28results about How to "Reduce storage" patented technology

A data quantization method and device, a computer readable storage medium and a chip, the data quantization method comprising: obtaining a data block to be quantized, dividing the data block to be quantized into one or more data groups to be quantized according to a preset grouping method; performing quantization calculation on each data group to be quantized according to a target quantization format, to obtain quantization data corresponding to data in each data group to be quantized and quantization metadata corresponding to each data group to be quantized, wherein the quantization metadata is used for dequantization of the quantization data; and storing the quantization metadata corresponding to the data block to be quantized and the quantization data as a continuous data structure.

This invention discloses a continuous synthesis apparatus and process for nitrobenzene. The synthesis apparatus includes a mixed acid preparation system, a continuous benzene nitration system, an organic phase continuous stratification system, and a continuous water washing-alkali washing-water washing system. The process includes: concentrated sulfuric acid and concentrated nitric acid are pumped into the mixing module of the mixed acid preparation system to obtain a mixed acid solution; benzene and the mixed acid solution are pumped into the microchannel reactor of the continuous benzene nitration system; the nitrated material is cooled and then pumped into the continuous organic phase stratification system; the resulting intermediate organic phase nitrate enters the next processing unit; the organic phase nitrate and water enter the continuous water washing-alkali washing-water washing system for washing to obtain the final product, nitrobenzene. The synthesis apparatus and process of this invention achieve continuous production of nitrobenzene throughout the entire process, realizing continuous and automated operation from raw material benzene to the final product, nitrobenzene.

The present application relates to the technical field of transport box, and discloses a transport box for egg circulation, which comprises a box body, a bottom plate arranged under the box body and used for supporting egg trays, a locking member movably arranged on the bottom plate and having a locking state and an unlocking state, a pushing assembly in transmission connection with the locking member, and a driving assembly used for driving the pushing assembly to move and switch the locking member between the locking state and the unlocking state. When the locking member is in the locking state, the box body is fixed relative to the bottom plate. When the locking member is in the unlocking state, the box body can be separated from the bottom plate. The transport box for egg circulation can realize overall loading and unloading through the separable design of the bottom plate and the box body. When loading, all the trays can be stacked on the bottom plate, and then the box body is buckled. When unloading, the box body can be lifted to expose the trays integrally, so that the loading and unloading time is greatly shortened, and the transport box is suitable for cooperation with automatic handling equipment and can realize rapid and batch circulation.

This invention discloses a lightweight few-shot incremental learning method for power line defects. The method includes: first, constructing an inspection image dataset containing basic and incremental categories, and designing a lightweight feature extraction network; training the network using the basic category data to generate prototype vectors for each category, forming an initial prototype classification model; in the incremental stage, constructing incremental prototypes for a small number of samples of the new category, and introducing a prototype transfer mechanism based on inter-class tension, adaptively adjusting the new prototype based on the geometric similarity and discrimination conflict strength between the new and existing prototypes to alleviate category conflicts; simultaneously, introducing an adaptive feature fusion mechanism that perceives discrimination uncertainty, dynamically fusing the discrimination results of the main and auxiliary branches to improve recognition stability. This invention, employing the above-mentioned lightweight few-shot incremental learning method for power line defects, can achieve efficient and stable power line defect recognition in scenarios with few samples and continuously expanding categories.

This invention discloses a multi-level index compression method, apparatus, and device for reducing image storage space, relating to the field of image processing technology. The method includes obtaining the total number of color categories of a security display icon, and calculating an index value representing each pixel in a single color based on the obtained total number of color categories and a preset encoding algorithm. The storage space occupied by the current security display icon is calculated by combining the index value with the current size of the security display icon, or by combining the index value with the current size of the security display icon and the region code of the target area, thereby achieving compression processing. This application significantly reduces the encoding bit width of pixels through multi-level encoding of image pixel data, effectively compressing the data volume of the security display icon and greatly reducing the data storage volume.

The present application relates to a kind of pneumonia detection model training method, specifically to a kind of hierarchical topology pneumonia detection model based on collaborative learning system and method.It overcomes the difficulty of existing pneumonia detection model training system, low efficiency and the problem that local detection node cannot achieve optimal detection performance.First, each node uses local pneumonia data to pre-train respective pneumonia detection model locally, then, center node is based on the feedback data of local model to build hierarchical topology collaborative learning system;After that, each cluster node and child node uses local pneumonia data to train respective pneumonia detection model locally;Finally, collaborative training is carried out, including intra-cluster collaborative training and inter-cluster collaborative training;Intra-cluster collaborative training includes cluster node aggregation training and child node random interactive training.The present application has small data transmission, storage and calculation pressure, and is easy to implement;At the same time, different client is provided with different model parameters, so that each hospital detection node achieves local detection performance maximization.

This invention specifically relates to an information management platform based on Internet of Things (IoT) technology, specifically in the fields of IoT data security and information management technology. It includes: a source-side data entanglement generation module; an edge-side local ledger maintenance module; a business event-triggered anchoring module; and a cloud-based auditing and dispute arbitration module. In this invention, standardized data collection and lightweight chained hash entanglement calculation lock the time-series data from the physical source of data generation. A lightweight algorithm with hardware-level optimization is used, occupying only 32 bytes of volatile memory to cache the latest hash value, adapting to the low power consumption, low computational cost, and small storage characteristics of IoT terminals. The edge side is equipped with a real-time packet-by-packet chain break detection and self-healing mechanism, which can quickly detect and attempt to repair hash chain breaks, preventing tamper-proofing failure.

The present application relates to a kind of cylindrical electrode paste and its preparation method.A kind of cylindrical electrode paste, by mass parts, including 15-20 parts of anthracite main material, 25-40 parts of residual anode, 3-10 parts of graphite fragment, 25-35 parts of coke, 15-30 parts of organic binder, 6-18 parts of bio-based binder. Among them, organic binder includes medium temperature pitch, anthracene oil, beta resin. Among them, bio-based binder includes carbonized hydrophobic composite modified wood bamboo powder, sodium carboxymethyl cellulose. The carbonized hydrophobic composite modified wood bamboo powder of the present application and sodium carboxymethyl cellulose are compounded to form a bio-based binder, which cooperates with the organic binder to ensure the bonding strength, high temperature resistance and electrical conductivity of the cylindrical electrode paste, while realizing the green and low-carbon utilization of biomass, solving the problems of high temperature failure, moisture absorption and easy caking, and many pores of traditional bio-based binder, reducing the resistivity and production cost, and improving the structural density and use stability.

This invention discloses a real-time personnel recording door lock system based on door lock handle action triggering, belonging to the field of smart lock technology. It includes: an inertia spectrum acquisition module for acquiring the rate of change of the angular velocity of the handle rotation and generating an idle inertia spectrum characterizing the handle's natural rotation; an energy-addition calculation module for decomposing the handle rotation into multiple phases and calculating the energy difference between the real-time inertia value of each phase and the idle inertia spectrum, defined as the operation energy-addition; and a feature window retrieval module for opening an attention window centered on the anchor point when the curve shape of the operation energy-addition matches a predetermined feature, with the handle rotation angle reaching a predetermined critical angle as the anchor point. This invention can avoid cluttered backend ledgers, reduce the difficulty and cost of data screening for management personnel, reduce system storage and computing power consumption, improve the response speed and operational stability of the door lock system, and prevent invalid logs from masking real abnormal events such as illegal intrusions.

The application discloses a weld surface defect detection method and system, and relates to the technical field of image recognition. The method comprises the following steps: acquiring a weld image to be detected; inputting the weld image to be detected into a preset weld defect detection model to obtain a defect detection result. The preset weld defect detection model comprises a preset backbone network, a preset neck network and a preset head network. The preset backbone network and the preset neck network each comprise a plurality of lightweight C2f modules that replace C2f modules in an original YOLOv8n model. Therefore, the model parameter quantity and the calculation quantity can be reduced to reduce the storage and calculation resource requirements of the model. In addition, the lightweight C2f modules are constructed based on a lightweight convolution layer and a double-channel attention mechanism. Therefore, the model detection accuracy for small target defects can be improved, and the missed detection rate can be effectively reduced.

This invention discloses a heterogeneous dual-stream Chinese memory reasoning method based on dynamic adjustment of semantic confidence, relating to the fields of natural language processing and large model architecture optimization in artificial intelligence. This application employs a semantic mapping table and gating mechanism to dynamically adjust the weights of the glyph feature vector and the context semantic vector of each Chinese character to generate a fused representation of each Chinese character, thereby more effectively distinguishing similar-looking characters and more accurately processing abstract words. Cross-attention calculation is performed on the semantic subgraph to obtain a corrected vector representation for the target text. Since the number of nodes in the semantic subgraph is limited, this correction process significantly reduces computational consumption compared to the global attention calculation of Transformer models or static hybrid architectures such as Jamba in the same text processing scenario.

