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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 better than RS and RW in identification the forward dynamics and provides good results in the Direct Inverse Neuro- Controller (DINC).

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Publication Date
Thu May 23 2019
Journal Name
The International Journal Of Artificial Organs
Real-time classification of shoulder girdle motions for multifunctional prosthetic hand control: A preliminary study
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In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho

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Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Biological Control of Acaudalerodes Rachipora (Singh) (Hemiptera: Alerodidae) by the Entomopathogenic Fungi on in Field
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This study was conducted in the College of Agriculture fields /University of Baghdad, during Autumn 2013. This study was aimed to examine the mortality rate on the all black fly stages of Acaudalerodes rachipora Singh) by the biotic fungus Beuveria bassiana. The results of a preliminary survey showed that the samples of Ziziphus spaina christi were infested by blakflies in Agriculture collage during Autumn seasons of 2013 , the presence of species of black flies A. rachipora on the lower surface of the leaf, the study aimed to study and research the effects of fungus B. bassiana on black fly A. rachipora. After six days of treatment results showed the continued superiority 106 spore / ml trends in the western, southern and

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Publication Date
Tue Jun 30 2015
Journal Name
Al-kindy College Medical Journal
Evidence Based Updating of HbA1c Targets: Global Guidelines forGlycemic Control in Type 2 Diabetes Mellitus
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Background:Measurement of hemoglobin A1c (A1C) is a renowned tactic for gauging long-term glycemic control, and exemplifies an outstanding influence to the quality of care in diabetic patients.The concept of targets is open to criticism; they may be unattainable, or limit what could be attained, and in addition they may be economically difficult to attain. However, without some form of targeted control of an asymptomatic condition it becomes difficult to promote care at allObjectives: The present article aims to address the most recent evidence-based global guidelines of A1C targets intended for glycemic control in Type 2 Diabetes Mellitus (T2D).Key messages:Rationale for Treatment Targets of A1C includesevidence for microvascular and ma

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Publication Date
Mon Oct 10 2022
Journal Name
International Journal Of Mathematics In Operational Research
Modelling time-series process of an agricultural crop production process by EWMA quality control chart
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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of a Kinematic Neural Controller for Mobile Robots based on Enhanced Hybrid Firefly-Artificial Bee Colony Algorithm
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The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

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Publication Date
Tue Aug 27 2024
Journal Name
Tem Journal
Preparing the Electrical Signal Data of the Heart by Performing Segmentation Based on the Neural Network U-Net
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Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

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Publication Date
Sat Mar 01 2025
Journal Name
Iraqi Journal Of Physics
Design an Efficient Neural Network to Determine the Rate of Contamination in the Tigris River in Baghdad City
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This article proposes a new technique for determining the rate of contamination. First, a generative adversarial neural network (ANN) parallel processing technique is constructed and trained using real and secret images. Then, after the model is stabilized, the real image is passed to the generator. Finally, the generator creates an image that is visually similar to the secret image, thus achieving the same effect as the secret image transmission. Experimental results show that this technique has a good effect on the security of secret information transmission and increases the capacity of information hiding. The metric signal of noise, a structural similarity index measure, was used to determine the success of colour image-hiding t

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
The Effect Of Optimizers On The Generalizability Additive Neural Attention For Customer Support Twitter Dataset In Chatbot Application
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When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

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Publication Date
Wed Jan 29 2020
Journal Name
Advances In Rheumatology
Neutrophil/lymphocyte and platelet/lymphocyte ratios as potential markers of disease activity in patients with Ankylosing spondylitis: a case-control study
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Abstract<sec> <title>Background

The neutrophil/ lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) have the potential to be inflammatory markers that reflect the activity of many inflammatory diseases. The aim of this study was to evaluate the NLR and PLR as potential markers of disease activity in patients with ankylosing spondylitis.

Methods

The study involved 132 patients with ankylosing spondylitis and 81 healthy controls matched in terms of age and gender. Their sociodemographic data, disease activity scores using the Bath Ankylosing

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Publication Date
Thu Mar 15 2018
Journal Name
Journal Of Baghdad College Of Dentistry
Assessment of Salivary Total Antioxidants Capacity Levels of Patients with Chronic Periodontitis in Comparison to Healthy Control
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Background: Chronic periodontitis (CP) is greatly prevalent condition of inflammatory behavior. Salivary biomarker total antioxidants capacity (T-AOC) status, may be related to both periodontal condition and oral hygiene. Aims of the study: To assess the level of salivary T-AOC of patients with chronic periodontitis in comparison to healthy control and to correlate between the level of this marker with the clinical periodontal parameters (plaque index (PLI), gingival index (GI), bleeding on probing (BOP), probing pocket depth (PPD), and clinical attachment level (CAL)). Materials and Methods: Ninety subjects of males and females with an age ranged between (35-55) years were participated in this study. Participants were divided into two grou

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