Viscosity is one of the most important governing parameters of the fluid flow, either in the porous media or in pipelines. So it is important to use an accurate method to calculate the oil viscosity at various operating conditions. In the literature, several empirical correlations have been proposed for predicting crude oil viscosity. However, these correlations are limited to predict the oil viscosity at specified conditions. In the present work, an extensive experimental data of oil viscosities collected from different samples of Iraqi oil reservoirs was applied to develop a new correlation to calculate the oil viscosity at various operating conditions either for dead, satura

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

A factorial experiment was applied with four replicates on rosemary plants (Rosmarinus officinalis L.) grown in pots inside the glasshouse of the Department of Biology, College of Science, Salahaddin University, Erbil, Iraq, during April, 2019 to July, 2020, to determine the effects of soil moisture content ( SM1: 100% and SM2: 60% field capacity), nitrogen fertilizer (N1: 100, N2: 200 and N3: 300kg/hectare), and magnesium fertilizer (Mg1: 0.0, Mg2: 30 and Mg3: 60kg/hectare) and their interactions on some growth characteristics  and essential oil content of rosemary plants. Two cuttings were taken from rosemary shoots (on March, 2020 and July, 2020) after 12 and 15 months of planting respectively. Results showed that cutting 1:

Acidizing is one of the most used stimulation techniques in the petroleum industry. Several reports have been issued on the difficulties encountered during the stimulation operation of the Ahdeb oil field, particularly in the development of the Mishrif reservoir, including the following: (1) high injection pressures make it difficult to inject acid into the reservoir formation, and (2) only a few acid jobs have been effective in Ahdeb oil wells, while the bulk of the others has been unsuccessful. The significant failure rate of oil well stimulation in this deposit necessitates more investigations. Thus, we carried out this experimental study to systematically investigate the influence of acid treatment on the geomechanical properties of Mi4

The importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. T

This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl