Engineering Commons^™

A Machine Learning Model Of Perturb-Seq Data For Use In Space Flight Gene Expression Profile Analysis, Liam F. Johnson, James Casaletto, Lauren Sanders, Sylvain Costes

Graduate Industrial Research Symposium

The genetic perturbations caused by spaceflight on biological systems tend to have a system-wide effect which is often difficult to deconvolute it into individual signals with specific points of origin. Single cell multi-omic data can provide a profile of the perturbational effects, but does not necessarily indicate the initial point of interference within the network. The objective of this project is to take advantage of large scale and genome-wide perturbational datasets by using them to train a tuned machine learning model that is capable of predicting the effects of unseen perturbations in new data. Perturb-Seq datasets are large libraries of …

Analyzing Video And Isobus Data To Understand Risk And Safety Practices For Roadside Mowing, Nathan Sprague, Timothy Wiegman, J. T. Evans

Graduate Industrial Research Symposium

In Indiana, roadside mowing covers 11,200 miles, presenting significant risks. The Indiana Department of Transportation (INDOT) seeks safer methods, including automated evaluations and autonomous robots. Analyzing 120 hours of video and ISOBUS data, we quantify mower interactions with the road and obstacles, finding mowers on -road up to 91% of the time in rural areas and 57% on highways. Key obstacles identified include signs and posts. This research aids in developing risk assessment models and safety evaluations, aiming to improve mowing safety and efficiency, and it supports future development of autonomous mowing technologies.

Characterizing Chemistry And Microbiomes During Continuous Anaerobic Codigestion Of Organics And Cattle Manure Digestate, Emily V. Schmitz, Hunter W. Schroer, Timothy E. Mattes, Craig L. Just

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

We characterized chemical and microbial responses to changes in the carbon-to-nitrogen ratio (C:N) and organic loading rate (OLR) during anaerobic codigestion (ACoD) of cattle manure digestate mixed with industrial organics. C:Ns of 25 and 35, both operating at OLRs ≤ 4 gVS L-1 d-1, sustained methane production averages of 0.36 ± 0.03 L gVS-1 d-1 and 0.32 ± 0.05 L gVS-1 d-1, respectively, throughout a 15-day period. Using 16S rRNA high-throughput sequencing coupled with PICRUSt2, taxonomy and predicted gene abundances were mapped to the major ACoD stages. C:N (25, 35) and the OLR (2, 4 gVS L-1 d-1) had minimal …

Farmer Perceptions Of Land Cover Classification Of Uas Imagery Of Coffee Agroecosystems In Puerto Rico, Jose Cabrera, Blake Neal, Kevin Adkins, Ronny Schroeder, Gwendolyn Klenke, Shannon Brines, Nayethzi Hernandez, Kevin Li, Riley Glancy, Ivette Perfecto

Publications

Highly diverse agroecosystems are increasingly of interest as the realization of farms’ invaluable ecosystem services grows. Simultaneously there has been an increased use of uncrewed aerial systems (UAS) in remote sensing as drones offer a finer spatial resolution and faster revisit rate than traditional satellites. With the combined utility of UAS and the attention on agroecosystems, there exists an opportunity to assess UAS practicality in highly biodiverse settings. In this study, we utilized UAS to collect fine-resolution 10-band multispectral imagery of coffee agroecosystems in Puerto Rico. We created land cover maps through a pixel-based supervised classification of each farm and …

A Phenomenological Thermodynamic Energy Density Function For Ferroelectric Wurtzite Al1−Xscxn Single Crystals, Yijia Gu, Andrew C. Meng, Aiden Ross, Long Qing Chen

Materials Science and Engineering Faculty Research & Creative Works

A Landau-Devonshire thermodynamic energy density function for ferroelectric wurtzite aluminum scandium nitride (Al1−xScxN) solid solution is developed. It is parametrized using available experimental and theoretical data, enabling the accurate reproduction of composition-dependent ferroelectric properties, such as spontaneous polarization, dielectric permittivity, and piezoelectric constants, for both bulk and thin films. The maximum concentration of Sc for the wurtzite structure to remain ferroelectric is found to be 61 at. %. A detailed analysis of Al1−xScxN thin films reveals that the ferroelectric phase transition and properties are insensitive to substrate strain. This study lays the foundation for quantitative modeling of novel ferroelectric wurtzite …

Resource Optimization For Air Mobility Under Emergency Situations, Yongxin (Jack) Liu

Math Department Colloquium Series

This project aims to improve air traffic management in emergencies. We first developed a GRU neural network to forecast weather-related airport capacity constraints using historical data, underscoring the value of real-time data analysis. We then optimized emergency evacuation air travel using Particle Swarm Optimization, demonstrating the ability to quickly aggregate evacuation flight resources cost-effectively. Finally, we provided a hybrid model combining a genetic algorithm with a neural network for evacuation planning, we show that neural network can be integrated accelerate genetic algorithms for efficient and performance assured system optimization.

