Physical Sciences and Mathematics Commons^™

Controller Software: Evolution, Identification, And Implementation, Balaji Balasubramaniam

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

In the annals of automation history and advancement, one can find control technology is at the core. Modern-day controllers rely heavily on software capability to provide stability and improve the system's performance. In particular, drone flight controllers use autopilot control software to accomplish autonomous navigation from take-off to landing. However, we know very little about how the controller code modifications and its impact, particularly at the software level. No general framework has been developed to identify the control code changes and observe the real values of software control loops at the kernel layer.

In this thesis, we lay the foundation …

Mining Work Items To Streamline Software Maintenance Tasks, Salomé Perez-Rosero

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

Software engineering maintenance tasks often require associating code changes into groupings of related units of work to have as much information as possible about the developments toward addressing a specific code task. A comprehensive understanding of how a code task has evolved helps developers make better decisions about changes in the overall codebase, where a commit represents the set of code changes made to the codebase at a specific time. While the concept of work items as logically related code changes has been primarily theoretical, its impact on software maintenance tasks, such as tracing the origins of bugs or fixes …

Leveraging Ai Tools In University Writing Instruction: Enhancing Student Success While Upholding Academic Integrity, Daisuke Akiba, Rebecca Garte

Publications and Research

The emergence of AI-powered Large Language Models (LLMs), such as ChatGPT and Google Gemini, presents both opportunities and challenges for higher education, particularly regarding academic integrity in writing instruction. This exploratory study examines a novel pedagogical approach that integrates LLMs as required feedback tools in a university-level psychology writing assignment. The exclusive online approach emphasizes improvement through revision, requiring students to obtain AI-generated feedback on ungraded initial drafts based on an instructor-provided rubric, with final assessment focused on the quality of subsequent revisions. Analysis of survey data from 39 undergraduate students, incorporating both quantitative measures and qualitative responses, revealed several …

Geochemical Evidence Of Drying During The 4.2 Ka Event In Sediment Cores From The Yucatán Peninsula, Mexico, Derek K. Gibson, Jonathan Obrist-Farner, Alex Correa-Metrio, Alejandra Rodriguez-Abaunza, Carlos Castañeda-Posadas

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Tropical hydroclimate variability during the Middle and Late Holocene was investigated using geochemical indicators of local-scale precipitation and evaporation preserved in sediment cores from two sites in the Mexican Yucatán Peninsula. Scanning X-Ray fluorescence spectroscopy data show generally decreasing precipitation trends during the Early and Middle Holocene. During the transition between the Middle and Late Holocene, geochemical evidence of reduced watershed erosion and increased evaporation indicate that a centennial-scale drying event impacted the region between 4.3 and 4.0 ka (kilo-anum; thousand years before present). These findings suggest that the 4.2 ka drying event, which has been previously recorded in Europe, …

Decoding Emotions: Unveiling Facial Expressions Through Acoustic Sensing With Contrastive Attention, Guangjing Wang, Juexing Wang, Ce Zhou, Weikang Ding, Huacheng Zeng, Tianxing Li, Qiben Yan

Computer Science Faculty Research & Creative Works

Expression recognition holds great promise for applications such as content recommendation and mental healthcare by accurately detecting users’ emotional states. Traditional methods often rely on cameras or wearable sensors, which raise privacy concerns and add extra device burdens. In addition, existing acoustic-based methods struggle to maintain satisfactory performance when there is a distribution shift between the training dataset and the inference dataset. In this paper, we introduce FacER+, an active acoustic facial expression recognition system, which eliminates the requirement for external microphone arrays. FacER+ extracts facial expression features by analyzing the echoes of near-ultrasound signals emitted between the 3D facial …

Adan: Adaptive Nesterov Momentum Algorithm For Faster Optimizing Deep Models, Xingyu Xie, Pan Zhou, Huan Li, Zhouchen Lin, Shuicheng Yan

Research Collection School Of Computing and Information Systems

In deep learning, different kinds of deep networks typically need different optimizers, which have to be chosen after multiple trials, making the training process inefficient. To relieve this issue and consistently improve the model training speed across deep networks, we propose the ADAptive Nesterov momentum algorithm, Adan for short. Adan first reformulates the vanilla Nesterov acceleration to develop a new Nesterov momentum estimation (NME) method, which avoids the extra overhead of computing gradient at the extrapolation point. Then Adan adopts NME to estimate the gradient's first- and second-order moments in adaptive gradient algorithms for convergence acceleration. Besides, we prove that …

