Jin Yang^1,2, Senye Liu¹, Xingyang He^1,2,*, Ying Su^1,2, Jingyi Zeng², Bohumír Strnadel^1,3

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.9, pp. 2077-2090, 2024, DOI:10.32604/fdmp.2024.050360

Abstract Phosphate tailings are usually used as backfill material in order to recycle tailings resources. This study considers the effect of the mix proportions of clinker-free binders on the fluidity, compressive strength and other key performances of cementitious backfill materials based on phosphate tailings. In particular, three solid wastes, phosphogypsum (PG), semi-aqueous phosphogypsum (HPG) and calcium carbide slag (CS), were selected to activate wet ground granulated blast furnace slag (WGGBS) and three different phosphate tailings backfill materials were prepared. Fluidity, rheology, settling ratio, compressive strength, water resistance and ion leaching behavior of backfill materials were determined.… More > Graphic Abstract

Sheng Xiang¹, Junhao Ma¹, Qunli Shang¹, Xianbao Wang^1,*, Defu Chen^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 713-731, 2024, DOI:10.32604/cmes.2024.052759

Abstract Effective small object detection is crucial in various applications including urban intelligent transportation and pedestrian detection. However, small objects are difficult to detect accurately because they contain less information. Many current methods, particularly those based on Feature Pyramid Network (FPN), address this challenge by leveraging multi-scale feature fusion. However, existing FPN-based methods often suffer from inadequate feature fusion due to varying resolutions across different layers, leading to suboptimal small object detection. To address this problem, we propose the Two-layer Attention Feature Pyramid Network (TA-FPN), featuring two key modules: the Two-layer Attention Module (TAM) and the… More > Graphic Abstract

Mohammed Mohammed^1,2,*, Jawad K. Oleiwi³, Aeshah M. Mohammed⁴, Anwar Ja’afar Mohamad Jawad⁵, Azlin F. Osman^1,2, Tijjani Adam⁶, Bashir O. Betar⁷, Subash C. B. Gopinath^2,8,9

Journal of Renewable Materials, Vol.12, No.7, pp. 1237-1290, 2024, DOI:10.32604/jrm.2024.051201

Abstract Natural fibre (NFR) reinforced functional polymer composites are quickly becoming an indispensable sustainable material in the transportation industry because of their lightweight, lower cost in manufacture, and adaptability to a wide variety of goods. However, the major difficulties of using these fibres are their existing poor dimensional stability and the extreme hydrophilicity. In assessing the mechanical properties (MP) of composites, the interfacial bonding (IB) happening between the NFR and the polymer matrix (PM) plays an incredibly significant role. When compared to NFR/synthetic fibre hybrid composites, hybrid composites (HC) made up of two separate NFR are… More > Graphic Abstract

Meijing Li^*, Runqing Huang, Xianxian Qi

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2283-2299, 2024, DOI:10.32604/cmc.2024.053630

Abstract Chinese Clinical Named Entity Recognition (CNER) is a crucial step in extracting medical information and is of great significance in promoting medical informatization. However, CNER poses challenges due to the specificity of clinical terminology, the complexity of Chinese text semantics, and the uncertainty of Chinese entity boundaries. To address these issues, we propose an improved CNER model, which is based on multi-feature fusion and multi-scale local context enhancement. The model simultaneously fuses multi-feature representations of pinyin, radical, Part of Speech (POS), word boundary with BERT deep contextual representations to enhance the semantic representation of text… More >

Zhibo Yang, Xiaohan Huang, Bingdong Wang, Bin Hu, Zhenyong Zhang^*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3001-3019, 2024, DOI:10.32604/cmc.2024.053369

Abstract With the widespread use of machine learning (ML) technology, the operational efficiency and responsiveness of power grids have been significantly enhanced, allowing smart grids to achieve high levels of automation and intelligence. However, tree ensemble models commonly used in smart grids are vulnerable to adversarial attacks, making it urgent to enhance their robustness. To address this, we propose a robustness enhancement method that incorporates physical constraints into the node-splitting decisions of tree ensembles. Our algorithm improves robustness by developing a dataset of adversarial examples that comply with physical laws, ensuring training data accurately reflects possible More >

Kexin Wang^*, Yingdong Gou, Dingrui Xue^*, Jiancheng Liu, Wanlong Qi, Gang Hou, Bo Li

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2941-2962, 2024, DOI:10.32604/cmc.2024.052893

Abstract The collective Unmanned Weapon System-of-Systems (UWSOS) network represents a fundamental element in modern warfare, characterized by a diverse array of unmanned combat platforms interconnected through heterogeneous network architectures. Despite its strategic importance, the UWSOS network is highly susceptible to hostile infiltrations, which significantly impede its battlefield recovery capabilities. Existing methods to enhance network resilience predominantly focus on basic graph relationships, neglecting the crucial higher-order dependencies among nodes necessary for capturing multi-hop meta-paths within the UWSOS. To address these limitations, we propose the Enhanced-Resilience Multi-Layer Attention Graph Convolutional Network (E-MAGCN), designed to augment the adaptability of More >

Zhuoyifan Zhang¹, Lu Zhang², Liang Wang³, Haoming Wu^2,*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3405-3420, 2024, DOI:10.32604/cmc.2024.052144

Abstract Research on neural radiance fields for novel view synthesis has experienced explosive growth with the development of new models and extensions. The NeRF (Neural Radiance Fields) algorithm, suitable for underwater scenes or scattering media, is also evolving. Existing underwater 3D reconstruction systems still face challenges such as long training times and low rendering efficiency. This paper proposes an improved underwater 3D reconstruction system to achieve rapid and high-quality 3D reconstruction. First, we enhance underwater videos captured by a monocular camera to correct the image quality degradation caused by the physical properties of the water medium… 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

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 >

Yu Wang^1,2, Mengyang Ma^1,2,*, Yong Long^1,2, Qingxiang Zhao^1,2, Zhifei Cheng^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.8, pp. 1773-1784, 2024, DOI:10.32604/fdmp.2024.048695

Abstract Shrinkage-induced cracking is a common issue in concrete structures, where the formation of cracks not only affects the aesthetic appearance of concrete but also potentially reduces its durability and strength. In this study, the effect of ceramsite sand addition on the properties of a ternary system of cement-ground granulated blast furnace slag (GGBFS)-phosphogypsum (PG) is investigated. In particular, the fluidity, rheology, hydration heat, compressive strength, autogenous shrinkage, and drying shrinkage of the considered mortar specimens are analyzed. The results indicate that an increase in PG content leads to a decrease in fluidity, higher viscosity, lower More >

Zhihui Du¹, Mengge Yu^1,*, Jiali Liu², Xiulong Yao¹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1687-1701, 2024, DOI:10.32604/fdmp.2024.047315

Abstract Snow interacting with a high-speed train can cause the formation of ice in the train bogie region and affect its safety. In this study, a wind-snow multiphase numerical approach is introduced for high-speed train bogies on the basis of the Euler-Lagrange discrete phase model. A particle-wall impact criterion is implemented to account for the presence of snow particles on the surface. Subsequently, numerical simulations are conducted, considering various snow particle diameter distributions and densities. The research results indicate that when the particle diameter is relatively small, the distribution of snow particles in the bogie cavity More >