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Solving Wordle Using Information Theory, Talal Aladaileh, Donald Stephens, Mallak Alqaisi, Congyu Wu
Solving Wordle Using Information Theory, Talal Aladaileh, Donald Stephens, Mallak Alqaisi, Congyu Wu
Northeast Journal of Complex Systems (NEJCS)
Wordle, a popular word-guessing game, challenges players to identify a five-letter secret word through iterative guesses and feedback on letter placement. The players must figure out the secret word within six guesses. After each guess, the letters will be color-coded based on different criteria. Optimizing the choice of guesses is critical for maximizing success within the limited attempts allowed. In this study, the application of Shannon entropy is explored as a strategy for selecting words that maximize information gain at each step of the game. By quantifying the uncertainty reduction achieved by potential guesses, this method prioritizes words that are …
Behavioral Biases As Drivers Of Complexity In Stock Markets: An Agent-Based Modeling Approach, David Joseph Dr, Alwin Joseph, Blesson James, Kajal Dass
Behavioral Biases As Drivers Of Complexity In Stock Markets: An Agent-Based Modeling Approach, David Joseph Dr, Alwin Joseph, Blesson James, Kajal Dass
Northeast Journal of Complex Systems (NEJCS)
By modeling financial systems as Complex Adaptive Systems, this study investigates how behavioral biases influence emergent complexity in stock markets. The study integrates heterogeneous agents, such as rational traders, herding agents, overconfident traders, and anchoring/disposition-driven investors, within a Limit Order Book framework calibrated to both U.S. and Indian market conditions using an Agent-Based Modeling (ABM) approach implemented through the high-fidelity ABIDES simulation environment. Price dynamics, volatility patterns, and liquidity structures were analyzed by Monte Carlo simulation experiments with different behavioral compositions. The results show that behavioral biases cause nonlinear price reactions, produce heavy-tailed return distributions that distort order-book complexity, and …
Evaluating Square Gradient Theory For Correlation And Prediction Of Surface Tension, J. Richard Elliot
Evaluating Square Gradient Theory For Correlation And Prediction Of Surface Tension, J. Richard Elliot
University Research
The ESD EOS [Elliott, Suresh, and Dohohue, IECR 1990, 29, 1476] is incorporated into the open-source Square Gradient Theory (SGT) library published by Mejia et al. [Mejia, Müller, and Chaparro-Maldonado, J. Chem. Inf. Model. 2021, 61, 1244]. The combined formalism is evaluated for accuracy compared to experimental measurements and empirical correlation methods. Earlier evaluations of the ESD EOS have shown it to provide accuracy like other EOSs for vapor pressure, vapor–liquid, liquid–liquid, and solid–liquid equilibria where the databases covered roughly 500 compounds and 100–200 mixtures each. For surface tension, a database of measured values for roughly 1000 compounds has been …
Comparative Evaluation Of Segmentation-Based And Pose-Assisted Head Temperature Estimation From Uas Thermal Imagery Under Controlled Conditions, Owais Ahmed, Justin A. Guye, Muhammad Hassan Tanveer, Adeel Khalid
Comparative Evaluation Of Segmentation-Based And Pose-Assisted Head Temperature Estimation From Uas Thermal Imagery Under Controlled Conditions, Owais Ahmed, Justin A. Guye, Muhammad Hassan Tanveer, Adeel Khalid
Faculty Articles
This paper presents a vision-based framework for detecting humans and estimating head surface temperature from aerial thermal imagery acquired by Unmanned Aerial Systems (UAS). A comparative evaluation of recent object detection architectures was conducted to identify the most stable and reliable model for thermal human detection under varying flight altitudes. The selected framework integrates two head localization strategies, namely, segmentation-based mask slicing and pose-assisted keypoint localization, to extract head regions and compute per-pixel temperature values from radiometric metadata. The results show that cross-domain inference using pre-trained YOLOv11 models achieves reliable human detection across controlled outdoor environments. Between the two pipelines, …
