In probability theory generalizing distribution is an important area. Several distributions are inappropriate for data modeling, either symmetrical, semi-symmetrical, or heavily skewed. In this paper, a new compound distribution with four parameters called Marshall Olkin Marshall Olkin Weibull (MOMOWe) is introduced. Several important statistical properties of new distribution were studied and examined. The estimation of unknown four parameters was carried out according to the maximum likelihood estimation method. The flexibility of MOMOWe distribution is demonstrated by the adoption of two real datasets (semi-symmetric and right-skewed) with different information fitting criteria. Such flexibility allows using the new distribution in various application areas.
Vehicular Ad Hoc Networks (VANETs) are integral to Intelligent Transportation Systems (ITS), enabling real-time communication between vehicles and infrastructure to enhance traffic flow, road safety, and passenger experience. However, the open and dynamic nature of VANETs presents significant privacy and security challenges, including data eavesdropping, message manipulation, and unauthorized access. This study addresses these concerns by leveraging advancements in Fog Computing (FC), which offers lowlatency, distributed data processing near-end devices to enhance the resilience and security of VANET communications. The paper comprehensively analyzes the security frameworks for fog-enabled VANETs, introducing a novel taxonomy that c
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
The present paper concerns with the problem of estimating the reliability system in the stress – strength model under the consideration non identical and independent of stress and strength and follows Lomax Distribution. Various shrinkage estimation methods were employed in this context depend on Maximum likelihood, Moment Method and shrinkage weight factors based on Monte Carlo Simulation. Comparisons among the suggested estimation methods have been made using the mean absolute percentage error criteria depend on MATLAB program.
A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re
... Show MoreIn this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes
Improved oral bioavailability of lipophilic substances can be achieved using self-emulsifying drug delivery systems. However, because the properties of self-emulsifying are greatly influenced by surfactant amount and type, type of oil used, droplet size, charge, cosolvents, and physiological variables, the synthesis of self-emulsifying is highly complex; consequently, only a small number of excipient self-emulsifying formulations has been developed so far for clinical use. This study reports a highly effective procedure for developing self-emulsifying formulations using a novel approach based on the hydrophilic-lipophilic difference theory. Microemulsion characteristics, such as the constituents and amounts of oil and surfactant electrolyte
... Show MoreSummed up the idea of this research in an attempt to find the establishment of the knowledge convergence to show the features of verbal acts that occurred a prime location in the lesson deliberative theory book unique contract ( IbnAbdRabbaAndalusian ) to prove that Arabic was the old literary studies included many of the features of this theory in both theoretical and practical
The Plerion nebula is characterized by its pulsar that fills the center of the supernova remnant with radio and X-ray frequencies. In our galaxy there are nine naked plerionic systems known, of which the Crab Nebula is the best-known example. It has been studied this instance in order to investigate how the pulsar energy affect on the distribution and evolution of the remnant as well as study the pulsar kick velocity and its influence on the remnant. From the obtained results it's found that, the pulsar of the Crab Nebula injects about (2−3)𝑥 1047 erg of energy to the remnant, although this energy is small compared to the supernova explosion energy which is about 1051 erg but still plays a significant role in the distribution and the m
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