594 results about "Cell Computing" patented technology

The invention discloses a liquid cooling charging module health state prediction system, and relates to the technical field of electrochemical detection, and the system comprises a multi-parameter collection unit which collects the pressure and flow data of a cooling liquid, and is provided with an independent collection node at each branch of a double-gun charging system, and provides basic data for monitoring; the dynamic calibration unit communicates with the acquisition unit, compensates data drift based on a temperature-vibration interference model of machine learning training, executes baseline calibration by using an idle period to update a reference value, and guarantees data accuracy; the leakage detection unit is used for calculating a data change rate after compensation, outputting an early warning according to a preset condition and positioning a leakage branch; and the health state evaluation unit fuses the early warning signal and the historical operation data to generate a prediction result. The problems that tiny leakage detection is difficult and a sensor is prone to interference can be solved, manual inspection is reduced, the maintenance cost is reduced, and the requirement of a high-power charging scene is met.

The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle detection tracking device, method and equipment, which comprises a data sensing unit, a calculation unit, a mechanical and power supply unit, a communication and storage unit and a countering execution unit, and is characterized in that the data sensing unit is used for acquiring image data and servo turntable rotation angle data; the calculation unit is used for deploying a lightweight neural network model and a multi-algorithm fusion process, processing sensor data and realizing unmanned aerial vehicle target detection and tracking logic control; the mechanical and power supply unit is used for providing physical support, servo motion capability and energy supply for the device; the communication and storage unit is used for real-time data transmission and storage and encryption archiving of historical data and image videos; and the countering execution unit is used for implementing signal interference or physical interception on the detected and tracked target. Therefore, the problems of easy target loss, low small target identification precision, poor complex environment adaptability, insufficient countering means and the like of a traditional device are solved.

The invention relates to the technical field of data processing, and discloses a college budget management system fused with a new quality productivity theory, comprising: a state characterization interface collects process characterization data and maps the process characterization data into a discrete innovation state bit vector; the differential efficiency mapping unit responds to the state bit jump to calculate an efficiency marginal increment and generate an injection instruction; the physical bypass monitoring channel collects physical consumption time sequence data, and the entropy analysis closed-loop unit calculates a metabolic entropy representing the resource consumption order degree; the budget dynamic response control unit generates a state locking instruction when the state bit is constant and the metabolic entropy meets the low-entropy convergence condition, the physical working condition entropy is used for correcting the logic state, and the project resource state is maintained by recognizing the low-entropy resource consumption characteristics when no dominant output exists; the problem that discrete evaluation indexes cannot represent blind areas of continuous scientific research activities is solved.

The present application relates to the field of equipment maintenance support, and particularly discloses a multi-stage task equipment selective maintenance decision and task allocation joint optimization method. Step S1: statistics of task type, statistics of the number of each unit continuous execution tasks under the task type and the interval period between tasks; Step S2: providing maintenance measures within the interval period, statistics of the maintenance measures and the corresponding maintenance effect, and calculation of the state probability distribution after executing the maintenance measures; Step S3: calculation of the total maintenance cost within the interval period of all tasks; Step S4: since each stage task contains multiple subtasks, the total task demand of each type unit needs to be calculated according to the state and maintenance of each unit before the task starts; Step S5: allocation of tasks and meeting the demand of each stage task; Step S6: calculation of the task completion probability according to the task demand of each stage. The present application aims to solve the problem of independent optimization of equipment selective maintenance decision and task allocation under the previous multi-stage task.

The invention provides a distributed MIMO clutter echo simulation method based on GIS information, and the method comprises the steps: obtaining the GIS information of a geographic information system, and dividing a surface scatterer irradiated by an MIMO radar into a plurality of basic scattering units based on the GIS information; calculating slope distances, Doppler frequencies, terrain elevation values and land cover types of the plurality of basic scattering units to form a scene model element set; mapping a plurality of basic scattering units to a radar resolution unit by combining a backscattering coefficient empirical model and a resolution adaptive grid mapping method according to the scene model element set; dividing the radar resolution unit into a permanent scattering area and a dynamic scattering area according to GIS information; performing clutter statistical characteristic simulation processing on the permanent scattering region and the dynamic scattering region to obtain a clutter amplitude sequence; and performing echo analysis processing on the clutter amplitude sequence in a time-frequency domain to obtain clutter echo simulation data. And the simulation precision of clutter echo simulation data is integrally improved.

The invention provides a gene module analysis method and device, equipment and a storage medium, and relates to the technical field of space transcriptomics. The method comprises the steps of obtaining space-time group chip expression data, performing linearization processing, and performing sliding window cutting to obtain a plurality of window units arranged according to a space sequence; calculating gene function activeness and constructing a matrix; clustering and grouping are carried out to obtain window groups; performing difference analysis screening on the window groups to obtain a difference expression gene set; and performing gene module analysis to obtain a functional gene module. According to the method, through an integrated processing flow of structure linearization, sliding window cutting, activeness quantification, clustering analysis and module identification, fine extraction and function reconstruction of spatial expression information in the curled tissue are realized under the condition that an additional algorithm or external data is not introduced; and the practicability and research value of the spatial omics data in a complex organization structure are improved.

The invention discloses a cooperative inspection task allocation method and device based on multi-vehicle state perception, and a storage medium. The method comprises the steps that a central cooperation unit calculates risk indexes of all inspection target nodes, and a priority index table is obtained; the central cooperation unit determines a target original parameter; the central cooperation unit constructs a target cost spectrum matrix; applying an operation constraint condition set to the target cost spectrum matrix, and executing constraint solution to obtain an initial scheduling scheme; each autonomous inspection unit constructs a composite return function; each autonomous inspection unit updates a preset strategy value function according to the composite return function to obtain a local strategy parameterization sequence; each autonomous inspection unit sends the local strategy parameterization sequence to a central cooperation unit to obtain a global strategy tuning parameter; and the central cooperation unit distributes the global strategy tuning parameter to each autonomous inspection unit, so that each autonomous inspection unit corrects the local strategy parameterization sequence and the composite return function of the autonomous inspection unit.

To enable appropriate error correction that suits an analysis task, an information processing apparatus (1) includes: an acquisition unit (11) that acquires target data; a calculation unit (12) that calculates, for respective ones of a plurality of errors included in the target data or for respective ones of attributes of the plurality of errors, corresponding degrees of influence that the respective ones of the plurality of errors exert on an evaluation index of a machine learning model; and a determination unit (13) that determines data to be corrected in the target data on the basis of the degrees of influence calculated by the calculation unit (12).

To provide an information processing apparatus capable of improving the efficiency of operation of a movable apparatus, an information processing apparatus comprises: a passing region calculation unit configured to calculate a passing region through which a movable apparatus passes; an object detection unit configured to detect an object around the movable apparatus by a sensor; and an object detection range setting unit configured to set an object detection range in which the object is detected by the object detection unit based on the passing region calculated by the passing region calculation unit.

A system and processes detect, identify a Unexploded Ordnances (UXOs) and / or categorize UXOs in near real-time using Unmanned Aerial Vehicles (UAVs). In accordance with various disclosed embodiments, the equipment includes such UAVs (also referred to herein as “drones,”) that include a plurality of sensors for imaging the terrain of a geographic area to analyze the terrain and detect anomalies and / or changes that may be indicative location of UXOs, for example, soil moving activity performed in association with the burying the UXO. Additionally, the UAVs include processing equipment, e.g., one or more small form factor devices, e.g., Next Unit of Computing (NUC) compute elements or the like, that provide processing power to provide EDGE computing on the data gathered at the UAV.

An information query system includes a receiving unit, a computing unit, and an output unit. The receiving unit is used to receive a query request, and the query request has a query value. The computing unit is used to select a plurality of data strings that match the query value from historical data. The plurality of data strings each have a first feature value and a second feature value. The first feature value is related to the query value. The output unit is used to output at least one second feature value and a proportion of the at least one second feature value.

The invention relates to the technical field of overvoltage monitoring, in particular to a wide-frequency-domain overvoltage online monitoring system and method for electric power high-voltage equipment. Comprising an electric field sensor array, an acquisition unit, a calculation unit and an output unit, the electric field sensor array comprises a plurality of sensors which are radially distributed on the same circumferential plane and have different measuring ranges and sensitivities, and sensors which are axially distributed; the electric field sensor comprises a sensing unit and a fiber bragg grating temperature measuring unit; the fiber bragg grating temperature measuring unit is suitable for measuring the temperature of the sensing unit; the acquisition unit is suitable for synchronously acquiring the emergent light intensity of the sensing unit and the temperature data of the fiber grating temperature measurement unit. The multi-range sensors distributed in the radial direction achieve wide-range and high-sensitivity voltage sensing through differential design, the intrusion direction of overvoltage can be determined through cooperation of the axial sensors and the radial sensors, and the problem that the range and sensitivity of a single electric field sensor are mutually restricted is solved.

The invention relates to the technical field of microelectronics, and discloses a three-dimensional stacked near-memory computing architecture, a chip and a data access method. The memory device comprises at least one computing chip layer and at least one memory chip layer which are stacked along a first direction, a plurality of vertical interconnection channels extending along the first direction; the memory chip layer comprises a plurality of memory banks; the computing chip layer comprises a plurality of computing cluster units; the computing cluster unit comprises at least one storage controller; and the storage controller is connected with at least one of the plurality of storage banks through the vertical interconnection channel and is used for managing data in the correspondingly connected storage banks. The problems that in a three-dimensional stacking computing architecture, storage access delay is high, and the bandwidth expansion capacity is limited are solved.

A system and method for executing a work process using a planning system. A planning system comprises a user interface, a communication unit, a computing unit and a memory unit. The planning system is configured to generate a plan for executing an agricultural work process or at least one sub-process included in the work process and transmitting it to an autonomous agricultural work machine configured for the execution for controlling, regulating and / or parameterizing the autonomous work machine and at least one attachment configured to the work machine. The planning system is configured to retrieve and use data saved in at least one database in order to generate the plan for the operation of the autonomous work machine, which data are working-machine-specific, attachment-specific and field-specific parameters, and ambient and environmental parameters available at the time of the generation of the plan, and to output the plan via the user interface.

The invention relates to the technical field of integrated energy systems, and particularly provides a multi-energy-flow scheduling method and system for a regional integrated energy system, and the method comprises the steps: S1, carrying out the unified modeling of a DC micro-grid, a heat supply network and a natural gas network based on a circuit comparison method, and obtaining a network model of each energy network; s2, constructing a direct-current micro-grid island hierarchical control strategy; and S3, according to the state parameters of the regional integrated energy system, performing dynamic load flow calculation on the direct-current microgrid under the island hierarchical control strategy based on a decomposition load flow method and the network model of each energy network, performing steady-state load flow calculation on the heat supply network and the natural gas network, and generating a scheduling instruction, so that multi-energy-flow coupling response can be accurately captured, and the scheduling efficiency is improved. According to the method, the model inconsistency error is reduced, the unit calculation burden is reduced, the expandability and fault tolerance of the system are improved, and high-precision support is provided for optimal scheduling and long-term planning.

The invention relates to the technical field of water conservancy project automation and industrial control, in particular to a water conservancy equipment collaborative operation system based on an industrial control system, which comprises a programmable input mapping and logic matching unit, a data processing unit and a data processing unit, the system carries out binary bit mode matching on the operation result and the feature data block in the memory; the logical operation and addressing unit is used for calculating control lag time and generating a structured digital control sequence data stack; the sequential control and instruction addressing unit is used for generating a cooperative control instruction set containing sequential logic; the output mapping and checking unit is used for reading real-time feedback, and if deviation exists, an interruption compensation program is triggered to correct an action curve of an executing mechanism; the storage rewriting and loop optimization unit is used for correcting transmission delay parameters of the model and realizing closed-loop optimization; according to the method, the problem of model distortion caused by physical property drift is solved, and stable full-life-cycle operation is ensured.

The invention relates to the technical field of building mechanical and electrical installation, and discloses an intelligent measuring tool for building mechanical and electrical installation engineering and a measuring method thereof. The system comprises a measurement environment preparation unit, a multi-parameter acquisition unit, a spatial topology analysis unit, an error optimization unit and a measurement verification unit. The measurement environment preparation unit obtains initial environment parameters and generates an environment parameter sequence; the multi-parameter acquisition unit synchronously captures multiple types of data, calculates a spatial adaptation value and establishes a measurement feature initial set; the spatial topology analysis unit identifies the topological connection direction and conflict area of the equipment group, and generates a spatial topology deviation data set; an error optimization unit calculates a spatial positioning compensation value and adjusts a coordinate mapping relation of the equipment; and the measurement verification unit compares the deviation values, recollects the deviation values when necessary, and finally generates a measurement topological graph. The tool can realize cooperative processing and accurate measurement of multiple parameters in the building mechanical and electrical installation process, and is suitable for the field of building mechanical and electrical installation.

The invention provides a forestry pest and disease damage real-time monitoring method and system, and relates to the technical field of data processing, and the method comprises the steps: selecting a position A of an early warning node, a node position B with the maximum yield per unit time in a past one hour, and a node position C with the maximum spatial distribution dispersion; forming a monitoring unit according to the position A, the node position B and the node position C of the early warning node; calculating the radius of a circumcircle of the measurement unit, and determining the grid division density based on the radius of the circumcircle; according to the grid division density, performing adaptive grid division on the monitoring unit to obtain a plurality of grid units; generating a space risk adjustment value according to the space distribution characteristics of the grid units; constructing a spatial diffusion model according to the regional and spatial risk adjustment values of the collaborative outbreak phenomenon; obtaining an insect condition risk level according to the spatial diffusion model; and generating a comprehensive insect condition early warning according to the insect condition risk level. According to the method, the time sequence mutation can be dynamically sensed, and the spatial diffusion risk can be accurately evaluated.

A sensor unit is coupled to a machine and configured to detect anomalous behavior of the machine. The sensor unit includes a low power microcontroller that learns to recognize a plurality of operations of the machine. The sensor unit generates mean vector and inverse of a Cholesky decomposition matrix for each operation. During a detection mode the sensor unit computes a Mahalanobis distance for each feature vector, mean vector and first matrix. The sensor unit detects anomalous behavior or classifies the operation of the machine based on the Mahalanobis distances.

An abnormal irregularity cause identifying device includes a process data acquisition unit that reads, from a storage device storing process data, the pieces of process data, an abnormality determination unit that calculates an abnormality degree representing an extent of an irregularity of process data of the pieces of process data read by the process data acquisition unit, and a cause diagnosis unit that obtains accuracy of a cause of the irregularity based on a proportion of process data having the abnormality degree calculated by the abnormality determination unit satisfying a predetermined criterion to the plurality of types of pieces of process data, by using causal relation information defining a combination between the cause and the irregularity, which appears as an influence resulting from the cause, of each of the plurality of types of pieces of process data.

The invention provides an intelligent work order automatic classification system, and relates to the technical field of work order management. According to the system, work order texts are analyzed through an LLM technology, core business phenomena are identified, auxiliary descriptions are eliminated, and an initial phenomenon mark set is generated. And further establishing a cross-sentence association analysis mechanism, dynamically inserting context associators with directivity between discrete phenomena based on syntactic dependency and semantic role labeling, and implementing dynamic weight assignment based on context proximity. The system generates a causal rule set with version identification, and a multi-decision trigger unit processes weighted phenomenon marks in parallel to generate a differentiated candidate root cause set. And the decision conflict quantization unit calculates rule matching degree distribution, and activates rule backtracking verification to ensure decision stability. And finally outputting a root cause classification work order entity with a rule version traceability identifier, thereby realizing automatic work order classification with high accuracy and stability.

The invention relates to a near-memory computing device, method and equipment, the device comprises a data arrangement unit, a computing normal form unit and a reconfigurable computing unit, the data arrangement unit is used for continuously storing key vectors corresponding to newly generated texts into preset lines of a memory storage unit, and the computing normal form unit is used for computing the newly generated texts; and / or splitting a value vector corresponding to the newly generated text and then dispersing and storing the value vector into a plurality of storage units of the memory; the calculation normal form unit is used for quoting different calculation normal forms according to different data arrangements of the key cache and the value cache; the reconfigurable calculation unit is used for executing inner product calculation and / or outer product calculation according to different calculation normal forms; the inner product calculation refers to internal accumulation of data read out through an adder tree, and the outer product calculation refers to accumulation of calculation results of matrix data read out multiple times through an accumulator. Therefore, the bandwidth waste in the data preparation stage can be completely eliminated, and the integrated bandwidth of the near memory architecture is fully utilized in the calculation stage.

To unlock a battery-less electronic lock using challenge data.SOLUTION: An electronic lock device according to an aspect of the present disclosure includes: an antenna unit which generates electric power by electromagnetic waves outputted from an electronic device; a generation unit which operates by using the electric power generated by the antenna unit and generates challenge data; a storage unit which stores the challenge data; a calculation unit which operates by using the electric power generated by the antenna unit and calculates authentication information on the basis of the challenge data stored in the storage unit; a communication unit which transmits the challenge data to an external device from the antenna unit and receives the authentication information calculated on the basis of the challenge data from the external device by using the antenna unit; an authentication unit which operates by using the electric power generated by the antenna unit and performs authentication processing on the basis of the authentication information received from the external device and the authentication information calculated by the calculation unit; and a locking / unlocking unit which operates by using the electric power generated by the antenna unit and locks / unlocks on the basis of the authentication result of the authentication processing.SELECTED DRAWING: Figure 1

The invention relates to a video coding image noise reduction processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring an original video frame image and a step length parameter; dividing the original video frame image into a plurality of pixel units according to the step length parameter; calculating local gradient data for each pixel unit to obtain a local gradient matrix; generating a filtering template according to the local gradient matrix; wherein the filtering template is used for representing a filtering weight of a pixel in the pixel unit; and performing weighted filtering processing on the pixel units according to the filtering template. By adopting the method, the quality of the video image to be coded can be improved.

