Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

A total of 20 raw milk samples were used as the fouling agent for evaluating the bacteriological effectiveness of cleaning and sanitizing of domestic milking equipment by using ozonated water at 0.5 ppm comparing to the warm water at 55! for 5 minutes respectively. The mean values of total aerobic bacteria, Coliform and E.coli that present on the plastic and stainless-steel containers after using the raw milk as fouling agent were 3.4×10-6 , 6.7x10-5 and 5.8×10-3 cfu/cm2 respectively , after cleaning the stainless steel containers by the ozonated water the mean values of total aerobic bacterial counts, Coliforms and E.coli bacteria were reduced to 1.2×10-6, 4.7×10-5 and 3.3×10-3 CFU/cm2 respectively. while after cleaning by the warm wa

     The bound radial wave functions of Cosh potential which are the solutions to the radial part of Schrodinger equation are solved numerically and used to compute the size radii; i.e., the root-mean square proton, neutron, charge and matter radii, ground density distributions and elastic electron scattering charge form factors for nitrogen isotopes 14,16,18,20,22N. The parameters of such potential for the isotopes under study have been opted so as to regenerate the experimental last single nucleon binding energies on Fermi's level and available experimental size radii as well.

Most available methods for unit hydrographs (SUH) derivation involve manual, subjective fitting of
a hydrograph through a few data points. The use of probability distributions for the derivation of synthetic
hydrographs had received much attention because of its similarity with unit hydrograph properties. In this
paper, the use of two flexible probability distributions is presented. For each distribution the unknown
parameters were derived in terms of the time to peak(tp), and the peak discharge(Qp). A simple Matlab
program is prepared for calculating these parameters and their validity was checked using comparison
with field data. Application to field data shows that the gamma and lognormal distributions had fit well.<

This paper discusses using H2 and H∞ robust control approaches for designing control systems. These approaches are applied to elementary control system designs, and their respective implementation and pros and cons are introduced. The H∞ control synthesis mainly enforces closed-loop stability, covering some physical constraints and limitations. While noise rejection and disturbance attenuation are more naturally expressed in performance optimization, which can represent the H₂ control synthesis problem. The paper also applies these two methodologies to multi-plant systems to study the stability and performance of the designed controllers. Simulation results show that the H2 controller tracks a desirable cl

In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application

The objective of this research was to estimate the dose distribution delivered by radioactive gold nanoparticles (198 AuNPs or 199 AuNPs) to the tumor inside the human prostate as well as to normal tissues surrounding the tumor using the Monte-Carlo N-Particle code (MCNP-6.1. 1 code). Background Radioactive gold nanoparticles are emerging as promising agents for cancer therapy and are being investigated to treat prostate cancer in animals. In order to use them as a new therapeutic modality to treat human prostate cancer, accurate radiation dosimetry simulations are required to estimate the energy deposition in the tumor and surrounding tissue and to establish the course of therapy for the patient. Materials and methods A simple geometrical