That communication between people is not only through speech but includes other images of the most important body inspiration. And that the Koran worked on the diversity of ways in which the meanings of the hearer and did not stop at the limit of speech, but included situations where the use of body inspiration and indicate its importance in communication. However, signals and organ movements play a major role in the process of communication between people. Facial and hands movements play an important role in the communication process as they are a tool for communicating ideas to others.

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

This paper suggest two method of recognition, these methods depend on the extraction of the feature of the principle component analysis when applied on the wavelet domain(multi-wavelet). First method, an idea of increasing the space of recognition, through calculating the eigenstructure of the diagonal sub-image details at five depths of wavelet transform is introduced. The effective eigen range selected here represent the base for image recognition. In second method, an idea of obtaining invariant wavelet space at all projections is presented. A new recursive from that represents invariant space of representing any image resolutions obtained from wavelet transform is adopted. In this way, all the major problems that effect the image and

The problem of finding the cyclic decomposition (c.d.) for the groups ), where  prime upper than 9 is determined in this work. Also, we compute the Artin characters (A.ch.) and Artin indicator (A.ind.) for the same groups, we obtain that after computing the conjugacy classes, cyclic subgroups, the ordinary character table (o.ch.ta.) and the rational valued character table for each group.

Vascular patterns were seen to be a probable identification characteristic of the biometric system. Since then, many studies have investigated and proposed different techniques which exploited this feature and used it for the identification and verification purposes. The conventional biometric features like the iris, fingerprints and face recognition have been thoroughly investigated, however, during the past few years, finger vein patterns have been recognized as a reliable biometric feature. This study discusses the application of the vein biometric system. Though the vein pattern can be a very appealing topic of research, there are many challenges in this field and some improvements need to be carried out. Here, the researchers reviewed

Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro

Background: occult blood loss must be considered as a
possible cause in every case of iron deficiency anemia.
Objective: to evaluate upper gastrointestinal endoscopy
in finding a potential cause for iron deficiency anemia
among children in Al-Anbar governorate.
Methods: Twenty five children aged 2-14 years, referred
to the gastroenterology unit in Al-Ramadi General Hospital
for upper gastrointestinal endoscopy had iron deficiency
anemia. Fiberoptic endoscopy was used under general
anesthesia and endoscopic tissue biopsies were taken from
22 patients for histopathological examination.
Results: The main presenting signs and symptoms were
pallor, abdominal pain, and stunting. The upper
gastrointestinal