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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
Tue Sep 01 2009
Journal Name
Al-nahrain Journal Of Science
Colorimetric assay of aspirin using modified method
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In this research, we did this qualitative and quantitative study in order to improve the assay of aspirin colorimetrically using visible spectrophotometer. This method depends on aqueous hydrolysis of aspirin and then treating it with the ferric chloride acidic solution to give violet colored complex with salicylic acid, as a result of aspirin hydrolysis, which has a maximum absorption at 530nm. This procedure was applied to determine the purity of aspirin powder and tablet. The results were approximately comparative so that the linearity was observed in the high value of both correlation coefficient (R= 0.998) and Determination Coefficient or Linearity (R2= 0.996) while the molar absorpitivity was 1.3× 103 mole

Publication Date
Fri Nov 24 2023
Journal Name
Iraqi Journal Of Science
Species Identification and Strain Differentiation of Dermatophyte by (GACA)4-Primer based PCR
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Dermatophytes are a group of morphologically and physiologically related molds some of which cause well defined infections: dermatophytoses (tineas or ringworm). The present study aims at identification of dermatophytes species and varieties from patients in Wasit province-Iraq using molecular approach based PCR fingerprint.
The short oligonucleotide (GACA)4 is a microsatellite primer was used in this study for identification of dermatophyte isolates. The results identified different species and varieties among dermatophytes. The numbers of resulting PCR bands ranged from 1 to 4 (size range, 600bp to 1600bp) for each species. The resulting patterns were distinct for Trichophyton and Microsporum species and varieties.
Trichophyton s

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Publication Date
Sat Dec 31 2011
Journal Name
Al-khwarizmi Engineering Journal
Path Planning Control for Mobile Robot
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Autonomous motion planning is important area of robotics research. This type of planning relieves human operator from tedious job of motion planning. This reduces the possibility of human error and increase efficiency of whole process.

This research presents a new algorithm to plan path for autonomous mobile robot based on image processing techniques by using wireless camera that provides the desired image for the unknown environment . The proposed algorithm is applied on this image to obtain a optimal path for the robot. It is based on the observation and analysis of the obstacles that lying in the straight path between the start and the goal point by detecting these obstacles, analyzing and studying their shapes, positions and

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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Detection and Classification of The Osteoarthritis in Knee Joint Using Transfer Learning with Convolutional Neural Networks (CNNs)
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    Osteoarthritis (OA) is a disease of human joints, especially the knee joint, due to significant weight of the body. This disease leads to rupture and degeneration of parts of the cartilage in the knee joint, which causes severe pain. Diagnosis of this disease can be obtained through X-ray. Deep learning has become a popular solution to medical issues due to its fast progress in recent years. This research aims to design and build a classification system to minimize the burden on doctors and help radiologists to assess the severity of the pain, enable them to make an optimal diagnosis and describe the correct treatment. Deep learning-based approaches, such as Convolution Neural Networks (CNNs), have been used to detect knee OA usin

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Publication Date
Mon Feb 08 2016
Journal Name
Iraqi Journal Of Science,
Synthesis, Identification and Evaluation Biological Activity for Some New Triazole, Triazoline and Tetrazoline Derivatives From 2-Mercapto-3- phenyl-4(3H)Quinazolinone
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This research, involved synthesis of some new 1,2,3-triazoline and 1,2,3,4- tetrazole derivatives from antharanilic acid as starting material .The first step includes formation of 2-Mercapto-3-phenyl-4(3H)Quinazolinone (0) through reacted of anthranilic acid with phenylisothiocyanate in ethanol, then compound (0) reaction with chloro acetyl chloride in dimethyl foramamide (DMF) to prepare intermediate S-(α-chloroaceto-2-yl)-3-phenylquinazolin-4(3H)-one (1); compound (1) reacted with sodium azide to yield S-(α-azidoaceto-2-yl)-3-phenylquinazolin-4(3H)-one (2), while Schiff bases (3-10) were prepared from condensation of substituted primary aromatic amines with different aromatic aldehydes in absolute ethanol as a solvent. Compound (2)

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Publication Date
Mon May 20 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Application of Iterative Method for Solving Higher Order Integro-Differential Equations
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The main aim of this paper is to apply a new technique suggested by Temimi and Ansari namely (TAM) for solving higher order Integro-Differential Equations. These equations are commonly hard to handle analytically so it is request numerical methods to get an efficient approximate solution. Series solutions of the problem under consideration are presented by means of the Iterative Method (IM). The numerical results show that the method is effective, accurate and easy to implement rapidly convergent series to the exact solution with minimum amount of computation. The MATLAB is used as a software for the calculations.           

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Algorithms Based Nonlinear PID Neural Trajectory Tracking Controller for the Differential Wheeled Mobile Robot Model
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This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi

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Publication Date
Sun Jun 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Effect of Microwave Treatment in Graphite Anode for Microbial Fuel Cell and Its Application in Biosensor
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The electrode in the microbial fuel cell has a significant effect on cell performance. The treatment of the electrode is a crucial step to make the electrode surface more habitable for bacteria growth, thus, increases the power production as well as waste treatment. In the current study, two graphite electrodes were treated by a microwave. The first electrode was treated with 100W microwave energy, while the second one was treated with 600W microwave energy. There is a significant enhancement in the surface of the graphite anode after the pretreatment process. The results show an increase in the power density from 10 mW/m2 to 15 mW/m2 with 100w treatment and to 13.47 mW/m2 with 600w treatment. An organic

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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

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