35results about How to "Strong computing power" patented technology

The invention discloses a matrix calculation unit optimization-based sparse LU decomposition solving method and a related device, and relates to the technical field of numerical algorithm optimization, and the method comprises the steps: calling an improved PRCM algorithm to carry out the reordering of a sparse matrix, improving the local density of data, obtaining a sparse matrix after bandwidth compression, and obtaining a sparse matrix; then converting the sparse matrix into a regular and dense Tile block structure, storing the Tile block structure in a pre-allocated continuous memory space, performing numerical decomposition on the sparse matrix after bandwidth compression by adopting a right view-based LU decomposition algorithm, and accelerating by using a matrix calculation unit in the numerical decomposition process to obtain an LU matrix; therefore, efficient solving of the to-be-solved linear equation can be completed. According to the scheme, the spatial locality of the sparse matrix is fully utilized, the strong computing power of the matrix computing unit is exerted, the computing efficiency is improved while the computing amount is reduced, and the time of sparse LU decomposition in symbol decomposition and numerical decomposition stages is remarkably shortened.

The invention relates to a commanding height analysis method and system based on double spatial indexing, and the method employs a double index construction method through an index construction link, i.e., constructing double indexes of a tile quadtree and a triangular patch K-D tree, thereby achieving the quick positioning of a triangular patch intersecting with a ray in a live-action three-dimensional model. By means of the powerful operational capability of a computer, potential hidden danger commanding height points along the security and protection route can be accurately found, the commanding height point calculation efficiency is greatly improved, the practical feasibility of completing large-scale commanding height point calculation based on a live-action three-dimensional model is enhanced, and security and protection work is promoted to be developed more scientifically and efficiently.

The invention provides a navigation computer for a small inertial navigation system, the size of the navigation computer is only 55mm * 86mm * 16mm, a navigation resolving module, an I / F conversion module and a power supply module are integrated, and the power consumption is less than 3W; the navigation resolving module takes a ZYNQ7000 all-programmable SoC as a core processor, and has the functions of inertial device original data acquisition, navigation information preprocessing, navigation resolving and the like; the I / F conversion module can directly convert a current signal of the accelerometer into a pulse signal, and the pulse signal is accessed to the navigation resolving module for navigation resolving; the power supply module can output + 5V (8W),-5V (3W), + 15V (9W) and-15V (3W) isolated voltage-stabilized power supplies to the outside, and can supply power to other loads of the inertial navigation equipment. The method is suitable for laser inertial navigation equipment with small volume, low power consumption and high reliability.

The invention relates to a block chain consensus method for the Internet of Things, and the method specifically comprises the steps: carrying out the statistics of the data collection frequencies of all data collection nodes in the Internet of Things, and determining a consensus target value according to the number of consensus nodes and the frequencies; the method comprises the following steps: acquiring network flow and a source of the network flow of a consensus node from last block generation to the current moment, determining the participation degree of the consensus node in the Internet of Things by utilizing the network flow, the source of the network flow and the type of the consensus node, taking a node of the source of the network flow as a verification node, and verifying the participation degree by the verification node, if the verification is not passed, the reputation value of the consensus node is adjusted based on the data volume sent to the consensus node by the verification node; and the consensus node recalculates the target value by using the reputation value and the participation degree to obtain the target value of the consensus node when the block is generated, generates the block based on the target value of the consensus node and adds the block into the block chain. The problem that resources are limited when the block chain is applied in the Internet of Things is effectively solved.

The invention relates to an FPGA (Field Programmable Gate Array)-based surfacing workpiece surface defect detection method and device. The method comprises the following steps: acquiring a magnetic induction intensity data matrix; performing phase-locked amplification on the magnetic induction intensity data matrix to obtain an original feature data matrix; performing convolution filtering processing on the original feature data matrix to obtain a smooth feature data matrix; performing binarization processing on the smooth feature data matrix to obtain a binarized data matrix; whether magnetic field distortion exists on the surface of the surfacing workpiece or not is determined according to the binary data matrix; and when the magnetic field distortion exists on the surface of the surfacing workpiece, judging whether the magnetic field distortion is caused by surface defects of the workpiece or not, and outputting a detection report according to a judgment result. Defect detection is realized by utilizing hardware, the advantage of high operational capability of the FPGA is fully utilized, and the efficiency of defect detection is remarkably improved.

