229results about "Data sorting" patented technology

An information processing method, an electronic device, and a storage medium. The method includes: obtaining a query statement of a user, determining at least one model identifier of at least one candidate service model based on the query statement; generating at least one first prompt word based on the query statement and the at least one model identifier, inputting the at least one first prompt word into a pre-trained target large model, and outputting, by the target large model, at least one screening parameter of the at least one candidate service model based on the at least one first prompt word; determining a target service model from the at least one candidate service model based on the at least one screening parameter; and inputting the query statement into the target service model, and obtaining feedback information corresponding to the query statement.

The invention discloses a computer system based on a unified information calculation model of electric power Internet of Things terminal equipment, and relates to the field of computer systems, in which a data acquisition module acquires information of a target power grid; the power supply path analysis module determines on-off state change information and a load point path and analyzes to obtain an initial power supply path; a path search module extracts a load point to be transferred and searches for alternative power supply paths to obtain a potential transfer path list; a marking module calls the unified calculation model for analysis, line capacity limitation information and switch operation sequence constraints are obtained, a potential transfer path list is marked through the line capacity limitation information, and a feasible transfer path set is obtained; and the load transfer execution module controls the target power grid to perform load transfer based on the deduced switching operation strategy on the basis of the constraints. According to the method, a data basis is provided for the computer system to execute accurate decision-making of load transfer, and meanwhile, the execution quality and accuracy of the computer system are improved.

Apparatuses, systems, and techniques to perform non-maximum suppression (NMS) with a bit-reduced radix sort to remove redundant bounding boxes are described. In at least one embodiment, one or more circuits perform i) a bit-reduced radix sort operation to sort a list of confidence scores associated with a set of bounding boxes corresponding to one or more objects within one or more digital images and ii) a non-maximum suppression (NMS) operation on the sorted list to remove one or more redundant bounding boxes from the set.

A data input sub-system of a parallelized database system includes processing core resources operable to obtain divisions of data slabs of a dataset and compress the divisions of data slabs using a null elimination compression scheme to produce divisions of compressed data slabs, A first data slab of a first division of data slabs of the divisions of data slabs is compressed using the null elimination compression scheme to produce a first compressed data slab. The first compressed data slab includes first compressed data and first compression information. The processing core resources are further operable to store a respective division of compressed data slabs of the divisions of compressed data slabs.

A point cloud data transmission method according to embodiments may comprise the steps of: encoding point cloud data; and transmitting a bitstream comprising the point cloud data. A point cloud data reception method according to embodiments may comprise the steps of: receiving a bitstream comprising point cloud data; and decoding the point cloud data.

Provided are a data processing method, an electronic device, a computer-readable storage medium and a computer program product, which relate to the field of databases. The data processing method comprises: determining, from a database, M data groups to be integrated, wherein M is a positive integer greater than 1, each data group to be integrated comprises a plurality of data records having sorting key values and has a corresponding sorting key value interval, a minimum endpoint value and a maximum endpoint value of the sorting key value interval are respectively a minimum sorting key value and a maximum sorting key value in each data record in the corresponding data group, and for any data group to be integrated, there is at least one other data group to be integrated, the sorting key value interval of which overlaps with the sorting key value interval thereof; and reintegrating the M data groups to be integrated into at least one target data group, and adding the at least one reintegrated target data group to the database.

A method for enhancing hybrid-classical algorithms for combinatorial optimization includes executing, on a quantum processor, a variational algorithm, the execution producing a subset of a set of solutions (solution space) of the variational algorithm within a predefined period, the variational algorithm computing a quantum state of a quantum system corresponding to a combinatorial optimization problem, each solution in the subset having a corresponding value; sorting, according to a sorting criterion, the subset of solutions; isolating, based on the sorting, a portion of the subset of solutions wherein a value corresponding to each solution in the portion is within a boundary defined by a threshold value; computing an average value of the solutions from the portion of the subset of solutions; and altering the variational algorithm to produce a second subset of solutions such that the second subset of solutions comprises solutions having values within the boundary.

A method is provided that includes performing, by a processor in response to a vector matrix multiply instruction, multiplying an m×n matrix (A matrix) and a n×p matrix (B matrix) to generate elements of an m×p matrix (R matrix), and storing the elements of the R matrix in a storage location specified by the vector matrix multiply instruction.

This specification discloses a data processing and visualization method, apparatus, medium, and device, which relate to the computer technology field. The method includes selecting a data platform to acquire source data of a target company, organizing the source data and loading it into a data system as a source database table, performing primary data operations to process the source data into target data, performing secondary data operations to process the target data into value-added data, performing tertiary data operations to process related data into graphical data, and performing data visualization to render the graphical data into a visualization diagram. The method of the present invention at least partially solves the problems of inability to timely and completely acquire source data and inability to effectively utilize source data without processing it, thereby improving data processing efficiency, increasing the accuracy of data analysis of the target company through data modeling, and automatically combining background data with front-end displays such as panel interfaces through data visualization, thereby improving the effectiveness of data presentation and the availability of the data system.

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.

A processor and a vector sort instruction for the processor to execute are provided, in which the vector sort instructions includes instructions for comparing a first element of a set of vector elements of a vector to a remainder of the set of vector elements; determining, based on the comparing, a control vector that specifies a respective sorted position for each element of the set of vector elements; and reordering the set of vector elements based on the control vector.

A parallelized data input sub-system of a database system includes a first set of loader nodes of pluralities of computing nodes of a plurality of computing device clusters. The first set of loader nodes includes a plurality of memory devices and a plurality of processing modules. The first set of loader node is operable to ingest at least a portion of a dataset (“data”), a set of the memory devices stores the data, and a set of the processing modules determines whether the data is regarding a query. When it is regarding the query, the set of processing modules provides the data to a query and response sub-system. When it is not regarding the query, the set of processing modules determines long term storage parameters, processes the data in accordance with the parameters to produce formatted data, and provides the formatted data to a store and compute sub-system.

A data paging automation method is used for processing a plurality of pieces of data, and comprises the following steps: determining a sorting basis for sorting the plurality of pieces of data according to an ordered non-repetitive key of the plurality of pieces of data; sorting and paging the plurality of pieces of data according to the sorting basis; and updating a paging information table of the plurality of pieces of data and collecting corresponding data according to the ordered non-repetitive key and at least one filtering condition.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for finding splits in gradient boosting systems. One example method includes identifying, based on multi-party computation (MPC), a first split among possible first splits in a first layer of a decision tree. Identifying the first split comprises determining a first derivative and a second derivative for each sample in a dataset of n samples and m features; generating a sorting array indicating a sorting order of at least one feature; identifying the first split based on first derivatives, second derivatives and the sorting array; and generating an index vector that indicates whether each sample belongs to a first or a second sub-dataset. The method further includes identifying a second split among possible second splits in a second layer of the decision tree based on the first derivatives, the second derivatives, the sorting array, and the index vector.

An example includes receiving a read request specifying a target range and a target checkpoint, and executing a first query to retrieve a first entry of a metadata table. The first entry is a most recent entry of those entries that are older than the target checkpoint and record write ranges overlapping the target range. The example also includes, if the write range in the first entry does not cover all of the target range, determining a remaining portion of the target range that excludes the write range in the first entry. The example also includes executing a second query to retrieve a second entry of the metadata table, where the second entry is a most recent record in a second subset of entries that are older that the target checkpoint and record write ranges overlapping the remaining portion of the target location range.

An initial data object associated with an initial user group is sorted by separation into multiple target data sets each associated with a respective target user group. The initial data object is sorted into multiple initial user profiles and evaluated to indicate each user of the initial user group as either differentiated as a unique user or non-differentiated as a unique user. The multiple target data sets are generated by adding, to each specific target data set of the multiple target data sets, a user-specific profile for each specific user of the target user group associated with the specific target data set, the user-specific profile including at least a portion of the initial user profile of the specific user. An alert signal is automatically transmitted to one or more agent device upon discriminating one or more user of the initial user group is indicated as non-differentiated as a unique user.

A system and method include receiving a plurality of elements in a data array to be sorted, assigning the elements a sequential index value, computing an amount of additional memory needed to sort the elements, creating a Linked-Array Tournament Tree (LATT), storing the LATT in the allocated amount of additional memory, initializing the LATT, initializing a number of iterations, initializing a next sorted index position in the data array, determining from the LATT, the index value of a champion element from all the winners of the pairwise comparisons, swapping the champion element with an element at the next sorted index position in the data array, updating the LATT responsive to the swapping, updating the next sorted index position, repeating a plurality of times, and outputting the data array having the elements in a sorted order.

Data selection systems and techniques are described. For instance, a system receives a data set with a plurality of data elements. The system generates a plurality of random values. The system generates a ranking of the plurality of random values. The system selects a subset of the plurality of data elements based on a comparison between the ranking and a predetermined threshold. The predetermined threshold is based on a predetermined proportion of the plurality of data elements to be included in the subset. The system outputs a randomization scheme that includes the ranking and the predetermined proportion, wherein a second selection of a second subset of the plurality of data elements is based on the randomization scheme. The system output an indication of the subset and the second subset.

A computer-implemented method for organizing tasks presented on a graphical user interface of a computer hardware system for a user includes the following operations. An electronic message associated with a collaborative messaging application executing with the computer hardware system is received. A first collaboration having one or more collaborative tasks is identified from the electronic message. A need-for-action, a time-to-act, and a time-to-complete are determined for the first collaboration. A moving average for the first collaboration is adjusted based upon the need-for-action, the time-to-action, and a time-to-complete. The presentation of the first collaboration within the graphical user interface is altered based upon the moving average.

Disclosed embodiments are methods, apparatuses, and computer-readable media for annotating distributed data without redundant data copying. In one embodiment, a method is disclosed comprising reading a raw dataset, the raw dataset comprising a first set of columns and a first set of rows; generating an annotation dataset, the annotation dataset comprising a second set of columns and a second set of rows; assigning row identifiers to each row in the second set of rows, the row identifiers aligning the second set of rows with the first set of rows based on the underlying storage of the raw dataset and annotation dataset; and writing the annotation dataset to a distributed storage medium.

The application relates to a multi-target manifold data analysis method, device, equipment and storage medium. The architecture comprises the following steps: acquiring multi-target manifold data; inputting the multi-target manifold data into a pre-trained manifold data analysis model to obtain an analysis result of the multi-target manifold data; and training an initial analysis model in a manifold space by using sample manifold data and a sample analysis sequence corresponding to the sample manifold data. According to the embodiment of the application, the initial analysis model in the manifold space is trained by using the sample manifold data and the sample analysis sequence corresponding to the sample manifold data, so that the manifold data analysis model can be used to well analyze high-dimensional manifold data, the accuracy of the manifold data analysis is ensured, the manifold data analysis model can be applied to massive high-dimensional manifold data analysis, and the manifold data analysis model has good popularization and application value.

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 invention provides a thermal power generating unit energy efficiency sorting method based on a full-capacity electric power spot environment, and the method comprises the steps: collecting the power climbing, inertia response, frequency modulation capability, reactive power support and other characteristic parameters of a unit, and constructing a support characteristic database; a normalization and quantitative modeling method is adopted to form a multi-dimensional feature matrix; energy efficiency indexes such as the heat consumption rate, the fuel consumption rate and the exhaust steam enthalpy value are fused through reinforcement learning, and a dynamic energy efficiency characterization model is established; collaborative optimization is carried out by using an ant colony algorithm, and global optimization of energy efficiency sorting is realized by combining pheromone updating and reward feedback; key features are further extracted through principal component analysis, feature importance is calculated, and sensitive parameters are recognized; and finally, performing consistency verification and explanation on a sorting result based on a mean absolute error (MAE) and a Pearson's correlation coefficient (PCC), and outputting a unit energy efficiency explanation matrix and an abnormal report.

A method for compressing RDF tuples. The method including obtaining RDF tuples, obtaining a dictionary of indices, encoding for each RDF tuple the indices attributed to the subject and the object, grouping RDF tuples sharing the same predicate and for each group sorting the RDF tuples by considering the encoding of the subject and the object, and for each group of sorted RDF tuples, serializing the index of the shared predicate, serializing the encoding of the subject and the object of a first RDF tuple, and for each RDF tuple of the group of sorted RDF tuples subsequent to the first RDF tuple of the group, computing a difference between the encoding of the subject and the object of a current RDF tuple and the encoding of the subject and the object of a previous RDF tuple, and serializing the computed difference in a form of a variable-length integer.

Hidden surface removal logic and methods for performing full resolution depth testing in a graphics processing system in which a rendering space is subdivided into a plurality of tiles and each tile comprises a plurality of pixel samples. The hidden surface removal logic is configured to: receive a primitive fragment of a set of primitive fragments associated with a tile of the plurality of tiles, the primitive fragment corresponding to a pixel sample of the tile; receive information indicating whether the primitive fragment requires a depth buffer read for full resolution hidden surface removal; if the primitive fragment is a first primitive fragment in the set, initialize a current best depth value buffer for the tile and a depth value update map for the tile, wherein the current best depth value buffer for the tile comprises a depth value for each pixel sample of the tile, the depth value update map indicates which values of the current best depth value buffer have been updated, and the depth value update map is initialized to indicate that no depth values in the current best depth value buffer have been updated; determine whether the primitive fragment has a best depth value for the pixel sample corresponding to the primitive fragment according to a depth compare mode; and in response to determining that the primitive fragment has the best depth value for the pixel sample corresponding to the primitive fragment, update the depth value for that pixel sample in the current best depth value buffer with the depth of the primitive fragment, and update the depth value update map to indicate that the depth value for that pixel sample has been updated; wherein, when the first primitive fragment does not require a depth buffer read, initializing the current best depth value buffer comprises initializing each depth value in the current best depth value buffer to a worst depth value according to the depth compare mode, and, when the first primitive fragment requires a depth buffer read, initializing the current best depth value buffer comprises initializing each depth value in the current best depth value buffer to the corresponding depth value in the depth buffer for the tile..

The present technology includes outlier detection circuitry, which can be employed to filter out outlier values so that they do not negatively impact statistical analysis or processing tasks. The outlier detection circuitry can receive data as a stream of multiple sets with multiple values contained within one set. The outlier detection circuitry comprises dedicated hardware and / or software resources that determines the largest and smallest values that occur within each set in the received stream.

The application discloses a Chinese character sorting, searching and dictionary constructing method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: obtaining a first character of a Chinese character as a first character according to a stroke order, and encoding the first character to obtain a first character code, wherein the first character comprises a first character component which can be independently formed into a character and cannot be split, and a first main stroke component of the Chinese character which does not comprise any character component; obtaining the number of strokes included in each Chinese character, and obtaining a stroke string corresponding to each Chinese character according to a preset stroke character coding rule; sorting the Chinese characters by taking the first character code as a first sorting field, the number of strokes as a second sorting field, and the stroke string as a third sorting field, wherein the first sorting field has the highest priority, and the third sorting field has the lowest priority. The embodiment can solve the problems of sorting and searching difficulties caused by the definition and position of the component.