Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul

This paper delves into the significant role played by local social and traditional structures in shaping Traditional Community Tenure (TCT) within Iraqi Land Tenure Legislation (ILTR), and examines their impact on gender inequalities, with a specific focus on women's land tenure rights. The methodological approach employed in this study identified the sources of barriers to gender equality within TCT as outlined in ILTR at two different bilateral levels, with input obtained from key stakeholders in a selected city in Iraq. The case study survey encompassed three districts, which served as local layers within the historic sectors of the Iraqi city of Al-Nasiriya. the study employed quantitative methods, including a household surveyو with

A field study was conducted on a sample of the public in Baghdad to study the audience's exposure to the television promotion of pharmaceutical products and their trends in order to determine the rate of exposure of the public to the television promotion of pharmaceutical products according to the theory of uses and rumors and to determine the public's attitudes towards television promotion of pharmaceutical products. A survey of (25) a questions was distributed to a sample of the audience of 150 people. The statistical program SPSS was used to unload the data and for the calculation of frequencies and percentages and correlation coefficients. The research reached several results, Most importantly, the television promotion is well receiv

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat