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

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

This study has been done on plant [Adhatoda vasicia , Acanthaceae family],which has been collected from gardens of university of Baghdad The leaves of plant were extracted by methanol alcohol obtain the crude extraction good ratio(30%).Eighty swabs or samples were collected from several wounds patients of hospitals in Baghdad city.These swabs were cultured on blood and MacConkey ager to isolate bacteria and identified by appearance and bio chemical tests.The results showed that(60)somples were positive(75%)for tests bacteria white the other(20)swabs were negative(25%).The bacteria were identified as Pseudomonas aeruginosa ,Staphylococcus awreus , Esherichia coli,Proteus spp and Klebsiella spp; and their number percentage were(32)isolates(

Studied competence spam to malicious moth figs at temperatures and Kagafat host different results showed that female intruder, despite their ability to shell larvae host and when densities of different, but it is able to lay eggs at a temperature of 14 + or -1 and finally urged the efficiency spam to malicious affected heavily host and that the greater the intensity of the host spam increased efficiency and its performance life

The use of male mothers fur c meat Fabro to learn Effect concentrations of ammonium chloride NH4CL and Bacarbonnat sodium NaHCO3 in drinking water by heat stress and Altsoam during heat stress on some of the qualities of productivity and Alvesrgih divided animals to 6 transactions, namely: - control without adding NH4CL, NaHCO3 and Altsoam (treatment 1) Altsoam-1200 of 7-4 weeks old chicken meat to heat patrol 25-34-25 .. 7 weeks old Weight was measured gravimetric vivo increase feed consumption

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

In this research, the X-ray diffraction pattern was used, which was obtained experimentally after preparation of barium oxide powder. A program was used to analyze the X-ray diffraction lines of barium oxide nanoparticles, and then the particle size was calculated by using the Williamson-Hall method, where it was found that the value of the particle size is 25.356 nm. Also, the dislocation density was calculated, which is equal to1.555 x1015 (lines/nm2), and the value of the unit cell number was also calculated, as it is equal to 23831.

The present work describes the adsorption of Ba2+ and Mg2+ions from aqueous solutions by activated alumina in single and binary system using batch adsorption. The effect of different parameters such as amount of alumina, concentration of metal ions, pH of solution, contact time and agitation speed on the adsorption process was studied. The optimum adsorbent dosage was found to be 0.5 g and 1.5 g for removal of Ba2+ and Mg2+, respectively. The optimum pH, contact time and agitation speed, were found to be pH 6, 2h and 300 rpm, respectively, for removal of both metal ions. The equilibrium data were analyzed by Langmuir and Freundlich isotherm models and the data fitted well to both isotherm modes as indicated by higher correlation of deter