The consensus algorithm is the core mechanism of blockchain and is used to ensure data consistency among blockchain nodes. The PBFT consensus algorithm is widely used in alliance chains because it is resistant to Byzantine errors. However, the present PBFT (Practical Byzantine Fault Tolerance) still has issues with master node selection that is random and complicated communication. The IBFT consensus technique, which is enhanced, is proposed in this study and is based on node trust value and BLS (Boneh-Lynn-Shacham) aggregate signature. In IBFT, multi-level indicators are used to calculate the trust value of each node, and some nodes are selected to take part in network consensus as a result of this calculation. The master node is chosen

The study seeks the relationship between the mathematical-procedural Knowledge and the logical-mathematical intelligence among students at the third stage in mathematics department. To this end, three questions were arisen: what is the level of mathematical-procedural Knowledge among the third stage students in mathematics department regarding their gender? Do male or female students have more logical-mathematical intelligence and are there significant differences base on their gender? What kind of correlation is between the level of mathematical-procedural Knowledge and the logical-mathematical intelligence of male and female students in the third stage in the mathematics department? A sample of (75) male and female students at the thir

This research seeks to try to address one of the important issues in society that prevents the state from achieving its social, economic, political and financial goals, represented by the low tax proceeds, through which it can achieve those goals. What is reflected on the tax proceeds, knowing that the General Tax Authority does not take into account the issue of analyzing the opportunity cost of corporate capital as one of the profit indicators when setting the annual controls, which leads to a decrease in the tax proceeds, and therefore the research objective will be to shed light on the importance of adopting the concept of analysis The opportunity cost by the General Tax Authority to achieve a tax proceeds commensurate with t

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

A research was conducted to determine the feasibility of using adsorption process to remove boron from aqueous solutions using batch technique. Three adsorbent materials; magnesium, aluminum and iron oxide were investigated to find their abilities for boron removal. The effects of operational parameters on boron removal efficiency for each material were determined.
The experimental results revealed that maximum boron removal was achieved at pH 9.5 for magnesium oxide and 8 for aluminum and iron oxide. The percentage of boron adsorbed onto magnesium,aluminum and iron oxide reaches up to 90, 42.5 and 41.5% respectively under appropriate conditions. Boron concentration in effluent water after adsorption via magnesium oxide comply with th

Production of fatty acid esters (biodiesel) from oleic acid and 2-ethylhexanol using sulfated zirconia as solid catalyst for the production of biodiesel was investigated in this work.

       The parameters studied were temperature of reaction (100 to 130°C), molar ratio of alcohol to free fatty acid (1:1 to 3:1), concentration of catalyst (0.5 to 3%wt), mixing speed (500 to 900 rpm) and types of sulfated zirconia (i.e modified, commercial, prepared  catalyst according to literature and reused catalyst). The results show the best conversion to biodiesel was 97.74% at conditions of 130°C, 3:1, 2wt% and 650 rpm using modified catalyst respectively. Also, modified c

In this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .