APPARATUS, METHOD AND COMPUTER PROGRAM

    公开(公告)号:US20250053376A1

    公开(公告)日:2025-02-13

    申请号:US18798937

    申请日:2024-08-09

    Abstract: Various example embodiments of the subject disclosure relate to apparatuses, methods and computer programs. There is provided, for example, an apparatus including means for determining at least one sorted list of elements from a plurality of lists of elements and means for providing information including the at least one sorted list to a network function, the information including an indication of the sorted list.

    System and method for improving load balancing in large database management system

    公开(公告)号:US12182531B2

    公开(公告)日:2024-12-31

    申请号:US17514636

    申请日:2021-10-29

    Applicant: Ocient Inc.

    Abstract: A method for execution, by a first intermediate node of a plurality of nodes in a database management system, includes receiving a message, where the first intermediate node is limited to communication with a subset of nodes of the plurality of nodes, where the message: includes data that is being sent in accordance with a routing path, is a first size, and indicates a next node of the routing path, and where the subset of nodes includes the next node. The method continues by generating a revised message, wherein the revised message includes the data and has a second size. The method continues by determining whether there is at least one additional intermediate node after the next node in the routing path. When yes, determining an optimal route for forwarding the revised message via a node of the subset of nodes, and sending the revised message to the node.

    Method and device for sorting Chinese characters, searching Chinese characters and constructing dictionary

    公开(公告)号:US12118292B2

    公开(公告)日:2024-10-15

    申请号:US17304849

    申请日:2021-06-27

    Abstract: The invention discloses a method and a device for sorting Chinese characters, searching for Chinese characters and constructing a dictionary, and relates to the technical field of computers. A specific implementation of the method includes: obtaining the first basic character-forming component of a Chinese character according to the stroke order as the First Character, and encoding the First Character to obtain the First Character code, where the First Character includes the first character-forming component and the first main stroke component of a Chinese character; obtaining the number of strokes included in each Chinese character, and obtaining the corresponding stroke string of each Chinese character; using the First Character code as the first and highest priority sorting field, the number of strokes as the second sorting field, and the stroke string as the third and the lowest priority sorting field to sort Chinese characters. This embodiment can solve the problem of difficulty in sorting and searching of Chinese characters caused by the unfixed definition and position of radicals.

    System and method for trustworthy internet whitelists

    公开(公告)号:US12088593B2

    公开(公告)日:2024-09-10

    申请号:US18327663

    申请日:2023-06-01

    CPC classification number: H04L63/101 G06F7/08 H04L63/1425

    Abstract: Information is received from a first networked device for a first user and from a second networked device for a second user. The first user and the second user are verified and registered. A first set of data for the first user and a second set of data for the second user that each specify one or more network parameters per network address that communicates with each user are received from a networked collector device. Addresses are selected from each of the first set and the second set where each of the one or more network parameters are above a first activity threshold level for that parameter. A first set and a second set of first level activity addresses are produced. A whitelist is generated for the first user from an intersection of the first set of first level activity addresses and the second set of first level activity addresses.

    A COMPUTER-IMPLEMENTED METHOD AND A DATA PROCESSING HARDWARE FOR PROCESSING SENSOR DATA POINTS

    公开(公告)号:US20240289091A1

    公开(公告)日:2024-08-29

    申请号:US18574047

    申请日:2022-06-14

    CPC classification number: G06F7/08

    Abstract: This disclosure relates to a computer-implemented method for processing sensor data points by means of a data processing hardware where a distributions buffer for storing an initial plurality of Gaussian distributions is initialized, each Gaussian distribution of the initial plurality of Gaussian distributions including an initial plurality of sensor data points received sequentially from at least one sensor and having an associated predetermined distribution distance threshold, and where the distributions buffer is sequentially updated for a number n of new sensor data points based on a distribution distance condition, generating an updated plurality of Gaussian distributions including either a new Gaussian distribution, or an updated single Gaussian distribution or an updated merged Gaussian distribution.

    COMPRESSION OF MATRICES FOR DIGITAL SECURITY

    公开(公告)号:US20240259185A1

    公开(公告)日:2024-08-01

    申请号:US18161729

    申请日:2023-01-30

    CPC classification number: H04L9/0662 G06F7/08 H04L9/0825 H04L9/3026

    Abstract: Systems and techniques are described herein for compressing data used in cryptographic operations. For example, a process may include obtaining a first data structure, wherein the first data structure comprises polynomials; generating a second data structure based on the first data structure, wherein the second data structure comprises coefficients of the polynomials; sorting the second data structure in an ascending order to obtain a sorted second data structure; updating the sorted second data structure based on differences between elements of the sorted second data structure to obtain a delta-encoded data structure; performing an entropy coding on the delta-encoded data structure to obtain an entropy-encoded output; recovering an updated first data structure using the entropy-encoded output, wherein the updated first data structure corresponds to the first data structure with a different order of first data structure elements; and performing a cryptographic operation using the updated first data structure.

    COMPRESSION OF AN EXCHANGE TRADED DERIVATIVE PORTFOLIO

    公开(公告)号:US20240233016A9

    公开(公告)日:2024-07-11

    申请号:US18486545

    申请日:2023-10-13

    CPC classification number: G06Q40/04 G06F7/08

    Abstract: An illustrative computing device may include a processor and a non-transitory memory device for storing a data structure capable of being compressed, where the data structure includes a plurality of data elements and each of the plurality of data elements includes a date field and a quantity field. The computing device may process instructions to arrange the plurality of data elements in a consecutive series in date order based on a value stored in the date field of each data element, determine whether a gap appears in the consecutive series of data elements based on a value stored in the quantity field of each element, remove the determined gaps in each of the data elements, and repeat the determining and removing steps until a predetermined criterion has been reached.

    METHOD, APPARATUS, AND COMPUTER-READABLE MEDIUM FOR EFFICIENTLY CLASSIFYING A DATA OBJECT OF UNKNOWN TYPE

    公开(公告)号:US20240232229A1

    公开(公告)日:2024-07-11

    申请号:US18543550

    申请日:2023-12-18

    Inventor: Igor BALABINE

    CPC classification number: G06F16/285 G06F7/08 G06F16/2237 G06F16/2264

    Abstract: An apparatus, computer-readable medium, and computer-implemented method for efficiently classifying a data object, including representing the data object as a data object vector in a vector space, each dimension of the data object vector corresponding to a different feature of the data object, determining a distance between the data object vector and centroids of data domain clusters in the vector space, each data domain cluster comprising data domain vectors representing data domains, sorting the data domain clusters according to their respective distances to the data object vector, and iteratively applying data domain classifiers corresponding to data domains represented in a closest data domain cluster in the sorted data domain clusters to the data object.

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