This paper presents an improved technique on Ant Colony Optimization (ACO) algorithm. The procedure is applied on Single Machine with Infinite Bus (SMIB) system with power system stabilizer (PSS) at three different loading regimes. The simulations are made by using MATLAB software. The results show that by using Improved Ant Colony Optimization (IACO) the system will give better performance with less number of iterations as it compared with a previous modification on ACO. In addition, the probability of selecting the arc depends on the best ant performance and the evaporation rate.

     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

The paper aims is to solve the problem of choosing the appropriate project from several service projects for the Iraqi Martyrs Foundation or arrange them according to the preference within the targeted criteria. this is done by using Multi-Criteria Decision Method (MCDM), which is the method of Multi-Objective Optimization by Ratios Analysis (MOORA) to measure the composite score of performance that each alternative gets and the maximum benefit accruing to the beneficiary and according to the criteria and weights that are calculated by the Analytic Hierarchy Process (AHP). The most important findings of the research and relying on expert opinion are to choose the second project as the best alternative and make an arrangement acco

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

We investigated at the optical properties, structural makeup, and morphology of thin films of cadmium telluride (CdTe) with a thickness of 150 nm produced by thermal evaporation over glass. The X-ray diffraction study showed that the films had a crystalline composition, a cubic structure, and a preference for grain formation along the (111) crystallographic direction. The outcomes of the inquiry were used to determine these traits. With the use of thin films of CdTe that were doped with Ag at a concentration of 0.5%, the crystallization orientations of pure CdTe (23.58, 39.02, and 46.22) and CdTe:Ag were both determined by X-ray diffraction. orientations (23.72, 39.21, 46.40) For samples that were pure and those that were doped with

This study delves into the design optimization of a hydropower harvesting system, exploring various parameters and their influence on system performance. By modifying the variables within the model to suit different flow conditions, a judiciously optimized design is attainable. Notably, the lift force generated is found to be intricately linked to the strategic interplay of the bluff body's location, cylinder dimensions, and flow velocity. The findings culminate in the establishment of empirical equations, one for lift force and another for displacement, based on the force equation. Many energy harvesting approaches hinge on the reciprocating motion inherent to the structural system. The methodology developed in this study emerges as a pot

Hazardous materials, heavy metals, and organic toxins released into the environment have caused considerable harm to microbes, plants, animals, and humans. Wastewater is one of the most contaminated ecosystems due to heavy metals emitted mostly by human activity. Bioremediation of wastewater is an ecologically acceptable and cost-effective method of removing heavy metals from sewage; the general purpose of this study is to analyse the dependability of anaerobic sludge biomass in removing sulfur compounds and heavy metals from waste water. The anaerobic sludge biomass evaluated in this work was taken from a wastewater treatment plant (WWTP) in Al-Rustumiya, Baghdad, and grown in the mineral medium for anaerobic growth. In serum bottl