زينب حسين محمد المهداوي

In this work we present a study on the performance of signal similarity measures under non-Gaussian noise. Pink noise has been considered, with 1/f power spectral density. This kind of noise has been generated by filtering Gaussian noise through an FIR filter. One-dimensional and two-dimensional signals have been considered. We tested 2D image similarity using the well-known similarity measures: Structural Similarity Index Measure (SSIM), modified Feature-based Similarity Measure (MFSIM), and Histogram-based Similarity Measure (HSSIM). Also, we tested 1D similarity measures: Cosine Similarity, Pearson Correlation, Tanimoto similarity, and Angular similarity. Results show that HSSIM and MFSIM outperform SSIM in low PSNR under pink noise and Gaussian noise. For 1D similarity, it is shown that Cosine Similarity and Pearson Correlation outperform other 1D similarity, especially at low SNR.

Some think that there is a gap between mathematics, poetry, and the vocabulary of the Arabic language by describing mathematics as mere numbers and equations, unlike Arabic poetry which consists of rhyme, weight, and promotion. Where, language, is a system of words or symbols used to express something within a system, the language may refer to a communication system using symbols or characters. But we think that the gap between them (especially in the modern era) is due to the lack of integration between workers in the field of mathematics and modern technologies with poets and specialists in the field of language. In this study, the computer was used to find two important applications in the field of the Arabic language. The first one focuses on measuring the power of the verb performance of Arabic words (measured in numerical value), based on the derivation of mathematical relationships that connect vocabulary and letters that able to apply in the computer. While the second topic of this study focused on finding a numerical value representing the degree of clarity of the words in the recipient's ear. The efficiency of the proposed algorithms was checked and examined, and the results were impressive and accurate.

Information security has become the topic of most interest nowadays. Because of significant technological development, transferring information from one person to another has become very easy. This information may be exposed to penetration by unauthorized persons, so the security interest in encryption and steganography has increased. In this paper presents a novel approach by integrating the methodologies of steganography and encryption, resulting in an algorithm that exhibits enhanced resilience against external attacks. The key is first initialized using Grigorchuk's group, which gives an unstructured permutation of data bits. Followed by the stage of encrypting the audio file using RC4, which relies on random generation of the final key in which it is encrypted. In order to increase security and protect data from hacking, the encrypted audio file is hidden in video frames using a non-sequential method based on LSB. The proposed method proved effective results in data preservation as it provided the Peak Signal-to-Noise Ratio scale value of 88, which makes high imputation capacity.

https://mng.uokufa.edu.iq/archives/14770

https://mng.uokufa.edu.iq/archives/14657

1 . الارتقاء بمستوى المختبرات التعليمية. 2 . زيادة الثقة في نتائج الاختبار والقياس . 3 . زيادة ثقة ادارة المؤسسة التعليمية في جودة اداء منتجها التعليمي . 4 . ضبط الاجراء غير المطابق للمعايرة او الاختبار من خلال الطريقة الاجرائية المتمثلة بالأجراء التصحيحي والاجراء الوقائي . 5 . تحقيق التطوير والتحسين المستمر .