Student performance may influence by several factors in all his study levels such as primary school, intermediate school and even in his college; some of these factors are psychological factors, social factors, and the factors which correlate with student environment.

In this paper we study some of these factors to discover their influence by using canonical correlation analysis to analyze the data. Many conclusions are discovered to help who focuses student performance or to make it pest in future.

Background: Saliva plays an important role in oral health. Several salivary proteins are involved in the antimicrobial defence mechanism and are able to eliminate or inhibit bacterial growth in the oral cavity. Secretory IgA (SIgA) is one of the principal antibodies present in saliva, could help oral immunity by preventing microbial adherence, neutralizing enzymes and toxins. The aim of this study was to investigate the relationship between salivary Streptococcus Mutans (SM) count and S IgA in stimulated whole saliva in children with primary dentition compared to those with permanent teeth in relation to some oral hygiene parameters. Material and methods: Stimulated whole saliva was collected from 50 children (25 with primary dentation and

Background: Saliva is a specific bio-fluid with important biomarkers. Analyzing any alternation in these markers could give valuable information, in relation to oral health status parameters. The aim of this study was to investigate the level of α -amylase in unstimulated whole saliva of healthy, primary school children in relation to some oral health parameters. Materials and Methods: A questionnaires consisted of demography and medical histories of participants were filled by children families. Saliva samples were collected for 5- minutes between 9:00 -11:00 AM from 114 healthy students aged 6-13 years, divided into four age groups. Flow- rate, Plaque and Gingival Index were assessed and dentition status was investigated by DMFT/dmft

Was conducted neutralize content Albulamedi for local isolates using Alacardan dye orange selection experience showed loss of local isolates resistant life antibiotic ampicillin, chloramphenicol

Those interested in the educational process and lesson management sought to invest the information experience with industrial intelligence and technology because of its importance in increasing the effectiveness of lesson management and developing the creative capabilities of the teacher in directing and managing his lesson. Field research for sports educational institutions that are interested in managing the lesson and preparing mathematical teaching cadres is an important issue and necessary means for identifying the most important phenomena that accompany the process of managing the educational process, as the teacher's success in providing the appropriate conditions to provide rich and influencing experiences in managing and directing

Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different

A strong sign language recognition system can break down the barriers that separate hearing and speaking members of society from speechless members. A novel fast recognition system with low computational cost for digital American Sign Language (ASL) is introduced in this research. Different image processing techniques are used to optimize and extract the shape of the hand fingers in each sign. The feature extraction stage includes a determination of the optimal threshold based on statistical bases and then recognizing the gap area in the zero sign and calculating the heights of each finger in the other digits. The classification stage depends on the gap area in the zero signs and the number of opened fingers in the other signs as well as