Digital Commons Network^™

Development Of A Deep Neural Network Model To Predict Pm2.5 Concentrations Based On Key Factors Affecting Air Pollution In Bangkok, Natsuda Klinklan, Tanawut Poothong, Nuttiwut Areeratphitak, Viganda Varabuntoonvit

Applied Environmental Research

PM2.5 is a significant air pollution concern in Thailand, particularly in urban areas such as Bangkok, where the 24-hour average concentration frequently exceeds national ambient air quality standards during severe seasonal episodes. Road transportation is the primary source of PM2.5 in Bangkok, accounting for 73% of total emissions, according to the Pollution Control Department. In this study, a predictive modeling framework is developed to investigate the relationship between vehicle count and the mass concentration of PM2.5 from vehicular exhaust emissions. Convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are employed for vehicle detection and counting, whereas a long short-term …

Weekly Spatiotemporal Dynamics Of Forest Fire Hotspots In Tak Province, Thailand : A Gis-Based Directional Analysis, Suphatphong Ruthamnong

Applied Environmental Research

Forest fires are recurrent dry-season hazards in northern and western Thailand, yet their short-term spatial dynamics remain insufficiently understood. In this study, weekly spatiotemporal dynamics of forest fire hotspots in Tak Province, Thailand, were examined using Visible Infrared Imaging Radiometer Suite (VIIRS) active-fire data and GIS-based directional analysis. Hotspots from five fire seasons (2021–2025) were grouped into 24 weekly intervals beginning on 1 December. The analysis integrated weekly hotspot counts, forest-type compositions, mean-center trajectories, standard deviational ellipses, temporal changes in topographic characteristics, and fishnet-based hotspot persistence mapping. The results revealed that fire activity was highly concentrated during the middle of …

Initial Screening Of Halophilic Plastic-Degrading Bacteria From Mangrove Water And Sediment In Pekalongan, Indonesia, Novia Safinatunnajah, Muhammad Zainuri, Aris Ismanto, Tony Hadibarata, Kunarso -, Sugeng Widada, Hermin Pancasakti Kusumaningrum, Candra Wahyuningsih

Applied Environmental Research

Microplastic pollution in tropical mangrove ecosystems represents an increasing environmental concern, particularly in coastal regions such as Pekalongan, Indonesia, where industrial and residential activities contribute substantially to plastic waste. This study aimed to isolate and preliminarily screen halophilic bacteria from mangrove sediments and seawater collected from a plastic-impacted coastal area. Using mineral salt medium (MSM) supplemented with polyethylene glycol (PEG), six bacterial strains were obtained and evaluated for their potential to interact with polyethylene (PE) and polypropylene (PP) on the basis of gravimetric weight loss measurements. Among the isolates, Halomonas Cupida A1, Marinobacter nauticus A6.3, and Marinobacter nauticus SD5.2 exhibited …

Effects Of The Psb-To-Ow Ratio And Light Intensity On Biogas Composition During Phototrophic-Assisted Anaerobic Fermentation Of Organic Waste, Kridsana Jirasansawat, Sirilak Prasertkulsak, Nitiwist Teangthai

Applied Environmental Research

The integration of phototrophic processes into anaerobic fermentation offers a promising strategy for improving biogas quality; however, the combined effects of the photosynthetic bacteria-to-organic waste (PSB-to-OW) ratio and light intensity remain unclear. In this study, the photosynthetic bacteria (PSB)-assisted anaerobic fermentation of municipal organic waste under varying PSB-to-OW ratios and light intensities was evaluated. An optimal PSB-to-OW ratio of 1:2 resulted in significantly higher CH4 concentrations and lower CO2 and H2S concentrations than the other tested ratios did (p < 0.05). At this ratio, moderate illumination (2000 lx) resulted in the highest CH4 concentration (68.2 ± 0.3%), compared with 1000 lx (61.5 ± 0.4%) and 4000 lx (63.1 ± 0.5%). Under illumination, the CO2 and H2S concentrations were lower than those under dark conditions, indicating a more favorable biogas composition. Kinetic analysis indicated that CO2 and H2S exhibited apparent first-order behavior under illumination, with the highest rates occurring at 2000 lx (kH2S = 0.093 day-1; kCO2 = 0.059 day-1), suggesting light-dependent transformation processes. Metagenomic analysis revealed a microbial community dominated by sulfide-oxidizing (Chlorobium sp.), photoheterotrophic (Rhodopseudomonas sp.), and syntrophic bacteria, supporting coupled carbon conversion and sulfur transformation. Overall, optimization of the …

