Physical Sciences and Mathematics Commons^™

Underwater Acoustic Signal Analysis Toolkit, Kirk Bienvenu Jr

University of New Orleans Theses and Dissertations

This project started early in the summer of 2016 when it became evident there was a need for an effective and efficient signal analysis toolkit for the Littoral Acoustic Demonstration Center Gulf Ecological Monitoring and Modeling (LADC-GEMM) Research Consortium. LADC-GEMM collected underwater acoustic data in the northern Gulf of Mexico during the summer of 2015 using Environmental Acoustic Recording Systems (EARS) buoys. Much of the visualization of data was handled through short scripts and executed through terminal commands, each time requiring the data to be loaded into memory and parameters to be fed through arguments. The vision was to develop …

Free-Space Measurements Of Dielectrics And Three-Dimensional Periodic Metamaterials, Clifford E. Kintner

Graduate Theses and Dissertations

This thesis presents the free-space measurements of a periodic metamaterial structure. The metamaterial unit cell consists of two dielectric sheets intersecting at 90 degrees. The dielectric is a polyetherimide-based material 0.001” thick. Each sheet has a copper capacitively-loaded loop (CLL) structure on the front and a cut-wire structure on the back. Foam material is used to support the unit cells. The unit cell repeats 40 times in the x-direction, 58 times in the y-direction and 5 times in the z-direction. The sample measures 12” × 12” × 1” in total. We use a free-space broadband system comprised of a pair …

Design And Implementation Of A Multi-Port Solid State Transformer For Flexible Der Integration, Mohammad Rashidi

Theses and Dissertations

Conventional power system includes four major sections, bulk generation, transmission network, distribution network, and loads. The main converter in the conventional electric grid is the low-frequency passive transformer providing galvanic isolation and voltage regulation for various voltage zones. In this configuration, small-scale renewable energy resources are generally connected to the power system at low voltage zones or inside microgrids.

Recent developments in the design of power electronic elements with higher voltage and power ratings and medium/high frequency enable making use of solid state transformer at different voltage levels in the distribution system and microgrid design. In this work, the concept …

Threshold Free Detection Of Elliptical Landmarks Using Machine Learning, Lifan Zhang

Theses and Dissertations

Elliptical shape detection is widely used in practical applications. Nearly all classical ellipse detection algorithms require some form of threshold, which can be a major cause of detection failure, especially in the challenging case of Moire Phase Tracking (MPT) target images. To meet the challenge, a threshold free detection algorithm for elliptical landmarks is proposed in this thesis. The proposed Aligned Gradient and Unaligned Gradient (AGUG) algorithm is a Support Vector Machine (SVM)-based classification algorithm, original features are extracted from the gradient information corresponding to the sampled pixels. with proper selection of features, the proposed algorithm has a high accuracy …

Asynchronous 3d (Async3d): Design Methodology And Analysis Of 3d Asynchronous Circuits, Francis Corpuz Sabado

Graduate Theses and Dissertations

This dissertation focuses on the application of 3D integrated circuit (IC) technology on asynchronous logic paradigms, mainly NULL Convention Logic (NCL) and Multi-Threshold NCL (MTNCL). It presents the Async3D tool flow and library for NCL and MTNCL 3D ICs. It also analyzes NCL and MTNCL circuits in 3D IC. Several FIR filter designs were implement in NCL, MTNCL, and synchronous architecture to compare synchronous and asynchronous circuits in 2D and 3D ICs. The designs were normalized based on performance and several metrics were measured for comparison. Area, interconnect length, power consumption, and power density were compared among NCL, MTNCL, and …

Graph-Based Latent Embedding, Annotation And Representation Learning In Neural Networks For Semi-Supervised And Unsupervised Settings, Ismail Ozsel Kilinc

USF Tampa Graduate Theses and Dissertations

Machine learning has been immensely successful in supervised learning with outstanding examples in major industrial applications such as voice and image recognition. Following these developments, the most recent research has now begun to focus primarily on algorithms which can exploit very large sets of unlabeled examples to reduce the amount of manually labeled data required for existing models to perform well. In this dissertation, we propose graph-based latent embedding/annotation/representation learning techniques in neural networks tailored for semi-supervised and unsupervised learning problems. Specifically, we propose a novel regularization technique called Graph-based Activity Regularization (GAR) and a novel output layer modification called …

Design And Simulation Of A Miniature Cylindrical Mirror Auger Electron Energy Analyzer With Secondary Electron Noise Suppression, Jay A. Bieber

USF Tampa Graduate Theses and Dissertations

In the nanoscale metrology industry, there is a need for low-cost instruments, which have the ability to probe the structrure and elemental composition of thin films. This dissertation, describes the research performed to design and simulate a miniature Cylindrical Mirror Analyzer, (CMA), and Auger Electron Spectrometer, (AES). The CMA includes an integrated coaxial thermionic electron source. Electron optics simulations were performed using the Finite Element Method, (FEM), software COMSOL. To address the large Secondary Electron, (SE), noise, inherent in AES spectra, this research also included experiments to create structures in materials, which were intended to suppress SE backgound noise in …

Investigating Scalable Manufacturing Of High-Conductivity Wires And Coatings From Ultra-Long Carbon Nanotubes, Pouria Khanbolouki

Mechanical Engineering ETDs

Carbon nanotubes (CNTs) are a promising candidate for next generation of electrical wirings and electromagnetic interference (EMI) shielding materials due to their exceptional mechanical and electrical properties. Wires and coatings from ultralong nanotubes that are highly crystalline, well-aligned and densely packed can achieve this goal. High-performance CNT conductors will be relatively lightweight and resistant to harsh conditions and therefore can potentially replace current conductors in many industries including aerospace, automotive, gas and oil.

This thesis investigates a new manufacturing approach, based on conventional solution coating and wire drawing methods, to fabricate high conductivity wires and coatings from ultra-long carbon nanotubes. …

Analyses Of Densely Crosslinked Phenolic Systems Using Low Field Nmr, Jigneshkumar Patel

Doctoral Dissertations

A uniform dispersion of reactants is necessary to achieve a complete reaction involving multi-components, especially for the crosslinking of rigid high-performance materials. In these reactions, miscibility is crucial for curing efficiency. This miscibility is typically enhanced by adding a third component, a plasticizer. For the reaction of the highly crystalline crosslinking agent hexamethylenetetramine (HMTA) with a strongly hydrogen-bonded phenol formaldehyde resin, furfural has been traditionally used as the plasticizer. However, the reason for its effectiveness is not clear. In this doctoral thesis work, miscibility and crosslinking efficiency of plasticizers in phenolic curing reactions are studied by thermal analysis and spectroscopic …

Adaft: A Resource-Efficient Framework For Adaptive Fault-Tolerance In Cyber-Physical Systems, Ye Xu

Doctoral Dissertations

Cyber-physical systems frequently have to use massive redundancy to meet application requirements for high reliability. While such redundancy is required, it can be activated adaptively, based on the current state of the controlled plant. Most of the time the physical plant is in a state that allows for a lower level of fault-tolerance. Avoiding the continuous deployment of massive fault-tolerance will greatly reduce the workload of CPSs. In this dissertation, we demonstrate a software simulation framework (AdaFT) that can automatically generate the sub-spaces within which our adaptive fault-tolerance can be applied. We also show the theoretical benefits of AdaFT, and …

Hierarchical Fusion Based Deep Learning Framework For Lung Nodule Classification, Kazim Sekeroglu

LSU Doctoral Dissertations

Lung cancer is the leading cancer type that causes the mortality in both men and women. Computer aided detection (CAD) and diagnosis systems can play a very important role for helping the physicians in cancer treatments. This dissertation proposes a CAD framework that utilizes a hierarchical fusion based deep learning model for detection of nodules from the stacks of 2D images. In the proposed hierarchical approach, a decision is made at each level individually employing the decisions from the previous level. Further, individual decisions are computed for several perspectives of a volume of interest (VOI). This study explores three different …

Nanowire-Based Light-Emitting Diodes: A New Path Towards High-Speed Visible Light Communication, Mohsen Nami

Physics & Astronomy ETDs

Nano-scale optoelectronic devices have gained significant attention in recent years. Among these devices are semiconductor nanowires, whose dimeters range from 100 to 200 nm. Semiconductor nanowires can be utilized in many different applications including light-emitting diodes and laser diodes. Higher surface to volume ratio makes nanowire-based structures potential candidates for the next generation of photodetectors, sensors, and solar cells. Core-shell light-emitting diodes based on selective-area growth of gallium nitride (GaN) nanowires provide a wide range of advantages. Among these advantages are access to non-polar m-plane sidewalls, higher active region area compared to conventional planar structures, and reduction of threading …

Solar Powered Single-Axis Heliostat Active Solar Tracking Device, Mason Kyle Roberts

Physics

As a means of cooking food, the burning of biomass accounts for over 4 million premature deaths in third world countries (“Household Air Pollution and Health”). The focus of this project was to explore an alternative that could utilize focused sunlight to cook food. A solar tracker was designed to be affixed to a parabolic, reflective, tilted single axis heliostat to follow the sun throughout the day and focus the reflected light to the bottom of a cooking surface. This surface became hot enough to for the preparation of food or boiling/sterilization of water.

A goal for each project was …

Secure Integer Comparisons Using The Homomorphic Properties Of Prime Power Subgroups, Rhys A. Carlton

Electronic Thesis and Dissertation Repository

Secure multi party computation allows two or more parties to jointly compute a function under encryption without leaking information about their private inputs. These secure computations are vital in many fields including law enforcement, secure voting and bioinformatics because the privacy of the information is of paramount importance.

One common reference problem for secure multi party computation is the Millionaires' problem which was first introduced by Turing Award winner Yao in his paper "Protocols for secure computation". The Millionaires' problem considers two millionaires who want to know who is richer without disclosing their actual worth.

There are public-key cryptosystems that …

Information Theoretic Study Of Gaussian Graphical Models And Their Applications, Ali Moharrer

LSU Doctoral Dissertations

In many problems we are dealing with characterizing a behavior of a complex stochastic system or its response to a set of particular inputs. Such problems span over several topics such as machine learning, complex networks, e.g., social or communication networks; biology, etc. Probabilistic graphical models (PGMs) are powerful tools that offer a compact modeling of complex systems. They are designed to capture the random behavior, i.e., the joint distribution of the system to the best possible accuracy. Our goal is to study certain algebraic and topological properties of a special class of graphical models, known as Gaussian graphs. First, …

Numerical Methods For Nonlinear Optimal Control Problems And Their Applications In Indoor Climate Control, Runxin He

McKelvey School of Engineering Theses & Dissertations

Efficiency, comfort, and convenience are three major aspects in the design of control systems for residential Heating, Ventilation, and Air Conditioning (HVAC) units. In this dissertation, we study optimization-based algorithms for HVAC control that minimizes energy consumption while maintaining a desired temperature, or even human comfort in a room. Our algorithm uses a Computer Fluid Dynamics (CFD) model, mathematically formulated using Partial Differential Equations (PDEs), to describe the interactions between temperature, pressure, and air flow. Our model allows us to naturally formulate problems such as controlling the temperature of a small region of interest within a room, or to control …

Bayesian Methods And Machine Learning For Processing Text And Image Data, Yingying Gu

Theses and Dissertations

Classification/clustering is an important class of unstructured data processing problems. The classification (supervised, semi-supervised and unsupervised) aims to discover the clusters and group the similar data into categories for information organization and knowledge discovery. My work focuses on using the Bayesian methods and machine learning techniques to classify the free-text and image data, and address how to overcome the limitations of the traditional methods. The Bayesian approach provides a way to allow using more variations(numerical or categorical), and estimate the probabilities instead of explicit rules, which will benefit in the ambiguous cases. The MAP(maximum a posterior) estimation is used to …

Understanding The Surface Fouling Mechanism Of Ultrananocrystalline Diamond Microelectrodes Using Microfluidics For Neurochemical Detection, An-Yi Chang

Doctoral Dissertations

Electrochemical methods are widely used for chronic neurochemical sensing, but thus far, the organic solution redox reactions fouled the electrodes' surface. It caused the reduction of sensitivity and the electrodes' lifetime.

