Physical Sciences and Mathematics Commons^™

Neutrosophic Graded Jordan–Bialgebra Framework For Ai-Driven Analysis, Mona Gharib, Rana Muhammad Zulqarnain, Xiao Long Xin, Muhammad Gulistan, Muhammad Abid

Neutrosophic Systems with Applications

Modern Artificial Intelligence (AI) systems face significant challenges in processing and analyzing datasets characterized by high degrees of uncertainty, ambiguity, and indeterminacy, which are prevalent features in complex real-world scenarios. To address this limitation, this study introduces a novel neutrosophic graded Jordan–bialgebra framework. This framework strategically integrates the inherent structural properties of Jordan–Bialgebras with the advanced capability of Neutrosophic Graded Structures to simultaneously model degrees of truth, indeterminacy, and falsehood. The primary objective of this study is to establish a rigorous algebraic foundation that enables AI models to perform a more robust and comprehensive analysis of data containing incomplete or …

Comprehensive Risk Evaluation Framework For Reducing Errors In Critical Airport Systems, Arshad Hameed, Muhammad Umer Farooq

Neutrosophic Systems with Applications

Airports are intricate systems that are subject to a number of operational hazards that might impair safety and cause service interruptions. There is a dearth of thorough approaches designed specifically for airport operations, despite a wealth of research on risk management in several industries. In order to anticipate and prevent breakdowns in vital airport systems, we offer a thorough risk assessment approach that combines quantitative evaluation and human factor analysis. This study uses the decision-making methodology such as MARCOS method to rank the alternatives. The criteria weights are computed in this study. This study uses six criteria and 14 alternatives.

Integrated Neutrosophic Set For Assessing The Route Options In Overweight Complex Transportation Planning Scenarios, Muhammad Abid, Tayyaba Akhtar, Harshit Bhatt

Neutrosophic Systems with Applications

Due to improvements in lifting and transportation technology that enable the long-distance movement of heavy loads, overweight and oversized transport (O&OT) has emerged as one of the most important aspects of project logistics. This kind of transportation operation, also known as abnormal transportation, is heavily influenced by external variables like weather, traffic density, and legal regulations, as well as technical factors like the load’s weight and geometry, road surface, axle load limitations, slope, and ground strength. Decision-Makers (DMs) and practitioners who plan and carry out operations without giving these variables and factors enough thought may cause operational delays, significant hazards, …

Evaluating Solar Energy Challenges And Strategies To Overcome Challenges Under Neutrosophic Decision Making Methodology, Ahmed A El-Douh, Mina Samir Shenouda

Neutrosophic Systems with Applications

Because of its reliance on fossil fuels and fast population expansion, the nation confronts severe socioeconomic problems that can result in political instability, environmental damage, health issues, and economic instability. A switch to clean energy is now necessary as a result of these problems widening the gap between supply and demand for energy. To close this gap, photovoltaic (PV) technology holds great potential. In order to reduce bias and handle ambiguity while assessing solar energy (SE) issues and regulations, this study offers a decision-making process in a single valued neutrosophic set (SVNS) environment. The neutrosophic set is used to overcome …

Evaluation Of Integrating Smart Technologies Into Business Ecosystems Using Neutrosophic Uncertainty Model, Kainat Muniba, Muhammad Naveed Jafar, Adil Ahmad, Aruna Pavate

Neutrosophic Systems with Applications

This study proposes a methodological framework for Evaluation of Integrating Smart Technologies into Business Ecosystems. We use the decision-making process to deal with different criteria and alternatives. The decision-making process is used under the neutrosophic set to overcome uncertainty information. Neutrosophic set has three membership functions such as truth, indeterminacy, and falsity. These functions are used to overcome vague information. The average method is used to compute the criteria weights. The COBRA method is used to rank the alternatives based on different alternatives. This study uses 8 criteria and 15 alternatives to be evaluated to show the best option.

Correlation With Car Density In Urban Environments And Its Influence On Chronic Obstructive Pulmonary Disease (Copd) Rates In The United States, Daniel Barreiro-Torres, Kedai Cheng

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Parameter Estimation And Simulation In Pollution-Induced Asthma Disease Model Using Physics-Informed Neural Networks, Aadi Gannavaram

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Spatial Model For Oyster Reef Growth With Sediment Interactions, Merryn E. Grindstaff

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Understanding The Spread Of Black Sigatoka Disease: A Deterministic And Stochastic Modeling Approach, Bernard Asamoah Afful, Luis F. Gordillo

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Modeling Sickle Cell Disease Using A Sleep-Pain-Inflammation Cycle, Milan Marsh

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Modeling The Probability Of N Clonal Rosettes In A Bromeliaceae Genetic Individual, Erin N. Bodine, Layla K. Lammers

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Modeling And Analysis Of The Impacts Of The Rise In Ai Use On Data Center Growth, Resulting Workforce Displacement, And Environmental Impacts Through A Coupled System Of Ordinary Differential Equations Within A Feedback Framework, Divya Laddha, Alonso Gabriel Ogueda, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Using Compartmental Systems Of Ordinary Differential Equations And Optimal Control Theory To Compute Ideal Quantities Of Mentors For Student Populations, Timofey B. Gafurov

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Modeling Probiotic Bacterial Control Of White-Nose Syndrome In Little Brown Bat Colonies, Bethany Droubay, Alex Capaldi

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Compartmental Model For Diurnal Atlantic Stingray Migration, Rhianna Yates, Leah Glasser, Elena Wheatley, Christopher Hay-Jahans

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Mathematically Modeling Stoichiometric Drivers Of Heterotrophic N2 Fixation, Corday R. Selden, Rebecca Everett, Halvor H. Halvorson, Megan E. Berberich, Luca Schenone, Angela Peace, Renn Schipper, Edwin Cruz-Rivera, James Powell, Keisuke Inomura, Robinson W. Fulweiler, Amy M. Marcarelli, J Thad Scott

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Compartmental Model For Annual Bat Migration, Elena D. Wheatley, Rhianna Yates, Leah Glasser, Christopher Hay-Jahans

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Modeling The Impact Of Treatment During An Ongoing Tuberculosis Outbreak, Bach Le, Jude Shive, Erin N. Bodine

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Balancing Stability And Complexity In Boolean Models Of Biological Networks, Venkata Sai Narayana Bavisetty

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Compartmental Model For Periodic Animal Migration, Rhianna Yates, Leah Glasser, Elena Wheatley, Christopher Hay-Jahans

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Spatial Strategies In Ants: Modeling Polydomy, Saya Zeleznik, Fred Adler

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Optimizing The Distribution Of Fruiting Agave On Bat-Friendly Tequila Plantations, Grace Gorreck, Clarissa Azurin, Lois Carpenter

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Predicting An Uncertain Future: Conservation Easements And The Difficulties Created By Speculative Valuations, Travis L. Strickler

Kentucky Law Journal

No abstract provided.

Startup Success Forecasting Through Machine Learning: A Comprehensive Analysis Of It Startups, Khaled Abdulla Alhassani

Thesis/ Dissertation Defenses

Lately, startups attracted significant attention from investors throughout the previous years. This raised several questions concerning startups and what they possibly define as them. It could refer to collective individuals who focus on innovative ideas with a reproducible and scalable business model; others refer to it as a newly established business. Nevertheless, all these definitions lead to a predictive question. Will these startups face success? This study explores startup success prediction methods, focusing on forecasting information technology startup (SIT) insights using Machine Learning (ML) models such as Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), K-Nearest Neighbor (k-NN), …

New Evidence Of Mid-Pleistocene Glaciations In The French Jura Mountains Using Debris Flow Deposits And U/Th Dating Of Speleothems (Verneau Karst Network), Margot Vivier, Stéphane Jaillet, Eglantine Husson, Edwige Pons Branchu, Jean-Baptiste Charlier

International Journal of Speleology

We redefine the extent of former glaciers in the northern Jura Mountains through the study of endokarst deposits. Sedimentary deposits (pebbly debris flows, laminated clays, and allochthonous limestone blocks) and chemical deposits (speleothems) were identified and studied using three complementary approaches: (i) detailed geomorphological mapping, (ii) petrographic analysis, and (iii) U/Th-dating. In addition, a surface geomorphological analysis made it possible to calculate the minimum erosion time required for the formation of the sinkhole linked to the underground study site. The study site is the Dolois Chamber, an underground site upstream of the Verneau karst network (Doubs Department, France). The combined …

Detecting Burned Vegetation Areas By Merging Spectral And Texture Features In A Resnet Deep Learning Architecture, Jiahui Fan, Yunjun Yao, Yajie Li, Xueyi Zhang, Jiquan Chen, Joshua B. Fisher, Xiaotong Zhang, Bo Jiang, Lu Liu, Zijing Xie, Luna Zhang, Fei Qiu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Timely and accurate detection of burned areas is crucial for assessing fire damage and contributing to ecosystem recovery efforts. In this study, we propose a framework for detecting fire-affected vegetation anomalies on the basis of a ResNet deep learning (DL) algorithm by merging spectral and textural features (ResNet-IST) and the vegetation abnormal spectral texture index (VASTI). To train the ResNet-IST, a vegetation anomaly dataset was constructed on high-resolution 30 m fire-affected remote sensing images selected from the Global Fire Atlas (GFA) to extract the spectral and textural features. We tested the model to detect fire-affected vegetation in ten study areas …

Infographic: Pisa Insights – Encouraging Mathematical Thinking, Dominique Russell

Teacher infographics

Each cycle of the global Programme for International Student Assessment (PISA) includes a teacher questionnaire. One questionnaire topic – encouraging mathematical thinking – can help foster critical thinking, enhance problem-solving skills and allow students to see the relevance and connectedness of mathematics in their lives.

An Analysis Of Large Language Model Hallucination And Creativity: Linear Representations And Causal Roles, Mckay Bowcut

Theses and Dissertations

Large language models (LLMs) show remarkable abilities in both factual and creative tasks, yet the problem of hallucination persists despite advances in training and post-training methods. Recent progress in model interpretability suggests that model behavior can be predicted and influenced by analyzing and manipulating internal activations. In this thesis, we address three questions: (1) Can we identify linear representations of hallucination and creativity in the model’s latent space? (2) Do these representations play a causal role in model behavior when manipulated? (3) Are creativity and hallucination causally intertwined? To answer these, we construct a novel dataset of factual, hallucinated, and …

From The Editors, Rully Karim Dr.

Journal of Project Management & Construction

The Journal of Project Management and Construction (JPMC) is a peer-reviewed publication dedicated to advancing the field of project management and construction, grounded in the principles outlined in the PMBOK 6th Edition. Our focus encompasses the ten knowledge areas essential to successful project management: Integration, Scope, Schedule, Cost, Quality, Resource, Communications, Risk, Procurement, and Stakeholder Management.

JPMC publishes original research papers written in English that provide deeper insights into these knowledge areas and contribute to the development of best practices in project management and construction. Submissions may include theoretical analyses, computational models, experimental observations, or a combination of both theoretical …

Statistical Challenges And Simulation Results For Pilot Clinical Trials, Weiliang Cen

USF Tampa Graduate Theses and Dissertations

Background: The effect size estimated from a pilot trial is often an inaccurate reflection of the true effect size observed in a large trial, leading to either underestimation or overestimation. Published data suggest that effect sizes from large trials are typically smaller than those reported in their corresponding pilot trials. To address this discrepancy, conservative or discount adjustment methods are widely recommended to modify pilot trial effect sizes when calculating sample sizes, thereby maintaining adequate statistical power. This study aims to assess effect sizes from both pilot and large trials and to evaluate the performance of existing adjustment methods.

Methods: …