firefly algorithm

The widespread application of cloud computing creates a wide range of application services on the Internet, which is a new challenge for cloud service composition models and algorithms. In this article, a new meta-heuristic method for combining cloud services is presented. The firefly algorithm is one of the most widely used metaheuristic algorithms based on nature, which has been simulated from the behavior of fireflies in moving to light sources in 2008. The proposed algorithm is the result of simulation with the latest information obtained from the behavior of fireflies, and with the new changes that have been made to this algorithm, it is balanced in the ability of exploration and exploitation, making it suitable for solving the problem of combining cloud services. The obtained results show that the proposed method works better than other State-of-the-Art algorithms in the field of service quality, and efficiency (especially on data with a large number of samples) and obtains the answers in the shortest possible time.

Housekeeping genes are expressed in all biological conditions and stages of tissue growth. A housekeeping gene is the basic gene required for maintaining the cell's primary function and is expressed in most cells of an organism to produces corresponding proteins. Normally, some genes are not expressed in different conditions and steps of the cell cycle that can determine the dynamics of the presence of a protein and consequently transient or stable interactions. Stable interactions play an important role in the determination of protein complexes. One of the challenges in system biology is to determine the appropriate thresholds to determine active proteins at each time point and to identify stable interactions. Our goal in this paper is to determine the unique threshold for each gene to characterize housekeeping genes and stable interactions. Determination of the specific threshold for each gene is determined by using the firefly optimization algorithm with the attraction function based on the combination of the standard protein complex and co-expression of genes. Experimental results on the existing dataset show that the thresholds created by the proposed method had better results than the previous methods.

Watermarking is a method for embedding a watermark in a digital image to preserve its copyright. Watermark should have two contradictory properties of transparency and robustness. Locations of embedding watermark in the image and threshold values play an important role in improving these two properties. In this paper, a novel robust image watermarking scheme in hadamard transform domain is proposed which uses Hybrid Firefly Algorithm (HFA) for selecting suitable blocks and threshold values to balance transparency and robustness. HFA is the modified version of firefly algorithm which is proposed and used in this paper for first time.This algorithmgenerates distinct and discrete values for selecting blocks and simultaneously continues values for selecting threshold values. Hadamard transform applies on each selected block of the cover image and four watermark bits are embedded in one block using selected threshold values. Watermark detection is done blindly and objective function of the optimization algorithm is a combination of transparency and robustness. This scheme is applicable to color and gray scale images. Experimental results show that the proposed scheme is highly robust against different attacks and gives better results in terms of transparency compared to other similar methods.