658results about How to "Reduce storage costs" patented technology

The invention discloses a live-action three-dimensional model construction method, system and device based on a digital city, and the method comprises the steps: obtaining the multi-source sensing data of a city, and carrying out the data preprocessing, and the multi-source sensing data comprises city image data, point cloud data and GIS data; converting the preprocessed multi-source sensing data in different formats into a preset standard format, and performing registration and fusion of the multi-source sensing data to obtain fused multi-source data; performing data optimization on the fused multi-source data, and constructing a city-level three-dimensional real scene model according to the optimized fused multi-source data and a preset three-dimensional space analysis tool; the preset three-dimensional space analysis tool provides space analysis and three-dimensional space visualization functions; according to the invention, efficient and accurate real-scene three-dimensional data of a city is provided, and three-dimensional and visual space information is provided.

The invention provides a time-space dynamic graph construction method and system for an engineering construction project, and relates to the field of railway tunnel engineering management.The method comprises the steps that construction data entities are extracted, and an entity set is generated; taking entities in the entity set as nodes to be added into the graph, and configuring attributes for each node; adding a relation edge for each node according to a logic structure between the construction data; adding a time label and a space label to each node so as to form a data graph; associating each entity in the data atlas with a time chain and a space chain to form a data atlas attached to the time-space chain; combining a node merging strategy and a graph neural network to optimize a graph structure; and dynamically modeling dimensional changes of entities and relationships in time by means of a time sequence diagram neural network. According to the method, the dynamic change graph of the relationship between the construction data entities is constructed, so that the spatial-temporal information and the entity relationship of each process are accurately expressed and efficiently associated, and the retrieval efficiency and the management level are favorably improved.

The invention provides a multi-data fusion method and system based on edge computing. Belongs to the technical field of edge computing. The method comprises the following steps: receiving heterogeneous resource data from different sensors, equipment and sources through an edge task allocation unit; according to the encryption level corresponding to each task in the heterogeneous resource data, dividing each task data into data groups with identifiers according to a preset segmentation strategy; according to the operation condition of the edge task processor, performing distribution calculation on the data set according to a preset distribution strategy; after the distribution is completed, obtaining an identification sequence of the distribution mode; the distributed data set is calculated and processed through the edge task processor, and after data calculation and processing are completed, the result in the data set is sent back to the edge task distribution unit. Through intelligent scheduling of the edge task distribution unit, data from different sensors and equipment can be received and processed in real time, so that the data processing efficiency and response speed are improved.

The invention discloses a safe and rapid storage method and system for image data of an imaging department, and relates to the technical field of medical image data processing. The method comprises the following steps: 1, designing a distributed storage system, and selecting and configuring storage nodes; 2, selecting and updating an encryption algorithm, and implementing file-level and block-level encryption; 3, realizing accurate data deduplication by utilizing a machine learning technology, and selecting a proper compression algorithm; 4, constructing an index system, and establishing a data warehouse and a data lake by using big data analysis and machine learning technologies; 5, establishing an image data backup and recovery mechanism; and 6, constructing a data integrity checking and monitoring system. According to the invention, by adopting the technologies of distributed storage, encryption, data deduplication, compression, big data analysis, machine learning, backup and recovery, data integrity verification, monitoring and early warning and the like, efficient storage and safety protection of image data are realized.

The invention relates to the technical field of data distributed storage, and discloses a distributed storage method and system for clinical test data, and the method comprises the steps: carrying out the ring signature encryption processing of the patient test data of a plurality of data centers, and obtaining a patient anonymization identifier and standardized clinical data; performing two-stage random storage node configuration to obtain an optimal storage node configuration scheme; constructing an LPPMM-DA data aggregation model based on the optimal storage node configuration scheme, and performing fragmentation processing on the patient test data to obtain a plurality of target data fragments; performing dynamic operation envelope analysis and alliance graph game calculation on the multiple target data fragments to obtain a storage resource scheduling scheme; according to the storage resource scheduling scheme and the anonymization identifier, distributed data block storage and access authentication are executed on the multiple target data fragments, data block storage distribution information is generated, a complete data access control system is constructed, and safe and reliable storage of clinical test data is ensured.

