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Alexander Isaev, Tatiana Dobroserdova, Alexander Danilov and Sergey Simakov
This study introduces an innovative approach leveraging physics-informed neural networks (PINNs) for the efficient computation of blood flows at the boundaries of a four-vessel junction formed by a Fontan procedure. The methodology incorporates a 3D mesh...
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Henrique José Wilbert, Aurélio Faustino Hoppe, Andreza Sartori, Stefano Frizzo Stefenon and Luís Augusto Silva
While there are several ways to identify customer behaviors, few extract this value from information already in a database, much less extract relevant characteristics. This paper presents the development of a prototype using the recency, frequency, and m...
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Shuaipeng Gao and Tijing Cai
Gravity-aided navigation is an effective navigation method for underwater vehicles. However, the distribution of the gravity field may affect the measurement errors of gravity anomalies and the precision of gravity-aided navigation. In this paper, the up...
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José Pinto, João R. C. Ramos, Rafael S. Costa and Rui Oliveira
In this paper, a computational framework is proposed that merges mechanistic modeling with deep neural networks obeying the Systems Biology Markup Language (SBML) standard. Over the last 20 years, the systems biology community has developed a large numbe...
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Haoyuan Cheng, Qi Chen, Xiangwei Zeng, Haoxun Yuan and Linjie Zhang
In response to the critical need for autonomous navigation capabilities of underwater vehicles independent of satellites, this paper studies a novel navigation and control method based on underwater polarization patterns. We propose an underwater course ...
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