Search Results - "XIA, Xiaoxu"
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Scientific Workflow Mining in Clouds
Published in IEEE transactions on parallel and distributed systems (01-10-2017)“…Computing clouds have become the platform of choice for the deployment and execution of scientific workflows. Due to the uncertainty and unpredictability of…”
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Journal Article -
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Subglacial bedforms and landscapes formed by an ice sheet of Ediacaran-Cambrian age in west Henan, North China
Published in Precambrian research (15-07-2020)“…•The well-preserved micro-macro scale subglacial forms and erosional landscapes are widely presented on the surface of the residual Mesoproterozoic quartzite…”
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Efficient Alignment Between Event Logs and Process Models
Published in IEEE transactions on services computing (01-01-2017)“…The aligning of event logs with process models is of great significance for process mining to enable conformance checking, process enhancement, performance…”
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The Firstly Discovered Cosmic Spherules in Carbonaceous Siltstone from the Taizi Formation of the Mesoproterozoic Shennongjia Group, Central China
Published in Acta geologica Sinica (Beijing) (01-06-2017)“…Objective Spherical micro-particles are often preserved in Precambrian sedimentary rocks. Finnish and Chinese scholars have previously discovered carbonaceous,…”
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Discovery of Cosmic Spherules from the Mesoproterozoic Strata and its Significance—in Case of the Ming Tombs Area, Beijing
Published in Acta geologica Sinica (Beijing) (01-02-2020)“…This study covers cosmic spherules derived from the Mesoproterozoic Dahongyu Formation in the Ming Tombs area, Beijing. The cosmic spherules include iron oxide…”
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Heuristic Recovery of Missing Events in Process Logs
Published in 2015 IEEE International Conference on Web Services (01-06-2015)“…Event logs are of paramount significance for process mining and complex event processing. Yet, the quality of event logs remains a serious problem. Missing…”
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Conference Proceeding -
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Exploring the Potential of Flexible 8-bit Format: Design and Algorithm
Published 20-10-2023“…Neural network quantization is widely used to reduce model inference complexity in real-world deployments. However, traditional integer quantization suffers…”
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Journal Article