Physical Sciences and Mathematics Commons^™

Star-Based Reachability Analysis Of Binary Neural Networks On Continuous Input, Mykhailo Ivashchenko

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

Deep Neural Networks (DNNs) have become a popular instrument for solving various real-world problems. DNNs’ sophisticated structure allows them to learn complex representations and features. However, architecture specifics and floating-point number usage result in increased computational operations complexity. For this reason, a more lightweight type of neural networks is widely used when it comes to edge devices, such as microcomputers or microcontrollers – Binary Neural Networks (BNNs). Like other DNNs, BNNs are vulnerable to adversarial attacks; even a small perturbation to the input set may lead to an errant output. Unfortunately, only a few approaches have been proposed for verifying …

Bidding Strategy For A Wind Power Producer In Us Energy And Reserve Markets, Anne Stratman

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

Wind power is one of the world's fastest-growing renewable energy resources and has expanded quickly within the US electric grid. Currently, wind power producers (WPPs) may sell energy products in US markets but are not allowed to sell reserve products, due to the uncertain and intermittent nature of wind power. However, as wind’s share of the power supply grows, it may eventually be necessary for WPPs to contribute to system-wide reserves. This paper proposes a stochastic optimization model to determine the optimal offer strategy for a WPP that participates in the day-ahead and real-time energy and spinning reserve markets. The …

Vr Circuit Simulation With Advanced Visualization For Enhancing Comprehension In Electrical Engineering, Elliott Wolbach

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

As technology advances, the field of electrical and computer engineering continuously demands innovative tools and methodologies to facilitate effective learning and comprehension of fundamental concepts. Through a comprehensive literature review, it was discovered that there was a gap in the current research on using VR technology to effectively visualize and comprehend non-observable electrical characteristics of electronic circuits. This thesis explores the integration of Virtual Reality (VR) technology and real-time electronic circuit simulation with enhanced visualization of non-observable concepts such as voltage distribution and current flow within these circuits. The primary objective is to develop an immersive educational platform that makes …

Detection Of Deficiencies And Data Analysis Of Bridge Members With Deep Convolutional Neural Networks, Bennett Jackson

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Concrete cracks and structural steel corrosion are two of the most common defects in bridges. Quantifying and classifying these defects provide bridge inspectors and engineers with valuable data for assessing deterioration levels. However, the bridge inspection process is typically a subjective, time intensive, and tedious task, as defects can be overlooked or in locations not easily accessible. Previous studies have investigated deep learning-based inspection methods, implementing popular models such as Mask R-CNN and U-Net. The architectures of these models offer certain advantages depending on the required task. This thesis aims to evaluate and compare Mask R-CNN and U-Net regarding their …

Next-Generation Crop Monitoring Technologies: Case Studies About Edge Image Processing For Crop Monitoring And Soil Water Property Modeling Via Above-Ground Sensors, Nipuna Chamara

Dissertations and Doctoral Documents from University of Nebraska-Lincoln, 2023–

Artificial Intelligence (AI) has advanced rapidly in the past two decades. Internet of Things (IoT) technology has advanced rapidly during the last decade. Merging these two technologies has immense potential in several industries, including agriculture.

We have identified several research gaps in utilizing IoT technology in agriculture. One problem was the digital divide between rural, unconnected, or limited connected areas and urban areas for utilizing images for decision-making, which has advanced with the growth of AI. Another area for improvement was the farmers' demotivation to use in-situ soil moisture sensors for irrigation decision-making due to inherited installation difficulties. As Nebraska …

Sliding Markov Decision Processes For Dynamic Task Planning On Uncrewed Aerial Vehicles, Trent Wiens

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Mission and flight planning problems for uncrewed aircraft systems (UASs) are typically large and complex in space and computational requirements. With enough time and computing resources, some of these problems may be solvable offline and then executed during flight. In dynamic or uncertain environments, however, the mission may require online adaptation and replanning. In this work, we will discuss methods of creating MDPs for online applications, and a method of using a sliding resolution and receding horizon approach to build and solve Markov Decision Processes (MDPs) in practical planing applications for UASs. In this strategy, called a Sliding Markov Decision …

Will Saf Turbocharge The Corn Ethanol Market?, Richard Perrin, Lilyan Fulginiti, Felipe Miranda De Souza Almeida

Cornhusker Economics

The long-run outlook for the corn ethanol industry is questionable, due to a transition to electric and hybrid vehicles. One source of hope for the long run is the potential demand for producing Sustainable Aviation Fuel (SAF). SAF is a key component in the United States Aviation Climate Action Plan, a path to net-zero greenhouse gas (GHG) emissions in the aviation industry by 2050. Demand for ethanol for SAF offers hope to the ethanol industry, but it depends a great deal on policy decisions that are being made now. Here we sketch out this story.

