Digital Commons Network^™

Role Of Alkali And Alkaline-Earth Doped In Zeolite A-Derived From Industrial Waste Toward Direct Ethanol Dehydrogenation To Acetaldehyde, Darunee Sukchit, Malee Prajuabsuk, Chan Inntam, Saisamorn Lumlong, Bongkochawan Pakamwong, Auradee Punkvang, Duangkamol Gleeson, Pantita Trongjitraksa, Paramasivam Shanmugam, Supakorn Boonyuen, Niramol Juntarachat, Sasijuta Wattanarach, Parjaree Thavorniti, Bunjerd Jongsomjit, Pornpan Pungpo

Journal of Metals, Materials and Minerals

In this study, a sustainable catalytic route for converting ethanol into value-added acetaldehyde was developed using alkali- and alkaline earth-modified zeolite A synthesized from sugarcane bagasse ash (SCBA). Zeolite A was first prepared via alkaline fusion followed by hydrothermal crystallization and subsequently doped with 1 wt% K+ or Ca2+ using incipient wetness impregnation. Comprehensive physicochemical characterization (X-ray fluorescence (XRF), X-ray diffraction (XRD), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), Fourier transform infrared spectroscopy (FTIR), nitrogen physisorption (N2 physisorption), ammonia temperature-programmed desorption (NH3-TPD), and carbon dioxide temperature-programmed desorption (CO2-TPD)) confirmed the formation of a highly crystalline LTA framework with tunable …

Magnetocaloric Effect Of Gdtbdyerpr Rare-Earth High-Entropy Alloy, Yu Liu, Lei Gao, Jun Peng, Haitao Guo

Journal of Metals, Materials and Minerals

In this study, a GdTbDyErPr rare-earth high-entropy alloy (RE HEA) was successfully synthesized and its magnetic properties and magnetocaloric effect (MCE) were systematically investigated. The results indicate that the as-cast GdTbDyErPr RE HEA exhibits a single-phase hexagonal close-packed (HCP) structure with lattice parameters of a = 3.609 Å and c = 5.734 Å. Based on large parameter Ω, high mixing entropy (ΔSmix), and small parameters δ and εi, it can be inferred that the GdTbDyErPr alloy forms a disordered solid solution. The GdTbDyErPr RE HEA undergoes a first-order magnetic transition near about 143 K. The parameters |∆ |, RC, and …

Investigating The Effects Of Lamno. On The Morphology, Structural And Optical Properties Of Epoxy-Based Plastic Scintillators, Yeni Febrianti, Airine Hijrah Handayani, Marzuki Naibaho, Phahul Zhemas Zul Nehan, Zulkarnain -, Arbi Dimyati, Budhy Kurniawan

Journal of Metals, Materials and Minerals

Plastic scintillators are widely used in radiation detection due to their low cost, fast response, and ease of fabrication, although their performace is often limited by low density, low atomic number, make them less efficient for applications requiring high-energy radiation. In this study, LaMnO3 was synthesized using the hydrothermal method and employed as a dopant to enhance the optical and scintillation properties of epoxy-based plastic scintillators. Structural, morphological, and optical characterizations of LaMnO3 were carried out using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscope (SEM), energy-dispersive spectroscopy (EDS), UV-Vis and  photoluminescence (PL) spectroscopy. The results confirm that …

C.A.S. Full Assessment Report: State Of Florida Government Portal, Delante Clark

Graduate Scholarship and Creative Works

The purpose of this assessment is to evaluate the cognitive overhead, transparency, and attentional integrity of

official State of Florida digital interfaces using the Cognitive Attentional Standards (C.A.S.) platform.

While the Florida Digital Bill of Rights (FDBR) establishes strict regulatory guardrails for consumer data

transparency, tracking opt-outs, and attentional safeguards, the State of Florida explicitly exempts its own

government agencies, public universities, and non-profit entities from complying with these rules.

