he effect of different cultural conditions on production of bioemulsifier from Serratia marcescens S10 was determined; different carbon and nitrogen sources were used such as: different oils include: edible (vegetable) oils (olive oil, sesame oil, sun flower oil and corn oil) and heavy oils (oil 150, oil 60, oil 40) as carbon sources and (NH4Cl, casein, (NH4)2SO4, peptone, tryptone, gelatin and yeast extract) as nitrogen sources were added to production media. Bioemulsifier was estimated by measuring the surface tension (S.T), emulsification activity (E.A) and emulsification index (E24%). The best results of bioemulsifier production from Serratia marcescens S10 were obtained at pH8 and incubated at 37ºC for 5days, using sesame oil

To test the effect of 4 levels of nitrogen (i.e. 0, 45, 90 and 135 Kg N ha^-1) as urea (46% N) and 3 levels of phosphorus (i.e. 0, 17.5 and 35 Kg P ha^-1) as triple superphosphate (21.8% P) on yield and concentration of dill (Anethum graveolens L. local cultivar) seed oil this experiment was carried out during winter season of 1999 - 2000 at the experimental field of Agriculture College, Abu-Ghraib.

 Both fertilizers were applied in two equal splits, first at seeds sowing and the second was added one month after emergence. Dried and ground seed samples were subjected to water distillation for extraction of volatile oils

 Result indicated that fertilization of dill plants with 90 Kg N

Nitrogen (N) is a key growth and yield-limiting factor in cultivated rice areas. This study has been conducted to evaluate the effects of different conditions of N application on rice yield and yield components (Shiroudi cultivar) in Babol (Mazandaran, Iran) during the 2015- 2016 season. A factorial experiment executed of a Randomized Complete Block Design (RCBD) used in three iterations. In the first factor, treatments were four N amounts (including 50, 90, 130, and 170 kg N ha^-1), while in the second factor, the treatments consisted of four different fertilizer splitting methods, including T₁:70 % at the basal stage + 30 % at the maximum tillering stage, T₂:1/3 at the basal stage + 1/3 at the maximum ti

In this study, the Halder-Wagner method was used for an analysisX-ray lines of Tio2 nanoparticles. Where the software was used to calculate the FWHM and integral breath (β) to calculate the area under the curve for each of the lines of diffraction. After that, the general equation of the halder- Wagner method is applied to calculate the volume (D), strain (ε), stress (σ), and energy per unit(u). Volume (β). Where the value of the crystal volume was equal to (0.16149870 nm) and the strain was equal to (1.044126), stress (181.678 N / m2), and energy per unit volume (94.8474 J m-3).The results obtained from these methods were then compared with those obtained from each of the new paradigm of the HalderWagner method, the Shearer developm

In this research work a composite material was prepared contains a matrix which is unsaturated polyester resin (UPE) reinforced with carbon nanotube the percentage weight (0.1, 0.2, 0.4.0.5) %, and Zn particle the percentage weight (0.1, 0.2,0.4,0.5)%.
All sample were prepared by hand lay-up, process the mechanical tests contains hardness test, wear rate test, and the coefficient of thermal conductivity. The results showed a significant improvement in the properties of overlapping, Article containing carbon nano-tubes and maicroparticles of zinc because of its articles of this characteristics of high quality properties led to an, an increase in the coefficient of the rmalconductivity, and increase the hardness values with increased pe

Pattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o

Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul