importumt educational institution as (kindergartens) need teachers which qualified ownes modalities in their education for children , as Marzanu method in a way of learning and own methods of crisis management, because the teachers that own those styles of learning ginekindergarten children knowledge and the childrenIeaving based on theMeaing and knowledge and integration of their information, And teachers that earn methods of crisis management provide for the children of the kindergarten security within the educational institution which in turn affect the growth and development of the Child and then abilities, health physical, mental, psychological …etc.., The aims of the current research have identified to recognize: 1- the dimension

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

Le présent travail aborde la question de l’enseignement de traduction en tant que matière faisant partie du programme élaboré dans des Départements de Français au sein de certaines universités irakiennes, en particulier celle de Bagdad. La méthode d’enseigner suivie constitue une véritable problématique qu’on a bien diagnostiquée à partir de quelques années d’expériences, à la lumière des observations faites dans des cours de traduction professionnelle, et dans la perspective des citations et témoignages établies par des traductologues et pédagogues et principalement par Marianne LEDERER qui a établi la Théorie Interprétative de la traduction. Mais pourquoi l’enseignement lui-même poserait une telle probl

Afamin, which is a human plasma glycoprotein, a putative multifunctional transporter of hydrophobic molecules and a marker for metabolic syndrome. Afamin concentration have been proposed to have a significant role as a predictor of metabolic disorders. Since NAFLD is associated with metabolic risk factors, e.g., dyslipidemia, insulin resistance and visceral obesity, it is considered as the hepatic manifestation of the metabolic syndrome. The objective of this study is to determine Afamin levels in hypothyroid patients with and without fatty liver disease and compare the results with controls. Also to study the relationship of Afamin level with the Anthropometric and Clinical Features (Age, Gender, BMI and Duration of Hypothyroidism) , Serum

Abstract

This study identified the developing of a range of students' geography learning skills and the change in their attitudes toward fieldwork as a consequence of leaning experiences that occurred within a field trip. The sample of the study consisted of (27) students within a special topic course enrolled in Geography Department at Umm Al-Qura University in Saudi Arabia in semester 2, 2018. A range of students' geography learning skills were measured by the skills questionnaire that consisted of 12 geography skills after completing field work. Changes in students' at

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Manual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that