Digital Commons Network^™

Symbolic Hyperplithogenic Set, Takaaki Fujita, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Concepts such as Fuzzy Sets, Neutrosophic Sets, and Plithogenic Sets have been widely investigated for tackling uncertainty, with numerous applications explored across various domains. As extensions of the Plithogenic Set, the HyperPlithogenic Set and the SuperHyperPlithogenic Set are also recognized. A Symbolic Plithogenic Set (SPS) is a structured set defined by symbolic components 𝑃𝑖 and coefficients 𝑎𝑖 , enabling flexible algebraic operations under a specified prevalence order. In this paper, we examine concepts including the Symbolic HyperPlithogenic Set and the Symbolic 𝑛-SuperhyperPlithogenic Set.

Some Types Of Hyperneutrosophic Set (4): Cubic, Trapozoidal, Q-Rung Orthopair, Overset, Underset, And Offset, Florentin Smarandache, Takaaki Fujita

Branch Mathematics and Statistics Faculty and Staff Publications

This paper builds upon the foundational work presented in [38–40]. The Neutrosophic Set provides a comprehensive mathematical framework for managing uncertainty, defined by three membership functions: truth, indeterminacy, and falsity. Recent advancements have introduced extensions such as the Hyperneutrosophic Set and the SuperHyperneutrosophic Set, which are specifically designed to address increasingly complex and multidimensional problems. The formal definitions of these sets are available in [30]. In this paper, we extend the Neutrosophic Cubic Set, Trapezoidal Neutrosophic Set, q-Rung Orthopair Neutrosophic Set, Neutrosophic Overset, Neutrosophic Underset, and Neutrosophic Offset using the frameworks of the Hyperneutrosophic Set and the SuperHyperneutrosophic Set. Furthermore, …

Some Types Of Hyperneutrosophic Set (3): Dynamic, Quadripartitioned, Pentapartitioned, Heptapartitioned, M-Polar, Takaaki Fujita, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

This paper builds upon the foundation established in [50, 51]. The Neutrosophic Set provides a robust mathematical framework for handling uncertainty, defined by three membership functions: truth, indeterminacy, and falsity. Recent developments have introduced extensions such as the Hyperneutrosophic Set and SuperHyperneutrosophic Set to tackle increasingly complex and multidimensional problems. In this study, we explore further extensions, including the Dynamic Neutrosophic Set, Quadripartitioned Neutrosophic Set, Pentapartitioned Neutrosophic Set, Heptapartitioned Neutrosophic Set, and m-Polar Neutrosophic Set, to address advanced challenges and applications.

Plithogenic Duplets And Plithogenic Triplets, Takaaki Fujita, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

A Neutrosophic Set is a mathematical framework that represents degrees of truth, indeterminacy, and falsehood to address uncertainty in membership values [41, 42]. In contrast, a Plithogenic Set extends this concept by incorporating attributes, their possible values, and the corresponding degrees of appurtenance and contradiction [50]. Among the related concepts of Neutrosophic Sets, Neutrosophic Duplets and Neutrosophic Triplets are well-known. This paper defines Plithogenic Duplets and Plithogenic Triplets as extensions of these concepts using the Plithogenic Set framework and briefly examines their relationship with existing concepts.

Some Types Of Hyperneutrosophic Set (2): Complex, Single-Valued Triangular, Fermatean, And Linguistic Sets, Takaaki Fujita, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

This paper is a continuation of the work presented in [35]. The Neutrosophic Set provides a mathematical framework for managing uncertainty, characterized by three membership functions: truth, indeterminacy, and falsity. Recent advancements have introduced extensions such as the Hyperneutrosophic Set and SuperHyperneutrosophic Set to address more complex and multidimensional challenges. In this study, we extend the Complex Neutrosophic Set, Single-Valued Triangular Neutrosophic Set, Fermatean Neutrosophic Set, and Linguistic Neutrosophic Set within the frameworks of Hyperneutrosophic Sets and SuperHyperneutrosophic Sets. Furthermore, we investigate their mathematical structures and analyze their connections with other set-theoretic concepts.

Soft Directed N-Superhypergraphs With Some Real-World Applications, Takaaki Fujita, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

This paper introduces the Directed Soft Super Hyper Graph, a unified framework for modeling complex, multi-layered directed networks. It combines directionality, recursive hyperstructure, and soft-set parameterization to address the integration of Soft Super HyperGraphs and Directed SuperHyperGraphs, which remains largely unexplored. The paper provides formal definitions, core operations, and real-world examples, such as urban infrastructure and transportation networks, to demonstrate the framework's effectiveness in managing deep hierarchies and uncertain relationships simultaneously.

Beyond Dialectics, Paradoxes, And Binary Logic, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Philosophy, long defined by its pursuit of truth, has historically been a battleground for dichotomies: truth vs. falsehood, materialism vs. idealism, reason vs. emotion. These oppositions often provide a framework for understanding philosophical discourse, but they fail to capture the full nuances of reality. To challenge these binary oppositions, I introduced the neutrosophic perspective in philosophy, rooted in Mathematics, and Many-Valued Logics.1 By emphasizing the interrelation of affirmation, negation, and neutrality, neutrosophy allows for the reconciliation of seemingly irreconcilable viewpoints, providing a new lens through which to reinterpret age-old philosophical questions.

When Emotions Flare: Solar Rhythms, Emotions And Cycles Of Political Revolution, Andreas Hernandez, Carolina Zilli Vieira, Alexandra Smith, Rebecca Olson

Geography and Environmental Studies Faculty Publications

Revolutions are among the most transformative events in human history. Analyzing 395 revolutionary episodes from 1900 to 2014, we find that major waves cluster around solar maxima - periods of intensified geomagnetic activity. Drawing on biomedical research linking geomagnetic disturbances to cardiovascular and stress regulation, and thus to emotional states, we propose that solar cycles modulate the affective ecologies within which revolutions arise. Solar activity may accelerate, shape, and amplify revolutionary cycles by heightening emotional climates and tipping fragile systems toward mass mobilization. This reframes revolutions as planetary events - entanglements of political conflict, embodied emotion, and cosmic …

Leaf-Based Varietal Categorization Of Sweetpotato (Ipomoea Batatas L. Lam.), A Potentially Healthful Vegetable, Using Image Processing And K-Means Clustering, Shahidul Islam, Md Towfiqur Rahman, Md Hamidul Rahman, Abdul Momin

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Sweetpotato (Ipomoea batatas Lam) leaves contain higher concentrations of phenolic compounds, flavonoids, and carotenoids that are remarkable in health promotion. However, the nutrient content in sweetpotato leaves varies from variety to variety, and leaf shape and color are the key identifying factors for the varietal classification of sweetpotatoes. So, detecting sweetpotato leaves is essential for the in-situ identification of sweetpotato varieties and for developing intelligent agricultural systems. This study aimed to create a leaf-shape-based varietal classification technique for sweetpotato using image processing techniques coupled with a K-means clustering algorithm. 38 leaf images (RGB) of two sweetpotato cultivars were collected …

The Signal Of Airplane Combustion In Soil At A Small Airport In Ohio, Rachel Engels

Williams Honors College, Honors Research Projects

Leaded gas has been banned for automobile use in the interest of public health since 1996. However, leaded gas is still used for small piston aircraft so the engine can run safely. To investigate potential environmental impacts of leaded gas, 90 soil samples were taken from around a small airport in Ohio. Soil elemental composition was measured by X-ray fluorescence (XRF), soil organic content determined by Loss-on-Ignition (LOI), and soil ferrimagnetic content measured by magnetic susceptibility. There is an unmistakable airplane fuel combustion signal in the soil at the ends of the runway, where aircraft wait to take off on …

Insights On The Cranial Anatomy And Osteohistology Of Cyonosaurus, Alexander Acker

Dissertations

This study investigates the cranial anatomy and life history of the small-bodied gorgonopsian Cyonosaurus. Previous research on gorgonopsians has disproportionately focused on larger members of the clade, leaving smaller forms relatively understudied. This gap has led to several unresolved questions, the most pressing of which concerns gorgonopsian ontogeny. Specifically, it remains unclear whether small-bodied gorgonopsians represent genuinely diminutive adult individuals or juveniles of larger species. The specimen NHCC LB1087 presents an ideal opportunity to address this issue and gain new insights into the biology of small-bodied gorgonopsians. The first chapter focuses on cranial anatomy. Due to the specimen’s preservation, many …

Depletion Of Adipose Stroma-Like Cancer-Associated Fibroblasts Potentiates Pancreatic Cancer Immunotherapy, Joseph Rupert, Alexes Daquinag, Yongmei Yu, Yulin Dai, Zhongming Zhao, Mikhail G Kolonin

Faculty, Staff and Student Publications

This study shows that populations of CAFs have distinct effects on pancreatic cancer progression and shows that depletion of CAFs expressing adipose markers potentiates tumor/metastasis suppression effects of immune checkpoint blockade.

Effects Of Chain Length, Saturation, And Bases On Saponification, Sarah Fenik

Williams Honors College, Honors Research Projects

This project will analyze the effects of chain length and saturation of fatty acids on saponification processes, as well as the effects of the base used in the reaction. Stearic acid, lauric acid, and oleic acid will be used for the fatty acid comparisons, and sodium hydroxide and potassium hydroxide will be used for the base comparisons. Stearic acid is considered a long chain fatty acid, while lauric acid is considered a short chain fatty acid. Oleic acid is a monounsaturated fatty acid. Five soap products are be made: sodium stearate, sodium laurate, sodium oleate, potassium stearate, and potassium oleate. …

User Interface For Custom Car Infotainment Systems, Dylan Miller

Williams Honors College, Honors Research Projects

The infotainment system is often considered one of the most functional and luxurious aspects of modern cars, containing functions that are useful to drivers in ways that range from convenient to safety-enhancing. However, modern infotainment systems can have some drawbacks such as making it more difficult to repair the vehicles they are in, helping to artificially limit the lifespan of the vehicles they are in, and not being present in most vehicles more than 15 years old. The software described in this paper, OpenQarUI, seeks to be a part of a solution to these problems. It is a piece of …

Advancing Generative Ai In 3d And 4d Spaces, Hasan Iqbal

Wayne State University Dissertations

Generative Artificial Intelligence (AI) has transformed how we synthesize, edit, and manipulate complex data, opening new possibilities for immersive digital content. This dissertation, titled “Advancing Generative AI in 3D and 4D Spaces,” investigates the capabilities and limitations of state-of-the-art generative models in static 3D scenes and time-aware 4D environments. In the 3D setting, scene editing is hindered by multi-view inconsistency and the high computational cost of per-scene retraining. To address these issues, the work introduces Free-Editor, a training free approach that utilizes an Edit Transformer to propagate a single edited view across all camera perspectives without additional optimisation, delivering prompt …

Interaction Of Cardiac Leiomodin With The Native Cardiac Thin Filament, Madison Little, Cristina M. Risi, Tania M. Larrinaga, Mason D. Summers, Tyler Nguyen, Garry E. Smith Jr., Jennifer Atherton, Carol C. Gregorio, Alla S. Kostyukova, Vitold E. Galkin

Department of Biomedical and Translational Sciences Faculty Publications

Every heartbeat depends on cyclical contraction-relaxation produced by the interactions between myosin-containing thick and actin-based thin filaments (TFs) arranged into a crystalline-like lattice in the cardiac sarcomere. Therefore, the maintenance of thin filament length is crucial for myocardium function. The thin filament is comprised of an actin backbone, the regulatory troponin complex and tropomyosin that controls interactions between thick and thin filaments. Thin filament length is controlled by the tropomodulin family of proteins; tropomodulin caps pointed ends of thin filaments, and leiomodin (Lmod) promotes elongation of thin filaments by a “leaky-cap” mechanism. The broader distribution of Lmod on the thin …

Procedural Terrain Generation: Noise Functions, Modern Methods, And Style Transfer, Hunter Barton

EWU Masters Thesis Collection

Procedural terrain generation, the algorithmic creation of digital terrain, finds use in multiple types of digital media. As the capabilities of modern computation increase, the ability to create more and more realistic terrains fully procedurally at scale improves. Modern methods of procedural generation have also overlapped with these advances, most notably advances in hardware. To account for this, a survey was done of modern methods for procedural terrain generation. Smooth procedural noise functions are one of the backbones of procedural terrain generation. Perlin noise, value noise, and fractal noise were explored in-depth. These noise functions were also tested for capabilities …

Bridging Prairie Restoration And Regenerative Agriculture With Compost Tea / The Rocket Incident: Post-Fire Soil Microbe Recovery On The Eastern Washington University Restoration Site, April Hersey

EWU Masters Thesis Collection

Inland Pacific Northwest prairie is an endangered ecosystem that has been reduced by conversion to agriculture. There is growing interest in the role of soil microorganisms in prairie ecosystems, which may be crucial for restoration of the plant community through interspecies interactions within the rhizosphere. One method for improving soil microorganism community composition is compost tea: enriched liquid compost extract. Compost tea is used in regenerative agriculture to improve crop yields and protect against pathogens. While research has supported compost tea application in regenerative agriculture, it has not been widely studied in the context of ecosystem restoration. After beginning a …

Improving The Performance Of Multi-Stakeholder Partnerships For Sustainable Development In Coastal Areas : Sweden (Hanö Bay) As A Case Study, Jennie Larsson

