Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

In this paper, we establish the conditions of the occurrence of the local bifurcations, such as saddle node, transcritical and pitchfork, of all equilibrium points of an eco-epidemiological model consisting of a prey-predator model with SI (susceptible-infected) epidemic diseases in prey population only and a refuge-stage structure in the predators. It is observed that there is a transcritical bifurcation near the axial and free predator equilibrium points, near disease-free equilibrium point is a saddle-node bifurcation and near positive (coexistence) equilibrium point is a saddle-node bifurcation, a transcritical bifurcation and a pitchfork bifurcation. Further investigations for Hopf bifurcation near coexistence equilibrium point

Background. Bone healing is a complex and dynamic process that represents a well-orchestrated series of biological events of cellular recruitment, proliferation, and differentiation. The use of medicinal plants in bone healing has attracted increasing interest because of their lower side effects. Punica granatum seed oil (PSO) contains high levels of phenolic compounds, promotes osteoblast function, and plays an important role in bone remodeling. A gelatin sponge (Spongostan) is a hemostatic agent that is extensively applied as scaffolds in engineering and as drug carriers in the medical field. This study aimed to evaluate the effectiveness of PSO for bone healing enhancement. Twenty adult male New Zealand rabbits, weighing an avera

Background: The healing process involves the restoration of the body’s structural integrity. The extracellular matrix, blood cells, cytokines, and growth factors are all involved in this dynamic, intricate, multicellular process. Hemostasis, the inflammatory phase, the proliferative phase, and the maturation phase are all included. Opuntia ficus-indica oil (OFI) and Punica grantum (PGS) oil are extensively used natural treatments that are regarded as advantageous for their sedative, spasmolytic, and anti-inflammatory properties, as well as for angiogenesis promotion, fibroblast increase, collagen production and deposition, and extracellular-matrix remodeling. Materials and methods: Twenty-four New Zealand rab

The problem of steady, laminar, natural convective flow in an square enclosure with and without partitions is considered for Rayleigh number (103-106) and Prandtl number (0.7). Vertical walls were maintained isothermal at different temperatures while horizontal walls and the partitions were insulated. The length of partition was taken constant. The number of partitions were placed on horizontal surface in staggered arrangement from (1– 3) and ratio of partition thickness (H/L= 0.033, 0.083, 0.124). The problem is formulated in terms of the vorticity-stream function procedure. A numerical solution based on a program in Fortran 90 with the finite difference method is obtained. Representative results illustrating the effects of the thickn

The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

Intended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted

The increasing availability of computing power in the past two decades has been use to develop new techniques for optimizing solution of estimation problem. Today's computational capacity and the widespread availability of computers have enabled development of new generation of intelligent computing techniques, such as our interest algorithm, this paper presents one of new class of stochastic search algorithm (known as Canonical Genetic' Algorithm ‘CGA’) for optimizing the maximum likelihood function strategy is composed of three main steps: recombination, mutation, and selection. The experimental design is based on simulating the CGA with different values of are compared with those of moment method. Based on MSE value obtained from bot