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Towards Reliable Hepatocytic Anatomy Segmentation In Laparoscopic Cholecystectomy Using U-Net With Auto-Encoder, Koloud Najem Alkhamaiseh
Towards Reliable Hepatocytic Anatomy Segmentation In Laparoscopic Cholecystectomy Using U-Net With Auto-Encoder, Koloud Najem Alkhamaiseh
Dissertations
Despite the advantages of minimally invasive surgeries that depend heavily on vision, the indirect access and lack of the 3D field of view of the area of interest introduce some complications in the desired procedures. Fortunately, the recorded videos from these procedures offer the opportunity for intra-operative and post-operative analyses, to improve future performance and safety.
Deep learning models for surgical video analysis could therefore support visual tasks such as identifying the critical view of safety (CVS) in laparoscopic cholecystectomy (LC), potentially contributing to the reduction of the current rates of bile duct injuries in LC. Most bile duct injuries …
Wideband Parameter Estimation Of Overhead Transmission Lines From Terminal Measurements, Fahad J. Alqahtani
Wideband Parameter Estimation Of Overhead Transmission Lines From Terminal Measurements, Fahad J. Alqahtani
Dissertations
The accurate and efficient determination of electrical parameters of transmission lines is essential when performing computer-aided analyses of power systems, including power-flow, state estimation, short-circuit, transient stability, power quality, and electromagnetic transients.
In this dissertation, a novel technique for wideband parameter estimation of frequency-dependent single-phase, three-phase transposed, and three-phase untransposed overhead lines, is proposed. The proposed technique utilizes terminal measurements of transient voltages and currents and is based on an analytical approach to solve the frequency domain 2-port nodal model of the line for the series impedance and shunt conductance per unit length as a function of the frequency. The …
Design, Simulation, Modeling, And Implementation Of Triboelectric Nanogenerator (Teng) Sensors For Automotive Applications, Sam Ali
Dissertations
Triboelectricity is a promising technique for energy harvesting in which mechanical energy converts to electricity for powering small electronic devices. This method of energy harvesting serves as an alternative to traditional battery power sources and can significantly benefit low-power sensing applications by generating unlimited electrical energy. This study focuses on the development of flexible triboelectric nanogenerators (TENG) and energy harvesting devices for various applications in the automotive industry.
The study is organized into four projects. In the first project, various polymeric materials were used to investigate the performance of different TENGs. Four designs (D1, D2, D3, and D4) of flexible …