One of the important units in Sharq Dijla Water Treatment Plant (WTP) first and second extensions are the alum solution preparation and dosing unit. The existing operation of this unit accomplished manually starting from unloading the powder alum in the preparation basin and ending by controlling the alum dosage addition through the dosing pumps to the flash mix chambers. Because of the modern trend of monitoring and control the automatic operation of WTPs due to the great benefits that could be gain from optimum equipment operation, reducing the operating costs and human errors. This study deals with how to transform the conventional operation to an automatic monitoring and controlling system depending on a Programmable

Cognitive-behavioral therapy is one of the most important relatively recent; treatment programs that attempt to modify behavior and control psychological disorders by modifying the individual's thinking style and awareness of himself and his environment, and cognitive reconstruction by replacing negative thoughts with positive ones. The current study aimed to know the effectiveness of a cognitive behavioral treatment program in reducing nervous fatigue among mothers of children with cerebral palsy. The sample on which the nervous fatigue scale was applied consisted of (30) mothers whose son suffers from cerebral palsy, and the results indicated that (24) mothers suffer from nervous fatigue. This sample was divided

بهذا البحث نقارن معاييرالمعلومات التقليدية (AIC , SIC, HQ , FPE ) مع معيارمعلومات الانحراف المحور (MDIC) المستعملة لتحديد رتبة انموذج الانحدارالذاتي (AR) للعملية التي تولد البيانات,باستعمال المحاكاة وذلك بتوليد بيانات من عدة نماذج للأنحدارالذاتي,عندما خضوع حد الخطأ للتوزيع الطبيعي بقيم مختلفة لمعلماته

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

Various speech enhancement Algorithms (SEA) have been developed in the last few decades. Each algorithm has its advantages and disadvantages because the speech signal is affected by environmental situations. Distortion of speech results in the loss of important features that make this signal challenging to understand. SEA aims to improve the intelligibility and quality of speech that different types of noise have degraded. In most applications, quality improvement is highly desirable as it can reduce listener fatigue, especially when the listener is exposed to high noise levels for extended periods (e.g., manufacturing). SEA reduces or suppresses the background noise to some degree, sometimes called noise suppression alg

Receipt date:06/23/2020 accepted date:7/15/2020 Publication date:12/31/2021

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The executive authority differs from one country to another, as it differs from a federal state to another according to the nature of the applied political systems, so this research focused on federal states according to their political systems, then going into the details of the executive authority and its role In the federal states by referring to the four federal experiments

In this paper, a fusion of K models of full-rank weighted nonnegative tensor factor two-dimensional deconvolution (K-wNTF2D) is proposed to separate the acoustic sources that have been mixed in an underdetermined reverberant environment. The model is adapted in an unsupervised manner under the hybrid framework of the generalized expectation maximization and multiplicative update algorithms. The derivation of the algorithm and the development of proposed full-rank K-wNTF2D will be shown. The algorithm also encodes a set of variable sparsity parameters derived from Gibbs distribution into the K-wNTF2D model. This optimizes each sub-model in K-wNTF2D with the required sparsity to model the time-varying variances of the sources in the s

Recently, wireless communication environments with high speeds and low complexity have become increasingly essential. Free-space optics (FSO) has emerged as a promising solution for providing direct connections between devices in such high-spectrum wireless setups. However, FSO communications are susceptible to weather-induced signal fluctuations, leading to fading and signal weakness at the receiver. To mitigate the effects of these challenges, several mathematical models have been proposed to describe the transition from weak to strong atmospheric turbulence, including Rayleigh, lognormal, Málaga, Nakagami-m, K-distribution, Weibull, Negative-Exponential, Inverse-Gaussian, G-G, and Fisher-Snedecor F distributions. This paper extensive

Globalisation and rapid environmental change have created many challenges for public and private organisations across Iraq as a developing country, particularly in the higher education sector. This includes, for example, decreases in government funding; increased demand for higher education; a need for economic transformation, and related competitiveness of organizations. Such challenges require exceptional leaders and strategic planning in order to take action to improve. In Iraq, the higher education sector is still one of the main foundations in progressing the knowledge economy. Studies into leadership style, strategic planning processes, and the importance of leadership and organisational culture to an organisation’s success have bee