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Articles 7951 - 7980 of 195925

Full-Text Articles in Engineering

Deformation And Earthquake Potential On The North America - Caribbean - Cocos Triple Junction In Guatemala, Jeremy Maurer, Andreas Eckert, Qiaoqi Sun, Jonathan Obrist-Farner Jul 2025

Deformation And Earthquake Potential On The North America - Caribbean - Cocos Triple Junction In Guatemala, Jeremy Maurer, Andreas Eckert, Qiaoqi Sun, Jonathan Obrist-Farner

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

The triple junction between the Cocos (CO), North American (NA), and Caribbean (CA) tectonic plates in Guatemala is a region of high seismic risk and includes many large faults and historic earthquakes. Previous analyses of the tectonic system have been overly simplified, resulting in discrepancies between geologically derived and geodetic models of fault slip rate. This study leverages available geodetic, seismic, and geologic data to develop new strain rate maps and faulting models for the region. We find that locking on the regional faults matches historic reports of large earthquakes and that multiple minor fault segments are active and accommodate …

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Efficient Small Tool Detection In Construction Via Lightweight Deep Neural Networks, Maryam Soleymani Jul 2025

Efficient Small Tool Detection In Construction Via Lightweight Deep Neural Networks, Maryam Soleymani

LSU Master's Theses

Construction sites are dynamic and inherently hazardous environments, where small hand tools—although essential—pose serious safety risks due to their frequent use, portability, and tendency to be misplaced or dropped. This study introduces a novel and lightweight deep learning-based architecture, Lightweight Small Tool Detection (LSTD), specifically designed for fast detection of small tools in unstructured and challenging construction environments. Recognizing that small object detection remains a persistent limitation in existing computer vision models, particularly under poor lighting or cluttered backgrounds, LSTD integrates advanced modules for enhanced feature extraction, fusion, and classification. It achieves notable improvements in accuracy, recall, and computational efficiency …

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Cost-Effective Automated Uhi Mapping With Ai: A Case Study Of A Scalable Framework For Climate Equity In San José, California, Martin Alvarez Lopez Jul 2025

Cost-Effective Automated Uhi Mapping With Ai: A Case Study Of A Scalable Framework For Climate Equity In San José, California, Martin Alvarez Lopez

Master's Theses

Urban areas experience the Urban Heat Island (UHI) effect, with higher temperatures than rural areas, disproportionately impacting low-income communities. Mapping UHIs is a process that usually requires significant amount of human resources, and is not scalable. The lack of accurate and detailed UHI maps makes it difficult for decision makers to design effective mitigation strategies. In this work we introduce a cost-effective, scalable, and universally applicable UHI mapping framework that leverages open-source data and AI-driven feature extraction from remote sensing imagery. Using various causative factors such as city characteristics, anthropogenic heat, city canyons, and meteorological variables, we create UHI maps …

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Quantization On Graph Neural Networks For Image Classification, Rithik Reddy Katpally Jul 2025

Quantization On Graph Neural Networks For Image Classification, Rithik Reddy Katpally

Master's Theses

Quantization has become a key approach for reducing storage and computational demands of deep neural networks while maintaining high accuracy. Although 8-bit quantization is well-established for convolutional architectures such as ResNet50 and MobileNetV2, its application to graph-based vision models remains underexplored. In this work, we extend quantization-aware training to Vision Graph Neural Networks (ViGs) and conduct comparisons with quantized CNNs on the CIFAR-100 dataset. To ensure parity, all models have same training hyperparameters such as learning rate, batch size, optimizer, number of epochs. We used numerous techniques to preserve performance for low-bit precision. First, Pauta Quantization clips activation outliers based …

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Stead: Spatio-Temporal Efficient Anomaly Detection For Time And Compute Sensitive Applications, Andrew Gao Jul 2025

Stead: Spatio-Temporal Efficient Anomaly Detection For Time And Compute Sensitive Applications, Andrew Gao

