To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

The equation of Kepler is used to solve different problems associated with celestial mechanics and the dynamics of the orbit. It is an exact explanation for the movement of any two bodies in space under the effect of gravity. This equation represents the body in space in terms of polar coordinates; thus, it can also specify the time required for the body to complete its period along the orbit around another body. This paper is a review for previously published papers related to solve Kepler’s equation and eccentric anomaly. It aims to collect and assess changed iterative initial values for eccentric anomaly for forty previous years. Those initial values are tested to select the finest one based on the number of iterations, as well as the

The increasing anti-bacterial drug resistance is one of the biggest challenges facing doctors around the globe, so finding alternative treatments is one of the ideal options to overcome this problem. The cruciferous family is one of the wealthiest plants worldwide because it contains the most important secondary metabolites, glucosinolates, known for their anti-microbial properties. The present study aimed to evaluate the anti-bacterial effect of glucosinolates (Sinigrin) against eight bacterial isolates (Staphylococcus aureus, Enterococcus faecalis, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Actinomyces, Proteus mirabilis and Streptococcus pneumoniae). The current study investigated six concentrations of pure

This study aimed to explore and separate the phytochemicals of the whole plant Conyza canadensis, a naturally growing plant in Iraq, since no phytochemical research was done previously in Iraq. The whole plant of C. canadensis was defatted by maceration in hexane for 24 hours. The defatted plant materials were extracted using Soxhlet apparatus, the aqueous ethanol 85% as a solvent extraction for 9 hours, and fractionated by petroleum ether, chloroform, ethyl acetate, and n-butanol. The petroleum ether, chloroform, and ethyl acetate fractions were analyzed by high-performance liquid chromatography (HPLC) for their steroids, alkaloids, and polyphenolic (phenolic acids and flavonoids) contents. One alkaloid was isolated from chloroform fractio