Graphene oxide (GO) was prepared from graphite (GT) with Hammer method, the GO was reduced with hydrazine hydrate to produce a reduced graphene oxide (RGO). The RGO was reacted with thiocarbohydrazide (TCH) to functionalize the RGO with 4-amino-3-symbol-1h-1, 2, 4-triazol-5 (4H) –thion group and to obtain (RGOT). All the prepared nanomaterial and the product of the functionalization RGOT were characterized with Fourier transformer infrared (FT-IR) spectroscopy, X-ray diffraction (XRD) analysis. RGOT mixed with ultrasonic device at different pH values of phosphate buffer solution (PBS), the mixture used to modifying a screen printed carbon electrodes SPCE and with cyclic voltammetry the sensitivity of selectivity of the new modifying elect

Cluster analysis (clustering) is mainly concerned with dividing a number of data elements into clusters. The paper applies this method to create a gathering of symmetrical government agencies with the aim to classify them and understand how far they are close to each other in terms of administrative and financial corruption by means of five variables representing the prevalent administrative and financial corruption in the state institutions. Cluster analysis has been applied to each of these variables to understand the extent to which these agencies are close to other in each of the cases related to the administrative and financial corruption.           

Hypertension is one of the leading causes of the global burden of disease, which causes serious health problems. The aim of this study is to investigate the lipid profile levels in sera of Iraqi hypertensive patients by measuring Total cholesterol (TC), triglyceride (TG) and low density lipoproteins (LDL) and kidney function levels by measuring uric acid, urea and creatinine. Seventy five individuals of Iraqi adults (Males) were divided into three groups: 25 hypertensive patients with duration of disease (1-10) year (group 1), 25 hypertensive patients with duration of disease (11-30) year (group 2) and 25 normal individuals as control group (group3). The findings indicate that serum (TC, TG and LDL) levels were significantly elevated (

Jurisprudential rules, a broad section to lower the legitimacy of the ruling on the developments of politics, which is increasing day by day, and developments of complex judicial issues, provided that the rule derived from the texts of the legitimate or verbal significance.
      And the introduction of jurisprudence rules in the provisions concerning the legitimate policy, the first to take from the provisions of the situation; because the rules of jurisprudence is a summary of the provisions reached by the scholars of the nation after study and scrutiny, which is qualified and largely to cover the need of the owners of public mandates.

There are many problems facing the economic entities  as a result of its mass production &variation of its products  , the matter which had  increased the need & importance of cost accounting which is regarded a main tool for the managerial control.

The actual costing system is unable to meet the contemporary management needs ,so the Standard costing system appear to provide the management  with required information to perform its functions by the best use& way.

This research aims to determine  the standard cost for the  direct material for oil extraction activity by applying it in the north oil company.

This paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

In our article, three iterative methods are performed to solve the nonlinear differential equations that represent the straight and radial fins affected by thermal conductivity. The iterative methods are the Daftardar-Jafari method namely (DJM), Temimi-Ansari method namely (TAM) and Banach contraction method namely (BCM) to get the approximate solutions. For comparison purposes, the numerical solutions were further achieved by using the fourth Runge-Kutta (RK4) method, Euler method and previous analytical methods that available in the literature. Moreover, the convergence of the proposed methods was discussed and proved. In addition, the maximum error remainder values are also evaluated which indicates that the propo