241 results about "Non critical" patented technology

The invention relates to the technical field of numerical control, in particular to a control method and system of numerical control equipment and a medium. The method comprises the following steps: collecting workpiece surface temperature distribution data and obtaining a workpiece CAD model; importing the workpiece surface temperature distribution data into a workpiece CAD model for internal temperature conduction inversion to obtain a first workpiece internal temperature distribution diagram; identifying a non-key area of the workpiece; performing a pre-cutting test on the non-key area of the workpiece to collect the temperature in the cutting process; performing nonlinear thermal expansion modeling on the workpiece based on the cutting process temperature to obtain a workpiece thermal expansion characteristic model; and an internal temperature distribution diagram of the second workpiece is obtained, and the internal temperature distribution diagram of the second workpiece represents the initial thermal state of the workpiece before formal machining. The numerical control machining precision and the cooling system efficiency are improved, the machining cost and resource consumption are reduced, and the machining adaptability, flexibility and stability are enhanced.

The invention discloses a manufacturing industry processing equipment information digitization system comprising a data acquisition layer which acquires data through a sensor which is connected to a data acquisition terminal in a wired or wireless mode; the data acquisition terminal is used for receiving the data acquired by the data acquisition layer, respectively marking the acquired data as key monitoring parameters and non-key monitoring parameters, and then transmitting the key monitoring parameters and the non-key monitoring parameters to the server; the invention relates to the technical field of manufacturing industry data processing, and can realize equipment fault point judgment when equipment fails, can more comprehensively capture subtle changes of equipment operation states in fault prediction, greatly improves the fault feature identification degree, and improves the production continuity by predicting the fault occurrence time and type. And the risks of capacity loss and sharp rise of maintenance cost caused by faults are reduced. Impact of faults on equipment is reduced, and the service life of the equipment is prolonged.

The present invention relates to the field of numerical control machine tool control technology, and particularly relates to a high-precision multi-axis machining composite numerical control machine tool control system, including: a collection module; a prediction module respectively determines a radius time series curve and a length time series curve according to the tool radius and the tool length, and constructs a tool wear prediction model in combination with the vibration amplitude and the preset movement path of the tool; an analysis module determines the tool wear degree according to the tool wear prediction model, and determines the critical influence path segment and the non-critical influence path segment according to the vibration amplitude; an optimization module determines the correction direction and the path correction amount according to the critical influence path segment, the non-critical influence path segment and the tool wear degree to determine the new tool movement path, and determines the adjustment method for the cutting speed / feed speed according to the tool wear degree. The present invention incorporates tool wear into the dynamic adjustment mechanism of the path, improving the machining accuracy.

The present disclosure relates to integration of integrated photonics-based optical gyroscopes and fiber-based optical gyroscopes into portable apparatuses that may include compass features. Novel small-footprint modularized fully integrated photonics optical gyroscopes are used for non-critical axes. However, for at least one critical axis, a fiber-optic gyroscope can be used to provide bias stability below 0.1° / Hr, which is directly correlated to predicting positional accuracy in the centimeter range. The positional accuracy results from the compassing ability of the gyroscope (referred to as gyrocompass) to calculate direction of heading using the earth's rotation.

The invention provides an FPGA lookup table merging and decomposing method and device, equipment and a medium, and relates to the technical field of integrated circuit netlist optimization. The method comprises the following steps: acquiring a mapped LUT network of an FPGA; then, candidate pair identification is carried out on the LUT network, conflict-free LUT candidate pairs with the optimal weight are selected to be merged, an LUT connection relation graph is constructed after merging, and a key path is identified; on the basis of the LUT connection relation graph, decomposing the LUT on a non-critical path into smaller cascaded LUT units according to a LUT priority sequence; and dynamically updating the network topology structure and time sequence information of the LUT connection relation graph after each decomposition to complete optimization of the FPGA netlist. According to the method, the number of LUTs can be remarkably reduced and the resource utilization rate of the FPGA can be improved on the premise of ensuring that the delay of the critical path is not changed.

The invention provides a forwarding proof obtaining method and device and a forwarding proof verification method and device, and belongs to the field of network security. In the application, the forwarding proof is obtained by combining the expected sequence position of the forwarding node in the forwarding path and the identity of the forwarding node, so that the position binding of the forwarding proof and the fault tolerance for the non-key node are realized. The forwarding proof is not only related to the identity of the forwarding node, but also related to the expected sequential position of the forwarding node. The correct forwarding proof can be calculated by the node with the correct identity when the data message is forwarded to the correct sequence position on the forwarding path, so that the forwarding proof is strongly bound with the real forwarding condition of the data message. If an expected node is skipped or redundant unexpected nodes are passed in the forwarding process, the identity of the node is not matched with the sequence position of the node, so that the forwarding proof obtained based on the identity of the node and the sequence position of the node cannot pass the verification, and the credibility of the forwarding proof is improved.

The invention discloses a cloud networking monitoring video lightweight processing method and a cloud networking monitoring video lightweight processing system based on U-ACE. The core of the method is to construct and operate a multi-task and multi-mode AI core engine U-ACE. The processing flow comprises the following steps of: sensing an input video in real time and judging a processing priority through a sensing and priority decision module PPM of the U-ACE; for high-priority content, a deep analysis and prediction enhancement module APEM of the U-ACE is used for analysis, prediction and enhancement; self-adaptive content compression is carried out on a non-high-priority or non-key area through an intelligent compression module (ICM) of the U-ACE; in combination with user preferences, enhanced display and layered rendering are carried out by using the user preferences of the U-ACE and an intelligent presentation module UPSM; and running parameters and strategies for dynamically adjusting the engine are fed back in real time through an engine self-optimization module ESOM of the U-ACE. The processing efficiency is improved, the resource consumption is reduced, and the key content presentation and the user experience are optimized.

The invention provides a convolutional neural network federated learning backdoor attack method based on gradient regulatory factors. The implementation steps are as follows: constructing a federated learning system; each client obtains a training sample set; each client performs iterative training on the local model; and the central server obtains a backdoor attack result. In the process that each client performs iterative training on a local model, a malicious client calculates a gradient regulation factor of each weight parameter through a normal loss value and a back door loss value of the local model, and updates the weight parameter based on the regulation factor; according to the method, the updating amplitude of the key weight parameters of the backdoor attack can be enhanced, meanwhile, updating of a large number of non-key weight parameters is weakened, the overall weight updating amplitude is limited, the backdoor attack can be effectively enhanced, the performance is similar to the gradient updating characteristics of a benign client side, and therefore the concealment and durability of the backdoor attack are improved.

The invention relates to the technical field of electric digital data processing, in particular to a BIM building model construction method for building engineering design, which comprises the following steps: determining a newly added building area of each construction stage relative to the previous construction stage based on the change condition of a BIM building model of a building project in different construction stages; key areas and non-key areas are screened out from all newly-added building areas; based on the construction complexity of the key area, the criticality of the key area is determined, and then the adaptive LOD hierarchy of the key area is determined; allocating a set LOD layer not higher than the adaptive LOD level for the non-key area; and constructing a BIM building model based on the set LOD hierarchy allocated to the non-key areas of all the construction stages and the adaptive LOD hierarchy of the key areas. According to the method, the self-adaptive LOD levels are determined for different key areas, so that the calculation amount is reduced while the construction quality of the BIM building model is ensured.

The invention belongs to the technical field of artificial intelligence, and provides a deep learning backdoor attack detection method and device based on a non-critical feature dynamic threshold. The method comprises the following steps: inputting a to-be-detected image to a second image classification model to obtain a non-key feature map and a classification result of the to-be-detected image; the second image classification model comprises a feature extraction network; the screening module is used for separating a key feature map and a non-key feature map from the feature map of the to-be-detected image by using the mask; the classifier is used for carrying out classification processing on the key feature map of the to-be-detected image to obtain a classification result; calculating a non-key feature score based on the non-key feature map of the to-be-detected image, and if the non-key feature score reaches a preset score threshold, setting the abnormal mark of the to-be-detected image as abnormal; and outputting the abnormal mark and the classification result of the to-be-detected image. According to the method, extremely fine adjustment of an attacker on some pixels of the image can be identified, and the method can adapt to hidden attacks such as feature space disturbance.

The invention discloses an intelligent processing method and system for clinical test data, and relates to the field of data processing, and the method comprises the steps: recognizing a high flow disturbance stage, and starting an uploading channel adjustment process; executing flow limiting operation in the high flow disturbance stage; obtaining a load pressure evaluation result; and completing data supplementation. According to the method, under the condition of data uploading peak or resource shortage in the clinical test process, the whole-process regulation and control of the disturbance data, such as current-limiting protection, back compensation and abnormal filing, is realized by effectively identifying the high-flow disturbance stage, dynamically adjusting the data uploading behavior and intelligently distinguishing the processing priorities of the key data and the non-key data. The method has the advantages of being high in adaptability, accurate in resource scheduling and safe and reliable in data, solves the problems of system congestion, uploading failure or important data lag in the data uploading stage, and improves the overall operation stability and the data integrity guarantee capability of a clinical test data processing system.

