Industrial Engineering Commons^™

Transparent Eeg Analysis: Leveraging Autoencoders, Bi-Lstms, And Shap For Improved Neurodegenerative Diseases Detection, Badr Mouazen, Ahmed Bendaouia, Omaima Bellakhdar, Khaoula Laghdaf, Aya Ennair, El Hassan Abdelwahed, Giovanni De Marco

Manufacturing & Industrial Engineering Faculty Publications

Highlights

• Novel hybrid architecture: Combined autoencoders with bidirectional LSTM networks for enhanced EEG signal classification, achieving 98% accuracy in distinguishing AD, FTD, and healthy controls.

• Explainable AI integration: Implemented SHAP (SHapley Additive exPlanations) framework to enhance model transparency and identify entropy as the most influential feature for neurodegenerative disease detection.

• Optimal temporal segmentation: Demonstrated that 5-s EEG windows with 50% overlap provide the best balance between classification accuracy and computational efficiency.

• Comprehensive feature extraction: Utilized Power Spectral Density (PSD) analysis across standard frequency bands (Delta, Theta, Alpha, Beta, Gamma) following autoencoder-based dimensionality reduction.

• Superior performance validation: Outperformed traditional machine learning …

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Using Statistical Clustering Of Trajectory Data To Support Analysis Of Subject Movement In A Virtual Environment, Martin Galicia Avila, Douglas Timmer, Alley C. Butler

Manufacturing & Industrial Engineering Faculty Publications

Gracia de Luna conducted experiments with an HMD virtual environment in which human subjects were presented with surprise distractions. His collected data for head, dominant hand, and non-dominant hand included 6 DOF human subject trajectories. This paper examines this data from 57 human subject responses to those surprise virtual environment distractions using statistical trajectory clustering algorithms. The data is organized and processed with a Dynamic Time Warping (DTW) algorithm and then analyzed using the Density Based Spatial Clustering (DBSCAN) algorithm. The K-means method was used to determine the appropriate number of clusters. Chi Squared goodness of fit was used to …

Enhanced Global Oil Spill Dataset From 1967 To 2023 Based On Text-Form Incident Information, Yiming Liu, Zhuoli Yin, Hua Cai

The School of Sustainability Engineering and Environmental Engineering (SEE) Faculty Publications

Knowing how much oil was released into the environment in each incident is critical to studying the environmental, ecological, and economic impacts of oil spills. However, the release amounts (RAs) for numerous oil spill incidents remain unavailable in a structured format for large-scale analysis. The most extensive global oil spill database, managed by NOAA’s Office of Response and Restoration, only documents the worst-case scenario estimations in the machine-readable dataset, while more accurate values are embedded within unstructured incident descriptions and subsequent updates. To enhance the dataset with more accurate RAs, we developed a framework to extract the actual RAs from …

Scalable And Adaptive Agile Framework For Semiconductor Foundry: Advanced Packaging And Heterogeneous Integration Perspective, Pravin Thorat

Harrisburg University Dissertations and Theses

This research addressed the critical requirement for a scalable and adaptive agile framework specifically designed for the unique demands of semiconductor foundries specializing in advanced packaging and heterogeneous integration (HI). The semiconductor industry was encountering growing pressure to innovate and respond quickly to rapidly evolving demands, yet traditional manufacturing processes often struggled to adapt. Existing agile frameworks, mainly developed for the software industry, lacked the necessary adaptations to address the complexities of semiconductor manufacturing, including extended lead times, high capital investment, rigorous quality requirements, and the integration of various technologies. This research gap hindered the ability of semiconductor foundries to …

Transforming Movement Assessment In Physical Therapy Through Subaquatic Data Collection, Kaitlyn Mcdonald

Theses and Dissertations

This study explored the interest and perceived barriers to integrating subaquatic diagnostic technologies (SDTs) into hydrotherapy among licensed physical therapists. Seventeen semi-structured interviews were conducted using a mixed-methods design, with 15 interviews included in the final analysis. Quantitative data were analyzed using chi-square tests, while qualitative responses were coded thematically. Results indicated no statistically significant relationships between SDT interest and career stage or hydrotherapy access, though qualitative data highlighted concerns about cost, limited access, and usability. Despite mixed interest in adoption, participants identified several potential benefits of SDTs, including improved treatment tailoring, increased patient buy-in, and enhanced outcome monitoring. Functional …

Multi-Stage Stochastic Programming For Disaster Relief Logistics Under Forecast Uncertainty, Sudhan Bhattarai

All Dissertations

Hurricanes are among the most destructive annual disasters in the United States, presenting interdependent challenges for evacuation planning and relief-supply logistics. Coordinating evacuation and relief operations is crucial to ensure the timely and effective movement of at-risk populations and the delivery of essential supplies. This dissertation develops and evaluates three progressively advanced multi-stage stochastic programming (MSSP) frameworks that integrate evacuation and relief-item pre-positioning while explicitly accounting for uncertainty in hurricane forecasts.

Chapter 1 introduces a fully adaptive MSSP model for the integrated hurricane relief logistics and evacuation planning (IHRLEP) problem. The model simultaneously optimizes evacuation flows and inventory pre-positioning over …

Machine Learning And Clinical Eeg Data For Multiple Sclerosis: A Systematic Review, Badr Mouazen, Ahmed Bendaouia, El Hassan Abdelwahed, Giovanni De Marco

Manufacturing & Industrial Engineering Faculty Publications

Multiple Sclerosis (MS) is a chronic neuroinflammatory disease of the Central Nervous System (CNS) in which the body’s immune system attacks and destroys the myelin sheath that protects nerve fibers, leading to a wide range of debilitating symptoms and causing disruption of axonal signal transmission. Accurate prediction, diagnosis, monitoring and treatment (PDMT) of MS are essential to improve patient outcomes. Recent advances in neuroimaging technologies, particularly electroencephalography (EEG), combined with machine learning (ML) techniques — including Deep Learning (DL) models — offer promising avenues for enhancing MS management. This systematic review synthesizes existing research on the application of ML and …

A Machine Learning Approach To Detect Pores In Laser Powder Bed Fusion Additive Manufacturing, Jose Galarza, Jose Barron Jr., Luis Jimenez, Tamer Oraby, Jianzhi Li, Farid Ahmed

Manufacturing & Industrial Engineering Faculty Publications

Real-time detection of pores in the Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) process is proposed in this study and can be utilized for in-situ process monitoring and quality control. The average light emission data from the process captured by an optical tomography camera can be integrated into a defect detection module to characterize defects after the deposition of a layer. The light emission contains information on the process zone which could be extracted with the appropriate data techniques. In this paper, we proposed a machine-learning approach that utilizes the mean light intensity data from the melt-pool monitoring …

Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan

All Dissertations

A dissertation is proposed to explore human comfort in human-robot collaboration (HRC) through modeling, prediction, and enhancement methodologies. Human comfort is a crucial yet underexplored factor in HRC, directly influencing task efficiency, trust, and overall collaboration effectiveness. Understanding the influential factors, developing computational models, and refining methods to improve human comfort in HRC are essential steps toward advancing the field of collaborative robotics. To address these challenges, multiple studies have been conducted. A series of experimental studies were performed to investigate how robot motion-based parameters affect human comfort in HRC. These studies examined both analytical comfort modeling approaches and physiological …

Understanding The Elements Of Sterile Processing Workflow: Or, Sterilization And Personnel, Sayed Rezwanul Islam

All Dissertations

The Sterile Processing Department (SPD), also known as the Central Sterile Services Department (CSSD), is an essential part of hospitals and healthcare facilities and is responsible for ensuring the cleanliness, sterility, and proper functioning of medical instruments. Sterile processing departments (SPDs) are key drivers of productivity, effectiveness, safety, and infection control in hospitals. A well-designed SPD workflow can enhance patient safety, reduce operating room (OR) delays, and improve productivity. To understand the flow of sterile processing and interactions between the OR and SPD, process maps and task analyses were developed through direct observations of the basic SPD functions: decontamination, assembly, …

Data-Driven Stochastic Programming For Disaster Housing Logistics Planning, Sheng-Yin Chen

All Dissertations

This dissertation develops an integrated modeling and solution framework for direct temporary disaster housing logistics under demand uncertainty. The proposed framework addresses the problem from short-term, long-term, and computational perspectives. First, a two-stage chance-constrained stochastic programming (TSCC) model is developed for short-term housing logistic planning, with demand scenarios generated via a data-driven spatial regression model that captures the relationship between housing demand, hazard exposure, and socioeconomic factors. A case study based on Hurricane Ian demonstrates that the TSCC model outperforms deterministic and traditional scenario-based models in both solution quality and robustness. Second, to address long-term housing logistics planning, a multi-horizon …

Trauma Network Design Considering Patient Safety And Cost., Lin Lin

Electronic Theses and Dissertations

Trauma, as the leading cause of mortality and morbidity for those under the age of 45 in the US, incurs trillions in annual economic costs. The time-sensitive nature of trauma treatment necessitates an effective, coordinated regional trauma system to optimize patient safety. However, the financial burden associated with trauma care, especially due to low-insured population, presents a significant challenge to the financial health of trauma centers (TCs). To address critical challenges in this domain and provide much-needed insights to trauma decision-makers regarding their trauma system cost, network design, and subsidy policy, this dissertation proposes 3 contributions. First, we introduce an …

Low-Dimensional Learning For Remaining Useful Life Prediction Of Batteries Operating Under Various Environments, Rodrigo Benavides

Theses and Dissertations

In reliability, we typically define the standard operating conditions under which a component operates. However, the differences in battery operating conditions cause variability in the degradation patterns of identically manufactured batteries, rendering remaining useful life prediction a major challenge. To aid this task, several sensors are utilized to monitor battery state-of-health. However, traditional prognostics algorithms do not scale well to the volume of data generated. Furthermore, several authors do not explicitly consider operating environments in their prediction models. Therefore, we present a high-dimensional data analytics framework that integrates operating environment information for battery prognostics. This framework combines Multilinear Principal Component …

Optimizing Park Locations While Considering Resident Behavior, Lu Liu

All Theses

Urban parks and green-spaces significantly enhance community well-being by improving physical health, mental wellness, and environmental quality. Given these extensive benefits, ensuring fair and widespread access to urban parks represents a critical priority in urban planning. Despite the advantages of parks, optimizing their location poses unique and complex challenges distinct from traditional facility location problems, such as those involving emergency services or schools. The core distinction arises from the decentralized nature of residents’ park selection behaviors. Unlike centralized allocations typically managed by public administrators, park usage decisions are driven by individual preferences and behaviors. This decentralized decision-making introduces two additional …

Optimization And Simulation Models For Integrating Social Determinants In Assessing And Optimizing The Accessibility And Efficiency Of Community Pharmacy Networks., Md Morshedul Alam

Electronic Theses and Dissertations

Community pharmacies are essential components of the healthcare system, serving not only as points of medication access but also as providers of health consultations and preventive care. However, disparities in pharmacy access persist due to a combination of geographic, socioeconomic, and behavioral factors. This dissertation develops a comprehensive methodological framework to evaluate and improve accessibility to community pharmacies, integrating optimization, choice modeling, and discrete event simulation. First, we develop an Optimal Community-Pharmacy Assignment (OCPA) model to quantify geographic accessibility across a regional population network. The model minimizes risk-adjusted travel distances between population centers and pharmacies, incorporating social determinants of health …

Replacement Optimization For Offshore Wind Turbine Farms, Morteza Soltani

All Dissertations

This dissertation is concerned with devising optimal replacement policies for offshore wind turbines with a focus on minimizing the costs associated with major component replacements and production losses due to downtime. Like their onshore counterparts, offshore wind turbines are subject to progressive degradation due to normal operations, as well as the influence of dynamic environmental conditions that influence their rate of degradation. Due to their proximity, wind farm turbines share common environmental conditions, as well as specialized maintenance resources. Their common exposure to the environment and need to share resources introduce both stochastic and economic dependence between the wind turbines. …

Advancing Life Cycle Assessment For Environmental Sustainability Of Carbon Fiber-Reinforced Polymer Composites (Cfrps)), Hao Chen

All Dissertations

Carbon fiber-reinforced polymer composites (CFRPs) have emerged as promising materials, particularly for lightweight applications, with the potential to reduce environmental impacts across multiple sectors, including automotive, aerospace, and renewable energy. However, fully realizing their sustainability potential requires a more comprehensive and context-specific understanding of their environmental performance throughout the entire life cycle—from raw material production to end-of-life management.

This dissertation advances life cycle assessment (LCA) practices for CFRPs by addressing key challenges across multiple phases of the CFRP life cycle. First, I conducted a critical review and meta-analysis of carbon fiber manufacturing, revealing substantial variability in reported data on energy …

Retrospective Study And Predictive Modeling Of The Impact Of Social Determinants Of Health On Sepsis Outcomes, Mwembezi Aaron Nyelele

LSU Doctoral Dissertations

Sepsis, a life-threatening organ failure caused by the body’s abnormal and harmful response to an infection, remains a major global and national health challenge. In the United States, it contributes significantly to hospital mortality and imposes a substantial economic burden, with billions spent annually on treatment. Early diagnosis is difficult due to the nonspecific nature of sepsis symptoms, often leading to delays in care and poorer outcomes. As the incidence and severity of sepsis rise, identifying factors that influence outcomes is increasingly critical. Emerging research has shown that Social Determinants of Health (SDOH), including economic stability, education, neighborhood and built …

Algorithms For Combined Regular Synthesis Of Controller Parameters In Control Systems For Dynamic Objects, Khusan Zakirovich Igamberdiev, Latafat Abbas Gizi Gardashova, Yulduz Mukhtarkhodjayevna Abdurakhmanova, Uktam Farkhodovich Mamirov

Technical science and innovation

Nonlinear control system that includes m-dimensional input control signal and extended (n+s) - dimensional state vector, the last s components of which form a vector of unknown parameters θ satisfying a general difference equation is being considered. The quality criterion is determined by the loss function. The optimal control must satisfy the Bellman equation with respect to the optimal loss function. To be defined an approximate solution that preserves an active use of information. For this purpose, the system is linearized in accordance to the nominal trajectory. This problem is seen as incorrectly stated. The values of the preliminary data …

Research On Technology Opportunity Identification By Integrating Technology Attribute Analysis And Competitive Environment Scanning —— A Case Study Of Industrial Robots, Daobin Gao

Journal of Scientific Information Research

[Purpose/significance] Placing technology opportunity identification in the perspective of technology attribute analysis and competitive environment scanning provides intelligence support for enterprises to select technology opportunities and formulate technology competitive strategies in complex and changing market competition environments.

[Method/process] Using patents as the data source, first, the BERTopic model is used to explore potential technical topics, Secondly, starting from the technical attributes, and from both global and local perspectives, we propose indicators of technical importance and technical attention, and use their cross screening to select candidate sets of technical opportunities, Finally, a market competition intensity index that takes into account market …

Investigation Of The Effect Of Material Density And Particle Size On Mixed Powder Spreading Behavior In Powder Bed Fusion Process, Alfred Kofi Apianing Achenie

Theses and Dissertations

Powder spreading marks a crucial step in the Laser powder bed fusion process, directly impacting the powder bed uniformity and paving the way for subsequent stages in the process. The laser powder bed fusion process depends heavily on the composition of the metallic powder feedstock. While most existing studies focus on pre-alloyed powders, limited work has explored the use of elemental powder blends as feedstock as used in in-situ alloying. Pre-alloyed powders are often costly, exhibit irregular morphologies and offer limited flexibility in material selection. This study uses Discrete Element Method (DEM) simulations to investigate how variations in material density …

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). …

Predicting The Influence Of Aggregate Size And Distribution On Cementitious Concrete Properties: A Review, Innocent J. Macha

Tanzania Journal of Engineering and Technology (TJET)

Cement concrete has been in use for centuries as one of the primary construction materials. Its demand in the construction industry is expected to continue for several centuries before the full development of alternative products. However, one of the main areas of research interest is understanding how its constituents can be tailored to make its properties predictable to reduce risks associated with structural failures, reconstruction and reduced durability. These hindrances associated with cementitious concrete result from several attributes, including constituent material characteristics, mixing ratios and workmanship. Understanding the predictability of cement concrete properties requires computer modelling tools to provide reliable …

Towards Future Sustainable Infrastructure: The Role Of Technical Audit In Tanzania’S Public Works, George C. Haule

Tanzania Journal of Engineering and Technology (TJET)

This study aimed to investigate the vital role and impact of technical audits in promoting sustainable infrastructure development in Tanzania. The role and effects of technical audits in long-term infrastructure development were studied using a mixed-methods approach with both quantitative and qualitative parts. Data were collected through analysis of technical audit documentation, a semi-structured questionnaire, and stakeholder interviews. The study revealed the various dimensions of infrastructure investment projects, including initiation and planning, design, procurement of contractors and consultants, contract management, environment, health, and safety. The technical audit findings reported weaknesses or non-performance issues in infrastructure planning at the national level …

Comprehensive Review Of Sensible Thermal Storage Systems For Cooking Applications, Anna K. Shariishoy

Tanzania Journal of Engineering and Technology (TJET)

