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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
Sat Nov 02 2013
Journal Name
International Journal Of Computer Applications
Mixed Transforms Generated by Tensor Product and Applied in Data Processing
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Finding orthogonal matrices in different sizes is very complex and important because it can be used in different applications like image processing and communications (eg CDMA and OFDM). In this paper we introduce a new method to find orthogonal matrices by using tensor products between two or more orthogonal matrices of real and imaginary numbers with applying it in images and communication signals processing. The output matrices will be orthogonal matrices too and the processing by our new method is very easy compared to other classical methods those use basic proofs. The results are normal and acceptable in communication signals and images but it needs more research works.

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Publication Date
Mon Apr 04 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effect of Multiple Intelligences on the Acquisition of Science Operations by Middle School Students of Arabic Grammar
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The current research aims to identify the multiple intelligences in the fourth students’ acquisition of the literary processes of Arabic grammar and to identify the differences in multiple intelligence according to gender (males - females). The study was determined for students of the fourth literary preparatory Al-Hakim Preparatory (for males) and Rabat Preparatory (for females) of the Second Karkh Education Directorate, topics from the Arabic grammar subject (past tense, present tense, imperative, subject, and object) for the first semester of the academic year 2019-2020. The results showed that there were no statistically significant differences at the significance level (0.05) between the average scores of the students who were tau

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Publication Date
Tue Nov 01 2016
Journal Name
International Journal Of Pharmaceutical Sciences Review And Research
A study on some variables affecting the preparation of ethyl cellulose based floating microspheres of lafutidine
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Lafutidine (LAF) a newly developed histamine H2-receptor antagonist with absorption window makes it a good candidate to be prepared as floating drug delivery system. The current study involves formulation and in- Vitro evaluation of lafutidine as floating microspheres. Different formulation variables that affect the physicochemical properties of the prepared microspheres besides to the drug release behavior were investigated. Fourteen formulas were prepared by emulsion (o/w) solvent evaporation method using Ethyl cellulose (EC) as the polymeric matrix and tween 80 (TW80) as an emulsifying agent. The prepared formulas were evaluated for their percentage buoyancy (%), Percentage yield (%) and Entrapment efficiency (EE %). The results obt

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Publication Date
Tue Feb 26 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Use the Style of the Activity Based Cost time Drivine (TDABC) and its Impact on the Untapped Resources: Empirical study in the General Company for Textile Industries - Wasit
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   The research aims to identify the importance of using the style of the cost on the basis of activity -oriented in time TDABC and its role in determining the cost of products more equitably and thus its impact on the policy of allocation of resources through the reverse of the changes that occur on an ongoing basis in the specification of the products and thus the change in the nature and type of operations . The research was conducted at the General Company for Textile Industries Wasit / knitting socks factory was based on research into the hypothesis main of that ( possible to calculate the cost of activities that cause the production through the time it takes to run these activities can then be re- distributed product cost

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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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Publication Date
Fri Oct 02 2020
Journal Name
International Journal Of Pharmaceutical Research
A turbidimetric method for the quantitative determination of cyproheptadine hydrochloride in tablets using an optoelectronic detector based on the LEDs array
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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
An algorithm for binary codebook design based on the average bitmap replacement error (ABPRE)
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In this paper, an algorithm for binary codebook design has been used in vector quantization technique, which is used to improve the acceptability of the absolute moment block truncation coding (AMBTC) method. Vector quantization (VQ) method is used to compress the bitmap (the output proposed from the first method (AMBTC)). In this paper, the binary codebook can be engender for many images depending on randomly chosen to the code vectors from a set of binary images vectors, and this codebook is then used to compress all bitmaps of these images. The chosen of the bitmap of image in order to compress it by using this codebook based on the criterion of the average bitmap replacement error (ABPRE). This paper is suitable to reduce bit rates

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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
Evaluation of the Accuracy of Digital Elevation Model Produced from Different Open Source Data
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This study aims to estimate the accuracy of digital elevation models (DEM) which are created with exploitation of open source Google Earth data and comparing with the widely available DEM datasets, Shuttle Radar Topography Mission (SRTM), version 3, and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. The GPS technique is used in this study to produce digital elevation raster with a high level of accuracy, as reference raster, compared to the DEM datasets. Baghdad University, Al Jadriya campus, is selected as a study area. Besides, 151 reference points were created within the study area to evaluate the results based on the values of RMS.Furthermore, th

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Determination of Optimal Time-Average Wind Speed Data in the Southern Part of Malaysia
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Mersing is one of the places that have the potential for wind power development in Malaysia. Researchers often suggest it as an ideal place for generating electricity from wind power. However, before a location is chosen, several factors need to be considered. By analyzing the location ahead of time, resource waste can be avoided and maximum profitability to various parties can be realized. For this study, the focus is to identify the distribution of the wind speed of Mersing and to determine the optimal average of wind speed. This study is critical because the wind speed data for any region has its distribution. It changes daily and by season. Moreover, no determination has been made regarding selecting the average wind speed used for w

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Data And Network Science
The effects of big data, artificial intelligence, and business intelligence on e-learning and business performance: Evidence from Jordanian telecommunication firms
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This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big

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