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The Role of Artificial Intelligence in Diagnosing Heart Disease in Humans: A Review
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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.

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Publication Date
Wed Dec 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Improvement of Surface Roughness Quality for Stainless Steel 420 Plate Using Magnetic Abrasive Finishing Method
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     An experimental study was carried out to improve the surface roughness quality of the stainless steel 420 using magnetic abrasive finishing method (MAF). Four independent operation parameters were studied (working gap, coil current, feed rate, and table stroke), and their effects on the MAF process were introduced. A rotating coil electromagnet was designed and implemented to use with plane surfaces. The magnetic abrasive powder used was formed from 33%Fe and 67% Quartz of (250µm mesh size). The lubricant type SAE 20W was used as a binder for the powder contents. Taguchi method was used for designing the experiments and the optimal values of the selected parameters were found. An empirical equation representing the r

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Publication Date
Tue Jan 19 2021
Journal Name
Archives Of Civil And Mechanical Engineering
Push-out test of steel–concrete–steel composite sections with various core materials: behavioural study
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Steel–concrete–steel (SCS) structural systems have economic and structural advantages over traditional reinforced concrete; thus, they have been widely used. The performance of concrete made from recycled rubber aggregate from scrap tires has been evaluated since the early 1990s. The use of rubberized concrete in structural construction remains necessary because of its high impact resistance, increases ductility, and produces a lightweight concrete; therefore, it adds such important properties to SCS members. In this research, the use of different concrete core materials in SCS was examined. Twelve SCS specimens were subjected to push-out monotonic loading for inspecting their mechanical performance. One specimen was constructed from co

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Synthesis and Characterization of Magnetic Iron Oxide Nanoparticles by Co-Precipitation Method at Different Conditions
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Magnetic nanoparticles (MNPs) of iron oxide (Fe3O4) represent the most promising materials in many applications. MNPs have been synthesized by co-precipitation of ferric and ferrous ions in alkaline solution. Two methods of synthesis were conducted with different parameters, such as temperature (25 and 80 ̊C), adding a base to the reactants and the opposite process, and using nitrogen as an inert gas. The product of the first method (MNPs-1) and the second method (MNPs-2) were characterized by x-ray diffractometer (XRD), Zeta Potential, atomic force microscope (AFM) and scanning electron microscope (SEM). AFM results showed convergent particle size of (MNPs-1) and (MNPs-2) with (86.01) and (74.14)

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Publication Date
Sun Mar 01 2015
Journal Name
Sust Journal Of Engineering And Computer Science (jecs)
Virtual failure influence of Roseires dam on Khartoum city using HEC-RAS Hydraulic simulation modeling
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Dam break is series phenomenon that can result in fatal consequences and loss of properties. Unfortunately, the observed consequences can only be available after the dam breaks. Therefore, it is important to anticipate what will happen prior to dam break to issue suitable warning and locate the possible risk areas. This study attempts to simulate the case of dam break in Blue Nile at Roseires dam and see its consequences downstream. Roseires dam lies at a distance of 630 km south of Khartoum, Sennar dam lies at about 260 km downstream of Roseires dam. In this study hydraulic model is developed based of Hydraulic Engineering Centre (HEC), River Analysis System (RAS), and HEC- RAS. The HEC-RAS based model is calibrated and validated usi

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Effect of Green-biosynthesis Aluminum Nanoparticles (Al NPs) on Salmonella enterica Isolated from Baghdad City
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This study is aimed to Green-synthesize and characterize Al NPs from Clove (Syzygium aromaticum
L.) buds plant extract and to investigate their effect on isolated and characterized Salmonella enterica growth.
S. aromaticum buds aqueous extract was prepared from local market clove, then mixed with Aluminum nitrate
Al(NO3)3. 9 H2O, 99.9% in ¼ ratio for green-synthesizing of Al NPs. Color change was a primary confirmation
of Al NPs biosynthesis. The biosynthesized nanoparticles were identified and characterized by AFM, SEM,
EDX and UV–Visible spectrophotometer. AFM data recorded 122nm particles size and the surface roughness
RMs) of the pure S. aromaticum buds aqueous extract recorded 17.5nm particles s

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Publication Date
Thu Dec 11 2025
Journal Name
Medical Forum Monthly
Diagnosis and Effectiveness of Calcium Peroxide Nanoparticles Prepared from Capsicum  Plant Extract against Colon Cancer
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Objective: To diagnose the function of natural biomolecules in the biological reduction of metal salts during nanoparticle synthesis.Study Design: Experimental studyPlace and Duration of Study: This study was conducted at the College of Education for Pure Sciences/Ibn Al- Haitham at the University of Baghdad from 1st January 2024 to 31st March 2025. Methods: Capsicum plant extract was used and treated with a readily available inorganic salt (CaSO4 2H2O). It was used as a basic material to obtain particles.Results: Calcium peroxide nanoparticles in the form of a yellowish-white powder were confirmed by using, UV, XRD, SEM, TEM, AFM, and EDX, confirmed that the compound is calcium peroxide nanoparticles with an average nano size of 31

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Publication Date
Wed Oct 01 2025
Journal Name
Civil Engineering Journal
Performance Evaluation of Composite CNT/PE-Modified Asphalt Concrete at Binder, Mixture, and Pavement Levels
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Advancing the multi-scale performance of asphalt pavements requires innovative binder modifications that address limitations in rutting resistance, fatigue resistance, and durability across the binder, mixture, and structural levels. This study evaluates the performance of asphalt cement, mixtures, and pavement systems modified with a combination of polyethylene (PE) and carbon nanotubes (CNTs). The binder was modified using 4% PE and varying CNT contents (0.5%, 1%, 1.5%, and 2% by weight of the modified binder). Binder performance was assessed through conventional and rheological tests, including penetration, softening point, viscosity, performance grade (PG) evaluation, and master curve analysis. Mixture-level performance was eval

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Investigation of Load and Pressure Distribution on Wing with Wake Rollup for Low Speed Aircraft
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The presented work shows a preliminary analytic method for estimation of load and pressure distributions on low speed wings with flow separation and wake rollup phenomena’s. A higher order vortex panel method is coupled with the numerical lifting line theory by means of iterative procedure including models of separation and wake rollup. The computer programs are written in FORTRAN which are stable and efficient.

      The capability of the present method is investigated through a number of test cases with different types of wing sections (NACA 0012 and GA(W)-1) for different aspect ratios and angles of attack, the results include the lift and drag curves, lift and pressure distributions along the wing s

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Publication Date
Thu Jan 30 2020
Journal Name
Journal Of Engineering
Comparison of Single and Group Bored Piles Settlement Based on Field Test and Theoretical Methods
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 Bored piles settlement behavior under vertical loaded is the main factor that affects the design requirements of single or group of piles in soft soils. The estimation of bored pile settlement is a complicated problem because it depends upon many factors which may include ground conditions, validation of bored pile design method through testing and validation of theoretical or numerical prediction of the settlement value. In this study, a prototype single and bored pile group model of arrangement (1*1, 1*2 and 2*2) for total length to diameter ratios (L/D) is 13.33 and clear spacing three times of diameter, subjected to vertical axial loads. The bored piles model used for the test was 2000

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Using Adaptive Neuro Fuzzy Inference System to Predict Rate of Penetration from Dynamic Elastic Properties
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Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in

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