This paper shows an approach for Electromyography (ECG) signal processing based on linear and nonlinear adaptive filtering using Recursive Least Square (RLS) algorithm to remove two kinds of noise that affected the ECG signal. These are the High Frequency Noise (HFN) and Low Frequency Noise (LFN). Simulation is performed in Matlab. The ECG, HFN and LFN signals used in this study were downloaded from ftp://ftp.ieee.org/uploads/press/rangayyan/, and then the filtering process was obtained by using adaptive finite impulse response (FIR) that illustrated better results than infinite impulse response (IIR) filters did.

In recent years, Wireless Sensor Networks (WSNs) are attracting more attention in many fields as they are extensively used in a wide range of applications, such as environment monitoring, the Internet of Things, industrial operation control, electric distribution, and the oil industry. One of the major concerns in these networks is the limited energy sources. Clustering and routing algorithms represent one of the critical issues that directly contribute to power consumption in WSNs. Therefore, optimization techniques and routing protocols for such networks have to be studied and developed. This paper focuses on the most recent studies and algorithms that handle energy-efficiency clustering and routing in WSNs. In addition, the prime

Abstract

The current research aims to identify the level of partnership between school and community agencies to improve secondary school outcomes for students with intellectual disabilities and develop strategies that help enhance community partnerships between schools and agencies. The researcher used the qualitative research approach; he utilized the interviews as a tool for data collection. The sample of research included (12) participants: three female school leaders, three male-school leaders, three female-school supervisors, and three male-school supervisors in schools that have programs for students with intellectual disabilities in Riyadh. The results of the study showed that the level of partnership bet

Drag reduction (DR) techniques are used to improve the flow by spare the flow energy. The applications of DR are conduits in oil pipelines, oil well operations and flood water disposal, many techniques for drag reduction are used. One of these techniques is microbubbles.  In this work, reduce of drag percent occurs by using a small bubbles of air pumped in the fluid transported. Gasoil is used as liquid transporting in the pipelines and air pumped as microbubbles. This study shows that the maximum value of drag reduction is 25.11%.

The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

Researchers classified deconstruction as a strategy concerned with reading the philosophical, literary, artistic and critical texts according to (construction and deconstruction) binarism, which is an applied procedural space that calls for researching the layers of meaning and its non-closure. It establishes reversals in the text level.  The center changes into a margin and vice versa.  Thus the two researchers sought to study the deconstruction strategy and its work in the theatre field, that deconstruction is considered one of the most important modern currents  that actively inters in reading the theatre show.  The research studies the procedure of the construction and deconstruction of the Iraqi theatre actor reg