In the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn

واحدة من أكثر مواد السيراميك الهيكلية الواعدة هي كربيد السيليكون(SiC) ، حيث له خصائص حرارية وكهروميكانيكية ممتازة. هذه الخصائص مفيدة ل CMC لتعزيز أداء المركب خاصة عند إضافات النانو المتكاملة. في هذا البحث, تم تصنيع مركب SiC من SiC بثلاثة تركيزات مع  ZnO و Si. تم اختبار الخواص المغناطيسية لجميع المخاليط باستخدام مراقبة العينة الاهتزازية (VSM). تم تلبيد العينات الخضراء في فرن التلبيد عند 1600 درجة مئوية في بيئة النيتروجي

This paper demonstrates the spatial response uniformity (SRU) of two types of heterojunctions (CdS, PbS /Si) laser detectors. The spatial response nonuniformity of these heterojunctions is not significant and it is negligible in comparison with p+- n silicon photodiode. Experimental results show that the uniformity of CdS /Si is better than that of PbS /Si heterojunction

A variety of new phenolic Schiff bases derivatives have been synthesized starting from Terephthaladehyde compound, all proposed structures were supported by FTIR, 1H-NMR, 13C-NMR, Elemental analysis, some derivatives evaluated by Thermal analysis (TGA).

There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it