37 results about "Compressed structure" patented technology

The invention relates to the technical field of communication base station energy-saving control, and discloses an energy-saving optimization control method and system for a communication base station. The method comprises the following steps: collecting and preprocessing traffic energy consumption data of a communication base station to obtain standardized characteristics; inputting the features into a double-flow space-time convolutional network, and carrying out parallel calculation through time and space branches to predict a load; performing hierarchical quantitative pruning on the network, and distributing bit width according to the influence degree to obtain a compression structure; and processing the real-time data based on the compression network, and generating an energy-saving control strategy for radio frequency resource configuration and power regulation. Based on accurate load prediction and differentiated resource scheduling strategies, the optimal balance between energy saving and service quality is realized, the problems of passive response and coarse-grained control in a traditional method are effectively solved, and the energy saving effect is maximized on the premise of ensuring communication quality.

The invention discloses a multi-dimensional time sequence data compression and rapid retrieval method and system, and relates to the technical field of large data compression retrieval. The multi-dimensional time sequence data compression and rapid retrieval method comprises the following steps: S1, collecting and preprocessing multi-source data in a monitoring abstract video stream, and constructing a standardized time sequence behavior data set; s2, analyzing behavior characteristics of frame segments in the sliding window, and dynamically adjusting anchor point labeling and compression strategies; s3, evaluating the coverage integrity of anchor point information in a compression section, and driving generation of an index path; s4, comprehensively evaluating the path behavior association strength and dynamically adjusting a loading decision; and S5, verifying the matching integrity of the behavior anchor point field and the jump pointer, and guaranteeing the localizability and jump stability of the event in the compression structure. The problems that in an intelligent monitoring scheme, video abstract compression is not bound with behavior semantics, a fine-grained positioning mechanism based on behavior labels is lacked, and key action segments cannot be directly positioned during user playback are solved.

A method for compressing molecular tagged sequence data includes: grouping sequence reads associated with a molecular tag sequence to form a family of sequence reads, corresponding vectors of flow space signal measurements and corresponding sequence alignments, calculating an arithmetic mean of the corresponding vectors of flow space signal measurements to form a vector of consensus flow space signal measurements, calculating a standard deviation of the corresponding vectors of flow space signal measurements to form a vector of standard deviations, determining a consensus base sequence based on the vector of consensus flow space signal measurements, determining a consensus sequence alignment and generating a compressed data structure comprising consensus compressed data, the consensus compressed data including for each family, the consensus base sequence, the consensus sequence alignment, the vector of consensus flow space signal measurements, the vector of standard deviations and the number of members.

The present application discloses a search optimization method, device and medium based on a large model, which relates to the field of data processing. The method includes: receiving query information input by a user and preprocessing the query information; performing semantic analysis on the query information based on a pre-trained deep learning model to extract the key information contained therein; using the query information and key information as input, generating a related first search result through a pre-trained large model; obtaining the business entity corresponding to the query information, determining the compressed structure information corresponding to the business entity, and optimizing the first search result based on the compressed structure information to obtain a second search result; and sorting and displaying the second search result. Accurately analyze the deep intention and context of the user's query, reduce irrelevant results caused by keyword ambiguity, and be able to quickly generate candidate results based on the reasoning ability of the large model to optimize search efficiency.

A geometry compression format is described. The compression format eliminates the need to store duplicate vertex information by storing unique vertices in each compressed data structure. Different triangles can refer to the same vertex using an index value, meaning that even if the same vertex is used multiple times in the compressed data structure, the entirety of the vertex information (e.g., positional information) does not need to be stored multiple times. An improvement includes representing further subdivision of the geometry in an efficient manner to represent highly detailed geometry. The subdivision can be specified by sideband information which can specify any of a variety of types of information.

The invention discloses a high-speed fixed-point multiplication circuit. The multiplication circuit is mainly composed of a multiplier coding module, a partial product generation module, a partial product compression module and a traveling wave carry adder module. The multiplier coding module is composed of a radix-4-Booth coding algorithm and an opposite number generation module, and is used for carrying out three-bit block coding on input multiplication data and generating an opposite number of a multiplicand in advance. The partial product generation module generates a plurality of groups of partial products with symbol extension according to the multiplicand coded signal. And the partial product compression module adopts an improved Wallace compression structure to perform layered compression on the partial product. And the traveling wave carry adder module sums the two groups of results output by compression and outputs a multiplication result. According to the invention, multiplication accumulation series can be reduced, the switching times of invalid signals in the circuit can be reduced, and the longest delay path in an operation link can be shortened, so that fixed-point multiplication which is high in speed, low in power consumption and more favorable for a comprehensive tool in structure is realized.