Reducing Systemic Bias In Behavioral Targeting Using Explainable Ai: The Harmonia Complex Systems Approach, Ruchira Deokar, Preethi Nanjundan, Jossy P. George, Carlos Gershenson
Reducing Systemic Bias In Behavioral Targeting Using Explainable Ai: The Harmonia Complex Systems Approach, Ruchira Deokar, Preethi Nanjundan, Jossy P. George, Carlos Gershenson
Northeast Journal of Complex Systems (NEJCS)
Behavioral targeting is a key part of the modern advertising web's algorithmic engine. However, it is unclear whether optimization processes worsen bias, promote unchecked spread in filter bubbles or lower overall users' trust levels. This paper introduces HARMONIA (Holistic Adaptive Regulatory Model for Optimizing Non-transparent Intelligent Advertising), a comprehensive, data-driven Explainable Artificial Intelligence (XAI) framework aimed at transforming behavioral targeting via transparency, interpretability, and adaptive ethical regulation. This paper conducted a comprehensive Explorative Data Analysis (EDA) on the public Criteo Display Advertising Dataset, which contains over 45 million records, to identify patterns in high-dimensional user-ad interaction space. This analysis uncovered …
Thermoacoustic Effects Of A Variable Equivalence Ratio In A Single Element Methane Combustor, Carter Green
Thermoacoustic Effects Of A Variable Equivalence Ratio In A Single Element Methane Combustor, Carter Green
Doctoral Dissertations and Master's Theses
Combustion instability is one of the leading factors in limiting the progress and innovations of liquid rocket engines and power plants. Under certain operating conditions, unsteady heat release and acoustic wave interactions can couple and lead to instabilities, such as self-sustaining pressure oscillations, that can lead to reduced combustor performance and potentially hardware damage. In this project, the thermoacoustic effects of controlling the equivalence ratio of a single-element natural gas combustor were modeled and analyzed. The project used Fidelity Pointwise for meshing, ANSYS Fluent for modeling, ERAU VEGA HPC for computing, and MATLAB for acoustic analysis. A numerical model of …
A Platform For Acquiring And Classifying Low-Noise Electrocardiogram Signals For Applications In Cardiovascular Monitoring, Begmamat Berdimurodovich Dushanov, Narzullo Mamatov Dr.
A Platform For Acquiring And Classifying Low-Noise Electrocardiogram Signals For Applications In Cardiovascular Monitoring, Begmamat Berdimurodovich Dushanov, Narzullo Mamatov Dr.
Technical science and innovation
The early screening and continuous monitoring of cardiovascular diseases need effective acquisition and smart processing of electrocardiogram (ECG) signals. In this article, we introduce a compact platform designed for the acquisition of low-noise ECG signals and classification of the signals using a one-dimensional convolutional neural network (1D-CNN). Our compact platform consists of a low-noise analog front-end (AFE), including an instrumentation amplifier and a chain of analog filters, along with a data acquisition component designed to ensure effective suppression of baseline wander and high frequencies. Our compact platform consumes a low amount of power and can therefore be used for continuous …
Exploring Scms And Fibers For Structural Build-Up In 3d Printing Using Penetration Test, Shiva Kumar Goud Kasani
Exploring Scms And Fibers For Structural Build-Up In 3d Printing Using Penetration Test, Shiva Kumar Goud Kasani
Miners Solving for Tomorrow Research Conference
Additive manufacturing with cementitious materials advances rapidly, but predicting structural build-up is critical for 3D printed structure buildability. Various supplementary cementitious materials (SCMs) and fibers are commonly used to enhance structural build-up in 3D printing. Evaluating their effects is necessary for successful printing. In this research, this effect is studied for common SCMs, including fly ash and silica fume, and fibers including polypropylene (0.375% and 0.75% by volume), steel (0.75% and 1.5% by volume), and hemp fibers (0.375% and 0.75% by volume). The Structural build-up was quantified through continuous static yield stress measurements (via vane rheometer, penetration, and slump) during …
Evaluation Of Channel Routing Module In The Nextgen National Water Model, Md Saiduzzaman
Evaluation Of Channel Routing Module In The Nextgen National Water Model, Md Saiduzzaman
Miners Solving for Tomorrow Research Conference
The Next Generation Water Resources Modeling (NextGen) framework has a modular structure that enables the integration of multiple hydrologic models with channel routing processes. Within NextGen, the T-Route model performs channel routing using vector-based river networks and supports a hybrid routing approach within a single watershed. This study evaluates the hydraulic diffusive wave routing method implemented in T-Route and compares its performance with the operational Muskingum-Cunge routing used in the National Water Model. The primary objective is to assess the operational capability of streamflow data assimilation across different routing methods using an extensive network of streamflow observations. The routing models …
Improving Energy Reliability In Mining Areas Through Modelling And Control Of Resonance Phenomena In Solar-Integrated Power Systems, Yurii Papaika, Gennadiy Pivnyak, Maksim Malyshko, Yuliya Pazynich, Natalia Howaniec, Adam Smolinski
Improving Energy Reliability In Mining Areas Through Modelling And Control Of Resonance Phenomena In Solar-Integrated Power Systems, Yurii Papaika, Gennadiy Pivnyak, Maksim Malyshko, Yuliya Pazynich, Natalia Howaniec, Adam Smolinski
Journal of Sustainable Mining
This study addresses the emergency and operational transient processes that arise when integrating large-scale solar power plants (SPPs) into electrical load nodes, particularly under conditions of limited power system capacity. With the increasing penetration of distributed generation in Ukraine's energy landscape, challenges related to electromagnetic compatibility and harmonic resonance are becoming more prominent. The research builds upon the foundational work of leading Ukrainian scientific schools and focuses on the specific resonance phenomena observed during the operation of solar inverters in medium-voltage networks, especially in regions with high industrial and mining Energy demand. A novel algorithm is proposed for determining the …
Scale-Dependent Particle Transport Over Urban-Like Roughness In Turbulent Flow, Rae Riddle
Scale-Dependent Particle Transport Over Urban-Like Roughness In Turbulent Flow, Rae Riddle
Dissertations and Theses
This study employs direct numerical simulation (DNS) to investigate the dispersion of inertial particles in turbulent flow over three-dimensional urban-like roughness at Reτ = 200. Particles with Stokes numbers St = 5, 25, and 100 are tracked over cubic arrays with spanwise spacings Sy from 2h to 32h, where h = δ/8 and δ is the half-channel height, alongside a smooth-wall reference case. The results reveal scale-dependent particle responses characterized by three distinct regimes. First, high-inertia particles (St = 100) align strongly with mean secondary flows, exhibiting organized plumes above roughness elements. Their vertical transport peaks at intermediate spacing …
Ais26s: Genai And Llms For Cybersecurity, Political Sciences, Transportation Security, And Resiliency, Latifur Khan
Ais26s: Genai And Llms For Cybersecurity, Political Sciences, Transportation Security, And Resiliency, Latifur Khan
Paul English Applied Artificial Intelligence (AI) Institute Publications
This presentation examines the role of generative artificial intelligence (GenAI) and large language models (LLMs) in addressing complex challenges across cybersecurity, political science, and transportation security. Dr. Latifur Khan discusses how advanced AI methods can be applied to threat detection, data analysis, and decision-making in high-risk and data-intensive environments. The talk highlights interdisciplinary applications of LLMs, emphasizing their ability to extract insights from large-scale data, improve system resilience, and support intelligent infrastructure. Emerging research directions and practical implications for real-world deployment are also discussed.