The invention relates to the technical field of artificial intelligence, in particular to a model construction method for a GUI agent, a program product and a storage medium, and the model construction method for the GUI agent provided by the invention comprises the following steps: performing pre-training based on a general data set in the GUI field to obtain a base model; a user demonstration operation track is collected online, and a personalized task execution track is obtained; automatically labeling the task execution track to obtain a labeled track; performing task planning training on the base model based on the marked track to obtain a scene planner, and combining the base model and the scene planner to obtain a personalized model; based on the plug-in scene knowledge base, corresponding scene knowledge is retrieved as context supplement during personalized task action planning. The task execution track is automatically labeled, a large model is guided to actively label and understand thinking in human execution operation, the next behavior is further planned, and the adaptive capacity of a GUI intelligent agent to the personalized use environment of a user is greatly improved.

The invention relates to a multi-mode intelligent question and answer reasoning method and device based on knowledge distillation, and belongs to the technical field of intelligent question and answer. Extracting multi-modal features of the user data; a pre-trained intention recognition model conducts reasoning on the multi-modal features, reply content is generated, or corresponding operation is executed; the training method of the pre-trained intention recognition model comprises the following steps: acquiring multi-modal data; preprocessing the multi-modal data to obtain a multi-modal fusion vector; performing fine tuning training on the base large model by using the multi-modal fusion vector to obtain a fine-tuned large model; inputting the multi-modal data into the fine-tuned large model for intention classification, judging whether the classified intention slot position is complete or not, and if the judgment result is that the classified intention slot position is incomplete, supplementing the intention to generate final intention information; and performing knowledge distillation on the fine-tuned large model to obtain the model. The real-time performance and accuracy of intelligent question answering are improved.

The invention discloses a data storage system of a digital country based on cloud computing, which comprises a client, a data transmission module and a cloud computing center, relates to the technical field of data storage, stores hot data on a high-performance hot data storage layer, ensures that frequently accessed data can be quickly responded, improves the system performance, and at the same time, stores the hot data on a high-performance hot data storage layer. The cold data is stored in a low-performance cold data storage layer, the storage cost is reduced, effective balance of performance and cost is achieved, the data is automatically migrated among different storage layers along with change of data access frequency, so that the performance and the cost are balanced, the frequently accessed data is migrated into a cache, the access speed of the data is increased, and the data access efficiency is improved. And establishing a relationship between a time interval and a data type of historical data, predicting data which are possibly accessed in a given time interval, adding the data into the cache, dynamically adjusting the cache, and ensuring the validity of the cache.

The invention discloses a life cycle visual management method based on data, and relates to the technical field of data management. The method comprises the following steps: 1, data acquisition and identification; 2, classifying and dividing data life cycle stages; 3, data state monitoring and updating; 4, recording and associating data operation; step 5, constructing a data life cycle visual framework; step 6, data life cycle decision analysis optimization; 7, performing data archiving and deletion management; according to the invention, fine management of the whole life cycle of the data is realized, and the systematic method not only improves the efficiency of data processing, but also enhances the transparency of data management, so that managers can monitor the data state in real time, quickly respond to the data problem, optimize the data circulation process and improve the overall operation efficiency. Through application of a data visualization technology, complex data information is displayed in a visual and understandable form, and managers are helped to better understand data dynamics.

The invention discloses a block chain-based data storage optimization method. The method comprises the following steps of 1, establishing a storage strategy and a continuous mechanism for optimizing storage; 2, according to a storage strategy, calculating storage cost caused by monitoring real-time change of a storage amount statistical value and storage resource allocation service calculation; 3, continuously optimizing data storage in the whole data life cycle by utilizing the object label and the life cycle strategy; step 4, synchronizing transfer optimization of the data storage layer based on the access frequency of the data storage block; the method is applied to a data storage optimization system based on the block chain, the system comprises a storage strategy mechanism module, a storage cost calculation module and a data storage optimization module, in cloud storage, an intermediate data set is used for carrying out storage layer conversion decision making on data through the change of access frequency, and the cloud storage cost is saved. The method has the characteristics of improving storage performance and reducing storage cost.

The invention relates to the technical field of data management, in particular to a data asset sorting method, which comprises the following steps: preliminarily classifying all data assets in an enterprise, performing quality evaluation on the preliminarily classified data assets, generating a quality evaluation report, and performing data redundancy detection and optimization based on the quality evaluation result. Cleaning redundant data by adopting a deduplication algorithm and an optimization algorithm, carrying out data correlation analysis, generating a data correlation graph through a graph model and a statistical model, and determining the relationship between data sets; and finally, according to a correlation analysis result, integrating the data sets with high correlation into a unified data set by adopting a data fusion algorithm, and reducing a storage space through a data compression technology. According to the method, the accuracy of data classification and management can be improved, the data redundancy is reduced, the data storage and access efficiency is optimized, and the data security and privacy protection are enhanced through security evaluation and protection measures.

The invention discloses a mine digital asset storage management method, which comprises the following steps of: extracting characteristics of mine data, dividing the mine data into hot data, warm data and cold data according to the characteristics, selecting different storage devices for the data, and dynamically adjusting migration of the data among the different storage devices based on access frequency and business requirements; future data storage requirements are predicted through a machine learning algorithm, and storage resources are scheduled; performing full life cycle management on the data, performing business value evaluation on the data, and adjusting storage priority and resource allocation based on the data value; carrying out full-life-cycle encryption on the data, and recording data operation through a block chain technology; energy consumption of the storage equipment is monitored in real time, and storage energy efficiency and carbon footprint management are adjusted. The problems of low storage efficiency, high storage cost and insufficient energy consumption optimization caused by data type diversity, access frequency difference and insufficient storage resource utilization in mine data management can be solved.

The invention relates to the technical field of hierarchical storage, in particular to a photo-electromagnetic storage method and system based on hierarchical management, and the method comprises the following steps: collecting read-write speed, error rate, durability and cost data of optical storage and electromagnetic storage media, carrying out the sorting and grading processing of the data according to the read-write speed and the error rate, and carrying out the sorting and grading processing of the data; and performing score calculation on each storage medium to obtain a medium performance score. According to the method and the device, the data is effectively distributed to the most suitable storage medium by accurately scoring the performance of the storage medium and combining specific requirements of the to-be-stored data, so that the data access speed and efficiency are improved, the total storage cost is reduced, and particularly, when a large amount of data is processed, the data compression level and the encoding format are dynamically adjusted, and the data compression efficiency is improved. The storage efficiency of the data is further optimized, data redundancy is reduced, the overall performance of data storage and access is remarkably improved through optimization measures, and meanwhile long-term safety and integrity of the data are ensured.

The invention relates to the field of technical data acquisition, and particularly discloses a data acquisition method and device for an industrial Internet of Things and a storage medium, and the method comprises the following steps: S1, constructing a dynamic sensor network, and collecting the operation data of industrial equipment in real time through a multi-modal sensor; s2, dynamically adjusting a data acquisition frequency # imgabs2 # based on an environment noise coefficient # imgabs0 # and an equipment health index # imgabs1 #; s3, performing hierarchical compression and encryption on the acquired data, and allocating a compression rate # imgabs4 # and encryption strength # imgabs5 # according to data type importance # imgabs3 #; s4, executing load balancing through an edge computing node, and distributing a computing task to an optimal node; and S5, storing the processed data into a distributed database according to spatial-temporal correlation, and generating a multi-copy disaster recovery index. Through dynamic acquisition, intelligent processing, optimized storage and adaptive strategy adjustment, accurate and efficient data acquisition is realized, data security and processing performance are flexibly guaranteed, storage query efficiency and disaster tolerance capability are improved, and storage resources are utilized to the maximum extent.

The invention relates to the technical field of freight scheduling, in particular to a freight scheduling information management method and system and a storage medium. The method comprises the following steps that uncompleted order collection is carried out on a freight platform to obtain an uncompleted order set, and the uncompleted order set comprises a plurality of uncompleted orders; each uncompleted order at least comprises an order ID, order release time, target cargo attribute data, publisher identity data, a departure place, a destination, an order state identifier, an order transportation task schedule, cargo stacking attributes, predicted delivery time and cargo expected arrival time; and performing order state classification and marking on the uncompleted order set to obtain a classified order set. By optimizing the loading space utilization rate of the vehicle, the unloaded and half-loaded conditions of the vehicle can be reduced, so that the fuel consumption and the transportation cost are reduced.

The invention, which relates to the technical field of digital information transmission, discloses an AI technology-based digital information transmission sharing operation and maintenance platform comprising a data acquisition module, an AI intelligent analysis module, a frequency spectrum dynamic allocation module, a data classification and transmission optimization module, and a storage adaptation module. According to the method, the spectrum resource utilization efficiency and the transmission stability are optimized, the platform can accurately master the spectrum use condition in real time through the AI real-time spectrum sensing and dynamic frequency allocation technology, the platform can quickly identify idle spectrums and dynamically allocate optimal frequencies for different services in the face of a complex and changeable wireless environment, spectrum congestion and interference are avoided, and the service quality of the system is improved. The fluency of bandwidth and time delay sensitive services is guaranteed, and the transmission interruption risk is reduced.

The present invention relates to the technical field of rock and soil reinforcement, and in particular to a method for urease-induced calcium carbonate precipitation and solidification of sandy soil. The present invention crushes plant seeds containing urease to obtain urease-containing powder; mixes the urease-containing powder with sandy soil to obtain mixed sandy soil; injects a binder into the mixed sandy soil to form calcium carbonate to solidify the sandy soil; the binder is an aqueous solution containing urea and calcium ions. The method provided by the present invention can not only solve the problems of difficult extraction and storage of urease, but also increase the thickness of the solidified layer and improve the mechanical properties, and the method is simple and easy to implement, low cost and risk-free.

The invention provides a single-channel speech enhancement method based on an improved convolutional recurrent network, and the method comprises the steps: 1, downloading a data set for model training and testing, carrying out the preprocessing of the speech of the data set through employing a VoiceBank + DEMAND data set, and extracting the amplitude spectrum of a speech signal through short-time Fourier transform (STFT); 2, inputting the amplitude spectrum into an encoder, and extracting high-dimensional features from the amplitude spectrum; step 3, using the Channel-S4D block as a recursion module of the model, inputting a result output by the Channel-S4D block into a decoder, and recovering the result to an original dimension; 4, constructing a joint loss function; and 5, reconstructing and evaluating the enhanced voice signal. According to the invention, the Channel-S4D module constructed based on the diagonalization state space model efficiently processes a voice sequence, captures channel-level voice key information, better models the time dependence relationship of voice signals, and improves the adaptability of the model to a complex noise environment while reducing the parameter quantity and the calculation quantity of the model.

The invention relates to the technical field of logistics, in particular to an intelligent stereoscopic warehouse and an operation method thereof. The method comprises the following steps: carrying out logistics tracking data acquisition on goods to be warehoused to obtain a current logistics tracking data set; according to the current logistics tracking data set, goods to be warehoused are classified, a goods classification list is obtained, and the goods classification list comprises a plurality of site fragile goods lists and a plurality of site non-fragile goods lists; according to the goods classification list, carrying out storage interval distribution on the to-be-warehoused goods to obtain a goods storage interval distribution list; according to the cargo storage interval distribution list, carrying out storage location distribution on the to-be-warehoused cargo to obtain a cargo storage location mapping table; and performing logistics updating on the current logistics tracking data set according to the cargo storage position mapping table to obtain an updated logistics tracking data set. The space utilization rate and the storage efficiency of the intelligent stereoscopic warehouse are improved, and the space pressure of a logistics center is effectively relieved.

The invention relates to the technical field of treatment devices, and discloses a hydraulic engineering safe sludge treatment device which comprises a shell, supporting legs are fixedly connected to the front portion of the shell, and a supporting plate is fixedly connected to the tops of the supporting legs; when sludge treatment is started, the sludge suction pipe is placed in a place with excessive sludge, the sludge suction pipe sucks the sludge into the filter barrel through the water suction pump, and the sludge sucked into the filter barrel can be dehydrated, so that the volume of the sludge is reduced, moisture in the dehydrated sludge is removed, and the volume is obviously reduced; the subsequent storage and transportation cost of the sludge can be effectively reduced, meanwhile, the situation that water filtering holes in the inner wall of the filtering barrel are blocked, so that separated water cannot be discharged is avoided, and substances such as branches and leaves mixed in the sludge can be smashed, so that the sludge and the branches can be fully mixed, and subsequent transportation is facilitated.

The invention discloses a hierarchical quantization and dynamic priority management-based model cache optimization method and device. The method comprises the following steps of: acquiring an importance score of each Token of a word sequence corresponding to a reasoning long text by utilizing a mask language model; constructing a Token importance scoring model, and dividing the cloud platform GPU into a head cache region, a middle cache region and a tail cache region; the service reasoning model stores the key value pairs of the first # imgabs0 # Token in a Token reasoning sequence corresponding to the reasoning long text in a head cache region in an FP16 format, stores the key value pairs of the first # imgabs1 # Token before the current processing Token in a tail cache region in the FP16 format according to an FIFO principle, and stores the key value pairs shifted out of the tail cache region in an intermediate cache region in an FP8 format; and after the intermediate cache region is full, updating the intermediate cache region by using the Token importance scoring model and the importance score. According to the method, the reasoning efficiency of the large language model in long text generation can be improved.

The invention discloses an information processing method and device for zero-knowledge certification and a storage medium, and the method comprises the steps: firstly obtaining a local private key, generating a blinding factor according to the local private key, generating a commitment ciphertext of local sensitive information according to the blinding factor and the local sensitive information, and then transmitting the commitment ciphertext to a certificate issuing party, receiving a verifiable voucher which is generated by the voucher issuer according to the commitment ciphertext and signed and issued by the voucher issuer; when challenge information for the local sensitive information sent by a verification party is received, a certification ciphertext used for representing that the local sensitive information meets the challenge information is generated according to the challenge information, the local sensitive information and a blinding factor, and then the certification ciphertext and a verifiable certificate are sent to the verification party; and the verification party can perform zero-knowledge proof verification on the proof ciphertext according to the verifiable certificate. According to the embodiment of the invention, the additional storage cost of the blinding factor can be reduced. The embodiment of the invention can be applied to various scenes such as zero-knowledge proof based on the block chain.

The invention provides a financial product recommendation method, and relates to the field of artificial intelligence. The method comprises the following steps: inputting user characteristics of a user into a pre-trained asset prediction model; obtaining N types of predicted underlying assets output by the asset prediction model and proportion information of each type of predicted underlying assets; on the basis of the risk assessment level of the user, querying one or more candidate financial products matched with the risk assessment level from a database to form a candidate product set; based on the N types of predicted underlying assets and the proportion information of each type of predicted underlying assets, matching M target financial products from a candidate product set, the candidate product set comprising at least one candidate product and the proportion information of each type of underlying assets of each candidate product; and recommending the M target financial products to the user. The invention further provides a silent customer activation method.

The embodiment of the invention provides a storage space management method and device, a storage medium and electronic equipment, and relates to the field of computers, and the method comprises the steps that to-be-processed object data is acquired; in response to a service request sent by a client, determining a first storage space corresponding to the object data from a storage hard disk of a distributed storage system; when it is detected that the first storage space contains an abnormal storage space, isolating the abnormal storage space, and recording a first space position and first time information of the abnormal storage space; and determining a second storage space required for executing the service request from the storage hard disk, and completing data interaction between the client and the distributed storage system through the second storage space.

The invention discloses a power electronic equipment parameter verification method and device based on a power distribution management system, equipment and a medium. The method comprises the following steps: receiving a data synchronization instruction of a user, obtaining a to-be-synchronized first equipment parameter, and accessing and analyzing the data synchronization instruction to obtain a target power distribution management system of to-be-synchronized data; and then, for each target power distribution management system, calling a corresponding target database, comparing the first equipment parameter with the historical equipment parameter, when the first equipment parameter is determined to be consistent with the historical equipment parameter, marking the first equipment parameter as a redundant parameter, and refusing the first equipment parameter to enter the target database. By implementing the method and the device, redundant parameters can be effectively identified and processed, effective equipment parameters stored in the database are ensured, the stability and the reliability of a power system are improved, and the system fault risk caused by data errors is reduced.

The invention provides a preparation method of a composite soft capsule shell containing plant starch, and belongs to the technical field of soft capsules. The composite soft capsule shell is prepared from the following components in percentage by mass: 15 to 30 percent of gelatin, 5 to 20 percent of modified plant starch, 1 to 15 percent of composite plant gum, 1 to 10 percent of dopamine grafted pulullan, 10 to 30 percent of plasticizer and 25 to 45 percent of solvent; compared with the existing soft capsule skin, the soft capsule skin prepared by the invention has better mechanical strength and toughness, overcomes the problem of disintegration and delayed release caused by a capsule shell crosslinking aging reaction, is beneficial to the preservation of the soft capsule and reduces the storage cost.

The invention relates to the technical field of archive storage and management, and discloses an archive classification management method which comprises the following steps: constructing an alliance chain property block chain network and an I PFS file system; for the received multi-dimensional electronic archive set, performing clustering analysis on the electronic archive set to obtain an archive classification result of the electronic archive set; based on the number of the electronic archives in the archive classification result, the storage nodes are classified to obtain node classification results, and the node classification results are in one-to-one correspondence with the archive classification results; according to a node classification result, uploading and storing the classified electronic archive file through the corresponding storage node, generating a hash ID table related to the storage node, and classifying the hash ID table; and the block chain network generates the Hash ID table into a block according to the category and a block chain network operation mechanism, and stores the block into the block chain network.

The invention relates to a data acquisition method and device, a medium and a product. The method comprises the following steps: acquiring a first observation parameter of each type of monitoring data of a monitoring device for a preset time monitoring window; wherein the first observation parameter comprises a first window observation value of each type of monitoring data and a first observation fluctuation threshold value of the first window observation value; determining a first prediction parameter of each type of monitoring data for the first time monitoring window; the first prediction parameter at least comprises a prediction value, an upper limit of the prediction value and a lower limit of the prediction value; based on the first observation parameter and the first prediction parameter, determining whether the first time monitoring window satisfies an acquisition condition; and under the condition of determining that the acquisition condition is satisfied, performing data acquisition on the monitoring equipment to obtain a target observation value. According to the method, a large amount of redundant data in the data acquisition process can be avoided, the data storage and calculation cost of hardware is reduced, and the data acquisition efficiency is improved.

The invention discloses an access control method and system for cross-platform video resource sharing, and belongs to the technical field of video sharing. Video platforms are divided into a plurality of groups, each group randomly selects one video platform to be marked as a national standard node, and each national standard node serves as a bridge between a center node and other video platforms and is responsible for seamless cascading and equipment access of video resources of a superior platform and other platforms; the system implements a unified access control strategy, and ensures that a user accesses resources according to authority through authority management; an organization tree configuration function is constructed, a video resource management system is constructed, and sharing and integration of lower-level platform resources are achieved; searching and browsing organization tree information and an equipment list through a resource retrieval function; sharing of organizations and devices is supported, and a superior platform is allowed to retrieve a shared directory and a device list; according to the invention, a safe, efficient and easy-to-manage cross-platform video resource sharing solution is realized.

The invention provides a small-size vehicle detection deep learning model based on multi-scale module feature fusion, which solves the problems of small-size vehicle image detection and the like, and comprises a Backbone network, a Neck layer and a Head network, a C2fDCNv3 module based on the combination of a variable convolution DCNv3 and a double-convolution cross-stage module C2f and an SPPFLSKA module based on the combination of a spatial pyramid pooling layer SPPF and a large separable convolution kernel attention module LSKA are introduced into the Backbone network. A C2fSCConv module based on the combination of a space channel reconstruction convolution SCConv and a double convolution cross-stage module C2f is introduced into the Neck layer; and a multi-scale convolution kernel detection module MSKDeect is introduced into the Head network. The method has the advantages of good small-size image detection effect, cost reduction and the like.