In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

Background: Women with previous two or
more caesarean deliveries are usually
managed by elective cesarean section to avoid
the possible risks of labor.
Objective: To compare the relative risks of
maternal and fetal outcomes in emergency
versus elective previous two or more
caesarean deliveries
Design: Randomized prospective clinical
study
Setting: Al-Elweya Maternity Teaching
Hospital, from 1st of March to 31st of
September 2008.
Methods: The study groups, those who had
previous two or more caesarean deliveries,
were included from the hospital admissions.
The 1st group (102 women) presented in labor
and was managed by caesarean delivery as
soon as it was possible. The second group (7

ABSTRUCT

In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

Copper (Cu) is an essential trace element for the efficient functioning of living organisms. Cu can enter the body in different ways, and when it surpasses the range of biological tolerance, it can have negative consequences. The use of different nanoparticles, especially metal oxide nanoparticles, is increasingly being expanded in the fields of industry and biomedical materials. However, the impact of these nanoparticles on human health is still not completely elucidated. This comparative study was conducted to evaluate the impacts of copper oxide nanoparticles (CuO NPs) and copper sulphate (CuSO4 0.5 (H2O)) on infertility and reproductive function in male albino mice BALB/c. Body weight, the weight of male reproductive organs, mal

Biotreatment using immobilized cells (IC) technology has proved to be the most promising and most economical approach for the removal of many toxic organic pollutants found in petroleum-refinery wastewater (PRW) such as phenol. This study was undertaken to evaluate the degradation of phenol by Pseudomonas cells individually immobilized in two different bio-carrier matrices including polyvinyl alcohol-guar gum (PVA-GG) and polyvinyl alcohol-agar agar (PVA-AA). Results of batch experiments revealed that complete removal of phenol was attained in the first cycle after 150 min using immobilized cells (IC) in both PVA-GG and PVA-AA. Additional cycles were confirmed to evaluate the validity of recycling beads of immob

Objective: To identify of the effect of the different concentrations of the special liquid (for mixing the investment, Gilvest)
and mixed with water/powder ratio on setting time of phosphate–bonded investment.
Method and materials: The present study is (60) specimens made from phosphate bonded investment divided into (4)
groups (control and experimental groups), (15) specimens for each group. The Gillmore needle device is used to setting
time of phosphate bonded investment mixed with different concentration of Gilvest and water.
Results: Showed that there is a high significant difference (P<0.01) between each groups in the ANOVA test and a
significant difference (P<0.05) between the group (A) and control group i

In this work, the effect of atomic ratio on structural and optical properties of SnO₂/In₂O₃ thin films prepared by pulsed laser deposition technique under vacuum and annealed at 573K in air has been studied.  Atomic ratios from 0 to 100% have been used. X-ray diffraction analysis has been utilized to study the effect of atomic ratios on the phase change using XRD analyzer and the crystalline size and the lattice strain using Williamson-Hall relationship. It has been found that the ratio of 50% has the lowest crystallite size, which corresponds to the highest strain in the lattice. The energy gap has increased as the atomic ratio of indium oxide increased.

Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model  in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling  the Symmetric gray scale texture image and estimating by using