In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and the plasticity index of the soil.
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Abstract Iraq has an important place in the regional and international balance, and the competition among countries has increased in rapprochement with Iraq, not only for its geography or its privileged location, but because it has many other components that make regional and international countries want to strengthen their relations with it (Regional and international powers). In addition to that, Iraq has become increasingly important for these international and regional powers after its victory over the terrorist organization (ISIS), which proved an important fact that Iraq represents the most important pillars in the international balance.
The accumulation of sediment in reservoirs poses a major challenge that impacts the storage capacity, quality of water, and efficiency of hydroelectric power generation systems. Geospatial methods, including Geographic Information Systems (GIS) and Remote Sensing (RS), were used to assess Dukan Reservoir sediment quantities. Satellite and reservoir water level data from 2010 to 2022 were used for sedimentation assessment. The satellite data was used to analyze the water spread area, employing the Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) to enhance the water surface in the satellite imagery of Dukan Reservoir. The cone formula was employed to calculate the live storag
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi
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Al-Dalmaj marsh and the near surrounding area is a very promising area for energy resources, tourism, agricultural and industrial activities. Over the past century, the Al-Dalmaje marsh and near surroundings area endrous from a number of changes. The current study highlights the spatial and temporal changes detection in land cover for Al-Dalmaj marsh and near surroundings area using different analyses methods the supervised maximum likelihood classification method, the Normalized Difference Vegetation Index (NDVI), Geographic Information Systems(GIS), and Remote Sensing (RS). Techniques spectral indices were used in this study to determine the change of wetlands and drylands area and of other land classes, th
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Electronic University Library: Reality and Ambition Case Study Central Library of Baghdad University
Phytoplankton community is a model for of monitoring aquatic systems and interpreting the environmental change in aquatic systems. The present study aimed to forecast environmental parameters that drive the change of phytoplankton community structure in the lake. The present study was carried out in Baghdad Tourist Island Lake (BTIL) for the period From October 2021 to May 2022. The study included the quality and quantity of phytoplankton, moreover, the highest and lowest value of the physical and chemical parameters were (Water temperature (13-30 °C), Light penetration (94-275cm), electric conductivity (837-1128 µS/cm), salinity (0.5-0.7 ‰), pH (7-8.2), total alkalinity (126-226 mg CaCO3/L), total Hardness (297-395 mg CaCO3/L), Ca
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Phytoplankton community is a model for of monitoring aquatic systems and interpreting the environmental change in aquatic systems. The present study aimed to forecast environmental parameters that drive the change of phytoplankton community structure in the lake. The present study was carried out in Baghdad Tourist Island Lake (BTIL) for the period From October 2021 to May 2022. The study included the quality and quantity of phytoplankton, moreover, the highest and lowest value of the physical and chemical parameters were (Water temperature (13-30 °C), Light penetration (94-275cm), electric conductivity (837-1128 µS/cm), salinity (0.5-0.7 ‰), pH (7-8.2), total alkalinity (126-226 mg CaCO3/L), total Hardness (297-395 mg CaCO3/L
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