Digital Commons Network^™

Contaminated Sweeping Langmuir Probes On Sounding Rocket Platforms, Rachel Conway

Doctoral Dissertations and Master's Theses

Sweeping Langmuir Probes (SLPs) are one of the most commonly used probes on sounding rocket missions. They offer measurements of plasma density, electron temperature, and both relative and absolute payload charging. One of the major implementation challenges, however, is contamination on the surface of the probe such that collected IV curves become distorted. This distortion can result in deflated densities, inflated temperatures, and erroneous charging measurements. This dissertation aims to expand our understanding of contamination's impact on SLP data and offer new mitigation methods appropriate for the sounding rocket platform.

SPICE, Simulation Program with Integrated Circuit Emphasis, is used to …

Applying Software Engineering Black-Box Methods For Testing Machine Learning Models, Timothy Elvira

Doctoral Dissertations and Master's Theses

This dissertation proposes researching an approach to incorporate and align Software black-box testing methods into Machine Learning (ML) applications, specifically in the context of computer vision models. Typically, testing methods within Software Engineering (SE) encompass a range of test types that assess levels of a software system, such as Unit, Integration, Functional, and System testing [1]. The testing spectrum offers two perspectives on the system: black-box, where the system’s code is hidden, and white-box, where the system's code is exposed for testing. Software Quality pairs testing with requirements, in a many-to-one relationship, to ensure proper validation of the software system. …

Modeling The Dynamics Of Flexible Aerospace Vehicles Using The Theory Of Functional Connections, Carlo Lombardi

Doctoral Dissertations and Master's Theses

Modeling and control of flexible vehicles is a topic of high interest in the aerospace field and a key challenge lies in finding accurate mathematical representations of the flexible dynamics of continuous elastic structures that allow simple integration into estimation and control algorithms. The answer was found in approximating the dynamics of these systems with sets of coupled Ordinary Differential Equations (ODE) for which a well-established estimation and control theory is available. Each of the techniques employed to achieve this goal is characterized by its own strengths and limitations. Hence, the main objective of this research is to develop the …

Developing Fixed-Bias Langmuir Probes For Multi-Point Constellation Deployments, Henry Carter Valentine

Doctoral Dissertations and Master's Theses

Since their initial development in the early 20th century, electrostatic Langmuir probes have proved invaluable in terrestrial and interplanetary ionospheric sounding applications. When deployed aboard rocket and satellite platforms, these probes yield high-cadence, in-situ measurements of key plasma parameters such as electron density, ion density, and electron temperature. Furthermore, the efficacy of Langmuir probes in characterizing the three-dimensional structure and dynamics of ionospheric plasmas can be augmented by the technique of multi-payload deployments. In this work, we discuss the design, development, and analysis of fixed-bias Langmuir probes constructed for two multi-point science campaigns: the Mars-bound, dual-satellite Escape and Plasma Acceleration …

Enhancing Multifactor Authentication Using Machine Learning Techniques, Rafea Mohammed Ibrahim

Mesopotamian Journal of CyberSecurity

Securing access to distributed database systems presents unique challenges because of their decentralized nature and exposure to multipoint threats. Traditional single-factor authentication mechanisms, such as passwords or PINs, are insufficient in such environments, prompting the need for more resilient solutions. This study proposes a biometric-based multifactor authentication (MFA) framework that combines fingerprint and facial modalities through a unified machine learning (ML) pipeline. ML plays a crucial role in enhancing classification performance by enabling the system to learn complex patterns across biometric inputs. The framework standardizes input preprocessing (by applying grayscale conversion, histogram equalization, and normalization) and employs the histogram of …

Framework For Integrating Industry Knowledge Into A Large Language Model To Assist Construction Cost Estimation, Prashnna Ghimire

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

The construction industry generates a large amount of data across projects produced by digital devices, tools, and methods, and this volume is rapidly increasing. However, the industry lags behind in adopting data-driven technologies. On the other hand, the rapid advancement of generative AI (GenAI) in recent years, especially state-of-the-art large language models (LLMs), shows great potential and has been increasingly adopted in many industries; however, the construction industry is behind in adoption. While academic studies have proposed various machine learning applications for construction, industry implementation has lagged due to a disconnect between these proof-of-concept developments and practical industry needs. Also, …

Reimagining The Potential Of Higher Education In Prison And Reentry, Darren Wheelock, Theresa Tobin, Robert Smith

Social and Cultural Sciences Faculty Research and Publications

No abstract provided.

Design Of Dmd Nano Logic Gates With Strip Waveguides For Communication System, Jabbar Khalaf Mohammed

Iraqi Journal of Computers, Communications, Control and Systems Engineering

COMSOL software is used to build and quantify optical logic circuits using plasmonic square ring resonators. An operation utilizing constructive and destructive control along with input port interferences as inputs results in the proposed gates. At 1010 nm resonance wavelength, the transmission threshold is 30% at a single interface, the ratio of input power to output optical power. All plasmonic gates are executed within a singular structure measuring 150 nm by 150 nm. The OR gate and the AND gate exhibit transmission rates exceeding 100%, with both reporting a rate of 221%. The OR and AND gates exhibit modulation depth …

Hiding Secret Message Into Gray Image Using 2-Bit Plan Slicing, Zahraa Abbas Al-Zubaydi, Layth Kamil, Israa Ali Al-Neami, Maisa'a Abid Ali Khodher

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The comprehensive utilization of the Internet has grown significant and widespread in contemporary times. Thus, the necessity for a robust method to facilitate the secure dissemination of data has emerged as a significant barrier for network users in the realm of data transmission.The proposed system comprises four stages: the first stage employs two-bit plane slicing (2-BPS) to partition the image into four subimages (covers), the second stage transforms a secret message from ASCII to binary format; the third stage produces a random secret key; and the four stage conceal the secret message into the covers(2BPS) images. The results obtained the …

Integrating Elementary Computer Science And Mathematics Instruction: One Size Does Not Fit All, Umar Shehzad, Jody Clarke-Midura, Mimi Recker

Publications

This paper presents a model, the double integration model, for integrating Computer Science (CS) and mathematics in upper elementary instruction. Fifth-grade students (n=1,037) participated either in the double integrated model (Condition 1; integrated in both CS and Math instruction) or integrated lessons only in CS instruction (Condition 2). After each lesson, students rated their enjoyment, perceived ease, and perceptions of CS-math connections. Multilevel analyses revealed that Condition 1 students reported significantly more positive perceptions and stronger CS-math connections of the lessons than Condition 2 students. Girls in Condition 1 responded more positively than boys on enjoyment and connection items, and …

Streamlining Field Note Analysis: Leveraging Gpt For Further Insights, Saríah López-Fierro, Umar Shehzad, Alireza (Sina) Zandi, Jody Clarke-Midura, Mimi Recker

Publications

As an integral part of qualitative research inquiry, field notes provide important data from researchers embedded in research sites. However, field notes can vary significantly, influenced by the researchers' immersion in the field, prior knowledge, beliefs, interests, and perspectives. As consequence, their interpretation presents significant challenges. This study offers a preliminary investigation into the potential of using large language models to assist researchers with the analysis and interpretation of field notes data. Our methodology consisted of two phases. First, a researcher deductively coded field notes of six classroom implementations of a novel elementary-level mathematics curriculum. In the second phase, we …

Zoophytophagous Predator Sex Pheromone And Visual Cues Of Opposing Reflectance Spectra Lure Predator And Invasive Prey, Bashiru Adams, Fathiya Mbarak Khamis, Abdullahi Ahmed Yusuf, Baldwyn Torto

All Peer-Reviewed Publications

Introduction: In sub-Saharan Africa, the invasive South American leafminer Phthorimaea absoluta is the most damaging tomato pest. Females of the pest can reproduce both sexually and through parthenogenesis and lay their eggs on all tomato plant parts. The mirid predator Nesidiocoris tenuis, a biological control agent for the pest, is also a tomato pest when prey population is low. To date, however, no study has developed an eco-friendly solution that targets both the predator and its host in a tomato farming system. Objective: To develop a bio-based management system for both pest and predator based on the combined use of …

Tritium As A Model Tracer For Predicting Per- And Polyfluoroalkyl Exposure And Potential Ecosystem And Human Health Impacts, Erika Craig

Theses and Dissertations

For this thesis, historical tritium and per-and polyfluoroalkyl substances (PFAS) concentrations measured in surface waters of South Carolina at or near the Savannah River Site (SRS) were compared. Statistical linear regression analysis was used to assess the ability of tritium as a model tracer for predicting PFAS concentrations, specifically perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) distributions. Nine years of tritium monitoring data, (2014 – 2022), were analyzed and used in linear regressions to assess their association with PFAS levels of PFOA and PFOS measured during 2023, in and around the SRS and the adjoining Savannah River. Initially, a normality …

Reclaiming The Body: Gender Politics And Embodied Meaning In Piano Performance And Pedagogy, Rachel Misheff

Theses and Dissertations

This study examines the impact of the mind-body duality and its gendered metaphor on the lived experiences of historical and contemporary female pianists. Specifically, it explores how the principles of mind-body dualism have constructed gendered practices in piano performance and pedagogy that have both marginalized female pianists and engendered distinct embodied relationships to music. The study draws upon research from other disciplines, such as phenomenology, theories of embodiment, feminist theory, psychoanalysis, and Embodied Music Cognition, to examine how these gendered musical norms resulting from mind-body dualism functioned as forces of social inscription. This research, therefore, suggests that the body’s lived …

Multiscale Modeling Techniques For Electrodynamic Systems, Hunter Teel

Theses and Dissertations

In order to rapidly develop better electromagnetic and electrochemical systems, approaching these complicated topics from multiple perspectives is necessary. The use of mathematical models and numerical simulation offers the ability to evaluate and predict the performance of these systems based off the principles of electrodynamics in an ideal setting. Through the use of Computational Fluid Dynamics (CFD), representative geometries of scales can be created and evaluated to provide insight into the behavior of these systems. Simulation offers a modifiable environment that can approach the relevant physics from both the microscale and macroscale. Conclusions, results, boundary conditions, or other information from …

Hallucinations In Large Foundation Models: Characterization, Quantification, Detection, Avoidance, And Mitigation, Vipula Rawte

Theses and Dissertations

Deception is an inherent aspect of social interactions, with research indicating that most people engage in deceptive behavior at least once or twice daily . In parallel, advances in artificial intelligence have led to machines exhibiting deceptive tendencies. These deceptions can be categorized into two types: unintended and intentional. Unintended deceptions - often referred to as hallucinations - occur when generative AI systems produce plausible and convincing narratives yet are factually inaccurate. This phenomenon primarily results from the systems' architectural design, extensive parametric memory, and reliance on statistical assumptions. In this thesis, we provide a comprehensive discussion on the characterization, …

A Novel Geometric Modeling Kernel For Automated Fiber Placement, Rowen Burney

Theses and Dissertations

Automated Fiber Placement (AFP) is a key manufacturing technique for producing high-performance composite structures, yet existing geometric modeling frameworks lack the specialized functionality required for efficient toolpath planning and laminate optimization. This work presents Knots, a Geometric Modeling Kernel (GMK) developed specifically to address these limitations by providing a unified geometric foundation tailored for AFP. Unlike general-purpose Computer Aided Design (CAD) libraries, Knots is optimized for AFP, offering specialized geometric operations that streamline the transition from design to manufacturing. It directly manages the loading and computation of geometric data, ensuring structured laminate generation while supporting automation and scripting for improved …

Literature Review Of Fuzzy Set Theory: Applications And Methodologies, Mohammed Jasim Mohammed

Journal of Economics and Administrative Sciences

This paper represents a comprehensive literature survey of the research published in the Journal of Economics and Administrative Sciences (JEAS) on applications and methodologies of fuzzy set theory. The review traced how fuzzy logic has been evolving in decision-making, optimization, and modeling uncertainties in published articles such as economics, management, and engineering. The categorization of fuzzy methodologies into various domains such as fuzzy linear programming, fuzzy regression, fuzzy control systems, and fuzzy multi-criteria decision-making relies heavily on the study of existing research. An analysis revealed an increasing trend of investigations highlighting the interplay of fuzzy logic with artificial intelligence, statistical …

Estimation And Analysis Of The Cost Function Of The Food Industries In Iraq, Mustafa Qopeis Qasim, Salah Mahdi Abbas Al-Birmani

