Engineering Commons^™

Development Of A Machine Learning System For Irrigation Decision Support With Disparate Data Streams, Eric Wilkening

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

In recent years, advancements in irrigation technologies have led to increased efficiency in irrigation applications, encompassing the adoption of practices that utilize data-driven irrigation scheduling and leveraging variable rate irrigation (VRI). These technological improvements have the potential to reduce water withdrawals and diversions from both groundwater and surface water sources. However, it is vital to recognize that improved application efficiency does not necessarily equate to increased water availability for future or downstream use. This is particularly crucial in the context of consumptive water use, which refers to water consumed and not returned to the local or sub-regional watershed, representing a …

In Situ Water Sensing Systems: Research On Advancements In Environmental Monitoring, Abigail Seibel

Honors Theses

In this work, two sensing systems were researched in order to improve in situ environmental monitoring. The first is a pH and Total Alkalinity sensor used to determine these characteristics of sea water. I explored the facets of this sensor over a 7-week internship with Dr. Ellen Briggs in her lab in summer of 2023. The second is a more holistic sensing system that reads temperature, turbidity, and pressure used for studying environmental characteristics of Alaskan bever ponds. Both systems were developed in close collaboration with scientists who are collecting data to better understand the impacts of climate change. Better …

An Investigation Of Match For Lossless Video Compression, Brittany Sullivan-Reicks

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

A new lossless video compression technique, Match, is investigated. Match uses the similarity between the frames of a video or the slices of medical images to find a prediction for the current pixel. A portion of the previous frame is searched to find a matching context, which is the pixels surrounding the current pixel, within some distance centered on the current location. The best distance to use for each dataset is found experimentally. The matching context refers to the neighborhood of w, nw, n, and ne, where the pixel in the previous frame with the closest matching context becomes the …

Low-Power, Event-Driven System On A Chip For Charge Pulse Processing Applications, Joseph A. Schmitz

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

This dissertation presents an electronic architecture and methodology capable of processing charge pulses generated by a range of sensors, including radiation detectors and tactile synthetic skin. These sensors output a charge signal proportional to the input stimulus, which is processed electronically in both the analog and digital domains. The presented work implements this functionality using an event-driven methodology, which greatly reduces power consumption compared to standard implementations. This enables new application areas that require a long operating time or compact physical dimensions, which would not otherwise be possible. The architecture is designed, fabricated, and tested in the aforementioned applications to …

Amorphous Boron Carbide-Amorphous Silicon Heterojunction Devices, Vojislav Medic

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

This dissertation will show successful development and characterization of amorphous boron carbide-amorphous silicon heterojunction device with potential for neutron detection. The amorphous hydrogenated boron carbide (a-BC:H) has been extensively researched as a semiconductor for neutron voltaic device fabrication. Naturally occurring boron contains 19.8% of boron isotope B¹⁰ that has a high absorption cross section of thermal neutrons at lower energies, and boron carbide contains 14.7% of that B¹⁰ isotope. Therefore, as a semiconductor compound of boron a-BC:H has the ability to absorb radiation, generate charge carriers, and collect those carriers. Previous work on a-BC:H devices investigated the fabrication …

On Dyadic Parity Check Codes And Their Generalizations, Meraiah Martinez

Department of Mathematics: Dissertations, Theses, and Student Research

In order to communicate information over a noisy channel, error-correcting codes can be used to ensure that small errors don’t prevent the transmission of a message. One family of codes that has been found to have good properties is low-density parity check (LDPC) codes. These are represented by sparse bipartite graphs and have low complexity graph-based decoding algorithms. Various graphical properties, such as the girth and stopping sets, influence when these algorithms might fail. Additionally, codes based on algebraically structured parity check matrices are desirable in applications due to their compact representations, practical implementation advantages, and tractable decoder performance analysis. …

Renovating The Ipmu Via Internet Of Things For Pollutant Emission Estimations In Poultry Facilities, Joshua Dotto

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

The emissions of ammonia (NH₃), particulate matter (PM_2.5), and carbon dioxide (CO₂) are major concerns in poultry facilities. They can pose environmental concerns and nuances. Robust and affordable measurement systems are needed to accurately measure in-barn concentrations and quantify the emissions.

