Titlebook: Recent Advances in Next-Generation Data Science; Third Southwest Data Henry Han Conference proceedings 2024 The Editor(s) (if applicable) a

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Common-Migraine

Data Entropy-Based Imbalanced Learning,ce among classes in machine learning. However, our recent study challenges this notion. We argue that the bias of classification performance comes from the imbalance of information of classes rather than just that of observations. To reflect the information imbalance of classes, we propose an indica

畢業(yè)典禮

Analysis of the Changes in Microbial Community During the Fermentation of Feng-Flavour Baijiu,ns of Feng-flavour Baijiu. A total of 133 fungi and 688 bacteria were detected at the genus level. The dominant fungi were . and . while the dominant bacteria are . and . The composition of the dominant microorganism in the fermented grains of Feng-flavour Baijiu was different from other flavor Baij

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貴族

,Classification of?In-Situ Solar Wind Data Measured by?Solar Orbiter/SWA-PAS and?HIS Using Machine Lnge can now be addressed using modern AI/ML techniques and big data analysis algorithms. In this work, we apply state-of-the-art AI/ML technology on in-situ solar wind measurements made by the Heavy Ion Sensor (HIS) and Proton and Alpha Particle Sensor (PAS) onboard the recent Solar Orbiter mission

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,Node Classification with?Multi-hop Graph Convolutional Network,tructures, and retaining structural and feature information within the node vectors. However, incorporating global structures into the latent representation is frequently overlooked despite being a central focus of many random-walk-based embedding techniques predating the advent of graph neural netw