6results about How to "Significant good" patented technology

The application discloses an abnormal flow cooperative detection method and system, relates to the field of network communication, and comprises the following steps: protocol adaptive identification and dynamic attack detection are carried out on a north-south WAF layer, attack fingerprints are generated, and global session IDs are bound; the application behavior is monitored in a whole link on an east-west RASP layer, context association and threat analysis are realized through the session IDs; WAF and RASP data are aggregated based on the session IDs, an attack feature propagation graph is constructed, and attack chain confidence is evaluated; when the confidence exceeds a threshold value, attack features are extracted by the RASP layer, virtual patch rules are generated, and feedback is fed back to the WAF layer for real-time updating; finally, bidirectional confidence fusion decision is realized through the WAF and the RASP, and cooperative blocking is realized. The application solves the problem that the north-south and east-west detection are split in the prior art, and cross-layer attack chains cannot be effectively blocked, realizes accurate and dynamic protection on complex attacks, especially encrypted flow and horizontal penetration.

The utility model relates to the technical field of safety helmets, in particular to an intelligent safety helmet of a scooter. The device is characterized by comprising a control unit, a warning lamp unit and a wireless communication unit, the wireless communication unit is connected with the control unit in a matched mode, the control unit is connected with the warning lamp unit in a matched mode, and the wireless communication unit is used for receiving steering information transmitted by a scooter controller and transmitting the steering information to the control unit. And the control unit controls the warning lamp unit to generate light warning according to the steering information. The safety helmet can play a role in warning pedestrians or other vehicles, and is high in safety.

The invention provides a ship type detection method and device based on improved YOLOv5. A lighter GhostConv convolution module is adopted as the main convolution operation of YOLOv5, meanwhile, a CA attention module is introduced, channel information and position information related to the direction are fully considered, the parameter quantity and the calculated quantity of the model are remarkably reduced, sufficient flexibility and light weight are guaranteed, and different types of operation ships on the sea can be accurately detected in real time by means of the device.

The invention provides a mark alignment method for a coaxial blurred image of a projection photoetching machine, which belongs to the field of photoetching, and comprises the following steps of: firstly, preprocessing an acquired image, including contrast enhancement and edge feature enhancement, so as to improve the visibility of key features in the image; then, through frequency domain analysis and a Gaussian filter, noise and background interference in the image are suppressed, and the significance of a target area is highlighted; then, carrying out binarization processing by using a gray histogram of the image, and extracting a key feature region in the pattern; and finally, accurately positioning the central positions of the mask and the workpiece stage alignment plate mark pattern through a shape matching method, and finally calculating the deviations of the workpiece stage alignment plate mark pattern relative to the mask mark pattern in the X direction, the Y direction and the rotation angle (R direction). The method not only can adapt to a complex image environment, but also can ensure a high-precision alignment effect in the photoetching process, and is suitable for the precision overlay requirement in the manufacturing of a high-density integrated circuit.

The application discloses an incomplete multi-omics cancer subtype identification method, system, device and medium, and belongs to the technical field of bioinformatics and artificial intelligence. The method comprises the following steps: incomplete multi-omics data acquisition and preprocessing; constructing an entry-level observation mask matrix and a view availability mask matrix; constructing a feature module in the omics based on a granulocyte division; extracting a module-level skeleton representation; recovering an entry-level missing value based on the skeleton structure; constructing a multi-expert skeleton recovery integrated result; constructing a central feature matrix of the feature module; constructing a cross-omics consensus structure space; performing a mask-aware skeleton consensus alignment; performing adaptive view weighting based on structure reliability; performing sample-level mask-aware fusion; and outputting a cancer subtype clustering result. The application provides reliable technical support for cancer typing research, patient stratification analysis, prognosis evaluation and precision medicine auxiliary decision-making.

The application provides a tunnel lining surface crack detection method and system, and relates to the technical field of tunnel engineering. The method comprises the following steps: obtaining the lining surface image and crack label of a detected tunnel and the lining surface image of a to-be-detected tunnel; performing feature extraction on the lining surface image based on a visual cell mechanism to obtain the perception feature map of the detected tunnel and the to-be-detected tunnel; performing embedding mapping and contrast learning constraint on the perception feature map of the detected tunnel and the crack label to obtain a crack embedding space; mapping the perception feature map of the to-be-detected tunnel to the crack embedding space, and performing distribution alignment on the embedding features of the detected tunnel and the to-be-detected tunnel in the crack embedding space through an adversarial mechanism; and generating the lining surface crack detection result of the to-be-detected tunnel through the aligned crack embedding space. The application solves the problem that the crack feature distribution is inconsistent in different tunnel scenes in the existing detection method, which leads to the difficulty in stably distinguishing cracks from non-cracks.