There is an assumption implicit but fundamental theory behind the decline by the time series used in the estimate, namely that the time series has a sleep feature Stationary or the language of Engle Gernger chains are integrated level zero, which indicated by I (0). It is well known, for example, tables of t-statistic is designed primarily to deal with the results of the regression that uses static strings. This assumption has been previously treated as an axiom the mid-seventies, where researchers are conducting studies of applied without taking into account the properties of time series used prior to the assessment, was to accept the results of these tests Bmanueh and delivery capabilities based on the applicability of the theo

In this research, Haar wavelets method has been utilized to approximate a numerical solution for Linear state space systems. The solution technique is used Haar wavelet functions and Haar wavelet operational matrix with the operation to transform the state space system into a system of linear algebraic equations which can be resolved by MATLAB over an interval from 0 to . The exactness of the state variables can be enhanced by increasing the Haar wavelet resolution. The method has been applied for different examples and the simulation results have been illustrated in graphics and compared with the exact solution.

In this research, we find the Bayesian formulas and the estimation of Bayesian expectation for product system of Atlas Company.  The units of the system have been examined by helping the technical staff at the company and by providing a real data the company which manufacturer the system.  This real data include the failed units for each drawn sample, which represents the total number of the manufacturer units by the company system.  We calculate the range for each estimator by using the Maximum Likelihood estimator.  We obtain that the expectation-Bayesian estimation is better than the Bayesian estimator of the different partially samples which were drawn from the product system after  it checked by the

In this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th

The aim of present study is to determine the optimum parameters of friction stir welding process and known the most important parameter along with percentage contribution of each parameter which effect on tensile strength and joint efficiency of FS welded joint of  dissimilar aluminum alloys AA2024-T3 and AA7075-T73 of 3 mm thick plates by applied specific number of experiments using Taguchi method .AA2024 was placed on the advancing side and AA7075 on the retreating side. FSW was achieved under three different rotation speeds (898, 1200 and 1710) rpm, three different welding speeds (20, 45 and 69) mm\min , three different pin profiles (cylindrical, threaded cylindrical and cone) and tool tilt angle 2^◦. Taguchi method w

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In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

Gingival crevicular fluid (GCF) may reflect the events associated with orthodontic tooth movement. Attempts have been conducted to identify biomarkers reflecting optimum orthodontic force, unwanted sequallea (i.e. root resorption) and accelerated tooth movement. The aim of the present study is to find out a standardized GCF collection, storage and total protein extraction method from apparently healthy gingival sites with orthodontics that is compatible with further high-throughput proteomics. Eighteen patients who required extractions of both maxillary first premolars were recruited in this study. These teeth were randomly assigned to either heavy (225g) or light force (25g), and their site specific GCF was collected at baseline and aft

A paraffin wax and copper foam matrix were used as a thermal energy storage material in the double passes air solar chimney (SC) collector to get ventilation effect through daytime and after sunset. Air SC collector was installed in the south wall of an insulated test room and tested with different working angles (30^o, 45^o and 60^o). Different SC types were used; single pass, double passes flat plate collector and double pass thermal energy storage box collector (TESB). A computational model based on the finite volume method for transient tw dimensional domains was carried out to describe the heat transfer and storage in the thermal energy storage material of collector. Also, equivalent specific heat metho

In this study, we focused on the random coefficient estimation of the general regression and Swamy models of panel data. By using this type of data, the data give a better chance of obtaining a better method and better indicators. Entropy's methods have been used to estimate random coefficients for the general regression and Swamy of the panel data which were presented in two ways: the first represents the maximum dual Entropy and the second is general maximum Entropy in which a comparison between them have been done by using simulation to choose the optimal methods.

The results have been compared by using mean squares error and mean absolute percentage error to different cases in term of correlation valu

The monitoring weld quality is increasingly important because great financial savings are possible because of it, and this especially happens in manufacturing where defective welds lead to losses in production and necessitate time consuming and expensive repair. This research deals with the monitoring and controllability of the fusion arc welding process using Artificial Neural Network (ANN) model. The effect of weld parameters on the weld quality was studied by implementing the experimental results obtained from welding a non-Galvanized steel plate ASTM BN 1323 of 6 mm thickness in different weld parameters (current, voltage, and travel speed) monitored by electronic systems that are followed by destructive (Tensile and Bending) and non