Liang Zeng^1,2,3, Ziyang Ding¹, Junyang Shi¹, Shanshan Wang^1,2,3,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1757-1787, 2024, DOI:10.32604/cmc.2024.055574 - 15 October 2024

Abstract In the manufacturing industry, reasonable scheduling can greatly improve production efficiency, while excessive resource consumption highlights the growing significance of energy conservation in production. This paper studies the problem of energy-efficient distributed heterogeneous permutation flowshop problem with variable processing speed (DHPFSP-VPS), considering both the minimum makespan and total energy consumption (TEC) as objectives. A discrete multi-objective squirrel search algorithm (DMSSA) is proposed to solve the DHPFSP-VPS. DMSSA makes four improvements based on the squirrel search algorithm. Firstly, in terms of the population initialization strategy, four hybrid initialization methods targeting different objectives are proposed to enhance… More >

K. Ishwarya, A. Alice Nithya^*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6081-6099, 2023, DOI:10.32604/cmc.2023.034654 - 28 December 2022

Abstract Human pose estimation (HPE) is a procedure for determining the structure of the body pose and it is considered a challenging issue in the computer vision (CV) communities. HPE finds its applications in several fields namely activity recognition and human-computer interface. Despite the benefits of HPE, it is still a challenging process due to the variations in visual appearances, lighting, occlusions, dimensionality, etc. To resolve these issues, this paper presents a squirrel search optimization with a deep convolutional neural network for HPE (SSDCNN-HPE) technique. The major intention of the SSDCNN-HPE technique is to identify the… More >

Doaa Sami Khafaga¹, El-Sayed M. El-kenawy², Fadwa Alrowais^1,*, Sunil Kumar³, Abdelhameed Ibrahim⁴, Abdelaziz A. Abdelhamid^5,6

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4027-4041, 2023, DOI:10.32604/cmc.2023.033039 - 31 October 2022

Abstract In data mining and machine learning, feature selection is a critical part of the process of selecting the optimal subset of features based on the target data. There are 2ⁿ potential feature subsets for every n features in a dataset, making it difficult to pick the best set of features using standard approaches. Consequently, in this research, a new metaheuristics-based feature selection technique based on an adaptive squirrel search optimization algorithm (ASSOA) has been proposed. When using metaheuristics to pick features, it is common for the selection of features to vary across runs, which can lead… More >

B. Jaishankar^1,*, Santosh Vishwakarma², Prakash Mohan³, Aditya Kumar Singh Pundir⁴, Ibrahim Patel⁵, N. Arulkumar⁶

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1815-1829, 2022, DOI:10.32604/iasc.2022.021822 - 09 December 2021

Abstract The Healthcare system is an organization that consists of important requirements corresponding to security and privacy, for example, protecting patients’ medical information from unauthorized access, communication with transport like ambulance and smart e-health monitoring. Due to lack of expert design of security protocols, the healthcare system is facing many security threats such as authenticity, data sharing, the conveying of medical data. In such situation, block chain protocol is used. In this manuscript, Efficient Block chain Network for securing Healthcare data using Multi-Objective Squirrel Search Optimization Algorithm (MOSSA) is proposed to generate smart and secure Healthcare… More >

Aman Bhaskar¹, Chirag Sharma¹, Khalid Mohiuddin², Aman Singh^1,*, Osman A. Nasr², Mamdooh Alwetaishi³

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3069-3089, 2022, DOI:10.32604/cmc.2022.019866 - 07 December 2021

Abstract Advancement in multimedia technology has resulted in protection against distortion, modification, and piracy. For implementing such protection, we have an existing technique called watermarking but obtaining desired distortion level with sufficient robustness is a challenging task for watermarking in multimedia applications. In the paper, we proposed a smart technique for video watermarking associating meta-heuristic algorithms along with an embedding method to gain an optimized efficiency. The main aim of the optimization algorithm is to obtain solutions with maximum robustness, and which should not exceed the set threshold of quality. To represent the accuracy of the More >

R. Rajaragavi^1,*, S. Palanivel Rajan²

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 1-14, 2022, DOI:10.32604/iasc.2022.021206 - 26 October 2021

Abstract A brain tumor is a portion of uneven cells, need to be detected earlier for treatment. Magnetic Resonance Imaging (MRI) is a routinely utilized procedure to take brain tumor images. Manual segmentation of tumor is a crucial task and laborious. There is a need for an automated system for segmentation and classification for tumor surgery and medical treatments. This work suggests an efficient brain tumor segmentation and classification based on deep learning techniques. Initially, Squirrel search optimized bidirectional ConvLSTM U-net with attention gate proposed for brain tumour segmentation. Then, the Hybrid Deep ResNet and Inception More >