This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

   The remediation oil production by matrix acidizing method on the well named "X" (for confidential reasons) is scrutinized in this paper. Initial production of 1150 bpd, production index of 2.8 STB/Psi/d and permeability of 150md, in 2018 two years down the lane this dropped to 450 bpd, production index 0.7 STB/Psi/d. The declined observed on the production index is trouble shouted and after elimination of (no completion damage/perforation damage), the skin is calculated by carrying out a well test (build-up test) whose extrapolation in excel over times gave us a skin of 40.The reservoir heterogeneity, containing >20% of feldspar, carbonates and paraffin’s guided thematrix acidizing design and treatment proposition to remedy thi

Background: Congenital club foot is a complex deformity of foot .It is a collection of different abnormalities, with different etiologies. Consequently, Severity varies with   difficulties in evaluating treatment strategies with outcome results. The treatment of congenital club foot remains controversial. Usually, the orthopedist's goal is to obtain anatomically and functionally normal feet in all patients.                                Objective: To asses short term follow up result of conservatively treated club feet in relation to the age

        In this study, Zinc oxide nanostructures were synthesized via a hydrothermal method by using zinc nitrate hexahydrate and sodium hydroxide as a precursor. Three different annealing temperatures were used to study their effect on ZnO NSs properties. The synthesized nanostructure was characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), Atomic force microscope (AFM), and Fourier Transform Infrared Spectroscopy (FTIR). Their optical properties were studied by using UV -visible spectroscopy. The XRD analysis confirms that all ZnO nanostructures have the hexagonal wurtzite structure with average crystallite size within the range of (30.59 - 34

In this study, aluminum nanoparticles (Al NPs) were prepared using explosive strips method in double-distilled deionized water (DDDW), where the effect of five different currents (25, 50, 75, 100 and 125 A) on particle size and distribution was studied. Also, the explosive strips method was used to decorate zinc oxide particles with Al particles, where Al particles were prepared in suspended from zinc oxide with DDDW. Transmission electron microscopy (TEM), UV-visible absorption spectroscopy, and x-ray diffraction are used to characterize the nanoparticles. XRD pattern were examined for three samples of aluminum particles and DDDW prepared with three current values (25, 75 and 125 A) and three samples prepared with the same currents for zin

This study introduced the effect of using magnetic abrasive finishing method (MAF) for finishing flat surfaces. The results of experiment allow considering the MAF method as a perspective for finishing flat surfaces, forming optimum physical mechanical properties of surfaces layer, removing the defective layers and decreasing the height of micro irregularities. Study the characteristics which permit judgment parameters of surface quality after MAF method then comparative with grinding

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri