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An In Depth Examination Of Educational, Family, Economic, And Personal Determinants On Academic Performance, Engagement, And Stress: A Comprehensive Study Among Engineering Students, Oumaima Larif 2025 Mississippi State University

An In Depth Examination Of Educational, Family, Economic, And Personal Determinants On Academic Performance, Engagement, And Stress: A Comprehensive Study Among Engineering Students, Oumaima Larif

Theses and Dissertations

This study explores the effects of family, education, economic, and personal factors on students’ decisions to pursue engineering as a profession and their long-term impact on performance as engineering students. We adopted a mixed-method approach, collecting data through surveys administered to undergraduate and graduate engineering students at Mississippi State University. The study results revealed that family, education, economic, and personal factors profoundly influence students' decisions to study engineering. We found that parental expectations, background information, and socioeconomic status, in conjunction with cultural norms, values, gender expectations, and religious beliefs, affect students. Additionally, this study identified gaps in the existing literature …


The Importance Of Community: An Investigation Of Stress, Coping, And The Value Of Social Support For First Responders, Brian Reid 2025 Mississippi State University

The Importance Of Community: An Investigation Of Stress, Coping, And The Value Of Social Support For First Responders, Brian Reid

Theses and Dissertations

People are designed to be in community with others, to work together and share the load and weight of life. First responders are a community that has not emphasized the importance of social support to mitigate and buffer against the stress inherent in their jobs. This study investigates the sources of stress, coping methods, and social support of first responders. Results from the first study show the impact of workplace and family stress on the first responder is impactful from the beginning. The secondary study finds that adaptive coping methods are the preferred method to cope with stress and that …


In-Hand Singulation, Scooping, And Cable Untangling With A 5-Dof Tactile-Reactive Gripper, Yuhao Zhou, Pokuang Zhou, Shaoxiong Wang, Yu She 2025 Purdue University

In-Hand Singulation, Scooping, And Cable Untangling With A 5-Dof Tactile-Reactive Gripper, Yuhao Zhou, Pokuang Zhou, Shaoxiong Wang, Yu She

School of Industrial Engineering Faculty Publications

Manipulation tasks often require a high degree of dexterity, typically necessitating grippers with multiple degrees of freedom (DOF). While a robotic hand equipped with multiple fingers can execute precise and intricate manipulation tasks, the inherent redundancy stemming from its high-DOF often adds complexity that may not be required. In this paper, we introduce the design of a tactile sensor-equipped gripper with two fingers and five-DOF. We present a novel design integrating a GelSight tactile sensor, enhancing sensing capabilities and enabling finer control during specific manipulation tasks. To evaluate the gripper's performance, we conduct experiments involving three challenging tasks: 1) retrieving, …


Data-Driven Dynamic Decision-Making Using Discrete Optimization And Supervised Machine Learning, Navid Rashedi 2025 Thayer School of Engineering

Data-Driven Dynamic Decision-Making Using Discrete Optimization And Supervised Machine Learning, Navid Rashedi

Dartmouth College Ph.D Dissertations

In recent years, the operations research community has developed data-driven optimization techniques to solve complex combinatorial problems with the aid of machine learning. This thesis contributes to these efforts by combining machine learning with optimization to expedite online decision-making, with applications in transportation and healthcare.

In the domain of airline operations recovery, the focus is on the aircraft recovery process—repairing disrupted schedules by minimizing overall disruption costs. Traditional exact methods are too time-consuming, while heuristic approaches often yield poor solution quality and lack generalizability across varying formulations. To address these challenges, this research employs supervised machine learning to identify near-optimal …


Fff Process Parameter Identification With Machine Learning Models, Owen Davis Smith 2025 Mississippi State University

Fff Process Parameter Identification With Machine Learning Models, Owen Davis Smith

Honors Theses

Additive manufacturing (AM) has seen increasing popularity in recent times, owing to its efficiency and high speeds, particularly with processes such as Fused Filament Fabrication (FFF). Input process parameters have large impacts on the final part. Incomplete process parameters, which can occur for a variety of reasons, make tasks such as replicating AM studies difficult. A machine learning model can be trained on in-situ layer-wise images collected during a print to combat this issue, predicting process parameters with sufficient data. In this study, two parameters were tested: infill pattern orientation and extrusion width. Twelve parts were produced per parameter and …


Minimizing Uncovered Triples: An Integer Programming Approach To College Football Conference Scheduling, Caleb Mallett 2025 University of Arkansas, Fayetteville

Minimizing Uncovered Triples: An Integer Programming Approach To College Football Conference Scheduling, Caleb Mallett

