3 results about "Matrix embedding" patented technology

The invention belongs to the technical field of flow shop scheduling, and discloses a replacement flow shop scheduling method and system based on a multi-view graph neural network, and the method comprises the steps: defining a problem, and constructing a target function and a constraint condition; the method comprises the steps of obtaining a time feature vector of a problem based on the same job node, constructing a node sparse graph, obtaining node matrix embedding based on the time feature vector and the node sparse graph, aggregating the node matrix embedding, obtaining global node embedding, and calculating graph embedding according to the global node embedding; then, node context embedding is constructed, node probability distribution is calculated according to the node context embedding, and jobs are selected according to the node probability distribution until all the jobs are completed; and optimizing model parameters to obtain a final scheduling scheme. According to the method, initial setting time is considered, a multi-feature representation method is provided, the feature information of the problem is extracted and embedded by using a multi-view graph neural network, and stability and high efficiency can be kept on problems of different scales.

A system (100, 200, 300, 1900) including an interlacing apparatus (104, 204, 304, 1902) for producing and separating an interlaced substrate matrix embedded with a planting material (102). The interlacing apparatus (104, 204, 304, 1902) including a first annular table and a second annular table arranged concentrically and configured to rotate in opposite directions. Inner carriers with inner bobbins attach to the first annular table, while outer carriers with outer bobbins attach to the second annular table. Guiding means guide outer substrate strands to alternatively move over and under inner carriers during interlacing for production of the interlaced substrate matrix. For separation of the interlaced substrate matrix an input mechanism feeds the interlaced substrate matrix to a separating point, with annular tables, carriers and bobbins rotating in reverse to wind separated strands onto respective bobbins for reuse.

The application provides a kind of collaborative office encryption method and system based on non-commutative group transformation and perturbation mapping, method includes: extracting the feature matrix of the heterogeneous data to be encrypted, and encoding as initial group element sequence after quantization processing;From the discrete Gaussian distribution sampling error polynomial matrix superimposed to the sequence to introduce perturbation;Conjugate transformation is carried out using the system public key to obtain ciphertext polynomial matrix sequence;Random mask matrix embedding group transformation attribute is generated;Blind processing is implemented by group multiplication, and the accumulated noise norm is limited within the decryption fault boundary by cooperating with the module switching mechanism;Dynamic routing identification is generated by analyzing network path state, and encrypted transmission message is constructed;Secondary blind is carried out on load header using algebraic operator, and network layer plaintext resolvable anti-quantum encryption data is generated.The application can effectively resist quantum computing attack and flow statistical analysis, and protect the efficient and safe flow of heterogeneous data in office environment.