Engineering Commons^™

Feasibility Of Eeg Based Detection Of Ischemic Stroke: Studies In A Simple Computational Model, Charles F. Babbs

Weldon School of Biomedical Engineering Faculty Working Papers

Objective: To explore quantitatively, using streamlined mathematics, how transmembrane potential differences across cell bodies of individual cortical neurons could act to produce the skin surface potentials of the electroencephalogram (EEG), and how ischemic stroke might be detected using EEGs in prehospital settings. Methods: From fundamental principles of electrostatics, anatomy, and physiology, one can characterize the strength of apparent dipoles created during activation of the cell bodies of individual cortical neurons. The transient dipole strength in a cortical neuron depends upon the size and surface area of its cell body, its capacitance, and the difference in transmembrane electrical potentials appearing across …

Belowground Plant Allocation Regulates Rice Methane Emissions From Degraded Peat Soils, Nijanthini Sriskandarajah, Chloe Wust-Galley, Sandra Heller, Jans Leifeld, Tiia Maatta, Zutao Ouyang, Benjamin R. K. Runkle, Marcus Schiedung, Michael W. I. Schmidt, Shersingh Joseph Tumber-Dávila, Avni Malhotra

Biological and Agricultural Engineering Faculty Publications and Presentations

Carbon-rich peat soils have been drained and used extensively for agriculture throughout human history, leading to significant losses of their soil carbon. One solution for rewetting degraded peat is wet crop cultivation. Crops such as rice, which can grow in water-saturated conditions, could enable agricultural production to be maintained whilst reducing CO₂ and N₂O emissions from peat. However, wet rice cultivation can release considerable methane (CH₄). Water table and soil management strategies may enhance rice yield and minimize CH₄ emissions, but they also influence plant biomass allocation strategies. It remains unclear how water and …

Learning By Evaluating: An Exploration Of Optimizing Design-Based Instruction, Scott Thorne, Nathan Mentzer, Greg J. Strimel, Scott R. Bartholomew, Jason A. Ware

School of Engineering Technology Faculty Publications

Learning by Evaluating (LbE) is an instructional approach that involves students making comparative judgements of pairs of artifacts, such as student work, portfolios, prototypes, or curated images related to a topic of instruction to enhance critical thinking and decision-making skills. Situated as a primer for learning, the efficacy of LbE stems from actively engaging students in the evaluation process, scaffolding their learning, fostering self-reflection in decision-making, and facilitating the transfer of acquired skills and concepts to academic contexts and project work. However, there is an opportunity to gain deeper insights into classroom integration of LbE and the factors that may …

Disk Engine With Circumferential Swirl Radial Combustor, Brian T. Bohan, Marc D. Polanka, Bennett Staton

AFIT Patents

A disk engine and system configured to provide high power at a reduced axial length is disclosed herein. The disk engine includes a radial compressor, a compressor discharge manifold positioned circumferentially about compressor, a combustion chamber positioned within the discharge manifold and a radial turbine positioned radially inward of the combustion chamber.

Malware Detection For Internet Of Things Using One-Class Classification, Tongxin Shi, Roy A. Mccann, Ying Huong, Wei Wang, Jun Kong

Electrical Engineering Faculty Publications and Presentations

The increasing usage of interconnected devices within the Internet of Things (IoT) and Industrial IoT (IIoT) has significantly enhanced efficiency and utility in both personal and industrial settings but also heightened cybersecurity vulnerabilities, particularly through IoT malware. This paper explores the use of one-class classification, a method of unsupervised learning, which is especially suitable for unlabeled data, dynamic environments, and malware detection, which is a form of anomaly detection. We introduce the TF-IDF method for transforming nominal features into numerical formats that avoid information loss and manage dimensionality effectively, which is crucial for enhancing pattern recognition when combined with n-grams. …

Storage And Interaction Diagrams: Extending The Diagrammatic Framework Of Kinetic And Free-Body Diagrams To Other Conservation And Accounting Principles, Amir H. Danesh-Yazdi

Faculty Publications - Mechanical Engineering

After defining a system for analysis, a rigorous process is taught to students in their Statics and Dynamics courses on how to draw proper kinetic, free-body, and impulse-momentum diagrams. While numerous techniques and mnemonics have been mentioned in literature, any experienced instructor can tell a correct free-body diagram apart from an incorrect one. Unfortunately, this is not the case when considering scalar properties such as mass, energy, exergy, and entropy. Different fluid mechanics and thermodynamics texts have treated the diagrammatic representation of these properties either very poorly, or in the case of the latter two, not at all. In this …

