63 results about "Data sorting" patented technology

The invention discloses an operation index determination method and device for an endoscopic surgery, equipment and a storage medium, and can be applied to the technical field of surgical operation data processing. The method comprises the following steps: firstly, acquiring a surgical operation data set of a target operation object for an endoscopic surgery; the surgical operation data set comprises a plurality of pieces of surgical operation data sorted according to a time sequence. Each piece of surgical operation data comprises five-dimensional data, namely endoscope action data, endoscope type data, instrument action data, instrument type data and surgical object data. And constructing a hidden Markov model by using the surgical operation data set. In the hidden Markov model, the surgical operation described by the surgical operation data is the observed quantity, and the surgical state is the state quantity, and based on the hidden Markov model, the statistical principle is utilized to carry out quantitative evaluation on the surgical operation indexes, so that the accurate evaluation of the surgical operation when a doctor carries out the endoscopic surgery is realized, and the reference effectiveness of the operation indexes is improved.

The disclosure includes a digital twin system. The digital twin allows for real time classification and ranking of data received from a distributed learning knowledge acquirer. The digital twin system ranks the data while the distributed learning knowledge acquirer is performing a drift evaluation. The distributed learning knowledge acquirer uses the ranked data as training data for discriminative AI models. The digital twin system offers more flexibility and precision in ranking the data. The digital twin system is a digital twin providing contextual active dynamic learning to the distributed learning knowledge acquirer's physical system. Digital twin system causes a model driven approach to allow for superior predictive capabilities by being able to examine large state spaces.

The invention relates to an enterprise data analysis method and device, and relates to the technical field of data governance, and the method comprises the steps: carrying out the Text2SQL task fine tuning of a large language model through a low-rank adaptation technology, constructing a structured knowledge base containing an enterprise data dictionary, a field calling relation and a national standard, converting the unstructured industry specification into a structured data standard knowledge base, and realizing knowledge vectorization storage by using an M3E-base vector model; sampling representative samples based on to-be-sorted data fields and retrieving related rules, integrating the representative samples into thinking chain cues, inputting the thinking chain cues into a fine tuning model to generate a labeling classification result, and outputting a data sorting result after multi-model evaluation and verification; generating a regular expression through a retrieval data standard to screen non-standard data, sampling to generate an SQL conversion code, iteratively cleaning until the standard is reached, and outputting standardized data; and finally, executing index optimization and anomaly detection based on the fine tuning model, and receiving natural language query to generate an SQL and a visual report.

The application discloses a circuit and method for long sequence data sorting. The circuit is used for sorting N data in K base, and the maximum element in the data contains m bits in K base. The circuit comprises a radix counting unit, a first address generating unit, a data distribution unit and two sorting buffers. The two sorting buffers are used as a source buffer and a target buffer respectively, and can read data in a given address or write a data into a specified address. The radix counting unit, the first address generating unit and the data distribution unit are connected in sequence. The two sorting buffers are connected with the data distribution unit and the radix counting unit respectively. The data sorting circuit of the application has simple structure, can be flexibly adjusted according to specific requirements, and the data sorting method has linear order time complexity and short sorting time.

The invention provides a method for realizing sorting and screening supporting functions of a PPT table, which comprises the following steps of: S1, receiving a PPT file input by a user, and creating a PPT object; s2, circularly traversing a Table table object in the PPT object, and putting the Table table object into a List set with the name of a table List; s3, reading a script in a self-defined format of the Table table object, and generating a data processing instruction object; s4, preparing data to be filtered in the Table table object; s5, filtering the data; s6, sorting the data; s7, replacing the data in the Table table object; s8, deleting redundant table lines in the Table table object; and S9, generating a PPT file by the PPT object, and returning a result. On the basis of the script in the self-defined format, by analyzing the script, executing corresponding data screening and data sorting operation, replacing the screened data into the PPT table and deleting redundant PPT table rows, sorting and screening of the data in the PPT table are completed, and the PPT table supports sorting and screening functions.

