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.
To determine the abilities of salivary E‐cadherin to differentiate between periodontal health and periodontitis and to discriminate grades of periodontitis.
E‐cadherin is the main protein responsible for maintaining the integrity of epithelial‐barrier function. Disintegration of this protein is one of the events associated with the destructive forms of periodontal disease leading to increase concentration of E‐cadherin in the oral biofluids.
A total of 63 patients with periodontitis (case) and 35
A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m
... Show MoreThe purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury p
... Show MoreRegression models are one of the most important models used in modern studies, especially research and health studies because of the important results they achieve. Two regression models were used: Poisson Regression Model and Conway-Max Well- Poisson), where this study aimed to make a comparison between the two models and choose the best one between them using the simulation method and at different sample sizes (n = 25,50,100) and with repetitions (r = 1000). The Matlab program was adopted.) to conduct a simulation experiment, where the results showed the superiority of the Poisson model through the mean square error criterion (MSE) and also through the Akaiki criterion (AIC) for the same distribution.
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... Show MoreThis study aims to assess the water quality index (WQI) according to the Canadian Council of Ministers of the Environment's Water Quality Index method (CCME WQI). Four locations (measurement stations) are selected along the Tigris River, in Iraq. Two of them are located in the north near Mosul City, (Mosul Dam and Mosul city), and the other two are located in the south near Al-Amarah city, (Ali Garbi and Al-Amarah). The water data collected is for the period 2011 to 2013, including eleven water quality parameters. These are magnesium (Mg+2), calcium (Ca2+), potassium (K+), sodium (Na+), sulfate (SO42-), chloride (Cl-), nitrate (NO3<
... Show MoreCrime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o
Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.