Abstract: The present invention relates to the technical field of network security, and in particular to an abnormal data detection method, system and device for industrial Internet. This detection method compares data distribution of an initial node with a normal feature expression performance in first normal data distribution subject to extraction processing to obtain a first anomaly score, compares the data distribution of the initial node with the normal feature expression performance in second normal data distribution subject to enhancement processing to obtain a second anomaly score, obtains a risk level of the node based on the first anomaly score and the second anomaly score, and immediately provides corresponding limits on a node communication permission; and the method provides dual detection, is high in accuracy and stable in detection results, and facilitates the maintenance of industrial Internet security.

Abstract: The present invention relates to the technical field of network security, and in particular to an abnormal data detection method, system and device for industrial Internet. This detection method compares data distribution of an initial node with a normal feature expression performance in first normal data distribution subject to extraction processing to obtain a first anomaly score, compares the data distribution of the initial node with the normal feature expression performance in second normal data distribution subject to enhancement processing to obtain a second anomaly score, obtains a risk level of the node based on the first anomaly score and the second anomaly score, and immediately provides corresponding limits on a node communication permission; and the method provides dual detection, is high in accuracy and stable in detection results, and facilitates the maintenance of industrial Internet security.

Abstract: The invention relates to the technical field of image processing, and in particular to a method, a system and a device for acquiring a seaweed bed area, and a storage medium. In the acquisition method, firstly, an initial seaweed bed image with fog is firstly subjected to the fog thickness removal which is convenient for quick calculation, checking whether the quality of the fog thickness removal chart meets the requirements. If the quality of fog thickness removal chart is not up to the standard, a more detailed fog concentration removal method is used to improve the image quality of the initial seaweed bed image until the fog concentration removal chart is up to the standard and then feature extraction is performed. If the quality of fog thickness removal chart is up to the standard, the feature extraction is performed directly.

Abstract: The present invention discloses a human-robot collaboration method based on a multi-scale graph convolutional neural network. The method includes the following steps: S1, data acquisition: acquiring a dataset of a human skeleton in human-robot collaboration scenes, and performing pre-processing to obtain pre-processed data; S2, model training: loading the pre-processed data, and obtaining a human behavior recognition network model by training a multi-scale graph convolutional neural network; S3, human behavior recognition: predicting human behaviors through a trained deep learning network model; and S4, human-robot interaction: sending predicted information to a robot system through a communication algorithm, and enabling a robot to make action plans based on the human behaviors. By the human-robot collaboration method based on a multi-scale graph convolutional neural network disclosed by the present invention, a robot can predict human behaviors and intents in real scenes and make correct interaction.

Abstract: The invention relates to the field of blockchain technologies, and is particularly a method, system and device for detecting an abnormal node in a blockchain and a storage medium. In the detection method, node data are extracted and analyzed in a defeatured manner through various information sources, and finally, a high-quality graph structure with high accuracy, strong applicability and small error is obtained, so that high-order neighbor features with rich feature information are obtained, thus being convenient for further classified detection, improving the accuracy of detection results, and being beneficial for maintaining the safety of blockchain.

Abstract: Disclosed are a control method, system and device with edge cloud service stability. The control method comprises the following steps of: first step: acquiring quality data of a task executor, monitoring data of an edge server, reward data of a task requester and supervision data of a cloud platform; second step: establishing revenue functions of the task executor, the cloud platform, the task requester and the edge server to obtain replication dynamic equations; and third step: establishing a Jacobian matrix to obtain a system stabilization strategy. Through the combination of the cloud platform and the edge server, a transmission amount of remote data is reduced, a time delay of network transmission is reduced, and an operation cost of the network is reduced.