World Maritime University Ph.D. Dissertations

Coastal areas are vital for both ecosystems and human societies. Comprising diverse terrestrial, freshwater, and marine ecosystems, coastal areas provide us with essential resources and services. However, these areas are under threat from human activities and climate change, necessitating new governance structures to ensure their sustainable management and conservation. This research investigates how to improve the performance of local multi-stakeholder partnerships (M-SPs) in coastal areas, promoted as key mechanisms for achieving sustainable development goals. By drawing on stakeholder theory and using Pattberg & Widerberg’s (2014) analytical framework with nine building blocks for successful M-SPs as a foundation, the study examined …

Hydrogen-Enriched Lng As A Mid-Term Solution To Mitigate Greenhouse Gas Emissions From Shipping, Kang-Ki Lee

World Maritime University Ph.D. Dissertations

In light of the International Maritime Organization’s (IMO) ambitious Initial GHG Strategy, the rise in international shipping’s carbon dioxide emissions by 2 percent in 2022 compared to 2019 poses a formidable challenge. This increase underscores the pressing need to address the limited availability of green hydrogen, prompting the exploration of mid-term solutions to bridge this critical gap. The IMO’s 2023 Strategy on Reduction of GHG Emissions from Ships attempted to tackle this challenge head-on, recognizing the urgency of reducing the industry’s substantial carbon footprint. While hydrogen offers a simple solution as a zero-carbon fuel, LNG remains the most widespread alternative …

Digital Transformation Of Education: An Integrated Framework For Metaverse, Blockchain, And Ai-Driven Learning, Mousa Al-Kfairy, Omar Alfandi, Ravi S. Sharma, Saed Alrabaee

All Works

The integration of Metaverse, Blockchain, and Artificial Intelligence (AI) has the potential to revolutionize the educational landscape by providing immersive, secure, and personalized learning environments. This study proposes a conceptual framework that combines these technologies to address the key challenges faced by contemporary education systems, including accessibility, engagement, security, and personalization. The Metaverse serves as the immersive platform, offering virtual classrooms, interactive simulations, and gamified learning experiences. Blockchain provides the foundation for secure and transparent academic records, enabling tamper-proof credential verification and decentralized data management. AI enhances the educational experience by powering adaptive learning systems, predictive analytics, and intelligent tutoring …

European Air Pollution And The Proposed Timelines Of Implementing The World Health Organization 2021 Air Quality Guidelines Ca3., Lukia Hartin

ICT

This research examines Ireland’s air pollution trends and evaluates whether current reductions in PM2.5, PM10, and NO₂ are sufficient to meet the WHO 2021 Air Quality Guidelines by 2040. Using four years of EPA-validated pollutant data (2020–2023), alongside Building Energy Rating (BER) and national transport datasets, the study applies the CRISP-DM methodology to guide analysis, preprocessing, modelling, and evaluation. Extensive data cleaning and alignment were required due to inconsistent station coverage, varying formats, and missing values. Forecasting models—including Random Forest, Gradient Boosting, SVR, and linear regression—were assessed using MSE, R², and trend significance to project pollutant levels across different Irish …

Analysis Of The Patterns And Features Importance In Predicting Demand For Sustainable Urban Mobility. A Comparative Analysis Of Machine Learning Models Using The Dublin Bikes Dataset., Wojciech Sochanski

ICT

This study explores the application of machine learning models to predict demand in the Dublin bike-sharing scheme. A comprehensive literature review examines prior work on sustainable urban mobility, the evolution of bike-sharing schemes, the application of machine learning in predictive analytics and relevant case studies. Secondary data were gathered from publicly available sources, pre-processed and merged into a single, unified dataset. Exploratory data analysis was conducted before preparing the data for modelling to assess the data quality, with a focus on missing values.

Four predictive machine learning models – Linear Regression (LR), Decision Tree (CART), Random Forest (RF) and Gradient …

Dogs Emotion System, Muhammad Anas Baig

ICT

For our capstone project, we built a machine learning model that can look at pictures of dogs and figure out how they’re feeling, like if they’re happy, sad, or just chill. The idea came from how important pets are in people’s lives these days and how cool it would be to actually understand their emotions better using tech. This system will allow users to upload images of dogs, which are then analysed by a trained model to classify the dog's emotional states such as happy, sad, or neutral. We followed the CRISP-DM process to build it, which basically means we …

Development Of A Deep Learning Model For Synthetic Vs. Real Image Classification Synthetic Vs. Real Image Classification, Bernardo Gandara, Ignacio Varela

ICT

The advancement of generative AI technologies has made it increasingly difficult to distinguish synthetic images from authentic ones. This capstone project addresses the challenge by developing a binary image classification model using deep learning techniques to differentiate AI-generated images from real photographs. Guided by the CRISP-DM methodology, we employed the DeepGuardDB dataset, consisting of 13,000 balanced image samples, evenly split between real and synthetic sources. We implemented and compared three Convolutional Neural Network (CNN) architectures through transfer learning, standardising input pipelines and integrating custom classification heads. Following a performance evaluation across multiple metrics, the best-performing model was selected for further …

Multi-Source Remote Sensing–Based Soil Moisture Prediction Using Machine Learning, Niraj Neupane

Electronic Theses and Dissertations

Soil moisture (SM) plays a central role in climatic and environmental processes, influencing shear strength of soil, agricultural productivity, land–atmosphere interactions, and hydrologic functioning. However, accurately estimating SM across diverse climatic regions remains challenging due to spatial heterogeneity, limited in situ measurements, and inconsistencies in sensor resolution. Machine learning (ML) and remote sensing offer promising avenues for improving SM prediction, yet many existing approaches struggle with generalization across climatic gradients and often fail to capture temporal variability. This study integrates multi-source satellite and climate datasets, including SMAP L4_SM, MODIS land surface temperature, Daymet meteorological variables, and in situ observations from …

Quantifying Avian And Vegetation Communities On Agricultural Conservation Easement Wetlands In Eastern South Dakota, Katherine Millman

Electronic Theses and Dissertations

The Prairie Pothole Region of eastern South Dakota contains numerous small depressional wetlands, colloquially known as potholes, that provide important ecosystem services, including water storage, water quality improvement, and wildlife habitat. The Agricultural Conservation Easement Program (ACEP) was established by the U.S. Department of Agriculture to protect and restore wetlands and grasslands on private land through easements such as Wetland Reserve Easements. Although ACEP requires management practices intended to maintain or improve habitat quality, few studies have evaluated their effectiveness at supporting wildlife communities and vegetation integrity. To address this gap, we evaluated wetlands at 30 ACEP sites and 20 …

Enhancing Alfalfa Persistence In Rangelands: Evaluating Morphological Traits Of Medicago Sativa Subsp. Falcata Germplasm, Abdulallah Mohammed Alomair

Electronic Theses and Dissertations

Rangelands cover nearly half of the Earth’s surface, representing about 54% (79 million km2), and occur in different types and climates worldwide. Alfalfa (Medicago sativa L.) is a major component in rangelands and covers about (320 thousand km2), representing about 0.4% of total global rangeland area. As a critical perennial legume crop, alfalfa can improve soil health by fixing approximately 336 kg/ha/year of nitrogen and sequestering up to 614 kg/ha/year of carbon, while enhancing livestock production due to its high content level of vitamins, magnesium, minerals, fiber, and protein. However, environmental stresses such as drought, freezing, and grazing limit alfalfa …

A New Deepfake Detection Method With No-Reference Image Quality Assessment To Resist Image Degradation, Jiajun Jiang, Wen-Chao Yang, Chung-Hao Chen, Timothy Young

Electrical & Computer Engineering Faculty Publications

Deepfake technology, which utilizes advanced AI models such as Generative Adversarial Networks (GANs), has led to the proliferation of highly convincing manipulated media, posing significant challenges for detection. Existing detection methods often struggle with the low-quality or compressed press, which is prevalent on social media platforms. This paper proposes a novel Deepfake detection framework that leverages No-Reference Image Quality Assessment (NRIQA) techniques, specifically, BRISQUE, NIQE, and PIQUE, to extract quality-related features from facial images. These features are then classified using a Support Vector Machine (SVM) with various kernel functions. We evaluate our method under both intra-dataset and cross-dataset settings. For …

Three Essays On Sustainability Economics, Hélène Flore Nguemgaing

Graduate Theses, Dissertations, and Problem Reports (ETD)

As global economies face increasing resource dependencies and supply chain challenges, it becomes essential to understand the vulnerabilities that threaten economic stability. This dissertation investigates three empirical issues in agribusiness and critical minerals using econometric models to estimate the following: 1) the impact of supply chain disruptions on stock market returns during COVID-19; 2) the extraction of rare earth elements from acid mine drainage treatment by investigating the impacts of ownership and legislation in West Virginia and Pennsylvania; 3) China-to�FOBb (Free-on-Board) price transmission in rare earth elements markets: a copula-based dynamic tail dependence analysis.

The first essay evaluates how events …