Several toxigenic cyanobacteria produce the cyanotoxin (microcystin). Being a health and environmental hazard, screening of water sources for the presence of microcystin is increasingly becoming a recommended environmental procedure in many countries of the world. This study was conducted to assess the ability of freshwater cyanobacterial species Westiellopsis prolifica to produce microcystins in Iraqi freshwaters via using molecular and immunological tools. The toxigenicity of W. prolifica was compared via laboratory experiments with other dominant bloom-forming cyanobacteria isolated from the Tigris River: Microcystis aeruginosa, Chroococcus turigidus, Nostoc carneum, and Lyngbya sp. signifi

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

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

The aim of this investigation was to study the impact of various reaction parameters on wastewater taken from Al-Wathba water treatment plant on Tigris River in south of Baghdad, Iraq with sodium hypochlorite solution. The parameters studied were sodium hypochlorite dose, contact time, initial fecal coliform bacteria concentration, temperature, and pH. In a batch reactor, different concentrations of sodium hypochlorite solution were used to disinfect 1L of water. The amount of hypochlorite ions in disinfected water was measured using an Iodimetry test for different reaction times, whereas the Most Probable Number (MPN) test was used to determine the concentration of coliform bacteria. Total Plate Count (TPC) was utilized in this study to

In 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

339 individuals , were sorted from 22 samples collected from three sites in Tigris River including , Al- Sarafiya district (S1), Al- Jaderiyah district (S2) and Al-Za'afaraniya district (S3), in addition to one site in the irrigation canal of the Al- Jaderiyah campus of the University of Baghdad (S4) , and in Al- Jeish canal(S5) east Baghdad. The sorting results revealed that the highest number of individuals of 102 was recorded at S4, whereas the lowest number of 24 individuals was recorded at S2. Regarding the sites, site S4 was the richest site with 30% of the total number represented 16 species, while each of S3 and S5 had 8 species only with 17.11% and 28.60% of the total individuals number respectively. The values of Jaccared Sim

Aromatic hydrocarbons present in Iraqi national surface water were believed to be raised principally from combustion of various petroleum products, industrial processes and transport output and their precipitation on surface water.
Polycyclic aromatic hydrocarbons (PAHs) were included in the priority pollutant list due to their toxic and carcinogenic nature. The concern about water contamination and the consequent human exposure have encouraged the development of new methods for
PAHs detection and removal.
PAHs, the real contaminants of petroleum matter, were detected in selected sites along Tigris River within Baghdad City in summer and winter time, using Shimadzu high performance liquid chromatography (HPLC) system.
Analysi

The South Baghdad electrical station located on the eastern bank of the Tigris River south of Baghdad city was selected within the municipality of Karrada between  two  latitude ( 33⁰ 15 , 33 ⁰  18 )North  and  longitude ( 44 ⁰  27 , 44 ⁰30 ) East . The purpose of the study is to determine the contribution of the station to the effect of pollution of the Tigris water by taking water samples at the station site and two sites, one before and the other after the station, distributed over time periods of three months between each sample of water and the beginning of August and November Shabat and Mayar and analyzed water samples physically, chemically and biologic

The presence of residual antibiotics in water results in the development of antibiotics resistant genes. The available wastewater treatment systems are not capable of removing such antibiotics from sewage. Thus, antibiotics need to be removed before the discharge of wastewater. Adsorption is among the promising techniques for the wastewater treatment to aid the removal of a wide range of organic and inorganic pollutants. The present work is a contribution to the search for an economical method for the removal of low concentrations of amoxicillin (AMX) from water by adsorption on water treatment residue, WTR, taken from a local drinking water facility. The chemical composition and the adsorptive characteristics of the material were first