Simplifying formulas that are used for calculations and design are the aim of researchers. For present work, the approach to distinguish the flow under sluice gate was conducted in a laboratory. The extensive experimental program was done to collect fifty-four data points for both free and submerged flow conditions. The data included different discharges, gate openings, flow depths at upstream as well as the flow depths represent a tail water and at a contracted section for downstream. The collected data are analyzed according to a problematic that may encounter in the field, to present a more straightforward (but with acceptable accurate) practical features equations and charts. Based on the proposed formulas, five meth

Identify the effect of an educational design according to the repulsive (allosteric) learning model on the achievement of chemistry and lateral thinking. The sample consisted of (59) students from third-grade intermediate students. They were randomly distributed into two groups (experimental and control), and the equivalence was done in (chronological age, previous achievement in chemistry, intelligence, lateral thinking). The (30) students from experimental group were taught according to the instructional design, other 29 students from the (control) group were taught according to the usual method. Two tests done, one of them is an achievement test consisted of (30) items of the type of multiple choice, the other was a lateral think

 Education is a process of learning and education at the same time. As the conditions of modern life necessitate every person to keep learning, education has become a necessity to meet life needs. The society today is concerned with the educational process and aims to live up the expectations. Since education is an integral part of education and its means, it has become as a mean to achieve its purposes. The educational environment was a traditional environment limited to specific inputs, possibilities and stimulus of both teacher and student. Due to the latest advancement, the educational environment has been expanded to become a rich, with strong connections. It has expanded to encompass the entire global environment. The current

     Face detection systems are based on the assumption that each individual has a unique face structure and that computerized face matching is possible using facial symmetry. Face recognition technology has been employed for security purposes in many organizations and businesses throughout the world. This research examines the classifications in machine learning approaches using feature extraction for the facial image detection system. Due to its high level of accuracy and speed, the Viola-Jones method is utilized for facial detection using the MUCT database. The LDA feature extraction method is applied as an input to three algorithms of machine learning approaches, which are the J48, OneR, and JRip classifiers.  The experiment’s

      Finding similarities in texts is important in many areas such as information retrieval, automated article scoring, and short answer categorization. Evaluating short answers is not an easy task due to differences in natural language. Methods for calculating the similarity between texts depend on semantic or grammatical aspects. This paper discusses a method for evaluating short answers using semantic networks to represent the typical (correct) answer and students' answers. The semantic network of nodes and relationships represents the text (answers). Moreover, grammatical aspects are found  by measuring the similarity of parts of speech between the answers. In addition, finding hierarchical relationships between nodes in netwo

      The transition of customers from one telecom operator to another has a direct impact on the company's growth and revenue. Traditional classification algorithms fail to predict churn effectively. This research introduces a deep learning model for predicting customers planning to leave to another operator. The model works on a high-dimensional large-scale data set. The performance of the model was measured against other classification algorithms, such as Gaussian NB, Random Forrest, and Decision Tree in predicting churn. The evaluation was performed based on accuracy, precision, recall, F-measure, Area Under Curve (AUC), and Receiver Operating Characteristic (ROC) Curve. The proposed deep learning model performs better than othe

One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first