Journal Port Science Research

A proposed Hyper-Heuristic optimizer Nesting Grey Wolf Optimizer and COOT Algorithm for Multilevel Task

Afrah U. Mosaa — 2023-11-18

It can be extremely difficult to find the optimal solution in many complex optimization problems. The goal of optimization algorithms in such cases is to locate a feasible solution that is as close as possible to the optimal one. These algorithms are called metaheuristic optimization algorithms and the majority of them take their inspiration from nature and work to solve challenging problems in a variety of fields. In this paper, a combination between GWO and Coot algorithm was proposed. The effectiveness of the GWO algorithm has been demonstrated in many fields, including engineering and medicine. However, GWO has a disadvantage: the potential to enter the local minima due to a lack of diversity. GWO and the Coot algorithm were merged to fix this flaw. Ten benchmark functions were used to evaluate the performance of this hybrid technique, and its results were compared to those of other common optimization algorithms, including GWO, Cuckoo Search (CS), and the Shuffled Frog Leaping algorithm (SFLA). The results show that the suggested algorithm can provide results that are both competitive and more consistent than the other algorithms in most test functions.

The Impact of Information Security Processes on Providing Secure Digital Systems

Balsam A. Mustafa — 2023-12-02

With the increasing use of the internet, a global network, Information security is a substantial issue in today's business. Information security has become one of the most important aspects of modern electronic society. Security of information, networks, and systems is vital to make information systems work satisfactorily and enable people to safely get the information they need. Security is the practice of defending information from unauthorized access. This paper discusses the essential characteristics of secure communication and the important processes used by administrators to protect data and systems.

Implementation Of The Swin Transformer and Its Application In Image Classification

1Rasha. A. Dihin — 2023-11-18

There are big differences between the field of view of the calculator and the field of natural languages, for example, in the field of vision, the difference is in the size of the object as well as in the accuracy of the pixels in the image, and this contradicts the words in the text, and this makes the adaptation of the transformers to see somewhat difficult.Very recently a vision transformer named Swin Transformer was introduced by the Microsoft research team in Asia to achieve state-of-the-art results for machine translation. The computational complexity is linear and proportional to the size of the input image, because the processing of subjective attention is within each local window separately, and thus results in processor maps that are hierarchical and in deeper layers, and thus serve as the backbone of the calculator's vision in image classification and dense recognition applications. This work focuses on applying the Swin transformer to a demonstrated mathematical example with step-by-step analysis. Additionally, extensive experimental results were carried out on several standardized databases from CIFAR-10, CIFAR-100, and MNIST. Their results showed that the Swin Transformer can achieve flexible memory savings. Test accuracy for CIFAR-10 gave a 71.54% score, while for the CIFAR-100 dataset the accuracy was 46.1%. Similarly, when the Swin transformer was applied to the MNIST dataset, the accuracy increased in comparison with other vision transformer results.

An Image Encryption Method Based on Lorenz Chaotic Map and Hunter-Prey Optimization

Qutaiba K. Abed — 2023-11-25

Through the development of communication technology, fast and efficient tools are required to practically secure the process of data exchange in securing images. This paper presents a new method of encryption for protecting images against many attacks from unsafe public networks. Lorenz chaos map is used to generate a sequence of random numbers for each stage depending on the initial parameters. The Hunter Prey optimization algorithm is applied in order to obtain these parameters to use them based on the original image. Therefore, the random sequence number generated by the Lorenz chaotic map will be different from one image to another. That will make it unpredictable and very difficult to discover the process of encryption. The results of simulation experiments demonstrate that the encryption algorithm have passed the plaintext sensitivity test with the NPCR of 0.99785 and the UACI of 0.33623. As well as the correlation coefficient test values in the three directions gave the values of (v = -0.0007, h = -0.0000, d = 0.0005). Also, the calculated information entropy test value was 7.9983. These results demonstrate that this algorithm is very strong enough to withstand the various types of attacks that images can be exposed during transmission on the Internet or any public network. The security analysis's comparison of the proposed changes to similar ones revealed that the proposed encryption system is more efficient.