Physical Sciences and Mathematics Commons^™

Towards Structured Planning And Learning At The State Fisheries Agency Scale, Caleb A. Aldridge

Theses and Dissertations

Inland recreational fisheries has grown philosophically and scientifically to consider economic and sociopolitical aspects (non-biological) in addition to the biological. However, integrating biological and non-biological aspects of inland fisheries has been challenging. Thus, an opportunity exists to develop approaches and tools which operationalize planning and decision-making processes which include biological and non-biological aspects of a fishery. This dissertation expands the idea that a core set of goals and objectives is shared among and within inland fisheries agencies; that many routine operations of inland fisheries managers can be regimented or standardized; and the novel concept that current information and operations can …

Image-Based Cancer Diagnosis Using Novel Deep Neural Networks, Hosein Barzekar

Theses and Dissertations

Cancer is the major cause of death in many nations. This serious illness can only be effectivelytreated if it is diagnosed early. In contrast, biomedical imaging presents challenges to both clinical institutions and researchers. Physiological anomalies are often characterized by modest modifications in individual cells or tissues, making them difficult to detect visually. Physiological anomalies are often characterized by slight abnormalities in individual cells or tissues, making them difficult to detect visually. Traditionally, anomalies are diagnosed by radiologists and pathologists with extensive training. This procedure, however, demands the participation of professionals and incurs a substantial expense, making the classification of …

Use Of Machine Learning And Natural Language Processing To Enhance Traffic Safety Analysis, Md Abu Sayed

Theses and Dissertations

Despite significant advances in vehicle technologies, safety data collection and analysis, and engineering advancements, tens of thousands of Americans die every year in motor vehicle crashes. Alarmingly, the trend of fatal and serious injury crashes appears to be heading in the wrong direction. In 2021, the actual rate of fatalities exceeded the predicted rate. This worrisome trend prompts and necessitates the development of advanced and holistic approaches to determining the causes of a crash (particularly fatal and major injuries). These approaches range from analyzing problems from multiple perspectives, utilizing available data sources, and employing the most suitable tools and technologies …

Water Hardness Removal By Electrochemical Precipitation In A Continuous Flow Condition Using Conductive Concrete As Cathode, Tahsin Tareque

Theses and Dissertations

This study focuses on the electrochemical precipitation (EP) process to reduce excess water hardness from the Lower Rio Grande Valley (LRGV) tap water using electrically conductive concrete as cathode in a continuous flow condition. LRGV tap water is extremely hard with hardness more than 350 mg/L as CaCO3. Humans can pleasantly consume water with hardness less than 150 mg/l as CaCO3 according to World Health Organization (WHO). Hard water is also known to cause mechanical problems to boilers and heat exchangers. In this process, electricity is passed through electrodes submerged in electrolyte, which causes an alkaline environment around the cathode …

Cnn-Based Dendrite Core Detection From Microscopic Images Of Directionally Solidified Ni-Base Alloys, Xiaoguang Li

Theses and Dissertations

Dendrite core is the center point of the dendrite. The information of dendrite core is very helpful for material scientists to analyze the properties of materials. Therefore, detecting the dendrite core is a very important task in the material science field. Meanwhile, because of some special properties of the dendrites, this task is also very challenging. Different from the typical detection problems in the computer vision field, detecting the dendrite core aims to detect a single point location instead of the bounding-box. As a result, the existing regressing bounding-box based detection methods can not work well on this task because …

Empirical Studies On Automated Software Testing Practices, Alireza Salahirad

Theses and Dissertations

Software testing is notoriously difficult and expensive, and improper testing carries economic, legal, and even environmental or medical risks. Research in software testing is critical to enabling the development of the robust software that our society relies upon. This dissertation aims to lower the cost of software testing without decreasing the quality by focusing on the use of automation. The dissertation consists of three empirical studies on aspects of software testing. Specifically, these three projects focus on (1) mapping the connections between research topics and the evolution of research topics in the field of software testing, (2) an assessment of …

Investigation Of Adhesion, Deformation Mechanics, And Electrical Properties Of Ag/Sio2/Pdms Tri-Layers For Stretchable Electronic Applications, Rhandy Joe Paladines

Theses and Dissertations

The motivation behind this research is to improve the interfacial layer bonding of metallic thin films to PDMS substrates with the aid of a buffer layer. The physical vapor deposition (PVD) technique of sputtering was used to deposit bilayer thin films of silver (Ag) and silicon dioxide (SiO2) on PDMS. Two chamber pressures were used in this work, 5 and 20 mTorr, to investigate the role of this parameter in determining the interfacial adhesion and the role in determining the resistance sensitivity. Studies of the surface energy and increased bonding strength for metallization are carried out. Surface characterization using atomic …

A Machine Learning Framework For Automatic Speech Recognition In Air Traffic Control Using Word Level Binary Classification And Transcription, Fowad Shahid Sohail

Theses and Dissertations

Advances in Artificial Intelligence and Machine learning have enabled a variety of new technologies. One such technology is Automatic Speech Recognition (ASR), where a machine is given audio and transcribes the words that were spoken. ASR can be applied in a variety of domains to improve general usability and safety. One such domain is Air Traffic Control (ATC). ASR in ATC promises to improve safety in a mission critical environment. ASR models have historically required a large amount of clean training data. ATC environments are noisy and acquiring labeled data is a difficult, expertise dependent task. This thesis attempts to …

Enabling Rapid Chemical Analysis Of Plutonium Alloys Via Machine Learning-Enhanced Atomic Spectroscopy Techniques, Ashwin P. Rao

Theses and Dissertations

Analytical atomic spectroscopy methods have the potential to provide solutions for rapid, high fidelity chemical analysis of plutonium alloys. Implementing these methods with advanced analytical techniques can help reduce the chemical analysis time needed for plutonium pit production, directly enabling the 80 pit-per-year by 2030 manufacturing goal outlined in the 2018 Nuclear Posture Review. Two commercial, handheld elemental analyzers were validated for potential in situ analysis of Pu. A handheld XRF device was able to detect gallium in a Pu surrogate matrix with a detection limit of 0.002 wt% and a mean error of 8%. A handheld LIBS device was …

Analyzing Microarchitectural Residue In Various Privilege Strata To Identify Computing Tasks, Tor J. Langehaug

Theses and Dissertations

Modern multi-tasking computer systems run numerous applications simultaneously. These applications must share hardware resources including the Central Processing Unit (CPU) and memory while maximizing each application’s performance. Tasks executing in this shared environment leave residue which should not reveal information. This dissertation applies machine learning and statistical analysis to evaluate task residue as footprints which can be correlated to identify tasks. The concept of privilege strata, drawn from an analogy with physical geology, organizes the investigation into the User, Operating System, and Hardware privilege strata. In the User Stratum, an adversary perspective is taken to build an interrogator program that …

Development Of A Security-Focused Multi-Channel Communication Protocol And Associated Quality Of Secure Service (Qoss) Metrics, Paul M. Simon

Theses and Dissertations

The threat of eavesdropping, and the challenge of recognizing and correcting for corrupted or suppressed information in communication systems is a consistent challenge. Effectively managing protection mechanisms requires an ability to accurately gauge the likelihood or severity of a threat, and adapt the security features available in a system to mitigate the threat. This research focuses on the design and development of a security-focused communication protocol at the session-layer based on a re-prioritized communication architecture model and associated metrics. From a probabilistic model that considers data leakage and data corruption as surrogates for breaches of confidentiality and integrity, a set …

Three Case Studies Of Using Hybrid Model Machine Learning Techniques In Educational Data Mining To Improve The Classification Accuracies, Sujan Poudyal

Theses and Dissertations

A multitude of data is being produced from the increase in instructional technology, e-learning resources, and online courses. This data could be used by educators to analyze and extract useful information which could be beneficial to both instructors and students. Educational Data Mining (EDM) extracts hidden information from data contained within the educational domain. In data mining, hybrid method is the combination of various machine learning techniques. Through this dissertation, the novel use of machine learning hybrid techniques was explored in EDM using three educational case studies. First, in consideration for the importance of students’ attention, on and off-task data …

Enhancement Of Energy Efficiency For Thermal Energy And Biomass Driven Applications, Osama Mansour Selim Elsayed