The invention belongs to the technical field of DC-AC converters, and relates to a single-stage current feed type bidirectional DC-AC converter and a fixed frequency control method thereof.The single-stage current feed type bidirectional DC-AC converter comprises a DC side composed of two Boost half bridges with inductors, an AC side composed of half bridges and an AC side filter, a transformer and a control device; the control device is used for controlling the direct current side and the alternating current side to describe the power transmission characteristics of the circuit by transconductance Gm, and the current control of the alternating current side is realized by a feedforward method; fixed-frequency linear phase shift control can be carried out in an ultra-wide DC side voltage range, bidirectional real-time power flow control can be realized in a relatively wide DC side voltage range, and a complex control loop design theory is not needed; therefore, the cost and the power consumption of the controller are effectively reduced, and a higher power density upper limit and a higher efficiency upper limit are achieved.

The invention relates to the technical field of navigation signal detection, and discloses a small portable navigation signal comprehensive detection system and method.The system comprises a building block type mobile antenna support, backpack type comprehensive detection equipment and a navigation equipment site evaluation system, the system is composed of a backpack type comprehensive detection host and an individual soldier handheld terminal, and rapid opening and comprehensive detection of navigation signals are achieved. The backpack comprehensive detection host integrates a battery, a power supply module, a high-performance signal processing board, a radio frequency channel and a medium-wave active antenna, adopts a high-performance battery and power supply management scheme and an advanced AC7Z020 core board for signal processing, and ensures high-precision and high-sensitivity detection. The system is further integrated with an electronic compass module to achieve a direction finding function, real-time data feedback and evaluation are achieved through Bluetooth communication between the individual soldier handheld terminal and the host, the detection convenience and reliability are greatly improved, and the system is particularly suitable for scenes such as field environments, emergency rescue and military actions.

The invention provides a structured data processing method and device based on a cloud mode, a medium and equipment. The method comprises the following steps: receiving structured data sent by equipment, and storing the structured data in a database; receiving a data query request sent by a user; analyzing the data query request to obtain query parameters; selecting an SQL statement template corresponding to the data query request from a template library; wherein SQL (Structured Query Language) statement templates in a plurality of business scenes are stored in the template library; the SQL statement template is filled with the query parameters, and SQL statements are obtained; and executing the SQL statement to query the required structured data from the database, and feeding back a query result to the user. According to the method, the distributed computing capability of cloud computing and the flexibility and the real-time performance of the end equipment are combined, the processing efficiency of the structured data can be improved, the cost is reduced, and more convenient and safer data processing services are provided for users.

The invention discloses a hyper-arithmetic scheduling server and a resource management method, and relates to the technical field of communication, the method comprises the following steps: 1, scheduling server data acquisition: acquiring server task requirements and resources acquired by a system; 2, preprocessing and classifying the collected server resource information; 3, performing classified management on effective resources; 4, constructing and updating an original scheduling strategy according to task requirements of workers; 5, monitoring server resources in real time; and 6, protecting the resource information of the scheduling server. According to whether the monitored resources are in the safe state or not, an alarm mechanism is established, related data are recorded, an external environment manager is warned of dangerous situations, the situation of resource leakage is blocked in time, losses caused to people are avoided, and the safety of the computing power scheduling server system is effectively guaranteed.

The application relates to a CAD drawing sharing and discussing system, which comprises a first terminal, one or more second terminals, a first CAD drawing sharing module and a first instant messaging module in the first terminal, a second CAD drawing sharing module and a second instant messaging module in each of the one or more second terminals, the first CAD drawing sharing module and the second CAD drawing sharing module transmitting and sharing CAD drawings with each other, and the first instant messaging module and the second instant messaging module transmitting instant messaging information with each other. In the application, each terminal can look at the CAD drawing while instant messaging, so that each party of CAD cooperation can view the CAD drawing at any time during the communication and discussion, which is convenient and fast.

