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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
Sat Dec 11 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Extraction and Identification of Phenolic Compounds from the Iraqi Heliotropium europaeum L. plant
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           The plants of genus Heliotropium L. (Boraginaceae) are well-known for containing the toxic metabolites called pyrrolizidine alkaloids (PAs) in addition to the other secondary metabolites. Its spread in the Mediterranean area northwards to central and southern Europe, Asia, South Russia, Caucasia, Afghanistan, Iran, Pakistan, and India, Saudi Arabia, Turkey, and over lower Iraq, Western desert. The present study includes the preparation of various extracts from aerial parts of the Iraqi plant. Fractionation, screening the active constituent, and identification by chromatographic techniques were carried out.Heliotropium  europaeum

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Publication Date
Thu Dec 01 2011
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
ISOLATION AND IDENTIFICATION OF INTESTINAL PARASITES FROM VEGETABLES FROM DIFFERENT MARKETS OF IRAQ.
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This investigation was designed to determine the occurrence of intestinal parasites in fresh
vegetables(Apium graveolense, Lepidium aucheri and Allium porrum), from different markets
as a primary effort in Iraq. Eight genera and species of intestinal parasites appear in
vegetables, they were as follow: Echinococcus sp. 50%,Oxyuris equi 45%,Habronema sp.
45%,Parascaris equroum 31.6%,Strongyloides westrei 30%,Toxocara sp. 18.3%,Ascaris
lumbricoides 11.6% and Hymenolepis sp. 8.3% .The scarcity of fresh water has meant that
urban gardeners are increasingly irrigating their plots with wastewater. This poses a threat to
public health in addition of roaming dogs in open farms. All studied areas showed high rates
of eggs

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

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Publication Date
Wed Jan 01 2020
Journal Name
Solid State Technology
Image Fusion Using A Convolutional Neural Network
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Image Fusion Using A Convolutional Neural Network

Publication Date
Sat Aug 03 2024
Journal Name
Proceedings Of Ninth International Congress On Information And Communication Technology
Offline Signature Verification Based on Neural Network
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The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

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Publication Date
Sun Jun 01 2008
Journal Name
2008 Ieee International Joint Conference On Neural Networks (ieee World Congress On Computational Intelligence)
Linear block code decoder using neural network
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Publication Date
Tue Jun 01 2021
Journal Name
Civil Engineering Journal
Marshall Performance and Volumetric Properties of Styrene-Butadiene-Styrene Modified Asphalt Mixtures
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The durability of asphalt pavement is associated with the properties and performance of the binder. This work-study intended to understand the impact of blending Styrene-Butadiene-Styrene (SBS) to conventional asphalt concrete mixtures and calculating the Optimum Asphalt Content (OAC) for conventional mixture also; compare the performance between SBS modified with the conventional mixture. Two different kinds of asphalt penetration grades, A.C. (40-50) and A.C. (60-70), were improved with 2.5 and 3.5% SBS polymer, respectively. Marshall properties were determined in this work. Optimum Asphalt Content (OAC) was 4.93 and 5.1% by weight of mixture for A.C. (40-50) and (60-70), respectively. Marshall properties results show an increasem

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Publication Date
Wed Aug 13 2025
Journal Name
Mechanics Of Time-dependent Materials
Performance evaluation of highly modified asphalt binders using elastomeric and plastomeric polymers
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Highly Modified Asphalt (HiMA) binders have garnered significant attention due to their superior resistance to rutting, fatigue cracking, and thermal distress under heavy traffic loads and extreme environmental conditions. While elastomeric polymers such as Styrene- Butadiene-Styrene (SBS) have been extensively used in HiMA applications, the potential of plastomeric polymers, including Polyethylene (PE) and Ethylene Vinyl Acetate (EVA), remains largely unexplored. This study aims to evaluate the performance of reference binder (RB) modified with plastomeric HiMA asphalt in comparison to SBS-modified binders and determine the optimal polymer dosage for achieving an optimal balance between rutting resistance and fatigue durability. The experi

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Publication Date
Sun Dec 01 2019
Journal Name
Materials Science-poland
Electrical and thermal characteristics of MWCNTs modified carbon fiber/epoxy composite films
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Abstract<p>To enhance interfacial bonding between carbon fibers and epoxy matrix, the carbon fibers have been modified with multiwall carbon nanotubes (MWCNTs) using the dip- coating technique. FT-IR spectrum of the MWCNTs shows a peak at 1640 cm<sup>−1</sup> corresponding to the stretching mode of the C=C double bond which forms the framework of the carbon nanotube sidewall. The broad peak at 3430 cm<sup>−1</sup> is due to O–H stretching vibration of hydroxyl groups and the peak at 1712 cm<sup>−1</sup> corresponds to the carboxylic (C=O) group attached to the carbon fiber. The peaks at 2927 cm<sup>−1</sup> and 2862 cm<sup>−1</sup> ar</p> ... Show More
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Publication Date
Mon Oct 20 2008
Journal Name
College Of Education Ibn Al-haitham
Study of the Mechanical and Electrical Properties of Modified Unsaturated Polyester Blends
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Study of the Mechanical and Electrical Properties of Modified Unsaturated Polyester Blends