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alkej-146
Genetic Algorithm Based PID Controller Design for a Precise Tracking of Two-Axis Piezoelectric Micropositioning Stage
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 In this paper, an intelligent tracking control system of both single- and double-axis Piezoelectric Micropositioner stage is designed using Genetic Algorithms (GAs) method for the optimal Proportional-Integral-Derivative (PID) controller tuning parameters. The (GA)-based PID control design approach is a methodology to tune a (PID) controller in an optimal control sense with respect to specified objective function. By using the (GA)-based PID control approach, the high-performance trajectory tracking responses of the Piezoelectric Micropositioner stage can be obtained. The (GA) code was built and the simulation results were obtained using MATLAB environment. The Piezoelectric Micropositioner simulation model with the (GA)-based PID control is illustrated to show the validity of the proposed control method for practical applications, such as scanning microscopy.

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
AGENT BASED MONITORING FOR INVESTIGATION PROCESS AND MAINTENANCE IMPROVEMENT
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Agent technology has a widespread usage in most of computerized systems. In this paper agent technology has been applied to monitor wear test for an aluminium silicon alloy which is used in automotive parts and gears of light loads. In addition to wear test monitoring، porosity effect on
wear resistance has been investigated. To get a controlled amount of porosity, the specimens have
been made by powder metallurgy process with various pressures (100, 200 and 600) MPa. The aim of
this investigation is a proactive step to avoid the failure occurrence by the porosity.
A dry wear tests have been achieved by subjecting three reciprocated loads (1000, 1500 and 2000)g
for three periods (10, 45 and 90)min. The weight difference a

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Cybersecurity And Information Management
Machine Learning-based Information Security Model for Botnet Detection
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Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

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Publication Date
Mon Jun 30 2003
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Two-Phase Pressure Drop Through Obstructions
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Publication Date
Wed Jun 01 2016
Journal Name
Nternational Journal Of Mathematics Trends And Technology (ijmtt)
Fuzzy Scheduling Problem on Two Machines
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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Appraisal of intelligent notification system for smart university campus based internet of objects for social activities
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Publication Date
Sun Jan 01 2017
Journal Name
International Journal Of Chem Tech Research
Synthesis of New Selective Electrodes for the Determination of Metronidazole Benzoate (MNZB) Based on a Molecularly Imprinted Polymer Combined With Poly Vinyl Chloride
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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Mon Mar 15 2021
Journal Name
Al-academy
Design Technologies in Promoting the Advertisement for National Product: وسام عبد الامير كريم المالكي
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The current research is concerned with studying the variables in the promotion process which influence the advertisement design structure, as the accomplished design and construction process is subject to many variables, whether they were intellectual or technological, internal or external variables. These variables may overlap in order to get a comprehensive system for the artistic configuration, that any design in its content reaches the highest levels of perfection is connected to the extent of its compliance with and approximation to these variables, that is why we find their reflections deeply rooted in the individual's mind, especially the designer artist who is influenced by everything surrounding him forming knowledge systems res

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Publication Date
Sun Mar 15 2020
Journal Name
Al-academy
Time and Design Construction for Costumes in the Iraqi Theater Show: محمــود جبــاري حــافظ
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The theatre costume with the rest of the theatre show elements constitute a system of the meaning relations that produce a visual image that helps the recipient to decipher the theatre scene, let alone the manifestation of time in its levels (past, present, future) through the design construction of the theatre elements among which is the theatre costume. In order to know the way of manifesting time through the formulation of the theatre costumes, the research question has been put as follows:  how to manifest time through the design construction for the theatre costumes unit, from which the research objective is derived as follows: Revealing the possibility of the designing unit of the costumes in manifesting the levels of time wit

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