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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 Jun 04 2026
Journal Name
International Journal Of Robotics And Control Systems
Integrating Multimodal Emotion Recognition with Deep Q-Learning for Adaptive Social Robot Interaction
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Publication Date
Sun Oct 09 2022
Journal Name
المجلة الع ا رقية لعلوم التربة
ISOLATION AND IDENTIFICATION OF MULTI-DRUD RESISTANCE STAPHYLOCOCCUS AUREUS WHICH ISOLATES FROM IRRIGATION AND WASTEWATER IN BAGHDAD CITY*
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A total number of 68 water samples was revealed 20 isolates being Staphylococcus aureus. Irrigation water isolates represented 25% of isolates while wastewater 75%. all isolates were identified by morphological, microscopial, biochemical tests and VITEK®2 Compact. Bacterial isolates were subjected to 16 antibiotics, all irrigation water and wastewater isolates were resistant to penicillin while they were fully sensitive to Ciprofloxcin. Irrigation water isolates showed relatively greater multi-drug resistance than wastewater, wherein irrigation water isolates showed 100% multi-drug resistance while wastewater isolates showed 73.3% multi-drug resistance, indicating the ability of S. aureus MDR to move from one site to another, which means t

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Publication Date
Thu Dec 28 2023
Journal Name
The Iraqi Journal Of Veterinary Medicine
Molecular Identification and Phylogenetic Analysis of Salmonella‎ species ‎Isolated from Diarrheal Children and Dogs in Baghdad Governorate, ‎Iraq‎
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This work aimed to use conventional PCR to identify Salmonella‎ spp. that ‎were isolated from diarrheal children and healthy and diarrheic dogs based on four ‎virulence genes, hilA, stn, spvR‎, and marT. Sixteen Salmonella‎ isolates including: 9 ‎isolated from children's diarrhea from three species (S. Typhimurium, S. Enteritidis, S. ‎Typhi) and seven isolated from dogs including (S. Typhimurium, S. Enteritidis, S. ‎Muenchen), were identified primarily by several methods. The PCR products of the 16S ‎rRNA gene were sequenced and examined using BLAST analysis to find differences and ‎similarities between these Iraqi isolates and already-known global strains in order to ‎construct the phylogenetic tree of S.

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Development and Assessment of Feed Forward Back Propagation Neural Network Models to Predict Sunshine Duration
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         The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Some Subclasses of Univalent and Bi-Univalent Functions Related to K-Fibonacci Numbers and Modified Sigmoid Function
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            This paper is interested in certain  subclasses of univalent and bi-univalent functions concerning  to shell- like curves connected with k-Fibonacci numbers involving modified Sigmoid activation function θ(t)=2/(1+e^(-t) ) ,t ≥0 in unit disk |z|<1 . For estimating of the initial coefficients |c_2 | , |c_3 |, Fekete-Szego ̈ inequality and the  second Hankel determinant have been investigated for the functions in our classes. 

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Materials In Civil Engineering
Moisture Susceptibility and Fatigue Performance of Hydrated Lime–Modified Asphalt Concrete: Experiment and Design Application Case Study
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Hydrated lime has been recognized as an effective additive used to improve asphalt concrete properties in pavement applications. However, further work is still needed to quantify the effect of hydrated lime on asphaltic concrete performance under varied weather, temperature, and environmental conditions and in the application of different pavement courses. A research project was conducted using hydrated lime to modify the asphalt concretes used for the applications of wearing (surface), leveling (binder), and base courses. A previous publication reported the experimental study on the resistance to Marshall stability and the volumetric properties, the resilient modulus, and permanent deformation at three different weather temperatures. This

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Publication Date
Mon Dec 28 2020
Journal Name
Journal Of The College Of Education For Women
Evaluating the Indicators and Quality of Potable Water Networks in Al-Shatrah City: سميع جلاب منسي السهلاني
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The present paper aims at evaluating the vailability quality and future horizons of potable water in the city of Shatra as a model. This is done in accordance with certain subjective and objective factors alongside the classification map of Shatra as a residential area. This system follows geographical studies specialized in urban construction. The problem of the present paper as well as the data approaching that problem have been chosen from the records of 2018. The researcher offered (919) questionnaire forms to be answered by a sample of dwellers in that area. Besides, the researcher also followed lab analysis of water samples collected from districts in the city of Shatra. GIS technology was also used to arrive at the real water shar

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Publication Date
Thu May 30 2024
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm for Improving the Quantity and Quality of the Detected Complexes from Protein Interaction Networks
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One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

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Publication Date
Thu Feb 29 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Design and Development of Powerful Neuroevolution Based Optimized GNNBiLSTM Model for Consumer Behaviour and Effective Recommendation in Social Networks
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Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte

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