Theses and Dissertations

The importance of gas turbine blades is to convert the thermal energy into shaft work output, which makes the turbine blades are one of the critical components of the gas turbines. Besides the mechanical stresses caused by the centrifugal force and the fluid forces, the thermal stresses arise because of the temperature gradient within the blade materials. This paper aims to have a uniform circumferential temperature field at the combustor exit, consequently reducing the thermal stresses caused by the non-uniform temperature distribution along the turbine blade. The validation of the simulation results with the experiments showed an acceptable agreement with …

Tree Ring Reconstructions Of Streamflow For The Lower Rio Grande Valley Of Texas, Adedolapo Mutiyat Adeyanju

Theses and Dissertations

The Rio Grande River is a major water source for people living within the USA-Mexico border. The Rio Grande River has its headwaters in the San Juan Mountains in Colorado and the Sierra Madre Occidental in Mexico before flowing into Texas through El-Paso. The water supply issues facing the Lower Rio Grande Basin (LRGB) are extremely complex from international restrictions to severe climate change. The river shares its flow between the U.S.A and Mexico based on the provisions of the 1944 treaty between the U.S.A and Mexico. The LRGB flow is regulated by releases from Falcon and Amistad Reservoirs managed …

Learning Depth From Images, Zhenyao Wu

Theses and Dissertations

Estimating depth from images has become a very popular task in computer vision which aims to restore the 3D scene from 2D images and identify important geometric knowledge of the scene. Its performance has been significantly improved by convolutional neural networks in recent years, which surpass the traditional methods by a large margin. However, the natural scenes are usually complicated, and hard to build the correspondence between pixels across frames, such as the region containing moving objects, illumination changes, occlusions, and reflections. This research explores rich and comprehensive spatial correspondence across images and designs three new network architectures for depth …

Cnn-Based Semantic Segmentation With Shape Prior Knowledge, Yuhang Lu

Theses and Dissertations

Semantic segmentation that aims at grouping discrete pixels into connected regions is a fundamental step in many high-level computer vision tasks. In recent years, Convolutional Neural Networks (CNNs) have made breakthrough progresses in public semantic segmentation benchmarks. The ability of learning from large-scale labeled datasets empowers them to generalize to unseen images better than traditional nonlearning-based methods. Nevertheless, the heavy dependency on labeled data also limits their applications in tasks where high-quality ground truth segmentation masks are scarce or difficult to acquire. In this dissertation, we study the problem of alleviating the data dependency for CNN-based segmentation with a focus …

Knowledge-Infused Learning, Manas Gaur

Theses and Dissertations

In DARPA’s view of the three waves of AI, the first wave of AI, symbolic AI, focused on explicit knowledge. The second and current wave of AI is termed statistical AI. Deep learning techniques have been able to exploit large amounts of data and massive computational power to improve human levels of performance in narrowly defined tasks. Separately, knowledge graphs have emerged as a powerful tool to capture and exploit a variety of explicit knowledge to make algorithms better apprehend the content and enable the next generation of data processing, such as semantic search. After initial hesitancy about the scalability …

Image Restoration Under Adverse Illumination For Various Applications, Lan Fu

Theses and Dissertations

Many images are captured in sub-optimal environment, resulting in various kinds of degradations, such as noise, blur, and shadow. Adverse illumination is one of the most important factors resulting in image degradation with color and illumination distortion or even unidentified image content. Degradation caused by the adverse illumination makes the images suffer from worse visual quality, which might also lead to negative effects on high-level perception tasks, e.g., object detection.