Biosensors For Biomedicine, Drake O'Leary
Biosensors For Biomedicine, Drake O'Leary
Miners Solving for Tomorrow Research Conference
This project investigated the use of engineered bacterial reporter systems to detect cellular stress responses associated with antibiotic activity. While constructs were successfully introduced and tested against known antibiotics, the reporter consistently produced a blue signal across conditions, limiting the ability to distinguish specific stress responses. This suggests issues such as leaky expression, insufficient regulatory control, or lack of specificity in the reporter design. Although results were inconclusive, this work highlights key challenges in developing reliable biosensors and provides a foundation for future optimization. Improving signal specificity and reducing background expression will be critical for enabling accurate characterization of antibiotic …
Logistics Center: Sustainable Design Build, Dylon Moala, Daryn Nguyen, Andrew Sabuda, Gage Urbach, Nicolae Vesca
Logistics Center: Sustainable Design Build, Dylon Moala, Daryn Nguyen, Andrew Sabuda, Gage Urbach, Nicolae Vesca
Civil, Environmental and Sustainable Engineering Senior Theses
The Cal Centre Distribution Center is a proposed 4,000,000 square foot, four (4) warehouses total, e-commerce warehouse and logistics facility located along Interstate 5 (the I-5) in Kern County, California. The site occupies a very strategic location for overall distribution logistics of the Western United States being close to the Port of Los Angeles allowing for 65,000,000 people to be reached within a two (2) day truck turn. The site also addresses the local economic needs of Kern County and the greater Bakersfield area. Ranking as one of the highest functional unemployment rates among cities, this site will provide approximately …
How Q-Succeed-Cny Connects Local Residents To Emerging Semiconductor And Quantum Career Opportunities, Moamer Hasanovic
How Q-Succeed-Cny Connects Local Residents To Emerging Semiconductor And Quantum Career Opportunities, Moamer Hasanovic
SyracuseCoE
This slide deck is from Professor Moamer Hasanovic's talk, "How Q-SUCCEED-CNY Connects Local Residents to Emerging Semiconductor and Quantum Career Opportunities," presented at SyracuseCoE's April 2026 Research & Technology Forum.
Roof Mounted Single-Axis Solar Tracking Platform, German Markaryan, Dean Schultz, Isabella Bravo, Lucas Matter, Quacy Moore, Robert Wang
Roof Mounted Single-Axis Solar Tracking Platform, German Markaryan, Dean Schultz, Isabella Bravo, Lucas Matter, Quacy Moore, Robert Wang
Mechanical Engineering Senior Theses
The growing need for efficient and reliable renewable energy sources has been increasing in the 21st century. All residential solar panel systems suffer from efficiency losses due to their inability to adjust their angle and a lack of a proper cleaning system. Automated Tracking Light Acquisition System (ATLAS) aims to solve this problem. Fixed solar panels without self cleaning harvest 30% less energy than adjustable counterparts. With an Arduino Nano ESP32 and Raspberry Pi 3B+ controlling ATLAS, it is designed to autonomously log data, have a night mode, have battery safety features and automatically adjust to the trajectory of the …
Optimization Of A High-Performance Lightweight Concrete Mix Design For Concrete Canoe Application, Caiden Sisson
Optimization Of A High-Performance Lightweight Concrete Mix Design For Concrete Canoe Application, Caiden Sisson
Honors Theses
Arkansas State University competes annually in the National Concrete Canoe Competition that requires the development of a concrete mix design capable of maintaining buoyancy while satisfying strength, workability, and performance criteria under racing and handling conditions. Because conventional structural concrete is too dense for buoyant applications, this research focused on developing and optimizing a concrete mixture for concrete canoe application.
Plasmoid Vortex System Retrofit A Sustainability And Efficiency Study On Internal Combustion Engines, Walker Hall
Plasmoid Vortex System Retrofit A Sustainability And Efficiency Study On Internal Combustion Engines, Walker Hall
Doctoral Dissertations and Master's Theses
The thesis addresses the persistent inefficiency and environmental degradation caused by internal combustion engines in modern vehicles, a major issue as the automotive industry faces increasing pressure to reduce fuel consumption and greenhouse gas emissions. Internal combustion engines, which power most cars today, convert only about 20-30% of fuel energy into useful work, with the remainder lost as heat and exhaust waste, including carbon monoxide (CO), carbon dioxide (CO₂), hydrocarbons (HC), and nitrogen oxides (NOx). This inefficiency contributes to global carbon emissions, with transportation accounting for approximately 29% of U.S. greenhouse gases in 2021 [1]. As regulatory standards tighten (e.g., …
Cooperative Unmanned Aerial System (Uas) Geolocation Of Emitters, Christopher Peters
Cooperative Unmanned Aerial System (Uas) Geolocation Of Emitters, Christopher Peters
Electrical Engineering Theses and Dissertations
A collection of unmanned aerial systems (UAS) can be networked as a cooperative wireless sensor array to geolocate an unknown-location RF emitter using time-based measurements. In operation, however, environmental multipath and hardware errors in sensor positioning and timing can degrade emitter localization accuracy and limit the practicality of single-snapshot solutions. This dissertation evaluates time-of-arrival and time-difference-of-arrival (TOA/TDOA) geolocation for cooperative UAS arrays under realistic error sources and develops geometry-control strategies that actively reduce localization uncertainty through iterative UAS repositioning.
This work studies the Location on a Conic Axis (LOCA) method for emitter localization. Using Monte Carlo simulations with hardware error …
Roadmap On Artificial Intelligence-Augmented Additive Manufacturing, Ali Zolfagharian, Liuchao Jin, Qi Ge, Wei-Hsin Liao, Andrés Díaz Lantada, Francisco Franco Martínez, Tianyu Zhang, Tao Liu, Charlie C.L. Wang, Mohammad Hossein Mosallanejad, Reza Ghanavati, Abdollah Saboori, Alejandro De Blas De Miguel, William Solórzano-Requejo, Yi Cai, Xiangyang Dong, Huangyi Qu, Najmeh Samadiani, Guangyan Huang, Austin Downey, Yanzhou Fu, Lang Yuan
Roadmap On Artificial Intelligence-Augmented Additive Manufacturing, Ali Zolfagharian, Liuchao Jin, Qi Ge, Wei-Hsin Liao, Andrés Díaz Lantada, Francisco Franco Martínez, Tianyu Zhang, Tao Liu, Charlie C.L. Wang, Mohammad Hossein Mosallanejad, Reza Ghanavati, Abdollah Saboori, Alejandro De Blas De Miguel, William Solórzano-Requejo, Yi Cai, Xiangyang Dong, Huangyi Qu, Najmeh Samadiani, Guangyan Huang, Austin Downey, Yanzhou Fu, Lang Yuan
Faculty Publications
Artificial intelligence-augmented additive manufacturing (AI2AM) represents a transformative frontier in digital fabrication, where artificial intelligence (AI) is embedded not as a peripheral tool, but as a central framework driving intelligent, adaptive, and autonomous additive manufacturing (AM) systems. The objective of this Roadmap is to present a comprehensive vision of the state-of-the-art developments in AI2AM while charting the future trajectory of this rapidly emerging field. As AM applications continue to expand across diverse sectors, conventional design and control strategies face growing limitations in scalability, quality assurance, and material complexity. AI uses tools like computer vision, generative design, and large language models …
Wright State University's Celebration Of Student Research, Scholarship & Creative Activities From Wednesday, April 1, 2026, Wright State University
Wright State University's Celebration Of Student Research, Scholarship & Creative Activities From Wednesday, April 1, 2026, Wright State University
Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials
The student abstract booklet is a compilation of abstracts from students' oral and poster presentations at Wright State University's Celebration of Student Research, Scholarship & Creative Activities on April 1, 2026.
Competitive Reaction Pathways In The Fully Green Synthesis And Surface Modification Of Silver Nanowires Under L-Ascorbic Acid-Limited Conditions, Finley Neal
Honors Theses
Silver nanowires (AgNWs) are critical building blocks for transparent conductive films (TCFs) in flexible electronics, yet their commercial viability is hindered by environmentally hazardous, energy-intensive synthesis methods and limited intrinsic chemical stability. This study investigated a fully green, room-temperature (25℃) batch synthesis of pristine AgNWs using tannic acid as a biodegradable dual reducing and capping agent under strict kinetic pH control (pH 1.25). To enhance oxidative resistance, a subsequent surface modification protocol was evaluated to deposit a protective palladium (Pd) shell using L-ascorbic acid (LAA) as a secondary reducing agent. The pristine green synthesis yielded one-dimensional Ag nanostructures with a …
Optimizing Auv Perception For Competitive Underwater Robotics: Analyzing Performance And Simplicity Of Machine Vision Hardware, Joseph King
Honors Theses
Underwater robotics is a growing field with many practical applications, such as pipeline and offshore structure monitoring, deep sea mining, mine reconnaissance/removal, and marine environmental monitoring. USM’s Robotics Club will participate in the international RoboSub competition, where student-led teams build autonomous underwater vehicles (AUVs) that perform a variety of tasks within a pool requiring camera-based object detection. This project analyzes affordable hardware and software options for providing machine vision to USM’s future RoboSub AUV. The performance of an ESP32-CAM microcontroller, Raspberry Pi 5, and Jetson Orin Nano single-board computers running FOMO and YOLO object detection models was compared. These models …
Numerical Study Of Nutrient Mixing In Trabecular Bone In Microgravity, Disuse And Normogravity, Sagar Gharti
Numerical Study Of Nutrient Mixing In Trabecular Bone In Microgravity, Disuse And Normogravity, Sagar Gharti
Doctoral Dissertations and Master's Theses
Mechanical loading is known to regulate bone remodeling by driving interstitial fluid flow which stimulates cells and drives nutrient transport within the trabecular network. In microgravity, the absence of mechanical stimulation or loading suppresses convective flow processes, causing diffusion-driven nutrient mixing and renewal, and accelerated bone loss. This thesis investigates how oscillation frequency and trabecular bone density jointly control nutrient mixing and wall shear stress within trabecular cavities.
A computational fluid dynamics (CFD) framework is developed in STAR-CCM+ using a soft-cap oscillation model that mimics cyclic compression. Three idealized trabecular morphologies are simulated across different frequencies to represent microgravity or …
Numerical Investigation Of Rotor-Gust Acoustic Interactions Using The Overflow Cfd Solver, Jordan Mills
Numerical Investigation Of Rotor-Gust Acoustic Interactions Using The Overflow Cfd Solver, Jordan Mills
Doctoral Dissertations and Master's Theses
The rapid expansion of Urban Air Mobility (UAM) necessitates high-fidelity modeling to predict and mitigate the noise signatures of electric vertical take-off and landing (eVTOL) aircraft within dense urban landscapes. A critical unknown in community-noise certification is the aeroacoustic response of rotors to unsteady inflow conditions. This research addresses this gap by investigating the aerodynamic and acoustic behavior of a representative rotor subjected to time-harmonic inflow disturbances. By establishing a robust numerical framework, this thesis quantifies the relationship between periodic atmospheric gusts and their impact on rotor performance, unsteady blade loading, and subsequent sound radiation. The research consists of a …
Insect Inspired Behavioral Strategies For Improving Multi-Agent System Resilience In The Presence Of Contagious Faults, James E. Hand
Insect Inspired Behavioral Strategies For Improving Multi-Agent System Resilience In The Presence Of Contagious Faults, James E. Hand
Doctoral Dissertations and Master's Theses
As Multi-Agent Systems (MASs) become increasingly involved in every aspect of everyday life the need to maintain reliability and resilience within these systems grows. However, in equal measure bad actors wishing to maliciously control or alter these systems are growing in both scale and capability. Thus, there is a present need for control schemes and agent behaviors that provide security against these threats while also avoiding large degradation in system performance as a tradeoff. Current research has covered a wide breadth of avenues and strategies that provide measurable resilience to faulted agents. However, these strategies often require group consensus, specialized …
Effect Of Nozzle Pressure Ratio On Thrust And Flow Behavior In A Supersonic De Laval Nozzle, Esha Jain
Effect Of Nozzle Pressure Ratio On Thrust And Flow Behavior In A Supersonic De Laval Nozzle, Esha Jain
Doctoral Dissertations and Master's Theses
Supersonic nozzles operate across a range of flow regimes. While an ideally expanded condition yields optimal thrust, practical propulsion systems rarely operate at this design point due to variations in altitude and engine operating conditions. As a result, nozzles frequently operate in off-design conditions. In overexpanded regime, where the exit pressure is lower than the ambient pressure, shock-induced separation may occur within the divergent section of the nozzle, potentially degrading nozzle performance. Understanding the aerodynamic behavior of nozzles operating under off-design conditions is therefore important for improving propulsion system performance and stability. In particular, direct thrust measurements provide a key …
Intelligent Flight Control Systems Using Adaptive Deep Neural Networks And Concurrent Learning-Based Design Methods, Maddox C. Morrison
Intelligent Flight Control Systems Using Adaptive Deep Neural Networks And Concurrent Learning-Based Design Methods, Maddox C. Morrison
Doctoral Dissertations and Master's Theses
This thesis investigates deep neural network (DNN)-based adaptive control strategies for unmanned aerial vehicles (UAVs) operating under aerodynamic uncertainty and complex actuator dynamics.
The first contribution presents a control strategy employing a concurrent learning (CL)-based DNN training algorithm, which combines online adaptive DNN weight adaptation with offline batch-like training updates using a recorded data stack. The analysis focuses on the closed-loop performance improvements resulting from the use of optimum CL data-selection algorithms, which ensure that the recorded data stack maintains sufficient data diversity to provide a statistically meaningful representation of the operating conditions using a reduced data set. Specifically, this …
Study Of Output And Behavior Of Llms Using Confidence Framing In Prompt Engineering, Micah Parrilla
Study Of Output And Behavior Of Llms Using Confidence Framing In Prompt Engineering, Micah Parrilla
Doctoral Dissertations and Master's Theses
While prompt engineering is pivotal for shaping Large Language Model (LLM) outputs, the impact of confidence framing on behavioral calibration remains underexplored. This study investigates the ways in which psychological framing, utilizing techniques such as capability praise, role amplification, and doubt induction, affects linguistic tone, objective accuracy, and internal calibration. A 1,080-trial experimental matrix evaluated six diverse models across factual, logical, coding, and cyber security domains. Analysis using the Kruskal-Wallis H-test revealed highly significant behavioral shifts across all measured dimensions, providing conclusive evidence that the applied frames exert a substantial influence on model performance.
The findings identify a distinct cognitive …
Guardrail Height Safety Requirements Given Recent Crash History And Evolution Of Vehicle Design, Delaney Morgan
Guardrail Height Safety Requirements Given Recent Crash History And Evolution Of Vehicle Design, Delaney Morgan
Doctoral Dissertations and Master's Theses
Roadside barriers such as guardrails are fundamental to roadway safety, providing a critical last line of defense in preventing vehicles from leaving the roadway and impacting potential hazards. As vehicles are ever changing, it is necessary for guardrail design to adapt in response. Many contemporary vehicles such as sport utility vehicles and light trucks have higher centers of gravity than previous years, while electric vehicles have increased weight. Having sufficient guardrail height is essential to ensure proper engagement with vehicles to prevent loss of containment during impact.
The purpose of this study is to evaluate the performance of current Florida …