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Optimizing Distributed Boundary Exchanges For Benchmarks, Solvers And Sparse Matrix Operations, Gerald Collom Jul 2025

Optimizing Distributed Boundary Exchanges For Benchmarks, Solvers And Sparse Matrix Operations, Gerald Collom

Computer Science ETDs

Boundary exchanges dominate the cost of both stenciled codes and those that rely on sparse matrix operations. The performance of large boundary exchanges is limited by synchronization overheads and injection bandwidth limitations. Irregular boundary exchanges incur additional overheads due to the large number of required messages. This thesis investigates multiple methods for improving the performance and scalability of both Cartesian and irregular boundary exchanges. Since boundary exchanges are typically performed iteratively, persistent communication presents an opportunity for optimization by sharing and amortizing setup costs. Partitioned communication is also explored to increase asynchrony, reducing bottlenecks from synchronization overheads and data congestion. …

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Network Intelligence For Next-Generation Wireless Networks: Advancing Distribution And Coordination, Yonatan Melese Worku Jul 2025

Network Intelligence For Next-Generation Wireless Networks: Advancing Distribution And Coordination, Yonatan Melese Worku

Electrical and Computer Engineering ETDs

Next-generation wireless networks, encompassing 6G and beyond, face rigorous demands for ultra-low latency, ubiquitous connectivity, exceptionally high data rates, and robust security, necessitating innovative approaches to resource optimization and network protection. This dissertation proposes a pioneering framework that synergizes advanced methodologies—deep reinforcement learning, deep learning, blockchain, and multi-agent systems—to address these challenges. Distributed architectures, underpinned by AI-driven multi-agent systems, form the backbone of this framework, enabling seamless integration and intelligent orchestration across diverse domains. The research advances IoT-based systems leveraging machine learning for resource efficiency in healthcare applications, develops reinforcement learning-driven frameworks to optimize energy and coverage for Unmanned Aerial …

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Reviving The Lost Art: Historical Foundations And Future Pathways For Bespoke Service In Luxury Retail, Andrew Burnstine Jul 2025

Reviving The Lost Art: Historical Foundations And Future Pathways For Bespoke Service In Luxury Retail, Andrew Burnstine

Faculty and Staff Publications & Presentations

The mid-20th century witnessed a zenith of deeply personalized, bespoke service within iconic luxury specialty retailers. This paper critically analyzes the foundational principles of this historical bespoke service model, extending Service-Dominant (S-D) Logic and retail evolution theory, to propose a robust framework for its modern revival. Employing a rigorous qualitative, multiple-case study approach, grounded in extensive historical and media analysis of four archetypal American and British luxury boutiques, and uniquely informed by an insider-ethnographic perspective on the central case exemplar ("Martha's"), the study distills six core principles: Profound Client Knowledge, Visionary Curation & Styling, Anticipatory & Proactive Service, The Exclusive …

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“Silent Is Not Actually Silent”: An Investigation Of Toxicity On Bug Report Discussion, Mia Mohammad Imran, Jaydeb Sarker Jul 2025

“Silent Is Not Actually Silent”: An Investigation Of Toxicity On Bug Report Discussion, Mia Mohammad Imran, Jaydeb Sarker

Computer Science Faculty Research & Creative Works

Toxicity in bug report discussions poses significant challenges to the collaborative dynamics of open-source software development. Bug reports are crucial for identifying and resolving defects, yet their inherently problem-focused nature and emotionally charged context make them susceptible to toxic interactions. This study explores toxicity in GitHub bug reports through a qualitative analysis of 203 bug threads, including 81 toxic ones. Our findings reveal that toxicity frequently arises from misaligned perceptions of bug severity and priority, unresolved frustrations with tools, and lapses in professional communication. These toxic interactions not only derail productive discussions but also reduce the likelihood of actionable outcomes, …

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Llput: Investigating Large Language Models For Bug Report-Based Input Generation, Alif Al Hasan, Subarna Saha, Mia Mohammad Imran, Tarannum Shaila Zaman Jul 2025

Llput: Investigating Large Language Models For Bug Report-Based Input Generation, Alif Al Hasan, Subarna Saha, Mia Mohammad Imran, Tarannum Shaila Zaman