The invention is applicable to the technical field of artificial intelligence, and provides a large-model multi-agent-based method for automatically generating a complex-structure document, which comprises the following steps of: mapping an original structured document template into a compressed structure mark sequence with a reserved layout, and performing zero-sample semantic understanding and planning through a structure planning agent to obtain a complex-structure document; generating an atomic operation execution plan; according to the semantic logic relationship among the atomic operations in the structured execution plan, constructing a field-dependent directed acyclic graph, carrying out topological sorting on the field-dependent directed acyclic graph, and determining an execution sequence of content generation; through collaborative iteration of the content generation agent and the symbol verification agent, each field content is generated under the condition that a hard constraint condition is met; and finally synthesizing a complete document. According to the method, accurate understanding, reliable generation and format guarantee of the complex document under the zero sample condition are realized.

A geometry compression format is described. The compression format eliminates the need to store duplicate vertex information by storing unique vertices in each compressed data structure. Different triangles can refer to the same vertex using an index value, which means that even if the same vertex is used multiple times in the compressed data structure, the entirety of the vertex information (e.g., positional information) does not need to be stored multiple times. While the format provides good compression characteristics, improvement can be gained by eliminating the indices and instead using an indication of an “implicit geometry.” The implicit geometry is a commonly-used geometry type that indicates a particular correspondence between unique vertices and triangles. In other words, by indicating an implicit geometry type, it is automatically known which vertices make up which triangles, and explicit index information does not need to be stored in the compressed data structure.

The present invention discloses a compression index and query method for an attribute graph, which is applied to an attribute graph database system. The attribute graph maintained by the attribute graph database system includes a plurality of vertices, edges, and their corresponding attributes. The method includes: constructing an adjacency list for each vertex according to the attribute graph; constructing a compressed structure of the graph structure according to the adjacency list of each vertex; calculating vertex / edge numbers according to the compressed structure of the graph structure, obtaining the location of the attribute in the attribute compression index according to the vertex / edge numbers and the corresponding bit arrays, and extracting the attribute values from the attribute compression index; the attribute compression index includes a vertex attribute compression index and an edge attribute compression index; the bit arrays correspondingly record the starting positions of all edge attributes / vertex attributes; querying the attribute graph according to the compressed structure of the graph structure and the attribute compression index. The method of the present invention improves the query efficiency of the attribute graph database and reduces the storage space.

The application relates to the technical field of energy-saving control of communication base stations, and discloses an energy-saving optimization control method and system for a communication base station. The method comprises the following steps: collecting and preprocessing traffic energy consumption data of the communication base station to obtain standardized features; inputting the features into a double-flow space-time convolution network to predict the load through parallel calculation of time and space branches; performing hierarchical quantization pruning on the network, allocating bit widths according to the influence degree to obtain a compressed structure; and processing real-time data based on the compressed network to generate an energy-saving control strategy for radio frequency resource configuration and power adjustment. Based on accurate load prediction and a differentiated resource scheduling strategy, the application realizes the optimal balance between energy saving and service quality, effectively overcomes the problems of passive response and coarse-grained control in traditional methods, and maximizes the energy saving effect under the premise of guaranteeing the communication quality.

A method for compressing molecular tagged sequence data includes: grouping sequence reads associated with a molecular tag sequence to form a family of sequence reads, corresponding vectors of flow space signal measurements and corresponding sequence alignments, calculating an arithmetic mean of the corresponding vectors of flow space signal measurements to form a vector of consensus flow space signal measurements, calculating a standard deviation of the corresponding vectors of flow space signal measurements to form a vector of standard deviations, determining a consensus base sequence based on the vector of consensus flow space signal measurements, determining a consensus sequence alignment and generating a compressed data structure comprising consensus compressed data, the consensus compressed data including for each family, the consensus base sequence, the consensus sequence alignment, the vector of consensus flow space signal measurements, the vector of standard deviations and the number of members.