Based on the information available …

Field Research Report: Results From The Enreec Vri Field For The 2021, 2022, And 2023 Crop Seasons, Derek M. Heeren, Ali T. Mohammed, Eric Wilkening, Christopher M. U. Neale, Alan L. Boldt, Ankit Chandra, Precious Nneka Amori, Ivo Z. Goncalves, Yeyin Shi, Guillermo R. Balboa

Department of Biological Systems Engineering: Conference Presentations and White Papers

Long-term irrigation management research has been conducted from 2014 to 2023 for corn and soybean at the Eastern Nebraska Research, Extension, and Education Center (ENREEC) Variable Rate Irrigation (VRI) Field located in subhumid east-central Nebraska (in the Lower Platte North Natural Resources District). The objective of this report was to present the overall results from the VRI Field for 2021 to 2023. Across the three growing seasons, there were the following irrigation treatments: Best Management Practice (BMP), 50% BMP, 125% BMP, rainfed, Spatial ET Modeling Interface (SETMI), SDD1, SDD2, machine-learning-based Cyber-Physical System (CPS), a student team recommended rate, and industry …

Soil Nitrate Prediction Using Ftir-Atr, Vis-Nir, And Raman Spectroscopy, Sabiha Ferdous

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

Fourier transform infrared spectroscopy (FTIR) combined with Attenuated total reflectance (ATR), Visible-Near Infrared spectroscopy (Vis-NIR), and Raman spectroscopy (RS) are non-destructive techniques for rapid determination of nitrogen compounds in soil. Leveraging FTIR-ATR and Vis-NIR spectra using partial least squares regression (PLSR) modeling, the study aims to predict soil nitrate content and explored the feasibility of Raman spectroscopy to detect nitrate (NO₃^-), nitrite (NO₂^-), and ammonium (NH₄⁺) in soil. Soil samples were collected from four different fields, dried, sieved (2mm), and then used for collecting spectra (FTIR-ATR and Vis-NIR). Laboratory analysis was …

Stage And Discharge Prediction From Documentary Time-Lapse Imagery, Kenneth W. Chapman, Troy E. Gilmore, Mehrube Mehrubeoglu, Christian D. Chapman, Aaron R. Mittelstet, John E. Stranzl Jr.

Department of Biological Systems Engineering: Papers and Publications

Imagery from fixed, ground-based cameras is rich in qualitative and quantitative information that can improve stream discharge monitoring. For instance, time-lapse imagery may be valuable for filling data gaps when sensors fail and/or during lapses in funding for monitoring programs. In this study, we used a large image archive (> 40,000 images from 2012 to 2019) from a fixed, ground-based camera that is part of a documentary watershed imaging project (https://plattebasintimelapse.com/). Scalar image features were extracted from daylight images taken at one-hour intervals. The image features were fused with United States Geological Survey stage and discharge data as …

Life Cycle Greenhouse Gas Emissions In Maize No-Till Agroecosystems In Southern Brazil Based On A Long-Term Experiment, Guilherme Rosa Da Silva, Adam J. Liska, Cimelio Bayer

Department of Biological Systems Engineering: Papers and Publications

Brazilian agriculture is constantly questioned concerning its environmental impacts, particularly greenhouse gas (GHG) emissions. This research study used data from a 34-year field experiment to estimate the life cycle GHG emissions intensity of maize production for grain in farming systems under no-tillage (NT) and conventional tillage (CT) combined with Gramineae (oat) and legume (vetch) cover crops in southern Brazil. We applied the Feedstock Carbon Intensity Calculator for modeling the “field-to-farm gate” emissions with measured annual soil N₂O and CH₄ emissions data. For net CO₂ emissions, increases in soil organic C (SOC) were applied as a proxy, …

