2053 results about "Data messages" patented technology

Apparatuses, systems, and methods for single-pass access of ECC information, metadata information, or combinations thereof. The memory array includes a number of column planes and an extra column plane. A memory device may be set in an ×4 single-pass operational mode. In this mode, the memory may store data in a selected ones of the column planes, and metadata may be stored in the extra column plane. An error correction code circuit (ECC) may store parity bits associated with the data and metadata in non-selected ones of the column planes. In this manner, the data, metadata, and parity may be accessed as part of a single access of the memory array.

The invention discloses a resource allocation method and system for 5G communication in an underground coal mine, and relates to the technical field of communication information processing, and the method comprises the steps: obtaining data information of an underground coal mine roadway, building a digital twin communication model through combining a synchronous positioning and map building algorithm and a wireless fingerprint matching algorithm, generating a channel profile map according to real-time data, and transmitting the channel profile map to a server; extracting channel data of each space node; constructing a computing resource pool for the 5G base station and the edge computing node, and packaging different service types into a plurality of network slice containers; according to the channel data, carrying out initial allocation on each container through a resource composer, and carrying out dynamic task migration among different MEC nodes to obtain a resource allocation state; dividing scheduling time according to a channel profile and a resource allocation state, and dynamically adjusting a duration proportion and bandwidth occupation of each window according to a task migration state; according to the invention, through digital twinning and dynamic scheduling, the problems of 5G communication coverage and interference in the underground coal mine are solved.

The invention discloses a pavement throwing detection method and device based on deep learning, electronic equipment and a program product. The method is realized through a trained detection model, the model adopts an LMSADet detection head, a multi-scale feature extraction and space attention mechanism is introduced into a task branch, and multi-scale modeling is decoupled from a backbone network and a neck network and integrated to the detection head so as to fit a detection task to directly optimize local details and scale differences of a throwing target. In order to suppress background interference and improve the recognition effect of fuzzy boundaries, the neck network is added into an MSHA module so as to efficiently capture the semantic relation between the thrown object and the background and enhance the regional understanding ability. A C3ESP module is introduced into the backbone network, deep features are extracted through stacking depth separable convolution, and information loss is avoided in combination with residual optimization fusion; meanwhile, a PEMA attention mechanism is introduced, the importance of different receptive field features is dynamically adjusted, the model focuses on key features, data information is captured more comprehensively, and therefore the detection performance is remarkably improved.

The invention relates to the technical field of RFID tag signal optimization, and discloses an RFID tag signal optimization method and system based on deep learning. According to the method, feature extraction is carried out on a backscattering signal, core features of a multipath channel are quantized from a frequency domain and a time domain respectively, numerical representation of a channel state is further obtained, then obtained data information is used as input of a deep learning network, training and forward calculation are carried out, original emission parameters are adjusted, and a multi-path channel is obtained. Therefore, the conversion from blind extensive control to precise control of the transmitting end is realized, so that the problem of mismatching of parameter control and channel state caused by information splitting of the transmitting end and the receiving end in the prior art is solved; according to the signal optimization method for realizing joint adjustment of transmitting and receiving parameters through an end-to-end deep learning architecture, the optimization effect of an RFID tag signal in a complex environment is remarkably improved.

The invention provides an SQL statement generation method and system based on execution of feedback iterative correction, and relates to the technical field of large language models.The method comprises the steps that a query request of a user is received, and metadata information of a target database is obtained; generating a current SQL statement based on the query request and the metadata information; pre-executing the current SQL statement in a database sandbox environment; obtaining a pre-execution result, directly outputting the pre-execution result if the pre-execution result succeeds, and performing iterative loop if the pre-execution result fails; and analyzing error information in the pre-execution result, and determining an error type. According to the method, the illusion problem of a large language model is fundamentally solved, and the semantic correctness of SQL generation is ensured. And meanwhile, the iterative correction process replaces low-efficiency manual cue word adjustment, so that the use experience and the problem solving efficiency can be remarkably improved. In addition, the whole pre-execution process is completed in a sandbox environment, so that the influence of potential misoperation on production data is effectively isolated, and the safety of the system is enhanced.

The invention belongs to the technical field of communication, and particularly relates to an NFC (Near Field Communication) encrypted IMS (IP Multimedia Subsystem) server security data exchange method, which comprises the following steps of: in response to a near field communication connection event, acquiring an original service data message of service equipment to be opened and physical environment data monitored when the event occurs, forming a seed data set, executing Hash operation to generate an initial data fingerprint, and sending the initial data fingerprint to a server; and generating a symmetric session key through a key derivation algorithm by combining a device identifier in the original service data message, so as to encrypt the original service data message, packaging an encrypted data packet and the initial data fingerprint into a transmission data packet, sending the transmission data packet to an IMS server, reconstructing the session key by the server based on expected service parameters stored locally, and sending the session key to the IMS server. According to the method, decryption verification of the encrypted data packet is carried out, and service opening is executed after the verification is passed, so that deep binding of an encryption process and data integrity verification is realized, and the security of data exchange and the system processing efficiency are improved.

Apparatuses, systems, and methods for single-pass access of ECC information, metadata information, or combinations thereof. The memory array includes a number of column planes and an extra column plane. A memory device may be set in an ×4 single-pass operational mode. In this mode, the memory may store data in a selected ones of the column planes, and metadata may be stored in the extra column plane. An error correction code circuit (ECC) may store parity bits associated with the data and metadata in non-selected ones of the column planes. In this manner, the data, metadata, and parity may be accessed as part of a single access of the memory array.

The invention relates to the technical field of data information retrieval, and discloses an efficient batch privacy information retrieval method and system based on OCD and GPU optimizing.The efficient batch privacy information retrieval method comprises the steps that firstly, a server is initialized, a database is subjected to bucket division through a PBC encoding algorithm based on the client query number, the database subjected to bucket division is obtained, and when a user conducts information retrieval, the user can retrieve privacy information in a batch mode; the method comprises the following steps of: finding a sub-bucket position of a retrieval request in a server at a client by using a PBC scheduling algorithm, carrying out homomorphic encryption on the retrieval request in each sub-bucket, compressing all the retrieval requests by using an OCD to obtain a retrieval ciphertext, sending the retrieval ciphertext to the server, and sending the retrieval ciphertext to the server according to the retrieval ciphertext provided by the client. The retrieval result in the ciphertext form is obtained and returned to the client side, the client side decrypts the retrieval result in the ciphertext form, and the required retrieval result in the plaintext form is obtained. According to the method, the GPU is used for parallel processing, computing resources in a real scene can be fully utilized, and the computing efficiency of privacy information retrieval is remarkably improved.

The invention relates to the technical field of data sharing and access control, in particular to a block chain and reputation mechanism-based education data adaptive access control method, which comprises the following steps of: firstly, constructing a historical interaction-based credible reputation mechanism: setting default trust and reputation values for an initial visitor by an attribute mechanism; calculating an initial reputation value by combining data of other fields acquired by an oracle machine, and binding public keys and reputation information of participants, a block chain storage address and a data abstract; a data owner encrypts data by using a ciphertext policy attribute-based encryption technology, formulates a policy containing an access matrix, trust and a reputation threshold in combination with a static attribute and a reputation mechanism, and binds own public key and data information to a key list; when a visitor requests, risks are quantified, attributes and reputation are verified based on related intelligent contracts, and tokens are generated if the standards are reached, so that safe and credible sharing and dynamic control of education data are realized, and the safety and flexibility are improved.

The invention discloses a block chain technology-based review data information security tamper-proofing method, and relates to the technical field of information security, the tamper-proofing method comprises the following steps: a data encryption storage step, a data evidence storage step, a trusted computing step and a data verification step, when a computing request is received, the trusted computing step is executed, and the trusted computing step is executed; whether the identity of a requester conforms to the access control strategy is verified through the smart contract, after verification is passed, the smart contract generates a calculation task event, the oracle monitors and captures the event, then a calculation task is transmitted to the trusted execution environment, ciphertext data is obtained in the trusted execution environment and decrypted, and the calculation task is sent to the target server. The method has the advantages that the balance of data privacy protection and integrity verification is realized through a hierarchical architecture combining on-chain evidence storage and off-chain encrypted storage, sensitive review data is stored in an off-chain database in an encrypted form, the security of the review data is improved, the security of the review data is improved, and the security of the review data is improved. Only data fingerprints are recorded on the block chain, data privacy is protected, and data integrity can be verified through the block chain.

The invention belongs to the technical field of artificial intelligence engineering, and particularly discloses a model training and deploying method and system based on Jenkins and version control, a terminal and a medium, and the method comprises the steps that a submission event of a GitLab code warehouse is monitored through Jenkins, difference data information including a training script, a data set version and model configuration is extracted in combination with DVC metadata, and the submission event of the GitLab code warehouse is obtained; and a training task is dynamically generated, and computing resources are automatically allocated to execute a training process. Through the process, full-process automation and closed-loop management of model training, verification, deployment and monitoring are achieved, development efficiency, deployment safety and model traceability are improved, and the method is suitable for intelligent model development scenes with high-frequency iteration and sensitive performance.

This disclosure is generally directed to wireless communication systems and methods and relates particularly to a mechanism for implementing an artificial intelligence framework for adaptively configure the over-the-air communication interfaces of the wireless communication systems. AI network configuration functions may be provided as services for AI-assisted network configuration (AI configuration services, or AICS). Such AICS may be requested and configured via various messaging and signaling mechanisms. The AI model life cycle management including training, delivery, activation, inference, deactivation, switching, performance evaluation, and the like may be configured, triggered, and otherwise provisioned via control and data messages and signaling communicated between the various network elements in the wireless communication system.

Examples relate to methods and systems for selective communication with electronic control units (ECUs) of a vehicle. A vehicle scan tool can provide user-selectable controls that correspond to predetermined group of ECUs representing subsets of all of the ECUs located in a vehicle. In response to receiving a selection of a particular user-selectable control, the scan tool transmits one or more first vehicle data messages with a diagnostic trouble code request to the predetermined group of ECUs associated with the selected option. The diagnostic trouble code request can include a request to clear one or more diagnostic trouble codes in the predetermined group of ECUs or a request to respond with a status of one or more diagnostic trouble codes being set in the predetermined group of ECUs. The scan tool can communicate with multiple subsets of ECUs when the user selects multiple user-selectable controls.

Embodiments of the present application provide an operating parameter recommendation method and apparatus, used for in a big data processing scenario, recommending operating parameters for a computing device on the basis of the resource consumption under different operating parameters, without depending on historical data. The method comprises: first, on the basis of information obtained during the processing of historical tasks in a big data system, establishing a first relationship among the corresponding data information, parameters of a computing device processing the tasks, and time required to process the tasks, and a second relationship among the data information, the parameters, and resources of the computing device consumed for processing the tasks; inputting data information of a task to be processed, and the first relationship and the second relationship to a genetic algorithm, and outputting multiple sets of time values and resource values, i.e., modeling the process of the computing device executing data processing tasks, so as to fit the relationship between the time and resource consumption of the computing device and the operating parameters of the computing device; and determining operating parameters on the basis of actual available resources of the computing device or resource consumption that a user desires.

