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An Autocorrelative Approach for EMG Time-Frequency Analysis
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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.

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Publication Date
Thu Oct 01 2026
Journal Name
Baghdad Science Journal
Study the effect of position on the time of astronomical twilight
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Twilight is that light appear on the horizon before sunrise and after sunset, Astronomically it is known that sunrise and sunset are effected by high above sea level, but the effect of high above sea level on the time of astronomical twilight still not decided and controversy among astronomers, in This research we studies the effect of high above sea level on the time of astronomical twilight, through adding the equation correct high above sea level to equation computation of twilight and then calculate of changing in the time of twilight for different highest (0-10000) meters above sea level , and the ratio of increase for time with high between (15.45-20.5) minutes. It was found that there was an increase in the time of the twilight along

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Publication Date
Fri Nov 29 2024
Journal Name
The Iraqi Geological Journal
Data Driven Approach for Predicting Pore Pressure of Oil and Gas Wells, Case Study of Iraq Southern Oilfields
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Precise 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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Publication Date
Wed Jun 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Optimal Operating Conditions for Adsorption of Heavy Metals from an Aqueous Solution by an Agriculture Waste
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   The aim of this work is to detect the best operating conditions that effect on the removal of Cu2+, Zn2+, and Ni2+ ions from aqueous solution using date pits in the batch adsorption experiments. The results have shown that the Al-zahdi Iraqi date pits demonstrated more efficient at certain values of operating conditions of adsorbent doses of 0.12 g/ml of aqueous solution, adsorption time 72 h, pH solution 5.5 ±0.2, shaking speed  300 rpm, and smallest adsorbent particle size needed for removal of metals.  At the same time the particle size of date pits has a little effect on the adsorption at low initial concentration of heavy metals. The adsorption of metals increases with increas

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Publication Date
Wed Jul 12 2023
Journal Name
Energies
Finite Time Disturbance Observer Based on Air Conditioning System Control Scheme
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A novel robust finite time disturbance observer (RFTDO) based on an independent output-finite time composite control (FTCC) scheme is proposed for an air conditioning-system temperature and humidity regulation. The variable air volume (VAV) of the system is represented by two first-order mathematical models for the temperature and humidity dynamics. In the temperature loop dynamics, a RFTDO temperature (RFTDO-T) and an FTCC temperature (FTCC-T) are designed to estimate and reject the lumped disturbances of the temperature subsystem. In the humidity loop, a robust output of the FTCC humidity (FTCC-H) and RFTDO humidity (RFTDO-H) are also designed to estimate and reject the lumped disturbances of the humidity subsystem. Based on Lyapunov theo

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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Sealing Depth of Q-Switched Nd:YAG 1064nm Laser in the Treatment of Patients with Hypersensitive Teeth: An In Vitro Study
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The purpose of this work was to study the effects of the Nd:YAG laser on exposed dentinal
tubules of human extracted teeth using a scanning electron microscope (SEM). Eighty 2.5mm-thick
slices were cut at the cementoenamel junction from 20 extracted human teeth with an electric saw. A
diamond bur was used to remove the cementum layer to expose the dentinal tubules. Each slice was
sectioned into four equal quadrants and the specimens were randomly divided into four groups (A to D ).
Groups B to D were lased for 2 mins using an Nd:YAG laser at 6 pulses per second at energy outputs of
80 , 100 and 120 mJ. Group A served as control. Under SEM observation, nonlased specimens showed
numerous exposed dentinal tubules. SEM o

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Publication Date
Sat Feb 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of the Causal Relationship Long-and Short-term Between the Price of Crude Oil, the Global Price of Gold and the US. Dollar Exchange Rate
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This research aims to test the causal relationship long-and short-run between the price of gold the global crude oil price and the exchange rate of the dollar and how you can take advantage of the nature of this relationship, particularly in the Arab oil states that achieve huge surpluses, including Iraq and how to keep on the purchasing power of these surpluses or reduce the levels of risk.

The problem is that the Arab oil countries, adversely affected, as a result of that relationship, due to the fact that its role confined to the sale of crude oil only. They do not have control in the dollar, then they are not able to take advantage of its impact on the price of gold the fact that gold is effective pr

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Publication Date
Mon Jun 15 2020
Journal Name
Al-academy
The effectiveness of the constructivist learning model in acquiring the Institute of Fine Arts' students of artistic analysis skills: اخلاص عبد القادر طاهر
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The constructivist learning model is one of the models of constructivist theory in learning, as it generally emphasizes the active role of the learner during learning, in addition to that the intellectual and actual participation in the various activities to help students gain the skills of analyzing artistic works. The current research aims to know the effectiveness of the constructivist learning model in the acquisition of the skills of the Institute of Fine Arts for the skills of (technical work analysis). To achieve the goal, the researcher formulated the following hypothesis: There are no statistically significant differences between the average scores of the experimental group students in the skill test for analyzing artworks befor

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Publication Date
Wed Dec 28 2022
Journal Name
Journal Of Chemical Technology And Metallurgy
THERMODYNAMIC ANALYSIS OF MOISTURE ADSORPTION ISOTHERM FOR MEFENAMIC ACID TABLETS
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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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Publication Date
Thu Mar 01 2012
Journal Name
Al-khwarzmi Engineering Journal
Dynamic response analysis for the parabolic trough of solar collector
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parabolic trough