Digital Commons Network^™

Water Quality Monitoring And Mapping Using Rapidly Deployable Sensor Nodes, Mohamed Abdelwahab

Theses and Dissertations

Efficient and continuous monitoring of water quality parameters plays a pivotal role in responding to pollution incidents and ensuring the safety of both human consumption and ecological resources. This research introduces an affordable and dependable in-situ water quality sensor package designed for seamless continuous monitoring, providing essential data to facilitate informed decision-making in water resource management. The sensor package enables comprehensive on-site assessment of key water characteristics, including pH, temperature, turbidity (measured in NTU), and total dissolved solids (TDS, measured in ppm). Spatial interpolation techniques, specifically Kriging, are employed to extrapolate variable values at unobserved locations based on nearby measurements. …

Simulation-Based Optimization Of A Dc Microgrid: With Machine-Learning-Based Models And Hybrid Meta-Heuristic Algorithms, Tyler Van Deese

Theses and Dissertations

The field of economic dispatch (ED) focuses on optimizing power flow in a power system to minimize costs. It has the potential to significantly enhance system effectiveness, and efficiency, and reduce operating costs. Various techniques have been employed to tackle this problem, each with its own strengths and weaknesses. One promising approach is simulation-based optimization (SBO), which allows for accurate modeling of system interactions and improved representation of expected results. However, SBO requires running numerous simulations to identify an optimal solution, and there is a possibility of not achieving the global optimum. This work aims to address these challenges using …

Practice, Community, And Algorithms: How Youtube Creators Learn Through Making, Morgan E. Forbush

Theses and Dissertations

In this thesis, I answer the following questions: How do YouTube content creators learncontent creation through their practice and participation in communities of practice? How do these communities help creators form identity? And, lastly, how do the YouTube’s automated systems shape creators’ practice and impact their identity? To explore these questions, I observed a community of new creators to understand how creators learned about content creation from others. I interviewed 11 YouTube creators that ranged in size of viewership and experience to understand how they personally adapted their content to the platform of YouTube as they create videos. I find …

A Comparative Study On Feature Extraction And Classification/Clustering Of Fake News And Conspiracy Theories From Twitter Data, Deb Shana

Theses and Dissertations

No abstract provided.

Analysis Of Music Genre Clustering Algorithms, Samuel Walter Stern

Theses and Dissertations

Classification and clustering of music genres has become an increasingly prevalent focusin recent years, prompting a push for research into relevant algorithms. The most successful algorithms have typically applied the Naive Bayes or k-Nearest Neighbors algorithms, or used Neural Networks to perform classification. This thesis seeks to investigate the use of unsupervised clustering algorithms such as K-Means or Hierarchical clustering, and establish their usefulness in comparison to or conjunction with established methods.

Algorithmic Robot Design: Label Maps, Procrustean Graphs, And The Boundary Of Non-Destructiveness, Shervin Ghasemlou

Theses and Dissertations

This dissertation is focused on the problem of algorithmic robot design. The process of designing a robot or a team of robots that can reliably accomplish a task in an environment requires several key elements. How the problem is formulated can play a big role in the design process. The ability of the model to correctly reflect the environment, the events, and different pieces of the problem is crucial. Another key element is the ability of the model to show the relationship between different designs of a single system. These two elements can enable design algorithms to navigate through the …

Way-Finding: A New Approach To Studying Digital Communications, William Daniel Glade

Theses and Dissertations

This work further develops the way-finding model first proposed by Pearson and Kosicki (2017) which examines the flow of information in the digital age. Way-finding systems are online systems that help individuals find information—i.e. social media, search engines, email, etc. Using a grounded theory methodology, this new framework was explored in greater detail. Way-finding theory was created using the context of the elaboration likelihood model, gatekeeping theory, algorithmic gatekeepers, and the existence of the filter bubble phenomenon. This study establishes the three basic pillars of way-finding theory: the user’s mindset when accessing way-finding systems, the perception of how popular way-finding …