The invention provides a method of an inter-core communication mode of a multi-core processor, which comprises the following steps of: S1, determining a processor module partition, performing inter-partition communication initialization, and configuring a corresponding virtual partition, a virtual port and a corresponding driving program; s2, calling an interface program for communication between corresponding partitions in each partition application needing communication; s3, providing a corresponding communication service by the partition application; and S4, when data messages are required to be continuously received in sequence, calling an interface for creating the queue ports, sending messages to a source port in the queue ports through the interface for sending the messages in the partition application, calling the interface in the partition application in the partition needing to receive the messages, and receiving the messages of a destination queue port in sequence. And finally, communication monitoring and maintenance are performed, ID and state information of queues and sampling ports are searched regularly or as required, communication conditions are judged according to results, and if the queues are jammed or no new messages exist in the sampling ports, strategies are adjusted in time, faults are eliminated in time, and stable and efficient communication is ensured.

The invention relates to an electric power pipe network intervention generation method of a diffusion model based on auto-reflection learning, belongs to the technical field of electric power pipe network space-time prediction, and solves the problem that modeling is insufficient on the influence of dynamic external environment factors such as weather change and load disturbance in the prior art. The method comprises the following steps of: S1, acquiring initial data information of the power pipe network, and obtaining a processed space-time observation sequence set, wherein the influence of dynamic external environments such as weather, human traffic, holidays and the like on the power pipe network and the power consumption is not considered; s2, performing causal mode decomposition by using a Koopman operator to obtain a dynamic environment component; s3, establishing a learnable denoising network; s4, establishing an environment network modulated by the dynamic environment component based on the dynamic environment component and a learnable denoising network; s5, establishing an auto-reflection learning mechanism model and training the auto-reflection learning mechanism model; and S6, processing the sampled data of the power pipe network by using the trained auto-reflection learning mechanism model to obtain an intervention generation result.

The invention relates to a computing power resource scheduling method and device. The method comprises the steps of obtaining task data information corresponding to a calculation task, determining a transmission idle time period and a calculation idle time period according to the occupation condition of calculation power resources in a future time period when a priority identifier in the task data information is the current highest priority, and calculating the calculation task according to the total data amount. Determining at least one target transmission time period from the transmission idle time period, determining at least one target calculation time period from the calculation idle time period, allocating corresponding calculation power resources to the calculation task according to the target transmission time period and the target calculation time period, and recording the execution condition of the calculation task; by adopting the method, the problem of cooperative scheduling of the transmission resources and the computing resources during computing power resource scheduling can be effectively solved, and the utilization rate of the computing power resources is remarkably improved.

Methods, systems, and devices for wireless communications are described. Some wireless communications systems may support power control for energy providing devices and energy harvesting devices. For example, a wireless device may receive a first control signal indicating a set of energy transfer power control schemes, for an energy providing wireless device, or a set of data transfer power control schemes, for an energy providing wireless device. Additionally, the wireless device may receive a second control message activating a first energy transfer power control scheme or a first data transmission power control scheme, respectively. The wireless device may communicate, to one or more additional wireless device, a scheduling message scheduling transmission of an energy transfer signal or a data message, respectively, and may transmit the energy transfer signal or the data message in accordance with the first energy transfer power control scheme or the first data transmission power control scheme.

Methods and apparatus are described for enhanced node communication within a wireless node network having nodes and a server. A first subset of nodes transmits first data messages to the server without using an intermediary device where the first data messages include sensed data generated by the nodes of the first subset of the plurality of nodes about or around the nodes of the first subset of the plurality of nodes. A second subset of the plurality of nodes receives external data from the other of the nodes. The second subset of the plurality of nodes are intermediary devices that transmit the received external data to the server, wherein the received external data from the other of the nodes comprises sensed data about or around the other of the nodes.

The invention provides a water conservancy data informatization management system and method. The method comprises the following steps: constructing an object association map of a water conservancy data entity object and business logic based on basic object data, mapping relation data and business logic data in water conservancy data; performing cryptographic hash operation on nodes and connecting lines in the object association map to obtain a data consanguinity fingerprint with uniqueness and tamper-proof characteristics, and storing the data consanguinity fingerprint and an authority strategy matrix for accessing the water conservancy data into an intelligent contract to obtain an authority control contract of the water conservancy data; capturing a data access request of an access user, and determining a data access permission of the access session according to the permission control contract and the data access request; and performing business scene-oriented controlled visual sharing on the water conservancy data extracted from the object association map based on the data access permission. By adopting the scheme of the invention, a water conservancy data security sharing system considering data dynamic adaptation, multi-attribute permission constraint and full-link credible tracing can be constructed.