This application provides a data sorting method, a database engine, and a storage medium. In this application, for scenarios involving multi-column sorting, the data rows to be sorted are first grouped according to the clustering column. Then, the sorting is performed between and within each data group according to the sorting column, using the same sorting order. The sorting result obtained in this way retains the clustering characteristics of the clustered columns while essentially ensuring the global order of the data, which is beneficial for improving the computational performance related to the clustered columns. Especially when querying based on the sorting result, it ensures that the performance of queries by data range is largely unaffected, while significantly improving the performance of queries by data grouping.

The application belongs to the technical field of additive manufacturing, and specifically discloses a composite manufacturing contour grinding allowance detection method and system based on point cloud matching. The method comprises the following steps: obtaining external contour data of a printed workpiece; generating a grinding path curve based on the external contour data by using a contour line method; discretizing the grinding path curve to obtain a plurality of discrete points; discretizing a digital model of the printed workpiece into point cloud data, and aligning the point cloud data with the external contour data based on a preset anchor point; sorting the external contour data and generating a triangular mesh model; obtaining the intersection point of the normal extension line of each discrete point and the corresponding triangular sub-face sheet in the triangular mesh model; and taking the Cartesian space distance value between the discrete point and the corresponding intersection point as the grinding allowance value. The application can accurately estimate the grinding allowance value required for completing the in-situ grinding task.

This invention relates to the field of artificial intelligence technology, providing a data sorting method, electronic device, storage medium, and computer program product. The method includes: performing local sorting of data to be processed in parallel using multiple processing units of a parallel processor; each processing unit acquiring a portion of the data to be processed; sorting the acquired portion of data and selecting a preset number of data points as local target data; and performing one or more merge sort operations on the local target data acquired by each processing unit, based on the amount of data to be processed and the hardware resources of the parallel processor, and selecting a preset number of data points as global target data from the merged and sorted data. This invention avoids the huge computational overhead of globally sorting all data to be processed, significantly improving the efficiency and performance of TopK operations.

The embodiment of the invention provides a distributed database query processing method and device, a storage medium and a program product, and relates to the field of distribution. The method comprises the following steps: receiving a query request containing a row number limiting condition and a sorting condition; splitting the line number limiting condition into a plurality of sub-limiting conditions, and generating a plurality of sub-query requests for instructing each storage node to perform data scanning by using the local index based on the sorting condition; distributing the plurality of sub-query requests to corresponding storage nodes for execution; and receiving the intermediate result from each storage node, and processing the intermediate result in a streaming merging mode to obtain a final result. According to the method, the optimization logic of the dynamic splitting row number limiting condition is added, and the response speed of mass data sorting query is increased.

To select an image serving as effective learning data, based on an index, with low load.SOLUTION: A learning data selection apparatus includes: an information addition unit which adds, as meta information of an image, to the image, environment information of a storage region that affects a difficulty level of recognizing an article included in the image obtained by imaging the storage region storing the article, definition information relating to the resolution of the image, and / or inference information based on an output of a model which recognizes the article; and an image selection unit which selects, according to the meta information, an image in a storage unit which stores a plurality of images with the mata information added thereto.SELECTED DRAWING: Figure 3

This specification provides one or more embodiments of a data sorting method and apparatus, relating to the field of database technology. The method includes: determining a sorting key and an associated additional field in a data table, wherein the sorting key stores at least one row of data to be sorted, and the additional field stores additional data corresponding to each row of data to be sorted; storing the at least one row of data to be sorted and the corresponding additional data independently in memory; sorting the at least one row of data to be sorted in memory according to a preset sorting rule; and merging the additional data stored in memory with the sorted at least one row of data to be sorted to obtain a sorting result. By storing the data to be sorted and the additional data separately, this specification allows for the separate retrieval of the data to be sorted during the sorting process, thereby reducing the amount of data that needs to be retrieved during sorting and improving sorting efficiency.

One or more implementations of the present specification provide a data processing method and apparatus, an electronic device, and a storage medium. The method includes: in a process of writing target data in a memory into a disk, in response to receiving a query instruction for the target data, separately querying data from at least one piece of first local data and at least one piece of second local data based on the query instruction, intermediate index layer information of the at least one piece of first local data, and intermediate index layer information of the at least one piece of second local data, and sorting the queried data as a data query result. The first local data includes some data stored in the disk in the target data, the second local data includes some data stored in the memory in the target data, the target data is in a column-stored form, and each column group of the target data corresponds to one piece of second local data.

The application belongs to the field of data processing, and particularly relates to a data sorting method and device, electronic equipment and storage medium, which are used to solve the problem of low efficiency and poor performance when a database is used to sort a large amount of data. The method comprises the following steps: obtaining data records to be sorted, and determining a plurality of fields contained in the data records as sorting fields; converting original values corresponding to each sorting field into information code values; sequentially splicing a plurality of information code values in the order of field priority to obtain a sorting key of the data records; obtaining data records containing the sorting key by combining the sorting key and the data records, and writing the data records into a key-value type database; and obtaining the data records sorted through the key-value type database. The method generates a sorting key containing a plurality of sorting fields by processing a plurality of fields in the data records, and realizes multi-dimensional combined sorting of the data records based on different sorting modes of the plurality of sorting fields, so that the sorting time is shortened and the sorting performance is improved in the case of a large amount of data.

The embodiment of the invention discloses a server anomaly detection and early warning method and device, electronic equipment and a readable medium. A specific embodiment of the method comprises the following steps: acquiring a historical monitoring index data sequence corresponding to a preset to-be-monitored server; creating a load index relation model; in a preset monitoring time period, performing adaptive dynamic monitoring processing on a preset to-be-monitored server so as to acquire monitoring index data according to the dynamic acquisition frequency, and performing real-time anomaly detection and early warning processing on the acquired monitoring index data; sorting the monitoring index data collected in the preset monitoring time period to train a preset health state combined prediction model to obtain a health state combined prediction model; inputting the to-be-predicted monitoring index data sequence into the health state joint prediction model to obtain a predicted monitoring index data sequence; and performing future potential risk early warning processing on the preset to-be-monitored server. According to the embodiment, waste of early warning resources is reduced.

The invention provides a data sorting method of a database and a related product. The data sorting method comprises the following steps: acquiring an array length of an array to be sorted; obtaining the number of adjacent inverted-sequence pairs of the array to be sorted; based on the array length and the number of adjacent inverted-sequence pairs, estimating the maximum global inverted-sequence pair number of the array to be sorted; according to the array length, the number of adjacent inverted-order pairs and the maximum global inverted-order pair number, a target sorting algorithm is determined in a first sorting algorithm and a second sorting algorithm, the first sorting algorithm is a data ordering degree irrelevant algorithm, and the second sorting algorithm is a data ordering degree relevant algorithm; and sorting the array to be sorted by using a target sorting algorithm. According to the data sorting method, the data sorting efficiency is remarkably improved, the sorting performance under various scenes is remarkably improved, the processing time is greatly shortened, the calculation overhead in the database query process is reduced, and the database query execution time is shortened.

The application relates to a data sorting method and device, a computer device, a storage medium and a computer program product. The method comprises the following steps: obtaining an initial data sequence, dividing the initial data sequence to obtain a plurality of basic sub-data sequences; taking each basic sub-data sequence as an initial sub-data sequence, combining each initial sub-data sequence to obtain a plurality of initial sub-data sequence combinations; performing merge sorting on each initial sub-data sequence in the same initial sub-data sequence combination to obtain an intermediate sub-data sequence combination corresponding to each initial sub-data sequence combination; taking the intermediate sub-data sequence combination as an initial sub-data sequence, returning to the step of combining each initial sub-data sequence until a termination condition is met, and obtaining an ordered data sequence corresponding to the initial data sequence. The method can improve the data sorting efficiency and can be applied to a multidimensional database.