Computer Science Faculty Research & Creative Works

Failure-inducing inputs play a crucial role in diagnosing and analyzing software bugs. Bug reports typically contain these inputs, which developers extract to facilitate debugging. Since bug reports are written in natural language, prior research has leveraged various Natural Language Processing (NLP) techniques for automated input extraction. With the advent of Large Language Models (LLMs), an important research question arises: how effectively can generative LLMs extract failure-inducing inputs from bug reports? In this paper, we propose LLPut, a technique to empirically evaluate the performance of three open-source generative LLMs-LLaMA, Qwen, and Qwen-Coder-in extracting relevant inputs from bug reports. We conduct an …

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Optimization And Model Averaging Of Histogram-Based Place Cell Firing Rate Maps Using The Point Process Framework, Murat Okatan Jul 2025

Optimization And Model Averaging Of Histogram-Based Place Cell Firing Rate Maps Using The Point Process Framework, Murat Okatan

Turkish Journal of Electrical Engineering and Computer Sciences

The firing rate of hippocampal place cells depends on the spatial position of the organism in an environment. This position dependence is often quantified by constructing spike-in-location and time-in-location histograms, the ratio of which yields a firing rate map. The purpose of this study is to present a new method for optimizing the spatial resolution of histogram-based firing rate maps. It is pointed out that histogram-based firing rate maps are conditional intensity functions of inhomogeneous Poisson process models of neural spike trains, and, as such, they can be optimized through model selection within the point process framework. The point process …

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Isar Imaging Of Drone Swarms At 77 Ghz, Remzi̇ye Büşra Çoruk, Ali̇ Kara, Eli̇f Aydin Jul 2025

Isar Imaging Of Drone Swarms At 77 Ghz, Remzi̇ye Büşra Çoruk, Ali̇ Kara, Eli̇f Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

The proliferation of easily available, internet-purchased drones, coupled with the emergence of coordinated drone swarms, poses a significant security threat for airspace. Detecting these swarms is crucial to prevent potential accidents, criminal misuse, and airspace disruptions. This paper proposes a novel inverse synthetic aperture radar (ISAR) imaging technique for high-resolution reconstruction of drone swarms at 77 GHz millimeter wave (mmWave) frequency, offering a valuable tool for military and defense anti-drone systems. The key parameters affecting down-range and cross-range resolution (0.05 m), ultimately enabling the generation of detailed ISAR images are discussed. Here, we create diverse scenarios encompassing various swarm formations, …

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Adaptive Backstepping Control With Real-Time Fuzzy Logic Parameter Selection Of A Field- Oriented Control-Based Permanent Magnet Synchronous Motor Driver, Fati̇h Bayir, Erkan Zergeroğlu Jul 2025

Adaptive Backstepping Control With Real-Time Fuzzy Logic Parameter Selection Of A Field- Oriented Control-Based Permanent Magnet Synchronous Motor Driver, Fati̇h Bayir, Erkan Zergeroğlu

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes an adaptive backstepping control approach integrated with a real-time fuzzy logic parameter selection algorithm to enhance the robustness and stability of a permanent magnet synchronous motor (PMSM) controller under parametric uncertainties and external disturbances. Although backstepping control performs well under varying disturbances, it must be supported by an adaptive control algorithm to effectively handle both variable disturbances and parameter uncertainties. Moreover, because the fixed parameters of the adaptive backstepping controller limit the dynamic performance of the velocity tracking loop, this study incorporates fuzzy logic control—a soft computing algorithm capable of real-time parameter adjustment—to achieve more robust outcomes. …

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Excitation Of Synchronous Machine By Contactless Power Transfer - Review From The Perspective Of Electric Vehicles, Erhan Tuncel, Emi̇n Yildiriz Jul 2025

Excitation Of Synchronous Machine By Contactless Power Transfer - Review From The Perspective Of Electric Vehicles, Erhan Tuncel, Emi̇n Yildiriz

Turkish Journal of Electrical Engineering and Computer Sciences

Electrically excited synchronous machines (EESMs) are one of the best choices for propulsion motor appli cation in electric vehicles (EVs) due to their wide torque-speed characteristics. Moreover, the air gap flux density can be easily controlled by varying the excitation current. Despite these advantages, it is difficult to transfer the current required by the rotating excitation winding into the motor under conventional methods, so it is not widely used in EVs. In this study, the emerging literature on contactless power transfer methods is reviewed for applicability to an EESM that can operate as an EV propulsion motor. Design criteria such …

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Rescon: Residual Consistency For Real-World Super-Resolution, Erdi̇ Saritaş, Hazim Kemal Ekenel Jul 2025

Rescon: Residual Consistency For Real-World Super-Resolution, Erdi̇ Saritaş, Hazim Kemal Ekenel

Turkish Journal of Electrical Engineering and Computer Sciences

Real-world super-resolution is a highly challenging problem in the field of computer vision. Besides enhancing image resolution and improving visual details, information loss due to complex real-world degradations is desired to be restored. One of the primary hardness of this problem is finding sufficiently large paired datasets for training. Researchers have developed techniques that generate synthetic low-resolution pairs using high-resolution images with a generative adversarial network-based degradation generator to address this issue. In these approaches, the degradation generator is trained by utilizing real-world low-resolution images as the target domain, generating a degraded low-resolution counterpart of the high-resolution input. However, in …

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Secure Frameworks For User Motion Data In Virtual Reality, Jayasri Sai Nikitha Guthula Jul 2025

Secure Frameworks For User Motion Data In Virtual Reality, Jayasri Sai Nikitha Guthula

Theses and Dissertations

Virtual Reality is an innovative technology transforming industries such as gaming, healthcare, and remote collaboration. The increasing deployment of these systems results in the continuous collection of telemetry data, including motion patterns, hand gestures, and spatial interactions. This data is valuable for enhancing user experiences and optimizing system performance. However, it also introduces significant privacy risks. Unlike traditional digital footprints, motion data captures fine-grained physical behaviors that can be linked to individual users, making anonymization ineffective in preventing re-identification.This research introduces secure frameworks for user motion data in virtual reality, each proposed framework addressing privacy preservation from a different angle. …

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Magnetic Macro Pendulum Design And Real-Time Control Application: Simulation And Experiment, Hüseyi̇n Yildiz, Serdar Yilmaz, Yasemi̇n Poyraz Koçak, Erol Uzal Jul 2025

Magnetic Macro Pendulum Design And Real-Time Control Application: Simulation And Experiment, Hüseyi̇n Yildiz, Serdar Yilmaz, Yasemi̇n Poyraz Koçak, Erol Uzal

Turkish Journal of Electrical Engineering and Computer Sciences

Over the last decade, the number of studies in the field of magnetic micro robots has significantly increased due to expectations of performing microsurgery, drug delivery, and similar medical procedures. Magnetic micro robots have advantages over other types of micro robots in terms of having independent designs for rotor and stator structures. Magnetic micro robots can be controlled by magnetic fields and can be programmed to move in certain directions and to perform various functions. This paper implements the computer-aided real-time control of a single-arm micro-pendulum structure to (eventually) perform cell manipulation tasks. The mechanical structure, mathematical model, control circuit …

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Urban Landscape Recovery And Lulc Analysis: A Deep Learning Approach To Post-Extreme Rainfall Impacts In Dubai, Xin Hong Jul 2025

Urban Landscape Recovery And Lulc Analysis: A Deep Learning Approach To Post-Extreme Rainfall Impacts In Dubai, Xin Hong

All Works

From April 14 to 18, 2024, the United Arab Emirates (UAE) experienced its heaviest rainfall in 75 years, resulting in widespread flooding across multiple emirates, including Dubai. This study utilizes high-resolution PlanetScope imagery and a U-Net deep learning model to assess the flood impact and analyze post-rainfall recovery patterns in Dubai’s urban landscape. By integrating Sentinel-2derived land use and land cover (LULC) data to refine the training dataset, a high-accuracy U-Net model was developed through transfer learning that effectively classified pre- and post-rainfall LULC. Post-rainfall LULC change detections indicate that 23.8 km2 of land was flooded, which is equivalent …

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Combination Of Irreversible Electroporation And Clostridium Novyi-Nt Bacterial Therapy For Colorectal Liver Metastasis, Zigeng Zhang, Guangbo Yu, Qiaoming Hou, Farideh Amirrad, Sha Webster, Surya M. Nauli, Jianhua Yu, Vahid Yaghmai, Aydin Eresen, Zhuoli Zhang Jul 2025

Combination Of Irreversible Electroporation And Clostridium Novyi-Nt Bacterial Therapy For Colorectal Liver Metastasis, Zigeng Zhang, Guangbo Yu, Qiaoming Hou, Farideh Amirrad, Sha Webster, Surya M. Nauli, Jianhua Yu, Vahid Yaghmai, Aydin Eresen, Zhuoli Zhang

Pharmacy Faculty Articles and Research

Colorectal liver metastasis (CRLM) poses a significant challenge in oncology due to its high incidence and poor prognosis in unresectable cases. Current treatments, including surgical resection, systemic chemotherapy, and liver-directed therapies, often fail to effectively target hypoxic tumor regions, which are inherently more resistant to these interventions. This review examines the potential of a novel therapeutic strategy combining irreversible electroporation (IRE) ablation and Clostridium novyi-nontoxic (C. novyi-NT) bacterial therapy. IRE is a non-thermal tumor ablation technique that uses high-voltage electric pulses to create permanent nanopores in cell membranes, leading to cell death while preserving surrounding structures, and …

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Multilingual Cyber Threat Intelligence Feeds Preprocessing For Threat Intelligence Event Extraction: A Systematic Literature Review, Jamal H. Al-Yasiri, Mohamad Fadli Bin Zolkipli, Nik Fatinah N. Mohd Farid Jul 2025

Multilingual Cyber Threat Intelligence Feeds Preprocessing For Threat Intelligence Event Extraction: A Systematic Literature Review, Jamal H. Al-Yasiri, Mohamad Fadli Bin Zolkipli, Nik Fatinah N. Mohd Farid

Karbala International Journal of Modern Science

In cyber threat intelligence (CTI), information security specialists face overwhelming data flows from multiple sources, including hacker forums, dark web markets, and social media. These diverse and multilingual information streams require extensive analysis and processing. However, the current state of CTI faces several challenges, such as reliance on manual annotation and evaluation, as well as limited support for non-English languages, which hinders advanced threat detection and comprehensive analysis. This systematic literature review proposes a conceptual framework designed to overcome existing state-of-the-art limitations. It evaluates recent advancements in CTI methodologies by following PRISMA guidelines and analyzing selected studies from reputable sources, …

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More Everything Forever: Ai Overlords, Space Empires, And Silicon Valley’S Crusade To Control The Fate Of Humanity, Joseph Kirby Jul 2025

More Everything Forever: Ai Overlords, Space Empires, And Silicon Valley’S Crusade To Control The Fate Of Humanity, Joseph Kirby

Consensus

Becker, A. (2025). More everything forever : AI overlords, space empires, and Silicon Valley’s crusade to control the fate of humanity. Basic Books. ISBN: 9781541619593

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Improving Large Language Models’ Summarization Accuracy By Adding Highlights To Discharge Notes: Comparative Evaluation, Mahshad Koohi Habibi Dehkordi, Yehoshua Perl, Fadi P. Deek, Zhe He, Vipina K. Keloth, Hao Liu, Gai Elhanan, Andrew J. Einstein Jul 2025

Improving Large Language Models’ Summarization Accuracy By Adding Highlights To Discharge Notes: Comparative Evaluation, Mahshad Koohi Habibi Dehkordi, Yehoshua Perl, Fadi P. Deek, Zhe He, Vipina K. Keloth, Hao Liu, Gai Elhanan, Andrew J. Einstein

School of Computing Faculty Scholarship and Creative Works

Background: The American Medical Association recommends that electronic health record (EHR) notes, often dense and written in nuanced language, be made readable for patients and laypeople, a practice we refer to as the simplification of discharge notes. Our approach to achieving the simplification of discharge notes involves a process of incremental simplification steps to achieve the ideal note. In this paper, we present the first step of this process. Large language models (LLMs) have demonstrated considerable success in text summarization. Such LLM summaries represent the content of EHR notes in an easier-to-read language. However, LLM summaries can also introduce inaccuracies. …

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Coli@Fire2024: Findings Of Word-Level Code-Mixed Language Identification In Dravidian Languages, Asha Hegde, Fazlourrahman Balouchzahi, Sabur Butt, Sharal Coelho, Kavya G, Harshitha S. Kumar, Sonith D, Shashirekha H. L., Ameeta Agrawal Jul 2025