This assessment serves to investigate the tension between legislative intent and government execution. By

analyzing public sector websites through the C.A.S. platform, this project will establish a “state-enforced vs.

state-executed” …

Towards Optimal And Resilient Ac/Dc Microgrids: Control Design, Analysis, And Implementation, Jun Zhang

Electronic Theses and Dissertations

Microgrids serve as a small-scale power grid for utilizing renewable energy to enhance energy reliability, sustainability, and resilience. As an autonomous system, an islanded microgrid can disconnect from the utility grid and operate independently by maintaining system voltage and frequency. However, this new feature introduces coordination problems among distributed generators (DGs), such as 1) how to make sure the voltage profile and current sharing in DC microgrid with different types of converters; 2) how to reduce the impact of cyberattack when the system coordination is performed based on communication, and 3) how to calculate the steady state under a droop …

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 …

Brrbox, Shawn J. Myers, Lane Cline, Michael Davis, Christian Secrest

Williams Honors College, Honors Research Projects

This report details the project known as “The BRRBOX”, a reusable, insulated thermoelectric cooler developed to keep internal temperatures at refrigeration levels or cooler for at least 48 hours. The cooler will track its internal temperature during this period and be able to give the data at the end of its delivery cycle to keep up with food and pharmaceutical standards during delivery. The BRRBOX uses Peltier-based cooling alongside vacuum insulation panels and fans to achieve efficient thermal control. An onboard microcontroller will monitor temperature, record the data, and adjust the cooling output to minimize power consumption. The box will …

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.

Adjustable Car-Camping Bed Frame, Zachary Lamonica, Mitchell Mcgrath

Williams Honors College, Honors Research Projects

This project explores an innovative camping solution designed to enhance mobility, comfort, and accessibility for outdoor enthusiasts. The first is the Adjustable Car-Camping Bed Frame, engineered to be lightweight, collapsible, and adjustable to various vehicle interiors. It prioritizes ease of setup, compact storage, reliability, and affordability, enabling convenient travel without sacrificing comfort. The design aims to simplify camping while maintaining durability. As an aerospace systems engineering student, I will apply systems engineering to the Bed Frame, using aerospace software and principles. The scope includes research, design, prototyping, and testing, with a focus on real-world usability and environmental adaptability. Additionally, my …

Automatic Pet Feeder Network, Daniel J. Herttna, David A. Bechtel, Alexander Deskovich

Williams Honors College, Honors Research Projects

This project will describe the design process and research behind the Automatic Pet Feeder Network, otherwise known as The Petwork. The system consists of a tank to hold the food, a latching system to drop the food at the desired time, a weight sensor to verify that the proper amount of food has been dispensed, a power supply unit that steps down 120V AC standard wall outlet power, & a microcontroller that will interpret the user's input from a mobile phone application. The networking portion is covered by having a primary and a secondary feeder. The mobile application will communicate …

How Do Different Flight Training Programs Impact Pilot Proficiency?, Abigail Henson

2026 Research Poster Competition

The Federal Aviation Administration (FAA), founded in 1958, ensures safe and efficient use of national airspace by regulating aircraft and pilot certification, setting standards for airports, and managing the National Airspace System. One such regulation is in the certification process for aspiring student pilots. Students who want to obtain their private pilots license can do so by picking either a Part 61 or Part 141 flight school. While both lead to the same certification, these two options differ significantly in terms of structure; Part 61 programs offer flexibility with their individualized approach and fewer requirements while Part 141 schools follow …

Uav-Based Sensor Integration For In-Situ Lake Water Quality Monitoring, Alec Campbell

2026 Research Poster Competition

Current water quality assessment methods rely heavily on manual sampling and laboratory analysis, which are time-consuming and difficult to perform in remote or hazardous environments. In surface water monitoring, spatial and temporal resolution is often constrained by labor, access, and logistical limitations of manual sampling programs. This research aims to develop a drone-based system for real-time, in situ lake water quality monitoring. To address these challenges, the project focuses on integrating multiple water quality sensors, including oxidation-reduction potential (ORP), pH, electrical conductivity (EC), turbidity, and a multispectral spectrometer, into a compact, UAV-compatible design capable of collecting spatially referenced data. Methods: …

Flair- Flow-Level Anomaly Intrustion Recognition, Joseph Dumond

2026 Research Poster Competition

Industrial control systems (ICS) and industrial Internet of Things (IIoT) networks support critical infrastructure such as power generation, water treatment, and manufacturing. As these systems become more connected, they are increasingly exposed to cyber threats. However, many existing intrusion detection approaches rely on detailed packet inspection or supervised machine learning techniques that require labeled attack data and extensive tuning, making them difficult to deploy in real industrial environments.ICS networks typically generate highly regular and predictable communication patterns due to periodic control logic and deterministic device behavior. Because of this structure, abnormal or malicious activity often appears as a disruption to …

P4 Driven Data Plane Analytics For Industrial Control Network Security, Haden Fowler

2026 Research Poster Competition

Industrial control systems manage critical infrastructure such as power grids, water treatment plants, and manufacturing facilities. These systems rely on specialized network protocols to send measurements and commands between sensors, controllers, and operator workstations. Protecting these networks from cyberattacks is essential because a successful intrusion could disrupt services that millions of people depend on daily. Most current security monitoring approaches analyze copies of network traffic after it has already passed through the system. This delay means that malicious commands may reach their targets before any alarm is raised. More importantly, when alerts do occur, operators often lack the evidence needed …

Development Of A Scalable 32x32 Capacitive Sensing Array Using Fpga Controlled Multi-Bus I2c Communication, Jonathan Digby

2026 Research Poster Competition

High-resolution capacitive sensor arrays are widely used in applications such as robotics, wearable devices, and biomedical devices where accurate detection of touch, proximity, and motion is crucial. As these systems are scaled up to achieve higher resolutions, challenges pertaining to communication reliability, data synchronization, and system latency become more important. Capacitive sensor arrays detect changes in capacitance caused by disturbances in nearby electric fields. While these arrays are effective at small scales, large arrays often suffer from signal degradation and latency when all sensors rely on a single controller and communication bus. This research addresses these challenges by developing a …

Make It Maritime: A Simulation-Based Engineering Design Challenge Using Multimodal Technologies, Jessica M. Johnson, Jennifer Renne, Jason Dudley

Virginia Digital Maritime Center (VDMC) Faculty Publications

This paper presents The Incredible Bulk, a multimodal, simulation-based engineering challenge that introduces Grades 4–12 to maritime careers and digital transformation. Students assume the roles of different maritime careers to assemble aircraft carrier bulkhead systems using: VR for spatial orientation and task preview; a 3D model as visual work instruction; paper blueprints for part identification and dimensioning; 3D-printed components for hands-on assembly; and an AR app for quality assurance/inspection. Grounded in constructionism and cognitive apprenticeship, the plan–build–inspect loop externalizes thinking and situates coached, authentic practice that advances engineering design, systems thinking, and technological literacy.

Multi-Level Energy Optimization For Connected And Automated Vehicles: From Cooperative Multi-Vehicle Control To Individual Powertrain Management, Pruthwiraj Santhosh

Dissertations, Master's Theses and Master's Reports

The transportation sector currently accounts for nearly 30% of global energy consumption, necessitating urgent advancements in vehicle efficiency to meet Net Zero targets. Leveraging connectivity and automation, this dissertation proposes and validates methodologies to reduce the energy consumption of light-duty vehicles at both fleet and individual levels.

First, a validation framework is developed to bridge the “simulation-to-real world” gap in Cooperative Automated Vehicle (CAV) research. Moving beyond virtual simulations, the study establishes a methodology for physically validating centralized control architectures via a custom Cellular V2X network. By synchronizing vehicle-powertrain models with physical test vehicles, the framework successfully orchestrates complex arterial …

Evaluating The Role Of Power Electronics In Enhancing Renewable Energy And Smart Grid Performance: A Review, Muhammad Irfan Habib

ASEAN Journal on Science and Technology for Development

The review article demonstrates the importance of power electronics in propelling the increase of renewables and increasing the efficiency of contemporary electrical grids. In particular, it highlights the need for bidirectional converters for effective energy management in vehicle-to-grid (V2G) systems with two-way power transfer. The paper examines the series of complications offered by the significantly large integration of power electronic converter-interfaced renewables, such as those related to system steadiness, power quality, and resignation bottlenecks. Also, it recognizes a mix of new technologies, such as wide bandgap (WBG) semiconductors like silicon carbide (SiC) and gallium nitride (GaN), that deliver superior performance …

Unlocking Green Potential In Indonesian Small Medium Enterprises: Challenges And Opportunities For Sustainable Vermicelli Production, Togar W. S. Panjaitan, Karina Agustin, Prayonne Adi, Jani Rahardjo, I Nyoman Sutapa

