cloud data used for mapping. This is done by finding planar surfaces in the point clouds. Median filtering is used as an alternative to compare the result for noise reduction. The planes estimation approach is also shown to reduce the drift, while the median estimation makes it worse. / Simultaneous localization and mapping (SLAM) är problemet att kartlägga sin omgivning samtidigt som man lokaliserar sig själv i kartan. Det är ett viktigt och aktivt forskningsområde inom robotik. I det här exjobbet testas två tillvägagångssätt för att minska felet i kameraposition och orientering som uppstår över tiden i SLAM-lösningar. Det första tillvägagångssättet testar 3 olika rörelsemodeller för kameran. Två av modellerna utnyttjar vetskapen om att kameran sitter monterad på en vagn. Dessa två metoder förbättrar resultatet för SLAM-algoritmen. Det andra tillväggagångssättet försöker minska felet genom att reducera bruset i punktmolnsdatan som används i kartläggningen. Det görs genom att hitta plana ytor i punktmolnen. Medianfiltrering används som en alternativ lösning för att jämföra hur bra planestimeringen står sig. Planestimeringen visar sig också minska felet i lösningen, medan medianfiltreringen endast försämrar resultatet.

It is commonly accepted that the induced noise on DFT phase spectrum has a negligible effect on speech intelligibility for short durations of analysis windows, as the early intelligibility studies pointed out. This fact is confirmed by recent intelligibility studies as well. Based on this phenomenon, classical speech enhancement algorithms do not modify DFT phase spectrum and only make changes in the DFT magnitude spectrum. However, in recent studies it is also indicated that these classical speech enhancement algorithms are not capable of improving the intelligibility scores of noise degraded speech signals. In other words, the contained information in a noise degraded signal cannot be increased by classical enhancement methods. Instead the ease of listening, i.e. quality, can be improved. Hence additional effort can be made to increase the amount of quality improvement using both DFT magnitude and DFT phase. Therefore if the performances of the classical methods are to be improved in terms of speech quality, the effect of DFT phase on speech quality needs to be studied. In this work, the contribution of DFT phase on speech quality is investigated through some simulations using an objective quality assessment criterion. It is concluded from these simulations that, the phase spectrum has a significant effect on speech quality for short durations of analysis windows. Furthermore, phase values of low frequency components are found to have the largest contribution to this quality improvement. Under the motivation of these results, a new enhancement method is proposed which modifies the phase of certain low frequency components as well as the magnitude spectrum. The proposed algorithm is implemented in MATLAB environment. The results indicate that the proposed system improves the performance of the classical methods in terms of speech quality.

This study uses a combination of user testing and analysis to evaluate the impact of brush and tooltip on the comprehension of time series visualizations. Employing a sequential mixed-methods approach, with qualitative data from semi-structured interviews used to inform the design of a visualization tool, followed by a quantitative user study to validate it. Sixteen (16) participants from various fields of study, predominantly computer science, participated in the study. A MANOVA test was conducted with results indicating a significant statistical difference between the groups. Results deriving from the study show that the use of brush and tooltip increases user accuracy on detecting outliers, as for perception of trends and patterns. The study’s context was limited to desktop usage, and all participants were treated as a homogenous group, presenting potential limitations in applying these findings to other devices or more diverse user groups. The results provide information about improving time series data visualizations for facilitating more efficient and effective understanding, which can be relevant specifically to data analysts and academic researchers.

This study uses a combination of user testing and analysis to evaluate the impact of brush and tooltip on the comprehension of time series visualizations. Employing a sequential mixed-methods approach, with qualitative data from semi-structured interviews used to inform the design of a visualization tool, followed by a quantitative user study to validate it. Sixteen (16) participants from various fields of study, predominantly computer science, participated in the study. A MANOVA test was conducted with results indicating a significant statistical difference between the groups. Results deriving from the study show that the use of brush and tooltip increases user accuracy on detecting outliers, as for perception of trends and patterns. The study’s context was limited to desktop usage, and all participants were treated as a homogenous group, presenting potential limitations in applying these findings to other devices or more diverse user groups. The results provide information about improving time series data visualizations for facilitating more efficient and effective understanding, which can be relevant specifically to data analysts and academic researchers.

Questa tesi presenta i risultati teorici, metodologici ed empirici di una ricerca di dottorato incentrata sul tema della percezione del tempo nell’esperienza cinematografica. La prima parte fornisce un’introduzione teorica al tema. Il Capitolo 1 precisa il taglio e l’oggetto della ricerca. Il Capitolo 2 presenta i principali modelli teorici di percezione del tempo. Il Capitolo 3 si concentra sulla percezione del tempo nel contesto cinematografico. La seconda parte comprende gli esperimenti condotti nel corso della ricerca. Il Capitolo 4 illustra il primo esperimento. Attraverso misure comportamentali, questo studio ha indagato gli effetti sulla stima di durata e sulla percezione del passaggio del tempo di due variabili cinematografiche: il tipo di azione rappresentata e lo stile di montaggio. Il Capitolo 5 presenta il secondo esperimento. Tramite un metodo chiamato micro-fenomenologia, questo studio ha esplorato i processi esperienziali che fondano i compiti di stima di durata e percezione del passaggio del tempo. Il Capitolo 6 descrive il terzo esperimento. Attraverso una tecnica di neurostimolazione (tDCS), questo studio ha testato il coinvolgimento di una specifica area cerebrale (Area Supplementare Motoria) negli stessi compiti temporali. La terza parte riassume i risultati della ricerca (Capitolo 7) e discute possibili futuri sviluppi di quest’ultima (Capitolo 8). / This dissertation presents the theoretical, methodological, and empirical results of a doctoral research concerning time perception in the experience of cinema. The first part provides a theoretical introduction to the topic. Chapter 1 carves out the dissertation’s precise angle and object. Chapter 2 presents the main models of subjective time perception. Chapter 3 restricts the scope to time perception in the specific context of cinema. The second part reports about the three experiments conducted during the research. Chapter 4 introduces the first experiment. By using behavioural measures, this study addressed the effects on duration estimation and time passage perception of two cinematographic variables: the type of represented action and the style of editing. Chapter 5 presents the second experiment. By adopting a method called micro-phenomenology, this study explored the processes underlying the performance of the duration estimation and time passage perception tasks. Chapter 6 is devoted to the third experiment. By using a neurostimulation technique (tDCS), this study tested the involvement of a specific brain area (the Supplementary Motor Area) in the same timing tasks. The third part summarizes the essential findings of the research (Chapter 7) and re-opens it to some of its possible future developments (Chapter 8).