The invention relates to the technical field of logistics, and discloses a role permission-based route query method, which comprises the following steps of: role identification: matching with a preset role database according to user login information, identifying a role and binding a permission template; permission filtering: modeling all website points into a directed acyclic graph, setting corresponding breadth-first search traversal starting points and ranges for different roles, and determining website data permissions which can be accessed by a user; site recommendation: calculating the correlation degree between the current user and the site, and outputting a final site recommendation result to the user; generating a combined site, generating all non-repeated site pair combinations for a plurality of sites, and generating an ordered routing combination list; and data sorting and display: supporting multi-dimensional sorting and performing data display. According to the method, the directed acyclic graph model and the role-based breadth-first search strategy are combined, so that the data access range of different roles is accurately, efficiently and dynamically delimited, and the data security and authority isolation are fundamentally guaranteed.

The application belongs to the technical field of single-cell metabolite detection, and specifically provides a single-cell metabolite qualitative method and system, the qualitative method comprising the following steps: A1. obtaining raw data of metabolites by using a detection module; A2. calculating similarity scores of the raw data and candidate data in a database by using a data analysis module; A3. arranging the candidate data in descending order from high to low according to the similarity scores, and cutting off the top 20% of candidate data with high confidence to form sequence 1, denoted as [candidate metabolites] i ; A4. re-arranging the candidate data in sequence 1 according to the biological rationality of metabolites by using a data arrangement module to form sequence 2, denoted as [candidate metabolites] j ; A5. qualitatively determining the metabolites as the candidate metabolites equal to min(i+j) . The application has the advantages of high metabolite qualitative accuracy, high efficiency, strong applicability and the like.

The invention discloses a psychological health assessment method based on dynamic time sequence hypergraph representation learning, and belongs to the technical field of artificial intelligence and psychological health assessment. The method comprises the steps that according to campus network behavior data of a target student in an evaluation time period, a dynamic time sequence hypergraph of the target student is constructed, and the campus network behavior data comprises N pieces of access behavior data sorted according to timestamps; determining weight values of N hyperedges connecting a single time slice node, a single website category node and a single access strength node in the dynamic time sequence hypergraph, and updating initial features of each node in the dynamic time sequence hypergraph based on the weight values of the N hyperedges to obtain target features corresponding to each node; and determining rhythm characterization features and preference characterization features based on the updated dynamic time sequence hypergraph, and evaluating the mental health state of the target student according to the rhythm characterization features and the preference characterization features. The psychological health state of the student is objectively and effectively evaluated by analyzing the campus network behavior data of the student.

The invention relates to a data sorting method and device, computer equipment and a storage medium. The method comprises the following steps: in response to a sorting request for any dimension column in a target database, determining a sorting strategy of the sorting request; the target database comprises at least one piece of target data and a data index having a mapping relationship with the target data; the target data comprises at least one dimension column; sorting the data indexes of the corresponding target data in the target database according to the data content of the dimension column based on a sorting strategy to obtain an index sorting result of the target data; wherein in the index sorting result, each data index is a sorting result obtained by sorting according to the sorting request, and the sorting sequence of each target data is not changed. By adopting the method, the sorting flexibility and the sorting efficiency can be improved.