Predicting The Water Situation In Jordan Using Auto Regressive Integrated Moving Average (Arima) Model, Shahed Al-Khateeb

Jerash for Research and Studies Journal مجلة جرش للبحوث والدراسات

Countries' water security is inextricably related to their economic position. Jordan is one of the world's five poorest countries regarding water resources. Climate change and water scarcity are threatening Jordan's economic growth and food security.

The objectives of the study are to use a statistical artificial intelligence model, which is called the Autoregressive Integrated Moving Average model to predict water productivity in Jordan and the world for the year 2021-2026, based on a real dataset from World Development Indicators from the World Bank. The study also aims to predict the total per capita share of fresh water based on the …

Performance Analysis Of Mobile Edge Computing Deployment Models In 5g Networks, Safaa Alali, Abdulkaim Assalem

Jerash for Research and Studies Journal مجلة جرش للبحوث والدراسات

5G networks and Mobile Edge Computing (MEC) are two main pillars of the next technological revolution. The first pillar provides ultra-reliable, high-bandwidth connectivity with ultra-low latency, while the second pillar gives mobile networks cloud computing capabilities at the edge of the network, enabling compute-dense, context-aware services for mobile users. So the next generation of mobile networks will see close integration between computing and communication. Therefore, it was necessary to study the different deployment options for edge hosts in 5G network, to know the effect of those options on the overall performance of the network. In this research, (Omnetpp 6.0) network …

Requirements For Employing Artificial Intelligence Applications In Higher Education And Its Challenges, Nuha Musa Otoom

Jerash for Research and Studies Journal مجلة جرش للبحوث والدراسات

The study aimed to determine the requirements for applications of artificial intelligence in the field of higher education, and its challenges. The descriptive survey method (content analysis) was used, where the researcher collected information and documents about artificial intelligence and the requirements for employing its applications and challenges, by referring to many reliable sources and references that contributed to Reaching the results that the research seeks to achieve, The results showed that there are a set of requirements for employing artificial intelligence applications in higher education, the most prominent of which is spreading a culture that supports artificial intelligence in …

Hybrid Deloading Control Strategy In Mmc-Based Wind Energy Conversion Systems For Enhanced Frequency Regulation, Jimiao Zhang, Jie Li

Henry M. Rowan College of Engineering Departmental Research

The growing integration of renewable energy sources, especially offshore wind (OSW), is introducing frequency stability challenges to electric power grids. This paper presents a novel hybrid deloading control strategy that enables modular multilevel converter (MMC)-based wind energy conversion systems (WECSs) to actively contribute to grid frequency regulation. This research investigates a permanent-magnet synchronous generator (PMSG)-based direct-drive configuration, sourced from the International Energy Agency’s (IEA’s) 15 MW reference turbine model. Specifically, phase-locked loop (PLL)-free grid-forming (GFM) control is employed via the grid-side converter (GSC), and DC-link voltage control is realized through the machine-side converter (MSC), both of which boost the energy …

Impact Of Welding Parameters In The Porosity Of A Dissimilar Welded Lap Joint Of Cp800-Xpf1000 Steel Weldment By Gmaw-P, Julio Cesar Garcia-Guerrero, Francisco Fernando Curiel-López, Víctor Hugo López-Morelos, Jaime Taha-Tijerina, Teresita Jesus Sánchez-Cruz, Maria Del Carmen Ramirez-Lopez, Eduardo Cortes-Carillo, Miguel Angel Quinones-Salinas

Informatics and Engineering Systems Faculty Publications

The use of the orthogonal array L4 allows a determination of the effect between the welding parameters peak current (Ip), background current (Ib) and frequency (f) on the porosities in a dissimilar welded lap joint of CP800 and XPF1000 steel weldment by the gas metal arc welding process with the transfer pulsed mode. According to the results, modifications in the welding parameters affect the heat input during welding. A heat input higher than 0.30 KJ/mm generates up to 0.32% porosity in the weld metal, while a heat input lower than 0.25 KJ/mm generates up to 28% porosity in the weld …

Composting Reduces The Risks Of Resistome In Beef Cattle Manure At The Transcriptional Level, Yuepeng Sun, Zachery R. Staley, Bryan Woodbury, Jean-Jack Riethoven, Xu Li

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Transcriptomic evidence is needed to determine whether composting is more effective than conventional stockpiling in mitigating the risk of resistome in livestock manure. The objective of this study is to compare composting and stockpiling for their effectiveness in reducing the risk of antibiotic resistance in beef cattle manure. Samples collected from the center and the surface of full-size manure stockpiling and composting piles were subject to metagenomic and metatranscriptomic analyses. While the distinctions in resistome between stockpiled and composted manure were not evident at the DNA level, the advantages of composting over stockpiling were evident at the transcriptomic level in …

Graph Theory And Graph Neural Network Assisted High-Throughput Crystal Structure Prediction And Screening For Energy Conversion And Storage, Joshua Ojih, Mohammed Al-Fahdi, Yagang Yao, Jianjun Hu, Ming Hu

Faculty Publications

Prediction of crystal structures with desirable material properties is a grand challenge in materials research, due to the enormous search space of possible combinations of elements and their countless arrangements in 3D space. Despite the recent progress of a few crystal structure prediction algorithms, most of those methods only target a few specific material families or are restricted to simple systems with limited element diversity. Moreover, these algorithms are usually coupled with first principles calculations and thus are computationally expensive and very time consuming. Therefore, establishing a workflow that can generate a large number of hypothetical structures with diverse elements …

Laboratory Exercise For The Radiometry Student, Michael A. Marciniak

Faculty Publications

The U.S. Air and Space Forces require optical expertise among their personnel. The Air Force Institute of Technology offers a graduate optics curriculum, which includes a three-course sequence to educate students in the optical concepts of radiometry and radiometric instrumentation. We find radiometry is often a deceptively difficult concept for students to master. To address this, we have developed an experiment in our optics-laboratory coursework to help them gain this mastery. A Fourier-transform infrared spectrometer (FTS) is used to collect spectral data from an unknown sample. FTS calibration and data collection are discussed here, as are the two specific samples …

Raman Spectroscopy Of Gan On Si With Varied Thin Film Thickness For High-Temperature Semiconductor Devices, Manika Tun Nafisa

Symposium of Student Scholars

This study explores the potential of GaN on Si thin films as a promising material for high-temperature semiconductor devices, owing to its impressive thermal properties and performance characteristics. Two GaN on Si samples were grown using Metal Organic Chemical Vapor Deposition (MOCVD), with different film thicknesses, and their potential for high-temperature applications was comprehensively assessed by performing Raman spectroscopy at various temperature levels. The experimental results provided valuable insights into the material's behavior at elevated temperatures. At 300°C, the GaN E₂ (High) peak showed a Raman shift at 562.38 cm⁻¹ for high-thickness samples and 561.49 cm⁻¹ for low-thickness samples. …

Temporospatial Deep Learning Strategies For Prediction Of Disease Progression In Radiology, John D. Mayfield

USF Tampa Graduate Theses and Dissertations

While the fields of machine learning and medicine are deeply rooted in axiomatic scientific principles, there is an element of art that makes the practice imperfect, yet innately human. As the two fields have seen the greatest overlap in their collective history, there remains a chasm between them in terms of practical translation for the patients who desire and deserve personalized medicine. As presented in this dissertation, I and my collaborators have contributed to the groundwork for future exploration of predicting disease progression by identifying signals within sequential medical imaging to provide a temporospatial relationship upon which we can make …

Mbe Growth Of Sb Based Alloys Using Interfacial Misfit Arrays For Mwir Devices, Fatih Furkan Ince

Optical Science and Engineering ETDs

This thesis explores the monolithic integration of antimonide based narrow bandgap semiconductors on commercially available substrates for mid-wave infrared (MWIR) devices. The research focuses on the integration and growth of antimonide based alloys using the interfacial misfit dislocation (IMF) arrays to enhance the cost efficiency, manufacturability and performance. The study particularly investigates the relaxation mechanisms of antimonide alloys on InAs and InP substrates, assessing the impact of mismatch strain on the quality of epilayers. The IMF arrays are examined using high-resolution transmission electron microscopy (HR-TEM) and x-ray diffraction (XRD), revealing information about the effective strain relief mechanisms behind IMF arrays …

Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor

Faculty Publications

Once realized, autonomous aerial refueling will revolutionize unmanned aviation by removing current range and endurance limitations. Previous attempts at establishing vision-based solutions have come close but rely heavily on near perfect extrinsic camera calibrations that often change midflight. In this paper, we propose dual object detection, a technique that overcomes such requirement by transforming aerial refueling imagery directly into receiver aircraft reference frame probe-to-drogue vectors regardless of camera position and orientation. These vectors are precisely what autonomous agents need to successfully maneuver the tanker and receiver aircraft in synchronous flight during refueling operations. Our method follows a common 4-stage process …

New Models For Estimating Minimum Miscibility Pressure Of Pure And Impure Carbon Dioxide Using Artificial Intelligence Techniques, Attia Attia, Ahmed Ashraf Soliman Eng., John Shahat Eng., Sayed Gomaa Prof., Fares Ashraf El Salamony Prof.

