The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi

يهدف البحث الحالي الى استكشاف علاقات التفاعل والتاثير بين الاحتكام للمكانة والتوجه للفردية– الجماعية والدمج التنظيمي مستنداً على مزج اختلاف القيم الشخصية مع افكار نظرية الهوية الاجتماعية لبلورة نموذج البحث. وفي ضوء هذا تم صياغة عدد من الفرضيات التي توضح علاقات التفاعل ما بين ابعاد الاحتكام للمكانة والتوجه للفردية– الجماعية للتنبؤ بوجود الدمج التنظيمي. جمعت البيانات باستخدام استمارة الاستبيان ووزع

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  Summary This research, entitled  (Distinguishing Voice Features of Qalqales Voices and their Expressive Values ​​in the Holy Quran), aims to shed light on five of the voices that are characterized by strength and intensity, whose pronunciation requires loud vocal tone, great effort and semantic dimensions.The research consists of two topics .in the first topic. We talked about the voices of Alqalqal , their definition, their degrees, their ranks, and the opinions of scholars about them.

In the second topic, titled Expressive Values ​​for Weak Voices in the Holy Qur’an, we talked about the relationship between sound and meaning, and we clarified in it the expressive values ​​of Qalqa

Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of