Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the

Existing leachate models over–or underestimates leachate generation by up to three orders of magnitude. Practical experiments show that channeled flow in waste leads to rapid discharge of large leachate volumes and heterogeneous moisture distribution. In order to more accurately predict leachate generation, leachate models must be improved. To predict moisture movement through waste, the two–domain PREFLO, are tested. Experimental waste and leachate flow values are compared with model predictions. When calibrated with experimental parameters, the PREFLO provides estimates of breakthrough time. In the short term, field capacity has to be reduced to 0.12 and effective storage and hydraulic conductivity of the waste must be increased to

Global date palm production is steadily increasing and adopting technologies such as unmanned aerial vehicles (UAVs) and deep learning can reduce costs, save time, and improve productivity. To address this issue, the authors have proposed an innovative approach that uses UAVs for high-resolution aerial imaging. These images, collected by the Department of Computer Engineering at Al-Salam University in Baghdad and the Institute of Machine Design, Faculty of Mechanical Engineering, Poznan University of Technology, support improved orchard management, palm counting, and yield estimation. Precise spraying and pollination are also facilitated and accelerated, reducing overall cultivation costs. The proposed methodology involves processing captur

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

Background: An accurate adaptation of the crown to the finish line is essential to minimize cement dissolution and to preserve periodontium in fixed partial denture cases. An accurate adaptation of crown is possible only when preparation details are captured adequately in the impression and transferred to cast. For these reasons, gingival displacement is necessary to capture subgingival preparation details.The aim of the present study is to measure in vivo the horizontal displacement of the gingival sulcus obtained by using three new cordless retraction materials (Magic Foam Cord®, Racegel and Astringent Retraction Paste) in comparison to medicated retraction cord. Materials and method: Thirty-two patients requiring porcelain fused to me

Silver diamine fluoride (SDF) has shown effectiveness in hardening tooth structure and killing bacteria. Therefore, it can be used to prevent and arrest dental caries. Riva Star (SDF) treatment alone will stop cavities but will not reverse the cavitation. The Silver Modified Atraumatic Procedure, often known as Smart, is the optimum technique for regaining the tooth's structure and function. Glass ionomer was introduced in (1972) as a new material that has become one of the most widely used materials in restorative dentistry. By releasing fluoride ions, this material has a therapeutic impact on the surrounding tooth structure. Microleakage is the ingress of bacteria, its byproducts, toxins, chemicals, oral fluids, and ions between t

Objective: The objectives of the present study were to evaluate the effectiveness of the instructional intervention
about medical and health knowledge of patients with diabetes mellitus type II.
Methodology: A Quasi- experimental study was carried out in National Center for Diabetes Mellitus/ Almustansria
University, started from 4th January 2012, to 1st April 2012. Non-probability (purposive sample) of (50) diabetes
mellitus type II, who visit National Center for Diabetes Mellitus/ Almustansria University. The study sample is
divided equally into (25) study and (25) control groups. The study group received the instructional intervention.
While the control not exposed to the instructional intervention. The data are coll