Tao Wu¹, Xinyu Wu¹, Jingjue Chen¹, Xi Chen^2,*, Amir Homayoon Ashrafzadeh³

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2879-2896, 2022, DOI:10.32604/cmc.2022.028942

Abstract Metaheuristic algorithm is a generalization of heuristic algorithm that can be applied to almost all optimization problems. For optimization problems, metaheuristic algorithm is one of the methods to find its optimal solution or approximate solution under limited conditions. Most of the existing metaheuristic algorithms are designed for serial systems. Meanwhile, existing algorithms still have a lot of room for improvement in convergence speed, robustness, and performance. To address these issues, this paper proposes an easily parallelizable metaheuristic optimization algorithm called team competition and cooperation optimization (TCCO) inspired by the process of human team cooperation and competition. The proposed algorithm attempts… More >

Walid El-Shafai^1,2, Amira A. Mahmoud¹, El-Sayed M. El-Rabaie¹, Taha E. Taha¹, Osama F. Zahran¹, Adel S. El-Fishawy¹, Naglaa F. Soliman³, Amel A. Alhussan^4,*, Fathi E. Abd El-Samie¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3119-3135, 2022, DOI:10.32604/cmc.2022.028935

Abstract This paper presents a study of the segmentation of medical images. The paper provides a solid introduction to image enhancement along with image segmentation fundamentals. In the first step, the morphological operations are employed to ensure image detail protection and noise-immunity. The objective of using morphological operations is to remove the defects in the texture of the image. Secondly, the Fuzzy C-Means (FCM) clustering algorithm is used to modify membership function based only on the spatial neighbors instead of the distance between pixels within local spatial neighbors and cluster centers. The proposed technique is very simple to implement and significantly… More >

Zhangdong Wang¹, Jiaohua Qin^1,*, Xuyu Xiang¹, Yun Tan¹, Neal N. Xiong²

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2931-2946, 2022, DOI:10.32604/cmc.2022.028896

Abstract Visual object tracking is a hot topic in recent years. In the meanwhile, Siamese networks have attracted extensive attention in this field because of its balanced precision and speed. However, most of the Siamese network methods can only distinguish foreground from the non-semantic background. The fine-tuning and retraining of fully-convolutional Siamese networks for object tracking(SiamFC) can achieve higher precision under interferences, but the tracking accuracy is still not ideal, especially in the environment with more target interferences, dim light, and shadows. In this paper, we propose criss-cross attentional Siamese networks for object tracking (SiamCC). To solve the imbalance between foreground… More >

Sara A. Althubiti¹, José Escorcia-Gutierrez^2,3,*, Margarita Gamarra⁴, Roosvel Soto-Diaz⁵, Romany F. Mansour⁶, Fayadh Alenezi⁷

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2423-2439, 2022, DOI:10.32604/cmc.2022.028878

Abstract Smart healthcare has become a hot research topic due to the contemporary developments of Internet of Things (IoT), sensor technologies, cloud computing, and others. Besides, the latest advances of Artificial Intelligence (AI) tools find helpful for decision-making in innovative healthcare to diagnose several diseases. Ovarian Cancer (OC) is a kind of cancer that affects women’s ovaries, and it is tedious to identify OC at the primary stages with a high mortality rate. The OC data produced by the Internet of Medical Things (IoMT) devices can be utilized to differentiate OC. In this aspect, this paper introduces a new quantum black… More >

Mahmoud Ragab^1,2,3,*, Alaa F. Nahhas⁴

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2849-2864, 2022, DOI:10.32604/cmc.2022.028855

Abstract Earlier recognition of breast cancer is crucial to decrease the severity and optimize the survival rate. One of the commonly utilized imaging modalities for breast cancer is histopathological images. Since manual inspection of histopathological images is a challenging task, automated tools using deep learning (DL) and artificial intelligence (AI) approaches need to be designed. The latest advances of DL models help in accomplishing maximum image classification performance in several application areas. In this view, this study develops a Deep Transfer Learning with Rider Optimization Algorithm for Histopathological Classification of Breast Cancer (DTLRO-HCBC) technique. The proposed DTLRO-HCBC technique aims to categorize… More >

