Engineering Commons^™

Design And Fabrication Of A Low Power 7.2 Terabit Transmitter For Exascale Computing, Scott Mcwilliams, Scott Mcwilliams

Electrical Engineering Theses and Dissertations

Enhanced Coupled Strength (ECS) gratings fabricated into III-V based devices offer high reflected power per unit length and broad band reflectivity as compared to conventional 1st order gratings, desired qualities for short-haul high speed transmitters that can be implemented without the need for chip-level temperature control, contributing to the low power per transmitted bit. For commercial DBR lasers, the grating reflectivity results in an extremely narrow reflectivity spectrum, which is highly desired for most/many applications, but requires a power hungry thermo-electric cooler to maintain a fixed frequency. The proposed LEAM (laser electro-absorption modulator) requires a broad reflectivity spectrum, which, by …

Closed-Loop Brain-Computer Interfaces For Memory Restoration Using Deep Brain Stimulation, David Xiaoliang Wang

Electrical Engineering Theses and Dissertations

The past two decades have witnessed the rapid growth of therapeutic brain-computer interfaces (BCI) targeting a diversity of brain dysfunctions. Among many neurosurgical procedures, deep brain stimulation (DBS) with neuromodulation technique has emerged as a fruitful treatment for neurodegenerative disorders such as epilepsy, Parkinson's disease, post-traumatic amnesia, and Alzheimer's disease, as well as neuropsychiatric disorders such as depression, obsessive-compulsive disorder, and schizophrenia. In parallel to the open-loop neuromodulation strategies for neuromotor disorders, recent investigations have demonstrated the superior performance of closed-loop neuromodulation systems for memory-relevant disorders due to the more sophisticated underlying brain circuitry during cognitive processes. Our efforts are …

Enhanced Security Utilizing Side Channel Data Analysis, Michael Taylor

Computer Science and Engineering Theses and Dissertations

The physical state of a system is affected by the activities and processes in which it is tasked with carrying out. In the past there have been many instances where such physical changes have been exploited by bad actors in order to gain insight into the operational state and even the data being held on a system. This method of side channel exploitation is very often effective due to the relative difficulty of obfuscating activity on a physical level. However, in order to take advantage of side channel data streams one must have a detailed working knowledge of how a …

Context-Aware Sensing And Fusion For Structural Health Monitoring And Night Time Traffic Surveillance, Xinxiang Zhang

Electrical Engineering Theses and Dissertations

Rapid developments in computer vision technologies have been transforming many traditional fields in engineering and science in the last few decades, especially in terms of diagnosing problems from visual images. Leveraging computer vision technologies to inspect, monitor, assess infrastructure conditions, and analyze traffic dynamics, has gained significant increase in both effectiveness and efficiency, compared to the cost of traditional instrumentation arrays to monitor, and manually inspect civil infrastructures and traffic conditions. Therefore, to construct the next-generation intelligent civil and transportation infrastructures, this dissertation develops a comprehensive computer-vision based sensing and fusion framework for structural health monitoring and intelligent transportation systems. …

Learning Deep Architectures For Power Systems Operation And Analysis, Mahdi Khodayar

Electrical Engineering Theses and Dissertations

With the rapid increase in size and computational complexities of power systems, the need for powerful computational models to capture strong patterns from energy datasets is emerged. In this thesis, we provide a comprehensive review on recent advances in deep neural architectures that lead to significant improvements in classification and regression problems in the area of power engineering. Furthermore, we introduce our novel deep learning methodologies proposed for a large variety of applications in this area. First, we present the interval deep probabilistic modeling for wind speed forecasting. Incorporating the Rough Set Theory into deep neural networks, we create an …

Accurate Vehicle Detection Using Multi-Camera Data Fusion And Machine Learning, Hao Wu

Electrical Engineering Theses and Dissertations

Computer-vision methods have recently been extensively used in intelligent transportation systems for vehicle detection. However, the detection of severely occluded or partially observed vehicles due to the limited camera fields of view remains a significant challenge. This paper presents a multi-camera vehicle detection system that significantly improves the detection performance under occlusion conditions. The key elements of the proposed method include a novel multi-view region proposal network that localizes the candidate vehicles on the ground plane. We also infer the vehicle occupancies by leveraging multi-view cross-camera context. Experiments are conducted on a dataset captured from a roadway in Richardson, TX, …

Investigating The Effect Of Detecting And Mitigating A Ring Oscillator-Based Hardware Trojan, Lakshmi Ramakrishnan

Electrical Engineering Theses and Dissertations

The outsourcing of the manufacturing process of integrated circuits to fabrications plants all over the world has exposed these chips to several security threats, especially at the hardware level. There have been instances of malicious circuitry, such as backdoors, being added to circuits without the knowledge of the chip designers or vendors. Such threats could be immensely powerful and dangerous against confidentiality, among other vulnerabilities.

Defense mechanisms against such attacks have been probed and defense techniques have been developed. But with the passage of time, attack techniques have improved immensely as well. From directly observing the inputs or outputs, adversaries …

Subspace Averaging Of Auditory Evoked Potentials, Xiaoliang Wang

Electrical Engineering Theses and Dissertations

The auditory evoked potential (AEP) is an electric potential generated in the brain in response to auditory stimuli. It has clinical importance in the detection of newborn infant hearing loss. The signal to noise ratio (SNR) of the AEP is low, so signal averaging is typically employed to estimate it. Often, thousands of trials must be averaged before a sufficiently high SNR estimate is obtained.

In this research, we have developed a new AEP averaging method called subspace averaging. The subspace averaging method projects onto the signal subspace: the span of the principal eigenvectors of the signal correlation matrix. The …

Computational Theories For Human Stereo Vision, Han Gao

Electrical Engineering Theses and Dissertations

Binocular stereopsis refers to the ability to perceive depth, which has always been a central problem in perception since the time of da Vinci. The foremost theoretical difficulty that arises when attempting to understand how the visual system computes disparity is known as the correspondence or matching problem. Decades of research upon macaque primary visual cortex has shown that in each layer of the primary visual cortex (V1) long-range horizontal connections among striate cortex cells exist which integrate information from different parts of the visual field. Inspired by long-range horizontal connections in V1 and the Jeffress model, a time-delay neural …