Ans D. Alghamdi^*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-35, 2026, DOI:10.32604/cmc.2025.071210 - 09 December 2025

Abstract Multimodal dialogue systems often fail to maintain coherent reasoning over extended conversations and suffer from hallucination due to limited context modeling capabilities. Current approaches struggle with cross-modal alignment, temporal consistency, and robust handling of noisy or incomplete inputs across multiple modalities. We propose MultiAgent-Chain of Thought (CoT), a novel multi-agent chain-of-thought reasoning framework where specialized agents for text, vision, and speech modalities collaboratively construct shared reasoning traces through inter-agent message passing and consensus voting mechanisms. Our architecture incorporates self-reflection modules, conflict resolution protocols, and dynamic rationale alignment to enhance consistency, factual accuracy, and user engagement. More >

Zeyu Chen¹, Jian Sun^2,*, Zhengda Huan¹, Ziyi Zhang¹

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-17, 2026, DOI:10.32604/cmc.2025.071182 - 09 December 2025

Abstract To address the issues of poor adaptability in resource allocation and low multi-agent cooperation efficiency in Joint Radar and Communication (JRC) systems under dynamic environments, an intelligent optimization framework integrating Deep Reinforcement Learning (DRL) and Graph Neural Network (GNN) is proposed. This framework models resource allocation as a Partially Observable Markov Game (POMG), designs a weighted reward function to balance radar and communication efficiencies, adopts the Multi-Agent Proximal Policy Optimization (MAPPO) framework, and integrates Graph Convolutional Networks (GCN) and Graph Sample and Aggregate (GraphSAGE) to optimize information interaction. Simulations show that, compared with traditional methods More >

Maryan Rizinski^1,2,*, Dimitar Trajanov^1,2

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-34, 2026, DOI:10.32604/cmc.2025.069678 - 10 November 2025

Abstract Artificial intelligence (AI) is reshaping financial systems and services, as intelligent AI agents increasingly form the foundation of autonomous, goal-driven systems capable of reasoning, learning, and action. This review synthesizes recent research and developments in the application of AI agents across core financial domains. Specifically, it covers the deployment of agent-based AI in algorithmic trading, fraud detection, credit risk assessment, robo-advisory, and regulatory compliance (RegTech). The review focuses on advanced agent-based methodologies, including reinforcement learning, multi-agent systems, and autonomous decision-making frameworks, particularly those leveraging large language models (LLMs), contrasting these with traditional AI or purely… More >

Haihao He^1,2, Xianzhou Dong^1,*, Shuangshuang Wang¹, Chengzhang Zhu¹, Xiaotong Zhao^1,2

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-23, 2026, DOI:10.32604/cmc.2025.069513 - 10 November 2025

Abstract Clock synchronization has important applications in multi-agent collaboration (such as drone light shows, intelligent transportation systems, and game AI), group decision-making, and emergency rescue operations. Synchronization method based on pulse-coupled oscillators (PCOs) provides an effective solution for clock synchronization in wireless networks. However, the existing clock synchronization algorithms in multi-agent ad hoc networks are difficult to meet the requirements of high precision and high stability of synchronization clock in group cooperation. Hence, this paper constructs a network model, named DAUNet (unsupervised neural network based on dual attention), to enhance clock synchronization accuracy in multi-agent wireless ad hoc… More >

Fatima Al-Quayed^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-16, 2026, DOI:10.32604/cmc.2025.069102 - 10 November 2025

Abstract Due to the growth of smart cities, many real-time systems have been developed to support smart cities using Internet of Things (IoT) and emerging technologies. They are formulated to collect the data for environment monitoring and automate the communication process. In recent decades, researchers have made many efforts to propose autonomous systems for manipulating network data and providing on-time responses in critical operations. However, the widespread use of IoT devices in resource-constrained applications and mobile sensor networks introduces significant research challenges for cybersecurity. These systems are vulnerable to a variety of cyberattacks, including unauthorized access,… More >

Hafida Khelafi¹, Wassima Lakhdari², Mustapha Mounir Bouhenna³, Said Boudeffeur⁴, Hayet Meamiche¹, Salah Neghmouche Nacer^5,*, Meriam Laouar⁶

Phyton-International Journal of Experimental Botany, Vol.94, No.12, pp. 3975-3989, 2025, DOI:10.32604/phyton.2025.073210 - 29 December 2025

Abstract Essential oils (EOs) derived from medicinal plants are gaining recognition as sustainable alternatives to synthetic fungicides in the management of plant pathogens. This study investigates the chemical composition, chromatographic profile, and antifungal of Mentha rotundifolia essential oil against Fusarium oxysporum f. sp. albedinis (Foa), the pathogen responsible for Bayoud disease in date palm. The oil was extracted through hydrodistillation and characterized using thin-layer chromatography (TLC) and gas chromatography–mass spectrometry (GC-MS), revealing multiple fractions corresponding to terpenoid constituents and 23 chemical constituents, predominantly oxygenated monoterpenes (68.51%), with piperitenone oxide as the major component (62.53%). The antifungal efficacy was evaluated… More >

Di Wu¹, Chunguang Ren¹, Liangliang Li¹, Chongpei Zheng², Wenwen Su^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.12, pp. 4079-4090, 2025, DOI:10.32604/phyton.2025.072856 - 29 December 2025

Abstract To identify the pathogen responsible for fruit rot disease in Rosa roxburghii Tratt. from Guiding County, Guizhou Province, China, diseased fruit samples were collected. The pathogen was isolated, purified, and identified through morphological, molecular, and pathogenic analyses. Subsequently, its biological characteristics were evaluated. Furthermore, to determine the agent with the strongest toxicity against the identified pathogen, the antifungal activity of six chemical and biological agents was evaluated through indoor toxicity assays. Finally, Neopestalotiopsis clavispora was identified as the pathogen responsible for fruit rot disease in R. roxburghii Tratt. The diameter of the pathogen grown under different carbon and… More >

Miah A. Robinson, Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Khalid H. Abed^*

Journal on Artificial Intelligence, Vol.7, pp. 615-632, 2025, DOI:10.32604/jai.2025.073535 - 01 December 2025

Abstract Ensuring the safety of Artificial Intelligence (AI) is essential for providing dependable services, especially in various sectors such as the military, education, healthcare, and automotive industries. A highly effective method to boost the precision and performance of an AI agent involves multi-configuration training, followed by thorough evaluation in a specific setting to gauge performance outcomes. This research thoroughly investigates the design of three AI agents, each configured with a different number of hidden units. The first agent is equipped with 128 hidden units, the second with 256, and the third with 512, all utilizing the… More >

Ihab Taleb, Guillaume Guerard^*, Frédéric Fauberteau, Nga Nguyen, Pascal Clain

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 597-619, 2025, DOI:10.32604/cmes.2025.070517 - 30 October 2025

Abstract Isolated power systems, such as those on islands, face acute challenges in balancing energy demand with limited generation resources, making them particularly vulnerable to disruptions. This paper addresses these challenges by proposing a novel control and simulation framework based on a holonic multi-agent architecture, specifically developed as a digital twin for the Mayotte island grid. The primary contribution is a multi-objective optimization model, driven by a genetic algorithm, designed to enhance grid resilience through intelligent, decentralized decision-making. The efficacy of this architecture is validated through three distinct simulation scenarios: (1) a baseline scenario establishing nominal… More >

Shuxun Li^1,2, Xinhao Liu^1,2,*, Yu Zhang^1,2, Yu Zhao^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.10, pp. 2495-2526, 2025, DOI:10.32604/fdmp.2025.068674 - 30 October 2025

Abstract Hydraulic control valves, positioned at the terminus of pipe networks, are critical for regulating flow and pressure, thereby ensuring the operational safety and efficiency of pipeline systems. However, conventional valve designs often struggle to maintain effective regulation across a wide range of system pressures. To address this limitation, this study introduces a novel Pilot hydraulic valves specifically engineered for enhanced dynamic performance and precise regulation under variable pressure conditions. Building upon prior experimental findings, the proposed design integrates a high-fidelity simulation framework and a surrogate model-based optimization strategy. The study begins by formulating a comprehensive… More >