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Using A Study Journal To Support Class Engagement And The Development Of Entrepreneurial Mindset Habits, Otilia Popescu, Dimitrie C. Popescu

Engineering Technology Faculty Publications

Engineering Technology programs were historically introduced to support non-traditional students and offer college pathways for students working and having already a developing career. This is even more true in the current academic environment, with a large percentage of students enrolled in engineering technology programs being either fully or part-time employed, active or retired military, and at different stages in their lives, usually with families to care for. Often, non-traditional students attend classes online, either synchronously or even more often asynchronously, due to their schedule constraints. Course instructors regularly face schedule or time management constraints from the students’ side, and they …

Wip: Arduino-Based Pbl To Foster Entrepreneurial Mindset, Nathan Q. Holland, Vukica M. Jovanovic

Engineering Technology Faculty Publications

This work-in-progress paper examines a semester-long project-based learning initiative begun in an introductory engineering course during the Fall 2025 semester. The project aims to enhance students' hands-on experience by integrating information literacy, the engineering design process (EDP), and an entrepreneurial mindset (EM) [1]. The objective is to boost student confidence in teamwork, technical problem-solving, and application of skills, preparing them for future courses in their discipline. Students in this introduction to engineering course received an Arduino Uno R3 Controller board kit and additional sensors. They were tasked to develop a device addressing engineering in the medicine challenge of their choosing. …

Modeling Healthcare Data With Logistic Quantile And Uniform-Based Mixture Polynomial Distributions, Mohan D. Pant, Aditya Chakraborty, Jovanna A. Tracz

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Continuous healthcare data often deviate from normality, which can substantially increase the risk of making invalid inferences, given that many inferential statistical procedures rely on normality assumption. To obviate this issue, we propose a new family of non-normal distributions based on a linear combination of the quantile functions of standard logistic and uniform (0, 1) distributions. This new family of non-normal distributions is studied within three different methods: L-moments, conventional moments, and percentiles. Its performance is compared among the three methods in the context of parameter estimation and data modeling. The results of Monte Carlo simulation and bootstrapping techniques indicate …

Adaptive Boundary-Aware Fact-Checker Placement For Misinformation Suppression In Social Networks, Mostafa Taghizade Firouzjaee, Ghazal Naderi, Ross Gore, Neda Moghim

School of Cybersecurity Faculty Publications

The spread of fake news on online social networks is driven by imitation-based user behavior and network topology, often leading to persistent misinformation clusters and echo chambers. In this study, we develop a spatial evolutionary game-theoretic framework in which agents update their latent opinions through payoff-biased imitation, while external fact-checkers act as non-imitative intervention nodes. Building on this formulation, we propose an adaptive, boundary-aware intervention mechanism that dynamically regulates both the density and spatial allocation of fact-checkers according to real-time system conditions. Competing information clusters are identified through local neighborhood composition, enabling boundary nodes, i.e., interfaces between fake-news and non-fake-news …

Element-Based Predictive Modeling Of Hydrothermal Liquefaction Bioproducts Derived From Corn Stover, Isamu Umeda, Meicen Liu, Yi Zheng, Jiefu Wang, Zhiwu Wang, Sandeep Kumar

Civil & Environmental Engineering Faculty Publications

The hydrothermal liquefaction (HTL) process offers an energetic advantage over pyrolysis because it does not require prior drying of the biomass feedstock. However, there are significant challenges in simultaneously estimating both the yields and characteristics of products from the HTL of biomass with theoretical support. This study developed a unique element-based kinetic model to predict the yields, higher heating values, and fuel characteristics of solid residue and heavy bio-oil, based on the temperature, residence time, solid loading, and elemental composition (C, H, N, and O) of corn stover. Furthermore, the model predicted the weights of dissolved carbon and nitrogen in …

Harnessing Activated Sludge For The Treatment Of Hydrothermal Liquefaction Wastewater: A Proof-Of-Concept Study, Cyrus Li, Jiefu Wang, Meicen Liu, Yi Zheng, Sandeep Kumar, Isamu Umeda, Chandan Mahata, John Norton

Civil & Environmental Engineering Faculty Publications

Although hydrothermal liquefaction (HTL) is the leading technology in converting wet biomass into bioenergy, the treatment of its toxic-laden aqueous phase wastewater presents a major challenge on its path toward commercial viability. This study presents the first-ever assessment of sewage sludge-fed HTL wastewater (SS-HTLWW) treatment and toxic compound removal using municipal activated sludge (AS) by optimizing its cultivation condition. It was found that AS with optimized pretreatment can remove up to 91.2% of the soluble chemical oxygen demand (sCOD) in SS-HTLWW, of which up to 82% can be attributed to biological mineralization and adsorption of sCOD by AS. Conventional bioprocess …

Nature-Based Solutions For Urban Resilience And Environmental Justice In Underserved Coastal Communities: A Case Study On Oakleaf Forest In Norfolk, Va, Farzaneh Soflaei, Mujde Erten-Unal, Carol L. Considine, Faeghe Borhani

Civil & Environmental Engineering Faculty Publications

Climate change and sea-level change (SLC) are intensifying flooding in U.S. coastal communities, with disproportionate impacts on Black and minority neighborhoods that face displacement, economic hardship, and heightened health risks. In Norfolk, Virginia, sea levels are projected to rise by at least 0.91 m (3 ft) by 2100, placing underserved neighborhoods such as Oakleaf Forest at particular risk. This study investigates the compounded impacts of flooding at both the building and urban scales, situating the work within the framework of the UN Sustainable Development Goals (UN SDGs). A mixed-method, community-based approach was employed, integrating literature review, field observations, and community …

Nonstationary Spatial Correlation Of Earthquake Ground Motions In California, Pengfei Wang, Busra Bocekli, Junhui Yang, Scott J. Brandenberg, Jonathan P. Stewart

Civil & Environmental Engineering Faculty Publications

Assessing seismic risk to spatially distributed infrastructure systems requires realistic representations of spatially correlated ground motions. Existing models for the spatial correlations of ground motions rely on strong second-order stationarity assumptions, under which the correlation structure is assumed to be invariant across space, potentially masking regional variations. Because repeatable site and path effects can vary spatially, the resulting correlation structure is likely to be nonstationary. We propose a nonstationary spatial correlation method that captures geographically varying correlation decay behavior. We compute site-to-site Pearson correlations of within-event residuals using earthquakes recorded at both sites in each site pair and model the …

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 …

Artificial Neural Network Based Protection For Dc Bus Using Solid State Dc Breaker, Eswaraiah Giddalur, Askani Jaya Laxmi

ASEAN Journal on Science and Technology for Development

Low voltage Direct Current (LVDC) microgrids have been extensively used as a hopeful technology with high access to distributed energy resources (DERs) and DC loads, due to the absence of multiple conversions. A high amplitude Fault current together with the vulnerability of electronic devices, poses a great challenge to the line protection in LVDC microgrids. Electromechanical switches are slow and take long tripping time to clear the short circuit fault. Power electronic circuit breakers are used to achieve fast fault interruption recent progress in areas like machine learning and natural language processing have affected nearly every assiduity and area of …

Extraction And Characterization Of Fresh And Dehydrated Cactus (Opuntia Ficus Indica) Polysaccharide For Hydrogel Preparation, Aye Thwe Thwesoe, May Myat Khine

ASEAN Journal on Science and Technology for Development

In this research, extraction of polysaccharide compounds from Cactus (Opuntia Ficus Indica) leaves in both fresh and dehydrated condition by solvent precipitation method using three types of water, acid (HCL) and NaOH. Before extraction, the physicochemical properties were examined to determine optimum yield (%) of extracted polysaccharide by optimization of Box-Behnken Design (BBD) of response surface methodology (RSM). The polysaccharide-based acrylamide hydrogel was prepared by free radical polymerization. The functional and structural characterization was done by FTIR, XRD and SEM for examination of extracted polysaccharide as raw polymer backbone in hydrogel preparation and prepared hydrogel as adsorbent for metal removal. …

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 …

Design Of An Economic Order Quantity–Based Dashboard For Vaccine Packaging Inventory Management, Hadi Susanto, Susmitha Canny, Alexandra Elizabeth Callistha, Shakira Dwi Purwandari, Naila Davina Aurelia

ASEAN Journal on Science and Technology for Development

Background: Timely availability of vaccine packaging is critical to pharmaceutical supply chain reliability, as packaging materials play a key role in maintaining cold chain integrity during distribution. Inadequate availability of packaging materials can disrupt vaccine delivery even when finished vaccines are ready for shipment. The case company faces frequent delivery delays, insufficient safety stock, and irregular replenishment of vaccine packaging materials, which have jeopardized the organization’s target of achieving a 90% on-time delivery rate.

Objective: To design and evaluate an Economic Order Quantity (EOQ)–based inventory dashboard for vaccine packaging that standardizes ordering decisions and strengthens stock visibility in pharmaceutical distribution …

Multiclass Skin Lesions Classification And Early Skin Cancer Detection Using An Attention-Enhanced Xception Architecture, Shamira Arshad Shaikh, Yogita Mistry

ASEAN Journal on Science and Technology for Development

Skin disorders are considered one of the major healthcare problems globally and need proper, prompt, effective and early diagnosis to enhance clinical practice. Traditional machine learning and deep learning approaches often exhibit limited generalization capability and reduced effectiveness in extracting discriminative features from complex multiclass dermatological datasets. For this purpose, an interpretable attention-enhanced Xception framework for automatic multiclass skin disease diagnosis based on dermoscopic images has been designed through the use of the International Skin Imaging Collaboration (ISIC) dataset. The dataset includes 2,357 dermoscopic images that belong to nine classes of skin lesions. The proposed framework integrates channel attention and …

Discrete Element Modeling Of Granular Soils: Critical State Behavior Applied To Impact Pile Driving, Esteban Patino Marin

Graduate Studies Theses and Dissertations 2026

This thesis investigates the use of the Discrete Element Method (DEM) to study two complementary aspects of granular soil mechanics: critical state behavior of granular materials and dynamic response of driven piles in sand, both of which are governed by the same particle-scale mechanisms of dilation, contraction, and fabric evolution.

The first examines the critical state behavior and fabric anisotropy of granular soils through DEM simulations of direct shear, direct simple shear, and true triaxial tests. Sphere-cluster particles representative of a uniform sand are used in two assemblages of approximately twenty-five thousand and one hundred twenty-five thousand spheres to evaluate …

Temperature And Speciation Measurements Of Aluminum-Laden Detonation Flows Via A Three-Color Wavelength Modulation Spectroscopic Sensor, Marc B. Etienne

Graduate Studies Theses and Dissertations 2026

Tunable diode lasers are widely used and are known to be great options for continuous wave lasing applications. Because of their stability and spectral selectivity, they have become an important diagnostic tool for modern combustion research. Previous combustion research, particularly those focused on solid and hybrid rocket systems, have shown that the interaction of aluminum with a reacting flow can greatly affect the dynamics and the thermochemical properties of the surrounding gas, therefore understanding the effects of aluminum-laden flows is critical for the advancement of these propulsion systems. However, due to the high degree of optical interference, high temperatures, and …

First-Principles Insights Into Electronic And Magnetic Structure At Hybrid Interfaces And Low-Dimensional Materials And Reaction On Surfaces, Bushra Ashraf

Graduate Studies Theses and Dissertations 2026

Low-dimensional materials and transition metal surfaces/interfaces provide complementary platforms for understanding how dimensionality, symmetry, spin–orbit coupling (SOC), and interfacial charge transfer/hybridization jointly control electronic structure, emergent magnetism, and surface reactivity. Using first-principles modeling with experimental comparisons, this work aims to establish interfacial structure–property relationships across low-dimensional systems.

Strained Pd adlayers on 2H-MoS₂(0001) provide a controlled platform to separate strain-driven exchange from interface-induced quenching in an itinerant d-electron metal. Although expansive strain promotes magnetism in free-standing Pd, strong Pd–MoS₂ hybridization and charge transfer suppress the monolayer moment and leave a narrow thickness window where magnetism re-emerges in …

Restoring Digital Trust: Decentralized Frameworks For Identity, Consent, And Media Provenance, Raghu N. Avula

Graduate Studies Theses and Dissertations 2026

Digital platforms are deeply embedded in modern society through centralized network architectures. As online interactions transition to the physical world handling sensitive data, user privacy and cryptographic security require enhancement beyond traditional limits. This dissertation presents a decentralized “Tri-Layer Trust Architecture” that leverages Verifiable Trust Registries, Cryptographic Binding, and Edge Verification to prioritize data sovereignty and local authentication. To demonstrate the architecture’s applicability across distinct operational environments, we implement three solutions: (1) Verifiable Presence for peer-to-peer ride-sharing via D-RideX, which encrypts biometric data on physical hardware (TEEs) and Soulbound Tokens (SBTs) to prevent impersonation without cloud database exposure; (2) Verifiable …

Understanding The Potential Biogeochemical Effects Of Alternative Restoration Materials: A Study Of Basalt And Other Materials, Cadie L. Barnes

