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  • Open Access

    ARTICLE

    Optimal Cooperative Spectrum Sensing Based on Butterfly Optimization Algorithm

    Noor Gul1,2, Saeed Ahmed1,3, Atif Elahi4, Su Min Kim1, Junsu Kim1,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 369-387, 2022, DOI:10.32604/cmc.2022.022260 - 03 November 2021

    Abstract Since the introduction of the Internet of Things (IoT), several researchers have been exploring its productivity to utilize and organize the spectrum assets. Cognitive radio (CR) technology is characterized as the best aspirant for wireless communications to augment IoT competencies. In the CR networks, secondary users (SUs) opportunistically get access to the primary users (PUs) spectrum through spectrum sensing. The multipath issues in the wireless channel can fluster the sensing ability of the individual SUs. Therefore, several cooperative SUs are engaged in cooperative spectrum sensing (CSS) to ensure reliable sensing results. In CSS, security is… More >

  • Open Access

    ARTICLE

    Disturbance Evaluation in Power System Based on Machine Learning

    Emad M. Ahmed1,*, Mohamed A. Ahmed1, Ziad M. Ali2,3, Imran Khan4

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 231-254, 2022, DOI:10.32604/cmc.2022.022005 - 03 November 2021

    Abstract The operation complexity of the distribution system increases as a large number of distributed generators (DG) and electric vehicles were introduced, resulting in higher demands for fast online reactive power optimization. In a power system, the characteristic selection criteria for power quality disturbance classification are not universal. The classification effect and efficiency needs to be improved, as does the generalization potential. In order to categorize the quality in the power signal disturbance, this paper proposes a multi-layer severe learning computer auto-encoder to optimize the input weights and extract the characteristics of electric power quality disturbances.… More >

  • Open Access

    ARTICLE

    Covid-19 CT Lung Image Segmentation Using Adaptive Donkey and Smuggler Optimization Algorithm

    P. Prabu1, K. Venkatachalam2, Ala Saleh Alluhaidan3,*, Radwa Marzouk4, Myriam Hadjouni5, Sahar A. El_Rahman5,6

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1133-1152, 2022, DOI:10.32604/cmc.2022.020919 - 03 November 2021

    Abstract COVID’19 has caused the entire universe to be in existential health crisis by spreading globally in the year 2020. The lungs infection is detected in Computed Tomography (CT) images which provide the best way to increase the existing healthcare schemes in preventing the deadly virus. Nevertheless, separating the infected areas in CT images faces various issues such as low-intensity difference among normal and infectious tissue and high changes in the characteristics of the infection. To resolve these issues, a new inf-Net (Lung Infection Segmentation Deep Network) is designed for detecting the affected areas from the… More >

  • Open Access

    ARTICLE

    Modified Mackenzie Equation and CVOA Algorithm Reduces Delay in UASN

    R. Amirthavalli1,*, S. Thanga Ramya2, N. R. Shanker3

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 829-847, 2022, DOI:10.32604/csse.2022.020307 - 25 October 2021

    Abstract In Underwater Acoustic Sensor Network (UASN), routing and propagation delay is affected in each node by various water column environmental factors such as temperature, salinity, depth, gases, divergent and rotational wind. High sound velocity increases the transmission rate of the packets and the high dissolved gases in the water increases the sound velocity. High dissolved gases and sound velocity environment in the water column provides high transmission rates among UASN nodes. In this paper, the Modified Mackenzie Sound equation calculates the sound velocity in each node for energy-efficient routing. Golden Ratio Optimization Method (GROM) and… More >

  • Open Access

    ARTICLE

    IRKO: An Improved Runge-Kutta Optimization Algorithm for Global Optimization Problems

    R. Manjula Devi1, M. Premkumar2, Pradeep Jangir3, Mohamed Abdelghany Elkotb4,5, Rajvikram Madurai Elavarasan6, Kottakkaran Sooppy Nisar7,*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4803-4827, 2022, DOI:10.32604/cmc.2022.020847 - 11 October 2021

    Abstract Optimization is a key technique for maximizing or minimizing functions and achieving optimal cost, gains, energy, mass, and so on. In order to solve optimization problems, metaheuristic algorithms are essential. Most of these techniques are influenced by collective knowledge and natural foraging. There is no such thing as the best or worst algorithm; instead, there are more effective algorithms for certain problems. Therefore, in this paper, a new improved variant of a recently proposed metaphorless Runge-Kutta Optimization (RKO) algorithm, called Improved Runge-Kutta Optimization (IRKO) algorithm, is suggested for solving optimization problems. The IRKO is formulated… More >

  • Open Access

    ARTICLE

    A Novel Binary Emperor Penguin Optimizer for Feature Selection Tasks

    Minakshi Kalra1, Vijay Kumar2, Manjit Kaur3, Sahar Ahmed Idris4, Şaban Öztürk5, Hammam Alshazly6,*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6239-6255, 2022, DOI:10.32604/cmc.2022.020682 - 11 October 2021

    Abstract Nowadays, due to the increase in information resources, the number of parameters and complexity of feature vectors increases. Optimization methods offer more practical solutions instead of exact solutions for the solution of this problem. The Emperor Penguin Optimizer (EPO) is one of the highest performing meta-heuristic algorithms of recent times that imposed the gathering behavior of emperor penguins. It shows the superiority of its performance over a wide range of optimization problems thanks to its equal chance to each penguin and its fast convergence features. Although traditional EPO overcomes the optimization problems in continuous search… More >

  • Open Access

    ARTICLE

    Swarm-Based Extreme Learning Machine Models for Global Optimization

    Mustafa Abdul Salam1,*, Ahmad Taher Azar2, Rana Hussien2

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6339-6363, 2022, DOI:10.32604/cmc.2022.020583 - 11 October 2021

    Abstract Extreme Learning Machine (ELM) is popular in batch learning, sequential learning, and progressive learning, due to its speed, easy integration, and generalization ability. While, Traditional ELM cannot train massive data rapidly and efficiently due to its memory residence, high time and space complexity. In ELM, the hidden layer typically necessitates a huge number of nodes. Furthermore, there is no certainty that the arrangement of weights and biases within the hidden layer is optimal. To solve this problem, the traditional ELM has been hybridized with swarm intelligence optimization techniques. This paper displays five proposed hybrid Algorithms… More >

  • Open Access

    ARTICLE

    Controller Placement in Software Defined Internet of Things Using Optimization Algorithm

    Sikander Hans1, Smarajit Ghosh1, Aman Kataria2, Vinod Karar2,*, Sarika Sharma3

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5073-5089, 2022, DOI:10.32604/cmc.2022.019971 - 11 October 2021

    Abstract The current and future status of the internet is represented by the upcoming Internet of Things (IoT). The internet can connect the huge amount of data, which contains lot of processing operations and efforts to transfer the pieces of information. The emerging IoT technology in which the smart ecosystem is enabled by the physical object fixed with software electronics, sensors and network connectivity. Nowadays, there are two trending technologies that take the platform i.e., Software Defined Network (SDN) and IoT (SD-IoT). The main aim of the IoT network is to connect and organize different objects… More >

  • Open Access

    ARTICLE

    Efficient Key Management System Based Lightweight Devices in IoT

    T. Chindrella Priyadharshini1,*, D. Mohana Geetha2

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1793-1808, 2022, DOI:10.32604/iasc.2022.020422 - 09 October 2021

    Abstract The Internet of Things (IoT) has changed our lives significantly. Although IoT provides new opportunities, security remains a key concern while providing various services. Existing research methodologies try to solve the security and time-consuming problem also exists. To solve those problems, this paper proposed a Hashed Advanced Encryption Standard (HAES) algorithm based efficient key management system for internet-based lightweight devices in IoT networks. The proposed method is mainly divided into two phases namely Data Owner (DO) and Data User (DU) phase. The DO phase consists of two processes namely authentication and secure data uploading. In… More >

  • Open Access

    ARTICLE

    AMBO: All Members-Based Optimizer for Solving Optimization Problems

    Fatemeh Ahmadi Zeidabadi1, Sajjad Amiri Doumari1, Mohammad Dehghani2, Zeinab Montazeri2, Pavel Trojovský3,*, Gaurav Dhiman4

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2905-2921, 2022, DOI:10.32604/cmc.2022.019867 - 27 September 2021

    Abstract There are many optimization problems in different branches of science that should be solved using an appropriate methodology. Population-based optimization algorithms are one of the most efficient approaches to solve this type of problems. In this paper, a new optimization algorithm called All Members-Based Optimizer (AMBO) is introduced to solve various optimization problems. The main idea in designing the proposed AMBO algorithm is to use more information from the population members of the algorithm instead of just a few specific members (such as best member and worst member) to update the population matrix. Therefore, in… More >

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