Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breathing difficulty) used to diagnose the person being infected by COVID-19 virus or not. Secondly, this approach divides the infected peoples into four classes, based on their immune system risk level (very high degree, high degree, mild degree, and normal), and using two indices of age and current health status like diabetes, heart disorders, or hypertension. Where, these people are graded and expected to comply with their class regulations. There are six important COVID-19 virus infections of different classes that should receive immediate health care to save their lives. When the test is positive, the patient age is considered to choose one of the six classifications depending on the patient symptoms to provide him the suitable care as one of the four types of suggested treatment protocol of COVID-19 virus infection in COVID-19 DSS application. Finally, a report of all information about any classification case of COVID-19 infection is printed where this report includes the status of patient (infection level) and the prevention protocol. Later, the program sends the report to the control centre (medical expert) containing the information. In this paper, it was suggested the use of C4.5 Algorithm for decision tree.
An experiment during the two seasons 2019, 2020. The experiment conducted according to Split Plot Design by two factors; the first was addition Nano NPK with five levels (control, addition 7.5 g.plant-1, addition 15 g.plant-1, spray 1 g.L-1, spray 2 g.L-1). The second factor was four levels of Mineral NPK which were (control, 50 g.plant-1, 100 g.plant-1, 50 g.plant-1+1.5 g.L-1) respectively. N3 (spray 1 g.L-1 ) increased plant height, stem diameter first season, branch number se
The importance of this research lies in developing a psychological expenditure scale and its relationship to the passing skills of specialized volleyball players. The research problem focused on psychological expenditure as one of the problems and challenges faced by specialized players and its negative impact, such as poor skill performance, which is reflected in the performance of the player and the team. This weakens the player's self-confidence and concentration and affects the team's performance in tournaments as well as their performance in training. The research aims to develop a psychological expenditure scale, and the researcher used the descriptive approach as it is appropriate for the nature of the research problem. The f
... Show MorePolycrystalline ingots of cadmium telluride have been synthesized using the direct
reaction technique, by fusing initial component consisting from pure elements in
stoichiometric ratio inside quartz ampoule is evacuated 10-6 torr cadmium telluride has
been grown under temperature at (1070) oC for (16) hr. was used in this study, the phases
observed in growing CdTe compound depend on the temperature used during the growth
process. Crystallography studies to CdTe compound was determined by X-ray diffraction
technique, which it has zinc blend structure and cubic unit cell, which lattice constants is
a=6.478
oA
In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method
Experimental study of heat transfer coefficients in air-liquid-solid fluidized beds were carried out by measuring the heat rate and the overall temperature differences across the heater at different operating conditions. The experiments were carried out in Q.V.F. glass column of 0.22 m inside diameter and 2.25 m height with an axially mounted cylindrical heater of 0.0367 m diameter and 0.5 m height. The fluidizing media were water as a continuous phase and air as a dispersed phase. Low density (Ploymethyl-methacrylate, 3.17 mm size) and high density (Glass beads, 2.31 mm size) particles were used as solid phase. The bed temperature profiles were measured axially and radially in the bed for different positions. Thermocouples were connecte
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