Diyala river is the most important tributaries in Iraq, this river suffering from pollution, therefore, this research aimed to predict organic pollutants that represented by biological oxygen demand BOD, and inorganic pollutants that represented by total dissolved solids TDS for Diyala river in Iraq, the data used in this research were collected for the period from 2011-2016 for the last station in the river known as D17, before the river meeting Tigris river in Baghdad city. Analysis Neural Network ANN was used in order to find the mathematical models, the parameters used to predict BOD were seven parameters EC, Alk, Cl, K, TH, NO3, DO, after removing the less importance parameters. While the parameters that used to predict TDS were fourteen parameters pH, DO, BOD, PO4, NO3,Ca, Mg, TH, K, Na, SO4,Cl, EC, Alk. The results indicated that the best correlation coefficient is 86.5% for BOD, and the most important parameter is Chloride Cl, and the best correlation coefficient is 95.4% for TDS and the most important parameters are total hardness TH and electrical conductivity EC, according to direct relation between these parameters and TDS.
The tagged research is concerned with observation and investigating the concepts of consistency and harmony in contemporary Iraqi painting (selected models) in order to reveal the mechanisms and rules of these two concepts in the artistic field and their mechanisms of operation. How reflected tools Consistency and harmony in contemporary Iraqi painting? What is consistency and what are its mechanisms and principles? Is consistency a unit product quality? Are there similarities between consistency and harmony? What is harmony and its principles and rules? As for the second chapter, it included two topics that dealt with the first topic - consistency and harmony between concept and significance, while the second topic meant - histor
... Show MoreABSTRACT
The results showed that the organic fertilizer mixture (1:1) 30 tons/ha with chemical fertilization recorded the lowest level of bulk density of 1.2 g/cm3, the organic fertilizer mixture (1:1) 30 tons/ha with chemical fertilization recorded the highest percentage of aggregation stability amounting to 16.17%, the organic fertilizer palm fronds recorded the highest level of ready water with an average of 5.50 cm3/cm3 and the organic fertilizer mixture (1:1) 30 tons/ha without chemical fertilization recorded the highest level of ready water as it reached 6.93%, the or
... Show MoreWater is a resource and a crucial aspect of living and surviving. In Iraq, the Tigris River is one of the most critical water sources. The present study aimed to provide an insight analysis of some water quality parameters including the microbial content of drinkable tap water and river water. Ten Water samples (T1- T10) in triplicate were collected from sampling sites -Site I (Tap water) from home water taps, supplied by the Water Filtration Station/ Al Karama Project/ Al-Karkh> 10 from Site II (R1- R10)River water from Tigris River (around or near the Water Filtration Station/ Al Karama Project) every week (from September to half of November 2022), then were immediately placed in sterile bottles and transported to Microbiolo
... Show MoreThe monitoring of lotic ecosystems is an important issue. This study investigated the total petroleum hydrocarbons (THP) in the Tigris River within Baghdad City, Iraq, which is considered the ultimate water supply source of the city. The study included measurement of THP concentrations, distribution, and origins of total petroleum hydrocarbons (TPHs) in various matrices (water, sediment, and macrophyte) in Tigris River within Baghdad City, in addition to some environmental factors during two seasons (dry and wet) for October 2020 to April 2021. The sampling was collected from three sites along the river. Thirteen compounds were identified in the current investigation from total petroleum h
A simple UV spectrophotometric differential derivatization method was performed for the simultaneous quantification of three aromatic amino acids of tryptophan, the polar tyrosine and phenylalanine TRP, TYR and PHE respectively. The avoidance of the time and reagents consuming steps of sample preparation or analyze separation from its bulk of interferences made the approach environmentally benign, sustainable and green. The linear calibration curves of differential second derivative were built at the optimum wavelength for each analyze (218.9, 236.1 and 222.5 nm) for PHE, TRP and TYR respectively. Quantification for each analyze was in the concentration range of (1.0– 45, 0.1–20.0 and 1.0– 50.0 μg/ml) at replicates of (n=3) with a re
... Show MoreZiegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (KP, KI, KD) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio
... Show MoreRecently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural
... Show MoreTransformers are a specific category of neural network design. Transformers often depend on extensive pre-training on a large scale and exhibit a notable degree of computational complexity. The disadvantage of using this method is a significant increase in computational complexity, which necessitates a significant commitment of time and computing resources in order to successfully work with these models. Transformer networks possess the desirable benefit of extracting distant characteristics effectively via their self-attention mechanism. In this paper, the Global Self-Attention Transformer module is applied to tackle these issues. The model is based on a segmentation problem called Brain-GS that works as a mechanism and encompasses
... Show More