59 results about "Incremental encoding" patented technology

The invention relates to the technical field of hydrogeological monitoring, in particular to a hydrogeological dynamic monitoring and analysis system and method based on big data. The method specifically comprises the steps that hydrogeological data are collected in real time, edge calculation is combined for data denoising, space-time calibration and error correction, variational mode decomposition, geologic model constraint and wavelet transform are adopted for eliminating noise and drift errors, storage and transmission efficiency are optimized through incremental coding and Huffman coding, and quadratic form calibration codes are generated to ensure data reliability; a hydrological evolution trend is predicted by fusing a space-time deep learning model and a self-attention mechanism, and adaptive anomaly detection is realized by combining DBSCAN clustering and prediction error analysis; and optimizing a water resource allocation strategy through reinforcement learning, hierarchically evaluating a risk level and generating a management scheme, and finally visually displaying monitoring data, an abnormal score and a decision result. According to the method, multi-source data fusion, space-time modeling and intelligent decision making are integrated, and hydrological monitoring precision and response efficiency are improved.

The invention relates to the technical field of audio encoding and decoding, in particular to a fast encoding and decoding method and system for real-time audio. The method comprises the following steps: acquiring real-time sampling data of an input audio stream, and performing multi-time-point sliding window division and coding preprocessing to generate a coding preprocessing enhanced audio; carrying out adaptive quantization strategy analysis on the coding preprocessing enhanced audio, carrying out multi-level residual quantization modeling, and constructing a real-time increment coding mapping table; performing multi-module decomposition execution based on the real-time incremental coding mapping table, performing multi-thread parallel coding optimization, and constructing a real-time audio parallel coding strategy; and carrying out real-time coding processing according to a real-time audio parallel coding strategy, and carrying out task-by-task code rate distortion optimization to obtain an optimal coding parameter of each coding task. According to the invention, high-fidelity and low-delay audio coding and decoding are realized, and the auditory experience of a user is improved.

The invention provides a construction engineering information management method and system, and belongs to the technical field of construction engineering information, and the method comprises the steps: responding to a received information updating instruction, and determining a source component unit from a plurality of component units based on the updating component unit information carried in the information updating instruction; recursively identifying an associated component unit of the source component unit based on the target dependency graph; the target dependency graph is used for representing a dependency relationship among the plurality of component units; at least one associated component unit is provided; performing incremental coding on the difference set of the source component unit and the associated component unit to form incremental data; and in response to the situation that conflict processing is not executed on the incremental data, uploading the incremental data to the cloud to obtain an updated building information model. According to the construction engineering information management method and system provided by the invention, efficient and accurate model updating can be realized, and the overall efficiency and performance of construction engineering information management are improved.

The invention provides a Flink multi-cluster security authentication data synchronization method and system, and relates to the technical field of distributed computing, and the method comprises the steps: establishing a secure connection channel, optimizing an execution plan by adopting an incremental coding compression algorithm, setting an adaptive computing load threshold, dynamically allocating computing resources, and writing state check point information. Data quality evaluation is executed, the evaluation data is written into the distributed account book, the state of the target cluster is recovered, the synchronization task is started, the data synchronization safety and efficiency are improved, the computing resource utilization rate is increased, and the data quality and synchronization consistency are ensured.

The invention discloses a grating-type high-precision contact-type displacement sensor, and the sensor comprises a housing main body, a probe linear motion assembly, a grating code ruler assembly, a light transmitting and receiving assembly, a limiting groove assembly, and a mainboard assembly. A containing space is formed in the shell body, and the grating code ruler assembly, the light emitting and receiving assembly, the limiting groove assembly and the main board assembly are all arranged in the containing space. The grating code ruler assembly comprises a grating code ruler, a plurality of transparent lines and opaque lines are formed on the grating code ruler, and the coding mode of the grating code ruler adopts a mixed coding mode of incremental coding and absolute coding. According to the invention, a mixed coding mode is adopted by the grating code ruler, zero searching operation is not needed, and a probe linear motion structure capable of realizing precise transmission is matched, so that the sensor has the advantages of high repetition precision, good performance stability, high response speed and strong anti-interference capability.

The invention discloses a block compression method, device and equipment based on a block chain, and a readable storage medium. The method comprises the steps of obtaining M to-be-packaged transactions; one to-be-packaged transaction comprises transaction attribute values of N transaction attribute types; according to the transaction attribute type priorities corresponding to the N transaction attribute types and the M transaction attribute values corresponding to the N transaction attribute types, performing position sorting processing on the M to-be-packaged transactions to obtain M position sorted transactions; adding transaction attribute values with the same transaction attribute type in the M position sorting transactions to the same to-be-compressed attribute value set to obtain N to-be-compressed attribute value sets; performing incremental coding compression processing on the N to-be-compressed attribute value sets to obtain N attribute value incremental codes; and performing block encapsulation processing on the N attribute value increment codes to obtain a to-be-chained block. By adopting the method and the device, the storage space required by the block can be reduced, and the performance of the block chain system is improved.

A method of database operations includes receiving a user query, generating a query vector embedding representative of the user query, querying a vector database using the query vector embedding, retrieving a first database vector of the plurality of database vectors based on the query and representative of a first data file corresponding to a first time and belonging to a first time-series data set, receiving a first plurality of delta encodings describing differences between vector representations of temporally-adjacent data files of the first time-series data set, identifying a second data file of the first time-series data set having a second vector representation that differs from the first database vector and corresponds to a second time, and retrieving the second data file from a database.

The invention discloses a gas detection alarm method and system for mining safety equipment, and relates to the technical field related to gas detection, and the method comprises the steps: obtaining basic gas detection related equipment information of a target mine, and constructing a mine topological graph; performing incremental coding identification on the node gas correlation detection data sequence of the M equipment topology nodes in the preset detection window; performing multi-dimensional structured interaction on the M signal token sequences to obtain a local association sub-graph set; and in combination with the M signal token sequences, carrying out local gas detection anomaly identification on the local association sub-graph set, and obtaining gas detection alarm information according to an identification result set. The technical problems that in the prior art, the semantic relation between signals is difficult to accurately understand in the complex and heterogeneous mine environment, local gas abnormity is difficult to recognize in time, and consequently the accuracy and timeliness of gas detection alarming are poor are solved, and the technical effects that abnormity accurate positioning is achieved, and the accuracy and timeliness of gas detection alarming are improved are achieved.

A data compression method is disclosed which involves obtaining a plurality of data blocks, each data block comprising a plurality of data values. The method performs base-delta encoding of the obtained plurality of data blocks, wherein a delta value means a difference between a data value and a base value. This involves determining, among the data values of the plurality of data blocks, a set of global base values common to said plurality of data blocks. The set of global base values is selected to minimize delta values for the data values of the plurality of data blocks with respect to the global base values in said set of global base values. The method further involve encoding individual data values of the plurality of data blocks by selecting, in the set of global base values, for each individual data value a global base value that is numerically closest to the individual data value and thus results in a smallest delta value, and then generating metadata for the encoded individual data value to represent the selected global base value and the resulting delta value.

The present application relates to the technical field of audio codec, and particularly relates to a fast coding and decoding method and system for real-time audio.The method comprises the following steps: obtaining real-time sampling data of an input audio stream, performing multi-time point sliding window division and coding preprocessing, and generating coding preprocessing enhanced audio; performing adaptive quantization strategy analysis on the coding preprocessing enhanced audio, and performing multi-level residual quantization modeling to construct a real-time incremental coding mapping table; performing multi-module decomposition and execution based on the real-time incremental coding mapping table, and performing multi-thread parallel coding optimization to construct a real-time audio parallel coding strategy; performing real-time coding processing according to the real-time audio parallel coding strategy, and performing task-by-task rate-distortion optimization to obtain optimal coding parameters of each coding task.The present application realizes high-fidelity rate and low-delay audio coding and decoding, and improves user auditory experience.

The invention provides a multi-agent reasoning optimization method and system based on Token calculation acceleration, and relates to the field of intelligent decision making, and the method comprises the steps: generating and maintaining a Token-level directed acyclic graph on line; constructing a reasoning path consistency sharing strategy, an approximate semantic sharing strategy and a forced sharing strategy to perform KV cache sharing; local change features are processed in an incremental coding mode, and context difference detection, incremental coding calculation and KV cache splicing are carried out; defining a contribution degree function for each Token so as to carry out Token contribution degree evaluation, and introducing a dynamic pruning mechanism based on the contribution degree; based on the Token-level directed acyclic graph, the parallel execution of the independent Token is realized through topology analysis and dynamic scheduling. According to the method, generation of redundant Token can be avoided, and the communication bandwidth and computing resources of the spacecraft are saved; the delay of the critical path is shortened, the decision-making efficiency of a multi-agent cooperation system can be improved, and the strict requirements of spacecraft tasks on the decision-making efficiency and the decision-making safety are met.

