Physical Sciences and Mathematics Commons^™

Unlocking The Black Box: Evaluating Xai Through A Mixed Methods Approach Combining Quantitative Standardised Scales And Qualitative Techniques, Helen Sheridan, Dympna O'Sullivan, Emma Murphy

Academic Posters Collection

In 1950 when Alan Turing first published his groundbreaking paper, computing machinery and intelligence and asked “Can machines think?” a new era of research exploring the intelligence of digital computers and their ability to deceive and/or imitate a human was ignited. From these first explorations of AI to modern day artificial intelligence and machine learning systems many advances, breakthroughs and improved algorithms have been developed usually advancing at an exponential pace. This has resulted in the pervasive use of AI systems in the processing of data. Concerns have been expressed related to biased decisions by AI systems around the processing …

Synthetic Heart Sound Dataset, Davoud Shariat Panah, Andrew Hines, Susan Mckeever

Datasets

The repository contains synthetic heart sound recordings. The publication related to this dataset is "Exploring the impact of noise and degradations on heart sound classification models", Biomedical Signal Processing and Control journal.

Comparative Adjudication Of Noisy And Subjective Data Annotation Disagreements For Deep Learning, Scott David Williams

Browse all Theses and Dissertations

Obtaining accurate inferences from deep neural networks is difficult when models are trained on instances with conflicting labels. Algorithmic recognition of online hate speech illustrates this. No human annotator is perfectly reliable, so multiple annotators evaluate and label online posts in a corpus. Labeling scheme limitations, differences in annotators' beliefs, and limits to annotators' honesty and carefulness cause some labels to disagree. Consequently, decisive and accurate inferences become less likely. Some practical applications such as social research can tolerate some indecisiveness. However, an online platform using an indecisive classifier for automated content moderation could create more problems than it solves. …

Application Of The Hvsr Technique To Map The Depth And Elevation Of The Bedrock Underlying Wright State University Campus, Dayton, Ohio, Devika L. Ghuge

Browse all Theses and Dissertations

Estimating sediment thickness and bedrock surface geometry is critical for many hydrogeologic studies. The horizontal-to-vertical spectral ratio (HVSR), a passive seismic method is a unique, non-invasive technique for speedily estimating bedrock depth. To record ambient seismic noise, the H/V method employs a single broadband three-component seismometer. A field assessment was conducted on the Wright State University Campus in Dayton, Ohio, to determine the depth (z) and elevation of the bedrock. Data were collected at 60 different locations. A known value for the depth of bedrock on campus was determined using the log from a local water well available from the …

Data-Driven Strategies For Pain Management In Patients With Sickle Cell Disease, Swati Padhee

Browse all Theses and Dissertations

This research explores data-driven AI techniques to extract insights from relevant medical data for pain management in patients with Sickle Cell Disease (SCD). SCD is an inherited red blood cell disorder that can cause a multitude of complications throughout an individual’s life. Most patients with SCD experience repeated, unpredictable episodes of severe pain. Arguably, the most challenging aspect of treating pain episodes in SCD is assessing and interpreting the patient’s pain intensity level due to the subjective nature of pain. In this study, we leverage multiple data-driven AI techniques to improve pain management in patients with SCD. The proposed approaches …

Solidity Compiler Version Identification On Smart Contract Bytecode, Lakshmi Prasanna Katyayani Devasani

Browse all Theses and Dissertations

Identifying the version of the Solidity compiler used to create an Ethereum contract is a challenging task, especially when the contract bytecode is obfuscated and lacks explicit metadata. Ethereum bytecode is highly complex, as it is generated by the Solidity compiler, which translates high-level programming constructs into low-level, stack-based code. Additionally, the Solidity compiler undergoes frequent updates and modifications, resulting in continuous evolution of bytecode patterns. To address this challenge, we propose using deep learning models to analyze Ethereum bytecodes and infer the compiler version that produced them. A large number of Ethereum contracts and the corresponding compiler versions is …

Encryption And Compression Classification Of Internet Of Things Traffic, Mariam Najdat M Saleh

Browse all Theses and Dissertations

The Internet of Things (IoT) is used in many fields that generate sensitive data, such as healthcare and surveillance. Increased reliance on IoT raised serious information security concerns. This dissertation presents three systems for analyzing and classifying IoT traffic using Deep Learning (DL) models, and a large dataset is built for systems training and evaluation. The first system studies the effect of combining raw data and engineered features to optimize the classification of encrypted and compressed IoT traffic using Engineered Features Classification (EFC), Raw Data Classification (RDC), and combined Raw Data and Engineered Features Classification (RDEFC) approaches. Our results demonstrate …

Merit Study Of Battery Or Hydrogen Energy Storage For Large Scale, Combined Wind And Solar Electricity Generation, Ashley K. Moore

Browse all Theses and Dissertations

In the past several years, the energy sector has experienced a rapid increase in renewable energy installations due to declining capital costs for wind turbines, solar panels, and batteries. Wind and solar electricity generation are intermittent in nature which must be considered in an economic analysis if a fair comparison is to be made between electricity supplied from renewables and electricity purchased from the grid. Energy storage reduces curtailment of wind and solar and minimizes electricity purchases from the grid by storing excess electricity and deploying the energy at times when demand exceeds the renewable energy supply. The objective of …

Modeling Growth And Stress Factors For Converted Silvopasture Systems In The Missouri Ozarks, Bailee N. Suedmeyer

MSU Graduate Theses

Silvopasture systems are becoming increasingly popular among sustainable agriculture ranchers, due to the increase in knowledge of benefits to the cattle and ability to grow cool season grasses beneath the canopy. This project focuses on the forest crop aspect of silvopasture systems from monitoring of the health of the trees over time to recommendations for thinning management to keep it functioning as viable silvopasture. The study site consists of five acres of upland hardwood forest area in Southern Missouri with 18 monumented fixed area plots. Arial and ground data was collected at each plot throughout the growing season, along with …

Bimee: Blockchain Based Incentive Mechanism Considering Endowment Effect, Jayanth Madupalli

MSU Graduate Theses

Crowdsensing, a paradigm in modern data collection, harnesses the collective power of mobile users equipped with sensory devices to contribute valuable data based on task-specific criteria. The efficacy of crowdsensing relies on sustained engagement from proficient users over extended periods. Incentivizing long-term participation is crucial, and blockchain technology emerges as a promising framework, providing a decentralized and immutable ledger. However, existing blockchain-based incentive mechanisms for crowdsensing encounter challenges. Firstly, they often overlook users' inherent bias towards loss aversion, a psychological phenomenon where individuals prioritize avoiding losses over acquiring equivalent rewards. Secondly, fairness issues arise, especially concerning newly participating users in …

Dataset: Global Seamless Tidal Simulation Using A 3d Unstructured-Grid Model, Yinglong J. Zhang, Tomas Fernandez-Montblanc, William Pringle, Hao-Cheng Yu, Linlin Cui, Saeed Moghimi

Data

Dataset:

We present a new 3D unstructured-grid global ocean model to study both tidal and non-tidal processes, with a focus on the total water elevation. Unlike existing global ocean models, the new model resolves estuaries and rivers down to ~8m without the need for grid nesting. The model is validated with both satellite and in-situ observations for elevation, temperature and salinity. Tidal elevation solutions have a mean complex RMSE of 4.2 cm for M2 and 5.4 cm for all 5 major constituents in the deep ocean (the RMSEs for the other 4 constituents (S2, N2, K1, O1) are respectively: 2.05cm, …

Cloud Seeding, Wildfire Smoke Emissions, And Solar Geoengineering: Why Is Climate Modification Unregulated?, Karen Bradshaw, Monika U. Ehrman

