5 results about "Independent samples" patented technology

The application belongs to the technical field of deep learning, and discloses a time sequence anomaly detection method based on a difference component. First, the original independent samples are changed into dependent samples through permutation and combination of a small sample data set, the number of samples is expanded to obtain combined sequence samples, and then the difference component including a learnable kernel is used to generate a difference feature map of the combined sequence samples, and the difference feature map is input into a feedforward network for training. The application effectively solves the problem of unsatisfactory classification effect between complex data in small sample learning, and proposes a new data expansion method and classification component, so that the classification detection task can be efficiently realized without long time training.

The invention relates to a sample-level task scheduling method and system based on a placeholder command line template, and belongs to the technical field of bioinformatics automatic processing. The method comprises the following steps of: performing automatic sample identification on a data file which is provided by a user and contains sample meta-information, and performing sample isolation; designing a declarative command generation mechanism based on a placeholder template, and generating an executable Shell command for each independent sample; generating an independent sub-process for the Shell command of each sample, and simultaneously running a plurality of tasks in parallel; calculating a new field value of the sample on the basis of a new metadata column and a value template predefined by a user for the sample of which the task is successfully executed, and adding the new field value to an original sample record; after all the samples are processed, a unified output file is generated through combination. According to the method, through the declarative placeholder template and an automatic execution mechanism, experimenters can construct a complex batch bioinformatics analysis process without writing any code, and the technical threshold is remarkably reduced.

The invention discloses a detachable sampling drill rod for stratified collection of radioactive samples. The detachable sampling drill rod comprises an outer sleeve, an inner sleeve and a drill bit. According to the detachable sampling drill rod for stratified collection of the radioactive samples, a drill bit is installed at one end of an outer sleeve, an inner sleeve matched with the outer sleeve is movably connected to the inner side of the outer sleeve, one end of the inner sleeve abuts against the drill bit, the other end of the inner sleeve is flush with the outer sleeve, and three communicating openings are formed in the outer sleeve at equal intervals; the interior of the inner sleeve is divided into three sampling cavities by partition plates, sample inlets corresponding to the sampling cavities are formed in the inner sleeve, the upper end and the lower end of each sample inlet in a section rod of the inner sleeve are closed to form an independent sample storage bin, and the section rod of the outer sleeve is a through pipe. The inner sleeve is rotated, so that the communicating ports in the inner sleeve and the outer sleeve can be aligned, staggered and aligned with the sample inlets, and then the samples do not enter the sampling rod before the sampling rod is tamped into the preset depth, and the samples at the corresponding depths of the sample inlets enter the independent sample storage bins after the sampling rod reaches the preset depth.

The invention relates to a text data set quality evaluation method and device of a power system and computer equipment. The method comprises the following steps: acquiring a text data set of the power system, performing text segmentation on the text data set to obtain independent samples, and distinguishing non-isolated samples and isolated samples from a plurality of independent samples; extracting a sample feature of each non-isolated sample, and performing feature homogeneous analysis on the sample features to obtain a homogeneous coverage index; for each non-isolated sample, obtaining an information overlapping index based on the sample information of the current non-isolated sample and the sample information of each other independent sample; screening out a verification set based on the homogeneous coverage index and the information overlapping index of each non-isolated sample, and taking the isolated samples and the remaining non-isolated samples as a corpus set; and sequentially performing fine tuning processing and verification on the artificial intelligence model of the power system through the corpus set and the verification set to obtain a quality verification result for reflecting the text data set. By adopting the method, the text data set of the power system can be evaluated.

The utility model relates to the technical field of protease detection, in particular to a portable storage box for protease detection, which comprises a heat preservation box body and a sealing cover, a first placing cavity and a second placing cavity are respectively arranged in the heat preservation box body, a plurality of groups of first clamping plates and a plurality of groups of second clamping plates are vertically clamped and connected, and the first clamping plates and the second clamping plates are arranged on the heat preservation box body. A plurality of groups of first clamping plates and second clamping plates jointly divide a plurality of groups of relatively independent sample storage cavities in the first placing cavity and the second placing cavity. The first clamping plate and the second clamping plate can be freely combined and installed, multiple groups of relatively independent sample storage cavities can be flexibly separated according to protease samples of different numbers and sizes, mutual collision and confusion of the samples are avoided, and classified storage and management of the different samples are facilitated; through the arrangement of the label assembly, a corresponding label plate is arranged above each sample storage cavity, relevant information of the samples can be clearly marked through the label plates, and protease detection samples in the heat preservation box body can be conveniently managed.