Hongwei Wu^*, Guojian Li, Hanyun Zhang, Zi Ye, Chao Ma

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071008 - 12 January 2026

Abstract Federated Learning (FL) protects data privacy through a distributed training mechanism, yet its decentralized nature also introduces new security vulnerabilities. Backdoor attacks inject malicious triggers into the global model through compromised updates, posing significant threats to model integrity and becoming a key focus in FL security. Existing backdoor attack methods typically embed triggers directly into original images and consider only data heterogeneity, resulting in limited stealth and adaptability. To address the heterogeneity of malicious client devices, this paper proposes a novel backdoor attack method named Capability-Adaptive Shadow Backdoor Attack (CASBA). By incorporating measurements of clients’… More >

Muhammad Adil¹, Nadeem Javaid^1,*, Imran Ahmed², Abrar Ahmed³, Nabil Alrajeh^4,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-20, 2026, DOI:10.32604/cmc.2025.071215 - 10 November 2025

Abstract Heart disease remains a leading cause of mortality worldwide, emphasizing the urgent need for reliable and interpretable predictive models to support early diagnosis and timely intervention. However, existing Deep Learning (DL) approaches often face several limitations, including inefficient feature extraction, class imbalance, suboptimal classification performance, and limited interpretability, which collectively hinder their deployment in clinical settings. To address these challenges, we propose a novel DL framework for heart disease prediction that integrates a comprehensive preprocessing pipeline with an advanced classification architecture. The preprocessing stage involves label encoding and feature scaling. To address the issue of… More >

Byeongjun Kim^1,#, Seung-Hun Lee^2,#, Won-Du Chang^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1237-1252, 2025, DOI:10.32604/cmes.2025.073530 - 26 November 2025

Abstract Side-scan sonar (SSS) is essential for acquiring high-resolution seafloor images over large areas, facilitating the identification of subsea objects. However, military security restrictions and the scarcity of subsea targets limit the availability of SSS data, posing challenges for Automatic Target Recognition (ATR) research. This paper presents an approach that uses Cycle-Consistent Generative Adversarial Networks (CycleGAN) to augment SSS images of key subsea objects, such as shipwrecks, aircraft, and drowning victims. The process begins by constructing 3D models to generate rendered images with realistic shadows from multiple angles. To enhance image quality, a shadow extractor and More >

Victor Kozlov^1,2,*, Yuriy Litvinenko¹, Andrey Shmakov^1,2, Alexander Pavlenko¹

Frontiers in Heat and Mass Transfer, Vol.22, No.6, pp. 1695-1717, 2024, DOI:10.32604/fhmt.2024.056866 - 19 December 2024

Abstract The objective of the present study is an experimental investigation of diffusion combustion of round microjets, i.e., mixtures of hydrogen with methane, helium, and nitrogen. It is found that the evolution of burning microjets is associated with generation of a “bottleneck flame region” close to the nozzle exit, as it was observed earlier during hydrogen combustion. Combustion of a mixture of hydrogen and methane with increasing flow velocity occurs with the transformation of the torch. At first, a torch stabilized on the nozzle is observed, then it is divided into a stabilized part in contact… More >

Cheng Yang^1,2, Miaojia Lou^2,*, Xiaoyu Chen^1,2, Zixuan Ren¹

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4107-4126, 2024, DOI:10.32604/cmc.2024.049183 - 20 June 2024

Abstract Chinese shadow puppetry has been recognized as a world intangible cultural heritage. However, it faces substantial challenges in its preservation and advancement due to the intricate and labor-intensive nature of crafting shadow puppets. To ensure the inheritance and development of this cultural heritage, it is imperative to enable traditional art to flourish in the digital era. This paper presents an Interactive Collaborative Creation System for shadow puppets, designed to facilitate the creation of high-quality shadow puppet images with greater ease. The system comprises four key functions: Image contour extraction, intelligent reference recommendation, generation network, and… More >

Kalpesh Jadav¹, Vishal Sorathiya^1,*, Walid El-Shafai², Torki Altameem³, Moustafa H. Aly⁴, Vipul Vekariya⁵, Kawsar Ahmed⁶, Francis M. Bui⁶

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2009-2030, 2023, DOI:10.32604/cmc.2023.043168 - 29 November 2023

Abstract Shadow extraction and elimination is essential for intelligent transportation systems (ITS) in vehicle tracking application. The shadow is the source of error for vehicle detection, which causes misclassification of vehicles and a high false alarm rate in the research of vehicle counting, vehicle detection, vehicle tracking, and classification. Most of the existing research is on shadow extraction of moving vehicles in high intensity and on standard datasets, but the process of extracting shadows from moving vehicles in low light of real scenes is difficult. The real scenes of vehicles dataset are generated by self on… More >

Lilan Zou¹, Bo Liang¹, Xu Cheng², Shufa Li^1,*, Cong Lin^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2641-2659, 2023, DOI:10.32604/cmes.2023.028037 - 03 August 2023

Abstract Target signal acquisition and detection based on sonar images is a challenging task due to the complex underwater environment. In order to solve the problem that some semantic information in sonar images is lost and model detection performance is degraded due to the complex imaging environment, we proposed a more effective and robust target detection framework based on deep learning, which can make full use of the acoustic shadow information in the forward-looking sonar images to assist underwater target detection. Firstly, the weighted box fusion method is adopted to generate a fusion box by weighted… More > Graphic Abstract

CH. Mohan Sai Kumar^*, R. S. Valarmathi

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1711-1728, 2023, DOI:10.32604/iasc.2023.038113 - 21 June 2023

Abstract Image dehazing is a rapidly progressing research concept to enhance image contrast and resolution in computer vision applications. Owing to severe air dispersion, fog, and haze over the environment, hazy images pose specific challenges during information retrieval. With the advances in the learning theory, most of the learning-based techniques, in particular, deep neural networks are used for single-image dehazing. The existing approaches are extremely computationally complex, and the dehazed images are suffered from color distortion caused by the over-saturation and pseudo-shadow phenomenon. However, the slow convergence rate during training and haze residual is the two… More >

Yajing Zhang¹, Chaoyang Song², Zhiguo Li^2,*

Energy Engineering, Vol.120, No.2, pp. 501-510, 2023, DOI:10.32604/ee.2022.021423 - 28 November 2022

Abstract To overcome the problems of natural decreases in power quality, and to eliminate wind speed fluctuation due to wind shear and tower shadow effect arising from wind turbine structural parameters, an improved prediction model accounting for the dual effect of wind shear and tower shadow is, in this paper, built. Compared to the conventional prediction model, the proposed model contains a new constraint condition, which makes the disturbance term caused by the tower shadow effect always negative so that the prediction result is closer to the actual situation. Furthermore, wind turbine structural parameters such as More > Graphic Abstract

Mesfer Al Duhayyim^1,*, Mohammed Maray², Ayman Qahmash², Fatma S. Alrayes³, Nuha Alshuqayran⁴, Jaber S. Alzahrani⁵, Mohammed Alghamdi^2,6, Abdullah Mohamed⁷

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3133-3149, 2023, DOI:10.32604/cmc.2023.032740 - 31 October 2022

Abstract Nowadays, security plays an important role in Internet of Things (IoT) environment especially in medical services’ domains like disease prediction and medical data storage. In healthcare sector, huge volumes of data are generated on a daily basis, owing to the involvement of advanced health care devices. In general terms, health care images are highly sensitive to alterations due to which any modifications in its content can result in faulty diagnosis. At the same time, it is also significant to maintain the delicate contents of health care images during reconstruction stage. Therefore, an encryption system is… More >