Here, we present the boron-doped nanocrystalline diamond microelectrodes (BDUNCD) as the next generation electrode material for neurochemical sensor development. To aid in long-term chronic monitoring of neurochemicals, they have a wide window of electrochemical potential, extremely low background current, and excellent chemical inertness. The main research goal is to reduce the rate of electrode fouling due to the reaction by-products, and significantly extend their useful lifetime.

We systematically characterize …

Electrochemical Behavior Of Dense Electrodes For Impedancemetric Nox Sensors, Nabamita Pal

Doctoral Dissertations

NOx (NO and NO2) exhaust gas sensors for diesel powered vehicles have traditionally consisted of porous platinum (Pt) electrodes along with a dense ZrO2 based electrolyte. Advancement in diesel engine technology results in lower NOx emissions. Although Pt is chemically and mechanically tolerant to the extreme exhaust gas environment, it is also a strong catalyst for oxygen reduction, which can interfere with the detection of NOx at concentrations below 100 ppm. Countering this behavior can add to the complexity and cost of the conventional NO x sensor design. Recent studies have shown that dense electrodes are less prone to heterogeneous …

Speech Based Machine Learning Models For Emotional State Recognition And Ptsd Detection, Debrup Banerjee

Electrical & Computer Engineering Theses & Dissertations

Recognition of emotional state and diagnosis of trauma related illnesses such as posttraumatic stress disorder (PTSD) using speech signals have been active research topics over the past decade. A typical emotion recognition system consists of three components: speech segmentation, feature extraction and emotion identification. Various speech features have been developed for emotional state recognition which can be divided into three categories, namely, excitation, vocal tract and prosodic. However, the capabilities of different feature categories and advanced machine learning techniques have not been fully explored for emotion recognition and PTSD diagnosis. For PTSD assessment, clinical diagnosis through structured interviews is a …

Multispectral Identification Array, Zachary D. Eagan

Computer Engineering

The Multispectral Identification Array is a device for taking full image spectroscopy data via the illumination of a subject with sixty-four unique spectra. The array combines images under the illumination spectra to produce an approximate reflectance graph for every pixel in a scene. Acquisition of an entire spectrum allows the array to differentiate objects based on surface material. Spectral graphs produced are highly approximate and should not be used to determine material properties, however the output is sufficiently consistent to allow differentiation and identification of previously sampled subjects. While not sufficiently advanced for use as a replacement to spectroscopy the …

Generalized Differential Calculus And Applications To Optimization, R. Blake Rector

Dissertations and Theses

This thesis contains contributions in three areas: the theory of generalized calculus, numerical algorithms for operations research, and applications of optimization to problems in modern electric power systems. A geometric approach is used to advance the theory and tools used for studying generalized notions of derivatives for nonsmooth functions. These advances specifically pertain to methods for calculating subdifferentials and to expanding our understanding of a certain notion of derivative of set-valued maps, called the coderivative, in infinite dimensions. A strong understanding of the subdifferential is essential for numerical optimization algorithms, which are developed and applied to nonsmooth problems in operations …

Operating Temperature Of A Solar Thermal Stirling Engine, Spencer Beck

Senior Theses

This paper explores the relationship between the operating temperature and electricity production of a simple heat engine. A Stirling engine was designed and constructed which runs on solar thermal energy collected by a Fresnel lens. The surface area of the solar collector was varied. This manipulated the operating temperature of the Stirling engine in order to measure power output. The mechanical energy from the engine was converted to electricity using a DC motor running in reverse, acting like a generator, in conjunction with an Arduino for data collection. Although adjustments must be made in order to improve the efficiency of …

Are Solar Panels A Viable Power Source For A Green Energy Vehicle?, Mason C. Adams

Senior Theses

A solar cell powered go-kart has been built and tested. The result shows using solar energy alone cannot meet the requirement of running a regular passenger car. This is due to the limited surface area of the passenger car. This thesis also discusses the operating principles of solar panels, the physics of P type and N type semiconductors, and the formation of the PN junction, as well as the solar current. Modifications of an existing go-kart are described in detail in this thesis. Suggestions for making green vehicles are discussed as well.

