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

     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

This research deals with processing and Interpretation of Bouguer anomaly gravity field, using two dimensional filtering techniques to separate the residual gravity field from the Bouguer gravity map for a part of Najaf Ashraf province in Iraq. The residual anomaly processed in order to reduce noise and give a more comprehensive vision about subsurface linear structures. Results for descriptive interpretation presented as colored surfaces and contour maps in order to locate directions and extensions of linear features which may interpret as faults. A comparison among gravity residual field , 1st derivative and horizontal gradient made along a profile across the study area in order to assign the exact location of a major fault. Furthermor

A newly developed analytical method characterized by its speed and sensitivity for the determination of mefenamic acid (MFA) in pure and pharmaceutical preparation is established via turbidimetric measurement (0-180o) by Ayah 6SX1-ST-2D Solar cell CFI Analyser . The method was based on the reaction of
phosphomolybdic acid with mefenamic acid in aqueous medium to form blue color precipitate as an ion-pair complex . Turbidity was measured via the reflection of incident light that collides on the surface precipitated particles at 0-180o . The chemical and physical parameters were studied and optimized. The calibration graph was linear in the range of 0.3-7 or 0.3-10 mMol.L-1, with correlation coefficient r = 0.9907 or 0.9556 respectively

In this work Different weight of pure Zinc powder suspended particles in 4ml base engine Oil were used.
Intensity of Kα Line was measured for the suspended particles ,also for mixture which consist from Zinc particle blended with Engine base Oil. Calibration Curve was drawn between Ikα line Intensity and Zinc concentration at different operation condition. The Lower Limit detection (LLD) and Sensitivity (m) of Spectrometer were determined for different Zinc Concentration (Wt%). The results of LLD and m for Samples were analyzed at Operation Condition of 30KV,17mA is best from Samples were analyzed at Operation Condition of 25KV,15mA

Dust storms are typical in arid and semi-arid regions such as the Middle East; the frequency and severity of dust storms have grown dramatically in Iraq in recent years. This paper identifies the dust storm sources in Iraq using remotely sensed data from Meteosat-spinning enhanced visible and infrared imager (SEVIRI) bands. Extracted combined satellite images and simulated frontal dust storm trajectories, using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, are used to identify the most influential sources in the Middle East and Iraq. Out of 132 dust storms in Iraq during 2020–2023, the most frequent occurred in the spring and summer. A dust source frequency percentage map (DSFPM) is generated using ArcGIS so