The aim of the current research is to know the degree to which middle school teachers and female teachers in the southern border schools use electronic educational alternatives in the field of education from their point of view and its relationship to some variables, and to achieve this goal, a random sample of (200) teachers was selected in southern border schools, and a questionnaire was prepared to collect The data, as well as the descriptive approach was used to achieve this goal. T-test and analysis of variance were used for the statistical treatment. The results concluded that the educational courses provided to male and female teachers are not sufficient. It has also been concluded that the use of electronic educational alternatives in girls ’schools is higher than that of boy’s schools. It has also been concluded that professional development did not differ according to specialization, and it did not differ in different education offices.
This research includes an analytical and critique study for the version of the University Service Law No.23 for the year 2008, containing all its aspects and failure whether in its legislation or its applications.
يناقش البحث المقومات المادية والمجتمعية والموضوعية للدور الاقليمي العراقي بعد العام 2010 والفرص المتاحة والقيود التي تحد منه والافاق المستقبلية لهذا الدور في ظل بيئة اقليمية تسودها منظومات تحالف متناقضة في الاهداف والاستراتيجيات
Television white spaces (TVWSs) refer to the unused part of the spectrum under the very high frequency (VHF) and ultra-high frequency (UHF) bands. TVWS are frequencies under licenced primary users (PUs) that are not being used and are available for secondary users (SUs). There are several ways of implementing TVWS in communications, one of which is the use of TVWS database (TVWSDB). The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. With this in mind, the authors present a reinforcement learning-ba
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الخلاصة
يتضمن البحث تعيين عنصر الزئبق السام بتراكيزنزرة عالية الدقة (نانوغرام) باستخدام منظومة يخار الزئبق البارد لنماذج غذائية (لحوم حمراء ، لحوم بيضاء ) مختلفة ونماذج مائية (ماء النهر، مياه صناعية ، ماء الشرب) وربط المنظومة بتقنية الامتصاص الذري اللهبي.
ان عنصر الزئبق من اشد العناصر سمية وان التراكيز المسموح بها عالميا لايتعدى جزء واحد
A prominent figure such as Yahya bin Khaldoun and a scholar of the moroccan countries in the medieval era, and had a special place in the history of the country and the state of Bani Zayan, and the positions he occupied in it and left his scientific, literary and historical traces, leaving him an imprint in the course of history and its events, and in this study
I dealt with the research: his personal life : his name and lineage, then his upbringing and his family.
The aim of the study is to know this character in the details of his personal and scientific life, according to the historical descriptive research method, including description and presentation of events, and linking them in a
... Show Moreفقد تناولت في موضوعي هذه الآية الكريمة فقد جاء في هذه الآية تعليم من الله عز وجل لرسوله (ص) فلكل داع الى الله من أمته, اسلوباٌ يدعوا به الناس ومحاجة الكافرين بالقرآن, وفيها بيان من الله عز وجل بأنه سيري الناس في المستقبل بعض آياته في كونه, وهي آيات دالات على أن القران حق منزل من عند الله جل جلاله, وليس من وضع البشر, فالناس عاجز عن معرفة الآيات الباهرات التي سيريها الله عز وجل للناس في كونه , وقد أخبرهم عنها في القرآ
... Show MoreThe convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.
Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
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