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Full-Text Articles in Engineering
Deep Learning For Automatic Microscopy Image Analysis, Shenghua He
Deep Learning For Automatic Microscopy Image Analysis, Shenghua He
McKelvey School of Engineering Theses & Dissertations
Microscopy imaging techniques allow for the creation of detailed images of cells (or nuclei) and have been widely employed for cell studies in biological research and disease diagnosis in clinic practices.Microscopy image analysis (MIA), with tasks of cell detection, cell classification, and cell counting, etc., can assist with the quantitative analysis of cells and provide useful information for a cellular-level understanding of biological activities and pathology. Manual MIA is tedious, time-consuming, prone to subject errors, and are not feasible for the high-throughput cell analysis process. Thus, automatic MIA methods can facilitate all kinds of biological studies and clinical tasks. Conventional …
Scatter Estimation And Correction For Experimental And Simulated Data In Multi-Slice Computed Tomography Using Machine Learning And Minimum Least Squares Methods, Cornelia Wang
McKelvey School of Engineering Theses & Dissertations
Current research aims to reduce the stopping power ratio prediction error in the inputs to the proton therapy planning process to less than 1%, which allows for improved radiation therapy planning. Our present study on reducing SPR error neglects the effect of scattering, which can increase SPR error by as much as 1-1.5%. The idea is that for each source-to-detector pair, 24 mm collimation data is close to 3 mm collimation data but with increased signal due to scattering. The goal is to estimate 3 mm collimation data from 24 mm collimation data. Pairs of sinograms, both experimental data and …
Machine Learning For Analog/Mixed-Signal Integrated Circuit Design Automation, Weidong Cao
Machine Learning For Analog/Mixed-Signal Integrated Circuit Design Automation, Weidong Cao
McKelvey School of Engineering Theses & Dissertations
Analog/mixed-signal (AMS) integrated circuits (ICs) play an essential role in electronic systems by processing analog signals and performing data conversion to bridge the analog physical world and our digital information world.Their ubiquitousness powers diverse applications ranging from smart devices and autonomous cars to crucial infrastructures. Despite such critical importance, conventional design strategies of AMS circuits still follow an expensive and time-consuming manual process and are unable to meet the exponentially-growing productivity demands from industry and satisfy the rapidly-changing design specifications from many emerging applications. Design automation of AMS IC is thus the key to tackling these challenges and has been …
Holistic Control For Cyber-Physical Systems, Yehan Ma
Holistic Control For Cyber-Physical Systems, Yehan Ma
McKelvey School of Engineering Theses & Dissertations
The Industrial Internet of Things (IIoT) are transforming industries through emerging technologies such as wireless networks, edge computing, and machine learning. However, IIoT technologies are not ready for control systems for industrial automation that demands control performance of physical processes, resiliency to both cyber and physical disturbances, and energy efficiency. To meet the challenges of IIoT-driven control, we propose holistic control as a cyber-physical system (CPS) approach to next-generation industrial automation systems. In contrast to traditional industrial automation systems where computing, communication, and control are managed in isolation, holistic control orchestrates the management of cyber platforms (networks and computing platforms) …