Industrial Engineering Undergraduate Honors Theses

Collegiate football teams often compete in groups of 8-20 teams known as conferences. One such conference, the Atlantic Coastal Conference (ACC), added three new schools for the 2024-25 season, bringing their total to 17 teams. Currently, each ACC team plays eight games against others within the ACC. At the season’s conclusion, the two ACC teams with the best intraconference record compete in a conference championship game. With 17 total teams each playing eight games, the ACC could have a three-way tie for the best record where none of top the three teams play one another. To avoid this situation, we …


Developing 3d-Printed Packaging To Protect Biodegradable Sensors Used For Large-Scale, Efficient Water Quality Monitoring, Han L. Siew 2025 University of Arkansas, Fayetteville

Developing 3d-Printed Packaging To Protect Biodegradable Sensors Used For Large-Scale, Efficient Water Quality Monitoring, Han L. Siew

Industrial Engineering Undergraduate Honors Theses

Freshwater degradation due to human activities costs the United States over $2.2 billion annually, highlighting the urgent need for improved water quality monitoring methods. Traditional water sampling techniques are labor-intensive, time-consuming, and reliant on single-use plastics that contribute to environmental pollution. This research aims to address these issues by developing 3D-printed biodegradable sensor packaging for unmanned aerial vehicle (UAV)-assisted water sampling. By utilizing biodegradable materials, the research seeks to create an eco-friendly solution that ensures sensor durability while reducing negative environmental impact. The study will involve adjusting the packaging design to withstand UAV deployment by testing and improving the resistance …


Survival Signature Estimation Using Optimization And Monte-Carlo Simulation For K ≥ 3 Classes Of Nodes On Two-Terminal Networks, Md Sazid Rahman 2025 University of Arkansas, Fayetteville

Survival Signature Estimation Using Optimization And Monte-Carlo Simulation For K ≥ 3 Classes Of Nodes On Two-Terminal Networks, Md Sazid Rahman

Graduate Theses and Dissertations

This research develops an efficient approach to estimating survival signatures for two-terminal networks with more than two classes of components. Recently, the survival signature has gained substantial attention in the literature on network reliability estimation due to its unique separability property, which enables passing the network topology information independent of the failure distribution of the components. Following recent results from the literature, estimating the two-terminal survival signature by Monte Carlo simulation entails solving a multi-objective maximum capacity path problem on a two-terminal network in each replication. We adapt a multi-objective Dijkstra’s algorithm from the literature to construct the set of …


Extending Simulation-Enhanced Bayesian Optimization Of System Designs: A Computational Study, Luke Kim 2025 University of Arkansas, Fayetteville

Extending Simulation-Enhanced Bayesian Optimization Of System Designs: A Computational Study, Luke Kim

Data Science Undergraduate Honors Theses

This honors thesis builds off work initially accepted for publication in the Proceedings of the 2025 IISE Annual Conference & Expo, which introduced “Simulation-Enhanced Bayesian Optimization” (SEBO)—a hybrid testing optimization approach that combined the usage of unbiased but costly physical experiments with the usage of cheaper but potentially biased computer experiments to optimize engineered systems. The original study established the SEBO methodology and demonstrated its effectiveness on a multimodal, two-dimensional benchmark function. Expanding on the work performed, we conduct a broader evaluation of the SEBO framework through parameter testing and experimentation under a variety of additional benchmark functions. This investigation …


A Causal Model Of Performance Shaping Factors For Human Reliability Analysis In Manufacturing., Prameet Ranjan Jha 2025 University of Louisville

A Causal Model Of Performance Shaping Factors For Human Reliability Analysis In Manufacturing., Prameet Ranjan Jha

Electronic Theses and Dissertations

Human reliability analysis is a critical component of probabilistic risk assessment, aimed at predicting and mitigating human errors in complex systems. This dissertation develops a novel approach to human reliability analysis in manufacturing by integrating structural equation modeling and Bayesian networks to improve the estimation of human error probabilities. Traditional human reliability assessment methods, such as the Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) and the Technique for Human Error Rate Prediction (THERP), provide structured techniques for estimating human error probabilities. However, these methods often fail to capture the complex interdependencies among performance shaping factors (PSFs), limiting their applicability in …


Engineering Solutions For The Transplant Supply Gap: Social Network Analysis, Artificial Intelligence, And Optimization In Living Kidney Donation., Joshua Nielsen 2025 University of Louisville

