Most of the Weibull models studied in the literature were appropriate for modelling a continuous random variable which assumes the variable takes on real values over the interval [0,∞]. One of the new studies in statistics is when the variables take on discrete values. The idea was first introduced by Nakagawa and Osaki, as they introduced discrete Weibull distribution with two shape parameters q and β where      0 < q < 1 and b > 0. Weibull models for modelling discrete random variables assume only non-negative integer values. Such models are useful for modelling for example; the number of cycles to failure when components are subjected to cyclical loading. Discrete Weibull models can be obta

Copulas are very efficient functions in the field of statistics and specially in statistical inference. They are fundamental tools in the study of dependence structures and deriving their properties. These reasons motivated us to examine and show  various types of copula functions and their families. Also, we separately explain each method that is used to construct each copula in detail with different examples. There are various outcomes that show the copulas and their densities with respect to the joint distribution functions. The aim is to make copulas available to new researchers and readers who are interested in the modern phenomenon of statistical inferences.

The capacity factor is the main factor in assessing the efficiency of wind Turbine. This paper presents a procedure to find the optimal wind turbine for five different locations in Iraq based on finding the highest capacity factor of wind turbine for different locations. The wind data for twelve successive years (2009-2020) of five locations in Iraq are collected and analyzed. The longitudes and latitudes of the candidate sites are (44.3661o E, 33.3152o N), (47.7738o E, 30.5258o N), (45.8160o E, 32.5165o N), (44.33265o E, 32.0107o N) and (46.25691o E, 31.0510o N) for Baghdad, Basrah, Al-Kut, Al-Najaf, and Al-Nasiriyah respectively. The average wind velocity, standard deviation, Weibull shape and scale factors, and probability density functi

In this paper, the reliability and scheduling of maintenance of some medical devices were estimated by one variable, the time variable (failure times) on the assumption that the time variable for all devices has the same distribution as (Weibull distribution.

The method of estimating the distribution parameters for each device was the OLS method.

The main objective of this research is to determine the optimal time for preventive maintenance of medical devices. Two methods were adopted to estimate the optimal time of preventive maintenance. The first method depends on the maintenance schedule by relying on information on the cost of maintenance and the cost of stopping work and acc

This article deals with estimations of system Reliability for one component, two and s-out-of-k stress-strength system models with non-identical component strengths which are subjected to a common stress, using Exponentiated Exponential distribution with common scale parameter. Based on simulation, comparison studies are made between the ML, PC and LS estimators of these system reliabilities when scale parameter is known.

Truncated distributions arise naturally in many practical situations. It’s a conditional distribution that develops when the parent distribution's domain is constrained to a smaller area. The distribution of a right truncated is one of the types of a single truncated that is restricted within a specific field and usually occurs when the specified period for the study is complete.  Hence, this paper introduces Right Truncated Inverse Generalized Rayleigh Distribution (RTIGRD) with two parameters  is introduced. Then, provided some properties such as; (probability density function, cumulative distribution function (CDF), survival function, hazard function, ‎rth moment, mean,   variance, Moment Generating Function, Skewness, kurtosi

In this research, a Co-polymer (Styrene / Allyl-2.3.4.6-tetra-O-acetyl-β-D-glucopyranoside) was synthesized from glucose in four steps using Addition Polymerization according to the radical mechanism using Benzoyl Peroxide (BP) as initiator. Initially, Allyl-2.3.4.6-tetra-O-acetyl-β-D-glucopyranoside monomer was prepared in three steps and the reaction was followed by (HPLC, FT-IR, TLC), in the fourth step the monomer was polymerized with Styrene and the structure was determined by FT-IR and NMR spectroscopy. The reaction conditions (temperature, reaction time, material ratios) were also studied to obtain the highest yield, the relative, specific and reduced viscosity of the prepared polymer was determined, from which the viscosity ave

Most frequently used models for modeling and forecasting periodic climatic time series do not have the capability of handling periodic variability that characterizes it. In this paper, the Fourier Autoregressive model with abilities to analyze periodic variability is implemented. From the results, FAR(1), FAR(2) and FAR(2) models were chosen based on Periodic Autocorrelation function (PeACF) and Periodic Partial Autocorrelation function (PePACF). The coefficients of the tentative model were estimated using a Discrete Fourier transform estimation method. FAR(1) models were chosen as the optimal model based on the smallest values of Periodic Akaike (PAIC) and Bayesian Information criteria (PBIC). The residual of the fitted models was diagn

    Predicting the network traffic of web pages is one of the areas that has increased focus in recent years. Modeling traffic helps find strategies for distributing network loads, identifying user behaviors and malicious traffic, and predicting future trends. Many statistical and intelligent methods have been studied to predict web traffic using time series of network traffic. In this paper, the use of machine learning algorithms to model Wikipedia traffic using Google's time series dataset is studied. Two data sets were used for time series, data generalization, building a set of machine learning models (XGboost, Logistic Regression, Linear Regression, and Random Forest), and comparing the performance of the models using (SMAPE) and

Many organizations today are  interesting to implementing lean manufacturing principles  that should enable them to eliminating the wastes to reducing a  manufacturing lead time.  This paper concentrates on  increasing  the competitive level of the company in globalization markets and improving of the productivity by reducing the manufacturing lead time. This will be by using the main tool of lean manufacturing which is value stream mapping (VSM) to identifying all the activities of manufacturing process (value and non-value added activities) to reducing elimination of wastes (non-value added activities) by converting a manufacturing system to pull instead of push by applying some of pull system strategies a