The goal of this work is demonstrating, through the gradient observation of a   of type linear ( -systems), the possibility for reducing the effect of any disturbances (pollution, radiation, infection, etc.) asymptotically, by a suitable choice of related actuators of these systems. Thus, a class of  ( -system) was developed based on finite time  ( -system). Furthermore, definitions and some properties of this concept -system and asymptotically gradient controllable system ( -controllable) were stated and studied. More precisely, asymptotically gradient efficient actuators ensuring the weak asymptotically gradient compensation system ( -system) of known or unknown disturbances are examined. Consequently, under convenient hypo

This study included synthesizing silver nanoparticles (AgNPs) in a green method using AgNO3 solution with glucose exposed to microwave radiation. The prepared NPs were also characterized using ultraviolet and visible (UV-vis) spectroscopy and scanning electron microscopy (SEM). The UV/vis spectroscopy confirmed the production of AgNPs, while SEM analysis showed that the typical spherical AgNPs were 30 nm and 50 nm in size for the NPs prepared using black tea (B) and green tea (G) as reducing agent, respectively. The changes in some of the biochemical parameters related to the liver and kidneys have been analyzed to evaluate the probable toxic effects of AgNPs. 40 adult male mice were included in this study. To assess the probable he

The research objective are analyze financial leverage advantage through analyze and discuss financial leverage cost, and achieve tax advantage. study include two firms ,oil firm and industrial companies firm with limited liability.The inductive method is used for the applied part in analyzing the financial data of the companies considered in 2011-2015.The result of the study shows that the financial leverage achieve present value of the costs is Negative . The study concluded that the most important conclusions of the tax advantage of leverage is higher costs as well as achieving a low tax shield ,This study found out the results that interest payments related to pre-tax all of the loan amount and the percentage of the interest rate on b

The Purpose of this study are  analyze financial lease advantage through analyze and discuss financial lease cost, and achieve tax advantage to reach study objective. study include two firms ,oil firm and construction firm with limited liability. The inductive method is used for the applied part in analyzing the financial data of the companies considered in 2011-2015.The result of the study shows that the financial  lease achieve present value of the costs is positive. This study found out the results that verify the hypothesis: The tax advantage of financial Leasing is characterized by decreasing cost and achieving higher tax shield. The study also found the most important recommendations of awareness of the benefits arising f

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Abstract

Robotics manipulators with structural flexibility provide an attractive alternative to rigid robotics manipulators for many of the new and evolving applications in robotics. In certain applications their use is unavoidable. The increased complexity in modeling and control of such manipulators is offset by desirable performance enhancements in some respects. In this paperthe single- link flexible robotics manipulator was designed and implemented from Perspex and designed with 0.5 m length , 0.02 m width and with 0.004 m thickness with mass located at the tip. There are four subsystems; motion, control, accelerometer and gyro and a host computer subsystem. The work principle of single-link robotics manipul

This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used

The research aims to identify how to enhance the quality of the human resources, focusing on four dimensions (efficiency, effectiveness, flexibility, and reliability), by adopting an adventure learning method that combines theoretical and applied aspects at the same time, when developing human resources and is applied using information technology, and that Through its dimensions, which are (cooperation, interaction, communication, and understanding), as the research problem indicated a clear deficiency in the cognitive perception of the mechanism of employing adventure learning dimensions in enhancing human resources quality, so the importance of research was to present treatments and proposals to reduce this problem. To achieve

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de