Physical Sciences and Mathematics Commons^™

Towards A Concurrency Platform For Scalable Multi-Axial Real-Time Hybrid Simulation, Marion Sudvarg, Oren Bell, Tyler Martin, Benjamin Standaert, Tao Zhang, Sun Beom Kwon, Chris Gill, Arun Prakash

Computer Science Faculty Research & Creative Works

Multi-axial real-time hybrid simulation (maRTHS) uses multiple hydraulic actuators to apply loads and deform experimental substructures, enacting both translational and rotational motion. This allows for an increased level of realism in seismic testing. However, this also demands the implementation of multiple-input, multiple-output control strategies with complex nonlinear behaviors. To realize true real-time hybrid simulation at the necessary sub-millisecond timescales, computational platforms will need to support these complexities at scale, while still providing deadline assurance. This paper presents initial work towards supporting (and is influenced by the need for) envisioned larger-scale future experiments based on the current maRTHS benchmark: it discusses …

Minerrouter : Effective Message Routing Using Contact-Graphs And Location Prediction In Underground Mine, Abhay Goyal, Sanjay Madria, Samuel Frimpong

Computer Science Faculty Research & Creative Works

Location-based distributed communication in underground mines has been a hard problem to solve due to unreliable centralized architecture such as leaky feeder systems, high attenuation, and the unavailability of GPS signals. Delay Tolerant Networks (DTN) enable decentralized message routing using the store-carry-forward method that can help in creating situational awareness needed to handle emergency and disaster scenarios. The ability to predict where the DTN nodes (miner) might have been at/are headed to (with respect to the mine regions and pillars) at different times, combined with contact-based routing and intelligent handling of buffer, can be used for better delivery of messages. …

Snow Spheres And Ice Cubes: Solutions For Fermi Questions, February 2024, John Adam

Mathematics & Statistics Faculty Publications

No abstract provided.

Infusing Machine Learning And Computational Linguistics Into Clinical Notes, Funke V. Alabi, Onyeka Omose, Omotomilola Jegede

Mathematics & Statistics Faculty Publications

Entering free-form text notes into Electronic Health Records (EHR) systems takes a lot of time from clinicians. A large portion of this paper work is viewed as a burden, which cuts into the amount of time doctors spend with patients and increases the risk of burnout. We will see how machine learning and computational linguistics can be infused in the processing of taking clinical notes. We are presenting a new language modeling task that predicts the content of notes conditioned on historical data from a patient's medical record, such as patient demographics, lab results, medications, and previous notes, with the …

Utility In Time Description In Priority Best-Worst Discrete Choice Models: An Empirical Evaluation Using Flynn's Data, Sasanka Adikari, Norou Diawara

Mathematics & Statistics Faculty Publications

Discrete choice models (DCMs) are applied in many fields and in the statistical modelling of consumer behavior. This paper focuses on a form of choice experiment, best-worst scaling in discrete choice experiments (DCEs), and the transition probability of a choice of a consumer over time. The analysis was conducted by using simulated data (choice pairs) based on data from Flynn's (2007) 'Quality of Life Experiment'. Most of the traditional approaches assume the choice alternatives are mutually exclusive over time, which is a questionable assumption. We introduced a new copula-based model (CO-CUB) for the transition probability, which can handle the dependent …

Sparse Representer Theorems For Learning In Reproducing Kernel Banach Spaces, Rui Wang, Yuesheng Xu, Mingsong Yan

Mathematics & Statistics Faculty Publications

Sparsity of a learning solution is a desirable feature in machine learning. Certain reproducing kernel Banach spaces (RKBSs) are appropriate hypothesis spaces for sparse learning methods. The goal of this paper is to understand what kind of RKBSs can promote sparsity for learning solutions. We consider two typical learning models in an RKBS: the minimum norm interpolation (MNI) problem and the regularization problem. We first establish an explicit representer theorem for solutions of these problems, which represents the extreme points of the solution set by a linear combination of the extreme points of the subdifferential set, of the norm function, …

A Copula Discretization Of Time Series-Type Model For Examining Climate Data, Dimuthu Fernando, Olivia Atutey, Norou Diawara

Mathematics & Statistics Faculty Publications

The study presents a comparative analysis of climate data under two scenarios: a Gaussian copula marginal regression model for count time series data and a copula-based bivariate count time series model. These models, built after comprehensive simulations, offer adaptable autocorrelation structures considering the daily average temperature and humidity data observed at a regional airport in Mobile, AL.

Pigeon Strike!, John Adam

Mathematics & Statistics Faculty Publications

This article, titled "Pigeon strike!" from the Physics Teacher journal, discusses an incident where a bird, likely a pigeon, struck a window leaving an imprint. The author went outside to check but found no trace of the bird, hoping it had flown away after receiving medical care. The article also includes questions for readers to estimate the momentum, kinetic energy, force, pressure, and wingspan of the bird. The answers to these questions can be found online in the current issue of the journal. The article concludes with information about Fermi Questions and how to submit ideas.

The Weighty Words Of Lord Rayleigh: Solutions For Fermi Questions, January 2024, John Adam

Mathematics & Statistics Faculty Publications

No abstract provided.

Earthquakes And Seismic Waves, John Adam

Mathematics & Statistics Faculty Publications

This article discusses earthquakes and seismic waves. It explains that earthquakes occur in the crust or upper mantle, with "shallow" earthquakes happening above a depth of 70 km in the crust. The article also introduces the slider-block model, which is a simple model used to understand earthquake behavior. It provides equations to calculate the displacement and maximum slip velocity of the fault based on various factors. The article then presents two questions related to earthquake calculations. Additionally, it mentions Fermi Questions, which are brief questions with estimation techniques.

Analysis Of Sir Model With Optimal Control Strategy For A Simple Traffic Congestion Process, Ratna Herdiana, Zani Anjani Rafsanjani, R. Heru Tjahjana, Yogi Ahmad Erlangga, Moch Fandi Ansori

All Works

Traffic analysis on highways at the macroscopic level is very similar to the analysis of the spread of infectious diseases, namely the susceptible-infected-recover (SIR) model. We propose the SIR model with a control variable. The dynamics with fixed control and stability of the model are analyzed. Sensitivity analysis was also carried out. Variable control is applied as an effort to regulate or change the duration of the green light at an intersection. We obtain an optimal control strategy when the control is time-dependent. Numerical results show the positive impacts of implementing the control to susceptible vehicles and treatment for congested …

Investigating Inland Waterway Transport Through A Sustainable Development Perspective: A Case Study Of Magdalena River (Colombia), Natalia Calderón-Rivera

World Maritime University Ph.D. Dissertations

The development of transport systems significantly influences economies, growth, and welfare of populations. However, these systems can have negative consequences, such as water and air pollution, traffic congestion, noise, and biodiversity loss. To address these challenges, it is essential to implement strategies that mitigate negative effects while improving the environmental, social, and economic conditions of the population. In this regard, inland water transport (IWT) is globally recognized as a more sustainable transport alternative due to its high cargo load capacities and comparatively lower environmental and social impacts. In Colombia, the Magdalena River – the country’s most important river basin – …

Generative Artificial Intelligence: Basic Terminology And Concepts, Kincaid Brown

Law Librarian Scholarship

Generative artificial intelligence (GenAI) has been a hard topic to avoid in the media for more than a year. But what do all of the terms mean and what are areas of concern with GenAI tools?

This column aims to provide a baseline explanation of terminology and concepts that are frequently in the media.

Towards Explainable Neural Network Fairness, Mengdi Zhang

Dissertations and Theses Collection (Open Access)

Neural networks are widely applied in solving many real-world problems. At the same time, they are shown to be vulnerable to attacks, difficult to debug, non-transparent and subject to fairness issues. Discrimination has been observed in various machine learning models, including Large Language Models (LLMs), which calls for systematic fairness evaluation (i.e., testing, verification or even certification) before their deployment in ethic-relevant domains. If a model is found to be discriminating, we must apply systematic measure to improve its fairness. In the literature, multiple categories of fairness improving methods have been discussed, including pre-processing, in-processing and post-processing.
In this dissertation, …

Electromagnetic Fields And Radiation From Localized Current Source Interacting With A Cosmic Axion Field In The Context Of Massive Axion Electrodynamics, Railing Chang, P. T. Leung

Physics Faculty Publications and Presentations

Electromagnetic fields from localized current source interacting with an oscillatory cosmic axion field are studied, accounting for the possibility of a finite photon mass. In particular, focus will be on the dipole radiation from static current sources. The Proca theory is generalized to include the axion field and solutions to the modified EM field equations are obtained to first order in the axion coupling parameter. Analysis of the interplay between the two vanishingly small parameters – the axion mass (via the coupling constant and the oscillating frequency) and the photon mass – is carried out with reference to possible future …

Are All Renewable Energy Sources The Same? A Comparative Analysis Of Public Perceptions And Preferences For Renewable Energy Types In Southeast Asian Cities, Daniel Del Barrio Alvarez, Nan Wang, Masahiro Sugiyama, Masako Numata, Truong Dang Thuy, Azlina Abd Aziz, Rosalina Palanca-Tan, Aung Ze Ya, Ariel Anshory Yusuf, Awang Noor Abd Ghani, Gem Castillo, Martin Daniel Siyaranamual, Sengprasong Phrakonkham, Vilas Nitivattananon, Wunna Swe

Economics Department Faculty Publications

The realization of a sustainable energy transition in Southeast Asia will require the overcoming of the current high reliance on fossil fuels in the energy mix and the steady and rapid growth in energy demand in the region. To achieve an economically, socially, and environmentally sustainable energy transition in the region, it is vital to utilize all available renewable energy sources to the greatest extent possible. It is therefore essential to gain an understanding of how citizens in each country perceive the available renewables. However, the majority of existing literature in this region has been constrained by a narrow focus …

Revisiting The Divergent Multipole Expansion Of Atom-Surface Interactions: Hydrogen And Positronium, Α -Quartz, And Physisorption, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

We revisit the derivation of multipole contributions to the atom-wall interaction previously presented in Łach et al. [G. Łach, M. DeKieviet, and U. D. Jentschura, Phys. Rev. A 81, 052507 (2010)10.1103/PhysRevA.81.052507]. A careful reconsideration of the angular momentum decomposition of the second-, third-, and fourth-rank tensors composed of the derivatives of the electric-field modes leads to a modification for the results for the quadrupole, octupole, and hexadecupole contributions to the atom-wall interaction. Asymptotic results are given for the asymptotic long-range forms of the multipole terms, in both the short-range and long-range limits. Calculations are carried out for hydrogen and positronium …

Two-Center And Path Interference In Dissociative Capture In P+ H2 Collisions, S. Bastola, M. Dhital, B. Lamichhane, A. Silvus, R. Lomsadze, A. Hasan, A. Igarashi, Michael Schulz

Physics Faculty Research & Creative Works

We have measured and calculated fully differential cross sections (FDCS) for dissociative capture in 75-keV p+H2 collisions. FDCS were analyzed in the kinetic energy release (KER) ranges 0 to 2.1 eV and 4 to 7 eV for two different molecular orientations. In the latter range, dissociation is dominated by electronic excitation to the 2pπu state. Here, we observed two-center interference for an orientation in the plane perpendicular to the initial beam axis and parallel to the transverse momentum transfer. The interference pattern is afflicted with a constant phase shift of π. In the range KER=0 to 2.1 eV, dissociation is …

Spectrum And Quench-Induced Dynamics Of Spin-Orbit-Coupled Quantum Droplets, Sonali Gangwar, Rajamanickam Ravisankar, S. (Simeon) I. Mistakidis, Paulsamy Muruganandam, Pankaj Kumar Mishra

Physics Faculty Research & Creative Works

We investigate the ground state and dynamics of one-dimensional spin-orbit coupled (SOC) quantum droplets within the extended Gross-Pitaevskii approach. As the SOC wave number increases, stripe droplet patterns emerge, with a flat-top background, for larger particle numbers. The surface energy decays following a power-law with respect to the interactions. At small SOC wave numbers, a transition from Gaussian to flat-top droplets occurs for either a larger number of atoms or reduced intercomponent attraction. The excitation spectrum shows that droplets for relatively small SOC wave numbers are stable, otherwise stripe droplets feature instabilities as a function of the particle number or …

Dam Dimensions And Surface Porosity Affect The Water Storage Capacity Of Beaver Dam Analogs Compared To Natural Beaver Dams, Sawyer Nagle

EWU Masters Thesis Collection

Widespread stream incision in the Western United States, exacerbated by climate change and anthropogenic activities, necessitates effective restoration strategies. My study compares water retention by Beaver Dam Analogs (BDAs) to natural beaver dams and undammed control reaches. I compared how dam dimensions affect the hydraulic performance of both BDAs and beaver dams, revealing gaps in research on their comparative effectiveness. My study was conducted across eight watersheds in Washington state and two in Idaho. Hydraulic retention time (HRT), water travel time, and pool volume were response variables used to determine dam effectiveness. Dam height, thickness, length and porosity were the …

Maximizing The Number Of H-Colorings Of Graphs With A Fixed Minimum Degree, John Engbers

Mathematical and Statistical Science Faculty Research and Publications

For graphs G and H, an H-coloring of G is an adjacency-preserving map from the vertex set of G to the vertex set of H.

Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas Crino, Bruce A. Cox, Nathan B. Gaw

Faculty Publications

Generative Adversarial Networks (GANs) have received immense attention in recent years due to their ability to capture complex, high-dimensional data distributions without the need for extensive labeling. Since their conception in 2014, a wide array of GAN variants have been proposed featuring alternative architectures, optimizers, and loss functions with the goal of improving performance and training stability. This manuscript focuses on quantifying the resilience of a GAN architecture to specific modes of image degradation. We conduct systematic experimentation to empirically determine the effects of 10 fundamental image degradation modes, applied to the training image dataset, on the Fréchet inception distance …

Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won

Faculty Publications

Taking the work conducted by the global navigation satellite system (GNSS) software-defined radio (SDR) working group during the last decade as a seed, this contribution summarizes, for the first time, the history of GNSS SDR development. This report highlights selected SDR implementations and achievements that are available to the public or that influenced the general development of SDR. Aspects related to the standardization process of intermediate-frequency sample data and metadata are discussed, and an update of the Institute of Navigation SDR Standard is proposed. This work focuses on GNSS SDR implementations in general-purpose processors and leaves aside developments conducted on …

Radiation Pressure Induced Oscillations Of An Optically Levitating Mirror, Satyam Shekhar Jha, Tal Carmon, Fan Cheng, Lev Deych

Publications and Research

Optical Fabry–Perot cavity with a movable mirror is a paradigmatic optomechanical system. While usually the mirror is supported by a mechanical spring, it has been shown that it is possible to keep one of the mirrors in a stable equilibrium purely by optical levitation without any mechanical support. In this work, we expand previous studies of the nonlinear dynamics of such a system by demonstrating a possibility for mechanical parametric instability and the emergence of the “phonon laser” phenomenon.

Abmscore: A Heuristic Algorithm For Forming Strategic Coalitions In Agent-Based Simulation, Andrew J. Collins, Gayane Grigoryan

Engineering Management & Systems Engineering Faculty Publications

Integrating human behavior into agent-based models has been challenging due to its diversity. An example is strategic coalition formation, which occurs when an individual decides to collaborate with others because it strategically benefits them, thereby increasing the expected utility of the situation. An algorithm called ABMSCORE was developed to help model strategic coalition formation in agent-based models. The ABMSCORE algorithm employs hedonic games from cooperative game theory and has been applied to various situations, including refugee egress and smallholder farming cooperatives. This paper discusses ABMSCORE, including its mechanism, requirements, limitations, and application. To demonstrate the potential of ABMSCORE, a new …

Predicting The Need For Cardiovascular Surgery: A Comparative Study Of Machine Learning Models, Arman Ghavidel, Pilar Pazos, Rolando Del Aguila Suarez, Alireza Atashi