The Non-Mechanical Beam Steering Of Light In Reflective Inverse Diffusion, Eric K. Nagamine

Theses and Dissertations

Wavefront shaping is a technique that uses spatial light modulators to conjugate the phase of light incident on a rough surface, such that the light will refocus after reflection. This refocusing effect is called reflective inverse diffusion. There currently are two different approaches used to achieve reflective inverse diffusion: iterative methods and matrix methods. Iterative methods find one phase mask which allows for reflected light to be focused at a single, specific position, with results that are immediately available and continuously improving. Matrix methods calculate the complex matrix which describes the rough surface and allows for reflected light to be …

Simulation And Piloted Simulator Study Of An Automatic Ground Collision Avoidance System For Performance Limited Aircraft, James D. Carpenter

Theses and Dissertations

The F-16 Automatic-Ground Collision Avoidance System (Auto-GCAS) has been a resounding success since implementation in Nov 2014, saving 8 pilots and 7 aircraft from Controlled Flight into Terrain (CFIT). However, there is no implemented Auto- GCAS for "heavy" performance limited aircraft. This research endeavors to expand on the success of F-16 Auto-GCAS to other aircraft in the Air Force inventory such as the C-130, C-17, and B-1. MIL-STD-1797 classifies performance limited aircraft as large, heavy, and low to medium maneuverability. Using a stitched Learjet-25D model (LJ-25D), an Auto-GCAS algorithm was developed to predict multiple escape-maneuver trajectories, compare these paths to …

Multi-Path Automatic Ground Collision Avoidance System For Performance Limited Aircraft With Flight Tests: Project Have Medusa, Kenneth C. Gahan

Theses and Dissertations

A multi-path automatic ground collision avoidance system (Auto-GCAS) for performance limited aircraft was further developed and improved to prevent controlled flight into terrain. This research includes flight test results from the United States Test Pilot School's Test Management Project (TMP) titled Have Multi-Path Escape Decisions Using Sophisticated Algorithms (MEDUSA). Currently, the bomber and mobility air- craft communities lack an Auto-GCAS. The F-16 Auto-GCAS was proven successful for fighter-type aircraft with seven aircraft and eight lives saved from 2014 to 2018. The newly developed and tested Rapidly Selectable Escape Trajectory (RSET) sys- tem included a 5-path implementation which continuously updated at …

An Investigation Of The Cortical Learning Algorithm, Anthony C. Samaritano

Theses and Dissertations

Pattern recognition and machine learning fields have revolutionized countless industries and applications from biometric security to modern industrial assembly lines. The fields continue to accelerate as faster, more efficient processing hardware becomes commercially available. Despite the accelerated growth of the pattern recognition and machine learning fields, computers still are unable to learn, reason, and perform rudimentary tasks that humans and animals find routine. Animals are able to move fluidly, understand their environment, and maximize their chances of survival through adaptation - animals demonstrate intelligence. A primary argument in this thesis that we have not yet achieved a level of intelligence …

Pulse Height Spectra Analysis Of A Neutron Energy Tuning Assembly, Jason R. Stickney

Theses and Dissertations

An energy tuning assembly (ETA) was previously designed and built for the purpose of irradiating samples with a combination of a thermonuclear and a prompt fission neutron spectrum. Initial research was performed to characterize the performance of the ETA at the Lawrence Berkeley National Laboratory 88-Inch Cyclotron using 33 MeV deuteron breakup on tantalum as the neutron source. This research analyzes detector responses collected from three EJ-309 detectors used to characterize the ETA generated neutron field. A signal processing chain was developed to reduce the full waveform data into a pulse height spectrum. The primary goal was to develop a …

Forecasting Lightning Initiation Utilizing Dual-Polarization Radar Parameters Over Washington, D.C., Sarah A. Olsen

