Abstract: A method for extracting a dam emergency event based on a dual attention mechanism is provided. The method includes: performing data preprocessing, building a dependency graph, building a dual attention network, and filling a document-level argument. The performing data preprocessing includes labeling a dam emergency corpus and encoding sentences. Building a dependency graph includes assisting a model to mine a syntactic relation based on a dependency. Building a dual attention network includes weighing and fusing an attention network based on a graph transformer network (GTN) and capturing key semantic information in the sentence. Filling a document-level argument includes filling a document-level argument by detecting a key sentence and ordering a semantic similarity. The method introduces a dependency and overcomes the long-range dependency problem based on the dual attention mechanism, thus achieving high identification accuracy and reducing a lot of labor costs.

Abstract: Disclosed is an intelligent recognition method for a time sequence image of a concrete dam defect. The method includes: extracting a feature sequence of the time sequence image containing the concrete dam defect; matching a located defect with a real defect by using an objective function; adding a loss term based on a tight sensing intersection-over-union to a loss function of a model so as to pay attention to integrity of a defect sequence and improve accuracy; and extracting a defect feature and recognizing a defect type after completing defect location. According to the present disclosure, the time sequence image of the concrete dam defect is detected effectively, so that a defect in a long image sequence can be located and the defect type can be recognized accurately.

Abstract: The present disclosure relates to a testing method and a testing system for a human stress reaction, and a computer-readable storage medium. The testing method for the human stress reaction includes acquiring position information and visual field information of a testee in a virtual road traffic scene after the virtual road traffic scene is established; guiding the testee into a test zone when the testee is within a test-waiting zone and when a visual field direction of the testee faces the test zone, and simultaneously, starting acquiring stress reaction data of the testee; controlling a virtual reality environment module to create a virtual stress event in the test zone after it is determined that the testee is within the test zone, and applying a stimulation to the testee, such that the testee make a stress reaction.

Abstract: A method for extracting a dam emergency event based on a dual attention mechanism is provided. The method includes: performing data preprocessing, building a dependency graph, building a dual attention network, and filling a document-level argument. The performing data preprocessing includes labeling a dam emergency corpus and encoding sentences. Building a dependency graph includes assisting a model to mine a syntactic relation based on a dependency. Building a dual attention network includes weighing and fusing an attention network based on a graph transformer network (GTN) and capturing key semantic information in the sentence. Filling a document-level argument includes filling a document-level argument by detecting a key sentence and ordering a semantic similarity. The method introduces a dependency and overcomes the long-range dependency problem based on the dual attention mechanism, thus achieving high identification accuracy and reducing a lot of labor costs.

Abstract: The present disclosure relates to a testing method and a testing system for a human stress reaction, and a computer-readable storage medium. The testing method for the human stress reaction includes acquiring position information and visual field information of a testee in a virtual road traffic scene after the virtual road traffic scene is established; guiding the testee into a test zone when the testee is within a test-waiting zone and when a visual field direction of the testee faces the test zone, and simultaneously, starting acquiring stress reaction data of the testee; controlling a virtual reality environment module to create a virtual stress event in the test zone after it is determined that the testee is within the test zone, and applying a stimulation to the testee, such that the testee make a stress reaction.

Abstract: A vehicle hood assembly includes a first panel member, a second panel member, and a third panel member disposed between the first panel member and the second panel member. The third panel member includes a corrugated body. The third panel member defines a plurality of panel perforations extending through the corrugated body in order to attenuate kinetic energy imparted to the hood assembly.

Abstract: A vehicle hood assembly includes a first panel member, a second panel member, and a third panel member disposed between the first panel member and the second panel member. The third panel member includes a corrugated body. The third panel member defines a plurality of panel perforations extending through the corrugated body in order to attenuate kinetic energy imparted to the hood assembly.