Modeling The Pollution From Latrines In A Low- And Middle-Income Country Setting, Christopher Nenninger

USF Tampa Graduate Theses and Dissertations

Latrines are an important sanitation infrastructure that are critical to the United Nations’ effort to end open defecation and achieve the target regarding safely managed sanitation outlined in Sustainable Development Goal #6. This global effort has led to 40,000,000 new users being introduced to improved latrines each year, and this number is expected to increase as the world’s population grows. One of the drawbacks related to these new latrine additions is the potential increase in pollution from hydraulically connected latrine pits to shallow groundwater. This is especially problematic in low- and middle-income countries (LMICs), where communities are more likely to …

Investigation Of Innovative Heat Pipes / Fins System For Diesel Engine Cooling, Mohammad Shafiq Anees

Thesis/ Dissertation Defenses

Engine cooling is considered one of the most important factors that affect their efficiency and therefore their performance, so a new cooling method is proposed using both heat pipes and fins to improve the cooling quality of internal combustion engines and shall be examined theoretically and experimentally. A test rig has been designed and built using a specimen material with similar properties to the real engine materials with similar dimensions as the engine cylinder head / liner thickness. In order to make the effectiveness of this research, a comparison between the cooling by fins alone and cooling the engine by …

Developing Students' Sociotechnical Thinking In The Humanities-Engineering Classroom: A Treatment Versus Control Study Using A Scenario-Based Assessment, Lori Czerwionka, Siddhant S. Joshi, Gabriel O. Rios-Rojas, Kirsten A. Davis

School of Engineering Education Faculty Publications

Background

Engineering problems are open-ended and complex, involving technical and social aspects, yet engineering education focuses on technical training and closed-ended problems. To prepare engineering students, curricula should foster sociotechnical thinking—the ability to consider the interplay of technical and social factors during problem solving. Although educational interventions in this area show promise, further insight into the benefits of interdisciplinary interventions is warranted, particularly with treatment and control group designs.

Purpose

We examine the effect of a Humanities-Informed Engineering Projects (HIEP) course on students' sociotechnical thinking development.

Method

We compared the sociotechnical thinking development of engineering students who took the HIEP …

3d Printed Living Hinges In Deployable Origami Structures, Davis Wing, Robert J. Lang, Spencer Magleby, Larry Howell

Student Works

Origami-based geometries are often difficult to prototype and construct. Although methods exist for creating surrogate folds in many materials, doing so often requires multiple manufacturing steps. While engineers studying foldable models can use single-material additive manufacturing to construct living hinges in their models, current techniques are limited. We present an approach for generating living hinges in stowed, deployable mechanisms using single-material 3D printing. This approach enables new models to be constructed with accurate geometry and kinematics in a single print and with no further manufacturing necessary beyond an initial folding step. Additionally, by printing deployable structures in their stowed form, …

Green Building Information Modeling Framework For Sustainable Residential Development In Egypt, Mohamed Nabawy

Civil Engineering

Rapid urbanization and environmental challenges necessitate innovative construction solutions in Egypt. This study presents a 6D Green Building Information Modeling (BIM) framework designed to enhance sustainability, reduce costs, and optimize construction processes. Integrating energy consumption, carbon footprint, and lifecycle performance metrics, the framework addresses critical gaps in Egypt’s construction sector, including limited technical expertise, high costs, and regulatory challenges. A mixed-methods approach was employed, combining global case study analysis, 3D modeling using Autodesk Revit, energy simulations with Autodesk Insight, and project scheduling through Primavera P6. Expert interviews with industry professionals further refined and validated the framework, ensuring its practicality and …

Green Building Information Modeling Framework For Sustainable Residential Development In Egypt, Mohamed Ahmed Nabawy Dr., Ahmed Gouda Mohamed, Ahmed Osama Daoud Dr.

Civil Engineering

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Green Building Information Modeling Framework for Sustainable Residential Development in Egypt

by Mohamed Nabawy *, Ahmed Gouda Mohamed , Israa Awad and Ahmed Osama Daoud * Construction Engineering and Management Programme, Civil Engineering Department, Faculty of Engineering, The British University in Egypt (BUE), El Sherouk City, Cairo 11837, Egypt * Authors to whom correspondence should be addressed. Buildings 2025, 15(7), 1035; https://doi.org/10.3390/buildings15071035 Submission received: 20 January 2025 / Revised: 23 February 2025 / Accepted: 27 February 2025 / Published: 24 March 2025 (This article belongs to the Special Issue Building …

How Engineering Students Learn And Are Impacted By Empathy Training: A Multi-Year Study Of An Empathy Program Focused On Disability And Technology, Eric Schearer

Faculty Scholarship

Measurable results of efforts to teach empathy to engineering students are sparse and somewhat mixed. This study’s objectives are (O1) to understand how empathy training affects students’ professional development relative to other educational experiences, (O2) to track empathy changes due to training over multiple years, and (O3) to understand how and what students learn in empathy training environments.

Analysis Of An Ultra-Broadband Terahertz Metamaterial Absorber, Md Ariful Islam, Md Rezwan Ahmed, Oishi Jyoti, Pritu Sarkar, Md. Samiul Habib

Mechanical Engineering Faculty Publications

This paper introduces a metamaterial absorber (MA) based on vanadium dioxide (VO2) that achieves over 90% absorption of incident terahertz (THz) waves in between 4.50 THz to 11.90 THz with an average absorption of 94.64% and a relative absorption bandwidth (RAB) of 90.18% — the highest reported absorption bandwidth for VO2-based absorbers to our knowledge. The proposed metamaterial absorber features a design with a central square surrounded by four ’T’-shaped elements on each side, symmetrically arranged on a TOPAS dielectric substrate. We perform all numerical analyses keeping the phase-changing material VO2 in the metallic state, and our simulation results show …

Improving The Stability And Selectivity Of Methane Dry Reforming Catalysis Through Active Site And Process Tuning, Jonathan Lucas

LSU Doctoral Dissertations

Dry reforming of methane (DRM) is a potential industrial solution to greenhouse emissions whereby CH₄ and CO₂ are reacted on a transition metal catalyst to produce syngas, a feed stock for higher value chemical products. Ni can be used as the catalyst for DRM replacing the high cost and low abundance noble metals (Pt, Pd, Rh). However, the harsh process conditions of DRM (T > 700°C, P of 1-10 bar) readily deactivate Ni through coking and sintering. Ni supported on reducible oxides, specifically CeO₂ and CeO₂-ZrO₂ (CZO), have been widely studied to combat the rapid …

The Impact Of Solar Angle And Cloud Shadows On 3d Reconstruction Of Rolling Stock Cargo, Carlina M. Ostrand, Adam D. Reiman, Frank W. Ciarallo, Scott L. Nykl, Clark N. Taylor, Joshua F. Krutz

Faculty Publications

Meeting the relentless demand for more efficient air cargo transportation is of paramount importance for commercial needs and military missions. This study describes an experiment to test an innovative approach that harnesses cutting-edge stereoscopic vision technology to create 3D point clouds of rolling stock cargo across varying solar angles and cloud shadow conditions. Virtual cargo point clouds are generated by calibrating and systematically organizing the depth and location points from an RGB-D camera and then reprojecting them in a virtual environment. Measurement accuracy was rigorously tested across six camera positions in various combinations of weather conditions against physical ground truth …

Confirmation Of The Scanpyramids North Face Corridor In The Great Pyramid Of Giza Using Multi-Modal Image Fusion From Three Non-Destructive Testing Techniques, Thomas Schumacher, Polina Pugacheva, Hussien Allam, Alejandro Ramirez-Pinero, Benedikt Maier, Johannes Rupfle, Khalid Helal, Olga Popovych, Amr G. Hamza, Mohamed Sholqamy, Multiple Additional Authors

Civil and Environmental Engineering Faculty Publications and Presentations

Abstract While non-destructive testing (NDT) measurements have been reported individually for archeological surveys of cultural heritage structures, only a few studies to date have attempted to combine NDT images by means of image fusion (IF). In this article, novel multimodal IF results from three different NDT techniques collected at the Chevron located on the Great Pyramid of Giza (aka. as Khufu’s Pyramid) are presented. The Chevron is an assembly of limestone blocks located in front of the recently confirmed ScanPyramids North Face Corridor (SP-NFC), which had been previously hidden for 4500 years. Under the research activities of the ScanPyramids mission, …

Arduino-Esp32 Based Smart Irrigation System, Ahmed D. Hassebo, Kevin B. Montes, Erick Cabrera

Publications and Research

In response to the growing demand for efficient water management in agriculture, this research presents the development of an Arduino-ESP32 based automated irrigation system. The project integrates an Arduino microcontroller with an ESP32 module to facilitate real-time data collection and control of irrigation processes. Sensors monitor soil moisture, water levels, and local weather conditions, with data displayed on an LCD I2C screen for user accessibility. The ESP32 module handles alert notifications via text messages, keeping users informed remotely. Key components, including a water pump, valve, relay module, OLED screen, and LED display, are synchronized to ensure precise irrigation control. Additionally, …

Development, Optimization, And Validation Of A High-Sensitivity Capillary Zone Electrophoresis System For Bioanalytical Applications, Aaron I. Mena

Electronic Theses and Dissertations

Capillary zone electrophoresis (CZE) is a powerful analytical technique widely used for biomolecular separation due to its high resolution, efficiency, and sensitivity. This report presents the development and validation of a novel CZE system designed to improve modularity, reproducibility, and operational efficiency. The system integrates a laser-induced fluorescence (LIF) detection method with a 488 nm laser, enhanced fluid control through a negative pressure system, and a user-friendly GUI for automated operation and data acquisition. Performance verification included pressure stability tests, fluorescence accuracy assessments, and electrophoretic reproducibility studies. Comparative analysis with a previous CZE iteration confirmed improved baseline stability, peak resolution, …

Advancing Tka Biomechanics: From Joint Simulator To Boundary Condition Development, Yashar Ali Behnam

Electronic Theses and Dissertations

This dissertation addresses four specific aims that collectively attempted to advance the experimental and computational analysis of total knee arthroplasty (TKA) components. The first study focused on the development of a novel whole knee joint simulator capable of simultaneous tibiofemoral and patellofemoral knee loading. This simulator employs custom fixturing to facilitate dynamic, unconstrained, muscle-driven PF articulation alongside controlled TF contact mechanics. Validation against experimental measurements showed strong agreement, demonstrating the simulator's potential as a valuable tool for future TKA design and surgical technique investigations.

The second study verified implant-specific physiological boundary conditions which accurately simulate activities of daily living using …

Determinants Of Knee Motion In Health, Disease, And Repair, Sean Edward Higinbotham

Electronic Theses and Dissertations

The human knee joint is a complex and intricate structure, enabling a wide range of motions and facilitating various dynamic activities throughout a person's lifetime. The combination of the knee's complexity and its role as a primary load-bearing joint has made it susceptible to regular wear and tear, leading to pain and the development of Osteoarthritis (OA), to which, the only treatment currently is total knee arthroplasty (TKA). Despite TKA being a mature procedure, 20% of patients receiving a TKA are dissatisfied with their “new” knee. To reduce that 20% dissatisfaction and improve surgical outcomes, orthopedic companies are developing advanced …

Conversational Open-Domain Question Answering For Resource-Constrained Languages, Emrah Budur, Tunga Güngör

Turkish Journal of Electrical Engineering and Computer Sciences

The growing interest in Conversational AI has led to the development of Conversational OpenQA systems as a crucial step for meeting users' information needs in real world scenarios. Conversational OpenQA systems enhance standard OpenQA performance by leveraging conversation history of the users. However, building effective Conversational OpenQA systems requires large-scale Conversational OpenQA datasets, often limited to the English language, hindering progress in low-resource languages. We present a robust Conversational OpenQA system enhanced by conversational context, designed for languages with limited resources and exemplified in our case study for Turkish. To address data limitations in a cost-effective way, we repurpose existing …

Insect Wing Flexibility Improves The Aerodynamic Performance Of Small Revolving Wings, Gal Ribak, Ori Stearns, Kiruthika Sundararajan, Duvall Dickerson-Evans, Dana Melamed, Maya Rabinovich, Roi Gurka

Physics and Engineering Science

Insect wings are flexible, elastically deforming under loads experienced during flapping. The adaptive value of this flexibility was tested using a revolving wing set-up. We show that the wing flexibility of the beetle Batocera rufomaculata, suppresses the reduction in lift coefficient that is expected to occur with a reduction of wing size compared to rigid propeller blades. Moreover, the scaling of wing flexibility with size is intra-specifically tuned through changes in wing-vein cross-section, resulting in smaller wings achieving proportionally larger chordwise deformations compared to larger wings, when loaded with aerodynamic forces. These elastic deformations control the separation of flow from …

The Artificial Intelligence-Enhanced Echocardiographic Detection Of Congenital Heart Defects In The Fetus: A Mini-Review, Khadiza Tun Suha, Hugh Lubenow, Stefania Soria-Zurita, Marcus Haw, Joseph Vettukattil, Jingfeng Jiang

Michigan Tech Publications

Artificial intelligence (AI) is rapidly gaining attention in radiology and cardiology for accurately diagnosing structural heart disease. In this review paper, we first outline the technical background of AI and echocardiography and then present an array of clinical applications, including image quality control, cardiac function measurements, defect detection, and classifications. Collectively, we answer how integrating AI technologies and echocardiography can help improve the detection of congenital heart defects. Particularly, the superior sensitivity of AI-based congenital heart defect (CHD) detection in the fetus (>90%) allows it to be potentially translated into the clinical workflow as an effective screening tool in …

Bayesian Network-Based Framework To Uncover Social Inequities In Flood Risk: Application To East Baton Rouge Parish, Louisiana, Fuad Hasan

LSU Master's Theses

Regional flood risk assessment requires understanding the complex interplay of sociodemographic, socioeconomic, hydrogeologic, built environment, and climatic variables that impact flood vulnerability. Traditional studies often focus on large-scale units, overlooking localized variations and disproportionate exposure within populations. To address these gaps, a methodological framework of flood risk assessment using the Bayesian network was proposed and applied to East Baton Rouge Parish, Louisiana, for the August 2016 flood event to identify relationships between flood risk variables at the housing unit level. Flood exposure representativeness (FER) was determined using the Bayesian network's inference capabilities to identify over- or under-represented groups. This study …

Artificial Intelligence Approaches To Energy Management In Hvac Systems A Systematic Review, Seyed Abolfazl Aghili, Amin Haji Mohammad Rezaei, Mohammadsoroush Tafazzoli, Mostafa Khanzadi, Morteza Rahbar

Civil Engineering & Construction: Faculty Publications

Heating, Ventilation, and Air Conditioning (HVAC) systems contribute a considerable share of total global energy consumption and carbon dioxide emissions, putting them at the heart of the issues of decarbonization and removing barriers to achieving net-zero emissions and sustainable development goals. Nevertheless, the effective implementation of artificial intelligence (AI)-based methods to optimize energy efficiency while ensuring occupant comfort in multifarious settings remains to be fully realized. This paper provides a systematic review of state-of-the-art practices (2018 and later) using AI algorithms like machine learning (ML), deep learning (DL), and other computation-based techniques that have been deployed to boost HVAC system …

Synergistic Effects Of Copper Oxide-Stigmasterol Nanoparticles: A Novel Therapeutic Strategy For Oral Pathogen Biofilms And Oral Cancer, Althaf Hussain, Rym Ghimouz, Siva Prasad Panda, Uttam Prasad Panigrahy, Vanitha Marunganathan, Mohammed Rafi Shaik, Paramasivam Deepak, Nathiya Thiyagarajulu, Baji Shaik, Anahas Perianaika Matharasi Antonyraj, Mohd Asif Shah, Ajay Guru

All Works

Oral pathogen biofilms contribute to chronic infections, while oral cancer remains a significant health threat, emphasizing the need for effective therapeutic strategies. This study investigates the fabrication, characterization, and therapeutic potential of copper oxide-stigmasterol nanoparticles (CuO-SS NPs) for oral pathogen biofilm disruption and oral cancer treatment. The antimicrobial activity of CuO-SS NPs was evaluated against oral pathogens, including S. aureus, S. mutans, E. faecalis, and C. albicans. In cancer cell studies, CuO-SS NPs exhibited a concentration-dependent cytotoxicity, reducing cell viability from 88% at 15 µg/mL to 29.33% at 120 µg/mL, comparable to doxorubicin (24.3%). The CuO-SS NPs significantly upregulated the …

A Case Study Of Gray-Box Fuzzing With Byte- And Tree-Level Mutation Strategies In Xml-Based Applications For Exposing Security Vulnerabilities, Şerafetti̇n Şentürk, Vahi̇d Garousi, Nejat Yumuşak

Turkish Journal of Electrical Engineering and Computer Sciences

Fuzzing is an automated process for detecting crashes and vulnerabilities in software system and it is classified as grammar- or mutation-based in terms of input generation. While the grammar-based fuzzing generates inputs from a specification and takes highly-structured inputs, mutation-based fuzzing generates inputs by modifying input files and abstract syntax trees randomly. There are not many case studies comparing the crash detection capabilities in the scope of mutation-based fuzzing. To add to the body of empirical evidence in this area, this case study compares fuzzing with different mutation strategies to evaluate their effectiveness in three aspects: fault detection effectiveness, fault …

Optimizing Parameters For Efficient Computation With Fully Homomorphic Encryption Schemes, Cavi̇dan Yakupoğlu Karaağaç, Kurt Rohloff

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we aim to provide a parameter selection approach for the BFVrns scheme, one of the prominent fully homomorphic encryption (FHE) schemes. Selecting parameters for lattice-based FHE schemes poses a practical challenge for both experts and nonexperts. To solve this problem, we introduce a hybrid approach that combines theoretical approach with experimental analysis. First, we employ regression analysis to examine the impact of parameters on both performance and security. The varying behavior of FHE parameters in terms of performance, security, and ciphertext expansion factor (CEF) makes parameter selection more challenging. To address this issue, we employ a multi-objective …

Decomposition Lstm With Dual Multi-Head Self-Attention For Wind Turbine Drivetrain State Forecasting, Haikun Jia, Huini Sun, Shuang Bai

Turkish Journal of Electrical Engineering and Computer Sciences

Due to the clean and renewable nature of wind energy, accurate prediction of rotor loads and operating states for wind turbine units has become of paramount importance. Currently, traditional methods relying on expert analysis combined with instrument testing for qualitative reasoning are both time-consuming and labor-intensive, and their accuracy guarantees are limited. In response to wind farm data entailing the interweaving of data from multiple sources and the diverse interrelations across various features and time steps, this study introduces a method for predicting rotor loads and operating states. Initially, we employ an iterative multi-scale seasonal-trend decomposition block to capture latent …

Fuzzy-Virtual Inertia Control To Improve The Frequency Response Of Multi-Area Power Systems, Nourelhouda Djaraf, Yacine Daili, Abderrahim Zemmit, Abdelghani Harrag