Engineering Management & Systems Engineering Faculty Publications

This research examines the efficacy of ensemble Machine Learning (ML) models, mainly focusing on Deep Neural Networks (DNNs), in predicting the need for cardiovascular surgery, a critical aspect of clinical decision-making. It addresses key challenges such as class imbalance, which is pivotal in healthcare settings. The research involved a comprehensive comparison and evaluation of the performance of previously published ML methods against a new Deep Learning (DL) model. This comparison utilized a dataset encompassing 50,000 patient records from a large hospital between 2015-2022. The study proposes enhancing the efficacy of these models through feature selection and hyperparameter optimization, employing techniques …

Improving Neuropathological Analysis With Aβgan: Addressing Morphology Imbalance For Efficient Alzheimer's Disease Diagnosis, Sujatha Alla, Prasanthi Chidipudi, Nagesh Bheesetty, Vedvikash Reddy Velur, Joshit Mohanty, Puneeth Bheesetty, Marisha Jmukhadze, Narendra Lakshmana Gowda, Sai Gireesh Komaragiri

Engineering Management & Systems Engineering Faculty Publications

Histopathologists are experiencing a digital revolution in their field thanks to the digitization of Whole Slide Images (WSIs), which are microscope slides of tissue that can measure gigapixels in size. With so much high resolution data at their disposal, computer vision techniques can now be used to automate laboratory processes, create visual standards, and increase analysis throughput, all of which reduce the workload of pathologists [1]. The "gold" standard in neuropathology, particularly for Alzheimer's Disease- is pathological diagnosis made by looking at White Matter Inclusions (WSIs) in brain tissue. Semi-quantitative scoring in accordance with the standards established by the Consortium …

Empowering Causal Machine Learning For Large-Scale Manufacturing Pipelines With Knowledge Graphs, Yuxin Zi, Cory Henson, Amit P. Sheth

Faculty Publications

Understanding causal relations within manufacturing pipelines is crucial for key manufacturing tasks such as anomaly detection and root cause analysis. However, existing causal machine learning (causal ML) approaches struggle to scale effectively to the vast number of variables present in manufacturing settings. We advocate for incorporating domain knowledge within the manufacturing pipelines, represented as knowledge graphs (KGs), for designing causal ML methods for large-scale manufacturing problems. Knowledge graphs can encode rich contextual information about the interactions and dependencies between different components and stages of the manufacturing pipeline, providing a structured framework to guide the discovery of causal relationships. By incorporating …

Beyond Binary: Revealing Variations In Islamophobic Content With Hierarchical Multi-Class Classification, Esraa Aldreabi, Khawlah M. Harahsheh, Mukul Dev Chhangani, Chung-Hao Chen, Jeremy Blackburn

Electrical & Computer Engineering Faculty Publications

In the digital age, the rise of Islamophobia-marked by an irrational fear or discrimination against Islam and Muslims-has emerged as a pressing issue, especially on social media platforms. In this paper we employs a multi-class classification system, moving beyond traditional binary models. We categorize Islamophobic content into three main classes and various subclasses, covering a range from subtle biases to explicit incitement. Comparative analysis of data from Reddit and Twitter illuminates the distinct prevalence and types of Islamophobic content specific to each platform. This paper deepens our understanding of digital Islamophobia and provides insights for crafting targeted online counter strategies. …

Parametrization Of Fluid Models For Electrical Breakdown Of Nitrogen At Atmospheric Pressure, Shirshak K. Dhali

Electrical & Computer Engineering Faculty Publications

In the transient phase of an atmospheric pressure discharge, the avalanche turns into a streamer discharge with time. Hydrodynamic fluid models are frequently used to describe the formation and propagation of streamers, where charge particle transport is dominated by the creation of space charge. The required electron transport data and rate coefficients for the fluid model are parameterized using the local mean energy approximation (LMEA) and the local field approximation (LFA). In atmospheric pressure applications, the excited species produced in the electrical discharge determine the subsequent conversion chemistry. We performed the fluid model simulation of streamers in nitrogen gas at …