The application belongs to the technical field of ice particle jet, and particularly relates to a device and a jet method for preparing straight-rotation mixed ice particle jet by using high-pressure superheated liquid flash evaporation, which comprises a high-pressure superheated liquid supply system and a water supply system, the high-pressure superheated liquid supply system and the water supply system are respectively connected with a straight-rotation mixed ice particle generation jet, the straight-rotation mixed ice particle generation jet system is connected with a recovery system, the recovery system is connected with the high-pressure superheated liquid supply system through a pipeline, the straight-rotation mixed ice particle generation jet system comprises a double-layer sleeve, the inner layer of the double-layer sleeve is connected with the water supply system, the outer layer is connected with the high-pressure superheated liquid supply system, an impeller is arranged at the outlet of the double-layer sleeve, a convergent atomizing nozzle is arranged at the outlet of the impeller, a protective shell is arranged outside the convergent atomizing nozzle, the convergent atomizing nozzle and the impeller center line are coincided with the inner layer, and the superheated liquid flash evaporation in the application has high refrigeration power and high speed, and can complete ice particle preparation in a short time.

This utility model discloses a rotary kiln for easy cleaning of aluminum ash slag. Relating to the field of aluminum ash slag treatment technology, the kiln includes a furnace body. A diversion device is fixedly connected to the upper middle part of the furnace body via a connecting bracket. The diversion device includes a funnel-shaped guide plate with several guide grooves on its surface. The tip of the guide plate faces upward and is fixedly connected to a storage tank. This easy-to-clean rotary kiln for aluminum ash slag treatment, by setting a diversion device within the furnace body, with a storage tank fixedly installed at the top of the diversion device, and a crushing device rotatably installed inside the storage tank, allows for the preliminary crushing of the aluminum ash slag added to the storage tank by the crushing device. The crushed aluminum ash slag is discharged through the diversion holes, while stones and other impurities, being harder and more difficult to crush, remain in the storage tank. This facilitates convenient preliminary crushing and impurity filtration of the aluminum ash slag.

The invention discloses a repositioning method, electronic equipment and a storage medium, and the method comprises the steps: responding to a target object to trigger repositioning, and obtaining a local panoramic image and a local point cloud corresponding to the current position of the target object; matching the local panoramic image with the historical image set to obtain a target local image and a target historical key frame image which are matched with each other; obtaining a relative pose relationship between the two images, and determining a target ray corresponding to global positioning information of the target historical key frame image according to the relative pose relationship; mapping the target ray to a preset grid map by using the direction information and the initial position of the target ray, and obtaining a target ray range from the grid map; and determining relocation information of the target object by using the target ray range and the local point cloud. According to the method and the device, the local range of the target object can be effectively reduced, the calculation amount and the storage amount are reduced, and the repositioning efficiency and the repositioning accuracy can be effectively improved.

The application provides an insulated gate bipolar transistor and a manufacturing method thereof. The insulated gate bipolar transistor comprises a substrate, a collector region located on one side of the substrate, at least one doped region located on the side of the substrate away from the collector region, each doped region being in contact with the substrate, and a plurality of doped regions being arranged at intervals, a drift region located on the side of the doped region away from the collector region, the drift region having a third surface away from the doped region, the doping concentration of the doped region being higher than that of the drift region, and at least one super junction penetrating into the drift region along the third surface, and part of the drift region being located between the doped region and the super junction, wherein the drift region and the doped region are of a first doping type, and the super junction and the collector region are of a second doping type. By arranging the doped region below the super junction, the current tailing phenomenon in the transistor off process is improved, the off energy loss of the transistor is effectively reduced, and the reliability of the device is greatly improved.

The application relates to the technical field of fine chemical production, and particularly discloses a crystallization process of short-rod-shaped ivermectin, which comprises the following steps: dissolving ivermectin crude product in a crystallization solvent, heating to 50-55 DEG C, adding a crystallization agent, uniformly mixing, then cooling to 35-40 DEG C at a rate of 0.1-0.3 DEG C / min, adding ivermectin crystal seeds, continuously cooling to 5-15 DEG C, and incubating and crystallizing to obtain ivermectin products. The crystallization process of ivermectin provided by the application realizes effective control of the particle size and crystal habit of ivermectin products in the crystallization process by adopting a combination strategy of selecting a specific crystallization solvent, adding a crystallization agent and crystal seeds at specific stages, controlling the cooling rate and the incubation time, obtaining short-rod-shaped ivermectin products with uniform particle size distribution, and the products have good fluidity, are convenient for subsequent preparation application, do not need repeated crystallization for multiple times, effectively reduce the cost of the crystallization process, and have extremely high practical application value.

