Fluid-structure interaction method is performed to predict the dynamic characteristics of axial fan system. A fluid-structure interface physical environment method (monolithic method) is used to couple the fluid flow solver with the structural solver. The integration of the three-dimensional Navier-Stokes equations is performed in the time Doman, simultaneously to the integration of the three dimensional structural model. The aerodynamic loads are transfer from the flow to structure and the coupling step is repeated within each time step, until the flow solution and the structural solution have converged to yield a coupled solution of the aeroelastic set of equations. Finite element method is applied to solve numerically

     In this paper, two different chaotic dynamic systems are coupled using a semiconductor laser to produce a new chaotic system. These two chaotic systems are Rossler and Chua systems. X-dynamic of Rossler system was coupled optically using optical fiber as a carrier of signal with x, y, and z-dynamics of Chua system. The results were analyzed and the behavior of Chua system was found to be changing in time series which, in turn, changed the attractor. The Chua attractor was converted from double scroll to single scroll. The results obtained from connecting two different systems in chaotic behavior showed a remarkable increase in the bandwidth of Chua system. This increase in bandwidth opens up a wide field for many

Cost estimation is considered one of the important tasks in the construction projects management. The precise estimation of the construction cost affect on the success and quality of a construction project. Elemental estimation is considered a very important stage to the project team because it represents one of the key project elements. It helps in formulating the basis to strategies and execution plans for construction and engineering.  Elemental estimation, which in the early stage, estimates the construction costs depending on  . minimum details of the project so that it gives an indication for the initial design stage of a project. This paper studies the factors that affect the elemental cost estimation as well as the rela

      In this study, an efficient photocatalyst for water splitting was developed. The Cr₂O₃ and TiO₂ nanoparticles (Cr₂O₃-TNPs) nanocomposite with (Chitosan extract) was created using ecologically friendly methods, such as the impregnation technique as TiO₂ exhibits nano spherical (TNPs) shape structure. According to the researchers, this nanocomposite material enhanced its ability to absorb ultraviolet light while also speeding up the recombination of photogenerated electrons and holes. The TNPs and prepared Cr₂O₃-TNPs were characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), energy dispersive x-ray sp

Polycystic ovary syndrome(PCOS) is a heterogeneous disorder of uncertain etiology , it is the most common endocrinopathy in women and most common cause of anovulatery infertility ,characterized by chronic anovulation and hyperandrogenemia .The present study was designed to investigate the effect of silymarin which is known to have antioxidant and insulin sensitivity effects on the  levels of glucose, insulin ,testosterone ,leutinizing hormone(LH) and progesterone .Ovulation rate and Homeostasis Model Assessment of insulin Resistance (HOMA) ratio were determined .A 3-months of treatment were conducted in 60 PCOS patients in three well-matched groups .The first one (n=20),received silymarin(750mg/day)  .The second group received

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m