Physical Sciences and Mathematics Commons^™

Exploring Quaternion Neural Network Loss Surfaces, Jeremiah Bill, Bruce A. Cox

Faculty Publications

This paper explores the superior performance of quaternion multi-layer perceptron (QMLP) neural networks over real-valued multi-layer perceptron (MLP) neural networks, a phenomenon that has been empirically observed but not thoroughly investigated. The study utilizes loss surface visualization and projection techniques to examine quaternion-based optimization loss surfaces for the first time. The primary contribution of this research is the statistical evidence that QMLP models yield smoother loss surfaces than real-valued neural networks, which are measured and compared using a robust quantitative measure of loss surface “goodness” based on estimates of surface curvature. Extensive computational testing validates the effectiveness of these surface …

Implementation And Evaluation Of Ai-Based Citizen Question-Answer Recommender (Acqar) To Enhance Citizen Service Delivery In Singapore Public Sector: A Case Study, Hui Shan Lee

Dissertations and Theses Collection (Open Access)

Government agencies prioritize citizen service delivery to foster trust with the public. Technological advancements, particularly in Artificial Intelligence (AI), hold promise for improving service provision and aligning government operations with citizens' needs. Yet the inherent inflexibility of Service Level Agreements (SLAs) often overlooks the nuances of human emotions and the varied nature of citizen inquiries, exacerbated by a lack of tools to guide appropriate responses. This dissertation aims to address the gaps of overlook of human emotions and non-support for appropriate responses, by exploring the following questions: (1) Can a predictive model incorporating both numeric and textual data effectively forecast …

Molecular Geometry Changes In Some Carbonyls And Aromatic Rings Upon Electronic Excitation: Herzberg-Teller Vibronic Coupling And Unitary Duschinsky Rotation, Maryam Yahya Al-Sakkaf

Theses

The common assumption in probing the dynamical motion of molecules is that the molecular electronic activity depends weakly on vibrational coordinates on electronic excitation. Therefore, electron-vibration interaction, which is known as Vibronic Coupling (VC), may be ignored. The Herzberg-Teller theory of Vibronic Coupling (HTVC) is a breakdown of the Born-Oppenheimer Approximation (BOA) since nuclear and electronic degrees of freedom can no longer be separated. The inclusion of a single quantum of a non-totally symmetric vibrational mode changes the overall symmetry of the state and permits the transition. Often, this assumption may be invalid, especially in carbonyl and aromatic compounds. This …

Theoretical And Computational Astrochemistry: A Variational Quantum Monte Carlo (Vqmc) Study Of The Trihydrogen Molecule Cation (H3+), Ahmad Saeed Alsaed

Theses

H₃⁺ is the simplest Three-Center Two-Electron molecule and it is of much interest in astrochemistry due to its high occurrence in the outer space, high reactivity, and strong acidic properties. In addition,H₃⁺ is involved in many chemical reactions in the interstellar medium (ISM) and its significant ability to absorb energy contributed to the cooling of the Universe during its early stages.

The main objective of this thesis is to approximate the ground state electronic energy of H₃⁺ by using a simple trial wavefunction consisting of a doubly occupied molecular orbital multiplied by a Jastrow …

The ''Lights Out!" Game On Threshold Graphs, Troy E. Conlay, Darren B. Parker

McNair Scholars Manuscripts

The 'Lights Out' game was originally played on a 5x5 grid of buttons that started as either on or off. Pressing the buttons flips the state of the button pressed and the directly adjacent buttons, the goal being to have all of the lights out. We can play 'Lights Out' on a graph if we assign 0 or 1 to each of the vertices on the graph, analogous to on and off in the original game, and switch the labels of a vertex and its neighbors from 0 to 1 and vice versa when the vertex is toggled. This paper …

Global Challenges In Accessing Mental Health Services And Addressing The Impact Of Alzheimer's Disease And Depression, Padmapriya Velupillai Meikandan

Master's Theses (2009 -)

This research project focuses on developing a quantum sensing system that can detect biomarkers associated with health disorders, like Alzheimer’s and depression. Our goal is to create a sensitive and highly selective quantum sensing device using a diamond nitrogen vacancy (NV) center. To train and test our quantum machine learning algorithms we will preprocess data from the available Human Connectome Project dataset. This dataset forms the basis of our quantum-based methods. The core of our project revolves around developing quantum machine learning algorithms that utilize techniques such as Support Vector Machines and neural networks to diagnose health disorders using data …

Integrating Drone And Satellite Imaging With Machine Learning For Green Stormwater Infrastructure Condition Assessments, Matthew Dupasquier

Master's Theses (2009 -)

Green Stormwater Infrastructure (GSI) has been increasingly utilized to improve urban stormwater management strategies. However, the performance and utility of GSI decrease over time if the infrastructure is not properly maintained. In recent history, the intrinsic operations and maintenance costs associated with the complex networks of new infrastructure have placed a burden on municipalities, ultimately prohibiting many from reaching the full extent of their stormwater management goals. One way for cities to achieve cost savings is through automated monitoring that can quickly assess the condition of GSI assets; however, existing cost-effective technologies are limited. Drones and satellites may be able …

Advanced Machine Learning Approaches For Predicting Mental Health Disorders Following Long Covid Diagnosis, Manoj Purohit

Master's Theses (2009 -)

After the global spread of COVID-19, the enduring effects of Long COVID and its health implications have emerged as a significant global issue, affecting people worldwide. The lingering symptoms post a COVID-19 infection can significantly affect individuals who had previously contracted the virus, exerting considerable influence over their mental well-being. Prolonged recuperation associated with Long COVID has been connected with the emergence of symptoms such as depression and anxiety, all of which can have adverse effects on emotional health. This project delves into an in-depth analysis of healthcare data pertaining to Long COVID from the Froedtert Health (FH) Medical System …

Paleozoic Evolution Of The Yukon-Tanana Terrane Of The North American Cordillera, Nw British Columbia, R. Soucy La Roche, A. Zagorevski, N. L. Joyce, J. L. Crowley

Geosciences Faculty Publications and Presentations

The origins and primary relationships between tectono-stratigraphic units are fundamental to the terrane concept in accretionary orogens, but they are challenging to assess in metamorphic terranes. In NW British Columbia, three tectonically bounded metamorphic suites of the Yukon-Tanana terrane formed in distinct tectonic settings, based on high-spatial-resolution geochronology and immobile trace-element geochemistry. The Florence Range suite comprises late Neoproterozoic or younger to pre–latest Devonian metasedimentary rocks derived from continental crust, 360 ± 4 Ma calc-alkaline intermediate orthogneiss, and 357 ± 4 Ma amphibolite with oceanic-island basalt composition, consistent with rifting of a continental margin. The detrital signature is dominated by …

Assessing Ai Detectors In Identifying Ai-Generated Code: Implications For Education, Wei Hung Pan, Ming Jie Chok, Jonathan Leong Shan Wong, Yung Xin Shin, Yeong Shian Poon, Zhou Yang, Chun Yong Chong, David Lo, Mei Kuan Lim

Research Collection School Of Computing and Information Systems

Educators are increasingly concerned about the usage of Large Language Models (LLMs) such as ChatGPT in programming education, particularly regarding the potential exploitation of imperfections in Artificial Intelligence Generated Content (AIGC) Detectors for academic misconduct.In this paper, we present an empirical study where the LLM is examined for its attempts to bypass detection by AIGC Detectors. This is achieved by generating code in response to a given question using different variants. We collected a dataset comprising 5,069 samples, with each sample consisting of a textual description of a coding problem and its corresponding human-written Python solution codes. These samples were …

Marie Curie: The Quantum Matriarch, Diptiman Das

Student Publications

Entitled “Marie Curie: The Quantum Matriarch,” this paper illuminates the extraordinary life and enduring legacy of Marie Curie, whose groundbreaking work in radioactivity revolutionized the scientific landscape. Born as Maria Skłodowska in the heart of Warsaw, Curie’s odyssey from Poland’s clandestine Flying University to the hallowed halls of Paris’ Sorbonne epitomizes her tenacious quest for enlightenment amidst the shackles of societal norms. In collaboration with her spouse, Pierre Curie, she discovered the elements polonium and radium, thereby introducing the concept of “radioactivity” to the world and securing Nobel accolades in both Physics and Chemistry. This paper ventures into her intimate …

Digital Frontiers In Aesthetics: Applying Dewey's Insights To Generative Ai, Malcolm F. Lathrop-Allen

Student Publications

The last few years have seen the emergence of ‘artificially intelligent’ systems en masse, which perform tasks which had previously only been possible by human intelligence. Arguably, the impact of ‘AI 2.0’ has been felt most prominently in the art world — artists have panicked as DALL-E, Midjourney, and other image generation algorithms manufacture pieces which previously required weeks of painstaking labor to create. This project seeks to develop a more critical framework for this novel mode of artistic creation and propose better ways of thinking about, using, and “becoming with” artificial intelligence in the domain of artistry. The first …

The Dynamics Of The Flavin, Nadph, And Active Site Loops Determine The Mechanism Of Activation Of Class B Flavin-Dependent Monooxygenases, Gustavo Pierdominici-Sottile, Juliana Palma, María Leticia Ferrelli, Pablo Sobrado

Chemistry Faculty Research & Creative Works

Flavin-dependent monooxygenases (FMOs) constitute a diverse enzyme family that catalyzes crucial hydroxylation, epoxidation, and Baeyer–Villiger reactions across various metabolic pathways in all domains of life. Due to the intricate nature of this enzyme family's mechanisms, some aspects of their functioning remain unknown. Here, we present the results of molecular dynamics computations, supplemented by a bioinformatics analysis, that clarify the early stages of their catalytic cycle. We have elucidated the intricate binding mechanism of NADPH and L-Orn to a class B monooxygenase, the ornithine hydroxylase from (Formula presented.) (Formula presented.) known as SidA. Our investigation involved a comprehensive characterization of the …

Santa Clara Magazine, Volume 65 Number 1, Spring 2024, Santa Clara University

Santa Clara Magazine

14 - A CAMPUS ON THE RISE Six new buildings on campus aren’t the only changes brought by a successful $1 billion fundraising campaign. Lauren Loftus & Leslie Griffy

20 - HUMAN AT HEART How Santa Clara University is distinguishing itself as a leader in human-focused health care innovation. Lauren Loftus

26 - SHEPHERDING INNOVATION How wonder, and God, can make us better scientists. Brother Guy Consolmagno, S.J.

30 - THE CO-OP Santa Clara University has long been a bastion of interdisciplinary learning. A new fund is taking cross-collaboration to new heights. SCM Staff

34 - MAKE AI THE BEST …

Generation, Dynamics, And Interaction Of Quartic Solitary Waves In Nonlinear Laser Systems, Sabrina Hetzel

Mathematics Theses and Dissertations

Solitons are self-reinforcing localized wave packets that have remarkable stability features that arise from the balanced competition of nonlinear and dispersive effects in the medium. Traditionally, the dominant order of dispersion has been the lowest (second), however in recent years, experimental and theoretical research has shown that high, even order dispersion may lead to novel applications. Here, the focus is on investigating the interplay of dominant quartic (fourth-order) dispersion and the self-phase modulation due to the nonlinear Kerr effect in laser systems. One big factor to consider for experimentalists working in laser systems is the effect of noise on the …

Predicting Biomolecular Properties And Interactions Using Numerical, Statistical And Machine Learning Methods, Elyssa Sliheet

Mathematics Theses and Dissertations

We investigate machine learning and electrostatic methods to predict biophysical properties of proteins, such as solvation energy and protein ligand binding affinity, for the purpose of drug discovery/development. We focus on the Poisson-Boltzmann model and various high performance computing considerations such as parallelization schemes.

Remote Sensing Techniques To Determine Volcanic Gas Components And Fluxes: Application For Lascar, Chile And Fagradalsfjall, Iceland Volcanos., Felipe S. Rojas Vilches

Earth and Planetary Sciences ETDs

Volcanic plumes allow us to understand different aspects of a volcanic system including magma movements, dynamics, mass transfer, overall gas emissions to the atmosphere, and many processes that impact human life. However, the H₂O gas is poorly constrained due to the intrinsic difficulties of this gas, with high background values and easily dispersed/integrated into the background. In this work we study the gas emissions from Lascar volcano, and Fagradalsfjall volcano, in Chile and Iceland, respectively, using a combination of different ground-based remote sensing techniques and in situ plume measurements, we measure H₂O, SO₂, CO₂, CO, and H₂S from longer and …

Hydrologic Impact Index For The Pinhoti Hiking Trail, Allie Field

Theses

This study aimed to identify flood-prone areas along the Pinhoti Trail and Chinnabee Silent Trail in the Talladega National Forest. Using the Hydrology Flood Index layer that was created using several essential data layers, the research aimed to provide campers, hikers, nature enthusiasts, and trail maintenance teams with information about areas at a higher risk of flash flooding. The Hydrology Flood Index layer rates the risk of flooding on a scale of 1 to 4, with level 1 indicating a low risk of flooding and level 4 indicating an extremely high risk. The data layers for analyzing flood hazards for …

Phys 401/801

Department of Physics and Astronomy: Syllabi

No abstract provided.

Phys 812

Department of Physics and Astronomy: Syllabi

No abstract provided.

Phys 142

Department of Physics and Astronomy: Syllabi

No abstract provided.

Phys 211h

Department of Physics and Astronomy: Syllabi

No abstract provided.

Phys 918

Department of Physics and Astronomy: Syllabi

No abstract provided.

Phys 926

Department of Physics and Astronomy: Syllabi

No abstract provided.

Can Organizational Focus On Responsible Ai Lead To Improved Ai Adoption By Employees?, Seema Chokshi

Dissertations and Theses Collection (Open Access)

The duality inherent in Artificial Intelligence technology entails that while AI has the potential to bring about transformative benefits to organizations, unintended consequences of AI applications could lead to biased and discriminatory outcomes, which could have negative consequences for the organization and society in general. Concerns about such unintended consequences are an impediment to AI adoption where unwilling employees and practitioners often fear ethical breaches, thereby, negatively impacting their engagement with AI driven applications. In response to these concerns various organizations and regulatory bodies have developed governing frameworks broadly known as Responsible AI standards, that set guidelines to design, …

Expanding Analytical Capabilities In Intrusion Detection Through Ensemble-Based Multi-Label Classification, Ehsan Hallaji, Roozbeh Razavi-Far, Mehrdad Saif

Electrical and Computer Engineering Publications

Intrusion detection systems are primarily designed to flag security breaches upon their occurrence. These systems operate under the assumption of single-label data, where each instance is assigned to a single category. However, when dealing with complex data, such as malware triage, the information provided by the IDS is limited. Consequently, additional analysis becomes necessary, leading to delays and incurring additional computational costs. Existing solutions to this problem typically merge these steps by considering a unified, but large, label set encompassing both intrusion and analytical labels, which adversely affects efficiency and performance. To address these challenges, this paper presents a novel …

Data Fusion Is More Complex Than Data Processing: A Proof, Robert Alvarez, Salvador Ruiz, Martine Ceberio, Vladik Kreinovich

Departmental Technical Reports (CS)

Empirical data shows that, in general, data fusion takes more computation time than data processing. In this paper, we provide a proof that data fusion is indeed more complex than data processing.

Towards An Optimal Design: What Can We Recommend To Elon Musk?, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich, Hung T. Nguyen

Departmental Technical Reports (CS)

Elon Musk's successful "move fast and break things" strategy is based on the fact that in many cases, we do not need to satisfy all usual constraints to be successful. By sequentially trying smaller number of constraints, he finds the smallest number of constraints that are still needed to succeed -- and using this smaller number of constrains leads to a much cheaper (and thus, more practical) design. In this strategy, Musk relies on his intuition -- which, as all intuitions, sometimes works and sometimes doesn't. To replace this intuition, we propose an algorithm that minimizes the worst-case cost of …

Monarch Science Observer, Volume 18, College Of Sciences, Old Dominion University

College of Sciences Newsletter

Spring 2024, issue of Monarch Science Observer, ODU Colleges of Sciences Newsletter.

Mut: Human-In-The-Loop Unit Test Migration, Yi Gao, Xing Hu, Tongtong Xu, Xin Xia, David Lo, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Test migration, which enables the reuse of test cases crafted with knowledge and creativity by testers across various platforms and programming languages, has exhibited effectiveness in mobile app testing. However, unit test migration at the source code level has not garnered adequate attention and exploration. In this paper, we propose a novel cross-language and cross-platform test migration methodology, named MUT, which consists of four modules: code mapping, test case filtering, test case translation, and test case adaptation. MUT initially calculates code mappings to establish associations between source and target projects, and identifies suitable unit tests for migration from the source …