The present application relates to the technical field of satellite attitude control, and particularly relates to a maximum angular momentum determination method of a wheel system with non-zero initial angular momentum. The maximum angular momentum envelope surface of the momentum wheel combination can be obtained through analytical calculation, which can effectively improve the angular momentum output capacity of the momentum wheel combination, thereby improving the rapid maneuvering capability of the whole satellite and the momentum wheel anti-saturation capability, and there is no numerical iterative search process, compared with the search method, the calculation efficiency is high, the storage amount is small, and the on-board calculation is easy to realize; in addition, the obtained maximum angular momentum envelope surface has a clear boundary, and the momentum wheel output angular momentum with the maximum envelope characteristic can be accurately obtained according to the envelope surface, compared with the pseudo-inverse method, the angular momentum output capacity of the wheel system can be more fully utilized.

The present application belongs to the technical field of computer-aided disease diagnosis and treatment, and discloses a medical diagnosis method and device based on cross-modal semantic hash retrieval, comprising: using an artificial neural network to hash encode category annotation information to form a semantic similarity preserving classifier; using the semantic similarity preserving classifier to guide the training process of multiple modal artificial neural network encoders; using the trained encoder to hash encode different modal medical data; and completing medical diagnosis through cross-modal semantic hash retrieval. The present application has the following advantages in medical diagnosis: low storage and computing resource consumption; good semantic representation ability, i.e. the hash encoding of samples can simultaneously represent the inter-class semantic relationship of samples and maintain intra-class mutual aggregation; and the ability to simultaneously process single-modal medical data-based and multi-modal medical data-based medical diagnosis tasks.

This invention discloses a multi-sensor monitoring system and method based on the Internet of Things (IoT), belonging to the field of multi-sensor monitoring technology. It includes: a data acquisition module for collecting patient physiological data and automatically adjusting the sampling strategy according to strategy adjustment instructions; an IoT gateway for receiving and transmitting physiological data and sampling strategy adjustment instructions; a data processing module that, when monitoring a patient post-surgery, sends an abnormal sampling strategy instruction to the IoT gateway, preprocesses the received physiological data, and extracts respiratory, status, and sound features from the preprocessed dataset; and a data visualization module for visualizing monitoring reports. This invention, by integrating multiple physiological features such as respiration, movement, and sound, and comprehensively utilizing the complementarity of different information sources, can more comprehensively and accurately assess physiological status compared to a single data source, reducing the risk of misjudgment.

This invention discloses a speaker recognition method, system, storage medium, and device based on ordinary pronunciation. The method includes: acquiring real-time audio data and extracting spectral features based on the real-time audio data to obtain spectral features corresponding to the real-time audio data; inputting the spectral features corresponding to the real-time audio data into a trained UNET network to generate a spectral mask corresponding to the real-time audio data, and detecting whether the real-time audio data is an ordinary pronunciation based on the spectral mask; if the real-time audio data is an ordinary pronunciation, fusing the spectral mask and spectral features to obtain an enhanced spectrum corresponding to the real-time audio data; inputting the enhanced spectrum corresponding to the real-time audio data into a trained speaker embedding layer network to obtain a real-time speaker embedding layer corresponding to the real-time audio data; and comparing the real-time speaker embedding layer with the registered speaker embedding layer to identify the speaker corresponding to the real-time audio data.

Hydrogen is produced by electrolysis of water using electricity generated from a renewable energy source such as wind and / or solar radiation, compressed in a multistage compression system and consumed in at least one downstream process. Supply of hydrogen to the downstream process(es) fluctuates with demand and / or the availability of the renewable energy source. In order to accommodate such fluctuations, excess hydrogen is stored during periods when production of hydrogen exceeds that required by the downstream process(es) so that, during periods when demand exceeds production, hydrogen is removed from storage and, after suitable pressure reduction, fed to the downstream process(es) via a stage of the multistage compression system.

