60results about How to "Increase the compression ratio" patented technology

The invention discloses a point cloud intelligent cutting and dynamic optimization method based on edge computing, and belongs to the technical field of intelligent traffic systems and edge computing, and the method comprises the steps: collecting three-dimensional point cloud data through a multi-line laser radar disposed on an RSU; generating a three-dimensional bounding box through a three-dimensional target detection network in an RSU edge calculation unit, generating an ROI mask, expanding a buffer region, and performing adaptive region cutting on the point cloud to form an ROI point set and a background point set; a perception-driven cutting decision is realized, and ROI extraction is converted into a self-learning process based on semantic features from fixed threshold judgment; voxelizing the non-uniform resolution point cloud, generating a unique hash index for each voxel unit, comparing a hash set of a current frame with a hash set of a previous frame, extracting newly added and disappeared point sets, and constructing a differential data packet according to a change ratio; while high timeliness is kept, data redundancy is reduced, and the point cloud updating rate and the incremental transmission efficiency are improved; and dynamic optimization of communication-calculation cooperation is realized.

The invention discloses a decision-making system and method based on a Dores database, and the system comprises a data access layer which is used for accessing multi-source heterogeneous financial data in real time, a Dores storage calculation layer, and achieves the data storage, column-type bucket separation and materialized view pre-calculation based on the Dores database; the visual application layer is used for providing bidirectional interactive financial data visualization and decision support; wherein the data access layer acquires data in real time through a streaming computing engine and transmits the data to the Dores storage computing layer, and the visual application layer performs real-time data interaction with the Dores storage computing layer through a two-way communication protocol. According to the method, the synchronous delay of financial data is shortened from 6 hours to 1 second, second-level real-time integration is realized, the aggregation query response time of billion-level data is reduced to be within 1 second based on a Dores column type storage and materialized view technology, the user interaction response delay is lower than 500 milliseconds through WebSocket two-way communication, and real-time adjustment of parameters and dynamic refreshing of a billboard are supported.

This invention provides a recycling and compression device for lithium battery positive and negative electrode waste, comprising a housing, a compaction unit, a purification unit, a waste collection trolley, and an electrical control system. The housing includes a settling chamber, a solid-gas separation device, an air duct switching device, and a housing frame. The compaction unit includes a compaction chamber, a push plate, and a drive device. This invention optimizes the air inlet structure design, significantly reducing the problem of waste material wandering inside the equipment and failing to fall into the compaction chamber, and reducing the risk of material blockage. Utilizing airflow guidance, it effectively ensures that the compaction chamber is filled with waste, improving collection efficiency, increasing the compression ratio, extending the service life of the servo cylinder, reducing energy consumption, and reducing the frequency of waste collection by workers. The addition of a pressure relief port at the outlet significantly reduces the frequency of equipment alarms and effectively pushes the waste into the collection trolley.

The utility model relates to the technical field of environment-friendly waste paperboard compression equipment, and discloses energy-saving environment-friendly waste paperboard compression equipment which comprises a compression box, a box frame is fixedly connected to the left side of the compression box, a door shaft is arranged on the front side of the box frame, and a box door is fixedly installed on the right side of the door shaft. A clamping base is fixedly connected to the front side of the box door, a door pin is arranged at the upper end of the clamping base, a control switch is fixedly installed on the right side of the compression box, and a main hydraulic cylinder and an auxiliary hydraulic cylinder are arranged in the compression box. According to the energy-saving and environment-friendly waste paperboard compression equipment, through the arrangement of the crushing mechanism, a driving motor can be used for driving a first gear and a second gear to rotate in an engaged mode, so that a first crushing roller and a second crushing roller are driven to crush waste paperboards, the waste paperboards are crushed into small blocks, and subsequent block pressing treatment is facilitated; when the small waste paper is compressed, the compression resistance can be reduced, the small waste paper can be stacked more tightly, gaps are reduced, and the compression ratio is increased.

