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Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm namely Particle Swarm Optimization (PSO) algorithm. The numerical simulation results show that the hybrid NARMA-L2 controller with PSO algorithm is more accurate than BPA in terms of achieving fast learning and adjusting the parameters model with minimum number of iterations, minimum number of neurons in the hybrid network and the smooth output one step ahead prediction controller response for the nonlinear CSTR system without oscillation.

 

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Publication Date
Wed Aug 31 2022
Journal Name
Al-kindy College Medical Journal
A Population based Study on Self Medication Practice in Pakistan
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Background: The risk of antibiotics resistance (AR) increases due to excessive of antibiotics either by health care provider or by the patients.

Objective: The assessment of the self-medication Practice of over the counter drugs and other prescription drugs and its associated risk factor.

Subjects and Methods: Study design: A descriptive study was conducted from “20th December 2019 to 08th January 2021”. A pre validated and structured questionnaire in English and Urdu language was created to avoid language barrier including personal detail, reasons and source and knowledge about over the counter drugs and Antibiotics. Sample of the study was randomly selected.

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Publication Date
Sat Oct 29 2022
Journal Name
Computers
Intelligent Robotic Welding Based on a Computer Vision Technology Approach
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Robots have become an essential part of modern industries in welding departments to increase the accuracy and rate of production. The intelligent detection of welding line edges to start the weld in a proper position is very important. This work introduces a new approach using image processing to detect welding lines by tracking the edges of plates according to the required speed by three degrees of a freedom robotic arm. The two different algorithms achieved in the developed approach are the edge detection and top-hat transformation. An adaptive neuro-fuzzy inference system ANFIS was used to choose the best forward and inverse kinematics of the robot. MIG welding at the end-effector was applied as a tool in this system, and the wel

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Publication Date
Sat Oct 29 2022
Journal Name
Computers
Intelligent Robotic Welding Based on a Computer Vision Technology Approach
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Robots have become an essential part of modern industries in welding departments to increase the accuracy and rate of production. The intelligent detection of welding line edges to start the weld in a proper position is very important. This work introduces a new approach using image processing to detect welding lines by tracking the edges of plates according to the required speed by three degrees of a freedom robotic arm. The two different algorithms achieved in the developed approach are the edge detection and top-hat transformation. An adaptive neuro-fuzzy inference system ANFIS was used to choose the best forward and inverse kinematics of the robot. MIG welding at the end-effector was applied as a tool in this system, and the wel

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Publication Date
Sun Jan 01 2017
Journal Name
Ieee Access
Low-Distortion MMSE Speech Enhancement Estimator Based on Laplacian Prior
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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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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Robotics And Control (jrc)
Automated Stand-alone Surgical Safety Evaluation for Laparoscopic Cholecystectomy (LC) using Convolutional Neural Network and Constrained Local Models (CNN-CLM)
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In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of the Current Financial Crisis : Causes and Solutions (Iraqi crisis a model , based on the public budget for the fiscal year 2016)
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The research aims to analysis of the current financial crisis in Iraq through knowing its causes and then propose some solutions that help in remedy the crisis and that on the level of expenditures and revenues, and has been relying on the Federal general budget law of the Republic of Iraq for the fiscal year 2016 to obtain the necessary data in respect of the current expenditures and revenues which necessary to achieve the objective of the research , and through the research results has been reached to a set of conclusions which the most important of them that causes of the current financial crisis in Iraq , mainly belonging to increased expenditures and especially the current ones and the lack of revenues , especially non-oil o

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
New Correlation for Predicting Undersaturated Oil Compressibility for Mishrif Reservoir in the Southern Iraqi Oil Fields
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Reservoir fluids properties are very important in reservoir engineering computations such as material balance calculations, well testing analyses, reserve estimates, and numerical reservoir simulations. Isothermal oil compressibility is required in fluid flow problems, extension of fluid properties from values at the bubble point pressure to higher pressures of interest and in material balance calculations (Ramey, Spivey, and McCain). Isothermal oil compressibility is a measure of the fractional change in volume as pressure is changed at constant temperature (McCain). The most accurate method for determining the Isothermal oil compressibility is a laboratory PVT analysis; however, the evaluation of exploratory wells often require an esti

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Publication Date
Thu Apr 18 2024
Journal Name
Eximia Journal
Forecasts some of functional indicators nervous system for dribbling skills in young basketball players from Baghdad Governorate
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The research study is important since it establishes predicted rates for various nervous system functional indicators.In terms of performing the skill of Dribbling in basketball for young players in Baghdad Governorate in order to reach scientific results that serve researchers, coaches, and players uniformly. The study's goal is to create predictive equations for specific functional indicators of the nervous system in relation to the Dribbling skill performance of young basketball players in Baghdad Governorate. The researchers used a descriptive approach with a survey method on (8) youth basketball league clubs in Baghdad Governorate for the 2022-2023 sports season, totaling (96) players . Three tests were used to measure the nervous sy

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Publication Date
Wed Aug 28 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
A Novel Anomaly Intrusion Detection Method based on RNA Encoding and ResNet50 Model
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

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