Engineering Commons^™

Thermo-Entropic Analysis Of Unsteady Mhd Nanofluid Couette Flow: A Classical Spectral Approach With An Exploratory Quantum Linear-Solver Application, Serai Israel Mosala, Oluwole Daniel Makinde, Azwinndini Muronga

Mathematical Modelling and Numerical Simulation with Applications

This study presents a thermo-entropic analysis of unsteady MHD nanofluid Couette flow, combining a classical bivariate spectral quasilinearisation (BI-SQLM) and Crank--Nicolson solution with an exploratory application of quantum linear solvers. An incompressible, electrically conducting nanofluid flows between parallel plates under partial slip and convective heat exchange; the discretised linear systems are additionally solved via the Harrow--Hassidim--Lloyd (HHL) algorithm and the Variational Quantum Linear Solver (VQLS). Results are presented for Pure Water, Cu-Water, and Al₂O₃-Water across seven parameter variations. The Hartmann number dominates velocity suppression and entropy amplification, while velocity slip reduces upper-wall entropy generation more than …

Urban Spatial Development Control In Tanzania: Analysis Of Factors Influencing Gis Application Using Structural Equation Modelling (Sem)., Happiness Protas Mmanda, Nestory Yamungu

Tanzania Journal of Engineering and Technology (TJET)

Rapid urbanization in developing countries has intensified urban expansion, creating challenges for sustainable development. Geographic Information Systems (GIS) enhance spatial planning, but empirical evidence on factors influencing their effectiveness remains limited. This study examines determinants of GIS application in Urban Spatial Development Control (USDC). The objectives are to (1) identify and categorize factors affecting GIS use, (2) assess relative strength, and (3) develop a validated structural model explaining GIS adoption in USDC. Data were collected from 103 LGAs by a mixed sampling method. Exploratory and Confirmatory Factor Analysis classified influencing factors into technology-related (α = 0.869, CR = 0.881), process-related …

Decision Support Tool For The Maintenance Of Meter Gauge Railway Permanent-Way Infrastructures: A Concept Paper, Hamisi J. Maulid, Beatus A.T Kundi, Juma M. Matindana, Ismail W. R. Taifa Dr

Tanzania Journal of Engineering and Technology (TJET)

A Decision Support Tool (DST) represents a transformative way of modernising maintenance practice on the permanent-way infrastructure of Meter Gauge Railway (MGR). Maintenance practice remains largely reactive, as the MGR plays a strategic role in transporting both freight and passengers, resulting in inefficient resource allocation, high operational risk, and growing Lifecycle expenses. This concept paper explores the potential and the design challenges for a DST that combines fuzzy analytic hierarchy process (Fuzzy-AHP) modelling, multi-criteria decision analysis (MCDA), Geographic Information Systems (GIS) and predictive machine learning (ML) analytics for evidence-based, future-oriented maintenance management. The paper draws on peer-reviewed studies from …

Contemporary Cybersecurity Challenges In Emerging Technologies: A Systematic Literature Analysis, Faztudo Languisse Prof

Journal of Cybersecurity Education, Research and Practice

The accelerating convergence of artificial intelligence (AI), the Internet of Things (IoT), cloud computing, blockchain, and quantum computing has fundamentally transformed the global threat landscape, introducing cybersecurity challenges of unprecedented complexity and scale. This systematic literature review synthesizes findings from peer-reviewed publications, institutional reports, and regulatory documents published primarily between 2020 and 2025 to provide an integrated analysis of contemporary cybersecurity challenges across five key emerging technology domains. The review identifies critical vulnerabilities inherent to each domain, documents the evolution of threat actors and attack methodologies — including AI-powered ransomware, adversarial machine learning, and harvest-now-decrypt-later quantum attacks — and evaluates …

Cybersecurity Governance Of Industrial Iot In Sub-Saharan Africa: Policy Gaps, Threat Landscape, And Lessons From Comparative African Contexts, Faztudo Languisse Eng.

Journal of Cybersecurity Education, Research and Practice

The rapid deployment of Industrial Internet of Things (IIoT) systems across Sub-Saharan Africa's extractive, energy, logistics, and agro-industrial sectors has introduced a cybersecurity challenge of growing urgency: industrial networks that were designed for operational efficiency are increasingly exposed to cyber threats for which neither the organizations nor the regulatory frameworks are adequately prepared. This article examines the cybersecurity governance of IIoT systems in a developing African economy, using Mozambique as a primary case study and drawing comparative lessons from South Africa, Rwanda, and Kenya. Through an integrative literature review and documentary analysis of national digital, cybersecurity, and industrial policies, the …

Energy Efficiency Limits And Future Electricity Demand Of Computing Devices, Ricardo Pinto, Tiago Domingos, Paul E. Brockway, Matthew Kuperus Heun, Tânia Sousa

University Faculty Publications and Creative Works

• ICT (information and communication technologies) represented 4% of the world electricity consumption in 2020; 
• Computing devices represented 2% of the world electricity consumption in 2020; 
• In recent scenarios datacentre electricity demand reaches 3% of world electricity in 2030, and more than 4% in 2035

Enhancing Community Engagement Through ‘Nitunze Kilombero’ Mobile App: Case Of Climate Land Use And Cover Management For Kilombero Basin, Ghanima Chanzi, Subira Munishi

Tanzania Journal of Engineering and Technology (TJET)

The Kilombero Basin in southeastern Tanzania faces significant challenges due to rapid land use and land cover (LULC) changes driven by climate change, population growth, and unsustainable farming practices. This study assessed the role of community engagement and digital reporting through the 'NITUNZE KILOMBERO', mobile application in supporting water resources management in the basin. The App facilitates real-time reporting of environmental issues, provides educational resources, and enables collaboration between local communities and authorities. A mixed-methods approach, including household surveys and key informant interviews, was employed to assess the app's effectiveness. Results indicate high community awareness of LULC impacts, with 85% …

Load Profile Analysis And Forecasting For Rural Mini Grids In Uganda, Prossy Mutesi, Santos L. Kihwele, Emmanuel S. Matee

Tanzania Journal of Science

Accurate load forecasting is essential for the reliable and cost-effective operation of rural mini grids, where constrained generation capacity and high penetration of renewable energy resources require well-informed operational decisions. This study examines electricity demand characteristics and forecasting performance for the Buzaami and Ssenyondo mini grids in Uganda, with particular focus on diurnal load profiles, peak demand behavior, and seasonal variability. 2022 operational data show extended peak demand from early morning to late evening, driven by socio-economic activities that strain resource scheduling and reliability management. To address these challenges, the study evaluates and compares Long Short-Term Memory (LSTM) networks, fuzzy …

Improving Fairness On Semantic Segmentation Using Large Language Models, Samuel E. Burggraf

Electrical & Computer Engineering Projects for D. Eng. Degree

As machine learning systems are increasingly integrated into critical decision-making processes, ensuring fairness in their design and implementation has become a significant concern. While fairness research has primarily focused on specific protected attributes, less attention has been given to spatial fairness, which can affect individuals at specific locations. If fairness is not addressed, models may systematically underperform in certain regions or across populations which can lead to unequal access to accurate predictions and potentially biased decision-making. Fairness considerations should extend across all machine learning applications to align with the National Institute of Standards and Technology (NIST) guidelines of fair and …

Automated Software Size Measurement Using Multilingual Domain-Adapted Language Models, Samet Tenekeci̇, Hüseyi̇n Ünlü, Burak Keçeci̇, Muhammed Efe İnci̇r, Onur Demi̇rörs

Turkish Journal of Electrical Engineering and Computer Sciences

Software Size Measurement (SSM) is crucial for estimating required project effort as well as budget and schedule. However, many small and medium-sized companies struggle to apply objective SSM due to limited resources and lack of expertise. This often leads to inaccurate estimates and project overruns. There is a need for practical, low-resource solutions that support these tasks without requiring expert involvement. Motivated by this challenge, this study proposes an automated software size measurement approach that formulates the measurement task as supervised regression over natural language requirements, using domain-adapted transformer models. We construct large-scale Turkish and English software engineering corpora to …

Predicting Water Quality Using Quantum Machine Learning: The Case Of The Umgeni Catchment (U20a) Study Region, Jamal Al-Karaki, Muhammad Al Zafar Khan, Amjad Gawanmeh, Marwan Omar

All Works

The assessment of water quality has become increasingly vital for maintaining the ecological balance and ensuring public safety across global water systems. This study examines the application of Quantum Machine Learning (QML) techniques in a real-world setting to predict water quality in the U20A region of the Umgeni Catchment, Durban, South Africa. We implemented the Quantum Support Vector Classifier (QSVC) and Quantum Neural Network (QNN) on a field-collected dataset. Our results demonstrate that the QSVC is more practical to implement and yields superior performance, achieving 75 % accuracy with polynomial and radial basis function kernels. In contrast, the QNN encountered …

A Review Of Routing Attacks In Routing Protocol Over Low-Power And Lossy-Based Iot Networks, Lanka Chris Sejaphala Mr., Vusimuzi Malele Prof, Francis Lugayizi Prof.