The utility model provides a vehicle machine, a vehicle machine system and a vehicle. The utility model relates to the technical field of vehicles. The vehicle machine comprises a micro-control unit, a tire pressure monitoring module, a power supply module, a communication module, an antenna module, a central processing unit, an information interaction module, a video module and an audio module, the micro-control unit is in communication connection with the tire pressure monitoring module; the micro-control unit is in circuit connection with the power supply module; the micro-control unit is in communication connection with the communication module; the communication module is in communication connection with the antenna module; the communication module is in communication connection with the central processing unit; the micro-control unit is in communication connection with the central processing unit; and the central processing unit is in communication connection with the information interaction module, the video module and the audio module, so that the efficiency of information transmission between the vehicle machine and the vehicle networking communication box is improved.

The present invention discloses a drinking reminder method, a water cup, and a smart device. The drinking reminder method comprises the following steps: S1: setting a drinking reminder condition; S2: calculating a user's drinking amount and drinking frequency; S3: when the drinking reminder condition is met, issuing a drinking reminder message. The technical solution of the present application can accurately measure and continuously correct an individual's daily drinking amount, and use a smart device to remind children to develop good drinking habits, thereby helping children grow up healthily and promoting their enlightenment education.

The application provides a press operation information and operation and maintenance service edge computing system and method, which is independent of a press control PLC, comprises a dual-core edge computing controller, a data acquisition module, a communication module and sensors deployed on the press, has press information acquisition and data processing, fault diagnosis, motion pair temperature and friction block life analysis and prediction, remote data management and other functions, interacts with the main control PLC in real time to exchange press information data, and uploads the data information of the press to a cloud platform to provide support for remote service of the press. The application can obtain more press state information, effectively overcomes insufficient data analysis and processing capacity of the press main control PLC, and moves the detection sensors to the edge side, shortens the main control PLC scanning cycle, realizes real-time sensing and rapid response to the press operation information state, avoids overload, overheating, excessive wear and brake failure, and improves the safety, reliability and intelligent level of the press.

The invention relates to a cooperative firepower attack intelligent decision-making system based on a CPS. The cooperative firepower attack intelligent decision-making system comprises an intelligent decision-making center, a fire control system, a weapon system, a situation awareness system, a combat command and control center, a combat data center, reconnaissance equipment and a real-time communication network. The situation awareness system is used for acquiring weapon and target information of a battlefield and transmitting the information to the intelligent decision center; the intelligent decision-making center fuses and processes information from all the systems to obtain a cooperative firepower strike decision-making scheme; the combat command control center is used for receiving the preliminary task decision and sending the final task decision to the intelligent decision center; the fire control system is used for receiving the attack decision task and controlling the weapon system to attack the target; the combat data center is used for providing data support; and the real-time communication network is used for realizing real-time information transmission. According to the method, the advantages of information-physical fusion of the decision making system are fully exerted, the cooperative firepower strike decision is optimized, and the overall firepower strike capability of the combat unit is improved.

The present invention provides a cloud computing-based narrow linewidth 1200nm semiconductor laser data processing system, which relates to the field of data processing technology, including: a laser emission module, which uses a semiconductor laser to emit a laser beam with a narrow linewidth of 1200nm; a data acquisition module, which is connected to the laser emission module, and obtains the state parameters of the laser beam in real time, including power, wavelength, linewidth and working environment data, and pre-processes and digitally converts the signal output by the sensor; a cloud processing platform module, which is used to receive and process the data of the data acquisition module, realize real-time analysis, anomaly detection, trend prediction and remote monitoring of the data, and the analysis results of the cloud processing platform. The present invention realizes remote intelligent monitoring and automatic optimization and adjustment of the laser, and improves the data processing efficiency and the stability of the laser performance.

The utility model discloses a desktop computer mainboard on-board BGA central processing unit DDR6 memory structure, which belongs to the technical field of desktop computer mainboard structures, and comprises a mainboard, an on-board BGA central processing unit is arranged in the middle of the upper end of the upper surface of the mainboard, a heat conduction plate is arranged above the on-board BGA central processing unit, and the heat conduction plate is connected with the mainboard. The mainboard comprises an onboard BGA central processing unit, a DDR6 memory slot is formed in one side of the onboard BGA central processing unit, a 24PIN power supply interface is formed in one side of the DDR6 memory slot, a plurality of vertically-arranged SATA interfaces are formed below the 24PIN power supply interface, and a startup jumper needle port and a Type-C needle port are sequentially formed in the lower edge position of the upper surface of the mainboard from right to left. The CPU of the mainboard is integrally packaged by adopting the BGA, and meanwhile, a special DDR6 slot is designed to be matched with a relevant IO interface and a mainboard needle port, so that the mainboard has better transmission rate, higher stability, lower power consumption and larger capacity, can meet the requirement of a current computer for large throughput data volume of AI large model operation, and is externally connected with a plurality of electronic devices.

The present disclosure provides a living body detection method and system, and relates to the technical field of data processing. The living body detection method provided by the present disclosure comprises: obtaining an initial feature vector graph of a target image; performing N times of vector grouping and aggregation on the L vectors based on a living body detection model to obtain N vector grouping results, and inputting the N vector grouping results into an attention submodule of the living body detection model to output a first feature vector graph; performing M times of grouped full connection on the first feature vector graph based on the living body detection model and a feature dimension D to obtain a grouped full connection result; and determining a living body classification result of the target image based on the living body detection model and the grouped full connection result. The living body detection method provided by the present disclosure can balance the recognition accuracy and recognition efficiency of living body detection.

The present application relates to a kind of tool measuring method and system based on UG / NX software, based on UG / NX software, comprising: the tool model created after using reverse scanning device to scan cutting tool is obtained;Obtain the key features of the cutting tool set;Obtain the key parameters of the cutting tool set;Based on the tool model, key features and key parameters, using static installation size automatic measurement algorithm and / or static non-installation size automatic measurement algorithm, the automatic measurement calculation of static installation geometric dimension and / or static non-installation geometric dimension of cutting tool is carried out on the tool model;Output the measurement data calculated by static installation size automatic measurement algorithm and / or static non-installation size automatic measurement algorithm.The present application combines reverse scanning and UG / NX software, can greatly improve the measurement accuracy and measurement efficiency of tool, improve product quality, bring more economic benefits for enterprise.

The invention provides a parking control method and device, a vehicle and a storage medium, and the method comprises the steps: responding to the detection of the existence of a target parking space which can be parked, transmitting the multimedia data of a parking area to a cloud end, and enabling the cloud end to recognize the parking decision information of the target parking space, the parking decision information, sent by the cloud, of the target parking space is obtained, parking control is conducted on the vehicle according to the parking decision information of the target parking space, the target parking space obtained through vehicle end recognition is achieved, and the parking decision information of the target parking space is obtained through cloud recognition. The accuracy of the parking decision information of the target parking space is improved, and the parking safety is improved through the cooperation of the vehicle terminal and the cloud terminal.

The invention provides an intelligent security system based on artificial intelligence and Internet of Things. The intelligent security system comprises a sensing layer, a data processing and analysis unit, an intelligent decision and control layer, a cloud platform service unit and a user interaction layer, the sensing layer is provided with a plurality of Internet of Things sensors and biological recognition equipment in a target area, the target area is monitored and people are recognized through the Internet of Things sensors and the biological recognition equipment, and collected data are sent to the data processing and analyzing unit in real time; the data processing and analyzing unit is used for mining and analyzing collected data in the sensing layer through a machine learning or deep learning algorithm, constructing a security threat model according to the collected data, setting an abnormal behavior database in the security threat model, performing automatic identification and early-warning tracking on abnormal behaviors in the collected data, and performing early-warning tracking on the abnormal behaviors in the security threat model. The processing information is fed back to the intelligent decision-making and control layer; and the intelligent decision and control layer sets a processing plan according to a preset security rule, and processes the information uploaded by the analysis unit according to the data.

The utility model relates to a kind of DTU edge gateway equipment, belong to communication equipment technical field, including central processing circuit, USB interface circuit, ethernet communication circuit, RS485 communication circuit, CAN communication circuit, input-output circuit and the power supply circuit for the power supply of entire equipment, central processing circuit includes gateway chip U1 and the peripheral subcircuit connected to gateway chip U1, USB interface circuit, ethernet communication circuit, RS485 communication circuit, CAN communication circuit and input-output circuit are all with gateway chip U1 communication connection.The utility model integrates USB interface circuit, ethernet communication circuit, RS485 communication circuit and CAN communication circuit, can simultaneously support multiple communication protocols, such as USB, ethernet, RS485 and CAN etc.;Greatly improve the data interaction efficiency and the interconnection intercommunication ability between equipment.

The invention discloses an intelligent circuit breaker control system and a control method. The control system comprises a plurality of sensors, a core processor, a man-machine interaction module, a communication module, a photoelectric isolation module, a power supply module, an action mechanism, a clock module and a storage module, the current sensor and the voltage sensor collect current signals and voltage signals in a loop, the current signals and the voltage signals are converted by the A / D converter, and digital signals are output to the core processor; the displacement sensor collects the displacement of the main contact of the circuit breaker to obtain an opening and closing signal of the circuit breaker, and the opening and closing signal is input into the core processor through the photoelectric isolation module to judge whether the circuit breaker breaks down. If the fault is judged, the core processor outputs an action signal, the action mechanism acts, and the circuit breaker breaks the fault; the information is displayed on a local man-machine interaction LCD interface and an alarm is given out; according to the invention, intelligent control and intelligent protection of the circuit breaker are realized, the working state of the circuit breaker can be quickly and remotely known in real time, the problems that the fault of the circuit breaker cannot be known in time and the fault signal of the circuit breaker is difficult to collect due to the problems of distance and the like are greatly reduced, and the intellectualization and high efficiency of the circuit breaker are met to the greatest extent.

The invention relates to the technical field of intelligent traffic, in particular to a highway traffic flow prediction method and system, and the method comprises the steps: data collection: collecting a public traffic flow data set, a national highway traffic flow data set, and a geological information and meteorological information data set; data preprocessing: preprocessing the collected data; model training: adopting a hierarchical GRU structure, wherein the model structure comprises detailed configuration of an input layer, a coding layer, an attention mechanism and an output layer; the model adopts a two-stage training strategy, model training is divided into a pre-training stage and a scene specific training stage, and in the pre-training stage, a large-scale public traffic flow data set is used for pre-training, so that the model learns a basic traffic flow change mode; in the scene specific training stage, an in-scene data fine tuning model is used, and model parameters are adjusted; model evaluation: adopting a plurality of evaluation standards to measure the performance of the model in the traffic flow prediction task, wherein the specific evaluation indexes and standards comprise mean absolute error, mean square error, mean square logarithm error and decision coefficient.

The utility model discloses a differential AGV (Automatic Guided Vehicle) control system based on laser navigation, which particularly relates to the technical field of AGVs and comprises a main control industrial personal computer, an IO (Input / Output) module, a CAN (Controller Area Network) communication module, a switch and a laser radar, the main control industrial personal computer is connected with the switch, and the switch is further connected with the IO module, the CAN communication module and the laser radar. The main control industrial personal computer is also connected with sound equipment, an IMU module and a WIFI module; the IO module comprises IO equipment; and the CAN communication module is also connected with a motor action module and a non-motor action module. According to the utility model, the main control industrial personal computer is utilized, so that the system has abundant external interfaces and can be connected with sensors with various interfaces; the processing speed and the calculation capability are high; by arranging the IO module, control over radar sudden stop, button sudden stop, touch edge sudden stop, upper and lower limiting sensors and a rotation zero position sensor is achieved, control over a motor and some peripherals is achieved through the CAN communication module, the motor and the peripherals are directly and mutually free of interference, and good reliability and stability are achieved.

The present invention discloses a neural network training method, a semantic similarity calculation method and a semantic retrieval system. The neural network training method comprises the following steps: S1: marking sentence similarity; S2: inputting two marked sentences into a neural network; S3: processing the features of the two sentences and calculating a loss function; S4: training the neural network according to the loss value of the loss function. The neural network training method used in the technical solution of the present invention has few neural network parameters, fast retrieval speed, can accurately calculate semantic similarity, and thus can obtain semantic information of the text, thereby improving the accuracy of retrieval, and is suitable for high concurrency and low latency demand scenarios.

The application discloses a reconfigurable target detection coprocessor and method based on RISC-V, relates to the technical field of embedded artificial intelligence and computer architecture, and is connected with a RISC-V main processor and a system on chip (SoC) memory, wherein the reconfigurable target detection coprocessor based on RISC-V, the RISC-V main processor and the SoC memory are integrated in a system on chip (SoC) chip; the application generates hardware configuration information through the RISC-V main processor, combines a dynamically reconfigured programmable data exchange network, realizes software definition of a hardware data path, enables a single hardware platform to efficiently accelerate support for multiple target detection algorithms with different structures, and improves flexibility and versatility of multi-target detection; and the data path dynamically reconfigured by the control unit ensures close coupling between basic computing units, eliminates idle resources caused by data flow mismatch in a fixed architecture, and significantly improves utilization of the basic computing units.

The utility model relates to a mining intelligent gateway device, which comprises a shell, a gateway PCB (Printed Circuit Board), a sealing assembly and a four-core socket assembly, the gateway PCB circuit board is arranged in the shell body; the shell is provided with four plugging holes; the four-core socket assembly is arranged in the shell corresponding to the four plugging holes, and is connected with the gateway PCB; and the sealing assembly is arranged in the shell and is used for sealing and protecting the gateway PCB circuit board and the four-core socket assembly in the shell. The four-core socket assembly comprises a four-core socket, four U-shaped clamping jacks and four positioning pins. The four-core socket is arranged corresponding to the four plugging holes and is connected with the gateway PCB; the four U-shaped clamping jacks are correspondingly arranged in the four plugging holes respectively, so that firm connection between a plug and the four-core socket is ensured, and a copper head cable is prevented from falling off due to external force; and the four positioning pins are correspondingly arranged in the four plugging holes respectively, so that the copper head cable is prevented from rotating in the shell. The gateway device provided by the utility model avoids the problem of damage caused by long-term working in a severe environment of an underground coal mine, and has the characteristics of high waterproof grade, good safety performance, small volume, convenience in installation and the like.

The invention discloses a cluster-based scheduling method and system. The method comprises the following steps: S1, analyzing batch service requests from the same address and the total data writing amount of the batch service requests; s2, judging whether the cluster of the area to which the batch service requests belong meets a write-in condition, if so, selecting the cluster of the area to which the batch service requests belong as a write-in cluster of the batch service requests, and if not, executing the step S3; and S3, sorting according to the candidate clusters accessed by the batch of service requests, and taking the candidate cluster which is optimally sorted and meets the write-in condition as a write-in cluster. When the dynamic change of the service request is not matched with the capacity of the local cluster, the address of the service request, the current to-be-recycled space of each cluster, the residual available space, the load and the recycling speed are comprehensively considered, and the service request is sent to the optimal cluster, so that the resources of each cluster are efficiently and fully utilized; and cluster resources can be adjusted in time under the continuous condition of not interrupting the service.

The application provides a method for ensuring data privacy and verifiable calculation results of a nonlinear GELU function. The method ensures the transparency of the calculation process by committing the local model parameters and private data on the server side. After the client-side encrypts the local private data, it is sent to the server for GELU operation to ensure the security of the data during transmission. The client verifies the validity of the server commitment to ensure the reliability of the server data processing. After receiving the GELU operation result, the client decrypts it and verifies the validity of the nonlinear function GELU operation result and the prediction result. The cloud server of the application provides powerful storage and computing capacity to support large-scale model inference services. The client is responsible for encrypting local data and sending data to the cloud server for inference and prediction. Through this method, user data privacy can be effectively protected, and the correctness and verifiability of the calculation results can be ensured.

This disclosure provides an image correction method, apparatus, electronic device, and program product. The method includes: preloading multiple pre-stored dark current noise models corresponding to different line frequencies; acquiring the real-time line frequency of the camera during the current image acquisition process; searching for a corresponding target dark current noise model from the pre-loaded multiple dark current noise models based on the real-time line frequency; and performing image correction based on the image data acquired by the camera and the target dark current noise model to obtain corrected image data. This disclosure solves the technical problems of high storage pressure, high response latency, and limited parameter coverage caused by the correction data being built into the camera in related technologies, achieving high-precision, fast-response real-time dark current correction in high-speed dynamic imaging scenarios.