The important factor in the success of construction projects is its ability to objective estimate of the cost of the project and adapt to the changes of the external environment, which is affected by a lot of elements and the requirements of the competitive environment. The faces of those projects are several problems in order to achieve particular goals. To overcome these difficulties has been the development of research in the last two decades and turn the focus on the role of the cost of project management, by providing information and assist management in planning and control of the budget among the main elements of the project, namely, (time-cost-quality),The research aims at the possibility of developing and implementing mechanisms

Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M

total of 17 Escherichia coli isolates were collected from urine specimens of patients with urinary tract infection. Antibiotics sensitivity test indicated that amikacin followed by chloramphenicol and ciprofloxacin are the most effective antibiotics. The isolates showed multidruge resistant, nine isolates were resistant to 11-15 antibiotics, 3 were resistant to 16-20 antibiotics and 5 were resistant to 21-25 antibiotic. Two isolates were selected, the first (ED1) was resistant to (22) antibiotics while the second isolate (ED2) was resistant to (14) antibiotics (out of 25). Minimum inhibitory concentration (MIC) of the black and green tea water boiled extracts were determined towards (ED1,ED2).Results showed that MIC of black tea extr

Metal nanoparticles can serve as an efficient nano-heat source with confinement photothermal effects. Thermo-plasmonic technology allows researchers to control the temperature at a nanoscale due to the possibility of precise light propagation. The response of opto-thermal generation of single gold-silica core-shell nanoparticle immersed in water and Poly-vinylpyrrolidone surrounding media is theoretically investigated. Two lasers (CW and fs pulses) at the plasmonic resonance (532 nm) are utilized. For this purpose, finite element method is used via COMSOL multiphysics to find a numerical computation of absorption cross section for the proposed core –shell NP in different media. Thermo-plasmonic response for both lasers is studied. The

Background: Plasma-activated water (PAW) is considered one of the emerging strategies that has been highlighted recently in the food industry for microbial decontamination and mycotoxin detoxification, due to its unique provisional characteristics. Aim: The effectiveness of PAW for aflatoxin B1 (AFB1), ochratoxin A (OTA), and fumonisin B1 (FB1) detoxification in naturally contaminated poultry feeds with its impacts on the feed quality were inspected. Methods: PAW-30 and PAW-60 were utilized for feed treatment for six time durations (5, 10, 15, 20, 40 and 60 min) each. The alterations in the physicochemical properties of PAW after different time durations of plasma inducement and treatment with and without feed samples were monit

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