Journal of Computational Science最新文献_第5页

Exploring network-level indicators for project analysis — A comparison of real and synthetic projects 探索项目分析的网络级指标——真实项目和综合项目的比较

IF 3.7 3区计算机科学

Journal of Computational Science Pub Date : 2026-01-01 Epub Date: 2025-11-26 DOI: 10.1016/j.jocs.2025.102745

Zsolt T. Kosztyán

引用次数: 0

Safe merging aircraft flows in multi-route schemes 多航路方案下的安全合流

IF 3.7 3区计算机科学

Journal of Computational Science Pub Date : 2026-01-01 Epub Date: 2025-11-13 DOI: 10.1016/j.jocs.2025.102741

Arseniy A. Spiridonov

引用次数: 0

ELM-UNet: An efficient and lightweight Vision Mamba UNet for skin lesion segmentation ELM-UNet：用于皮肤病变分割的高效轻量级视觉曼巴UNet

IF 3.7 3区计算机科学

Journal of Computational Science Pub Date : 2026-01-01 Epub Date: 2025-11-11 DOI: 10.1016/j.jocs.2025.102743

Songling Xia , Hongwei Deng , Feng Chen

{"title":"ELM-UNet: An efficient and lightweight Vision Mamba UNet for skin lesion segmentation","authors":"Songling Xia , Hongwei Deng , Feng Chen","doi":"10.1016/j.jocs.2025.102743","DOIUrl":"10.1016/j.jocs.2025.102743","url":null,"abstract":"<div><div>Skin lesion segmentation plays a critical role in the early detection and treatment of skin cancer. Although models based on CNNs and Transformers have achieved notable progress in image segmentation, they still exhibit some limitations. Specifically, CNNs struggle with capturing long-range dependencies effectively, while Transformers suffer from high computational costs due to the self-attention mechanism. Recently, Mamba as a representative State Space Models (SSMs), has drawn attention for its ability to efficiently model long-range dependencies with lower computational overhead. To address these challenges, we propose ELM-UNet, an efficient and lightweight skin lesion segmentation method based on the Mamba architecture. We introduce the LKA-MLP Synergy Module (LMSM), which significantly enhances the model’s ability to capture fine details and handle complex regions in skin lesion images, thus improving segmentation precision. Additionally, we present the SSM-Conv Fusion Module (SSM-CFM), which effectively combines the strengths of SSM in modeling long-range dependencies and convolution operation in local feature extraction, further boosting lesion feature representation. The experimental results show that compared to UltraLight VM-UNet, on the ISIC2017 dataset, ELM-UNet achieves improvements of 2.04%, 1.21%, and 1.61% in mIoU, DSC, and Sen, respectively. On the ISIC2018 dataset, it achieves improvements of 1.81%, 1.10%, and 2.36% in mIoU, DSC, and Sen, respectively.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"93 ","pages":"Article 102743"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145529200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Parallel sparsity patterns for factored incomplete inverse matrices 分解不完全逆矩阵的并行稀疏模式

IF 3.7 3区计算机科学

Journal of Computational Science Pub Date : 2026-01-01 Epub Date: 2025-10-28 DOI: 10.1016/j.jocs.2025.102736

Christos K. Filelis-Papadopoulos, George A. Gravvanis

引用次数: 0

Fuzzy data imputation with DIMP and FGAIN 模糊数据的DIMP和FGAIN插值

IF 3.7 3区计算机科学

Journal of Computational Science Pub Date : 2026-01-01 Epub Date: 2025-10-31 DOI: 10.1016/j.jocs.2025.102738

Maciej Romaniuk , Przemysław Grzegorzewski

{"title":"Fuzzy data imputation with DIMP and FGAIN","authors":"Maciej Romaniuk , Przemysław Grzegorzewski","doi":"10.1016/j.jocs.2025.102738","DOIUrl":"10.1016/j.jocs.2025.102738","url":null,"abstract":"<div><div>Missing values in a dataset are usually replaced by their imputed counterparts. Although many imputation methods are dedicated to real-valued data, the situation is quite different for fuzzy values. Moreover, the issue of missing data in a fuzzy dataset is fundamentally different from the case of real values — the lack of real data only means there are no observations in the database in a specific place. Meanwhile, in the case of fuzzy observations, which are mathematically more complex than real-valued data, missing data may mean both the lack of observations and the fact that a particular component of the fuzzy observations is unknown. In this paper, we propose an imputation method called DIMP, specifically designed to deal with imprecise data that is missing and modeled with fuzzy numbers. We consider two algorithms explicitly tailored for triangular and trapezoidal LR-fuzzy numbers. We also discuss another approach called FGAIN, a special GAIN variant adapted to fuzzy data. Then, we compare DIMP with FGAIN, using both simulated and real-life datasets. Various statistical tools, including error measures and tests, are proposed as suitable benchmarks for this comparison. The conducted numerical analysis shows that both considered methods, with an indication in favor of DIMP, are promising tools that could be recommended for practitioners to handle fuzzy data imputation problems.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"93 ","pages":"Article 102738"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145475487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Computational modeling of incompressible two-phase fluid dynamics via the conservative Allen–Cahn framework on a virtual cube 虚拟立方体上不可压缩两相流体动力学的保守Allen-Cahn框架计算模型

IF 3.7 3区计算机科学

Journal of Computational Science Pub Date : 2026-01-01 Epub Date: 2025-11-24 DOI: 10.1016/j.jocs.2025.102755

Ahmed Zeeshan , Juho Ma , Zhengang Li , Xinpei Wu , Junseok Kim

{"title":"Computational modeling of incompressible two-phase fluid dynamics via the conservative Allen–Cahn framework on a virtual cube","authors":"Ahmed Zeeshan , Juho Ma , Zhengang Li , Xinpei Wu , Junseok Kim","doi":"10.1016/j.jocs.2025.102755","DOIUrl":"10.1016/j.jocs.2025.102755","url":null,"abstract":"<div><div>We present a robust computational algorithm for the simulation of incompressible two-phase fluid flows on a virtual cubic surface, i.e., the models of incorporating the conservative Allen–Cahn (CAC) equation into the Navier–Stokes (NS) equation. By using a phase-field approach, the proposed method effectively captures the evolution of complex interfaces among distinct fluid phases instead of explicit interface tracking. The projection method is combined with the finite difference method (FDM) to solve the governing equations in an efficient manner. In addition, a multigrid solver is adopted to handle the pressure Poisson equation, which improves computational accuracy and reduces computational cost. The virtual cubic surface is modeled as a two-dimensional unfolded domain to facilitate straightforward discretization while preserving geometric fidelity. Numerical experiments, including benchmark shear flow and vortex dynamics on the cubic surface, back up the efficacy of the method in handling two-phase flows. The computational results validate that the proposed scheme has significant potential to advance the simulation of multiphase incompressible flows on curved or complex surfaces. This approach provides an effective numerical method applicable to various scientific and engineering problems.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"93 ","pages":"Article 102755"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145693905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Numerical solution of the biological SIR model for COVID-19 with convergence analysis 基于收敛分析的COVID-19生物SIR模型数值解

IF 3.7 3区计算机科学

Journal of Computational Science Pub Date : 2025-12-01 Epub Date: 2025-09-17 DOI: 10.1016/j.jocs.2025.102704

Walid Remili , Wen-Xiu Ma

引用次数: 0

Darcy-scale digital core models for rock properties upscaling and computational domain reduction 达西尺度数字岩心模型的岩石性质升级和计算域缩减

IF 3.7 3区计算机科学

Journal of Computational Science Pub Date : 2025-12-01 Epub Date: 2025-09-15 DOI: 10.1016/j.jocs.2025.102715

Denis Orlov, Batyrkhan Gainitdinov, Dmitry Koroteev

{"title":"Darcy-scale digital core models for rock properties upscaling and computational domain reduction","authors":"Denis Orlov, Batyrkhan Gainitdinov, Dmitry Koroteev","doi":"10.1016/j.jocs.2025.102715","DOIUrl":"10.1016/j.jocs.2025.102715","url":null,"abstract":"<div><div>The rapid development of Digital Rock Physics (DRP) requires the elaboration of robust techniques for closing the gaps between different scales of rock studies (upscaling). The upscaling workflows are especially needed to support the applicability of DRP for heterogeneous rocks. Basically, DRP involves two primary stages: model construction and simulation of physical processes on the models created. For heterogeneous rocks, there is an inherent trade-off between the spatial resolution of the data and the representativeness of the model size. The primary objective of this study was to implement and test a technique for upscaling digital core models from microscale to macroscale, enabling the computation of rock properties while accounting for heterogeneity of various scales. The upscaling is based on establishing correlations between tomography data of different resolutions and transforming low-resolution tomography into a multi-class model according to the defined correlation. The convolutional neural network for high-resolution tomography data was considered as the optimal algorithm for transforming low-resolution tomography into a multi-class model. The output of the neural network was an upscaled model of lower resolution than the original tomography image. Each cell in the upscaled model belonged to one of several types of formation, whose generalized characteristics were determined on the basis of the analysis of high-resolution tomography data. To validate the upscaling technique, we constructed a digital model of a complex carbonate reservoir based on data from multi-scale microtomography (<span><math><mi>μ</mi></math></span>CT). A Darcy-scale model has been used and validated as a multi-class model, enabling the computation of flows in pore samples of various scales. By incorporating diverse pore space structures as different classes in the Darcy-scale model, it is possible to preserve the substantial physical size of the model while enhancing its level of complexity.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"92 ","pages":"Article 102715"},"PeriodicalIF":3.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A decomposition based imputation algorithm for long consecutive missing atmospheric pollution data and its application 一种基于分解的长时间连续缺失大气污染数据插值算法及其应用

IF 3.7 3区计算机科学

Journal of Computational Science Pub Date : 2025-12-01 Epub Date: 2025-09-01 DOI: 10.1016/j.jocs.2025.102697

Xinyi Wei , Hao Meng , Lizhen Shao , Dongmei Fu , Lingwei Ma , Dawei Zhang

{"title":"A decomposition based imputation algorithm for long consecutive missing atmospheric pollution data and its application","authors":"Xinyi Wei , Hao Meng , Lizhen Shao , Dongmei Fu , Lingwei Ma , Dawei Zhang","doi":"10.1016/j.jocs.2025.102697","DOIUrl":"10.1016/j.jocs.2025.102697","url":null,"abstract":"<div><div>With the intensification of environmental air pollution, the impact of air pollutants on both the ecological environment and human health has attracted widespread attention. However, due to the relatively late introduction of environmental monitoring systems, there were long consecutive missing values in early pollutant data. In this paper, we propose a decomposition-based imputation method for long consecutive missing pollution data. Firstly, wavelet coherence analysis is employed to investigate the periodic relationship between the pollution data and the relevant air data, decomposing them into periodic and non-periodic components. Then, machine learning and transfer learning are used to impute the periodic and non-periodic components, respectively. Furthermore, the effectiveness of the method is validated on artificially missing <span><math><msub><mrow><mi>NO</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> and <span><math><msub><mrow><mi>SO</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> concentration data from five regions of China. Comparison results show that the proposed method significantly outperforms some other imputation methods in the literature in terms of both mean absolute error and mean absolute percentage error. Finally, the proposed imputation method is applied in the study of accelerated aging of polycarbonate materials. Experimental results show that the predictive accuracy of the aging model is improved when using the imputed pollutant data.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"92 ","pages":"Article 102697"},"PeriodicalIF":3.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Numerical study of two-dimensional sediment transport using momentum-conserving staggered grid scheme 二维保动量交错网格输沙数值研究

IF 3.7 3区计算机科学

Journal of Computational Science Pub Date : 2025-12-01 Epub Date: 2025-09-11 DOI: 10.1016/j.jocs.2025.102714

Riski Kurniawan , Sri Redjeki Pudjaprasetya , Rani Sulvianuri

{"title":"Numerical study of two-dimensional sediment transport using momentum-conserving staggered grid scheme","authors":"Riski Kurniawan , Sri Redjeki Pudjaprasetya , Rani Sulvianuri","doi":"10.1016/j.jocs.2025.102714","DOIUrl":"10.1016/j.jocs.2025.102714","url":null,"abstract":"<div><div>Sediment transport plays a crucial role in the evolution of bed morphology through deposition and erosion. This study presents numerical simulations of two-dimensional sediment transport induced by fluid flow. The fluid-sediment interaction is governed by a capacity model, i.e., the coupled system of shallow water and Exner equations, a simplification of more physically advanced non-capacity models. The system is solved using a momentum-conserving staggered grid (MCS) scheme. Model validation is performed using the Meyer-Peter and Müller (MPM) bedload transport formula, applied to experimental data from dam-break flows in various channel configurations. The proposed method successfully reproduces trends in the evolution of the water surface and quasi-steady sediment profiles. In general, the MCS scheme provides more accurate water level predictions than the numerical benchmark schemes. Although the predictions of maximum depths of deposition and erosion are less accurate, the overall results are consistent with those obtained from non-capacity models. Furthermore, the model is applied to the Kampar River estuary to simulate sediment transport due to the tidal bore.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"92 ","pages":"Article 102714"},"PeriodicalIF":3.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0