A new approach presented in this study to determine the optimal edge detection threshold value. This approach is base on extracting small homogenous blocks from unequal mean targets. Then, from these blocks we generate small image with known edges (edges represent the lines between the contacted blocks). So, these simulated edges can be assumed as true edges .The true simulated edges, compared with the detected edges in the small generated image is done by using different thresholding values. The comparison based on computing mean square errors between the simulated edge image and the produced edge image from edge detector methods. The mean square error computed for the total edge image (Er), for edge regio

Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

 In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.

Abstract

      In this study, we compare between the autoregressive approximations (Yule-Walker equations, Least Squares , Least Squares ( forward- backword ) and Burg’s (Geometric and Harmonic ) methods, to determine the optimal approximation to the time series generated from the first - order moving Average non-invertible process, and fractionally - integrated noise process, with several values for d (d=0.15,0.25,0.35,0.45) for different sample sizes (small,median,large)for two processes . We depend on figure of merit function which proposed by author Shibata in 1980, to determine the theoretical optimal order according to min

Permeability data has major importance work that should be handled in all reservoir simulation studies. The importance of permeability data increases in mature oil and gas fields due to its sensitivity for the requirements of some specific improved recoveries. However, the industry has a huge source of data of air permeability measurements against little number of liquid permeability values. This is due to the relatively high cost of special core analysis.
The current study suggests a correlation to convert air permeability data that are conventionally measured during laboratory core analysis into liquid permeability. This correlation introduces a feasible estimation in cases of data loose and poorly consolidated formations, or in cas

An experiment was carried out in the vegetables field of Horticulture Department / College of Agriculture / Baghdad University , for the three seasons : spring and Autumn of 2005 , and spring of 2007 , to study the type of gene action in some traits of vegetative , flowery growth , yield and its components in summer squash crosses (4 x 3 = cross 1 , 3 x 7 = cross 2 , 3 x 4 = cross 3 , 3 x 5 = cross 4 , 5 x 1= cross 5 , 5 x 2 = cross 6). The study followed generation mean analysis method which included to each cross (P1 , P2 , F1 , F2 , Bc1P1 , Bc1P2) , and those populations obtained by hybridization during the first and second seasons. Experimental comparison was performed in the second (Two crosses only) and third seasons , (four crosses)

  The study was aimed to isolate and identify endophytic fungi from myrtle (Mrtus communis) leaves and study their extracellular enzymes activity. Results revealed isolation of 99 species or ioslated of endophytic fungi obtained from 500 leaves fragment, which represented colonization frequency (CF) of 20.4%. Those fungi were related to 23 species or isolates, Aspergilli were dominated over all species (11 species) with CF 14%. Moreover A. niger and A. flavus showed the higtest CF values over all. Other isolated fungi were related to the genera: Penicillium spp., Cladosporium sp., Cunninghamella sp., Derchslera sp., Alternaria sp. Paecilomyces sp. and sterile fungi (mycelia sterilia). Extracelluar enzymes activity showed varation in

In the current study, gold nanoparticles were made using Acinetobacter baumannii broth culture. UV-vis, FTIR, XRD, FESEM, AMF, and zeta potential measurements were also used to study the properties of the Ab-AuNPs. The average was 66 nm, ranging from 20 to 90 nm. The examination results proved that the Ab-AuNPs are semi-spherical and varied from 20 to 90 nm, with an average of 66 nm. 

   MTT assay on the breast cancer cell line MCF-7 confirmed the anticancer activity in vitro. Cancer cells showed an important cytotoxic activity of Ab-AuNPs. The breast. Cancer cell. Line.MCF-7 but ineffective against the normal.cell line.MCF-10. The IC50 values of Ab-AuNPs were at 11.45 μg ml-1. The results proved that Ab-