Motivations. Breast cancer is the second greatest cause of cancer mortality among women, according to the World Health Organization (WHO), and one of the most frequent illnesses among all women today. The influence is not confined to industrialized nations but also includes emerging countries since the authors believe that increased urbanization and adoption of Western lifestyles will lead to a rise in illness prevalence. Problem Statement. The breast cancer has become one of the deadliest diseases that women are presently facing. However, the causes of this disease are numerous and cannot be properly established. However, there is a huge difficulty in not accurately recognizing breast cancer in its early stages or prolonging the detection process. Methodology. In this research, machine learning is a field of artificial intelligence that employs a variety of probabilistic, optimization, and statistical approaches to enable computers to learn from past data and find and recognize patterns from large or complicated groups. The advantage is particularly well suited to medical applications, particularly those involving complicated proteins and genetic measurements. Result and Implications. However, when using the PCA method to reduce the features, the detection accuracy dropped to 89.9%. IG-ANFIS gave us detection accuracy (98.24%) by reducing the number of variables using the “information gain” method. While the ANFIS algorithm had a detection accuracy of 59.9% without utilizing features, J48, which is one of the decision tree approaches, had a detection accuracy of 92.86% without using features extraction methods. When applying PCA techniques to minimize features, the detection accuracy was lowered to the same way (91.1%) as the Naive Bayes detection algorithm (96.4%).

This study analyzes actuator disc (AD) models of horizontal-axis turbines to determine optimal performance, defined as the maximum power extracted at any tip speed ratio. We use the calculus of variations to maximize rotor torque relative to the thrust without making any assumptions about the rotor loading. The torque was obtained from the angular momentum equation and the thrust from the Kutta-Joukowsky equation which depends on the circumferential velocity and tip speed ratio. The optimality requirement is that the pitch of the vorticity exiting the rotor must be constant across the wake and equal to the ratio of torque to thrust. This result generalizes the classical finding of Betz and Goldstein that optimal lightly-loaded ADs have constant pitch. Optimizing the torque in the far-wake, well downstream of the rotor, leads to the same requirement of constant pitch. This implies that the pitch of an optimal rotor is constant everywhere in the wake at all tip speed ratios. We show that it is not possible for the pitch to reach its optimal value because of the vorticity distribution in the wake, and propose modifications to the pitch at the rotor and in the far-wake. The axial and circumferential velocities in the far-wake, which are easily determined, were used to find those at the rotor from the “disc loading equation” for the angular momentum which is also the normalized bound circulation at the rotor. For the simplest case of a lightly-loaded rotor at zero tip speed ratio, the induced circumferential velocity is linear in radius and the axial component is quadratic, As the tip speed ratio increases, the optimal power and thrust asymptote to the familiar Betz-Joukowsky values, and the induced axial velocity and rotor bound circulation become constant. At low tip speed ratios, the optimal wakes are constrained by the need to avoid breakdown of the flow at high swirl, and the conventional thrust equation, involving the axial velocity only, is inaccurate. As found in previous studies, the power coefficient increases monotonically with tip speed ratio, but the thrust coefficient reaches a maximum value slightly above the Betz-Joukowsky limit at a tip speed ratio of two, before decreasing towards the limit.

A simple unsteady blade element analysis is used to account for the effect of the trailing wake on the induced velocity of a wind turbine rotor undergoing fast changes in pitch angle. At sufficiently high tip speed ratio, the equation describing the thrust of the element reduces to a first order, nonlinear Riccti's equation which is solved in a closed form for a ramp change in pitch followed by a constant pitch. Finite tip speed ratio results in a first order, nonlinear Abel's equation. The unsteady aerodynamic forces on the NREL VI wind turbine are analyzed at different pitch rates and tip speed ratio, and it is found that the overshoot in the forces increases as the tip speed ratio and/or the pitch angle increase. The analytical solution of the Riccati's equation and numerical solution of Abel's equation gave very similar results at high tip speed ratio but the solutions differ as the tip speed ratio reduces, partly because the Abel's equation was found to magnify the error of assuming linear lift at low tip speed ratio. The unsteady tangential induction factor is expressed in the form of first order differential equation with the time constant estimated using Jowkowsky's vortex model and it was found that it is negligible for large tip speed ratio operation.

This research aims to study the catalyst activity in specific reactions and the characteristics of the catalyst in order to optimize its performance. This research investigates PVP based catalysts and their properties and applications. PVP was prepared in combination with different metal oxides in order to be tested for different catalytic applications including dye removal. Methyl orange was used as a dye and different concentrations were tested against different metallic ions in order to optimize the catalyst for being used in dye removal applications. Spectrophotometer was used to calculate the concentration of the dye before and after catalyst exposure and investigate the relation between contact time and concentrations. Applying different contact time to the same weight percent of PVP based catalyst with metallic ions revealed that increasing the contact time with a good shaking leads to decrease in the concentration of the dye mixed with the sample. The tests showed that the mixture between PVP and Nickel has the best dye removal within the other metal ions (copper and ferric) as well it showed that ferric has the least effect on dye removal. Wide angle x-ray diffraction (WA-XRD) was applied to different sample copper with PVP and ferric with PVP.

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