Classifying Dual Mechanisms Cognitive Control Modes From Eeg Using Machine Learning, Jian Bin Wu

Open Access Master's Theses

Confidential material has been removed.

Design Of Team Performance Evaluation Scenario Under Stress And Failures, Sam Tola

Open Access Master's Theses

THE CONTENT OF THIS DOCUMENT HAS BEEN REMOVED BECAUSE IT CONTAINS CONTROLLED UNCLASSIFIED INFORMATION.

Vortex-Vortex Interaction Cavitation Inception Using Statistical And Multi-Phase Models, Nicholas Berthiaume

Open Access Master's Theses

This document is not being released in full, as it contains Controlled Unclassified Information (CUI) subject to safeguarding and dissemination controls under the policies of the National Institute for Undersea Vehicle Technology (NIUVT). Only those portions authorized for release are included herein.

Investigation Of Automated 3d Scanning Strategies For Large-Scale Polishing Applications, Casey Egan

Open Access Master's Theses

In automated scanning for industrial refinishing applications, large workpieces often exceed the reach of a single robot base position, and may require the environment to be scanned from multiple locations and stitched to a common reference frame. This thesis compares two robotic scanning workflows for such an object: a full scan that reconstructs the object from a single robot base position, and a segmented scan occurring across multiple simulated robot base positions that are stitched together through fiducial-based localization. The results from both workflows are compared for measurement accuracy of the object's bounding box against known dimensions, position of the …

Metal–Organic Frameworks : Opportunities And Challenges In Nutrient Recovery, Suchana Amnuaychaichana, Chi-Wang Li, Pongsak (Lek) Noophan, Sumeth Wongkiew

Applied Environmental Research

Nutrient recovery from waste streams is a critical strategy for promoting sustainable agriculture and mitigating environmental degradation. Essential nutrients commonly present in organic waste and wastewater, such as nitrogen and phosphorus, can be reclaimed and reintegrated into agricultural systems. Metal‒organic frameworks (MOFs), which are composed of metal clusters coordinated with organic ligands, have emerged as promising materials for adsorption and have the potential for nutrient recovery and pollutant removal because of their high porosity, large surface area, and tunable physicochemical properties. These attributes enable MOFs to serve in diverse applications, including heavy metal adsorption, organic pollutant degradation, and nutrient transformations. …

Recycling Waste Polyethylene Terephthalate For Asphalt Modification: A Comprehensive Review On Material Properties, Processing Techniques, And Engineering Applications, Ruizhe Huang, Feng Ma, Ke Shi, Zhen Fu, Jenny Liu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Polyethylene terephthalate (PET) is a thermoplastic polyester widely used in beverage bottles and packaging materials, accounting for approximately 60% of global plastic production. Due to its non-biodegradable nature, the accumulation of waste PET has posed a serious environmental challenge worldwide. In recent years, the recycling of PET for use in road engineering has been considered an effective approach to promote resource circulation and reduce plastic pollution. This paper first reviews the main recycling methods of PET, including mechanical shredding and chemical depolymerization, and analyzes its molecular structure, thermal properties, and reprocessing adaptability. Two typical engineering application paths are then evaluated: …

Evaluating The Use Of Machine Learning For Road Maintenance Cost Estimation, Shahla Shirinzad, David Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Accurate estimation of highway maintenance costs is essential for efficient resource allocation and long-term infrastructure sustainability. This study evaluates the effectiveness of advanced machine learning models, including ResNet, Transformer, and other neural network architectures, for forecasting maintenance costs using historical data from the Highway Maintenance Improvement Program (HMIP) provided by the North Carolina Department of Transportation (NC DOT). A comprehensive comparative analysis is conducted across multiple models using standard performance metrics, including R², MAE, RMSE, and MSE. The results demonstrate that advanced architectures, particularly ResNet and Transformer, consistently outperform traditional statistical approaches and baseline machine learning models, achieving …

Wideband Acoustic Immittance: Suitable Quantities For Assessing Middle-Ear Status, Kren Monrad Nørgaard, Jingxin Jessica Feng, Susan E. Voss

Engineering: Faculty Publications

This paper investigates the physical significance of ear-canal wave quantities—such as absorbance—that are commonly measured in wideband-acoustic-immittance tests and evaluates whether these quantities uniquely characterize middle-ear function. This is explored using simulations of lumped-element and transmission-line ear canals, along with measurements in three-dimensional-printed uniform and anatomical ear canals of varying geometry, terminated by the same middle-ear simulator. The results demonstrate the following points: (1) Wave quantities computed using estimated or geometrical cross-sectional areas do not uniquely characterize the middle ear because they describe the wave interaction between ear canal and middle ear and are therefore confounded by variations in ear-canal …

Security-Oriented Voice Authentication Using Machine Learning, Ifeoluwa Stella Elegbe

College of Graduate Studies: Theses & Dissertations

This study develops and evaluates a machine learning and deep learning-based voice authentication system for secure identity verification. As traditional authentication methods such as passwords, PINs, and security tokens continue to face challenges, including identity theft, forgetting, and unauthorized access, voice biometrics offers a more secure, convenient, and user-friendly alternative, especially for remote, hands-free, and accessibility-focused applications. The study adopts a closed-set speaker identification framework, where the system determines the most likely speaker from a predefined group of enrolled users. A structured methodology is implemented, beginning with audio preprocessing and feature extraction. Key acoustic features, including Mel-Frequency Cepstral Coefficients (MFCCs), …

Data-Driven Prediction Of Compressive Strength In Pofa-Modified Concrete: A Comparative Study Of Lr, Nlr, And Ann Models, Shuaaib A. Mohammed, Hawdin Ismael Ibrahim, Diar Fatah Abdulrahman Askar, Hersh F Mahmood, Mehdi Khodaei, Soran Abdrahman Ahmad

Mansoura Engineering Journal

Production of concrete results in high CO₂ emissions, high energy demand, and consumption of various raw materials; however, it is one of the most widely used materials in construction to date. Therefore, researchers aim to minimize the impact of concrete production through various methods, such as introducing sustainable sources of materials that can be used in concrete. For instance, agricultural waste materials can be used as partial cement replacement. This study presents a comprehensive data-driven analysis of the effects of POFA on the properties of normal-strength concrete. By synthesizing a database of 196 experimental datasets from existing literature, three …

Recycling Of Plastic Into Fibers Using A Novel Machine Design And Analysis Of Fiber Characteristics, Mahmoud Khamees, Nasser Ayoub, Sabreen Addullah Abdelwahab, M. M. Maghawry

Mansoura Engineering Journal

This study presents a modified extrusion-based recycling system with an improved nozzle design and controlled fiber production capability. The machine was conceptualized and fabricated to efficiently process waste plastic and extrude it into fibers of varying diameters. The study focuses on evaluating how fiber diameter influences critical material properties. Microstructural analysis by scanning electron microscopy (SEM) was conducted to investigate the morphology and fiber diameters, while tensile testing provided insights into mechanical performance, including strength and elongation. Moisture absorption tests were also performed to assess durability and environmental resistance. The results demonstrate clear correlations between fiber diameter and the examined …

Federated And Explainable Spiking Neural Networks For Fair And Privacy-Preserving Nail Disease Diagnostics, Ch Pavani Reddy, Krishnanaik Vankdoth

Mansoura Engineering Journal

Automated nail disease diagnostics provide a non-invasive pathway for identifying underlying systemic health conditions; however, conventional centralized deep learning approaches often raise concerns related to privacy, fairness, and interpretability. Although the original NeuroNail-SNN framework demonstrated an energy-efficient and edge-ready diagnostic solution, its broader clinical adoption remained limited by unresolved trust, transparency, and ethical considerations. In this study, we propose the Federated and Explainable NeuroNail-SNN, which extends the original spiking neural architecture by integrating federated learning (FL), explainable artificial intelligence (XAI), fairness evaluation, and uncertainty quantification within a unified framework. Federated learning enables decentralized model training across hospitals and mobile clinics …

Event-Related Potential Variation In Response Accuracy: A Comparative Analysis Using Mne-Python, Akash Rajak, Sachin Umrao

Mansoura Engineering Journal

Event-Related Potentials (ERPs) are extensively employed in the examination of neural responses linked with cognitive processing and changes in brain activity. In this work, we conducted a comparative analysis of ERPs on a publicly available EEG dataset (122 subjects, alcoholic and control groups) with the help of the MNE-Python framework. The 64 electrodes for EEG were placed according to the international 10 - 20 system, and EEG was sampled at a 256 Hz sampling rate over 1-second epochs. The preprocessing pipeline consisted of 1 - 40 Hz bandpass filtering, noise reduction, spectral computation, and ERP waveform analysis. Temporal neural activity …

Optimisation Of Stepped Basin Solar Still With Response Surface Methodology And Machine Learning Methods, M. Balamurugan, V. Santhanam, B. Deepanraj, S. P Manikandan, M. Yuvaperiyasamy, N. Senthilkumar

Mansoura Engineering Journal

This research focuses on enhancing the distillate output of a stepped basin solar still by optimizing key operational variables using Response Surface Methodology (RSM) and advanced machine learning techniques. As water scarcity remains a critical global challenge, solar stills offer a viable, sustainable solution for desalination. These systems offer an energy-efficient approach to converting saline water intofreshwater, providing an alternative to conventional desalination methods. The primary objective was to investigate how variations in solar radiation, step height, and water inlet temperature influence the productivity of the stepped basin solar still. The solar radiation ranged from 600 to 1000 W/m², the …

Pafex: Compiler-Based Floating-Point Exception Detection For Gpu Kernels With Papispecific Software-Defined Events, Samin Islam, Shirley V. Moore, Christoph Q. Lauter

Graduate Student Papers (CS)

As high-performance computing becomes progressively heterogeneous, the dependence upon vendor specific tools for numerical correctness has become an impediment to portability. Although modern GPUs comply with the IEEE 754 standard, the lack of practical native hardware support to raise and handle exceptions (special values like ±∞ or NaN) is a well-known architectural limitation. To embed portable numerical correctness across heterogeneous systems, we propose an architecture agnostic prototype based on LLVM-compiler infrastructure. This framework detects floating-point exceptions in GPU kernels at the Intermediate Representation (IR) level, instrumenting both device code and host code, strictly complying with the 2019 IEEE 754 standard. …

Gaze Transition Entropy And Automation Trust In Multitasking Workspace, Yusuke Yamani, Austin Jackson, Tetsuya Sato, Feyishola Ashimi, Michael S. Politowicz, Eric T. Chancey, Makoto Itoh

Psychology Faculty Publications

Safe flight operation requires visual scanning across multiple displays in a cockpit, which collectively represent the state of the aircraft and supporting automation. Trust is a crucial factor that drives human-automation interaction, and recent work has suggested a relationship between an operator's visual attention and automation trust. One index that captures predictability of eye movements between different areas of interest is gaze transition entropy. The current work reanalyzed data from Sato et al., which examined eye movement patterns and trust in automation associated with the system monitoring task of the Multi-Attribute Task Battery. Results showed credible positive correlations between the …

Implications Of Quantum Computing For Enterprise Cybersecurity And Data Integrity, Manikantha Varaprasad Inakollu

Computer Science and Engineering Faculty Publications

Quantum computing represents a paradigm shift in computational capabilities that poses both unprecedented threats and opportunities for enterprise cybersecurity. This research examines the implications of quantum computing advancement on current cryptographic systems, data protection mechanisms, and organizational security frameworks. Through analysis of quantum computing developments from 2019-2024 and surveys of 280 cybersecurity professionals across various industries, this study identifies critical vulnerabilities in existing encryption standards and explores emerging quantum-resistant solutions. The findings reveal that approximately 78% of enterprises remain unprepared for quantum threats, with current RSA and ECC encryption systems facing potential compromise within the next 10-15 years. The research …

Biomechanical Advancements In Hydroxyapatite, Magnesium-Substituted Hydroxyapatite, And Strontium-Substituted Hydroxyapatite In Clinical And Non-Clinical Studies For Maxillofacial Bone Tissue Engineering: A Review, Elham Zafarrazzaghnia, Stuart Hampshire, Aran Rafferty, Dermot Brabazon, Eamonn Debarra, Maura Kelleher

Articles

Hydroxyapatite (HA) is a bioceramic known for its bioactivity and osteoconductivity, which should make it an ideal candidate for maxillofacial bone regeneration. However, its brittleness limits its suitability for load-bearing applications. Over recent decades, substantial efforts have focused on enhancing its performance, particularly through ionic substitution, including magnesium-substituted HA (Mg-HA) and strontium-substituted HA (Sr-HA). This review summarises the available information on the structural, physical and mechanical properties of facial bones (maxilla, mandible, zygoma and frontal bone). The crystal structure, physical, and mechanical properties and in-vitro biological responses of dense and porous HA, Mg-HA and Sr-HA ceramics are described, with particular …

Application Of A Hyaluronic Acid-Based Lotions Containing Hydroxyapatite Nano-Particles Approach For Treatment Of Initial Dental Caries, Zahra Gharavi, Zahra Namazi, Fatemehsadat Pishbin, Helia Givian, Maryam Torshabi, Farhood Najafi, Parisa Amdjadi

Electrical & Computer Engineering Faculty Publications

This study evaluated the remineralization potential of a ceramic–polyelectrolyte system, based on a novel combination of hydroxyapatite nanoparticles (HAp NPs) and a hyaluronic acid (HY) matrix, for dental enamel, a tissue that remains challenging to repair in clinical dentistry. Nano-Hydroxyapatite (nanoHAp) powder was synthesized and characterized using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), field-emission scanning electron microscopy (FE-SEM), dynamic light scattering (DLS), and zeta potential analysis to confirm their crystalline structure, functional groups, morphology, particle size distribution, and colloidal stability. HY-based suspensions (remineralizing lotions) containing 5, 10, and 12 wt% of the synthesized nanoHAp particles were formulated via a …

The Professional Constructor, Full Issue

The Professional Constructor

Full Issue, Winter 2026

Volume 50, Number 01

Automation And Habitat Development For A Space Based Marine Life Environment, Logan Trimmer, Alexander Hang

Harrisburg University Other Works

This project was a cross-collaboration between the Environmental Sciences and Advanced Manufacturing and Robotics programs for the company Monolith Space.

The goal of this project was to design an autonomous system to be able to track qualities of water in an aquaculture system designed to be sent to space.

