In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending

The purpose of this paper is to find the best multiplier approximation of unbounded functions in    –space by using some discrete linear positive operators. Also we will estimate the degree of the best multiplier approximation in term of modulus of continuity and the averaged modulus.

In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients

      A comparison of gas sensing performance of V₂O₅:Ag nanoparticles as thin film and as bulk pellet toward NO₂ and NH₃ is presented. V₂O₅:Ag nanoparticles thin films were deposited by vacuum thermal evaporation method on glass substrates while the pellets were prepared by powder technology. XRD patterns of thin film and pellet were polycrystalline with an orthorhombic structure. The value of average grain size is about 60 nm. The morphological properties of the samples have been distinguished by atomic force microscopy (AFM) and field effect scanning electron microscopy (FESEM) which indicated that the films showed homogeneous surfaces morphology a

The coefficient of performance of a window type Air-Conditioner system can be improved if a reduction in the work of compressor can be achieved by a suitable technique. The present study investigates the effect of dispersing a low concentration of TiO2 nanoparticles in the mineral oil based lubricant, as well as on the overall performance of a window type Air-Conditioner system using R22 as the working fluid. An enhancement in the COP of the refrigeration system has been observed and the existence of an optimum volume fraction noticed, with low concentrations of nanoparticles suspended in the mineral oil. Results showed that the average compressor work reduced by 13.3%, which ultimately resulted in an increase of 11.99% in the COP due to

In this study we using zirconium sulfate, Punica granatum plant extract, and an alkaline medium, to created ZrO₂ nanoparticles. They were then characterized using a variety of techniques, including FT-IR, UV-visible, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The Debye-Scherrer equation was used to calculate the crystal size in X-ray diffraction and found to be 27.82 nm. The particle size of ZrO₂ nanoparticles was determined using atomic force microscopy, scanning electron microscopes, and transmission electron microscopy. Utilizing ZrO₂ NPs, the metal ions M (II) = Co, Ni, and Cu were successfully a

In this research, porous silicon (PS) prepared by anodization etching on surface of single crystalline p-type Si wafer, then Gold nanoparticle (AuNPs) prepared by pulsed laser ablation in liquid. NPs deposited on PS layer by drop casting. The morphology of PS, AuNPs and AuNPs/PS samples were examined by AFM. The crystallization of this sample was characterized by X-ray diffraction (XRD). The electrical properties and sensitivity to CO2 gas were investigated to Al/AuNPs/PS/c-Si/Al, we found that AuNPs plays crucial role to enhance this properties.

Citrate-gel auto combustion technique was used to synthesize nickel-copper mixed ferrite nanoparticles Ni_xCu_1-xFe₂O₄ (x= 0.0, 0.4, 1.0) with different calcinating temperatures (200, 450, 650 and 850 °C). Structural, morphological, magnetic, and electrical properties were studied using X-ray diffraction (XRD), transmission electron microscopy (TEM), field emission scanning electron microscopy (FE-SEM), Fourier transform infrared spectroscopy (FTIR), vibrating sample magnetometer (VSM), and LCR meter in order to determine significant influences of Cu²⁺ cations content in nickel ferrite. The XRD patterns showed that all compositions had cubic spinels, except CuFe₂O₄

Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencies were 32.79%, 75