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Preparing the Electrical Signal Data of the Heart by Performing Segmentation Based on the Neural Network U-Net
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Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files that are read and then processed by removing empty data and unifying the width of the signal at a length of 250 in order to remove noise accurately, and then performing the process of identifying the QRS in the first place and P-T implicitly, and then the task stage is determining the required peak and making a cut based on it. The U-Net pre-trained model is used for deep learning. It takes an ECG signal with a customisable sampling rate as input and generates a list of the beginning and ending points of P and T waves, as well as QRS complexes, as output. The distinguishing features of our segmentation method are its high speed, minimal parameter requirements, and strong generalization capabilities, which are used to create data that can be used in diagnosing diseases or biometric systems.

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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Study the Effect of Manganese Ion Doping on the Size- Strain of SnO2 nanoparticles Using X-Ray Diffraction Data
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In this study, SnO2 nanoparticles were prepared from cost-low tin chloride (SnCl2.2H2O) and ethanol by adding ammonia solution by the sol-gel method, which is one of the lowest-cost and simplest techniques. The SnO2 nanoparticles were dried in a drying oven at a temperature of 70°C for 7 hours. After that, it burned in an oven at a temperature of 200°C for 24 hours. The structure, material, morphological, and optical properties of the synthesized SnO2 in nanoparticle sizes are studied utilizing X-ray diffraction. The Scherrer expression was used to compute nanoparticle sizes according to X-ray diffraction, and the results needed to be scrutinized more closely. The micro-strain indicates the broadening of diffraction peaks for nano

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Publication Date
Sun Mar 31 2024
Journal Name
Techhub Journal
The effect of increasing the intensity of specialized endurance training on runners' ability in the advanced 1500-meter run in terms of vital capacity indicators (V.C.) and heart rate (S.V.)
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The 1500m race event is part of the athletics system, and the continuous competition to break records and achieve the highest levels of achievement in athletics events, especially the 1500m race event, is one of the topics that occupies the minds of many people interested in achieving digital development for this event, given the distance of the race and the time it takes to complete it. Because it is unique from other events, it has characteristics that distinguish it from other events, despite it being a middle-distance event, which shares with them that its speed is measured by the step, which consists of the length of the step and its frequency. Increasing any of these two factors while keeping one of them constant or increasing

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Publication Date
Fri Dec 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Experimental investigation and modelling of residual stresses in face milling of Al-6061-T3 using neural network
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Milling process is a common machining operation that is used in the manufacturing of complex surfaces. Machining-induced residual stresses (RS) have a great impact on the performance of machined components and the surface quality in face milling operations with parameter cutting. The properties of engineering material as well as structural components, specifically fatigue life, deformation, impact resistance, corrosion resistance, and brittle fracture, can all be significantly influenced by residual stresses. Accordingly, controlling the distribution of residual stresses is indeed important to protect the piece and avoid failure. Most of the previous works inspected the material properties, tool parameters, or cutting parameters, bu

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
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The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

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Publication Date
Fri Apr 30 2021
Journal Name
Eastern-european Journal Of Enterprise Technologies
Implementation of artificial neural network to achieve speed control and power saving of a belt conveyor system
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According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through

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Publication Date
Tue Jun 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Comparison of the RLS and LMS Algorithms to Remove Power Line Interference Noise from ECG Signal
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    Biomedical signal such as ECG is extremely important in the diagnosis of patients and is commonly recorded with a noise. Many different kinds of noise exist in biomedical environment such as Power Line Interference Noise (PLIN). Adaptive filtering is selected to contend with these defects, the adaptive filters can adjust the filter coefficient with the given filter order. The objectives of this paper are: first an application of the Least Mean Square (LMS) algorithm, Second is an application of the Recursive Least Square (RLS) algorithm to remove the PLIN. The LMS and RLS algorithms of the adaptive filter were proposed to adapt the filter order and the filter coefficients simultaneously, the performance of existing LMS

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Engineering
Impact of Preparing HMA with Modified Asphalt Cement on Moisture and Temperature Susceptibility
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Many researchers tried to prevent or reduce moisture damage and its sensitivity to temperature to improving the performance of hot mix asphalt because it is decreasing the functional and structural life of fixable pavement due to the moisture damage had exposed to it.

The main objective of this study is to inspect the effect of (fly ash “3%, 6%, 12%”, hydrated lime”5%, 10%, 20%” and silica fumes”1%, 2%, 4%) referring to previous research by the net weight asphalt cement as a modified material on the moisture and temperature sensitivity of hot mix asphalt. This was done using asphalt from AL-Nasiria refinery with penetration grade 40-50, nominal maximum size (12.5) mm (surface course) of aggregate and on

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Publication Date
Wed Dec 30 2009
Journal Name
Iraqi Journal Of Physics
Study the Effect of annealing temperature on the Structure of a-Se and Electrical Properties of a-Se/c-Si Heterojunction
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In this work Study effect of annealing temperature on the Structure
of a-Se and electrical properties of a-Se/c-Si hetrojunction have been
studied.The hetrojunction fabricated by deposition of a-Se film on c-
Si using thermal evaporation.
Electrical properties of a-Se/ c-Si heterojunction include I-V
characteristics, in dark at different annealing temperature and C-V
characteristics are considered in the present work.
C-V characteristics suggested that the fabricated diode was
abrupt type, built in potential determined by extrapolation from
1/C2-V curve. The built - in potential (Vbi) for the Se/ Si System
was found to be increase from 1.21 to 1.62eV with increasing of
annealing temperature

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Publication Date
Thu Jan 04 2018
Journal Name
International Journal Of Science And Research (ijsr)
Effect of Doping on Properties of the Hall Effect and Electrical Conductivity for AgInTe2 Thin Films
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The effect of different doping ratio (0.3, 0.5, and 0.7) with thickness in the range 300nmand annealed at different temp.(Ta=RT, 473, 573, 673) K on the electrical conductivity and hall effect measurements of AgInTe2thin film have and been investigated AgAlxIn(1-x) Te2 (AAIT) at RT, using thermal evaporation technique all the films were prepared on glass substrates from the alloy of the compound. Electrical conductivity (σ), the activation energies (Ea1, Ea2), Hall mobility and the carrier concentration are investigated as a function of doping. All films consist of two types of transport mechanisms for free carriers. The activation energy (Ea) decreased whereas electrical conductivity increases with increased doping. Results of Hall Effect

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Publication Date
Wed Mar 08 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Effect of Temperature and Nickel Concentration on the Electrical and Dielectric Properties of Polyethylene-Nickel Composites
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The effect of temperature range from 298 K to 348 K and volume filler content ф on electrical properties of polyethylene PE filled with nickel Ni powders has been investigated. The volume electrical resistivity V  of such composites decreases suddenly by several orders of magnitude at a critical volume concentration (i.e. фc=14.27 Vol.%) ,whereas the dielectric constant   and the A.C electrical conductivity AC  of such composites increase suddenly at a critical volume concentration (i.e. фc=14.27 Vol.%).For volume filler content lower than percolation threshold ф<фc the resistivity decreases with increasing temperature, whereas the dielectric constant and the A.C electrical conductivity of

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