Engineering Commons^™

Importance Of Soft Skills Comparative Study With Cybersecurity Professionals In The Manufacturing And Finance Critical Sectors, Stanley Mierzwa, Mary Lind

Center for Cybersecurity

Cybersecurity professionals require and will benefit from having strong and competent technical and soft skills, knowledge, and abilities. Cyber-attacks continue to plague our organizations and businesses, and finding the individuals with the skills needed for industry teams to contend with these broad and varying types of breaches is essential. This research article will outline the results of a comparative quantitative study that compares the importance of soft skills or nontechnical competencies by information security and cybersecurity professionals in the finance and manufacturing critical infrastructure sectors. This research study used a validated survey instrument from a previous seminal study to capture …

11.11.2024 Orsp Connect, Liz Williamson

ORED Newsletter

Radiation Safety Committee Updates

Getting Started with PIVOT_RP

Small Grants Program

Impact Of Coverage And Guest Residue On Polyproline Ii Helix Peptide Antifouling, Rebecca S. Ahn, Henry T. Grome, Sogol Asaei, Geeta Verma, Christina S. Dang, Harihara Baskaran, Julie N. Renner

Faculty Scholarship

Polyproline II (PPII) peptide sequences are recognized as promising biomaterials because of their attractive antifouling properties. However, the mechanisms behind their antifouling behavior have not been fully characterized. In this work we show that PPII peptide coverage, controlled by adsorption time, significantly reduces the fouling of bovine serum albumin (BSA, a model foulant). In addition, guest residues introduced into the PPII sequence are shown to significantly impact BSA adsorption as well as human mesenchymal stem cell (hMSC) spreading. This research will help guide future PPII peptide designs for incorporation into novel biomaterials.

A Benchmark Knowledge Graph Of Driving Scenes For Knowledge Completion Tasks, Ruwan Wickramarachchi, Cory Henson, Amit Sheth

Publications

Knowledge graph completion (KGC) is a problem of significant importance due to the inherent incompleteness in knowledge graphs (KGs). The current approaches for KGC using link prediction (LP) mostly rely on a common set of benchmark datasets that are quite different from real-world industrial KGs. Therefore, the adaptability of current LP methods for real-world KGs and domain-specific ap- plications is questionable. To support the evaluation of current and future LP and KGC methods for industrial KGs, we introduce DSceneKG, a suite of real-world driving scene knowledge graphs that are currently being used across various industrial applications. The DSceneKG is publicly …

Biomechanical Insights Of Head Trauma Based On Computational Simulation, Ghaidaa Abdulrahman Khalid

AUIQ Technical Engineering Science

Head injuries from falls are a major cause of illness and death in children due to trauma. Despite their prevalence and impact, there is limited understanding of how children's heads react during impact events. Infant Post-Mortem-Human-Surrogate (PMHS) testing, a reasonable method for studying impact biomechanics, faces significant restrictions due to emotional, moral, and ethical issues. Computer modeling, though holding significant promise for creating alternative pediatric head surrogates, encounters numerous challenges because of the intricacies of child growth and development. A finite-element (FE) model of an infant head was created from high-resolution CT scans, utilizing published data on tissue material properties. …

Large Dams Establishment Impacts On Different Environmental Aspects: A Review, Anas Ahmad

AUIQ Technical Engineering Science

The construction of large dams has been an essential component of the development of global infrastructure, offering significant advantages such as ensuring water storage, reducing the risk of flooding, and producing about 20% of the world's electricity through hydropower. On the other hand, these structures have significant and varied environmental effects. The environmental effects of large dams are critically examined in this analysis, with an emphasis on four main areas: fish biodiversity, riparian vegetation, sediment deposition, and water quality. The study estimates the degree of these consequences by examining global case studies and evaluating data from over 145 significant rivers …

Biocorrosion Analysis Via Multiscale Time Series Analysis, Victor Hugo Mendoza Vejar, Eliseo Hernandez Martinez, Hector Puebla

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Study Of Different Treatment Strategies In Epidemic Models Using Nonlinear Model Predictive Control, Hector Puebla, Luis A. Ricardez-Sandoval, Priti Kumar Roy

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Harvesting Modulation In Three Species Food Chains Using A Robust Control Approach, Hector Puebla, Mariana Rodriguez-Jara, Priti Kumar Roy