Graduate Studies Theses and Dissertations 2026

Concern over the effects of microplastics on estuarine ecosystems and public health has prompted many restoration practitioners to switch from plastic materials to more “natural” substrates. These natural (BESE-biopolymer, cement-jute structures) and non-plastic (basalt fiber) materials should not contain harmful substances; however, their chemical composition is unknown. Natural materials may degrade faster in subtropical environments and release nutrients into surrounding waters, which is concerning for eutrophic restoration areas. Basalt fiber bags, made from melted basalt rock spun into fibers, have not been evaluated for biogeochemical impacts within estuaries. To address this knowledge gap, two field experiments and two laboratory experiments …

An Integrated Framework For Last-Mile Delivery Optimization Using Reinforcement Learning And Social Media-Based Traffic Prediction In Underdeveloped Megacities, Vasanth Bhat

Graduate Studies Theses and Dissertations 2026

Supply chain management has become increasingly critical as transportation costs rise and urban delivery systems place additional pressure on already congested networks. Last-mile delivery—the movement of goods from distribution centers to end users—represents the most expensive and operationally complex segment of the logistics process, particularly in underdeveloped megacities characterized by unpredictable traffic, limited infrastructure, and sparse real-time data. This dissertation proposes an integrated framework for optimizing last-mile delivery in such environments by combining social media–based traffic intelligence, machine learning, and deep reinforcement learning. The framework leverages unstructured, real-time data from social media platforms to enhance traffic prediction and incorporates these …

Investigation Of Exotic Phenomena In Topological Quantum Materials, Iftakhar Bin Elius

Graduate Studies Theses and Dissertations 2026

he First Quantum Revolution established quantum mechanics as the foundation of modern physics, enabling transformative technologies such as semiconductors, lasers, and transistors through prin-ciples of quantization, wave-particle duality, and uncertainty. The ongoing Second Quantum Rev-olution harnesses entanglement, superposition, and coherence to advance quantum computation, communication, simulation, and sensing. Central to this endeavor is the study of quantum mate-rials hosting novel electronic structures and emergent phases, including topological insulators and Dirac, Weyl, and nodal-line semimetals. In this thesis, using angle-resolved photoemission spec-troscopy (ARPES), transport measurements, and density functional theory (DFT) calculations, we investigate three classes of materials: (i) magnetic topological semimetals, …

Learning-Based Optimization For Collaborative Truck-Drone Routing And Scheduling, Ahmad A. Bany Abdelnabi

Graduate Studies Theses and Dissertations 2026

Modern delivery networks increasingly rely on innovative technologies such as drones working alongside trucks to meet rising demands for fast and efficient last–mile transportation. Hybrid truck–drone delivery offers strong potential, but its effectiveness depends on careful synchronization between trucks and drones. Although drones provide fast, direct travel, their limited endurance and the need to coordinate launch and recovery with trucks create tightly coupled routing and scheduling interactions. Poor dispatch decisions can cause truck waiting, reduce parallelism, and increase mission completion time. These challenges motivate decision frameworks that explicitly model synchronization and develop scalable methods for coordinated truck–drone operations. This dissertation …

Computational Modeling Of Bubble Dispersion In Alginate Hydrogel Foams For Radiologically Equivalent Biomedical Phantoms, Godson N. Brako

Graduate Studies Theses and Dissertations 2026

The foaming of hydrogels presents a promising strategy for tailoring mechanical and radiological properties to replicate biological soft tissues for biomedical phantoms. Achieving uniform and predictable void fraction distributions in alginate hydrogel foams remains a challenge due to the complex interplay between bubble dynamics, matrix rheology, and interfacial forces during the pre-gelation aeration stage. This thesis develops a Computational Fluid Dynamics framework using the transient Eulerian two-fluid approach to predict void fraction distribution in alginate hydrogel precursor solutions aerated by air injection through a bottom nozzle. The objective is to use the framework for design of the foaming system to …

Detonability Limits Of Liquid Fuel Cloud, Khaoula Chougag

Graduate Studies Theses and Dissertations 2026

Detonation-based propulsion systems are of significant interest owing to their high thermodynamic efficiency, rapid energy release, and favorable entropy production relative to deflagration-based systems. Liquid fuels offer practical advantages in storage and volumetric energy density, making them attractive candidates for next-generation detonation engines. This dissertation investigates the detonability characteristics of liquid hydrocarbon fuel clouds through three interconnected studies conducted in a turbulent shock-tube environment using high-speed imaging and pressure diagnostics. The first study maps the detonability limits of monodisperse n-dodecane clouds by systematically varying droplet diameter (5-50 μm) and O₂/N₂ oxidizer composition at equivalence ratios spanning ϕ = 0.8-2.0. Results …

Detection And Discrimination Of Targets In Infrared Imagery, Adam T. Cuellar

Graduate Studies Theses and Dissertations 2026

Automated infrared (IR) imagery analysis is essential for persistent surveillance, defense, and security, yet it remains difficult when sensors move and when unknown objects appear. This dissertation addresses two fundamental problems: (1) detecting small moving targets amid platform-motion induced parallax and (2) distinguishing between known stationary targets and out-of-distribution (OOD) objects.   For detecting moving targets while the platform itself is in motion, auxiliary Global Positioning System and Inertial Navigation System data are combined with image analysis. Direction Cosine Matrices from calibrated inertial measurements enable sub-pixel frame alignment unattainable with purely image-based registration. The stabilized sequence is processed by a Reed–Xiaoli …

High-Efficiency And Compact Virtual Reality Displays, Zhenyi Luo

Graduate Studies Theses and Dissertations 2026

Virtual reality (VR) and augmented reality (AR) technologies are revolutionizing the way humans interact with digital information. However, current near-eye display systems still face critical challenges regarding optical efficiency, image quality, and device weight. This dissertation focuses on addressing these limitations through innovative liquid-crystal (LC) optics and system-level design strategies to achieve high-efficiency and compact VR displays.

First, to solve the longstanding problem of severe chromatic aberrations in ultrathin LC optics, I proposed an achromatic diffractive LC device. By stacking three LC layers with specifically designed spectral responses and polarization selectivity, I successfully reduced the chromatic aberrations. This idea enables …

High Intensity Ablation By Laser Filaments At Standoff Distances, Owen Thome

Graduate Studies Theses and Dissertations 2026

The high-power densities delivered to a target material by a laser allow for melting and vaporization to occur, a process called laser ablation. At higher intensities, plasma formation occurs and more complex material removal mechanisms take place. As laser power increases, nonlinear effects occur during propagation. One such effect, Kerr self-focusing, leads to beam collapse and ionization, resulting in a channel of plasma and region of high intensity light referred to as a laser filament. Filaments carry intensities on the order of 10¹³ W/cm² to significant distances without the use of large-scale focusing optics. Laser filament ablation is …

Integrating Self-Organizing Maps And Explainable Artificial Intelligence To Unravel Surface Water-Groundwater Hydrochemical Evolution And Drinking-Water Suitability Controls In A Data-Limited Arid Basin, Hui Tong, Ruizhong Gao, Yinlong Wang, Xixi Wang, Limin Duan, Guoqiang Wang

Civil & Environmental Engineering Faculty Publications

Study region

The Dahei River Basin, located in the semi-arid northern region of China's Great Bend of the Yellow River.

Study focus

This study integrates hydrochemical characterization, stable hydrogen-oxygen isotopes, Self-Organizing Maps (SOM), the entropy-weighted water quality index (EWQI), and explainable ensemble learning (XGBoost-TreeSHAP) to investigate surface water-groundwater evolutionary patterns and identify key hydrochemical contributors to drinking-water suitability in the Dahei River Basin.

New hydrological insights for the region

Waters in the basin are predominantly weakly alkaline and are characterized by HCO₃^--Ca-Mg and HCO₃^--Na facies, indicating the combined effects of carbonate weathering and cation exchange, with …

A Comprehensive Survey Of Prompt Engineering Techniques In Large Language Models, Tonmoy Debnath, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Prosenjit Das, Antu Kumar Guha, Muhammad Rezaur Rahman, H. M. Dipu Kabir

Electrical & Computer Engineering Faculty Publications

Prompt engineering has arisen as a pivotal discipline in optimizing the performance of Large Language Models (LLMs) by structuring inputs to enhance coherence, accuracy, and task alignment. This paper comprehensively surveys various prompting techniques, systematically categorizing them according to their application domains and methodological foundations. Fundamental approaches like zero-shot and few-shot prompting are examined along with advanced strategies, including chain-of-thought reasoning, retrieval-augmented generation, and self-consistency mechanisms. A rigorous qualitative analysis is conducted to evaluate each technique's strengths, limitations, and optimal use cases, offering a structured framework for selecting the most effective prompting strategies. Theoretical insights and empirical findings are consolidated …