Engineering Commons^™

Effect Of Workload And Trust On Automation Levels In Human-Robot Collaboration, Abhiram Maddula

LSU Master's Theses

Automation is becoming increasingly common in manufacturing and assembly plants. The future lies in hybrid workspaces where the strengths of humans and robots complement each other, with robots excelling in precision, speed, and strength, and humans excelling in creativity, emotional intelligence, and complex decision-making. Collaborative robots can foster a more efficient and productive work environment by bridging the gap between human and machine capabilities. This study examines how semi-automated and automated modes impact human-robot collaboration, focusing on mental workload, trust, and task performance.

In this experiment, 58 participants performed a primary task alongside a collaborative robot assembling a miniature lamppost …

The Santa Clara, 2024-11-15, Santa Clara University

The Santa Clara

No abstract provided.

Optimizing Electric Vehicle Fleet Integration In Industrial Demand Response: Maximizing Vehicle-To-Grid Benefits While Compensating Vehicle Owners For Battery Degradation, Andre Leippi, Markus Fleschutz, Kevin Davis, Anna-Lena Klingler, Michael D. Murphy

Publications

This paper addresses the integration of electric vehicle (EV) fleets into industrial smart grids to increase operational flexibility. It focuses on an extended multi-objective optimization problem that minimizes two primary objectives: (i) the electricity expenditure of a company using its employees’ EV batteries as temporary distributed energy storage, and (ii) the costs associated with the degradation of EV batteries, given the additional usage from the company’s perspective. In this paper, the utilization of an EV fleet is simulated at the individual car level over a one-year period. These optimization problems were balanced by using real-time electricity prices and the effective …

Modeling W/V-Band Satellite Communications In The Presence Of Noise Jamming, Ryan Michael Eckman

Electrical and Computer Engineering ETDs

Understanding the performance of wideband modulated signals under noise jamming conditions is important for advancing W/V-band military satellite communications. This research developed and validated models to predict performance degradation of a communication channel in the presence of wideband noise jamming. Channel models were developed that included both modulated communication signals and jammer signals. Integrated models included environmental link factors and practical implementation factors. Integrated models were verified and validated using outdoor radio frequency environments utilizing two W/V-band transceivers, a portable W-band jammer, and software defined radios. Experimental results demonstrated excellent agreement with integrated model predictions. Channel degradation due to the …

Trust-Me: Resource Allocation And Server Selection Based On Trust In Multi-Access Edge Computing, Sean Tsikteris

Electrical and Computer Engineering ETDs

Multi-access Edge Computing (MEC) is crucial for Internet of Things (IoT) applications by optimizing data processing and reducing latency. This thesis presents contributions to resource allocation and decision-making in edge computing environments. The TRUST-ME model is introduced, involving multiple edge servers and IoT devices (users) offloading computing tasks to MEC servers. A utility function is designed to assess latency and cost benefits for IoT devices using server resources. The core innovation is a novel trust model that evaluates IoT devices’ confidence in MEC servers by integrating both direct and indirect trust, based on interactions and feedback from other devices. In …

Enhancing Frp-Concrete Interface Bearing Capacity Prediction With Explainable Machine Learning: A Feature Engineering Approach And Shap Analysis, Yanping Zhu, Woubishet Zewdu Taffese, Genda Chen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study introduces a novel approach to predict the shear bearing capacity of FRP-concrete interfaces using explainable machine learning. Eight algorithms are employed: three standalone models (Artificial Neural Network, Support Vector Regression, and Decision Tree) and five ensemble learning models (Bagging, Random Forest, Adaptive Boosting, Gradient Boosting, and Extreme Gradient Boosting). Four scenarios with varying input features, including engineered features inspired by mechanics-based bearing capacity equations, are examined. Notably, the inclusion of engineered features such as the stiffness of the FRP strip (Kf) significantly enhanced prediction accuracy and efficiency, although the width correction coefficient (bf/bc) did not yield significant benefits, …

Robotic Multi-Object Grasping From A Pile: Techniques And Algorithms For Enhanced Dexterity, Tianze Chen

USF Tampa Graduate Theses and Dissertations

As robots become increasingly integrated into real-world applications such as warehousing, fulfillment centers, and manufacturing, the need for efficient and adaptable robotic systems grows. One of the key challenges is enabling robots to grasp multiple objects simultaneously, as this significantly boosts the efficiency of tasks like batch picking, sorting, and object transferring, reducing both time and energy consumption. This dissertation presents a comprehensive multi-object grasping (MOG) pipeline that includes pre-grasp selection, end-pose selection, grasping synergy calculation, and a data-driven model for estimating the number of objects being grasped. Central to this work is the development of the Experience Forest structure, …

