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Full-Text Articles in Physical Sciences and Mathematics

Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso Jan 2024

Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso

Theses and Dissertations--Electrical and Computer Engineering

The emergence of deep learning models and their success in visual object recognition have fueled the medical imaging community's interest in integrating these algorithms to improve medical diagnosis. However, natural images, which have been the main focus of deep learning models and mammograms, exhibit fundamental differences. First, breast tissue abnormalities are often smaller than salient objects in natural images. Second, breast images have significantly higher resolutions but are generally heavily downsampled to fit these images to deep learning models. Models that handle high-resolution mammograms require many exams and complex architectures. Additionally, spatially resizing mammograms leads to losing discriminative details essential …


Peer-To-Peer Energy Trading In Smart Residential Environment With User Behavioral Modeling, Ashutosh Timilsina Jan 2023

Peer-To-Peer Energy Trading In Smart Residential Environment With User Behavioral Modeling, Ashutosh Timilsina

Theses and Dissertations--Computer Science

Electric power systems are transforming from a centralized unidirectional market to a decentralized open market. With this shift, the end-users have the possibility to actively participate in local energy exchanges, with or without the involvement of the main grid. Rapidly reducing prices for Renewable Energy Technologies (RETs), supported by their ease of installation and operation, with the facilitation of Electric Vehicles (EV) and Smart Grid (SG) technologies to make bidirectional flow of energy possible, has contributed to this changing landscape in the distribution side of the traditional power grid.

Trading energy among users in a decentralized fashion has been referred …


Unmanned Aircraft Systems For Precision Meteorology: An Analysis Of Gnss Position Measurement Error And Embedded Sensor Development, Karla S. Ladino Jan 2023

Unmanned Aircraft Systems For Precision Meteorology: An Analysis Of Gnss Position Measurement Error And Embedded Sensor Development, Karla S. Ladino

Theses and Dissertations--Biosystems and Agricultural Engineering

The overarching objective of this research was to enhance our comprehension of the three-dimensional precision of meteorological measurements obtained using small unmanned aircraft systems (UAS). Two complimentary experiments were conducted to achieve this objective.

The first experiment entailed the development and implementation of a system to determine the global navigation satellite system (GNSS) position accuracy on a UAS platform. This system was utilized to assess the static and dynamic accuracy of L1 and L1/L2 GNSS receivers in real-time kinematic (RTK) and non-RTK fix modes. Adjusted two-sample t-tests revealed significant differences in horizontal and vertical error between RTK and non-RTK receivers …


Determining Power System Fault Location Using Neural Network Approach, Edward O. Ojini Jan 2022

Determining Power System Fault Location Using Neural Network Approach, Edward O. Ojini

Theses and Dissertations--Electrical and Computer Engineering

Fault location remains an extremely pivotal feature of the electric power grid as it ensures efficient operation of the grid and prevents large downtimes during fault occurrences. This will ultimately enhance and increase the reliability of the system. Since the invention of the electric grid, many approaches to fault location have been studied and documented. These approaches are still effective and are implemented in present times, and as the power grid becomes even more broadened with new forms of energy generation, transmission, and distribution technologies, continued study on these methods is necessary. This thesis will focus on adopting the artificial …


Suppressing Bias Stress Degradation In High Performance Solution Processed Organic Transistors Operating In Air, Hamna F. Iqbal, Qianxiang Ai, Karl J. Thorley, Hu Chen, Iain Mcculloch, Chad Risko, John E. Anthony, Oana D. Jurchescu Apr 2021

Suppressing Bias Stress Degradation In High Performance Solution Processed Organic Transistors Operating In Air, Hamna F. Iqbal, Qianxiang Ai, Karl J. Thorley, Hu Chen, Iain Mcculloch, Chad Risko, John E. Anthony, Oana D. Jurchescu

Chemistry Faculty Publications

Solution processed organic field effect transistors can become ubiquitous in flexible optoelectronics. While progress in material and device design has been astonishing, low environmental and operational stabilities remain longstanding problems obstructing their immediate deployment in real world applications. Here, we introduce a strategy to identify the most probable and severe degradation pathways in organic transistors and then implement a method to eliminate the main sources of instabilities. Real time monitoring of the energetic distribution and transformation of electronic trap states during device operation, in conjunction with simulations, revealed the nature of traps responsible for performance degradation. With this information, we …


