Kaituo Jiao¹, Dongxu Han^2,*, Bo Yu²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-3, 2024, DOI:10.32604/icces.2024.011520

Abstract Motivated by the fractures being very thin compared to the size of rock matrix, utilizing the non-conforming grid is an efficient approach to simulate fluid flow in fractured porous media. The embedded discrete fracture model (EDFM) is the typical one that using the conforming grid and modelled based on the finite volume method (FVM) framework. The EDFM maintains advantages of mass conservation and low computational complexity, but it cannot characterize blocking fractures and has a low accuracy on the mass exchange between fractures and matrix [1]. In our previous work [2], we developed the enriched-EDFM… More >

Muhammad Aamer Ejaz^1,*, Kamalrulnizam Abu Bakar¹, Ismail Fauzi Bin Isnin¹, Babangida Isyaku^1,2,*, Taiseer Abdalla Elfadil Eisa³, Abdelzahir Abdelmaboud⁴, Asma Abbas Hassan Elnour³

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1511-1528, 2024, DOI:10.32604/cmc.2024.054938 - 15 October 2024

Abstract Localization is crucial in wireless sensor networks for various applications, such as tracking objects in outdoor environments where GPS (Global Positioning System) or prior installed infrastructure is unavailable. However, traditional techniques involve many anchor nodes, increasing costs and reducing accuracy. Existing solutions do not address the selection of appropriate anchor nodes and selecting localized nodes as assistant anchor nodes for the localization process, which is a critical element in the localization process. Furthermore, an inaccurate average hop distance significantly affects localization accuracy. We propose an improved DV-Hop algorithm based on anchor sets (AS-IDV-Hop) to improve… More >

Shaoqi Zheng¹, Zihao Yang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.012200

Abstract This study proposes a novel method for predicting the microcrack propagation in composites based on coupling the local and non-local micromechanics. The special feature of this method is that it can take full advantages of both the continuum micromechanics as a local model and peridynamic micromechanics as a non-local model to achieve composite fracture simulation with a higher level of accuracy and efficiency. Based on the energy equivalence, we first establish the equivalent continuum micromechanics model with equivalent stiffness operators through peridynamic micromechanics model. These two models are then coupled into a closed equation system, More >

Zhaoxu Lian¹,Wenbin Wu^2,*, Moubin Liu^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011054

Abstract The underwater explosion (UNDEX) could cause the fatal damage of naval ships and submarines in the naval battle, and seriously threaten their combat capability [1]. The UNDEX process is very complicated, including the propagation and reflection of the shock wave, formation and collapse of cavitation zone, trainset dynamic structural response and so on [2]. In this paper, we develop the three-dimensional Discontinuous Galerkin method (DGM) model for simulating the propagation of incident shock loading in fluid domain. The pressure cutoff model is employed to deal with the cavitation effect due to the reflection of the More >

Feyza Altunbey Özbay¹, Erdal Özbay², Farhad Soleimanian Gharehchopogh^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1067-1110, 2024, DOI:10.32604/cmes.2024.054334 - 27 September 2024

Abstract Artificial rabbits optimization (ARO) is a recently proposed biology-based optimization algorithm inspired by the detour foraging and random hiding behavior of rabbits in nature. However, for solving optimization problems, the ARO algorithm shows slow convergence speed and can fall into local minima. To overcome these drawbacks, this paper proposes chaotic opposition-based learning ARO (COARO), an improved version of the ARO algorithm that incorporates opposition-based learning (OBL) and chaotic local search (CLS) techniques. By adding OBL to ARO, the convergence speed of the algorithm increases and it explores the search space better. Chaotic maps in CLS… More > Graphic Abstract

Nada Charfi^1,3,*, Nour Regaieg^1,3, Ines Ayadi^2,3, Najeh Smaoui^1,3, Rim Feki^1,3, Imen Gassara^1,3, Sana Omri^1,3, Lobna Zouari^1,3, Jihène Ben Thabet^1,3, Manel Maâlej Bouali^1,3, Afef Khanfir^2,3, Mohamed Maâlej^1,3

Psycho-Oncologie, Vol.18, No.3, pp. 241-248, 2024, DOI:10.32604/po.2024.049038 - 12 September 2024

Abstract Le diagnostic et la prise en charge du cancer du sein (CS) affectent d’une manière complexe la vie sexuelle des femmes et touchent au symbole de la féminité, qui est très important dans la constitution de l’image du corps. Nos objectifs ont été d’évaluer le fonctionnement sexuel et l’image du corps des patientes en rémission d’un CS localisé, de déterminer les liens entre ces deux paramètres et d’étudier leur rapport avec les modalités thérapeutiques du CS. Nous avons mené une étude transversale, descriptive et analytique au sein des services d’oncologie médicale et de radiothérapie du… More >

Qianyao Zhu¹, Kaizhou Gao^1,*, Wuze Huang¹, Zhenfang Ma¹, Adam Slowik²

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3573-3589, 2024, DOI:10.32604/cmc.2024.055244 - 12 September 2024

Abstract The flow shop scheduling problem is important for the manufacturing industry. Effective flow shop scheduling can bring great benefits to the industry. However, there are few types of research on Distributed Hybrid Flow Shop Problems (DHFSP) by learning assisted meta-heuristics. This work addresses a DHFSP with minimizing the maximum completion time (Makespan). First, a mathematical model is developed for the concerned DHFSP. Second, four Q-learning-assisted meta-heuristics, e.g., genetic algorithm (GA), artificial bee colony algorithm (ABC), particle swarm optimization (PSO), and differential evolution (DE), are proposed. According to the nature of DHFSP, six local search operations… More >

Mingyuan Luo¹, Shiyu Tian¹, Xinzhuan Yao², Yue Wan⁴, Zhouzhuoer Chen¹, Zifan Yang⁴, Huagen Hao⁴, Fei Liu³, Hu Tang^1,2,*, Litang Lu^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.8, pp. 2019-2036, 2024, DOI:10.32604/phyton.2024.052938 - 30 August 2024

Abstract The ATP-binding cassette (ABC) transporter is a gene superfamily in plants. ATP-binding cassette subfamily C (ABCC) protein is a multidrug resistance-associated (MRP) transporter. They play various roles in plant growth, development, and secondary metabolite transport. However, there are few studies on ABCC transporters in tea plants. In this study, genome-wide association study (GWAS) analysis of epigallocatechin gallate (EGCG) content in 108 strains of Kingbird revealed that CsABCCs may be involved in EGCG transport. We identified 25 CsABCC genes at the genomic level of the tea plant, their phylogenetic tree, gene structure, targeted miRNA and other bioinformatics… More >

Meijing Li^*, Runqing Huang, Xianxian Qi

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2283-2299, 2024, DOI:10.32604/cmc.2024.053630 - 15 August 2024

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 >

Gonghui Deng, Dunzhi Wu, Weizhen Chen^*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1985-2003, 2024, DOI:10.32604/cmc.2024.052174 - 15 August 2024

Abstract The task of food image recognition, a nuanced subset of fine-grained image recognition, grapples with substantial intra-class variation and minimal inter-class differences. These challenges are compounded by the irregular and multi-scale nature of food images. Addressing these complexities, our study introduces an advanced model that leverages multiple attention mechanisms and multi-stage local fusion, grounded in the ConvNeXt architecture. Our model employs hybrid attention (HA) mechanisms to pinpoint critical discriminative regions within images, substantially mitigating the influence of background noise. Furthermore, it introduces a multi-stage local fusion (MSLF) module, fostering long-distance dependencies between feature maps at… More >