Petroleum Engineering and Gas

CO2 miscible flooding stands out as one of the most-commonly employed and promising processes in enhanced oil recovery. The key factor for ensuring success in designing and executing CO2 injection projects lies in the precise determination of the Minimum Miscibility Pressure (MMP). Despite significant research endeavors in measuring and predicting the MMP through the use of empirical, analytical, numerical, and experimental approaches, the need for a comprehensive, accurate, efficient, and easy-to-use model remains. In response to this gap, our study developed various predictive models with 205 datasets, including well-established ones such as Artificial Neural Network (ANN), Random Forest (RF), and …

Assessment Of Educational Facilities In Osogobo Metropolis Nigeria, Dele S. Ogundahunsi, Martins B. Gasu, Samuel B. Adedotun, Olayiwola Olayode, Akintayo O. Ojo, Christiana Olayode

CSID Journal of Infrastructure Development

This study assessed educational facilities in the Osogbo metropolis, Nigeria, aiming to evaluate the available educational facilities, examine student and staff satisfaction levels, and analyze their availability across schools in the area. The sample consisted of 476 schools, from which 73 were randomly selected. A multistage sampling procedure was employed to sample 1,863 pupils/students and 87 teachers for questionnaire administration, complemented by observation. Data were analyzed using Mean Weighted Average, Summation of Weighted Value, and Analysis of Variance. Findings showed that 63.4% of primary schools had the listed facilities, while 75% of secondary schools reported 81% availability. Public primary school …

Increasing The Dissolution Rate Of Polystyrene Waste In Solvent-Based Recycling, Rita Kol, Ruben Denolf, Gwendoline Bernaert, Dave Manhaeghe, Ezra Bar Ziv, George W. Huber, Norbert Niessner, Michiel Verswyvel, Angeliki Lemonidou, Dimitris S. Achilias, Steven De Meester

Michigan Tech Publications

Solvent-based recycling of plastic waste is a promising approach for cleaning polymer chains without breaking them. However, the time required to actually dissolve the polymer in a lab environment can take hours. Different factors play a role in polymer dissolution, including temperature, turbulence, and solvent properties. This work provides insights into bottlenecks and opportunities to increase the dissolution rate of polystyrene in solvents. The paper starts with a broad solvent screening in which the dissolution times are compared. Based on the experimental results, a multiple regression model is constructed, which shows that within several solvent properties, the viscosity of the …

Western Science And Eastern Zen To Seek The Origin Of Truth: Philosophical Background Of Scale Modeling, Kozo Saito

Progress in Scale Modeling, an International Journal

This article was written to introduce philosophical background of scale modeling, where Zen philosophy was applied to overcome the limitation of logical thinking and hypotheses-driven deductive science. Three specific reasons are as follows. The first is related to the law approach in scale modeling; it uses the kufu principle, originated in Zen Buddhism, together with the other three scientific methods: experimental, theoretical, and computational. The second reason is because scale modeling seeks relativistic understanding by attempting to realize similarity; the concept is closer to Eastern philosophy rather than absolute understanding cultivated by deductive science. The third is in the educational …

03.04.2024 Orsp Connect, Liz Williamson

ORED Newsletter

ORSP On-demand Training for PIs, Liz Williamson spotlight, Grant for Studying Clean Energy Production Awarded, NIH Simplified Peer Review Framework.

Machine Learning A Universal Harmonic Interatomic Potential For Predicting Phonons In Crystalline Solids, Huiju Lee, Yi Xia

Mechanical and Materials Engineering Faculty Publications and Presentations

Phonons, as quantized vibrational modes in crystalline materials, play a crucial role in determining a wide range of physical properties, such as thermal and electrical conductivity, making their study a cornerstone in materials science. In this study, we present a simple yet effective strategy for deep learning harmonic phonons in crystalline solids by leveraging existing phonon databases and state-of-the-art machine learning techniques. The key of our method lies in transforming existing phonon datasets, primarily represented in interatomic force constants, into a force-displacement representation suitable for training machine learning universal interatomic potentials. By applying our approach to one of the largest …

