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Deep Learning and Its Role in Diagnosing Heart Diseases Based on Electrocardiography (ECG)
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Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was adopted, which is considered a challenge for researchers because it includes different age groups. Many diseases, and the results obtained by the system were 96% accurate.

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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning
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In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning
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In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

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Publication Date
Mon Apr 27 2026
Journal Name
Applied Fruit Science
Predicting Bitter Orange (Citrus aurantium L.) Maturity by Machine Learning Based on Picking Force in Smart Picker
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Manual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that

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Publication Date
Thu May 05 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Classification SINGLE-LEAD ECG by using conventional neural network algorithm
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Publication Date
Tue Mar 01 2011
Journal Name
Al-khwarizmi Engineering Journal
Noise Removal of ECG Signal Using Recursive Least Square Algorithms
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This paper shows an approach for Electromyography (ECG) signal processing based on linear and nonlinear adaptive filtering using Recursive Least Square (RLS) algorithm to remove two kinds of noise that affected the ECG signal. These are the High Frequency Noise (HFN) and Low Frequency Noise (LFN). Simulation is performed in Matlab. The ECG, HFN and LFN signals used in this study were downloaded from ftp://ftp.ieee.org/uploads/press/rangayyan/, and then the filtering process was obtained by using adaptive finite impulse response (FIR) that illustrated better results than infinite impulse response (IIR) filters did.

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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
The role of strategic management accounting and its impact on the competitive advantage in Jordanian industrial companies
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This study aimed to recognize and understand the concept of strategic management accounting (SMA) and how it's the effect on the competitive advantage for industrial companies in Jordan. The study's importance arises due to the lack of Arab studies that dealt with this topic, in addition to the important and vital role of strategic management accounting on companies that represent the artery of the decision-making process, and to identify the benefits associated with SMA technology. The necessary data were collected through the literature review and theoretical study of the references that relevant to the study subject, in addition to a questionnaire developed for this purpose, the study used (124) out of (250) questionnaires tha

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Rock facies classification and its effect on the estimation of original oil in place based on petrophysical properties data
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The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri

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Publication Date
Fri Jul 30 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and Machine learning algorithm
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The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi

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Publication Date
Mon Sep 30 2024
Journal Name
مجلة نسق
Social media and its role in reinforcing educational values in Iraqi Society
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This day, we see the Significant role that social media platforms play, it plays a vital role in shaping the Social, political, and economic awareness of individuals. The Iraqi Society, which is experiencing rapid cultural and social transformations, is considered a fertile ground for social media and its influences, whether negative or positive. Research and studies indicate that the negative use of social media will lead to weaking of the sense of belonging and citizenship among members of Iraqi society. This, in turn, threatens moral and educational values, increases feelings of family estrangement, and leads to social isolation. On the contrary, if social is used correctly, it can significantly contribute to enhancing educational values

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Environmental awareness in the curriculum and its role in sustainable environmental planning
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                The goal of current research to the definition of environmental awareness in the curriculum and its role in sustainable environmental planning, was the research community official regular educational schools (kindergarten, primary, secondary) for the province of Baghdad - Iraq, the sample consisted search of (100) teacher and a teacher, and what research was descriptive analytical, researchers have selected the right tool for the research procedures (closed) questionnaire, distributed to the research sample, has been used by researchers appropriate statistical methods for procedures including: the weighted average extraction unit paragraph,

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