Digital Commons Network^™

Distribution System Reliability Evaluation Considering Protection Coordination Using Petri Nets, Rani Kumari, Bhukya Krishna Naick

Turkish Journal of Electrical Engineering and Computer Sciences

Maintaining reliable and high-quality power delivery becomes increasingly complex with expanding power grids. The lack of protection coordination poses a significant threat, compromising overall system reliability. This research addresses this challenge by proposing a method for coordinating protective devices within the distribution system, specifically during network faults. The proposed approach utilizes a stochastic timed Petri net (STPN) based methodology to model protective device coordination across various fault scenarios. This technique effectively captures the dynamic behavior and interactions of protective equipment, allowing for the anticipation of potential disturbances. This proactive insight facilitates preventative measures to address prewarning situations, thereby preventing cascading …

Spectroscopic Investigations On Polyvinylidene Fluoride Nanofibers, Parinaz Amaniabdolmalaki, Jui Vitthal Kharade, Alexandro Trevino, Lydia Morales, Karen Lozano, Victoria Padilla, Karen S. Martirosyan, Horacio Vasquez, Mircea Chipara

Physics & Astronomy Faculty Publications

The production of polyvinylidene fluoride nanofibers by force-spinning from polymer solutions was confirmed by electron microscopy. The structural and phase characteristics of the resulting nanofiber mats were examined using Fourier Transform Infrared Spectroscopy in Attenuated Total Reflectance mode, Raman spectroscopy, and X-ray Diffraction. Results from all these techniques consistently indicated that both the powder and the mats of polyvinylidene fluoride predominantly contain the α phase, with a small admixture of the β phase. Within experimental errors, no other phases were noticed both in the powder and in the as-obtained mats. The ratios of the areas of the Raman lines at …

Pythagorean Neutrosophic Mathematical Modelling, M. Kavitha, R. Irene Hepzibah

Neutrosophic Systems with Applications

Survey-based assessments often suffer from ambiguity, inconsistency, and uncertainty, which weaken the reliability of decision-making outcomes. To address these challenges, this study proposes a novel decision-support framework for data fuzzification, ranking, and agility measurement using Pythagorean Neutrosophic Fuzzy Sets (PNFS). The proposed method offers three major advantages: (i) enhanced ability to capture high levels of indeterminacy compared with classical fuzzy and intuitionistic models, (ii) improved ranking accuracy through a newly developed score function and ranking algorithm, and (iii) greater robustness in scenarios involving conflicting, incomplete, or imprecise expert judgments. The framework includes a refined Pythagorean Neutrosophic fuzzification technique, mathematically supported …

A Study Of Regular And Irregular Complex Neutrosophic Vague Graphs, Suriyakumar G, V. J. Sudhakar

Neutrosophic Systems with Applications

In this paper, We define the regular complex neutrosophic vague graph and the irregular complex neutrosophic vague graph for this purpose. We specify a node’s degree and total degree in a normal complex neutrosophic vague graph. A few features and theorems of those regular and irregular complex neutrosophic vague graphs are presented. This article defines busy and free nodes in a normal complex neutrosophic vague graph. Also, we describe a regular and irregular complex neutrosophic vague graph with a cycle as the underlying crisp graph.

Neutrosophic Hankel Transforms And Their Application To Cross-Domain Legislative Integration, Mona Gharib, Mehboob Ali, Ishtiaq Hussain

Neutrosophic Systems with Applications

This paper introduces the Neutrosophic Hankel Transform (NHT) as a novel mathematical framework for modeling systems with radial structure under uncertainty, indeterminacy, and inconsistency. Building upon classical Hankel transforms and neutrosophic logic, we define two complementary realizations: a componentwise transform (NHT–C) that transports uncertainty with the signal, and a kernel-weighted transform (NHT–K) that embeds neutrosophic weights into the integral kernel. We establish linearity, inversion, and Parseval-type relations, and derive operational rules that diagonalize the Bessel radial operator.

