Abstract. Shatt Al-Arab River was the most important tide river in Iraq, it suffered from neglect and lack of maintenance in the past decades. The river embankment is constantly exposed to erosion processes due to several factors, one of the most important of these factors is the movement of water currents due to the tidal energy coming from the Arabian Gulf. In this study, one dimension unsteady-state model was implemented to study river flood capacity simulation by using HEC-RAS (5.0.7) software in Shatt Al Arab River and its tributaries. The data included flow rate, water level records were collected daily from 2018 to 2020 at different stations along the mentioned river and its feeders, additionally, the considered flood discharge data

Human Resources Management Practices (HRMP) and managerial control represent two academic fields that have been and still are the focus of many studies. However, merging both fields and studying the relationship that connects them and also the role that HRMP play in achieving the requirements of managerial control represents a new and novel study according to the available literature in these fields.

To achieve these goals, this study has been conducted, using the surveying questionnaire method, on a sample of ten general inspector offices in Iraq that work in the field of control for ministries and independent committees. A questionnaire has been used to collect the data which was analyzed with several s

This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

The hydraulic conditions of a flow previously proved to be changed when placing large-scale geometric roughness elements on the bed of an open channel. These elements impose more resistance to the flow.  The geometry of the roughness elements, the numbers used, and the configuration are parameters that can affect the hydraulic flow characteristics. The target is to use inclined block elements to control the salt wedge propagation pointed in most estuaries to prevent its negative effects. The Computational Fluid Dynamics CFD Software was used to simulate the two-phase flow in an estuary model. In this model, the used block elements are 2 cm by 3 cm cross-sections with an inclined face in the flow direction, with a length

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

Quality is one of the important criteria to determine the success of product. So quality control is required for all stages of production to ensure a good final product with lowest possible losses. Control charts are the most important means used to monitor the quality and its accuracy is measured by quickly detecting unusual changes in the quality to maintain the product and reduce the costs and losses that may result from the defective items. There are different types of quality control charts and new types appeases involving the concept of fuzziness named multinomial fuzzy quality control chart (FM) , dividing the product to accepted and not may not be accurate therefore adding fuzziness concept to quality charts confirm and a

Abstract

The current research aims to identify the attitudes towards the Covid-19 vaccine and the Locus of Control (internal, external) among university students, to identify the significance of the difference in attitudes towards the Covid-19 vaccine, the significance of the difference in the Locus of Control (internal, external) according to the gender variable (male, female), and to identify the significance of the difference in students’ attitudes towards Covid-19 vaccine according to the Locus of Control (internal, external). To achieve the objective of the research, the researcher developed two scales, a scale of (20) items to identify the attitudes toward a covid-19 vaccine, and a scale of the locus of c

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

In this paper, a subspace identification method for bilinear systems is used . Wherein a " three-block " and " four-block " subspace algorithms are used. In this algorithms the input signal to the system does not have to be white . Simulation of these algorithms shows that the " four-block " gives fast convergence and the dimensions of the matrices involved are significantly smaller so that the computational complexity is lower as a comparison with " three-block " algorithm .