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Assessment Of Heavy Metal Contamination In Surface Water Near Tailings Dam, Gera Techane Mengistu, Tesema Kebede, Enatfenta Melaku, Engdasew Temere

Journal of Sustainable Mining

Elevated levels of heavy metals in surface water can lead to the degradation of water quality, especially in mining areas where tailing dams are sources of heavy metal pollution. This study focuses on evaluating the concentrations of heavy metals in surface water near the Legadembi tailings dams. The mean concentrations (in µg/L) of various heavy metals including: arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), mercury (Hg), molybdenum (Mo), nickel (Ni), lead (Pb), antimony (Sb), selenium (Se), thallium (Tl), uranium (U), vanadium (V), tungsten (W), zinc (Zn), and zirconium (Zr) were determined: 79.7, 0.15, 162.3, 0.66, 18.1, 0.01, …

Toward Sustainable Water Security: A Novel Assessment And Recharge Strategy For North Bekaa Plain, Rida Tadmouri, Amin Shaban, Mohamad Soliman

BAU Journal - Science and Technology

The demand for water in the northern Bekaa Plain is of utmost significance, especially given the substantial portion of land dedicated to irrigated agriculture. Additionally, the region experiences population growth, further exacerbating the water supply challenge. Understanding the groundwater potential zones and identifying appropriate recharge areas are crucial steps towards sustainable water resource management. The study focuses on reaching the best solutions for the study area, by utilizing advanced Geographic Information System (GIS) tools, including overlying slope, rainfall, lithology, attitude, soil, fracture, and stream maps, a Groundwater Potential (GWP) map was generated using ArcGIS. This map serves as a valuable …

Ai In Society: A Regulatory Framework For Responsible Integration, Ziad Doughan, Sari Itani, Hadi Al Mubasher

BAU Journal - Science and Technology

This review paper studies the influence of Artificial Intelligence (AI) and Machine Learning (ML) on society in various categories in detail. AI and ML have developed rapidly in the past two decades, thus changing our lifestyles. These developments have various positive and negative impacts on society. This paper explores the many societal impacts of AI and ML, in economics, social aspects, ethics, and policy, shedding light on the opportunities and challenges that arise. An interdisciplinary insight is capable of understanding the challenges society faces when it uses AI and ML, locking opportunities that lie ahead and identifying promising paths towards …

Universal Sound Separation: Distance-Aware Mixture Simulation, Co-Occurrence Conditioning, And Chain-Of-Inference, Wonjun Park

Computer Science and Engineering Theses - Archive

Universal Sound Separation (USS) -- the task of disentangling arbitrary sound sources from a single-channel acoustic mixture -- remains an open challenge due to the ill-posed nature of the problem and the distributional gap between synthetic training data and real-world recordings. This thesis addresses three distinct bottlenecks in the USS pipeline: training data realism, inference strategy, and conditioning richness. We first present two knowledge-guided approaches to sound source separation. The first is a distance-aware mixing strategy that leverages Large Language Models (LLMs) to assign plausible loudness relationships between audio sources during training data synthesis. By querying an LLM about the …

Mechanistic Auditing Of Privacy Retention In Llm Summarization, Samreen Begum

Computer Science and Engineering Theses - Archive

Anonymized summarization aims to produce useful summaries while replacing person names with placeholders such as [PERSON]. In practice, privacy is often evaluated by checking that no real names appear in the generated text. However, suppressing a name in the output does not guarantee that the model has removed identity information from its internal computation. This gap is critical in collaborative inference frameworks, where intermediate internal states (ISs) are exposed for safety auditing. We study this question in a controlled setting where a language model reads a document containing a real name and is required to generate a summary that replaces …

Study Of Clustering Technique And Communication Topologies For Cooperative Control-Based Volt-Var Optimization, Gaurav Yadav, Yuan Liao, Dan M. Ionel

Electrical and Computer Engineering Faculty Publications

Introducing renewable distributed generation (DG) in the power distribution system causes rapid voltage fluctuations due to its intermittency. This intermittency renders conventional voltage regulation devices such as on-load tap changers (OLTCs) and capacitor banks (CBs) inefficient to regulate rapid voltage changes and leads to reduced equipment lifetime and high operation and maintenance costs. Hence, this calls for non-conventional methods to mitigate such voltage fluctuations. This paper presents a cooperative control-based method aimed to optimally control the reactive power of DG inverters to mitigate the voltage deviations by establishing communication among the DG nodes, and between DG and non-DG nodes. This …

Electromagnetic Formation Flying Using Alternating Magnetic Field Forces And Control Barrier Functions For State And Input Constraints, Sumit Suryakant Kamat, Thomas Michael Seigler, Jesse B. Hoagg

Mechanical Engineering Faculty Publications

This article presents a feedback control algorithm for electromagnetic formation flying with constraints on the satellites’ states and control inputs. The algorithm combines several key techniques. First, we use alternating magnetic field forces to decouple the electromagnetic forces between each pair of satellites in the formation. Each satellite’s electromagnetic actuation system is driven by a sum of amplitude-modulated sinusoids, where amplitudes are controlled in order to prescribe the time-averaged force between each pair of satellites. Next, the desired time-averaged force is computed from an optimal control that satisfies state constraints (i.e., no collisions and an upper limit on intersatellite speeds) …

Elli’S Liquid Flow In A Wavy Channel With Slip Effect, Wall Properties, And Heat Transfer, P. Devaki, Yatin Sood

Mansoura Engineering Journal

The dual behavior of Elli’s fluid motivated us to work on it. The fluid behaves as both Newtonian/ non-Newtonian based on the low and high shear rates, respectively. The paper focused on the flow of Ellis fluid in a peristaltic channel with wall properties and heat transfer. The channel is symmetric in nature, and slip conditions are considered near the elastic walls. The governing equations of the flow are solved analytically using suitable boundary conditions, which yield velocity and temperature functions. The novelty of the paper is to analyze the nature of Newtonian/non-Newtonian fluids under the same conditions so that …

High-Speed Non-Pneumatic Tire (Npt) Design For Speeds Above 60 Mph, Jacob Grams, Brady Maurer, Jake Groewa

Williams Honors College, Honors Research Projects

This project focuses on developing a high-speed non-pneumatic tire (NPT) capable of safely operating at speeds greater than 60 mph, a performance range where most existing airless tire designs fail due to structural instability and performance limitations. The objective of this work is to design, analyze, and prototype a structurally optimized honeycomb-based tire structure with improved load distribution, deformation control, and durability. Multiple geometries were evaluated using finite element analysis (FEA) to assess stress and maximum resultant (total) displacement behavior under loading conditions, and a material selection study was performed to identify a suitable material for the design. The final …

Yk-4-250, A Synthetic Telmisartan-Tempol Conjugate: Crystal Structure Of A Stabilized Free Radical Containing An Angiotensin At₁ Receptor Inhibitor, Simon Friedrich, Yali Kong, Faik N. Musayev, Milton L. Brown, B. Frank Gupton

Department of Biomedical and Translational Sciences Faculty Publications

We report the first crystal structure of the telmisartan-tempol conjugate 2,2,6,6-tetramethyl-1-(λ'-oxidaneyl)piperidin-4-yl 4'-[(1,7'-dimethyl-2'-propyl-1H,3'H-[2,5'-bibenzo[d]imidazol]-3'-yl)methyl]-[1,1'-biphenyl]-2-carboxylate free radical (YK-4-250, C₄₂H₄₆N₅O₃), a dual-function inhibitor designed to target both the angiotensin II type 1 receptor (AT₁R) and reactive oxygen species (ROS). Structural analysis reveals a unique crystal architecture in which the nitroxide radical is stabilized within a sterically protected environment while preserving the telmisartan pharmacophore essential for high-affinity receptor antagonism. YK-4-250 is a novel small-molecule conjugate of telmisartan and tempol that incorporates a catalytic stabilized nitroxide radical and was rationally designed to mitigate gastrointestinal acute radiation syndrome (GI-ARS).

Deep Learning-Based Co-Current Upward Gas-Liquid Two-Phase Flow Regime Identification In An Annular Conduit, Joshua Robert Macomber

Graduate Theses, Dissertations, and Problem Reports (ETD)

Flow regime identification in co-current upward gas-liquid flow through annular conduits remains a significant challenge in petroleum engineering, with major safety and operational implications. It is also important across industries involving the transport of multiphase fluids. Misidentifying flow regimes can introduce major operational risk, yet regime boundaries in annular gas-liquid flow are often visually complex and context dependent.

The objective of this study was to evaluate the utility of convolutional neural network (CNN) classifiers for flow regime identification. The CNN was trained using annular flow image dataset published by Texas A&M University. The dataset consists of approximately 947 RGB images …

Comprehensive Evaluation Of Co₂ Eor Numerical Modeling In The Clinton Sandstone Of The Appalachian Tri-State Region Using Compositional Reservoir Simulation (Cmg Gem), Bushra Aref Alqattan

Graduate Theses, Dissertations, and Problem Reports (ETD)

ABSTRACT

The Clinton Sandstone of the Appalachian Basin represents a mature hydrocarbon-producing formation with potential for carbon dioxide (CO₂) enhanced oil recovery (EOR). This study develops a compositional reservoir simulation model using the CMG software suite (WinProp, Builder, and GEM) to evaluate the performance of CO₂ injection in improving oil recovery within the Clinton formation.

A three-dimensional reservoir model was constructed using representative geological and petrophysical properties consistent with those of the Clinton Sandstone. Fluid behavior was modeled using a compositional equation-of-state (EOS) approach to accurately capture phase behavior, miscibility development, and CO₂–oil interactions under reservoir conditions. Injection scenarios were …

Comparative Evaluation Of Deep Learning Models: Resnet18, Minivgg, And Yolov8 For Five-Class Blood Cell Classification, Keita Sakurai

Master's Theses or Doctor of Nursing Practice

Accurate classification of blood cell types is a critical task in automated hematological analysis. This study presents a comparative evaluation of three deep learning architectures, ResNet18, MiniVGG, and YOLOv8, for five-class blood cell image classification. To ensure a fair comparison, all models were trained under standardized conditions, including a consistent 90:10 training–validation split, controlled dataset size, and fixed training epochs. ResNet18 was trained to establish a baseline using residual learning. MiniVGG employed a compact VGG-inspired design with regularization to balance efficiency and accuracy, while YOLOv8 leveraged a lightweight, pretrained classification backbone with integrated data augmentation. Experimental results demonstrate a clear …

Investigation Of Factors Influencing Electric Vehicle Adoption In Indonesia: Ev Owners’ Perspectives, Desrina Yusi Irawatia, Nur Aini Masruroh, Nur Mayke Eka Normasari

ASEAN Journal on Science and Technology for Development

Electric vehicle (EV) uptake in Indonesia remains markedly below policy benchmarks. This study applies the Unified Theory of Acceptance and Use of Technology version 3 (UTAUT3), an extension of UTAUT2 that incorporates personal innovativeness as an additional construct to examine its impact on both behavioral intention and actual EV adoption within the Indonesian context. Unlike studies that typically survey the general public, this study focuses on actual EV users and owners, providing more representative and responsive insights into real-world EV usage. A total of 208 respondents participated, with 135 from the Jabodetabek area and 73 from Surabaya. The UTAUT3 framework …

A Deep Neural Approach To Network-Based Obfuscated Malware, Meera Parmar, Sunil Gautam

ASEAN Journal on Science and Technology for Development

The rising prevalence of obfuscated malware poses a critical threat to network security, undermining traditional detection methods and jeopardizing data integrity and system reliability in an increasingly connected world. This growing danger highlights the urgent need for advanced solutions to protect against evolving cyber risks. This research intro-duces a novel framework to enhance malware detection, employing a hybrid architecture that integrates spatial and temporal analysis with attention mechanisms. The approach leverages a large dataset subsample, focusing on key feature selection and augmentation to improve robustness against evasion techniques. This innovative framework offers a significant advancement in identifying malicious network traffic, …

Part Ii: Industrial Information Integration Review 2020-2025, Jinzhi Li

Information Technology & Decision Sciences Faculty Publications

Industrial Information Integration Engineering (IIIE) has become increasingly essential for improving operational efficiency and harmonizing heterogeneous industrial systems through advanced digital integration approaches. Fueled by rapid advancements in Industry 4.0 technologies—including digital twins, artificial intelligence, immersive interfaces, and IoT infrastructures—IIIE is substantially transforming traditional enterprise architecture and integration frameworks. This systematic review synthesizes recent developments and emerging trends, with particular attention to the accelerating adoption of digital twins and the deepening convergence between operational technologies (OT) and information technologies (IT) across multiple sectors. While notable progress has been made, significant challenges persist, especially in developing resilient integration architectures and fully …

When Words Flow Like Water: How The Enbridge Line 3 Pipeline Environmental Impact Statement Failed To Prevent Hydrogeologic Harm In Minnesota, Carly Gutzmann

Journal of Earth and Life Science

For the aquifers of Minnesota, the environmental impact statement (EIS) was a promise of protection that never left the page. An environmental impact statement is meant to be an aid in the decision making process in order to ensure that projects consider potential environmental harms that may occur. However, they are often used instead as another regulatory box to check, rather than as active considerations when planning. As such, a project plan can be flawed from the start—if project developers only consider environmental impacts after they have already put considerable time, effort, and funding into their project as-is, they may …

Measuring The Impact Of 3d Printers On The Health Of Youth, Alexis Kostin, Olla Obeid, Oz Trost

Wetterhahn Science Symposium Posters

3D printers are used more widely than ever before; they can be found in factories, hospitals, and even schools. However, the health effects of the VOCs and UFPs that these machines emit have yet to be fully understood. In collaboration with the University of Nevada, Las Vegas, this study utilizes an Air Gradient One sensor at the Diamond Lab to monitor VOC and UFP emissions before, during, and after 3D printing sessions. By comparing these levels to EPA and CDC safety standards, we aim to quantify the respiratory risks posed to youth.