Master's Theses

This paper presents a new method for anomaly detection in automated systems with time and compute sensitive requirements, with unparalleled efficiency. As these systems become increasingly popular, ensuring their safety has become more important than ever. Therefore, this paper focuses on how to quickly and effectively detect various anomalies in the aforementioned systems, with the goal of making them safer and more effective. Many detection systems have been developed with great success under spatial contexts; however, there is still significant room for improvement when it comes to temporal context. While there is substantial work regarding this task, there is minimal …

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Using Facial Recognition For Selective Pose Detection, William J. Parker Jul 2025

Using Facial Recognition For Selective Pose Detection, William J. Parker

Master's Theses

Pose detection involves locating and identifying key body points for all individuals within a frame. This enables the ability to convert the pose into a digital format, which can then be recorded and analyzed for a variety of purposes. Advancements in the field have already opened applications in areas such as digital fitness coaches, fall detection, and virtual reality. Existing approaches primarily focus on tracking all detected individuals, which limits the practical applications when attempting to analyze a single or specific subject when there are other people in frame. Previous work has discussed integrating identification, but these approaches use identification …

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Quantum Algorithm Emulation Using Fpgas, Samuel Petruescu Jul 2025

Quantum Algorithm Emulation Using Fpgas, Samuel Petruescu

Master's Theses

Field Programmable Gate Arrays (FPGAs) have been used in most of the physics sub-fields for various unique purposes. This includes particle physics, quantum optics, and, more recently, quantum computing. FPGAs boast many benefits over previous experimental and computational setups. They are versatile, easy to program, and cost-effective, leading to an understandable desire to incorporate them into the new field of quantum computing. While FPGAs have been used to help control the readout and control of physical qubits, they can also be a good tool for improving algorithm simulations, which is the focus of this paper. Different algorithms have different computational …

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Sirilla: Predicting Traffic Flow Via Stacked Decentralized Federated Learning, Andrew Selvia Jul 2025

Sirilla: Predicting Traffic Flow Via Stacked Decentralized Federated Learning, Andrew Selvia

Master's Theses

Billions of people today rely on traffic predictions to optimize their travels. Digital mapping services deliver accurate predictions by learning from vast troves of historical data. Impressive as these systems are, their assumptions do not always apply. They depend on an endless flow of sensitive user data to a central authority, a stable Internet connection, and trustworthiness on both sides of the traditional client-server model. This thesis explores a novel architecture which bucks those assumptions. In the proposed model, traffic data remains on edge devices which individually train models via federated learning. Beyond the obvious privacy benefits, this architecture enables …

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Uptake, Distribution, And Activity Of Pluronic F68 Adjuvant In Wheat And Its Endophytic Bacillus Isolate, Anthony Cartwright, Mohammad Zargaran, Anagha Wankhade, Astrid Jacobson, Joan E. Mclean, Anne J. Anderson, David W. Britt Jul 2025

Uptake, Distribution, And Activity Of Pluronic F68 Adjuvant In Wheat And Its Endophytic Bacillus Isolate, Anthony Cartwright, Mohammad Zargaran, Anagha Wankhade, Astrid Jacobson, Joan E. Mclean, Anne J. Anderson, David W. Britt

Biological Engineering Student Research

Surfactants are widely utilized in agriculture as emulsifying, dispersing, anti-foaming, and wetting agents. In these adjuvant roles, the inherent biological activity of the surfactant is secondary to the active ingredients. Here, the hydrophilic non-ionic surface-active tri-block copolymer Pluronic® F68 is investigated for direct biological activity in wheat. F68 binds to and inserts into lipid membranes, which may benefit crops under abiotic stress. F68’s interactions with Triticum aestivum (var Juniper) seedlings and a seed-borne Bacillus spp. endophyte are presented. At concentrations below 10 g/L, F68-primed wheat seeds exhibited unchanged emergence. Root-applied fluorescein-F68 (fF68) was internalized in root epidermal cells and …

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Mechanical Properties And Temperature Resistance Of Fly Ash-Based Geopolymer Concrete, Hala Emad Elden Fouad, Mohamed I. Serag, Ahmed Ragab, Abdelrahman Hussein Jul 2025

Mechanical Properties And Temperature Resistance Of Fly Ash-Based Geopolymer Concrete, Hala Emad Elden Fouad, Mohamed I. Serag, Ahmed Ragab, Abdelrahman Hussein

Mansoura Engineering Journal

Global warming is pressing issue, primarily driven by increasing in greenhouse gas emissions with CO2 accounting for 64% of total emissions. It was founded that produce one ton of Ordinary Portland Cement (OPC) producing one ton of CO2. To address these issues, geopolymers derived from fly ash (FA) have been proposed as a superior alternative to cement. This research presents a comparative review of OPC and FA-based geopolymers in the context of CO2 sequestration. The research investigates the behavior of FA-based geopolymer cement, focusing on the influence of preparation conditions on its mechanical performance, bond strength, and the effect of …

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Structural Differential Privacy In Graph Neural Networks, Bibek Giri Jul 2025

Structural Differential Privacy In Graph Neural Networks, Bibek Giri

Master’s Dissertations

Graph Neural Networks (GNNs) have demonstrated impressive performance across a range of graph-based learning tasks. However, their application to domains with sensitive relational data raises serious privacy concerns, as the graph structure itself may leak confidential information. This thesis investigates a decentralized framework for enforcing edge-level local di!erential privacy (LDP) in graph-structured data. We introduce two mechanisms that perturb a node’s neighborhood in a privacy-preserving yet utility-aware manner. The first approach replaces randomly selected neighbors with feature-similar nodes from the 2-hop neighborhood, ensuring structural realism while preserving degree. The second approach eliminates the need for explicit 2-hop propagation and dummy …

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Investigating The Impact Of Agent Openness On Planning In Multi-Agent Systems, Bala Subramanyam Duggirala Jul 2025

Investigating The Impact Of Agent Openness On Planning In Multi-Agent Systems, Bala Subramanyam Duggirala

School of Computing: Dissertations, Theses, and Student Research

Multi-agent systems (MAS) possess significant potential for modeling real-world scenarios requiring coordinated actions (like wildfire fighting or ridesharing) among autonomous entities or agents (e.g., wildfire fighting agents) in complex, dynamic environments. Effective decision-theoretic planning (where each agent must carefully consider both the immediate and the future situations or states, and coordinate with the other agents (neighbors) to evaluate what needs to be done at present) within MAS, especially multiagent planning, where the planning agent directly models its neighbors in order to estimate their optimal actions, is critical, yet challenged by factors like partial observability, openness, and diverse agent types with …

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Shock Induced Droplet Aerobreakup For Newtonian And Non-Newtonian Fluids, James Leung Jul 2025

Shock Induced Droplet Aerobreakup For Newtonian And Non-Newtonian Fluids, James Leung

LSU Doctoral Dissertations

This research investigates shock-induced aerodynamic breakup (aerobreakup) of fluids with different stress-strain behaviors. The central hypothesis is that shear stress from highspeed gas flow manifests differently depending on a fluid’s strain response, influencing droplet breakup morphology, fragment size distribution, and drag-induced acceleration. To test this, experiments and simulations were performed on μm–mm sized droplets of Newtonian (water) and shear-thinning fluids (nanofluids or xanthan gum). Two experimental setups were used: an open-ended shock tube and a closed conventional shock tube. In the openended setup, a normal shock impacts a stationary droplet held by an acoustic levitator. Droplet breakup and gas dynamics …

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From Devices To The Cloud: Digital Forensics In The Changing Social Media Landscape, Joseph Brown Jul 2025

From Devices To The Cloud: Digital Forensics In The Changing Social Media Landscape, Joseph Brown

LSU Master's Theses

This thesis presents a comprehensive digital forensic analysis of emerging and alternative social media platforms, including Truth Social, Threads, Bluesky, Nextdoor, and Neighbors. These platforms, which range from politically aligned alt-tech networks to hyperlocal neighborhood apps, present unique forensic challenges and security vulnerabilities. Across all case studies, established forensic techniques were applied using a hybrid methodology combining mobile device analysis, network traffic monitoring, and API interrogation. Findings include the discovery of plaintext credentials, session tokens, and other sensitive artifacts, particularly in platforms with weaker security postures such as Truth Social, Bluesky, Nextdoor, and Neighbors. Threads, by contrast, demonstrated greater resilience …

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Dynamic Sparsification In Secure Gradient Aggregation For Federated Learning, Bikash Samanta Jul 2025

Dynamic Sparsification In Secure Gradient Aggregation For Federated Learning, Bikash Samanta

Master’s Dissertations

Secure aggregation is a critical component of privacy-preserving federated learning. However, existing fixed-sparsity approaches often incur unnecessary communication overhead. We present DynamicSecAgg, a novel framework that introduces dynamic sparsity while preserving coordinate-level privacy. Our method achieves significant improvements in communication efficiency while maintaining — and in some cases improving — model accuracy across both IID and non-IID user distributions. The framework maintains information-theoretic privacy guarantees via adaptive gradient thresholding and polynomial-based aggregation, proving particularly effective under heterogeneous data settings. These results establish dynamic sparsity as a key optimization for efficient and privacy-preserving federated learning.

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Cloud-Assisted Multi-Channel Data Broadcasting, Debabrata Maji Jul 2025

Cloud-Assisted Multi-Channel Data Broadcasting, Debabrata Maji

Master’s Dissertations

The convergence of Internet of Things (IoT) and cloud computing has transformed technology, impacting commerce, industrial production, data management, etc. Multi- Channel Broadcast Encryption (MCBE), first introduced by Phan et al. (ASIACCS 2013), is a cryptographic encryption primitive used for both IoT and Cloud that permits a sender to e!ciently and securely encrypt several messages for di”erent groups of receivers. After thoroughly exploring the existing literature, we observe that none achieves the robust provable security within the standard model. This paper addresses this gap, aiming to achieve adaptive INDistinguishable under full-IDentity Chosen-Ciphertext Attack (IND-ID-CCA) security by constructing an e!cient identity-based …

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Modeling The Influence Of Silicon Content On Electrochemical Performance Of Silicon-Graphite Blended Electrodes Considering Voltage Hysteresis, Mohamed Atwair, Paul T. Coman, Ralph E. White Jul 2025

Modeling The Influence Of Silicon Content On Electrochemical Performance Of Silicon-Graphite Blended Electrodes Considering Voltage Hysteresis, Mohamed Atwair, Paul T. Coman, Ralph E. White

Faculty Publications

Silicon, with its high specific capacity, is a highly promising material for lithium-ion battery anodes. To enhance durability, it is commonly combined with graphite in composite anodes. Despite this, the electrochemical dynamics between silicon and graphite are not yet fully understood. Modeling serves as an important tool for analyzing and improving batteries, but current models lack comprehensive representation of the coupled electrochemical and structural behavior of silicon-graphite blended electrodes. Herein, we present a comprehensive model for blended Si/Gr electrodes that incorporates the distinct properties and kinetics of each material. Our approach accounts for the dependence of electrode thickness and solid …

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Influence Of Zinc Oxide Nanoparticles On The Efficiency Of Oxytetracycline Removal From Wastewater Using Continuous Catalytic Ozonation, Sarmad Al-Anssari, Hassanain A. Hassan, Maha K. Mohsin, Ahmed A. Mohammed Jul 2025

Influence Of Zinc Oxide Nanoparticles On The Efficiency Of Oxytetracycline Removal From Wastewater Using Continuous Catalytic Ozonation, Sarmad Al-Anssari, Hassanain A. Hassan, Maha K. Mohsin, Ahmed A. Mohammed

Research outputs 2022 to 2026

Antibiotics must be fully eliminated before they are released into the environment. In most cases, conventional wastewater treatment systems are not built to handle polar microcontaminants such as antibiotics. Oxytetracycline (OTC) is one of these antibiotics, an environmental hazard contaminant in aqueous solutions. Therefore, an advanced treatment method is needed for wastewater contaminated with antibiotics. In this study, we employed zinc oxide nanoparticles (ZnO), and the catalytic ozonation procedure was employed to increase the ozonation efficiency. A continuous experiment was carried out to compare the effectiveness of catalytic and single ozonation in degrading OTC in a continuous reactor. The flow …

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Sbv_Dps: A Stacking-Bagging-Voting Nested Ensemble Based Diabetes Prediction System Using K-Fold Cross Validation, Sourabh Shastri, Sachin Kumar, Paramjit Kour, Vibhakar Mansotra Jul 2025

Sbv_Dps: A Stacking-Bagging-Voting Nested Ensemble Based Diabetes Prediction System Using K-Fold Cross Validation, Sourabh Shastri, Sachin Kumar, Paramjit Kour, Vibhakar Mansotra

Mansoura Engineering Journal

With the advancement of machine learning techniques, the introduction of the most accurate model has become a necessity. In real-world scenarios, every model has some constraints and assimilates errors, so their performance is not always highly efficient; this sparked the development of ensemble learning. The ensemble approach aims to consolidate the strengths of existing approaches and minimize their weaknesses or decision-making risks. The proposed diabetes prediction system encases a resampling filter, applied to balance the dataset and model builder method, i.e., without the SBV ensemble and with the SBV ensemble method. The model is initially built without using the SBV …

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Humanization Strategy Of The Public Urban Space In Cairo, Rania Badawy Shokry Jul 2025

Humanization Strategy Of The Public Urban Space In Cairo, Rania Badawy Shokry

Mansoura Engineering Journal

An accurate scientific definition of the term “humanization of cities” has not yet crystallized, which refers the term to the word from which it is derived. She is "human". Obviously, anything contrary to it is inhuman; starting from wild nature or a life entirely dependent on vehicles. If a person cannot dispense with vehicles when carrying out his daily activities, then here we know that the standard of humanization in a place is low. However, if the planning of a city or neighborhood takes into account the needs of the population and the human standard, then the city may reach …

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Multi-Party Key Establishment For Resource-Constrained Devices, Supriyo Banerjee Jul 2025

Multi-Party Key Establishment For Resource-Constrained Devices, Supriyo Banerjee

Master’s Dissertations

As the number of IoT (Internet of Things) devices continues to grow, ensuring secure communication among them has become increasingly important. Traditional pairing schemes rely on centralized architectures, which are vulnerable to temporary or permanent failures due to operational malfunctions of their central hubs or gateways. To address these challenges, decentralized communication is essential. However, existing decentralized pairing schemes suffer from high pairing times and significant computational overhead. Given the diverse capabilities of IoT devices, ranging from high-performance edge devices to resource-constrained sensors, many of these schemes become impractical in real-world scenarios. Therefore, we require a lightweight pairing scheme. Our …

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Turning Data Into Guardrails-Decoding Financial Vulnerability Through Behavioural Signs, Debanwita Hajra Jul 2025

Turning Data Into Guardrails-Decoding Financial Vulnerability Through Behavioural Signs, Debanwita Hajra

Master’s Dissertations

This report presents the work I did during my internship at Hongkong and Shanghai Banking Corporation (HSBC), Kolkata. As a financial institution, the strength of the bank is fundamentally rooted in the behavior and reliability of its customers. Understanding this behavior is not only desirable; it is essential for the security, risk mitigation and future strategic planning of the bank. To do this, banks must invest in a thorough analysis of the financial behavior of their customers to detect early signs of risk and act accordingly. I worked in the Finance Support Team within the Data and Analytics division, where …

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Peak Connection Strength Of Reduced Beam Section Moment Frame Connections, Jonathan T. Tshibanda Jul 2025

Peak Connection Strength Of Reduced Beam Section Moment Frame Connections, Jonathan T. Tshibanda

Theses and Dissertations

In the design of reduced beam section (RBS) moment frame connections, the peak connection strength factor (𝐶𝑝𝑟) is used to estimate the expected maximum moment at the reduced section in the capacity-based design of moment-resisting frames. Current design provisions in AISC 358-22 define C𝑝𝑟 as the average of the yield and ultimate strengths of the beam material divided by the yield stress, resulting in a standard value of 1.15 for A992 steel. However, experimental studies have often reported higher values, occasionally exceeding 1.40. This study reevaluates the 𝐶𝑝𝑟 factor using experimental data from 35 existing RBS tests specimens along with …