The Intelligent Portable Monitoring Unit (iPMU or PMU3) developed in 2016 was reconstructed into PMU4 to include upgraded NH₃ and PM_2.5 sensors and wireless connectivity for a low-cost, robust, and accurate air quality monitoring device with contactless data transfer using the concept of Internet of Things (IoT). In addition, a user-friendly …

Sc-Fuse: A Feature Fusion Approach For Unpaved Road Detection From Remotely Sensed Images, Aniruddh Saxena

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Road network extraction from remote sensing imagery is crucial for numerous applications, ranging from autonomous navigation to urban and rural planning. A particularly challenging aspect is the detection of unpaved roads, often underrepresented in research and data. These roads display variability in texture, width, shape, and surroundings, making their detection quite complex. This thesis addresses these challenges by creating a specialized dataset and introducing the SC-Fuse model.

Our custom dataset comprises high resolution remote sensing imagery which primarily targets unpaved roads of the American Midwest. To capture the diverse seasonal variation and their impact, the dataset includes images from different …

Room Temperature Two-Dimensional Electron Gas Scattering Time, Effective Mass, And Mobility Parameters In AlXGa1−XN/Gan Heterostructures (0.07 ≤ X ≤ 0.42), Sean Knight, Steffen Richter, Alexis Papamichail, Philipp Kühne, Nerijus Armakavicius, Shiqi Guo, Axel R. Persson, Vallery Stanishev, Viktor Rindert, Per O. Å. Persson, Plamen P. Paskov, Mathias Schubert, Vanya Darakchieva

Department of Electrical and Computer Engineering: Faculty Publications

Al_xGa_1-xN/GaN high-electron-mobility transistor (HEMT) structures are key components in electronic devices operating at gigahertz or higher frequencies. In order to optimize such HEMT structures, understanding their electronic response at high frequencies and room temperature is required. Here, we present a study of the room temperature free charge carrier properties of the two-dimensional electron gas (2DEG) in HEMT structures with varying Al content in the Al_xGa_1-xN barrier layers between x = 0:07 and x = 0:42. We discuss and compare 2DEG sheet density, mobility, effective mass, sheet resistance, and scattering times, …

Study On Debinding And Sintering Conditions In Extrusion-Based Additive Manufacturing Of 316l And 316l + Cu, Jean-François Silvain, Daniel Lincoln Gifford, Sébastien Fourcade, Laurent Cuzacq, Jean-Luc Grosseau-Poussard, Catherine Debiemme-Chouvy, Nicolas Tessier Doyen, Yongfeng Lu

Department of Electrical and Computer Engineering: Faculty Publications

This study investigates the use of a methylcellulose binder in extrusion additive manufacturing of 316L as an alternative to common wax-based binders. Various quantities of copper (Cu) powder were also added in the paste composition to attempt to reduce the sintering temperature by promoting persistent liquid phase sintering. Debinding experiments were conducted under different temperatures and dwell times using argon (Ar), Ar/5%H₂, and Ar/1%O₂ atmospheres. Debinding reduced carbon (C) content to 0.032 wt.% by using a two-step debinding process of Ar/5%H₂ and Ar/1%O₂ thermal treatments. Using this debinding process, sintering was conducted at 1200 ^{o …}

Continuous Time Recurrent Network For Human Activity Detection, Abdallah Al Zubi

Durham School of Architectural Engineering and Construction: Dissertations, Thesis, and Student Research

Human activity detection is crucial to personalize the control of the building environment. For example, understanding certain human activities (e.g., walking, sitting, etc.) for an occupant in a building helps provide the proper thermal comfort control. However, these applications require large-scale neural networks that are challenging to implement and train.

In this thesis, we implemented a continuous-time recurrent neural network implementation (CTRNN) network that can solve real-time human activity detection with a smaller-size network. The CTRNN uses differential equations with a time constant to describe the neuron equations. It was implemented and trained for the first time using TensorFlow. Specifically, …

Executive Order On The Safe, Secure, And Trustworthy Development And Use Of Artificial Intelligence, Joseph R. Biden

Copyright, Fair Use, Scholarly Communication, etc.

Section 1. Purpose. Artificial intelligence (AI) holds extraordinary potential for both promise and peril. Responsible AI use has the potential to help solve urgent challenges while making our world more prosperous, productive, innovative, and secure. At the same time, irresponsible use could exacerbate societal harms such as fraud, discrimination, bias, and disinformation; displace and disempower workers; stifle competition; and pose risks to national security. Harnessing AI for good and realizing its myriad benefits requires mitigating its substantial risks. This endeavor demands a society-wide effort that includes government, the private sector, academia, and civil society.

My Administration places the highest urgency …

Nitrogen Radiofrequency Plasma Treatment Of Graphene, Antoine Bident, Nathalie Caillault, Florence Delange, Christine Labrugere, Guillaume Aubert, Cyril Aymonier, Etienne Durand, Alain Demourgues, Yongfeng Lu, Jean-François Silvain

Department of Electrical and Computer Engineering: Faculty Publications

The incorporation of nitrogen (N) atoms into a graphitic network such as graphene (Gr) remains a major challenge. However, even if the insertion mechanisms are not yet fully understood, it is certain that the modification of the electrical properties of Gr is possible according to the configuration adopted. Several simulations work, notably using DFT, have shown that the incorporation of N in Gr can induce an increase in the electrical conductivity and N acts as an electron donor; this increase is linked to the amount of N, the sp²/sp³ carbon configuration, and the nature of C-N bonding. …

Detection Of Cancer-Associated Gene Mutations In Urinary Cell-Free Dna Among Prostate Cancer Patients In South Africa, Dada Oluwaseyi Temilola, Martha Wium, Juliano Paccez, Azola Samkele Salukazana, Solomon O. Rotimi, Hasan H. Otu, Giuseppina M. Carbone, Lisa Kaestner, Stefano Cacciatore, Luiz Fernando Zerbini

Department of Electrical and Computer Engineering: Faculty Publications

Prostate cancer (PCa) is the most common cause of cancer death among African men. The presence of tumor-specific variations in cell-free DNA (cfDNA), such as mutations, microsatellite instability, and DNA methylation, has been explored as a source of biomarkers for cancer diagnosis. In this study, we investigated the diagnostic role of cfDNA among South African PCa patients. We performed whole exome sequencing (WES) of urinary cfDNA. We identified a novel panel of 31 significantly deregulated somatic mutated genes between PCa and benign prostatic hyperplasia (BPH). Additionally, we performed whole-genome sequencing (WGS) on matching PCa and normal prostate tissue in an …

Laser-Direct-Drive Fusion Target Design With A High-Z Gradient-Density Pusher Shell, S. S. Hu, L. Ceurvorst, J. L. Peebles, A. Mao, P. Li, Yongfeng Lu, A. Shvydky, V. N. Goncharov, R. Epstein, K. A. Nichols, R. M. N. Goshadze, M. Ghosh, J. Hinz, V. V. Karasiev, S. Zhang, N. R. Shaffer, D. I. Mihaylov, J. Cappelletti, D. R. Harding, C. K. Li, E. M. Campbell, R. C. Shah, T. J. B. Collins, S. P. Regan, C. Deeney

Department of Electrical and Computer Engineering: Faculty Publications

Laser-direct-drive fusion target designs with solid deuterium-tritium (DT) fuel, a high-Z gradient-density pusher shell (GDPS), and a Au-coated foam layer have been investigated through both 1D and 2D radiationhydrodynamic simulations. Compared with conventional low-Z ablators and DT-push-on-DT targets, these GDPS targets possess certain advantages of being instability-resistant implosions that can be high adiabat (α ≽ 8) and low hot-spot and pusher-shell convergence (CR_hs ≈22 and CR_PS ≈17), and have a low implosion velocity (v_imp < 3 × 10⁷ cm/s). Using symmetric drive with laser energies of 1.9 to 2.5 MJ, 1D LILAC simulations of these GDPS implosions can result …