Study Of Polymer-On-Polymer Cold Spray Deposition Windows Under Apparently Similar Conditions, Ülar Tiitma

Theses and Dissertations

The purpose of this thesis is to explore and expand the capabilities of polymer-on-polymer cold spray demonstrated herein using polyamide 6 (PA6)-based powder and substrates. Experiments were conducted using three different cold spray systems described in this work, permitting more in-depth examination of process response to different cold spray process control parameters, such as nominal system pressure and temperature. Two specific responses of interest were the deposition window (DW) and deposition efficiency (DE) of PA6. The DW was determined by performing several sprays at different calculated particle impact velocities and temperatures. The composite result from these experiments was identification of …

06.24.2024 Orsp Connect, Liz Williamson

ORED Newsletter

Research Networking Lunch (LINC), NIH podcast, CREW (Community First Research Center for Wellbeing and Creative Achievement) Premier Physics Experiment

Economic Planning And Operation Of Ev Charging Infrastructure Participating In Electric Power Markets, Diwas Paudel

USF Tampa Graduate Theses and Dissertations

As electric vehicles (EVs) are becoming more common, there are not enough charging infrastructures to keep up with the projected EV charging demands. This necessitates investment from private enterprises in the charging infrastructure, along with additional government investments, to support the expected EV growth. The profit potential of the EV charging business will be crucial in attracting private enterprises to invest in the infrastructure. The profitability of these infrastructures depends on their location and effective operation. The charging infrastructure needs to be strategically placed and sized in the service area of interest. Once built, they need a robust strategy to …

Pch-Em: A Solution To Information Loss In The Photon Transfer Method, Aaron J. Hendrickson, David P. Haefner, Stanley H. Chan, Nicholas R. Shade, Eric R. Fossum

Dartmouth Scholarship

Working from a Poisson-Gaussian noise model, a multisample extension of the photon counting histogram expectation-maximization (PCH-EM) algorithm is derived as a general-purpose alternative to the photon transfer (PT) method. This algorithm is derived from the same model, requires the same experimental data, and estimates the same sensor performance parameters as the time-tested PT method, all while obtaining lower uncertainty estimates. It is shown that as read noise becomes large, multiple data samples are necessary to capture enough information about the parameters of a device under test, justifying the need for a multisample extension. An estimation procedure is devised consisting of …

Transforming Organizational Cyber Security With Artificial Intelligence And Data-Driven Optimization, Soumyadeep Hore

USF Tampa Graduate Theses and Dissertations

This dissertation presents a comprehensive framework for enhancing organizational cybersecurity through data-driven intelligence. The research integrates multiple methodologies to tackle challenges in network intrusion detection and vulnerability management within cybersecurity operations centers (CSOCs). First, the research investigates vulnerability prioritization and mitigation techniques currently employed by CSOCs. To further streamline the vulnerability prioritization and mitigation process a machine learning (ML)-based Vulnerability Priority Scoring System (VPSS) is introduced, significantly improving the prioritization and mitigation of context-sensitive vulnerabilities. The VPSS outperforms traditional methods, reducing the cumulative vulnerability exposure score by up to 30% by considering both organizational context and vulnerability severity. Next, the …

Deep Learning Framework For Graph-Based Molecular Drug Discovery, Daniel Manu

Electrical and Computer Engineering ETDs

This dissertation proposes the GraphGANFed framework, which combines Graph Convolutional Networks (GCN), Generative Adversarial Networks (GAN), and Federated Learning (FL) to generate novel molecules while preserving data privacy. FL allows learning from distributed clients without sharing local datasets, GCN extracts molecular structural properties, and GAN generates new molecules retaining the learned properties. Extensive simulations on three benchmark datasets show GraphGANFed's effectiveness, producing molecules with high novelty (≈ 100) and diversity (> 0.9). Results indicate a trade-off among evaluation metrics, and the right dropout ratio avoids mode collapse. Additionally, Conditional GraphGANFed (cGraphGANFed) incorporates a critic network from Reinforcement Learning (RL) to …

Sliding Mode Control With Chattering Reduction, Suryamshu Ramesh

Doctoral Dissertations and Master's Theses

Sliding Mode Control is a powerful nonlinear control methodology that can handle parametric uncertainties and external disturbances. However, the discontinuous and high-frequency switching nature of the control law introduces the chattering phenomenon, which leads to potential actuator degradation, alterations to the desired response characteristics and, sometimes, instability during control implementation. The main objective of this thesis is to study Sliding Mode Control with chattering reduction. The Sliding Mode Control law involves an equivalent control component and a discontinuous control component. A disturbance estimation is performed based on Lyapunov analysis and adaptive control techniques and then included in the control law …

A Robust Data-Driven Framework For Artificial Intelligent Systems, Quoc H. Nguyen

USF Tampa Graduate Theses and Dissertations

Artificial Intelligence (AI) systems have demonstrated remarkable performance across various domains. However, their robustness remains a critical concern, particularly in terms of data and model reliability. This dissertation aims to address the challenges associated with building robust AI systems by focusing on two key aspects: data robustness and model robustness. Data robustness poses significant challenges, including data shift, concept shifting, limited and imbalanced datasets, and interoperability issues in IoT systems for data collection. Existing methods fall short in handling dynamic business objectives and evolving data landscapes effectively. To bridge these gaps, we propose an IoT framework that ensures interoperability, seamless …

Pathways From Engineering Programs To Labor Unions, Joey Valle, Lazlo Stepback, Polly Parkinson, Fawn Groves, Angela Minichiello, Matthew W. Ohland

Teacher Education and Leadership Student Research

According to the United States Bureau of Labor Statistics, union density amongst engineering workers within the US hovers around 7%. Despite hundreds of thousands of US engineers participating in the labor movement, engineering education on labor unions has been virtually non-existent within US higher education engineering programs. US higher education engineering programs are critical junctures in the making of engineers that have long histories of ensnarement by corporate industries with vested interests in undermining organized labor. This stark and significant absence of labor education coupled with decades-long denunciations that many engineering professional societies have made to discourage participation of engineers …

Wip: A Novel Learning Log Application For Classifying Learning Events Using Bloom’S Taxonomy, Alex M. Phan, Jenna Metera, Sonia Fereidoona, Cham Yang, Minju Kim, Carolyn L. Sandoval, Phuong Truong

Psychology Faculty Articles and Research

Learning can be a daunting and challenging process, particularly in engineering. While cognitive models for learning such as Bloom's taxonomy have been developed since the 1950s and evidenced to be useful in designing engineering courses, these models are not commonly explicitly taught in classrooms to help students manage and regulate their own learning. In highly demanding curriculum such as engineering, ineffective strategies can lead to poor academic performance that cascades throughout a student’s academic career. Feedback from traditional examinations often do not provide personalized and actionable changes to study habits (i.e., with suboptimal scores, students may know they need to …

Creative Insights Into Motion: Enhancing Human Activity Understanding With 3d Data Visualization And Annotation, Isaac Browen, Hector M. Camarillo-Abad, Franceli L. Cibrian, Trudi Di Qi

Engineering Faculty Articles and Research

This paper presents a novel 3D system for human motion analysis - Motion Data Visualization and Annotation (MoViAn). Designed to provide a comprehensive visual representation of 3D human motion data, MoViAn incorporates detailed visualization of gaze direction, hand movements, and object interactions, alongside an interactive interface for efficient data annotation. A user study involving eight participants indicates that MoViAn enables users to thoroughly explore and annotate human motion data, with System Usability Scale (SUS) results demonstrating a satisfactory usability level. The contribution of this paper lies in the development of an interactive and usable data analytics tool aimed at deepening …

Ai-Based Concept Inventories: Using Cognitive Diagnostic Computer Adaptivetesting In Lasso For Classroom Assessment, Jason Morphew, Amirreza Mehrabi, Ben Van Dusen, Jayson Nissen

School of Engineering Education Faculty Publications

Research-based concept inventories, such as the Force Concept Inventory, the Force and Motion Conceptual Evaluation, or the Energy and Momentum Conceptual Survey have played a pivotal role in designing and evaluating instruction in introductory physics courses. While these concept inventories have helped identify inequity in course instruction and have led to improved pedagogical methods, concerns about their ability to provide actionable feedback for formative assessment remain. In addition, using the same questions for both a pre- and a post- assessment leaves the potential for students learning the correct answers without undergoing conceptual change. To address these issues, we designed a …

Board 303: Implementing Oral Exams In Engineering Classes To Positively Impact Students' Learning, Huihui Qi, Carolyn L. Sandoval, Curt Schurgers, Marko Lubarda, Alex M. Phan, Saharnaz Baghdadchi, Maziar Ghazinejad, Minju Kim, Zongnan Wang, Nathan Delson

Psychology Faculty Articles and Research

In this paper, we present the outcomes of a three-year NSF IUSE project focused on the integration of oral examinations in engineering classes. Our exploration begins with an examination of the manifold advantages of oral exams, benefiting both students and instructors. We delve into oral exams as an assessment tool, elucidating their learning benefits and emotional advantages. While some of these aspects align with existing literature, we also unveil novel findings. Additionally, we address the benefits for instructors and Teaching Assistants (TAs), encompassing informative insights that can catalyze instructional improvements. Next, we share our strategies for mitigating the scalability challenges …

Board 125: Work In Progress: Faculty Experiences And Learning Through Oral-Assessment Implementation In Engineering Courses, Minju Kim, Carolyn L. Sandoval, Josephine Relaford-Doyle, Torus Washington Ii, Saharnaz Baghdadchi, Nathan Delson, Marko Lubarda, Alex M. Phan, Curt Schurgers, Huihui Qi

Psychology Faculty Articles and Research

This WIP qualitative research paper explores faculty experiences with implementing oral exams in high-enrollment undergraduate engineering courses at a research university. With a primary goal to improve conceptual mastery, as well as a desire to ensure academic integrity in the sudden move to remote instruction at the height of the pandemic, a group of faculty in Mechanical and Aerospace Engineering and Electrical and Computer Engineering departments implemented oral assessments in their own engineering courses across several quarters. They formed a research group with educational developers in a teaching and learning center on campus, and investigated the impact of oral assessments …

Automating An Industrial Dishwashing System Using Hardware-In-The-Loop Plc Simulation With Factory I/O, Paniz Khanmohammadi Hazaveh, Nathir Rawashdeh, Dunsten M. X. Dsouza, Joshua Olusola, Joshua Albrecht, Eric Houck

Michigan Tech Publications

While industrial automation is growing in many industries, the hospitality industry has not seen much technological innovation recently. This leaves a wealth of potential for the implementation of automated solutions, especially at large-scale operations, like university dining halls or cruise ship restaurants. This paper details a student project developed in the advanced programmable logic controllers class. It is part of the master program in mechatronics. Students work in groups in a creative setting, where they learn to integrate various automation technologies and learn to write scientific publications. The project implements the automation of a student dining hall dishwashing system using …

Plc Multi-Robot Integration Via Ethernet For Human Operated Quality Sampling, Jeevan S. Devagiri, Paniz Khanmohammadi Hazaveh, Nathir Rawashdeh, Sai Revanth Reddy Dudipala, Pratik Mohan Desmuhk, Aditya Prasad Karmarkar

Michigan Tech Publications

In automation, quality control inspection is a critical requirement to ensure product standards. The goal of this work is to insure product quality without interrupting the production line flow. The multi-robot system presented, connects a programmable logic controller (PLC), as the main controller, to a conveyor belt and two FANUC industrial robotic arms via EtherNet/IP. Human interaction is implemented to pick a work piece from the moving conveyor and return it with a quality label. This label is used by the PLC to execute the correct robot action; either to return the inspected part to the conveyor or discard it …

Model-Based Systems Engineering For Engineering Education Systems Simulation, Pallavi Singh

USF Tampa Graduate Theses and Dissertations

As the engineering education system continuously evolves to meet the demands of modern industry and society, there is a need for a methodology that would manage and resolve the complexities inherent in engineering educational systems. Model-based Systems Engineering (MBSE) is a structured approach to system design that utilizes models across all stages of the system's life cycle and supports requirements management, design, analysis, verification, and validation processes. While MBSE has been applied successfully in industries like defense, aerospace, and automotive, its application in engineering educational systems remains unexplored. This dissertation develops a dynamic model of the university-level engineering education system …

A First Step Towards Understanding Thermomechanical Behavior Of The Nb-Cr System Through Interatomic Potential Development And Molecular Dynamics Simulations, Lucas A. Heaton, Adib J. Samin

Faculty Publications

Utilizing a preliminary interatomic potential, this work represents an initial exploration into the thermomechanical behavior of NbCr solid solutions. Specifically, it examines the effect of different amounts of Cr solute, for which information in the literature is limited. The employed interatomic potential was developed according to the embedded atom model (EAM), and was trained on data derived from density functional theory calculations. While the potential demonstrated reasonable accuracy and predictive power when tested, various results highlight deficiencies and encourage further development and training. Mechanical strength, heat capacities, thermal expansion coefficients, and thermal conductivities were found to decrease with Cr content. …

How Could Future Climate Conditions Reshape A Devastating Lake-Effect Snow Storm?, Miraj Kayastha, Chenfu Huang, Jiali Wang, Yun Qian, Zhao Yang, T. C. Chakraborty, William J. Pringle, Robert D. Hetland, Pengfei Xue

Michigan Tech Publications

Lake-effect snow (LES) storms, characterized by heavy convective precipitation downwind of large lakes, pose significant coastal hazards with severe socioeconomic consequences in vulnerable areas. In this study, we investigate how devastating LES storms could evolve in the future by employing a storyline approach, using the LES storm that occurred over Buffalo, New York, in November 2022 as an example. Using a Pseudo-Global Warming method with a fully three-dimensional two-way coupled lake-land-atmosphere modeling system at a cloud-resolving 4 km resolution, we show a 14% increase in storm precipitation under the end-century warming. This increase in precipitation is accompanied by a transition …

Authentic Impediments: The Influence Of Identity Threat, Cultivated Perceptions, And Personality On Robophobia, Kate K. Mays

Human-Machine Communication

Considering possible impediments to authentic interactions with machines, this study explores contributors to robophobia from the potential dual influence of technological features and individual traits. Through a 2 x 2 x 3 online experiment, a robot’s physical human-likeness, gender, and status were manipulated and individual differences in robot beliefs and personality traits were measured. The effects of robot traits on phobia were non-significant. Overall, subjective beliefs about what robots are, cultivated by media portrayals, whether they threaten human identity, are moral, and have agency were the strongest predictors of robophobia. Those with higher internal locus of control and neuroticism, and …

What’S In A Name And/Or A Frame? Ontological Framing And Naming Of Social Actors And Social Responses, David Westerman, Michael Vosburg, Xinyue Liu, Patric R. Spence

Human-Machine Communication

Artificial intelligence (AI) is fundamentally a communication field. Thus, the study of how AI interacts with us is likely to be heavily driven by communication. The current study examined two things that may impact people’s perceptions of socialness of a social actor: one nonverbal (ontological frame) and one verbal (providing a name) with a 2 (human vs. robot) x 2 (named or not) experiment. Participants saw one of four videos of a study “host” crossing these conditions and responded to various perceptual measures about the socialness and task ability of that host. Overall, data were consistent with hypotheses that whether …

Exploring The Experiences Of African American Female Students In Engineering: A Narrative Literature Review, Anissa Guerin, Phd

Tapestry: Journal of Research in Education

Abstract

This narrative literature review delves into the experiences of African American female students in engineering, addressing their persistent underrepresentation in the field despite advancements in postsecondary education. By examining a broad range of research, the study explores the unique challenges faced by these students and investigates tools for their persistence and degree completion. The theoretical framework draws from intersectionality theory, emphasizing the intersecting identities of race and gender in shaping these experiences. Methodologically, a narrative literature review approach was employed, facilitating a comprehensive analysis of existing scholarship. Data collection involved rigorous criteria focusing specifically on empirical research or original …

Estimation Of Vehicle Traffic Parameters Using An Optical Distance Sensor For Use In Smart City Road Infrastructure, Rafał Burdzik, Ireneusz Celiński, Minvydas Ragulskis, Vinayak Ranjan, Jonas Matijošius

Henry M. Rowan College of Engineering Departmental Research

In recent decades, the dynamics of road vehicle traffic have significantly evolved, compelling traffic engineers to develop innovative traffic monitoring solutions, especially for dense road networks. Traditional methods for measuring traffic volume along road sections may no longer suffice for modern traffic control systems. This is particularly true for induction loops, a widely used method since the last century. In contrast, measuring techniques using microwaves or visible light offer better accuracy but are often hindered by the high cost of sensors. This paper presents new techniques for measuring traffic flow and other parameters that adapt to changing traffic dynamics using …

Anonymized Identity Recognition And Classification Using Privacy Preserving Facial Encoding, Manas Sanjay Pakalapati

USF Tampa Graduate Theses and Dissertations

The need for sharing large-scale datasets to train deep neural network models, particularly in healthcare, raises significant data security and privacy concerns. To address these issues, methods such as data encryption or encoding are utilized. These techniques can encrypt the data and make it unreadable to humans, while still retaining its usefulness for training models.

In this study, we investigate various image encoding techniques designed to protect privacy by making images unrecognizable while still retaining their usefulness for model training. Our investigation utilized publicly available facial databases and focused on evaluating the trade-offs inherent in image encoding techniques, with a …