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Evaluating Machine Learning Models On Classification Of Novel Cyber Attacks In The Healthcare Domain, Promise Ehimen Jul 2026

Evaluating Machine Learning Models On Classification Of Novel Cyber Attacks In The Healthcare Domain, Promise Ehimen

Dissertations, Theses, and Projects

The increasing adoption of the Internet of Medical Things (IoMT) has improved healthcare delivery through connected medical devices while simultaneously expanding the cybersecurity risks facing healthcare organizations. Although machine learning based intrusion detection systems have demonstrated high detection accuracy, their ability to respond reliably to previously unseen cyberattacks remains uncertain. This study investigated how a Neural Network model and a Logistic Regression model classified novel cyberattacks within the IoMT environment. The Neural Network and Logistic Regression models were both trained and tested using a subset of the CICIoMT2024 benchmark dataset. The Neural Network achieved 99.82% test accuracy and a 0.94 …

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Systematic Review Of The Institutionalization Of Service Learning In Higher Education, Wilmer Hernan Cruz Gutierrez Jul 2026

Systematic Review Of The Institutionalization Of Service Learning In Higher Education, Wilmer Hernan Cruz Gutierrez

ASEAN Journal of Community Engagement

An increasing number of universities are integrating service-learning (SL) to fulfill their social mission. However, sustainable institutionalization of SL remains a persistent challenge. This study identifies and analyzes the factors, actors, and strategies that drive and inhibit SL institutionalization in higher education. Using the PRISMA 2020 guidelines, a systematic literature review analyzed 52 documents from seven academic databases (including WoS, Scopus, and ERIC). The findings were grouped into three sections: cultural (integration into institutional values/missions), process (articulation within teaching, research, and outreach), and structural dimensions (dedicated support entities). The results obtained reveal a reciprocal relationship where cultural alignment enables processual …

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Evaluating Generative Ai-Based User Interfaces Using An Integrated Neutrosophic Multi-Criteria Decision-Making Framework, Nada Mohamed, Alshaimaa A. Tantawy Jul 2026

Evaluating Generative Ai-Based User Interfaces Using An Integrated Neutrosophic Multi-Criteria Decision-Making Framework, Nada Mohamed, Alshaimaa A. Tantawy

Neutrosophic Systems with Applications

User Interface (UI) design can be seen as an essential aspect of human-computer interaction (HCI) and makes communication easier between people and technology. In today's digital economy, interface quality has become one of the most important business concerns, since it has a direct impact on customer satisfaction and retention while affecting revenue. Although creating user-centered and accessible interfaces is crucial, doing so is a difficult and time-consuming process, which leads to burnout for many usability professionals. Although conventional artificial intelligence (AI) was utilized for design assessment and automation, the arrival of generative AI technology has created new possibilities for automated …

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2026 Final Unreclaimed Sites Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc. Jul 2026

2026 Final Unreclaimed Sites Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Final Insufficiently Reclaimed Sites Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc. Jul 2026

Final Insufficiently Reclaimed Sites Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Public Responses About Air Quality In The World’S Ten Most Populous Countries, Noah Lim, Alessandro Del Ponte, Lina Ang, Wei Jie Seow Jul 2026

Public Responses About Air Quality In The World’S Ten Most Populous Countries, Noah Lim, Alessandro Del Ponte, Lina Ang, Wei Jie Seow

Political Science Faculty Articles and Research

Understanding how people view and react to outdoor air quality is crucial to effectively managing and responding to air pollution, which is a major threat to global public health. Using a quota sample of 10,618 respondents from 1,372 localities across the world’s ten most populous countries (Bangladesh, Brazil, China, Indonesia, India, Mexico, Nigeria, Pakistan, Russia, and the United States), we assessed the association between exposure to fine particulate matter with diameter ≤ 2.5 micrometers (PM2.5) and people’s knowledge, attitudes, perceptions, practices, and concern about air quality. Overall, we find an inverse association between air pollution exposure and knowledge about air …

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A Visitation Grid For Complete Coverage Foraging In Robot Swarms, Arturo Gonzalez, Yifeng Gao, Li Zhang, Qi Lu Jul 2026

A Visitation Grid For Complete Coverage Foraging In Robot Swarms, Arturo Gonzalez, Yifeng Gao, Li Zhang, Qi Lu