Aptamer-Based Proteomics Measuring Preoperative Cerebrospinal Fluid Protein Alterations Associated With Postoperative Delirium, Simon T. Dillon, Sarinnapha M. Vasunilashorn, Hasan H. Otu, Long Ngo, Tamara Fong, Xuesong Gu, Michele Cavallari, Alexandra Touroutoglou, Mouhsin Shafi, Sharon K. Inouye, Zhongcong Xie, Edward R. Marcantonio, Towia A. Libermann

Department of Electrical and Computer Engineering: Faculty Publications

Delirium is a common postoperative complication among older patients with many adverse outcomes. Due to a lack of validated biomarkers, prediction and monitoring of delirium by biological testing is not currently feasible. Circulating proteins in cerebrospinal fluid (CSF) may reflect biological processes causing delirium. Our goal was to discover and investigate candidate protein biomarkers in preoperative CSF that were associated with the development of postoperative delirium in older surgical patients. We employed a nested case–control study design coupled with high multiplex affinity proteomics analysis to measure 1305 proteins in preoperative CSF. Twenty-four matched delirium cases and non-delirium controls were selected …

Integrating Glycolysis, Citric Acid Cycle, Pentose Phosphate Pathway, And Fatty Acid Beta‑Oxidation Into A Single Computational Model, Sylwester M. Kloska, Krzysztof Pałczyński, Tomasz Marciniak, Tomasz Talaśka, Beata J. Wysocki, Paul H. Davis, Tadeusz A. Wysocki

Department of Electrical and Computer Engineering: Faculty Publications

The metabolic network of a living cell is highly intricate and involves complex interactions between various pathways. In this study, we propose a computational model that integrates glycolysis, the pentose phosphate pathway (PPP), the fatty acids beta-oxidation, and the tricarboxylic acid cycle (TCA cycle) using queueing theory. The model utilizes literature data on metabolite concentrations and enzyme kinetic constants to calculate the probabilities of individual reactions occurring on a microscopic scale, which can be viewed as the reaction rates on a macroscopic scale. However, it should be noted that the model has some limitations, including not accounting for all the …

Potential Of Mirnas In Plasma Extracellular Vesicle For The Stratification Of Prostate Cancer In A South African Population, Dada Oluwaseyi Temilola, Martha Wium, Juliano Paccez, Azola Samkele Salukazana, Hasan H. Otu, Giuseppina M. Carbone, Lisa Kaestner, Stefano Cacciatore, Luiz Fernando Zerbini

Department of Electrical and Computer Engineering: Faculty Publications

Prostate cancer (PCa) is the most common cause of cancer death among African men. The analysis of microRNAs (miRNAs) in plasma extracellular vesicles (EVs) can be utilized as a non-invasive tool for the diagnosis of PCa. In this study, we used small RNA sequencing to profile miRNAs cargo in plasma EVs from South African PCa patients. We evaluated the differential expression of miRNAs between low and high Gleason scores in the plasma EVs of South African patients and in the prostatic tissue from data available in the Cancer Genome Atlas (TCGA) Data Portal. We identified 7 miRNAs differently expressed in …

Integration Of Meta-Multi-Omics Data Using Probabilistic Graphs And External Knowledge, Handan Can, Sree K. Chanumolu, Barbara D. D., Sophie Alvarez, Michael J. Naldrett, Gülhan Ünlü, Hasan H. Otu

Department of Electrical and Computer Engineering: Faculty Publications

Multi-omics has the promise to provide a detailed molecular picture of biological systems. Although obtaining multi-omics data is relatively easy, methods that analyze such data have been lagging. In this paper, we present an algorithm that uses probabilistic graph representations and external knowledge to perform optimal structure learning and deduce a multifarious interaction network for multi-omics data from a bacterial community. Kefir grain, a microbial community that ferments milk and creates kefir, represents a self-renewing, stable, natural microbial community. Kefir has been shown to have a wide range of health benefits. We obtained a controlled bacterial community using the two …

