The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The developed ANN mode gave a high correlation coefficient reaching 0.927 for the prediction of TDS from the model and showed high levels of TDS in Al-Hawizeh marsh that pose threats to people using the marsh for drinking and other uses. The dissolved Oxygen concentration has the highest importance of 100% in the model because the water of the marsh is fresh water, while Turbidity had the lowest importance.
In this research, the effect of changing the flood level of Al-Shuwaija marsh was studied using the geographic information systems, specifically the QGIS program, and the STRM digital elevation model with a spatial analysis accuracy of 28 meters, was used to study the marsh. The hydraulic factors that characterize the marsh and affecting on the flooding such as the ranks of the water channels feeding the marsh and the degree of slope and flat areas in it are studied. The area of immersion water, the mean depth, and the accumulated water volume are calculated for each immersion level, thereby, this study finds the safe immersion level for this marsh was determined.
Air pollution evaluation of the operational processes in the East Baghdad oil field was carried out. The analysis was carried out by ICP-MS technique. Total Suspended Particles (TSP) air load was higher than Iraqi Standards and world international allowable limits of World Health Organization. The mean concentrations of gases carbon monoxide, carbon dioxide, sulfur dioxide, in the air were within national and world standards, while the mean concentration of nitrogen dioxide was higher than standard limits. The air of the study area is considered a good quality for CO, CO2 and NO2 with no health effect, while it is hazardous for TSP that have serious risk for people with respiratory disease. The mean concentrations of Cd, Cr, Cu and
... Show MoreGroundwater is an essential source because of its high quality and continuous availability characterize this water resource. Therefore, the study of groundwater has required more attention. The present study aims to assess and manage groundwater quality's suitability for various purposes through the Geographical Information System GIS and the Water Quality Index WQI. The study area is located in the city of Baghdad in central Iraq, with an approximate area of 900 , data were collected from the relevant official departments representing the locations of 97 wells of groundwater in the study area for the year 2019, as it included physicochemical parameters such as pH, EC, TDS, Na, K, Mg, Ca, Cl, , and &nbs
... Show MoreTotal of 170 samples were collected from Al-Chibayish Marsh reality in Dhi-Qar governorate southern of Iraq to study the epidemology of viral hepatitis in these areas and to detect the type of hepatitis viruses which include A ,B,C,D .The percentage of hepatitis A was 1.17% and most of them below age of ?10 (66.6%) while infection with hepatitis B account 5.29% and includes all age groups. There was no detected cases of hepatitis C,D. The laboratory study showed that the incidence of hepatitis B higher in male (4.11%) compared to female ( 2.35%)
The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
... Show MoreAl-Yusifia river was assessed at three sampling stations with study period from Autumn 2010 to the end of Summer 2011. The present investigation was carried out on diversity of fungi and bacteria from Al-Yusifia river, Baghdad city. During the study, a total of 12 fungal genus and 6 bacterial genus were isolated during the year seasons. The dominant fungus at the three stations were Penicillium sp., then Rhizopus and Trichophyton megninii while the dominant bacteria was Escherichia coli and Klebsiella sp.
The higher
... Show MoreThe Web Design Quality Index, known as WDQI, was applied to assess the quality of websites for six Iraqi universities, namely Basra University, Mosul, Muthanna, Samarra, Dijla University College, and Al-Isra University College. The results of the index showed that the universities of Basra and Dijla University College had the highest value, at 71.07 and 70.39, respectively. Its final evaluation metric was that the website of these two universities needed a slight improvement. As for the rest of the other universities, the final values of the index ranged from 64.72-69.71. When the final values of the index are displayed on the final evaluation scale, it appears that the websites of the four universities need many improvements. The study
... Show MoreIn 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
Studied the effect of foliar fertilizers Alaongrin results showed that spraying fertilizer Alaongrin and Fertilizers and Ministry of Agriculture and rack licorice extract every three weeks after thirty days from planting seedlings
Specimens of the sesarmid crab Nanonsesarma sarii (Naderloo and Türkay 2009) were collected from the intertidal zone of Khor Al-Zubair, Basrah, Iraq 2012 far from the Arabian Gulf coasts. Morphological features of this species are highlighted and a figure is provided.