In this paper, a procedure to establish the different performance measures in terms of crisp value is proposed for two classes of arrivals and multiple channel queueing models, where both arrival and service rate are fuzzy numbers. The main idea is to convert the arrival rates and service rates under fuzzy queues into crisp queues by using graded mean integration approach, which can be represented as median rule number. Hence, we apply the crisp values obtained to establish the performance measure of conventional multiple queueing models. This procedure has shown its effectiveness when incorporated with many types of membership functions in solving queuing problems. Two numerical illustrations are presented to determine the validity of the

Artichoke (Cynara scolymus L.) is a nutritious vegetable that grown all over the world. It is a promising herbal plant, rich in bioactive components. It is considered as medicinal plant due to its nutritional and phytochemical composition, especially high proportion of phenolic compounds. The primary aim of this study was to achieve chemical profile analyses of artichoke for different phytochemcials, especially Scolymoside and Cynaroside. Methanolic crude was extracted from Artichoke leaves by rotary evaporator and separated by column chromatography. The fractions monitored by Thin Layer Chromatography (TLC), and identified in High-Pressure Liquid Chroma

A novel Schiff base ligand (DBC) synthesized from 4-chlorobenzoic acid, along with its Cu (II) and Co (II) complexes, was prepared and characterized using FT-IR, 1H and 13C-NMR, UV-Vis spectroscopy, as well as magnetic and conductivity measurements. Based on this, a tetrahedral structure of [M(DBC)Cl2] was proposed for the complexes. Antioxidant activity of the compounds was assessed and compared to ascorbic acid, revealing that the copper complex exhibited superior antioxidant properties compared to the cobalt complex and the ligand. Furthermore, the antibiofilm potential of the copper and cobalt complexes was assessed against five clinically relevant bacterial species (P.aeruginosa, E.coli, K.pneumoniae, S.aureus and S.typhi) usin

DeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detectio

the study including isolation and identification of candida spp causing UTIs from patintes coming to al-yarmouk hospital

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

Digital change detection is the process that helps in determining the changes associated with land use and land cover properties with reference to geo-registered multi temporal remote sensing data. In this research change detection techniques have been employed to detect the changes in marshes in south of Iraq for two period the first one from 1973 to 1984 and the other from 1973 to 2014 three satellite images had been captured by land sat in different period. Preprocessing such as geo-registered, rectification and mosaic process have been done to prepare the satellite images for monitoring process. supervised classification techniques such maximum likelihood classification has been used to classify the studied area, change detection aft