Theses and Dissertations

Accurate forecasts of thunderstorms are vital to space launch, aviation, and public safety. Prior studies by Woodard (2011), Thurmond (2014), and Travis (2015) show that dual-polarization radar can be utilized to identify the presence of hydrometeors necessary for cloud charging. These studies emphasized that a combination of radar reflectivity (Z) and differential reflectivity (Z_DR) predictors have the potential to improve forecast skill of lightning initiation over methods that rely on Z alone (Roeder and Pinder, 1998; Yang and King, 2010). Travis (2015) discovered two parameters, when used together, produced the best results: Z ≥ 36.5 dBZ and ZDR …

Academic Packing For Commercial Fpga Architectures, Travis D. Haroldsen

Theses and Dissertations

With a few exceptions, academic packing algorithms for FPGAs are typically applied solely to theoretical architectures. This has allowed the algorithms to focus on the basic components of packing while abstracting away many of the details dictated by real hardware. As commercially available FPGAs have advanced, however, the academic algorithms and architectures have diverged significantly from their commercial counterparts. In this dissertation, the RapidSmith 2 framework is presented. This framework accurately reflects the architecture of Xilinx FPGAs and provides support for integrating custom tools into the commercial CAD tools. Using this framework, the RSVPack packing algorithm is implemented. The RSVPack …

Energy Efficient Clustering Algorithms For Homogeneous Wireless Sensor Networks, John Robert Corn

Theses and Dissertations

Wireless sensor networks (WSNs) are systems of resource-constrained sensor nodes (SNs), distributed throughout a sensor field. Energy limitations persist due to the wireless nature of SNs and an interest in minimizing the cost and physical footprint of SNs. Due to the resource-constrained nature of SNs, much WSN research has focused on energy-efficient communication algorithms. Communication algorithms are necessary for energy-efficient data transmission between SNs and the transmission of data collected by SNs to a base station. A popular algorithm known as Low-Energy Adaptive Clustering Hierarchy (LEACH) achieves more energy-efficient communication by organizing SNs into clusters for localized communication. When SNs …

Partitions Of Finite Frames, James Michael Rosado

Theses and Dissertations

An open question stated by Marcus, Spielman, and Srivastava [10] asks "whether one can design an efficient algorithm to find the partitions guaranteed by Corollary 1.5." This corollary states that given a set of vectors in C whose outer products sum to the identity there exists a partition of these vectors such that norms of the outer-product sums of each subset satisfy an inequality bound. Here particular types of vector sets called finite frames are analyzed and constructed to satisfy the inequality described in Corollary 1.5. In this thesis, rigorous proofs and formulations of outer-product norms are utilized to find …

Evaluating And Improving The Efficiency Of Software And Algorithms For Sequence Data Analysis, Hugh L. Eaves

Theses and Dissertations

With the ever-growing size of sequence data sets, data processing and analysis are an increasingly large portion of the time and money spent on nucleic acid sequencing projects. Correspondingly, the performance of the software and algorithms used to perform that analysis has a direct effect on the time and expense involved. Although the analytical methods are widely varied, certain types of software and algorithms are applicable to a number of areas. Targeting improvements to these common elements has the potential for wide reaching rewards. This dissertation research consisted of several projects to characterize and improve upon the efficiency of several …

Identifying Image Manipulation Software From Image Features, Devlin T. Boyter

Theses and Dissertations

As technology steadily increases in the field of image manipulation, determining which software was used to manipulate an image becomes increasingly complex for law enforcement and intelligence agencies. To combat this difficult problem, new techniques that examine the artifacts left behind by a specific manipulation are converted to features for classification. This research implemented four preexisting image manipulation detection techniques into a framework of modules: Two-Dimensional Second Derivative, One-Dimensional Zero Crossings, Quantization Matrices Identification, and File Metadata analysis. The intent is the creation of a framework to develop a capability to determine which specific image manipulation software program manipulated an …

Quasinovo: Algorithms For De Novo Peptide Sequencing, James Paul Cleveland

Theses and Dissertations

High-throughput proteomics analysis involves the rapid identification and characterization of large sets of proteins in complex biological samples. Tandem mass spectrometry (MS/MS) has become the leading approach for the experimental identification of proteins. Accurate analysis of the data produced is a computationally challenging process that relies on a complex understanding of molecular dynamics, signal processing, and pattern classification. In this work we address these modeling and classification problems, and introduce an additional data-driven evolutionary information source into the analysis pipeline.

The particular problem being solved is peptide sequencing via MS/MS. The objective in solving this problem is to decipher the …

Determining Angular Frequency From A Video With A Generalized Fast Fourier Transform, Lindsay N. Smith

Theses and Dissertations

Suppose we are given a video of a rotating object and suppose we want to determine the rate of rotation solely from the video itself and its known frame rate. In this thesis, we present a new mathematical operator called the Geometric Sum Transform (GST) that can help one determine the angular frequency of the object in question. The GST is a generalization of the discrete Fourier transform (DFT) and as such, the two transforms have much in common. However, whereas the DFT is applied to a sequence of scalars, the GST can be applied to a sequence of vectors. …

A Multi-Objective Approach To A Bipartite Assignment Matching Problem Using Weighted Values From Multiple Contraints, Greg S. Jeong

Theses and Dissertations

US Air Force recruiters routinely assign new recruits to available jobs every month. The goal is to find the best assignments in an efficient manner. Although this problem is modeled as a bipartite assignment matching problem, it is not new to the field of Operations Research. This research presents a new approach to solve assignment matching problems given multiple side constraints. Using two multi-criteria optimization techniques, lexicographic optimization and the elastic constraint method, the assignment matching algorithm efficiently produces an optimal solution in a fraction of the time currently spent. This approach is demonstrated in assigning new USAF recruits to …

Stealthy River Navigation In Jungle Combat Conditions, Fabio Ayres Cardoso

Theses and Dissertations

One of the biggest challenges for Brazilian military logisticians is to support effective jungle warfare for both real and training operations carried out by their combat forces in the Amazonian region. The jungle's heat, humidity, and dense vegetation put significant demands on the supply chain. Further, because of the difficulties of land or air transportation, water transport is the most reasonable transportation option to sustain these deployed forces. Planners must select from among the available watercourses those whose surroundings provide stealthy navigation to the combat force location where the requested supplies can be safely unloaded. We seek a method of …

Effect Of Advanced Synthetically Enhanced Detector Resolution Algorithm On Specificity And Sensitivity Of Portable High Purity Germanium Gamma Detector Spectra, Latosha M. Bell

Theses and Dissertations

The ability to identify special nuclear material is one of the necessary prevention mechanisms for preventing proliferation of special nuclear materials. Additionally, if a nuclear event were to occur, information about the nuclear material used may be extracted from gamma spectra, provided it is obtained quickly and accurately. This can be made possible with the use of the exceptional resolution of the HPGe detector. This experiment applied the Advanced Synthetically Enhanced Detector Resolution Algorithm (ASEDRA) to a portable HPGe detector's spectra, to investigate whether improvements in specificity and sensitivity can be obtained. This method has been used to improve performance …

Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James

Theses and Dissertations

The purpose of the algorithm developed in this thesis was to create a post processing method that could resolve objects at low signal levels using polarization diversity and no knowledge of the atmospheric seeing conditions. The process uses a two-channel system, one unpolarized image and one linearly polarized image, in a GEM algorithm to reconstruct the object. Previous work done by Strong showed that a two-channel system using polarization diversity on short exposure imagery could produce images up to twice the diffraction limit. In this research, long exposure images were simulated and a simple Kolmogorov model used. This allowed for …