The application relates to the technical field of hydrogeological monitoring, in particular to a hydrogeological dynamic monitoring and analysis system and method based on big data; specifically, hydrogeological data is collected in real time, data denoising, space-time calibration and error correction are carried out in combination with edge computing, noise and drift error are eliminated by adopting variational mode decomposition, geological model constraint and wavelet transform, and the storage and transmission efficiency is optimized by increment encoding and Huffman encoding, and a quadratic form check code is generated to ensure data reliability; a space-time deep learning model and a self-attention mechanism are fused to predict a hydrological evolution trend, adaptive anomaly detection is realized by combining DBSCAN clustering and prediction error analysis; water resource allocation strategies are optimized through reinforcement learning, risk levels are evaluated in layers, and management schemes are generated, and finally, monitoring data, abnormal scores and decision results can be visually displayed. The application integrates multi-source data fusion, space-time modeling and intelligent decision-making, and improves hydrological monitoring precision and response efficiency.

The invention provides a double-track absolute position detection method and system, computer equipment and a storage medium, and the method comprises the steps: detecting a to-be-detected object through a double-track magnetic railing ruler, enabling the to-be-detected object to be connected with a reading head, enabling the reading head to move along with the to-be-detected object, and enabling the reading head to read the to-be-detected object when the to-be-detected object linearly moves relative to the double-track magnetic railing ruler. Incremental magnetic track information of the incremental coding magnetic track is read through an incremental coding reading head; a level signal is output through a plurality of switch position detection chips in an absolute coding reading head based on the polarity of an absolute coding magnetic track position closest to the switch position detection chips, and absolute magnetic track information is determined according to the level signal; and performing combined calculation according to the incremental magnetic track information and the level signal to obtain a double-magnetic-track absolute position detection result. According to the method, the defect that an existing incremental displacement sensor needs to make a zero position again or search the zero position after being powered off or restarted is overcome, and the application scene of non-contact displacement detection is expanded.

A method of database operations includes receiving a user query, generating a query vector embedding representative of the user query, querying a vector database using the query vector embedding, retrieving a first database vector of the plurality of database vectors based on the query and representative of a first data file corresponding to a first time and belonging to a first time-series data set, receiving a first plurality of delta encodings describing differences between vector representations of temporally-adjacent data files of the first time-series data set, identifying a second data file of the first time-series data set having a second vector representation that differs from the first database vector and corresponds to a second time, and retrieving the second data file from a database.

A computer-implemented method for optimizing encoding video frames from a video is provided. In an embodiment, the method comprises receiving a video frame to be encoded. The method further comprises using one or more machine learning models to generate an encoding parameter value for encoding the video frame. The method further comprises comparing a first set of delta encoding values, based on the encoding parameter value, representing differences between groups of pixels of the video frame to a second set of delta encoding values, based on an alternative encoding parameter value, representing differences between the groups of pixels of the video frame, and in response to determining that the first set of delta encoding values is less than the second set of delta encoding values, selecting the encoding parameter value. The method further comprises based on the encoding parameter value, encoding the video frame to generate an encoded video frame.

Data compaction using codebooks, that applies delta encoding methods to entropy encoding methods to improve data compaction of entropy encoding methods under certain conditions and when compacting data having certain characteristics. Delta encoding may be applied to entropy encoding methods to further compact data sets by reducing the number of sourceblocks included in a codebook to those most commonly encountered in data to be encoded and, where mismatches occur during encoding, using delta encoding of bit differences with existing sourceblocks in the codebook rather than adding new sourceblocks to the codebook.

The invention provides a fractional order differential analog-to-digital conversion device for neural peak potential acquisition. Firstly, a fractional order difference operator is designed to calculate any fractional order increment code, nerve peak potential sparsity can be more effectively utilized, the nerve peak potential compression ratio is remarkably improved, meanwhile, higher flexibility is achieved, the difference order is adjustable, and the method can adapt to more nerve peak potential collection application scenes. Secondly, a fractional order buffer module is designed, and any fractional order increment coding value can be generated in a simple and efficient mode. And finally, a serialized bit stream generator is designed, the fractional order incremental data collected by a plurality of parallel channels can be subjected to serialized packaging, the expandability is very high, the method can be suitable for multi-channel collection, and the method can be reliably connected with a subsequent synchronous clock wireless transmission system. The overhead and delay of synchronous-asynchronous interface coordination are avoided, and the nerve peak potential acquisition efficiency is further improved.

According to the data set processing method and device provided by the embodiment of the invention, a three-layer storage architecture is innovatively constructed, and efficient collaboration of edge caching, center storage and memory grids is realized through heat value calculation and dynamic allocation. And designing a small file processing mechanism based on file similarity, and establishing a logic large file generation strategy by combining dynamic partitioning and incremental coding. And an access mode prediction mechanism is introduced, and data prefetching and training optimization are realized through feature vector analysis and zero-copy transmission. According to the method, the defects of the traditional technology in the aspects of storage architecture, small file processing, data prefetching and the like are effectively overcome, and the data set processing efficiency and performance are remarkably improved.

A method of recreating vector database data from delta encoding data includes receiving first time-series vector data from a vector database and comprising a first plurality of vector embeddings representative of a first plurality of data files corresponding to a first time point, receiving a first plurality of delta encodings representative of differences between corresponding vector embeddings of the first plurality of vector embeddings and a second plurality of vector embeddings, and recreating the second plurality of vector embeddings based on the first plurality of vector embeddings and the first plurality of delta encodings. The second plurality of vector embeddings is representative of a second plurality of data files corresponding to a second time point each vector embedding of the second plurality of vector embeddings corresponds to one vector embedding of the first plurality of vector embeddings.

Systems and methods for coding of handles in meshes. In an example mesh encoding method, information is obtained describing a geometry of a mesh comprising a plurality of triangles, each triangle having a plurality of corners associated with a respective corner index. Handle information is encoded identifying a pair of corner indices. The pair of corner indices includes a first corner index and a second corner index. The encoding of the handle information comprises encoding a sign of the first corner index. In some embodiments, encoding the handle information further comprises encoding an offset of the second corner index. In some embodiments, the first and / or second corner index are encoded using delta coding.

This invention proposes an integer-order differential analog-to-digital converter (ADC) for intracranial neural potential acquisition. First, an integer-order differential operator is designed to calculate arbitrary integer-order incremental codes, which more effectively utilizes the sparsity of intracranial neural potentials, significantly improving the compression rate of intracranial neural potentials. It also offers greater flexibility, with adjustable differential order, adapting to a wider range of intracranial neural potential acquisition applications. Second, a multi-level buffer matrix module is designed to generate arbitrary integer-order incremental code values ​​in a concise and efficient manner. Finally, a serialized bitstream generator is designed to serialize and package integer-order incremental data acquired from multiple parallel channels. This not only offers high scalability but also allows for reliable interfacing with subsequent synchronous clock wireless transmission systems, avoiding the overhead and latency of synchronous-asynchronous interface coordination, further improving signal acquisition efficiency.

Embodiments of the present disclosure relate to an extended delta coding technique for compressing raw data of optical detection and ranging. A light detection and ranging (LIDAR) receiver includes: an array of light detectors configured to generate a plurality of electrical signals; a receiver circuit including a plurality of readout channels and a plurality of multi-bit ADCs, the plurality of readout channels being configured to read out the plurality of electrical signals from the array of light detectors, wherein each of the plurality of readout channels includes a different one of the plurality of multi-bit ADCs, and each of the plurality of multi-bit ADCs is configured to convert at least one electrical signal into an ADC data sample, causing the plurality of multi-bit ADCs to generate a sequence of ADC data samples; an encoder coupled to the plurality of readout channels and configured to receive the sequence of ADC data samples and generate a compressed data packet based on the sequence of ADC data samples; and a communication interface configured to transmit the compressed data packet.

The present application discloses a method, apparatus, and related equipment for compressing genetic data in the context of high-throughput sequencing. The method comprises: obtaining genetic data to be compressed, and obtaining metadata, base data, and quality data of each short sequence from the genetic data; compressing the metadata of each short sequence using incremental coding technology or run-length coding technology; comparing the base data of each short sequence using a preset reference genome, and compressing the base data of each short sequence based on the comparison results; and compressing the quality data of each short sequence using a combination of run-length coding technology, contextual statistical model, ANS+FSE coding technology, arithmetic coding technology, and / or Huffman coding technology. The present application improves the compression rate by using compression methods adapted to different parts of the data, thereby saving storage space for massive genetic data.

The invention discloses a sepsis organ dysfunction early warning method based on sparse data incremental coding, and the method comprises the steps: obtaining event sequence data and non-event sequence data of a target object, the event sequence data comprising at least one of clinical diagnosis data, treatment record data and laboratory historical detection data, and the non-event sequence data comprising at least one of the clinical diagnosis data, the treatment record data and the laboratory historical detection data; the non-event sequence data at least comprises past medical history data and target sign data; performing incremental coding on the event sequence data to obtain a sparse mode of the event sequence data; processing the sparse mode, the event sequence data and the non-event sequence data according to a pre-constructed early warning model to obtain sepsis risk indexes of the target object; and under the condition that the sepsis risk index meets a preset early warning condition, outputting target early warning information.

The invention provides an integer order differential analog-to-digital conversion device for intracranial neural field potential acquisition. Firstly, an integer order difference operator is designed to calculate any integer order increment code, the intracranial nerve field potential sparsity can be more effectively utilized, the intracranial nerve field potential compression ratio is remarkably improved, meanwhile, higher flexibility is achieved, the difference order is adjustable, and the method can adapt to more intracranial nerve field potential collection application scenes. Secondly, a multi-stage buffer matrix module is designed, and any integer order increment coding value can be generated in a simple and efficient mode. Finally, a serialization bit stream generator is designed, integer order incremental data collected by a plurality of parallel channels can be subjected to serialization packaging, high expandability is achieved, reliable butt joint with a follow-up synchronous clock wireless transmission system can be achieved, overhead and delay of synchronous-asynchronous interface coordination are avoided, and the system performance is improved. And the signal acquisition efficiency is further improved.

A method of vector database compression includes receiving first time-series vector data comprising a first plurality of vectors representative of data corresponding to a first time point, receiving second time-series vector data comprising a second plurality of vectors representative of data corresponding to a second time point, generating a plurality of delta encodings, discarding the second time-series vector data after generating the plurality of delta encodings, and modifying database data to store the plurality of delta encodings. Each vector of the second plurality of vectors corresponds to one vector of the first plurality of vectors. The plurality of delta encodings is generated by, for all corresponding vectors of the first plurality of vectors and the second plurality of vectors, generating one delta encoding that describes differences between values of corresponding elements of the vector of the second plurality of vectors and the corresponding vector of the first plurality of vectors.

The invention provides a verifiable resource transmission method and device based on incremental coding, and the method comprises the steps: pulling certificate information from a key server, and determining a mapping relation between each communication entity and a public key; determining a target communication entity and an intermediate communication entity on the communication path based on respective forwarding strategies and certificate information of the communication entities; transmitting the resource information on the source communication entity to an intermediate communication entity on the next path, and verifying the incremental code contained in the resource information by the intermediate communication entity; and if the verification is successful, adding the verifiable code of the intermediate communication entity to the incremental code, sending the resource information to the intermediate communication entity on the next path, and repeating the verification process and the addition process until the target communication entity receives the resource information. Incremental coding of hop-by-hop generation and hop-by-hop verification is adopted, the verifiable trust of the path nodes to the resources is proved, and the problem of trusted transmission of the resources in the network can be solved.

The present invention belongs to the field of electronic information technology, and specifically relates to an improved differential compression algorithm for unstructured data. The following steps are included: step 1, setting a buffer; step 2, reading reference data R and target data T; step 3, running the 1.5-pass algorithm, when the ADD command appears, or the data T has been matched, suspending the operation, and placing the commands of the selected area and the new area into the buffer in sequence; step 4, sequentially merging the commands of the selected area in the buffer with rules R5, R1, R3 or R4, R4 or R3, R2, outputting the new command after completion and suffixing it to the corrected area; step 5, alternately executing steps 3 and 4 until there is no new area, and ending the operation. The present invention proposes a cost model based on the actual storage method of the computer system, which reduces the cost of the incremental coding sequence by merging instructions, and then uses the incremental cost coding sequence to replace the original data for storage and transmission, which can effectively save data storage space and network transmission speed.

Provided are a blockchain-based block compression method and apparatus, a device, and a readable storage medium. The method comprises: acquiring M transaction data packets, each of the transaction data packets comprising transaction attribute values of N transaction attribute types; on the basis of the transaction attribute values and type priorities respectively corresponding to the N transaction attribute types, determining a positional order of the M transaction data packets, so as to obtain a transaction data packet sequence; for the N transaction attribute types, on the basis of the transaction attribute values corresponding to the same transaction attribute types in the transaction data packet sequence, respectively generating attribute value sets according to the positional order, so as to obtain N attribute value sets; respectively performing delta encoding processing on the N attribute value sets to obtain N attribute value delta encodings; and performing block encapsulation processing on the N attribute value delta encodings to obtain a block pending for blockchain uploading.

The present invention relates to a method for transmitting data originating from an event-based image sensor (1) via a data channel (4). In this process, a camera stream (2) from the event-based image sensor (1) is converted and compressed into a bit stream (11) using event prediction (7) and delta coding (8) as well as subsequent entropy coding (10), and the bit stream (11) is transmitted via the data channel (4) to a receiver side (5).