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A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comparison to the actual observational results. ANN simulation gives a clear insight into three crescent moon visibility regions: invisible (I), probably visible (P), and certainly visible (V). The proposed ANN is suitable for building lunar calendars, so it was used to build a four-year calendar on the horizon of Baghdad. The built calendar was compared with the official Hijri calendar in Iraq.

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Publication Date
Wed Mar 16 2022
Journal Name
Journal Of Educational And Psychological Researches
Biology Textbook for Scientific Sixth Class in Iraq (A Comparative Study)
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The textbook is the primary means of creativity and thinking, which has a major role in the development of the readership and mental abilities of the student. It is the basic tool in education in Iraq for the teacher and the student, which cannot be dispensed in any educational program. The current study aimed at the book of the biology of the sixth grade of science in Iraq (comparative study). It was compared to the book of biology for the twelve grade in the Kingdom of Jordan to identify the ratio of similarity and differences between them, in addition, to identify the weaknesses in the Iraq curriculum and developing appropriate solutions and suggestions to address them. The sample was represented with books of biology (six-science cla

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
A new approach for the topical treatment of acne vulgaris by clindamycin HCL supported on kalion
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Has been studied both processes Almetzaz and extortion of a substance Alklanda Maysan different amounts of Alcaúlan Guy 70% alcohol solution using the method when the wavelength

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Publication Date
Fri Dec 15 2023
Journal Name
Al-academy
The role of artificial intelligence in revolutionizing the clothing and textile industry
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 The integration of AI technologies is revolutionizing various aspects of the apparel and textile industry, from design and manufacturing to customer experience and sustainability. Through the use of artificial intelligence algorithms, workers in the apparel and textile industry can take advantage of a wealth of opportunities for innovation, efficiency and creativity.
The research aims to display the enormous potential of artificial intelligence in the clothing and textile industry through published articles related to the title of the research using the Google Scholar search engine. The research contributes to the development of the cultural thought of researchers, designers, merchants and the consumer with the importance of integ

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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Optimization Algorithms Based on Path Planning and Neural Controller for Mobile Robot
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In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

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Publication Date
Mon Apr 01 2013
Journal Name
International Journal Of Electrical, Electronics And Telecommunication Engineering
Performance Analysis of xPON Network for Different Queuing Models
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Passive optical network (PON) is a point to multipoint, bidirectional, high rate optical network for data communication. Different standards of PONs are being implemented, first of all PON was ATM PON (APON) which evolved in Broadband PON (BPON). The two major types are Ethernet PON (EPON) and Gigabit passive optical network (GPON). PON with these different standards is called xPON. To have an efficient performance for the last two standards of PON, some important issues will considered. In our work we will integrate a network with different queuing models such M/M/1 and M/M/m model. After analyzing IPACT as a DBA scheme for this integrated network, we modulate cycle time, traffic load, throughput, utilization and overall delay

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Publication Date
Thu Apr 18 2019
Journal Name
Al-kindy College Medical Journal
Prescribing pattern of antibiotics in AL-Elwia Pediatric Teaching Hospital, Baghdad, 2016.
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Background: Antibiotics are among the most commonly used medicine, in both community and hospital setting, all over the world especially in countries where no strict guideline to regulate their use. In Iraq, only a few studies conducted to describe the antibiotic prescription pattern in general hospitalsand even less in pediatric hospital.

Objective: To describe the patterns for antibiotics used in Elwia pediatric teaching hospital in Baghdad, Iraq

Type of the study: Descriptive cross sectional study.

.Methodology: The study was conducted at AL-Elwia Pediatric Teaching Hospitalduring the year 2016. A random sample from all the prescriptions sheets

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Publication Date
Wed Sep 27 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Assessing the reliability of serum macrophage migration inhibitory factor as a marker for diabetic nephropathy prediction in type 2 diabetes patients and the effect of ACE inhibitors on its level
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Abstract Diabetic nephropathy (DN) is a prevalent chronic microvascular diabetic complication. As inflammation plays a vital role in the development and progress of DN the macrophages migration inhibitory factor (MIF), a proinflammatory multifunctional cytokine approved to play a critical function in inflammatory responses in various pathologic situations like DN. This study aimed To assess serum levels of MIF in a sample of Iraqi diabetic patients with nephropathy supporting its validity as a marker for predicting nephropathy in T2DM patients. In addition, to evaluate the nephroprotective effect of angiotensin-converting enzyme (ACE) inhibitors in terms of their influence on MIF levels. This is a case-control study involving ninety

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Implementation of Neural Control for Continuous Stirred Tank Reactor (CSTR)
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In this paper a dynamic behavior and control of  a jacketed continuous stirred tank reactor (CSTR)  is developed using different control strategies, conventional feedback control (PI and PID), and neural network (NARMA-L2, and NN Predictive) control. The dynamic model for CSTR process is described by a first order lag system with dead time.

The optimum tuning of control parameters are found by two different methods; Frequency Analysis Curve method (Bode diagram) and Process Reaction Curve using the mean of Square Error (MSE) method. It is found that the Process Reaction Curve method is better than the Frequency Analysis Curve method and PID feedback controller is better than PI feedback controller.

The results s

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Publication Date
Fri May 20 2016
Journal Name
Journal Of Biodiversity And Environmental Sciences Jbes
New record of the Epaulet Skimmer: Orthetrum chrisostigma (Burmeister) (Odonata: Libellulidae) from Iraq
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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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