Optical Metasurfaces, Fatih Balli Jan 2021

Optical Metasurfaces, Fatih Balli

Theses and Dissertations--Physics and Astronomy

Traditional optical elements, such as refractive lenses, mirrors, phase plates and polarizers have been used for various purposes such as imaging systems, lithographic printing, astronomical observations and display technology. Despite their long-term achievements, they can be bulky and not suitable for miniaturization. On the other hand, recent nanotechnology advances allowed us to manufacture micro and nanoscale devices with ultra-compact sizes. Metasurfaces, 2D engineered artificial interfaces, have emerged as candidates to replace traditional refractive lenses with ultra-thin miniaturized optical elements. They possess sub-wavelength unit cell structures with a specific geometry and material selection. Each unit cell can uniquely tailor the phase, …


Weakly Supervised Learning For Multi-Image Synthesis, Muhammad Usman Rafique Jan 2021

Weakly Supervised Learning For Multi-Image Synthesis, Muhammad Usman Rafique

Theses and Dissertations--Electrical and Computer Engineering

Machine learning-based approaches have been achieving state-of-the-art results on many computer vision tasks. While deep learning and convolutional networks have been incredibly popular, these approaches come at the expense of huge amounts of labeled data required for training. Manually annotating large amounts of data, often millions of images in a single dataset, is costly and time consuming. To deal with the problem of data annotation, the research community has been exploring approaches that require less amount of labelled data.

The central problem that we consider in this research is image synthesis without any manual labeling. Image synthesis is a classic …


A Hybrid Achromatic Metalens, Fatih Balli, Mansoor A. Sultan, Sarah K. Lami, J. Todd Hastings Aug 2020

A Hybrid Achromatic Metalens, Fatih Balli, Mansoor A. Sultan, Sarah K. Lami, J. Todd Hastings

Electrical and Computer Engineering Faculty Publications

Metalenses, ultra-thin optical elements that focus light using subwavelength structures, have been the subject of a number of recent investigations. Compared to their refractive counterparts, metalenses offer reduced size and weight, and new functionality such as polarization control. However, metalenses that correct chromatic aberration also suffer from markedly reduced focusing efficiency. Here we introduce a Hybrid Achromatic Metalens (HAML) that overcomes this trade-off and offers improved focusing efficiency over a broad wavelength range from 1000-1800 nm. HAMLs can be designed by combining recursive ray-tracing and simulated phase libraries rather than computationally intensive global search algorithms. Moreover, HAMLs can be fabricated …


Resource Efficient Design Of Quantum Circuits For Cryptanalysis And Scientific Computing Applications, Edgard Munoz-Coreas Jan 2020

Resource Efficient Design Of Quantum Circuits For Cryptanalysis And Scientific Computing Applications, Edgard Munoz-Coreas

Theses and Dissertations--Electrical and Computer Engineering

Quantum computers offer the potential to extend our abilities to tackle computational problems in fields such as number theory, encryption, search and scientific computation. Up to a superpolynomial speedup has been reported for quantum algorithms in these areas. Motivated by the promise of faster computations, the development of quantum machines has caught the attention of both academics and industry researchers. Quantum machines are now at sizes where implementations of quantum algorithms or their components are now becoming possible. In order to implement quantum algorithms on quantum machines, resource efficient circuits and functional blocks must be designed. In this work, we …


Fault Identification On Electrical Transmission Lines Using Artificial Neural Networks, Christopher W. Asbery Jan 2020

Fault Identification On Electrical Transmission Lines Using Artificial Neural Networks, Christopher W. Asbery

Theses and Dissertations--Electrical and Computer Engineering

Transmission lines are designed to transport large amounts of electrical power from the point of generation to the point of consumption. Since transmission lines are built to span over long distances, they are frequently exposed to many different situations that can cause abnormal conditions known as electrical faults. Electrical faults, when isolated, can cripple the transmission system as power flows are directed around these faults therefore leading to other numerous potential issues such as thermal and voltage violations, customer interruptions, or cascading events. When faults occur, protection systems installed near the faulted transmission lines will isolate these faults from the …


A Comparative Analysis Of Reinforcement Learning Applied To Task-Space Reaching With A Robotic Manipulator With And Without Gravity Compensation, Jonathan Fugal Jan 2020

A Comparative Analysis Of Reinforcement Learning Applied To Task-Space Reaching With A Robotic Manipulator With And Without Gravity Compensation, Jonathan Fugal

Theses and Dissertations--Electrical and Computer Engineering

Advances in computing power in recent years have facilitated developments in autonomous robotic systems. These robotic systems can be used in prosthetic limbs, wearhouse packaging and sorting, assembly line production, as well as many other applications. Designing these autonomous systems typically requires robotic system and world models (for classical control based strategies) or time consuming and computationally expensive training (for learning based strategies). Often these requirements are difficult to fulfill. There are ways to combine classical control and learning based strategies that can mitigate both requirements. One of these ways is to use a gravity compensated torque control with reinforcement …


Filtered-Dynamic-Inversion Control For Unknown Minimum-Phase Systems With Unknown Relative Degree, Sumit Suryakant Kamat Jan 2020

Filtered-Dynamic-Inversion Control For Unknown Minimum-Phase Systems With Unknown Relative Degree, Sumit Suryakant Kamat

Theses and Dissertations--Mechanical Engineering

We present filtered-dynamic-inversion (FDI) control for unknown linear time-invariant systems that are multi-input multi-output and minimum phase with unknown-but-bounded relative degree. This FDI controller requires limited model information, specifically, knowledge of an upper bound on the relative degree and knowledge of the first nonzero Markov parameter. The FDI controller is a single-parameter high-parameter-stabilizing controller that is robust to uncertainty in the relative degree. We characterize the stability of the closed-loop system. We present numerical examples, where the FDI controller is implemented in feedback with mathematical and physical systems. The numerical examples demonstrate that the FDI controller for unknown relative degree …


Influence Spread In Two-Layer Interdependent Networks: Designed Single-Layer Or Random Two-Layer Initial Spreaders?, Hana Khamfroush, Nathaniel Hudson, Samuel Iloo, Mahshid R. Naeini Jun 2019

Influence Spread In Two-Layer Interdependent Networks: Designed Single-Layer Or Random Two-Layer Initial Spreaders?, Hana Khamfroush, Nathaniel Hudson, Samuel Iloo, Mahshid R. Naeini

Computer Science Faculty Publications

Influence spread in multi-layer interdependent networks (M-IDN) has been studied in the last few years; however, prior works mostly focused on the spread that is initiated in a single layer of an M-IDN. In real world scenarios, influence spread can happen concurrently among many or all components making up the topology of an M-IDN. This paper investigates the effectiveness of different influence spread strategies in M-IDNs by providing a comprehensive analysis of the time evolution of influence propagation given different initial spreader strategies. For this study we consider a two-layer interdependent network and a general probabilistic threshold influence spread model …


Relation Prediction Over Biomedical Knowledge Bases For Drug Repositioning, Mehmet Bakal Jan 2019

Relation Prediction Over Biomedical Knowledge Bases For Drug Repositioning, Mehmet Bakal

Theses and Dissertations--Computer Science

Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches are first attempted to identify promising candidates. Likewise, identifying other essential relations (e.g., causation, prevention) between biomedical entities is also critical to understand biomedical processes. Hence, it is crucial to develop automated relation prediction systems that can yield plausible biomedical relations to expedite the discovery process. In this dissertation, we demonstrate three approaches to predict treatment relations between biomedical entities for the drug repositioning task …


Facepet: Enhancing Bystanders' Facial Privacy With Smart Wearables/Internet Of Things, Alfredo J. Perez, Sherali Zeadally, Luis Y. Matos Garcia, Jaouad A. Mouloud, Scott Griffith Dec 2018

Facepet: Enhancing Bystanders' Facial Privacy With Smart Wearables/Internet Of Things, Alfredo J. Perez, Sherali Zeadally, Luis Y. Matos Garcia, Jaouad A. Mouloud, Scott Griffith

Information Science Faculty Publications

Given the availability of cameras in mobile phones, drones and Internet-connected devices, facial privacy has become an area of major interest in the last few years, especially when photos are captured and can be used to identify bystanders’ faces who may have not given consent for these photos to be taken and be identified. Some solutions to protect facial privacy in photos currently exist. However, many of these solutions do not give a choice to bystanders because they rely on algorithms that de-identify photos or protocols to deactivate devices and systems not controlled by bystanders, thereby being dependent on the …


X-Search: An Open Access Interface For Cross-Cohort Exploration Of The National Sleep Research Resource, Licong Cui, Ningzhou Zeng, Matthew Kim, Remo Mueller, Emily Ruth Hankosky, Susan Redline, Guo-Qiang Zhang Nov 2018

X-Search: An Open Access Interface For Cross-Cohort Exploration Of The National Sleep Research Resource, Licong Cui, Ningzhou Zeng, Matthew Kim, Remo Mueller, Emily Ruth Hankosky, Susan Redline, Guo-Qiang Zhang

Computer Science Faculty Publications

Background: The National Sleep Research Resource (NSRR) is a large-scale, openly shared, data repository of de-identified, highly curated clinical sleep data from multiple NIH-funded epidemiological studies. Although many data repositories allow users to browse their content, few support fine-grained, cross-cohort query and exploration at study-subject level. We introduce a cross-cohort query and exploration system, called X-search, to enable researchers to query patient cohort counts across a growing number of completed, NIH-funded studies in NSRR and explore the feasibility or likelihood of reusing the data for research studies.

