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Influence of A River Water Quality on The Efficiency of Water Treatment Using Artificial Neural Network
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Tigris River is the lifeline that supplies a great part of Iraq with water from north to south. Throughout its entire length, the river is battered by various types of pollutants such as wastewater effluents from municipal, industrial, agricultural activities, and others. Hence, the water quality assessment of the Tigris River is crucial in ensuring that appropriate and adequate measures are taken to save the river from as much pollution as possible. In this study, six water treatment plants (WTPs) situated on the two-banks of the Tigris within Baghdad City were Al Karkh; Sharq Dijla; Al Wathba; Al Karama; Al Doura, and Al Wahda from northern Baghdad to its south, that selected to determine the removal efficiency of turbidity and the water quality index used to assess the quality of water for drinking purposes, in addition to finding the model based on past information to predict the quality of treated wastewater produced in each WTP using an artificial neural network (ANN) approach. The selected parameters for this study were turbidity, total hardness, total solids, suspended solids, and alkalinity. The results showed that all the WTPs possessed a high rate of efficiency in the removal of turbidity from raw water. Also, the results of the water quality index for all WTPs were classified over a study period of three years from 2015 to 2017 as being a good water quality and based on these results, the water treatment plants can be considered to be doing efficient water treatment process. The ANN model has been found at all WTPs to have a coefficient of determination (R2) for expected models was more than 0.7 to provide a WQI prediction tool that can be used with a moderate level of predictive acceptance to describe the suitability of WTP water quality for drinking purposes.

Publication Date
Sat Jul 08 2023
Journal Name
Al-nahrain Journal For Engineering Sciences
The Influence of Using Recycled Asphalt Pavement and Crumbed Rubber on Asphalt Pavement: A Review
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Reclaimed (recycled) asphalt pavement (RAP), the most recycled material worldwide, is the mostly reclaimed material utilized in hot mix asphalt. Polymer (Crumb rubber) incorporation frequently leads to enhanced durability and resistance to heat cracking and rutting, two forms of permanent deformation. It also relieves stiffness and minimizes fatigue damage. This study aims to gather all previous RAP-related research and crumb rubber CR, so that the impact of using these materials on mechanical, physical properties of asphalt pavement, environmental effect and cost effective are clarify and explained. The finding of this research proved that the use of RAP and CR provide considerable structural and financial enhancements to the const

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Publication Date
Tue Dec 16 2025
Journal Name
Cab Reviews: Perspectives In Agriculture, Veterinary Science, Nutrition And Natural Resources
From data to decision: How wearable plant sensors help improving proactive irrigation strategies and water use efficiency
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Wearable sensors are a revolutionary tool in agriculture because they collect accurate data on plant environmental conditions that affect plant growth in real-time. Moreover, this technology is crucial in increasing agricultural sustainability and productivity by improving irrigation strategies and water resource management. This review examines the role of wearable sensors in measuring plant water content, leaf and air humidity, stem flow, plant and air temperature, light, and soil moisture sensors. Wearable sensors are designed to monitor various plant physiological parameters in real-time. These data, obtained through wearable sensors, provide information on plant water use and physiology, making our agricultural choices more informed an

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Publication Date
Thu Mar 05 2020
Journal Name
Irrigation And Drainage
ECONOMIC ASSESSMENT OF DUYRIDGE DAM AS A WATER‐HARVESTING SCHEME IN IRAQ
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Abstract<p>Iraq, home of the Tigris and Euphrates rivers, has survived an extreme deficiency of surface water assets over the years. The gap is due to the decline of the Iraqi water share every year, as well as a high demand for water use from different sectors, particularly agriculture.</p><p>Dam development has long given significant economic benefits to Iraq in circulating low‐priced electricity and supporting low‐income farmers by supplying them with a free irrigation system (Zakaria et al, 2012). This encouraged domestic consumption and investment.</p><p>Despite the fact that numerous advantages are expected from dam construction, it should be painstakingly assessed, utilizing cost</p> ... Show More
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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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Publication Date
Wed Mar 24 2021
Journal Name
Ieee Access
Smart IoT Network Based Convolutional Recurrent Neural Network With Element-Wise Prediction System
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An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
The Effects of Different Water Types on the Dissolution, Physical Appearance, and Compressive Strength of Gypsum Rock
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Dissolution of gypsum rock in water is significant, which may result in hydrocarbon reservoir formation and evaporate deposits. However, the complexity of the gypsum dissolution process is still of interest because of its uncleanness that requires more critical analysis. The objectives of this experimental study are emphasis on the dissolution characteristics of gypsum rock under room temperature and by various types of water; namely: deionized, tap, fresh, acidic, well, and normal rainwatre. In addition, the influences of dissolution on gypsum rock's mechanical and physical characteristics. Gypsum rock was obtained from Agjalar area, in the southwest of Sulaymaniyah city, Northern Iraq. Experimental results show that we

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Publication Date
Thu Apr 01 2021
Journal Name
Iop Conference Series: Materials Science And Engineering
Evaluating the Efficiency of some Wastewater Treatment Plants in Najaf Governorate
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Abstract<p>Although there are many wastewater treatment plants, we still suffer from many problems resulting from a lack of experience or technical operating problems. In this research, the service’s efficiency is evaluated according to the design laws required for small factories in the province of Najaf, which works with filtering technology through point filtration, the old project in the Al-Baraka plant, and the second works. Within the biological treatment mbbr + activated sludge, which is a biomass technology where samples were taken from both plants and annual values of the pollutant rate after treatment in the old Al-Baraka plant project COD 64 mg/L and the demand for biochemical oxyge</p> ... Show More
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Publication Date
Sat Dec 31 2022
Journal Name
International Journal On “technical And Physical Problems Of Engineering”
Age Estimation Utilizing Deep Learning Convolutional Neural Network
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Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

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Publication Date
Thu Sep 01 2022
Journal Name
Https://www.researchgate.net/journal/university-of-baghdad-engineering-journal-1726-4073
Hazard analysis in drinking water plant
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Source, sedimentation, coagulation, flocculation, filter, and tank are parts of a water treatment plant. As a result, some issues threaten the process and affect the drinking water quality, which is required to provide clean drinking water according to special standards and international and local specifications, determined by laboratory results from physical, chemical, and biological tests. In order to keep the water safe for drinking, it is necessary to analyze the risks and assess the pollution that occurs in every part of the plant. The method is carried out in a common way, which is monitoring through laboratory tests, and it is among the standards of the global and local health regulators

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Publication Date
Tue Apr 01 2014
Journal Name
Journal Of Engineering
Priority Based Transmission Rate Control with Neural Network Controller in WMSNs
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Wireless Multimedia Sensor Networks (WMSNs) are networks of wirelessly interconnected sensor nodes equipped with multimedia devices, such as cameras and microphones. Thus a WMSN will have the capability to transmit multimedia data, such as video and audio streams, still images, and scalar data from the environment. Most applications of WMSNs require the delivery of multimedia information with a certain level of Quality of Service (QoS). This is a challenging task because multimedia applications typically produce huge volumes of data requiring high transmission rates and extensive processing; the high data transmission rate of WMSNs usually leads to congestion, which in turn reduces the Quality of Service (QoS) of multimedia applications. To

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