This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

          A novel median filter based on crow optimization algorithms (OMF) is suggested to reduce the random salt and pepper noise and improve the quality of the RGB-colored and gray images. The fundamental idea of the approach is that first, the crow optimization algorithm detects noise pixels, and that replacing them with an optimum median value depending on a criterion of maximization fitness function. Finally, the standard measure peak signal-to-noise ratio (PSNR), Structural Similarity, absolute square error and mean square error have been used to test the performance of suggested filters (original and improved median filter) used to removed noise from images. It achieves the simulation based on MATLAB R2019b and the resul

The Traveling Salesman Problem is a story application of Atom Swarm Optimizations in this research. We have developed several novel techniques intended for solving TSP with PSO. Additionally, we introduced the notions to Swap Operative and Swap Chronological sequence and redefining the remaining operatives their foundation; that way, the study created unique PSO. Research prove it can produce satisfactory outcomes. The aim of this paper be there to assess the functioning of particle swarm optimization, for the going salesman issue TSP. The solution to this trouble is common to be NP-hard, it has N! permutations. The study's goal is to examine the capacity of both algorithms to solve intercontinental and other benchmark problems. Overall, th

Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m

Background: Polymethyl methacrylate (PMMA) is the most commonly used material in denture fabrication. The material is far from ideal in fulfilling the mechanical requirements, like low impact and transverse strength, poor thermal conductivity. The purpose of this study was to evaluate the effect of addition a composite of surface treated Nano Aluminum oxide (Al2O3) filler and plasma treated polypropylene fiber (PP) on some properties of denture base material. Materials and methods: One hundred fifty prepared specimens were divided into 5 groups according to the tests, each group consisted of 30 specimens and these were subdivided into 3 groups (unreinforced heat cured acrylic resin as control group),reinforced acrylic resin with( 0.5%wt Nan

The present work involved a study the effect of cobalt(II) complex with formula [CoL(H2O)NO3] .4ETOH where L=Nitro [5-(P-nitro phenyl) -4-phenyl-1,2,4 traizole-3-dithiocarbamato hydrazide] aqua. (4) Ethanol and anti-cancer drug - cyclophosphamide on specific activity of two liver enzymes (GPT,ALP) by utilizing an in vivo system in female mice. On the enzymatic level an inhibition in the activity of GPT was noticed in different body organs such as liver, kidney and lung. The inhibition was noticed in both test and cyclophosphamide drug (cp). Mice were treated with three doses of cyclophosphamide (90,180, 250) ?g/ mouse for three days. The same doses were used for the cobalt (II) complex. The liver shows the highest rate of(GPT) inhibition co

KE Sharquie, AA Noaimi, GA Ibrahim, AS Al-Husseiny, Our Dermatology Online, 2016 - Cited by 3