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Effect of laser process an inclined surface cutting of mild steel then analysis data statistically by RSM
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The regression analysis process is used to study and predicate the surface response by using the design of experiment (DOE) as well as roughness calculation through developing a mathematical model. In this study; response surface methodology and the particular solution technique are used. Design of experiment used a series of the structured statistical analytic approach to investigate the relationship between some parameters and their responses. Surface roughness is one of the important parameters which play an important role. Also, its found that the cutting speed can result in small effects on surface roughness. This work is focusing on all considerations to make interaction between the parameters (position of influence) because laser power directly depends on cutting speed with high gas pressure and vice versa to obtain a less surface roughness. Data analysis showed that the lower value for roughness was (0.68) µm and the high roughness was (8.56) µm.  The model values for considered fit are suggested to be as (R2) = 51.76%. The selected coefficient is referred to the amount of model variation in the response. The adjusted value of (R2) = 8.34% will calculate the number of forecasting model and is normally useful for comparing models with different numbers of predictions. The (F) test is used to determine whether interaction and major effects are significant. The p-value is the probability of obtaining a statistic test which is considered as the extreme of actual calculated values if the null hypothesis is true. A commonly cut-off value that used for the p-value is (0.05). This value is used to be the active contribution to investigate the correlation between laser machining parameter with the surface roughness. Also the goal of this research highlights the experimental control parameters of mild steel laser processing with their responses.

 

 

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Publication Date
Mon Jun 22 2020
Journal Name
Baghdad Science Journal
Using Evolving Algorithms to Cryptanalysis Nonlinear Cryptosystems
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            In this paper, new method have been investigated using evolving algorithms (EA's) to cryptanalysis one of the nonlinear stream cipher cryptosystems which depends on the Linear Feedback Shift Register (LFSR) unit by using cipher text-only attack. Genetic Algorithm (GA) and Ant Colony Optimization (ACO) which are used for attacking one of the nonlinear cryptosystems called "shrinking generator" using different lengths of cipher text and different lengths of combined LFSRs. GA and ACO proved their good performance in finding the initial values of the combined LFSRs. This work can be considered as a warning for a stream cipher designer to avoid the weak points, which may be f

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Publication Date
Thu Mar 19 2026
Journal Name
International Journal Of Mechatronics And Applied Mechanics
NONLINEAR TRACKING MOTION CONTROL BASED MULTI-VERSE OPTIMIZATION FOR MAGNETIC LEVITATION SYSTEMS
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Magnetic levitation (Maglev) systems are employed in a wide range of applications and are therefore of significant practical importance, which has led to growing research interest. This paper presents the design of a terminal synergetic control (TSC) and feedback linearization-based proportional-integral-derivative plus second-order derivative (FL-PIDD2) controller for the Maglev system. For developing the control law of both controllers, the mathematical model of the Maglev system is converted into a canonical system where the expression of the nonlinearity is displayed in the last differential dynamic equation of the system. The determination of the TSC and FL-PIDD2 gains for achieving the desired dynamic response is carried out using the

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
SBOA: A Novel Heuristic Optimization Algorithm
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A new human-based heuristic optimization method, named the Snooker-Based Optimization Algorithm (SBOA), is introduced in this study. The inspiration for this method is drawn from the traits of sales elites—those qualities every salesperson aspires to possess. Typically, salespersons strive to enhance their skills through autonomous learning or by seeking guidance from others. Furthermore, they engage in regular communication with customers to gain approval for their products or services. Building upon this concept, SBOA aims to find the optimal solution within a given search space, traversing all positions to obtain all possible values. To assesses the feasibility and effectiveness of SBOA in comparison to other algorithms, we conducte

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
A Cognitive Hybrid Tuning Control Algorithm Design for Nonlinear Path-Tracking Controller for Wheeled Mobile Robot
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Abstract

This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is m

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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Wed May 07 2025
Journal Name
Applied Science And Engineering Progress
Optimizing Methyl Orange Degradation via Electro-Fenton with Copper Foam Cathode: A Comparative Approach Using Iron Waste vs. Iron Salts and Exploring Catalyst and Cathode Durability
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The use of foam electrodes as a cathode has proven its efficiency in wastewater treatment. In this study, methyl orange (MO) was treated by Electro-Fenton technology (EFT) using a copper foam (Cf) as a cathode. EFT was an advanced strategy for MO degradation, which accomplished excellent degradation efficiency (%ReMO) exceeded 98% over 35 min treatment period at prime conditions using 0.124 mM of iron salts (FeSO4.7H2O), 0.3 LPM of air flow, 0.2 mA/cm2 of current density (CD), and initial pH of 3.0. The outcomes showed that the air flow rate had the main impact on the %ReMO. Furthermore, the contribution of anodic oxidation (AO) to dye removal was investigated to distinguish its role relative to the EFT mechanism, revealing that the MO degr

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
New Method for the On-Line Determination of Molybdenum Via New Microphotometric Home Mode Instrument, Using Hight Emitting Diode as a Variable Intensity Radiant Source with a Miniture Photosilicone Diode Detector for System: Molybdenum(VI)-Hydrogen Peroxide-Ammonium Solution
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This research work aims to the determination of molybdenum (VI) ion via the formation of peroxy molybdenum compounds which has red-brown colour with absorbance wave length at 455nm for the system of ammonia solution-hydrogen peroxide-molybdenum (VI) using a completely newly developed microphotometer based on the ON-Line measurement. Variation of responses expressed in millivolt. A correlation coefficient of 0.9925 for the range of 2.5-150 ?g.ml-1 with percentage linearity of 98.50%. A detection limit of 0.25 ?g.ml-1 was obtained. All physical and chemical variable were optimized interferences of cation and anion were studied classical method of measurement were done and compared well with newly on-line measurements. Application for the use

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Publication Date
Tue Jan 01 2019
Journal Name
Advances In Materials Physics And Chemistry
The Role of Cooling Condition on the Superconducting Properties of Tl<sub>2-x</sub>Hg<sub>x</sub>Sr<sub>2</sub>Ca<sub>2</sub>Cu<sub>3</sub>O<sub>10+δ</sub> System
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Publication Date
Fri Oct 31 2025
Journal Name
Mathematical Modelling Of Engineering Problems
Modified Optimization Algorithms for Infinite Integro-Differential Equations via Generalized Laguerre Polynomials
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This study emphasizes the infinite-boundary integro-differential equation. To examine the approximate solution of the problem, two modified optimization algorithms are proposed based on generalized Laguerre functions. In the first technique, the proposed method is applied to the original problem by approximating the solution using the truncated generalized Laguerre polynomial of the unknown function, optimizing coefficients through error minimization, and transforming the integro-differential equation into an algebraic equation. In contrast, the second approach incorporates a penalty term into the objective function to effectively enforce boundary and integral constraints. This technique reduces the original problem to a mathematical optimi

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
3-D Packing in Container using Teaching Learning Based Optimization Algorithm
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The paper aims to propose Teaching Learning based Optimization (TLBO) algorithm to solve 3-D packing problem in containers. The objective which can be presented in a mathematical model is optimizing the space usage in a container. Besides the interaction effect between students and teacher, this algorithm also observes the learning process between students in the classroom which does not need any control parameters. Thus, TLBO provides the teachers phase and students phase as its main updating process to find the best solution. More precisely, to validate the algorithm effectiveness, it was implemented in three sample cases. There was small data which had 5 size-types of items with 12 units, medium data which had 10 size-types of items w

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