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Sardar Anisul Haque, Mohammad Tanvir Parvez and Shahadat Hossain
Matrix?matrix multiplication is of singular importance in linear algebra operations with a multitude of applications in scientific and engineering computing. Data structures for storing matrix elements are designed to minimize overhead information as wel...
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Xiaoyi Fu, Yuntao Hua, Wenlai Ma, Hutao Cui and Yang Zhao
Thermal uncertainty analysis of spacecraft is an important method to avoid overdesign and underdesign problems. In the context of uncertainty analysis, thermal models representing multiple operating conditions must be invoked repeatedly, leading to subst...
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Xiaoyi Fu, Lei Liang, Wenlai Ma, Hutao Cui and Yang Zhao
Designing spacecraft involves a careful equilibrium to avoid overengineering or underdesigning, which underscores the importance of employing thermal uncertainty analysis. A key part of this analysis is modeling thermal conditions, but this is often a co...
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Yang Wang, Jie Liu, Xiaoxiong Zhu, Qingyang Zhang, Shengguo Li and Qinglin Wang
Structured grid-based sparse matrix-vector multiplication and Gauss?Seidel iterations are very important kernel functions in scientific and engineering computations, both of which are memory intensive and bandwidth-limited. GPDSP is a general purpose dig...
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Betty Saridou, Isidoros Moulas, Stavros Shiaeles and Basil Papadopoulos
Image conversion of malicious binaries, or binary visualisation, is a relevant approach in the security community. Recently, it has exceeded the role of a single-file malware analysis tool and has become a part of Intrusion Detection Systems (IDSs) thank...
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Anargiros I. Delis, Maria Kazolea and Maria Gaitani
This work aims to supplement the realization and validation of a higher-order well-balanced unstructured finite volume (FV) scheme, that has been relatively recently presented, for numerically simulating weakly non-linear weakly dispersive water waves ov...
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Jialu Sui and Jian Yin
Nowadays, as the number of items is increasing and the number of items that users have access to is limited, user-item preference matrices in recommendation systems are always sparse. This leads to a data sparsity problem. The latent factor analysis (LFA...
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Taghreed Alghamdi, Khalid Elgazzar and Taysseer Sharaf
Hierarchical Bayesian models (HBM) are powerful tools that can be used for spatiotemporal analysis. The hierarchy feature associated with Bayesian modeling enhances the accuracy and precision of spatiotemporal predictions. This paper leverages the hierar...
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Usman Mahmood, Zening Fu, Vince D. Calhoun and Sergey Plis
Functional connectivity (FC) studies have demonstrated the overarching value of studying the brain and its disorders through the undirected weighted graph of functional magnetic resonance imaging (fMRI) correlation matrix. However, most of the work with ...
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Luca Bergamaschi
The aim of this survey is to review some recent developments in devising efficient preconditioners for sequences of symmetric positive definite (SPD) linear systems ????????=????,??=1,?
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arising in many scientific applications, ...
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