This paper suggests a new nature inspired metaheuristic optimization algorithm which is called Sea Lion Optimization (SLnO) algorithm. The SLnO algorithm imitates the hunting behavior of sea lions in nature. Moreover, it is inspired by sea lions' whiskers that are used in order to detect the prey. SLnO algorithm is tested with 23 well-known test functions (Benchmarks). Optimization results show that the SLnO algorithm is very competitive compared to Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), Grey Wolf Optimization (GWO), Sine Cosine Algorithm (SCA) and Dragonfly Algorithm (DA).
Esta es la versión de autor del artículo publicado en: This is an author produced version of a paper published in: The rapid development of communication technology due to the global spread of the Internet and the digital information revolution has given rise to a huge increase in the use and transmission of multimedia information (images, audio, and video). As a result, information security during storage and transmission has become a critical issue. For example, images are widely used in industrial processes. These images could contain private information, so they must be protected.Digital image scrambling, often used for image encryption and data hiding, reorders and changes the position of image pixels to break the relationship between adjacent pixels. 1 These methods include Advanced Encryption Standard, 2 Twice Interval Division, 3 Cat Chaotic Mapping, 4 Magic Cube, 5 and Arnold Transformation. 6 We propose a new scrambling method based on a 2D cellular automaton (CA).The ability to obtain complex global behavior from simple local rules makes CA an interesting platform for digital image scrambling. The most widely known example, the Game of Life (GL), is a 2D CA that produces large amounts of patterned data. The GL (which was designed by John Conway) can scramble the digital image by providing the complex behavior that would produce the most useful operationsIn this work, we analyze the GL's complex characteristics using digital image scrambling to decide whether the degree of scrambling is influenced by different GL configurations (such as the number of generations and boundary conditions). We also design various sets of 2D CA rules, variations on the GL rules, with different Lambda parameters around the critical value of Lambda. Our resulting model is simple and robust, and our tests show that the scrambling effects are good. Cellular AutomataCA are widely used in applications such as art (generated images and music), random number generation, pattern recognition, routing algorithms, and games. The application of CA in the area of digital image processing includes image enhancement, compression, encryption, and watermarking. 8 CA are dynamic, complex space and time discrete systems originally proposed by Stanislaw Ulam and John von Neumann in the 1940s as formal models for self-reproducing organisms. 7 They consist of a certain number of identical cells, each of which can take a finite number of states. The cells are distributed in space in a rectangular grid in one or more dimensions. At every time step, all the cells update their states synchronously by applying rules (transition function), which take as input the state of the cell under consideration and the states of its neighboring cells. The various CA models differ in the number of dimensions, the number of possible states, the neighborhood relationship, and the state update rules.In spite of their simple construction, CA can produce complex behavior and generate useful operations. Stephen Wolfram classified 1D CA into four broad categories: clas...
An interconnection network architecture that promises to be an interesting option for future-generation parallel processing systems is the OTIS (Optical Transpose Interconnection System) optoelectronic architecture. Therefore, all performance improvement aspects of such a promising architecture need to be investigated; one of which is load balancing technique. This paper focuses on devising an efficient algorithm for load balancing on the promising OTIS-Hypercube interconnection networks. The proposed algorithm is called Clusters Dimension Exchange Method (CDEM). The analytical model and the experimental evaluation proved the excellence of OTIS-Hypercube compared to Hypercube in terms of various parameters, including execution time, load balancing accuracy, number of communication steps, and speed.
The software testing phase in the software development process is considered a time-consuming process. In order to reduce the overall development cost, automatic test data generation techniques based on genetic algorithms have been widely applied. This research explores a new approach for using genetic algorithms as test data generators to execute all the branches in a program. In the literature, existing approaches for test data generation using genetic algorithms are mainly focused on maintaining a single-population of candidate tests, where the computation of the fitness function for a particular target branch is based on the closeness of the input execution path to the control dependency condition of that branch. The new approach utilizes acyclic predicate paths of the program's control flow graph containing the target branch as goals of separate search processes using distinct island populations. The advantages of the suggested approach is its ability to explore a greater variety of execution paths, and in certain conditions, increasing the search effectiveness. When applied to a collection of programs with a moderate number of branches, it has been shown experimentally that the proposed multiple-population algorithm outperforms the single-population algorithm significantly in terms of the number of executions, execution time, time improvement, and search effectiveness.
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