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Learning to write the Arabic alphabet is crucial for Arab children’s cognitive development, enhancing their memory and retention skills. However, the lack of Arabic language educational applications may hamper the effectiveness of their learning experience. To bridge this gap, SamAbjd was developed, an interactive web application that leverages deep learning techniques, including air-writing recognition, to teach Arabic letters. SamAbjd was tailored to user needs through extensive surveys conducted with mothers and teachers, and a comprehensive literature review was performed to identify effective teaching methods and models. The development process involved gathering data from three publicly available datasets, culminating in a collection of 31,349 annotated images of handwritten Arabic letters. To enhance the dataset’s quality, data preprocessing techniques were applied, such as image denoising, grayscale conversion, and data augmentation. Two models were experimented with using a convolution neural network (CNN) and Visual Geometry Group (VGG16) to evaluate their effectiveness in recognizing air-written Arabic characters. Among the CNN models tested, the standout performer was a seven-layer model without dropout, which achieved a high testing accuracy of 96.40%. This model also demonstrated impressive precision and F1-score, both around 96.44% and 96.43%, respectively, indicating successful fitting without overfitting. The web application, built using Flask and PyCharm, offers a robust and user-friendly interface. By incorporating deep learning techniques and user feedback, the web application meets educational needs effectively.

The recognition of alphabet signs is pivotal for the educational, linguistic, and cognitive development of individuals. This paper delves into the application of Convolutional Neural Networks (CNNs) on the ArASL database, a compilation of Arabic alphabet sign language images. Several CNN architectures underwent testing for image classification, with the EfficientNet B7 model emerging as the most effective, achieving an outstanding test accuracy of 99.24%. Capitalizing on the success of this optimized model, we have developed a real-time application with a dual purpose: to serve as a user-friendly tool for learning Arabic sign language and to enhance communication for individuals who are deaf or hard of hearing. The application, designed for seamless integration into users' daily lives, facilitates an intuitive engagement with the Arabic sign language alphabet. Its real-time functionality empowers users to learn and communicate effortlessly, breaking down barriers and fostering inclusivity in communication. This research contributes not only to the field of computer vision and deep learning but also to the broader spectrum of inclusive education and accessibility. By harnessing cutting-edge technology, our application represents a significant step forward in leveraging artificial intelligence for the betterment of education.

This work presents the design and analysis of newly developed reconfigurable, flexible, inexpensive, optically-controlled, and fully printable chipless Arabic alphabet-based radio frequency identification (RFID) tags. The etching of the metallic copper tag strip is performed on a flexible simple thin paper substrate (ϵr = 2.31) backed by a metallic ground plane. The analysis of investigated tags is performed in CST MWS in the frequency range of 1–12 GHz for the determination of the unique signature resonance characteristics of each tag in terms of its back-scattered horizontal and vertical mono-static radar cross section (RCS). The analysis reflects that each tag has its own unique electromagnetic signature (EMS) due to the changing current distribution of metallic resonator. This EMS of each tag could be used for the robust detection and recognition of all realized 28 Arabic alphabet tags. The study also discusses, for the first time, the effect of the change in font type and size of realized tags on their EMS. The robustness and reliability of the obtained EMS of letter tags is confirmed by comparing the RCS results for selective letter tags using FDTD and MoM numerical methods, which shows very good agreement. The proposed tags could be used for smart internet of things (IoT) and product marketing applications.

From the seventeenth century to the nineteenth century Philippine Moros increasingly wrote the Spanish language in Arabic script known as Philippine Jawi. This cultural phenomenon, which went beyond mere code switching, is illustrated through documents found in the National Archives of the Philippines, particularly protocols involving the Tausug and Maguindanao sultanates. The use of Spanish in Jawi documents increased, thanks to Zamboanga's role as a cultural center in the south and Manila's ability to attract sultans politically. Jawi was also used as the script in language primers through the strategic work of the Jesuit Jacinto Juanmartí, who originated Moro philology.

Books in this series are concise works that furnish learners with relevant contemporary expressions, jargon and new coinages to express modern concepts across broad areas of interest such as the media, the Internet, law and business.

No country in the world has changed its language policy--including the choice of alphabet --as frequently as the Soviet Union did. There were three main periods of alphabet change: the 1920s; the second part of the 1930s; and the last years of the USSR. The revolution set new goals--it expressed the need to transfer official communication from Russian into the languages of ethnic minorities, to create middle and higher education in them and so on. However, many languages were unwritten; the existing scripts of some other languages (traditional Arabic or Mongolian) were considered unacceptable. It was necessary to create new alphabets. After some hesitation, the Latin script was chosen as predominant in the world. More than 80 alphabets were constructed in the 1920s-1930s. However from 1935 to 1938 it was decided that all Soviet languages using the Latin alphabet would adopt Cyrillic. This Cyrillization was completed in 1941, before the beginning of the war. The official slogans remained the same, but the spread of Russian and the Cyrillic script became a main task of Soviet language policy. This situation did not change until the 1980s when national movements in the USSR spoke out against Russian and the use of the Cyrillic script. After the disintegration of the USSR in 1991 and the formation of new states, the problem of alphabet choice became urgent. Latinization was accomplished in Azerbaijan, Uzbekistan, Turkmenistan and Moldavia; it is planned in Kazakhstan and Kyrgyzstan. Some proposals to latinize Russian have no practical significance.KeywordsSoviet Union; Language Policy; Alphabet; Latin Alphabet; Cyrillic Alphabet; Arabic Alphabet; Latinization; Change of Policy; New States.

This book gives you up-to-date expressions, jargon and new coinages to express modern concepts across broad areas of interest such as the media, the internet, law and business.

The Arabic script in Africa is a collection of sixteen papers on the past and present use of Arabic script to write African languages other than Arabic, discussing the (ethno-)historical, (socio-)linguistic, and in particular grammatological aspects of such writing traditions.

No detailed description available for \"Peter the Venerable and Islam\".

ISLAMIC PAINTING