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Optimization Kerosene Bio-degradation by a Local Soil Bacterium Isolate Klebsiella pneumoniae Sp. pneumonia
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Isolated Bacteria from the roots of barley were studied; two stages of processes Isolated and screening were applied in order to find the best bacteria to remove kerosene from soil. The active bacteria are isolated for kerosene degradation process. It has been found that Klebsiella pneumoniae sp. have the highest kerosene degradation which is 88.5%. The optimum conditions of kerosene degradation by Klebsiella pneumonia sp. are pH5, 48hr incubation period, 35°C temperature and 10000ppm the best kerosene concentration. The results 10000ppm showed that the maximum kerosene degradation can reach 99.58% after 48 h of incubation. Higher Kerosene degradation which was 99.83% was obtained at pH5. Kerosene degradation was found to be maximum at 35°C with 98.63%, where 10000ppm kerosene showed the highest degradation at 99.527%. The results indicate that the isolated Klebsiella pneumonia sp. is extremely efficient in degrading kerosene hydrocarbons.

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Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Computational Optimization of the Radial and Spiral Distortion Aberration Coefficients of Magnetic Deflector
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Abstract:The optimum design of the magnetic deflector with the lowest values of the radial and spiral distortion aberration coefficients was computed. The optimized calculations were made using three models, Glaser bell-shaped, Grivet-lenz and exponential models. By using the optimum axial field distribution, the pole pieces shape which gave rise to those field distributions was found by using the reconstruction method. The calculations show that the results of the three models coincide at the lower values of the excitation parameter. In general the Glaser- bell shaped model gives the optimum results at the whole range of the excitation parameter under investigation.The negative values of the spiral distortion aberration coefficient appears

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Robot Arm Path Planning Using Modified Particle Swarm Optimization based on D* algorithm
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Abstract

Much attention has been paid for the use of robot arm in various applications. Therefore, the optimal path finding has a significant role to upgrade and guide the arm movement. The essential function of path planning is to create a path that satisfies the aims of motion including, averting obstacles collision, reducing time interval, decreasing the path traveling cost and satisfying the kinematics constraints. In this paper, the free Cartesian space map of 2-DOF arm is constructed to attain the joints variable at each point without collision. The D*algorithm and Euclidean distance are applied to obtain the exact and estimated distances to the goal respectively. The modified Particle Swarm Optimization al

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Publication Date
Thu Oct 22 2020
Journal Name
2020 4th International Symposium On Multidisciplinary Studies And Innovative Technologies (ismsit)
Artificial Intelligence in Smart Agriculture: Modified Evolutionary Optimization Approach for Plant Disease Identification
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Publication Date
Fri Jan 01 2021
Journal Name
Computers, Materials & Continua
Fused and Modified Evolutionary Optimization of Multiple Intelligent Systems Using ANN, SVM approaches
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Publication Date
Sun Jan 01 2017
Journal Name
Lecture Notes In Computer Science
Constrained Differential Evolution for Cost and Energy Efficiency Optimization in 5G Wireless Networks
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The majority of real-world problems involve not only finding the optimal solution, but also this solution must satisfy one or more constraints. Differential evolution (DE) algorithm with constraints handling has been proposed to solve one of the most fundamental problems in cellular network design. This proposed method has been applied to solve the radio network planning (RNP) in the forthcoming 5G Long Term Evolution (5G LTE) wireless cellular network, that satisfies both deployment cost and energy savings by reducing the number of deployed micro base stations (BSs) in an area of interest. Practically, this has been implemented using constrained strategy that must guarantee good coverage for the users as well. Three differential evolution

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Ant Colony Optimization Based Force-Position Control for Human Lower Limb Rehabilitation Robot
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The aim of human lower limb rehabilitation robot is to regain the ability of motion and to strengthen the weak muscles. This paper proposes the design of a force-position control for a four Degree Of Freedom (4-DOF) lower limb wearable rehabilitation robot. This robot consists of a hip, knee and ankle joints to enable the patient for motion and turn in both directions. The joints are actuated by Pneumatic Muscles Actuators (PMAs). The PMAs have very great potential in medical applications because the similarity to biological muscles. Force-Position control incorporating a Takagi-Sugeno-Kang- three- Proportional-Derivative like Fuzzy Logic (TSK-3-PD) Controllers for position control and three-Proportional (3-P) controllers for force contr

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Publication Date
Fri Jan 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Quasi Semi and Pseudo Semi (p,E)-Convexity in Non-Linear Optimization Programming
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The class of quasi semi -convex functions and pseudo semi -convex functions are presented in this paper by combining the class of -convex functions with the class of quasi semi -convex functions and pseudo semi -convex functions, respectively. Various non-trivial examples are introduced to illustrate the new functions and show their relationships with -convex functions recently introduced in the literature. Different general properties and characteristics of this class of functions are established. In addition, some optimality properties of generalized non-linear optimization problems are discussed. In this generalized optimization problems, we used, as the objective function, quasi semi -convex (respectively, strictly quasi semi -convex

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Community Detection in Modular Complex Networks Using an Improved Particle Swarm Optimization Algorithm
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     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

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Publication Date
Mon Jul 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
Semi E<sup>h</sup>-b-preinvexity and its applications to optimization problems
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Abstract<p>In this paper, the class of semi <italic>E</italic> <sup> <italic>h</italic> </sup>-<italic>b</italic>-preinvex and pseudo <italic>E</italic> <sup> <italic>h</italic> </sup>-b-preinvex functions are defined as an extension of <italic>E-B</italic>-preinvex and <italic>h</italic>-preinvex functions. In this extension the functions <italic>E</italic>:ℝ<sup> <italic>n</italic> </sup> → ℝ<sup> </sup></p> ... Show More
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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
Optimum Design of Power System Stabilizer based on Improved Ant Colony Optimization Algorithm
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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.

 

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