There is no doubt that teachers are the leaders of positive changing in community where they directed the students and build their brains. In our current generation that characterized by accelerated technological development that communication changes, economic and politics, needs from the teacher an active leadership skills that match with the soul of our generation and contribute in confrontation the current challenges and the future challenges in the form that lead to create a conscious generation where they will be a basic brick for the future community where the listeners looking forward the education where they support the continuity communication of develop process, economy, scientifically and in all life fields. In our study we take a different ways for training teachers, the basic principles that assist in the organization of curricula, basics and goals of education to achieve that the teacher must have skills that qualifies him to achieve the main goals and all of that depends on his responsibilities for humiliating the difficulties in the education of a foreign language and find a sequences of techniques that facilitate the education process.
This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att
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The work in this paper involves the planning, design and implementation of a mobile learning system called Nahrain Mobile Learning System (NMLS). This system provides complete teaching resources, which can be accessed by the students, instructors and administrators through the mobile phones. It presents a viable alternative to Electronic learning. It focuses on the mobility and flexibility of the learning practice, and emphasizes the interaction between the learner and learning content. System users are categorized into three categories: administrators, instructors and students. Different learning activities can be carried out throughout the system, offering necessary communication tools to allow the users to communicate with each other
... Show MoreThe paper examines key aspects of the use of phraseologi-cal units related to colors in Russian culture and speech. It explores their role in shaping cultural identity, reflecting national characteristics and men-tality. The study analyzes the frequency and contexts of the use of color-related phraseological units in contemporary speech, as well as the influ-ence of media and literature on their popularization. The author highlights the significance of phraseological units in preserving cultural heritage and fostering a deeper understanding of language and culture.
The objective of the current research is to identify the degree of awareness of the teachers of Arabic language with the requirements of sustainable development. The research sample consisted of (100) male and female teachers of the Arabic language. A 3-likert scale of (71) items grouped into practical and cognitive aspects, five trends for each aspect was designed by the researcher to explore the required data. The results showed that the level of awareness of teachers of the Arabic language was moderate of both the cognitive and practical aspects of sustainable education with means (1.69) and (1.48) respectively. The researcher presented a set of recommendations and suggestions.
ABSTRACT
Threw this research to the following:
1 - Know the impact of strategy Puglia in the collection of the rules of the Arabic language
students at the Institute of preparation parameters .
2 - Know the impact of the retention strategy in Puglia collection rules Arabic language
students at the Institute of preparation parameters .
To verify the status Mmermaa Find researcher Elsafreeten following two hypotheses :
1 - There is no statistically significant difference between the average score for the collection
of the fourth grade students at the Institute for the preparation of material parameters who
were studying grammar strategy Puglia and average grades collectible fourth grade
students at the Institu
That achieve a level of excellence for the quality of university education cannot be achieved only by uniting the efforts of all employees at the university and active participation by students and by alumni and the labor market and society, however we can say that the administrative and academic university staff play an active role and the largest in achieving equivalent quality of higher education, It should unite the efforts of all employees in the educational institution in order to achieve quality education. It is the concept of quality of education, quality assurance and overall management of the quality of the basic pillars on which it is based university education. That highlight the need fo
... Show MoreThis study investigates the complex challenges of managing heritage sites in Iraq, focusing on the Prophet Tho Al-Kifl Shrine in Babylon due to its religious, historical, and architectural significance. The site exemplifies critical management issues, including institutional fragmentation, limited technical and financial resources, and insufficient legislative frameworks. Left unaddressed, these challenges threaten the site's material integrity and symbolic identity through uncoordinated interventions and neglect. The research aims to propose a context-sensitive framework for sustainable heritage management by combining theoretical perspectives with practical analysis. Using a case study methodology, the study draws on field observations, h
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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
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