COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in order to select the best features that affect the prediction of the proposed model. These are the Recursive Feature Elimination (RFE) as wrapper feature selection and the Extra Tree Classifier (ETC) as embedded feature selection. Two classification methods are applied for classifying the features vectors which include the Naïve Bayesian method and Restricted Boltzmann Machine (RBM) method. The results were 56.181%, 97.906% respectively when classifying all features and 66.329%, 99.924% respectively when classifying the best ten features using features selection techniques.
This paper presents a point multiplication processor over the binary field GF (2233) with internal registers integrated within the point-addition architecture to enhance the Performance Index (PI) of scalar multiplication. The proposed design uses one of two types of finite field multipliers, either the Montgomery multiplier or the interleaved multiplier supported by the additional layer of internal registers. Lopez Dahab coordinates are used for the computation of point multiplication on Koblitz Curve (K-233bit). In contrast, the metric used for comparison of the implementations of the design on different types of FPGA platforms is the Performance Index.
The first approach attains a performance index
... Show MoreThe removal of fluoride ions from aqueous solution onto algal biomass as biosorbent in batch and continuous fluidized bed systems was studied. Batch system was used to study the effects of process parameters such as, pH (2-3.5), influent fluoride ions concentration (10- 50 mg/l), algal biomass dose (0–1.5 g/ 200 ml solution), to determine the best operating conditions. These conditions were pH=2.5, influent fluoride ions concentration= 10 mg/l, and algal biomass dose=3.5 mg/l. While, in continuous fluidized bed system, different operating conditions were used; flow rate (0.667- 0.800 l/min), bed depth (8-15 cm) corresponded to bed weight of (80- 150 g). The results show that the breakthrough time increases with the inc
... Show MoreThis research investigates the adsorption isotherm and adsorption kinetics of nitrogen from air using packed bed of Li-LSX zeolite to get medical oxygen. Experiments were carried out to estimate the produced oxygen purity under different operating conditions: input pressure of 0.5 – 2.5 bar, feed flow rate of air of 2 – 10 L.min-1 and packing height of 9-16 cm. The adsorption isotherm was studied at the best conditions of input pressure of 2.5 bar, the height of packing 16 cm, and flow rate 6 Lmin-1 at ambient temperature, at these conditions the highest purity of oxygen by this system 73.15 vol % of outlet gas was produced. Langmuir isotherm was the best models representing the experimental data., and the m
... Show MorePoverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distanc
... Show MoreMetronidazole-MIPs were prepared by using (MDZ) as the template as well as allylchloride (AYC) or allylbromide (AYB) as monomer, used (TMPTA) tri-methylol propane tri-acrylate or ethylene glycol di-methyl acrylate (EGDMA) as cross-linker and initiator used (BP) benzyl peroxide. By using different plasticizers (di butyl Phthalate (DBPH), Nitrobenzene (NB), oleic acid (OA) and paraffin) for MDZ-MIP1 and (Di-butyl sebecate (DBS), Di-methyl acrylate (DMA), Tributylphosphate(TBP) and Tris(ethylhexyl phosphate (TEHP) ) for MDZ-MIP2. Membranes of MIPs were prepared in PVC matrix. The characterizations of each electrode were determined The Slope range from (55.083 - 43.711) mV/decade, Limit of Detection (8 X 10 -4- 2 X 10-6) and Linearity
... Show MoreThis study aimed at evaluating the torsional capacity of reinforced concrete (RC) beams externally wrapped with fiber reinforced polymer (FRP) materials. An analytical model was described and used as a new computational procedure based on the softened truss model (STM) to predict the torsional behavior of RC beams strengthened with FRP. The proposed analytical model was validated with the existing experimental data for rectangular sections strengthened with FRP materials and considering torque-twist relationship and crack pattern at failure. The confined concrete behavior, in the case of FRP wrapping, was considered in the constitutive laws of concrete in the model. Then, an efficient algorithm was developed in MATLAB environment t
... Show More