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 ad

In this study, pebble bed as an absorber and storage material was placed in a south facing, flat plate air-type solar collector at fixed tilt angle of (45°). The effect of this material and differ- ent parameters on collector efficiency has been investigated experimentally and
theoretically. Two operation modes were employed to study the performance of the solar air heater. An inte- grated mode of continuous operation of the system during the period of (11:00 am – 3:00 pm) and non-integrated mode in which the system stored the solar energy through the day then used the stored energy during the period of (3:00 pm – 8:00 pm). The results of parametric study in case of continuous operating showed that the maximum average temperatur

Tight reservoirs have attracted the interest of the oil industry in recent years according to its significant impact on the global oil product. Several challenges are present when producing from these reservoirs due to its low to extra low permeability and very narrow pore throat radius. Development strategy selection for these reservoirs such as horizontal well placement, hydraulic fracture design, well completion, and smart production program, wellbore stability all need accurate characterizations of geomechanical parameters for these reservoirs. Geomechanical properties, including uniaxial compressive strength (UCS), static Young’s modulus (Es), and Poisson’s ratio (υs), were measured experimentally using both static and dynamic met

The idea of ​​carrying out research on incomplete data came from the circumstances of our dear country and the horrors of war, which resulted in the missing of many important data and in all aspects of economic, natural, health, scientific life, etc.,. The reasons for the missing are different, including what is outside the will of the concerned or be the will of the concerned, which is planned for that because of the cost or risk or because of the lack of possibilities for inspection. The missing data in this study were processed using Principal Component  Analysis and self-organizing map methods using simulation. The variables of child health and variables affecting children's health were taken into account: breastfeed

The objective of this study is to analyze the difficulties faced by intermediate-level Iraqi students in the use of Spanish unstressed pronouns as a foreign language (ELE). Through a mixed methodology, a descriptive and explanatory analysis was conducted based on written and oral productions of B1-level students at the University of Baghdad.The results show that factors such as interference from the native language (Arabic) and English, as well as grammatical differences between Spanish and Arabic, generate difficulties in the correct use of unstressed pronouns. A contrastive teaching approach is proposed that takes advantage of students' cognitive abilities to highlight similarities and differences between both languages.This stu

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

This paper presents theoretical parametric study of the curvature ductility capacity for reinforced concrete column sections. The study considers the behavior of concrete and reinforcing steel under different strain rates. A computer program has been written to compute the curvature ductility taking into account the spalling in concrete cover. Strain rate sensitive constitutive models of steel and concrete were used for predicting the moment-curvature relationship of reinforced concrete columns at different rate of straining. The study parameters are the yield strength of main reinforcement, yield strength of transverse reinforcement, compressive strength of concrete, spacing of ties and the axial load. The results indicated that hi