Turkish Journal of Electrical Engineering and Computer Sciences

Virtual inertia control (VIC) is essential for power systems dominated by electronic devices to compensate for the lack of inertia and ensure frequency regulation. However, most existing VICs often focus solely on optimizing the virtual inertia parameter to adapt to the high penetration of renewable energy sources (RESs) without considering the damping factor. This oversight can lead to significant fluctuations and power mismatches, especially in interconnected systems where the coordination between MGs is sensitive and essential, and there is a risk of propagation of deviations between MGs, which makes the control more complex. To address these issues, this paper presents …

Multikernel Embedded Fusion Unet (Mkef-Unet): A Robust Deep Learning Approach For Accurate Segmentation Of Chagas Parasites, Preet Kumar, Carlos Brito-Loeza, Lavdie Rada

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces a novel approach for segmenting Chagas parasites on stained blood smear samples from mice during the acute phase of infection with Trypanosoma cruzi utilizing a U-Net-based deep learning model named multikernel embedded fusion UNet (MKEF-UNet). Our proposed model incorporates DenseNet-121 for feature extraction, a classifier module for predicting parasite information, and a segmentation decoder with multiscale feature fusion to generate precise segmentation results. Notably, the integration of the embedded vector module, multikernel convolutions with dilations, and advanced data augmentation techniques significantly enhance the model’s robustness and generalization capabilities. In extensive experiments on the Chagas dataset, MKEF-UNet achieves …

Enhancing Spatial-Temporal Video Prediction With Ts-Vq-Vae: A Novel Encoder-Processor-Decoder Approach, Mei Feng, Fan Li

Turkish Journal of Electrical Engineering and Computer Sciences

Video prediction is a significant and actively researched area within the data science community. Its primary objective is to generate future video frames based on historical frames, finding applications in diverse domains such as human motion prediction, climate change analysis, and traffic flow forecasting. Traditional methods combine Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to capture complex correlations in spatial-temporal signals. Recent methods improve video prediction accuracy by introducing external information such as optical flow, semantic maps, and human pose data. However, these methods have limitations, such as not fully exploring the intermediate states of learning representations, overlooking …

Increasing Electric Vehicle Charger Availability With A Mobile, Self-Contained Charging Station, Robert Serrano, Arifa Sultana, Declan Kavanaugh, Hongjie Wang

Electrical and Computer Engineering Student Research

As the transition to sustainable transportation has accelerated with the rise of electric vehicles (EVs), ensuring drivers have access to charging to maximize the electric miles driven is critical to lowering carbon emissions in the transportation sector. Limited charging station capacity and poor reliability, especially during peak travel times, long distance travels, holidays, and events, have hindered the adoption of EVs and threaten the progress toward reducing greenhouse gas emissions. Adaptive, flexible deployment strategies combined with innovative approaches integrating mobility and renewable energy are essential to address these systemic challenges and bridge the current infrastructure gap. To address these challenges, …

New Method Of Impact Localization On Plate-Like Structures Using Deep Learning And Wavelet Transform, Asaad Migot, Ahmed Saaudi, Victor Giurgiutiu

Faculty Publications

This paper presents a new methodology for localizing impact events on plate-like structures using a proposed two-dimensional convolutional neural network (CNN) and received impact signals. A network of four piezoelectric wafer active sensors (PWAS) was installed on the tested plate to acquire impact signals. These signals consisted of reflection waves that provided valuable information about impact events. In this methodology, each of the received signals was divided into several equal segments. Then, a wavelet transform (WT)-based time-frequency analysis was used for processing each segment signal. The generated WT diagrams of these segments’ signals were cropped and resized using MATLAB code …

New Hydrographic Survey Specifications - Updates And Enhancements, Matt Wilson, Tyanne Faulkes, Giuseppe Masetti

Center for Coastal and Ocean Mapping

No abstract provided.