Elzaki Transform Adomian decomposition technique (ETADM), which an elegant combine, has been employed in this work to solve non-linear Riccati matrix differential equations. Solutions are presented to demonstrate the relevance of the current approach. With the use of figures, the results of the proposed strategy are displayed and evaluated. It is demonstrated that the suggested approach is effective, dependable, and simple to apply to a range of related scientific and technical problems.
John Updike’s use of setting in his fiction has elicited different and even conflicting reactions from critics, varying from symbolic interpretations of setting to a sense of confusion at his use of time and place in his stories. The present study is an attempt at examining John Updike’s treatment of binary settings in Pigeon Feathers and Other Stories (1962) to reveal theme, characters’ motives and conflicts. Analyzing Updike’s stories from a structuralist’s perspective reveals his employment of two different places and times in the individual stories as a means of reflecting the psychological state of the characters, as in “The Persistence of Desire”, or expressing conflicting views on social and political is
... Show MoreA new colorimetric-flow injection method has been developed and validated for the detection of Cefotaxime sodium in pharmaceutical formulations. This method stands out for its rapid and sensitive nature. The formation of a brown-colored complex between Cefotaxime sodium and the Biuret reagent in a highly alkaline environment serves as the basis for the detection. The intensity of this colored complex is measured using a custom-built Continuous Flow Injection Analyzer, enabling accurate quantification of Cefotaxime sodium. Optimization studies of the chemical and physical parameters such as dilution of Biuret reagent, effect of the medium basicity, flow rate, sample loop and others have been investigated. The calibration gra
... Show MoreMassive multiple-input multiple-output (massive-MIMO) is a promising technology for next generation wireless communications systems due to its capability to increase the data rate and meet the enormous ongoing data traffic explosion. However, in non-reciprocal channels, such as those encountered in frequency division duplex (FDD) systems, channel state information (CSI) estimation using downlink (DL) training sequence is to date very challenging issue, especially when the channel exhibits a shorter coherence time. In particular, the availability of sufficiently accurate CSI at the base transceiver station (BTS) allows an efficient precoding design in the DL transmission to be achieved, and thus, reliable communication systems can be obtaine
... Show MoreSeveral stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti
... Show MoreInformation security in data storage and transmission is increasingly important. On the other hand, images are used in many procedures. Therefore, preventing unauthorized access to image data is crucial by encrypting images to protect sensitive data or privacy. The methods and algorithms for masking or encoding images vary from simple spatial-domain methods to frequency-domain methods, which are the most complex and reliable. In this paper, a new cryptographic system based on the random key generator hybridization methodology by taking advantage of the properties of Discrete Cosine Transform (DCT) to generate an indefinite set of random keys and taking advantage of the low-frequency region coefficients after the DCT stage to pass them to
... Show MoreIn the midst of the public narrative film , we discussed the issue of dealing with the current narrative more specialized which its future dimension form shift and twist on the level of construction narrative film in some of its diverse and renewable trends in its two ways theoretical and practical and non-give important implications for the modes of operation of the renewable narrative structures and the fact that the cinema is an arts which always open to ideas in neighboring fields and this come naturally as a result of the continuing intellectual and knowledge sharing between cinema and other science . our current research has already begun to address the issue in a stream of consciousness narrative structure film based on all that t
... Show MoreThe study aimed at designing a training program by using training for the anaerobic differential threshold stand and the effects of those trainings on the variables of (Concentration of Lactic Acid and LDH Enzyme, VO2 MaX and Cortisol Hormone). The Researchers used the experimental program with one-group style. Also, they used a sample with (8) men-players in a (free 400 m men-runners) and they used many instruments and procedures, most notably the training-program prepared for 10 weeks and for 3 training units weekly, (70-90 min) for each unit. They used the training intensity from 85-100% of the player's ability. After finishing the training program and doing some pre-tests and post-tests then statistically checking the results, the resea
... Show MorePrecise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables
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