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Marco Scutari
Bayesian networks (BNs) are a foundational model in machine learning and causal inference. Their graphical structure can handle high-dimensional problems, divide them into a sparse collection of smaller ones, underlies Judea Pearl?s causality, and determ...
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Bao Liu, Maarten Vanierschot and Frank Buysschaert
The present work examines the capabilities of two transition models implemented in ANSYS Fluent in the open-water performance prediction of a rim-driven thruster (RDT). The adopted models are the three-equation ??-????-??
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and the four-equati...
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Erdem Dikbas and Özgür Ugras Baran
In this study, we present our improved RANS results of the missile aerodynamic flow computation involving leading edge vortex separation. We have used our in-house tailored version of the open source finite volume solver FlowPsi. An ongoing study in the ...
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K. L. Kostenko, T. M. Serdiuk, V. V. Skalko
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Xueying Zhao, Zhi Tian, Lintao Cheng, Jia Jiang, Yujiao Liu, Lizhi Liu, Chunxu You, Xun Liu, Fuchun Xie, Ligang Qin and Yajun Chen
White clover (Trifolium repens L.) is one of the legume herbages with high feed quality, but it is sensitive to water deficiency. The objectives of this study were to compare morpho-physiological responses to drought stress and post-drought recovery in f...
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Yi Zhang, Lanxin Qiu, Yangzhou Xu, Xinjia Wang, Shengjie Wang, Agyemang Paul and Zhefu Wu
Software-Defined Networking (SDN) enhances network control but faces Distributed Denial of Service (DDoS) attacks due to centralized control and flow-table constraints in network devices. To overcome this limitation, we introduce a multi-path routing alg...
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Yuefeng Cen, Mingxing Luo, Gang Cen, Cheng Zhao and Zhigang Cheng
It is meaningful to analyze the market correlations for stock selection in the field of financial investment. Since it is difficult for existing deep clustering methods to mine the complex and nonlinear features contained in financial time series, in ord...
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Xing Wu, Yifan Jin, Jianjia Wang, Quan Qian and Yike Guo
Large-scale automatic speech recognition model has achieved impressive performance. However, huge computational resources and massive amount of data are required to train an ASR model. Knowledge distillation is a prevalent model compression method which ...
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Shunlei Li, Muhammad Adeel Azam, Ajay Gunalan and Leonardo S. Mattos
Optical coherence tomography (OCT) is a rapidly evolving imaging technology that combines a broadband and low-coherence light source with interferometry and signal processing to produce high-resolution images of living tissues. However, the speckle noise...
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Yining Ma, Suri Guga, Jie Xu, Yulin Su, Xingpeng Liu, Zhijun Tong and Jiquan Zhang
The negative impact of high-temperature disaster on agricultural production is becoming more and more serious, and reducing the vulnerability to high-temperature disaster is fundamental to achieving sustainable agricultural development. This study is mai...
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