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Spectrum Optimization For Advanced Air Mobility Communications Using Deep Reinforcement Learning., Rafael D. Apaza Dec 2024

Spectrum Optimization For Advanced Air Mobility Communications Using Deep Reinforcement Learning., Rafael D. Apaza

Electronic Theses and Dissertations

As aviation operations expand and new participants enter the National Airspace System (NAS), the demand for aeronautical communications will experience a significant rise. This surge is propelled by increased air travel and the emergence of Urban Air Mobility (UAM) operations, a subset of Advanced Air Mobility (AAM). UAM aims to facilitate intra-city transportation of people and cargo utilizing remotely piloted aircraft capable of electric vertical takeoff and landing operations. The growing dependence on efficient wireless communication systems underscores the critical importance of intelligent spectrum allocation and effective airspace management to ensure safe, seamless, and technologically advanced air operations. However, the …


Reinforcement Learning Assisted Communication Resources Optimization In Advanced Air Mobility., Ruixuan Han Aug 2024

Reinforcement Learning Assisted Communication Resources Optimization In Advanced Air Mobility., Ruixuan Han

Electronic Theses and Dissertations

Advanced air mobility (AAM), which envisages a safe and efficient aviation transportation system, has drawn significant attention to support the increasing mobility demand in metropolitan areas. Communication services for AAM aerial vehicles (AVs) are crucial for ensuring flight safety. This dissertation explores three research topics on communication resource allocation problems in AAM applications. The first topic, addressed in Chapter II, investigates the joint velocity selection and spectrum allocation problem for AAM applications to enhance spectrum utilization efficiency (SUE). In the AAM scenario, multiple AVs travel along predefined paths for passenger and cargo deliveries. Given that AAM aims to provide fast …


Data-Driven Approaches For Enhancing Power Grid Reliability, Behrouz Sohrabi Mar 2024

Data-Driven Approaches For Enhancing Power Grid Reliability, Behrouz Sohrabi

Electronic Theses and Dissertations

This thesis explores the transformative potential of data-driven approaches in addressing key operational and reliability issues in power systems. The first part of this thesis addresses a prevalent problem in power distribution networks: the accurate identification of load phases. This study develops a data-driven model leveraging consumption measurements from smart meters and corresponding substation data to reconstruct topology information in low-voltage distribution networks. The proposed model is extensively tested using a dataset with more than 5,000 real load profiles, demonstrating satisfactory performance for large-scale networks. The second part of the thesis pivots to a crucial safety concern: the risk and …


Consensus-Based Active And Reactive Power Control And Management Of Microgrids, Shruti Singh Aug 2023

Consensus-Based Active And Reactive Power Control And Management Of Microgrids, Shruti Singh

Electronic Theses and Dissertations

Microgrids incorporating distributed generation and renewable energy sources offer potential solutions to the energy crisis while modernizing traditional grids. Despite cost-effectiveness in some technologies, financial support remains crucial for expensive ones like PV, fuel cells, and storage technologies. Microgrids bring economic benefits, efficiency, reduced emissions, and improved power quality. Their success hinges on cost reductions in renewables, storage, reliability, and energy management systems, enabling operation both with and without the utility grid.

Economic Dispatch optimizes system costs, considering all constraints. Various methods tackle this problem, including quadratic convex functions, Lagrangian relaxation, and quadratic programming. For microgrids with distributed generators, seamless …


Unsupervised Learning Algorithm For Noise Suppression And Speech Enhancement Applications, Abdullah Zaini Alsheibi Mar 2023

Unsupervised Learning Algorithm For Noise Suppression And Speech Enhancement Applications, Abdullah Zaini Alsheibi

Electronic Theses and Dissertations

Smart and intelligent devices are being integrated more and more into day-to-day life to perform a multitude of tasks. These tasks include, but are not limited to, job automation, smart utility management, etc., with the aim to improve quality of life and to make normal day-to-day chores as effortless as possible. These smart devices may or may not be connected to the internet to accomplish tasks. Additionally, human-machine interaction with such devices may be touch-screen based or based on voice commands. To understand and act upon received voice commands, these devices require to enhance and distinguish the (clean) speech signal …


Learning Approach For Fast Approximate Matrix Factorizations, Haiyan Yu Jan 2022

Learning Approach For Fast Approximate Matrix Factorizations, Haiyan Yu

Electronic Theses and Dissertations

Efficiently computing an (approximate) orthonormal basis and low-rank approximation for the input data X plays a crucial role in data analysis. One of the most efficient algorithms for such tasks is the randomized algorithm, which proceeds by computing a projection XA with a random projection matrix A of much smaller size, and then computing the orthonormal basis as well as low-rank factorizations of the tall matrix XA. While a random matrix A is the de facto choice, in this work, we improve upon its performance by utilizing a learning approach to find an adaptive projection matrix A from a set …


Biometric Features Modeling To Measure Students Engagement., Islam Mohamed Ahmed Mohamed Mahmoud Alkabbany Aug 2021

Biometric Features Modeling To Measure Students Engagement., Islam Mohamed Ahmed Mohamed Mahmoud Alkabbany

