Raza Hasan^*, Shakeel Ahmad, Ismet Gocer, Zakirul Bhuiyan

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079708 - 08 May 2026

Abstract Maritime Domain Awareness (MDA) is critical for global security and economic stability, yet it is increasingly challenged by sophisticated adversarial tactics such as signal spoofing and “dark vessel” activities. Traditional surveillance systems, often reliant on single-sensor modalities, are ill-equipped to handle these deceptive behaviors. To address this, we propose the Multimodal Attention-based Fusion Transformer (MAFT), a novel deep learning architecture that integrates four distinct data modalities—Aerial imagery, Synthetic Aperture Radar (SAR), acoustic signatures, and Automatic Identification System (AIS) data—to achieve robust and interpretable maritime anomaly detection. A key contribution of our work is a principled… More > Graphic Abstract

Qian Rong¹, Lu Zhang², Ling Yuan^1,*, Zhong Yang³, Guohui Li³

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.075102 - 08 May 2026

Abstract Federated learning (FL) enables collaborative model training across decentralized clients without sharing raw data, thereby preserving privacy. However, in real-world FL deployments—such as sensor-based activity recognition, wearable health monitoring, and industrial Internet of Things, where local training data often suffer from heterogeneous noisy labels due to diverse collection environments, sensor limitations, and labeling errors. These noisy labels, typically distributed unevenly across clients due to differences in client-side annotation, exacerbate Non-Independent and Identically Distributed (non-IID) data issues, leading to biased updates, unstable convergence, and degraded global model performance. Accurate estimation of client-specific noise rates is therefore… More >

Taher Alzahrani¹, Saima Rashid^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.076957 - 27 April 2026

Abstract Air pollution poses a serious public health threat in developing countries such as Pakistan, where rapid urbanization and industrialization have intensified atmospheric contamination. Although mobile sensing deployed on public transportation expands spatial coverage beyond fixed monitoring stations, accurate high-resolution pollution mapping remains constrained by sparse observations, computational burden, neglected pollutant interactions, and limited interpretability. To address these challenges, this study proposes a unified physics-informed deep learning framework for fine-grained air pollution map reconstruction and joint multi-pollutant estimation. The framework integrates mobile and stationary monitoring data with atmospheric dispersion principles to enhance physical consistency under limited… More >

Taimoor Hassan¹, Ibrar Hussain^1,*, Hafiz Mahfooz Ul Haque², Hamid Turab Mirza³, Muhammad Nadeem Ali⁴, Byung-Seo Kim^4,*, Changheun Oh⁴

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077510 - 09 April 2026

Abstract The expeditious proliferation of the smart computing paradigm has a remarkable upsurge towards Artificial Intelligence (AI) assistive reasoning with the incorporation of context-awareness. Context-awareness plays a significant role in fulfilling users’ needs whenever and wherever needed. Context-aware systems acquire contextual information from sensors/embedded sensors using smart gadgets and/or systems, perform reasoning using reinforcement learning (RL) or other reasoning techniques, and then adapt behavior. The core intention of using an RL-based reasoning strategy is to train agents to take the right actions at the right time and in the right place. Generally, agents are rewarded for… More >

Suman Sukhavasi, Thinagaran Perumal^*, Norwati Mustapha, Razali Yaakob

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.075613 - 12 March 2026

Abstract The Internet of Things (IoT) ecosystem is inherently heterogeneous, comprising diverse devices that must interoperate seamlessly to enable federated message and data exchange. However, as the number of service requests grows, existing approaches suffer from increased discovery time and degraded Quality of Service (QoS). Moreover, the massive data generated by heterogeneous IoT devices often contain redundancy and noise, posing challenges to efficient data management. To address these issues, this paper proposes a lightweight ontology-based architecture that enhances service discovery and QoS-aware semantic data management. The architecture employs Modified-Ordered Points to Identify the Clustering Structure (M-OPTICS)… More >

Jinwei Mao^1,2, Wang Luo^1,2,*, Jiangtao Xu³, Daohua Zhu³, Wei Liang³, Zhechen Huang³, Bao Feng^1,2, Shuang Yang^1,2

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.072505 - 12 March 2026

Abstract With the rapid development of power Internet of Things (IoT) scenarios such as smart factories and smart homes, numerous intelligent terminal devices and real-time interactive applications impose higher demands on computing latency and resource supply efficiency. Multi-access edge computing technology deploys cloud computing capabilities at the network edge; constructs distributed computing nodes and multi-access systems and offers infrastructure support for services with low latency and high reliability. Existing research relies on a strong assumption that the environmental state is fully observable and fails to thoroughly consider the continuous time-varying features of edge server load fluctuations,… More >

Chun-Chieh Hu^1,*, Shuhan Zheng^1,2, Youjia Lin^1,2

International Journal of Mental Health Promotion, Vol.28, No.2, 2026, DOI:10.32604/ijmhp.2025.073744 - 27 February 2026

Abstract Objectives: In recent years, mental health has emerged as a pressing public health concern in China, driven by mounting societal pressures and fast-paced urban lifestyles. Physical activity, a well-established means of enhancing psychological well-being, has received growing scholarly and policy attention. This study uses panel data from the 2020 and 2022 waves of the China Family Panel Studies (CFPS) to examine the impact of exercise frequency on mental health (with indicators such as CESD-8 depression scores) among college students and young employees, thereby providing empirical support for targeted mental health interventions. Methods: This study examines the… More >

Adnan Ashique¹, Nehad Ali Shah¹, Usman Afzal¹, Yazen Alawaideh², Sohaib Abdal³, Jae Dong Chung^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.2, 2026, DOI:10.32604/cmes.2025.073292 - 26 February 2026

Abstract There is a need for accurate prediction of heat and mass transfer in aerodynamically designed, non-Newtonian nanofluids across aerodynamically designed, high-flux biomedical micro-devices for thermal management and reactive coating processes, but existing work is not uncharacteristically remiss regarding viscoelasticity, radiative heating, viscous dissipation, and homogeneous–heterogeneous reactions within a single scheme that is calibrated. This research investigates the flow of Williamson nanofluid across a dynamically wedged surface under conditions that include viscous dissipation, thermal radiation, and homogeneous-heterogeneous reactions. The paper develops a detailed mathematical approach that utilizes boundary layers to transform partial differential equations into ordinary… More >

Borja Bordel Sánchez^*, Ramón Alcarria, Tomás Robles

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.2, 2026, DOI:10.32604/cmes.2025.072603 - 26 February 2026

Abstract In this paper, we propose a new privacy-aware transmission scheduling algorithm for 6G ad hoc networks. This system enables end nodes to select the optimum time and scheme to transmit private data safely. In 6G dynamic heterogeneous infrastructures, unstable links and non-uniform hardware capabilities create critical issues regarding security and privacy. Traditional protocols are often too computationally heavy to allow 6G services to achieve their expected Quality-of-Service (QoS). As the transport network is built of ad hoc nodes, there is no guarantee about their trustworthiness or behavior, and transversal functionalities are delegated to the extreme nodes. However, More >

Huihui Zhu¹, Fei Tang^2,*, Chunhua Jin³, Ping Wang¹

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073550 - 10 February 2026

Abstract The ubiquitous adoption of mobile devices as essential platforms for sensitive data transmission has heightened the demand for secure client-server communication. Although various authentication and key agreement protocols have been developed, current approaches are constrained by homogeneous cryptosystem frameworks, namely public key infrastructure (PKI), identity-based cryptography (IBC), or certificateless cryptography (CLC), each presenting limitations in client-server architectures. Specifically, PKI incurs certificate management overhead, IBC introduces key escrow risks, and CLC encounters cross-system interoperability challenges. To overcome these shortcomings, this study introduces a heterogeneous signcryption-based authentication and key agreement protocol that synergistically integrates IBC for client More >