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bsj-3847
Fuzzy-assignment Model by Using Linguistic Variables
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      This work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.

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Publication Date
Sat Feb 28 2015
Journal Name
Al-khwarizmi Engineering Journal
Stabilizing Gap of Pole Electric Arc Furnace Using Smart Hydraulic System
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Abstract

Electric arc furnace applications in industry are related to position system of its pole, up and down of pole. The pole should be set the certain gap. These setting are needed to calibrate. It is done manually. In this research will proposed smart hydraulic to make this pole works as intelligent using proportional directional control valve. The output of this research will develop and improve the working of the electric arc furnace. This research requires study and design of the system to achieve the purpose and representation using Automation Studio software (AS), in addition to mathematically analyzed and where they were building a laboratory device similar to the design and conduct experiments to stud

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Publication Date
Fri Mar 15 2019
Journal Name
Al-khwarizmi Engineering Journal
Desalination of Highly Saline Water Using Direct Contact Membrane Distillation (DCMD)
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In this work, laboratory experiments were carried out to verify direct contact membrane distillation system’s performance in highly saline water desalination. The study included the investigation of various operating conditions, like feed flow rate, temperature and concentration of NaCl solution and their impact on the permeation flux were discussed. 16 cm2 of a flat sheet membrane module with commercial poly-tetra-fluoroethylene (PTFE) membrane, which has 0.22 μm pore size, 96 µm thickness and 78% average porosity, was used. A high salt rejection factor was obtained greater than 99.9%, and the permeation flux up to 17.27 kg/m2.h was achieved at 65°C for hot feed side and 20°C for cold side stream.

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption
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A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
Evaluations of Potable Water Tanks Epoxy Coatings Performance Using Electrochemical Impedance Spectroscopic Method
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Abstract  

The aim of this paper is to investigate and discuss the mechanisms of corrosion of epoxy coatings used for potable water tanks. Two distinct types of Jotun epoxy coatings: Tankguard 412 contained polyamine cured epoxy and Penguard HB contained polyamide cured epoxy, were tested and studied using the electrochemical impedance spectroscopic (EIS) method. The porosity of epoxy coatings was determined using EIS method. The obtained results showed that the two epoxy coatings have excellent behavior when applied and tested in potable water of Basrah city. Polyamine is more resistance to water corrosion compared to polyamide curing epoxy and has high impedance values. Microscopic inspection after te

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Wed Jan 01 2020
Journal Name
2nd International Conference On Materials Engineering & Science (iconmeas 2019)
A kinetic model for prodigiosin production by Serratia marcescens as a bio-colorant in bioreactor
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Publication Date
Mon Mar 01 2021
Journal Name
Desalination And Water Treatment
Extraction model to remove antibiotics from aqueous solution by emulsion and Pickering emulsion liquid membrane
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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Optimal Dimensions of Small Hydraulic Structure Cutoffs Using Coupled Genetic Algorithm and ANN Model
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A genetic algorithm model coupled with artificial neural network model was developed to find the optimal values of upstream, downstream cutoff lengths, length of floor and length of downstream protection required for a hydraulic structure. These were obtained for a given maximum difference head, depth of impervious layer and degree of anisotropy. The objective function to be minimized was the cost function with relative cost coefficients for the different dimensions obtained. Constraints used were those that satisfy a factor of safety of 2 against uplift pressure failure and 3 against piping failure.
Different cases reaching 1200 were modeled and analyzed using geo-studio modeling, with different values of input variables. The soil wa

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Publication Date
Fri May 13 2022
Journal Name
Electronics
Fuzzy Luenberger Observer Design for Nonlinear Flexible Joint Robot Manipulator
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The process of controlling a Flexible Joint Robot Manipulator (FJRM) requires additional sensors for measuring the state variables of flexible joints. Therefore, taking the elasticity into account adds a lot of complexity as all the additional sensors must be taken into account during the control process. This paper proposes a nonlinear observer that controls FJRM, without requiring equipment sensors for measuring the states. The nonlinear state equations are derived in detail for the FJRM where nonlinearity, of order three, is considered. The Takagi–Sugeno Fuzzy Model (T-SFM) technique is applied to linearize the FJRM system. The Luenberger observer is designed to estimate the unmeasured states using error correction. The develop

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