Abstract: A method for searching a path by using a 3D reconstructed map includes: receiving 3D point-cloud map information and 3D material map information; clustering the 3D point-cloud map information with a clustering algorithm to obtain clustering information, and identifying material attributes of objects in the 3D point-cloud map information with a material neural network model to obtain material attribute information; fusing the those map information based on their coordinate information, thereby outputting fused map information; identifying obstacle areas and non-obstacle areas in the fused map information based on an obstacle neural network model, the clustering information, and the material attribute information; and generating 3D path information according to the non-obstacle areas. Since the 3D path information is generated based on those map information, the obstacle areas and flight spaces are effectively determined to generate an accurate flight path.

Abstract: A semiconductor structure includes a source/drain feature in the semiconductor layer. The semiconductor structure includes a dielectric layer over the source/drain feature. The semiconductor structure includes a silicide layer over the source/drain feature. The semiconductor structure includes a barrier layer over the silicide layer. The semiconductor structure includes a seed layer over the barrier layer. The semiconductor structure includes a metal layer between a sidewall of the seed layer and a sidewall of the dielectric layer, a sidewall of each of the silicide layer, the barrier layer, and the metal layer directly contacting the sidewall of the dielectric layer. The semiconductor structure includes a source/drain contact over the seed layer.

Abstract: The invention provides a real-time control and navigation system for watercrafts environmental risk, which has a processor, a 3D radar, an inertial sensor and a global positioning system (GPS) configured on the watercrafts. The 3D cloud point detected by the lidar sensor is converted into a 2D point cloud, the processor converts the coordinates of the 2D point cloud according to the GPS, and the image algorithm calculates the position of the obstacle according to the real-time condition of the watercrafts detected by the inertial sensor, and then navigate the path of the watercrafts. The present invention can improve the position accuracy of the obstacles on the water, and the path navigation also improves the safety of the route by considering the required margin for the running of the watercrafts itself.

Abstract: The present disclosure provides an automatic berthing image ranging system for vessels and operation method thereof, the method comprising: obtaining a reference image around a position in which a vessel is located, the reference image comprises a first pattern and at least two second patterns; the reference image is projected to a reference plane to generate projection coordinates corresponding to the first pattern and the at least two patterns; determining a positional relationship between the vessel and a port by a predetermined distance, and the positional relationship is represented by an angle value.

Abstract: The present disclosure provides an automatic berthing image ranging system for vessels and operation method thereof, the method comprising: obtaining a reference image around a position in which a vessel is located, the reference image comprises a first pattern and at least two second patterns; the reference image is projected to a reference plane to generate projection coordinates corresponding to the first pattern and the at least two patterns; determining a positional relationship between the vessel and a port by a predetermined distance, and the positional relationship is represented by an angle value.

Abstract: A data processing method is proposed, including: sensing, via at least one sensing portion, target information of a target device; receiving and processing, via an electronic device, the target information of the sensing portion to form feature information; processing, via the electronic device, the feature information into a label matrix, and establishing, via an artificial intelligence training method, a target model based on the label matrix; and after the electronic device captures real-time information of the target device, predicting, via the target model, a life limit of the target device, wherein a content of the target information is corresponding to a content of the real-time information. Thus, a good target model is constituted and is advantageous in training artificial intelligence by processing the feature information into the label matrix.

Abstract: This invention discloses an inland river Lidar navigation system for vessels, comprising a receiver, a memory, a processor and a display. The processor coupled to the receiver and the memory, and the display coupled to the processor. Overall, the inland river navigation Lidar system based on Lidar is able to make use of the preset map data identification uncalculatable points of a point cloud of the predetermined procedure, thereby removing of the alignment step in traditional method can be omitted. Therefore, the processing speed can be improved.

Abstract: The present invention discloses an autonomous vessel simulation system, comprising an environment model building system, a vessel model building system and a central processing system. The environment model building system builds at least one environment model; the vessel model building system builds at least one vessel model and an operation module of the central processing system integrates the environment model and the vessel model. The vessel model is navigated in the environment model according to at least one navigational parameter, and a display module displays the navigation status of the vessel model. In addition, an operating method of the autonomous vessel simulation system is also provided.

Abstract: A data processing method is proposed, including: sensing, via at least one sensing portion, target information of a target device; receiving and processing, via an electronic device, the target information of the sensing portion to form feature information; processing, via the electronic device, the feature information into a label matrix, and establishing, via an artificial intelligence training method, a target model based on the label matrix; and after the electronic device captures real-time information of the target device, predicting, via the target model, a life limit of the target device, wherein a content of the target information is corresponding to a content of the real-time information. Thus, a good target model is constituted and is advantageous in training artificial intelligence by processing the feature information into the label matrix.