ASEAN Journal on Science and Technology for Development

Due to limited initiatives and support, the transition to green manufacturing among small and medium enterprises (SMEs) in developing countries remains challenging. Through a critical literature review and case study of the Indonesian vermicelli industry, this study highlights the importance of collaboration and strong policies to address this. Other findings also reveal that the energy intensity and emissions in the sector exceed best practice benchmarks, with the cooking and drying stages contributing significantly to emissions due to high energy consumption. Lack of government regulations, company awareness, and understanding of applicable practices and technologies creates challenges in green manufacturing. The study …

Hybrid Model For Phishing Website Detection Using Transfer Learning, Atul Dubal, Mansi Subhedar, Santosh Dhamala, Manasi Patil

ASEAN Journal on Science and Technology for Development

The rapid digitization of human activities has intensified reliance on internet-based platforms, creating fertile ground for cybercriminal exploits such as phishing. Despite advancements in detection mechanisms, phishing attacks continue to evolve, leveraging sophisticated visual mimicry to deceive users. This paper proposes a robust vision-based phishing detection system using ensemble deep learning to analyse webpage screenshots. The framework integrates transfer learning with pre-trained VGG16 and DenseNet121 models, extracting complementary low-level texture features (edges, gradients) and high-level hierarchical patterns (logos, layouts). These features are fused through a custom classifier with dropout regularization to mitigate overfitting. A balanced dataset of 3,000 webpage screenshots …

Beyond The Binary: Navigating Ai’S Role In Palliative Ethics-A Review, Reebu Sara Varghese, Tijo Cherian

ASEAN Journal on Science and Technology for Development

Palliative care is being influenced by artificial intelligence, especially when it comes to data-related aspects. In this context, care can be enhanced in terms of the quality of its results and the level of its efficiency, particularly with the help of technological tools such as artificial intelligence, which is capable of managing different types of information in the field of health care. Such characteristics have the potential to improve the quality of patient care while at the same time reducing the workload of healthcare professionals in palliative care. However, there are considerable ethical issues that need to be addressed with …

Ai-Assisted Hybrid Ga–Pso Channel Allocation Under 3gpp Tr 38.901 Uma For Efficient 5g Radio Resource Management, Sharada Narsingrao Ohatkar

ASEAN Journal on Science and Technology for Development

The increased traffic and heterogeneity in the 5G/B5G network require efficient radio resource management (RRM). However, the existing methods, such as GA and PSO, have poor convergence speed and require proper initial conditions. Additionally, learning-based methods have high computational complexity. Hence, in this paper, a novel AI-assisted Hybrid Channel Allocation (AI–HCA) framework is proposed by using a support vector regression (SVR)-based predictive initialization method and GA-PSO optimization. Simulation results using the 3GPP UMa channel model show that the proposed method has a 28% reduction in call blocking probability (CBP), a 15-25% enhancement in spectral efficiency (SE), and a 18-25% enhancement …

A Rapid, Accessible Active Learning Framework For Stem At Wvu Tech, Somenath Chakraborty, Zahmeeth Sayed Sakkaff

2026 Scholarly Teaching Conference: Poster Session Papers

Many undergraduates find it difficult to move from listening to doing—especially in STEM courses that require sustained practice, timely feedback, and confidence. This poster describes a rapid, low-cost active-learning routine that can be added to existing lectures at WVU Tech with minimal redesign. Instructors insert brief engagement micro-cycles every 10–15 minutes: a concept question or mini-problem, a one-minute individual attempt, a short pair discussion, and a concise explanation that targets common misconceptions.

Towards Increasing The Retention Of Freshman Engineering Students: Implementing A New Course, Ee 101 Introduction To Electrical And Computer Engineering, Omer Lateef, Mingyu Lu, Waseem Alaqqad, Charan Litchfield, Kenan Hatipoglu

2026 Scholarly Teaching Conference: Poster Session Papers

To assist with improving student retention in the undergraduate electrical and computer engineering program, a course was developed and implemented at the freshman level in the Spring of 2021.  This course was named EE 101: Introduction to Electrical and Computer Engineering and served to give freshman students an opportunity to meet the professors of the ECE department and experience live sessions dedicated to presenting “upcoming” topics and research endeavors of their expertise.  Students typically will not be attending the electrical or computer engineering subjects until their sophomore year and this course, set in second semester for a freshman, attempts to …

Rubric Enhanced Assessment Of Coursework And Teaching (React): Using Portfolios And Rubrics In An Engineering Classroom To Refocus From Grades To Learning, Nathan Lee Galinsky

