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The Distinguishing Number of Some Special Kind of Graphs
Get PDFIn the present study, the distinguishing number of some different graphs is examined where different graphs like the coconut tree graph, firecracker graph, jellyfish graph, triangular book graph, and banana tree graph have been taken into account. The major goal of the proposed study is to understand the distinguishing number of different graphs for better insights. It is evident from the results that the distinguishing numbers and automorphism groups of the above-mentioned graphs have been carried out successfully
Some Generalizations of Corona Product of Two Graphs
Get PDFIn this paper we are seeking to conceptualize the notion of corona product of two graphs to contrive some special types of graphs. That is, here our attempt is to regenerate a familiar graph as a product graph. We are considering seven familiar graphs here to reconstruct them with the help of corona product of two graphs. Such types of families of the graphs and operations can be used to study biological pathways as well as to find the optimal order and size for the special types of graphs
A Novel Fuzzy Time Series Forecasting Method Based on Probabilistic Fuzzy Set and CPBD Approach
Get PDFProbabilistic fuzzy set is used to model the non-probabilistic and probabilistic uncertainties simultaneously in the system. This study proposes a cumulative probability-based discretization and probabilistic fuzzy set based novel fuzzy time series forecasting method. It also proposes a novel discretization approach based on cumulative probability to tackle the probabilistic uncertainty in partitioning of datasets. Gaussian probability distribution function has been used to construct probabilistic fuzzy set. The advantage of the proposed work is that it addresses the uncertainties due to randomness and fuzziness simultaneously and also improves accuracy rate in time series forecasting. A proposed forecasting method is applied on two time series data set of enrollments of University of Alabama and Taiwan Exchange (TAIEX). A reduction of the amount of average forecasting error rate (AFER) and root mean square error (RMSE) shows the proposed method outperforms over other existing forecasting methods
Addressing The Mathematical Achievement Gap Through Improvements In School Facilities: The Case Of Fort Bend Isd School District In Texas
Get PDFIn 1966, Americans were introduced to the term achievement gap by James S. Coleman, a Johns Hopkins sociologist. Coleman et al.’s (1966) study explained most of the gap between the achievement of America’s White and Black students. Since that study was published, scholars have identified strategies to close the achievement gap. Accordingly, my research investigated the possibility of using the quality of school facilities as a potential strategy to enhance learning equity across racial categories. My findings may fuel policies targeting the development of local communities through inclusive learning achievements.
My empirical methodology was sustained by an expanded theoretical framework that considered schooling, or quality of education, as an output that derives from a combination of inputs, including the quality of facilities. The main dataset contained information from a Texas school district with over 80,000 students. I used the State of Texas Education Agency (TEA)
students’ categorization and measured their performance using the State of Texas Assessments of Academic Readiness (STAAR) exam results. The results of a comprehensive survey conducted by a consulting firm were used as a measure of the building condition. Alternative datasets were used to check the robustness of the findings.
Keywords: achievement gap, facilities, academic outcome
Enhancing Ai Ethics Through Integrating Aif360 With Generative Ai
Get PDFIn recent years, Artificial Intelligence (AI) has brought about significant positive changes in people\u27s lives with respect to convenience and efficiency. The primary aim of AI is to emulate human intelligence in machines, creating a system capable of thinking and replicating human cognitive functions. AI encompasses tasks that mirror human behaviors, such as visual perception, speech recognition, and language translation.
The realm of AI ethics is an evolving and interdisciplinary field dedicated to addressing ethical considerations in AI. The establishment of ethical standards for AI is vital for developing morally upright AI systems and ensuring ethical conduct in AI applications. Fairness AI strives to recognize and mitigate bias throughout the entire life cycle of AI technique development, spanning data curation and preparation, modeling, evaluation, and deployment. However, two concerns have been raised regarding current efforts: first, existing endeavors seem to lack a thorough and comprehensive evaluation of the effectiveness of techniques in mitigating bias; second, existing work has not fully explored enhancing bias mitigation techniques via generative AI.
This dissertation conducts a comprehensive evaluation of the effectiveness of reweighing samples with the addition of AI generated data in addressing bias associated with traditional machine learning models, utilizing the AI Fairness 360 (AIF360) framework. The reweighing process is conducted with respect to privileged attributes such as sex and race. Subsequently, each traditional machine learning model undergoes classification tasks on both the original datasets and the new datasets resulting from reweighing samples.
In addition, this dissertation explores the potential of diffusion models to generate synthetic tabular data to improve AI fairness. The Tabular Denoising Diffusion Probabilistic Model (TabDDPM), a diffusion model adaptable to any tabular dataset and capable of handling various feature types, was utilized with different amounts of generated data for data augmentation. Additionally, reweighting samples from AIF360 was employed to further enhance AI fairness. Experimental results demonstrate that the synthetic data generated by TabDDPM improves fairness in binary classification.
Index Terms: Artificial Intelligence, AIF360, Generative AI, Reweighting
(R2117) Cost Optimization of Queueing System with Differentiated Vacations and Reneging of Customers
Get PDFThis manuscript deals with an infinite-capacity queueing system under multiple differentiated working vacations and customers’ impatience. The first vacation is assumed to be a working vacation where the server, instead of being idle, serves the customers at a lower rate. In contrast, the second one is considered a non-working vacation of a different duration. The customers may leave the system at any time due to long delays in service during vacations but, via some convincing mechanisms, they are retained in the system. The operating characteristics of the system are obtained in a steady state. The results obtained are illustrated numerically and graphically with the help of MATLAB software. The cost model is formulated for the proposed system, and the optimal cost is obtained relative to the service rate
(R2098) Dynamic Analysis of Stochastic Leslie-Gower Biological Predator-Prey Model with Prey Cannibalism
Get PDFIn this paper, we study the dynamical analysis of a stochastic Leslie–Gower biological predator– prey model. Earlier, the Leslie–Gower model was studied in the context of biological systems, including cases involving cannibalism. In our model, we investigate the dynamic properties of a stochastic Leslie–Gower predator–prey ecological system using the stability of invariant measures on invariant sets, where the invariant measures are shown to be ergodic. We also conduct a threshold analysis to study the stochastic persistence and extinction of species. Stochastic bifurcation is also examined. The theoretical results are supported by numerical simulations and examples. Intra-species competition is considered and described through theoretical analysis. The numerical results provide insights for modeling new stochastic ecological systems. Simulations are carried out to verify all the results
(R2111) Effect of Stenotic-Aneurysmal Arterial Regime on Unsteady Magnetohydrodynamic Non-Newtonian Blood Flow with Heat Radiation
Get PDFThe study aims to investigate the effect of magneto-hydrodynamic on a non-Newtonian unsteady blood flow with internal heat energy in the presence of blood ironic properties characterized by stenosis. The formulated mathematical equations resulted in differential forms and were solved analytically by Differential Transform Method. The obtained solutions were displayed by graphs showing different flow physiognomies like blood velocity, temperature profile, Nusselt number, wall shear stress and stream function.
The results indicated that velocity profile increases as magnetic field, Darcy number and aneurysmal artery rise, while it decreases as heat radiation, Reynold number, and Casson parameter speedup. The temperature profile increases as magnetic field, and Reynold number rise.
Furthermore, wall shear stress increases as heat radiation increases but drops as Reynold number accelerates. This happens due to the fact that magnetic field on blood flow increases the viscosity of the blood flow that bring rise in the Lorentz force and Reynolds number indicates the significant dominance of viscous forces over inertial forces, which keeps the flow in the laminar path
PV Panther April 1969 Foreign Language Honor Society
No full texthttps://digitalcommons.pvamu.edu/dr-robert-alphonso-henry-professional/1001/thumbnail.jp
(SI13-06) Analysis of Some Unified Integral Equations of Fredholm Type Associated with Multivariable Incomplete H and I-Functions
Get PDFIn this research paper, we examine various effective methods for addressing the problem of solving Fredholm-type integral equations. Our investigation commences by applying the principles of fractional calculus theory. We employ series representations and products of multivariable incomplete H-functions and multivariable incomplete I-functions to solve these integrals. The outcomes derived from our analysis possess a general nature and hold the potential to yield numerous results