Range Estimation Algorithm Comparison In 3-D Flash Ladar Data, Steven P. Jordan

Theses and Dissertations

Range estimation algorithms have been applied to Laser Detection and Ranging (LADAR) data to test for accuracy and precision. Data was acquired from Matlab® simulations and an experiment using the Advanced Scientific Concepts 3-D flash LADAR camera. Simulated LADAR data was based on a Gaussian pulse shape model with Poisson noise added. Simulations were performed to test range estimation algorithm performance with respect to waveform position within the range gate. The effectiveness of each algorithm is presented in terms of its average root mean square error and standard deviation in 1000 trials. The measured data experiment examined the effectiveness of …

On Graph Isomorphism And The Pagerank Algorithm, Christopher J. Augeri

Theses and Dissertations

A graph is a key construct for expressing relationships among objects, such as the radio connectivity between nodes contained in an unmanned vehicle swarm. The study of such networks may include ranking nodes based on importance, for example, by applying the PageRank algorithm used in some search engines to order their query responses. The PageRank values correspond to a unique eigenvector typically computed by applying the power method, an iterative technique based on matrix multiplication. The first new result described herein is a lower bound on the execution time of the PageRank algorithm that is derived by applying standard assumptions …

Multi-Objective Optimization Of Mixed-Variable, Stochastic Systems Using Single-Objective Formulations, Todd J. Paciencia

Theses and Dissertations

Many problems exist where one desires to optimize systems with multiple, often competing, objectives. Further, these problems may not have a closed form representation, and may also have stochastic responses. Recently, a method expanded mixed variable generalized pattern search/ranking and selection (MVPS-RS) and Mesh Adaptive Direct Search (MADS) developed for single-objective, stochastic problems to the multi-objective case by using aspiration and reservation levels. However, the success of this method in approximating the true Pareto solution set can be dependent upon several factors. These factors include the experimental design and ranges of the aspiration and reservation levels, and the approximation quality …

Constellation Design Of Geosynchronous Navigation Satellites Which Maximizes Availability And Accuracy Over A Specified Region Of The Earth, Halil Ibrahim Ozdemir

Theses and Dissertations

Currently, there are four Global Navigation Satellite Systems (GNSS) either being developed or in existence-GPS, GLONASS, Compass, and Galileo. Additionally, there are several Regional Navigation Satellite Systems (RNSS) planned or in existence, as well as numerous augmentation systems (which require a GNSS for operation). It can be anticipated that there will be interest in developing additional independent regional navigation satellite systems to cover areas of interest to particular countries or regions, who want to have their own system. In this paper, a genetic algorithm is used in an effort to determine near-optimal RNSS constellations. First, a cost function is setup, …

Characterization And Implementation Of A Real-World Target Tracking Algorithm On Field Programmable Gate Arrays With Kalman Filter Test Case, Benjamin D. Hancey

Theses and Dissertations

A one dimensional Kalman Filter algorithm provided in Matlab is used as the basis for a Very High Speed Integrated Circuit Hardware Description Language (VHDL) model. The JAVA programming language is used to create the VHDL code that describes the Kalman filter in hardware which allows for maximum flexibility. A one-dimensional behavioral model of the Kalman Filter is described, as well as a one-dimensional and synthesizable register transfer level (RTL) model with optimizations for speed, area, and power. These optimizations are achieved by a focus on parallelization as well as careful Kalman filter sub-module algorithm selection. Newton-Raphson reciprocal is the …

Statistical Removal Of Shadow For Applications To Gait Recognition, Brian D. Hockersmith

Theses and Dissertations

The purpose of this thesis is to mathematically remove the shadow of an individual on video. The removal of the shadow will aid in the rendering of higher quality binary silhouettes than previously allowed. These silhouettes will allow researchers studying gait recognition to work with silhouettes unhindered by unrelated data. The thesis begins with the analysis of videos of solid colored backgrounds. A formulation of the effect of shadow on specified colors will aid in the derivation of a hypothesis test to remove an individual’s shadow. Video of an individual walking normally, perpendicular to the camera will be utilized to …