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Prediction of spot welding parameters using fuzzy logic controlling
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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Surface Roughness and Material Removal Rate in Electrochemical Machining Using Taguchi Method
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Electrochemical machining is one of the widely used non-conventional machining processes to machine complex and difficult shapes for electrically conducting materials, such as super alloys, Ti-alloys, alloy steel, tool steel and stainless steel.  Use of optimal ECM process conditions can significantly reduce the ECM operating, tooling, and maintenance cost and can produce components with higher accuracy. This paper studies the effect of process parameters on surface roughness (Ra) and material removal rate (MRR), and the optimization of process conditions in ECM. Experiments were conducted based on Taguchi’s L9 orthogonal array (OA) with three process parameters viz. current, electrolyte concentration, and inter-electrode gap. Sig

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Publication Date
Sat Aug 02 2025
Journal Name
Engineering, Technology & Applied Science Research
A New Method for Face-Based Recognition Using a Fuzzy Face Deep Model
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Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

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Publication Date
Sun Jan 01 2017
Journal Name
Proceedings - European Metallurgical Conference, Emc 2017
Friction stir welding of aluminum alloy AA2024-T351 with OFHC copper
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Scopus
Publication Date
Wed Apr 05 2023
Journal Name
Journal Of Engineering
Study of the Friction Stir Welding For A516 Low Carbon Steel
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The main objective of present work is to describe the feasibility of friction stir welding (FSW) for
joining of low carbon steel with dimensions (3 mm X 80 mm X 150 mm). A matrix (3×3) of welding
parameters (welding speed and tool rotational speed) was used to see influence of each parameter on
properties of welded joint .Series of (FSW) experiments were conducted using CNC milling machine
utilizing the wide range of rotational speed and transverse speed of the machine. Effect of welding
parameters on mechanical properties of weld joints were investigated using different mechanical tests
including (tensile and microhardness tests ). Micro structural change during (FSW) process was
studied and different welding zones

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Crossref
Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Prediction of Compressive Strength of Reinforced Concrete Structural Elements by Using Combined Non-Destructive Tests
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This research is devoted to investigate relationship between both Ultrasonic Pulse Velocity and Rebound Number (Hammer Test) with cube compressive strength and also to study the effect of steel reinforcement on these relationships.
A study was carried out on 32 scale model reinforced concrete elements. Non destructive testing campaign (mainly ultrasonic and rebound hammer tests) made on the same elements. About 72 concrete cubes (15 X 15 X15) were taken from the concrete mixes to check the compressive strength.. Data analyzed.Include the possible correlations between non destructive testing (NDT) and compressive strength (DT) Statistical approach is used for this purpose. A new relationships obtained from correlations results is give

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Publication Date
Tue Mar 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Separation of Bovine Serum Albumin Using Chromatographical Column: Parameters and Simulation
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A liquid-solid chromatography of Bovine Serum Albumin (BSA) on (diethylaminoethyl-cellulose) DEAE-cellulose adsorbent is worked experimentally, to study the effect of changing the influent concentration of (0.125, 0.25, 0.5, and 1 mg/ml) at constant volumetric flow rate Q=1ml/min. And the effect of changing the volumetric flow rate (1, 3, 5, and 10 ml/min) at constant influent concentration of Co=0.125mg/ml. By using a glass column of (1.5cm) I.D and (50cm) length, packed with adsorbent of DEAE-cellulose of height (7cm). The influent is introduced in to the column using peristaltic pump and the effluent concentration is investigated using UV-spectrophotometer at 30oC and 280nm wavelength. A spread (steeper) break-through curve is gained

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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

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Crossref
Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Statistical Methods for Controlling the Quality of Crude Oil Products in Iraq
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The purpose of this study is to measure the levels of quality control for some crude oil products in Iraqi refineries, and how they are close to the international standards, through the application of statistical methods in quality control of oil products in Iraqi refineries. Where the answers of the study sample were applied to a group of Iraqi refinery employees (Al-Dora refinery, Al-Nasiriyah refinery, and Al-Basra refinery) on the principles of quality management control, and according to the different personal characteristics (gender, age, academic qualification, number of years of experience, job level). In order to achieve the objectives of the study, a questionnaire that included (12) items, in order to collect preliminary inform

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Crossref
Publication Date
Mon Dec 01 2014
Journal Name
Annals Of Fuzzy Mathematics And Informatics
Fuzzy n-fold
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In this paper, we introduce the concept of fuzzy n-fold KUideal in KU-algebras, which is a generalization of fuzzy KU-ideal of KUalgebras and we obtain a few properties that is similar to the properties of fuzzy KU-ideal in KU-algebras, see [8]. Furthermore, we construct some algorithms for folding theory applied to KU-ideals in KU-algebras.