To demonstrate utility, we formulate a radial diffusion–reaction model for pollutant concentration in a radialized river cross-section and solve it in closed form …

From Uncertainty To Lucidity: Awareness Neutrosophic Kähler-Einstein Innovative Evaluator Methodological In Era Of Green Artificial Intelligence, Mona Mohamed, Ahmed M. Ali

Neutrosophic Systems with Applications

The rapid development of generative artificial intelligence (Gen AI) is a double-edged sword. On the positive side, Large Language Models (LLMs) of Gen AI as chatbot considered intelligent friend. Due to its potential to stimulate the maturation of ideas and cultivate fundamental general abilities like problem-solving and critical thinking. The advancement of Gen AI continued after that, moving from “chatbots” to “AI agents” that carry out multi-step activities in addition to responding to queries.

Regarding the downside, the terminology of “Red AI” era brought about by generative AI is marked by a performance at any expense that puts pressure on …

Comparing And Optimizing Hollow Fibre And Flat Sheet Vacuum Membrane Distillation, Hamed Kariman, Mehdi Khiadani, Hussein A. Mohammed

Research outputs 2022 to 2026

Membrane Distillation (MD) systems have the potential to tackle the growing global water demand. Within various MD systems, Vacuum Membrane Distillation (VMD) systems are particularly important in addressing this issue. Hollow Fibre VMD (HF-VMD) and Flat Sheet VMD (FS-VMD) are the two main configurations of VMD systems, where limited studies are available on their comparison and optimisation under identical operational conditions. This study firstly charts the mathematical modelling of HF-VMD and FS-VMD systems that have been developed, accounting for the amount of flux, Gain Output Ratio (GOR), Temperature Polarisation Coefficient (TPC), and Specific Thermal Energy Consumption (STEC) of both configurations …

Single-Valued Neutrosophic Pessimistic Multi-Granulation Rough Set Model Based On (A,B,C)-Cut Relations And Its Applications, Xu-Xi Wu, Hu Zhao, Qiao-Ling Song, Xiong-Wei Zhang

Neutrosophic Systems with Applications

To address uncertainty in multi-source data, this paper proposes a single-valued neutrosophic pessimistic multi-granulation rough set (P-SVN-MGRS) model based on (a,b,c)-cut relations. In this framework, each neutrosophic relation is characterized by three membership-degree functions: T(x,y), I(x,y), and F(x,y). These functions correspond to truth-membership, indeterminacy, and falsity, respectively. The (α,β,γ)-cut relation employs parameters α,β,γ∈(0,1] as thresholds for the three functions. A pair (x,y) belongs to …

Applications For The Quasi-Atomic Orbital And Constrained Density Functional Theory Methods On Catalytic Reactions, Alvaro David Loaiza Orduz

LSU Doctoral Dissertations

Selective activation of C–O, C–H, and C–C bonds underpins biomass upgrading, alkane functionalization, and CO₂ conversion. Despite their importance, the electronic factors governing catalytic performance remain incompletely understood, and many industrial processes still rely on empirical trends or material-specific observations. This dissertation addresses this gap by applying density functional theory (DFT), thermodynamic decomposition, and electronic-structure analysis to identify unifying principles of reactivity across transition-metal phosphides, vanadate oxides, copper-based electrocatalysts, and mixed IrO₂–RuO₂ layers. This work examines how charge transfer, orbital localization, and ligand-induced perturbations control reaction pathways in diverse catalytic systems. C–O bond scission in 2-methyltetrahydrofuran (MTHF) and methanol was …

Volumetric Wear Analysis Of Polyethylene Orthopedic Liners Using Point Clouds, Gabriel Landi

Dartmouth College Master’s Theses

In vivo wear of ultra-high molecular weight polyethylene (UHMWPE) orthopedic bearings represents a major problem in shoulder and knee arthroplasty, with significant amounts of devices failing due to the complication itself, and even more due to associated reasons for retrieval, including aseptic loosening. However, quantification of UHMWPE wear has largely been limited to linear and in vitro volumetric analyses, obscuring the understanding of the amount of clinically relevant material loss. This study proposes new methods to measure articular, rim, and backside surfaces of retrieved shoulder and knee UHMWPE liners, centered around the coordinate measuring machine (CMM)-based collection of high density …

Securing U.S. Leadership In Agentic Ai Literacy And Adoption: U.S. Vs Chinese Government Policies And Initiatives, Satyadhar Joshi

Harrisburg University Other Works

This paper conducts a comparative analysis of U.S. and Chinese frameworks for AI literacy and adoption, with focus on agentic AI and Artificial General Intelligence (AGI) systems capable of autonomous reasoning and execution. We examine national policies, educational integration, governance structures, and technological roadmaps, employing both qualitative review and quantitative modeling. Mathematical formulations include multi-dimensional literacy scoring, Bass diffusion models for adoption dynamics, risk assessment functions, regulatory effectiveness indices, competitiveness metrics, and optimization frameworks for resource allocation. Our analysis reveals divergent paradigms: the U.S. Favors decentralized, innovation-driven approaches with emphasis on interoperability and public-private collaboration; while China pursues centralized, state-led …

Reproducible Semantic Data Management Workflow For Materials Data Science: Generating Knowledge Graphs With Robust Fairifcation Pipelines, Kyle R. Henrikson, Van D. Tran, Meredith Francis, Isabella Giammattei, Quynh D. Tran, Laura S. Bruckman, Erika I. Barcelos, Roger H. French

Student Scholarship

Combining data from multiple sources is crucial for efficient knowledge aggregation in materials data science. FAIR data from ontology and Linked Data principles enable this. Semantic data management streamlines data exchange and aggregation, ensuring information is available and extractable. FAIRLinked and GraphDB provide solutions for consolidating, hosting, and extracting meaningful insight from multimodal data.

Methods For Radiation-Sparing Navigation In Endovascular And Spine Surgery, William Ross Warner

Dartmouth College Ph.D Dissertations

Modern surgical navigation systems improve procedural accuracy, limit complications, and can reduce reliance on intraoperative ionizing radiation, yet their adoption remains uneven across surgical domains. Informed by clinical immersion, this thesis identifies and addresses two unmet needs revealed through contrasting image-guidance practices in endovascular and spine surgery, where existing guidance techniques are costly, intermittent, or fundamentally limited. Specifically, these needs include (1) the absence of radiation-sparing navigation techniques for endovascular procedures, which rely heavily on 2D x-ray angiography, and (2) the need for dynamic registration methods in open spine surgery, where navigation accuracy can degrade after initial registration and intraoperative …

Distributed Model Predictive Control-Based Power Management Scheme For Grid-Integrated Microgrids, Sergio Escareno, Sijo Augustine, Liang Sun, Sathishkumar J. Ranade, Olga Lavrava, Enrico Pontelli, John Hedengren

Faculty Publications

Transitioning from traditional electrical grids to smart grids is currently an ongoing process that many nations are striving for due to their access to renewable resources. Energy management is one of the key parameters that decides the performance of such complex systems. Distributed Model Predictive Control (DMPC) is a promising technique that can be used to improve the energy management of grid-connected systems. This paper analyzes a grid-connected inverter system with DMPC that exchanges key operating parameters with the grid to optimize coordinated power sharing between its respective loads. The state-space model for the inverter is derived and verified to …

Molecular Survival Strategies Against Kidney Filtration: Implications For Therapeutic Protein Engineering, William Heaps, Anna Elise Packard, Kristina M. Mccammon, Tyler P. Green, Joseph P. Talley, Bradley C. Bundy, Dennis Della Corte

Faculty Publications

The glomerular filtration barrier poses a significant challenge for circulating proteins, with molecules below ~60–70 kDa facing rapid renal clearance. Endogenous proteins have evolved sophisticated evasion mechanisms including oligomerization, carrier binding, electrostatic repulsion, and FcRn-mediated recycling. Understanding these natural strategies provides blueprints for engineering therapeutic proteins with improved pharmacokinetics. This review examines how endogenous proteins resist filtration, evaluates their application in protein engineering, and discusses clinical translation including established technologies (PEGylation, Fc-fusion) and emerging strategies (albumin-binding domains, glycoengineering). We address critical challenges of balancing half-life extension with tissue penetration, biological activity, and immunogenicity—essential considerations for the rational design of next-generation …

A Review Of Routing Attacks In Routing Protocol Over Low-Power And Lossy-Based Iot Networks, Lanka Chris Sejaphala Mr., Vusimuzi Malele Prof, Francis Lugayizi Prof.

Journal of Cybersecurity Education, Research and Practice

Low-power and Lossy IoT Networks (LLNs) comprise physical sensors, processing capability, power, and other technologies to exchange information between systems and devices over the internet. However, these networks are susceptible to routing attacks affecting resources, traffic flow, and topology formation. In the related work, it has been discovered that many previous studies do not consider algorithms and implementation approaches for routing attacks. This research study provides a comprehensive in-depth synthesis insight into the description, effects, and algorithms & implementation of four routing attacks in LLNs i.e., rank, sinkhole, DIS-flooding, and worst parent attacks. The findings of this research study highlight …

Reformulation Of The Protein Databank For Real-Time Search Of Geometrical Attributes Of Protein Structures, Musa Azeem, Christopher Lee, Aaron Hein, Christopher Ott, Homayoun Valafar

Faculty Publications

Introduction:

In this study, we introduce the design and implementation of PDBMine, a large-scale, queryable platform for mining sequence-structure statistics from the Protein Data Bank (PDB). PDBMine enables rapid analysis of local conformational trends across proteins by extracting dihedral angles and sequence patterns at scale. In addition to the design and implementation of PDBMine, we also present results validating its ability to return structurally meaningful information.

Methods:

We first assess the accuracy of its dihedral angle distributions by comparing them to established Ramachandran space and verifying expected behaviors of residues such as glycine and proline. We then use PDBMine to …

General And Special Relativity May Explain The Hubble Tension And Galactic Rotation, Charles F. Babbs

Weldon School of Biomedical Engineering Faculty Working Papers

Using two equations from general and special relativity, one can explore the hypothesis that gravitational time dilation and the relativistic Doppler effect cause the Hubble tension. Predicted results show good agreement between theory and observation, as long as mass is restricted to ordinary baryonic matter. This unexpected finding suggested a surprising continuation, namely that observed galactic rotation also be explained by special relativity. This idea survived initial tests using both Vera Rubin’s original data and more recent observations.

Jiving With Llms: Assessing First Year Students’ Computer Programming Self Efficacy After Reading Code With Llms, Michelle Jarvie-Eggart, Joseph Roy Teahen, Daniel T. Masker, Jose Padilla, Leo C. Ureel Ii, Laura E. Brown, Scott Pomerville, Jon Sticken

Michigan Tech Publications

This study investigated the impact of leveraging generative artificial intelligence (GenAI) to assist 1st-year engineering and computer science (CS) students in reading code in a new (to them) language. Students were asked to comment code in FORTRAN. They were then asked to run the code through ChatGPT-4.0 for its comments and reflect on what they learned from the experience. Participants completed survey items from Ramalingam and Wiedenbeck’s Computer Programming Self-Efficacy Scale (CPSES) prior to and after the intervention. Additional open-ended reflective (qualitative) questions were added to the quantitative questions in the postintervention questionnaire. This study documents increases in self-efficacy for …

Combinatorial Synthesis Of Protein-Polymer Conjugates By Post-Polymerization Modification Of Poly(Pentafluorophenyl Acrylate)S, Emily W. Kish, Thatcher M. Lee, Alexis M. Ziemba, Ama Boamah, Bianca Figueroa, Margherita Piccardi, Carey E. Dougan, Sarah J. Moore, Maren E. Buck

Chemistry: Faculty Publications

Combinatorial methods for preparing polymeric biomaterials enable the rapid identification of materials useful for many applications in science, medicine, and engineering. In the work described here, we demonstrate that side-chain reactive polymers can be used as templates for the rapid preparation of a small library of diversely functionalized protein–polymer conjugates. The activated ester polymer poly(pentafluorophenyl acrylate) (PPFPA) was modified postpolymerization with substoichiometric equivalents of three hydrophilic primary amines to yield a library of amphiphilic, side-chain reactive copolymers. These copolymers were then conjugated to two receptor-targeting proteins, holotransferrin (hTF) and an engineered fibronectin-based protein (Fn3), through amine-activated ester coupling. We investigated …

Simulation Results Of Spaceborne Ssa Using A Comprehensive Passive Radar Model, Chinmay Gaikwad, Filipe Senra, Thomas Alan Lovell, Hao Peng, Berker Pekoz, Tianyu Yang

Publications

In this paper, a high-fidelity simulation framework is developed to assess the feasibility of tracking space debris using a large low-Earth orbit (LEO) satellite constellation equipped with onboard passive radar sensors. By exploiting illumination from a distributed network of ground-based transmitters, the constellation provides consistent line-of-sight access to debris objects at higher altitudes, enabling angles-only detection and tracking. This approach yields a scalable, automated, and cost-effective architecture for next-generation space surveillance and contributes to more resilient space traffic management. A complete angles-only passive-radar orbit-determination pipeline is introduced and demonstrated. Initial orbital states are generated using a rate-aware constrained admissible-region multiple-hypothesis …

Optimized Resnet-18 Architecture For Multi-Class Oral Diseases Classification, Ahmed Ahmed

Karbala International Journal of Modern Science

In recent years, the classification of oral diseases has gained significant attention due to its influence on public health and the necessity for early and accurate diagnosis. Traditional diagnosis depends on manual clinical assessment, which can be slow and subjective. An optimized and subsequently quantized model is required to provide a faster and more consistent diagnostic support tool. This paper proposes an optimized ResNet-18 architecture for the classification of six oral diseases. The optimization process is based on removing the Rectified Linear Unit (ReLU), Batch Normalization (BN), and convolutional layers from the base ResNet-18 blocks that contain 128 filters. This …

Optimal Placement Of Electric Vehicle Chargers: A Mixed-Integer Linear Programming Model, Joubin Zahiri Khameneh, Emmanuel Fagbenle

Faculty Publications

Electric vehicle adoption is growing, but New Hampshire lags in public charging infrastructure, especially in rural areas. This gap increases range anxiety and economic inefficiencies. In this study, we developed a mixed-integer linear programming (MILP) model to optimally locate new electric vehicle chargers statewide, maximizing coverage and equity under budget constraints. The model includes geographic coverage requirements, population-weighted equity, capacity limits, and a $28 million budget. Moreover, the model recommends 855 Level 2 chargers and 149 Direct Current Fast Chargers (DCFCs) across 247 ZIP Codes, nearly doubling public charging capacity and achieving 98.8% coverage within defined service radii. The plan …

Merging Terrestrial And Satellite Gravity Data For Africa: A Possibility To Fill-In The Data Gaps, Hussein A. Abd-Elmotaal, Norbert Kuhtreiber

Mansoura Engineering Journal

The major challenge that the IAG Sub-Commission on gravity and geoid in Africa faces is the significantly large gravity data gaps. It is essential to properly tackle this issue for all geodetic applications in Africa due to the large interpolation errors occur at these large gaps. Simple interpolation (using any type of interpolation technique) of the gravity data does not add new information at the large data gaps, and the solution is free there. Global Earth gravity models offer themselves as a possible way to fill-in such large data gaps, provided that they approximate the African gravity field to an …

A Contextual Attention-Based Transformer Model For Enhanced Hate Speech Detection On Twitter, Mira Mansour, Nancy Akoum, Seifedine Kadry

Iraqi Journal for Computer Science and Mathematics

Hate speech on social media poses significant societal challenges, necessitating accurate and context-sensitive automated detection. Traditional machine learning (ML) models typically rely on lexical or superficial features, limiting their ability to capture nuanced or contextually ambiguous expressions of hate speech. Recent transformer-based methods (e.g., RoBERTa) provide improved contextual understanding but often lack explicit mechanisms guiding the model’s attention to critical semantic tokens, thereby reducing interpretability and sensitivity to nuanced linguistic contexts. This paper introduces a novel contextual attention-guided transformer model that explicitly incorporates lexicon-guided attention supervision into RoBERTa fine-tuning, significantly enhancing semantic precision in hate speech detection on Twitter. Evaluations …

