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On Shrinkage Estimators For Pareto Ii Parameters For Right Censored Type Ii Data, Jubran Abdulameer Labban, Hadeel Alkutubi Aug 2026

On Shrinkage Estimators For Pareto Ii Parameters For Right Censored Type Ii Data, Jubran Abdulameer Labban, Hadeel Alkutubi

Iraqi Journal for Computer Science and Mathematics

The aim of this study is to estimate the first two shrinkage estimators for the parameters of the Pareto II distribution with right-censored Type II data. The methods we used in this study are: maximum likelihood and Bayesian. In the Bayesian method, we use non-informative priority, which is Jeffries priority, and we use the squared error loss function. These estimators were compared through Monte Carlo simulation to indicate preference based on the mean square error criterion.


The Self-Aware Room: A Framework For Operational Self-Awareness In Evolvable Blended Environments, David B. Smith Aug 2026

The Self-Aware Room: A Framework For Operational Self-Awareness In Evolvable Blended Environments, David B. Smith

Publications and Research

The Self-Aware Room (SAR) is a room-scale research environment developed within the larger Balanced Blended Space and Blended Reality Performance System research trajectory. Rather than treating the room as a conventional “smart” environment composed of fixed automation technologies, SAR approaches it as an evolvable blended environment made from physical, virtual, conceptual, sensory, computational, and performative relationships. Its defining feature is not any particular sensor, model, or output device, but the set of transformations through which physical activity becomes structured observation, bounded representation, interpreted state, governed decision, and mediated response.

This paper develops the conceptual and methodological foundations of SAR as …


Research Status And Prospects Of Monitoring Technology For Large-Span Cable-Stayed Bridges Based On Machine Learning, Liu Guoliang, Liu Guokun, Yan Donghuang, Wang Wenxi, Wang Qishun Aug 2026

Research Status And Prospects Of Monitoring Technology For Large-Span Cable-Stayed Bridges Based On Machine Learning, Liu Guoliang, Liu Guokun, Yan Donghuang, Wang Wenxi, Wang Qishun

Journal of China & Foreign Highway

Machine learning and intelligent optimization algorithms have been increasingly applied to construction and health monitoring of long-span cable-stayed bridges. Based on the construction history of cable-stayed bridges both domestically and internationally, an overview of the origin and development process of cable-stayed bridges was provided. Firstly, from the perspective of the entire life cycle of bridges, bridge monitoring was divided into construction period monitoring and operation period monitoring. The applications of mainstream construction monitoring methods in large cable-stayed bridge projects were elaborated, and the specific composition of bridge health monitoring systems was clarified. Secondly, the basic principles of several machine learning …


Explaining Safety Challenges And Their Relationships Using A Qualitative-Fuzzy Dematel Approach: A Surface Mine Case Study, Neda Molamehdizadeh, Gholam Hossein Halvani, Hossein Ebrahimi, Ali Asghar Farshad, Seyedeh Melika Kharghani Moghadam, Saber Moradi Hanifi Aug 2026

Explaining Safety Challenges And Their Relationships Using A Qualitative-Fuzzy Dematel Approach: A Surface Mine Case Study, Neda Molamehdizadeh, Gholam Hossein Halvani, Hossein Ebrahimi, Ali Asghar Farshad, Seyedeh Melika Kharghani Moghadam, Saber Moradi Hanifi

Journal of Sustainable Mining

Safety in surface mining operations is a major organizational management challenge due to the inherently hazardous nature of mining activities. This study aimed to explain safety challenges and identify their interrelationships through a combined qualitative-fuzzy DEMATEL approach in a surface mine in Yazd Province, Iran. The research was carried out in two sequential phases: first, key safety challenges were identified through qualitative interviews with employees, supervisors, and safety experts; then, the relationships among these challenges were analyzed and prioritized using the fuzzy DEMATEL technique. The main challenges identified included insufficient specialized training, inadequate safety equipment, weak organizational safety culture, and …


The Carbon Footprint Of The Hard Coal Sector In Poland In The Context Of The Evolution Of The European Union’S Climate Neutrality Policy, Katarzyna Widera Aug 2026

The Carbon Footprint Of The Hard Coal Sector In Poland In The Context Of The Evolution Of The European Union’S Climate Neutrality Policy, Katarzyna Widera

Journal of Sustainable Mining

The topic of the article is the carbon footprint of coal as a primary source of energy. In light of climate change and the energy transition in the European Union, it is increasingly important to analyse the carbon footprint of individual economic sectors. The aim of this review article is to present an analysis of the carbon footprint of the hard coal sector in Poland against the background of the EU’s climate neutrality policy. The paper reviews EU strategic documents, such as the European Green Deal, the ”Fit for 55” package, and the REPowerEU and Clean Industrial Deal initiatives, in …


Rickettsia Africae Discovered In A Short-Term Urban Traveller To South Africa: A Case Report, Zunairah Sikder Aug 2026

Rickettsia Africae Discovered In A Short-Term Urban Traveller To South Africa: A Case Report, Zunairah Sikder

Binghamton University Undergraduate Journal

Rickettsia Africae is a pathogen that causes African tick-bite fever (ATBF). Transmission typically occurs from ticks within the Central and South African regions. Previous studies suggested that ATBF is not uncommon amongst travelers to rural sub-Saharan Africa, especially during the rainy months of November through April. However, this case report highlights a woman who contracted ATBF in novel conditions. The 70-year-old woman reported travelling strictly to and from the local church and hotel for her four-day stay in July. After returning to America, the patient experienced extreme irritation on her arm, as well as complaints of headaches. She presented to …


A Message From The Managing Editor, Carissa Bayack Aug 2026

A Message From The Managing Editor, Carissa Bayack

Binghamton University Undergraduate Journal

A message from the 2025-2026 Managing Editor of the Binghamton University Undergraduate Journal, Carissa Bayack.


Effects Of Ab Mix Hydroponic Solution And Ameliorant Mixtures On Cayenne Pepper Growth And Yield In An Inceptisols, Tien Turmuktini, Betty Natalie Fitriatin, Tualar Simarmata, Firda Widayanti, Nuryanti, Lia Amalia, Elly Roosma Ria, Linlin Parlinah Aug 2026

Effects Of Ab Mix Hydroponic Solution And Ameliorant Mixtures On Cayenne Pepper Growth And Yield In An Inceptisols, Tien Turmuktini, Betty Natalie Fitriatin, Tualar Simarmata, Firda Widayanti, Nuryanti, Lia Amalia, Elly Roosma Ria, Linlin Parlinah

Jurnal Kultivasi

Cayenne pepper (Capsicum frustescens L.) cultivation faces several problems, including acidic pH and inadequate nutrient management. These problems can be addressed by using a mixture of various ameliorants and AB mix nutrient solutions. This study aimed to determine the effect of ameliorant mixture dosage and AB mix solution concentration on soil chemical properties, growth, and yield of cayenne pepper. The experiment used a randomized block design, consisting of two factors: nutrient solution concentration and ameliorant dosage. The factor of nutrient solution concentration consisted of four levels, i.e., 700, 1000, 1300, and 1600 ppm, while the factor of ameliorant dosage also …


Correlation And Redundancy Analysis Of Statistical Features For Permanent Magnet Synchronous Motor Fault Detection, Ibrahim Muhammad, Benjamin Olabisi Akinloye Aug 2026

Correlation And Redundancy Analysis Of Statistical Features For Permanent Magnet Synchronous Motor Fault Detection, Ibrahim Muhammad, Benjamin Olabisi Akinloye

Mansoura Engineering Journal

Feature selection plays a critical role in designing efficient and interpretable condition monitoring frameworks for electrical drives. In this paper, a correlation analysis of statistical and spectral features is performed for Permanent Magnet Synchronous Motor (PMSM) fault detection in naval windlass systems. Using both simulated data from a MATLAB/Simulink model and real shipboard current signals acquired from five Nigerian Navy vessels over one-month monitoring periods, higher-order statistical moments (Mean, Variance, Standard Deviation, Skewness, Kurtosis) and the Fault Severity Index (FSI) were computed alongside Total Harmonic Distortion (THD). Pearson correlation coefficients were employed to quantify feature relationships under healthy and faulty …


Flight Testing And System Identification Of An Experimental Cessna 182, Mariano Chavez Rangel Aug 2026

Flight Testing And System Identification Of An Experimental Cessna 182, Mariano Chavez Rangel

Discovery Day - Daytona Beach

Flight testing and system identification are essential for accurately characterizing aircraft dynamics and supporting the development of reliable flight control systems. This work presents the use of an experimental Cessna 182 as a full-scale platform for flight testing and system identification, conducted by the Eagle Flight Research Center. The objective is to generate high-fidelity flight data to estimate aerodynamic and dynamic coefficients and establish a baseline model for comparison with a sub-scale aircraft incorporating Integrated High-Lift Propulsor (IHLP) technology. The experimental aircraft is equipped with a comprehensive onboard instrumentation suite designed to capture synchronized measurements of air data, aircraft motion, …


Data-Driven Learning Algorithms To Predict Spacecraft Trajectories In The Dro Family, Sarath Murarisetty, Hansaka Aluvihare Aluvihare, Oshani Jayawardane, Annika Anderson Aug 2026

Data-Driven Learning Algorithms To Predict Spacecraft Trajectories In The Dro Family, Sarath Murarisetty, Hansaka Aluvihare Aluvihare, Oshani Jayawardane, Annika Anderson

Discovery Day - Daytona Beach

Generating precise, accurate, and efficient trajectories in the Earth-Moon circular restricted three-body problem (CR3BP) is crucial for long-term lunar missions, yet it remains challenging. A primary reason for this is that the CR3BP is an extremely nonlinear and chaotic system. Fortunately, neural networks present a promising approach for addressing such complex nonlinear challenges. In “Data-driven Learning Algorithms to Predict Spacecraft Trajectories in the DRO Family,” this work addresses the challenge of solving a nonlinear system within the CR3BP framework to determine the trajectories of spacecraft within the Distant Retrograde Orbit (DRO) family using neural networks (NNs). For a comprehensive comparison …


Learning Casual Structures From Aviation Accident Narratives Using Natural Language Processing And Graph-Based Knowledge Representation, Stephanie Ramsey, Katherine Hoffsetz, Madeline Gorman, Logan Lambeth Aug 2026

Learning Casual Structures From Aviation Accident Narratives Using Natural Language Processing And Graph-Based Knowledge Representation, Stephanie Ramsey, Katherine Hoffsetz, Madeline Gorman, Logan Lambeth

Discovery Day - Daytona Beach

Understanding the complex causal relationships underlying aviation accidents is critical for improving safety and preventing future incidents. However, much of this information exists in unstructured narrative reports, making large-scale analysis difficult. This project aims to automatically extract and model causal chains from National Transportation Safety Board (NTSB) accident narratives using a combination of traditional natural language processing (NLP) techniques, transformer-based architectures, and graph-based knowledge representation. Traditional NLP methods, including named entity recognition, dependency parsing, and rule-based pattern matching, will be used to identify structured cause–effect relationships. These approaches will be compared with transformer-based models, including a lightweight encoder for classification …


High-Level Trajectory Learning For Non-Prehensile Object Manipulation With Hierarchical Reinforcement Learning, Gulsum Tuba Cibuk Girgin Aug 2026

High-Level Trajectory Learning For Non-Prehensile Object Manipulation With Hierarchical Reinforcement Learning, Gulsum Tuba Cibuk Girgin

Discovery Day - Daytona Beach

Site exploration requires in-situ resource utilization when the physical properties of resources are unknown. Therefore, a generalizable object manipulation method is crucial for extraterrestrial environments. Existing studies develop reinforcement learning policies that enable interaction with objects, in which quadruped robots learn to reach commanded goals with one foot while balancing with the remaining legs. However, in these studies, goal-oriented task execution relies on high-level trajectories provided by human experts, which limits autonomous robotic operations. In this study, we propose a hierarchical DRL in which a high-level pedipulation policy outputs commands for a low-level reach policy, enabling autonomous, smooth and affordable …


Sequential Causal Architecture For Multimodal Aviation Accident Prediction, Kaitlyn Cavanaugh, Isaac Morrison Aug 2026

Sequential Causal Architecture For Multimodal Aviation Accident Prediction, Kaitlyn Cavanaugh, Isaac Morrison

Discovery Day - Daytona Beach

Aviation accidents are rarely the result of a single failure but rather from a complex causal chain of latent failures. While traditional data mining models often predict incident occurrence, they frequently overlook the sequential mechanics defined by known accident causation theoretical frameworks like the Swiss Cheese Model and the FAA's HFACS. This project addresses the need for interpretable, reliable, multi-stage forecasting by proposing a Sequential Causal Architecture that transforms theoretical causation models into a structured Directed Acyclic Graph (DAG) for multimodal accident causation chain prediction. Data from the NTSB and DOT is used and connected together in a meaningful way …


Assured Learning For Intelligent Dynamic Systems: A Metacognitive Framework, Rocio Jado Puente, Michael Budihartono, Eduar Cabrera Gaspar Aug 2026

Assured Learning For Intelligent Dynamic Systems: A Metacognitive Framework, Rocio Jado Puente, Michael Budihartono, Eduar Cabrera Gaspar

Discovery Day - Daytona Beach

Assured Learning for Intelligent Dynamic Systems: A Metacognitive Framework   Advanced Air Mobility systems, including electric vertical takeoff and landing (eVTOL) aircraft and autonomous drone platforms, require increasingly high levels of autonomy and safety. Meeting these demands calls for intelligent systems that can adapt in real time to uncertainty and changing environmental conditions. However, traditional certification methods are not well suited to rigorously measure or quantitatively verify the performance of online learning components because of their non-deterministic behavior.   This work introduces a novel runtime safety assurance method based on a metacognitive architecture (MCA) that supervises and regulates learning-enabled components. The approach …


Modeling Aircraft Collision Risk Using Machine Learning And Traffic Density Data Ac, Jadia Renee Ewing, Alexander Van Baelan, Conrad Prisby, Rafal P. Smietana Aug 2026

Modeling Aircraft Collision Risk Using Machine Learning And Traffic Density Data Ac, Jadia Renee Ewing, Alexander Van Baelan, Conrad Prisby, Rafal P. Smietana

Discovery Day - Daytona Beach

Air traffic congestion is an increasingly important factor in aviation safety as global flight activity continues to grow. This project investigates whether higher traffic density is associated with an increased risk of aviation incidents and identifies key contributing factors. Using publicly available flight (ADS-B) and incident (NTSB) data, we apply several machine learning models to analyze traffic patterns and predict risk. We begin with logistic regression to evaluate the relationship between density and incident probability, followed by decision trees to extract interpretable rules describing high-risk conditions. K-nearest neighbors (KNN) is used to examine similarity in traffic patterns among incident flights, …


Vibration And Thermal-Vacuum Feasibility For Micro Carbon Fiber Filled Nylon Filament Lunar Applications, Andrew Murphy, Shannon O'Sullivan, Daniel Lopez Aug 2026

Vibration And Thermal-Vacuum Feasibility For Micro Carbon Fiber Filled Nylon Filament Lunar Applications, Andrew Murphy, Shannon O'Sullivan, Daniel Lopez

Discovery Day - Daytona Beach

The proposed work seeks to improve the fundamental understanding of the properties concerning 3-D printing filaments that have potential to be used for lunar applications. The associated properties in focus for the proposed study, vibration and thermal-vacuum-resistance, are fundamental aspects of spaceflight and are critical to mission success for objectives associated with the environmental factors in space. The successful outcome of the proposed work will answer questions relating to the feasibility of micro carbon fiber filled nylon 3-D printing filaments such as Markforged’s Onyx® for application for projects in the Space Technologies Laboratory, including for the development of structures relating …


