Pengujian High Fidelity Prototipe Media Pembelajaran Interaktif Bahasa Inggris Dengan Gamifikasi Menggunakan User Experience Questionare,
2026
Lampung University
Pengujian High Fidelity Prototipe Media Pembelajaran Interaktif Bahasa Inggris Dengan Gamifikasi Menggunakan User Experience Questionare, Adhitya Prastyadi, Meizano Muhammad Ardhi, Daniel Rinaldi, Margaretha Karolina Sagala
Jurnal Sosial Humaniora Terapan
Abstract
Testing a Hi-Fi Prototype of Interactive English Learning Media with Gamification Using UEQ
This study aims to test and evaluate the User Experience (UX) quality of a High-Fidelity prototype for interactive English learning media integrating gamification elements. The research is motivated by the low English proficiency and motivation among Indonesian students, and the potential of digital media and gamification to enhance learning engagement. Inspired by the success of the Duolingo application, this prototype was designed to create an enjoyable and effective learning experience. A quantitative research methodology was employed, involving high school students as participants selected via purposive sampling. …
Comparative Evaluation Of Deep Learning Models: Resnet18, Minivgg, And Yolov8 For Five-Class Blood Cell Classification,
2026
Fort Hays State University
Comparative Evaluation Of Deep Learning Models: Resnet18, Minivgg, And Yolov8 For Five-Class Blood Cell Classification, Keita Sakurai
Master's Theses or Doctor of Nursing Practice
Accurate classification of blood cell types is a critical task in automated hematological analysis. This study presents a comparative evaluation of three deep learning architectures, ResNet18, MiniVGG, and YOLOv8, for five-class blood cell image classification. To ensure a fair comparison, all models were trained under standardized conditions, including a consistent 90:10 training–validation split, controlled dataset size, and fixed training epochs. ResNet18 was trained to establish a baseline using residual learning. MiniVGG employed a compact VGG-inspired design with regularization to balance efficiency and accuracy, while YOLOv8 leveraged a lightweight, pretrained classification backbone with integrated data augmentation. Experimental results demonstrate a clear …
Ai-Driven Network Orchestration: Adaptive Routing For Federated Learning Over Software-Defined Hybrid Wans,
2026
University of Texas at Arlington
Ai-Driven Network Orchestration: Adaptive Routing For Federated Learning Over Software-Defined Hybrid Wans, Osama Abu Hamdan
Computer Science and Engineering Dissertations - Archive
Modern wide-area networks increasingly adopt hybrid architectures that combine high-capacity wired backbones with flexible wireless links to extend connectivity to remote and underserved locations. However, the bandwidth variability inherent in wireless segments creates routing challenges that traditional protocols, designed for static link capacities, cannot adequately address. Simultaneously, Federated Learning (FL) has emerged as a privacy-preserving distributed machine learning paradigm in which geographically dispersed clients collaboratively train shared models without exchanging raw data. When deployed over wide-area networks, FL training is severely bottlenecked by communication overhead, particularly in cross-silo settings where model payloads reach hundreds of megabytes and synchronous aggregation protocols …
Scaling Llm Inference: From Novel Attention Mechanisms To Efficient Kv Cache Management,
2026
University of Texas at Arlington
Scaling Llm Inference: From Novel Attention Mechanisms To Efficient Kv Cache Management, Weishu Deng
Computer Science and Engineering Dissertations
The rapid scaling of artificial intelligence workloads has shifted the dominant performance bottleneck of modern computing systems from compute to memory. Graph neural networks (GNNs) issue increasingly irregular memory accesses, while large language models (LLMs) issue increasingly large ones; in both cases, the relative scaling of memory bandwidth and capacity continues to lag behind the scaling of compute. Consequently, naively executing these workloads on commodity GPUs results in stalled streaming multiprocessors, exhausted high-bandwidth memory (HBM), and serving stacks that incur PCIe transfers on the critical path. This dissertation argues that the efficient scaling of attention-based AI workloads requires the joint …
Formalizing Asymmetric Control-Telemetry Separation In Distributed Industrial Control Systems,
2026
Georgia Southern University
Formalizing Asymmetric Control-Telemetry Separation In Distributed Industrial Control Systems, Andrew Manison
College of Graduate Studies: Theses & Dissertations
Distributed industrial control systems often place control and telemetry traffic on the same communication substrate even though the two workloads impose different requirements. Control paths need bounded request-response latency and predictable acknowledgement semantics, whereas telemetry paths benefit from scalable publish-subscribe fanout and tolerance for consumer-side delay. This thesis argues that, for the tested class of mixed workloads on shared commodity infrastructure, these communication roles should be separated architecturally rather than forced through a single protocol. To evaluate that claim, the thesis formalizes an asymmetric control- telemetry pattern and instantiates it in the Asymtra framework using gRPC for synchronous control and …