A computer-implemented method of assessing a candidate point cloud is provided. The method includes receiving a source point cloud representing a ground truth and the candidate point cloud. Each of the candidate point cloud and the source point cloud is divided into a plurality of cells of equal size. Two or more sub-metrics are calculated. For example, two or more of a resolution sub-metric, an accuracy sub-metric, a coverage sub-metric, and an artifact sub-metric may be calculated. A point quality metric based on the sub-metrics (e.g., the coverage sub-metric, the artifact sub-metric, the accuracy sub-metric, and the resolution sub- metric). The point quality' metric is output as a normalized value.

The invention relates to the technical field of chip micro-architecture, and provides a task assignment system and a computing chip wherein the system comprises a central controller and a plurality of computing units; the central controller comprises a queue manager, and the queue manager is used for managing task queues in the central controller; identifiers of a plurality of to-be-processed task blocks are stored in the task queue; the computing unit is used for sending a task request to the queue manager under the condition that any task block is completed; the queue manager is used for responding to the task request, acquiring an identifier of a to-be-processed target task block from the managed task queue, and returning the identifier of the target task block to the computing unit corresponding to the task request; and the computing unit is also used for receiving the identifier of the target task block and performing task execution based on the identifier of the target task block, so that full utilization of chip computing resources is realized, a'trailing effect 'that other computing units are forced to be idle and wait due to long time consumption of individual tasks is avoided, and the overall operation performance is improved.

The invention relates to the technical field of data processing, in particular to a material purchasing demand response system based on intelligent decision making, and the system comprises a data acquisition unit which collects environment physical data and purchasing business data, and outputs a cross-dimensional original data flow; the data processing unit fuses the heterogeneous data to generate multi-modal feature data; the prediction unit calculates a blocking risk probability and an optimal path, and generates a path optimization instruction; the reconstruction control unit allocates a high-blocking task to a low-delay optical channel, allocates a conventional task to a high-fault-tolerance channel, and outputs a task and path mapping table; the scheduling unit decomposes the mapping table into a neuromorphic scheduling instruction and a quantum optimization instruction and fuses the neuromorphic scheduling instruction and the quantum optimization instruction to generate a cross-scale scheduling command; and when resource contention is detected, rescheduling and acquisition strategy adjustment are triggered. Nanosecond instruction writing is realized through a photon and quantum direct connection architecture, and the problems of resource contention and delay accumulation of an electronic digital data processing system in a high-concurrency scene are solved in combination with a dynamic entropy reduction regulation and control and hardware resource isolation mechanism.

The invention provides a data processing method and system based on an AI chip, and relates to the technical field of electric digital data processing, and the method comprises the steps: obtaining a current data unit in a target data stream; calculating a data similarity C between the data unit and a previous data unit; in neural network layer-by-layer processing, entropy attenuation indexes D {N} between adjacent calculation layers are calculated, and the entropy attenuation indexes D {N} are used for quantifying the decline degree of information uncertainty; and performing joint judgment on the data similarity C and the entropy attenuation index D {N}, and when C is higher than a similarity threshold value and D {N} is lower than an attenuation threshold value, interrupting processing of a subsequent calculation layer and taking feature data of the current level as redundant data to be removed. According to the method, by constructing dual verification criteria of the input similarity and the model internal processing entropy change, dynamic pruning of the calculation path is realized, the redundant calculation amount can be reduced on the premise that the risk identification precision is not sacrificed, and the processing efficiency and the energy efficiency ratio of an AI chip are improved.

The application provides a window drift processing method and an optical line terminal, an optical network unit and a computer readable storage medium. The window drift processing method applied to the OLT comprises the following steps: in the case that a first burst signal corresponding to an ONU is received, first information is determined according to the first burst signal, the first information is used for representing a window drift condition of the first burst signal; a drift domain is constructed according to the first information and the first burst signal; a GTC frame is transmitted to the ONU, so that the ONU corrects the window drift condition of the first burst signal according to the GTC frame, and the GTC frame is filled with the drift domain. In the embodiment of the application, the deviation can be quickly and accurately corrected directly according to the GTC frame, so that the efficiency of correcting the window drift of the burst signal is improved, and the stability of the passive optical fiber network is improved.