Performance Optimization And Application Of P-Type Transparent Semiconductors In The Cdte Solar Cells, Md Zahangir Alom

USF Tampa Graduate Theses and Dissertations

CdTe thin-film solar cells are one of the major interests in the solar industry for their favorable properties. For example, CdTe has a near-ideal bandgap (1.45 eV) for absorption of the solar spectrum, and a high absorption coefficient ( ̴ 105 cm-1) and can capture 99% of light with only 2 µm of film thickness. Moreover, CdTe can be doped both n and p-type. Additionally, low production costs contribute to more affordable panel prices (0.40 $/W) [1]. The highest efficiency achieved to-date for this material is 23.1% demonstrated by First Solar, which is still lower than the theoretical limit [2]. …

Analyzing The Key Characteristics And Benefits Of Ccpr (Cold Central Plant Recycling) In Road Rehabilitation And Sustainability, Bassam Abou Yassine

Civil Engineering ETDs

Cold mix asphalt (CMA) technologies are being used in the United States and have environmental benefits. However, these technologies are not fully developed. We do not yet know their resilient and dynamic modulus, which are important for designing pavement thickness. They have not being used widely because we do not know also their performance. This study looks at three Cold Central Plant Recycling (CCPR) materials to help fill this gap. We conducted several lab tests, including the Hamburg Wheel Tracking Test (HWTT), Semi-Circular Bending Test (SCB), and Texas Overlay Test (TOT). We also tested the mechanical properties of the CCPR …

How Wildfires Threaten Water Resources: A Case Study Following The Largest Wildfire Recorded In New Mexico, Eric A. Joseph

Civil Engineering ETDs

Wildfire disturbance propagation along fluvial networks remains poorly understood. We use incident, atmospheric, and water-quality data from the largest wildfire in New Mexico’s history to quantify how this gigafire affected surface runoff processes and mobilized wildfire disturbances into fluvial networks after burning 1382 km². Surface runoff post-fire increased compared to pre-fire conditions, and precipitation events that are frequently observed in the affected watershed (<2-year recurrence) and fell during the post-fire first rainy season resulted in uncorrelated, less frequently observed runoff events (10-year recurrence). Wavelet coherence analysis highlighted that water quality disturbances propagated variably along the network, even at sites located >160 km downstream of the burn perimeter. Our findings emphasize the need to incorporate spatially resolved longitudinal sampling designs into wildfire water quality research and highlight the spatiotemporal co-dependency among atmospheric, terrestrial, aquatic processes …

Robust Data-Driven Run-To-Run Control Via One-Step Constrained Optimization For Automated Serial Sectioning, Rhianna M. Oakley

Mechanical Engineering ETDs

This Thesis develops a one-step predictive run-to-run controller (R2R-MPC) for automating a mechanical serial sectioning (MSS) system. MSS is a destructive material analysis process that iteratively removes slices of material and captures 2D images, reconstructing them into 3D representations. Commonly used in material science for characterizing materials and failure analysis, MSS typically operates in an open-loop fashion, which experiences high variability in material removal due to system disturbances. To address this, a robust closed-loop R2R-MPC is presented, modeling MSS process uncertainty using a linear differential inclusion identified from operational historical data. The R2R-MPC is posed as an optimization problem that …

Antimicrobial Activity And Photostability Of Cationic Conjugated Polyelectrolytes, Mohammed Ismael Khalil

Chemical and Biological Engineering ETDs

Antimicrobial resistance is a growing global health concern, driving the need for novel

therapeutic strategies. This study explores the antimicrobial efficacy of conjugated

polyelectrolytes (CPEs) and oligo-phenylene ethynylenes (OPEs) in bacterial and viral

inactivation. Quantitative analysis revealed that light-activated CPEs and OPEs

effectively reduced bacterial viability within minutes, with significant log reductions

observed under both light and dark conditions. Additionally, the antiviral potential of a

cationic conjugated oligomer was investigated, demonstrating rapid and near-complete

inactivation of SARS-CoV-2 under visible light, both in solution and on filter materials.

Further analysis of their photophysical properties revealed that, even after

photobleaching, the compounds …

From A Traditional City To A Smart City: The Measurement Of Cities’ Readiness For Transition, Egypt As A Case Study, Ahmed Hassebo, Mohamed Tealab, Mosaad Hamouda

Publications and Research

The transition from traditional legacy cities to smart cities represents a pivotal juncture in urban development and governance. As cities worldwide grapple with the challenges of rapid urbanization, resource constraints, and the need to enhance the quality of life for their citizens, the concept of a “smart city” has gained significant attention. This paper delves into the multifaceted process of urban transformation, shedding light on the essential criteria and considerations that guide a city’s conversion into a smart city. To provide a comprehensive framework for the conversion process, this paper outlines a computer program utilized to measure the readiness to …

Formation Mechanism And Strengthening Method Of Geometric-Mechanical Structure Of Plugging Zone In Deep Naturally Fractured Reservoir, Chengyuan Xu, Honglin Zhang, Jianhong Fu, Yili Kang, Zhenjiang You

Research outputs 2022 to 2026

Efficient fracture plugging plays a critical role during drilling and completion of deep naturally fractured reservoirs, minimizing fluid loss, and ensuring reservoir protection. This study investigates the formation process of the geometric-mechanical structure of fracture plugging zones through a series of experiments including microscopic visualization, photoelastic and fracture plugging experiments. By examining these experiments, we reveal the relationship between lost circulation materials (LCMs) at the micro-scale, force chain network structures at the meso-scale, and the pressure stability of plugging zones at the macro-scale. Based on the analytic hierarchy process (AHP), we introduce an evaluation index for assessing the stability of …

Identifying Hidden Factors Influencing Soil Olsen-P In An Alkaline Calcareous Soil Using Machine Learning And Geostatistical Techniques, Moussa Bouray, Mohammed Bayad, Adnane Beniaich, Ahmed G. El-Naggar, Rebecca Muenich, Kahlil El Mejahed, Abdallah Oukarroum, Mohamed El Gharous

Biological and Agricultural Engineering Faculty Publications and Presentations

Phosphorus (P) deficiency is one of the major constraints for sustainable crop production in calcareous soils. This study aimed to elucidate the key soil characteristics modulating the variability of soil Olsen P in these typical soils. A comprehensive soil sampling initiative (1.5 samples per hectare) was conducted on a 100-ha farm, considering 31 attributes that included soil physical and chemical properties, and geographic attributes. Three machine learning algorithms—partial least squares regression (PLSR), random forest (RF), and cubist regression (CR)—were employed to understand key variables controlling soil Olsen P. Furthermore, the same data set was used to spatially map the …

Surely You Can’T Be Serious: A Student’S Guide For Flight School Closure, Aidan Mcglasson, Sarah Nilsson

Publications

Flying aircraft, whether at a general aviation, commercial, or military level, is deeply engrained in American culture. Opinion polls place being a professional pilot as one of the most respected, and prestigious jobs in the country (Mushtaque, 2023). As evidenced by the popularity of movies such as Airplane!, Top Gun, or Sully, flying is something that fascinates many people. Perhaps contributing to its mystique is the difficulty and expense in obtaining the necessary training and certifications to be a pilot. Some people undergo flight training with the goal of flying commercially, as an airline or corporate pilot, while others do …

Structural Behavior Of Corroded Reinforced Concrete Beam Elements Repaired With Fabric-Reinforced Matrix Composites, Youssef Ibrahim Elmezayen

Thesis/ Dissertation Defenses

Advanced methods for rehabilitation of reinforced concrete (RC) beams with corroded reinforcement were designed and implemented in this research. The nonlinear flexural and shear behaviors of RC beams with corroded reinforcement repaired with fabric-reinforced matrix (FRM) composites were investigated. Numerical simulation models were developed to predict the flexural response of flexure-deficient continuous RC beams before and after repair with FRM composites. A novel sustainable repair solution that involves the use of cement-free geopolymeric matrix reinforced with nonmetallic fabrics was also introduced for rehabilitation of shear-critical RC beams with corroded stirrups. Simplified and easy-to-use analytical approaches were adopted to estimate the …

Utility Of New Remote Sensing Data In Evaluating The Hydrological Response To Land Use And Land Cover Changes, Chithrika Jayamini Alawathugoda