Journal of Economics and Administrative Sciences

The paper analyses the production costs of Iraq's food industry and tries to establish its optimum production level. Declining contribution to GDP resulting from high production costs, competition brought about by imported products, and economic instability has been showed by the study in focusing on the industry. The paper employs econometric analysis through EViews-10 to estimate cost functions across different industrial scales (Small, Medium, and Large) for the period between the years 2004 and 2022. Findings reveal that the optimal production efficiency has not been attained so far for the food industry of Iraq. It is suffering from a high …

Spatial Quantile Autoregressive Model: A Review, Sawsan Qassim Hadi, Omar Abdulmohsin Ali

Journal of Economics and Administrative Sciences

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. …

Cutting-Edge Deep Learning Methods For Image-Based Object Detection In Autonomous Driving: In-Depth Survey, Narges Saeedizadeh, Seyed Mohammad Jafar Jalali, Burhan Khan, Shady Mohamed

Research outputs 2022 to 2026

Object detection is a critical aspect of computer vision (CV) applications, especially within autonomous driving systems (AVs), where it is fundamental to ensuring safety and reducing traffic accidents. Recent advancements in computational resources have enabled the widespread adoption of Deep Learning (DL) techniques, significantly enhancing the efficiency and accuracy of object detection tasks. However, the technology for autonomous driving has yet to reach a level of maturity that guarantees consistent performance, reliability, and safety, with several challenges remaining unresolved. This study specifically focuses on 2D image-based object detection methods, which offer several advantages over other modalities, such as cost-effectiveness and …

A Survey On Unauthorized Uav Threats To Smart Farming, Peng Chen, Shihao Yan, Helge Janicke, Arash Mahboubi, Hang Thanh Bui, Hamed Aboutorab, Michael Bewong, Rafiqul Islam

Research outputs 2022 to 2026

The integration of Internet of Things (IoT) and unmanned aerial vehicles (UAVs) in smart farming has revolutionized agricultural practices by enhancing monitoring, automation, and decision-making to improve agricultural productivity and sustainability. However, the widespread use of these technologies has also introduced new security challenges, particularly the risk of interference from unauthorized UAVs. This survey provides an analysis of the threats posed by unauthorized UAVs to smart farms, highlighting potential vulnerabilities such as data interception, communication jamming, and physical damage. This paper first explores recent advancements in IoT and UAV technologies, which are integral to the functioning of smart farms. Then, …

I Really Try To Model Good Practices: Reflecting On Journal Article Publication From Mid-Career, Margaret K. Merga, Shannon Mason, Julia Morris

Research outputs 2022 to 2026

Publishing research in scholarly journals takes up much time and energy for many academics, and the early career phase may be particularly challenging, as researchers navigate the processes and politics of academic publishing for the first time. We previously explored these challenges as early-career researchers in a collaborative autoethnographic study in 2018. Now, 6 years later, we have once again reflected on our shared and divergent experiences, this time from our positions as mid-career researchers, socialised into the world of scholarly publishing and with longer histories of success and failure in scholarly publication. Our critical discussions revealed a continued commitment …

Hybrid Renewable Multi-Generation System Optimization: Attaining Sustainable Development Goals, Md Shahriar Mohtasim, Barun K. Das, Utpol K. Paul, Md Golam Kibria, Md Sanowar Hossain

Research outputs 2022 to 2026

The optimization of hybrid renewable multi-generation systems is crucial for enhancing energy efficiency, reducing costs, and ensuring sustainable power generation. These factors can be significantly affected by system designs, optimization methods, climate changes, and varying energy demands. The optimization of a stand-alone hybrid renewable energy system (HRES) that integrates various combinations of electricity, heating, cooling, hydrogen, and freshwater needs has not been reported in a single comprehensive study. Additionally, there has been insufficient attention given to the impact of temporal resolution, the recovery of excess energy usage, and aligning these efforts with the sustainable development goals (SDGs). This study reviews …

Performance Comparison Of Flat Sheet And Hollow Fibre Air Gap Membrane Distillation: A Mathematical And Simulation Modelling Approach, Hamed Kariman, Hussein A. Mohammed, Masoumeh Zargar, Mehdi Khiadani

Research outputs 2022 to 2026

Membrane Distillation (MD) systems could address current challenges related to global water demand. Among MD systems, Air Gap Membrane Distillation (AGMD) systems play crucial roles in addressing this challenge. AGMD systems can be categorized into two main structural groups: flat sheet and hollow fibre forms. It is important to study, analyse, model and compare these two systems under the same operational conditions. In this study, a detailed mathematical model of flat sheet and hollow fibre AGMD modules under the same conditions (i.e., membrane type, membrane area, porosity, and pore radius of membrane) has been introduced. The simulation of system performance …

Reply To Bratchenko And Bratchenko, “Overestimation Of The Classification Model For Raman Spectroscopy Data Of Biological Samples”, Xin Ru Wen, Jia-Wei Tang, Liang Wang

Research outputs 2022 to 2026

No abstract provided.

Climate Change Threatens Water Resources For Major Field Crops In The Serbian Danube River Basin By The Mid-21st Century, Jamshid Jalali, Nishan Bhattarai, Jillian Greene, Tao Liu, Oskar Marko, Mirjana Radulović, Molly Sears, Sean A. Woznicki

Open Access Publishing Support Funded Articles

Study region: Serbian Danube River Basin

Study focus: As climate change makes weather patterns more erratic, water supply for agriculture is becoming increasingly uncertain. This is concerning in the Serbian Danube River Basin, where crops are mainly rainfed and the growing season is becoming warmer and drier. Assessing the balance between future agricultural water demand and availability in a changing climate is critical to address agricultural water scarcity. To understand how changing climate will affect water availability during 2041–2070, we used the Soil and Water Assessment Tool+ hydrological model with field-scale crop rotations and irrigated extent data and forced with …

Statistical Inference For Noisy Matrix Completion Incorporating Auxiliary Information, Shujie Ma, Po-Yao Niu, Yichong Zhang, Yinchu Zhu

Research Collection School Of Economics

This article investigates statistical inference for noisy matrix completion in a semi-supervised model when auxiliary covariates are available. The model consists of two parts. One part is a low-rank matrix induced by unobserved latent factors; the other part models the effects of the observed covariates through a coefficient matrix which is composed of high-dimensional column vectors. We model the observational pattern of the responses through a logistic regression of the covariates, and allow its probability to go to zero as the sample size increases. We apply an iterative least squares (LS) estimation approach in our considered context. The iterative LS …

Experimental Investigation Of External Flow Condensation Heat Transfer In Horizontal Tube-In-Tube Configuration, Jiayuan Li, Jayachandran K. Narayanan, Chirag R. Kharangate

Faculty Scholarship

Flow condensation is an important process used to achieve heat rejection across thermal power and energy systems. Studies on tube condensation have concentrated on the condensing fluid flowing in the inner tube. However, common heat exchanger configurations like the shell-and-tube types see the condensing fluid on the outer surface of the tubes. To address this gap, in this study, we investigate the local and channel-averaged heat transfer characteristics of flow condensation happening on the exterior of a horizontal tube in the tube-in-tube configuration. An external flow condensation module is developed and tested to obtain heat transfer and flow visualization data, …

Science-Based Policy Recommendations For Managing Emerging Pollutants: Protecting Water Quality For The Health Of People And The Environment, Sarantuyaa Zandaryaa, Ali Fares, Gabriel Eckstein, Regina M. Buono, Mary Trudeau, James E. Nickum, Xingui Xia, Atikur Rahman, Marijn Korndewal, Cassiana C. Montagner, Piero R. Gardinali, Robert Michael Di Filippo, Anoop Veettil

Faculty Scholarship

Emerging water pollutants are a growing global concern due to their ubiquitous presence in water resources worldwide and their potential adverse effects on human health and ecosystems. Limited scientific understanding of sources of emerging pollutants’ emissions to water bodies and their pathways, behaviour, and fate in aquatic environments, as well as human health and ecological effects, is a significant hindrance in managing emerging water pollutants. With exceptions concerning PFAS/PFOS and microplastic beads, there are few regulations for emerging pollutants in national water and environmental policies, which results in a critical gap in safeguarding human health and aquatic ecosystems through effective …