Physical Sciences and Mathematics Commons^™

Evaluation Of Robust Deep Learning Pipelines Targeting Low Swap Edge Deployment, David Carter Cornett

Masters Theses

The deep learning technique of convolutional neural networks (CNNs) has greatly advanced the state-of-the-art for computer vision tasks such as image classification and object detection. These solutions rely on large systems leveraging wattage-hungry GPUs to provide the computational power to achieve such performance. However, the size, weight and power (SWaP) requirements of these conventional GPU-based deep learning systems are not suitable when a solution requires deployment to so called "Edge" environments such as autonomous vehicles, unmanned aerial vehicles (UAVs) and smart security cameras.

The objective of this work is to benchmark FPGA-based alternatives to conventional GPU systems that have the …

Modeling And Characterization Of Optical Metasurfaces, Mahsa Torfeh

Masters Theses

Metasurfaces are arrays of subwavelength meta-atoms that shape waves in a compact and planar form factor. During recent years, metasurfaces have gained a lot of attention due to their compact form factor, easy integration with other devices, multi functionality and straightforward fabrication using conventional CMOS techniques. To provide and evaluate an efficient metasurface, an optimized design, high resolution fabrication and accurate measurement is required. Analysis and design of metasurfaces require accurate methods for modeling their interactions with waves. Conventional modeling techniques assume that metasurfaces are locally periodic structures excited by plane waves, restricting their applicability to gradually varying metasurfaces that …

Power System Stability Assessment With Supervised Machine Learning, Mirka Mandich

Masters Theses

Power system stability assessment has become an important area of research due to the increased penetration of photovoltaics (PV) in modern power systems. This work explores how supervised machine learning can be used to assess power system stability for the Western Electricity Coordinating Council (WECC) service region as part of the Data-driven Security Assessment for the Multi-Timescale Integrated Dynamics and Scheduling for Solar (MIDAS) project. Data-driven methods offer to improve power flow scheduling through machine learning prediction, enabling better energy resource management and reducing demand on real-time time-domain simulations. Frequency, transient, and small signal stability datasets were created using the …

A Simple Background Elimination Method For Miniaturized Fiber-Optic Raman Probe, Bohong Zhang

Masters Theses

"Raman scattering is called a photonic - molecular interaction based on the kinetic model of the analytic. Due to the uniqueness of the Raman scattering technique, it can provide a unique fingerprint signal for molecular recognition. However, a serious challenge often encountered in Raman measurement comes from the requirements of fast, real-time remote sensing, background fluorescence suppression, and micro-environmental detection.

A new Miniaturized Fiber-Optic Raman Probe (MFORP) for Raman spectroscopy, used especially for eliminating background fluorescence and enhancing sampling, is presented. Its main purpose is to provide an overview of excellent research on the detection of very small substances and …

A Compact Wavelength Meter Using A Multimode Fiber, Ogbole Collins Inalegwu

Masters Theses

“Wavelength meters are very important for precision measurements of both pulses and continuous-wave optical sources. Conventional wavelength meters employ gratings, prisms, interferometers, and other wavelength-sensitive materials in their design. Here, we report a simple and compact wavelength meter based on a section of multimode fiber and a camera. The concept is to correlate the multimodal interference pattern (i.e., speckle pattern) at the end-face of a multimode fiber with the wavelength of the input lightsource. Through a series of experiments, specklegrams from the end face of a multimode fiber as captured by a charge-coupled device (CCD) camera were recorded; the images …