The invention discloses a root cause speculation method and device based on host state abnormity, equipment and a medium. Comprising the following steps: receiving an abnormal alarm notification of a target host system, and analyzing to obtain structured alarm data containing a host identifier and an alarm item; matching abnormal components in the relational database, generating a fault associated component list according to upstream and downstream components, and extracting a target host system architecture topological relation; calling a monitoring interface and a configuration management database system to collect real-time operation data of the list component, and generating semantic real-time state data in combination with a semantic mapping template; searching a preliminary historical case based on the alarm item, and generating case data sorted according to the matching degree in combination with user feedback; and performing multi-modal processing on the data, inputting the data into a large language reasoning model, outputting a root cause speculation result sorted according to probability, and displaying the root cause speculation result on a user interaction interface. According to the method, rapid and accurate root cause positioning of the abnormal state fault of the complex system host is realized, the operation and maintenance efficiency is improved, and the service loss is reduced.

The invention discloses a satellite cluster data cargo sorting storage and transfer method, and the method comprises the steps: constructing a data storage and transfer mechanism based on a satellite cluster circuit data support node disposed between a satellite terminal and a ground station core network; different high-level application function entities of a satellite ground gateway station core network are uniformly subjected to cluster data sorting by taking a terminal user or a cluster group identifier as an index by utilizing a satellite cluster circuit data support node transmission protocol and a satellite cluster data cargo transfer protocol, and are stored in a cargo packaging form and transferred in a cargo container form. The scheme provided by the invention can be suitable for the transfer of various types of application data, multiple types of application data can be loaded in one transfer, a developer only needs to develop one transfer protocol, and only one type of label needs to be added for the data goods whenever high-level applications are increased.

The application belongs to the technical field of data labeling, and discloses a method, system, device and terminal for automatically labeling text about judgment documents, wherein the text with punctuation symbols is divided into sentences and then input into a Jieba Chinese parser for word segmentation; based on the word frequency word segmentation result, a dynamic programming method is used to find the path with the maximum probability, and the text word segmentation terms are stored in an intermediate database; the manually labeled text is trained through a machine learning model, and automatic labeling of the text is realized through a constructed corpus labeling library; after the annotation data in the database are scored, the labeling is automatically reloaded, and data sorting is performed according to the labeling score. Through the method combining text enhancement and semi-supervised learning, the target case document is subjected to event extraction and labeling according to preset event extraction rules, and combined with an external online database, the labor cost of text entity labeling is greatly reduced, and the efficiency and accuracy of text labeling are improved.

The invention provides an analysis method, device and equipment of a rail transit signal system, a medium and a product, and relates to the technical field of rail transit, and the method comprises the steps: obtaining the basic attribute information of the rail transit signal system in the operation process, health score information and fault trend early warning information of the rail transit signal system in the operation process are determined; obtaining a user information screening condition; determining target system information according to the user information screening condition, the basic attribute information, the health score information and the fault trend early warning information; and determining a system analysis result of the rail transit signal system according to the target system information. According to the technical scheme of the invention, by obtaining the multi-dimensional basic attribute information, the health score information and the fault trend early warning information of the rail transit signal system in the operation process, comprehensive in-depth evaluation of the operation condition of the rail transit signal system is realized, the low-efficiency mode of depending on manual data arrangement is changed, and the operation efficiency of the rail transit signal system is improved. And the generation efficiency and accuracy of the system analysis result are improved.

This application discloses a method, apparatus, device, and medium for optimizing the execution of database SQL statements, relating to the field of database technology. The method includes: acquiring an SQL statement and identifying several target parsing functions from it; configuring operators for the first target parsing function; executing a data sorting operation corresponding to the first target parsing function using the operators to sort the database data to be processed, obtaining a first data sorting result; determining the association between other target parsing functions and the first target parsing function in data sorting, and determining a second data sorting result corresponding to the other target parsing functions based on the association, operators, and the first data sorting result; and generating the execution result corresponding to the SQL statement based on the first and second data sorting results. By determining the second data sorting result of other target parsing functions based on the association and the first data sorting result, the execution efficiency of the SQL statement is improved.