Abstract: A hydrogen-bonded organic framework nanosheet, a preparation method and application thereof are provided. The preparation method includes in a small heat-resistant glass container, mixing 1,2,4,5-tetrakis (4-carboxyphenyl) benzene (H4TCPB) with N,N-dimethylformamide (DMF), heating until the solid is dissolved, placing the uncapped small glass container in a large heat-resistant glass container filled with some water, sealing the large glass container, standing and heating the large glass container in a constant-temperature oven to obtain colorless crystals, suction filtering to obtain a solid material, drying, grinding, and then dispersing the solid material in a solvent, performing ultrasonication in an ice-water bath, centrifuging to discard supernatant, and drying to obtain the hydrogen-bonded organic framework nanosheets.

Abstract: A suspended bed electro-membrane bioreactor system is provided, including a cathode chamber with a tubular structure with a sealed bottom; an anode chamber with a tubular structure located in the cathode chamber, where there is a gap between an outer wall of the anode chamber and an inner wall of the cathode chamber, and the anode chamber is provided with a proton channel region in a middle, is fixedly connected with an anode cover plate in a top and is filled with an anode assembly; a stainless steel membrane module located in the gap and electrically connected with the anode assembly; a polymethyl methacrylate partition plate located in the gap, forming a closed cylindrical space with the stainless steel membrane module and communicating the cathode chamber and the anode chamber; and a suspended bed filled between the closed cylindrical space and the anode chamber.

Abstract: Disclosed is a method for detecting a block chain abnormal behavior based on graph embedding. The method comprises S100: data collection: acquiring public block chain abnormal behavior node data on the Internet, and acquiring normal nodes in a number equal to that of abnormal behavior nodes at the same time; S200: establishment of abnormal behavior recognition model: extracting features of all nodes, constructing the nodes subjected to feature extraction into a transaction graph, and forming the abnormal behavior recognition model based on a graph embedding technology according to the constructed transaction graph; and S300: transaction detection: determining a transaction risk according to the obtained abnormal behavior recognition model when a transaction occurs, and prompting a user of a risk level. According to the method for detecting the block chain abnormal behavior based on graph embedding, abnormal behaviors possibly existing in block chain transactions can be effectively detected and early warned.

Abstract: The present invention discloses a double cantilever beam-encoding lead screw combined sensing tensile test method and machine. The double cantilever beam-encoding lead screw combined sensing tensile test machine comprises a main frame, a standard, a test piece and a microcomputer numerical control unit. The main frame is a force-deformation combined sensing mechanism composed of a double cantilever beam sensor, an encoding lead screw and a drive device. The double cantilever beam sensor is composed of a fixed cantilever beam sensor and a movable cantilever beam sensor. The encoding lead screw is composed of a drive lead screw and a tristate encoder. The double cantilever beam sensor matches with the encoding lead screw to achieve three functions, namely, test piece clamping, force sensing and deformation sensing, as well as to measure the size of the test piece.

Abstract: A method for preparing carbon nanotubes graphene modified aqueous polyurethane coatings and adhesives, which includes the steps of: (a) preparing carboxylated carbon nanotubes graphene nano-sheets; (b) mixing polytetrahydrofuran ether glycol with isophorone diisocyanate for reaction in the presence of dibutyltin dilaurate; and then adding 2-sulfobenzoic anhydride, carboxylated carbon nanotubes and graphene sheet into the mixture and allowing reaction under 90° C. for 2 hours to obtain a polyurethane prepolymer A; and (c) adding chain extender and acetone into the prepolymer A and allowing reaction under 65° C. to 75° C., adding D-panthenol and 2,4,6-trihydroxy benzoic acid and allowing reaction under 75° C. to 85° C. for 0.

Abstract: The present invention relates to a benzothiazole derivative of formula 1 or a pharmaceutically acceptable salt thereof and a process for preparation thereof. The present invention also relates to a pharmaceutical composition comprising the compounds and the use of the compounds in the preparation of an anti-tumor medicament.

Abstract: The present invention relates to a pyrazolo[1,5-a]pyrimidine derivative of general formula 1 and a pharmaceutically acceptable salt thereof. The present invention also relates to use of compounds of formula 1 in the preparation of an anti-tumor medicament.