Experimental Study Of Linux Flightsize Estimation, Mingrui Zhang

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Transmission Control Protocol (TCP) is a fundamental Internet protocol responsible for controlling and coordinating the Internet traffic. As a result, TCP significantly influences the overall performance and stability of the Internet. One critical information required by a TCP connection to make decisions is FlightSize, which is the total amount of outstanding data contributed by the connection to the Internet. The FlightSize information is used by a TCP connection to determine its future sending rate and also avoid traffic congestion and collapse in the Internet. Consequently, an inaccurate estimation of FlightSize can result in degraded performance and instability of the Internet. …

A Unified Switched Nonlinear Dynamic Model Of An Electric Vehicle For Performance Evaluation, Dibyendu Khan, Kuntal Mandal, Anjan Kumar Ray, Abdelali El Aroudi

Department of Electrical and Computer Engineering: Faculty Publications

The advanced modeling and estimation of overall system dynamics play a vital role in electric vehicles (EVs), as the selection of components in the powertrain and prediction of performance are the key market qualifiers. The state-space averaged model and small-signal transfer function model are useful for assessing long-term behavior in system-level analysis and for designing the controller parameters, respectively. Both models take less computation time but ignore the high-frequency switching dynamics. Therefore, these two models could be impractical for the development and testing of EV prototypes. On the other hand, the multi-domain model in available simulation tools gives in-depth information …

An Ai-Based Intervention For Improving Undergraduate Stem Learning, Mohammad Rashedul Hasan, Bilal Khan

Department of Electrical and Computer Engineering: Faculty Publications

We present results from a small-scale randomized controlled trial that evaluates the impact of just-in-time interventions on the academic outcomes of N = 65 undergraduate students in a STEM course. Intervention messaging content was based on machine learning forecasting models of data collected from 537 students in the same course over the preceding 3 years. Trial results show that the intervention produced a statistically significant increase in the proportion of students that achieved a passing grade. The outcomes point to the potential and promise of just-in-time interventions for STEM learning and the need for larger fully-powered randomized controlled trials.

Generation Of Vector Vortex Wave Modes In Cylindrical Waveguides, Md Khadimul Islam, Pawan Gaire, Arjuna Madanayake, Shubhendu Bhardwaj

Department of Electrical and Computer Engineering: Faculty Publications

In this paper, we propose a method to generate Vector Vortex Modes (VVM) inside a metallic cylindrical waveguide at microwave frequencies and demonstrate the experimental validation of the concept. Vector vortex modes of EM waves can carry both spin and orbital angular momentum as they propagate within a tubular medium. The existence of such waves in tubular media can be beneficial to wireless communication in such structures. These waves can carry different orbital angular momentum and spin angular momentum, and therefore, they feature the ability to carry multiple orthogonal modes at the same frequency due to spatial structure of the …

A Flexible Ot Testbed For Evaluating On-Device Implementations Of Iec-61850 Goose, Matthew Boeding, Michael Hempel, Hamid Sharif, Juan Lopez Jr., Kalyan Perumalla

Department of Electrical and Computer Engineering: Faculty Publications

The growing convergence of Information Technology and Operational Technology has enhanced communication and visibility across power grids. This, coupled with the growing use of Distributed Energy Resources in power grids, has enhanced the grid capabilities while also creating a larger attack surface for malicious actors. A common protocol vulnerable to these attacks is the IEC-61850 GOOSE protocol due to its low-latency requirements, multicast packet delivery method, and lack of encryption. In this paper, we evaluate the security implications of different hardware implementations of this protocol by contrasting device response and recovery of two commercial off-the-shelf Intelligent Electronic Devices from separate …

Cometrics: A New Software Tool For Behavior‑Analytic Clinicians And Machine Learning Researchers, Walker S. Arce, Seth G. Walker, Morgan L. Hurtz