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Performance Analysis Of University Wifi Using 802.11e Information Elements, Douglas Christopher Hales Jul 2025

Performance Analysis Of University Wifi Using 802.11e Information Elements, Douglas Christopher Hales

Theses and Dissertations

Wireless networks, including IEEE 802.11 (WiFi), continue to become more important for many uses, including university classrooms. Factors that impact the performance of these networks have changed greatly over time, with increased scale at which they are used, and growing dependence of latency sensitive applications. In order to better understand the performance of current WiFi networks, a methodology was created to capture and analyze beacon frames with optional 802.11e information elements (IE), using Quality of Service enhanced Basic Service Set or QBSS load (channel utilization) and station count. This methodology is able to collect channel use more frequently than many …

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Modeling Self-Discharge In Li/S Batteries Through Electrochemical Anode Reactions: A Theoretical Perspective, Ralph E. White, Paul T. Coman Jul 2025

Modeling Self-Discharge In Li/S Batteries Through Electrochemical Anode Reactions: A Theoretical Perspective, Ralph E. White, Paul T. Coman

Faculty Publications

The growing demand for high-energy-density batteries has renewed interest in lithium–sulfur (Li/S) systems, which offer significant advantages but suffer from severe self-discharge during rest. While prior studies attribute this degradation to chemical parasitic reactions or polysulfide shuttling, they overlook the inherently electrochemical nature of anode-side processes. In this work, a 1D physics-based model of a Li/S battery was developed to explicitly incorporate lithium-metal oxidation and the stepwise electrochemical reduction of polysulfides at the anode. Using COMSOL Multiphysics, galvanostatic discharge followed by open-circuit rest under two conditions was analyzed - with and without parasitic anode reactions. The results show that when …

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Incorporating Industry-Standard Technical Writing Into A Materials Testing Laboratory, Caleb Levi Head Jul 2025

Incorporating Industry-Standard Technical Writing Into A Materials Testing Laboratory, Caleb Levi Head

Theses and Dissertations

The fluid analysis and materials testing laboratories are crucial for engineering students to learn experimental procedures and data interpretation. Engineers spend a significant portion of their workday on report writing, yet many feel their undergraduate education did not adequately prepare them for this task. At the University of Arkansas at Little Rock, students were given an industry-influenced lab report template to expand their knowledge of the necessary information required in technical writing, thereby teaching and improving their technical writing skills actively. These reports were evaluated qualitatively and quantitatively against previous submissions over two semesters in the mechanical engineering fluids and …

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Single-Step Conversion Of Metal Impurities In Cnts To Electroactive Metallic Nitride Nanoclusters For Electrochemical Co2 Reduction, Ahmed Badreldin, John Pellessier, Francisco Alejandro Ospina Acevedo, Siyuan Fang, Carter Racine, Jin Feng, Alvin Chang, Yulu Ge, Yang Gang, Shengyao Wang, Xiaokun Yang, Sergei Ivanov, Zhenxing Feng, Yun Hang Hu, Perla B. Balbuena, Ying Li Jul 2025

Single-Step Conversion Of Metal Impurities In Cnts To Electroactive Metallic Nitride Nanoclusters For Electrochemical Co2 Reduction, Ahmed Badreldin, John Pellessier, Francisco Alejandro Ospina Acevedo, Siyuan Fang, Carter Racine, Jin Feng, Alvin Chang, Yulu Ge, Yang Gang, Shengyao Wang, Xiaokun Yang, Sergei Ivanov, Zhenxing Feng, Yun Hang Hu, Perla B. Balbuena, Ying Li