The invention discloses a power distribution network short-circuit parameter real-time monitoring method, system and equipment based on edge calculation and a medium, and belongs to the technical field of power system monitoring and protection, and the method comprises the steps: collecting data information in real time at each monitoring node of a power distribution network, generating a state vector reflecting a node operation state, and inputting the state vector to an edge calculation unit, processing through an internal first calculation model to obtain a power grid fault evaluation result of a corresponding node, and compressing and uploading the power grid fault evaluation result to a cloud; based on the uploaded data and the system operation state, a system performance evaluation result is generated in real time, and an adaptive optimization algorithm is used for dynamically adjusting internal model parameters of the edge calculation unit. According to the method, the composite algorithm model fusing feature extraction and parameter calculation is deployed at the edge node, the problems that a traditional centralized processing mode is large in data transmission delay and central node calculation pressure is concentrated are solved, and the technical effect of reducing bandwidth occupation of a backbone communication network is achieved.

The invention relates to the technical field of wireless communication, and discloses an interface protocol switching method and device, equipment, a storage medium and a product, and the method comprises the steps: obtaining state features between a transmitting end and a receiving end through a sensing layer, and collecting data information of a corresponding type according to the state features, the state features including a service feature, a network state and a server state; inputting data information into the intelligent decision layer, determining a switched transport layer protocol stack, and transmitting the transport layer protocol stack to a protocol execution layer; and switching the sending end and the receiving end to a transport layer protocol stack based on the protocol execution layer to perform data transmission. According to the application, the service features, the network state and the server state are dynamically perceived and extracted through the intelligent protocol adaptation system, the protocol stack of the optimal transmission layer is dynamically decided according to the extracted data, protocol requirements under different interaction scenes are adapted, and the flexibility and accuracy of data transmission are guaranteed.

This application provides a communication method and apparatus. The method includes: acquiring multi-domain data information, which includes first data information and second data information. The first data information is data information related to user service experience, and the second data information is data information related to wireless key performance indicators of user services. Based on the multi-domain data information, a digital twin is determined. The digital twin includes entity objects and corresponding attribute information. The entity objects include user entity objects, network function entities, grid entity objects, and service entity objects. The attribute information corresponding to the entity objects includes attribute information of the user entity objects, attribute information of the network function entities, attribute information of the grid entity objects, and attribute information of the service entity objects. The digital twin is used for network optimization. Using this application, a digital twin can be constructed and used for network optimization, thereby improving the service experience.

The invention discloses a shallow reinforcement mesh echo suppression method and system based on deep learning, and the method comprises the steps: employing a ground penetrating radar to detect a shallow reinforcement mesh shielding scene, obtaining corresponding data information, and processing the data information to obtain a training data set; based on a U-net network structure, combining a convolution unit, a pooling unit, an attention mechanism, interpolation operation and a jump connection mechanism, constructing a shallow reinforcement mesh echo suppression initial model, and training to obtain a shallow reinforcement mesh echo suppression model; and adopting the obtained shallow reinforcing mesh echo suppression model to perform shallow reinforcing mesh echo suppression in the actual ground penetrating radar detection process. According to the method, echo suppression of the shallow reinforcing mesh based on deep learning is realized, the reliability is higher, and the accuracy is better.

A wireless device receives, from a base station, a system information block (SIB) indicating time information for when a cell, provided via non-terrestrial network, stops serving an area. The wireless device receives, from a location management function (LMF), a provide assistance data message, for a multi-round transmission time (RTT) positioning, indicating at least one downlink positioning reference signal (DL PRS) resource. The wireless device starts a measurement period for measuring user-equipment (UE) reception-transmission (Rx−Tx) time difference measurements. The wireless device initiates, based on the time information indicated by the SIB, a satellite switch, wherein the satellite switch is to switch satellites without changing a physical cell identifier (PCI). In response to the satellite switch occurring during the measurement period, the wireless device suspends, during an interruption time for the satellite switch, measuring the at least one DL PRS resource.

Methods, systems, and devices for wireless communications are described. Various aspects relate generally to signaling- or configuration-based mechanisms according to which user equipments (UEs) may prioritize between participating in communication of a sidelink reference signal or participating in communication of a sidelink data message in scenarios in which a candidate sidelink reference signal transmission occasion at least partially overlaps in time with the sidelink data message. Some aspects more specifically relate to prioritization techniques or transmission modes according to which a UE may select or otherwise ascertain a priority of a sidelink reference signal transmission or reception based on how recently a previous sidelink reference signal transmission or reception occurred. Further, some aspects relate to how a UE may transmit signaling in accordance with a decision at the UE to prioritize one of a sidelink reference signal or a sidelink data message.

The invention discloses a heart sound, electrocardio and echocardiogram multi-modal data phase synchronization method, which belongs to the technical field of medical image processing, and comprises the following steps: A1, obtaining an original echocardiogram video and independently recorded heart sound audio data information; a2, preprocessing the acquired data and performing sample automatic construction; a3, a double-path neural network architecture is constructed, electrocardiogram waveform extraction is carried out, and a digital electrocardiogram signal sequence is obtained; a4, periodic feature points of the heart sound and the electrocardio are recognized based on the digital electrocardio signals; and A5, aligning the asynchronous data based on linear phase resampling. According to the method, the video frames, the electric signals and the heart sound signals under different sampling rates are forcibly mapped into the unified phase coordinate system through a linear interpolation algorithm, absolute synchronization of the video frames, the electric signals and the heart sound signals in cardiac pulsation physiological logic is finally achieved, and the influence of individual heart rate differences on data alignment is eliminated.

The invention discloses a data loading device and electronic equipment. The data loading device comprises a crossbar switch circuit and N storage units in a storage part, wherein N is a positive integer greater than 1; the storage component is configured to store data; the crossbar switch circuit is configured to load the data in the storage component to the corresponding processing core for calculation or processing; the crossbar switch circuit comprises N demultiplexers and N multiplexers; wherein the N storage units are configured to send request data to the multiplexers coupled with the N storage units in sequence according to the same preset return sequence; each demultiplexer is also provided with N first-in first-out cache modules in one-to-one correspondence with the N processing cores, and each first-in first-out cache module is configured to cache data information of each data packet sent by a storage unit coupled with the demultiplexer according to a receiving sequence. The data loading device can effectively relieve the arbitration conflict that a plurality of storage units return to the same processing core at the same moment, and the data transmission performance is effectively improved.

Techniques are provided for filtering object detection information provided via V2X communication links. An example method for partially filtering a sensor data sharing message includes receiving the sensor data sharing message from a vehicle, decoding a first portion of the sensor data sharing message to determine an area of interest associated with the vehicle, determine a relative position of the area of interest, and decoding or discarding a second portion of the sensor data sharing message based on the relative position of the area of interest.

In communication with components of a cloud platform, namely a software-defined network constructed to overlay at least one public cloud network, a controller features a virtual processor and a data store. The data store includes network address translation (NAT) processing logic configured to determine whether a control plane message from tenant resources is associated with a network address overlapping condition, which represents a first network address included in the control plane message overlaps a network address range relied upon by either (a) at least one of the components of the cloud platform or (b) a component associated with other tenant resources. The NAT processing logic is further configured to alter routing data stores that maintain routing information for each of the components of the cloud platform to substitute the first network address with a first virtual network address for subsequent data message routing.