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Three-Dimensional Technique For Accurate Pavement Macrotexture Measurement Using Surface Volume Parameters, Alireza Pourhassan, Ahmed A. Gheni, Mohamed A. Elgawady

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study introduces a novel three-dimensional (3D) pavement macrotexture measurement technique using ISO 25178 Surface Volume Parameters (SVP). The method calculates pavement material volume and texture height using cutoff thresholds based on the cumulative probability density function of measured heights. The research aims to optimize these cutoff thresholds for accurate 3D analysis of pavement macrotexture. The study evaluates the performance of various 3D and 2D parameters—assessing their repeatability, reliability, and accuracy—across thirty pavement samples with diverse macrotexture conditions. Findings show that the 3D SVP method, with optimized cutoff thresholds, strongly correlates with sand patch mean texture depth (MTD) and exhibits …

Internet Of Things-Based Automated Solutions Utilizing Machine Learning For Smart And Real-Time Irrigation Management: A Review, Bryan Nsoh, Abia Katimbo, Hongzhi Guo, Derek M. Heeren, Hope Njuki Nakabuye, Xin Qiao, Yufeng Ge, Daran R. Rudnick, Joshua Wanyama, Erion Bwambale, Shafik Kiraga

Department of Agricultural and Biological Systems Engineering: Faculty Publications

This systematic review critically evaluates the current state and future potential of real-time, end-to-end smart, and automated irrigation management systems, focusing on integrating the Internet of Things (IoTs) and machine learning technologies for enhanced agricultural water use efficiency and crop productivity. In this review, the automation of each component is examined in the irrigation management pipeline from data collection to application while analyzing its effectiveness, efficiency, and integration with various precision agriculture technologies. It also investigates the role of the interoperability, standardization, and cybersecurity of IoT-based automated solutions for irrigation applications. Furthermore, in this review, the existing gaps are identified …

The Impact Of Hearing Aid User Speech On Environment Classification And Own Voice Listener Preferences, Robert Andrew Budinsky Iii

USF Tampa Graduate Theses and Dissertations

Hearing aids (HA) have improved over the past few decades with advanced signal processing, such as environment classification and background noise reduction, but are still limited by challenges related to when the user is speaking. These challenges include the potential interference a HA user’s voice has on device environment classification and the potential influence a HA has on own voice (OV) sound quality. However, the effects of OV on HA environment classification and signal processing are not well established, nor are the desired HA program settings regarding OV listening preferences. In this study, a combination of electroacoustic and behavioral methods …

If Androids Dream, Are They More Than Sheep?: Westworld, Robots And Legal Rights, Amanda J. Dipaolo

Dialogue: The Interdisciplinary Journal of Popular Culture and Pedagogy

The robot protagonists in HBO’s Westworld open the door to several philosophical and ethical questions, perhaps the most complex being: should androids be granted similar legal protections as people? Westworld offers its own exploration of what it means to be a person and places emphasis on one’s ability to feel and understand pain. With scientists and corporations actively working toward a future that includes robots that can display emotion in a way that can convincingly pass as that of a person’s, what happens when androids pass the Turing test, feel empathy, gain consciousness, are sentient, or develop free will? The …

Biodegradable Polymeric Microspheres For Magnetically Guided Drug Delivery To Tumors, Tyler Payson Green

Theses and Dissertations

This thesis investigates the feasibility of utilizing biodegradable polymeric microspheres loaded with the anticancer drug 5-fluorouracil (5FU) and superparamagnetic iron oxide nanoparticles (SPIONs) to magnetically deliver the cancer therapeutic 5FU to a target tumor in the human body. The primary method of material loading consisted of a w/o/w double emulsion mechanism which 1) loads and protects 5FU in the inner water phase consisting of distilled water and polyvinyl alcohol (PVA), 2) dispersed SPIONs in the biodegradable polymeric organic phase consisting of methylene chloride (MeCl2) for eventual magnetic transport, and 3) suspended these w/o emulsion droplets in an outer aqueous phase …

Boosting The Power Performance Of Microbial Fuel Cells By Using Dual Nanomaterial-Modified Carbon Felt Electrodes, Krishna Thapa, Wenyan Liu, Yuwei Zhang, David J. Westenberg, Yishu Zhou, Risheng Wang

Chemistry Faculty Research & Creative Works

Innovative design enhancements to microbial fuel cells (MFCs) are pivotal for improving their viability as renewable energy sources. This study introduces a dual approach to electrode modification, integrating polyaniline (PANI) and gold nanoparticles (AuNPs) on carbon felt (CF) anodes coupled with a unique cathode composed of DNA origami and chitosan. The synergistic effect of PANI and AuNPs significantly increases the hydrophilicity and conductivity of the anode, leading to a considerable surge in power density. Concurrently, the biocompatible DNA origami and chitosan-functionalized cathode facilitates efficient electron transfer without relying on conventional catalysts. Together, these modifications yield a 52.42% increase in the …

Trisc: Low-Cost Design Of Trigonometric Functions With Quasi Stochastic Computing, Mehran Shoushtari Moghadam, M. Hassan Najafi

Faculty Scholarship

Low-cost and hardware-efficient design of trigonometric functions is challenging. Stochastic computing (SC), an emerging computing model processing random bit-streams, offers promising solutions for this problem. The existing implementations, however, often overlook the importance of the data converters necessary to generate the needed bit-streams. While recent advancements in SC bit-stream generators focus on basic arithmetic operations such as multiplication and addition, energy-efficient SC design of non-linear functions demands attention to both the computation circuit and the bit-stream generator. This work introduces TriSC, a novel approach for SC-based design of trigonometric functions enjoying state-of-the-art (SOTA) quasi-random bit-streams. Unlike SOTA SC designs of …

Sensitivity Of Wavelet-Based Optical Flow Velocimetry (Wofv) To Common Experimental Error Sources, Bryan E. Schmidt, Gauresh Raj Jassal

Faculty Scholarship

The influence of several potential error sources and non-ideal experimental effects on the accuracy of a wavelet-based optical flow velocimetry (wOFV) method when applied to tracer particle images is evaluated using data from a series of synthetic flows. Out-of-plane particle displacements, severe image noise, laser sheet thickness reduction, and image intensity non-uniformity are shown to decrease the accuracy of wOFV in a similar manner to correlation-based particle image velocimetry (PIV). For the error sources tested, wOFV displays a similar or slightly increased sensitivity compared to PIV, but the wOFV results are still more accurate than PIV when the magnitude of …

Deterministic Transport Of Coupled Energetic Light-Ions And Neutrons With Application To Inertial Confinement Fusion, Kyle Beling

Nuclear Engineering ETDs

Numerical simulations of an inertial confinement fusion (ICF) target during the implosion process require high fidelity models of the radiation transport process. This work is interested in the transport of high-energy light-ions and neutrons in a background ICF plasma. As these energetic particles slow down, they experience knock-on (recoil) and thermonuclear (TN) collisions with the light-ions in the background plasma. These recoil and TN collisions excite the background light-ions causing them to transport through the plasma further exciting background light-ions. Mathematically, this cascading effect is described as a system of linear Boltzmann transport equations coupled through recoil and TN collision …

Physical Layer Entropy Analysis For Physical Unclonable Functions, Jenilee Jao

Electrical and Computer Engineering ETDs

Process variations within Field Programmable Gate Arrays (FPGAs) provide a rich source of entropy, making them well-suited for the implementation of Physical Unclonable Functions (PUFs). This dissertation presents three studies on FPGA-based PUFs. First, we explore a ring-oscillator (RO) PUF that leverages localized entropy from individual look-up table (LUT) primitives, analyzing design bias. Next, we investigate delay variations that occur through the routing network and switch matrices of FPGAs using a feature of Xilinx called dynamic partial reconfiguration (DPR). Finally, we evaluate entropy across FPGAs from Xilinx, Altera, and Microsemi using the Shift-Register Reconvergent-Fanout (SiRF) PUF architecture to compare path …

Single-Molecule Profiling Of Per- And Polyfluoroalkyl Substances By Cyclodextrin Mediated Host-Guest Interactions Within A Biological Nanopore, Xiaojun Wei, Aditya Choudhary, Leon Y. Wang, Lixing Yang, Mark J. Uline, Mario Tagliazucchi, Qian Wang, Dmitry Bedrov, Chang Liu