Michigan Tech Publications

A novel single-step low-temperature pyrolysis method is developed to efficiently remove encapsulated Ni nanoparticles (NPs, 10–50 nm) from both regular-grade (< 5 wt.% metal impurities) and industrial-grade (< 10 wt.% metal impurities) carbon nanotubes (CNTs). This approach eliminates the need for conventional multi-step purification processes, which often involve high-temperature corrosive gas oxidation and acid washing. The new strategy transforms and redistributes encapsulated Ni-NPs into homogeneously sized nanoclusters (NCs, ≈1 nm) that are evenly dispersed on the surface of CNTs. Surface and bulk sensitive spectroscopic analyses reveal the predominant formation of Ni3N-NCs, along with some metallic Ni-NCs. The treated materials demonstrate exceptional electroactivity toward CO2 reduction to CO, with the best-performing CNT-PTFE-Mel-650 sample achieving an ultra-low onset overpotential of −19 mV and 98% CO selectivity in a current density range of 100–700 mA cm−2. This NC catalyst demonstrates 25% lower voltage at 700 mA cm−2 compared to the single atom catalyst (SAC) control. Experimentally verified ab initio molecular dynamics (AIMD) models are simulated, and subsequent density functional theory (DFT) calculations further support the thermodynamic stability of Ni3N-NCs and their favorability for CO2 reduction. This work establishes a new method for creating ligand-free electroactive NCs for efficient electrochemical reactions.

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A Descriptive Case Study On How Suburban Texas Police Department Drone Use Conforms To Public Opinion, Terrill Brett Spell Jul 2025

A Descriptive Case Study On How Suburban Texas Police Department Drone Use Conforms To Public Opinion, Terrill Brett Spell

Doctoral Dissertations and Projects

The purpose of this qualitative case study was to describe the use of drones by suburban police departments in Texas, and its central research question asked how that drone use aligns with what prior research found the public supports. The research design used a holistic multiple-case approach that involved interviewing police officers who use drones as part of their law enforcement responsibilities. Relevant theoretical frameworks were social contract theory, Packer’s theory on law enforcement, and evidence-based policing theory. Data collection involved semistructured interviews of 13 officers representing the same number of Texas suburban police departments. The data collected and analyzed …

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A Comprehensive Study Of Transportation Projects Impact In Congested Cities Through Travel Demand Modeling And Decision-Making Tools: A Case Study Of Zagazig City, Egypt, Amr M. Sakr, Metwally Gouda Mohamed Altaher, Mahmoud El-Saied Ali Solyman, Mohamed Ibrahim El-Sharkawi Attia Jul 2025

A Comprehensive Study Of Transportation Projects Impact In Congested Cities Through Travel Demand Modeling And Decision-Making Tools: A Case Study Of Zagazig City, Egypt, Amr M. Sakr, Metwally Gouda Mohamed Altaher, Mahmoud El-Saied Ali Solyman, Mohamed Ibrahim El-Sharkawi Attia

Mansoura Engineering Journal

Transportation projects are major resource-intensive projects that largely influence the transportation system’s resilience, human health, and quality of life. This study aims to assess and prioritize four transportation projects in Zagazig City, Egypt, in an attempt to build a more sustainable transport system. The travel demand model is used to determine various traffic characteristics and environmental impacts, and decision-making tools are used to evaluate the proposed projects. Benefit-cost analysis (BCA) is employed to investigate the economic feasibility of the proposed projects, and two hybrid multiple-criteria decision-making (MCDM) methods are used to prioritize the proposed projects. Through the work conducted in …

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A Deep-Learning-Based Dehazing Framework For Non-Homogenous Scenes, Shimaa Mohammed Abd Elghany, Doaa A. Altantawy, Hossam El-Din Moustafa Moustafa Jul 2025

A Deep-Learning-Based Dehazing Framework For Non-Homogenous Scenes, Shimaa Mohammed Abd Elghany, Doaa A. Altantawy, Hossam El-Din Moustafa Moustafa

Mansoura Engineering Journal

The advancement of single-image dehazing techniques has been rapid in recent years. Several existing algorithms that are based on deep learning have shown remarkable efficiency for dealing with homogeneous hazing-free issues, but convolutional neural networks (CNNS) frequently fail on non-homogeneous dehazing datasets. Meanwhile, dehaze results from dense haze regions are often blurry because the information of these regions is typically unknown and difficult to estimate. To address these issues, an efficient image enhancement dehazing algorithm that utilizes deep learning techniques, and a non-uniform atmospheric scattering model had been proposed. Unlike the majority of existing dehazing methods, the medium transmission function …

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