Scopus Research — Zahraa Hussein

The aim of this paper is to solve the problem of representing refined neutrosophic matrices by linear functions, where it describes the structure of refined neutrosophic linear transformations that represent refined neutrosophic matrices. On the other hand, this work introduces a novel algorithm to compute a basis of any refined neutrosophic vector space depending on the classical basis of its corresponding classical vector space. © 2022, American Scientific Publishing Group (ASPG). All rights reserved.

Coronavirus (COVID) is one of the world's most devastating diseases, affecting the lives of millions of people around the globe. Accurate and timely detection of the COVID virus is critical for human survival. The standard medical history of diagnosing COVID disease has been deemed unreliable in several ways. Noninvasive methods such as Machine Learning (ML) are efficient and reliable for classifying healthy persons and people with COVID disease. In this paper, we improved a Smart Forecasting Model using Machine Learning (SFML) for COVID prediction (positive, negative) by using COVID data. We applied, two algorithms of feature selection (correlation and gain ratio), two supervised ML algorithms (Random forest and support vector machine) and the technique of cross-validation was applied for evaluating the SFML, such as specificity, accuracy, F-measure, sensitivity, and running time. The proposed SFML may easily distinguish COVID infected individuals from healthy individuals. The proposed SFML has been tested on a full set of COVID features as well as a smaller set of features. The results reveal that reducing COVID features has an impact on SMFL performance measures. © 2022 IEEE.

'Security' has formed into a critical concern in the digital data storage and transfer via communication that is not secure channels, which can be addressed by employing trusted encryption methods. Because of its remarkable superior qualities, such as simplicity, high security, and speed faster, chaos-based encryption algorithms are becoming more prominent. Furthermore, employing DNA in cryptography opens a new area due to three factors: storage capacity, computation power, and parallelism. 'This paper for text encryption, a hyperchaotic sequence and a DNA sequence are used together. The intensity levels of an input text are translated to a serial binary digit stream, and the hyperchaotic sequence scrambles this bitstream globally. To achieve a robust encryption performance, DNA operations are done between the hyperchaotic sequence and the DNA sequence. The findings of the experiment show that the encryption algorithm outperforms state-of-the-art approaches in terms of quality, security, and robustness. resistant to brute force attacks. and has a bigger key space. © 2021 IEEE.