Abstract: The present invention discloses a right-angle turning method for small-diameter TBM exploration adit excavation and belongs to the field of geological exploration of water conservancy and hydropower projects.

Abstract: Provided is a globally optimal robot visual positioning method and device based on point-line features. The method comprises the following steps: acquiring a priori three-dimensional map of a current scene constructed in advance; acquiring a current image of the robot and the inertial measurement data; calculating a pitch angle and a roll angle of the current robot pose according to the current inertial sensor data and the inertial sensor data in the priori map; matching the two-dimensional point-line features detected in the current image with three-dimensional point-line features in a priori map; separating the rotation and translation of the pose to be solved according to the matched feature pairs, solving the rotation and then solving the translation so as to complete the dimensionality reduction of the search space.

Abstract: Disclosed are various approaches for providing a natural language interface for searching databases. A natural language query is parsed to identify a plurality of tokens. At least one operator is identified with a machine-learning model based at least in part on the plurality of tokens. Next, at least one attribute and at least one respective attribute value are identified with a machine-learning model based at least in part on the plurality of tokens. Then, at least one constraint is identified with a machine-learning model based at least in part on the plurality of tokens. Finally, a machine language query is generated based at least in part on the at least one operator, the constraint(s), the attribute(s), and the respective attribute value(s).

Abstract: Disclosed are various approaches for providing a natural language interface for searching databases. A natural language query is parsed to identify a plurality of tokens. At least one operator is identified with a machine-learning model based at least in part on the plurality of tokens. Next, at least one attribute and at least one respective attribute value are identified with a machine-learning model based at least in part on the plurality of tokens. Then, at least one constraint is identified with a machine-learning model based at least in part on the plurality of tokens. Finally, a machine language query is generated based at least in part on the at least one operator, the constraint(s), the attribute(s), and the respective attribute value(s).

Abstract: A shutdown verification method executed by a mobile terminal is provided. At first, a shutdown command is received. Then, a shutdown verification prompt which requests a verification input is output. After the verification input is received, the verification input is compared with preset verification data previously stored in the mobile terminal. At last, the mobile terminal is shut down if the verification input matches the preset verification data. A shutdown verification device corresponding to the shutdown verification method is also provided. The mobile terminal cannot be shut down without verification. Therefore, malicious shutdown of the mobile terminal is avoided.