Virtualized And Distributed Neighborhood Data Centers,
2026
University of Texas at Arlington
Virtualized And Distributed Neighborhood Data Centers, Benjamin T. Niccum
Computer Science and Engineering Theses
This thesis evaluates whether PCIe-fabric-based resource pooling can support a decentralized neighborhood micro-data-center model under real implementation constraints. The work combines architecture design, prototype deployment, performance benchmarking, and security assessment. Results show strong prototype-scale feasibility with low-latency and high-throughput behavior, while also identifying deployment-blocking security gaps and operational maturity requirements. The thesis contributes an evidence-traceable path from concept validation to deployment-grade roadmap planning.
Beyond Permissions: A Privacy And Security Analysis Of Sensor And Network Activity On Xr Devices Using Xrmonitor,
2026
University of Texas at Arlington
Beyond Permissions: A Privacy And Security Analysis Of Sensor And Network Activity On Xr Devices Using Xrmonitor, Gayatri Sravya Siripurapu
Computer Science and Engineering Theses - Archive
Standalone virtual reality headsets integrate multiple sensors and cameras whose runtime behavior is not transparently documented, creating potential privacy and security risks that are difficult to audit using existing tools. The relationship between software feature activation and the underlying hardware engaged at runtime remains opaque, limiting the ability of users and researchers to assess what data is being collected and when.
This thesis presents XRMonitor, a unified framework for monitoring and analyzing sensor activation behavior and network traffic on Meta Quest devices. The framework is motivated by the lack of transparency in how standalone XR devices engage their hardware sensors …
Minimizing Performance Overheads For Crash-Consistency In Disaggregated Persistent Memory,
2026
University of Central Florida
Minimizing Performance Overheads For Crash-Consistency In Disaggregated Persistent Memory, Khan Shaikhul Hadi
Graduate Studies Theses and Dissertations 2026
Compute express link (CXL) enables persistent memory disaggregation with memory pooling and hardware managed multi-host memory sharing capability, resulting in better resource utilization, increased scalability. Persistency-aware applications need to manage crash consistency across the system which results in significant performance overhead. This dissertation systematically investigates performance overhead to achieve crash consistency in disaggregated persistent memory and proposes solutions to enable persistency-aware application scaling for distributed system. First, we study persistent parallel programming to scale computation capability beyond single processor and determine the underlying hardware limitation to adopt lock-free data structure. We propose hardware support to design durable atomic instruction (DAI) …
Online Community Dynamics: An Analysis Using Louvain During Major Sporting Events,
2026
SVKM's NMIMS Mukesh Patel School of Technology Management & Engineering, Mumbai
Online Community Dynamics: An Analysis Using Louvain During Major Sporting Events, Anushka Jaint, Yashodhan Karulkar, Kashish Jindal, Sri Sai Harshita Gadavarthi, Sanya Gulati
Journal of International Technology and Information Management
With the power of social media transforming the way people connect and interact with each other, the dynamics of community formation on platforms such as X during major events are of crucial importance. While social media is an increasingly key driver in determining interactions, little is known about the online influence forming and developing fan communities in high-stakes events. This study looks into the development of user communities for datasets drawn from Kaggle on two of the world’s largest sporting events: the FIFA World Cup 2022, or football, and the T20 World Cup 2022, or cricket, with the aim of …
Blockchain As A Digital Coordination Infrastructure For Project Management: A Systematic Review And Integrative Framework,
2026
Dakota State University
Blockchain As A Digital Coordination Infrastructure For Project Management: A Systematic Review And Integrative Framework, Cherie Bakker Noteboom, Sai Neelima Seru, Aravindh Sekar
Journal of International Technology and Information Management
Blockchain technology has gained increasing attention as a digital infrastructure capable of improving transparency, trust, and coordination in complex, multi-organizational project environments. However, existing research on blockchain-enabled project management remains fragmented and industry-focused, providing limited guidance for organizational adoption and integration. This study addresses this gap through a systematic literature review of 29 peer-reviewed studies, following PRISMA guidelines, to examine how blockchain capabilities are incorporated into project management practices across industries and maturity stages.