This paper reviewed the sensible thermal storage systems specifically designed for cooking applications. The review focuses on the characteristics of storage materials, their practical applications, and the overall performance of the systems. The review consolidated an array of experimental and numerical research published across various sources such as journals, conferences, books, online resources, and professional reports. A systematic review is used to reach the conclusion of this paper. Significant findings from this study include the wide range of storage capacities attained from small-scale systems that can store ~1–5 MJ of energy for a single meal to bigger systems that can …

Towards Effective Academia-Industry Collaborations: The Case Of Higher Learning Institutions In Tanzania, Fatuma S. Ikuja

Tanzania Journal of Engineering and Technology (TJET)

Industries are the main consumers of products from higher learning institutions (HLIs); graduates for employment and research outputs for socio-economic development. Research outputs from HLIs are commercialized as services or products facilitated by academia-industry collaborations. The collaborations are expected to address mismatch between labour market needs and HLIs’ products, which has resulted in graduates’ employability challenges. Despite their importance, effective academia-industry collaborations remain challenging. This study explores the effectiveness of Academia-Industry collaborations established by HLIs in implementing the Higher Education Economic Transformation (HEET) project (2021-2026) in Tanzania. One of the project objectives is to build functional linkages between industry and …

Fuzzy Logic-Based Decision Support System For Adoption Of Industry 4.0 Predictive Maintenance By Manufacturing Industries, Fred E. Peter

Tanzania Journal of Engineering and Technology (TJET)

In the context of Industry 4.0, predictive maintenance enhances operational efficiency by optimizing processes, minimizing downtime, and improving cost-effectiveness. However, implementing predictive maintenance requires a systematic approach due to its complexity. This study collected expert input from 15 food and beverage manufacturing industries located in Dar es Salaam, Tanzania, using a purposive sampling technique. Six representatives were selected from each industry, and their opinions were analyzed using MATLAB 7.6 through a fuzzy logic inference system. The analysis focused on key factors influencing Industry 4.0 technology adoption for predictive maintenance, including adoption intention (strategic decision, equipment data, perceived benefit) and perceived …

Assessment Of Digital Solutions For Conformity Assessment Of Legally Controlled Measuring Instruments In Tanzania, Faraja Nyoni

Tanzania Journal of Engineering and Technology (TJET)

The advent of state-of-the-art digital technologies since 2011 has led to the digital transformation of legal metrology practices to ensure the trustworthiness of software-controlled measuring instruments globally. Despite the digital transformation in legal metrological practices, the conformity assessment of legally controlled measuring instruments is manually done (i.e., paper-based) in Tanzania. The paper-based conformity assessment of legally controlled measuring instruments is prone to error and lacks efficiency and effectiveness. This study aimed to assess digital solutions for improving conformity assessment through a comprehensive survey conducted across various regions in Tanzania, targeting a stratified sample of 51 respondents from organizations involved in …

Evaluation Of Thermal And Emission Performances Of Briquettes Produced From Carbonized Corn Cob And Corn Husk, Karina S. Motani

Tanzania Journal of Engineering and Technology (TJET)

The Mozambican agro-industrial sector relies heavily on various crops, with maize being the most significant. During processing, substantial waste is generated, which is often discarded as organic matter or burned, contributing to environmental pollution and the loss of potential energy resources. This study evaluated the thermal and emission performance of briquettes made from carbonized corn cob (CCC) and carbonized corn husk (CCH), using cashew nut skin as a binder for clean cooking applications. The briquettes were assessed against firewood and charcoal as control fuels, focusing on several energy performance parameters: water boiling time (WBT), combustion index (CI), thermal efficiency (TE), …

The Royal Academy Of Engineering, Uk And The Enriching Of Engineering Education Training And Practice Programme In Sub-Saharan Africa, Bavo B. Nyichomba

Tanzania Journal of Engineering and Technology (TJET)

This paper elucidates initiatives taken by the Royal Academy of Engineering, UK, to overcome barriers in education and training in Sub-Sahara African higher learning engineering institutions. The said barriers include mismatches of curriculum, ineffectual teaching and learning and little exposure of academic staff to engineering practice. In order to overcome such barriers, the Royal Academy of Engineering established the two programmes in the region. The first one, Enriching Engineering Education Programme (EEEP) from 2014/15 to 2015/16 where the University of Dar es Salaam coordinated this programme as a hub for East African universities namely; Makerere University (Uganda), Moi University (Kenya), …