In recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne

Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m

Deep submicron technologies continue to develop according to Moore’s law allowing hundreds of processing elements and memory modules to be integrated on a single chip forming multi/many-processor systems-on-chip (MPSoCs). Network on chip (NoC) arose as an interconnection for this large number of processing modules. However, the aggressive scaling of transistors makes NoC more vulnerable to both permanent and transient faults. Permanent faults persistently affect the circuit functionality from the time of their occurrence. The router represents the heart of the NoC. Thus, this research focuses on tolerating permanent faults in the router’s input buffer component, particularly the virtual channel state fields. These fields track packets f

    This study aims to set up a 3D static model to characterize and evaluate Mishrif Formation which represents the main reservoir in Buzurgan Oilfield, southern Iraq. Six wells have been selected to set up structural, facies and petrophysical models of Mishrif reservoir by using Petrel Software. The structural model has been built based on the structural contour map of the top of Mishrif Formation, which derived from seismic interpretation, and by using different static algorithms in Petrel Software. The structural model showed that the Buzurgan Oilfield represents an anticlinal fold with two domes north and south separated by a depression. The petrophysical model included the porosity model and water saturation model. Th

     In this study, the effect of increasing pump pulse energy and delay time on the energy conversion efficiency of the Potassium Titanyl Phosphate (KTP) crystal at room temperature was investigated. It was found that the higher the pump pulse the greater the efficiency at a certain value of the delay time. Moreover, at the delay time 3.524ns, we found that the efficiency of the conversion of energy increases from 0.0112 to 0.0159. We  also observed that the lower delay time between the pump and the probe pulses leads to increase the rate of energy conversion efficiency of the KTP crystal, where the reaches up to 3, which is higher than the value recorded in the absence of a pump pulse. The highest value of the

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

     Getting knowledge from raw data has delivered beneficial information in several domains. The prevalent utilizing of social media produced extraordinary quantities of social information. Simply, social media delivers an available podium for employers for sharing information. Data Mining has ability to present applicable designs that can be useful for employers, commercial, and customers. Data of social media are strident, massive, formless, and dynamic in the natural case, so modern encounters grow. Investigation methods of data mining utilized via social networks is the purpose of the study, accepting investigation plans on the basis of criteria, and by selecting a number of papers to serve as the foundation for this arti

     In this model, we use the C++ programming language to develop a program that calculates the atmospheric earth model from the surface to 250 kilometers. The balance forces theory is used to derive the pressure equation. The hydrostatic equation is utilized to calculate these parameters analytically. Variations of the parameters with altitude (density, pressure, temperature, and molecular weight) are investigated intensively. The equations for gravitational acceleration, sound speed, and scale height are also obtained. This model is used to investigate the effects of the earth's atmosphere on the space shuttle and the moving bodies inside it.

Undesirable growth of potato (Solanum tuberosum L.) crop under an excessive N fertilizer application is the main obstacle presently. This research was conducted to investigate the response of different potato cultivars; Russet Burbank, Shepody, and Superior, and its qualitative characteristics under a series of N rates. Six rates of N fertilization (0–280 kg ha−1) were applied on 11 sites in a randomized complete block design, with four replications. Sites with ≥30 g kg−1 of soil organic matter (OM) produced total tuber yield, marketable yield, and tuber weight per plant 39.5, 45.2, and 54.9%, respectively, higher than sites with ≤30 g kg−1 of OM. Tubers specific gravity increased by 0.18% in the sites with ≥30 g kg−1 of OM.

Dell Hymesin 1964coined The Ethnography of Communication in an attempt to explain the ways in which people use the language to interact. It hypothesizes that ethnography is less applicable among participants who have the same sociocultural background. It was proven that all the basic speech components occur whenever there is an interactional situation. The elements of (SPEAKING) schema are closely connected. However, the findings establish the fact that these elements take place effectively among participants who have the same sociocultural background.One of the most outstanding conclusions is the capability of the (SPEAKING) model to analyze not only an interaction between two or more participants, but also any event which consists of a mo