4 results about "Natural sequence" patented technology

The application relates to the technical field of ID generation, in particular to a dynamic self-description unique ID generation method and system. The method comprises the following steps: S1, obtaining an instance code, and calculating the effective binary bit number of the instance code as a length indication field; S2, obtaining a current system timestamp, performing a rollback state judgment based on the timestamp and a historical time maintained by the system, setting a rollback state field according to a judgment result, and the rollback state field at least comprising a rollback identification bit and a plurality of cycle state counter bits; the rollback identification bit is used for identifying whether in a time rollback window, and the cycle state counter bits are used for distinguishing different running periods and continuous rollback events; S3, comparing the relationship between the length indication field and a preset mode switching threshold, and determining an ID dynamic part according to a comparison result, wherein the dynamic part comprises an instance code and a natural sequence number; and S4, splicing the timestamp, the length indication field, the rollback state field and the dynamic part to obtain a globally unique ID.

According to the method for improving the crosspiece chart, the super crosspiece chart obtained through the method, the terminal product of the super crosspiece chart and the storage medium of the super crosspiece chart, a string of work completed in a natural sequence in the longitudinal axis direction of the crosspiece chart is combined into one work to be expressed, and the work is defined as a work set; a different code name is correspondingly set for each subitem work under the work set to serve as an assignment of each subitem work, and the same type of work of different work sets has the same code name; the code names of the sequential sub-item work of each work sink are recorded on the corresponding position, representing the work process through the time continuation, of the row where the work sink is located in the crosspiece chart, so that the time continuation expressed by the transverse line of the position is replaced. According to the method, the number of longitudinal tables of the crosspiece chart is greatly reduced, adverse effects on vision and psychology caused by huge increase of the number of lines and the number of the tables are eliminated, the application range of the crosspiece chart is greatly expanded, the method is visual, vivid, simple and clear, and key paths of work are easy to find.

The invention relates to a method for generating a yeast core promoter sequence based on a potential diffusion model. The problems that in the prior art, a promoter sequence generation method is unstable in training, the quality of generated samples is low, and the calculation cost is high are solved. The method comprises the following steps: S1, collecting and preprocessing data; s2, sequence coding; s3, constructing a potential diffusion model; s4, performing model training; s5, generating a new promoter sequence; and S6, comparing the generated sequence with an original natural sequence. The method has the advantages that a potential diffusion model based on deep learning is trained by using an existing saccharomycetes core promoter sequence data set, so that the model learns and has the capability of generating a new saccharomycetes core promoter, high-quality and diversified saccharomycetes core promoter sequences are generated, and the defects that a traditional method is high in calculation cost and high in calculation efficiency are overcome. The generation speed is slow, and the quality of generated samples is poor. The biological experiment cost of the saccharomycetes promoter is reduced, the research process is accelerated, and the industrial fermentation optimization of the saccharomycetes is promoted.

The invention provides a 5G LDPC (Low Density Parity Check Code) hierarchical scheduling decoding method. The 5G LDPC hierarchical scheduling decoding method comprises the following steps: step 1, setting and respectively representing an ith check node and a jth variable node in a PCM (Pulse Code Modulation); sums are set as messages from transmitted verification to variables and messages from transmitted variables to verification in the t-th iteration respectively; if yes, a posterior probability message of the jth coding bit in the tth iteration is represented, and a normalized minimum sum hierarchical decoding algorithm is executed; and step 2, generating a decoding updating sequence of each layer different from a natural sequence in the check matrix by adopting a hierarchical scheduling algorithm. According to the scheme, the average number of iterations of decoding is reduced while the decoding performance is improved, and the complexity of the decoding process is almost not required to be increased in the improvement.