Systems, devices and methods for adaptive compression of stored information includes a memory management computing device programmed to monitor a size of a plurality of data structures stored in a data repository. The computing device compares the size of each of a plurality of data structures to a predetermined threshold. When a size of an uncompressed data structure meets the threshold, the memory management computing device calculates a value of a first compression parameter based on a value of a first parameter and a value of a second parameter of each data element of the uncompressed data structure, calculates a value of a second compression parameter based the value of the first parameter of each data element of the uncompressed data structure, generates a compressed data structure based on the value of the first compression parameter and the second compression parameter; and replaces, in the data repository, the uncompressed data structure with the compressed data structure.

The utility model relates to the technical field of scroll compressors, in particular to a scroll compression structure for a scroll compressor and the scroll compressor, the scroll compression structure for the scroll compressor comprises a movable scroll plate, the movable scroll plate is made of aluminum alloy, and the surface of the movable scroll plate is coated with a nano graphene coating; and the static scroll plate is meshed with the movable scroll plate. According to the scroll compression structure for the scroll compressor and the scroll compressor, the problem that an existing scroll compression structure for the scroll compressor is seriously abraded can be solved.

An accelerator device determines a compression format based on a header of a structured data element to be decompressed. The accelerator device may configure the accelerator device based on the compression format. The accelerator device may decompress a data block of the structured data element based on the configuration.

The present application discloses a search optimization method, device, and medium based on a large model, which relates to the field of data processing. The method includes: receiving query information input by a user and preprocessing the query information; performing semantic analysis on the query information based on a pre-trained deep learning model to extract key information contained therein; using the query information and the key information as inputs to generate relevant first search results through a pre-trained large model; obtaining a business entity corresponding to the query information, determining compressed structure information corresponding to the business entity, and optimizing the first search results based on the compressed structure information to obtain second search results; and sorting and displaying according to the second search results. It can accurately analyze the deep intention and context of the user's query, reduce irrelevant results caused by keyword ambiguity, and can quickly generate candidate results based on the reasoning ability of the large model, optimizing the search efficiency.

The invention discloses a Fibonacci weight digital code conversion system and method, and belongs to the technical field of digital circuits. Obtaining a weight digital code of the Fibonacci sequence through a decomposition module, decomposing each Fibonacci weight in the weight digital code into a binary weight combination, and grouping the Fibonacci weights by using the binary weights; performing hierarchical compression on the grouped Fibonacci weights according to the digit of the Fibonacci sequence through a Wallace Tree compression structure, and outputting a plurality of groups of compressed Fibonacci additions; and the carry lookahead adder receives the plurality of groups of compressed Fibonacci adders, performs additive operation and outputs corresponding binary digital codes. A digital code of the Fibonacci weight is directly converted into a binary digital code through the sequential logic circuit, and the problem that an existing Fibonacci weight digital code is low in conversion speed is solved.

This invention discloses a structured crime scene modeling method based on 3D graph convolution, comprising the following steps: collecting data to generate a multi-source crime scene input dataset; constructing a 3D spatial graph of the crime scene, establishing graph edges based on the constraint set of structural relationships between nodes, and generating the 3D spatial graph; initializing node features and edge weights to generate an initial graph structure; performing 3D graph convolution processing on the initial graph structure, constraining the convolutional neighborhoods of nodes, performing neighborhood-based convolution operations on the features of nodes within the neighborhoods, and generating an intermediate feature map; performing graph pooling operations on the intermediate feature map to generate a compressed structural representation of the crime scene; and decoding and modeling the compressed structural representation to obtain a structured 3D scene representation. This invention constructs a structured crime scene model based on 3D graph convolution, realizing the fusion of multi-source data and criminal investigation relationships, and possesses the advantages of high semantic fidelity, complete structural representation, and strong modeling reliability.

A hardware-implemented file reader includes an interface, multiple hardware-implemented column readers and a hardware-implemented record reconstructor. The interface is configured to access a file including multiple records. The records store values in accordance with a nested structure that supports optional values and repeated values. The file is stored in a columnar format having multiple columns, each column storing (i) compressed values and (ii) corresponding compressed structure information that associates the values in the column to the nested structure of the records. Each column reader is configured to be assigned to a respective selected column, and to read and decompress both the values and the structure information from at least a portion of the selected column. The record reconstructor is configured to reconstruct one or more of the records from at least portions of the columns that are read by the column readers, and to output the reconstructed records.

The application discloses an OFD cross-format conversion method, computer equipment and a storage medium, relates to the technical field of electronic document format conversion, and comprises the following steps: scanning an OFD document file, detecting a compression header identifier, recursively decompressing a nested compression structure and performing directory verification to obtain an OFD document structure; analyzing the structure to obtain root document information, signature information and resource information containing fonts and pictures; constructing a font mapping relationship for replacing missing fonts during rendering based on the resource information; obtaining the page content of each document page according to the root document information and the signature information; concurrently rendering all the page content in a multithreading mode to generate rendering data corresponding to each page; and merging the rendering data of each page to generate a target format output file. The application ensures complete extraction of nested compressed resources through recursive decompression, guarantees consistency of formats by using font mapping, improves conversion efficiency by combining multithreading rendering, and realizes high-fidelity and high-efficiency conversion of OFD documents into formats such as PDF.

The present application relates to the technical field of data transmission, and particularly relates to an information transmission method and system for a data center, the method comprising: obtaining original information data to be transmitted, and dividing the original information data into a plurality of data blocks; calculating a periodic autocorrelation significant index and a periodic regularity index of the data blocks; taking the product of the periodic autocorrelation significant index and the periodic regularity index as a periodic structure significant index, and calculating a compression structure change index of the data blocks, the compression structure change index being negatively correlated with the periodic structure significant index; adjusting the search depth of a Zstd compression algorithm by using the compression structure change index to obtain an optimal search depth, and compressing the original information data by using the Zstd compression algorithm, so as to be used for transmission of the original information data. The present application improves the information transmission real-time performance and overall computing resource utilization rate of the data center.

The invention relates to the technical field of data transmission, in particular to an information transmission method and system for a data center, and the method comprises the steps: obtaining to-be-transmitted original information data, and dividing the original information data into a plurality of data blocks; calculating a periodic autocorrelation significance index and a periodic rule index of the data block; the product of the periodic self-correlation significance index and the periodic rule index serves as a periodic structure significance index, a compression structure change index of the data block is calculated, and the compression structure change index is in negative correlation with the periodic structure significance index; and adjusting the search depth of the Zstd compression algorithm by using the compression structure change index to obtain the optimal search depth, and compressing the original information data by using the Zstd compression algorithm for transmission of the original information data. According to the invention, the information transmission real-time performance and the overall computing resource utilization rate of the data center are improved.

The application discloses a kind of multi-dimensional time series data compression and fast retrieval method and system, it is related to big data compression retrieval technical field.The kind of multi-dimensional time series data compression and fast retrieval method and system, including S1, the multi-source data in monitoring abstract video stream is collected and preprocessed, constructs standardization time series behavior dataset;S2, the behavior characteristics of frame section in sliding window are analyzed, anchor point labeling and compression strategy are dynamically adjusted;S3, the coverage completeness of anchor point information in compressed section is evaluated, and index path generation is driven;S4, the behavior correlation strength of path is comprehensively evaluated and dynamically adjusted loading decision;S5, the matching integrity of behavior anchor point field and jump pointer is verified, and the positionability and jump stability of event in compression structure are guaranteed.Solve the problem that video abstract compression is not bound with behavior semantics in intelligent monitoring scheme, lacks fine-grained positioning mechanism based on behavior label, and user playback cannot directly locate key action section.

The invention relates to the technical field of cryptography, and discloses a stream cipher algorithm and device based on a multilayer filter, and the device comprises an initialization algorithm and a key stream generation algorithm. The initialization algorithm fully fuses a seed key and an initial vector through a multiplexing key stream generation algorithm. According to the key stream generation algorithm, the unpredictability of the key stream is increased through an extension-diffusion confusion-compression structure, so that the generated password sequence has an excellent pseudo-random statistical characteristic, and known cryptographic analysis methods such as algebraic attacks and related attacks can be effectively resisted. The algorithm does not depend on special hardware and has the advantage of low use cost; and high-speed encryption and decryption operation can be realized in a lightweight environment, and the requirements of 5G and even 6G times on encryption and decryption speeds can be met.

An embodiment of the present invention provides a method, device, equipment and medium for compressed transmission of parameterized classes. The method includes: obtaining parameters to be processed in a verification component; classifying and hierarchically compressing the parameters in the verification component according to functions by using a compressed structure to customize data types in a package file, so as to obtain final compressed parameters of the customized data types; using the final compressed parameters of the customized data types to write a parameterized verification platform component and transmit the same therein. By classifying the application scenarios and functions of the parameters in the verification platform component, the present invention can achieve classified and hierarchical compression of more parameters, which is convenient for simplifying the transmission of a large number of parameters in a complex verification platform component and is also convenient for verification developers to read and understand.

A hardware-implemented file reader (20) includes an interface (32), a plurality of hardware-implemented column readers (36), and a record reconstructor (40). The interface is configured to access a file (24) comprising a plurality of records. The recording stores values according to a nested structure that supports selectable values and duplicate values. The file is stored in a column format having a plurality of columns, each column storing (i) a compressed value and (ii) corresponding compressed structure information associating values in the column with a recorded nested structure. Each column reader is configured to be assigned to a respective selected column, and to read and decompress values and structure information from at least a portion of the selected column. The record reconstructor is configured to reconstruct one or more of the records according to at least a portion of the column read by the column reader, and output the reconstructed records.

A method for compressing molecular tagged sequence data includes: grouping sequence reads associated with a molecular tag sequence to form a family of sequence reads, corresponding vectors of flow space signal measurements and corresponding sequence alignments, calculating an arithmetic mean of the corresponding vectors of flow space signal measurements to form a vector of consensus flow space signal measurements, calculating a standard deviation of the corresponding vectors of flow space signal measurements to form a vector of standard deviations, determining a consensus base sequence based on the vector of consensus flow space signal measurements, determining a consensus sequence alignment and generating a compressed data structure comprising consensus compressed data, the consensus compressed data including for each family, the consensus base sequence, the consensus sequence alignment, the vector of consensus flow space signal measurements, the vector of standard deviations and the number of members.

A hardware-implemented file reader includes an interface, multiple hardware-implemented column readers and a hardware-implemented record reconstructor. The interface is configured to access a file including multiple records. The records store values in accordance with a nested structure that supports optional values and repeated values. The file is stored in a columnar format having multiple columns, each column storing (i) compressed values and (ii) corresponding compressed structure information that associates the values in the column to the nested structure of the records. Each column reader is configured to be assigned to a respective selected column, and to read and decompress both the values and the structure information from at least a portion of the selected column. The record reconstructor is configured to reconstruct one or more of the records from at least portions of the columns that are read by the column readers, and to output the reconstructed records.

The invention relates to a task scheduling method and system for warehouse connection, and the method comprises the steps: obtaining task data, and extracting task features based on the task data; encoding the task features, and compressing the task features to obtain a compressed structure encoding vector; identifying the compressed structure coding vector to obtain a task identification tag; dynamically adjusting the priority of the task according to the task identification tag; and allocating an execution path for the task according to the priority of the task. According to the invention, the scheduling efficiency and flexibility of the storage connection link are significantly improved, and the overall storage operation process is optimized, so that the system can efficiently deal with multi-task, high-frequency and dynamically changing complex scenes, and the development of storage operation in the intelligent, real-time and high-precision directions is comprehensively promoted.

A hardware-implemented file reader includes an interface, multiple hardware-implemented column readers and a hardware-implemented record reconstructor. The interface is configured to access a file including multiple records. The records store values in accordance with a nested structure that supports optional values and repeated values. The file is stored in a columnar format having multiple columns, each column storing (i) compressed values and (ii) corresponding compressed structure information that associates the values in the column to the nested structure of the records. Each column reader is configured to be assigned to a respective selected column, and to read and decompress both the values and the structure information from at least a portion of the selected column. The record reconstructor is configured to reconstruct one or more of the records from at least portions of the columns that are read by the column readers, and to output the reconstructed records.

The invention discloses a quantum storage compression structure supporting online calculation, which is characterized in that the compression structure comprises an input module, a compression module, a conversion module, a calculation module and a decompression module, and the input module is used for converting an input form of an initial state vector and a quantum circuit into an identified legal form; the compression module is used for compressing and converting the state vector into a linked list for storage through a vernier, and compressing and unloading the periodic data again; the conversion module is used for converting the quantum circuit into a form which can be processed by RepeatCounter; and the decompression module decompresses the output stream or the memory according to requirements, and decompresses and destroys the RepeatCounter when the memory is limited. Compared with the prior art, the method has the advantages of optimization of storage space, reduction of calculation loss, efficient parallel support and the like, online quantum calculation can be performed without frequent compression and decompression, frequent internal and external memory exchange caused by offline compression can be reduced, and larger-scale quantum calculation can be better simulated on a machine with lower configuration.