Methods: X-search has been designed as a general framework with two loosely-coupled components: …


A Simple Method Of Coil Design, M. Rawlik, A. Eggenberger, J. Krempel, Christopher Crawford, K. Kirch, F. M. Piegsa, G. Quéméner Aug 2018

A Simple Method Of Coil Design, M. Rawlik, A. Eggenberger, J. Krempel, Christopher Crawford, K. Kirch, F. M. Piegsa, G. Quéméner

Physics and Astronomy Faculty Publications

In this article, we present a method to design a coil producing an arbitrarily shaped magnetic field by restricting the path of the coil's wires to a regular grid. The solution is then found by a simple least squares minimum. We discuss practical applications, in particular, in the active magnetic field stabilization system of the neutron electric dipole moment experiment at the Paul Scherrer Institute in Villigen, Switzerland. We also publish the software implementation of the method.


Query-Constraint-Based Mining Of Association Rules For Exploratory Analysis Of Clinical Datasets In The National Sleep Research Resource, Rashmie Abeysinghe, Licong Cui Jul 2018

Query-Constraint-Based Mining Of Association Rules For Exploratory Analysis Of Clinical Datasets In The National Sleep Research Resource, Rashmie Abeysinghe, Licong Cui

Computer Science Faculty Publications

Background: Association Rule Mining (ARM) has been widely used by biomedical researchers to perform exploratory data analysis and uncover potential relationships among variables in biomedical datasets. However, when biomedical datasets are high-dimensional, performing ARM on such datasets will yield a large number of rules, many of which may be uninteresting. Especially for imbalanced datasets, performing ARM directly would result in uninteresting rules that are dominated by certain variables that capture general characteristics.

Methods: We introduce a query-constraint-based ARM (QARM) approach for exploratory analysis of multiple, diverse clinical datasets in the National Sleep Research Resource (NSRR). QARM enables rule mining on …


Compact Hardware Implementation Of A Sha-3 Core For Wireless Body Sensor Networks, Yi Yang, Debiao He, Neeraj Kumar, Sherali Zeadally Jul 2018

Compact Hardware Implementation Of A Sha-3 Core For Wireless Body Sensor Networks, Yi Yang, Debiao He, Neeraj Kumar, Sherali Zeadally

Information Science Faculty Publications

One of the most important Internet of Things applications is the wireless body sensor network (WBSN), which can provide universal health care, disease prevention, and control. Due to large deployments of small scale smart sensors in WBSNs, security, and privacy guarantees (e.g., security and safety-critical data, sensitive private information) are becoming a challenging issue because these sensor nodes communicate using an open channel, i.e., Internet. We implement data integrity (to resist against malicious tampering) using the secure hash algorithm 3 (SHA-3) when smart sensors in WBSNs communicate with each other using the Internet. Due to the limited resources (i.e., storage, …


Performance Evaluation Of Energy-Autonomous Sensors Using Power-Harvesting Beacons For Environmental Monitoring In Internet Of Things (Iot), George Dan Moiş, Teodora Sanislav, Silviu Corneliu Folea, Sherali Zeadally May 2018

Performance Evaluation Of Energy-Autonomous Sensors Using Power-Harvesting Beacons For Environmental Monitoring In Internet Of Things (Iot), George Dan Moiş, Teodora Sanislav, Silviu Corneliu Folea, Sherali Zeadally

Information Science Faculty Publications

Environmental conditions and air quality monitoring have become crucial today due to the undeniable changes of the climate and accelerated urbanization. To efficiently monitor environmental parameters such as temperature, humidity, and the levels of pollutants, such as fine particulate matter (PM2.5) and volatile organic compounds (VOCs) in the air, and to collect data covering vast geographical areas, the development of cheap energy-autonomous sensors for large scale deployment and fine-grained data acquisition is required. Rapid advances in electronics and communication technologies along with the emergence of paradigms such as Cyber-Physical Systems (CPSs) and the Internet of Things (IoT) have led to …


Advancing The Understanding Of Environmental Transformations, Bioavailability And Effects Of Nanomaterials, An International Us Environmental Protection Agency—Uk Environmental Nanoscience Initiative Joint Program, Mitch M. Lasat, Kian Fan Chung, Jamie Lead, Steve Mcgrath, Richard J. Owen, Sophie Rocks, Jason M. Unrine, Junfeng Zhang Apr 2018

Advancing The Understanding Of Environmental Transformations, Bioavailability And Effects Of Nanomaterials, An International Us Environmental Protection Agency—Uk Environmental Nanoscience Initiative Joint Program, Mitch M. Lasat, Kian Fan Chung, Jamie Lead, Steve Mcgrath, Richard J. Owen, Sophie Rocks, Jason M. Unrine, Junfeng Zhang

Plant and Soil Sciences Faculty Publications

Nanotechnology has significant economic, health, and environmental benefits, including renewable energy and innovative environmental solutions. Manufactured nanoparticles have been incorporated into new materials and products because of their novel or enhanced properties. These very same properties also have prompted concerns about the potential environmental and human health hazard and risk posed by the manufactured nanomaterials. Appropriate risk management responses require the development of models capable of predicting the environmental and human health effects of the nanomaterials. Development of predictive models has been hampered by a lack of information concerning the environmental fate, behavior and effects of manufactured nanoparticles. The United …


Scheduling Based On Interruption Analysis And Pso For Strictly Periodic And Preemptive Partitions In Integrated Modular Avionics, Hui Lu, Qianlin Zhou, Zongming Fei, Rongrong Zhou Mar 2018

Scheduling Based On Interruption Analysis And Pso For Strictly Periodic And Preemptive Partitions In Integrated Modular Avionics, Hui Lu, Qianlin Zhou, Zongming Fei, Rongrong Zhou

Computer Science Faculty Publications

Integrated modular avionics introduces the concept of partition and has been widely used in avionics industry. Partitions share the computing resources together. Partition scheduling plays a key role in guaranteeing correct execution of partitions. In this paper, a strictly periodic and preemptive partition scheduling strategy is investigated. First, we propose a partition scheduling model that allows a partition to be interrupted by other partitions, but minimizes the number of interruptions. The model not only retains the execution reliability of the simple partition sets that can be scheduled without interruptions, but also enhances the schedulability of the complex partition sets that …


The 3d Stress-Tensor Bootstrap, Anatoly Dymarsky, Filip Kos, Petr Kravchuk, David Poland, David Simmons-Duffin Feb 2018

The 3d Stress-Tensor Bootstrap, Anatoly Dymarsky, Filip Kos, Petr Kravchuk, David Poland, David Simmons-Duffin

Physics and Astronomy Faculty Publications

We study the conformal bootstrap for 4-point functions of stress tensors in parity-preserving 3d CFTs. To set up the bootstrap equations, we analyze the constraints of conformal symmetry, permutation symmetry, and conservation on the stress-tensor 4-point function and identify a non-redundant set of crossing equations. Studying these equations numerically using semidefinite optimization, we compute bounds on the central charge as a function of the independent coefficient in the stress-tensor 3-point function. With no additional assumptions, these bounds numerically reproduce the conformal collider bounds and give a general lower bound on the central charge. We also study the effect of gaps …


Three Dimensional View Of Arbitrary Q Syk Models, Sumit R. Das, Aminik Ghosh, Antal Jevicki, Kenta Suzuki Feb 2018

Three Dimensional View Of Arbitrary Q Syk Models, Sumit R. Das, Aminik Ghosh, Antal Jevicki, Kenta Suzuki

Physics and Astronomy Faculty Publications

In [15] it was shown that the spectrum and bilocal propagator of SYK model with four fermion interactions can be realized as a three dimensional model in AdS2 ×S1/Z2 with nontrivial boundary conditions in the additional dimension. In this paper we show that a similar picture holds for generalizations of the SYK model with q-fermion interactions. The 3D realization is now given on a space whose metric is conformal to AdS2 × S1/Z2 and is subject to a non-trivial potential in addition to a delta function at the center of …


Preventing Crossover In Redox Flow Batteries Through Active Material Oligomerization, Susan A. Odom Feb 2018

Preventing Crossover In Redox Flow Batteries Through Active Material Oligomerization, Susan A. Odom

Chemistry Faculty Publications

No abstract provided.


Effect Of Molecular Side Groups And Local Nanoenvironment On Photodegradation And Its Reversibility, Nicole Quist, Mark Li, Ryan Tollefsen, Michael Haley, John Anthony, Oksana Ostroverkhova Feb 2018

Effect Of Molecular Side Groups And Local Nanoenvironment On Photodegradation And Its Reversibility, Nicole Quist, Mark Li, Ryan Tollefsen, Michael Haley, John Anthony, Oksana Ostroverkhova

Chemistry Faculty Publications

Degradation of organic semiconductors in the presence of oxygen is one of the bottlenecks preventing their wide-spread use in optoelectronic devices. The first step towards such degradation in functionalized pentacene (Pn) derivatives is formation of endoperoxide (EPO), which can either revert back to the parent molecule or proceed to molecule decomposition. We present the study of reversibility of EPO formation through probing the photophysical properties of functionalized fluorinated pentacene (Pn-R-F8) derivatives. Experiments are done in solutions and in films both at the single molecule level and in the bulk. In solutions, degradation of optical absorption and its partial recovery after …


Universality Of Fast Quenches From The Conformal Perturbation Theory, Anatoly Dymarsky, Michael Smolkin Jan 2018

Universality Of Fast Quenches From The Conformal Perturbation Theory, Anatoly Dymarsky, Michael Smolkin

Physics and Astronomy Faculty Publications

We consider global quantum quenches, a protocol when a continuous field theoretic system in the ground state is driven by a homogeneous time-dependent external interaction. When the typical inverse time scale of the interaction is much larger than all relevant scales except for the UV-cutoff the system’s response exhibits universal scaling behavior. We provide both qualitative and quantitative explanations of this universality and argue that physics of the response during and shortly after the quench is governed by the conformal perturbation theory around the UV fixed point. We proceed to calculate the response of one and two-point correlation functions confirming …


A Fast And Robust Extrinsic Calibration For Rgb-D Camera Networks, Po-Chang Su, Ju Shen, Wanxin Xu, Sen-Ching S. Cheung, Ying Luo Jan 2018

A Fast And Robust Extrinsic Calibration For Rgb-D Camera Networks, Po-Chang Su, Ju Shen, Wanxin Xu, Sen-Ching S. Cheung, Ying Luo

Electrical and Computer Engineering Faculty Publications

From object tracking to 3D reconstruction, RGB-Depth (RGB-D) camera networks play an increasingly important role in many vision and graphics applications. Practical applications often use sparsely-placed cameras to maximize visibility, while using as few cameras as possible to minimize cost. In general, it is challenging to calibrate sparse camera networks due to the lack of shared scene features across different camera views. In this paper, we propose a novel algorithm that can accurately and rapidly calibrate the geometric relationships across an arbitrary number of RGB-D cameras on a network. Our work has a number of novel features. First, to cope …


Magneto-Optical Properties Of Thin Permalloy Films: A Study Of The Magneto-Optical Generation Of Light Carrying Angular Momentum, Patrick D. Montgomery Jan 2018

Magneto-Optical Properties Of Thin Permalloy Films: A Study Of The Magneto-Optical Generation Of Light Carrying Angular Momentum, Patrick D. Montgomery

Theses and Dissertations--Electrical and Computer Engineering

Magneto-optical materials such as permalloy can be used to create artificial spin- ice (ASI) lattices with antiferromagnetic ordering. Magneto-optical materials used to create diffraction lattices are known to exhibit magnetic scattering at the half- order Bragg peak while in the ground state. The significant drawbacks of studying the magneto-optical generation of OAM using x-rays are cost, time, and access to proper equipment. In this work, it is shown that the possibility of studying OAM and magneto-optical materials in the spectrum of visible light at or around 2 eV is viable. Using spectroscopic ellipsometry it is possible to detect a change …


Self-Image Multimedia Technologies For Feedforward Observational Learning, Nkiruka M. A. Uzuegbunam Jan 2018

Self-Image Multimedia Technologies For Feedforward Observational Learning, Nkiruka M. A. Uzuegbunam

Theses and Dissertations--Electrical and Computer Engineering

This dissertation investigates the development and use of self-images in augmented reality systems for learning and learning-based activities. This work focuses on self- modeling, a particular form of learning, actively employed in various settings for therapy or teaching. In particular, this work aims to develop novel multimedia systems to support the display and rendering of augmented self-images. It aims to use interactivity (via games) as a means of obtaining imagery for use in creating augmented self-images. Two multimedia systems are developed, discussed and analyzed. The proposed systems are validated in terms of their technical innovation and their clinical efficacy in …