Faculty Publications

Biological nanopores are increasingly used in molecular sensing due to their single-molecule sensitivity. The detection of per- and polyfluoroalkyl substances (PFAS) like perfluorooctanoic acid and perfluorooctane sulfonic acid is critical due to their environmental prevalence and toxicity. Here, we investigate selective interactions between PFAS and four cyclodextrin (CD) variants (α-, β-, γ-, and 2-hydroxypropyl-γ-CD) within an α-hemolysin nanopore. We demonstrate that PFAS molecules can be electrochemically sensed by interacting with a γ-CD in a nanopore. Using HP-γ-CDs with increased steric resistance, we can identify homologs of the perfluoroalkyl carboxylic acid and the perfluoroalkyl sulfonic acid families and detect common PFAS …

Nature Inspired Optimization For Spectrum Sensing And Allocation In Cognitive Radio Networks, Saravanan R

Theses and Dissertations

Cognitive radio (CR) refers to intelligent radio technology that scans its environment to optimize spectrum use and adjusts its parameters accordingly. It employs a communication system that is aware of its surroundings, including spectrum usage and availability. A key aspect of CR is identifying idle channels by analyzing traffic patterns using effective learning strategies.

However, CRNs face challenges such as cross-layer design issues, spectrum sensing errors, hidden node problems, and complex spectrum management. Spectrum sensing is critical for accessing unused radio spectrum while minimizing interference. Efficient sensing techniques must be cost-effective, fast, and capable of detecting weak primary signals. Although …

Biofabrication Of Tissue Constructs Using Protein-In-Polysaccharide Bioinks For Muscle Regeneration, Harshavardhan B

Theses and Dissertations

Myocardial infarction (MI) and volumetric muscle loss (VML) are debilitating conditions that severely affect patient quality of life and challenge healthcare systems, particularly in diagnosis and treatment. Conventional therapies often result in long recovery periods with limited functional restoration. Advances in regenerative medicine, especially extrusion-based 3D bioprinting, offer promising potential to improve the regeneration of complex tissues by precisely depositing cells and biomaterials layer-by-layer to create tailored tissue constructs.

A critical challenge in muscle tissue regeneration is developing protein-polysaccharide bioinks that closely mimic the native muscle tissue microenvironment. In this study, two protein-inpolysaccharide bioinks (alginate-fibrinogen and methylcellulose-gelatin-alginate) were developed to …

A Study Of Fit And Friction Force As A Function Of The Printing Process For Fff 3d-Printed Piston–Cylinder Assembly, Philippe A. Passeraub, Quentin Allen, Elizabeth Clark, Michael Miles, Siddartha Berns, Maija Pearson, Sterling Allred, Jonah Brooks, Sylvain Hugon

ScholarsArchive Data

Dataset DOI: https://doi.org/10.26067/hjm6-3d45

The shared data comprises the experimental measurements performed presented in the figures 5, 6, 7, 9, 10, 11, 12, and in the tables for the following article:

Passeraub, P.A.; Allen, Q.; Clark, E.; Miles, M.; Berns, S.; Pearson, M.; Allred, S.; Brooks, J.; Hugon, S. A Study of Fit and Friction Force as a Function of the Printing Process for FFF 3D-Printed Piston–Cylinder Assembly. J. Manuf. Mater. Process. 2024, 8, 249. https://doi.org/10.3390/jmmp8060249

Quantifying Chemomechanical Weakening In Muscovite Mica With A Simple Micromechanical Model, Jordan J. Sickle, William M. Mook, Frank W. Delrio, Anastasia G. Ilgen, Wendelin Wright, Karin A. Dahmen

Faculty Journal Articles

In response to gradual nanoindentation, the surface of muscovite mica deforms by sudden stochastic nanometer-scale displacement bursts. Here, the statistics of these displacement events are interpreted using a statistical model previously used to model earthquakes to understand how chemically reactive environments alter the surface properties of this material. We show that the statistics of nanoindentation displacement bursts in muscovite mica are tuned by chemomechanical weakening in a manner similar to how the statistics of model events are tuned by a mechanical weakening parameter that describes how easily system-spanning cracks can be nucleated. Because the predictions of this model are independent …

A Distributed Secure System For Threads Detection In Crowded Environments Based On Biometric Facial Expression, Nourhan Zayed, Hassan I. Sayed, Ghada F. El-Kabbany