Ai Is A Viable Alternative To High Throughput Screening: A 318-Target Study, Izhar Wallach, Denzil Bernard, Kong Nguyen, Gregory Ho, Adrian Morrison, Adrian Stecula, Andreana Rosnik, Ann Marie O'Sullivan, Aram Davtyan, Ben Samudio, Bill Thomas, Brad Worley, Brittany Butler, Christian Laggner

Chemistry Faculty Research & Creative Works

High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, …

Flexfl: Heterogeneous Federated Learning Via Apoz-Guided Flexible Pruning In Uncertain Scenarios, Zekai Chen, Chentao Jia, Ming Hu, Xiaofei Xie, Anran Li, Mingsong Chen

Research Collection School Of Computing and Information Systems

Along with the increasing popularity of Deep Learning (DL) techniques, more and more Artificial Intelligence of Things (AIoT) systems are adopting federated learning (FL) to enable privacy-aware collaborative learning among AIoT devices. However, due to the inherent data and device heterogeneity issues, existing FL-based AIoT systems suffer from the model selection problem. Although various heterogeneous FL methods have been investigated to enable collaborative training among heterogeneous models, there is still a lack of i) wise heterogeneous model generation methods for devices, ii) consideration of uncertain factors, and iii) performance guarantee for large models, thus strongly limiting the overall FL performance. …

Converting Vocal Performances Into Sheet Music Leveraging Large Language Models, Jinjing Jiang, Nicole Teo, Haibo Pen, Seng-Beng Ho, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Advanced natural language processing (NLP) models are increasingly applied in music composition and performance, particularly for generating vocal melodies and simulating singing voices. While NLP techniques have been effective in analyzing vocal performance data to assess quality and style, the automatic transcription of vocal performances into sheet music remains a significant challenge. Manual transcription tools often fall short due to the intricate dynamics of vocal expression. This study tackles the automation of vocal performance transcription into sheet music using innovative techniques, including large language models (LLMs). We propose a method to translate vocal audio input into display-ready sheet music effectively. …

A Strategic Insight Into The Market For Carbon Management Capacity, Mahelet G. Fikru, Ting Shen, Jennifer Brodmann, Hongyan Ma

Economics Faculty Research & Creative Works

This study presents the market for carbon management capacity via carbon capture, utilization, and storage technologies, identifying demand and supply forces, as well as clarifying the potential impact of market and non-market-based shocks on technology developers versus adopters. The paper addresses a prevailing gap in market analysis, introducing a microeconomic framework and unique dataset to identify key players, market forces, and policy incentives shaping the carbon capture, utilization, and storage landscape. The analysis equips industry stakeholders, policymakers, and investors with valuable insights regarding (1) leaders in the design, development, and manufacture of carbon capture, utilization, and storage technologies (supply), (2) …

A Novel Approach To Sustainable Behavior Enhancement Through Ai-Driven Carbon Footprint Assessment And Real-Time Analytics, Ahmad Jasim Jasmy, Heba Ismail, Noof Aljneibi

All Works

This research introduces an Artificial Intelligence-driven mobile application designed to help users calculate and reduce their Carbon Footprint (CFP). The proposed system employs an Intelligent Sustainable Behavior Tracking and Recommendation System, analyzing users' carbon emissions from daily activities and suggesting eco-friendly alternatives. It facilitates sustainability discussions through its chat community and educates users on sustainable practices via an intelligent chatbot powered by a sustainability knowledge base. To promote social engagement around sustainability, the application incorporates a competition and reward system. Additionally, it aggregates behavioral data to inform government sustainability policies and address challenges. Emphasizing individual responsibility, the proposed system stands …

Sustainable Energysense: A Predictive Machine Learning Framework For Optimizing Residential Electricity Consumption, Murad Al-Rajab, Samia Loucif

All Works

In a world where electricity is often taken for granted, the surge in consumption poses significant challenges, including elevated CO2 emissions and rising prices. These issues not only impact consumers but also have broader implications for the global environment. This paper endeavors to propose a smart application dedicated to optimizing the electricity consumption of household appliances. It employs Augmented Reality (AR) technology along with YOLO to detect electrical appliances and provide detailed electricity consumption insights, such as displaying the appliance consumption rate and computing the total electricity consumption based on the number of hours the appliance was used. The application …

Comparison Of Statistical And Machine Learning Genomic Prediction Methods In Plant Breeding: Case Studies In Maize And Soybean, Igor Kuivjogi Fernandes

Graduate Theses and Dissertations

Plant breeding is essential to increase genetic gain and food production worldwide. This study was conducted to evaluate new ways to use machine learning (ML) to tackle plant breeding challenges, where two ideas were tested — the first chapter focuses on how to combine genetic and environmental data using ML to improve the prediction of maize grain yield in multi-environment trials, while the second chapter centers on how to couple feature selection of molecular markers with ML to enhance prediction of yield in soybean, and, in both cases, ML approaches were compared to well-established statistical methods greatly adopted by the …

Oceano Dunes Community Survey Results, Michele Romolini, Eric G. Strauss, Marni Goldenberg, Keri Schwab

Center for Urban Resilience Reports

This report presents the findings of a 42-question survey conducted by Loyola Marymount University and Cal Poly San Luis Obispo from June 2023-May 2024 among visitors and local residents regarding their perceptions and experiences at California’s Oceano Dunes State Vehicular Recreation Area (SVRA). The survey aimed to gather insights into visitor and community demographics, frequency and types of use, barriers to use, environmental awareness and perceptions of use, and familiarity with park opportunities. In particular, we sought to seek responses from communities local to the parks, especially from the community of Oceano itself, and Latino and Hispanic community members. In …

Enhancing Mathematical Models For Covid-19 Pandemic Response: A Philippine Study, Timothy Robin Teng, Elvira De Lara-Tuprio, Ma. Regina Justina Estuar, Christian Pulmano, Lu Christian S. Ong, Zachary Pangan, Lenard Paulo V. Tamayo, Jasper John V. Segismundo, Mark Anthony C. Tolentino, Alyssa Nicole N. Ty

Mathematics Faculty Publications

Mathematical models supported by a robust automated data pipeline proved to be useful tools for a data-driven and science-based response and policy-making during the COVID-19 pandemic in the Philippines. In the first year of the pandemic, FASSSTER (Feasibility Analysis on Syndromic Surveillance using Spatio-Temporal Epidemiological modeleR) used a compartmental model to generate scenario-based projections of COVID-19 cases. The emergence of the Delta variant, however, and the administration of vaccines over the second half of 2021 caused significant changes in the Philippine pandemic landscape. This necessitated making adjustments to the model to better capture the local disease transmission dynamics and address …

Community Co-Production Of The Meaning Of Local Climate Resilience And Action: A Case Study, Michele Romolini, Mary Hillemeier, Dustin L. Herrmann

Center for Urban Resilience Scholarship

In the face of a rapidly urbanizing and warming planet, there is urgency for local governments to develop community resilience strategies. Successful climate change adaptation will likely require the inclusion of local knowledge, especially from historically marginalized communities. One pathway for this is through research projects and government planning activities that employ processes of co-production to generate actionable knowledge relevant to the community. This paper describes the approach, results, and reflections of a multi-sectoral partnership organized to engage residents of a small municipality to co-produce the meaning of community climate resilience, through methods including individual interviews, cognitive mapping, and a …

Populations Digitally Excluded From Education: Issues, Factors, Contributions And Actions For Policy, Practice And Research In A Post-Pandemic Era, Don Passey, Jean Gabin Ntebutse, Manal Yazbak Abu Ahmad, Janet Cochrane, Simon Collin, Asmaa Ganayem, Elizabeth Langran, Sadaqat Mulla, Ma. Mercedes T. Rodrigo, Toshinori Saito, Miri Shonfeld, Saunand Somasi

Department of Information Systems & Computer Science Faculty Publications

This conceptual paper draws on a wide range of research and policy literature, providing a contemporary view of issues, factors and practices that affect education for digitally excluded populations. Concern for how education for digitally excluded populations can be supported is focal to this paper, with different sections offering key related perspectives. From an analysis of issues, factors and practices, actions for policy, practice and research are identified. Given a key finding that power issues can have major effects on plans, implementation processes and outcomes when addressing needs of education for digitally excluded populations, the paper concludes by offering frameworks …

Understanding The Influence Of Traffic And Noise On The Wildlife Community Surrounding Fm106 And Sh100 In South Texas, Anna Rose Mehner

Theses and Dissertations

In South Texas, highways create landscape fragmentation, habitat degradation, and result in wildlife vehicle collisions. Vehicle collisions are the highest known cause of mortality of the endangered ocelot (Leopardus pardalis), which led Texas Department of Transportation to install nine wildlife crossing structures (WCS) on Farm-to-Market 106 and five on State Highway 100. These highways are along Laguna Atascosa National Wildlife Refuge, which is the location of the southernmost breeding population of ocelots in the United States. Many other wildlife species including bobcat (Lynx rufus) and coyote (Canis latrans), are present along these highways and …

Structure Modifications And Alternative Monitoring Designs Of Wildlife Road Mitigation Structures, Madison T. Nadler

Theses and Dissertations

Wildlife mitigation structures are designed to keep animals off roadways while providing them safe passage to the other side and not impeding traffic flow. Camera traps are commonly used to assess the success of these mitigation structures, but there are downfalls to both the methods and structures. Alternative mitigation structure designs are needed to better prevent wildlife from accessing roadways in areas where they should be deterred. Additionally, traditional camera trapping methods do not accurately capture the full wildlife communities that may be utilizing these structures and other survey methods are needed, specifically aimed at small mammals, amphibians, and reptiles. …

Technical Potential And Challenges For Agrivoltaic Development In Nigeria, Ifeoluwa Ezekiel Babarinde

Theses and Dissertations

The co-location of agriculture and solar photovoltaic (PV) infrastructure, known as agrivoltaics, is an increasingly popular practice that offers co-benefits like reduced plant drought stress and improved yields of shade-tolerant crops, particularly in water-scarce agricultural regions. Despite its global growth, knowledge on the technical potential, opportunities, and challenges for agrivoltaic development remains limited in the Global South. Here we address this knowledge gap for Nigeria, Africa’s most populous country, by identifying high-potential regions based on the premise that agrivoltaic co-benefits are generally most pronounced in arable lands with both high solar irradiation and water stress. We find that northern regions, …

Guiding Wildlife: Evaluating Wildlife Exit Designs And Sensor Lights For Safer Highways In South Texas, Rupesh Maharjan

Theses and Dissertations

Roadside exclusionary fencing is more prevalent on highways to prevent wildlife-vehicle collisions. Although it can mitigate wildlife road mortality by limiting their access to the road, it can also create a barrier for wildlife stranded within the right-of-way. In State Highway 100 of Texas, the Texas Department of Transportation installed ten wildlife exits to allow wildlife to escape the fenced roadway, and a pair of sensor lights on 13 wildlife guards (WGs) to scare off target species (bobcats and coyotes) from crossing the guards and accessing the roadway. In this study, the effectiveness of three wildlife exit (WE) designs were …

Implementing Organic Fertilization Practices To Improve Aloe Vera Growth And Soil Health In The Lower Rio Grande Valley, Isaiah Edward Jaramillo

Theses and Dissertations

Aloe vera (L.) (Aloe) Burm. f., is valued for its applications across the cosmetic, medicinal, and food industries due to its leaf gel. In the aloe industry, the extraction of gel from leaves generates significant quantities of organic waste, which presents an opportunity to repurpose this material as an amendment in aloe cultivation. While Aloe is renowned for its resilience, understanding the feasibility of using these organic shavings as a soil fertility amendment in aloe production is critical. This research aims to identify sustainable fertilization methods for Aloe that can maintain and/or improve crop yield while enhancing soil health. This …

Proof Of Concept: Simulating Drone Tracking In A Border Security Context, Jose Ruben Espinoza

Theses and Dissertations

Worldwide availability of drone technology has risen to unprecedented levels within the past century due to its commercial availability. While there has been various positive applications of such technology, it has additionally found usage within security critical contexts. Specifically, there have been reports of illegal drug smuggling along the Mexico-United States border in which quadrocopter based drones have been used. Within our research we aim to showcase, as a proof of concept, that autonomous drone technology can be leveraged within a defensive approach via the usage of reinforcement learning and object detection for security critical contexts. To promote the importance …

Evaluation Of Polymerization Condition Reactions Of Methyl Vinyl Ketone For Hydrogen Storage, Rituborna Ghosh

Theses and Dissertations

Hydrogen is widely regarded as one of the most promising clean alternative fuel sources; however, its widespread adoption has been hindered by significant challenges related to storage and transportation. Various storage methods have been proposed and developed, with continuous advancements being made to address these issues. Among the most effective solutions is the utilization of polymers, which serve as safe and efficient hydrogen storage media. This work investigated the polymerization of methyl vinyl ketone using different ratio of monomer: initiator and monomer: crosslinker using N,N′-methylenebisacrylamide (MBA) as crosslinker and ammonium persulfate (APS) as initiator in a free radical polymerization mechanism. …