Engineering Solutions For The Transplant Supply Gap: Social Network Analysis, Artificial Intelligence, And Optimization In Living Kidney Donation., Joshua Nielsen

Electronic Theses and Dissertations

Kidney transplantation is the gold standard for treating end-stage renal disease, yet over 90,000 patients remain on the transplant waitlist. This dissertation introduces engineering-driven solutions to help reduce the transplant supply gap by addressing three challenges: illicit trafficking, donor recruitment, and evaluation inefficiencies. First, we model illicit organ trafficking networks using social network analysis. We demonstrate that targeting transplant clinics alone is insufficient to disrupt operations. Instead, disrupting the network requires detaining brokers who organize behind-the-scenes logistics—offering a more effective strategy for intervention. Second, we seek to identify a latent population of potential living donors who face barriers such as …


A Digital Twin Approach To Job Shop Scheduling: Simulation And Optimization In Anylogic, Alan Alejandro Corral Lopez 2025 University of Texas at El Paso

A Digital Twin Approach To Job Shop Scheduling: Simulation And Optimization In Anylogic, Alan Alejandro Corral Lopez

Open Access Theses & Dissertations

In complex manufacturing environments such as job shops, machine breakdowns and maintenance activities can significantly disrupt production flow, leading to delays, bottlenecks, and reduced throughput. This thesis presents the development of a digital twin for a job shop system using AnyLogic simulation software to evaluate the effectiveness of fallback routing logic, where jobs are dynamically rerouted to alternative machines when primary machines are unavailable due to scheduled and unscheduled events. The digital twin replicates real-world job shop conditions, incorporating variable job sequences, machine-specific processing times, and both preventive and corrective maintenance schedules. Two scenarios were compared: a baseline configuration with …


A Systems Engineering Approach For Mitigating Space Debris In Earth's Orbital Regimes, Manuel Soto 2025 University of Texas at El Paso

A Systems Engineering Approach For Mitigating Space Debris In Earth's Orbital Regimes, Manuel Soto

Open Access Theses & Dissertations

Space debris in Earth's orbital regimes is a complex threat that originates with human space activity and is maintained by Earth's gravitational force. Space debris poses the risk of colliding with and destroying operational space assets. These collisions, in turn, pose the risk of compounding space debris fragments by turning operational space entities involved in collisions into additional space debris. In other words, the space debris impact does not end with a fragment colliding with a space entity. Instead, the collision is a new space-debris birth since the entities colliding are likely to become multiple fragments. Depending on the collision's …


Multistage Random Key Genetic Algortihm Optimization For Scheduling Flexible Flow Lines With Sequence Depenedent Setup Times, Aadithan Anbuvanan 2025 Clemson University

Multistage Random Key Genetic Algortihm Optimization For Scheduling Flexible Flow Lines With Sequence Depenedent Setup Times, Aadithan Anbuvanan

All Theses

This thesis proposes a new variation to the Random Key Genetic Algorithm (RKGA) for scheduling optimization in flexible flow line manufacturing with sequence dependent setup times. The proposed RKGA representation decodes scheduling information independently at each stage, unlike the traditional RKGA, which is only sequenced based on the first stage, limiting flexibility. The proposed method's performance is compared to the traditional method with varying numbers of jobs and stages. It is compared regarding performance ratio and statistical significance of differences through the Wilcoxon Signed Rank Test. Results show that the proposed RKGA outperformed traditional RKGA in high complexity (8 Stage …


Survival Signature Estimation For All-Terminal Networks By Solving The Multi-Objective Bottleneck Spanning Tree Problem, Dewan Maisha Zaman 2025 University of Arkansas, Fayetteville

Survival Signature Estimation For All-Terminal Networks By Solving The Multi-Objective Bottleneck Spanning Tree Problem, Dewan Maisha Zaman

Graduate Theses and Dissertations

This research examines the problem of estimating the survival signature of all-terminal networks using Monte Carlo (MC) simulation. Following a recent similar result for twoterminal networks, we show that the work required within each MC replication corresponds to solving a multi-objective bottleneck spanning tree (MOBST) problem. We implement the resulting MC procedure using a “Blocks” algorithm from the literature to solve the MOBST in each replication by identifying its minimal set of non-dominated points. We compare this implementation against intuitive benchmark procedures for completing the work within an MC replication. We conduct numerical experiments to assess the efficacy of multi-objective …


Bridging The Gap: Care Team’S Perspectives On Technology And Ai Integration In Healthcare, Sarah Fernandes, Pranathi Boyina, Awatef Ergai Dr., Wellstar Health System, Mohammad Yousef Mousa Naser, Sylvia Bhattacharya Dr. 2025 Kennesaw State University

Bridging The Gap: Care Team’S Perspectives On Technology And Ai Integration In Healthcare, Sarah Fernandes, Pranathi Boyina, Awatef Ergai Dr., Wellstar Health System, Mohammad Yousef Mousa Naser, Sylvia Bhattacharya Dr.

