Estimation of the unknown parameters in 2-D sinusoidal signal model can be considered as important and difficult problem. Due to the difficulty to find estimate of all the parameters of this type of models at the same time, we propose sequential non-liner least squares method and sequential robust M method after their development through the use of sequential approach in the estimate suggested by Prasad et al to estimate unknown frequencies and amplitudes for the 2-D sinusoidal compounds but depending on Downhill Simplex Algorithm in solving non-linear equations for the purpose of obtaining non-linear parameters estimation which represents frequencies and then use of least squares formula to estimate linear parameters which represents amplitude . solve non-linear equations using Newton –Raphson method in sequential non-linear least squares method and obtain parameters estimate that represents frequencies and linear parameters which represents amplitude at the same time, and compared this method with sequential robust M method when the signal affected by different types of noise including the normal distribution of the error and the heavy-tailed distributions error, numerical simulation are performed to observe the performance of the estimation methods for different sample size, and various level of variance using a statistical measure of mean square error (MSE), we conclude in general that sequential non-linear least squares method is more efficiency compared to others if we follow the normal and logistic distribution of noise, but if the noise follow Cauchy distribution it was a sequential robust M method based on bi-square weight function is the best in the estimation.
In this work, the nano particles of Na-A zeolite were synthesized by sol –gel method. The samples were characterized by X-ray diffraction (XRD), X-ray luorescence (XRF), Surface area and pore volume, Atomic Force Microscope (AFM) and Fourier Transform Infrared Spectroscopy (FTIR). Results show that the nano A zeolite is with average crystal size is 74.77 nm., Si/Al ratio 1.03, BET surface area was 581.211m2/g and the pore volume for NaA was found equal to 0.355cm3/g.
The -multiple mixing ratios of γ-transitions from levels of populated in the are calculated in the present work by using the a2-ratio methods. We used the experimental coefficient (a2) for two γ -transitions from the same initial state, the statistical tensor, which is related to the a2-coefficient would be the same for the two transitions. This method was used in a previous work for pure transitions or which can be considered pure. In these cases the multiple mixing ratios for the second transition ( ) equal zero, but in our work we applied this method for mixed γ-transitions and then the multiple mixing ratio ( ) is known for one transition. Then we calculate the ( ) value and versareversa. The we
... Show MoreBackground: 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 of initial casting by Ponseti technique. Methods :A cross sectional observational study with some comparative content done in Al-kindy
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CD-nanosponges were prepared by crosslinking B-CD with diphenylcarbonate (DPC) using ultrasound assisted technique. 5-FU was incorporated with NS by freeze drying, and the phase solubility study, complexation efficiency (CE) entrapment efficiency were performed. Also, the particle morphology was studied using SEM and AFM. The in-vitro release of 5-FU from the prepared nanosponges was carried out in 0.1N HCl.
5-FU nanosponges particle size was in the nano size. The optimum formula showed a particle size of (405.46±30) nm, with a polydispersity index (PDI) (0.328±0.002) and a negative zeta potential (-18.75±1.8). Also the drug entrapment efficiency varied with the CD: DPC molar ratio from 15.6 % to 30%. The SEM an
... Show MoreIn this research, A thin film of Rhodamine B dye and TiO2 Nanoparticles doped in PMMA Polymer has been prepared by a casting method. The sample was spectrum absorption by UV-Vis. The nonlinear optical properties were measured by Z- scan technique using Nd:YAG laser with (1064 nm) wavelength. The nonlinear refractive index (n2) and nonlinear absorption coefficient (β) were estimated for the thin film for different energies of the laser, n2 and β were decreased with increasing intensity of incident laser beam. Also, the type of β was two-photon absorption and n2 negative nonlinear reflective.
Measuring the efficiency of postgraduate and undergraduate programs is one of the essential elements in educational process. In this study, colleges of Baghdad University and data for the academic year (2011-2012) have been chosen to measure the relative efficiencies of postgraduate and undergraduate programs in terms of their inputs and outputs. A relevant method to conduct the analysis of this data is Data Envelopment Analysis (DEA). The effect of academic staff to the number of enrolled and alumni students to the postgraduate and undergraduate programs are the main focus of the study.
<p>In this paper, a simple color image compression system has been proposed using image signal decomposition. Where, the RGB image color band is converted to the less correlated YUV color model and the pixel value (magnitude) in each band is decomposed into 2-values; most and least significant. According to the importance of the most significant value (MSV) that influenced by any simply modification happened, an adaptive lossless image compression system is proposed using bit plane (BP) slicing, delta pulse code modulation (Delta PCM), adaptive quadtree (QT) partitioning followed by an adaptive shift encoder. On the other hand, a lossy compression system is introduced to handle the least significant value (LSV), it is based on
... Show MoreThis paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance
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