The Ant System Algorithm (ASA) is a member of the ant colony algorithms family in swarm intelligence methods (part of the Artificial Intelligence field), which is based on the behavior of ants seeking a path and a source of food in their colonies. The aim of This algorithm is to search for an optimal solution for Combinational Optimization Problems (COP) for which is extremely difficult to find solution using the classical methods like linear and non-linear programming methods. 

The Ant System Algorithm was used in the management of water resources field in Iraq, specifically for Haditha dam which is one of the most important dams in Iraq. The target is to find out an efficient management system for

Research summarized in applying the model  of fuzzy goal programming for aggregate production planning , in General Company for hydraulic industries / plastic factory to get an optimal production plan  trying to cope with the impact that fluctuations in demand and  employs all available resources using two strategies where they are available   inventories  strategy and  the strategy of  change in the level of the workforce, these   strategies  costs are usually imprecise/fuzzy. The plant administration trying to minimize total production costs, minimize carrying costs and minimize changes in labour levels. depending on the gained data from th

Malaysia's growing population and industrialisation have increased solid waste accumulation in landfills, leading to a rise in leachate production. Leachate, a highly contaminated liquid from landfills, poses environmental risks and affects water quality. Conventional leachate treatments are costly and time-consuming due to the need for additional chemicals. Therefore, the Electrocoagulation process could be used as an alternative method. Electrocoagulation is an electrochemical method of treating water by eliminating impurities by applying an electric current. In the present study, the optimisation of contaminant removal was investigated using Response Surface Methodology. Three parameters were considered for optimisation: the curr

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

Carbon fiber reinforced polymers (CFRP) were widely used in strengthening reinforced concrete members
in the last few years, these fibers consist mainly of high strength fibers which increase the member capacity in addition to changing the mode of failure of the reinforced concrete beams. Experimental and theoretical investigations were carried to find the behavior of reinforced concrete beams strengthened by CFRP in shear and bending. The experimental work included testing of 12 beams divided into 4 groups; each group contains 3 beams. The following parameters were taken into consideration: - Concrete crushing strength. - CFRP strengthening location (shear strengthening and both shear and flexure strengthening). Reinforced beams were

The utilization and incorporation of glass fiber-reinforced plastics (GFRP) in structural applications and architectural constructions are progressively gaining prominence. Therefore, this paper experimentally and numerically investigates the use of GFRP I-beams in conjunction with concrete slabs to form composite beams. The experimental design incorporated 2600 mm long GFRP I-beams which were connected compositely to concrete slabs with a 500 mm width and 80 mm thickness. The concrete slabs are categorized into two groups: concrete slabs cast using normal-strength concrete (NSC), and concrete slabs prepared using high-strength concrete (HSC). Various parameters like the type of concrete (normal and high-strength concrete), type of

In this paper, Response Surface Method (RSM) is utilized to carry out an investigation of the impact of input parameters: electrode type (E.T.) [Gr, Cu and CuW], pulse duration of current (I_p), pulse duration on time (T_on), and pulse duration off time (T_off) on the surface finish in EDM operation. To approximate and concentrate the suggested second- order regression model is generally accepted for Surface Roughness Ra, a Central Composite Design (CCD) is utilized for evaluating the model constant coefficients of the input parameters on Surface Roughness (Ra). Examinations were performed on AISI D2 tool steel. The important coefficients are gotten by achieving successfully an Analysis of V

BACKGROUND: Burkholderia cepacia adhesion and biofilm formation onto abiotic surfaces is an important feature of clinically relevant isolates. The in vitro biofilm formation of B. cepacia onto coated indwelling urinary catheters (IDCs) with moxifloxacin has not been previously investigated. OBJECTIVES: To examine the ability of B. cepacia to form biofilms on IDCs and the effect of coating IDCs with moxifloxacin on biofilm formation by B. cepacia in vitro. MATERIAL AND METHODS: The adhesion of B. cepacia to coated and uncoated IDCs with moxifloxacin was evaluated. Pieces of IDCs were coated with moxifloxacin (adsorption method). The spectrophotometric method was used to check moxifloxacin leaching into tubes. Coated and uncoated tubes were i

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample