Ping Ma^1,2, Quan Wang^1,2, Yiyang Chen^3,*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084488 - 13 August 2026

Abstract Connected vehicles operating in V2X-enabled intelligent transportation systems often perform repetitive trajectory tracking in repeated tasks. In practical applications, traffic conditions, communication quality, and sensing accuracy may vary from trial to trial. These variations induce time-varying dynamics across repeated runs and reduce the effectiveness of iterative learning control (ILC) schemes when fixed or inaccurately identified models are used. To address this issue, this paper proposes a parameter-estimation-based ILC framework for connected vehicles. Parameter estimation is integrated with a norm-optimal ILC design through an expectation-maximization strategy. The time-varying model parameters and the learning input are updated More >

Zulfiqar Ali, Azhar Mahmood^*, Shaheen Khatoon, Seyed Ali Ghorashi

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084386 - 13 August 2026

Abstract Smart city systems increasingly depend on data analytics and visualization to support informed and timely decision making in complex urban environments. However, existing middleware solutions predominantly focus on data acquisition and communication, while analytical processing and visualization are typically delegated to external applications, resulting in increased development complexity, reduced reusability, and fragmented system architectures. This study presents analytics and visualization-centric middleware named “Service-Oriented Middleware for Smart City Applications” (SOMSCA), in which these capabilities are embedded directly within the middleware layer. SOMSCA adopts a service-oriented approach, exposing analytics and visualization functionalities as reusable platform services, and… More >

Tian Liu¹, Xichao Wang^1,*, Jun Wang², Song Gao², Hang Gao¹, Yuxi Liu¹, Yitao Zhuang¹

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084300 - 13 August 2026

Abstract In unmanned aerial vehicle (UAV) flight behaviour understanding, the lack of a unified semantic representation for continuous multi-source temporal data makes it difficult to model flight events, behavioural relationships, and composite behaviours in an interpretable manner. To address this issue, this paper proposes a knowledge graph construction method for UAV flight behaviour understanding. The proposed method integrates atomic event detection, temporal knowledge modelling, and composite behaviour reasoning, thereby enabling the automatic transformation of continuous flight logs into structured behavioural knowledge. First, local statistical features, including smoothed velocity and robust climb rate, are extracted from multi-source… More >

Hsiao-Chun Han¹, Der-Chen Huang^2,*, Chin-Ling Chen^3,*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084216 - 13 August 2026

Abstract Semiconductors represent the most complex production activities and stand at the forefront of smart manufacturing. In particular, the yield of advanced processes is strongly influenced by coupling among engineering systems, material behavior, and computational infrastructure. Consequently, the integration of deep learning (DL) and digital twins has become essential for driving the next-generation transformation of smart manufacturing. However, existing reviews predominantly organize literature through algorithm-oriented taxonomies, while isolated AI paradigms alone remain insufficient to effectively capture system-level interactions and industry-driven technological evolution. Therefore, this study proposes a system-oriented and industry-driven review framework, termed the System-under-Industry Guided… More >

Peixuan Wang¹, Lingyun Yuan^1,2,*, Yi Xiang¹, Tianyu Xie^1,2, Haochen Bao¹, Kexin Wang^1,2

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.083887 - 13 August 2026

Abstract With the development of the Internet of Things (IoT), there is a rising demand for ciphertext retrieval. However, existing searchable encryption schemes mainly support single-modal retrieval, while current cross-modal searchable encryption methods often suffer from high computational overhead and lack reliable result verification. To address these problems, we propose a cross-modal searchable encryption scheme with result verification (VCMSE). First, we design a cross-modal hash extraction method that combines contrastive learning with a residual similarity matrix to generate encryption-friendly binary features with enhanced semantic consistency. Second, we designed a lightweight garbled circuit-based matching mechanism that enables More >

Kiran Saleem¹, Upinder Kaur^2,*, Abdulrahman Mohammed Alamoudi³, Mai Alduailij⁴, Ahmad Subhi Salem Mufleh⁵, Ateeq Ur Rehman^6,*, Salil Bharany⁷

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.083670 - 13 August 2026

Abstract Underwater Wireless Sensor Networks (UWSNs) are exceedingly critical for large-scale underwater applications, such as environmental monitoring, infrastructure inspection, target tracking, and marine surveillance. Nevertheless, network lifetime and communication reliability are severely constrained by harsh underwater acoustic conditions, limited battery power, large propagation delays, node mobility, and uneven energy consumption. In response to these issues, this study proposes a Climate-Aware Hybrid Clustering and Routing (CA-HCR-UWSN) framework to enable sustainable, long-term underwater monitoring. This work proposes a hybrid framework that combines Elephant Herding Optimization (EHO) with the Gravitational Search Algorithm (GSA) to provide an effective solution to… More >

Jixin Xu, Xingxin Li^*, Senlin Zhu, Qingqing Song

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.083290 - 13 August 2026

Abstract Complex procedural workflows in maintenance and parametric design often fail due to violated long-range dependencies, unsatisfied preconditions, and inconsistent parameter bindings. In such workflows, an early structural deviation may propagate silently and eventually induce global failure. Existing workflow auditing methods, particularly those based on large language models (LLMs) or sequence matching, often rely on implicit reasoning, exhibit unstable outputs, and provide limited support for reproducible error localization. To address these limitations, we propose a verification-centric auditing framework that couples an explicit typed dependency graph with an executable state transition system. The dependency graph represents data… More >

Kezhen Xie, Syed Mohd Zahid Syed Zainal Ariffin^*, Muhammad Izzad Ramli

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.083216 - 13 August 2026

Abstract Low-light infrared–visible image fusion remains challenging due to severe modality imbalance caused by visible-image degradation under insufficient illumination. In low-light conditions, visible images often suffer from luminance attenuation, blurred details, and amplified noise, whereas infrared images preserve stable structural information but lack texture representation. Existing fusion frameworks commonly perform feature interaction within a shared representation space, which may cause degraded visible responses to be progressively suppressed by dominant infrared structures during fusion. To address this issue, this paper proposes DSCAttFuseNet for low-light infrared–visible image fusion. The proposed framework adopts a structure–detail–luminance decoupled modeling strategy to… More >

Kui Hu, Peng Zhang^*, Xiang Xiao, Yuan Xu, Yunhuang Zhang, Yuan Yuan, Zhiyuan Feng

Energy Engineering, Vol.123, No.9, 2026, DOI:10.32604/ee.2026.078340 - 06 August 2026

Abstract The rapid development of gas-cooled microreactors (GMRs) for remote and modular power supply necessitates highly efficient and autonomous core power monitoring systems. Traditional monitoring systems, such as those deployed in commercial power plants, rely on dense in-core instrumentation, whereas due to the limitation of space and simplicity in hardware designs, only sparse ex-core detectors are employed in microreactor designs. To address this challenge, this study proposes an advanced online power reconstruction approach based on the higher-order harmonic expansion. A dedicated higher-order harmonic calculation module was developed within a multi-group diffusion framework, capable of executing rapid… More >

Longbin Lin¹, Hua Hu^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.7, 2026, DOI:10.32604/fdmp.2026.085657 - 31 July 2026

Abstract Seepage-induced rheological deformation represents a critical factor governing the long-term stability of coastal soft-soil excavations subjected to intense rainfall infiltration and groundwater fluctuations. This study elucidates the individual and interactive effects of seepage pressure and seepage duration on the time-dependent deformation behavior of undisturbed mucky soft soil containing medium-fine sand, collected from a deep foundation pit. A comprehensive experimental campaign based on triaxial seepage-shear rheological testing for a confining pressure of 180 kPa is presented, encompassing sixteen combinations of seepage pressure and duration together with a directly measured zero-seepage reference condition. Three replicate specimens are… More >