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Improved Naked Mole-Rat Algorithm Based on Variable Neighborhood Search for the N-Queens Problem
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     Solving problems via artificial intelligence techniques has widely prevailed in different aspects. Implementing artificial intelligence optimization algorithms for NP-hard problems is still challenging. In this manuscript, we work on implementing the Naked Mole-Rat Algorithm (NMRA) to solve the n-queens problems and overcome the challenge of applying NMRA to a discrete space set. An improvement of NMRA is applied using the aspect of local search in the Variable Neighborhood Search algorithm (VNS) with 2-opt and 3-opt. Introducing the Naked Mole Rat algorithm based on variable neighborhood search (NMRAVNS) to solve N-queens problems with different sizes. Finding the best solution or set of solutions within a plausible amount of time is the main goal of the NMRAVNS algorithm. The improvement of the proposed algorithm boosts the exploitation capability of the basic NMRA and gives a greater possibility, with the emerging search strategies, to find the global best solution. This algorithm proved successful and outperformed other algorithms and studies with a remarkable target. A detailed comparison is performed, and the data results are presented with the relevant numbers and values. NMRA and NMRAVNS comparisons are implemented and recorded. Later on, a comparison between the Meerkat Clan Algorithm, Genetic Algorithm, Particle Swarm Optimization, and NMRAVNS is tested and presented. Finally, NMRAVNS is evaluated against the examined genetic-based algorithm and listed to prove the success of the proposed algorithm. NMRAVNS outperformed previous findings and scored competitive results with a high number of queen sizes, where an average time reduction reached about 87% of other previous findings.

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Spectrophotometric Determination of Salbutamol Sulphate and Isoxsuprine Hydrochloride in Pharmaceutical Formulations
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A simple, sensitive and accurate spectrophotometric method has been developed for the determination of salbutamol sulphate (SAB) and isoxsuprine hydrochloride (ISX) in pure and pharmaceutical dosage. The method involved oxidation of (SAB) and (ISX) with a known excess of N-bromosuccinamid in acidic medium, and subsequent occupation of unreacted oxidant in decolorization of Evans blue dye (EB). This, in the presence of SAB or ISX was rectilinear over the ranges 1.0-12.0, 1.0-11.0 µg/mL, with molar absorptivity 4.21×104 and 2.58×104 l.mol-1.cm-1 respectively. The developed method had been successfully applied for the determination of the studied drugs in their pharmaceutical dosage resulting i

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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

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Publication Date
Sun Nov 26 2017
Journal Name
Journal Of Engineering
Compression Index and Compression Ratio Prediction by Artificial Neural Networks
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Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

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Publication Date
Mon Apr 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Review: Saccharin Discovery, Synthesis, and Applications
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    Saccharin is firstly synthesized in 1879. It is a very well-known as an inexpensive substitute for sugar as it is a non-caloric sweetener. The article shows the properties, use, metabolism and various synthesis and reactions of saccharine. Moreover, the toxicological reports explain that saccharin is mostly responsible for the bladder tumors observed in the male rats, the relationship between the consumption of saccharin and bladder cancer is afforded by epidemiological studies.  The benefit-risk evaluation for saccharin is hardly to indicate. Saccharin is a sugar substitute, frequently used either in food industry, or in pharmaceutical formulations and even in tobacco products. The chemistry of saccharin is inter

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Mechanical Engineering
Process Parameters Optimization in Single Point Incremental Forming Of Al1050
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This work aims to optimize surface roughness, wall angle deviation, and average wall thickness as output responses of ALuminium-1050 alloy cone formed by the single point incremental sheet metal forming process. The experiments are accomplished based on the use of a mixed level Taguchi experimental design with an L18 orthogonal array. Six levels of step depth, three levels of tool diameter, feed rate, and tool rotational speed have been considered as input process parameters. The analyses of variance (ANOVA) have been used to investigate the significance of parameters and the effect of their levels for minimum surface roughness, minimum wall angle deviation, and maximum average wall thickness. The results indicate that step depth and tool r

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Optimization of Voltammetric Determination of Dysprosium (III) Using Plackett-Burman and RSM-CCD Experimental Designs
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This study was aimed to develop an optimized Dy determination method using differential pulse voltammetry (DPV). The Plackett-Burman (PB) experimental design was used to select significant factors that affect the electrical current response, which were further optimized using the response surface method-central composite design (RSM-CCD). The type of electrolyte solution and amplitude modulation were found as two most significant factors, among the nine factors tested, which enhance the current response based on PB design. Further optimization using RSM-CCD shows that the optimum values for the tw

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Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Science
Numerical Solution to Recover Time-dependent Coefficient and Free Boundary from Nonlocal and Stefan Type Overdetermination Conditions in Heat Equation
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This paper investigates the recovery for time-dependent coefficient and free boundary for heat equation. They are considered under mass/energy specification and Stefan conditions. The main issue with this problem is that the solution is unstable and sensitive to small contamination of noise in the input data. The Crank-Nicolson finite difference method (FDM) is utilized to solve the direct problem, whilst the inverse problem is viewed as a nonlinear optimization problem. The latter problem is solved numerically using the routine optimization toolbox lsqnonlin from MATLAB. Consequently, the Tikhonov regularization method is used in order to gain stable solutions. The results were compared with their exact solution and tested via

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Publication Date
Wed May 31 2023
Journal Name
Iraqi Geological Journal
A Survey of Infill Well Location Optimization Techniques
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The maximization of the net present value of the investment in oil field improvements is greatly aided by the optimization of well location, which plays a significant role in the production of oil. However, using of optimization methods in well placement developments is exceedingly difficult since the well placement optimization scenario involves a large number of choice variables, objective functions, and restrictions. In addition, a wide variety of computational approaches, both traditional and unconventional, have been applied in order to maximize the efficiency of well installation operations. This research demonstrates how optimization approaches used in well placement have progressed since the last time they were examined. Fol

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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Using Approximation Non-Bayesian Computation with Fuzzy Data to Estimation Inverse Weibull Parameters and Reliability Function
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        In real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson” and the “Expectation-Maximization” techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function i

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