Articles — Thesis

This Project posits elementary analogies of existing Probabilistic and Machine Learning models that have been used to find solutions to the problem of the Structural Segmentation of Musical audio. I have tried to use the idea that the chord of a given beat or frame of a song is an analogous representation of the states generated by trained Hidden Markov Models in generating feature vectors for the aforementioned problem; and that the knowledge of the temporal boundaries within which, a group of frames lie, can be used as constraints in creating the feature vectors that are eventually clustered to identify the pattern in which the various segments of a song repeat.

The Antarctic Impulsive Transient Antenna (ANITA) is a NASA long-duration balloon experiment with the primary goal of detecting ultra-high-energy (\(> 10^{18}\)eV) neutrinos via the Askaryan Effect. In the fourth ANITA mission, the Tunable Universal Filter Frontend (TUFF) boards were deployed for mitigation of narrow-band, anthropogenic noise with tunable, switchable notch filters. They contributed to a factor of 2.8 higher total instrument livetime in ANITA-4 compared to ANITA-3. A search for a diffuse flux of ultra-high-energy neutrinos was conducted using the data collected during the ANITA-3 flight with a new approach where the Antarctic ice area is sectioned off into bins and a search is performed with different thresholds in different bins. The binned analysis methods were extended to the development of a search for neutrinos from Gamma Ray Bursts, implementing constraints in time, and for the first time, in direction. Lower analysis thresholds were achieved in a feasibility search even when extending the search to include longer afterglow periods. Authored with osudiss-2.cls (v0.9.1)

My dissertation for my Astrophysics MPhys degree at the University of Liverpool compiles research, simulations and calculations to come to concise conclusions about the feasibility of a human mission as stated in the project title.

Introduction to quantum mechanical effects and an implementation example of quantum key distribution

Musical Attitudes and Expectations

The aim of this thesis is to investigate the ability of cardiovascular biomarkers calculated from peripheral pulse waveforms to estimate central properties of the cardiovascular system (e.g. aortic stiffness) using nonlinear one-dimensional (1-D) modelling of pulse wave propagation in the arterial network. To test these biomarkers, I have produced novel 1-D models of pulse wave propagation under normal and pathological conditions. In the first part of my thesis, I extended the modelling capabilities of the existing 1-D/0-D code to represent arterial blood flow under diabetes, hypertension, and combined diabetes and hypertension. Cardiac and vascular parameters of the 1-D model were tailored to best match data available in the literature to produce generalised hypertensive, diabetic, and combined diabetic and hypertensive population models. Using these models, I have shown that the pulse waveform at the finger is strongly affected by the aortic flow wave and the muscular artery stiffness and diameter. Furthermore the peak to peak time measured from the pulse waveform at the finger can identify hypertensive from diabetic patients. In the second part, I developed a new methodology for optimising the number of arterial segments in 1-D modelling required to simulate precisely the blood pressure and flow waveforms at an arbitrary arterial location. This is achieved by systematically lumping peripheral 1-D model branches into 0-D models that preserve the net resistance and total compliance of the original model. The methodology is important to simplify the computational domain while maintaining the precision of the numerical predictions — an important step to translate 1-D modelling to the clinic. This thesis provides novel computational tools of blood flow modelling and waveform analysis for the design, development and testing of pulse wave biomarkers. These tools may help bridge the gap between clinical and computational approaches.

Se busco la posibilidad de desincronizar una red de mapas acoplados mediante la aplicacion de una perturbacion externa.

Este trabalho apresenta o estudo da performance de algoritmos de criptografia em plataformas de Internet das Coisas. O presente trabalho tem como objetivo estudar o funcionamento de algoritmo de criptografia simétrico AES e assimétrico RSA e aplicá-los a ambientes de Internet das Coisas, para que se possa avaliar o impacto na performance dos mesmos. Assim como, aplicar algoritmos de criptografia na camada de rede, na tentativa de garantir a segurança dos dados trocados em um ambiente de Internet das Coisas. Através do estudo, foi verificado que algoritmos assimétricos possuem maior impacto na performance do dispositivo, pois se baseam em cálculos complexos. Com isso, foram escolhidas plataformas utilizadas em prototipagem para mensurar o impacto no processamento. Ao realizar os testes, foi possível provar o impacto na rede e ajudar, através dos dados coletados, a escolher o algoritmo que melhor se adequa ao ambiente de Internet das Coisas, assim como, às necessidades de segurança dos mesmos. Created with the UNIFOR dissertation template

Microscopic spatial defects (inhomogeneities) in solar cells have a detrimental impact on the overall performance of the solar cells. These defects can be due to the polycrystalline nature of the photovoltaic absorber (general case) or on the other hand, the characterization method itself can induce such inhomogeneities (ex: local excitation with confocal system). Photoluminescence imaging in particular is the most attractive type of experimental character- ization technique which has been studied by many research groups. Since it is contactless, it allows a complete analysis of the photovoltaic material and it can actually be performed at each step of the solar cell fabrication process. To properly analyze the recorded images, one has to model the transport properties. In this work we model the transport properties in 2D using both a numerical and analytic approach. First,we model the global illumination of the sample, we then analyze the effects of grains and surface recombination. Second, we study lateral transport that can be influenced by recombination at the surface (passivation issues), grain boundaries (polycrystalline cells) or local artifacts (shunts, defects...). At the same time we are able to extract the lifetime knowing the generation rate and solving the excess carrier density from our model. And finally we implement our model to extract some cell parameters like the diffusion length from experimental data through data fitting.