The swarm intelligence and evolutionary methods are commonly utilized by researchers in solving the difficult combinatorial and Non-Deterministic Polynomial (NP) problems. The N-Queen problem can be defined as a combinatorial problem that became intractable for the large ‘n’ values and, thereby, it is placed in the NP class of problems. In the present study, a solution is suggested for the N-Queen problem, on the basis of the Meerkat Clan Algorithm (MCA). The problem of n-Queen can be mainly defined as one of the generalized 8-Queen problem forms, for which the aim is placing 8 queens in a way that none of the queens has the ability of killing the others with the use of the standard moves of the chess queen. The Meerkat Clan environm

An Optimal Algorithm for HTML Page Building Process

The data communication has been growing in present day. Therefore, the data encryption became very essential in secured data transmission and storage and protecting data contents from intruder and unauthorized persons. In this paper, a fast technique for text encryption depending on genetic algorithm is presented. The encryption approach is achieved by the genetic operators Crossover and mutation. The encryption proposal technique based on dividing the plain text characters into pairs, and applying the crossover operation between them, followed by the mutation operation to get the encrypted text. The experimental results show that the proposal provides an important improvement in encryption rate with comparatively high-speed Process

Krawtchouk polynomials (KPs) and their moments are promising techniques for applications of information theory, coding theory, and signal processing. This is due to the special capabilities of KPs in feature extraction and classification processes. The main challenge in existing KPs recurrence algorithms is that of numerical errors, which occur during the computation of the coefficients in large polynomial sizes, particularly when the KP parameter (p) values deviate away from 0.5 to 0 and 1. To this end, this paper proposes a new recurrence relation in order to compute the coefficients of KPs in high orders. In particular, this paper discusses the development of a new algorithm and presents a new mathematical model for computing the

This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t

In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

     In the current study, 2D seismic data in west An-Najaf (WN-36 line) were received after many steps of processing by Oil Exploration Company in 2018. Surface Consistent Amplitude Compensation (SCAC) was applied on the seismic data. The processing sequence in our study started by sorting data in a common mid-point (CMP) gather, in order to apply the velocity analysis using Interactive Velocity Analysis Application (INVA) with Omega system. Semblance of velocity was prepared to preform normal move-out (NMO) vs. Time. Accurate root mean square velocity (V_RMS) was selected, which was controlled by flatness of the primary events. The resultant seismic velocity section for the study area shows that the veloci

Object detection in real time is considered as a challenging problem. However, it is very important in a wide range of applications, especially in field of multimedia. The players and ball are the most important objects in soccer game videos and detecting them is a challenging task because of many difficulties, such as shadow and illumination, ball size, ball occluded by players or merged with lines, and similar appearance of players. To overcome these problems, we present a new system to detect the players and ball in real-time by using background subtraction and Sobel detection. The results were more accurate and approximately two times faster than those using only background subtraction.

       Recently, much secured data has been sent across the internet and networks. Steganography is very important because it conceals secure data in images, texts, audios, protocols, videos, or other mediums. Video steganography is the method of concealing data in frames of video format. A video is a collection of frames or images used for hidden script messages. This paper proposes a technique to encrypt secret messages using DNA and a 3D chaotic map in video frames using the raster method. This technique uses three steps: Firstly, converting video frames into raster to extract features from each frame. Secondly, encryption of secret messages using encoded forms of DNA bases, inverse/inverse complements of DNA, a