The application provides a target tracking method, an electronic device, a storage medium and a program product, and relates to the technical field of target tracking. The method comprises the following steps: acquiring a video frame sequence, at least part of images in the video frame sequence comprising a target to be tracked; performing feature extraction on a current frame image by using a search network to obtain search features of the current frame image, the search features representing a position of the target to be tracked in the current frame image, and the search network being a convolutional neural network; performing convolution on the search features based on current template features corresponding to the current frame image to obtain a feature response map, the current template features representing a predicted target position of the target to be tracked in the current frame image, and the feature extraction network used for extracting the current template features and the search network being different neural networks; and inputting the feature response map into a regression network to obtain a tracking result, the tracking result comprising position information of the target to be tracked in the current frame image. The application can realize long-term and stable tracking of a target.

The invention discloses an environment-friendly long-acting antifouling paint and a preparation method thereof, and belongs to the technical field of paint materials and antifouling. The environment-friendly long-acting antifouling paint comprises the following components in parts by weight: 30-50 parts of a component A, 25-45 parts of a component B, 8-25 parts of a functional body, 1-5 parts of color paste and 0.3-3 parts of an auxiliary agent, the component A is an aliphatic isocyanate prepolymer which is prepared from aliphatic isocyanate and castor oil through a reaction, and the specific preparation raw materials comprise the following components in parts by weight: 20-40 parts of aliphatic isocyanate and 10-20 parts of castor oil; the component B is polyaspartic acid ester, and the molecular weight of the polyaspartic acid ester is 800-1500 g / mol; the castor oil has good reaction activity with aliphatic isocyanate, can significantly improve the flexibility of a prepolymer (polyurea precursor) and the cohesiveness with a base material, and can optimize the compatibility of the polyurea precursor with polyaspartic acid ester with the molecular weight of 800-1500 g / mol, thereby improving the mechanical stability and weather resistance of the whole polyurea paint coating. The technical problem that an existing coating material cannot give consideration to synergistic improvement of environmental protection property and mechanical property is solved.

The utility model relates to a lamp tube clamping type warmer, including the shell, is provided with first heating area and second heating area on the shell, and first heating area and second heating area are communicated in the shell inside, first heating area and second heating area have different radiation direction, the reflector board is located in the inside of first heating area, the lamp tube is located in the inside of first heating area, the shell inside is provided with the mounting plate who penetrates first heating area and second heating area, the outside of mounting plate is equipped with the card and carries out the constraint to the lamp tube in axial direction, the utility model has the advantages of: through the design that the mounting plate is radially restrained to the lamp tube, the card is axially restrained, the installation stability of the lamp tube and mounting plate is guaranteed, simultaneously, the card and mounting plate are all simple sheet body structure, and production assembly flow is simple, and production cost is reduced, and the design of limiting buckle and limiting male prevents the card from falling off automatically, and the connection stability of card and lamp tube, mounting plate is ensured.

The application discloses a kind of dynamic electronic fence generation methods for car, this method first gathers vehicle information after denoising, excavates risk area and permanent site, generates initial risk area model with boundary coordinates and risk level;Again, administrative division, road vector data are fused, and three-dimensional hierarchical fence structure is constructed, and fence boundary is optimized by Douglas-Pork algorithm and cubic B-spline function;Then according to the real-time driving state of vehicle, the fence radius is dynamically adjusted by linear inflation algorithm, and the alarm sensitivity is controlled by classification, to generate dynamic fence configuration;Finally, based on state machine model monitoring vehicle positioning, combined with priority arbitration, hysteresis comparison mechanism handles fence switching and boundary jitter, filters redundant alarm through time sliding window and behavior intention analysis, generates warning report with context.The application realizes the dynamicization of electronic fence, multi-level management and control, improves the accuracy and adaptability of vehicle risk control monitoring, and reduces the false alarm rate.

This invention relates to the field of emotional robots, specifically disclosing a voice emotion recognition system for an emotional companion robot. The system includes a voice input port embedded within the robot, a large-scale model processing system, and an emotion recognition output port. The voice input port collects voice data, which is then processed by the large-scale model processing system and output through the emotion recognition output port. The large-scale model processing system comprises a voice preprocessing module, a feature extraction module, a feature fusion module, an emotion classification module, and a result feedback module. This system optimizes the voice preprocessing flow, improves anti-interference capabilities, extracts seven types of multi-dimensional features, and comprehensively characterizes emotional information. It designs a 1D CNN network with "3 convolutional layers + 3 fully connected layers" to enhance global feature integration capabilities. It employs a triple data augmentation strategy and an optimized training strategy to improve model generalization ability and training effect. A result feedback module is added to optimize the recognition results in real time.