American scientific publishing group

As an extension of the fuzzy soft set, Ayman A. Hazaymeh presented the idea of the time-fuzzy soft set in his doctoral thesis in 2013. By introducing the Generalized Time-Fuzzy Soft Expert Set (GT-FSES) as an additional extension of the fuzzy soft set, we expand on this concept in this paper. We examine the most important functions of this new architecture, such as intersection, complement, union, and the logical operations "AND" and "OR." Additionally, we show how GT-FSES may be used practically to solve decision-making issues, providing a fresh method for managing complexity and ambiguity in decision-making processes.

This paper introduces the novel concept of single valued heptapartitioned neutrosophic sets (SVHNSs) which is the generalized version of the neutrosophic sets. This set consists of seven membership functions which are more sensitive to real-world problems. Membership functions are defined as an absolute true, relative true, absolute false, relative false, contradiction, unknown (undefined) and ignorance respectively. This scenario of indeterminacy provides a better accuracy. Moreover, several properties of this set are also addressed. This study focuses on the romantic sensations experienced by young boys and girls in a variety of contexts. The dataset supporting this study comprises individuals aged 18–25, with data collected from the Psychology Department at Peshawar University, Pakistan. This data was critically analyzed using the Single-Valued Heptapartitioned Neutrosophic Set (SVHNS). For a real-world application involving the romantic feelings of young individuals across various dimensions, machine learning and graphical algorithms—such as Encrypted K-Means Clustering, Encrypted K-Means Clustering Heat Map, Encrypted Elbow Method, Decrypted K-Means Clustering, Encrypted Correlation Matrix, and Decrypted Correlation Matrix—were applied and visualized. These algorithms assist in examining and developing relationships among various factors that influence the romantic feelings of young men and women. The proposed techniques offer new dimensions not only for psychological studies in general but also specifically for understanding emotional disorders and breakups in romantic relationships among university students.

In this article, we combined the Epanechnikov kernel function with the pareto distribution to produce the Epanechnikov-Pareto distribution (EPD). Some properties of this distribution are studied, like the moments, MLEs, reliability analysis functions, ordered statistics, and quintile function.

In this paper, we suggested a new transformation for the selection a sample with probability proportional to size measure with replacement under a positive correlation coefficient between the study variable and the measure of size variable . The relative efficiency of the proposed estimator has been studied under a super-population model. A numerical investigation into the performance of the estimator has been made.

This paper develops a fixed-point iteration method for maximum likelihood estimation of the shape parameter θ in the Epanechnikov-Pareto Distribution (EPD). Building on Banach’s contraction principle, we establish a computationally efficient algorithm that reformulates the MLE problem as a fixed-point equation. Numerical simulations demonstrate rapid convergence within 6-10 iterations, reducing geometric error from 0.325 to 4.04×10−7. The proposed method significantly outperforms conventional optimization techniques, requiring only 18 iterations compared to 145 for Nelder-Mead while maintaining equivalent accuracy. Bootstrap validation with 500 replications confirms estimator stability, yielding a narrow 95% confidence interval [0.324015, 0.340532] with standard deviation 0.004148. The fixed-point approach provides a robust framework for parameter estimation in heavy-tailed distributions, with applications in reliability engineering and financial modeling.