Electronic Theses and Dissertations

The ability to measure students’ engagement in an educational setting may improve student retention and academic success, revealing which students are disinterested, or which segments of a lesson are causing difficulties. This ability will facilitate timely intervention in both the learning and the teaching process in a variety of classroom settings. In this dissertation, an automatic students engagement measure is proposed through investigating three main engagement components of the engagement: the behavioural engagement, the emotional engagement and the cognitive engagement. The main goal of the proposed technology is to provide the instructors with a tool that could help them estimating …


Variable Autonomy Assignment Algorithms For Human-Robot Interactions., Christopher Kevin Robinson Aug 2021

Variable Autonomy Assignment Algorithms For Human-Robot Interactions., Christopher Kevin Robinson

Electronic Theses and Dissertations

As robotic agents become increasingly present in human environments, task completion rates during human-robot interaction has grown into an increasingly important topic of research. Safe collaborative robots executing tasks under human supervision often augment their perception and planning capabilities through traded or shared control schemes. However, such systems are often proscribed only at the most abstract level, with the meticulous details of implementation left to the designer's prerogative. Without a rigorous structure for implementing controls, the work of design is frequently left to ad hoc mechanism with only bespoke guarantees of systematic efficacy, if any such proof is forthcoming at …


Mechanisms Of Sensory Adaptation In The Primate Visual System, Boris Isaac Peñaloza Rojas Jan 2021

Mechanisms Of Sensory Adaptation In The Primate Visual System, Boris Isaac Peñaloza Rojas

Electronic Theses and Dissertations

Under ecological conditions, the luminance impinging on the retina varies within a dynamic range of 220 dB. Stimulus contrast can also vary drastically within a scene, and eye movements leave little time for sampling luminance. In addition, the amount of information reaching our visual system far exceeds the brain’s information processing capacity. Given the limited dynamic range of its neurons and its limited capacity in processing visual information in real-time, the brain deploys both structural and functional solutions that work in tandem to adapt to the surroundings. In this work, employing visual psychophysics and computational neuroscience, we study the mechanisms …


Inventory Management Of The Refrigerator's Produce Bins Using Classification Algorithms And Hand Analysis., Sarah Virginia Morris Aug 2020

Inventory Management Of The Refrigerator's Produce Bins Using Classification Algorithms And Hand Analysis., Sarah Virginia Morris

Electronic Theses and Dissertations

Tracking the inventory of one’s refrigerator has been a mission for consumers since the advent of the refrigerator. With the improvement of computer vision capabilities, automatic inventory systems are within reach. One inventory area with many potential benefits is the fresh food produce bins. The bins are a unique storage area due to their deep size. A user cannot easily see what is in the bins without opening the drawer. Produce items are also some of the quickest foods in the refrigerator to spoil, despite being temperature and humidity controlled to have the fruits and vegetables last longer. Allowing the …


Deep Siamese Neural Networks For Facial Expression Recognition In The Wild, Wassan Hayale Jan 2020

Deep Siamese Neural Networks For Facial Expression Recognition In The Wild, Wassan Hayale

Electronic Theses and Dissertations

The variation of facial images in the wild conditions due to head pose, face illumination, and occlusion can significantly affect the Facial Expression Recognition (FER) performance. Moreover, between subject variation introduced by age, gender, ethnic backgrounds, and identity can also influence the FER performance. This Ph.D. dissertation presents a novel algorithm for end-to-end facial expression recognition, valence and arousal estimation, and visual object matching based on deep Siamese Neural Networks to handle the extreme variation that exists in a facial dataset. In our main Siamese Neural Networks for facial expression recognition, the first network represents the classification framework, where we …


Receptive Fields Optimization In Deep Learning For Enhanced Interpretability, Diversity, And Resource Efficiency., Babajide Odunitan Ayinde May 2019

Receptive Fields Optimization In Deep Learning For Enhanced Interpretability, Diversity, And Resource Efficiency., Babajide Odunitan Ayinde

Electronic Theses and Dissertations

In both supervised and unsupervised learning settings, deep neural networks (DNNs) are known to perform hierarchical and discriminative representation of data. They are capable of automatically extracting excellent hierarchy of features from raw data without the need for manual feature engineering. Over the past few years, the general trend has been that DNNs have grown deeper and larger, amounting to huge number of final parameters and highly nonlinear cascade of features, thus improving the flexibility and accuracy of resulting models. In order to account for the scale, diversity and the difficulty of data DNNs learn from, the architectural complexity and …


Development Of A Capacitive Photocurrent Scanning Microscope With Carrier Depletion Super-Resolution., Austin Levi Carver Jan 2018

Development Of A Capacitive Photocurrent Scanning Microscope With Carrier Depletion Super-Resolution., Austin Levi Carver

Electronic Theses and Dissertations

This dissertation discusses the development and refinement of a new two-dimensional imaging technique, funded in part through a NSF MRI equipment development grant. Capacitive-Photocurrent (CPC) spectroscopy allows for the probing of samples without the requirement of free-carrier collection. The CPC technique allows for the studying of various states within a material. With this electronic measurement technique, we developed a scanning technique, scanning-CPC, that provides two-dimensional material property images without requiring environments that must be high-vacuum, humidity-controlled, or temperature-controlled. This new technique also provides two-dimensional, electronic mapping without damaging samples. With this successful result, we then modified an existing resolution improving …


Optimized Trajectory Generation For Car-Like Robots On A Closed Loop Track, Tyler Friedl Jan 2017

Optimized Trajectory Generation For Car-Like Robots On A Closed Loop Track, Tyler Friedl

Electronic Theses and Dissertations

This thesis presents a method for generating an optimized path through a given track. The path is generated by choosing waypoints throughout the track then iteratively optimizing the position of these waypoints. The waypoints are then connected by optimized paths represented by curvature polynomials. The end result is a path through the track represented as a spline of curvature polynomials. This method is applied to multiple simulated tracks and the results are presented. By generating and representing the paths in the continuous domain, the method has improved computational efficiency from many of the discrete methods used to generate an optimal …


Data-Centric Situational Awareness And Management In Intelligent Power Systems, Xiaoxiao Dai Jan 2017

Data-Centric Situational Awareness And Management In Intelligent Power Systems, Xiaoxiao Dai

Electronic Theses and Dissertations

The rapid development of technology and society has made the current power system a much more complicated system than ever. The request for big data based situation awareness and management becomes urgent today. In this dissertation, to respond to the grand challenge, two data-centric power system situation awareness and management approaches are proposed to address the security problems in the transmission/distribution grids and social benefits augmentation problem at the distribution-customer lever, respectively.

To address the security problem in the transmission/distribution grids utilizing big data, the first approach provides a fault analysis solution based on characterization and analytics of the synchrophasor …


Photoelectrochemical Water Splitting For Hydrogen Production With Metal Oxide (Hematite And Cupric Oxide) Based Photocatalysts, Houwen Tang Jan 2012

Photoelectrochemical Water Splitting For Hydrogen Production With Metal Oxide (Hematite And Cupric Oxide) Based Photocatalysts, Houwen Tang

Electronic Theses and Dissertations

Solar hydrogen is one ideal energy source to replace fossil fuel, as it is sustainable and environmentally friendly. Solar hydrogen can be generated in a number of ways. Photoelectrochemical (PEC) water splitting is one of the most promising methods for solar-to-chemical energy conversion. In this research project, metal oxide-based photocatalysts, especially hematite (fÑ-Fe2O3) and cupric oxide (CuO), were investigated for use as electrodes in PEC water splitting for solar hydrogen production.

In our research project of hematite-based electrodes, we started with the incorporation of transition metal, particularly titanium (Ti), in hematite thin films to modify the valence and …


Toward A Distributed Actuation And Cognition Means For A Miniature Soft Robot, Xiaoting Yang Jan 2010

Toward A Distributed Actuation And Cognition Means For A Miniature Soft Robot, Xiaoting Yang

Electronic Theses and Dissertations

This thesis presents components of an on-going research project aimed towards developing a miniature soft robot for urban search and rescue (USAR). The three significant contributions of the thesis are verifying the water hammer actuation previous work, developing an estimator of water hammer impulse direction from hose shape, and creating the infrastructure for distributed cognitive networks. There are many technical issues in designing soft robots, in terms of perception, actuation, cognition, power, physical structure and so on. We are focusing on actuation and cognition issues in this thesis. We investigated water hammer actuation as an alternative system which provides a …


Fabrication Of Silicon Photovoltaic Micro-Particles For Low-Cost Solar Energy Generation, Siddhartha Kala Jan 2009

Fabrication Of Silicon Photovoltaic Micro-Particles For Low-Cost Solar Energy Generation, Siddhartha Kala

Electronic Theses and Dissertations

The relatively high cost of the high quality semiconductor materials (typically silicon) and complex conventional techniques for the fabrication of solar cells result in the overall high cost of the commercially available solar cells. Although, research in the field of solar technologies has been going on for a long time, but, utilization of solar energy still remains limited to a very few applications, owing to the high manufacturing costs and lower efficiency. In this work we present a new solar technology based on silicon photovoltaic micro-particles and demonstrate a fabrication technique for such particles. The photovoltaic micro-particles can be manufactured …


Design And Applications Of A Graphics Package For The Hp1000 Computer., Hsiao-Chih George Lee May 1986

Design And Applications Of A Graphics Package For The Hp1000 Computer., Hsiao-Chih George Lee

Electronic Theses and Dissertations

The objective of this thesis is to develop the FORTRAN subroutine PLOTER which is a general-purpose plotting tool to plot charts on a Hewlett Packard plotter. The programs RESP and INVLAP which can plot the frequency and time responses of system functions are modified to adopt the PLOTER subroutine and are stored of the HP1000-A900 minicomputer whose software, the GRAPHICS/1000, supports the graphics ability of PLOTER. This thesis describes the theories, functions, software techniques and operations of the PLOTER subroutine and the application programs RESP and the INVLAP. It also provides program listings and example plots.