Engineering Commons^™

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 …

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 …

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.

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 …

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 …

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 …

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 …

Collapse Of Pre-Covid-19 Differences In Performance In Online Vs. In-Person College Science Classes, And Continued Decline In Student Learning, Gregg R. Davidson, Hong Xiao, Kristin Davidson

Faculty and Student Publications

Abstract: Studies comparing student outcomes for online vs. in-person classes have reported mixed results, though with a majority finding that lower-performing students, on average, fare worse in online classes, attributed to the lack of built-in structure provided by in-person instruction. The online/in-person outcome disparity was normative for non-major geology classes at the University of Mississippi prior to COVID-19, but the difference disappeared in the years after 2020. Previously distinct trendlines of GPA-based predictions of earned-grade for online and in-person classes merged. Of particular concern, outcomes for in-person classes declined to match pre-COVID-19 online expectations, with lower-GPA students disproportionally impacted. Objective …

Platform Path Optimization Method Based On Cumulative Detection Probability Of Sonar Search, Xiang Wei, Xingxuan Liu, Dianzheng Fu, Tianji Yang, Jiaxuan Yang

Journal of System Simulation

Abstract: To address the lack of research on the optimal path of mobile search platform to search for moving targets, this paper proposes a path optimization method of mobile search platform based on cumulative search probability theory. Based on the cumulative detection probability (CDP), one of the important criteria of sensor performance evaluation, a single-peak CDP calculation formula is constructed by using a time series correlation model, namely the (λ, σ) process model. A set of target motion scenarios are constructed, and the trajectory probability of target scenarios and their CDP at different time are corrected by Bayesian posterior probability. …

Modeling For Decision Support Of Flight Ground Support Process, Zhiwei Xing, Ruiwen Yu, Biao Li, Zhaoxin Chen

Journal of System Simulation

Abstract: Aiming at the problems of insufficient decision-making ability and low operational efficiency of the flight ground support process, a decision support model of the flight ground support process based on the department of defense architecture framework (DoDAF) is proposed. Starting from the support operation, support resources, and the relationship between them, the quantitative description of the flight ground support process is performed. DoDAF and the model-based systems engineering (MBSE) modeling method are combined to establish a decision support model of the flight ground support process. The decision utility function is established to analyze the utility value of the comprehensive …

End-To-End Motion Planning Of Unmanned Vehicles Based On Multimodal Deep Reinforcement Learning, Kaiyuan Ding, Askar Hamdulla, Bin Zhu, Eksan Firkat, Zhengtang Ma

Journal of System Simulation

Abstract: Since the agent cannot sense the surrounding environment and cannot successfully avoid obstacles, reinforcement learning fails to be generalized to robot motion planning in difficult terrain. Therefore, a solution based on multimodal deep reinforcement learning, which learns to blend proprioceptive states with high-dimensional depth sensor inputs, is proposed for the motion planning of unmanned vehicles. To be specific, proprioceptive states offer contact measurement for immediate reaction, and the unmanned vehicle can learn and forecast environmental changes with its attached visual sensors, proactively navigating around obstacles and uneven terrains numerous time steps ahead. TransProAct (transformer-based proactive action), a unique end-to-end …

Flexible Job Shop Scheduling Method Based On Collaborative Agent Reinforcement Learning Algorithm, Jian Li, Huankun Li, Pengbo He, Huabei Wang, Liping Xu, Kui He

Journal of System Simulation

Abstract: To enhance the efficiency of flexible job shop scheduling, this paper develops a Markov decision process with specific constraints tailored to the scheduling problem. A cooperative agent reinforcement learning method is proposed to solve the problem of concurrent selection of workpieces and machines. During the construction of the Markov decision process, a disjunctive graph is introduced to represent the state characteristics. Two agents are introduced to select the workpieces and machines. The reward parameters governing the entire scheduling process are established by predicting variations in the minimum-maximum completion time across different time points. A GIN(graph isomorphic network) graph neural …

Dual-Resource Constrained Distributed Flexible Scheduling For Aerospace Structural Components, Yufang Wang, Dianqing Zhang, Xiaolin Hua, Binbin Yao, Fan Chen

Journal of System Simulation

Abstract: A dual-resource constrained distributed flexible job-shop scheduling model was established by taking into account the worker constraints of the finishing process and the requirements of distributed multi-factory collaboration in the production of aerospace structural components. A hybrid grey wolf optimization algorithm based on the critical factory was proposed to solve this problem. The model contained four subproblems: factory selection, operation sequencing, machine selection, and worker selection. In view of these four sub-problems, a four-layer coding and a new decoding method were designed to avoid the use conflict of machines and workers. In addition, a new mechanism for hunting and …

Advanced Strategies For Improving The Robustness Of Deep Learning, Keyu Chen

USF Tampa Graduate Theses and Dissertations

Machine Learning (ML) and Deep Learning (DL) have achieved great success across diverse fields in the last decades, such as facial recognition, medical diagnosis, and language translation. The success, however, largely hinges on the assumption that the training and testing data share the same distribution or domain. In practice, real-world data often exhibits domain shifts, leading to notable degradation in model performance. Hence, the generalization capability of machine lea=rning models is of great importance, which refers to the domain generalization problem. In this dissertation, we present DADG, an effective algorithm for domain generalization, aiming to learn domain-invariant features from seen …

Automatic Detection Algorithm For Typical Defects Of Substation Based On Improved Yolov5, Zhongkai Xu, Yanling Liu, Xiaojuan Sheng, Chao Wang, Wenjun Ke

Journal of System Simulation

Abstract: In response to the challenges present in the context of defect recognition in substations, such as complex substation defects and sample imbalance, an improved YOLOv5 algorithm was proposed. The Transformer model was introduced into the YOLOv5 network structure, leveraging the self-attention mechanism to capture long-range dependencies among features. A focal loss-based optimization was employed to improve the loss function, as well as the detection accuracy and robustness of defects of small sample substations. To meet the requirements of substation defect recognition, a dedicated dataset was constructed. A clustering algorithm was applied to the real annotation boxes to generate more …

Investigation On The Impact Of Loading Effect Of Fruit Juices On The Performance Of Pulsed Electric Field Generators, Devi S

Theses and Dissertations

Pulsed Electric Field (PEF) treatment is one of the efficient non-thermal food processing techniques which is being preferred as a replacement for thermal pasteurization methods. The effectiveness of PEF treatment was measured in terms of reduction in the microbial load in the food, extension of shelf life of the food and retention of nutritional properties of the food. The successful implementation of the PEF treatment depends upon various aspects such as design of pulse generator, parameters of pulse generator, shape and size of the treatment chamber and most importantly the characteristics of each food items. Design and fabrication of a …

Electrostatically Actuated Bio-Mems Circular Membrane Resonator Sensors: Voltage Response Of Primary Resonance, Dumitru I. Caruntu, Marcos Alipi

Mechanical Engineering Faculty Publications

This paper deals with the voltage-amplitude relationship during the primary resonance of electrostatically actuated circular membrane resonator sensors within the context of BIO-MEMS. The motion of these membranes is governed by a partial differential equation, which is nondimensionalized for analysis. This equation incorporates both damping effects and soft electrostatic actuation. The actuation AC frequency is set close to half of the membrane’s first natural frequency, leading to primary resonance. To investigate membrane’s voltage response, two principal methods were employed: the method of multiple scales (MMS) and a reduced order model (ROM) that incorporates two modes of vibration. This research provides …

Quality Assurance Of Cast-In-Place Foundation Elements, Tristen Mee

USF Tampa Graduate Theses and Dissertations

Construction of cast-in-place concrete deep foundation elements is a common practice, yet performed almost entirely blind, leaving uncertainty in the quality of the as-built, below-ground element. This dissertation focuses on three quality assurance aspects of cast-in-place foundations: an automated concrete tracking system for drilled shafts, an alternate approach to identifying if mass concrete conditions exist in cast-in-place foundations, and as-built auger cast pile grout volume determination.

