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Due to the wide variety of distant information transmission, data encryption has become an absolute necessity for practically all data transaction applications. Sensitive data gets uploaded to the cloud every day through many methods. AES algorithm is now the best option for many applications that require security services. Because of this, a lot of research has been carried out to improve the performance and efficiency of the algorithm. This paper's main goal is to propose an improved method for encrypting and decrypting data. As key sharing was a significant problem in the symmetric approach, we generate the key using the ECC and will encrypt and decrypt data using the AES using this key. The suggested algorithm, which is simpler than ECC and solely utilized for key generation-not data encryption or decryption-is more secure than AES because it circumvents the key-sharing issue that plagued AES. [ABSTRACT FROM AUTHOR]

Image compression is one of the most important branches of digital image processing as it is concerned with reducing the size of the captured images to save the space allocated to them on the storage drive and facilitate the process of transferring and sending them. In this paper, we present a new method for compressing digital images depending on two algorithms: the Ant Lion Optimization and the Firefly. The performance of the suggested algorithms is evaluated using the compression ratio; i.e., Ratio of bits before and after compression, (PSNR); i.e., the extent to which the restored image is similar to the original image, and the standard for average squared errors (MSE), meaning the amount of error in the recovered image, where the lowest value of image compression ratio with the highest value for image quality should be obtained with the lowest value of errors. A comparison was made between both methods in order to determine the best of them in conducting the pressure process through the results that will be reviewed. [ABSTRACT FROM AUTHOR]

In this paper, we introduce the concept of separability of an intuitionistic fuzzy relation (IFR). First, we explain the concept of a fuzzy relation and IFR. Some operations and relations on IFRs are defined and examined. Then we introduc the definition of separability on IFR as a generalization of separability on a fuzzy relation. We present some basic properties and identify separability for some operations with examples. We characterize the separability of IFR. Finally, we construct an algorithm to check the separability of IFR. [ABSTRACT FROM AUTHOR]

With the need to store a huge amount of personal information, Computer hardware has become extremely vital nowadays. However, some challenges follow this expansion; for instance, solving the problem of maintaining security challenges by using high-security algorithms. As a result, a high-security cryptosystem with low computation power is needed. One of the lattice-based cryptosystems that meet these requirements is NTRU. Since the NTRU cryptosystem proposal, many variants were proposed by researchers using different algebraic structures. In this paper, we design a new cryptosystem variant of NTRU, called BOTRU, which is a high-performing system based on bi-octonion subalgebra and it has good resistance to some well-known attacks, such as a brute force attack. The creation of two public keys in the system proposed has differentiated it from NTRU and NTRU like cryptosystems. Some arithmetic operations are used for comparing the efficiency of BOTRU with the OTRU cryptosystem. Based on arithmetic assessment, the comparison reveals that the BOTRU has a higher speed than the OTRU. [ABSTRACT FROM AUTHOR]

One of the problems in distinguishing numbers written in Arabic and in handwriting is the difference in the writing style for each person and the accompanying impurities with Arabic letters which requires purification in order to obtain the letters in their correct form. Through the proposed network, we reached accurate results with a very low error rate and high accuracy which distinguishes it from previous methods used to distinguish written numbers. [ABSTRACT FROM AUTHOR]

The product of two polytopes P and Q of orders m and n, respectively, yields a polytope of order m+n. The resulting polytope is very important in various fields of sciences. The goal of our research is to create a new relationship for the Ehrhart polynomial of the free sum for two polytopes, as well as the product for two cyclic polytopes. We also discuss the roots of all obtained polynomials. Finally, we give applications for these results and provide an algorithm in Matlab. [ABSTRACT FROM AUTHOR]

Breast cancer is one of the most common diseases whose seriousness has raised concern and anxiety worldwide with over 7 million cases and around 685 thousand deaths globally (according to the World Health Organization(WHO)), making it one of the world’s most prevailing diseases. Scientists and doctors tried to cure breast cancer disease using many types of therapeutic treatment, the most common of them being Endo-therapy. Unfortunately however, Endo-therapy did ot have much better results than the other types of treatments. Some breast cancer cells have estrogen receptors which can attract estrogen proteins and make a cancer cell grow. In this study, we introduce deep neural networks on QSAR model to find inhibitors for those estrogen receptors and thus stop the breast cancer cells from growing. We present a comprehensive comparison between our model (the DNNR model) and the Random forest model, in which the DNNR outperformed the RF algorithm (an increase of 21.2% in the accuracy of the algorithm). [ABSTRACT FROM AUTHOR]

Early blight commonly attacks the tomato leaf. The drone and image processing technologies offer a tool to detect the symptom of the tomato disease. One of the stages in the early blight detection is the segmentation of the tomato leaf. The K-means algorithm is a known image segmentation method which works simply and quickly. However, randomized initialization of centroids causes the K-means algorithm to easily get stuck in the local optimum and, as a result, gives imprecise segmentation. The swarm intelligence-based algorithm can avoid this problem. For this reason, we propose the early blight disease segmentation method on tomato leaves uses K-means algorithm with swarm intelligence-based algorithm. This research uses the Particle Swarm Optimization (PSO) because PSO is one of the swarm intelligence-based algorithms which has a balance in exploration and exploitation. The Hue of the HSV color space is used as input. From the experimental results, we can conclude that the performance of the early blight disease segmentation method using the K-means algorithm with swarm intelligence-based algorithm is much better. [ABSTRACT FROM AUTHOR]