Xiusen Wang^1,*, Zheng Fang², Jie Chen^2,*

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.088952 - 15 September 2026

Abstract Complex networks in cyber–physical, transportation, and information infrastructures operate under topology variations, unmeasured disturbances, and limited actuation. This paper proposes robust disturbance-aware data-driven decision control (R-D3C), which couples a sliding-window graph-regularized estimator, disturbance-envelope adaptation, sparse intervention allocation, receding-horizon optimization, and a robust safety projection. The theory directly bounds the dynamic prediction regret of the implemented sliding-window estimator. A checkable sufficient condition for safety-filter feasibility is coupled with an explicit slack-and-backup fallback when the strict projection is infeasible. Practical input-to-state stability and sparse-allocation risk reduction are established. The nominal comparison uses 30 paired runs with standard More >

Zhihao Liu^1,2, Yi Zhang³, Wei Zhang^1,2, Jian Wang⁴, Huiling Shi^1,2, Xiaolong Wang^1,2,*

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.088018 - 15 September 2026

Abstract Mobile edge services require deterministic communication across Time-Sensitive Networking (TSN) and 5G access, where the standardized integration architecture exposes the 5G System (5GS) to the TSN controller as a logical bridge. We study dynamic admission of time-triggered (TT) flows using reported 5GS bridge delay and TSN-to-5GS Quality of Service (QoS) mapping in route selection and Gate Control List (GCL) scheduling. Arrivals and departures can split available transmission time into noncontiguous windows. Online insertion preserves admitted schedules but may reduce subsequent schedulability, whereas full recomputation can restore schedulability but changes many routes and GCL entries, complicating… More >

Long Yu^1,2,3, Ma Zhu^1,2,3,*, Xu Wang^1,2,3, Yang Pei^1,2,3, Chunfang Yang^1,2,3

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.087636 - 15 September 2026

Abstract Cross-view geo-localization (CVGL) estimates the location of a street-level image by retrieving its matching GPS-tagged satellite tile. Semi-supervised methods reduce the need for dense annotations by mining pseudo labels, but most of them keep only one positive reference for each query. In real-world galleries, several overlapping satellite tiles may cover the same ground location. As a result, valid matches can be discarded as negatives, which gives the model conflicting supervision. To address this problem, we propose DMP-Geo, a semi-supervised cross-view geo-localization method that mines multiple positives for each query from unlabeled data. A bird’s-eye fusion More >

Mohammed Alonazi¹, Muhammad Adeel Ahmed Tahir², Adnan Ahmed Rafique², Maha Abdelhaq³, Raed Alsaqour⁴, Ahmad Jalal^5,6, Jeongmin Park^7,*

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.086550 - 15 September 2026

Abstract Accurate vehicle detection, tracking, and counting are fundamental components of Intelligent Transportation Systems (ITS) and urban traffic surveillance. However, real-world deployment remains challenging due to domain shifts, illumination variations, occlusions, dense traffic conditions, and heterogeneous data distributions. Existing studies often address detection, tracking, and counting as independent tasks, resulting in limited cross-domain generalization and inconsistent performance in complex traffic environments. To overcome these limitations, this paper proposes a unified cross-domain framework that jointly integrates vehicle detection, tracking, and lane-aware counting within a single intelligent traffic analytics pipeline. The proposed framework begins with image enhancement using… More >

Shengxuan Dong, Xiongwei Li^*

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.086535 - 15 September 2026

Abstract To address the conflict between navigation performance and safety constraints in safe reinforcement learning, this paper proposes Dual Stream-Analytic Hierarchy Process-Safe Soft Actor (DS-AHP-SAC), a safe soft actor-critic algorithm based on a dual-stream Q-network and dynamic Analytic Hierarchy Process (AHP) stratified experience replay. The algorithm achieves a balance between reward maximization and constraint satisfaction through three synergistic designs: (1) decoupling the Q-network into independent navigation and safety value streams to eliminate gradient interference at the Critic level and mitigate gradient competition at the Actor level; (2) constructing a three-criterion dynamic sampling strategy based on AHP, More >

Jincheng Cai¹, Li Feng^1,*, Ni Zhao²

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.086183 - 15 September 2026

Abstract Federated Variational Autoencoders (VAEs) keep interaction data local, but existing federated VAE recommenders typically apply uniform KL regularization and do not adapt dimension-wise penalties to unreliable posteriors in sparse interaction scenarios. We propose $\alpha$-FedVAE, which uses a detached, clipped normalized signal-to-noise ratio as a local confidence gate for each KL dimension of a fused user posterior, without extra communication. Across MovieLens-100K, MovieLens-1M, and Amazon Video, $\alpha$-FedVAE improves mean HR@20 by 7.8%–55.3% and NDCG@20 by 8.0%–65.8% over FedDAE. These results indicate that $\alpha$-FedVAE improves personalized recommendation under sparse and decentralized settings while preserving the communication More >

Shigan Ding^1,2, Zihe Qin^1,3,*, Feng Zhang^1,3, Mao Zheng², Bowen Lin²

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.086097 - 15 September 2026

Abstract To address the challenge of precise station-keeping for underactuated unmanned surface vehicles (USVs) in unknown current environments, our team previously proposed a solution based on a “virtual anchoring” method. However, field tests revealed that the inherent “virtual anchor line” constraint limits positioning accuracy. This work introduces a novel control strategy to overcome the aforementioned issue, which enables accurate unmanned surface vehicle (USV) station-keeping by significantly reducing the distance constraint inherent to traditional virtual anchoring. The core innovation lies in a Dynamic Virtual Guide-Point, whose position is updated based on a real-time estimate of the current… More >

Hassaan Idrees^1,*, Pattabhi Ramaiah Budarapu², Marco Paggi^1,*

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.085634 - 15 September 2026

Abstract Hail impacts on photovoltaic laminates generate strongly nonlinear contact forces whose polynomial restoring form and coefficients govern the resulting damage pattern. Predicting the dynamic response across a range of impact velocities, and inferring substrate properties from post-event vibration measurements, are two tasks that classical time-integration schemes do not address in a unified manner. This work develops a physics-informed neural network (PINN) framework that handles both. For the forward problem, the network is conditioned on the initial velocity and trained simultaneously at four representative hail-impact speeds, i.e., $v_0\in \{2,3,4,6\}$ m/s, so that it learns… More >

Yanyu Zhu¹, Jie Jin^2,*, Lv Zhao^2,3, Fei Yu⁴

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.085516 - 15 September 2026

Abstract To address the issues of multi-neuron architectures, high parameter redundancy, and complex hardware implementation in existing memristive Hopfield neural networks (MHNN) for image encryption, a simple structure dual-neuron memristive Hopfield neural network (DNMHNN) modulated by multifrequency square waves is proposed in this study. The proposed DNMHNN model consists of only two neurons and one memristor, and by introducing dual-frequency square-wave external excitation into the memristor, the dynamical behavior of the DNMHNN model can be flexibly regulated. The simulation results verify that the proposed DNMHNN model can generate stable chaotic behavior over a wide parameter range.… More >

Hui Xu, Ruiqi Qu^*, Xinlu Zong

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.084624 - 15 September 2026

Abstract With the rapid growth of the Internet of Things, intrusion detection systems face severe challenges in processing massive, high-dimensional, and redundant network traffic while satisfying strict low-latency and high-efficiency requirements. To address these challenges,this paper improves the original artificial lemming algorithm (ALA) and proposes a dynamic multi-subpopulation artificial lemming algorithm (DMSALA) for feature selection, and then constructs an intrusion detection framework for IoT based on DMSALA. The proposed DMSALA introduces an adaptive clustering-based dynamic multi-subpopulation structure to alleviate premature convergence during the search process. In addition, a cosine-based nonlinear weighting strategy is designed to achieve… More >