The purpose of this resesrh know (the effectiveness of cooperative lerarning implementation of floral material for calligraphy and ornamentation) To achieve the aim of the research scholar put the two zeros hypotheses: in light of the findings of the present research the researcher concluded a number of conclusions, including: -
1 - Sum strategy helps the learner to be positive in all the information and regulations, monitoring and evaluation during the learning process.
2 - This strategy helps the learner to use information and knowledge and their use in various educational positions, and to achieve better education to increase its ability to develop thinking skills and positive trends towards the article.
In light of this, the researcher put a number of recommendations concerning the results of research, including: - the need to adopt a strategic Tags in teaching, which enables students to employ their skills in guiding thought processes, and take personal responsibility in learning, based on the principle of self-learning.
To complement the aspects of research suggest that the researcher the following:a similar study of the current study to know the impact of strategic Tags in variables other than a collection (such as motivation, direction and orientation towards the material, and expressive performance, and reasoning, etc.).
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The research problem lies in the lack of accurate scientific perceptions concerning the reality of the communicator and the factors influencing his job. The research is aimed at introducing the communicator in the university press, clarifying the obstacles facing him, and uncovering the level of his job satisfaction and his visions of developing his work. The researcher adopted the survey method in the collection, analysis, and interpretation of the data using a questionnaire. A set of results and conclusions has been reached, most importantly are:
*The communicator performs multiple missions including writing, editing, and collecting info |
The article approaches the characteristics of Russian literature in the time of Khrushchev or the "thaw" period a very short period of Soviet history, characterized by the easing of the dictatorship of power and relaxation in various areas of people's lives. The interest in the research is focused on the importance of interpreting the family portrait in a short but distinct period in the development of Russian/Soviet literature. The research material is the story of Sholokhov's “The Fate of Man” 1956, the story of Panova “Serioga” 1955, and Abramov’s story “Fatherless” 1961. В статье рассматриваются особенности художественной литературы периода хруще
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The management of wisdom is concerned with the level of expertise, methods of transmission, use and ability to problems and their impact on behavior and human behavior in order to improve it in the form of successful decisions. The importance of management of wisdom in making successful decisions that ensure the survival and development of society through the provision of leaders capable of planning, organization and decision-making to achieve the goals and objectives required in a complex and changing environment. Where the administration faces positions and problems that require operational decisions to organize the activities of the institution in line with the strategic decisions already taken under the proper strategic planning. The ex
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This study aims to highlight the role of financial control in the development of government performance through the use of "GFS" system and its application in the service of government units, which will help them in how to use financial resources efficiently through the quality of accounting information provided by this system in the financial statements that reflect the predictability in that fiscal policy of the state through government programs and activities fee as well as to identify weaknesses and address them quickly in order to avoid wastage and loss of public money, which leads to the possibility of utilization of available financial resources of the state to effectively and efficiently, has been reached that the failure of gove
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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