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A new multi-objective evolutionary framework for community mining in dynamic social networks
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Publication Date
Sun Mar 31 2013
Journal Name
Inventi Impact: Artificial Intelligence
SIMULATION OF IDENTIFICATION AND CONTROL OF SCARA ROBOT USING MODIFIED RECURRENT NEURAL NETWORKS
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

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Publication Date
Wed Dec 27 2017
Journal Name
Al-khwarizmi Engineering Journal
Human Face Recognition Using GABOR Filter And Different Self Organizing Maps Neural Networks
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This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Recognizing Different Foot Deformities Using FSR Sensors by Static Classification of Neural Networks
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Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar

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Publication Date
Fri May 01 2026
Journal Name
Retos
Using artificial neural networks to assign soccer players by physical and motor abilities
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Introduction: The introduction of analytics tools in sports indicates that artificial neural networks can be one of the intelligent approaches to process complex data and identify patterns that help players move according to their most suitable positions. Objective: The purpose of this research is to investigate the possibility of using artificial neural networks to determine the physical and motor abilities of football players and determine their suitable playing positions based on exact quantitative indicators. Method: The study sample consists of 45 youth players aged (15–16) years from the Espanyol Football Academy in Baghdad. The results are analyzed using a multilayer perceptron (MLP) artificial neural network model to ident

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Publication Date
Sun Aug 01 2021
Journal Name
Eurasian Chemical Communications
New sensitive turbidimetric method for determination of losartan potassium in pharmaceutical formulations using flow injection combined with homemade turbidimeter
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Publication Date
Thu Jul 11 2024
Journal Name
الموئتمخر الدولي للعلم والتعليم
SUFFIXAL METHOD FOR FORMING NEW VOCABULARY IN RUSSIAN AND ARARBIAN LANGUAGES AND ITS INFLUENCE ON ACHIEVEMENT OF TRANSLATION ADEQUACY
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Abstract. In this scientific work, we investigate the problem of the practical necessity of achieving the adequacy of translation activities with active translation from Russian into Arabic in various fields of translation. Based on the material of the latest suffix vocabulary, a serious attempt is made to clarify and specify the rules for the development of translator's intuition when translating from Russian into Arabic and vice versa. Based on the material collected by the latest suffix vocabulary, we try to make an attempt to reveal the role of suffix word creation in highlighting the general rules for achieving translation equivalence. The paper examines the process of creating words in multi-family languages, the difference between th

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Publication Date
Fri Sep 05 2014
Journal Name
Engineering And Technology Journal
New Method to Increase the Ability of the Water for Dissolving Total Salts in Soil by Using the Magnetism
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Publication Date
Thu Dec 01 2016
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
NEW HOST PLANTS RECORD FOR THE BROWN SOFT SCALE COCCUS HESPERIDUM LINNAEUS, 1758 (HEMIPTERA: COCCIDAE) IN BAGHDAD PROVINCE, IRAQ
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    An investigation was provided in this work for the host range of brown soft scale Coccus hesperidum Linnaeus in Baghdad Province.  Five plant species were found infected by this insect, three of these species, Citrusaurantium L. (Rutaceae); Nerium oleander L. (Apocynaceae); Ficuscarica L. (Moraceae) reported earlier, and the remaining two, Dahlia pinnata Cav. (Asteraceae) and Myrtuscommunis L. (Myrtaceae) are recordedhere for the first time as host plants for this pest.

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Publication Date
Tue Dec 22 2020
Journal Name
Collaboration And Integration In Construction, Engineering, Management And Technology
A Hybrid Conceptual Model for BIM Adoption in Facilities Management: A Descriptive Analysis for the Collected Data
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Publication Date
Thu Dec 15 2022
Journal Name
Journal Of Petroleum Research And Studies
Selection of an Optimum Drilling Fluid Model to Enhance Mud Hydraulic System Using Neural Networks in Iraqi Oil Field
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In drilling processes, the rheological properties pointed to the nature of the run-off and the composition of the drilling mud. Drilling mud performance can be assessed for solving the problems of the hole cleaning, fluid management, and hydraulics controls. The rheology factors are typically termed through the following parameters: Yield Point (Yp) and Plastic Viscosity (μp). The relation of (YP/ μp) is used for measuring of levelling for flow. High YP/ μp percentages are responsible for well cuttings transportation through laminar flow. The adequate values of (YP/ μp) are between 0 to 1 for the rheological models which used in drilling. This is what appeared in most of the models that were used in this study. The pressure loss

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