Coli@Fire2024: Findings Of Word-Level Code-Mixed Language Identification In Dravidian Languages, Asha Hegde, Fazlourrahman Balouchzahi, Sabur Butt, Sharal Coelho, Kavya G, Harshitha S. Kumar, Sonith D, Shashirekha H. L., Ameeta Agrawal

Computer Science Faculty Publications and Presentations

Code-mixing, a linguistic phenomenon where multiple languages are blended within a single text, has become increasingly prevalent in multilingual societies, particularly in digital communication. The CoLI-Dravidian shared task, organized as part of Forum for Information Retrieval and Evaluation (FIRE) 2024, aimed to address these challenges by inviting researchers to develop models capable of classifying words in code-mixed texts involving Dravidian languages — Tamil, Kannada, Malayalam, and Tulu - interwoven with English. The task presents significant challenges due to the complexity of linguistic structures, mixed-language tokens, and dialectal variations, especially in low-resource languages like those in the Dravidian family. The participating …

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Assessing The Adversarial Robustness Of Multimodal Medical Ai Systems: Insights Into Vulnerabilities And Modality Interactions, Ekaterina Mozhegova, Asad Masood Khattak, Adil Khan, Roman Garaev, Bader Rasheed, Muhammad Shahid Anwar Jul 2025

Assessing The Adversarial Robustness Of Multimodal Medical Ai Systems: Insights Into Vulnerabilities And Modality Interactions, Ekaterina Mozhegova, Asad Masood Khattak, Adil Khan, Roman Garaev, Bader Rasheed, Muhammad Shahid Anwar

All Works

The emergence of both task-specific single-modality models and general-purpose multimodal large models presents new opportunities, but also introduces challenges, particularly regarding adversarial attacks. In high-stakes domains like healthcare, these attacks can severely undermine model reliability and their applicability in real-world scenarios, highlighting the critical need for research focused on adversarial robustness. This study investigates the behavior of multimodal models under various adversarial attack scenarios. We conducted experiments involving two modalities: images and texts. Our findings indicate that multimodal models exhibit enhanced resilience against adversarial attacks compared to their single-modality counterparts. This supports our hypothesis that the integration of multiple modalities …

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Antibacterial Potential Of Tapanuli Orangutan (Pongo Tapanuliensis) Food In Batang Toru Forest Against Escherichia Coli And Salmonella Typhi, Herna Febrianty Sianipar, Wahyu Widoretno, Luchman Hakim, Rezi Rahmi Amolia, Fatchiyah Fatchiyah Jul 2025

Antibacterial Potential Of Tapanuli Orangutan (Pongo Tapanuliensis) Food In Batang Toru Forest Against Escherichia Coli And Salmonella Typhi, Herna Febrianty Sianipar, Wahyu Widoretno, Luchman Hakim, Rezi Rahmi Amolia, Fatchiyah Fatchiyah

Karbala International Journal of Modern Science

Diarrhea is a common disease affecting orangutans, primarily caused by Escherichia coli and Salmonella typhi bacteria. To treat this disease, antibacterial food sources are essential as therapeutic agents for orangutans. The fruits consumed by Tapanuli orangutans include Campnosperma auriculatum, Agathis borneensis, Artocarpus heterophyllus, Castanopsis argantea, and Aglaia tomentosa. This study aims to examine the amino acid and phytochemical components with potential antibacterial properties in these five fruit species and their inhibitory effects on E. coli and S. typhi growth through cell lysis, observed using a Scanning Electron Microscope (SEM). The samples were tested for amino acids, phytochemicals, vitamin C content, …

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Investigating The Impact Of Agent Openness On Planning In Multi-Agent Systems, Bala Subramanyam Duggirala Jul 2025

Investigating The Impact Of Agent Openness On Planning In Multi-Agent Systems, Bala Subramanyam Duggirala

