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Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the 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. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm namely Particle Swarm Optimization (PSO) algorithm. The numerical simulation results show that the hybrid NARMA-L2 controller with PSO algorithm is more accurate than BPA in terms of achieving fast learning and adjusting the parameters model with minimum number of iterations, minimum number of neurons in the hybrid network and the smooth output one step ahead prediction controller response for the nonlinear CSTR system without oscillation.

 

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Publication Date
Sun Sep 05 2010
Journal Name
Baghdad Science Journal
Design of six electrode Enzial electrostatic lens low aberrations for electron gun
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A computerized investigation has been carried out on the design of six electrodes electrostatic lenses used in electron gun application. The Finite-Element Method (FEM) was used in the solution of Laplace equation for determine the axial potential distribution. The electron trajectory under zero magnification condition. The optical properties, spherical and chromatic aberrations, the object and image focal length and object and image position are calculated. A very good futures for the electron gun with these lenses have been computed where are a beam current of 8.7*10-7A can be supplied using cathode tip of radius 10nm.

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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Mechanical Engineering Research And Developments
Slot Design Procedure for a NACA 4412 at High Angle of Attack
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The main objective of the present work is to find a method increases the efficiency of the airfoil that is used for blade in wind turbine, wing in aircraft, propeller and helicopter (like NACA 4412). By overcoming the separation of flow at high angle of attacks, a slotted airfoil had been used and solved numerically through connecting the pressure side in the bottom surface with the suction side in the top surface of the airfoil to energize the separated flow. Slot exit, width and slope were considered as a parameters of slot configuration to determine the effective design of consideration. Reynolds number was taken as [1.6 x106 ] and the angle of attacks were ranged from (0o - 20o ). The numerical solution with Ansys Fluent commercial prog

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Publication Date
Fri Jul 01 2022
Journal Name
Ieee Transactions On Systems, Man, And Cybernetics: Systems
Design of Robust Terminal Sliding Mode Control for Underactuated Flexible Joint Robot
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Flexible joint robot (FJR) manipulators can offer many attractive features over rigid manipulators, including light weight, safe operation, and high power efficiency. However, the tracking control of the FJR is challenging due to its inherent problems, such as underactuation, coupling, nonlinearities, uncertainties, and unknown external disturbances. In this article, a terminal sliding mode control (TSMC) is proposed for the FJR system to guarantee the finite-time convergence of the systems output, and to achieve the total robustness against the lumped disturbance and estimation error. By using two coordinate transformations, the FJR dynamics is turned into a canonical form. A cascaded finite-time sliding mode observer (CFTSMO) is construct

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Publication Date
Thu Oct 01 2009
Journal Name
Journal Of The College Of Languages (jcl)
Lexical Bundles: Identification and Distinguishing Features
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It is not often  easy to identify a certain group of words as a lexical bundle, since the same set of words can be, in different situations, recognized as idiom,  a collocation, a lexical phrase or a lexical bundle. That is, there are many cases where the overlap among the four types is plausible. Thus, it is important to extract the most identifiable and distinguishable characteristics with which a certain group of words, under certain conditions, can be recognized as a lexical bundle, and this is the task of this paper.

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Publication Date
Mon Feb 01 2021
Journal Name
Pakistan Journal Of Medical & Health Sciences
Entamoeba histolytica, identification in asymptomatic infection
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Background: Reliable detection the etiological agent of amoebic dysentery and extra-intestinal amoebiasis have Public health importance specially in asymptomatic human and animals, Since the acquisition of pet dogs in the recent period has become widespread in our city. Aim: To give correct perception of infection rate in asymptomatic individuals (human and domestic dogs) for the first aspect and about detection and diagnosis of the pathogenic species of Entamoeba histolytica from another morphologically similar and commensal one using the molecular technique in stool samples of asymptomatic individuals the second aspect. Methods: During the study period from the beginning of September 2020 to the end of February 2021, a total of 95 stool s

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Publication Date
Mon Jul 01 2024
Journal Name
International Journal Of Engineering In Computer Science
Human biometric identification: Application and evaluation
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Publication Date
Tue Dec 01 2009
Journal Name
Iraqi Journal Of Physics
Laplacian Operator as Speaker Identification Parameter
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New speaker identification test’s feature, extracted from the differentiated form of the wave file, is presented. Differentiation operation is performed by an operator similar to the Laplacian operator. From the differentiated record’s, two parametric measures have been extracted and used as identifiers for the speaker; i.e. mean-value and number of zero-crossing points.

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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Use projection pursuit regression and neural network to overcome curse of dimensionality
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Abstract

This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model

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Publication Date
Sat Nov 22 2025
Journal Name
Journal Of Baghdad College Of Dentistry
The Effect of Remineralizing Toothpastes on Enamel Surface Roughness after Hybrid Laser Bleaching (An In vitro Study)
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Background: one of the complications of power bleaching is surface roughness of enamel which increases the possibility of post bleaching teeth discoloration. The aim of the present study is to evaluate the effect of toothpaste containing nano hydroxyapatite, NovaMin and kin sense fluoride on surface roughness of human tooth enamel after laser bleaching with 35% hydrogen peroxide bleaching gel. Materials and Methods: Twenty human enamel incisors were cleaned and their labial surface polished up to #1200, then categorized into four equal groups; first group kept without bleaching as a control group, while the remaining three experimental groups were bleached with 35% hydrogen peroxide, and each group treated with a restore paste containing o

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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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