Date stones were used as precursor for the preparation of activated carbons by chemical
activation with ferric chloride and zinc chloride. The effects of operating conditions represented
by the activation time, activation temperature, and impregnation ratio on the yield and adsorption
capacity towards methylene blue (MB) of prepared activated carbon by ferric chloride activation
(FAC) and zinc chloride activation (ZAC) were studied. For FAC, an optimum conditions of 1.25
h activation time, 700 °C activation temperature, and 1.5 impregnation ratio gave 185.15 mg/g
MB uptake and 47.08 % yield, while for ZAC, 240.77 mg/g MB uptake and 40.46 % yield were
obtained at the optimum conditions of 1.25 h activation time, 500

Voice over Internet Protocol (VoIP) is important technology that’s rapidly growing in the wireless networks. The Quality of Service (QoS) and Capacity are two of the most important issues that still need to be researched on wireless VoIP. The main aim of this paper is to analysis the performance of the VoIP application in wireless networks, with respect to different transport layer protocols and audio codec. Two scenarios used in the simulation stage. In the first scenario VoIP with codec G.711 transmitted over User Datagram Protocol (UDP), Stream Control Transmission Protocol (SCTP), and Real-Time Transport Protocol (RTP). While, in the second scenario VoIP with codec G.726 transmitted over UDP, SCTP, and RTP protocols. Network simulator

Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-201

The goal of this study is to provide a new explicit iterative process method  approach for solving maximal monotone(M.M )operators in Hilbert spaces utilizing a finite family of different types of  mappings as( nonexpansive mappings,resolvent mappings and projection mappings. The findings given in this research strengthen and extend key previous findings in the literature. Then, utilizing various structural conditions in Hilbert space and variational inequality problems, we examine the strong convergence to nearest point projection for these explicit iterative process methods Under the presence of two important conditions for convergence, namely closure and convexity. The findings reported in this research strengthen and extend

     The work in this paper focuses on solving numerically and analytically a  nonlinear social epidemic model that represents an initial value problem  of ordinary differential equations. A recent moking habit model from Spain is applied and studied here. The accuracy and convergence of the numerical and approximation results are investigated for various methods; for example, Adomian decomposition, variation iteration, Finite difference and Runge-Kutta. The discussion of the present results has been tabulated and graphed. Finally, the comparison between the analytic and numerical solutions from the period 2006-2009 has been obtained by absolute and difference measure error.

The method of operational matrices based on different types of polynomials such as Bernstein, shifted Legendre and Bernoulli polynomials will be presented and implemented to solve the nonlinear Blasius equations approximately. The nonlinear differential equation will be converted into a system of nonlinear algebraic equations that can be solved using Mathematica^®12. The efficiency of these methods has been studied by calculating the maximum error remainder ( ), and it was found that their efficiency increases as the polynomial degree (n) increases, since the errors decrease. Moreover, the approximate solutions obtained by the proposed methods are compared with the solution of the 4^th order Runge-Kutta meth

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a local

Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p