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The 1215 MHz to 1400 MHz band is important for radio astronomers to observe redshifted extragalactic hydrogen ionic (HI). Observations at these frequencies are complicated by radio frequency interference (RFI) from strong man-made transmissions such as the ARSR-3 Air Surveillance Radar. In this thesis, we characterize some data files recorded at the National Radio Astronomy Observatory (NRAO) at Green Bank, West Virginia, USA, where this RADAR system causes significant data corruption. Using this data, we present a blanking technique to separate RFI from cosmic signal. There are generally two blanking approaches, time window blanking and detected pulse blanking. Compared with time window blanking, the advantage of detected pulse blanking is that the loss of integration time is much less (i.e. less data is discarded). But some pulses fail to be blanked because they are too weak to detect. So in order to blank weak pulses, it is desirable to optimize detection performance. In this work, we will combine these two blanking techniques and present a new Bayesian algorithm which combines Kalman tracking with pulse detection. This new algorithm will help to locate the weaker or missed detections, so as to help improve the performance of pulse blanking.

As of 2014, 81% of sub-Saharan population or 792 million people rely on the traditional use of biomass to provide in their cooking needs. This situation causes harmful health, environmental, and development hazards with a substantial annual economic cost of USD58.2 billion. The concern about the issue of access to clean cooking facilities is growing as international organizations and national governments define steps to transform the existing situation. Literature provides a good view on determinants for the cooking fuel choice in developing regions, but comprehensive outlooks for the future cooking fuel mix in sub-Saharan countries are limited. To this extent, the presented master's thesis aims to shed light on a history-inspired pathway for the evolution of the biomass dominated cooking fuel mix in sub-Saharan countries to 2050. A quantitative model was developed to estimate the future uptake of various cooking technologies, from which the fuel mix can be derived using energy intensities. Projections were constructed for urban and rural areas in 45 countries. Economic development, population expansion, urbanization, and to a certain extent policies are the key drivers of the model. Despite a moderate improvement in the share of population relying on traditional biomass, 808 million people in sub-Saharan Africa are expected to make use of traditional three-stone fires in 2050, an increase compared to 2014. Biomass remains the dominant cooking fuel as a result of limited switching and the low efficiency of employed stoves. Driven by higher incomes and a better developed infrastructure, urban areas experience a faster shift to modern fuels. Demand for LPG grows at an annual rate of 6% across sub-Saharan Africa, in sharp contrast with the phase out of kerosene and the limited uptake of electric cookstoves. The speed of evolutions is dissimilar across countries because of differences in economic growth and urbanization, and non-homogeneous starting points. The results demonstrate the vast size of the challenge to improve living conditions in sub-Saharan Africa and suggest that universal access by 2030, a target stated by several international organizations, is rather unrealistic.

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The core of this project was the development of a column flotation dynamic model that can reasonably predict the changes in the concentrations of all solid and bubble species, along the full column height. A dynamic model of a process is normally composed of a set of partial or ordinary differential equations that describe the state of the process at any given time or position inside the system volume. Such equations can be obtained from fundamental material and/or energy balances, or from phenomenological derivations based on knowledge about the behavior of the system. A phenomenological approach referred to as population balance modeling was employed here. Initially, a two-phase model was formulated, which represents the behavior of the gas phase in a frother solution. The column was viewed as consisting of three main regions: a collection region, a stabilized froth and a draining froth. Experiments were carried out, based on conductivity techniques, for obtaining empirical data for model validation and parameter estimation. After testing the two-phase model, the equations for the solid species were derived. Consideration of the effects of bubble loading, slurry density and slurry viscosity on bubble rise velocity and, therefore, on air fraction is included in the model. Bubble coalescence in the froth is represented as a rate phenomenon characterized by a series of coalescence efficiency rate parameters. Auxiliary equations that help describe the settling of free particles, the buoyancy of air bubbles, and the processes of attachment and detachment, were also developed and incorporated into the model. The detachment of solids from the bubbles in the froth zones was attributed to coalescence, and it was assumed to be proportional to the net loss of bubble surface area. Almost all parameters needed to solve the model equations are readily available. The set of differential equations that comprise the model can be solved numerically by applying finite difference approximation techniques. An iteration has to be performed, which involves calculating the product flowrate at steady state, modifying the tailings rate and solving the model again until a mass balance is satisfied. / Ph. D.