Articles — University

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

University Assignment

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

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 trabajo presenta la aplicación de un conjunto de articulos con propias teorías de los robots manipuladores y el modelamiento de pinzas. Para ello el brazo humano se modela como un robot manipulador redundante. En particular se aplica el concepto de índices de desempeño para predecir posturas óptimas del brazo durante la realización de tareas. En el estudio se incluyen tanto estructuras estáticas, como tambien los analisis de estabilidad del brazo y los materiales para su respectiva realizacion. This work presents the application of a set of articles with the own theories of the manipulative robots and the modeling of tweezers. For this, the bearing is modeled as a redundant manipulator robot. In particular, the concept of performance indices is applied to predict the optimal postures of the task during the performance of tasks. The study includes both static structures, as well as safety management analyzes and materials for their respective realization.

In most corruption scandals, the use of front companies for money laundering is almost ubiquitous. This work proposes to apply image classification to detect such organizations, through the use of Convolutional Neural Networks (CNN), namely the AlexNet architecture. The images are obtained by address search in Google Street View API, and the resulting classification will be further used along with other features to detect front com- panies in order to help the auditors from the Ministry of Transparency and Office of the Comptroller General (CGU, in Portuguese). To this moment, we applied classification to almost 15 thousand suppliers scenes with active contracts with the Brazilian Government until September 2016, obtained through data matching between the Government Purchases database and the Brazilian Federal Revenue Office database (more recent scenes should be added as this work progresses). Preliminary results with a pre-trained AlexNet CNN show the need for developing new scene classes more suited to the Brazilian context. In order to do this, we propose to apply clustering algorithms in features extracted from the last fully-connected layer of this net. The classes obtained will be used to fine-tune the AlexNet CNN for future classification, through the use of training from scratch or fine tuning techniques.

A basic understanding on Bayes' theorem and how to apply it to baseball statistics.

solucion es alos efectos decorrosión en estructuras de concreto armado