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  • Open Access

    ARTICLE

    Siphon-Based Divide-and-Conquer Policy for Enforcing Liveness on Petri Net Models of FMS Suffering from Deadlocks or Livelocks

    Murat Uzam1, Bernard Berthomieu2, Wei Wei3,*, Yufeng Chen3, Mohammed El-Meligy4,5, Mohamed Abdel Fattah Sharaf 6

    CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-30, 2026, DOI:10.32604/cmc.2025.069502 - 10 November 2025

    Abstract A novel siphon-based divide-and-conquer (SbDaC) policy is presented in this paper for the synthesis of Petri net (PN) based liveness-enforcing supervisors (LES) for flexible manufacturing systems (FMS) prone to deadlocks or livelocks. The proposed method takes an uncontrolled and bounded PN model (UPNM) of the FMS. Firstly, the reduced PNM (RPNM) is obtained from the UPNM by using PN reduction rules to reduce the computation burden. Then, the set of strict minimal siphons (SMSs) of the RPNM is computed. Next, the complementary set of SMSs is computed from the set of SMSs. By the union… More >

  • Open Access

    ARTICLE

    The Impact of EU Immigration Law and Policy on Immigrants’ Subjective Well-Being

    Quan Cheng, Yun Lin, Hui Yu*

    International Journal of Mental Health Promotion, Vol.27, No.12, pp. 1961-1988, 2025, DOI:10.32604/ijmhp.2025.072232 - 31 December 2025

    Abstract Background: Against the backdrop of the complex interplay between global migration flows and the European Union’s governance system, immigrants’ subjective well-being (SWB) has become a crucial indicator for assessing both their social integration and the effectiveness of integration policies. However, few studies have systematically linked immigration law and policy to SWB through a structured framework of human needs. This study aims to assess how European Union (EU) immigration policies influence immigrants’ SWB by facilitating the fulfillment of hierarchical needs based on Maslow’s theory. Methods: Using data from the European Social Survey (ESS, 2010–2023), this study analyzed… More >

  • Open Access

    ARTICLE

    Multi-Domain Network Intent Policy Enforcement

    Ana Hermosilla1,2,*, Pedro Martinez-Julia3, Diego R. Lopez4, Antonio F. Skarmeta1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4279-4316, 2025, DOI:10.32604/cmes.2025.072607 - 23 December 2025

    Abstract In this study, we analyzed the processes involved in the resolution and enforcement of multi-domain network intent policies for intent-based networking (IBN). Previous studies on IBN analyzed the basis of the network intent resolution processes. These processes produce the artifacts required by network intent policy enforcement. Thus, we continued such studies with the inclusion of network intent policy enforcement in the analysis, for which we constructed a model that predicts the accuracy of a multi-domain network intent policy enforcement system. We validated the model by designing a new multi-domain network intent policy enforcement system, and… More >

  • Open Access

    ARTICLE

    Optimization Scheduling of Hydrogen-Coupled Electro-Heat-Gas Integrated Energy System Based on Generative Adversarial Imitation Learning

    Baiyue Song1, Chenxi Zhang2, Wei Zhang2,*, Leiyu Wan2

    Energy Engineering, Vol.122, No.12, pp. 4919-4945, 2025, DOI:10.32604/ee.2025.068971 - 27 November 2025

    Abstract Hydrogen energy is a crucial support for China’s low-carbon energy transition. With the large-scale integration of renewable energy, the combination of hydrogen and integrated energy systems has become one of the most promising directions of development. This paper proposes an optimized scheduling model for a hydrogen-coupled electro-heat-gas integrated energy system (HCEHG-IES) using generative adversarial imitation learning (GAIL). The model aims to enhance renewable-energy absorption, reduce carbon emissions, and improve grid-regulation flexibility. First, the optimal scheduling problem of HCEHG-IES under uncertainty is modeled as a Markov decision process (MDP). To overcome the limitations of conventional deep… More >

  • Open Access

    ARTICLE

    A Dynamic Deceptive Defense Framework for Zero-Day Attacks in IIoT: Integrating Stackelberg Game and Multi-Agent Distributed Deep Deterministic Policy Gradient

    Shigen Shen1,2, Xiaojun Ji1,*, Yimeng Liu1

    CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3997-4021, 2025, DOI:10.32604/cmc.2025.069332 - 23 September 2025

    Abstract The Industrial Internet of Things (IIoT) is increasingly vulnerable to sophisticated cyber threats, particularly zero-day attacks that exploit unknown vulnerabilities and evade traditional security measures. To address this critical challenge, this paper proposes a dynamic defense framework named Zero-day-aware Stackelberg Game-based Multi-Agent Distributed Deep Deterministic Policy Gradient (ZSG-MAD3PG). The framework integrates Stackelberg game modeling with the Multi-Agent Distributed Deep Deterministic Policy Gradient (MAD3PG) algorithm and incorporates defensive deception (DD) strategies to achieve adaptive and efficient protection. While conventional methods typically incur considerable resource overhead and exhibit higher latency due to static or rigid defensive mechanisms,… More >

  • Open Access

    ARTICLE

    Evaluating Geographical Variations of Road Traffic Accidents in Matara, Sri Lanka: A Geospatial Perspective to Policy Decisions

    Buddhini Chaturika Jayasinghe1, Neel Chaminda Withanage1, Prabuddh Kumar Mishra2,*

    Revue Internationale de Géomatique, Vol.34, pp. 707-729, 2025, DOI:10.32604/rig.2025.067395 - 12 September 2025

    Abstract Road Traffic Accidents (RTAs) pose significant threats to public safety and urban infrastructure. While numerous studies have addressed this issue in other countries, there remains a notable gap in localized RTA research in Sri Lanka. In this context, the present study investigates the spatial and temporal patterns of RTAs in the Matara urban area in 2023, with the goal of supporting evidence-based policy interventions. A suite of GIS-based spatial analysis techniques including hotspot analysis, kernel density estimation, GiZscore mapping, and spatial autocorrelation (Moran’s I = 0.36, p < 0.01) was applied to examine the distribution and… More >

  • Open Access

    ARTICLE

    Innovative Aczel Alsina Group Overlap Functions for AI-Based Criminal Justice Policy Selection under Intuitionistic Fuzzy Set

    Ikhtesham Ullah1, Muhammad Sajjad Ali Khan2, Fawad Hussain1, Madad Khan3, Kamran4,*, Ioan-Lucian Popa5,6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2123-2164, 2025, DOI:10.32604/cmes.2025.064832 - 31 August 2025

    Abstract Multi-criteria decision-making (MCDM) is essential for handling complex decision problems under uncertainty, especially in fields such as criminal justice, healthcare, and environmental management. Traditional fuzzy MCDM techniques have failed to deal with problems where uncertainty or vagueness is involved. To address this issue, we propose a novel framework that integrates group and overlap functions with Aczel-Alsina (AA) operational laws in the intuitionistic fuzzy set (IFS) environment. Overlap functions capture the degree to which two inputs share common features and are used to find how closely two values or criteria match in uncertain environments, while the… More >

  • Open Access

    ARTICLE

    Dynamic Decoupling-Driven Cooperative Pursuit for Multi-UAV Systems: A Multi-Agent Reinforcement Learning Policy Optimization Approach

    Lei Lei1, Chengfu Wu2,*, Huaimin Chen2

    CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1339-1363, 2025, DOI:10.32604/cmc.2025.067117 - 29 August 2025

    Abstract This paper proposes a Multi-Agent Attention Proximal Policy Optimization (MA2PPO) algorithm aiming at the problems such as credit assignment, low collaboration efficiency and weak strategy generalization ability existing in the cooperative pursuit tasks of multiple unmanned aerial vehicles (UAVs). Traditional algorithms often fail to effectively identify critical cooperative relationships in such tasks, leading to low capture efficiency and a significant decline in performance when the scale expands. To tackle these issues, based on the proximal policy optimization (PPO) algorithm, MA2PPO adopts the centralized training with decentralized execution (CTDE) framework and introduces a dynamic decoupling mechanism,… More >

  • Open Access

    ARTICLE

    Simultaneous Depth and Heading Control for Autonomous Underwater Vehicle Docking Maneuvers Using Deep Reinforcement Learning within a Digital Twin System

    Yu-Hsien Lin*, Po-Cheng Chuang, Joyce Yi-Tzu Huang

    CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4907-4948, 2025, DOI:10.32604/cmc.2025.065995 - 30 July 2025

    Abstract This study proposes an automatic control system for Autonomous Underwater Vehicle (AUV) docking, utilizing a digital twin (DT) environment based on the HoloOcean platform, which integrates six-degree-of-freedom (6-DOF) motion equations and hydrodynamic coefficients to create a realistic simulation. Although conventional model-based and visual servoing approaches often struggle in dynamic underwater environments due to limited adaptability and extensive parameter tuning requirements, deep reinforcement learning (DRL) offers a promising alternative. In the positioning stage, the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm is employed for synchronized depth and heading control, which offers stable training, reduced overestimation… More >

  • Open Access

    ARTICLE

    Several Attacks on Attribute-Based Encryption Schemes

    Phi Thuong Le1, Huy Quoc Le2, Viet Cuong Trinh1,*

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4741-4756, 2025, DOI:10.32604/cmc.2025.064486 - 19 May 2025

    Abstract Attribute-based encryption () is a cryptographic framework that provides flexible access control by allowing encryption based on user attributes. is widely applied in cloud storage, file sharing, e-Health, and digital rights management. schemes rely on hard cryptographic assumptions such as pairings and others (pairing-free) to ensure their security against external and internal attacks. Internal attacks are carried out by authorized users who misuse their access to compromise security with potentially malicious intent. One common internal attack is the attribute collusion attack, in which users with different attribute keys collaborate to decrypt data they could not… More >

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