Journal of Cybersecurity Education, Research and Practice

Low-power and Lossy IoT Networks (LLNs) comprise physical sensors, processing capability, power, and other technologies to exchange information between systems and devices over the internet. However, these networks are susceptible to routing attacks affecting resources, traffic flow, and topology formation. In the related work, it has been discovered that many previous studies do not consider algorithms and implementation approaches for routing attacks. This research study provides a comprehensive in-depth synthesis insight into the description, effects, and algorithms & implementation of four routing attacks in LLNs i.e., rank, sinkhole, DIS-flooding, and worst parent attacks. The findings of this research study highlight …

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 …

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 …

Adaptive Self-Attention For Enhanced Segmentation Of Adult Gliomas In Multi-Modal Mri, Evan P. Savaria, Jiangwen Sun

Computer Science Faculty Publications

Every year there are an estimated 80,000–90,000 new glioma cases, highlighting the need for reliable imaging-based decision support. Although deep learning has improved tumor sub-region segmentation, many state-of-the-art models fail to fully capture complementary information across T1, T1Gd, T2, and FLAIR MRI modalities and often operate as “black boxes,” limiting physician trust when precise delineation is critical for surgical planning, radiation targeting, and treatment monitoring. To address these limitations, we propose AIMS, an Adaptive Integrated Multi-Modal Segmentation framework that maintains modality-specific feature streams and employs adaptive self-attention within a hierarchical CNN-Transformer architecture to prioritize and fuse multi-modal MRI features. We …

Tests Without Borders: A Global Approach To Measuring Visualization Literacy, Olivia A. Guess

McKelvey School of Engineering Graduate Student Theses & Dissertations

Visualization literacy assessments shape how we understand people's ability to interpret data, yet most existing instruments embed Western datasets and assumptions that limit their relevance for global audiences. This thesis argues that because data is personal, assessments must also be culturally grounded. We introduce a unified framework for adapting the Mini-VLAT into 22 regionally responsive short-form assessments, each retaining the structure of the original test while incorporating datasets and scenarios tailored to specific regions around the world. To demonstrate how such adaptations can be customized and validated, we present a detailed case study of a Ghana-adapted Mini-VLAT, developed in collaboration …

Spatially Mapped Statewide Estimated Potential Evapotranspiration Using An Efficient Surface Interpolation Method: A Case Study Of South Carolina, Sudhanshu S. Panda, Devendra M. Amatya, Ka Kit Liu, Augustine Muwamba, Timothy J. Callahan

Journal of South Carolina Water Resources

Potential evapotranspiration (PET) exhibits substantial spatial and temporal variability across large landscapes, necessitating site-specific estimation for accurate environmental and water resource assessments. However, obtaining PET or ET data for specific locations across an entire state remains challenging due to the limited number of weather stations and associated environmental datasets. This study aimed to develop an automated geospatial modeling framework to map PET distribution across South Carolina, USA, using PET estimated by the temperature-based Hargreaves–Samani (H–S) method with daily weather data from 59 NOAA stations. Because the accuracy of spatial interpolation depends on both the target variable and the desired spatial …

Mosquito Classification And Explainability From Image Data Via Deep Learning Techniques, Farhat Binte Azam

USF Tampa Graduate Theses and Dissertations

According to the World Health Organization (WHO), mosquitoes are the deadliest animals on Earth, responsible for more human deaths annually than any other species. Mosquito-borne illnesses continue to pose severe risks to global health. In 2015 alone, there were an estimated 214 million malaria cases worldwide. Similarly, a 2016 report from the Centers for Disease Control and Prevention (CDC) revealed that Puerto Rico’s Department of Health received over 62,500 suspected cases of Zika, with 29,345 confirmed positive cases. In 2019, Southeast Asia experienced its worst dengue outbreak in recorded history. Of the approximately 4,500 mosquito species distributed across 34 genera, …

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, …

Towards Metrology 4.0 In Developing Countries’ Manufacturing Industries, Jailos Nzumile

Tanzania Journal of Engineering and Technology (TJET)

A systematic literature review was conducted to unveil the status of the digital transformation of metrology in developing countries, as they are lagging in utilising fourth industrial revolution (IR4.0) technologies to transform manufacturing industries. A PRISMA technique was employed using various keywords to identify, screen, and select the relevant literature. Forty publications were selected for the review, mainly discussing IR 4.0 technologies in metrological operations. The results indicate that the digital transformation of metrology has yet to be initiated in developing countries. However, the employment of IR4.0 technologies in advancing metrological operations in manufacturing industries is mostly discussed in the …

Fuzzy-Ahp Based Decision Support System For The Selection Of Optimal Maintenance Strategy For Meter Gauge Railway Infrastructure: A Review, Hamisi J. Maulid

Tanzania Journal of Engineering and Technology (TJET)

There are many uncertainties and complexities associated with maintaining Meter Gauge Railway (MGR) infrastructure, which calls for a methodical approach to decision-making. The development and application of a fuzzy-AHP-based decision support system (DSS) to select the optimal maintenance strategy for the MGR are presented in this study. The review covers research from 2013 to 2023 and focusses on the use of Multi-Criteria Decision Making (MCDM) and Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) techniques in railway infrastructure maintenance. To manage the inherent uncertainties and subjective judgements involved in maintenance decision-making, the Fuzzy-AHP methodology combines fuzzy logic with the Analytic Hierarchy Process (AHP). …

Meta-Learning Hyperparameters For Foundation Model Adaptation In Remote-Sensing Imagery, Zichen Tian, Yaoyao Liu, Qianru Sun

Research Collection School Of Computing and Information Systems

Training large foundation models of remote-sensing (RS) images is almost impossible due to the limited and long-tailed data problems. Fine-tuning natural image pre-trained models on RS images is a straightforward solution. To reduce computational costs and improve performance on tail classes, existing methods apply parameter-efficient fine-tuning (PEFT) techniques, such as LoRA and AdaptFormer. However, we observe that fixed hyperparameters -- such as intra-layer positions, layer depth, and scaling factors, can considerably hinder PEFT performance, as fine-tuning on RS images proves highly sensitive to these settings. To address this, we propose MetaPEFT, a method incorporating adaptive scalers that dynamically adjust module …

Designing An Interactive Exit Ticket System To Enhance Learning In Engineering Education, Tapanga Witt

McNair Scholars Manuscripts

Within Grand Valley State University's (GVSU) Padnos College of Engineering, many first-year Engineering courses consistently see pass rates below 70%, signaling a need for stronger academic support. This is an issue across many universities; students are underprepared and face a lot of challenges with workload, pace, and independence due to the transition from high school to college (Flanigan, 2024). For this project, I designed and developed a website-based exit ticket system to support student reflection and instructor feedback. Using UX design principles, the platform offers a weekly self-reflection form that recommends resources like tutoring, office hours, or study groups. Gamification …

Single Valued Neutrosophic Hypersoft Set Based On Merec-Moosra Mcdm Methods For Evolution Of Sustainable Strategies For The Circular Supply Chain Based On The Beverage Industry, Alaa Salem, Rayan Hussein, Ahmed Abdelmouty, Mohamed Abouhawwash

Neutrosophic Systems with Applications

Corporate enterprises around the world are facing increasing pressure to operate sustainably due to rising environmental concerns such as climate change, resource scarcity, and ecological degradation. In response, circular supply chain (CSC) practices have emerged as a promising solution, especially within the manufacturing and beverage sectors. CSC focuses on reusing materials, minimizing waste, and creating value from products that have reached the end of their lifecycle. This study investigates the challenges and opportunities of applying circular supply chain management (CSCM) in the beverage industry, which is known for generating significant waste due to high production volumes. The research identifies key …

A Fuzzy Based Framework For Sustainable Technology Selection In Small-Scale Gold Mining Operations, John M. Kafuku

Tanzania Journal of Engineering and Technology (TJET)

