Engineering Commons^™

Expanding The Horizons Of Nonagonal Neutrosophic Numbers As A Versatile Framework For Decision-Making And Scientific Applications In Covid-19, Muhammad Naveed Jafar, Kainat Muniba, Hamiden Abd El-Wahed Khalifa, Fahd Jarad

Neutrosophic Systems with Applications

In this article, the concept of nonagonal neutrosophic numbers has been introducing in the disjunctive frame of reference. We also proposed the dependency and independency of membership function in regards to nonagonal neutrosophic number. We also introduce a new score function and its computation also formulated in a distinct rational viewpoint. We developed the concept of weighted arithmetic averaging operator and weighted geometric averaging operator for nonagonal neutrosophic numbers. It will open new doors for MCDM and develop the concept with new approaches. Additionally, we analyze the effect of COVID-19 for different ages.

Assessing The Sustainable Blockchain-Metaverse-Iot Platform In The Healthcare Industry: An Intelligent Decision Support Model, Ibrahim M. Hezam, Ahmed M. Ali, Ibrahim A. Hameed, Karam Sallam, Mohamed Abdel-Basset

Neutrosophic Systems with Applications

Healthcare services must fulfill patients' desires for secure data sharing and high accessibility. Blockchain technology, through blockchain platforms (BPs), can overcome healthcare challenges. This study develops a decision-making methodology for selecting the best BP, by integrating blockchain with IoT and Metaverse, the proposed approach ensures data integrity, quality, privacy and security, secure data sharing, and interoperability. The decision-making methodology uses the multi-criteria decision-making (MCDM) methodology to handle conflicting criteria. Two MCDM methods are used in this study: CRiteria Importance Through Intercriteria Correlation (CRITIC) for weight computation, and Ranking of Alternatives with Weights of Criterion (RAWEC) for alternative ranking. To deal …

Appraisal Of Uncertainty-Driven Financial Performance: Bringing Multi-Criteria Decision Making Techniques With Neutrosophic Theory, Mona Mohamed, Nurhan Alaa, Eman Sayed

Neutrosophic Systems with Applications

Evaluating financial performance is essential yet challenging due to various factors, including ambiguity, insufficient information, and conflicting evaluation criteria. Conventional Multi-Criteria Decision-Making (MCDM) techniques often struggle to manage these complexities effectively. To address these limitations and enhance financial performance assessments, this research proposes an innovative approach integrating Single-Valued Neutrosophic Sets (SVNS) with established MCDM methodologies. SVNS uniquely manages uncertainty by concurrently quantifying degrees of truth, indeterminacy, and falsity within financial data. This research specifically employs entropy-based weighting methods integrated with Additive Ratio Assessment (ARAS) and Multi-Objective Optimization by Ratio Analysis (MOORA) methodologies in the SVNS environment to systematically rank enterprises …

A Novel Neutrosophic Decision-Making Approach For Optimizing Metaverse Headphone Design: Balancing Technical Performance And User Emotional Needs, Mai Mohamed, Amira Salam, Karam Sallam, Bilal Arain

Neutrosophic Systems with Applications

The concept of the metaverse, which combines various technologies to create a wide range of virtual experiences, has gained significant popularity in recent years. To fully engage in these metaverse environments, users rely on access devices such as virtual reality (VR) headsets and smartphones for augmented reality (AR). These devices must be lightweight, compact, and user-friendly to ensure comfort and enhance customer satisfaction. There is a growing focus on innovating and designing products that not only meet technical requirements but also address the emotional needs of users, ultimately improving the overall experience. Selecting the ideal design for Metaverse headphones is …

A Comprehensive Intelligent Traffic Monitoring System Based On A Novel Integration Of Neutrosophic Multi-Criteria Decision-Making Techniques, Mai Mohamed, Amira Salam, Rana Muhammad Zulqarnain, Muhammad Gulistan

