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Development of Intelligent Control Strategy for an Anesthesia System Based on Radial Basis Function Neural Network Like PID Controller
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Publication Date
Mon Dec 01 2014
Journal Name
Advances In Engineering Software
System identification and control of robot manipulator based on fuzzy adaptive differential evolution algorithm
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Publication Date
Thu Jun 20 2024
Journal Name
Fizjoterapia Polska
Development Artificial Neural Network (ANN) computing model to analyses men's 100¬meter sprint performance trends
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Coaches and analysts face a significant challenge of inaccurate estimation when analyzing Men's 100 Meter Sprint Performance, particularly when there is limited data available. This necessitates the use of modern technologies to address the problem of inaccurate estimation. Unfortunately, current methods used to estimate Men's 100 Meter Sprint Performance indexes in Iraq are ineffective, highlighting the need to adopt new and advanced technologies that are fast, accurate, and flexible. Therefore, the objective of this study was to utilize an advanced method known as artificial neural networks to estimate four key indexes: Accelerate First of 10 meters, Speed Rate, Time First of 10 meters, and Reaction Time. The application of artifi

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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
Development of Bridges Maintenance Management System based on Geographic Information System Techniques (Case study: Al-Muthanna \ Iraq)
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A Geographic Information System (GIS) is a computerized database management system for accumulating, storage, retrieval, analysis, and display spatial data. In general, GIS contains two broad categories of information, geo-referenced spatial data and attribute data. Geo-referenced spatial data define objects that have an orientation and relationship in two or three-dimensional space, while attribute data is qualitative data that can be counted for recording and analysis. The main aim of this research is to reveal the role of GIS technology in the enhancement of bridge maintenance management system components such as the output results, and make it more interpretable through dynamic colour coding and more sophisticated visualization

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Publication Date
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

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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
Mon Oct 01 2018
Journal Name
2018 Ieee/acs 15th International Conference On Computer Systems And Applications (aiccsa)
Utilizing Hopfield Neural Network for Pseudo-Random Number Generator
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Publication Date
Sat Jun 30 2018
Journal Name
Proceedings Of The International Conference On Intelligent Science And Technology
The nature of intelligent system in buildings
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Publication Date
Mon Dec 24 2018
Journal Name
Civil Engineering Journal
Artificial Neural Network Model for the Prediction of Groundwater Quality
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The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be

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Publication Date
Fri Jan 01 2016
Journal Name
Machine Learning And Data Mining In Pattern Recognition
A New Strategy for Case-Based Reasoning Retrieval Using Classification Based on Association
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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

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