Abstract: The invention discloses a weighted heterogeneous graph-oriented malicious behavior identification method, system and storage medium. The method comprises the following steps: constructing an inductive graph neural network model. The inductive graph neural network model comprises a subgraph extraction module, a plurality of feature vector generation and fusion modules and a classification learning module; performing training and learning for the inductive graph neural network model, extracting subgraphs, learning the latent vector representation of nodes in the subgraphs, obtaining a plurality of subgraph feature vectors corresponding to the subgraphs, and fusing a plurality of subgraph feature vectors. The node feature vector obtained by fusion is used for classification learning in the classification learning module; using the trained inductive graph neural network model for malicious behavior identification.

Abstract: The invention of biological dura mater patch and a preparation method thereof. Raw material of patch does not come from commercial meat animals, but from breeding animals, such as SIS patch of the sow, has natural good mechanical properties; the method uses plant-derived reagents in the decellularization process, no damage to ECM natural structural base, and retain more active ingredients, has a better ability to induce tissue repair and growth; neither uses a cross-linking agent to enhance mechanical properties, nor synthetic detergents used to remove cells; chemical residues and their toxicity are avoided, while more effective ingredients in ECM, especially GAGs be retained. The patch has soft texture and good toughness, easy to sew tightly, and prevent cerebrospinal fluid leakage; and degradation rate is basically synchronized with the growth of the new dura mater, which is more conducive to repair and regeneration of dura mater.

Abstract: Techniques for identifying air pollution sources based on aerosol retrieval and a glowworm swarm algorithm are described herein. According to these techniques, a satellite remote sensing image is obtained and a wind speed vector is obtained from the satellite remote sensing image. A GSO algorithm is applied, introducing a glowworm similarity correction factor obtained from an attribute value and a wind speed and wind direction correction factor obtained from the wind speed vector, and pollution sources are identified.

Abstract: The present invention discloses a method for retrieving atmospheric aerosol based on statistical segmentation. Firstly a multi-band remote sensing image including an apparent reflectance and an aerosol optical thickness look-up table corresponding to a retrieval band is obtained, then pixels are partitioned and screened according to apparent reflectance segments of a mid-infrared 2.1 micrometer band. After that the retained pixel sets are further partitioned and screened according to the apparent reflectance segments of the mid-infrared 1.6 micrometer band. Finally the obtained pixel sets are partitioned into two categories according to the pixel number, one category including pixels having more pixels, the other including those with less pixels. The category with more pixels is taken as the reference part for retrieval.

Abstract: The present invention discloses a method for retrieving atmospheric aerosol based on statistical segmentation. Firstly a multi-band remote sensing image including an apparent reflectance and an aerosol optical thickness look-up table corresponding to a retrieval band is obtained, then pixels are partitioned and screened according to apparent reflectance segments of a mid-infrared 2.1 micrometer band. After that the retained pixel sets are further partitioned and screened according to the apparent reflectance segments of the mid-infrared 1.6 micrometer band. Finally the obtained pixel sets are partitioned into two categories according to the pixel number, one category including pixels having more pixels, the other including those with less pixels. The category with more pixels is taken as the reference part for retrieval.

Abstract: A method and apparatus for identifying an object are disclosed. The method includes: performing linear feature detection on an image to be identified by using a linear feature detecting method to obtain detected linear features, wherein the linear feature detection method transforms detection of linear features in an image space to detection of extremal points in another space and assigns larger weights to continuous image points than to discrete image points during the transformation by using a continuous cluster factor; and identifying an object to be identified from the detected linear features by considering characteristics of the object to be identified. The method and apparatus for identifying an object of the invention, when used to detect and identify weak linear objects in high resolution remote sensing images, can effectively suppress the system noise and ambient noise, thereby successfully identifying the interested object and avoiding false alarms.

Abstract: The present invention discloses a method for identifying air pollution sources based on aerosol retrieval and a glowworm swarm algorithm.

Abstract: There is provided a portable heating assembly for in situ asphalt road renewal. The assembly includes a housing with a top wall and a plurality of side walls coupled to and extending downwards from the top wall. The top and side walls include insulating material therewithin. The housing has an open end spaced-apart below the top wall. The assembly includes at least one heating plate coupled to the housing and in communication with the open end of the housing. The heating plate is between the side walls. The heating plate is a carbon crystal mica heating plate in one embodiment.

Abstract: A method and apparatus for identifying an object are disclosed. The method includes: performing linear feature detection on an image to be identified by using a linear feature detecting method to obtain detected linear features, wherein the linear feature detection method transforms detection of linear features in an image space to detection of extremal points in another space and assigns larger weights to continuous image points than to discrete image points during the transformation by using a continuous cluster factor; and identifying an object to be identified from the detected linear features by considering characteristics of the object to be identified. The method and apparatus for identifying an object of the invention, when used to detect and identify weak linear objects in high resolution remote sensing images, can effectively suppress the system noise and ambient noise, thereby successfully identifying the interested object and avoiding false alarms.

Abstract: A method for identifying and extracting a linear object from an image is disclosed. The method comprises: acquiring an original image to be processed, wherein the original image is taken by a camera, received through network transmission or copied from a compact disc or a removable disk; preprocessing the original image to obtain an enhanced image; extracting an edge information image from the enhanced image; then extracting linear features by performing, on the edge information image, a linear feature extracting transform improved with a cluster operator; finally; identifying and extracting the linear object by distinguishing the linear object from other linear features by considering characteristics of the linear object to be identified and extracted.

Abstract: A method for identifying and extracting a linear object from an image is disclosed. The method comprises: acquiring an original image to be processed, wherein the original image is taken by a camera, received through network transmission or copied from a compact disc or a removable disk; preprocessing the original image to obtain an enhanced image; extracting an edge information image from the enhanced image; then extracting linear features by performing, on the edge information image, a linear feature extracting transform improved with a cluster operator; finally; identifying and extracting the linear object by distinguishing the linear object from other linear features by considering characteristics of the linear object to be identified and extracted.