Engineering Commons^™

A Meta-Analysis Of Historic Drinking Water Emergency Events Reported In News Articles, Victor Yu, Haiying Wang, Weiwei Mo

Faculty Publications

This study seeks to investigate historical drinking water contamination events that reported by news media to find the key determinants of their outcomes, including the duration and economic cost, and to quantitatively describe the characteristics of past contamination events. ProQuest Global Newsstream and Regional Business News were used to identify an initial list of events and supplemented by additional search on specific information including the response actions, economic cost, and more. These events were analyzed using descriptive statistics, correlation analysis, and regression modeling. Smaller community water systems were found to be more frequently impacted by contamination events. Use restrictions, except …

Validity Of Body Composition Estimates In Women Assessed By A Multifrequency Bioelectrical Impedance Device, Mitchell Evan Zaplatosch, Juliana F. Meireles, Janeen S. Amason, Sadaf Dabeer, Brian M. Kliszczewicz, Gerald Mangine, Valene G. Barry, Barbara A. Gower, Katherine H. Ingram

Faculty Articles

Background: Multifrequency bioelectrical impedance devices such as the InBody 770 (IB770) offer faster measurements and lower costs compared with other body composition assessments. This study validated measures from IB770 against the deuterium oxide dilution technique (D2O) and DXA and compared a four-compartment (4C) model using total body water (TBW) derived from IB770 compared with D2O. Methods: A total of 55 adult females (mean ± SD, age: 21.1 ± 2.6 years) completed IB770 and DXA scans and the D2O protocol. Lin’s concordance correlation coefficients (CCCs), Bland–Altman analyses, and other equivalence tests evaluated agreement between IB770 and the criterion for measures of …

Improving Particle-Phase Nitrate Measurement In Pm2.5 Filter Sampling: Evaluation Of A Denuder–Nylon Filter Modification In The Spartan Network, Wenyu Liu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Accurate measurement of PM_2.5 composition is of global importance. Evaporation-induced mass loss introduces potential bias in filter-based PM_2.5 measurements, with ammonium nitrate volatilization from Teflon filters being a major contributor to negative mass artifacts. Previous studies have demonstrated that using an acid gas denuder in combination with nylon filters can help recover the nitrate mass. This study evaluates design modifications to the AirPhoton sampling station setup within the globally distributed Surface Particulate Matter Network (SPARTAN) incorporating an additional acid gas denuder upstream and a nylon filter downstream of the existing Teflon filter.

Two co-located AirPhoton Sampling stations were …

Career: Flavones As Safe, Sustainable Additives To Tune Biodegradable Plastic Stability, Kyle Moor

Funded Research Records

No abstract provided.

Rapid: Data Collection On Roadway Vehicle Abandonment In The Fast-Moving Los Angeles Wildfire Evacuations, Sarah Grajdura

Funded Research Records

No abstract provided.

Csa-Xai: Channel–Spatial Attention And Explainable Ai In A Modular Multi-Backbone Framework For Lung Cancer Classification, Omar Ibrahim Obaid, Abdulbasit Alazzawi

Iraqi Journal for Computer Science and Mathematics

Computed tomography (CT) scans require precise and early lung cancer detection to produce better clinical results. High accuracy in deep learning approaches (DL) poses an existing challenge to interpret their functionality effectively. This research presents an innovative modular multi-backbone structure that combines channel-spatial attention together with explainable AI (XAI) methods for three-class lung cancer diagnosis (Normal, Benign, and Malignant). Research was carried out to evaluate six pre-trained CNN backbones (ResNet-50, VGG19, Inception-V3, EfficientNet-B0, MobileNet-V2, DenseNet-121) which received hybrid attention enhancement on the IQ-OTH/NCCD dataset. The experimental data showed four pre-trained models reaching perfect accuracy at 100 percent whereas the others …

Class Weighting In Imbalanced Data For Leukocyte Classification Using Fine-Tuning Inception-V3, Wahyudi Setiawan, Meidya Koeshardianto, Eka Mala Sari Rochman, Aeri Rachmad, Tutut Herawan

Iraqi Journal for Computer Science and Mathematics

This study investigates the classification of leukocyte images in an imbalanced dataset using deep learning techniques. The dataset consists of 14,514 images, categorized into five leukocyte types: basophils (301), neutrophils (8,891), lymphocytes (3,461), monocytes (795), and eosinophils (1,066). To address class imbalance, we applied class weighting alongside transfer learning and fine-tuning using the Inception-v3 architecture. The dataset was split into 80% for training and 20% for testing, and 5-fold cross-validation was conducted to evaluate model robustness. Hyperparameters were set with a learning rate of 0.0001, batch size of 32, and 30 training epochs, optimized using the Adam optimizer. Fine-tuning was …

Symmetric Toeplitz Matrices For A Class Of New Subclass Functions And Bazilevič Functions, Nihad H. Shehab, Abdul Rahman S. Juma

Iraqi Journal for Computer Science and Mathematics

In this work, we describe and investigate a novel collection of analytic functions, including the new functions and the Bazilevič functions. An important component of analytic functions, Bazilevič functions have numerous uses in both pure and practical mathematics. For this class of functions, we concentrate on building Toeplitz matrices, examining their structural characteristics, and evaluating their eigenvalues and trends. We utilise these studies to draw sophisticated mathematical conclusions on the stability and convergence characteristics of Bazilevič functions, as well as possible uses in geometry and differential equations. This work aims to determine coefficient estimates for the functions in this family …

Classify Cancers Types Using Mirnas Profiles And Machine Learning, Wafaa Khazaal Shams

AUIQ Technical Engineering Science

Cancer classification is important for early diagnosis and effective treatment. This study proposes a hybrid framework that combines Fisher Discriminant analysis (FD) with Linear Support Vector Machine (LSVM) and Long Short-Term Memory (LSTM) networks. MicroRNAs (miRNAs) expression profiles for three types of cancer are used to evaluate the model. These are: lung- adenocarcinoma, ovary and pancreas cancers. The classification process is done using 5-fold cross valuation. Results show significant performance for LSTM compared to LSVM with and without features reduction. However, using FD analysis results in high accuracy reached 0.97and 0.96 for LSTM and LSVM respectively, using 50 miRNAs. The …

Architectural Optimization Of Façade Design Using Nano-Ceramic Films For Green Buildings In Baghdad’S Hot Climate, Lina M. Shaker, Wan Nor Roslam Wan Isahak, Ahmed Salih Mahdi

AUIQ Technical Engineering Science

This study aims to optimize the architectural integration and energy performance of nano-ceramic window films in a three-story Baghdad commercial building having an overall area of 2,000 m². In a 40% window-to-wall ratio (WWR) and climate-responsive orientation, films were selected for solar exposure; north façade overhanging high-transmittance movies, east and west vertical fins on medium-transmittance movies, and south horizontal louvers on low-transmittance movies. Architectural strategies for daylighting, comfort, and façade appearance with low solar heat gain (SHG) were considered. MATLAB 2022 simulations evaluated energy savings, daylight transmission, and solar rejection. The most effective film (either film, HD-IR05100) achieved …

Orbital Maneuvers And Interplanetary Trajectory Design Via Reinforcement Learning, Roberto Cuéllar Rangel

Doctoral Dissertations and Master's Theses

This dissertation investigates the application of reinforcement learning (RL) to the design and optimization of low-thrust spacecraft trajectories, with an emphasis on autonomy, adaptability, and robustness in the presence of system uncertainties and unmodeled perturbations. Classical approaches to low-thrust trajectory design are predominantly grounded in optimal control theory, which relies on the availability of precise dynamical models and often requires problem-specific reformulation and solver tuning. While optimal control methods offer high accuracy under deterministic conditions, their sensitivity to stochastic disturbances and computational limitations in highly nonlinear or uncertain environments pose significant challenges for future autonomous space missions.

To address these …

Comparative Analysis Of Codes Of Ethical Conduct And Professionalism In Engineering And Project Management Associations, Valarie Denney, James W. Marion

Publications

This research details the similarities and differences in moral values and perspective from 15 engineering and project management association codes of conduct and professionalism. The methodology uses text mining of selected codes counting and summarizing keywords, evaluating document similarities through cosine similarity, and assessing the influence of various ethical schools of thought. Key findings reveal differences in the emphasis of core ethical values like fairness, honesty, and responsibility across different associations. This research is important for engineering and project management professionals to purposefully develop and evolve codes of ethics and professional development to enhance integrity, accountability, and ethical decision-making.

Life And Performance Improvement Trenches, Thomas J. Praisner, John R. Farris, Connor Wiese

AFIT Patents

A blade outer air seal assembly includes a plurality of seal segments circumferentially disposed about an array of blades rotatable about an axis, each of the plurality of seal segments having a radially inner surface facing a tip of each blade of the array of blades, the radially inner surface having an arrangement of trenches formed therein, and a radially outer surface opposite the radially inner surface. The arrangement of trenches is disposed between 30% and 80% of a chord of a blade of the array of blades as taken at the respective tip, and the arrangement of trenches is …

Note For Quadripartitioned Neutrosophic Offset, Pentapartitioned Neutrosophic Offset, And Heptapartitioned Neutrosophic Offset, Takaaki Fujita

Neutrosophic Systems with Applications

Neutrosophic sets assign each element three independent membership values—truth, indeterminacy, and falsity—and their partitioned extensions introduce additional components subject to sum-bounded constraints. Notable examples include quadripartitioned, pentapartitioned, and heptapartitioned neutrosophic sets. The O set concept further extends this framework by allowing membership values outside the standard [0, 1] interval, including negative values and values exceeding one. In this paper, we introduce and analyze the Quadripartitioned Neutrosophic O set, Pentapartitioned Neutrosophic O set, and Heptapartitioned Neutrosophic O set. These extensions are intended to enhance the expressiveness of neutrosophic theory and to stimulate further research in neutrosophic and fuzzy uncertainty.

Integrated Algorithm And Hardware Design For Hybrid Neuromorphic Systems, James Seekings, Mahsa Ardakani, Peyton Chandarana, Arshia Eslami, Mohammadreza Mohammadi, Ramtin Zand

Faculty Publications

This paper investigates the combined potential of neuromorphic and edge computing to develop a flexible machine learning (ML) system designed for processing data from dynamic vision sensors. We build and train hybrid models that integrate spiking neural networks (SNNs) and artificial neural networks (ANNs) using the PyTorch and Lava frameworks. We explore the effects of quantization on ANN models to assess its impact on both accuracy and energy efficiency. Additionally, we address the challenges of deploying hybrid models on hardware by implementing individual components on specific edge platforms. We also propose an accumulator circuit to bridge the spiking and non-spiking …

Characterizing And Modeling The Nonlinear Behavior Of Additively Manufactured Trapped-Powder Dampers, Jonathan Knight Black

Theses and Dissertations

Laser Powder Bed Fusion (LPBF) can be used to create metal parts with pockets of retained, unfused powder that serve as mechanical dampers. These trapped-powder dampers show promise for reducing the amplitude of vibrations at resonance by orders of magnitude. However, little is currently understood about the nonlinearity and repeatability of trapped-powder dampers, meaning that the design process currently consists of expensive trial-and-error prototyping and iteration. The present work contributes a corpus of experimental measurements for rectangular beams with trapped-powder dampers of various dimensions and locations. Preliminary testing revealed the presence of a memory effect which we hypothesize to be …

Investigating Radiation Induced Rowhammer And Retention Failures In Dram, Tyler Ricks

Theses and Dissertations

It is desirable for DRAM devices to be used in harsh radiation environments. Exposure to radiation causes DRAM cells to lose their retention time as their ability to store charge effectively declines. Exposure also worsens the effect of disturbance that causes neighboring cells to flip when a row is opened multiple times: an effect known as the Row Hammer Effect. This thesis evaluates the impact of radiation-induced memory cell degradation by comparing memory cell's retention time and their resilience to the row hammer vulnerability. Three generations of DRAM were placed under a neutron radiation beam. Sections of the irradiated devices …

Digital Trading Platform Selection Under Neutrosophic Numbers And Multi-Criteria Decision-Making Methodology: An Illustrative Example, Eman Sayed, Karam M. Sallam, Ibrahim Alrashdi

Neutrosophic Systems with Applications

Uncertainty, vagueness, and incomplete information are pervasive in real-world decision-making scenarios, particularly in multi-criteria decision-making (MCDM) contexts involving expert judgments. To address these challenges, this study introduces a comprehensive decision-making framework that integrates Triangular Neutrosophic Numbers (TNNs) with the Weighted Aggregated Sum Product Assessment (WASPAS) method. The framework begins by capturing expert evaluations using TNNs, which effectively represent the degrees of truth, indeterminacy, and falsity inherent in subjective assessments. These evaluations are then transformed into crisp values using a novel score function that preserves the embedded uncertainty. The resulting decision matrices are aggregated into a unified structure to ensure consistency …

Quantified Possibility Neutrosophic Soft Set Based Decision Support System For Enhanced Accuracy In Sustainable Supplier Selection Decision Analysis, Neha Andaleeb Khalid, Muhammad Saeed

Neutrosophic Systems with Applications

To deal with the concepts of vulnerability, ambiguity, and indeterminacy that are typical in complex decision analysis contexts, neutrosophic set-like structures are frequently used. Although neutrosophic sets are particularly good at handling indeterminate circumstances, indeterminacy plays a part in making the decision making process imprecise and ambiguous. This paper develops a more advanced technique to improve the accuracy of decision analysis problems: the Quantified Possibility Neutrosophic Soft Set Decision Support System (Q^t PNSSDSS). In order to reduce the element of indeterminacy present in conventional neutrosophic sets, the proposed DSS is based on the Quantified Neutrosophic Set, which employs a …

Development Of Construction Materials With Natural Fibers And Flax Shives For Green Eco-Friendly Buildings. Mrs Advances (2025), Iman El-Mahallawi, Lamiaa Mohamed, Rania El‑Shorbagy, Mahmoud Tash, Aliaa Abdelfatah

Mechanical Engineering

Sustainability-oriented solutions are essential to address the depletion of natural resources, solid waste accumulation, and high CO2 emissions in the construction industry. This research focuses on the development of environmentally friendly green bricks by replacing high-carbon-footprint constituents with local, natural materials. Specifically, flax shives, a natural agricultural by-product, and marble powder, an industrial waste, were used as partial substitutes in the binder matrix. The natural fibers not only promote sustainability but also enhance insulation and reduce the environmental burden. The bricks were molded into rectangular specimens (60 × 100 × 200 mm) and tested for thermal conductivity, moisture absorption, and …

Understanding And Evaluating Genomic Language Models, Aadit Kapoor

Master's Theses

Large Language Models (LLMs) have shown remarkable capabilities in interpreting complex patterns across various domains, yet their application to genomic data remains limited. We see great potential in leveraging LLMs for vital biological tasks, such as predicting transcription factor binding sites and identifying antibiotic-resistant genes. This emergent behavior positions LLMs as powerful tools for enhancing our understanding of intricate biological language. LLMs trained specifically on genomic data, such as DNA sequences, operate distinctly compared to those trained on natural language. This difference is evident not only in the architectural landscape of the models but also in the methodologies employed by …

Some Properties Of Neutrosophic Cubic Hypersoft Sets, Lubna Nayab, Muhammad Gulistan, Fawad Hussain

Neutrosophic Systems with Applications

This study addresses the limitations of NCS in managing uncertainties associated with multiple attributes and their further bifurcation. To address this challenge, we propose a generalization of the neutrosophic cubic soft set, introducing the concept of "neutrosophic cubic hyper soft set." Within this framework, we define internal and external neutrosophic cubic hypersoft sets, along with operations such as P-intersection, P-union, P-restricted union, P-extended intersection, P-OR operator, P-AND operator, R-intersection, R-union, R-restricted union, R-extended intersection, R-OR operator, R-AND operator, complement, and relative complement of neutrosophic cubic hyper soft sets. The study explores and presents relevant results, demonstrating the enhanced capability of …

Application Of Multi-Criteria Decision Analysis For Quantifying Responsibility In Ml-Based Intrusion Detection System, Mona Mohamed, Zekra Sakr

Neutrosophic Systems with Applications

With the swift growth in Internet of Things (IoT), certifying secure and trustworthy networks has turned to be a critical challenge, particularly as IoT devices are increasingly vulnerable to sophisticated cyberattacks. As a remedy, intelligent intrusion detection systems (IDS) evolved as promising solutions in recent years, but deciding on the appropriate model remains difficult because of competing performance and trustworthiness criteria. To this end, this paper explores a novel application of an ML-augmented decision-making framework to enhance security-related decision-making in IoT environments. The framework systematically evaluates and ranks ML-based IDS systems according to different evaluation criteria with distinct trade-offs, including …

Compact Heterogeneous Architectures And Algorithmic Methods For Enhanced Real-Time Digital True Time Delay Beamforming And Radar Applications, Nathan Lynn Burnett

Theses and Dissertations

Modern radar and signal processing systems require efficient computational architectures to handle increasing data rates while still being able to maintain dynamic configurability and complex tasks. This thesis presents and explores hardware and algorithmic approaches addressing these demands across several different applications. First, a low-cost tracking platform and architecture for unmanned aerial vehicles (UAVs) is developed, which provides detection and tracking capabilities, compliant with new FAA remote ID regulations. Second, a GPU-FPGA based digital true time delay beamformer is implemented to achieve real-time wideband radio frequency interference (RFI) mitigation. Specifically this beamformer explores weight calculation and calibration through particle swarm …

Versatile Waveform Generation And Clocking Techniques For Rfsoc-Based Digital Designs, Michael David Jones

Theses and Dissertations

Within an ever-evolving radio-frequency (RF) environment, designers are required to adapt systems to increasingly constricted parameters. The available tools continually grow to match this need, but so does the complexity in using them. The radio-frequency system-on-chip (RFSoC) is an innovation that combines a field-programmable gate array (FPGA) with an integrated RF chain. Designing with an RFSoC allows for high-precision data transmission, sampling, and processing, but it can be difficult and time-consuming to develop specialized circuits. The open-source CASPER project aims to provide a library of abstracted block-design components to simplify the design process. An arbitrary waveform generator (AWG) is created …

Accelerating Gnn Inference On Multi-Core Systems, Binglin Ji

McKelvey School of Engineering Graduate Student Theses & Dissertations

Graph Neural Networks (GNNs) are becoming increasingly popular, with their applications expanding across diverse domains. As the scale of graph data continues to grow, including larger numbers of nodes, edges, and higher embedding dimensions, standardized libraries such as DGL and PyG have been developed to facilitate GNN computation. However, with the rapid increase in the number of processor cores and the evolution of multi-core architectures, these libraries often show poor scalability and fail to execute GNN inference efficiently on the latest multi-core systems, particularly those with upwards of a hundred cores. To address this limitation, we present FGI, a Fast …

Land8fire: A Complete Study On Wildfire Segmentation Through Comprehensive Review, Human-Annotated Multispectral Dataset, And Extensive Benchmarking, Anh Tran, Minh Tran, Esteban Marti, Jackson Cothren, Chase Rainwater, Sandra Eksioglu, Ngan Le

Electrical Engineering and Computer Science Faculty Publications and Presentations

Early and accurate wildfire detection is critical for minimizing environmental damage and ensuring a timely response. However, existing satellite-based wildfire datasets suffer from limitations such as coarse ground truth, poor spectral coverage, and class imbalance, which hinder progress in developing robust segmentation models. In this paper, we introduce Land8Fire, a new large-scale wildfire segmentation dataset composed of over 20,000 multispectral image patches derived from Landsat 8 and manually annotated for high-quality fire masks. Building on the ActiveFire dataset, Land8Fire improves ground truth reliability and offers predefined splits for consistent benchmarking. We evaluate a range of state-of-the-art convolutional and transformer-based models, …

Satellite Passive Ranging Metasurface Optics For Space Rendezvous And Proximity Operations, Zachary Coppens, Cameron Vo, Addison Long, Jeremy Harris

Space Dynamics Laboratory Publications

SDL Presentation on Satellite Passive Ranging Metasurface Optics for Space Rendezvous and Proximity Operations

How Low A Colorado River Flow To Go? Insights From Numerically Stabilizing Lake Powell And Lake Mead During Crisis, David Rosenberg, Anabelle Myers, Motasem Abualqumboz, Erik Porse

Civil and Environmental Engineering Faculty Publications

Colorado River users are now discussing dividing river flow on a percentage basis (Fleck, 2025; Hager, 2025, Winslow, 2025). This is an important step to managing a declining and more volatile supply. In our prior May 2025 post, we shared a strategy we have worked on for several years— division of river flow—as one of 13 reasons why we have hope for consensus on Colorado River management. In this post, we address the question: How extreme low river flow and reservoir storage should we plan for going forward (Figure 1)? We also share our insights from numerically stabilizing and recovering …

High Temperature In Potato: Plant Responses And Adaptive Cultivation Strategies To Increase Production, Siska Rahmayani Gultom, Jajang Sauman Hamdani, Kusumiyati

Jurnal Kultivasi

Climate change, with global temperatures rising by 1.09°C from 1850–1900 to 2011–2020, threatens potato production, a critical staple crop, by exceeding the optimal temperature range of 15–20°C. This review synthesizes over 45 peer-reviewed studies published between 2015 and 2025 from Google Scholar and ScienceDirect to evaluate the physiological, morphological, and tuber quality responses of potatoes to high temperatures and to identify adaptive cultivation strategies for sustainable production. High temperatures reduce photosynthetic efficiency through chlorophyll degradation and stomatal closure, increase respiration, and divert photosynthates to vegetative growth, leading to 18–32% yield losses globally by the 2050s. Heat-tolerant varieties, such as Atlantic …