Hoi Chuen Cheng, Frederick Ziyang Hong, Babar Hussain, Yiru Wang, Chik Patrick Yue^*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 161-181, 2024, DOI:10.32604/cmc.2024.053079 - 15 October 2024

Abstract Large-scale indoor 3D reconstruction with multiple robots faces challenges in core enabling technologies. This work contributes to a framework addressing localization, coordination, and vision processing for multi-agent reconstruction. A system architecture fusing visible light positioning, multi-agent path finding via reinforcement learning, and 360° camera techniques for 3D reconstruction is proposed. Our visible light positioning algorithm leverages existing lighting for centimeter-level localization without additional infrastructure. Meanwhile, a decentralized reinforcement learning approach is developed to solve the multi-agent path finding problem, with communications among agents optimized. Our 3D reconstruction pipeline utilizes equirectangular projection from 360° cameras to More >

Mingzhao Han¹, Susilawati Kasim^1,*, Zhongming Yang², Xi Deng², Noor Baity Saidi³, Md Kamal Uddin¹, Effyanti Mohd Shuib¹

Phyton-International Journal of Experimental Botany, Vol.93, No.9, pp. 2149-2166, 2024, DOI:10.32604/phyton.2024.054009 - 30 September 2024

Abstract It is imperative to enhance crop yield to meet the demands of a burgeoning global population while simultaneously safeguarding the environment from adverse impacts, which is one of the dominant challenges confronting humanity in this phase of global climate change. To overcome this problem and reduce dependency on chemical fertilizer, scientists now view the implementation of biostimulant strategies as a cost-effective and environmentally friendly approach to achieving sustainable agriculture. Plant extracts are rich in bioactive phytocompounds, which can enhance plant resistance to disease, pest, and abiotic stresses (e.g., drought, salinity, and extreme temperature), and promote… More >

Annesha Kar¹, Niranjan Karak^1,2,*

Journal of Renewable Materials, Vol.12, No.9, pp. 1507-1540, 2024, DOI:10.32604/jrm.2024.052220 - 25 September 2024

Abstract The pursuit of incorporating eco-friendly reinforcing agents in polymer composites has accentuated the exploration of various natural biomass-derived materials. The burgeoning environmental crisis spurred by the discharge of synthetic dyes into wastewater has catalyzed the search for effective and sustainable treatment technologies. Among the various sorbent materials explored, biochar, being renewable, has gained prominence due to its excellent adsorption properties and environmental sustainability. It has also emerged as a focal point for its potential to replace other conventional reinforcing agents, viz., fumed silica, aluminum oxide, treated clays, etc. This study introduces a novel class of… More > Graphic Abstract

Jin Yang^1,2, Hailong Zhao¹, Jingyi Zeng¹, Ying Su^1,2, Mengdi Zhu¹, Xingyang He^1,2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.10, pp. 2163-2181, 2024, DOI:10.32604/fdmp.2024.055448 - 23 September 2024

Abstract To achieve higher strength and better durability, ultra-high performance concrete (UHPC) typically employs a relatively small water-binder ratio. However, this generally leads to an undesired increase in the paste viscosity. In this study, the effects of liquid and powder polycarboxylate superplasticizers (PCE) on UHPC are compared and critically discussed. Moreover, the following influential factors are considered: air-entraining agents (AE), slump retaining agents (SA), and defoaming agents (DF) and the resulting flow characteristics, mechanical properties, and hydration properties are evaluated assuming UHPC containing 8‰ powder PCE (PCE-based UHPC). It is found that the spread diameter of… More >

Wanwei Huang^1,*, Qiancheng Zhang¹, Tao Liu², Yaoli Xu¹, Dalei Zhang³

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4875-4893, 2024, DOI:10.32604/cmc.2024.055622 - 12 September 2024

Abstract Aiming at the rapid growth of network services, which leads to the problems of long service request processing time and high deployment cost in the deployment of network function virtualization service function chain (SFC) under 5G networks, this paper proposes a multi-agent deep deterministic policy gradient optimization algorithm for SFC deployment (MADDPG-SD). Initially, an optimization model is devised to enhance the request acceptance rate, minimizing the latency and deploying the cost SFC is constructed for the network resource-constrained case. Subsequently, we model the dynamic problem as a Markov decision process (MDP), facilitating adaptation to the… More >

Yong Wan¹, Li Li¹, Jiaxin Zou¹, Hucheng Xiao², Mengdi Zhu², Ying Su², Jin Yang^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.9, pp. 1941-1956, 2024, DOI:10.32604/fdmp.2024.053910 - 23 August 2024

Abstract Due to the low water-cement ratio of ultra-high-performance concrete (UHPC), fluidity and shrinkage cracking are key aspects determining the performance and durability of this type of concrete. In this study, the effects of different types of cementitious materials, chemical shrinkage-reducing agents (SRA) and steel fiber (SF) were assessed. Compared with M2-UHPC and M3-UHPC, M1-UHPC was found to have better fluidity and shrinkage cracking performance. Moreover, different SRA incorporation methods, dosage and different SF types and aspect ratios were implemented. The incorporation of SRA and SF led to a decrease in the fluidity of UHPC. SRA More >

Saket Sarin¹, Sunil K. Singh¹, Sudhakar Kumar¹, Shivam Goyal¹, Brij Bhooshan Gupta^2,3,4,8,*, Wadee Alhalabi⁵, Varsha Arya^6,7

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3123-3138, 2024, DOI:10.32604/cmc.2024.051599 - 15 August 2024

Abstract In the rapidly evolving landscape of today’s digital economy, Financial Technology (Fintech) emerges as a transformative force, propelled by the dynamic synergy between Artificial Intelligence (AI) and Algorithmic Trading. Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning (MARL) and Explainable AI (XAI) within Fintech, aiming to refine Algorithmic Trading strategies. Through meticulous examination, we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm, employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions. These AI-infused Fintech platforms harness collective intelligence More >

Shiming Lin^1,2,3, Ling Ye², Yijie Zhuang¹, Lingyun Lu^2,*, Shaoqiu Zheng^2,*, Chenxi Huang¹, Ng Yin Kwee⁴

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 299-317, 2024, DOI:10.32604/cmc.2024.051379 - 18 July 2024

Abstract In recent years, with the continuous development of deep learning and knowledge graph reasoning methods, more and more researchers have shown great interest in improving knowledge graph reasoning methods by inferring missing facts through reasoning. By searching paths on the knowledge graph and making fact and link predictions based on these paths, deep learning-based Reinforcement Learning (RL) agents can demonstrate good performance and interpretability. Therefore, deep reinforcement learning-based knowledge reasoning methods have rapidly emerged in recent years and have become a hot research topic. However, even in a small and fixed knowledge graph reasoning action… More >

Tengda Li, Gang Wang, Qiang Fu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2559-2586, 2024, DOI:10.32604/cmes.2024.052039 - 08 July 2024

Abstract Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation (DTA) and high-dimensional decision space with single agent, this paper combines the deep reinforcement learning (DRL) theory and an improved Multi-Agent Deep Deterministic Policy Gradient (MADDPG-D2) algorithm with a dual experience replay pool and a dual noise based on multi-agent architecture is proposed to improve the efficiency of DTA. The algorithm is based on the traditional Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm, and considers the introduction of a double noise mechanism to increase the action exploration… More >

Meignanamoorthi Dhandapani^*, V. Vetriselvi, R. Aishwarya

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2449-2486, 2024, DOI:10.32604/cmes.2024.050986 - 08 July 2024

Abstract The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale. Network slicing is crucial in delivering services for different, demanding vertical applications in this context. Next-generation applications have time-sensitive requirements and depend on the most efficient routing path to ensure packets reach their intended destinations. However, the existing IP (Internet Protocol) over a multi-domain network faces challenges in enforcing network slicing due to minimal collaboration and information sharing among network operators. Conventional inter-domain routing methods, like Border Gateway Protocol (BGP), cannot make routing decisions based on performance,… More >