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.
Mobile-based human emotion recognition is very challenging subject, most of the approaches suggested and built in this field utilized various contexts that can be derived from the external sensors and the smartphone, but these approaches suffer from different obstacles and challenges. The proposed system integrated human speech signal and heart rate, in one system, to leverage the accuracy of the human emotion recognition. The proposed system is designed to recognize four human emotions; angry, happy, sad and normal. In this system, the smartphone is used to record user speech and send it to a server. The smartwatch, fixed on user wrist, is used to measure user heart rate while the user is speaking and send it, via Bluetooth,
... Show MoreObjective: To evaluate the therapeutic activity of probiotics mixture of Lactobacillus plantarum and Lactobacillus acidophilus towards Cryptosporidium infection in experimentally infected mice. Oocysts of Cryptosporidium were separated from the stool of humans to infect mice. Methods: Forty male albino mice were split equally into four groups, every group contained 10 mice, the group I (early treated group), were treated from the 1st day from infection to the 11th post-infection, group II (late treated group), were treated from the 4th day from infection to the 15th post-infection, and group (III) (untreated group), were mice considered as a positive control group. Results: It was showed that daily application of a mixture of L. plantarum w
... Show MoreThe research aims to identify the impact of the merger of the companies affiliated to the Ministry of Industry and Minerals on their financial profitability since the companies before the merger suffered a rise in losses and the deficit reached very high levels that affected its overall performance and even on the morale of workers as losses are increasing and solutions Efficiency is absent. The problem stems from knowing the impact of the merger on the profitability ratios of the companies. The research field was represented by the companies affiliated to the Ministry of Industry and Minerals (21) companies, while the research sample reached (6) companies after the merger (14) companies before the merger, was based on data The f
... Show MoreThe launch of the EU’s Eastern Partnership in 2009 intended to signal a new, elevated level of EU engagement with its Eastern neighborhood. Yet there remain several long-simmering and potentially destabilizing conflicts in the region, with which EU engagement thus far has been sporadic at best. The Union’s use of its Common Security and Defense Policy (CSDP) in the region and to help solve these disputes has been particularly ad hoc and inconsistent, wracked by inter-institutional incoherence and undermined by Member States’ inability to agree on a broad strategic vision for engagement with the area.
The three CSDP missions deployed to the region thus far have all suffered from this incoherence to various extents. In particu
... Show MoreBackground: Chronic kidney disease is a worldwide health problem, with adverse outcomes of cardiovascular disease and premature death, can be divided into five stages, depending on how severe the damage is to the kidneys, or the level of decrease in kidney function, the final stage of chronic kidney disease is called end-stage renal disease, salivary immunoglobulin A is the main immunoglobulin found in mucous secretions, including tears, saliva, colostrum and secretions from the genitourinary tract gastrointestinal tract, prostate and respiratory epithelium . It is also found in small amounts in blood.This study aimedto measuresalivary flow rate and salivaryimmunoglobulin Alevels in chronic kidney disease patients on hemodialysis treatment
... Show MoreIn the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably
Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp
... Show MoreThe research seeks to identify the correlation relationship between strategic intelligence and fifth preparatory students’ achievement in mathematics. To achieve this objective, stratified random sampling were used based on participants’ gender and the branch of study. The sample consisted of (200) male and female fifth preparatory students for both (literary and scientific branch) who were displaced to Arbil city in Iraq for the academic year 2016-2017. As for research tool, the researcher administered strategic intelligence test to the study sample in the second semester which was designed by Ibrahim (2017), it includes (30) items divided into five domains (predictability, organized thinking, future view, motivation, and pa
... Show Moreدور التدقيق الاستراتيجي لإدارة الموارد البشرية في بلورة القدرات التنظيمية دراسة استطلاعية في رئاسة جامعة بغداد