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MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet function. This approach has been performed very successfully, with better results
obtained with the FFNN with modified wavelet activation function (FFMW) when compared with classic
FFNN with Sigmoid activation function (FFS) .One can notice from the simulation that the FFMW can be
capable of identifying the 4-Links of SCARA robot more efficiently than the classic FFS.

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Publication Date
Sun Oct 18 2026
Journal Name
Journal Of Physical Education
The impact of a training field in Lake Al-Razzaza to develop the strength of the legs and arms for young boxers
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Publication Date
Tue Oct 31 2023
Journal Name
College Of Islamic Sciences
Asking for permission and its legal ruling
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Praise be to God, Lord of the Worlds, and the best blessings and peace be upon our master Muhammad and all his family and companions, and those who follow them with goodness until the Day of Judgment. . And after:

God created man in the best manner, and subjugated the universe to him and favored him over the rest of creation when he gave him a mind to contemplate and know how to distinguish between the harmful and the beneficial, the bad and the good, in order to exploit him in achieving the meaning of worship, because it is the highest goal of his creation. God Almighty said (And I did not create the jinn and mankind. Except that they worship them.” [Al-Dhariyat: 56]

If knowing what is harmful from what is beneficial a

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Publication Date
Mon Jul 18 2022
Journal Name
Ieee Access
Moderately Multispike Return Neural Network for SDN Accurate Traffic Awareness in Effective 5G Network Slicing
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Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

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Publication Date
Thu Oct 13 2022
Journal Name
Computation
A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Intelligent Systems
Trip generation modeling for a selected sector in Baghdad city using the artificial neural network
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Abstract<p>This study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to</p> ... Show More
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Publication Date
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
The Identification Party of University Students
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The Political loyalties of the individual considered as the most important democracies through direct psychological identification in a particular party. The political parties regarded as the important elements and the foundations of the democratic system. They have effective interaction between the voters and the government institutions. The aim of the current research is to identify the quality of Islamic, the Civilian parties, and the most preferred for students. also, the research attempt to identify the level of identification  party that the  university students have, and the difference of identification party  according to the gender (male, female), the difference of of social class (upper, middle, poor). The sample

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Publication Date
Thu Nov 17 2016
Journal Name
International Journal Of Computer Applications
Colour Recognizing Robot Arm Equipped with a CMOS Camera and an FPGA
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In this paper a system is designed on an FPGA using a Nios II soft-core processor, to detect the colour of a specific surface and moving a robot arm accordingly. The surface being detected is bounded by a starting mark and an ending mark, to define the region of interest. The surface is also divided into sections as rows and columns and each section can have any colour. Such a system has so many uses like for example warehouses or even in stores where their storing areas can be divided to sections and each section is coloured and a robot arm collects objects from these sections according to the section’s colour also the robot arm can organize objects in sections according to the section’s colour.

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Publication Date
Wed Mar 29 2023
Journal Name
Journal Of Robotics
Real-Time SLAM Mobile Robot and Navigation Based on Cloud-Based Implementation
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This study investigates the feasibility of a mobile robot navigating and discovering its location in unknown environments, followed by the creation of maps of these navigated environments for future use. First, a real mobile robot named TurtleBot3 Burger was used to achieve the simultaneous localization and mapping (SLAM) technique for a complex environment with 12 obstacles of different sizes based on the Rviz library, which is built on the robot operating system (ROS) booted in Linux. It is possible to control the robot and perform this process remotely by using an Amazon Elastic Compute Cloud (Amazon EC2) instance service. Then, the map to the Amazon Simple Storage Service (Amazon S3) cloud was uploaded. This provides a database

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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Using Fuzzy Games Theory to Determine the optimal Strategy for The Mobile Phone Networks in The Baghdad And Basra governorates
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      The objective of this research is employ the special cases of  function  trapezoid in the composition of fuzzy sets to make decision within the framework of the theory of games traditional to determine the best strategy for the mobile phone networks in the province of  Baghdad and Basra, has been the adoption of different periods of the  functions belonging to see the change happening in the matrix matches and the impact  that the strategies  and decision-making  available to each player and the impact on  societ

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Publication Date
Thu Aug 01 2024
Journal Name
Water Practice &amp; Technology
Artificial neural network and response surface methodology for modeling oil content in produced water from an Iraqi oil field
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ABSTRACT<p>The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value &lt;0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe</p> ... Show More
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