Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-201

In this research the specifications of Iraqi drinking bottled water brands are investigated throughout the comparison between local brands, Saudi Arabia and the World Health Organization (WHO) for bottled water standard specifications. These specifications were also compared to that of Iraqi Tap Water standards. To reveal variations in the specifications for Iraqi bottled water,  and above mentioned standards some quality control tools are conducted for more than 33% of different bottled water brands (of different origins such as spring, purified,..etc) in Iraq by investigating the  selected quality parameters registered on their marketing labels. Results employing Minitab software (ver. 16) to generate X bar,

Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

Groundwater 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

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca