Background: Dental caries is one of the most prevalent chronic diseases of people worldwide that lead to the pain and disability across all age groups and still consider as a major cause of tooth loss. The aim of this study was to assess the prevalence and severity of dental caries and treatment needs among school children in Heet city. Materiales and methods: The sample included all school children at age of (12 years old) males and females from urban areas in Heet city. Diagnosis and recording of dental caries and treatment needs were done according to the criteria of WHO. Results: The prevalence of dental caries was (90.2%). The DMFS/dmfs values were (5.85±0.168, 1.57±0.146) respectively for the total sample. Females were foun

Background: The autism spectrum disorder (ASD) describes a wide range of symptoms, including difficulty with social interaction and communication skills. Controversial thinking about oral health of children with ASD, in general may have a lower hygiene level than healthy individuals, low caries rate and high body weight in comparison to healthy children. This study was conducted to assess the oral health status in relation to nutritional status among institutionalized autistic children and adolescents. Materials and methods: From 12 institutes in Baghdad, the study group contained 364 child and adolescent with ASD (Male= 294, Female=70), while control group included 441 normal child and adolescent (Male=357, Female=84) from primary and seco

The problem of slow learning in primary schools’ pupils is not a local or private one. It is also not related to a certain society other than others or has any relation to a particular culture, it is rather an international problem of global nature. It is one of the well-recognized issues in education field. Additionally, it is regarded as one of the old difficulties to which ancient people gave attention. It is discovered through the process of observing human behaviour and attempting to explain and predict it.
Through the work of the two researchers via frequent visits to primary schools that include special classes for slow learning pupils, in addition to the fact that one of the researcher has a child with slow learning issue, t

Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n^-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

KE Sharquie, AA Noaimi, MA Al-Shukri, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 3

      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

Survival analysis is one of the types of data analysis that describes the time period until the occurrence of an event of interest such as death or other events of importance in determining what will happen to the phenomenon studied. There may be more than one endpoint for the event, in which case it is called Competing risks. The purpose of this research is to apply the dynamic approach in the analysis of discrete survival time in order to estimate the effect of covariates over time, as well as modeling the nonlinear relationship between the covariates and the discrete hazard function through the use of the multinomial logistic model and the multivariate Cox model. For the purpose of conducting the estimation process for both the discrete

Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi