The environmental problems that have emerged recently as a result of pressure on the environment due to the increase in population size, especially in urban cities, where this increase was accompanied by the need for housing as well as the need for services and activities. This led to the establishment of many vertical residential buildings represented by residential complexes within the urban fabric of the city of Baghdad. As part of following the methodology of urban dictation policies in empty areas, and to accommodate the largest number of residents as a result of the multiplicity of floors and housing, these buildings must be subject to the standards and requirements of sustainability at the level of their spatial location and their

     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

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust EA wit

    The Mawat Ophiolite Complex located in north-eastern Iraq represents part of the Iraqi Zagros Suture Zone, located at the border between the Arabian-Iranian plates. It consists of peridotite, gabbro, subvolcanic sheeted dykes and volcanic pillow lava. The geochemical signatures of the gabbro show a significant variation in major elements concentration, low concentrations of TiO₂ (0.06-0.36 wt.%), Na₂O (0.44-0.98 wt.%), K₂O (0.024-0.48 wt.%), P₂O₅ (0.002-0.009 wt.%) and moderate variations in SiO₂ (46.13-53.77 wt.%) with wide ranges and high concentration of Al₂O₃ (13.87-22.18 wt.%), Fe₂O₃ (0.04-2.95 wt.%), FeO (2.68-8.76 w

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

     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

The 2D resistivity imaging technique was applied in an engineering study for the investigation of subsurface weakness zones within University of Anbar, western Iraq. The survey was carried out using Dipole-dipole array with an n-factor of 6 and a-spacing values of 2 m and 5 m. The inverse models of the 2D electrical imaging clearly show the resistivity contrast between the anomalous parts of the weakness zones and the background resistivity distribution. The thickness and shape of the subsurface weakness zones were well defined from the 2D imaging using Dipole-dipole array of 2 m a-spacing. The thickness of the weakness zone ranges between 9.5 m to 11.5 m. Whereas the Dipole-dipole array with a-spacing of 5 m and n-factor of 6 allocated

Gurney flap (GF) is well-known as one of the most attractive plain flaps because of the simple configuration and effectiveness in improving the lift of the airfoil. Many studies were conducted, but the effects of GF on the various airfoil types need to be further investigated. This study aimed to clarify the effect of GF in the case of the supercritical airfoil RAE2822. This research includes a steady, two-dimensional computational investigation carried out on the supercritical airfoil type RAE-2822 to analyze Gurney flap (GF) effects on the aerodynamic characteristics of this type of airfoil utilizing the Spalart-Allmaras turbulence model within the commercial software Fluent. The airfoil with the Gurney flap was analyz

It is well known that petroleum refineries are considered the largest generator of oily sludge which may cause serious threats to the environment if disposed of without treatment. Throughout the present research, it can be said that a hybrid process including ultrasonic treatment coupled with froth floatation has been shown as a green efficient treatment of oily sludge waste from the bottom of crude oil tanks in Al-Daura refinery and able to get high yield of base oil recovery which is 65% at the optimum operating conditions (treatment time = 30 min, ultrasonic wave amplitude = 60 micron, and (solvent: oily sludge) ratio = 4). Experimental results showed that 83% of the solvent used was recovered meanwhile the main water