A Comparative Classical And Data-Driven Facial Analysis Of Wide-Field-Of-View Lens Captures, Andrew Murphy, Giovanni C. Decapua, Anthony M. Cafiso, Max E. Raabe, Kaden E. Van Leuven Aug 2026

A Comparative Classical And Data-Driven Facial Analysis Of Wide-Field-Of-View Lens Captures, Andrew Murphy, Giovanni C. Decapua, Anthony M. Cafiso, Max E. Raabe, Kaden E. Van Leuven

Discovery Day - Daytona Beach

WFOV lenses are becoming popular in facial recognition due to the fact that they enhance subject coverage and improve the chances of detecting target faces. However, wide-angle optics introduce nonlinear distortion around the image periphery, which degrades the performance of recognition pipelines. In this poster presentation, we use WFOV lens captures to analyze facial recognition using classical low-complexity algorithms based on the discrete Fourier transform (DFT), discrete cosine transform (DCT), principal component analysis (PCA), and data-driven learning with convolutional neural networks. Finally, we present computational efficiency, compression, accuracy, and precision of recognizing distorted images with qualitative and quantitative measures.


Advancements In Spacecraft Trajectory Generation Through Matrix Decomposition Techniques, David Stoev, Oshani Jayawardane, Kaitlyn Cavanaugh, Kristiyan Stefanov, Andrew Murphy Aug 2026

Advancements In Spacecraft Trajectory Generation Through Matrix Decomposition Techniques, David Stoev, Oshani Jayawardane, Kaitlyn Cavanaugh, Kristiyan Stefanov, Andrew Murphy

Discovery Day - Daytona Beach

The Circular Restricted Three-Body Problem (CR3BP) is renowned for its intricate and chaotic dynamics, leaving it without a closed-form solution. In this poster, we introduce an innovative approach to determine spacecraft trajectories within the CR3BP framework using matrix factorization techniques. We formulate a matrix equation where the right-hand side vector is constructed from the spacecraft's position and velocity data, while the coefficient matrix is derived from the spacecraft's temporal data. Subsequently, we apply several matrix decomposition techniques, including modified Gram-Schmidt, the Householder technique, and Givens Rotation, to analyze the coefficient matrix and derive the spacecraft trajectories. Finally, we evaluate the …


Earthquake-Resistant Design And Base Isolation Techniques, Christian George, Jacob Sweeten, Gabriela Cotto, Savion Stewart Aug 2026

Earthquake-Resistant Design And Base Isolation Techniques, Christian George, Jacob Sweeten, Gabriela Cotto, Savion Stewart

Discovery Day - Daytona Beach

Earthquake-resistant design has become a critical feature in construction near active fault lines, where seismic activity is most frequent and potentially destructive. In recent years, technological advancements have significantly improved methods for protecting buildings from earthquake damage. Among these innovations, base isolation systems have appeared as one of the most effective solutions. By decoupling a building from ground motion, base isolators reduce the transmission of seismic forces, helping to prevent structural damage and support building stability during earthquakes. In addition to improving safety, base isolation systems can also reduce long-term costs associated with earthquake-related repairs and maintenance. Base-isolated structures are …


Characterization Of An Ambe Tagged Neutron Source For A 30-Ton Wbls Detector, Rylee Grover Aug 2026

Characterization Of An Ambe Tagged Neutron Source For A 30-Ton Wbls Detector, Rylee Grover

Discovery Day - Daytona Beach

Understanding the detection capabilities of water-based liquid scintillator (WbLS) is critical for its deployment in next-generation neutrino detectors such as THEIA and Phase II of the Deep Underground Neutrino Experiment (DUNE). This study focuses on the characterization and alignment testing of an Americium-Beryllium (AmBe) radioactive neutron source. We plan to dope the 30-ton WbLS detector at Brookhaven National Laboratory (BNL) with Gadolinium (Gd) to improve neutron detection capabilities. This will be tested by the implementation of an AmBe source as a calibration metric. The AmBe source emits neutrons coincident with a 4.4 MeV gamma ray, making it possible to perform …


Lightweight Uav-To-Uav Detection And Tracking For Advanced Air Mobility Applications, Taylor Hostetter Aug 2026

Lightweight Uav-To-Uav Detection And Tracking For Advanced Air Mobility Applications, Taylor Hostetter

Discovery Day - Daytona Beach

Lightweight UAV-to-UAV Detection and Tracking for Advanced Air Mobility Applications addresses the significant challenge of reliable UAV-to-UAV detection on resource-constrained platforms, particularly within Advanced Air Mobility (AAM) environments where dense, low-altitude airspace requires robust detect-and-avoid capabilities. This work presents the development and experimental evaluation of a lightweight detection and tracking framework for autonomous detect-and-avoid applications. The approach is designed to support real-time onboard operation in multi-vehicle environments characteristic of emerging AAM systems. The proposed framework integrates optical and LiDAR sensing with a low-complexity machine learning decision-support layer that reduces false detections without replacing the underlying control-oriented detection pipeline. This design …


Project Minerva, Lena Wang, Gannon English, Ethan Yemm, Gabrielle Guirguis, Jose Murphy Aug 2026

Project Minerva, Lena Wang, Gannon English, Ethan Yemm, Gabrielle Guirguis, Jose Murphy

Discovery Day - Daytona Beach

Project Minerva is a multidisciplinary engineering initiative at Embry-Riddle Aeronautical University (ERAU) dedicated to the design, integration, and deployment of high-altitude balloon (HAB) systems for stratospheric research and aerospace hardware validation. The project challenges student researchers to engineer flight-ready payloads capable of maintaining structural and electronic integrity in extreme temperatures and low-pressure environments in the stratosphere. Typically utilizing 600g latex balloons filled with helium, Project Minerva missions aim to achieve altitudes exceeding 22,000 meters to facilitate vertical atmospheric profiling of variables such as CO₂ concentration, humidity, temperature, and pressure. Beyond its technical objectives, the project serves as a professional training …


System And Method For Detecting Subsurface Voids Using Controlled Heat Addition, Chase Nilsson Aug 2026

System And Method For Detecting Subsurface Voids Using Controlled Heat Addition, Chase Nilsson

Discovery Day - Daytona Beach

This study evaluates controlled heat addition in a confined space to estimate enclosed volumes for irregularly shaped spaces. The intent is to detect hidden voids in cave environments. Conventional methods for identifying such voids are often costly, logistically difficult, and limited in accuracy. Preliminary experiments were conducted with a controlled heat source, a temporary thermal barrier to isolate the test chamber, and simple temperature sensors. Temperatures were recorded for the pre-test baseline, the heating interval, followed by a cooling period. The thermal response showed clear engineering trends that warrant further exploration and modeling. Preliminary results indicate that transient temperature changes …


A Cyber-Physical Flight Simulation Platform For Real-Time Visualization Of Aircraft Dynamics And Sensor-Based Control, Gabriel Martinez, Michael Poinsett Aug 2026

A Cyber-Physical Flight Simulation Platform For Real-Time Visualization Of Aircraft Dynamics And Sensor-Based Control, Gabriel Martinez, Michael Poinsett

Discovery Day - Daytona Beach

Understanding aircraft dynamics through traditional simulations can be limiting, as results are often confined to screen-based visualization. This project aims to enhance learning and experimentation by creating a system where aircraft motion can be both simulated and physically observed in real time. The primary objective is to develop a cyber-physical flight simulation platform that links mathematical models with physical hardware. The system is designed to (1) represent aircraft dynamic behavior through real-time motion and (2) provide a foundation for integrating sensors and control strategies for responsive flight behavior. The platform combines aircraft dynamic models with a hardware interface capable of …


The Impact Of Environmental Contributing Factors In Spatial Disorientation And Non-Spatial Disorientation Related General Aviation Accidents, Victoria Cornaro, Molly Mersinger Aug 2026