This application relates to the field of natural language processing, and more particularly to a method for ultra-long context tensor parallel incremental attention and differential compression transmission. It employs a multi-level precision sliding window attention mechanism, dynamically allocating precision levels such as fp16 / int8 / int4 based on the distance between the window and the current computation position, and the information entropy of the window content. A tensor parallel incremental attention engine enables cross-GPU / node incremental attention computation and asynchronous All-Reduce synchronization, improving computational efficiency. Semantic differential compression transmission technology is used, transmitting only the differential data based on similarity detection, significantly reducing cross-node transmission overhead. Combined with an extreme performance optimization and security control strategy, a balance between performance and security is achieved through hardware monitoring and dynamic power consumption / frequency adjustment. This invention can significantly reduce memory usage and transmission overhead in ultra-long context processing, improve computational efficiency and hardware utilization, enhance the understanding ability of large models for long texts, adapt to heterogeneous hardware environments, and is suitable for large model inference and training scenarios.

The application discloses a low-temperature oil-free centrifugal compressor placed in an adiabatic environment, comprising an adiabatic cold box, a centrifugal compressor unit, connecting pipelines and a vacuum pump. The centrifugal compressor is placed in the adiabatic cold box and comprises a motor, an impeller, a volute and a bearing. The impeller and the motor at two ends of the centrifugal compressor are placed in different chambers of the adiabatic cold box. The centrifugal compressor can adopt the same rotor structure at two ends. The motor does not need to be cooled. The centrifugal compressor is provided with a motor heat preservation loop. The bearing adopts a gas bearing or a gas-magnetic hybrid bearing, and the gas bearing type is full dynamic pressure, dynamic-static pressure or full static pressure. The low-temperature oil-free centrifugal compressor placed in the adiabatic environment can greatly reduce the power consumption and cold leakage loss of the compressor. The compressor with the same structure at two sides does not need to consider the axial force. Through the measures of setting different adiabatic chambers and heat preservation loops, the compressor can operate at an import temperature of -268 to -20 DEG C. The low-temperature centrifugal compressor is purely oil-free, and the system volume and weight are greatly reduced.

The invention provides a dynamic sampling vehicle track processing method and device, a medium and equipment. The method comprises the following steps: acquiring current track point data of a target vehicle; determining attribute characteristics of the current track point data based on the current track point data and the historical track point data, predicting next track point data, and determining a leaving state of the current track point data; determining a sampling proportion of the target vehicle based on the current track point data and the historical track point data; on the basis of the sampling proportion, track data of the target vehicle in a road section corresponding to the current track point data and the historical track point data are reserved; whether the current track point data is normal or not is judged according to the historical track point data, the next track point data is predicted according to the historical track point data so as to judge whether the current track point data is reserved or not, and the sampling proportion of the corresponding road section is determined according to the track point data, so that track point sampling and storage can be performed in a more targeted manner. The compression rate is improved, and the integrity and authenticity of the track are kept.

The invention discloses a damaged carton recycling device and method for carton packaging, and relates to the technical field of waste recycling, the damaged carton recycling device comprises a shell, two door bodies rotationally installed on the shell, a control module fixedly installed outside the shell and a data display module, the compaction assembly is mounted in the shell; the hydraulic rod is fixedly mounted at the top of the shell; and the compaction assembly comprises a bottom plate fixedly mounted at the bottom of the shell and an extrusion plate slidably mounted in the shell, a connecting sleeve is fixedly mounted on the extrusion plate, and the driving end of the hydraulic rod is fixedly connected with the connecting sleeve. The carton compacting device has the advantages that in the carton compacting process, through pressure equalizing and buffering of the pressure buffering assembly, negative pressure air exhaust gap discharging and resistance reducing, lateral protection restraining deformation and repeated tamping successive exhaust plastic deformation, the interlayer fitting degree and uniformity of paperboards can be synergistically improved, and the higher compression ratio and the lower rebound rate are achieved.

This application relates to an information scheduling method, a data compression and transmission method, and a data decompression method. The method involves obtaining a locally cached list of popular patterns, which includes interrelated pattern numbers and parser identifiers. This list is broadcast by a central scheduling system, which generates the list by tracking parsers that appear frequently in recent node reports. A target parser matching the original message to be sent is determined from the popular pattern list. A data packet is constructed based on the dynamic variable vector obtained after encoding the original message by the target parser, and the target pattern number corresponding to the target parser. The data packet is then sent to a second node. This method effectively improves the compression rate for data with uncertain structures.

The application relates to the technical field of VR interaction data management, in particular to a VR interaction data management method based on artificial intelligence. The method comprises the following steps: acquiring coordinate point sequences of each joint point and normal fluctuation thresholds of various coordinates respectively; obtaining action change coordinate points; dividing the coordinate point sequences to obtain different compressed data segments; forming two compressed data segments with time containing or equal relationship in the compressed data segments corresponding to two joint points into a to-be-analyzed combination, and then obtaining a data segment combination; acquiring relative position vectors of various coordinates of the data segment combination; judging whether the data segment combination is a linkage combination; acquiring an action mode code of the linkage combination and a fitting slope value of each coordinate of a basic data segment in the linkage combination; and storing the action mode code of the data segment combination, initial coordinate points in the basic data segment and the fitting slope value of each coordinate. The application can improve the compression rate of VR interaction data.

The application provides a database monitoring operation and maintenance method and system based on time series data compression, which realizes real-time monitoring of various index data of a database platform through efficient data acquisition and compression technology. The system can efficiently collect various performance data generated during the operation of the database, and optimize the time series data through a compression algorithm to reduce the redundant storage of data. In the data storage and management process, the first-order difference sequence and the second-order difference sequence are calculated to reduce the amount of stored data. The use of difference removes the trend in the original data sequence, making the subsequent difference sequence easier to compress. At the same time, for non-constant difference, by setting a dynamic threshold, only the difference values greater than the threshold are recorded, and the small changes are ignored on the premise of not losing important information of the data, thereby improving the compression rate. On the other hand, by using S relation The regularity of the difference sequence is determined, and the compression strategy can be selectively applied, so that suitable compression methods can be applied to time series data with different characteristics, thereby improving the processing efficiency. Through the above design, the storage and processing efficiency of the compressed data are improved, the system can quickly decompress and analyze the data, and the real-time monitoring of the running state of the database is realized.

The present application belongs to the technical field of data processing, and in particular to an optimal iterative data compression method based on Huffman coding. The method first counts the frequency of each symbol in the original data and sorts them, and performs the 0th layer Huffman coding as the initial optimal result. Then, the method enters the iterative replacement compression loop, sorts the data of the current layer according to the frequency, replaces the 1st symbol with the 2nd symbol, and so on, generates a new data string and records the replacement mask string, performs Huffman coding on the new data string, and calculates the total compression length containing the mask string. The result of each layer is compared with the current optimal length, and if it is better, the optimal result is updated. The iteration continues until the symbol type is reduced to 1 or the total length of the mask exceeds the optimal length. Finally, the compressed data composed of the prefix coding, the mask string of each layer and the optimal layer compression coding string is output. The present application significantly improves the compression efficiency of Huffman coding by reducing the symbol type through iterative pairing replacement and combining with hierarchical optimal selection.

This invention provides a lossless frame compression method that is easy to implement in HEVC hardware, comprising: S1. Data alignment of the image, expanding the width to a multiple of 64 and the height to a multiple of 16; S2. Block partitioning; S3. Compression of 4*64 size luma PLCU and chroma PLCU, each PLCU being an independent compression unit, with compression performed in units of sbk; obtaining the data_val of all pixels in the luma and chroma PLCU; setting different data_len values ​​according to the characteristics of the data_val of pixels in sbk; S4. Generating the Body, compressing pixels according to the information obtained above; S5. Generating the Head. This method breaks away from the original encoding framework, is more adaptable, and achieves a better compression ratio and faster compression speed through appropriate block partitioning, better luma and chroma component processing, and fewer syntax elements.