Small-scale gold mining (SSGM) operations in Tanzania has been operating inefficiently due to inadequate mining processing technologies, poor working tools, lack of enough capital, and insufficient electricity. Despite the efforts made by different stakeholders in boosting the sustainability of SSGM yet the sector has not reached the expected goal. This paper proposes a framework for appropriate technology selection to help small scale gold miners in evaluating various gold mineral processing technologies. The framework utilizes the fuzzy logic set theory for technology evaluation and selection. The developed framework for technology selection upon validation provided results that technology adequacy of more than …

A Critical Realist Erp Implementation In Zimbabwean Mining Industry Organisations, Jairos Mukwenha

Tanzania Journal of Engineering and Technology (TJET)

This research uses a critical realist framework to examine the factors influencing the success of enterprise resource planning (ERP) system implementation in Zimbabwean mining industry organisations. From the perspective of critical realism, the mining industry in Zimbabwe faces a complex interplay of opportunities and obstacles while implementing ERP systems. The deployment of ERP in mining firms is critically examined in this paper, emphasising how these systems might improve operational efficiency while considering Zimbabwe's particular socioeconomic circumstances. By exploring underlying structures, mechanisms, and outcomes, the research aims to identify critical challenges and opportunities and develop practical recommendations for improving ERP adoption …

Neutrosophic Automata And Its Algebraic Properties, Anil Kr. Ram, Anupam K. Singh

Neutrosophic Systems with Applications

This research endeavors to elucidate the interrelationships among various classes of operators, including neutrosophic successor/neutrosophic source/neutrosophic core operators of neutrosophic automata based on neutrosophic resituated lattices. Furthermore, it delves into the characterization of algebraic properties such as neutrosophic subsystem, neutrosophic connectivity, and neutrosophic separability of a neutrosophic automaton using these operators. Finally, we study the concepts of neutrosophic primaries of the given neutrosophic automata using neutrosophic core operators.

In Memoriam - Nora Sabelli: Master Orchestrator Of Grant Programs And Mentor For Advancing The Interdisciplinary Learning Sciences Field, Eric Hamilton, Jeremy Roschelle, Roy Pea, Barbara Means, Louis Gomez, Kim Gomez, Nancy Butler Songer

Education Division Scholarship

On Friday, September 6, 2024, the learning sciences field lost a giant in Dr. Nora Sabelli, 87 years old, a personal mentor to many researchers and an inspiration to so many learning scientists and STEM leaders. Nora’s first professional career was as a computational chemist, and later she became a passionate leader in research for improving STEM education. Nora’s time as a senior program officer at the National Science Foundation’s (NSF) Education and Human Resources (EHR) directorate was legendary; she was a force of nature who reshaped funding priorities for stronger science and a stronger connection of science to education …

Feasibility And Acceptability Of The Mazi Umntanakho Digital Tool In South African Settings: A Qualitative Evaluation, Catherine E. Draper, Caylee J. Cook, Elizabeth A. Ankrah, Jesus A. Beltran, Franceli L. Cibrian, Kimberley D. Lakes, Hanna Mofid, Lucretia Williams, Gillian R. Hayes

Engineering Faculty Articles and Research

To address the need for interventions targeting social emotional development and mental health of young children in South Africa, the Mazi Umntanakho (‘know your child’) digital tool was co-designed, and piloted with caregivers and 3–5-year-old children involved in home visiting programmes promoting early childhood development. The aim of this study was to qualitatively evaluate the feasibility and acceptability of this tool in four urban and four rural low-income communities, from the perspective of home visitors and caregivers. Focus groups were conducted with home visitors (n = 117) and caregivers (n = 72). Issues relating to the feasibility of …

Applying Transfer Learning For Street-Scale Nuisance Flood Forecasting In Coastal-Urban Cities, Binata Roy, Jonathan L. Goodall, Diana Mcspadden, Chetan Kumar, Steven Goldenberg, Yidi Wang, Malachi Schram

VMASC Publications

An important challenge with Machine Learning (ML) is its transferability; i.e., whether a ML model trained on one set of data can be applied to a second set of data without requiring full re-training of the model. Transfer Learning (TL) addresses this challenge by transferring knowledge learned in the source domain (the data it was trained on) to the target domain (a second set of data that is statistically different but related, which the model was not trained on). This study investigates the use of TL for street-scale nuisance flood forecasting by exploring whether a ML model trained for one …