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 …

Co2 Storage Capacity And Injectivity Of Stacked Carbonates Of The Pennsylvanian And Permian In Western Nebraska, Lateef Lawal

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Geological carbon storage (GCS) is a critical aspect of carbon capture and storage (CCS) in which captured CO₂ from power plants and industrial processes is injected and stored securely underground. Potential subsurface rock formations include saline aquifers, depleted oil and gas reservoirs, unmineable coal seams and volcanic rocks. GCS technology has been proven in the United States and many other parts of the world as a net-zero carbon emission strategy to mitigate the current climate crisis of our planet. Unlike other states such as Wyoming, GCS projects are still in the early phases in Nebraska. The goal of this …

Experimental Analysis Of Nonlinear Wave Propagation In Bistable Mechanical Metamaterials With A Defect, Samuel R. Harre

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Mechanical metamaterials built up of compliant units can support the propagation of linear and nonlinear waves. A popular architecture consists of a one-dimensional chain of bistable elements connected by linear springs. This type of chain can support nonlinear transition waves that switch each element from one stable state to the other as they propagate along the chain. One way to manipulate the propagation of such waves is via introduction of a local inhomogeneity, i.e., a defect in the otherwise periodic chain. Recent analytical and numerical work has shown that based on its initial velocity, a transition wave may be reflected, …

Enhanced Privacy-Enabled Face Recognition Using Κ-Identity Optimization, Ryan Karl

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

Facial recognition is becoming more and more prevalent in the daily lives of the common person. Law enforcement utilizes facial recognition to find and track suspects. The newest smartphones have the ability to unlock using the user's face. Some door locks utilize facial recognition to allow correct users to enter restricted spaces. The list of applications that use facial recognition will only increase as hardware becomes more cost-effective and more computationally powerful. As this technology becomes more prevalent in our lives, it is important to understand and protect the data provided to these companies. Any data transmitted should be encrypted …

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. …

Characterization Of Interlayer Laser Shock Peening During Fused Filament Fabrication Of Polylactic Acid (Pla), Fabien Denise

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

The field of additive manufacturing (AM) has gained a significant amount of popularity due to the increasing need for more sustainable manufacturing techniques and the adaptive development of complex product geometries. The problem is that AM parts routinely exhibit flaws or weaknesses that affect functionality or performance. Over the years, surface treatments have been developed to compensate certain flaws or weaknesses in manufactured products. Combining surface treatments with the modularity of additive manufacturing could lead to more adaptable and creative improvements of product functions in the future. The current work evaluates the feasibility of pursuing a new research axis in …

Enhancing Urban Water Quality Through Biological-Chemical Treatment: Aquatic Macroinvertebrate Community And Temporal Chlorophyll-A Response, Matthew Chaffee

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

With a growing human population, urbanization is impeding a plethora of natural waterways. Of these, urban ponds play a vital role in nutrient sequestration, flood prevention, and habitat sanctuaries. However, nutrient loading can reduce habitat effectiveness and promote harmful algae blooms. To reduce internal nutrient loads, a biological-chemical treatment strategy consisting of floating treatment wetlands (FTWs) and lanthanum were applied to two urban retention ponds, Densmore and Wilderness Ridge Ponds. To measure effectiveness, chlorophyll-a samples were collected and correlated with Sentinel-2. A novel band algorithm termed 3BR1 produced a strong correlation (R² = 0.72) to physical chlorophyll-a …

Motif-Cluster: A Spatial Clustering Package For Repetitive Motif Binding Patterns, Mengyuan Zhou

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

Previous efforts in using genome-wide analysis of transcription factor binding sites (TFBSs) have overlooked the importance of ranking potential significant regulatory regions, especially those with repetitive binding within a local region. Identifying these homogenous binding sites is critical because they have the potential to amplify the binding affinity and regulation activity of transcription factors, impacting gene expression and cellular functions. To address this issue, we developed an open-source tool Motif-Cluster that prioritizes and visualizes transcription factor regulatory regions by incorporating the idea of local motif clusters. Motif-Cluster can rank the significant transcription factor regulatory regions without the need for experimental …