Department of Electrical and Computer Engineering: Faculty Publications

Cometrics is a Microsoft Windows compatible clinical tool for the collection and recording of frequency- and duration-based target behaviors, physiological signals, and video data. This software package is designed to record in-vivo observational and physiological data. In addition, we have included features that allow observers to capture video from real-time camera feeds and import saved video for retroactive data collection. By using Microsoft Excel-based spreadsheets, also called keystroke files, assessment and treatment sessions are exported into a single document using the click of a button. Integrated interobserver agreement metrics allow comparisons across primary and reliability observers, with the output exported …

Guest Editorial: Special Issue On Green Iot For Future Space–Air–Ground–Ocean-Integrated Networks And Applications, Bo Rong, Mohamed Cheriet, Jon Montalban, Lei Shu, Yi Qian

Department of Electrical and Computer Engineering: Faculty Publications

The Internet of Things (IoT) plays a critical role in enabling the seamless integration of disparate devices. Future IoT will rapidly expand its coverage to offer future worldwide omnipresent applications and services by merging communications in diverse spatial domains to build the space–air–ground–ocean-integrated network (SAGOI-Net). SAGOI-Net will include a significant number of battery-powered network nodes, such as satellites, unmanned vehicles, and underwater devices, due to the extremely vast geographic reach and dynamics in free space. Given the battery limitations, high-energy-efficiency communications and networking will be critical to the future system. Green SAGOI-Net seeks to not only bring ubiquitous connectivity to …

A Novel Graph Neural Network-Based Framework For Automatic Modulation Classification In Mobile Environments, Pejman Ghasemzadeh

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Automatic modulation classification (AMC) refers to a signal processing procedure through which the modulation type and order of an observed signal are identified without any prior information about the communications setup. AMC has been recognized as one of the essential measures in various communications research fields such as intelligent modem design, spectrum sensing and management, and threat detection. The research literature in AMC is limited to accounting only for the noise that affects the received signal, which makes their models applicable for stationary environments. However, a more practical and real-world application of AMC can be found in mobile environments where …

Modern Practices For Responsive Web Design And Web Accessibility, Keyaun Washington

Honors Theses

Responsive web design and web accessibility play crucial roles in ensuring an optimal user experience on the web. By designing websites with responsiveness and accessibility in mind, more opportunities are opened up for a wider audience to access and interact with our content. Through modern practices, responsive web design allows websites to reach several different devices ranging from compact smartwatches to expansive television screens. Designing for accessibility provides accommodations for individuals with impairments while also providing benefits for individuals without impairments. However, designing for responsiveness and accessibility can present challenges; a poor attempt at providing accessibility features can worsen a …

Unobtrusive Data Collection In Clinical Settings For Advanced Patient Monitoring And Machine Learning, Walker Arce

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

When applying machine learning to clinical practice, a major hurdle that will be encountered is the lack of available data. While the data collected in clinical therapies is suitable for the types of analysis that are needed to measure and track clinical outcomes, it may not be suitable for other types of analysis. For instance, video data may have poor alignment with behavioral data, making it impossible to extract the videos frames that directly correlate with the observed behavior. Alternatively, clinicians may be exploring new data modalities, such as physiological signal collection, to research methods of improving clinical outcomes that …

Anticancer Activities Of Tetra-, Penta-, And Hexacyclic Phenothiazines Modified With Quinoline Moiety., Małgorzata Jel, Beata Morak-Młodawska, Rafał Korlacki

Department of Electrical and Computer Engineering: Faculty Publications

The quinoline molecule is a chemical motif showing a highly promising pharmacological potential. Its numerous derivatives introduced into medicine revolutionized in the treatment of many entities of disease. The presence of the quinoline system in the structure of phenothiazines made it possible to obtain new aza- and diazaphenothiazine derivatives that show promising anticancer potential. The aza-analogs of the phenothiazines are structurally modified phenothiazines by the substitution of one or both benzene rings in the phenothiazine ring system with various azine rings. This approach to the strategy of obtaining new substances with biological potential can be classified as molecular hybridization methods …