This invention relates to a dry ice spray cleaning and sterilizing device, aiming to solve the technical problem of the current dry ice spray cleaning and sterilizing devices having only a single spraying operation function. The device includes a cabinet; an embedded sterilization and cleaning tank is provided on the upper surface of the cabinet; the gap between the inner wall of the cabinet and the outer wall of the embedded sterilization and cleaning tank forms a multi-stage operating chamber; the embedded sterilization and cleaning tank is an electrically heated structure; and multiple cleaning components are provided inside the multi-stage operating chambers; and a dual-mode sterilization and cleaning system is provided at the output end of the multi-stage cleaning components; a transparent splash guard is hinged to the outer wall of the cabinet relative to the embedded sterilization and cleaning tank. This invention improves the cleaning effect of high-pressure dry ice spraying by adapting two operating modes to the continuous, efficient, and fully covered contact of the foam cleaner, and adapting the intermittent contact of the dry ice spraying operation to the changes in spray distance caused by angle changes during actual operation.

The application discloses a lossless compression method and system for image sensor raw data, and relates to the technical field of image sensors.The application fully utilizes the statistical characteristics that the pixel value difference between adjacent frames under the same exposure is extremely small, combines the inherent color arrangement rule of the Bayer format image, separates the color channels first and then performs time domain difference calculation, greatly reduces the data entropy value, and obtains a compression ratio much higher than that of a general lossless compression algorithm on the premise of completely lossless original pixel values; meanwhile, independent compression and packaging are performed with the minimum service unit as the granularity, target data can be directly located and accessed without decompression and large-scale package, the data retrieval and calculation overheads are reduced, the traceability of the original data is retained, the statistical confidence of the test result is not affected, and the batch data storage requirement in the image sensor production test scene is adapted.

The utility model provides an engine which comprises an air cylinder, a piston and a cylinder cover, the piston is movably arranged in the air cylinder, and a protruding part gradually protruding inwards in the radial direction is formed on the edge of the top of the piston. The cylinder cover is installed on the cylinder, a combustion chamber is defined by the cylinder cover, the cylinder and the piston, a matching part surrounding the combustion chamber is formed on the surface, facing the combustion chamber, of the cylinder cover, and the protruding part is configured to respond to the piston to move upwards to the upper dead center to be in clearance fit with the matching part.

The utility model discloses a kind of axial flow centrifugal compressor for compressed air energy storage, it is related to energy storage technical field, comprising: axial flow section, centrifugal section and main shaft;The axial flow section has casing and the axial flow rotor in the casing, the centrifugal section has volute and the centrifugal rotor in the volute, the casing is connected with the volute;The axial flow rotor is connected with the one end of the main shaft by fastener, the centrifugal rotor is sleeved on the main shaft, the upstream end of the centrifugal rotor is supported on the boss of the main shaft the downstream end of the centrifugal rotor is detachably connected with the main shaft by connecting structure.The utility model technical scheme, axial flow rotor and centrifugal rotor are respectively set as detachably connected with main shaft, so that axial flow rotor, centrifugal rotor and main shaft can be separately produced, for large flow, high pressure ratio compressor, independent production facilitates each part manufacturing.

This invention belongs to the field of communication technology, specifically relating to a method for content delivery and local confirmation for glasses in a private network environment. The method includes the following steps: Step 1: The content delivery server assigns a task identifier to each task content data and sends it to the glasses terminals within the private network via a User Datagram Protocol (UDP) broadcast channel; Step 2: Each glasses terminal receives the UDP broadcast data until it recovers the complete task content data and registers it in its local task table; Step 3: When a glasses terminal executes task content data in the registered state, it triggers a voice confirmation module to collect the wearer's confirmation-type command voice to generate a task confirmation event. The content delivery server then parses the Bloom filter digest bit array to obtain the set of completed tasks and updates the task management record. This invention significantly improves the efficiency, reliability, and controllability of task management in a private network environment.

The application relates to the technical field of artificial intelligence, and discloses a large model construction method, device, equipment and medium, the method comprising the following steps: performing block processing on a Transformer weight matrix of a target model to form a plurality of sub-matrices; performing low-rank approximation on each sub-matrix through two-dimensional Kronecker decomposition to obtain the Kronecker product of two small matrices corresponding to each sub-matrix; freezing the parameters of all the small matrices, using LoRA to obtain additional parameters corresponding to all the small matrices to obtain a two-dimensional Kronecker-LoRA compression model; taking the target model as a teacher model, and using a data set to train the two-dimensional Kronecker-LoRA compression model to obtain a large model. The method can reduce the parameter size and resource demand of an existing large model, form a suitable large model, effectively reduce performance loss, achieve a balance between high compression rate and high precision, adapt the dynamic reasoning and image processing process depth, and facilitate wide deployment on edge devices.