The Impact Of Environmental Contributing Factors In Spatial Disorientation And Non-Spatial Disorientation Related General Aviation Accidents, Victoria Cornaro, Molly Mersinger

Discovery Day - Daytona Beach

The Impact of Environmental Contributing Factors in Spatial Disorientation and Non-Spatial Disorientation Related General Aviation Accidents   Spatial disorientation (SD) is an inherent risk of flying and with a high risk of resulting in a fatal accident (Gibbs et al, 2011). SD related accidents occur when a pilot’s perception of the aircraft altitude, position, or relative motion conflict with reality (Benson, 1999). SD accidents are significantly more likely to result in a fatality than non-SD cases. The purpose of this study was to investigate the role of different contributing factors on SD and non-SD general aviation accidents. We used the NTSB …


Supply Chain Analysis: The Oregonator Autocatalytic Case Study, Abigail Butcher Aug 2026

Supply Chain Analysis: The Oregonator Autocatalytic Case Study, Abigail Butcher

Discovery Day - Daytona Beach

Understanding stability in complex supply chains remains a critical challenge due to nonlinear feedback, delayed responses, and sensitivity to parameter changes. This project presents a novel framework that applies bifurcation analysis to evaluate system stability, using the Oregonator autocatalytic chemical reaction model as an analog for supply chain dynamics. A parameter sweep of key model variables, particularly the stoichiometric factor f and the reaction rate constants k, is used to identify transitions between stable and oscillatory regimes. These transitions provide insight into how variations in feedback strength can drive instability in real-world systems. The framework will then be extended to …


Synchrotron X-Ray Diffraction Method For Continuous Strain Analysis Across Heterogenous Material Interface Layers, Sierra Damon Aug 2026

Synchrotron X-Ray Diffraction Method For Continuous Strain Analysis Across Heterogenous Material Interface Layers, Sierra Damon

Discovery Day - Daytona Beach

Synchrotron X-ray diffraction method for continuous strain analysis across heterogenous material interface layers   The transfer of strain across a material interface is a relevant concept to quantify for numerous aerospace applications that involve coatings applied to substrates of different materials, particularly in the field of high temperature materials. X-ray diffraction (XRD) is a metrology technique capable of resolving strain within an arbitrary material by quantifying the shifts of Bragg peaks with respect to an unstrained sample and has seen increased use due to the capability of XRD to perform in-situ measurements on materials in extreme environments. Since different materials have …


Intrinsic Memory In Digital Snns: Enhancing Performance On The Cart-Pole Task With Fractional-Order Dynamics, Niklas Karl Anderson Aug 2026

Intrinsic Memory In Digital Snns: Enhancing Performance On The Cart-Pole Task With Fractional-Order Dynamics, Niklas Karl Anderson

Dissertations and Theses

Researchers working with Spiking Neural Networks (SNNs) are faced with the challenge of identifying useful biologically plausible features for inclusion in neuron models. Prior research indicates that dynamics of fractional-order calculus, which impart a form of intrinsic memory, are a key feature of biological neurons. In this work, we present the development and usage of neural networks with intrinsic memory in application to the cart-pole task, a common benchmark for neural network performance. We found that usage of fractional-order neurons may allow for up to a 37.5% reduction in neural network size as compared to networks using a standard Leaky …


The Influence Of Urban Form On The Distribution Of Air Pollutants, Takin Khosrownia Aug 2026

The Influence Of Urban Form On The Distribution Of Air Pollutants, Takin Khosrownia

Dissertations and Theses

Urban form exerts strong control on how pollution from outside a city is transported through the urban canopy and experienced at street level. This study uses the prognostic microclimate model ENVI-met to simulate an active pollutant released from an upwind rural highway and advected through an urban region represented by ten Local Climate Zone (LCZ) types. The cases share identical inflow and are isothermal, dry, and non-vegetated, so that differences among them are attributable to building morphology alone. PM2.5 is the primary exposure diagnostic. Its transport and ejection are characterized through plan-view contours, vertical plume sections, and spatially averaged streamwise …