The volume of concrete in a drilled shaft is relatively easy to track on a truck-by-truck basis, as well as the height of the rising concrete per truck. However, a more detailed volume distribution …

Object Detection Of Lightweight Transformer Based On Knowledge Distillation, Gaihua Wang, Kehong Li, Qian Long, Jingxuan Yao, Bolun Zhu, Zhengshu Zhou, Xuran Pan

Journal of System Simulation

Abstract: In autonomous driving, the efficiency and accuracy of object detection are significant. Object detection based on Transformer structure has gradually become the mainstream method, eliminating the complex anchor generation and non-maximum suppression (NMS). It has problems of high computing cost and slow convergence. An object detection model of the based lightweight pooling transformer (LPT) is designed, which contains a pooling backbone network and dual pooling attention mechanism. A general knowledge distillation method is intended for the DETR (detection transformer) model, which transfers prediction results, query vector, and features extracted by the teacher as knowledge to the LPT model to …

A Hybrid Genetic Search Algorithm For Capacitated Electric Vehicle Routing Problem, Dongyao Jin, Mi Liu, Yena Zhu, Yijiang Zhao

Journal of System Simulation

Abstract: The capacitated electric vehicle routing problem (CEVRP) is an NP-hard combinatorial optimization problem in logistics distribution, aiming to minimize the total delivery distance of electric vehicles while satisfying carrying capacity and battery charge constraints. A hybrid genetic search algorithm is proposed to solve CEVRP by decomposing it into two subproblems: capacitated vehicle routing problem (CVRP) and fixed-route vehicle charging problem (FRVCP). A coding scheme with a two-layer chromosome structure is designed to represent the decision variables of these two subproblems. A Split operation is employed to generate vehicle routes for solving CVRP, and five neighborhood search operators, including Relocate, …

Traffic Sign Recognition Model With Long-Tail Distribution Based On Yolox-Tiny, Yunpeng Wu, Yingxiong Fu, Lijun Shen, Feng Cui

Journal of System Simulation

Abstract: Accurate recognition of traffic signs plays an important role in the field of intelligent driving. Traffic sign training datasets with long-tail distribution increase the difficulty of traffic sign recognition. A traffic sign recognition model with long-tail distribution based on YOLOX-Tiny was proposed to improve the poor performance of the model trained on long-tail distribution datasets. A long-tail traffic sign dataset was created based on the TT100K_2021 (tsinghua-tencent 100K 2021) dataset. YOLOX-Tiny was chosen as the underlying model by considering picture numbers in datasets, sample distribution, and model size. Equalization loss v2 (EQL v2) was used as classification loss to …

Real-Time Lidar Slam Algorithm Based On Distribution Optimal Registration, Weigang Li, Chuxiang Yu, Yongqiang Wang, Shaofeng Zou

Journal of System Simulation

Abstract: When scanning the surrounding environment, a lidar will generate some cluttered and sparse point cloud, which will cause excessive distribution fitting errors and correlation distances in the registration process, thus affecting the accuracy of the registration algorithm and the effect of simultaneous localization and mapping (SLAM). To address this problem, a real-time lidar SLAM algorithm based on distribution optimal registration is proposed. An eigenspectrum filter is designed, which takes the normalized minimum eigenvalue as the filtering object to filter out the points that do not match the set distribution in order to reduce the distribution fitting error. Secondly, a …

Research On Green Job Shop Scheduling Based On Herd Immunity Optimizer, Xunde Ma, Li Bi, Junjie Wang

Journal of System Simulation

Abstract: In view of the green flexible job shop scheduling problem where machines have multiple speeds, a green flexible job shop scheduling model under multiple speeds was constructed to minimize the makespan and total energy consumption under different speeds. A discrete coronavirus herd immunity optimizer (DCHIO) was proposed for a solution. A discrete individual updating method was introduced for the relatively large solution space of the multi-speed problem, based on which a population updating mechanism with multi-scale joint search was proposed to search the solution space quickly and uniformly. A dynamic mutation operation was designed to enhance the population diversity …