Computer Science Faculty Publications

The complete collection of sparse resources in large, unknown environments remains a challenging problem for autonomous robot swarms. Previous studies have shown that a substantial portion of total mission time is consumed during the final stage of collection, where only a small fraction of randomly scattered resources remain. Consequently, many existing swarm foraging algorithms (search and collection) focus on collecting most resources within a limited time window, rather than improving end-stage efficiency for collecting all resources. We propose a grid-based stochastic foraging strategy that explicitly reduces redundant visits and accelerates late-stage collection. The unknown search area is partitioned into a …

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Governance, Culture, And Law: The Expanding Scope Of Environmental Science And Sustainable Development Research, Ahyaudin Sodri, Herdis Herdiansyah Jul 2026

Governance, Culture, And Law: The Expanding Scope Of Environmental Science And Sustainable Development Research, Ahyaudin Sodri, Herdis Herdiansyah

Journal of Environmental Science and Sustainable Development

Environmental science emerged as a discipline based on physical measurements, such as soil pollutant levels (Ailijiang et al., 2022), ecological restoration (Yue et al., 2026), city surface temperature (Shafizadeh-Moghadam et al., 2025), and microbial density in air samples (Hayleeyesus & Manaye, 2014). However, its objects of study increasingly extend beyond the confines of the laboratory. Questions that were once sufficiently answered with measurement data now require answers through draft laws, Constitutional Court decisions, financial reports of mining companies, and even traditional ritual discourses governing community access to forests. In other words, environmental …

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Bridging The Gap In Science Research: Preparing Students For College- Level Research In The Sciences, Victoria Helwig, Yaoguang Li Jul 2026

Bridging The Gap In Science Research: Preparing Students For College- Level Research In The Sciences, Victoria Helwig, Yaoguang Li

UConn Library Presentations

Many first-year students enter college unprepared to fully engage with scientific literature and academic library resources. Drawing on experiences from academic librarians working with STEM students, this session explores common gaps in science research skills, including navigating databases, identifying scholarly sources, and understanding the structure of scientific literature. Participants will be introduced to practical strategies and classroom-ready activities to better prepare students for college-level research. Discussion questions: What science research skills do students struggle with most when entering college? How can high school instruction better support these skills? Where can librarians and educators collaborate to support student success?

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A Mathematical Decision-Making Framework For Athlete Development In A Collegiate Taekwondo Community: Prioritizing Coaching Interventions Using Statistical Analysis And The Analytic Hierarchy Process, King Harold A. Recto, Hazel Jade L. Antonio, Jhyrald Anthony P. Dalida Jul 2026

A Mathematical Decision-Making Framework For Athlete Development In A Collegiate Taekwondo Community: Prioritizing Coaching Interventions Using Statistical Analysis And The Analytic Hierarchy Process, King Harold A. Recto, Hazel Jade L. Antonio, Jhyrald Anthony P. Dalida

Electronics, Computer, and Communications Engineering Faculty Publications

Athlete development within collegiate sports communities requires informed decisions regarding the prioritization of coaching interventions and allocation of developmental resources. However, such decisions are frequently guided by experience and intuition, limiting opportunities for systematic and evidence-based decision-making. This study develops a mathematical decision-making framework for athlete development by integrating statistical analysis and the Analytic Hierarchy Process (AHP) within a collegiate taekwondo community. Data were collected from 25 collegiate taekwondo athletes who satisfied established eligibility criteria, including participation in University Athletic Association of the Philippines (UAAP) competitions during the previous three seasons. Athletes evaluated coaching practices across five dimensions: Training and …

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Ai-Powered Resume Screening, Sang Suh, Numery Zaber Jul 2026

Ai-Powered Resume Screening, Sang Suh, Numery Zaber

Faculty Publications

Traditional resume screening is manual, slow, and susceptible to bias, and it struggles to keep pace with today’s application volumes. This paper presents a dual-engine, AI-powered resume screening system designed for transparency and reproducibility. The primary (classical) pipeline encodes resumes and job descriptions using Sentence-BERT (SBERT), computes a resume–job match score via cosine similarity, classifies candidates into 25 job categories using XGBoost, and provides model interpretability through SHAP. In parallel, a prompted large language model (LLM) baseline (GPT-4o/4o-mini) outputs a match score and predicted category for comparative analysis. A Streamlit-based interface integrates both engines to support recruiter workflows and human-in-the-loop …