Ahmed ElShafee¹, Walid El-Shafai², Abdulaziz Alarifi^3,*, Mohammed Amoon³, Aman Singh⁴, Moustafa H. Aly⁵

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4157-4177, 2022, DOI:10.32604/cmc.2022.028847

Abstract Real-time disease prediction has emerged as the main focus of study in the field of computerized medicine. Intelligent disease identification framework can assist medical practitioners in diagnosing disease in a way that is reliable, consistent, and timely, successfully lowering mortality rates, particularly during endemics and pandemics. To prevent this pandemic’s rapid and widespread, it is vital to quickly identify, confine, and treat affected individuals. The need for auxiliary computer-aided diagnostic (CAD) systems has grown. Numerous recent studies have indicated that radiological pictures contained critical information regarding the COVID-19 virus. Utilizing advanced convolutional neural network (CNN) architectures in conjunction with radiological… More >

Kais Tissaoui^1,2,*, Sahbi Boubaker^3,4, Waleed Saud Alghassab¹, Taha Zaghdoudi^1,5, Jamel Azibi⁶

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4291-4309, 2022, DOI:10.32604/cmc.2022.028830

Abstract The application of optimization methods to prediction issues is a continually exploring field. In line with this, this paper investigates the connectedness between the infected cases of COVID-19 and US fear index from a forecasting perspective. The complex characteristics of implied volatility risk index such as non-linearity structure, time-varying and non-stationarity motivate us to apply a nonlinear polynomial Hammerstein model with known structure and unknown parameters. We use the Hybrid Particle Swarm Optimization (HPSO) tool to identify the model parameters of nonlinear polynomial Hammerstein model. Findings indicate that, following a nonlinear polynomial behaviour cascaded to an autoregressive with exogenous input… More >

Hafeez ur Rehman^1,*, Tariq Shah¹, Mohammad Mazyad Hazzazi², Ali Alshehri³, Bassfar Zaid⁴

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2913-2930, 2022, DOI:10.32604/cmc.2022.028765

Abstract Elliptic curves (ECs) are deemed one of the most solid structures against modern computational attacks because of their small key size and high security. In many well-known cryptosystems, the substitution box (S-box) is used as the only nonlinear portion of a security system. Recently, it has been shown that using dynamic S-boxes rather than static S-boxes increases the security of a cryptosystem. The conferred study also extends the practical application of ECs in designing the nonlinear components of block ciphers in symmetric key cryptography. In this study, instead of the Mordell elliptic curve (MEC) over the prime field, the Galois… More >

Xiaofang Qiu^1,2, Zhi Qin^1,2,*, Wunan Wan^1,2, Jinquan Zhang^1,2, Jinliang Guo^1,2, Shibin Zhang^1,2, Jinyue Xia³

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2577-2589, 2022, DOI:10.32604/cmc.2022.028757

Abstract In recent years, Blockchain is gaining prominence as a hot topic in academic research. However, the consensus mechanism of blockchain has been criticized in terms of energy consumption and performance. Although Proof-of-Authority (PoA) consensus mechanism, as a lightweight consensus mechanism, is more efficient than traditional Proof-of-Work (PoW) and Proof-of-Stake (PoS), it suffers from the problem of centralization. To this end, on account of analyzing the shortcomings of existing consensus mechanisms, this paper proposes a dynamic reputation-based consensus mechanism for blockchain. This scheme allows nodes with reputation value higher than a threshold apply to become a monitoring node, which can monitor… More >

Walid El-Shafai^1,2, Hayam A. Abd El-Hameed³, Ashraf A. M. Khalaf³, Naglaa F. Soliman⁴, Amel A. Alhussan^5,*, Fathi E. Abd El-Samie¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2713-2730, 2022, DOI:10.32604/cmc.2022.028739

Abstract Authentication of the digital image has much attention for the digital revolution. Digital image authentication can be verified with image watermarking and image encryption schemes. These schemes are widely used to protect images against forgery attacks, and they are useful for protecting copyright and rightful ownership. Depending on the desirable applications, several image encryption and watermarking schemes have been proposed to moderate this attention. This framework presents a new scheme that combines a Walsh Hadamard Transform (WHT)-based image watermarking scheme with an image encryption scheme based on Double Random Phase Encoding (DRPE). First, on the sender side, the secret medical… More >