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Water Quality Assessment of Al-Najaf City Potable Water Network
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 Water is an essential aspect of life and important in evolution. Recently the potable water quality topic has received much attention. The study aims to determine drinking water quality in Al-Najaf City by collecting samples throughout Al-Najaf city and comparing the results with the Iraqi guidelines (IQS 417) and World Health Organization (WHO) guidelines, as well as to calculate the WQI. Samples were tested in the laboratory between December 2021 and June 2022. The results showed that multiple parameters exceeded the allowable limits during both testing periods; during winter months, the results of TDS and turbidity exceeded the upper limits in multiple locations. Total hardness values also exceeded the limit of 500 ppm for all samples taken in the winter period. For magnesium and calcium, summer measurements were mainly within limits, unlike winter period measurements which mostly exceeded the limits. Residual chlorine tests in winter had higher concentrations, generally ranging from 0.25 to 0.8 mg/l. While During summer, concentrations dropped below the allowable limit in multiple sampling points. The study concluded that the majority of the water samples gathered during the winter months were of poor quality as the total WQI values were between (99-110), While the total WQI values for water samples collected during the summer period were rated as good quality water ranged between (75-81).

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Publication Date
Tue Oct 25 2022
Journal Name
Minar Congress 6
HANDWRITTEN DIGITS CLASSIFICATION BASED ON DISCRETE WAVELET TRANSFORM AND SPIKE NEURAL NETWORK
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In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

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Publication Date
Sat Dec 31 2022
Journal Name
International Journal Of Intelligent Engineering And Systems
Dynamic Virtual Network Embedding with Latency Constraint in Flex-Grid Optical Networks
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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Crescent Moon Visibility: A New Criterion using Deep learned Artificial Neural-Network
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     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Planner And Development
The "actor network theory" approach in dealing with landscapes in historical centers
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The historical center's landscape suffers from neglect, despite their importance and broad capabilities in enhancing the cultural value of the historical center, as landscape includes many heterogeneous human and non-human components, material and immaterial, natural and manufactured, also different historical layers, ancient, modern and contemporary. Due to the difference in these components and layers, it has become difficult for the designer to deal with it. Therefore, the research was directed by following a methodology of actor-network theory as it deals with such a complex system and concerned with an advanced method to connect the various components of considering landscape as a ground that can include various elements and deal wi

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Publication Date
Sat Jan 01 2022
Journal Name
Computers, Materials & Continua
An Optimal Method for Supply Chain Logistics Management Based on Neural Network
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Publication Date
Thu Oct 31 2024
Journal Name
Iraqi Geological Journal
Artificial Neural Network Application to Permeability Prediction from Nuclear Magnetic Resonance Log
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Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network
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Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Shaikh Al-Fadhali's Thesis in Parsing the phrase 'No god but Allah' written by Al-Shaikh Saif-el-Deen Atta Abu-el Futouh Al-Wafa'y Al- Fadhali (1020 A.D.)
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Abstract
Praise be to Allah, The Lord of the worlds, and peace be upon
Muhammad the master of former and latter people, and peace be upon His
relatives, companions and those who followed Him to Judgment day.
After recognizing the prescription which is called (Al- Fadhaly's Thesis in
parsing of "There is no god but God") as it is related with the word of the
investigation of this issue attracted me, as being related with the idea of the
only one God that is mentioned in the prophetic speech, which is said by
Anas- God satisfies him- Who said, Said the Messenger Muhammad peace
be upon him " Goes out of the Hell who said: there is no god but God, and in
his heart a hair weight of charity, and goes out of the He

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Publication Date
Sat Jul 18 2020
Journal Name
College Of Islamic Sciences
Soort of Hamid al-Taie and his sons in the poetry of Abu Tammam and Al-Bohtari
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The phenomenon of celebration of army leaders in the Abbasid era formed a distinct phenomenon at which the poets stood, and among those leaders was the Arab leader Hamid al-Taie, and the poets who stood on him and his sons Abu Tammam and al-Bohtari recorded in their poems the exploits of that leader, and the exploits of his sons through images that represented sadness, courage In this research, the generosity, and the rhetorical and artistic aspects of those images, have been spotted, balancing the poets.

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