Neutrosophic Systems with Applications

With the spread of road accidents and traffic congestion that costs countries and governments a lot of money in addition to the loss of human lives, and since traditional methods of monitoring traffic have not been as effective as desired, attention has been drawn to the search for more effective solutions to the problem of monitoring and regulating traffic. With the spread of technology and the Internet of Things, UAVs have emerged as a promising tool for monitoring traffic, as they can fly for a sufficient period and operate in difficult climatic conditions, in addition to their ability to monitor …

Nash Equilibrium Solutions For Continuous Static Games Under Neutrosophic Environment, M. G. Brikaa

Neutrosophic Systems with Applications

Neutrosophic set theory plays an important role in dealing with the impreciseness and inconsistency in data encountered in solving real life problems. This paper presents a novel approach to solving a new class of continuous static games within a neutrosophic framework. In the proposed methodology, the neutrosophic continuous static games are redefined into two separate crisp problems: the lower problem and the upper problem. The study further establishes the necessary conditions for determining equilibrium strategies in neutrosophic continuous static games. To demonstrate its effectiveness and practical applicability, the proposed method is validated through a numerical example.

Selective Lithium Extraction Using Ion-Sieves From Geothermal Brine, Agyare Asante, Abigail Berardi, Jayla Standin, Elliott Walker, Ujjwal Pokharel, Sandeep Kumar

Graduate Student Government Association Research Conference

Lithium (Li) is a critical component in modern green energy technologies, serving as the cornerstone for advanced batteries used in electric vehicles, renewable energy storage, and portable electronics. To address the increasing global demand for lithium, this study explores the synthesis and performance of ion-sieve novel adsorbents derived from the spinel-type precursor Li₄Mn_4.5Zr_0.5O₁₂ (LMZO). The precursor was produced using an economical solid-phase reaction that involved lithium, manganese, magnesium, and zirconium salts. This was followed by a two-stage calcination process involving 200 K for 2 hours and 450 K for 24 hours. Acid activation …

Carbon Accountability Scores: A Process-Oriented Approach For Carbon Offsetting Using Ai Agents, Joshit Mohanty, Vaishali Vaishali

Graduate Student Government Association Research Conference

Conventional carbon offset programs rely on quantified emissions to determine balancing requirements. While this approach offers a standardized means of measuring carbon output, it often provides industries with a loophole—allowing them to offset their emissions by purchasing equivalent credits for activities such as tree planting rather than tackling inefficiencies at the source. This research proposes a process-based framework called Carbon Accountability Scores (CA scores) to offer a proactive strategy for assessing and reducing carbon footprints. Instead of focusing on the mere balancing of emitted and sequestered carbon, CA scores integrate an organization’s operational processes into the calculation, thereby offering the …

Digital Thread: Bridging Macro–Micro Services In System-Of-Systems, Joshit Mohanty

Graduate Student Government Association Research Conference

Organizations and industries increasingly rely on distributed services in decentralized environments—ranging from large-scale, system-of-system architectures to fine-grained, agent-based microservices. While this distributed paradigm offers flexibility and innovation, it presents critical challenges such as interoperability gaps, inconsistent data formats, and a lack of holistic oversight. Traditional integration approaches, including ad-hoc middleware or enterprise service buses, tend to solve these issues reactively. As a result, technical debt accumulates, stakeholder misalignments persist, and scaling to new demands becomes complex.

This research proposes digital thread (DT) as the unifying framework to create an authoritative source of truth: a continuous flow of information across the …

Meta-Clustering For Specialized Language Models: Enhancing Contextual Adaptation And Mitigating Hallucinations In Diverse Healthcare Environments, Joshit Mohanty, Vaishali Vaishali, Sandeep Kumar Nayak, Sumit Lahiri

Graduate Student Government Association Research Conference

Large Language Models (LLMs) have significantly advanced conversational AI by enabling dialogic information-seeking and task execution across diverse domains. However, their extensive parameters and broad domain scope lead to “data hallucinations.” These shortcomings are particularly evident in dynamic and diverse environments like India’s healthcare sector, where myriad languages, regional practices, and cultural nuances demand specialized, localized expertise rather than one-size-fits-all generalist models. This paper introduces a meta-clustering framework that integrates Distilled Language Models (DLMs) and Small/Specialized Language Models (SLMs) with meta-learning principles to address these limitations. By drawing on evidence from works such as MedHalu and Med-HALT, the framework seeks …

Tamos: Task-Aware Multi-Agent Orchestrator System, Joshit Mohanty, Sandeep Kumar Nayak, Sumit Lahiri

Graduate Student Government Association Research Conference

Large language models (LLMs) are increasingly at the core of multi-agent systems (MAS). However, the high resource demand, error propagation, and lack of adaptive evaluation mechanisms pose significant challenges in deploying these agentic solutions at scale. To address these concerns, this research proposes a Task-Aware Multi-Agent Orchestrator System designed to refine the agentic framework, categorizing tasks autonomously, assigning specialized evaluation datasets, and balancing token usage against functional effectiveness. This approach underscores robust data management, including AsyncHow, Mosaic AI, and Synthetic Preference Optimization (PO) corpora. Each dataset targets specific dimensions of agent performance, such as dynamic task decomposition and tool integration …

Graphtreemed: A Hybrid Graph-Tree Rag Architecture For Mission-Critical Medical Applications, Joshit Mohanty, Sandeep Kumar Nayak, Sumit Lahiri

Graduate Student Government Association Research Conference

Studies within engineering management indicate that decision-making is often based on the cognitive processing of grouped and pictographic information clusters entangled with high-level pattern recognition. Similarly, graph-based retrieval-augmented generation (RAG) architectures substantially improve diagnostic accuracy and interpretability, while tree-structured systems reduce critical misses through hierarchical reasoning. However, existing solutions often lack a unified framework that seamlessly integrates these two paradigms to address the multifaceted demands of mission-critical healthcare settings. This proposal introduces GraphTreeMed, a novel hybrid RAG architecture designed to harness the complementary strengths of graph-based and tree-based retrieval mechanisms, thereby advancing the safety and efficacy of clinical decision support …

Longitudinal Analysis Of Evergreen Forest Cover Dynamics In The Great Salt Lake Basin: A Landsat-Based Stochastic Classification Approach And Comparative Assessment With The National Land Cover Dataset, Kaleb Markert

Theses and Dissertations

This dissertation presents an investigation into the changes of evergreen forest cover within the Great Salt Lake Basin and its implications for regional water resources. Utilizing a Random Forest Classifier (RFC) model trained on Landsat imagery, this research developed a methodology to map and track changes in evergreen forest coverage over the period from 1984 to 2019. The initial phase of this study focused on the development of model trained within the Bear Lake sub-basin, demonstrating the feasibility of the method for analysis of coniferous coverage. The model incorporated summer and winter Normalized Difference Vegetation Index (NDVI) to enhance the …

Establishing Particle Size Recommendations For Cationic Asphalt Emulsions, Tanner Turben, Pedro Diaz-Romero, Andrew Braham

Civil Engineering Faculty Publications and Presentations

Asphalt emulsions are used in flexible pavement maintenance and rehabilitation treatments. Emulsion specifications for material characterization are based on testing methodology dating to the 1930s. Newer test methods, including particle size analysis (PSA) of binder droplets in emulsion, have been explored but not implemented into specifications. The objective of this study is to observe the particle size and performance of cationic slow-setting (CSS) emulsions and establish baseline particle size recommendations for cationic emulsions. Four physical property tests (residue, oversize particles, viscosity, and particle size) and two cold mix asphalt performance tests (indirect tensile strength (IDT) and direct shear test (DST)) …

Frost Heave Of Clayey Soils Treated With Cement Or Lime, Ammon K. Hymas

Theses and Dissertations

The objective of this research was to measure and compare the effects of portland cement and lime at low, medium, and high concentrations on the frost-heave susceptibility of multiple clayey soils with varying plasticity indices. The scope of work included laboratory frost-heave testing of three clayey soils sampled from Monticello, Utah; Bloomington, Indiana; and San Antonio, Texas. Each soil was tested with two stabilizers, cement or lime, at three concentrations, as well as with no treatment. Two replicate samples were prepared for each combination, for a total of 42 specimens. The frost-heave testing procedures for this research involved preparing specimen …

04.21.2025 Ored Connect, Liz Williamson

ORED Newsletter

ORED Stakeholder Meetings

SEC Travel Grants

Leadership In The Age Of Ai: Review Of Quantitative Models And Visualization For Managerial Decision-Making, Satyadhar Joshi

Harrisburg University Other Works

This paper offers a comprehensive review of existing literature on the intersection of Artificial Intelligence (AI) and leadership, drawing on both theoretical insights and practical implementations. By analyzing scholarly publications from the past two years (2023-2025), the review traces emerging patterns in how AI technologies are being integrated into leadership practices. Key themes include the growing relevance of learning-based systems for adaptive decision-making and the application of attention-based models to improve responsiveness in dynamic environments. The review also addresses ethical dimensions of AI-enabled leadership, emphasizing the need to balance algorithmic efficiency with human judgment and oversight. Concerns around transparency, psychological …

Decadal To Millennial-Scale Morphodynamic Evolution Of Microtidal Marshes, Samuel Mason Zapp

LSU Doctoral Dissertations

Tidal marshes are susceptible to rapidly converting to open water due to their low elevations within the tidal frame. A continuous supply of externally supplied mineral sediment and in situ organic material production is necessary to offset elevation losses from relative sea level rise and erosion. Complex feedbacks between hydrodynamics, the erosion, transport, and deposition of sediment, and physical modification of the landscape by the establishment of intertidal vegetation govern the spatial and temporal patterns of elevation response. This dissertation focuses on modeling how these dynamics drive marsh landscape evolution in the past, present, and into the future under changing …

Bioactivity And Mechanical Performance Of Centrifugally Spun Poly(D,L-Lactide)/Poly(3-Hydroxybutyrate) Submicrometric Fibers Containing Zinc Oxide And Hydroxyapatite Nanostructures, Victoria Padilla-Gainza, Heriberto Rodríguez-Tobías, Karen Lozano, Cristobal Rodriguez, Robert Gilkerson, Antonio Ledezma-Pérez, Narcedalia Anaya-Barbosa, Graciela Morales

Mechanical Engineering Faculty Publications

This study investigates the morphological, thermal, mechanical, and bioactive properties of centrifugally spun fibrous composites made from poly(D,L-lactide)/poly(3-hydroxybutyrate) (PLA/PHB) blends with zinc oxide (ZnO) and hydroxyapatite (Hap) nanoparticles. A 75/25 PLA/PHB weight ratio was chosen to balance mechanical and thermal properties. The precursor solution viscosities ranged from 0.25 to 0.50 Pa s, increasing with nanoparticle incorporation probably due to polymer-nanoparticle interactions. SEM revealed a uniform fibrous morphology, with diameters of 1.21 for PLA/PHB, 2.65 for PLA/ZnO/Hap, and 1.80 μm for PLA/PHB/ZnO/Hap. TGA showed two-step degradation for PLA/PHB fibers, while PLA/PHB/ZnO/Hap degraded in a single step at 249°C, leaving a residue …

Using Eeg Signal For Smart Health: An Overview, Addison Clark, Chelsea Bonyata, Ishfaq Ahmad, Hansheng Lei, Khalid Saifullah, Victor Ibarra

Informatics and Engineering Systems Faculty Publications

This survey paper aims to provide an overview of the current state of EEG (Electroencephalography) signal technology as it relates to people with disabilities. It will highlight the various methods and techniques employed, discussing their advantages and disadvantages. The paper will also examine the applications of EEG technology in assisting individuals with disabilities, specifically focusing on Brain-Computer Interfaces (BCIs) and assistive device control. By understanding the current state of EEG signal technology, we can identify the opportunities and challenges involved in utilizing this technology to improve the lives of people with disabilities.

Bayesian Belief Networks Approach To Prioritize Road Safety Mitigation Measures For Eco-Mobility Modes, Fatmah Mohamed Alyammahi

Thesis/ Dissertation Defenses

This study presents a novel approach to prioritizing road safety mitigation measures for eco-mobility modes in Abu Dhabi, employing a sophisticated Bayesian methodology integrated with cost-benefit analysis. The research addresses the pressing need for enhanced safety in sustainable urban transportation, focusing on pedestrians, cyclists, and users of micro-mobility devices. A comprehensive Bayesian Belief Network (BBN) model was developed, incorporating key variables influencing eco-mobility safety, including visibility, predictability, road curvature, obstructions, and lighting conditions. The model was constructed using a combination of historical accident data and Probabilistic reasoning. This approach allowed for the quantification of complex relationships between various risk factors …

Imine Crosslinked, Injectable, And Self-Healing Fucoidan Hydrogel With Immunomodulatory Properties, Asma Talib Qureshi, Shajia Afrin, Saad Asim, Muhammad Rizwan

Michigan Tech Publications

Biomaterials with inherent anti-inflammatory properties and the ability to foster a pro-regenerative environment hold significant promise for enhancing cell transplantation and tissue regeneration. Fucoidan, a sulfated polysaccharide with well-documented immune-regulatory and antioxidant capabilities, offers strong potential for creating such biomaterials. Yet, there is a lack of engineered fucoidan hydrogels that are injectable and provide tunable physicochemical properties. In this study, the ability of fucoidan to undergo periodate-mediated oxidation is leveraged to introduce aldehydes into backbone (oxidized fucoidan, OFu), enabling the formation of reversible, imine-crosslinks with amine-containing molecules such as gelatin. The imine-crosslinked OFu-gelatin hydrogel provided excellent control over gelation rate …

Hydrologic Decision Support In The Nile Basin: Creating Status And Outlook Products From The Geoglows Hydrologic Model, Rachel Huber

Theses and Dissertations

Decision makers and stakeholders need information about current and future streamflow to make informed decisions and we show how the GEOGLOWS Hydrologic Model, known as River Forecast System (RFS), can be used to provide hydrologic status and outlook products to inform these decisions. We examine a specific use case of RFS in the Nile River Basin and how RFS is used to provide users with hydrologic status products. We work with stakeholders at the Nile Basin Initiative to assess their needs for this information. We use basic low flow calculations to compute the Standardized Streamflow Index (SSI) and the 95th …

Systematic Analysis On The Applications Of Infrastructure Asset Management In Utah, Kelvin Kozakevitch

Theses and Dissertations

Public infrastructure is essential to a region’s economic stability and quality of life, especially its rural infrastructure where most consumable and essential goods derive from. Given the high capital investment required for infrastructure development and maintenance, asset management plans (IAM) are critical. Even though academic research exists on the problems rural infrastructure management face, little is known about the actual state, barriers and causes for the challenges IAM faces in rural Utah. This study examines the current challenges and barriers in IAM among rural communities in Utah. Employing a grounded theory approach, data was collected through a two-phase methodology: phase …

Enabling Next-Generation Microfluidics Through Advances In High-Resolution 3d Printing, Matthew S. Viglione

Theses and Dissertations

This dissertation advances the field of microfluidic device fabrication through the development and application of high-resolution 3D printing technologies. The convergence of stereolithography (SLA) with digital light processing (DLP) has created unprecedented opportunities for microfluidic device fabrication, enabling truly three-dimensional structures with feature sizes approaching the single-micron scale. Building upon foundational work in custom 3D printer development, this research addresses critical limitations in 3D printing that have historically constrained microfluidic innovation, spanning multiple generations of custom 3D printers and technical innovations that have enabled the fabrication of increasingly complex microfluidic devices while enhancing resolution, repeatability, speed, and accessibility. A comprehensive …

A Low-Cost Micro Actuator Driven By Electrowetting-On-Dielectric, Behzad Parsi

Theses and Dissertations

Microfluidic techniques have been shown to address limitations of reconfigurable radio frequency (RF) antennas and filters in efficiency, power handling capability, cost, and frequency tuning. However, the current devices suffer from significant integration challenges associated with packaging, actuation, and control. Recent advances in reconfigurable microfluidics that utilize the motion of a selectively metalized plate (SMP) for RF tuning have demonstrated promising RF capabilities but have exposed a need for an accurate fluid actuation model. This research presents models for the dynamics of plate actuation under multiple scenarios. In the first phase, the mechanical motion of a moving plate (e.g. SMP) …

Polymetal Phosphate Cement From Tin Fuming Furnace Slag: Hydration Mechanism, Mechanical Performance, And Environmental Safety, Peiwen Lv, Xintao Zhou, Zhongqiu Luo, Cuirong Yan, Xiunan Cai, Ting Huang, Pingyan Wang, Hongyan Ma

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Phosphate cement materials are ideal binders for the rapid repairment of civil engineering and solidification/stabilization of hazardous solid wastes due to their fast setting, high early strength and strong adhesion. However, the use of pure metal oxides as the raw base materials and their deactive pretreatment result in the high cost and energy consumption, limiting its broad applications. In this study, an eco-friendly polymetal phosphate cement (PMPC) was developed using tin fuming furnace slag (TFFS) as the primary base material. The hydration behavior, microstructure, mechanical properties, and environmental safety of PMPC were comprehensively evaluated. The results showed that the hydration …

Balancergnn: Balancer Graph Neural Network For Imbalanced Datasets, Mallika Boyapati

Dissertations

Addressing imbalanced datasets is challenging due to machine learning models' inclination to learn the majority class. Graph construction plays a major role in determining how Graph Neural Networks (GNNs) perform on imbalanced datasets. In this research, we introduce the BalancerGNN framework to tackle highly imbalanced datasets, demonstrating its effectiveness in fraud detection as one of the case studies. This framework is designed to work for any binary node classification dataset with significant class imbalances. This research addresses the following questions: i) How effective are feature engineering techniques in the case of imbalanced datasets? ii) How do graph representation learning and …

Impact Of Repeated Washing Cycles On Surface Integrity And Mechanical Properties Of Glass Bottles, Siwat Patamakam Mr., Thitisilp Kijchavengkul, Siriyupa Netramai, Gong Yaijam

Journal of Applied Packaging Research

Glass bottles are a top choice in the global beverage industry, but their inherent brittleness poses challenges in maintaining durability. This study focused on investigating the impact of numbers of washing processes from reusing on the surface quality and mechanical properties of glass bottles after each washing cycle. Contact angle technique was used to determine surface quality of glass bottles. It was found that mechanical integrity, as reflected in internal pressure resistance values, and surface quality of glass bottles exhibited an exponential decline with each washing cycle. Furthermore, a predictive model (R² = 0.8882) was developed to estimate its …

Survey On Intelligent Planning Methods From Large Language Models Perspective, Yanzhong Zhou, Junren Luo, Xueqiang Gu, Wanpeng Zhang

Journal of System Simulation

Abstract: Starting from the perspective of large language models, this paper gives an overview of the definition and development of intelligent planning, and briefly introduces the traditional methods of intelligent planning; based on the close relationship between large language model intelligent agents and intelligent planning, introduces the architecture of large language models and typical large model intelligent agents; focusing on the intelligent planning for large language models, combs through the learning of planning languages, chain of thought, feedback optimization, and process automation; combining with the current challenges and difficulties, introduces the outlook of cutting-edge research on intelligent planning with large …