Faculty Journal Articles and Book Chapters

This Article is the first to identify that companies and agencies systemically modify climatic airspaces through wildfire smoke emissions, weather modification (cloud seeding to cause rain), and solar geoengineering. Climate modification is not a conspiracy theory or a hypothetical: it is happening, and it is changing weather patterns. Yet, climate modification is almost wholly unregulated. Further, it is also not recorded or tracked in systemic ways. That is to say, even government agencies do not have comprehensive records of whether; how often; or how much climate modification is occurring. The data is simply not gathered, aggregated, or stored. As a …

Broadening Views Of Mathematical Creativity: Inclusion Of The Undergraduate Student Perspective, Emily Cilli-Turner, V. Rani Satyam, Miloš Savić, Gail Tang, Houssein El Turkey, Gulden Karakok

Mathematics: Faculty Scholarship

Numerous conceptions of creativity exist in the literature; yet these are commonly based on the perspectives of professional mathematicians. Including students’ perspectives in creativity is crucial not only for a more robust picture of what it means to be creative but also to combat damaging dominant narratives about who can be creative. We examined calculus students’ views of mathematical creativity, a group not often considered in the creativity literature, to broaden future considerations of creativity. Interviews with N=55 calculus students across various institutions were conducted. Results show six emergent wide-ranging themes of these students’ creativity views: actions and attitudes, application, …

Advancing Estuarine Shoreline Change Analysis Using Small Uncrewed Autonomous Systems, Thomas R. Allen, Devon Eulie, Mariko Polk, George Mcleod, Robert Stuart, Alexandra Garnand, A. J. Manning (Editor)

Political Science & Geography Faculty Publications

Estuarine shorelines face the threats of accelerating sea-level rise, recurrent storms, and disruptions of natural sediment and ecological adjustments owing to historic human interventions. The growing availability and technical capability of uncrewed systems (UxS), including remote or autonomous aerial and surface vessels, provide new opportunities to study and understand estuarine shoreline changes. This chapter assesses the state of the technology, interdisciplinary science and engineering literature, and presents case studies from the Chesapeake Bay, Virginia, and coastal North Carolina, USA, that demonstrate new insights into coastal geomorphic processes and applications to managing complex and dynamic estuarine shorelines. These technologies enhance the …

Development Of A Simevents Model For Printed Circuit Board (Pcb) Assembly Processes, Siqin Dong, Mileta Tomovic, Krishnanand Kaipa

Engineering Technology Faculty Publications

Printed circuit boards (PCBs) are the foundational building blocks of most modern electronic devices. PCB assembly is defined as the process of mounting different electronic components on a PCB. Circuit board assembly utilizes an automated technique with most steps completed by machines for different operations (e.g., pick-and-place components, soldering, etc.). In this paper, details of a student course project, carried out at Old Dominion University, on the design and simulation of PCB assembly processes based on MATLAB discrete-event system are presented. An essential component in the advanced manufacturing technology course is the hands-on experience where students implement multiple software simulation …

Harvesting Publication Data To The Institutional Repository From Scopus, Web Of Science, Dimensions And Unpaywall Using A Custom R Script, Yrjo Lappalainen, Nikesh Narayanan

All Works

Institutional repositories are established tools for archiving and increasing the visibility and availability of academic outputs. Although the potential benefits of institutional repositories are well researched and many funders and institutions already mandate open access publishing via gold or green open access routes, institutional repositories often struggle with lack of growth and sustained workflows for content recruitment. Institutions have come up with various (and often creative) workflows for populating their repositories, including institutional open access mandates, library-mediated self-archiving, fully or partially automated content harvesting and integrations between repositories and Current Research Information Systems (CRIS). Zayed University launched the ZU Scholars …

Understanding Influencers Of College Major Decision: The Uae Case, Mohammad Amin Kuhail, Joao Negreiros, Haseena Al Katheeri, Sana Khan, Shurooq Almutairi

All Works

This study aims to understand and analyze what influences female students to choose a college major in the United Arab Emirates (UAE). To accomplish our target, we conducted a survey with mostly female first-year undergraduate students (N = 496) at Zayed University to understand the personal, social, and financial factors influencing students’ major choices. Further, this study also asked students to specify their actions before deciding on their major and assessed the information that could be helpful for future students to decide on their majors. Last, the study investigated how Science, Technology, Engineering, and Mathematics (STEM) students differ from other …

Social Media Bot Detection With Deep Learning Methods: A Systematic Review, Kadhim Hayawi, Susmita Saha, Mohammad Mehedy Masud, Sujith Samuel Mathew, Mohammed Kaosar

All Works

Social bots are automated social media accounts governed by software and controlled by humans at the backend. Some bots have good purposes, such as automatically posting information about news and even to provide help during emergencies. Nevertheless, bots have also been used for malicious purposes, such as for posting fake news or rumour spreading or manipulating political campaigns. There are existing mechanisms that allow for detection and removal of malicious bots automatically. However, the bot landscape changes as the bot creators use more sophisticated methods to avoid being detected. Therefore, new mechanisms for discerning between legitimate and bot accounts are …

Model Based Systems Engineering With A Docs-As-Code Approach For The Sealion Cubesat Project, Kevin Chiu, Sean Marquez, Sharanabasaweshwara Asundi

Mechanical & Aerospace Engineering Faculty Publications

The SeaLion mission architecture team sought to create a model-based systems engineering approach to assist improving CubeSat success rates as well as for the SeaLion CubeSat project to guide an implementation for the flight software. This is important because university CubeSat teams are growing in number but often have untrained students as their core personnel. This was done using a document-as-code, or docs-as-code, approach. With this the team created tools for the systems architecture with the Mach 30 Modeling Language to create an architecture that is easy to learn and use even for newly admitted team members with little to …

Remote Ambient Aerosols Found In The Southern Great Plains And Eastern North Atlantic: A Comprehensive Analysis Of Optical Behavior And Aerosol-Cloud Interaction, Daniel J. Bonanno

University of the Pacific Theses and Dissertations

The data presented in this thesis showcases the investigation of various aerosol types and the role they play in the hydrological system and global climate models. Long-range transport aerosols, including atmospheric soot, mineral dust, and ammonium sulfate, in addition to near-site sources such as secondary organic aerosols (SOAs), sea spray, aliphatic hydrocarbons, and other organics, are prioritized in the analysis of two separate remote field studies. Each of these campaigns revealed the juxtaposition between dry summer months and wet winter months, and the connection between seasonal variability and sample collection. Two spectromicroscopic techniques were used to elucidate chemical composition, morphology …

Beam Dynamics Simulations And Systematic Studies For The Muon G-2 Experiment At Fermilab, Abel M. Lorente Campos

Theses and Dissertations--Physics and Astronomy

The first results of the positive muon anomalous magnetic moment from the Muon g-2 Experiment at Fermilab differs from the Standard Model prediction by 3.3 standard deviations, with an experimental uncertainty of 0.46 ppm. Combining this result with the previous measurement from the Brookhaven National Laboratory, it sets the difference between experiment and theory at 4.2 standard deviations. The goal of the Muon g-2 Experiment at Fermilab is to increase this discrepancy to 5 standard deviations, which would require unprecedented precision in the measurements of 0.14 ppm. Of significant importance to achieving this precision, beam and spin dynamics simulations are …

Application Of A Gene Modular Approach For Clinical Phenotype Genotype Association And Sepsis Prediction Using Machine Learning In Meningococcal Sepsis, Asrar Rashid, Arif R. Anwary, Feras Al-Obeidat, Joe Brierley, Mohammed Uddin, Hoda Alkhzaimi, Amrita Sarpal, Mohammed Toufiq, Zainab A. Malik, Raziya Kadwa, Praveen Khilnani, M. Guftar Shaikh, Govind Benakatti, Javed Sharief, Syed Ahmed Zaki, Abdulrahman Zeyada, Ahmed Al-Dubai, Wael Hafez, Amir Hussain

All Works

Sepsis is a major global health concern causing high morbidity and mortality rates. Our study utilized a Meningococcal Septic Shock (MSS) temporal dataset to investigate the correlation between gene expression (GE) changes and clinical features. The research used Weighted Gene Co-expression Network Analysis (WGCNA) to establish links between gene expression and clinical parameters in infants admitted to the Pediatric Critical Care Unit with MSS. Additionally, various machine learning (ML) algorithms, including Support Vector Machine (SVM), Naive Bayes, K-Nearest Neighbors (KNN), Decision Tree, Random Forest, and Artificial Neural Network (ANN) were implemented to predict sepsis survival. The findings revealed a transition …

A Comparative Assessment Of Human Factors In Cybersecurity: Implications For Cyber Governance, Muhammad Umair Shah, Farkhund Iqbal, Umair Rehman, Patrick C.K. Hung

All Works

This paper provides an extensive overview of cybersecurity awareness in the young, educated, and technology-savvy population of the United Arab Emirates (UAE), compared to the United States of America (USA) for advancing the scholarship and practice of global cyber governance. We conducted comparative empirical studies to identify differences in specific human factors that affect cybersecurity behaviour in the UAE and the USA. In addition, we employed several control variables to observe reliable results. We used Hofstede’s theoretical framework on culture to advance our investigation. The results show that the targeted population in the UAE exhibits contrasting interpretations of cybersecurity awareness …

Of Stances, Themes, And Anomalies In Covid-19 Mask-Wearing Tweets, Jwen Fai Low, Benjamin C.M. Fung, Farkhund Iqbal, Ebrahim Bagheri

All Works

COVID-19 is an opportunity to study public acceptance of a ‘‘new’’ healthcare intervention, universal masking, which unlike vaccination, is mostly alien to the Anglosphere public despite being practiced in ages past. Using a collection of over two million tweets, we studied the ways in which proponents and opponents of masking vied for influence as well as the themes driving the discourse. Pro-mask tweets encouraging others to mask up dominated Twitter early in the pandemic though its continued dominance has been eroded by anti-mask tweets criticizing others for their masking behavior. Engagement, represented by the counts of likes, retweets, and replies, …

When Chatgpt Goes Rogue: Exploring The Potential Cybersecurity Threats Of Ai-Powered Conversational Chatbots, Farkhund Iqbal, Faniel Samsom, Faouzi Kamoun, Áine Macdermott

All Works

ChatGPT has garnered significant interest since its release in November 2022 and it has showcased a strong versatility in terms of potential applications across various industries and domains. Defensive cybersecurity is a particular area where ChatGPT has demonstrated considerable potential thanks to its ability to provide customized cybersecurity awareness training and its capability to assess security vulnerabilities and provide concrete recommendations to remediate them. However, the offensive use of ChatGPT (and AI-powered conversational agents, in general) remains an underexplored research topic. This preliminary study aims to shed light on the potential weaponization of ChatGPT to facilitate and initiate cyberattacks. We …

3d Indoor Modeling And Game Theory Based Navigation For Pre And Post Covid-19 Situation, Jaiteg Singh, Noopur Tyagi, Saravjeet Singh, Babar Shah, Farman Ali, Ahmad Ali Alzubi, Abdulrhman Alkhanifer

All Works

The COVID-19 pandemic has greatly affected human behavior, creating a need for individuals to be more cautious about health and safety protocols. People are becoming more aware of their surroundings and the importance of minimizing the risk of exposure to potential sources of infection. This shift in mindset is particularly important in indoor environments, especially hospitals, where there is a greater risk of virus transmission. The implementation of route planning in these areas, aimed at minimizing interaction and exposure, is crucial for positively influencing individual behavior. Accurate maps of buildings help provide location-based services, prepare for emergencies, and manage infrastructural …

Quantum Efficiency Enhancement In Simulated Nanostructured Negative Electron Affinity Gaas Photocathodes, Md Aziz Ar Rahman, Shukui Zhang, Hani E. Elsayed-Ali

Physics Faculty Publications

Nanostructured negative electron affinity GaAs photocathodes for a polarized electron source are studied using finite difference time domain optical simulation. The structures studied are nanosquare columns, truncated nanocones, and truncated nanopyramids. Mie-type resonances in the 700–800 nm waveband, suitable for generation of polarized electrons, are identified. At resonance wavelengths, the nanostructures can absorb up to 99% of the incident light. For nanosquare columns and truncated nanocones, the maximum quantum efficiency (QE) at 780 nm obtained from simulation is 27%, whereas for simulated nanopyramids, the QE is ∼21%. The high photocathode quantum efficiency is due to the shift of Mie resonance …

Gluon Transverse-Momentum-Dependent Distributions From Large-Momentum Effective Theory, Ruilin Zhu, Yao Ji, Jian-Hui Zhang, Shuai Zhao

Physics Faculty Publications

We demonstrate that gluon transverse-momentum-dependent parton distribution functions (TMDPDFs) can be extracted from lattice calculations of appropriate Euclidean correlations in large-momentum effective theory (LaMET). Based on perturbative calculations of gluon unpolarized and helicity TMDPDFs, we present a matching formula connecting them and their LaMET counterparts, where the latter are renormalized in a scheme facilitating lattice calculations and converted to the MS ¯ scheme. The hard matching kernel is given up to one-loop level. We also show that the perturbative result is independent of the prescription used for the pinch-pole singularity in the relevant correlations. Our results offer a guidance for …

Prospects For 𝛾*𝛾* → 𝜋𝜋 Via Lattice Qcd, Raúl Briceño, Andrew W. Jackura, Arkaitz Rodas, Juan V. Guerrero

Physics Faculty Publications

The 𝛾*𝛾* → 𝜋𝜋 scattering amplitude plays a key role in a wide range of phenomena, including understanding the inner structure of scalar resonances as well as constraining the hadronic contributions to the anomalous magnetic moment of the muon. In this work, we explain how the infinite-volume Minkowski amplitude can be constrained from finite-volume Euclidean correlation functions. The relationship between the finite-volume Euclidean correlation functions and the desired amplitude holds up to energies where 3𝜋 states can go on shell, and is exact up to exponentially small corrections that scale like 𝒪(e^−m𝜋L), where L is the spatial extent …

A Multidimensional Study Of The Structure Function Ratio Σlt'/ Σ₀ From Hard Exclusive ��⁺ Electro-Production Off Protons In The Gpd Regime, S. Diehl, A. Kim, K. Joo, P. Achenbach, Z. Akbar, M. J. Amaryan, H. Atac, H. Avagyan, C. Ayerbe Gayoso, L. Baashen, L. Barion, M. Bashkanov, M. Battaglieri, I. Bedlinsky, B. Benkel, F. Benmokhtar, A. Bianconi, A. S. Biselli, M. Bondi, W.A. Booth, M. Zurek, Et Al.

Physics Faculty Publications

A multidimensional extraction of the structure function ratio from the hard exclusive ^→ep → e'n��+ reaction above the resonance region has been performed. The study was done based on beam-spin asymmetry measurements using a 10.6 GeV incident electron beam on a liquid-hydrogen target and the CLAS12 spectrometer at Jefferson Lab. The measurements focus on the very forward regime (t/Q²≪ 1) with a wide kinematic range of in the valence regime (0.17 < ��_B < 0.55), and virtualities ranging from 1.5 GeV² up to 6 GeV². The results and their comparison to theoretical models based on Generalized Parton Distributions demonstrate the sensitivity to chiral-odd …