Mechanical Engineering

Ensuring security in crowded areas poses a significant problem due to the dense population and the intricate task of monitoring their behaviors. This research presents a real-time security system that utilizes facial expression analysis to identify potential threats. The technology utilizes sophisticated facial recognition and emotion detection techniques to accurately recognize emotions such as wrath, fear, and anxiety. These feelings can serve as indicators of suspicious activities or potential security risks. The system utilizes a Convolutional Neural Network (CNN) to classify facial expressions and recognize objects. In addition, it integrates an SVM classifier trained on features derived from the combined …

A Comparative Analysis Of Optimizing Classification Techniques On Fruits Images Dataset, Ghada F. Elkabbany, Youssef G. Fouad, Kerollos W. Youssef, Jannah A. Amir, Nourhan Zayed

Mechanical Engineering

Data mining; known as data dredging or data archeology; provides several techniques to extract new and interpretable information from existing datasets. This work presents a comparison of the performance of various classification techniques, specifically Support Vector Machine (SVM), Radial Basis Function (RBF), K-Nearest Neighbors (KNN), and decision trees, using images of fruits. An open-source dataset called fruits360 is used focusing on three specific fruits: pineapple, cocos, and avocado. This selection allows testing the classification techniques in different ways, as pineapples and cocos are similar in color, while cocos and avocados resemble each other in shape due to their oval-like geometry. …

Ignis: A One-Dimensional Laminar Flame Code, Jansen P. Berryhill, Jacob K. Spinti, David O. Lignell

Faculty Publications

Laminar flame codes have an important role in combustion modeling. They can provide a fundamental understanding of flame dynamics and provide a basis for building subgrid scale models in turbulent flow simulations. This paper presents Ignis, an open-source laminar flame code with the capability to offload submodels, like soot formation and radiation, using external packages and libraries. Ignis is written in C++, is documented with Doxygen, and is available on GitHub. It contains three different flame formulations: diffusion flames, premixed flames, and laminar flamelets solved in the mixture fraction coordinate. An option to facilitate creation of a diffusion flame table …

Advancing Drug Discovery And Disease Understanding Through Knowledge Graphs And Machine Learning Techniques, Swastika Tenkila Purushotham

Electrical and Computer Engineering ETDs

This thesis investigates knowledge graphs with particular reference to the NIH-funded Common Fund Data Ecosystem Data Distillery project. By combining data from nine Common Fund projects and other sources, this project has created a large knowledge graph using Neo4j. To find new and undiscovered drug targets, UNM’s Illuminating the Druggable Genome (IDG) Data Coordinating Center has supplied data and use cases. Condensed Knowledge Graph, a condensed version that is based on the Data Distillery Knowledge Graph, improves usability for IDG applications. Condensed Knowledge Graph research endeavors to enhance data organization through the categorization of disease terms, examination of Cerebellar Stroke …

Integrating Gis And Ca-Markov Model To Study Urban Dynamics Of Salem, India In Terms Of Pattern, Intensity And Direction, Linda Theres B

Theses and Dissertations

Urban populations have grown substantially in the modern era and the information age as people seek better living prospects. Currently, more than half of the world's population resides in the cities. Such growth must be monitored to ensure that people enjoy the boons of urban spaces, not the banes. Recognising the significance of urban studies, several researchers have attempted to analyse and predict urban dynamics using remote sensing, Geographic Information Systems, and machine learning methods. However, certain limitations exist, especially in improving the CAMarkov model's prediction performance. In addition, studies have suggested that growth characteristics, such as pattern, intensity, and …

Reducing Carbon Footprint In Ai: A Framework For Sustainable Training Of Large Language Models, Sunbal Iftikhar, Steven Davy

Conference papers

In the world of artificial intelligence (AI), large language models (LLMs) are leading the way, transforming how people understand and use language. These models have significantly impacted various domains, from natural language processing (NLP) to content generation, sparking a wave of innovation and exploration. However, this rapid progress brings to light the environmental implications of LLMs, particularly the significant energy consumption and carbon emissions during their training and operational phases. This requires a shift towards more energy-efficient practices in training and deploying LLMs, balancing AI innovation with environmental responsibility. This paper emphasizes the need for improving the energy efficiency of …