Image restoration under adverse illumination is an effective way to remove such kind of degradations to obtain visual pleasing images. Existing state-of-the-art deep neural networks (DNNs) based image restoration …

Cross Domain Semantic Segmentation, Xinyi Wu

Theses and Dissertations

As a long-standing computer vision task, semantic segmentation is still extensively researched till now because of its importance to visual understanding and analysis. The goal of semantic segmentation is to classify each pixel of images based on the pre-defined classes. In the era of deep learning, convolutional neural networks largely improve the accuracy and efficiency of semantic segmentation. However, this success is achieved with two limitations: 1) a large-scale labeled dataset is required for training while the labeling process for this task is quite labor-intensive and tedious; 2) the trained deep networks can get promising results when testing on the …

Identifying And Discovering Curve Pattern Designs From Fragments Of Pottery, Jun Zhou

Theses and Dissertations

The surface of many cultural heritage objects, such as pottery sherds found in the Southeastern Woodlands, were embellished with curve patterns. The original full designs of these patterns reflect rich historical and cultural information. However, in practice, most objects are fragmentary, making the complete underlying designs unknowable at the scale of the sherd fragment. The challenge to reconstruct and study complete designs is stymied because 1) most pottery sherds contain only a small portion of the underlying full design, 2) curve patterns detected on a sherd are usually incomplete and noisy, and 3) in the case of a stamping application, …

Development Of Software Tools For Efficient And Sustainable Process Development And Improvement, Jake P. Stengel

Theses and Dissertations

Infrastructure is a key component in the well-being of our society that leads to its growth, development, and productive operations. A well-built infrastructure allows the community to be more competitive and promotes economic advancement. In 2021, the ASCE (American Society of Civil Engineers) ranked the American infrastructure as substandard, with an overall grade of C-. The overall ranking suffers when key infrastructure categories are not maintained according to the needs of the population. Therefore, there is a need to consider alternative methods to improve our infrastructure and make it more sustainable to enhance the overall grade. One of the challenges …

Methods For Focal Plane Array Resolution Estimation Using Random Laser Speckle In Non-Paraxial Geometries, Phillip J. Plummer

Theses and Dissertations

The infrared (IR) imaging community has a need for direct IR detector evaluation due to the continued demand for small pixel pitch detectors, the emergence of strained-layer-super-lattice devices, and the associated lateral carrier diffusion issues. Conventional laser speckle-based modulation transfer function (MTF) estimation is dependent on Fresnel propagation and a wide-sense-stationary input random process, limiting the use of this approach for lambda (wavelength)-scale IR devices. This dissertation develops two alternative methodologies for speckle-based resolution evaluation of IR focal plane arrays (FPAs). Both techniques are formulated using Rayleigh-Sommerfield electric field propagation, making them valid in the non-paraxial geometries dictated for resolution …

Full Pattern Analysis And Comparison Of The Center Fed And Offset Fed Cassegrain Antennas With Large Focal Length To Diameter Ratios For High Power Microwave Transmission, Derek W. Mantzke

Theses and Dissertations

High power microwaves (HPM) have been a topic of research since the Cold War era. This paper will present a comparison between two Cassegrain-type antennas: the axially, or center fed, and the offset fed. Specifically, the 10 GHz operating frequency will be investigated with large focal length to diameter () ratios. Beam patterns which encompass the entire radiation pattern will be included for data validation and optimization. The simulations will follow a design of experiments factorial model to ensure all possible combinations of prescribed parameters are included, including an analysis of variance (ANOVA) study to find parameter influence on the …

Evaluating A Statistical-Based Assessment Tool For Stratifying Risk Among U.S. Air Force Organizations, Tiffany A. Low

Theses and Dissertations

The Air Force Inspection System is a proponent of utilizing a risk-based sampling strategy (RBSS) for conducting inspections from major command levels down to the unit level. The strategy identifies areas deemed most important or risky by commanders and prioritizes them accordingly for an independent assessment by the Inspector General. While Air Force regulation specifies the need to use a RBSS for inspection, the implementation process is delegated to individual commands and, subsequently, wings. The 23rd Wing, the sponsor for this research, directed us to analyze a RBSS tool highlighted as an example from which to adopt for those units …

Development And Evaluation Of Seasonal, Continental-Scale Streamflow Forecasts, Elissa Marie Yeates

Theses and Dissertations

Methods of forecasting streamflow using atmospheric ensembles and hydrologic routing have greatly improved over the past decades. These forecasts anticipate the timing and magnitude of streamflow peaks, enabling early warning of floods. Recent advances in atmospheric modeling have enabled production of forecasts months ahead, which are less precise but give a useful sense of trends.

