The current research creates an overall relative analysis concerning the estimation of Meixner process parameters via the wavelet packet transform. Of noteworthy presentation relevance, it compares the moment method and the wavelet packet estimator for the four parameters of the Meixner process. In this paper, the research focuses on finding the best threshold value using the square root log and modified square root log methods with the wavelet packets in the presence of noise to enhance the efficiency and effectiveness of the denoising process for the financial asset market signal. In this regard, a simulation study compares the performance of moment estimation and wavelet packets for different sample sizes. The results show that wavelet p

A total of nine swab samples were collected from inflamed teeth and gingiva of human’soral cavity from a dentist clinic in Baghdad. All specimens were cultured in Mitis Salivarius agar medium and the isolated bacterial pure colonies werethen identified by using VITEK2. Three samples were diagnosed and identified as Staphylococcus lentus. One of the three isolates which showed a distinctive heavy growth on the media was selected for further analysis in this study. Paper disk diffusion method was used to detect the antibacterial activityof three of mouthwash solutions (Zak, Colgate and Listerine). The results showed that “Colgate” was the most active solution with antibacterial activity compared with the other two s

In this reserch Some new substituted and unsubstituted poly imides compounds. were synthesized by reaction of acrylol chloride with different amides (aliphatic and aromatic) in a suitable solvent in the presence amount triethyl amine (Et3N) with heating. The Structure confirmation of all polymers were confirmed using FT-IR,1H-NMR,13C-NMR and UV spectroscopy. Thermal analysis (TG) for some polymers showed their thermal stabilities. Other physical properties including softening points, melting point and solubility of the polymers were also measured

This study investigates the improvement of Iraqi atmospheric gas oil characteristics which contains 1.402 wt. % sulfur content and 16.88 wt. % aromatic content supplied from Al-Dura Refinery by using hydrodesulfurization (HDS) process using Ti-Ni-Mo/γ-Al₂O₃ prepared catalyst in order to achieve low sulfur and aromatic saturation gas oil. Hydrodearomatization (HDA) occurs simultaneously with hydrodesulfurization (HDS) process. The effect of titanium on the conventional catalyst Ni-Mo/γ-Al₂O₃ was investigated by physical adsorption and catalytic activity test.Ti-Ni-Mo/γ-Al₂O₃ catalyst was prepared under vacuum impregnation condition to ensure efficient pr

In this work, diamond-like carbon (DLC) thin films were prepared from Cyclohexane. Thin films were deposited on quartz substrate by atmospheric pressure Argon plasma jet system. The plasma jet system was applying high voltage sinusoidal waves of frequency 28 kHz and potential difference of 7.5kV peak to peak across the electrodes. The effect of annealing at 400, 500 and 600 °C under vacuum for two hours on optical properties and structural properties of the DLC thin films were investigated. This effect was clarified by X-ray diffraction (XRD), FTIR, UV-Visible absorption, Scanning Electron Microscopy (SEM) and Raman Spectroscopy. The X-ray diffraction patterns for the annealing DLC thin films show two broad peaks at 2θ, 26.62° and 51.58

A Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton

This work revealed the spherical aromaticity of some inorganic E4 cages and their protonated E4H+ ions (E=N, P, As, Sb, and Bi). For this purpose, we employed several evaluations like (0D-1D) nucleus independent chemical shift (NICS), multidimensional (2D-3D) off-nucleus isotropic shielding σiso(r), and natural bond orbital (NBO) analysis. The magnetic calculations involved gauge-including atomic orbitals (GIAO) with two density functionals B3LYP and WB97XD, and basis sets of Jorge-ATZP, 6-311+G(d,p), and Lanl2DZp. The Jorge-ATZP basis set showed the best consistency. Our findings disclosed non-classical aromatic characters in the above molecules, which decreased from N to Bi cages. Also, the results showed more aromaticity in E4 than E4H+

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol