The COVID-19 coronavirus illness is caused by a newly discovered species of coronavirus known as SARS-CoV-2. Since COVID-19 has now expanded across many nations, the World Health Organization (WHO) has designated it a pandemic. Reverse transcription-polymerase chain reaction (RT-PCR) is often used to screen samples of patients showing signs of COVID-19; however, this method is more expensive and takes at least 24 hours to get a positive or negative response. Thus, an immediate and precise method of diagnosis is needed. In this paper, chest X-rays will be utilized through a deep neural network (DNN), based on a convolutional neural network (CNN), to detect COVID-19 infection. Based on their X-rays, those with COVID-19 indications may be categorized as clean, infected with COVID-19 or suffering from pneumonia, according to the suggested CNN network. Sample pieces from every group are used in experiments, and categorization is performed by a CNN. While experimenting, the CNN-derived features were able to generate the maximum training accuracy of 94.82% and validation accuracy of 94.87%, The F1-scores were 97%, 90% and 96%, in clearly categorizing patients afflicted by COVID-19, normal and having pneumonia, respectively. Meanwhile, the recalls are 95%, 91% and 96% for COVID-19, normal and pneumonia, respectively.
A well known cryptographic techniques is Playfair Cryptography, it is considered one of the classical method. After the invention of different techniques, it is easy to break Playfair. This paper proposed some way for removal of the traditional Playfair drawbacks. The Adaptive playfair algorithm proposed in this paper, add more security and complexity to the classical playfair algorithm. In addition to the use of two keys in form of matrices to encrypt the message, the proposed method works depending on using the odd even positions for the every pairs of the letters. The odd pairs encrypt through the first matrix key and the even pairs encrypt by using the second matrix, then applying XOR function with the third key to the result. The resulting cipher text will be in binary form, the plain text obtained by run proposed step backwards.
In order to develop the cryptographic systems, it must always find new techniques to construct the strong cryptosystem, the proposed method try to employ the nature and animals activates in their society to propose the new algorithm for new cryptosystem, depending completely on the behaver of the wolfs communications between each other’s through howls to exchange the information between the wolf’s group to determine the locations and for warning each other’s against the dangers, in this paper propose a new algorithm through classify the characters of the message into groups and exchange the keys between the groups to be difficult on the cryptanalytics to follow the path of constructing the system, also using the different cryptanalysis techniques to evaluate the proposed algorithm.
Now days many institutions and organizations needs to protect their information and secret data from theft and many other attempts to destroy and fabricate these data and information by unauthorized persons who tries to manipulate by the privacy of these institutions and organizations. So, it is necessary to find a secure way to protect such a data and information, therefore in this paper a new method proposed to develop the encryption techniques through using the McLaurin series as a new cryptosystem, and through using different cryptanalysis techniques and tools, the proposed method was inevitable against the different attacks, it is also a one way function technique.
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