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Wildfire Impacts On Fluvial Hydrology From Watershed To National Scales, Paige G. Tunby Jul 2026

Wildfire Impacts On Fluvial Hydrology From Watershed To National Scales, Paige G. Tunby

Civil Engineering ETDs

Wildfires alter the water quantity and quality in downstream river networks. Fires promote biodiversity, maintain habitat, and provide many ecosystem services in a fire-adapted landscape. However, changes in the natural fire regimes can alter ecosystem function and threaten the water security of impacted downstream communities. The magnitude, timing, and persistence of these impacts are difficult to predict due to the lack of high-resolution datasets with adequate coverage to evaluate spatiotemporal trends after a fire. This dissertation moves us beyond the status quo to evaluate post-fire fluvial responses across scales, from the event-scale impacts after the Hermit’s Peak-Calf Canyon wildfire in …

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Mapping And Modeling Threat-Evoked Brain States After Early Life Adversity, Taylor W. Uselman Jul 2026

Mapping And Modeling Threat-Evoked Brain States After Early Life Adversity, Taylor W. Uselman

Biomedical Sciences ETDs

Early life adversity (ELA) increases lifelong neuropsychiatric vulnerability. Yet how ELA reorganizes brain-wide activity and circuit coordination across later experience remains unclear. This dissertation tests the hypothesis that ELA alters adult brain-wide activity and responses to threat through disrupted coordination among neural systems that regulate emotional experience, including prefrontal-limbic and monoaminergic systems. Longitudinal manganese-enhanced MRI of adult mice exposed to standard or fragmented early care, combined with computational processing and statistical modeling, quantified brain states before, during, and long after innate predator threat. These studies established that acute threat evokes large-scale, distributed brain activity that evolves over time. ELA potentiates …

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Surveyception: An Exploration Of Deceptive Survey Forms, Muhammad Danish Jul 2026

Surveyception: An Exploration Of Deceptive Survey Forms, Muhammad Danish

Computer Science ETDs

Survey platforms such as Google Forms and Microsoft Forms are widely used for feedback, data collection, and engagement, but scammers increasingly exploit them to distribute phishing and deceptive attacks. This thesis presents a large-scale study of survey-form abuse across ten major providers. We collected 140,000 forms from three sources: public posts on X, search-engine results, and web pages from the top 10 million DomCop-ranked domains. Using automated filtering and manual qualitative review, we identified 2,645 forms requesting sensitive information and classified 566 as scams. These forms used techniques including phishing, private-secret theft, account and personal-data harvesting, financial deception, and psychological …

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Quantum Control Of Qubits And Qudits In Neutral Atom Systems, Sri Datta Vikas Buchemmavari Jul 2026

Quantum Control Of Qubits And Qudits In Neutral Atom Systems, Sri Datta Vikas Buchemmavari

Physics & Astronomy ETDs

This dissertation explores control of neutral atom quantum systems across multiple levels of abstraction, from atomic physics to system-level fault tolerance, using optimal control to improve performance. First, we propose a Rydberg entangling gate based on dressing with only the qubit control field; an interaction energy near the Rabi frequency benefits both gate speed and Rydberg decay. Second, with Sandia National Laboratories, we show that leakage errors in neutral atom systems can be converted to atom loss errors and detected using two entangling gates with an auxiliary atom, where a SWAP-based leakage detection unit outperforms the standard design. Next, we …

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How Forest Structure And Climate Influence Snowpack For Water Resources In The Southwestern United States, Lindsey L. Rotche Jul 2026

How Forest Structure And Climate Influence Snowpack For Water Resources In The Southwestern United States, Lindsey L. Rotche

Geography ETDs

Climate change, declining snowpack, and increasing wildfire risk have profound impacts on water availability in the southwestern United States. Because the southwestern United States is a global hotspot for freshwater vulnerability, and snowpack provides much of the region’s freshwater, understanding how climate and forest structure influence snowpack dynamics is increasingly important. In this dissertation I aim to better understand and communicate these dynamics through empirical data collection and the development of a simple vegetation driven temperature-index snow model: SNOW-17(VEG). I then implement the model at a watershed scale using remotely sensed imagery to create vegetation zones and climate simulations to …

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A Hybrid Deep Learning Model Combining Cnn And Extreme Learning Machine For Cyberattack Classification, Israa S. Kamil Jul 2026

A Hybrid Deep Learning Model Combining Cnn And Extreme Learning Machine For Cyberattack Classification, Israa S. Kamil

Journal of Intelligent Informatics, Networking, and Cybersecurity

As ransomware attacks and zero-day exploits grow sophisticated, the need for intelligent, accurate systems to detect such threats becomes clearer. In this paper, a hybrid learning model based on Convolutional Neural Networks (CNNs) and Extreme Learning Machine (ELM) is presented to improve multiclass classification performance for cybersecurity applications. The framework combines CNNs' hierarchical feature learning with ELMs' fast classification. An attention mechanism that assigns weights to each feature based on importance is included in the final model. The hybrid model performed well on the metrics: precision = 0.97, recall = 0.98, and F1- score = 0.97, and, as expected from …

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Towards Intelligent Iot-Ndn Security: Ai-Driven Pit Attack Detection And Cache Attack Analysis, Sura Haidar Ali, Alaa Shawqi Jaber Jul 2026

Towards Intelligent Iot-Ndn Security: Ai-Driven Pit Attack Detection And Cache Attack Analysis, Sura Haidar Ali, Alaa Shawqi Jaber

Journal of Intelligent Informatics, Networking, and Cybersecurity

Beginning with Named Data Networking (NDN), an early form of information-centric networks, the paradigm of how data is transmitted over a network was changed through the use of ``content-based'' communication instead of ``host-based'', while creating native caching at intermediate points along the path to each destination, and improving upon the security of all previous paradigms. NDN contains many inherent benefits such as caching, security, etc., but like any other paradigm, NDN creates new types of vulnerabilities, particularly within some of the key elements of this paradigm; namely the Content Store (CS), Pending Interest Table (PIT), and the Forwarding Information Base …

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Stop Blaming My Users: Illumination Of The Technocentric Mythos Bias, Ervin H. Frenzel, Richard Lightcap Jul 2026

Stop Blaming My Users: Illumination Of The Technocentric Mythos Bias, Ervin H. Frenzel, Richard Lightcap

Journal of Cybersecurity Education, Research and Practice

 Abstract -This conceptual essay addresses the need for systemic and systematic transdisciplinary analytical techniques within cybersecurity and technical security. This conceptual essay is contingent upon recognition that cybersecurity is not simply technical in nature, it does not need an adversary, and more importantly it is based upon systems engineering and systems thinking.  The essay contributes a socio-technical attribution chain and field-specific ontology/taxonomy which distinguish user-triggered events from root causes, latent conditions, technical debt, validation failures, governance failures, and attribution bias before assigning responsibility to end users. It systematically defines an ontology inclusive of developer technical debt, organizational debt arising from …

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Match Made In Ml: Developing Compatibility Relationships In Evidential Reasoning Approaches With Machine Learning, Ella Jolie Thomas Jul 2026

Match Made In Ml: Developing Compatibility Relationships In Evidential Reasoning Approaches With Machine Learning, Ella Jolie Thomas

Master's Theses

The presented expectation maximization informed evidential reasoning model extends the ability of the evidential reasoning calculus to support decision making by integrating an adaptive model learning capability. Compatibility relationships in Evidential Reasoning models are traditionally built by human domain experts. This process is labor-intensive, especially for large and complex models. Additionally, when new data becomes available, compatibility relationships must be reconstructed. Using machine learning and the expectation maximization algorithm, it is demonstrated that compatibility relationships can be constructed that learn relationships between domain knowledge that is used to make decisions. Using drug development as a domain of application, a traditional …

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Rewriting The Calculus 3 Workshop At San José State University, Moorea Lippert Jul 2026

Rewriting The Calculus 3 Workshop At San José State University, Moorea Lippert

Master's Theses

Calculus 3 at San José State University is a very important course for any student pursuing a STEM degree. However, the course is very challenging, so the university offers a supplemental workshop course for Calculus 3 students. Unfortunately, this workshop has not aligned with modern research in math education. This thesis documents efforts to recreate the workshop to better align with this modern research.

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Reskilling And Retraining The Water Technology Workforce: An Agentic Generative Ai Framework For Water Purification, Nano‑Mems, And Curriculum Development, Satyadhar Joshi, Noor Zulfiqar Jul 2026

Reskilling And Retraining The Water Technology Workforce: An Agentic Generative Ai Framework For Water Purification, Nano‑Mems, And Curriculum Development, Satyadhar Joshi, Noor Zulfiqar

Harrisburg University Other Works

The rapid digitalization of water infrastructure is bringing artificial intelligence, advanced sensing, and membrane materials science into routine water treatment practice. At the same time, utilities, regulators, and training institutions face a persistent workforce challenge: many operators, engineers, and managers are being asked to adopt data-driven tools without a coherent educational pathway that links AI literacy to real treatment workflows. This article synthesizes recent literature on agentic generative AI, reinforcement learning, smart sensing, nano-enabled membranes, and digital twins for water systems, then translates those developments into a structured reskilling model for the water sector. The proposed framework is organized around …

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Enhanced Adaptive Smith Predictor Control For Underground Coal Gasification With Long Time Delays, Tang Yang, Wu Qiong, Zhang Lei, Zhou Mingjun, Wan Min, Liao Zhuodong Jul 2026

Enhanced Adaptive Smith Predictor Control For Underground Coal Gasification With Long Time Delays, Tang Yang, Wu Qiong, Zhang Lei, Zhou Mingjun, Wan Min, Liao Zhuodong

Coal Geology & Exploration

Background Underground coal gasification (UCG) represents an in situ conversion technology used to convert solid coals into gaseous fuel. However, the reaction process during UCG exhibits significant time delays. Such a limitation will reduce the response capability of the UCG system and is prone to induce overshoot and oscillation, thereby increasing the system’s control difficulty and reducing its stability and dynamic performance. Method To address these issues, this study proposed an enhanced Smith predictor control algorithm based on a genetic algorithm and established a semi-physical experimental platform integrating a physical distributed control system DCS-Matlab for modeling. Using the platform, experiments …

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Comparison Of Log-Based Coal Structure Identification Methods For Structurally Complex Areas: A Case Study Of The Huainan Mining Area, Zhang Zixin, Zhou Xiaozhi, Chen Xuehua Jul 2026

Comparison Of Log-Based Coal Structure Identification Methods For Structurally Complex Areas: A Case Study Of The Huainan Mining Area, Zhang Zixin, Zhou Xiaozhi, Chen Xuehua

Coal Geology & Exploration

Objective CO2 displacing coalbed methane (CBM) provides substantial environmental and energy benefits. However, differences in coal structures represent a key geological factor influencing the effectiveness of this technique. Constrained by the complex geological conditions for CBM occurrence and the impacts of multiple factors on the log responses of coal structures, traditional log-based methods for coal structure identification face challenges such as much human intervention, complex feature engineering, and poor adaptability. This study aims to achieve effective identification of complex coal structures within a single coal seam. Methods An asymmetric convolution kernel-based convolutional neural network (CNN) model for coal structure …

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Culmination Of The Arts And Stem To Enhance Creativity And Promote Learning, Kaleigh Evans Jul 2026

Culmination Of The Arts And Stem To Enhance Creativity And Promote Learning, Kaleigh Evans

Physics and Astronomy Summer Fellows

In this work, we investigate the results from a survey, issued to a course in “Stained Glass” (n= 23 students). Major findings include that the introduction of a problem-based learning (PBL) course in the arts of stained glass may support high demand skills such as interdisciplinary conceptual learning as well as soft skills such as scientific confidence, interdisciplinary transfer, and collaborative learnings. A journal paper draft was completed and will be submitted this Fall. This summer, work was also done to establish a guide to modeling and 3D printing to help establish and grow a makerspace on campus for use …

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Can Machines Testify? Llms And The Boundaries Of Testimonial Epistemology, Michael J. Cummins Jul 2026

Can Machines Testify? Llms And The Boundaries Of Testimonial Epistemology, Michael J. Cummins

