Supreet Kaur^*, Vijay Kumar Joshi

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 217-226, 2020, DOI:10.31209/2018.100000064

Abstract Wireless sensor networks (WSNs) are susceptible to safety threats due to cumulative dependence upon transmission, computing, and control mechanisms. Therefore, securing the end-to-end communication becomes a major area of research in WSNs. A majority of existing protocols are based upon signature and recommended-based trust evaluation techniques only. However, these techniques are vulnerable to wormhole attacks that happen due to lesser synchronization between the sensor nodes. Therefore, to handle this problem, a novel hybrid crossover-based ant colony optimization-based routing protocol is proposed. An integrated modified signature and recommendationbased trust evaluation protocol for WSNs is presented. Extensive More >

Machiraju Jayalakshmi^{1, *}, S. Nagaraja Rao²

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1081-1096, 2020, DOI:10.32604/cmc.2020.011710 - 20 August 2020

Abstract In recent years, the development in the field of computer-aided diagnosis (CAD) has increased rapidly. Many traditional machine learning algorithms have been proposed for identifying the pathological brain using magnetic resonance images. The existing algorithms have drawbacks with respect to their accuracy, efficiency, and limited learning processes. To address these issues, we propose a pathological brain tumour detection method that utilizes the Weiner filter to improve the image contrast, 2D- discrete wavelet transformation (2D-DWT) to extract the features, probabilistic principal component analysis (PPCA) and linear discriminant analysis (LDA) to normalize and reduce the features, and More >

Ahmed Y. Hamed¹, Monagi H. Alkinani², M. R. Hassan^{3, *}

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1159-1173, 2020, DOI:10.32604/cmc.2020.09176 - 30 April 2020

Abstract In the distributed networks, many applications send information from a source node to multiple destination nodes. To support these applications requirements, the paper presents a multi-objective algorithm based on ant colonies to construct a multicast tree for data transmission in a computer network. The proposed algorithm simultaneously optimizes total weight (cost, delay and hop) of the multicast tree. Experimental results prove the proposed algorithm outperforms a recently published Multi-objective Multicast Algorithm specially designed for solving the multicast routing problem. Also, it is able to find a better solution with fast convergence speed and high reliability. More >

Purvashi Baynath, Sunjiv Soyjaudah, Maleika Heenaye-Mamode Khan

Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 651-661, 2019, DOI:10.31209/2018.100000060

Abstract The goal of this paper is (i) adopt fusion of features (ii) determine the best method of feature selection technique among ant Colony optimisation, artificial bee colony optimisation and genetic algorithm. The experimental results reported that ant colony Optimisation is a promising techniques as feature selection on Keystroke Dynamics as it outperforms in terms of recognition rate for our inbuilt database where the distance between the keys has been considered for the password derivation with recognition rate 97.85%. Finally the results have shown that a small improvement is obtained by fused features, which suggest that More >

Qi Wang^1,*, Wei Liu¹, Hualong Yu¹, Shang Zheng¹, Shang Gao¹, Fabrizio Granelli²

CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.1, pp. 83-103, 2019, DOI:10.32604/cmes.2019.06897

Abstract The wireless sensor network (WSN) is widely employed in the application scenarios of the Internet of Things (IoT) in recent years. Extending the lifetime of the entire system had become a significant challenge due to the energy-constrained fundamental limits of sensor nodes on the perceptual layer of IoT. The clustering routing structures are currently the most popular solution, which can effectively reduce the energy consumption of the entire network and improve its reliability. This paper introduces an enhanced hybrid intelligential algorithm based on particle swarm optimization (PSO) and ant colony optimization (ACO) method. The enhanced More >

F. Aymerich¹, M. Serra²

CMES-Computer Modeling in Engineering & Sciences, Vol.13, No.1, pp. 49-66, 2006, DOI:10.3970/cmes.2006.013.049

Abstract The study reported in this paper explores the potential of Ant Colony Optimization (ACO) metaheuristic for stacking sequence optimization of composite laminates. ACO is a recently proposed population-based search approach able to deal with a wide range of optimization problems, especially of a combinatorial nature, and inspired by the natural foraging behavior of ant colonies. ACO search processes, in which the activities of real ants are simulated by means of artificial agents that communicate and cooperate through the modification of the local environment, were implemented in a specifically developed numerical algorithm aimed at the lay-up… More >