Hydroxyapatite-Based Coatings On Silicon Wafers And Printed Zirconia, Antoine Chauvin

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Dental surgery needs a naturally attract implant design that can ensure both osseointegration and soft tissue integration. Hydroxyapatite (HAp), the main mineral constituent of dentine and tooth enamel, is commonly used as a coating component, notably for overlaying titanium– or ceramics–based implants. This thesis aims to investigate the behavior of a HAp-based coating, specifically designed to be compatible with a porous substrate. Coating layers are made by sol–gel dip coating by immersion of porous substrates made by additive manufacturing into solutions of HAp, having been mixed with polyethyleneimine (PEI), to improve the adhesion of HAp on the substrate. First, the …

Modeling Overdraft-Driven Nitrate Transport In Shallow Wells For Mitigation And Scenario Planning, Jonathan Cronk

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

In Nebraska, average nitrate concentrations in groundwater have doubled since 1974, making water quality management more important than ever. As droughts, heat waves, and floods become more common climate events, understanding their impacts will be necessary to make informed management decisions. Emerging literature describes that drought correlates to an increase in the concentration of nitrate-N at domestic and irrigation wells, however the relative contributions of the mechanisms thought to be responsible is currently unknown.

This research assessed the impact of recharge and pumping rate changes as two mechanisms affecting nitrate-N concentration during drought, assessed the relationship between well depth and …

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 …

Examining The Corn Seedling Emergence–Temperature Relationship For Recent Hybrids: Insights From Experimental Studies, Sahila Beegum, Charles Hunt Walne, Krishna N. Reddy, Vangimalla Reddy, Kambham Raja Reddy

Nebraska Water Center: Faculty Publications

Corn seedling emergence is a critical factor affecting crop yields. Accurately predicting emergence is crucial for precise crop growth and development simulation in process-based crop models. While various experimental studies have investigated the relationship between corn seedling emergence and temperature, there remains a scarcity of studies focused on newer corn hybrids. In the present study, statistical models (linear and quadratic functional relationships) are developed based on the seedling emergence of ten current corn hybrids, considering soil and air temperatures as influencing factors. The data used for model development are obtained from controlled soil plant atmospheric research chamber experiments focused on …

Analysis Of Wastewater Samples To Explore Community Substance Use In The United States: Pilot Correlative And Machine Learning Study, Marie A. Severson, Sathaporn Onanong, Alexandra Dolezal, Shannon L. Bartelt-Hunt, Daniel D. Snow, Lisa M. Mcfadden

Nebraska Water Center: Faculty Publications

Background: Substance use disorder and associated deaths have increased in the United States, but methods for detecting and monitoring substance use using rapid and unbiased techniques are lacking. Wastewater-based surveillance is a cost-effective method for monitoring community drug use. However, the examination of the results often focuses on descriptive analysis.

Objective: The objective of this study was to explore community substance use in the United States by analyzing wastewater samples. Geographic differences and commonalities of substance use were explored.

Methods: Wastewater was sampled across the United States (n=12). Selected drugs with misuse potential, prescriptions, and over-the-counter drugs …

Breakdown Of The Drift-Diffusion Model For Transverse Spin Transport In A Disordered Pt Film, Kirill D. Belashchenko, Giovanni G. Baez Flores, Wuzhang Fang, Alexey Kovalev, Mark Van Schilfgaarde, Paul M. Haney, Mark D. Stiles

Department of Physics and Astronomy: Faculty Publications

Spin-accumulation and spin-current profiles are calculated for a disordered Pt film subjected to an in-plane electric current within the nonequilibrium Green's function approach. In the bulklike region of the sample, this approach captures the intrinsic spin Hall effect found in other calculations. Near the surfaces, the results reveal qualitative differences with the results of the widely used spin-diffusion model, even when the boundary conditions are modified to try to account for them. One difference is that the effective spin-diffusion length for transverse spin transport is significantly different from its longitudinal counterpart and is instead similar to the mean-free path. This …

Statistical And Machine Learning Approaches To Describe Factors Affecting Preweaning Mortality Of Piglets, Md Towfiqur Rahman, Tami M. Brown-Brandl, Gary A. Rohrer, Sudhendu R. Sharma, Vamsi Manthena, Yeyin Shi