The purpose of this study is to produce and evaluate a seasonal streamflow forecast model using a Muskingum routing hydrologic model coupled with runoff from a land surface model, and atmospheric input from a medium-term atmospheric and precipitation model. To evaluate the skill of the …

A Modular Synthesis Of Processable And Thermally Stable Semi-Fluorinated Aryl Ether Polymers Via Step-Growth Polymerization Of Fluoroalkenes, Ketki Eknath Shelar

Theses and Dissertations

Tailored fluoropolymers remain the leading choice for a wide variety of advanced high-performance applications, including electronic/optical and energy conversion, owing to their unique blend of complementary high-performance properties. Amorphous semi-fluorinated polymers exhibit improved solubility and melt processability when compared to traditional perfluoropolymers. A leading class of semi-fluorinated aryl ether polymers includes perfluorocyclobutyl (PFCB), perfluorocycloalkenyl (PFCA), and fluoroarylene vinylene ether (FAVE) polymers. Monomers containing aromatic trifluorovinyl ethers (TFVE) are used to synthesize PFCB polymers via radical-mediated [2+2] cyclodimerization. On the other hand, FAVE and PFCA polymers are polymerized via base-mediated nucleophilic addition/elimination of bisphenols with TFVE monomers and decafluorocyclohexene respectively. The …

Direct Simulation And Reduced-Order Modeling Of Premixed Flame Response To Acoustic Modulation, Zheng Qiao

Theses and Dissertations

This dissertation introduces a general, predictive and cost-efficient reduced-order modeling (ROM) technique for characterization of flame response under acoustic modulation. The model is built upon the kinematic flame model–G-equation to describe the flame topology and dynamics, and the novelties of the ROM lie in i) a procedure to create the compatible base flow that can reproduce the correct flame geometry and ii) the use of a physically-consistent acoustic modulation field for the characterization of flame response. This ROM addresses the significant limitations of the classical kinematic model, which is only applicable to simple flame configurations and relies on ad-hoc models …

Photocatalytic Degradation Of Organic Contaminants By Titania Particles Produced By Flame Spray Pyrolysis, Noah Babik

Theses and Dissertations

Advanced oxidation of organic pollutants with TiO2 photocatalysts is limited due to the wide bandgap of TiO2, 3.2 eV, which requires ultraviolet (UV) radiation. When nanosized TiO2 is modified by carbon doping, charge recombination is inhibited and the bandgap is narrowed, allowing for efficient photodegradation under visible light. Here, we propose a flame spray pyrolysis (FSP) technique to create TiO2. The facile process of FSP has been successful in preparing highly crystalline TiO2 nanoparticles. Using the same procedure to deposit TiO2 onto biochar, the photocatalyst was doped by the carbonaceous material. The morphology, crystalline and electronic structure of the FSP …

A Novel Method For Sensitivity Analysis Of Time-Averaged Chaotic System Solutions, Christian A. Spencer-Coker

Theses and Dissertations

The direct and adjoint methods are to linearize the time-averaged solution of bounded dynamical systems about one or more design parameters. Hence, such methods are one way to obtain the gradient necessary in locally optimizing a dynamical system’s time-averaged behavior over those design parameters. However, when analyzing nonlinear systems whose solutions exhibit chaos, standard direct and adjoint sensitivity methods yield meaningless results due to time-local instability of the system. The present work proposes a new method of solving the direct and adjoint linear systems in time, then tests that method’s ability to solve instances of the Lorenz system that exhibit …

Impact Of Climate Oscillations/Indices On Hydrological Variables In The Mississippi River Valley Alluvial Aquifer., Meena Raju

Theses and Dissertations

The Mississippi River Valley Alluvial Aquifer (MRVAA) is one of the most productive agricultural regions in the United States. The main objectives of this research are to identify long term trends and change points in hydrological variables (streamflow and rainfall), to assess the relationship between hydrological variables, and to evaluate the influence of global climate indices on hydrological variables. Non-parametric tests, MMK and Pettitt’s tests were used to analyze trend and change points. PCC and Streamflow elasticity analysis were used to analyze the relationship between streamflow and rainfall and the sensitivity of streamflow to rainfall changes. PCC and MLR analysis …