The electrical activity of the heart and the electrocardiogram (ECG) signal are fundamentally related. In the study that has been published, the ECG signal has been examined and used for a number of applications. The monitoring of heart rate and the analysis of heart rhythm patterns, the detection and diagnosis of cardiac diseases, the identification of emotional states, and the use of biometric identification methods are a few examples of applications in the field. Several various phases may be involved in the analysis of electrocardiogram (ECG) data, depending on the type of study being done. Preprocessing, feature extraction, feature selection, feature modification, and classification are frequently included in these stages. Every stage must be finished in order for the analysis to go smoothly. Additionally, accurate success measures and the creation of an acceptable ECG signal database are prerequisites for the analysis of electrocardiogram (ECG) signals. Identification and diagnosis of various cardiac illnesses depend heavily on the ECG segmentation and feature extraction procedure. Electrocardiogram (ECG) signals are frequently obtained for a variety of purposes, including the diagnosis of cardiovascular conditions, the identification of arrhythmias, the provision of physiological feedback, the detection of sleep apnea, routine patient monitoring, the prediction of sudden cardiac arrest, and the creation of systems for identifying vital signs, emotional states, and physical activities. The ECG has been widely used for the diagnosis and prognosis of a variety of heart diseases. Currently, a range of cardiac diseases can be accurately identified by computerized automated reports, which can then generate an automated report. This academic paper aims to provide an overview of the most important problems associated with using deep learning and machine learning to diagnose diseases based on electrocardiography, as well as a review of research on these techniques and methods and a discussion of the major data sets used by researchers.
In a resource-limited world, there is an urgent need to develop new economic models, from the traditional unsustainable industrial model of product consumption and disposal, to a new model based on the concepts of sustainability in its comprehensive sense, the so-called circular economy, using fewer resources in manufacturing processes and changing practices in product disposal to waste, by removing its use, recycling and manufacturing to start another manufacturing process. In an era of intense competition in domestic and global markets, the importance of the circular economy is highlighted in its ability to strengthen the competitiveness of enterprises in those markets, by reducing the cost and increasing the quality of the pro
... Show MoreThe present study deals with the morphological and histological aspects of the forebrain(Cerebrum) in the Columba livia domestica (Gmelin, 1789) to identify the histoarchitecture of its layers. This bird' has a large head found as perpendicular to the longitudinal axis. The morphological results reveal that for brain (Cerebrum) pear shaped, its outer surface is smooth without folds or deep grooves. Cerebrum is made up of two regions, the Pallium and the Subpallium. The Cerebral cortex includes four layers of hyperpallium (Wulst) , Dorsolateral corticoid area (CDL), Hippocampus, Piriform cortex. The internal cortex of cerebrum consists of Dorsal Ventricle ridge which includes the mesopallium, nidopallium, and archospallium. All these reg
... Show MoreThis paper presents an analytical study for the magnetohydrodynamic (MHD) flow of a generalized Burgers’ fluid in an annular pipe. Closed from solutions for velocity is obtained by using finite Hankel transform and discrete Laplace transform of the sequential fractional derivatives. Finally, the figures are plotted to show the effects of different parameters on the velocity profile.
This research aims to knowledge the extent of the application of Tuz General Hospital to the concept of tacit knowledge dimensions (mental models, intuition, experience, skill) and methods of acquiring knowledge dimensions (training, job rotation, work teams) and the measurement and analysis of the link and the kind of impact between the methods of acquiring knowledge and tacit knowledge of the Angels nursing in the researched hospital, and was the questionnaire primary means of collecting information adopted by the researcher that, the research sample of (90) individuals, including the Angels nursing, has been using the statistical program spss for the purpose of conducting statistical treatments, and through the diagnosis and m
... Show More The TV has the ability to combine sound and picture, which makes it of a direct impact on the recipient as it is a rich communicative tool with various artistic forms that display through this small screen programs and films, so that the TV has become superior over many other means of communication.
This research is concerned with the technical and artistic ability in the production of programs owned by the TV as a means of attraction of educated children aged between 5-12 years old, which makes it an educational supplement for the school that helps them in providing knowledge, acquiring skills and being informed about the different sciences through educational programs. It is known that the child at this stage enjoys when wa
The present study aims to present a proposed realistic and comprehensive cyber strategy for the Communications Directorate for the next five years (2022-2026) based on the extent of application and documentation of cybersecurity measures in the Directorate and the scientific bases formulating the strategy. The present study is significant in that it provides an accurate diagnosis of the capabilities of the cyber directorate in terms of strengths and weaknesses in its internal environment and the opportunities and threats that surround it in the external environment, based on the results of the assessment of the reality of cybersecurity according to the global Cybersecurity index, which provides a strong basis for building its strategic dire
... Show MoreCommunity detection is useful for better understanding the structure of complex networks. It aids in the extraction of the required information from such networks and has a vital role in different fields that range from healthcare to regional geography, economics, human interactions, and mobility. The method for detecting the structure of communities involves the partitioning of complex networks into groups of nodes, with extensive connections within community and sparse connections with other communities. In the literature, two main measures, namely the Modularity (Q) and Normalized Mutual Information (NMI) have been used for evaluating the validation and quality of the detected community structures. Although many optimization algo
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