Philosophy Summer Fellows

As Large Language Models and AI chatbots become increasingly prevalent, pressing questions are raised about whether beliefs formed through LLM interactions carry the same epistemic weight as beliefs formed through human testimony. How we answer this question depends on whether LLMs can function as testifiers, a role which is typically assumed to require a human or human-like agent. This assumption has gone largely unexamined, yet its consequences are significant: if LLM outputs cannot constitute testimony, then the justificatory tools of testimonial epistemology are unavailable to any beliefs formed through LLM interaction. This paper challenges that assumption. It first argues that …

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Sustainable Consumer Behavior Modeling: A Complex-Systems Approach To Neuromarketing, Preethi Nanjundan, Nupoor Sanjay Bhute, Ragini Topre, Lijo Thomas Jul 2026

Sustainable Consumer Behavior Modeling: A Complex-Systems Approach To Neuromarketing, Preethi Nanjundan, Nupoor Sanjay Bhute, Ragini Topre, Lijo Thomas

Northeast Journal of Complex Systems (NEJCS)

This study examines the application of complex-systems modeling to neuromarketing data for gaining deeper insights into the mechanisms underlying sustainable consumer behavior. It investigates how neural and biometric responses, interpreted through a systems-based perspective, can uncover dynamic interactions, feedback mechanisms, and emergent behavioral patterns influencing sustainable purchase decisions. The research explores the impact of sustainability-oriented marketing stimuli on long-term behavioral intentions by emphasizing the interconnected roles of cognitive processing, emotional engagement, implicit associations, and collective consumer dynamics. Through simulation-based modeling and structural analysis, the study demonstrates how subconscious neural responses and affective mechanisms mediate the relationship between marketing interventions, consumer …

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Simulations Of Skyrmions And Merons, Ryan Friesen, Aidan Kirk, Tom Carroll, Xuemei Cheng Jul 2026

Simulations Of Skyrmions And Merons, Ryan Friesen, Aidan Kirk, Tom Carroll, Xuemei Cheng

Physics and Astronomy Summer Fellows

Skyrmions and merons are particle-like spin structures that are found in specific magnetic materials. Due to their stability and nanoscale size, these quasiparticles have been proposed as promising candidates for qubits in quantum computing applications. Our goal is to design materials that can host and stabilize these quasiparticles. Skyrmions and merons exist only under specific conditions, and the parameter space for these materials is vast. Thus, we use the simulation package MuMax3 to run simulations to test the viability of potential materials to simplify this search. We present on our simulations of these skyrmions and merons. This work was supported …

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Stylometric And Formal Patterns In The Scholarly Impact Of Scientific Literature, Joshua Ange, Eric Godat, Rajani Sudan Jul 2026

Stylometric And Formal Patterns In The Scholarly Impact Of Scientific Literature, Joshua Ange, Eric Godat, Rajani Sudan

SMU Journal of Undergraduate Research

Scientific communication is typically tied to promoting public engagement and interest in science, increasing scientific literacy, and playing an essential role in policymaking. The success of public communication of scientific findings is largely associated with secondary characteristics of research (e.g. the style of writing and presentation), rather than the primary content or research quality. But it is unclear to what extent the success of scientific literature intended for working scientists is influenced by those same secondary characteristics. Does the writing style of scientific articles impact their success in academic spheres? In this study, we explore the stylometric and formal characteristics …

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Lossless Medical Image Compression Using Integer Discrete Wavelet Transform With Adaptive Subband Differencing And Context-Adaptive Entropy Coding, Rasha F. Nadhim, Ibrahim Adel Ibrahim, Ashwaq T. Hashim Jul 2026

Lossless Medical Image Compression Using Integer Discrete Wavelet Transform With Adaptive Subband Differencing And Context-Adaptive Entropy Coding, Rasha F. Nadhim, Ibrahim Adel Ibrahim, Ashwaq T. Hashim

Journal of Intelligent Informatics, Networking, and Cybersecurity

From transform-domain decorrelation and adaptive entropy coding, we propose a method for efficient lossless compression of medical images in this work. We implement the Integer Discrete Wavelet Transform (IDWT) to decompose the input image into four subbands of LL, LH, HL, HH, encompassing approximation and directional detail elements, in the initial implementation. It also removes spatial redundancy in image information and decomposes image information into a less correlated and more sparsely distributed set of coefficients. To decrease redundancy further, it proposes a subband-dependent differencing scheme, which decorrelates neighbouring wavelet coefficients with directional prediction. So horizontal differencing is done on LH, …

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