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Evaluation Of Electromagnetic Pollution Of Cellular Mobile Network
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Wireless communications are characterized by their fastest growth in history, as they used ever-evolving and renewed technologies, which have allowed them to spread widely. Every day, communication technology introduces a new invention with features that differ from its predecessor. Bell Laboratories first suggested mobile wireless communication services to the general population in the late 1940s. Still, it wasn't easy at that time to use on a large scale due to its high costs. This paper aims to describe the state of cellular mobile networks; by comparing the sources of electromagnetic pollution caused by these networks, measure the level of power density in some residential areas, and compare them with international standards adopted in determining the level of power density by calculating the effect of the transmitted power and the angle of transmission of the antenna from the station. The importance of the paper lies in the fact that it investigates the levels of non-ionizing radiation produced by cellular mobile networks and the identification of other types of pollution caused by these networks.

Publication Date
Wed Aug 11 2021
Journal Name
Neuroquantology
Measuring the Pollution Level with Uranium and Radon in the Soil of Some Areas Inside Baghdad University Campus-AL-Jadiriyah
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In present study, the technique was used, including nuclear track detector type (CR-39), for appreciative concentrations uranium and radon in soil samples from Baghdad University Campus-AL-Jadiriyah utilizing a prolonged -term with a solid-state nuclear path sensor, a technique for charged particles has been developed., the radon concentrations, effective dose rate and uranium concentrations have measured in soil samples. Eight various venues from soil Baghdad University Campus have appointed. The results indicated variant values about uranium and radon concentrations, the average value for radon gas, effective dose rate and uranium concentrations was found to be 281.59 Bq/cm3, 7.09 mSv/y and 0.01 Bq/mm-2 respectively. All results a

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Publication Date
Fri Mar 13 2020
Journal Name
Sustainability
Consumers’ Perceptions and Attitudes toward Products Preventing Microfiber Pollution in Aquatic Environments as a Result of the Domestic Washing of Synthetic Clothes
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Microfibers released by synthetic clothes have a significant negative effect on the environment. Several solutions have been proposed and evaluated for their effectiveness, but studies have failed to address the human-centered aspects of these products. In this research, the possibilities and needs from a consumer perspective for a new filtering system for domestic washing machines were examined. First, a quantitative (questionnaire) and a qualitative (interviews and observations) exploration were done to understand the desired requirements from a user perspective. Next, the acceptance of various existing solutions for microfiber catching was investigated. To verify these requirements, a new concept was designed and evaluated with a

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Artificial Neural Network Models to Predict the Cost and Time of Wastewater Projects
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Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

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Publication Date
Wed Feb 27 2019
Journal Name
Journal Of Low Power Electronics And Applications
Tolerating Permanent Faults in the Input Port of the Network on Chip Router
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Deep submicron technologies continue to develop according to Moore’s law allowing hundreds of processing elements and memory modules to be integrated on a single chip forming multi/many-processor systems-on-chip (MPSoCs). Network on chip (NoC) arose as an interconnection for this large number of processing modules. However, the aggressive scaling of transistors makes NoC more vulnerable to both permanent and transient faults. Permanent faults persistently affect the circuit functionality from the time of their occurrence. The router represents the heart of the NoC. Thus, this research focuses on tolerating permanent faults in the router’s input buffer component, particularly the virtual channel state fields. These fields track packets f

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Spatial Prediction of Monthly Precipitation in Sulaimani Governorate using Artificial Neural Network Models
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ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

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Publication Date
Thu Jun 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Performance Improvement of Neural Network Based RLS Channel Estimators in MIMO-OFDM Systems
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The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

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Publication Date
Sat Oct 29 2022
Journal Name
Current Trends In Geotechnical Engineering And Construction
Simulation Design and Performance of a Residential Complex Using Liquefied Petroleum Gas Network
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The population has been trying to use clean energy instead of combustion. The choice was to use liquefied petroleum gas (LPG) for domestic use, especially for cooking due to its advantages as a light gas, a lower cost, and clean energy. Residential complexes are supplied with liquefied petroleum gas for each housing unit, transported by pipes from LPG tanks to the equipment. This research aims to simulate the design and performance design of the LPG system in the building that is applied to a residential complex in Baghdad taken as a study case with eight buildings. The building has 11 floors, and each floor has four apartments. The design in this study has been done in two parts, part one is the design of an LPG system for one building, an

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of The Mechanical Behavior Of Materials
Simulation and assessment of water supply network for specified districts at Najaf Governorate
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Abstract<p>This study aims to simulate and assess the hydraulic characteristics and residual chlorine in the water supply network of a selected area in Al-Najaf City using WaterGEMS software. Field and laboratory work were conducted to measure the pressure heads and velocities, and water was sampled from different sites in the network and then tested to estimate chlorine residual. Records and field measurements were utilized to validate WaterGEMS software. Good agreement was obtained between the observed and predicted values of pressure with RMSE range between 0.09–0.17 and 0.08–0.09 for chlorine residual. The results of the analysis of water distribution systems (WDS) during maximum demand </p> ... Show More
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