The Efficacy Of Hybrid Manufacturing For High Stress Automotive Components, Logan Trimmer

Harrisburg University Other Works

The goal of this research was to establish the viability of using hybrid manufacturing for automotive applications. By verifying that high-stress components can be created, it can be assumed that any other lower stress part could be made to match the strength requirements. A limiting factor of adoption for hybrid manufacturing is how new the technology is. Studies on time and cost were performed allowing for comparisons with traditional manufacturing technologies (casting, forging, milling) used in automotive applications. This research utilized a Haas Automation UMC750 5-axis CNC mill with a Meltio laser wire direct energy deposition attachment. Fusion 360 was …

Bridging Mission And Execution: Integrating Participatory Design In Early-Phase Mission Engineering For Stakeholder Alignment And Mission Clarity, Rafi Soule

Knowledge and Creativity Expo

This research examines mission framing during the early phase of Mission Engineering. Stakeholder interpretations diverge under ambiguity. Interoperability constraints are often not surfaced early. These conditions reduce mission clarity and weaken mission-to-system mapping readiness. The study integrates a participatory design-inspired, artifact-first workflow with RAG-enabled retrieval from a closed corpus to support evidence-grounded reasoning and traceable citations.

Phase 1 uses an online survey to establish baseline patterns in practice (N = 86). Shared understanding is positively associated with mission clarity (r = 0.60, p < 0.001). Phase 2 uses a time-bounded comparative workshop with two conditions. Expert reviewers rate mission statement quality higher for the participatory design condition (mean 3.5) than the traditional condition (mean 2.8). Technical feasibility ratings are similar across conditions. Phase 3 demonstrates RAG-enabled, closed-corpus, retrieval-supported traceability using the Referencer tool. It is reported as a proof-of-concept for evidence-grounded rationale and auditability, and as a pathway …

Rapid Urbanization Reduces Genetic Diversity And Increases Genetic Differentiation Of A Lynx Spider Oxyopes Sertatus In Central Taiwan, Ying-Yuan Lo, Chi Wei, Wan-Jyun Chen, Chung-Ping Lin

Biological Sciences Faculty Publications

Urbanization is a dominant force driving destructive and irreversible changes of natural habitats in modern times. While the effects of urbanization on community composition and phenotypic responses are well-documented, its influence on genetic diversity and population structure remains understudied, particularly for invertebrates in subtropical regions. This study tested the hypothesis that urbanization reduces genetic diversity and increases population differentiation in the lynx spider Oxyopes sertatus, a common foliage-dwelling spider in Taiwan. We sampled 245 individuals from 17 sites distributed along an urban-rural gradient and quantified urbanization intensity using land-use composition at both landscape (4 km²) and local (0.25 km²) …

Experimental Investigation Into The Effects Of Air Staging On Fouling In A Fixed-Bed Biomass Combustor, Akram Elsebaie

Theses: Doctorates and Masters

Biomass offers significant potential as a sustainable and renewable substitute for fossil fuels in energy generation, playing a critical role in the reduction of global warming. However, despite its environmental benefits, biomass combustion faces persistent operational challenges, particularly fouling, which reduces efficiency and increases maintenance costs. Although fouling mechanisms have been studied in various combustion systems, there is limited research which addresses its formation and behaviour in fixed-bed biomass combustors under different air staging conditions. This research investigates fouling behaviour in a counter-current combustor, focusing on the influence of design (secondary air location), operational (air staging flowrates between the primary …

Enhancing Deep Reinforcement Learning With Expert Demonstrations For Mobile Robot Navigation In Unstructured Off-Road Environments, Dulitha Dabare

Theses: Doctorates and Masters

Advancements in the field of Deep Learning has ushered in a boom in autonomous navigation research. Most of the work being conducted in this space, however, has focused on on-road urban navigation scenarios, with unstructured outdoor terrain navigation receiving much more limited attention. Given the wide range of applications that exist for legged and wheeled ground robots in off-road environments in areas such as agriculture, mining and disaster recovery, there is a growing need for research work to improve the navigational capabilities of mobile robots deployed in these challenging environments.

A promising candidate for application to these navigation challenges in …