Grounded in Resource-Based View and Coordination Theory, the analysis employs a feature-to-process mapping approach to link six core blockchain capabilities—decentralization, transparency, immutability, smart contracts, traceability, and …
Advancing Ethical Innovation In Human–Ai Collaboration: Trust And Legitimacy In Technology-Mediated Teams,
2026
University of Texas at Tyler
Advancing Ethical Innovation In Human–Ai Collaboration: Trust And Legitimacy In Technology-Mediated Teams, Sanket Ramchandra Patole
Human Resource Development Theses and Dissertations
Human Resource Development (HRD) confronts a central paradox in the digital age. The technologies designed to broaden access to learning and collaboration often reproduce the same social hierarchies that HRD seeks to challenge. Artificial intelligence (AI), digital collaboration platforms, and algorithmic management are widespread features of organizational life. Yet these systems do not generate inclusive outcomes for all workers. Women of Color (WoC), situated at the intersection of racialized, gendered, and technological structures, experience digital transformation as both possibility and constraint. They encounter opaque decision systems, diminished authority in virtual teams, and digitally-mediated microaggressions, while also developing new capacities for …
Towards Application-Driven Optimal Memory And Storage Management,
2026
University of Texas at Arlington
Towards Application-Driven Optimal Memory And Storage Management, Venkata Naga Prajwal Challa
Computer Science and Engineering Dissertations
Modern computing systems increasingly run on diverse hardware platforms and support applications with widely different access patterns, performance goals, and data lifecycles. In this setting, traditional one-size-fits-all approaches to memory and storage management are often inefficient because they apply fixed policies regardless of application behavior, workload context, or hardware asymmetry. Such generic designs can lead to unnecessary data movement, wasted bandwidth, excessive rewriting, poor resource utilization, and degraded user-perceived performance. This dissertation is motivated by the view that optimal memory and storage management should be application-driven: instead of treating all data uniformly, systems should adapt their decisions to how applications …
The Crowdfunding Paradox In Crisis: Rising Funder Demand Vs. Declining Entrepreneur Supply,
2026
James Madison University
The Crowdfunding Paradox In Crisis: Rising Funder Demand Vs. Declining Entrepreneur Supply, Dan Liu, Guangzhi Shang, Cynthia Fan Yang
Journal of International Technology and Information Management
This study investigates how the crowdfunding marketplace responds to major crises, focusing on behavioral shifts among funders and entrepreneurs. Results show a dual impact on platform dynamics. On the demand side, funders become more engaged, with notable increases in the number of backers, average contributions, and total pledge amounts. This heightened activity suggests stronger altruistic motivations, as individuals view crowdfunding as a way to support others during difficult times. On the supply side, however, entrepreneurs act more cautiously, leading to a decline in new project launches. This drop likely reflects increased risk aversion and uncertainty as creators navigate volatile conditions. …
Too Warm To Win Big? Unpacking The Backer Dynamics Behind Female Crowdfunding Success Using A Warmth And Competence Perspective,
2026
James Madison University
Too Warm To Win Big? Unpacking The Backer Dynamics Behind Female Crowdfunding Success Using A Warmth And Competence Perspective, Dan Liu
Journal of International Technology and Information Management
While crowdfunding is often heralded as a democratized funding avenue that empowers women with higher success rates, this study reveals a more nuanced picture of gender dynamics. The Stereotype Content Model suggests that women are often perceived as warmer but less competent. Using a large dataset from Kickstarter, we find that female-led projects can attract more backers, likely due to warmth-driven appeal, but receive smaller average contributions, potentially due to concerns about risk linked to lower perceived competence. However, the total funding raised by female-led campaigns is comparable to that of male-led ones, showing no clear advantage or disadvantage. This …
Analyzing Network Traffic And Data Exfiltration Via Smb In Post-Vm Escape Scenarios,
2026
The University of Akron
Analyzing Network Traffic And Data Exfiltration Via Smb In Post-Vm Escape Scenarios, Noah M. Disanza
Williams Honors College, Honors Research Projects
Virtual machines (VMs) play a crucial role in modern IT infrastructure environments by providing isolation and enhanced security, among other things, for both personal and corporate systems. VMs are heavily rely upon to safely test malware, manage infrastructure, and reduce risk to host systems. This reliance is so substantial that the idea of reducing risk to the host system is believed to be erasing risk entirely. However, this mindset has shown to be challenged time and time again by the emergence of exploits known as virtual machine escapes. These exploits allow malicious actors to break out of the virtualized environment …
Ai-Based Music Mood Analysis With Historical And Real-Time Data,
2026
The University of Akron
Ai-Based Music Mood Analysis With Historical And Real-Time Data, Biswash Bhattarai
Williams Honors College, Honors Research Projects
The Music Mood Analyzer Dashboard identifies and visualizes the emotional tone of songs using audio features like tempo, energy, and valence. It classifies tracks into moods such as happy, sad, or calm and presents insights through an interactive dashboard. The project combines music analysis and data visualization to help users understand how sound relates to emotion.
Clear Skies,
2026
The University of Akron
Clear Skies, Avery C. Munn
Williams Honors College, Honors Research Projects
Air quality impacts public health, environmental sustainability, and quality of life. However, accurate and easily accessible short-term air quality forecasting is challenging to find. This project, Clear Skies, presents a machine learning–based system for forecasting next-day Air Quality Index (AQI) levels across regions in Ohio. By using historical pollutant data with variables such as temperature, humidity, wind speed, and atmospheric pressure, the system finds relationships that traditional statistical models often don’t show.
Machine learning models are evaluated alongside AI techniques to find the environmental factors that influence AQI predictions. This helps reduce the “black box” nature of many AI systems …
Secure Peer-To-Peer Messaging Using Distributed Servers,
2026
University of Akron
Secure Peer-To-Peer Messaging Using Distributed Servers, Jack Stoller
Williams Honors College, Honors Research Projects
Traditional messaging systems that rely on centralized infrastructure often introduce three security vulnerabilities: single points of failure susceptible to availability attacks, metadata leakage, and man-in-the-middle attacks.
This project designs, implements, and validates a distributed peer-to-peer messaging system that addresses each of these concerns through architectural design. A consistent hash ring is used with virtual nodes to distribute user data across a mesh of connected nodes, eliminating centralized dependency on any single server. Message contents travel directly between browser clients over a WebRTC data channel secured with end-to-end DTLS encryption, bypassing the server infrastructure. Inter-node communication is protected by mutual TLS …
Automated Pill Dispenser,
2026
The University of Akron
Automated Pill Dispenser, Ryan Oderkirk, Connor Beaven, Rachelle Labrie, Josue Panchana
Williams Honors College, Honors Research Projects
The project we propose is an automated system for dispensing dosages of medication throughout the day. It will be able to alert a user when their pills need to be taken and give them the correct dosages of up to four different medications. These dosages are configurable as well as the scheduled time they are to be taken. In addition, the pill dispenser will alert users when they are low on medications and need to refill the machine.
Nanomagnet Based Reservoir Computing And Quantum Control,
2026
Virginia Commonwealth University
Nanomagnet Based Reservoir Computing And Quantum Control, Fahim F. Chowdhury
Theses and Dissertations
Conventional CMOS scaling has driven remarkable advances in computing but faces increasing physical and energy constraints, motivating alternative computing paradigms that integrate memory and computation while improving energy efficiency. Nanoscale magnetic systems offer a promising platform for such approaches because their intrinsic nonlinear dynamics and localized magnetic fields can support both classical and quantum information processing. This thesis investigates nanomagnetic systems for physical reservoir computing and, with primary emphasis, for localized quantum control of spin qubits.
The first part explores dipole-coupled nanomagnet arrays as physical reservoirs. Micromagnetic simulations demonstrate nonlinear dynamical behavior with high short-term memory and parity-check capacity, enabling …
