Umanesan Ramakrishnan^1,*, Nandhagopal Nachimuthu²

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1547-1559, 2022, DOI:10.32604/iasc.2022.017123

Abstract Recently, various research fields have begun dealing with massive datasets forseveral functions. The main aim of a feature selection (FS) model is to eliminate noise, repetitive, and unnecessary featuresthat reduce the efficiency of classification. In a limited period, traditional FS models cannot manage massive datasets and filterunnecessary features. It has been discovered from the state-of-the-art literature that metaheuristic algorithms perform better compared to other FS wrapper-based techniques. Common techniques such as the Genetic Algorithm (GA) andParticle Swarm Optimization (PSO) algorithm, however, suffer from slow convergence and local optima problems. Even with new generation algorithms such as Firefly heuristic and Fish… More >

Srinath Doss¹, Jothi Paranthaman², Suseendran Gopalakrishnan³, Akila Duraisamy³, Souvik Pal⁴, Balaganesh Duraisamy⁵, Chung Le Van^6,*, Dac-Nhuong Le⁷

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1577-1594, 2021, DOI:10.32604/cmc.2020.012379

Abstract In the healthcare system, the Internet of Things (IoT) based distributed systems play a vital role in transferring the medical-related documents and information among the organizations to reduce the replication in medical tests. This datum is sensitive, and hence security is a must in transforming the sensational contents. In this paper, an Evolutionary Algorithm, namely the Memetic Algorithm is used for encrypting the text messages. The encrypted information is then inserted into the medical images using Discrete Wavelet Transform 1 level and 2 levels. The reverse method of the Memetic Algorithm is implemented when extracting a hidden message from the… More >