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公开(公告)号：US12118292B2
公开(公告)日：2024-10-15
申请号：US17304849
申请日：2021-06-27
申请人： John Zhongqi Wang
发明人： John Zhongqi Wang
IPC分类号： G06F16/00 , G06F7/08 , G06F16/245 , G06F16/31 , G06F40/123 , G06F40/129 , G06F40/177 , G06F40/242
CPC分类号： G06F40/129 , G06F7/08 , G06F16/245 , G06F16/316 , G06F40/123 , G06F40/177 , G06F40/242
摘要： 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.
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公开(公告)号：US20240303468A1
公开(公告)日：2024-09-12
申请号：US18637142
申请日：2024-04-16
发明人： Bernardo José Amaral Nunes de Almeida Branco , Pedro Caldeira Abreu , Ana Sofia Leal Gomes , Mariana S.C. Almeida , João Tiago Barriga Negra Ascensão , Pedro Gustavo Santos Rodrigues Bizarro
IPC分类号： G06N3/045 , G06F7/08 , G06F16/23 , G06F16/27 , G06N3/042 , G06N3/044 , G06N3/063 , G06N3/08 , G06Q20/40 , G06Q40/12
CPC分类号： G06N3/045 , G06F7/08 , G06F16/2379 , G06F16/27 , G06N3/042 , G06N3/044 , G06N3/063 , G06N3/08 , G06Q20/4016 , G06Q20/409 , G06Q40/12
摘要： A process for handling interleaved sequences using RNNs includes receiving data of a first transaction, retrieving a first state (e.g., a default or a saved RNN state for an entity associated with the first transaction), and determining a new second state and a prediction result using the first state and an input data based on the first transaction. The process includes updating the saved RNN state for the entity to be the second state. The process includes receiving data of a second transaction, where the second transaction is associated with the same entity as the first transaction. The process unloops an RNN associated with the saved RNN state including by: retrieving the second state, determining a new third state and a prediction result using the second state and an input data based the second transaction, and updating the saved RNN state for the entity to be the third state.
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公开(公告)号：US12088593B2
公开(公告)日：2024-09-10
申请号：US18327663
申请日：2023-06-01
发明人： Brian Girardi , Philip Girardi
CPC分类号： H04L63/101 , G06F7/08 , H04L63/1425
摘要： 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.
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4.发明公开公开(公告)号：US20240289091A1
公开(公告)日：2024-08-29
申请号：US18574047
申请日：2022-06-14
IPC分类号： G06F7/08
CPC分类号： G06F7/08
摘要： 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.
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公开(公告)号：US20240259185A1
公开(公告)日：2024-08-01
申请号：US18161729
申请日：2023-01-30
发明人： Remi GERAUD-STEWART
CPC分类号： H04L9/0662 , G06F7/08 , H04L9/0825 , H04L9/3026
摘要： 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.
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公开(公告)号：US20240233016A9
公开(公告)日：2024-07-11
申请号：US18486545
申请日：2023-10-13
发明人： Suzanne Sprague , Sean Downey , Robert Taylor , Dhiraj Bawadhankar , Stephen Hurst , Matthew Simpson , Frederick Sturm
摘要： 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.
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7.发明公开公开(公告)号：US20240232229A1
公开(公告)日：2024-07-11
申请号：US18543550
申请日：2023-12-18
申请人： INFORMATICA LLC
发明人： Igor BALABINE
CPC分类号： G06F16/285 , G06F7/08 , G06F16/2237 , G06F16/2264
摘要： 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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公开(公告)号：US20240220480A1
公开(公告)日：2024-07-04
申请号：US18608327
申请日：2024-03-18
CPC分类号： G06F16/2365 , G06F7/08
摘要： Methods and systems are described herein for improving anomaly detection in timeseries datasets. Different machine learning models may be trained to process specific types of timeseries data efficiently and accurately. Thus, selecting a proper machine learning model for identifying anomalies in a specific set of timeseries data may greatly improve accuracy and efficiency of anomaly detection. Another way to improve anomaly detection is to process a multitude of timeseries datasets for a time period (e.g., 90 days) to detect anomalies from those timeseries datasets and then correlate those detected anomalies by generating an anomaly timeseries dataset and identifying anomalies within the anomaly timeseries dataset. Yet another way to improve anomaly detection is to divide a dataset into multiple datasets based on a type of anomaly detection requested.
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公开(公告)号：US11977536B2
公开(公告)日：2024-05-07
申请号：US18189174
申请日：2023-03-23
CPC分类号： G06F16/2365 , G06F7/08
摘要： Methods and systems are described herein for improving anomaly detection in timeseries datasets. Different machine learning models may be trained to process specific types of timeseries data efficiently and accurately. Thus, selecting a proper machine learning model for identifying anomalies in a specific set of timeseries data may greatly improve accuracy and efficiency of anomaly detection. Another way to improve anomaly detection is to process a multitude of timeseries datasets for a time period (e.g., 90 days) to detect anomalies from those timeseries datasets and then correlate those detected anomalies by generating an anomaly timeseries dataset and identifying anomalies within the anomaly timeseries dataset. Yet another way to improve anomaly detection is to divide a dataset into multiple datasets based on a type of anomaly detection requested.
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公开(公告)号：US11966868B2
公开(公告)日：2024-04-23
申请号：US16879219
申请日：2020-05-20
发明人： Jing Long , Randall B. Smith , Alan P. Wood
IPC分类号： G06Q10/0631 , G06F3/0482 , G06F7/08 , G06Q10/04 , G06Q10/0875 , G06Q10/10
CPC分类号： G06Q10/06315 , G06F7/08 , G06Q10/04 , G06Q10/06312 , G06Q10/06316 , G06Q10/0875 , G06Q10/10 , G06F3/0482
摘要： Systems, methods, and other embodiments for sorting-based assignment to optimize order fulfillment with short supply. One embodiment includes identifying a set of one or more distributions within a series of days. Sorting all demands of a first priority level occurring in the series of days by ascending order of size of the demand. For each demand of the first priority level in sorted order, (a) selecting an initial distribution during which the demand is scheduled to be fulfilled from the set of distributions, and (b) generating an indication that the demand can cannot be completely fulfilled, based on the size of the demand and the amount of supply available. Automatically arranging a graphical representation of a schedule of supplies and met and unmet demands for the series of days in a graphical user interface based at least on the indications generated for each demand.
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