Optical coherence tomography (OCT) is a rapidly growing imaging modality that produces high resolution three dimensional images that can be applied to different medical and industrial applications . Obtaining higher depth of imaging and higher imaging quality are important goals in OCT systems. One of the main factors that affects the penetration depth and imaging quality of OCT systems is the presence of noise. The depth-scan photocurrent of time domain (TD) OCT system is degraded by a class of correlated and signal dependent noise. The joint probability density function of the depth-scan photocurrent can be considered as Gaussian random process that is completely characterized by its second order statistics. Both the mean and the covariance functions of the depth-scan photocurrent are functions of the depth variant axial reflectance of the object. We present a stable and computationally efficient OCT image restoration technique to obtain the maximum likelihood estimates of the axial reflectance of the object and to estimate the electrical noise variance. / February 2016

This thesis is an investigation of "Using POMDP-based Reinforcement Learning for Online Optimization of Teaching Strategies in an Intelligent Tutoring System". A challenge in building an intelligent tutoring system (ITS) is to create and maintain an optimal teaching strategy. We cast an ITS as a partially observable Markov decision process (POMDP), and apply a reinforcement learning (RL) algorithm to learn the optimal teaching strategy through interactions between the system and the students. The optimal teaching strategy is chosen correctly and e ciently in tutoring a student, it is also learned and maintained in an online model. We present an RL algorithm based on POMDP for learning optimal teaching strategy, then describe the experiments and analyse the experimental results. The experiment has showed that the technique can remarkably improve an ITS's teaching performance / Using POMDP-based Reinforcement Learning for Online Optimization of Teaching Strategies in an Intelligent Tutoring System

This Master Thesis is the research done in the country of Rwanda. The project leads to study the climate of this country in order to establish whether this climate could be used to produce energy from air and to implement the first wind turbine for serving the nation.   After an introduction about the historical background of wind power, the thesis work deals with assessment of wind energy potential of Rwanda in focusing of the most suitable place for wind power plants. The best location with annual mean wind speed, the rate of use of turbine with hub height for an annual production per year, the mean wind speeds for 6 sites of Rwanda based on ECMWF for climatic data for one year at relief of altitude of 100m and coordinates are reported too.   The result of energy produced and calculations were done based on power hitting wind turbine generator in order to calculate Kinetic energy and power available at the best location to the measurement over the period of 12 months, that could be hoped for long term.   With help of logarithmic law, where wind speed usually increases with increasing in elevation and the desired wind speeds at all 6 sites were used. The annual energy production was taken into account at the best site with desired wind speed at the initial cost of turbine as well as the cost of energy (COE).However, with comparison of the tariff of EWSA, the price of Wind designed in this Research per kWh is cheaper and suitable for people of Rwanda. / <p><em>Rwanda has considerable opportunities development energy from hydro sources, methane gas, solar and peat deposits. Most of these energy sources have not been fully exploited, such as solar, wind and geothermal. As such wood is still being the major source of energy for 94 per cent of the population and imported petroleum products consume more than 40 per cent of foreign exchange. Energy is a key component of the Rwandan economy. It is thus recognized that the current inadequate and expensive energy supply constitutes a limiting factor to sustainable development. Rwanda’s Vision 2020 emphasizes the need for economic growth, private investment and economic transformation supported by a reliable and affordable energy supply as a key factor for the development process. To achieve this transformation, the country will need to increase energy production and diversify into alternative energy sources. Rwandan nations don’t have small-scale solar, wind, and geothermal devices in operation providing energy to urban and rural areas. These types of energy production are especially useful in remote locations because of the excessive cost of transporting electricity from large-scale power plants. The application of renewable energy technology has the potential to alleviate many of the problems that face the people of Rwanda every day, especially if done so in a sustainable manner that prioritizes human rights.</em></p>