13 results about "Independent samples" patented technology

The utility model discloses a sample adding device and a sample adding instrument, the sample adding device comprises a sample adding base, a batch sample adding needle group and an independent sample adding needle group, the batch sample adding needle group is fixedly arranged at the bottom of the sample adding base, and a batch sample adding assembly comprises a plurality of batch sample adding needle rods which are arranged in parallel; the independent sample adding needle group is arranged on one side of the sample adding base in a sliding manner. When the independent sample adding needle group slides to the retraction position, the sample adding parts of all the batch sample adding needle rods exceed the independent sample adding needle group so as to realize batch sample adding; when the independent sample adding needle group slides to the extending position, the independent sample adding needle group exceeds the sample adding part of all the batch sample adding needle rods so as to realize independent sample adding. According to the utility model, the telescopic independent sample adding needle group is arranged, so that the task of adding a plurality of samples can be realized by virtue of the batch sample adding needle group, and the tasks of adding a small amount of samples and supplementing samples at leakage points can also be realized by virtue of the independent sample adding needle group, the types of tasks which can be completed are richer, the application scenes are increased, and the adaptability is effectively improved.

The invention relates to the technical field of metallurgical sampling devices, in particular to a metallurgical detection sampling device. Comprising an auxiliary pipe and a sampling pipe, the lower portion of the sampling pipe is spirally arranged to form a sampling part, a positioning plug and a plurality of sampling balls are contained in the auxiliary pipe, the positioning plug is located on the upper sides of the sampling balls, the lower end of the auxiliary pipe is communicated with the lower end of the sampling part to form a feeding section, and the outer end of the feeding section is detachably connected with a limiting ring; the inner diameter of the limiting ring is smaller than the diameter of the sampling ball; the diameter of the sampling ball is the same as the inner diameter of the sampling part, air enters the upper end of the auxiliary pipe, air pressure pushes the positioning plug and the sampling ball to move downwards into the feeding section, the upper end of the sampling pipe sucks, the sampling ball moves upwards along the sampling part, molten steel is driven to move upwards along the sampling part, and sampling is completed. Each group of balls can independently drive molten steel to rise under the driving of air pressure, and the subsequent sampling balls can separate the extracted molten steel samples and synchronously extract new samples, so that multiple independent samples can be obtained at one time, and the detection efficiency is greatly improved.

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 utility model discloses a portable sampling box for agricultural product detection, which comprises a shell, an integrally formed lining shell is inserted in the shell, two rows of clamping grooves arranged at equal intervals are formed in the lining shell, a classification sampling box is inserted in the clamping grooves, the top of the lining shell is fixedly connected with a convex block, and the convex block is fixedly connected with the bottom of the lining shell. And three groups of positioning pieces are mounted on the convex block. According to the utility model, the clamping blocks are used for limiting and closing the sealing covers again by utilizing the extrusion force of the transverse springs, when one type of samples need to be taken independently, only the corresponding convex blocks need to be pressed to repeat the operation for opening, other sealing covers can not be influenced to realize independent sample taking and placing, and after all the sealing covers are opened, the other sealing covers can be opened. At the moment, the lining shell can be directly drawn out, and the classified sampling box can be independently drawn out and is convenient to clean, so that the device has the advantages that classified samples can be independently taken during taking, other samples cannot be polluted, and the inner wall is convenient to clean.

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 utility model discloses a sample adding device and a sample adding instrument, the sample adding device comprises a batch sample adding assembly and an independent sample adding needle group, the batch sample adding assembly comprises a plurality of fixed sample adding needles which are arranged in parallel, and the independent sample adding needle group comprises at least one telescopic sample adding needle which is telescopically arranged relative to the fixed sample adding needles; when the independent sample adding needle group is in an independent sample adding mode, the telescopic sample adding needle extends out and exceeds all the fixed sample adding needles, so that independent sample adding is realized; when the batch sample adding assembly is in a batch sample adding mode, the telescopic sample adding needle retracts, all the fixed sample adding needles exceed the telescopic sample adding needle, and batch sample adding is achieved. The sample adding processes of the batch sample adding needle group and the independent sample adding needle group are mutually independent and do not interfere with each other, a plurality of sample adding tasks can be realized by virtue of the batch sample adding needle group, a small amount of sample adding and leakage point sample supplementing tasks can be realized by virtue of the independent sample adding needle group, manual participation is not needed in the sample adding process, the automation degree is relatively high, and the sample adding efficiency is high. And the sample adding efficiency is high.

The invention discloses a static detection method and device for malicious code injection attacks of an intelligent system, and the method comprises the steps: firstly, obtaining an example code list from a target intelligent device, splitting the example code list into a plurality of independent samples, each sample containing an instruction character string and a corresponding executable code character string, and forming a split list together; thirdly, performing feature vectorization on the instruction character string and the executable code character string of each sample in the split list to obtain an instruction feature vector and an executable code feature vector, and forming a feature vector list; then, calculating the semantic similarity between the instruction feature vector and the executable code feature vector of each sample to obtain a self-consistency score, and forming a global sample self-consistency score list; and finally, performing anomaly detection on the basis of the list, and marking the sample of which the self-consistency score is remarkably deviated from the majority score as a malicious code injection attack suspicion sample. The method solves the problem that malicious code injection attacks are difficult to effectively detect.

The invention discloses high-flux heating equipment and a control method thereof. Relates to the technical field of experimental instruments and aims to solve the problems of low heating efficiency and limited sample processing capacity of traditional heating equipment. A to-be-heated sample is placed on a sample table, the sample table supports a plurality of independent to-be-heated samples to be placed, a controller controls a sample table moving module to move, so that one or more target to-be-heated samples of the sample table are sequentially located below a heater, and the heater efficiently transmits energy to heat the sample through heat radiation. And parallel heating treatment of various samples can be completed in a single experiment. Various types and a large number of samples can be efficiently processed in the single heating process, the experiment period is remarkably shortened, the data output efficiency is improved, diversified experiment requirements are met, and the whole experiment operation process is optimized.

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 present invention belongs to the field of teaching experiments, and specifically discloses a safety culture basic teaching experiment research method and system. The method includes: using a literature review method to summarize and organize existing definitions of safety culture and concretize safety culture elements; selecting a safety culture measurement questionnaire as a quantitative measurement method for safety culture, selecting a corresponding safety culture definition and the safety culture elements involved to set up a questionnaire; according to the specific personnel composition and corresponding proportion of the measured unit, selecting a suitable sampling method to calculate the sample capacity, and collecting and organizing questionnaires after conducting quantitative measurements of safety culture on teachers and students in the school; conducting reliability and validity tests, independent sample tests and single-variance factor analysis on the collected valid questionnaires, and proposing corresponding improvement measures for the measured unit based on the analysis results. The present invention designs a hybrid teaching model to improve and perfect teaching methods and enhance students' innovation and practical ability in safety culture learning.

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.

This invention relates to an adversarial active learning method based on independence enhancement. It includes the following steps: 1. Using a generator to reconstruct samples to learn their feature representations, and concatenating these representations with annotation features extracted from the task model; 2. Designing a Batch Loss Prediction Module (BLPM) to re-label the state values ​​of the samples, and training the discriminator based on the new state values; 3. Designing an independent sample selection module based on hierarchical clustering to perform independence selection on the samples, labeling the selected samples, adding the labeled samples to the label pool, and updating and training the model. This invention not only considers the information content of a single sample but also takes into account the independence between samples within a group, while reducing the total labeling cost.