This invention discloses a lossless data compression and encrypted transmission method based on federated middleware, belonging to the field of computer application technology. The method includes: performing run-length encoding on the data to be processed based on federated middleware to obtain first compressed data; processing the first compressed data using a compression algorithm based on a raw-middleware dual dictionary to obtain second compressed data. This compression algorithm uses both the raw dictionary and the middleware dual dictionary, adding only values ​​that appear at a set frequency to the dictionary; sequentially performing Huffman coding and DES processing on the second compressed data to obtain encrypted data and a key; performing RSA processing on the key to obtain an encrypted key; and transmitting the encrypted data and the encrypted key to the target end using an encrypted compression transmission plugin of an experiment-and-train-enabled architecture. This method achieves lossless data compression and encryption based on federated middleware, with fast algorithm speed and high security.

The invention relates to a self-adaptive quantum random number generation method based on real-time entropy estimation, and belongs to the technical field of quantum random number generation. According to an existing integrated quantum random number generator, due to the non-stationary characteristic of a physical entropy source, the entropy rate dynamically drifts, and after-processing parameters are fixed, randomness safety and generation efficiency are difficult to guarantee at the same time. According to the method, the state transition probability of the original random bit stream is counted in real time, the confidence interval correction is introduced to calculate the minimum entropy, the input bit width is dynamically adjusted accordingly, the Toeplitz matrix is reconstructed for random extraction, and self-adaptive adjustment of the compression ratio is achieved. According to the method, the compression ratio is increased to ensure the security of the output random number when the entropy source quality is reduced, and the compression ratio is reduced to improve the generation efficiency when the entropy source quality is improved, so that the dynamic balance between the randomness security and the generation efficiency is realized on the premise of keeping integration and low cost.

The invention relates to the technical field of big data analysis, in particular to a space-time big data acquisition and analysis system and method based on the Internet of Things, and the method comprises the following steps: inserting a drift compensation tag at the tail part of each time grid block, and outputting the time grid block with the drift compensation tag; combining the associated data items into a logic data unit; performing semantic isomorphic compression on the logic data unit and the data items with the same spatial hash codes at an edge node to generate a compression block with a spatial-temporal index; and the cloud server receives the compressed block, performs time conflict disambiguation and event-level causal reasoning on the spatio-temporal index by using a causal chain engine, and directly outputs drifting-free and redundancy-free spatio-temporal knowledge which is used for driving high-order application. According to the method, cross-space causal path matching and standard time sequence verification of the uploaded data are realized, and a plurality of actually occurring event-level causal chains can be automatically identified.

This invention discloses a high-efficiency video analysis method based on cloud-edge collaboration and adaptive MoE. The method includes: when an edge device performs a video analysis task, it first constructs a meta-request containing current task data and device resource constraints, and sends it to the cloud; the cloud uses a pre-trained basic model to extract features from the video data and clusters the data based on the feature space, dividing complex video scenes into multiple semantic subdomains; a lightweight expert model is trained in the cloud for each semantic subdomain; a routing decision model is further trained in the cloud; after deploying an expert model pool and routers on the edge device, for input data, the router first calculates the matching degree of each expert model and performs a comprehensive evaluation based on its computational cost. Through knowledge distillation, the large-scale basic model is decomposed into lightweight expert models, achieving a significant compression of the model size, enabling efficient deployment on resource-constrained edge devices.

This invention provides a method and system for compressing power messages, relating to the field of power system control technology. The method includes: acquiring power messages via a first FPGA; timestamping the acquired power messages; caching the timestamped messages in a first shared memory; extracting messages from the first shared memory; parsing the messages according to their type and classifying and storing them in a second shared memory; extracting messages from the second shared memory by control block using a second FPGA; compressing the compressed packages corresponding to the control blocks; storing the compressed packages in a third shared memory; packaging and secondary compression according to a set time period; generating a total compressed package for that time period; and storing it on an SSD for dual-disk storage. This invention effectively reduces the storage space requirements for historical messages, improves the storage time of historical messages, and solves the problem of frequent failures in storing historical messages for post-event analysis of power systems.

