The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge have the most significant affect on the predicted TDS concentrations. The results showed that a network with (8) hidden neurons was highly accurate in predicting TDS concentration. The correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE) between measured data and model outputs were calculated as 0.975, 113.9 and 11.51%, respectively for testing data sets. Comparisons between final results of ANNs and multiple linear regressions (MLR) showed that the ANNs model could be successfully applied and provides high accuracy to predict TDS concentrations as a water quality parameter.
Quality is the key to success in today's world, which is based mainly on competition in the provision of high quality services through the application of the modern management method which is called total quality management in organizations. This includes describing the provision of health services and satisfaction of patients . .  
... Show MoreIn this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p
... Show MoreCountries have faced the challenges of high levels of public debt and seek to define the optimum limits to reduce risks to which the financial system can be exposed and its impact on the economy as a whole. Hence the importance of research in studying the impact of internal and external public debt components on indicators of stability of the financial system for the period 2005-2017 for the purpose of knowing the extent of the financial stability indicators response to the high level of the public debt from its optimum ratio, as the aim of the research is to estimate and analyze the dynamic relationship of short and long term between the components of public debt and indicators of financial stability using the (ARDL) model that
... Show MoreDBNRSK Sayed, Journal of Strategic Research in Social Science (JoSReSS), 2020
We study the physics of flow due to the interaction between a viscous dipole and boundaries that permit slip. This includes partial and free slip, and interactions near corners. The problem is investigated by using a two relaxation time lattice Boltzmann equation with moment-based boundary conditions. Navier-slip conditions, which involve gradients of the velocity, are formulated and applied locally. The implementation of free-slip conditions with the moment-based approach is discussed. Collision angles of 0°, 30°, and 45° are investigated. Stable simulations are shown for Reynolds numbers between 625 and 10 000 and various slip lengths. Vorticity generation on the wall is shown to be affected by slip length, angle of incidence,
... Show MoreDiyala Governorate was recently exposed to high flood waves discharged from Hemrin Dam. Since the dam was at its full capacity during the flood period, these waves were discharged to the Diyala River. Because of the reduction in Diyala River capacity to 750m3/s, the cities and villages on both sides of the river banks were inundated. Thus, the study's objective is to design a flood escape out of the Diyala River, to discharge the flood wave through it. The flood escape simulation was done by using HEC- RAS software. Two hundred twenty-three cross sections for the escape and 30 cross-sections of the Diyala River were used as geometric data. Depending on the geological formation that the escape passed t
... Show Moreفقدان الزوج يعد حدثًا يغير حياة النساء، مما يضطرهن إلى السباحة في عالم جديد مليء بالحزن والوحدة والشكوك. مع الوقت، تطورت طريقة تصوير الأرامل بشكل كبير تعكس التغييرات في الآراء والقيم الثقافية. تُمثل الأرامل تقليديًا بأنهن ضعيفات ومعتمدات في الأدب، مستندة إلى افتراض أنهن يفتقدن الدعم المالي بعد وفاة شركائهن. ومع ذلك، فإن هذا التصوير لا يعترف بتأثير الأرملة على الرفاهية والهوية الشخصية. يسعى هذا النص إلى
... Show MoreThis research examines the future of television work in light of the challenges posed by artificial intelligence (AI). The study aims to explore the impact of AI on the form and content of television messages and identify areas where AI can be employed in television production. This study adopts a future-oriented exploratory approach, utilizing survey methodology. As the research focuses on foresight, the researcher gathers the opinions of AI experts and media specialists through in-depth interviews to obtain data and insights. The researcher selected 30 experts, with 15 experts in AI and 15 experts in media. The study reveals several findings, including the potential use of machine learning, deep learning, and na
... Show MoreComputer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul
... Show MoreRegarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct
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