The invention relates to the technical field of electrical fault detection, in particular to an online fault judgment and automatic detection method for a marine cable, which comprises the following steps of: acquiring ground leakage current and load current in operation, extracting an active component of the leakage current and analyzing the nonlinear correlation between the active component and the load current to realize online early warning of insulation degradation; when the ship is in a working condition of allowing short-time power failure of partial non-critical loops, positioning a fault branch based on a normalization result of the ground capacitance variation before and after the power failure of each branch and the cable length; after power supply is recovered, the fault type is judged by combining the leakage current fundamental wave and phase voltage phase difference and the harmonic distortion rate; during power-off maintenance, high-frequency carrier waves are injected, the position of a fault point is determined according to current attenuation abnormity, correction is carried out by combining temperature and vibration factors, and the detection accuracy and the positioning precision are improved.

A technique monitors and detects a loss of utility power supplied by a main utility grid so that power modules of a virtual critical load panel (vCLP) may shed non-critical loads substantially before a battery inverter switches to backup power. grid detection module of the vCLP may be configured with profiles of industry standard power ranges utilized by a plurality of battery inverters to monitor and detect the loss of the utility power as an indication to switch to the backup power. The grid detection module employs the profiles in a manner that not only enables monitoring and detection of the loss of utility power but also enables shedding of the non-critical loads of the vCLP earlier than the switch to the backup power by the inverters.

The invention discloses an elastic scheduling method and system for a power grid based on a dynamic security domain, and relates to the technical field of elastic scheduling methods, and the method comprises the steps: determining the boundary of a non-key constraint based on an elastic adjustment factor, a power grid operation event corresponding to the power grid, and a plurality of constraints; the corresponding optimization event is determined according to the dynamic security domain, the boundary of the non-critical constraint and the real-time working data of the power grid, and the elastic scheduling system of the power grid is determined based on the optimization event, the real-time load data of the power grid and the corresponding real-time power supply data, so that the accuracy of the elastic scheduling system of the power grid is improved; and the elastic scheduling effect of the power grid is further improved. Therefore, the plurality of sub elastic scheduling projects are determined according to the identification of the elastic scheduling mode, the power optimization event of the power grid is determined based on the project content of each sub elastic scheduling project, the corresponding project position and the real-time load data of the power grid, and the accuracy of the online optimization logic of the power grid is ensured.

The invention relates to a key area high-definition video transmission method and device under a limited network condition, and belongs to the technical field of video processing, and the method comprises the steps: obtaining a network transmission speed; sending the key picture information of the to-be-transmitted video to a receiving end, and receiving a key region mark returned by the receiving end; dividing the video to be transmitted into a key area and a non-key area according to the key area mark; respectively determining a first definition parameter corresponding to the key area and a second definition parameter corresponding to the non-key area according to the network transmission speed; executing a circulation step: obtaining a local high-definition video according to the first definition parameter and the second definition parameter; transmitting the local high-definition video to a receiving end, and judging whether the local high-definition video can be normally played or not based on the transmission monitoring information; and if the playing is abnormal, updating the first definition parameter and / or the second definition parameter according to the network transmission speed, and repeatedly executing the loop step until the playing is normal. The video transmission stability is improved.

The invention discloses a large model reasoning method and device, related equipment and a computer program product, and relates to the field of artificial intelligence, and the method comprises the steps: firstly obtaining a problem statement of a to-be-processed problem, then judging whether a current node is a key node or not according to an input token of a current reasoning node in a chain reasoning process of a large model based on the problem statement, and if yes, judging whether the current node is the key node or not; and if not, performing compression processing on the original output token of the previous node, and reasoning subsequent nodes based on a compression processing result. According to the method, whether the reasoning nodes are critical or not is judged, and then the output token of the non-critical reasoning nodes is compressed during subsequent reasoning, so that the input data volume needing to be processed in the subsequent reasoning process is reduced, the subsequent processing speed is increased, and optimization of the calculation efficiency of chain reasoning, particularly long chain reasoning is facilitated.

The invention relates to the technical field of laser cutting, in particular to a waterproof material laser cutting path optimization method based on deep learning, which comprises the following steps: acquiring basic size data, thickness change rate distribution data and preloading stress distribution data of a target test piece, and identifying key / non-key path sections through discretized grid units; cutting is conducted on the non-critical path section through basic cutting parameters, edge size data are monitored in real time, and the parameters are dynamically adjusted to form verification cutting parameters; screening a first confidence path segment based on stable cutting quality, and extracting verification parameters to construct a confidence collection data set; key cutting parameters are determined through parameter fluctuation analysis and correlation calculation, and a confidence data set is formed; cutting the key path section by adopting the parameter; and finally, establishing a deep learning model based on the historical confidence data set, and outputting basic cutting parameters of the new test piece. According to the method, self-adaptive optimization of cutting parameters and paths is achieved, and the cutting precision of the waterproof material test piece is remarkably improved.

The invention relates to the technical field of safety control of mining equipment, in particular to a mining intrinsic safety type multi-mode cooperative control system. The system comprises a main controller, a sensor module, a voice alarm module and an equipment execution unit. According to the invention, by setting a hierarchical protection shielding function, an effect of accurately preventing and controlling major safety risks is achieved, based on a dual judgment mechanism of a comprehensive risk coefficient and an operation risk index, an early warning-alarm-emergency response three-level protection system is systematically constructed, and when risks of equipment temperature abnormity, speed overrun and the like are detected, the system can give an alarm. The method comprises the following steps: firstly, triggering voice alarm and reserving emergency disposal time, and automatically shielding a non-key protection function when the risk is upgraded to a system-level emergency state, thereby avoiding economic loss caused by whole-line production halt, breaking through the limitation of once-by-once stopping of a traditional safety system, and remarkably improving the intrinsic safety level of mine production.

The invention provides a processor resource management method and a related device. The electronic device may identify critical threads, critical dependent threads, and non-critical threads. When the key thread and the key dependent thread are operated, the electronic device can dynamically adjust the frequency of the processor according to the task processing conditions of the key thread and the key dependent thread, and accurate supply of processor resources to the key thread and the key dependent thread is achieved. An electronic device may constrained provisioning of processor resources provided to non-critical threads. The method can improve the utilization efficiency of processor resources. According to the electronic equipment, the electric quantity of the electronic equipment can be saved while the experience of smoothly using the electronic equipment is provided for a user, the situation that the temperature of the electronic equipment is too fast is reduced, and balance between equipment performance smoothness and the requirements of long endurance and rapid cooling is achieved.

The embodiment of the present specification provides a task processing model training method, a task processing method and a request processing method based on the task processing model. The task processing model training method comprises the following steps: obtaining a sample set and a test result of a sample task; determining a key processing unit corresponding to the sample task from a plurality of processing units according to the test result, wherein the influence degree of the key processing unit on the test result is greater than the influence degree of a non-key processing unit on the test result, and the non-key processing unit is a processing unit other than the key processing unit in the task processing model; and adjusting parameters of the key processing unit according to the sample set to obtain a trained task processing model. The key processing unit is determined before the model training, and only the parameters of the key processing unit corresponding to the sample task are adjusted, which reduces the mutual interference between different tasks, effectively solves the performance conflict problem, and improves the multi-task processing performance of the task processing model.

The present application belongs to the field of network security. Provided are a method and apparatus for acquiring a forwarding proof, and a method and apparatus for verifying a forwarding proof. In the present application, a forwarding proof is obtained in view of an expected sequential position of a forwarding node on a forwarding path and the identity of the forwarding node, thereby realizing the position binding of the forwarding proof and the fault tolerance for non-critical nodes. The forwarding proof is not only related to the identity of the forwarding node, but is also related to the expected sequential position of the forwarding node. Only when a data packet is forwarded to a correct sequential position on the forwarding path can a node having correct identity calculate a correct forwarding proof, such that the forwarding proof and the actual forwarding condition of the data packet are strongly bound. If an expected node is skipped or redundant unexpected nodes are passed by during a forwarding process, the identities of the nodes no longer match the sequential positions of the nodes; therefore, forwarding proofs obtained on the basis of the identities of the nodes and the sequential positions of the nodes cannot pass verification, thus improving the credibility of the forwarding proofs.

The invention belongs to the field of artificial intelligence platform development, operation and maintenance, and particularly relates to an artificial intelligence platform task management method and system. The method specifically comprises the steps of creating a Pod corresponding to a training task of an artificial intelligence platform through K8s; the created Pod comprises a resource demand of a training task; the K8s is utilized to allocate nodes meeting resource requirements to the Pod according to the resource requirements of the training tasks so as to execute the training tasks corresponding to the Pod; reducing the upper limit value of the resource demand of the Pod corresponding to the non-key training task in a set resource consumption peak period; and increasing the upper limit value of the resource demand of the Pod corresponding to the non-key training task in the set resource consumption valley period. In this way, it can be ensured that the key tasks are executed preferentially in the time period of resource shortage, completion of the non-key training tasks is accelerated in the time period of resource sufficiency, and therefore the completion progress of the training tasks of the artificial intelligence platform is optimized on the whole.

The invention relates to a method for manufacturing a donor wafer comprising the following steps: a) supplying a donor substrate made of a single-crystal material, said donor substrate having been recycled at least once, after a transfer of a thin layer of said donor substrate onto a receiving substrate so as to form a composite structure, said composite structure comprising a surface layer formed in whole or in part by the thin layer and disposed on the receiving substrate, b) checking the quality of the composite structure by inspecting a free surface of the surface layer to detect defects present on and / or in the surface layer, said defects then being classified into a first category, considered non-critical, or into a second category, considered critical.c) the selection of the donor substrate if the density of defects classified in the second category during step b) is less than a predetermined density, d) the assembly of the donor substrate selected in step c) onto a support substrate, by bonding, to form the donor wafer. The invention also relates to a donor wafer comprising a single-crystal silicon carbide donor substrate, having a thickness between 100 μm and 300 μm, disposed on a support substrate, and characterized in that a free face of the donor substrate has fewer than 0.5 micro-hole or inclusion defects / cm². Figure to be published with the abstract: No figure.

A multi-node, multi-container cluster system that generates, aggregates, and manages log files from services and components to be used for audit logs and to debug and perform other serviceability tasks provided by a vendor of the cluster system. Logs are collected from all components of the system and aggregated using a central persistent volume for non-critical applications and additional dedicated persistent volumes for critical tasks. The logs are implemented to minimize the risk of losing log lines and reduce resource overheads. Logs are formatted to provide a consistent logging format utilizing industry standard data formats, such as timestamps. Log files are stored persistently outside of pods to ensure high availability for any audit log management needs.

This invention relates to the field of communication technology, providing a communication method and device for a charging pile and its control board. The method includes: when a data transmission request event is detected, determining the target communication link based on an address mapping table and transmitting data; if reliable transmission is required for the data, storing a copy of the data in a pending confirmation queue and starting a retransmission timer; when a retransmission timer trigger event is detected, checking the unacknowledged data in the pending confirmation queue and retransmitting it according to a pre-set retransmission strategy for the communication link; and when an ACK response message is received, matching and removing the corresponding data from the pending confirmation queue. The retransmission strategy is dynamically configured based on the communication link medium type and data priority. This invention, by configuring differentiated reliable transmission mechanisms for different medium types and different priorities, ensures the reliability of critical instruction transmission while reducing bandwidth consumption by non-critical data.

In an embodiment of the present disclosure, a timing optimization method is provided, comprising: performing static timing analysis on the integrated circuit and obtaining a path to be processed in the integrated circuit; determining a network to be processed based on the path to be processed, wherein the network to be processed includes a network appearing on the path to be processed; isolating the load in each network to be processed, wherein the load isolation includes classifying the load in the network to be processed, wherein the classification results include critical loads and non-critical loads, and adding buffer units around the non-critical loads; and the load classification includes trying different load marking schemes, estimating the delay variation of each marking result, and selecting the best scheme to classify the loads. The processing scheme disclosed in the present disclosure can improve the efficiency of timing convergence on critical paths.

Methods and systems for improved impact detection in a device, such as a head-wearable device, are disclosed. The methods and systems relate to accurately detecting impact events such as falls or vehicular crashes to reduce false positives and enable a swift, appropriate emergency response. A method includes detecting use of the device by a user, for instance, confirming that a head-wearable device is being worn. The method further includes detecting a change in at least one of an orientation or a movement of the device within a threshold time period. An impact is then determined based on the confirmed use of the device and the detected change in its orientation or movement. This approach distinguishes genuine emergencies from non-critical events like dropping the device, thereby improving accuracy and conserving power by intelligently activating additional sensors only when a potential impact is detected.

The invention discloses an embedded data forwarding method and system based on adaptive token scheduling, and aims to solve the problems of high-frequency redundancy and flow conflict of analog quantity data in an embedded system. The method comprises the following steps: collecting multiple paths of analog quantity data, and storing the analog quantity data into each path of FIFO circular queue; key data and non-key data are distinguished through slope prediction, and the token generation rate is adjusted in a self-adaptive mode; the short-period tasks preferentially forward key data, and the long-period tasks summarize non-key data; and the real-time performance of key data is ensured by distributed arbitration. The system achieves the effect of data flow control through the cooperation of acquisition, sequence management, prediction, token control, arbitration, scheduling and forwarding modules.