This invention discloses a method for producing large-size H13 round steel, comprising the following steps: (1) Electric furnace smelting: the steel charge to the furnace includes 5-10t of DRI direct reduced iron, and the steel output C≥0.05%; (2) Refining: using the LF+RH process; the LF furnace performs a slag return operation, with a slag return amount of 500-1000kg; in the LF furnace, after slag formation and deoxidation, 20-30t of H13 continuous casting head billet and / or tail billet are added for partial alloying, with a white slag time of 110-160min; the vacuum time in the RH furnace is 30-35min; (3) Vertical continuous casting: casting is performed using a vertical continuous casting machine with a casting speed of 0.36-0.40m / min. This invention improves the steelmaking and rolling processes, thereby increasing the internal flaw detection pass rate of large-size H13 round steel, significantly improving the core quality of the round steel, and obtaining green, high-quality large-size H13 round steel that meets market demands.

The present application relates to a high-fidelity key cache compression method and system based on spectral quantization, comprising: step S1: spectral transformation and feature analysis process; receiving original key cache data from the model, mapping the original key cache data from the time domain to the frequency domain, and deeply analyzing the signal structure by using the energy concentration characteristics unique to the discrete cosine transform (DCT); step S2: frequency domain hybrid quantization encoding process; by using the main frequency extraction mechanism, the high frequency pre-emphasis technology and the hybrid bit width allocation strategy, the frequency domain coefficient is compressed into a sparse representation with extremely low bit; step S3: fusion decoding and sparse accumulation process; by using the hardware-aware fusion operator and the delay inverse transform technology, the attention score is calculated directly in the compression domain. The present application realizes the limit compression and efficient inference under the lossless precision.

This invention relates to a method for manufacturing high-surface-quality steel wire for chain pins, comprising the following steps: steel smelting → continuous casting → heating of continuously cast billets → billet preparation → flaw detection and grinding of intermediate billets → wire rod heating → high-pressure water descaling → annealing → pickling and phosphating → wire drawing → finished product. The method employs a two-stage forming process, with a high compression ratio in billet rolling, wire rod rolling, and wire drawing, which reduces the impact of defects in the raw material on the finished product. During billet rolling, flame cleaning is used to remove surface defects from the billet. Before wire rod rolling, the intermediate billet undergoes surface flaw detection and full grinding to ensure a defect-free surface. Eddy current testing and high-reduction-ratio wire drawing ensure the depth of surface defects in the steel wire, and the high-reduction-ratio drawing results in higher wire hardness, improving the cutting performance for pin processing. Finally, the steel wire used in pin production can control the single-sided grinding residue to within 0.03mm, significantly improving material yield and surface defect compliance. Simultaneously, the high wire hardness provides excellent cutting performance for pin processing.

The embodiment of the application discloses a kind of generation method, equipment, storage medium and program product of visibility information file, belong to image processing technical field.The method comprises: generating initial visibility matrix based on virtual scene;Based on the hamming distance between model visibility vector in initial visibility matrix, the arrangement order of model visibility vector is adjusted, and target visibility matrix is obtained;The target visibility matrix is compressed in binary, and the visibility information file is generated.The application improves the compression rate of visibility information, reduces the size of visibility information file, thereby improves the loading performance of scene rendering under the premise of guaranteeing information accuracy.

This invention relates to a method and system for visualizing a bridge BIM model. Specifically, the method involves acquiring a bridge BIM model, calculating the folding cost and the degree of local optimization after folding for each edge, sorting the edges according to the folding cost and the degree of local optimization, and placing them into a priority queue. Edges are then sequentially removed from the priority queue, and topology and boundary preservation checks are performed. If the checks pass, the two vertices of the removed edge are merged into a new vertex, and the folding cost and the degree of local optimization after folding for the affected edge are updated; otherwise, the removed edge is skipped. The simplified BIM model is divided into multiple components, and a starting triangle is determined from each component based on the normal vector of the triangle neighborhood in the component. The component is compressed using the starting triangle and then sent to a mobile device. The mobile device decompresses and renders the BIM model.