The invention discloses a method, a device, equipment and a medium for detecting and sorting frequency hopping signals of an unmanned aerial vehicle, and relates to the technical field of signal detection. And different clustering centers divide data objects in a certain radius range into different classes by taking the distance as a reference. Compared with a traditional K-means algorithm, when unmanned aerial vehicle frequency hopping signal detection data is processed, an initial k supervision value does not need to be set, self-adaptive classification is directly carried out through elements in a data set, and the influence on a data sorting result by setting an initial manually determined k classification value is avoided; and secondly, the clustering radius weight is adopted to balance the value, so that the clustering result is more reasonable, and non-spherical clusters can be processed.

This invention discloses a multi-GPU bitone sorting Top-K optimization method based on shared memory and a dynamic threshold queue. The method includes the following steps: reconstructing the bitone sorting Top-K into a two-stage iterative execution logic; constructing a global dynamic elimination threshold queue, extracting candidate elimination thresholds from each data block and storing them in the queue; designing an adaptive update mechanism for the global elimination threshold queue, dynamically calculating the elimination threshold for the current round based on the distribution of candidate elimination thresholds in the queue; eliminating elements in the sorted data that do not meet the conditions according to the elimination threshold, and reorganizing the remaining data; when the data size shrinks to below a preset threshold, sending the remaining data back to the host to perform a complete bitone sort, outputting the final Top-K ordered sequence. The purpose of this invention is to address the challenges of computational power and memory bottlenecks on single-GPU platforms and difficulties in multi-GPU expansion when processing massive data sorting queries, by proposing a multi-GPU bitone sorting Top-K optimization method based on shared memory and a dynamic threshold queue. This method achieves rapid data elimination and dynamic recombination by reconstructing the bitonetic sorting algorithm and introducing a candidate threshold extraction mechanism and a global dynamic threshold queue in shared memory. This significantly improves the resource utilization and parallel efficiency of multi-GPU platforms, thereby accelerating the processing of large-scale Top-K query tasks.

The application discloses a data sorting method and device, and belongs to the technical field of computers. The method comprises the following steps: in response to a change in the sorting position of target data in a data source table, acquiring the record identifier and segment sorting number of the target data in the data source table, and the value of a preset sorting position influence factor of the target data; updating a pre-created sorting control table according to the record identifier, the segment sorting number and the value of the preset sorting position influence factor; generating segment-in sorting position description information according to the updated sorting control table; and sorting and outputting data in the data source table according to the segment-in sorting position description information. The method does not need to traverse the data source table, only needs to operate the sorting control table, can realize local data sorting position adjustment, reduces the amount of operation and improves the sorting efficiency.

The invention provides a credential equipment maintenance method, system and equipment and a storage medium, and relates to the technical field of operation and maintenance. According to the method, for the problem of low multi-source heterogeneous data processing efficiency, semantic importance evaluation is carried out on collected data through a service weight distribution algorithm, and the data sorting priority is dynamically adjusted in combination with a BM25 weight value fusion technology, so that key service information is highlighted in operation and maintenance monitoring, and the continuity of high-priority services is ensured; aiming at the problem of abnormal data recognition lag in a maintenance scene, a comprehensive weight index model is constructed through personnel behavior feature analysis (access times, diversity and repeatability), the abnormal behavior risk of personnel entering and exiting from a spare part library is quantified, and the real-time recognition capability of abnormal data is improved. According to the invention, intelligentization, precision and high efficiency of operation and maintenance integration can be realized, and the business continuity and equipment reliability of the data center are remarkably improved.

Sorting data in memory is a fundamental computation that facilitates a wide range of search and query problems, aids in the construction and manipulation of data structures, and can improve the spatial and temporal locality of data and computation. Oftentimes, merge-based designs are used for sorting data, where a block sorting pass is performed followed by merging passes that produce increasingly larger sorted sublists until only a single list remains. While conventional merge-based designs can support multiple (K) merge operations in a single pass, a balance must be struck since there exists a point where K-scaling is no longer profitable. The present disclosure provides an alternative merge-based design in which data is merged using a single feed-forward data path.