This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett
... Show MoreThe research aimed to compare the performance of the commercial and the Islamic banks listed in the Palestinian's Stock Exchange .To achieve the objectives of the study we selected all the commercial and the Islamic banks listed in the Palestinian Stock Exchange to obtain the necessary data for the analysis process during the period of (2009-2013) .the comparison based on the performance indicators ( liquidity rate, profitability rate ,the activity rate and the market rate).
a statistical method was used to analyze the date to find the performance differences between the commercial banks,
... Show MoreAbstract A descriptive (cross sectional) study was conducted to assess psychosocial domain of quality of life for (100) women who had hysterectomy for non malignant indications during 6-12 months post operative. The study carried out in both consultation clinics of Al-Elwiya Maternity Hospital and Baghdad Teaching Hospital from January 5th 2003 to July 10th 2003). The results of the study show that hysterectomy achieved a highly successful outcome in terms of psychological and social adjustments for hysterectomies women, a highly significant differences between quality of life (QoL) and some of demographic cha
The development of a meaningful dissolution procedure for drug products with limited water solubility has been a challenge to both the pharmaceutical industry and the agencies that regulate them. Natural surfactants aid in the dissolution and subsequent absorption of drugs with limited aqueous solubility. In vitro, various techniques have been used to achieve adequate dissolution of the sparingly water – soluble or water insoluble drug products such as the use of mechanical methods (i.e., increased agitation and the disintegration method) or hydro alcoholic medium or large volumes of medium. The necessity of assuring the quality of drugs , especially those with low aqueous solubility and in vivo absorption , has led to the development and
... Show MoreSafe drinking water is essential for the present and future generations' health. This study aims to assess drinking water quality in Baghdad's Al-Rusafa neighborhood. Water samples were taken from 32 neighborhoods on this side. The quality of the examined potable water samples differed depending on the water source. This investigation's pH, chlorine, EC, TDS, TSS, Cd, and Pb levels were below acceptable ranges. TDS levels in Al-Mada'in are more significant than acceptable (>600ppm) water levels. Bacteria have polluted six communities (Shigella, Salmonella, Escherichia coli, and Klebsiella). Bacterial quality of drinking water and gram-negative bacteria resistant to chlorine in Baghdad's municipal water supply. Regarding pH, the w
... Show MoreIraq, home of the Tigris and Euphrates rivers, has survived an extreme deficiency of surface water assets over the years. The gap is due to the decline of the Iraqi water share every year, as well as a high demand for water use from different sectors, particularly agriculture.
Dam development has long given significant economic benefits to Iraq in circulating low‐priced electricity and supporting low‐income farmers by supplying them with a free irrigation system (Zakaria et al, 2012). This encouraged domestic consumption and investment.
Despite the fact that numerous advantages are expected from dam construction, it should be painstakingly assessed, utilizing cost
COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in