Thesis/ Dissertation Defenses

Land use and land-cover (LULC) changes have profound impacts on hydrological responses, influencing both runoff dynamics and flood risks. This study focuses on two contrasting environments undergoing rapid LULC transformations: the arid Wadi Ham watershed in the UAE and the tropical Imphal watershed in India. The study addresses the need for accurate LULC data in hydrological modeling, particularly in climate-sensitive regions where changes in land use are accelerating. The primary objective of this research was to assess the impact of LULC changes on the hydrological behavior of the Wadi Ham and Imphal watersheds. It aimed to elucidate how these changes …

A Novel Reinforcement Learning Method For Efficient Cross-Training Between Real And Simulated Robots, Zhonglin Liang

Master's Theses

Training reinforcement learning policy in a simulated environment can be a go-to choice for many research topics, as a simulated environment provides flexibility and costs less than building a physical environment for training. However, policy trained in a simulated environment often fails to transfer to the real environment for problems that have a more complex dynamics. As the solution, Sim2Real was proposed and it categorizes techniques that improve the performance of the transfer from simulation to reality. Sim2Real is an area of study that focuses on utilizing simulation data to train models that can apply to real world environment. It …

Characterization Of Non-Gaussianity In The Snow Distributions Of Various Landscapes, Noriaki Ohara, Andrew D. Parsekian, Benjamin M. Jones, Rodrigo C. Rangel, Kenneth M Hinkel, Rui A.P. Perdigão

Michigan Tech Publications

Seasonal snowpack is an important predictor of the water resources available in the following spring and early-summer melt season. Total basin snow water equivalent (SWE) estimation usually requires a form of statistical analysis that is implicitly built upon the Gaussian framework. However, it is important to characterize the non-Gaussian properties of snow distribution for accurate large-scale SWE estimation based on remotely sensed or sparse ground-based observations. This study quantified non-Gaussianity using sample negentropy; the Kullback-Leibler divergence from the Gaussian distribution for field-observed snow depth data from the North Slope, Alaska; and three representative SWE distributions in the western USA from …

Electrochemical Copper Printing For Wearable Electronics, Nirmita Roy

USF Tampa Graduate Theses and Dissertations

Wearable electronics have become a transformative force across industries like healthcare, aerospace, and military applications. However, a significant challenge persists in directly integrating electronic circuits onto fabrics. Addressing this challenge, the aim of this research is to introduce a novel sequential manufacturing process. Initially, a fabric is coated with a customized ink containing lignin, establishing a conductive template through laser burning. Subsequently, a localized Hydrogen Evolution Assisted (HEA) copper electroplating method is applied, resulting in a low-resistive circuit layout. Our investigations encompassed nanostructure analyses using Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDX), Raman Spectroscopy, and Fourier Transform Infrared …

Investigating Spatiotemporal Trends Using Precursory Signatures: Implications To Develop Short-Term Earthquake Forecasting Techniques In Sumatra-Andaman Region, Ramya Jeyaraman J

Theses and Dissertations

Earthquake forecasting is a challenging field due to Earth's heterogeneous nature. This research aims to develop a short-term earthquake forecasting model by analyzing spatiotemporal trends and precursory signatures in the Sumatra-Andaman region, known for its high seismic activity and tsunami risk. The study adopts an interdisciplinary approach, integrating solid earth tides (SET), micro shocks, and outgoing longwave radiation (OLR) to gain deeper insights into seismic nucleation processes. The research begins by using Singular Spectral Analysis (SSA) to identify potential seismically vulnerable areas through the analysis of irregularities in SET.

A spatiotemporal analysis of micro shocks is conducted to assess the …

Cactus Infused Beads For Off-Flavor Mitigation In Aquaculture Systems, Rama Mahita Kambhampati

USF Tampa Graduate Theses and Dissertations

Aquaculture has become a vital component of global food production, now providing 50% of the world's fish supply. However, the industry encounters major challenges due to off-flavor compounds like Geosmin and 2-Methylisoborneol (MIB), which give fish an unpleasant earthy or musty smell. These compounds are detectable by humans at extremely low levels 0.7 parts per billion (ppb) for MIB and ten parts per trillion (ppt) for Geosmin—making them a persistent problem. Their presence not only reduces the sensory quality of aquaculture products but also results in significant economic losses, with U.S. catfish production incurring an additional $15–$23 million annually due …

Longitudinal Pedestrian Safety Trends By Vehicle Type And Model: A 2015-2022 Study Of Texas, Olivia Tafoya

Civil Engineering ETDs

We observed pickup trucks, SUVs, and passenger cars and their two most popular vehicle models across Texas from 2015 through 2022. For each vehicle type and model, we obtained all reported pedestrian crashes, counts of registered vehicles, and vehicle design characteristics. Results suggest that older vehicles are more likely to seriously injure or kill a pedestrian than newer ones. They also indicate that SUVs were more deadly, after controlling for exposure using the number of registered vehicles, than other vehicle types. Of the models studied, the full-size SUVs proved to be particularly dangerous for pedestrians, being 2.08 times more likely …

Effect Of Specimen Size On The Tensile Properties Of Selective Laser Melted Ti-6ai-4v, Timothy L. Tan

Master's Theses

Metal additive manufacturing (MAM) is a burgeoning industry. It is capable of manufacturing metal components with fine, intricate features and enables localized microstructural control. Due to its fine resolution and compatibility with common engineering alloys, selective laser melting (SLM) is one particular MAM process popular in academia and industry. The biomedical and aerospace industries have shown exceptional interest in the capabilities of SLM with the alloy Ti-6Al-4V. Because SLM Ti-6Al-4V components are aimed for use in critical applications, it is necessary to understand how SLM processing characteristics affect final part performance. One characteristic of SLM Ti-6Al- 4V that requires further …

Enhancing Cross-Cultural Communication In Low-Resource Language Conversational Agents, Hardi V. Trivedi

Master's Theses

Recent advancements in natural language processing (NLP) and large language models (LLMs) have facilitated the development of systems capable of generating human-like responses across a wide range of tasks. However, the majority of research has focused predominantly on English, overlooking the vast linguistic diversity globally. For true global inclusivity, extending research to other languages is crucial, particularly as it can significantly benefit various sectors such as business, healthcare, government, and education. A major challenge in this expansion is the scarcity of digital data available and the limited number of pre-trained models for low-resource languages. Our research specifically addresses these challenges …

Sustainable Mobility: Machine Learning-Driven Deployment Of Ev Charging Points In Dublin, Ruairí De Fréin, Alexander Mutiso Mutua Mr

Articles

Electric vehicle (EV) drivers in urban areas face range anxiety due to the fear of running out of charge without timely access to charging points (CPs). The lack of sufficient numbers of CPs has hindered EV adoption and negatively impacted the progress of sustainable mobility. We propose a CP distribution algorithm that is machine learning-based and leverages population density, points of interest (POIs), and the most used roads as input parameters to determine the best locations for deploying CPs. The objects of the following research are as follows: (1) to allocate weights to the three parameters in a $6$ km …

The Future Of Flying: An Exploration Of New Aircraft Design And Energy Required To Support Advanced Air Mobility – Part 1, Sarah Nilsson

Publications

Lecture exploring new aircraft design and energy required to support advanced air mobility.

An Open Approach To Clinical Study Recruitment Automation, Andrew Bouras, Andrew Bouras, Dhruv Patel, Rahul Kataria

HCA-NSU MD Research Day

Objective: To present an innovative Patient Recruitment Automation System that leverages open standards and promotes open data in clinical research. Background: Patient recruitment for clinical studies faces challenges in efficiency, data security, and regulatory compliance. These issues can delay research timelines and impact healthcare advancements. Methods: We developed a system that integrates with Electronic Health Record (EHR) systems to identify potential participants using predefined criteria. The platform employs Azure-based infrastructure with advanced data protection techniques, ensuring HIPAA compliance. It features an automated screening process using adaptive questionnaires and a communication module for participant engagement. Results: The system demonstrates improved efficiency …

Use Of Electrical Bone Growth Stimulators In High-Risk Patients Following Spinal Fusion, Soumya Malhotra, Khavir Sharieff

HCA-NSU MD Research Day

Title: Use of Electrical Bone Growth Stimulators in High-Risk Patients Following Spinal Fusion Authors: Soumya Malhotra, BA., MS1 & Khavir Sharieff, DO, MBA2 1Class of 2027, Nova Southeastern University Dr. Kiran C. Patel College of Osteopathic Medicine, Fort Lauderdale, FL 2Assistant Professor of Surgery, Nova Southeastern University Dr. Kiran C. Patel College of Osteopathic Medicine, Tampa Bay, FLNova Southeastern University Dr. Kiran C. Patel College of Osteopathic Medicine Objective: This study aimed to elucidate the advantages of EBGSs following high-risk spinal fusions. Background: Pseudarthrosis is a condition where bones fail to fuse after an injury or surgery. It causes significant …