As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detected signals with various degrees of automation. This paper investigates the application of autocorrelation function (ACF) method to decompose EMG signals to their frequency components. It was found that using the proposed method gives a quite good frequency resolution as compared to that resulting from using short time fast Fourier transform (STFFT); thus more MU’s can be distinguished.
Often there is no well drilling without problems. The solution lies in managing and evaluating these problems and developing strategies to manage and scale them. Non-productive time (NPT) is one of the main causes of delayed drilling operations. Many events or possibilities can lead to a halt in drilling operations or a marginal decrease in the advancement of drilling, this is called (NPT). Reducing NPT has an important impact on the total expenditure, time and cost are considered one of the most important success factors in the oil industry. In other words, steps must be taken to investigate and eliminate loss of time, that is, unproductive time in the drilling rig in order to save time and cost and reduce wasted time. The data of
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Cloud computing offers a new way of service provision by rearranging various resources over the Internet. The most important and popular cloud service is data storage. In order to preserve the privacy of data holders, data are often stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for big data storage and processing in the cloud. Traditional deduplication schemes cannot work on encrypted data. Among these data, digital videos are fairly huge in terms of storage cost and size; and techniques that can help the legal aspects of video owner such as copyright protection and reducing the cloud storage cost and size are always desired. This paper focuses on v
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The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr
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ABSTRACT
Metal (II) complexes of Co, Ni, Cu and Zn with cefdinir C14H13N5O5S2 derivative (L) were synthesized and identification by elemental analysis CHNS Uv-Vis, FTIR, TGA, metal analysis AA, magnetic susceptibility and conduct metric measurement. by analysis the ligand behaves as a bidentate. For the cobalt complex, Tetrahedral geometry shape was suggested, while other complexes that have nickel, copper and zinc ions were proposed as octahedral geometry shape. The experimental method was studied for prevention of corrosion carbon steel in 3.5% NaCl by using a novel Cefdinir derivations drugs. The results showed that metal complex was a strong corro
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