The fully coupled pressure-based algorithm is widely recognised for its superior convergence and robustness in solving incompressible flow problems. However, the increased scale of equations and the difficulty in solv...
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The fully coupled pressure-based algorithm is widely recognised for its superior convergence and robustness in solving incompressible flow problems. However, the increased scale of equations and the difficulty in solving linear systems have limited the widespread use of this algorithm in large-scale simulations. This paper presents an optimised block selective algebraic multigrid method significantly reducing computational complexity. Our approach employs a parallel modified independent set algorithm, allowing each process to perform matrix coarsening individually. Furthermore, an aggressive coarsening strategy is introduced to reduce complexity and enable the solution of larger-scale problems. Numerical experiments demonstrate that the solution time is shortened by 14% to 49% compared to the latest existing methods and outperforms the segregated algorithm. By addressing the computational challenges associated with the selective algebraic multigrid solver, this work unleashes the superior convergence properties of the fully coupled method.
For medical images, domain shift is a very common phenomenon. To address this issue, researchers have proposed unsupervised domain adaptation and multi-source domain generalization. However, these methods are sometime...
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Accurately locating the question-related regions in one given image is crucial for visual question answering (VQA). The current approaches suffer two limitations: (1) Dividing one image into multiple regions may lose ...
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Recently the analysis of remotely sensed images has played a vital role in various aspects of research. The current researches ignore the unique prior knowledge in remote sensing images and do not consider exploring t...
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ChatGPT can improve software engineering (SE) research practices by offering efficient, accessible information analysis, and synthesis based on natural language interactions. However, ChatGPT could bring ethical chall...
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Exploring robust and efficient association methods has always been an important issue in multi-object tracking (MOT). Although existing tracking methods have achieved impressive performance, congestion and frequent oc...
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With the advancement of marine science research, the study and monitoring of benthic organisms have gained prominence. These organisms, inhabiting the seafloor, play crucial roles in marine ecosystems. However, tradit...
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The large Key-Value (KV) cache is a significant challenge in deploying Large Language Models (LLMs). Current research addressing these issues employs cache compression techniques, which we find suffer from information...
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Ethereum has officially provided a set of system-level cryptographic APIs to enhance smart contracts with cryptographic capabilities. These APIs have been utilized in over 13.8% of Ethereum transactions, motivating de...
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Variational Autoencoders (VAEs) have gained popularity as one of the main approaches for generating diverse and high-quality synthetic images. This study examines the suitability of evaluation metrics, specifically In...
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