Symposium of Student Scholars

As healthcare systems increasingly integrate digital solutions, understanding the perspectives of frontline healthcare workers on technology adoption is critical. This study explores how Registered Nurses (RNs), Licensed Practical Nurses (LPNs), and Certified Nursing Assistants (CNAs), collectively referred to as the Care Team, interact with existing and emerging healthcare technologies, including artificial intelligence (AI). Given the growing reliance on digital tools for clinical and administrative tasks, this research examines the challenges and benefits perceived by healthcare professionals when incorporating AI-driven solutions into their workflows.

A cross-sectional research design was employed, involving 30 semi-structured interviews with Care Team members from an Intensive …


A Critical Realist Erp Implementation In Zimbabwean Mining Industry Organisations, Jairos Mukwenha 2025 Zimbabwe Open UNiversity

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 …


Cellulose Recovery From Waste Denim Fabrics Through Indigo Vat Dye Reduction And Spandex Dissolution, Tito N. Venance 2025 Department of Mechanical and Industrial Engineering, College of Engineering and Technology, University of Dar es Salaam, P.O. Box 35131, Dar es Salaam, Tanzania

Cellulose Recovery From Waste Denim Fabrics Through Indigo Vat Dye Reduction And Spandex Dissolution, Tito N. Venance

Tanzania Journal of Engineering and Technology (TJET)

This study addresses environmental conservation by tackling end-of-life management for post-consumer denim garments through the recycling of cotton fibres from waste denim. The purification process involved dithionite reduction of vat dyes in the presence of an alkali followed by selective dissolution of spandex using N,N-dimethylformamide (DMF). Optimal conditions for dye removal were determined at 90°C for 120 minutes with sodium hydroxide at 25 g/L, sodium dithionite at 6 g/L and PVP at 4.5 g/L, while spandex extraction was achieved using a 5% DMF solution at 70°C for 4 hours. Ultraviolet (UV)-vis spectrophotometric analysis indicated a significant increase in whiteness (DL*). …


Assessment Of Factors Contributing On Early Rotting Of Chromated Copper Arsenate Treated Utility Power Distribution Wood Poles In Tanzania, Innocent J. Macha 2025 Department of Mechanical and Industrial Engineering, University of Dar es Salaam, P.O Box 35131, Dar es Salaam, Tanzania

Assessment Of Factors Contributing On Early Rotting Of Chromated Copper Arsenate Treated Utility Power Distribution Wood Poles In Tanzania, Innocent J. Macha

Tanzania Journal of Engineering and Technology (TJET)

The study aimed to assess the factors contributing to the premature decay of Chromated Copper Arsenate (CCA) treated utility power distribution wooden poles in Tanzania. Deteriorated poles samples from various regions in Tanzania were analyzed using handheld X-ray spectrometry to quantify the retention of CCA preservative chemicals. The ages of these poles were estimated based on annual growth rings. The findings indicated that premature failure of CCA treated wooden poles is attributed to an imbalance in the chemical composition of the preservative solution. The study found that CuO retention in most samples ranged between 10-18 kg/m3, significant lower that the …


Developing Predictive Mathematical Model For Optimizing Coating Weight Variation In Galvalume Production: A Case Study Of A Metal Industry, Victoria Mahabi 2025 Mechanical and Industrial Engineering Department, College of Engineering and Technology, University of Dar es Salaam, P.O. Box 35131, Dar es Salaam, Tanzania

Developing Predictive Mathematical Model For Optimizing Coating Weight Variation In Galvalume Production: A Case Study Of A Metal Industry, Victoria Mahabi

Tanzania Journal of Engineering and Technology (TJET)

Variations in coating weight for galvanized steel sheets can result in notable differences between batches. Such variations may cause various issues, such as diminished corrosion resistance, lower mechanical strength, and visual defects, which can ultimately drive-up costs, lead to customer dissatisfaction, and pose safety risks. Even with attempts to manage elements like air knife pressure and line speed, coating weight inconsistencies remain challenging. The research focuses on developing a predictive mathematical model designed to optimize variations in coating weight during Galvalume production. The critical parameters influencing coating weight variation were identified and analysed using a systematic literature review, primary data …


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