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A Light Weight Multi-Objective Task Offloading Optimization for Vehicular Fog Computing
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Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mobile vehicles. Several studies have tackled the task offloading problem in the VFC field. However, recent studies have not carefully addressed the transmission path to the destination node and did not consider the energy consumption of vehicles. This paper aims to optimize the task offloading process in the VFC system in terms of latency and energy objectives under deadline constraint by adopting a Multi-Objective Evolutionary Algorithm (MOEA). Road Side Units (RSUs) x-Vehicles Mutli-Objective Computation offloading method (RxV-MOC) is proposed, where an elite of vehicles are utilized as fog nodes for tasks execution and all vehicles in the system are utilized for tasks transmission. The well-known Dijkstra's algorithm is adopted to find the minimum path between each two nodes. The simulation results show that the RxV-MOC has reduced significantly the energy consumption and latency for the VFC system in comparison with First-Fit algorithm, Best-Fit algorithm, and the MOC method.

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Publication Date
Thu Apr 01 2021
Journal Name
Journal Of Engineering Science And Technology
Applying box-behnken design with statistical optimization for removal vat orange dye from aqueous solution using kaolin
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Publication Date
Sat Mar 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Optimization of Separator Size and Operating Pressure for Three-phase Separators in the West Qurna1 Oil Field
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An optimization study was conducted to determine the optimal operating pressure for the oil and gas separation vessels in the West Qurna 1 oil field. The ASPEN HYSYS software was employed as an effective tool to analyze the optimal pressure for the second and third-stage separators while maintaining a constant operating pressure for the first stage. The analysis involved 10 cases for each separation stage, revealing that the operating pressure of 3.0 Kg/cm2 and 0.7 Kg/cm2 for the second and third stages, respectively, yielded the optimum oil recovery to the flow tank. These pressure set points were selected based on serval factors including API gravity, oil formation volume factor, and gas-oil ratio from the flow tank.    To impro

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Publication Date
Mon Sep 13 2021
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Cutting Parameters for Milling Process of (4032) Al-Alloy using Taguchi-Based Grey Relational Analysis
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The objective of this work is to study the influence of end milling cutting process parameters, tool material and geometry on multi-response outputs for 4032 Al-alloy. This can be done by proposing an approach that combines Taguchi method with grey relational analysis. Three cutting parameters have been selected (spindle speed, feed rate and cut depth) with three levels for each parameter. Three tools with different materials and geometry have been also used to design the experimental tests and runs based on matrix L9. The end milling process with several output characteristics is solved using a grey relational analysis. The results of analysis of variance (ANOVA) showed that the major influencing parameters on multi-objective response w

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Publication Date
Tue Sep 04 2018
Journal Name
Al-khwarizmi Engineering Journal
Modified Elman Neural-PID Controller Design for DC-DC Buck Converter System Based on Dolphin Echolocation Optimization
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This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Classical and Statistical Optimization of Medium Composition for Promoting Prodigiosin Produced by Local Isolate of Serratia Marcescens
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Prodigiosin is a ‘natural red pigment produced by Serratia marcescens which exhibits immunosuppressive and anticancer properties in addition to antimicrobial activities. This work presents an attempt to maximize the production of prodigiosin by two different strategies: one factor at time (OFAT) and statistical optimization. The result of OFAT revealed that sucrose and peptone were the best carbon and nitrogen sources for pigment production with concentration of prodigiosin of about 135 mg/ L. This value was increased to 331.6mg/ L with an optimized ratio of C/N (60:40) and reached 356.8 with pH 6 and 2% inoculum size at end of classical optimization. Statistical experimental design based on Response surface methodology was co

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Publication Date
Tue Dec 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
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 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Ecological Engineering
Modification of Electro-Fenton Process with Granular Activated Carbon for Phenol Degradation – Optimization by Response Surface Methodology
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As a result of rapid industrialization and population development, toxic chemicals have been introduced into water systems in recent decades. Because of its excellent efficiency and simple design, the three-dimensional (3D) electro-Fenton method has been used for the treatment of wastewater. The goal of the current study is to explore the efficiency of phenol removal by the 3D electro-Fenton process, which is one of the advanced oxidation processes (AOPs). In the present work, the effect of the addition of granular activated carbon (GAC) particles to the electro-Fenton system as the third electrode would be investigated in the presence of graphite as the anode and nickel foam as the cathode, which is the source of electro-generated hydrogen

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Publication Date
Fri May 28 2021
Journal Name
Journal Of Microbiology And Biotechnology
Bioactive Levan-Type Exopolysaccharide Produced by <i>Pantoea agglomerans</i> ZMR7: Characterization and Optimization for Enhanced Production
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Publication Date
Thu Feb 27 2025
Journal Name
Journal Of Lifestyle And Sdgs Review
Integrating Quantum Computing and Predictive Analytics and Their Role in Reducing Costs and Achieving Sustainable Development Goals
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Objectives: The research aims to demonstrate the integration between Quantum Computing (QC) and Predictive Analysis (PA) and their role in reducing costs while achieving Sustainable Development Goals (SDGs). The study addresses the inefficiencies in calculating and measuring product costs under traditional systems and examines how QC and PA can enhance cost reduction and product quality to better meet customer needs. Additionally, the research seeks to strengthen the theoretical framework with practical applications, illustrating how this integration improves a company’s competitive position while promoting social, environmental, and economic sustainability.   Methods: The study employs a descriptive analytical approach, focusi

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Publication Date
Wed Mar 04 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
The Effect of Using Fit Light Exercise in Some Physiological Indicators and Smash Shot for Badminton’s Players
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The reason for applying the project is for the development of some physiological variables and skill performance using a device for the first time applied in Iraq to a sample of badminton players, and this device has a patent on 7/2/2019. An experimental method is used for a sample of (12) players from (Al-Orthodoxy club). The experimental group is applied the proposal technique, while, the control group is instructed by the coach.The results of the research attribute to the role of the proposal exercises of fit light technology, thus, this technology has increased the attention and focusing of the sample and some physiological variables and smash shot skill. It has been concluded that the exercises using fit light technology is helped to i

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