Numerical And Machine Learning Based Recreation Of Damage Morphologies Of Barely Visible Impact Damage, Oscar A. Valdez

Mechanical and Aerospace Engineering Dissertations

Composite laminates are highly sought after in the aerospace industry as they provide strength without dramatically increasing the weight of manufactured structures. However, composite laminates are susceptible to barely visible impact damage caused by routine activities. This type of damage can easily go unnoticed while significantly reducing the load-carrying capability of the laminate. Current non-destructive evaluation techniques, such as ultrasonic scanning, can reveal the damage footprint but provide no insight into delamination through-the-thickness due to the shadowing effect. Micro-computed tomography offers ply-by-ply damage resolution but is unsuitable for field inspections and is constrained by specimen size. This study aims to …

Set-Theoretic Reachability-Informed Model Predictive Control For Mechanical And Aerospace Systems, Jinaykumar Nitinkumar Patel

Mechanical and Aerospace Engineering Dissertations

Modern mechanical and aerospace systems increasingly operate autonomously in environments characterized by nonlinear dynamics, uncertainty, and safety constraints. In these settings, estimation and control methods based on nominal models and single-point trajectory predictions are usually insufficient to ensure safe and reliable operation. This dissertation uses a set-theoretic perspective, in which the system state, uncertainty, and admissible behavior are described by sets instead of point estimates. The key question is not only what the state is, but what set of states remains consistent with the dynamics, disturbances, control limits, and available measurements. This provides bounded descriptions of uncertainty and supports control …

Forcing A Molecule To Switch: Quantifying Mechanical Control At The Atomic Scale, A. M. Shashika D. Wijerathna, Markus Zirnheld, Michael L. Hildebrand, Myles Perry, Marjorie Cenese, Yuan Zhang

Physics Faculty Publications

Mechanically induced conformational switching at the single-molecule level represents a fundamental mechanism for molecular functionality, yet quantitative characterization of the underlying force and energy landscape remains limited. Here, we study individual TBrPP-Co(II) molecules on Au(111) using qPlus atomic force microscopy. By reconstructing interaction potentials from 3D Δf(x,y,z) data, we determine a threshold force of ∼96 ± 8 pN and a tip-induced switching interaction energy of ∼38 ± 4 meV associate with the conformational transition. The isolated tip-molecule force follows a power law (exponent ∼6), indicating dominance of long-range van der Waals interactions. …

Beyond The Honeypot: Increasing Adversarial Cognitive Load Through Interactionless Cyber Deception, Marcus Rozier, Connor Dedic, Ted Mcdaniel, Hadley Westover

Space Dynamics Laboratory Publications

Traditional cyber deception mechanisms, such as honeypots and honey-tokens, typically rely on adversary interaction to trigger alerts and provide defensive value. This paper introduces the concept of interactionless deception—a defensive paradigm focused on the strategic manipulation of the environment to disrupt the cyber kill chain without requiring direct engagement. By utilizing a greedy top-k selection method to analyze MITRE ATT&CK® data across 178 Advanced Persistent Threat (APT) groups, this research identifies seven high-frequency sub-techniques that represent common attacker behavior. To counter these, the authors developed a series of proof-of-concept tools, including deceptive web proxies, simulated command-and-control (C2) beacons, and …

A Low Noise, High Qe, Large Format Ccd Camera System For The Nasa Mighti Instrument, Jed Hancock, Joel Cardon, Mike Watson, James Cook, Mitch Whiteley, James Beukers, Chris Englert, Charlie Brown, John Harlander

Space Dynamics Laboratory Publications

Outline

• MIGHTI Instrument Overview and Configuration
• Camera System Block Diagram
• Flight Camera Heads, Electronics Box, and CCDs
• CCD Testing at e2v
• AI&T at the Space Dynamics Lab
• Electro-Optical Characterization and Performance Results
• Conclusions

Assessment Of Soybean Response To Irrigation Variability In Eastern Nebraska Using The Aquacrop Model, Anmol Singh, Saleh Taghvaeian, Yufeng Ge, Derek M. Heeren, Frank Bai

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Soybean [Glycine max (L.) Merr.] is a major irrigated crop in eastern Nebraska, where recent expansions in irrigated agriculture and projected trends in irrigation demand necessitate thorough investigations of approaches that can optimize its irrigation management. In this study, the AquaCrop model was calibrated and validated using 19 variable irrigation treatments from a five-year field experiment. The model accurately simulated canopy cover, soil water content, and grain yield, with validation normalized root mean square error (nRMSE) of 12%, 7%, and 7%, respectively. The model was subsequently applied to estimate soybean yield and water requirement during a 15-year period (2010–2024) …

End-To-End Development And Experimental Validation Of A 1/10-Scale Autonomous Vehicle, Rikkin Pankaj Panchal

Electrical Engineering Theses

Autonomous vehicle development demands vast resources, making scaled down platforms a critical alternative for solving core algorithmic challenges. The primary contribution of this thesis is the end to end development and validation of a complete real time autonomous driving pipeline deployed on a one tenth scale vehicle. To streamline platform development, an AI assisted annotation framework automates dataset generation, significantly reducing manual labor while improving training data quality. The system perception stack features a reinforcement learning guided online multi camera calibration framework that enables adaptive surround view stitching without the need for offline recalibration. This is paired with robust lane …

Data-Driven Optimization Of Memory Effects And Critical Components In Cascading Failure Interaction Networks, Md Farhan Tanvir

Electronic Theses and Dissertations

Cascading failures are a major concern for modern power systems‚ where a small failure can cascade through the network to create a large blackout. Because such an event could have catastrophic economic and social costs it is important to understand cascading failures‚ how to model them‚ and the possibility of reducing them. In this thesis‚ we develop a data-driven framework based on actual utility outage data to model and reduce cascading failures. The proposed methodology is based on generation-dependent interaction models and in this study interaction matrices obtained from historical outage events are used to describe the interaction between generations. …

Computational Modeling Of Biophysical Transport: Respiratory Drug Delivery And Tissue-Level Physics, Md Tariqul Hossain

Electronic Theses and Dissertations

The nasopharynx, the upper part of the pharynx located at the back of the nose serves as a critical hotspot for initial respiratory infections via inhaled transmission, largely due to the presence of specific surface receptors that pathogens can exploit for cell invasion, combined with a relatively sparse local mucociliary substrate. To enhance the therapeutic efficacy against certain pathogens, such as the SARS and Influenza viruses, it is therefore essential to improve the targeted delivery of drugs to the nasopharynx. This study explores the use of intranasal sprays as a method for drug administration and models the transport of sprayed …

Effects Of Matched Freespace And Wall Damping On Stiffness Perception, Madeleine Toland, M Bourgeois, Emma Treadway

Engineering Faculty Research

Stiffness perception has previously been shown to be influenced by damping. This work addresses open questions about what damping conditions are best for enabling classification of virtual walls by their stiffness. Through a forced-choice classification experiment with 12 participants, we found that the highest mean classification performance (in terms of both information transfer and percent correct responses) occurred when freespace damping matched wall damping, rather than being higher or lower. However, statistically significant differences did not appear between the closest damping values employed, suggesting that the effects do not become pronounced until the damping is quite mismatched.

Work In Progress: The Impact Of Classroom Interventions On Student Success And Retention In Electric Circuits, Cherian Mathews

All Faculty Articles - School of Engineering and Computer Science

University of the Pacific has embarked on a university-wide endeavor to improve student success and retention. This effort involves academic coaches being placed in each unit, early grade reporting in the fifth week of the semester, follow-ups by faculty advisors and academic coaches for struggling students, and documentation of interactions with such students in the university CRM system. These follow-ups with students typically involve conversations to explore factors contributing to poor performance (e.g., health issues, excessive work hours, study skills), suggesting approaches to improve performance, and making referrals to care teams and supplemental instruction. Despite all these efforts, DFW rates …

Ai For Life Sciences: From Geometric Protein Modeling To Multimodal Drug Design, Feng Jiang

Computer Science and Engineering Dissertations

Predicting biomolecular interactions, from immune recognition to drug–target binding, is a central problem in the life sciences and computational drug discovery. Deep learning has advanced this area, yet three challenges persist: the topology of large, highly imbalanced interaction networks; structural noise in computationally predicted protein models; and the integration of multimodal information such as functional text and taxonomic annotations. This dissertation develops a coherent set of models spanning immune complex prediction and small-molecule drug design: graph learning that addresses network topology and severe class imbalance; a noise-tolerant method that fuses predicted structures with evolutionary sequence features; and multimodal representation learning …