Theoretical Insights And Analysis Into Luneburg Lens, Aram Flores

Theses and Dissertations

Advancements in wireless communications necessitate innovative antenna designs for radar systems and satellite communications. The Luneburg lens, theorized by Rudolf Luneburg in 1944, is a gradient-index lens capable of focusing electromagnetic waves onto a point on its surface, offering potential improvements in antenna gain and performance. Access to the lenses, courtesy of Assured Space Access Incorporated, enabled me to research the lenses response, and specific design details remain confidential. Practical assessments of 3D-printed Luneburg lenses of varying sizes are limited, including factors such as lens alignment and focal point offset. This study investigates the performance of 6-inch and 13.25-inch Luneburg …

Bayesian Lasso Regularized Quantile Regression And Its Applications, Priscilla Kissi-Appiah

Theses and Dissertations

Since the pioneering work of (Koenker and Bassett Jr 1978), quantile regression has been a popular regression technique that helps researchers investigate a whole distribution of the response variable. In addition, due to the quantile check loss function, it is robust against outliers and heavy-tailed distributions of the response variable and can provide a more comprehensive picture of modeling via exploring the conditional quantiles of the response variable. In this research, we study the lasso regularized quantile regression from a Bayesian perspective. We develop an efficient sampling algorithm to generate posterior samplings for making posterior inference by using a location-scale …

Examining Hispanic Beginning Farmers And Ranchers In The Rio Grande Valley Through A Community Capitals Framework, Perla Kimberly Schrock

Theses and Dissertations

While existing literature addresses the experiences of beginning farmers and ranchers (BFR), there is a notable gap in research focused on Hispanic beginning farmers and ranchers (HBFR). This study aimed at exploring the unique experiences of HBFR in a predominantly Hispanic region, the Rio Grande Valley (RGV), employed the Community Capitals Framework (Flora et al., 2016). I conducted 16 semi-structured interviews with HBFR and local nonprofit organizations and federal employees, complemented by participant observations. Through thematic and content analysis of the interview transcripts, findings revealed valuable insights into the livelihoods of HBFR. Despite HBFR facing significant challenges, this study demonstrated …

Thermal Conductivity Characterization Of High Oleic Vegetable Oils Based Hybrid Nanofluids Formulated Using Gnp, Tio2, Mos2, Al2o3 Nanoparticles For Mql Machining, Anthony Chukwujekwu Okafor, Tobechukwu Kingsley Abor, Saidanvar Esanjonovich Valiev, Ignatius Echezona Ekengwu, Abiodun Saka, Monday Uchenna Okoronkwo

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper presents the results of thermal conductivity characterization of six high oleic soybean oil (HOSO) and four high oleic canola oil (HOCO)-based hybrid nanofluids formulated with four types of nanoparticles (Graphene nanoplatelet (xGnP), TiO2, MoS2, and Al2O3) at nanoparticles wt.% concentration from 1 % to 7 % in 1 % increment using the two-step method for use in MQL machining of difficult-to-cut metals. Thermal conductivity of the formulated hybrid nanofluids were measured using Thermtest Transient Hot Wire Liquid Thermal Conductivity Meter at temperatures from 25 °C to 75 °C in increment of 10 °C. Obtained results showed that thermal …

Physicochemical Property Effects On Immune Modulating Polymeric Nanoparticles: Potential Applications In Spinal Cord Injury, Daniel J. Kolpek, Jaechang Kim, Hisham Mohammed, John C. Gensel, Jonghyuck Park

Markey Cancer Center Faculty Publications

Nanoparticles (NPs) offer promising potential as therapeutic agents for inflammation-related diseases, owing to their capabilities in drug delivery and immune modulation. In preclinical studies focusing on spinal cord injury (SCI), polymeric NPs have demonstrated the ability to reprogram innate immune cells. This reprogramming results in redirecting immune cells away from the injury site, downregulating pro-inflammatory signaling, and promoting a regenerative environment post-injury. However, to fully understand the mechanisms driving these effects and maximize therapeutic efficacy, it is crucial to assess NP interactions with innate immune cells. This review examines how the physicochemical properties of polymeric NPs influence their modulation of …

A Comparative Study Of Patterns, Causes, And Impacts Of Data Breaches Across Geographical Regions And Time Frames, Bhavish Balsara

Electronic Theses, Projects, and Dissertations

The rise of digital technologies and interconnected systems has made data breaches a growing global concern. This culmination project explores the patterns, causes, and impacts of data breaches across various countries with varying levels of economic development and cybersecurity infrastructure from 2020 to 2023. This research aims to provide insights into the global landscape of data breaches and how they have evolved in recent years. The research questions are: (Q1) How do data breach patterns differ between countries with different levels of economic development and cybersecurity infrastructure? (Q2) What patterns and trends can be identified in data breaches when analyzing …