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.
The influence of silver doped n-type polycrystalline CdTe film with thickness of 200 nm and rate deposition of 0.3 nm.s -1 prepared under high vacuum using thermal co-evaporation technique on its some structural and electrical properties was reported. The X- ray analysis showed that all samples are polycrystalline and have the cubic zinc blend structure with preferential orientation in the [111] direction. Films doping with impurity percentages (2, 3, and 4) %Ag lead to a significant increase in the carrier concentration, so it is found to change from 23.493 108 cm -3 to 59.297 108 cm -3 for pure and doped CdTe thin films with 4%Ag respectively. But films doping with impurity percentages above lead to a significant decrease in the electrica
... Show MoreThe study aimed to analyze the effect of meteorological factors (rainfall rate and temperature) on the change in land use in the marshes of the Al‐Majar Al‐Kabir region in southern Iraq. Satellite images from Landsat 7 for 2012 and Landsat 8 for 2022 were used to monitor changes in the land coverings, the images taken from the Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) sensors of the Landsat satellite. Geometric correction was used to convert images into a format with precise geographic coordinates using ArcMap 10.5. The maximum likelihood classification method was used to examine satellite image data using a supervised approach, and the data were analyzed statistically. We obtained clear images of the area,
... Show MoreThe paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme
... Show MoreIn this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal
... Show MoreIn this paper, we used two monomers, 3,3',4,4'-benzophenone tetracarboxylic dianhydride (BTDA) and m,m'-diaminobenzophenone (m, m’-DABP), to produce polyamide acid and then converted it to polyimide (PI). The effects of phosphoric acid (H3PO4) molarity (1, 2, and 3 M) on the structural, thermal, mechanical, and electrical characteristics of the polyimides/polyaniline (PI/PANI) nanocomposites were studied. Two sharp reflection peaks were developed by the addition of PANI to PI. When 3 M H3PO4 is added, the crystalline sharp peak loses some of its intensity. The complex formation of PI/PANI-H3PO4 was confi
... Show MoreNano-structural of vanadium pentoxide (V2O5) thin films were
deposited by chemical spray pyrolysis technique (CSPT). Nd and Ce
doped vanadium oxide films were prepared, adding Neodymium
chloride (NdCl3) and ceric sulfate (Ce(SO4)2) of 3% in separate
solution. These precursor solutions were used to deposit un-doped
V2O5 and doped with Nd and Ce films on the p-type Si (111) and
glass substrate at 250°C. The structural, optical and electrical
properties were investigated. The X-ray diffraction study revealed a
polycrystalline nature of the orthorhombic structure with the
preferred orientation of (010) with nano-grains. Atomic force
microscopy (AFM) was used to characterize the morphology of the
films. Un-do
In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe
... Show MoreIn recent years, the positioning applications of Internet-of-Things (IoT) based systems have grown increasingly popular, and are found to be useful in tracking the daily activities of children, the elderly and vehicle tracking. It can be argued that the data obtained from GPS based systems may contain error, hence taking these factors into account, the proposed method for this study is based on the application of IoT-based positioning and the replacement of using IoT instead of GPS. This cannot, however, be a reason for not using the GPS, and in order to enhance the reliability, a parallel combination of the modern system and traditional methods simultaneously can be applied. Although GPS signals can only be accessed in open spaces, GP
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