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-

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

In this study, an efficient compression system is introduced, it is based on using wavelet transform and two types of 3Dimension (3D) surface representations (i.e., Cubic Bezier Interpolation (CBI)) and 1 st order polynomial approximation. Each one is applied on different scales of the image; CBI is applied on the wide area of the image in order to prune the image components that show large scale variation, while the 1 st order polynomial is applied on the small area of residue component (i.e., after subtracting the cubic Bezier from the image) in order to prune the local smoothing components and getting better compression gain. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, t

Introduction: Cardiovascular diseases are the main cause of death among type 2 diabetic patients. Higher levels of plasminogen activator urokinase receptor have been found to predict morbidity and mortality across acute and chronic diseases in the common populace. This study aims to explore the role of serum plasminogen activator urokinase receptor levels as a cardiometabolic risk factor among type 2 diabetic Iraqi patients. Methods: Seventy type 2 diabetic patients (40 male and 30 female) (mean age: 46.20±7.56 years) participated in this study; 35 patients were with cardiovascular disease and 35 were without cardiovascular disease; their ages range was 40-55 years. In addition, 30 individuals who apparently healthy were selected a

• Islamic art is applied art that searches for everything that is useful and beneficial and Both are properties of Islamic art. Islamic art has many well-established elements and styles and pictures that distinguish it from the rest of the arts among those elements and methods that were used in the architectural cladding artwork Or mosaic murals and mosaic was known in its first form in Babylon in a primitive style similar to it, but the Muslim artist in the era of the Caliphs made the art of mosaic In mosques and palaces.
  Chapter one: This chapter is concerned with introducing the art of mosaic historically and focusing on it.
  Chapter Two: This chapter deals with contemporary Islamic mosaics, especially in Mecca

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

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.

Background: Waterpipe tobacco smoking has become common especially among young people, Waterpipe smoking misconcepted as a safer mean of smoking, so in this study we will highlight the effect of Waterpipe smoking ‎on periodontal and oral health.‎ Materials and method. The selected ‎‎‎100 male subjects of 30-40 years, ‎categorized into 4 groups (each group ‎‎25 subject): Waterpipe smoker ‎with ‎healthy periodontium, ‎Waterpipe smoker ‎‎with chronic periodontitis, Non-‎‎smoker ‎with healthy periodontium and Non-smoker ‎with chronic periodontitis. Whole ‎unstimulated ‎saliva was collected. Clinical measurements: plaque ‎index

Background: Obesity is a serious public health concern that has reached epidemic proportions; the prevalence, as well as the severity of obesity in adolescents is increasing at an alarming rate. A close relationship was found between weight status and dental caries. Thus this research aimed to assess the prevalence and severity of dental caries among overweight adolescent females in relation to physicochemical characteristics of stimulated whole saliva in comparison with normal weight adolescent females. Materials and methods: The total sample involved for nutritional status assessment is composed of 2678 females aged 13-15 years. This was performed using Body Mass Index specific for age and gender according to CDC growth chart (2000). The