Adsorption Of Crystal Violet Dye From Synthetic Wastewater By Ball-Milled Royal Palm Leaf Sheath, Neloy Sen, Nawrin Rahman Shefa, Kismot Reza, Sk Md Ali Zaker Shawon, Md. Wasikur Rahman

Physics & Astronomy Faculty Publications

The current study shows that using a batch approach to remove crystal violet dye from synthetic wastewater is feasible when using royal palm leaf sheath powder as an adsorbent. In order to investigate the effects of many parameters, including starting concentration, pH effect, dye concentration, adsorbent dose, contact time, and temperature, experiments were carried out under various operating conditions. Maximum removal was obtained at pH 6 and at a concentration of 100 ppm, which are considered as ideal values. The influence of pH and dye concentration was shown to be substantial. Langmuir, Freundlich, and Temkin isotherm models were fitted to …

How Can Generative Ai (Genai) Enhance Or Hinder Qualitative Studies? A Critical Appraisal From South Asia, Nepal, Niroj Dahal

The Qualitative Report

Qualitative researchers can benefit from using generative artificial intelligence (GenAI), such as different versions of ChatGPT—GPT-3.5 or GPT-4, Google Bard—now renamed as a Gemini, and Bing Chat—now renamed as a Copilot, in their studies. The scientific community has used artificial intelligence (AI) tools in various ways. However, using GenAI has generated concerns regarding potential research unreliability, bias, and unethical outcomes in GenAI-generated research results. Considering these concerns, the purpose of this commentary is to review the current use of GenAI in qualitative research, including its strengths, limitations, and ethical dilemmas from the perspective of critical appraisal from South Asia, Nepal. …

Blow-Spun Hybrid Pcl-Peo/Hnts Scaffolds With Enhanced Biological And Mechanical Properties, Meichen Liu

Doctoral Dissertations

With the development of technology and engineering, nanotechnology has been a multidisciplinary scientific field applied in nearly all science areas, including medicine, genetics, food industry, robotics. In this respect, nanomedicine has gained increasing attention and been a useful, effective therapy for cancer diagnosis, gene transfer, and drug delivery. To design an ideal nano drug delivery system with controlled drug releasing and improved encapsulated drug’s pharmacokinetic and pharmacodynamic profiles, hydrogels and polymer composites have witnessed increased research interest during the last decades. Recently, numerous polymers have been studied to fabricate the ideal wound dressing with biocompatibility, biodegradability, porous structural, and suitable …

Development Of An Integrated Workflow For Nucleosome Modeling And Simulations, Ran Sun

Doctoral Dissertations

Nucleosomes are the building blocks of eukaryotic genomes and thus fundamental to to all genetic processes. Any protein or drug that binds DNA must either cooperate or compete with nucleosomes. Given that a nucleosome contains 147 base pairs of DNA, there are approximately 4^147 or 10^88 possible sequences for a single nucleosome. Exhaustive studies are not possible. However, genome wide association studies can identify individual nucleosomes of interest to a specific mechanism, and today's supercomputers enable comparative simulation studies of 10s to 100s of nucleosomes. The goal of this thesis is to develop and present and end-to-end workflow that serves …

Selective Targeting Of Microglia By Quantum Dots And Green Synthesis Of Metal Organic Biohybrids; Applications In Dynamic Cell And Assay Systems, Navya Uppu

Doctoral Dissertations

Neurological disorders are the leading cause of physical and cognitive disability across the globe, currently affecting approximately 15% of the worldwide population. Part of the glioma microenvironment are microglia, resident immune cells of the CNS that were thought to be involved in the pathogenesis of diverse neurodegenerative diseases. Though it remains uncertain what triggers microglial activation in these disorders, targeting and tracking microglial functions using nanotools like Quantum Dots (QDs) could help us elucidate them in such neurological diseases. This research focuses on the comparative study of different QDs formulations and their selective uptake by brain microglia in primary cultures …

Development And Characterization Of Injectable, Cell-Encapsulated Chitosan-Genipin Hydrogels, Tyler R. Priddy-Arrington

Doctoral Dissertations

Over 150,000 patients undergo lower extremity amputation every year in the United States, most commonly caused by complications due to diabetes mellitus, peripheral vascular disease, and trauma. Diseased or damaged tissues that are unable to naturally repair themselves must either be fully removed or replaced, otherwise the injuries can lead to further complications such as infection or death. Tissue resection and amputation, as forms of removing damaged tissue, are not favorable to patients as they can cause pain, reduce mobility, and negatively impact quality of life. However, replacing lost or damaged tissues with donor tissues carries the risks of tissue …