Research Progress On Generating Perfect Vortex Beams Based On Metasurfaces, Xiujuan Liu, Manna Gu, Ying Tian, Mingfeng Zheng, Bo Fang, Zhi Hong, Chee Leong Tan, Xufeng Jing

Electrical and Computer Engineering Faculty Publications and Presentations

This article reviews the latest advances in the generation and control of perfect vector beams using metasurfaces. In recent years, metasurfaces have garnered increasing interest due to their simple fabrication and easy integration. Perfect vortex beams (PVBs), as a type of vector beams, exhibit complex polarization states that require the superposition of multiple phases for their generation. The use of metasurfaces provides a compact platform for the generation of perfect vortex beams and enables more complex vortex beam control tasks, which are quite challenging for traditional optics. This paper begins by introducing the principle of perfect vortex beam generation using …

Numerical Solution Of A Coupled Nonlinear Dynamic Problem Of Thermoviscoelasticity, Abdali Abdukarimov, Ibodat Turabekovna Khaldybaeva, Askarova Shamshetdinovna Ayjamal

Technical science and innovation

This paper presents a numerical solution of a coupled nonlinear dynamic problem of thermoviscoelasticity. A Duffing-type oscillator with temperature-dependent properties is used to model nonlinear hereditary deformable systems. After specifying the temperature dependences of the elastic modulus 𝐸 and viscosity parameter 𝜂 and introducing dimensionless variables, the problem is reduced to a system of nonlinear integro-differential equations. A numerical procedure for solving this system is developed, and representative examples are computed. The results are presented in graphical form for various values of the governing parameters.

Blockchain-Based Peer-To-Peer Renewable Energy Trading And Traceability Of Transmission And Distribution Losses, Amit Kumar Vishwakarma, Pratyush Kumar Patro, Adolf Acquaye, Raja Jayaraman, Khaled Salah

Industrial Engineering: Faculty & Staff Publications

In attempts to progress the transition towards decarbonizing energy systems and achieving sustainable development goals linked to energy, renewable energy sources (RES), which are decentrally deployed, are being widely promoted. However, RES are constrained by many barriers, some of which are technical in nature, such as energy losses. For instance, traditional peer-to-peer (P2P) trading systems have been used as a mechanism to advance RES because they offer a promising solution for decentralized energy trading without third-party intermediaries. However, it faces significant challenges, notably in accounting for energy losses during transmission and distribution, thus reducing overall system efficiency. We propose an …

Exploring The Role Of Occupational Therapy In The Delivery Of Trauma-Informed Services To Hospital-Based Clients Ot, Frank Czuba

Journal of Applied Disciplines

Hospitalization can traumatize clients and impact overall health outcomes, leading to increased hospital readmission rates and resulting in a negative impact for both clients and providers. Limited information exists regarding how hospital-based occupational therapists evaluate and address trauma, even though incorporating trauma-informed principles into professional practice can enhance the occupational therapy process. The study explored the comprehension and perceived significance of trauma-informed tenets among occupational therapists delivering services in hospital-based settings. A quantitative research study with an exploratory design was implemented to explore how occupational therapists (OT) understand and utilize trauma-informed practices with their clients in a hospital setting. An …

The Impact Of Natural Cavities On Mining Feasibility In Brazil: Dilemma Between The Sustainability Of Mining Operations And The Environment, Tiago Leite, Felipe Souza, Mariana Silva, Iuri Brandi, Hernani De Lima

Journal of Sustainable Mining

Due to the legislation on natural underground cavities in Brazil, mineral reserves have been blocked, causing a great dilemma between the sustainability of the mineral activity and the preservation of cavities. This study presented an analysis of the evolution of the federal cave legislation, pointing out the main gains and contribution to the theme, in which the importance in the Brazilian scenario of the publication in 2017 of Normative Instruction N° 01, which updated the procedures for the definition of these “other forms of compensation” to the irreversible negative impact on cavities with a high degree of relevance. In this …