The Modi Exponentiated Exponential Distribution

In this study, a new four-parameter distribution called the Modi Exponentiated Exponential distribution was proposed and studied. The new distribution has three shape and one scale parameters. Its mathematical and statistical properties were investigated. The parameters of the new model were estimated using the method of Maximum Likelihood Estimation. Monte Carlo simulation was used to evaluate the performance of the MLEs through average bias and RMSE. The flexibility and goodness-of-fit of the proposed distribution were demonstrated by applying it to two real data sets and comparing it with some existing distributions.

Marshall-Olkin Exponentiated Fréchet Distribution

In this paper, a new distribution called Marshall-Olkin Exponentiated Fréchet distribution (MOEFr) is proposed. The goal is to increase the flexibility of the existing Exponentiated Fréchet distribution by including an extra shape parameter, resulting into a more flexible distribution that can provide a better fit to various data sets than the baseline distribution. A generator method introduced by Marshall and Olkin is used to develop the new distribution. Some properties of the new distribution such as hazard rate function, survival function, reversed hazard rate function, cumulative hazard function, odds function, quantile function, moments and order statistics are derived. The maximum likelihood estimation is used to estimate the model parameters. Monte Carlo simulation is used to evaluate the behavior of the estimators through the average bias and root mean squared error. The new distribution is fitted and compared with some existing distributions such as the Exponentiated Fréchet (EFr), Marshall-Olkin Fréchet (MOFr), Beta Exponential Fréchet (BEFr), Beta Fréchet (BFr) and Fréchet (Fr) distributions, on three data sets, namely Bladder cancer, Carbone and Wheaton River data sets. Based on the goodness-of-fit statistics and information criteria values, it is demonstrated that the new distribution provides a better fit for the three data sets than the other distributions considered in the study.

Exponentiated Weibull大气湍流下混合RF/FSO系统容量分析

RF/FSO混合通信系统弥补了自由空间光通信受天气影响严重的问题,提高了系统的可用性。本文研究了Exponentiated Weibull大气湍流下双门限混合RF/FSO系统平均信道容量,考虑大气湍流和指向误差对平均信道容量的联合影响,利用Meijier G函数推导出平均信道容量的闭合表达式。根据平均信道容量闭合表达式进行了仿真,分析了在不同距离、大气湍流强度、抖动标准差和波束宽度条件下,平均信道容量随信噪比变化的关系。

基于Exponentiated Weibull湍流模型的OFDM光链路性能分析

研究了Exponentiated Weibull大气湍流下OFDM光链路误码性能,分别考虑大气湍流的单独影响及大气湍流和指向误差对误码率的联合影响,利用Meijer G函数推导出多载波条件下总平均误码率的闭合表达式。根据总平均误码率闭合表达式进行了仿真,分析了在不同大气湍流强度、QAM调制阶数、抖动标准差和波束宽度条件下,链路误码率随发射功率变化的关系。通过仿真分析证明仅在大气湍流影响下发射功率的增加对误码率的改善优于在大气湍流与指向误差的联合影响下;不同调制阶数,增大发射功率对链路误码性能的改善近乎相同;随着湍流强度、抖动标准差和波束宽度的增加,误码率增加。

Exponentiated Weibull大气湍流下PSK-OFDM机载光链路性能分析

本文研究了指向误差、气动光学效应及Exponentiated Weibull大气湍流联合效应对OFDM光链路通信性能的影响。其中OFDM链路采用PSK调制,应用Meijer G函数推导得到多载波条件下总平均误码率的闭合表达式。根据平均误码率闭合表达式进行了仿真,分析了不同大气湍流强度、PSK调制阶数、抖动标准差和波束宽度对误码率的影响。通过仿真分析证明基于Exponentiated Weibull大气湍流模型,在不同湍流强度条件下误码率随着发射功率的增加改善近似。当抖动标准差小于0.7及调制阶数小于4时,增大发射功率对改善链路误码率效果明显。

基于Exponentiated Weibull模型的M-PPM调制空间光链路误码性能

本文研究了Exponentiated Weibull大气湍流下光链路误码性能,考虑大气湍流和指向误差对误码率的联合影响,利用Meijier'G函数推导出误码率的闭合表达式。根据误码率闭合表达式进行了仿真,分析了在不同大气湍流强度、PPM调制阶数、抖动标准差和波束宽度条件下,链路误码率随发射功率变化的关系。通过仿真分析证明:不同调制阶数,增大发射功率对链路误码性能的改善近乎相同;随着湍流强度、抖动标准差和波束宽度的增加,误码率增加。

A Study on Mixture of Exponentiated Rayleigh and Exponentiated Exponential Distributions Based on Order Statistics

Mixtures of lifetime distributions occur when two different causes of failure arc present, each with the same parametric form of lifetime distributions. This paper is considered with the mixture model of exponentiated Rayleigh and exponentiated exponential distributions. The author＇s objectives are finding the statistical properties of the model and estimating the parameters of the model by using point estimation and interval estimation methods. First, some properties of the model with some graphs of the density function are discussed. Next, the maximum likelihood method of estimation is used for estimating scale and shape parameters of the model. Estimating the parameters is studied under complete and type II censored samples for different sample sizes. Asymptotic Fisher information matrix of the estimators for complete samples is founded with different sample sizes. The asymptotic variances of the maximum likelihood estimates are derived. Based on the asymptotic variances of the maximum likelihood estimates, interval estimates of the parameters are obtained. Some of the equations in this paper are solved by using numerical iteration such as Newton Raphson method by using Mathematica 7.0. The performance of findings in the paper is showed by demonstrating some numerical illustrations through Monte Carlo simulation study based on absolute relative bias and mean square error.

Maximum Likelihood Estimation of the Parameters of Exponentiated Generalized Weibull Based on Progressive Type II Censored Data

Exponentiated Generalized Weibull distribution is a probability distribution which generalizes the Weibull distribution introducing two more shapes parameters to best adjust the non-monotonic shape. The parameters of the new probability distribution function are estimated by the maximum likelihood method under progressive type II censored data via expectation maximization algorithm.

The exponentiated generalized power Lindley distribution: Properties and applications

In this paper, we introduce a new extension of the power Lindley distribution, called the exponentiated generalized power Lindley distribution. Several mathematical properties of the new model such as the shapes of the density and hazard rate functions, the quantile function, moments, mean deviations, Bonferroni and Lorenz curves and order statistics are derived. Moreover, we discuss the parameter estimation of the new distribution using the maximum likelihood and diagonally weighted least squares methods. A simulation study is performed to evaluate the estimators. We use two real data sets to illustrate the applicability of the new model. Empirical findings show that the proposed model provides better fits than some other well-known extensions of Lindley distributions.

Product Spacing of Stress–Strength under Progressive Hybrid Censored for Exponentiated-Gumbel Distribution

Maximum product spacing for stress–strength model based on progressive Type-II hybrid censored samples with different cases has been obtained.This paper deals with estimation of the stress strength reliability model R=P(Y<X)when the stress and strength are two independent exponentiated Gumbel distribution random variables with different shape parameters but having the same scale parameter.The stress–strength reliability model is estimated under progressive Type-II hybrid censoring samples.Two progressive Type-II hybrid censoring schemes were used,Case I:A sample size of stress is the equal sample size of strength,and same time of hybrid censoring,the product of spacing function under progressive Type-II hybrid censoring schemes.Case II:The sample size of stress is a different sample size of strength,in which the life-testing experiment with a progressive censoring scheme is terminated at a random time T 2 e0;1T.The maximum likelihood estimation and maximum product spacing estimation methods under progressive Type-II hybrid censored samples for the stress strength model have been discussed.A comparison study with classical methods as the maximum likelihood estimation method is discussed.Furthermore,to compare the performance of various cases,Markov chain Monte Carlo simulation is conducted by using iterative procedures as Newton Raphson or conjugate-gradient procedures.Finally,two real datasets are analyzed for illustrative purposes,first data for the breaking strengths of jute fiber,and the second data for the waiting times before the service of the customers of two banks.

Estimation under a Finite Mixture of Exponentiated Exponential Components Model and Balanced Square Error Loss

By exponentiating each of the components of a finite mixture of two exponential components model by a positive parameter, several shapes of hazard rate functions are obtained. Maximum likelihood and Bayes methods, based on square error loss function and objective prior, are used to obtain estimators based on balanced square error loss function for the parameters, survival and hazard rate functions of a mixture of two exponentiated exponential components model. Approximate interval estimators of the parameters of the model are obtained.

Statistical Inference of Stress-Strength Model for Exponentiated Pareto Model with Censored Data

The reliability of a system is discussed when the strength of the system and the stress imposed on it are independent and non-identical exponentiated Pareto distributed random variables with progressively censored scheme.Different interval estimations are proposed.The interval estimations obtained are exact,approximate and bootstrap confidence intervals.Different methods and the corresponding confidence intervals are compared using Monte-Carlo simulations.Simulation results show that the confidence intervals(CIs)of exact and approximate methods are really better than those of the bootstrap method.

Bayes Prediction of Future Observables from Exponentiated Populations with Fixed and Random Sample Size

Bayesian predictive probability density function is obtained when the underlying pop-ulation distribution is exponentiated and subjective prior is used. The corresponding predictive survival function is then obtained and used in constructing 100(1 – ?)% predictive interval, using one- and two- sample schemes when the size of the future sample is fixed and random. In the random case, the size of the future sample is assumed to follow the truncated Poisson distribution with parameter λ. Special attention is paid to the exponentiated Burr type XII population, from which the data are drawn. Two illustrative examples are given, one of which uses simulated data and the other uses data that represent the breaking strength of 64 single carbon fibers of length 10, found in Lawless [40].

Estimation Using Censored Data from Exponentiated Burr Type XII Population

Maximum likelihood and Bayes estimators of the parameters, survival function (SF) and hazard rate function (HRF) are obtained for the three-parameter exponentiated Burr type XII distribution when sample is available from type II censored scheme. Bayes estimators have been developed using the standard Bayes and MCMC methods under square error and LINEX loss functions, using informative type of priors for the parameters. Simulation comparison of various estimation methods is made when n = 20, 40, 60 and censored data. The Bayes estimates are found to be, generally, better than the maximum likelihood estimates against the proposed prior, in the sense of having smaller mean square errors. This is found to be true whether the data are complete or censored. Estimates improve by increasing sample size. Analysis is also carried out for real life data.

Gumbel-Exponentiated Weibull {Logistic} Lifetime Distribution and Its Applications

A new generalized exponentiated Weibull model called Gumbel-exponentiated Weibull {Logistic} distribution is introduced and studied. The new distribution extends the exponentiated Weibull distribution with additional parameters and bimodal densities. Some new and earlier distributions formed the sub-models of the proposed distribution. The mathematical properties of the new distribution including expressions for the hazard function, survival function, moments, order statistics, mean deviation and absolute mean deviation from the mean, and entropy were derived. Monte Carlo simulation study was carried out to assess the finite sample behavior of the parameter estimates by maximum likelihood estimation approach. The superiority of the new generalized exponentiated Weibull distribution over some competing distributions was proved empirically using the fitted results from three real life datasets.

Statistical Properties of The Exponentiated Nakagami Distribution

This paper is an improvement over beta-Nakagami distribution developed by Shittu and Adepoju （2013）. Here we propose the addition of one parameter to the two parameter continuous Nakagami-m distribution （Nakagami, 1960） that was designed for modeling the fading of radio signals. The resulting distribution referred to as Exponentiated Nakagami （ENAK） distribution is a generalization of the classical Nakagami distribution. The statistical properties of the proposed distribution such as moments, moment generating function, the asymptotic behavior among others were investigated. The method of maximum likelihood is used to estimate the model parameters and the observed information matrix is derived. A real data set is used to compare the new model with the class of Nakagami distributions. Our findings showed that the Exponentiated Nakagami distribution is more flexible than beta-Nakagami distribution with better representation and less computational effort.

Exponentiated Weibull大气湍流下航空激光通信性能分析

研究了Exponentiated Weibull(EW)大气湍流信道下航空激光通信的性能,综合考虑大气湍流及气动光学效应的影响,利用Meijer′s G函数推导出了航空激光通信链路的性能指标的闭合表达式,包括平均误码率(BER)、中断概率及平均信道容量。在不同的航空飞行条件下,根据平均BER、中断概率和平均容量闭合表达式分别给出了数值仿真实例,分析了航空飞行高度、传输距离、信噪比(SNR)与航空激光通信系统性能的关系,同时分析了孔径平均效应对航空激光通信链路性能改善作用。

基于改进YOLOv8-CEFG的垃圾检测算法研究

随着我国经济的高速发展和人口的急剧增加,生活垃圾污染问题日益突出。然而,传统的人工垃圾检测方法效率低且主观性强。为提高复杂场景下垃圾检测的准确率,文章提出了一种基于改进YOLOv8的垃圾检测模型。为提升检测精度和识别效果,引入了EMA(Exponential Moving Average)注意力机制。实验结果显示,YOLOv8-CEFG在垃圾检测数据集上表现优异,最终其mAP达到了88.8%,比原始YOLOv8模型提高了3.1%。YOLOv8-CEFG算法能较好地满足实时检测任务的需求,并展示了良好的检测效果。

A LOW-REGULARITY FOURIER INTEGRATOR FOR THE DAVEY-STEWARTSON II SYSTEM WITH ALMOST MASS CONSERVATION

In this work,we propose a low-regularity Fourier integrator with almost mass conservation to solve the Davey-StewartsonⅡsystem(hyperbolic-elliptic case).Arbitrary order mass convergence could be achieved by the suitable addition of correction terms,while keeping the first order accuracy in H~γ×H^(γ+1)for initial data in H^(γ+1)×H^(γ+1)withγ>1.The main theorem is that,up to some fixed time T,there exist constantsτ_(0)and C depending only on T and‖u‖_(L^(∞)((0,T);H^(γ+1)))such that,for any 0<τ≤τ_(0),we have that‖u(t_(n),·)-u^(n)‖H_γ≤C_(τ),‖v(t_(n),·)-v^(n)‖_(Hγ+1)≤C_(τ),where u^(n)and v^(n)denote the numerical solutions at t_(n)=nτ.Moreover,the mass of the numerical solution M(u^(n))satisfies that|M(u^(n))-M(u_0)|≤Cτ~5.

Efficiency of a Modular Cleanroom for Space Applications

A prototype cleanroom for hazardous testing and handling of satellites prior to launcher encapsulation,satisfying the ISO8 standard has been designed and analyzed in terms of performances.Unsteady Reynolds Averaged Navier-Stokes(URANS)models have been used to study the related flow field and particulate matter(PM)dispersion.The outcomes of the URANS models have been validated through comparison with equivalent large-eddy simulations.Special attention has been paid to the location and shape of the air intakes and their orientation in space,in order to balance the PM convection and diffusion inside the cleanroom.Forming a cyclone-type flow pattern inside the cleanroom is a key to maintaining a high ventilation efficiency.