CPBA-CLIM: An entity-relation extraction model for ontology-based knowledge graph construction in hazardous chemical incident management.

In recent years, hazardous chemical incidents have occurred frequently, resulting in significant human casualties, property damage, and environmental pollution due to human or natural factors. Accurately mining the lessons learned from accumulating incident reports and constructing the knowledge graph for hazardous chemical incident management can assist managers in identifying patterns and analyzing common attributes, thereby preventing the recurrence of similar incidents. This article addresses the challenges of dispersed textual information, specialized vocabulary, and data formats in hazardous chemical incidents.

A cross-modal conditional mechanism based on attention for text-video retrieval.

Current research in cross-modal retrieval has primarily focused on aligning the global features of videos and sentences. However, video conveys a much more comprehensive range of information than text. Thus, text-video matching should focus on the similarities between frames containing critical information and text semantics.

Theoretical analysis and simulation calculation of hydrodynamic pressure pulsation effect and flow induced vibration response of radial gate structure.

This work aims to explore the characteristics of stochastic fluctuant water pressure acted on the surface of large radial gate, and to investigate the flow-induced vibration response of the whole radial gate structure. The finite element calculation model structure of the radial gate is established by taking a large-scale radial gate as prototype to discuss the hydrodynamic pressure acting on the gate leaf with different opening, analyze the dynamic pressure time curves, and achieve the flow-induced vibration response by deeming hydrodynamic pressure as dynamic load. When taking 10% opening of the radial gate, the results indicate that the hydrodynamic pressure distributed on the arc surface of the radial gate changes with the flow conditions, with the maximum pressure occurred at the center of the lower edge of the gate leaf.

A mutually-exclusive binary cross tagging framework for joint extraction of entities and relations.

Joint extraction from unstructured text aims to extract relational triples composed of entity pairs and their relations. However, most existing works fail to process the overlapping issues that occur when the same entities are utilized to generate different relational triples in a sentence. In this work, we propose a mutually exclusive Binary Cross Tagging (BCT) scheme and develop the end-to-end BCT framework to jointly extract overlapping entities and triples.