Athletics are different from other games as a competition between individuals to show their competence and physical ability to achieve new record numbers in the various activities and various between the boards, jumping and throwing and each type of these activities in particular performance so found the researcher to find the method of training resistors in the development of special power and achievement In the effectiveness of javelin, where the researchers chose the sample of the athletes from the specialized school of athletics to effectively throw the spear at the ages of 15-17 years and carried out the tests of the research, which includes the strength of the speed of the arms and explosive power and The various resistance exercise

The research deals with the problem of visual pollution, as it is one of the most important urban problems that cities suffer from. The concept of visual pollution has recently emerged to describe the deformation and degradation of the urban environment. Visual pollution is defined as any component of the surrounding environment that is inconsistent and not homogeneous with its natural and human components. The volume of visual pollution has doubled due to the non-compliance with the laws, regulations and controls set by the Municipality of Baghdad by the citizens, and to the weak municipal role that the municipality plays in implementing these laws. Therefore, it has become necessary to know the manifestations of visual pollution and th

We are used Bayes estimators for unknown scale parameter  when shape Parameter  is known of Erlang distribution. Assuming different informative priors for unknown scale  parameter. We derived The posterior density with posterior mean and posterior variance using different informative priors for unknown scale parameter  which are the inverse exponential distribution, the inverse chi-square distribution, the inverse Gamma distribution, and the standard Levy distribution as prior. And we derived Bayes estimators based on the general entropy loss function (GELF) is used the Simulation method to obtain the results. we generated different cases for the parameters of the Erlang model, for different sample sizes. The estimates have been comp

In this study, the thermal buckling behavior of composite laminate plates cross-ply and angle-ply all edged simply supported subjected to a uniform temperature field is investigated, using a simple trigonometric shear deformation theory. Four unknown variables are involved in the theory, and satisfied the zero traction boundary condition on the surface without using shear correction factors, Hamilton's principle is used to derive equations of  motion depending on a Simple Four Variable Plate Theory for cross-ply and angle-ply, and then solved through Navier's double trigonometric sequence, to obtain critical buckling temperature for laminated composite plates. Effect of changing some design parameters such as, ortho

The aim of the present research is to investigate the effecting of pH parameter on the feasibility of lead removal from simulated wastewater using an electrochemical system. Electrocoagulation method is one of electrochemical technology which is used widely to treat industrial wastewater. Parameters affecting this operation, such as initial metal concentration, applied current, stirrer speed, and contact time of electroprocessing were taken as 155ppm, 1.5 Ampere, 150 rpm, 60 minutes respectively. While pH of the simulated wastewater was in the range of  2 to 12 in the experiments. It was found from the results that pH is an important parameter affecting lead removal operation. The best value of pH parameter is appro

The experiences in the life are considered important for many fields, such as industry, medical and others. In literature, researchers are focused on flexible lifetime distribution.

In this paper, some Bayesian estimators for the unknown scale parameter  of Inverse Rayleigh Distribution have been obtained, of different two loss functions, represented by Suggested and Generalized loss function based on Non-Informative prior using Jeffery's and informative prior represented by Exponential distribution. The performance of   estimators is compared empirically with Maximum Likelihood estimator, Using Monte Carlo Simulation depending on the Mean Square Error (MSE). Generally, the preference of Bayesian method of Suggeste

     In this paper, some estimators for the unknown shape parameter and reliability function of Basic Gompertz distribution have been obtained, such as Maximum likelihood estimator and Bayesian estimators under Precautionary loss function using Gamma prior and Jefferys prior. Monte-Carlo simulation is conducted to compare mean squared errors (MSE) for all these estimators for the shape parameter and integrated mean squared error (IMSE's) for comparing the performance of the Reliability estimators. Finally, the discussion is provided to illustrate the results that summarized in tables.

In all process industries, the process variables like flow, pressure, level, concentration
and temperature are the main parameters that need to be controlled in both set point
and load changes.
A control system of propylene glycol production in a non isothermal (CSTR) was
developed in this work where the dynamic and control system based on basic mass
and energy balance were carried out.
Inlet concentration and temperature are the two disturbances, while the inlet
volumetric flow rate and the coolant temperature are the two manipulations. The
objective is to maintain constant temperature and concentration within the CSTR.
A dynamic model for non isothermal CSTR is described by a first order plus dead
time (FO

The method of solving volterra integral equation by using numerical solution is a simple operation but to require many memory space to compute and save the operation. The importance of this equation appeares new direction to solve the equation by using new methods to avoid obstacles. One of these methods employ neural network for obtaining the solution.

This paper presents a proposed method by using cascade-forward neural network to simulate volterra integral equations solutions. This method depends on training cascade-forward neural network by inputs which represent the mean of volterra integral equations solutions, the target of cascade-forward neural network is to get the desired output of this network. Cascade-forward neural