2026 Scholarly Teaching Conference: Poster Session Papers

The goal of using rubrics in an engineering classroom is to make grading clearer for students and to enhance the learning efforts. Point based grading of work leaves students looking for the correct numerical solution or choice without thinking about their assumptions, process, or approximations. A rubric dissects grading to include the entire solution procedure emphasizing key steps in a solution procedure. Students also don’t have to wonder where partial credit will be focused or what emphasis a solution will be graded on when using rubrics. By combining the rubric assessment techniques with portfolios, students will be empowered to feel …

Robotizing Complex Welding Processes Through Imitation Learning And Generative Models From Human Demonstration, Yue Cao

Theses and Dissertations--Electrical and Computer Engineering

Arc welding processes demand real-time adaptive control that current robotic systems cannot achieve autonomously. This dissertation develops a systematic framework to robotize complex welding by learning from human demonstration, integrating generative modeling, physics-informed reconstruction, and model-based imitation learning. First, human--robot collaboration systems are established for both Gas Tungsten Arc Welding (GTAW) and Double-Electrode Gas Metal Arc Welding, combining robotic teleoperation with virtual reality interfaces to capture high-quality operator demonstrations. Second, a physics-informed neural network framework reconstructs complete molten pool flow fields from high-speed imaging, enriching process understanding beyond direct sensor observation. Third, generative models, including a hybrid latent variational autoencoder …

Design Of Energy-Efficient, Scalable, And Flexible Tensor Processing Architectures With Electro-Photonic Integrated Circuits, Oluwaseun Alo

Theses and Dissertations--Electrical and Computer Engineering

In recent years, artificial intelligence has achieved remarkable success across domains such as computer vision, natural language processing, and scientific computing. This progress has been driven largely by advances in deep learning, particularly deep neural networks (DNNs), including convolutional neural networks (CNNs) and transformer-based models. While these models deliver unprecedented accuracy, often surpassing human performance, their computational complexity continues to grow rapidly due to multibillion- and trillion-parameter designs. As model sizes and deployment scales expand, the demand for energy-efficient and high-throughput hardware accelerators has intensified. Conventional electronic platforms based on CPUs, GPUs, ASICs, and FPGAs are increasingly constrained by the …

Learning-Enabled Methods For Optimal, Constrained, And Fault-Tolerant Robot Motion Planning, Charles L. Clark

Theses and Dissertations--Electrical and Computer Engineering

Safe and efficient motion planning is a core requirement for robots operating in complex real-world environments, yet traditional model-based approaches struggle to simultaneously achieve computational efficiency, solution optimality, and the ability to handle complex constraints and potential hardware failures. This dissertation investigates how neural networks, as general purpose function approximators, can be leveraged in both traditional and novel ways to overcome these limitations and advance beyond what purely model-based methods can offer. Three distinct contributions are presented. First, a new motion planner is developed that uses ReLU neural networks to decompose the configuration space into linear cost regions, enabling existing …

Advancing Edge Intelligence: Strategies For Improving Machine Learning On Embedded Devices, Prakash Dhungana

Theses and Dissertations--Electrical and Computer Engineering

Artificial intelligence (AI) has demonstrated tremendous success in handling complex tasks across multiple domains, a leap largely attributed to complex deep neural network (DNN) architectures. However, the increasing demand for real-time processing, low latency, limited connectivity, and enhanced privacy necessitates edge intelligence, where computation is performed directly on resource-constrained embedded devices rather than relying on cloud infrastructures. While optimized TinyML techniques such as pruning, quantization, and neural architecture search (NAS) have made edge deployment feasible by significantly reducing computation and memory demands, achievable performance remains severely limited by hardware constraints. Furthermore, models deployed in highly dynamic real-world environments suffer from …

Lecture Notes On Cloud Computing (Ver. Winter 2026), Jun Li

Open Educational Resources

This collection of lecture notes provides a comprehensive technical foundation for modern cloud computing, spanning from physical infrastructure to high-level application patterns. The text explores how warehouse-scale computers and virtualization transformed traditional data centers into flexible, on-demand resource pools characterized by elasticity and a pay-as-you-go economic model. Detailed chapters examine core architectural components, including Kubernetes orchestration, serverless computing (FaaS), and distributed key-value stores like Dynamo. The sources also emphasize the critical nature of fault tolerance, utilizing techniques like erasure coding and replication to manage the statistical inevitability of hardware failure. Security and management are addressed through frameworks like the Shared …