Multidataset Independent Subspace Analysis: A Framework For Analysis Of Multimodal, Multi-Subject Brain Imaging Data, Rogers F. Silva

Electrical and Computer Engineering ETDs

Mental illnesses are serious disorders of the brain that have devastating effects on individuals and society. In addition to their disabling and impairing effects, mental illnesses have deep social and economical implications, accounting for an estimated loss of 12 billion working days and a care cost surge to $6 trillion a year by 2030. For diseases such as depression and anxiety, enhancing preventive programs and treatment accessibility, in combination with accurate early diagnosis and personalized treatments, are projected to result in a four-fold return on every dollar invested, a strategy that can drastically help curtail those losses. Notably, within the …

Investigating Student Learning Of Analog Electronics, Kevin L. Van De Bogart

Electronic Theses and Dissertations

Instruction in analog electronics is an integral component of many physics and engineering programs, and is typically covered in courses beyond the first year. While extensive research has been conducted on student understanding of introductory electric circuits, to date there has been relatively little research on student learning of analog electronics in either physics or engineering courses. Given the significant overlap in content of courses offered in both disciplines, this study seeks to strengthen the research base on the learning and teaching of electric circuits and analog electronics via a single, coherent investigation spanning both physics and engineering courses.

This …

Target Detection With Neural Network Hardware, Hollis Bui, Garrett Massman, Nikolas Spangler, Jalen Tarvin, Luke Bechtel, Kevin Dunn, Shawn Bradford

Chancellor’s Honors Program Projects

No abstract provided.

Hexarray: A Novel Self-Reconfigurable Hardware System, Fady Hussein

Boise State University Theses and Dissertations

Evolvable hardware (EHW) is a powerful autonomous system for adapting and finding solutions within a changing environment. EHW consists of two main components: a reconfigurable hardware core and an evolutionary algorithm. The majority of prior research focuses on improving either the reconfigurable hardware or the evolutionary algorithm in place, but not both. Thus, current implementations suffer from being application oriented and having slow reconfiguration times, low efficiencies, and less routing flexibility. In this work, a novel evolvable hardware platform is proposed that combines a novel reconfigurable hardware core and a novel evolutionary algorithm.

The proposed reconfigurable hardware core is a …

A Manufacturer Design Kit For Multi-Chip Power Module Layout Synthesis, Jonathan Main

Electrical Engineering Undergraduate Honors Theses

The development of Multi-Chip Power Modules (MCPMs) has been a key factor in recent advancements in power electronics technologies. MCPMs achieve higher power density by combining multiple power semiconductor devices into one package. The work detailed in this thesis is part of an ongoing project to develop a computer-aided design software tool known as PowerSynth for MCPM layout synthesis and optimization. This thesis focuses on the definition and design of a Manufacturer Design Kit (MDK) for PowerSynth, which enables the designer to design an MCPM for a manufacturer’s fabrication process.

The MDK is comprised of a layer stack and technology …

Characterization Of Coupled Gold Nanoparticles In A Sparsely Populated Square Lattice, Roy Truett French Iii

Graduate Theses and Dissertations

Metal nanoparticles deposited in regular arrays spaced at optical wavelengths support a resonance due to a coherent coupling between localized surface plasmon mode and lattice diffraction allowing for engineering of tunable devices for use in biological sensors, nanoantennae, and enhanced spectroscopy. Techniques such as electron beam lithography, focused ion beam lithography, nanosphere lithography, and nanoimprint lithography are used for fabrication but are limited by cost, device throughput, and small deposition. Polymer soft lithography and continuous dewetting of particles is a potentially viable alternative showing promise in all of those areas. This thesis developed the fabrication of a refined hydrophilic nanoimprinted …