School of Computing: Dissertations, Theses, and Student Research

Multi-agent systems (MAS) possess significant potential for modeling real-world scenarios requiring coordinated actions (like wildfire fighting or ridesharing) among autonomous entities or agents (e.g., wildfire fighting agents) in complex, dynamic environments. Effective decision-theoretic planning (where each agent must carefully consider both the immediate and the future situations or states, and coordinate with the other agents (neighbors) to evaluate what needs to be done at present) within MAS, especially multiagent planning, where the planning agent directly models its neighbors in order to estimate their optimal actions, is critical, yet challenged by factors like partial observability, openness, and diverse agent types with …

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Zero Trust Architecture For Electric Transportation Systems: A Systematic Survey And Deep Learning Framework For Replay Attack Detection, Grace Muriithi, Behnaz Papari, Ali Arsalan, Laxman Timilsina, Alex Muriithi, Elutunji Buraimoh, Asif Khan, Gokhan Ozkan, Christopher Edrington, Akram Papari Jul 2025

Zero Trust Architecture For Electric Transportation Systems: A Systematic Survey And Deep Learning Framework For Replay Attack Detection, Grace Muriithi, Behnaz Papari, Ali Arsalan, Laxman Timilsina, Alex Muriithi, Elutunji Buraimoh, Asif Khan, Gokhan Ozkan, Christopher Edrington, Akram Papari

Montclair State University Scholarship & Creative Works

Modern and autonomous hybrid electric vehicles (HEVs), as complex cyber-physical systems, represent a key innovation in the future of transportation. However, the increasing interconnectivity and reliance on digital components expose these vehicles to significant cybersecurity risks. To address these challenges, Zero Trust Architecture (ZTA) has emerged as a promising security framework. Operating on the principle of ‘never trust, always verify,’ ZTA offers a comprehensive approach to ensuring continuous trust verification in HEV systems. Despite its potential, the application of ZTA within cyber-physical vehicular systems remains underexplored, and its practical benefits and limitations are not yet fully understood by the engineering …

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Multiscale Modeling And Dynamic Mutational Profiling Of Binding Energetics And Immune Escape For Class I Antibodies With Sars-Cov-2 Spike Protein: Dissecting Mechanisms Of High Resistance To Viral Escape Against Emerging Variants, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker Jul 2025

Multiscale Modeling And Dynamic Mutational Profiling Of Binding Energetics And Immune Escape For Class I Antibodies With Sars-Cov-2 Spike Protein: Dissecting Mechanisms Of High Resistance To Viral Escape Against Emerging Variants, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The rapid evolution of SARS-CoV-2 has underscored the need for a detailed understanding of antibody binding mechanisms to combat immune evasion by emerging variants. In this study, we investigated the interactions between Class I neutralizing antibodies—BD55-1205, BD-604, OMI-42, P5S-1H1, and P5S-2B10—and the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein using multiscale modeling, which combined molecular simulations with the ensemble-based mutational scanning of the binding interfaces and binding free energy computations. A central theme emerging from this work is that the unique binding strength and resilience to immune escape of the BD55-1205 antibody are determined by leveraging a broad epitope …

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Effects Of Plasma-Activated Water On Wheat: Germination And Seedling Development, Wafaa Abdulrazzaq Abdullah, Hadeel O. Ismael, Duaa A. Uamran, Hammad R. Humud Jul 2025

Effects Of Plasma-Activated Water On Wheat: Germination And Seedling Development, Wafaa Abdulrazzaq Abdullah, Hadeel O. Ismael, Duaa A. Uamran, Hammad R. Humud

Karbala International Journal of Modern Science

The food sector must contend with issues such as pathogen resistance to some of the available chemical agents, environmental pollution, and climate change to provide healthy food for livestock and people. The application of atmospheric pressure plasma jets (APPJs) is one potential solution for such problems. Plasma is appropriate for effective surface decontamination regarding food products and seeds, surface decontamination, and achieving improved agricultural production yields. The impact of plasma-activated water (PAW) produced by plasma jet discharge (PJD) system on in vitro-cultivated wheat seeds is examined in this work. For this aim, a plasma jet system was constructed with a …

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Teaching Ai Ethics And Skepticism: The Impact Of Instruction On Ethical Usage On Students’ Perceptions, Jenna D. Justin Jul 2025

Teaching Ai Ethics And Skepticism: The Impact Of Instruction On Ethical Usage On Students’ Perceptions, Jenna D. Justin

Journal of Practitioner Research

This study investigates the ethical implications of artificial intelligence (AI) in K-12 education, focusing on how explicit instruction influences students' perceptions of AI tools like ChatGPT. Conducted with 80 sixth-grade students at A.D. Henderson University School and FAU High School, the research tracks changes in student understanding and skepticism of AI following a World History unit. Pre- and post-instruction surveys revealed a decline in comfort with AI as students became more aware of its ethical concerns, including plagiarism, bias, and misinformation. The findings suggest integrating AI ethics into the middle school curriculum to foster responsible AI usage among students.

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Policy-Based Redactable Set Signatures, Zachary A. Kissel Jul 2025

Policy-Based Redactable Set Signatures, Zachary A. Kissel

Computer and Data Science Faculty Publications

A redactable set signature scheme is a signature scheme that allows a redactor, without possessing the signing key, to convert a signature on set S to a signature on set S' if S' ⊂ S. This paper introduces a new form of redactable set signature scheme called a policy-based redactable set signature scheme. These redactable set signatures allow for a signer to provide a redaction policy at signing time that limits the possible redactions that can be made by a redactor. In particular, a signature on set S can only be redacted to a signature on if S' ⊂ …

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Digital Identity Management As A Critical Criminal Justice And Homeland Security Legal Issue: A Qualitative Analysis Of The Reasonable Person Factors Involved In Court Decisions, William H. Nicholson Jul 2025

Digital Identity Management As A Critical Criminal Justice And Homeland Security Legal Issue: A Qualitative Analysis Of The Reasonable Person Factors Involved In Court Decisions, William H. Nicholson

Doctoral Dissertations and Projects

The purpose of this descriptive qualitative applied study is to define and explain through analysis the reasonable person standard as it relates to prosecution and sentencing computer crime cases involving digital identities while addressing the problem of digital anonymity. This has been done by analyzing computer crime cases with the advent of current and planned technologies, and surveying potential jurors to understand the current state of knowledge of digital attribution. This descriptive qualitative research method analyzed the problem through the use of criminological theories of control and social learning theory to better understand the reasonable person standard in computer crime …

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Alignment Of Perceptual Similarity Metrics With Human Perception, Abhijay Ghildyal Jul 2025

Alignment Of Perceptual Similarity Metrics With Human Perception, Abhijay Ghildyal

Dissertations and Theses

Perceptual similarity metrics are used for quantitatively evaluating the similarity between two images as it would appear to human perception. These metrics aim to mimic the human visual system, providing a more accurate assessment of visual similarity. Such visual assessments are considered to be more advanced than simple pixel-wise comparisons such as ℓp norm distances. Thus, a human-like assessment of visual similarity, makes the metrics valuable for applications in image compression, restoration, and enhancement, where evaluating perceptual quality is crucial. Perceptual similarity metrics have progressively become more correlated with human judgments on perceptual similarity; however, despite recent advances, the …

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Securing Ai-Generated Code, Andreas E. Nelson Jul 2025

Securing Ai-Generated Code, Andreas E. Nelson

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

The increasing use of AI for code generation presents significant security challenges, as these tools often lack inherent security awareness and can produce vulnerable code. This paper investigates these security risks, outlining common types of vulnerabilities (such as injection flaws and improper resource handling) found in AI-generated code. It further explores and evaluates mitigation techniques aimed at im-proving code security, including model fine-tuning and adversarial strategies like Security Verifier Enhanced Neural Steering (SVEN). Findings indicate that while current methods offer promising ways to reduce vulnerabilities, ongoing research and development are crucial for the secure and responsible deployment of AI in …

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Relightable Neural Radiance Fields For Novel View Synthesis, Malena I. Mahoney Jul 2025

Relightable Neural Radiance Fields For Novel View Synthesis, Malena I. Mahoney

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

This paper describes relighting neural radiance fields for novel view synthesis. View synthesis is the problem of using input images with corresponding camera angles to produce a photorealistic 3D model of an environment and its objects. Neural radiance fields (NeRFs) were created as a solution to view synthesis. Neural radiance field models work well for generating realistic 3D models from 2D image inputs; how-ever, they do not support changing the lighting or placing the objects from the input images into different environments. The problem comes from the fact that NeRFs rely on a neural network that is essentially overfitted to …

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