Department of Biological Systems Engineering: Papers and Publications

High preweaning mortality (PWM) rates for piglets are a significant concern for the worldwide pork industries, causing economic loss and well-being issues. This study focused on identifying the factors affecting PWM, overlays, and predicting PWM using historical production data with statistical and machine learning models. Data were collected from 1,982 litters from the United States Meat Animal Research Center, Nebraska, over the years 2016 to 2021. Sows were housed in a farrowing building with three rooms, each with 20 farrowing crates, and taken care of by well-trained animal caretakers. A generalized linear model was used to analyze the various sow, …

Characterization Of Environmental Levels Of Pesticide Residues In Household Air And Dust Samples Near A Bioenergy Plant Using Treated Seed As Feedstock, Jabeen Taiba, Eleanor G. Rogan, Daniel D. Snow, Chandran Achutan, Muhammad Zahid

Nebraska Water Center: Faculty Publications

Exposure to neonicotinoid insecticides is associated with adverse human health outcomes. There is environmental contamination in Saunders County, Nebraska, due to the accumulation of fungicides and insecticides from a now-closed ethanol plant using seed corn as stock. A pilot study quantified environmental contamination in nearby houses from residual pesticides by measuring dust and air (indoor/outdoor) concentrations of neonicotinoids and fungicides at the study site (households within two miles of the plant) and control towns (20–30 miles away). Air (SASS^® 2300 Wetted-Wall Air Sampler) and surface dust (GHOST wipes with 4 × 4-inch template) samples were collected from eleven study …

Majorana Bound States In A D-Wave Superconductor Planar Josephson Junction, Hamed Vakili, Moaz Ali, Mohamed Elekhtiar, Alexey Kovalev

Department of Physics and Astronomy: Faculty Publications

We study phase-controlled planar Josephson junctions comprising a two-dimensional electron gas with strong spin-orbit coupling and d-wave superconductors, which have an advantage of a high critical temperature. We show that a region between the two superconductors can be tuned into a topological state by the in-plane Zeeman field, and can host Majorana bound states. The phase diagram as a function of the Zeeman field, chemical potential, and the phase difference between superconductors exhibits the appearance of Majorana bound states for a wide range of parameters. We further investigate the behavior of the topological gap and its dependence on the …

Does Drought Stress Eliminate The Benefit Of Elevated Co2,/Sub> On Soybean Yield? Using An Improved Model To Link Crop And Soil Water Relations, Wenguang Sun, David Fleisher, Dennis Timlin, Chittaranjan Ray, Zhuangji Wang, Sahila Beegum, Vangimalla Reddy

Daugherty Water for Food Global Institute: Faculty Publications

Crop simulation models are indispensable tools that facilitate studies to assess climate impacts and adaptation responses, but have not been adequately tested in terms of accurately predicting crop growth and water stress responses to high carbon dioxide concentrations [CO₂]. The soybean model, GLYCIM, previously modified with a coupled leaf-level gas exchange – energy balance model, was integrated with a two-dimensional convectivediffusive root growth module which linked soil and leaf water potentials with the regulation of stomatal conductance. We evaluated the accuracy of this modified GLYCIM using experimental data from a Free-Air CO₂ Enrichment (FACE) site, SoyFACE, and …

Leaching Performance Of Nanotechnology-Induced High-Arsenic-Bearing Tooeleite-Like Mineral Nanowaste, Arindam Malakar, Sanjit Das, Samirul Islam, Rajneesh Singh, Sugata Ray

Nebraska Water Center: Faculty Publications

For arsenic decontamination from groundwater, arsenic crystallization is becoming adopted due to its sustainability and economic benefits. However, arsenic crystallization technology is a two-step process, which makes it complex and generates hazardous waste. Successful efforts toward making it a single-step process are presented here. The addition of nanorods and ball-milled zinc sulfide nanoparticles to arsenic-contaminated water result in highly monodispersed and higharsenic- containing mineralized nanowaste with a crystalline structure similar to the mineral Tooeleite ((Fe³⁺₆(As³⁺O₃)₄SO₄(OH)₄•4H₂O)). This study reports the results of a short-term stability test …