This study examines the vibrations produced by hydropower operations to improve embankment dam safety. This study consists of two parts: In the first part, ANSYS-CFX was used to generate a three-dimensional (3-D) finite volume (FV) model to simulate a vertical Francis turbine unit in the Mosul hydropower plant. The pressure pattern result of the turbine model was transformed into the dam body to show how the turbine unit's operation affects the dam's stability. The upstream reservoir conditions, various flow rates, and fully open inlet gates were considered. In the second part of this study, a 3-D FE Mosul dam model was simulated using an ANSYS program. The operational turbine model's water pressure pattern is conveyed t

The research (The Aesthetics of Lumia Art in Contemporary Textile Arts: An Analytical Study) included four chapters, the first to explain the research problem summarized by the question: Does the art of Lumia achieve aesthetic values in contemporary textile arts?, and aims to: Identify the aesthetics of Lumia art and its applied uses in contemporary textile arts, within the time period (2013-2022). The third chapter included: research procedures and sample analysis (4) models according to the descriptive analytical approach, and the fourth chapter dealt with: results, conclusions and recommendations as well as sources.

Abstract:
The aim of the present research is to evaluate the child’s nutritional
method (2-5 years old) which is based on his resistance of the food highly rich
with nutritional elements and his acceptance of the food of a low nutritional
value in addition to his having forbidden food with other mates and making
use of all mates when having food, in establishing the sound social values and
affection since child hood. The required statistical equation have been used
by the researcher namely (Z test).
The sample of the present study consists of (26) children who were selected
intentionally and randomly from the kindergartens of Al-Bayaa region and the
college of Education for women. The questionnaires were d

Abstract

          Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s

What is the contract of cultivating the land of the waqf in Islamic jurisprudence and the Algerian Awqaf law

1-[4-(2-Hydroxy-4, 6-dimethyl-phenylazo)-phenol]-ethanone (HL1) and 2-(4-methoxy-phenylazo)-3, 5- dimethyl-phenol (HL2) were produced by combination the diazonium salts of amines with 3, 5- dimethylphenol. The geometry of azo compounds was resolved on the basis of (C.H.N) analyses, 1H and 13CNMR, FT-IR and UV-Vis spectroscopic mechanisms. Complexes of La (III) and Rh (III) have been performed and depicted. The formation of complexes has been identified by using elemental analysis, FTIR and UV-Vis spectroscopic process as well, conductivity molar quantifications. Nature of complexes produced have been studied obeyed mole ratio and continuous alteration ways, Beer's law followed through a concentration scope (1×10-4 - 3×10-4 M). High molar

This investigation reports application of a mesoporous nanomaterial based on dicationic ionic liquid bonded to amorphous silica, namely nano-N,N,N′,N′-tetramethyl-N-(silican-propyl)-N′-sulfo-ethane-1,2-diaminium chloride (nano-[TSPSED][Cl]2), as an extremely effectual and recoverable catalyst for the generation of bis(pyrazolyl)methanes and pyrazolopyranopyrimidines in solvent-free conditions. In both synthetic protocols, the performance of this catalyst was very useful and general and presented attractive features including short reaction times with high yields, reasonable turnover frequency and turnover number values, easy workup, high performance under mild conditions, recoverability and reusability in 5 consecutive runs without lo

In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor

Over the last period, social media achieved a widespread use worldwide where the statistics indicate that more than three billion people are on social media, leading to large quantities of data online. To analyze these large quantities of data, a special classification method known as sentiment analysis, is used. This paper presents a new sentiment analysis system based on machine learning techniques, which aims to create a process to extract the polarity from social media texts. By using machine learning techniques, sentiment analysis achieved a great success around the world. This paper investigates this topic and proposes a sentiment analysis system built on Bayesian Rough Decision Tree (BRDT) algorithm. The experimental results show