110 results about "Non critical" patented technology

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 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.

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 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.

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.

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.

This invention discloses an optimization method and system based on mechanism importance and defect merging. The method includes: collecting multi-source evidence of bridge defects; determining the occurrence mechanism and impact dimensions of various defects through coupled defect model matching; classifying defects into critical defects affecting structural safety or causing systemic failure and non-critical defects affecting serviceability or durability based on the risk level of the upstream defect diagnosis module; establishing a defect importance classification list and clarifying the classification basis and judgment criteria; obtaining the preliminary defect assessment scale and the risk level and development trend given by the upstream module; maintaining the preliminary scale for critical defects and adjusting the optimization scale of non-critical defects according to a preset calibration rule set; for calibrated non-critical defects, if they belong to a preset minor defect merging pair, merging them into one item and determining their representative scale and contribution order. This ensures bridge operation safety and improves maintenance economy.

The invention discloses a state evaluation method and system of a photovoltaic power generation assembly, and relates to the technical field of state evaluation of the photovoltaic power generation assembly, and the method comprises the steps: determining whether there is only one crack type feature in a target key region of a target assembly according to the area of a crack coverage region and the concentration degree of cracks in the coverage region if there is only one crack type feature in the target key region of the target assembly; evaluating the induced fault risk value of the target component, if no less than one crack category feature exists and if a crack crossing phenomenon exists, evaluating the induced fault risk value of the target component according to the crack crossing number, and comparing the obtained first or second risk evaluation value with a preset key risk early warning threshold value, or determining the risk value of the induced fault of the target component according to the preset key risk early warning threshold value. And comparing the third risk assessment value or the fourth risk assessment value to which the target non-key area of the target component belongs with a preset non-key risk early warning threshold, and performing different levels of risk early warning. According to the state evaluation method and system for the photovoltaic power generation assembly, the risk early warning efficiency can be improved.

A computer-implemented method includes training a machine-learning model, using a training dataset that distinguishes between critical systems and non-critical systems, to classify a particular comput

The method, the control device (7), the computer program product (11) and the fuel injection device (1) according to the invention are designed to operate a fuel injector (4) which has an injector valve (4a) and is associated with a combustion chamber (3a) of the internal combustion engine (2), in particular within a critical operating range of the fuel injector (4). For this purpose, an electronic control device (7) associated with the fuel injector (4) first applies a test control signal to the injector valve (4a) during a non-critical operating interval and receives a corresponding response signal from the fuel injector (4) and determines therefrom an opening duration deviation of the injector valve (4a). Control parameters for controlling the fuel injector (4) to inject fuel in a critical operating interval of the fuel injector (4) are determined by means of a transfer function as a function of a specified target fuel injection amount and a determined opening duration deviation of the injector valve (4a), and a current pressure and / or a current fuel temperature, and a corresponding control signal is output to drive the fuel injector (4). In this way, a nominal specified fuel injection quantity and optionally a desired injection starting time can be achieved with high accuracy even in a critical operating range of the fuel injector (4).

The invention discloses a power plant unit control method and system based on edge calculation, and relates to the technical field of edge calculation. The method comprises the following steps: acquiring and processing a first data set in real time by utilizing an edge computing node; when the key time period is identified, triggering a corresponding dynamic adjustment mechanism; the technical key points are as follows: on the basis of an originally divided key period and an originally divided non-key period, the period is divided twice to obtain a calibrated period and a non-calibrated period, different constraint condition correction factors are adopted to adjust an originally determined probability factor, so that a control strategy is more targeted, and by constructing a parameter adjustment model, the accuracy of the control strategy is improved. The time difference adjusted in advance is output, and the control is dynamically adjusted according to the time difference, so that a preset management mode is realized, the accuracy of regulation and control is realized, much inconvenience caused by instant response is avoided, the problem that a traditional single control strategy is difficult to meet diversified working requirements is solved, and the flexibility and adaptability of the control strategy are improved.

The utility model relates to the technical field of forming dies, in particular to a forming die with a guide structure, which comprises an upper die plate, the bottom of the upper die plate is in threaded connection with the top of an upper die, and a lower die is arranged at the bottom of the upper die. Guide plates are arranged on the outer walls of the left side and the right side of the upper mold; a pressing groove is formed in the bottom of the upper mold; and guide grooves are formed in the outer walls of the left side and the right side of the lower mold. According to the device, the upper die plate and the upper die are rapidly and accurately assembled according to the design of corresponding screw holes, the connection firmness is enhanced, disassembly and maintenance are convenient, the T-shaped guide plate is inserted into the guide groove to limit transverse deviation and automatically align, and the part forming precision and the service life of the die are guaranteed. The pressing groove and the curved surface of the lower die are attached to the outline of a part, plate materials are guided to deform evenly, cracks are reduced, and shape precision is ensured. The weight of the upper die weight reducing groove is reduced by removing non-critical materials, the equipment load is reduced, the operation safety and the forming stability are improved, and material utilization and function balance are optimized.

Techniques are disclosed for a fault monitor to determine that no fault has been lost. The fault monitor may distinguish between critical and non-critical faults without the risk of missing a critical fault. The fault monitor may detect a new fault event from a fault source and may set a fault overrun flag when the new fault event is detected while an existing fault event from the fault source is being processed. When the fault monitor receives a fault acknowledgement to indicate completion of processing of the existing fault event, the fault monitor may generate a request to process the new fault event as an overrun fault based on the fault overrun flag is set. The fault monitor may generate a request to process the new fault event as a non-overrun fault when the new fault event is detected without an existing fault event from the fault source being processed.

The application discloses a kind of translation lookaside buffer table entry processing method, system, medium and product, applied to processor technical field, comprising: when process switching, determine the non-critical table entry corresponding to the process before switching in translation lookaside buffer, obtain target non-critical table entry;The target non-critical table entry is stored in the first cache corresponding to processor core, and the target non-critical table entry is deleted from the translation lookaside buffer;The recovery deadline corresponding to the process before switching issued by operating system is acquired;Based on the recovery deadline, before switching back to the process before switching, the target non-critical table entry is written back to the translation lookaside buffer from the first cache.This way, in the case of guaranteeing the process before switching fast recovery, the hit rate of translation lookaside buffer table entry can be improved, and then the processor performance is improved.

This application relates to digital twin 3D modeling, specifically to a method and device for constructing a digital twin waterway scene using electronic navigation charts. The method includes: analyzing the historical trend of water depth values ​​at each depth point to determine the inherent terrain feature values ​​of each depth point set at the current time; determining the terrain ruggedness feature value by fitting the last data point in the temporal sequence of the trend components of all depth points in each depth point set at the current time with its fitted value and the fitting error; and determining interpolation feature values ​​by combining the inherent terrain feature values ​​to classify all depth points into critical and non-critical points; and performing interpolation processing on the water depth values ​​of all critical and non-critical points using different interpolation methods respectively. This application solves the problem that a single interpolation method cannot simultaneously ensure the realism and real-time performance of the model construction, thus improving the realism and real-time performance of the digital twin waterway scene model.

Disclosed are system and methods of dynamically balancing power and performance of a processing unit. The method includes receiving workloads to be processed by the processing unit; classifying, using a recurrent neural network, the workloads according to expected resources to be expended by different functional blocks; identifying a critical path workload based on the classification of workloads; determining a temperature-independent operating frequency for the critical path workload; determining a temperature-dependent operating frequency for the critical path workload based on a junction temperature of the processing unit; adjusting the temperature-dependent operating frequency to a target operating frequency having a value within a predetermined difference from the temperature-independent operating frequency by actively cooling the processing unit; setting a critical path supply voltage based on the target operating frequency; and setting a non-critical path voltage for remaining ones of the workloads at a value less than the critical path supply voltage.

A memory controller is provided and configured to control access to a memory with a memory access bandwidth by a plurality of processing components of a data processing system. The memory controller comprises a control unit configured to allocate a respective fraction of the memory access bandwidth to each of the plurality of processing components for accessing the memory by a plurality of memory access operations. Moreover, the memory controller comprises a monitoring unit configured to obtain timing information about a duration of a respective memory access operation by each of the plurality of processing components via a bus of the data processing system. The control unit is further configured to adjust, for one or more of the plurality of processing components, the respective fraction of the memory access bandwidth based on the timing information obtained by the monitoring unit.

Disclosed in embodiments of the present disclosure are a method and apparatus for applying a large language model. A specific implementation of the method comprises: inputting an original question to be queried and a preset prompt into a large language model, and outputting a first question, wherein the prompt is used for instructing the large language model to extract, from the original question, a question reflecting a real intention; deleting non-key information from the first question to obtain a second question; and inputting the second question and a preset security prompt into the large language model, and outputting an answer, wherein the security prompt is used for indicating that the large language model needs to comply with a security policy when answering a question. The implementation can effectively defend against jailbreak attacks having deceptive and implicit intentions.

This invention belongs to the field of triple mode redundancy (TMR) technology, and particularly relates to a selective TMR conversion method and system based on two-stage decoupling. The method includes acquiring the Verilog design code to be converted and parsing the circuit signals; calculating the dynamic activity of each circuit signal, dividing the circuit signals into critical and non-critical circuit signals, and forming a list of critical circuit signals; reading the list of critical circuit signals, traversing each assignment statement in the Verilog design code to be converted, and identifying whether the current circuit signal is a critical circuit signal; performing TMR operation on the identified critical circuit signals, and using logical assignment to make the replica signals track the original signals in real time for the identified non-critical circuit signals, thus completing the selective TMR conversion. This invention completely decouples the two stages of dynamic activity analysis of circuit signals and selective conversion of source code, and performs true / pseudo-TMR splitting processing.

The application discloses a network attack detection method, device, equipment, storage medium and program product, and belongs to the technical field of network security. The method comprises the following steps: in response to a network event being a new network attack event, a plurality of attack characteristics are obtained by analyzing the new network attack event; a target attack event is determined according to the similarity between a pre-stored attack event and the plurality of attack characteristics; a defense processing result is obtained by performing defense processing on the new network attack event according to a defense strategy of the target attack event; and an alarm level of the new network attack event is determined according to the defense processing result. In this way, the new network attack event can be adaptively defended, the occurrence of non-critical alarms can be reduced, and the processing efficiency of the new network attack event can be improved.

The invention discloses a distributed non-replacement dynamic flow shop scheduling optimization method based on deep reinforcement learning, and belongs to the technical field of distributed green production scheduling. The method aims at solving the problem of multi-target dynamic scheduling in a distributed heterogeneous environment and aims at minimizing the maximum completion time, the total energy consumption and the tardiness cost. The method comprises the following steps: firstly, constructing a workshop state heterogeneous graph model, and extracting topological features of processes and machines by using a graph attention network; secondly, constructing a PPO decision model combined with an action mask mechanism, and outputting a scheduling action meeting physical constraints; and finally, mining the energy-saving potential of the non-critical process through a post-processing strategy based on the critical path. Dynamic disturbance such as emergency order insertion can be responded in real time, the production efficiency and the green energy-saving index are effectively balanced, and efficient utilization of workshop resources is achieved.

The invention relates to the technical field of capacitive screens, in particular to a high-precision hot pressing process of a capacitive screen. Comprising the following steps: step 1, defining and calibrating a key monitoring area and a non-key monitoring area; step 2, embedding a micro temperature sensor array and a micro pressure sensor array, establishing a hot-pressing surface and a pressure-bearing surface, and ensuring that the sensor layout density in the key monitoring area is higher than that in the non-key area; 3, ensuring that the calibrated key monitoring area corresponds to the non-key monitoring area; 4, executing a hot pressing process, and setting a plurality of continuous process monitoring nodes in a linear pressing stage; synchronously acquiring and recording full-field data of the sensor array; on the basis of comparison between the full-field data and node full-field data in a preset data model, triple monitoring judgment is executed in sequence; and 5, the linear pressing stage is finished, and whether subsequent pressure maintaining and cooling operation is executed or not is judged based on the triple monitoring judgment result.

The invention provides a robot sensing self-cleaning method based on deep learning, and aims to solve the problems that availability is reduced and cleaning opportunity and intensity are difficult to cooperate with tasks due to the fact that sensors are shielded and stained, the method comprises the steps of obtaining task states and sensor original signals, dividing task functional areas according to view fields and marking key / non-key areas; extracting features such as brightness change, texture contrast, marginal definition and depth loss, inputting the features into a one-dimensional combined neural network, and outputting an overall pollution influence value and an area influence value; according to a threshold value and a task cooperative cleaning control rule, whether cleaning is conducted or not, cleaning intensity and starting time are determined, and execution is conducted after the posture, the action sequence and the duration are planned in combination with the reachable space of the robot; review is carried out after cleaning, and cleaning completion or additional cleaning and priority areas are given; according to the method, task collaboration and adaptive cleaning of priority of key areas are realized, the availability of the sensor is improved, and task interruption is reduced.

A memory management method and an electronic device, where the method includes: detecting a running status of a first application; and processing, when detecting that the running status of the first application is switched from a first running status to a second running status, a partial memory referenced by the first application, where the partial memory is a memory associated with a target service of the first application, and the target service is a non-critical service of the first application in the second running status.

The invention relates to a vector retrieval system and method based on storage and calculation integration, and the system comprises an analog-to-digital converter module which compares a result with a preset code bit by bit, generates a termination signal when the result reaches the standard, and outputs a result micro-packet. And the buffer state unit is used for storing and calculating the front and rear end cache subtasks and results of the array block at the front and rear ends, converging the query results, monitoring the cache occupancy rate and grading the operation time so as to provide the task residual duration. And the queue jumping scheduling module is used for judging whether the new task can be jumped in a non-critical path or not according to the cache occupancy rate, the new task duration and the current task residual duration on the premise of not influencing the completion time of the critical path of the current task, and otherwise, entering a waiting queue according to the priority. Therefore, through cooperative work of the three modules, the problems that power consumption time delay is too high, task input and output are prone to being blocked, and task scheduling efficiency is low in total calculation are solved, and task processing fluency, the calculation resource utilization rate and the task scheduling efficiency are greatly improved.

The invention relates to the technical field of computer computing resource scheduling, and discloses a DAG task energy-saving scheduling method and device and a storage medium, through dynamic analysis of a DAG structure, utilization of elastic time recovery on a non-critical path and combination of DVFS adjustment frequency, the real-time deadline requirement is finally met, and meanwhile the power consumption of a system is greatly reduced. In combination with the mapping schematic from the task to the core, the most necessary hardware resources are preferentially used in the execution process of the strategy, and the idle cores are timely combined and closed, so that the scheduling characteristics of high efficiency and energy conservation are embodied; the problems that in an existing technical scheme, a non-critical path dynamic elastic space cannot be utilized at the same time, DVFS frequency adjustment and idle core combination cannot be combined to achieve real-time scheduling, and the energy consumption cannot be reduced while the SLA requirement is guaranteed are solved.

Selective data compression for non-critical memory requests is described. In accordance with the described techniques, memory request packets are generated and communicated for retrieval of data from computer memory, and data packets including the retrieved data are communicated to a hardware compression engine. The compression engine selectively compresses the retrieved data and the compressed data is communicated through an interconnect architecture for decompression by a decompression engine. The compression of the data decreases communication congestion within the interconnect architecture. The memory request packets are configurable to include metadata providing hints to the compression engine to guide selective compression of data.

This application discloses a task processing method, apparatus, device, storage medium, and program product, relating to the field of industrial internet technology. The method includes: updating the global ready state of task sets with dependencies on each terminal at scheduling time slot boundaries; calculating the scheduling priority of tasks in the global ready state and sorting them by scheduling priority to obtain a ready task list; wherein the scheduling priority of a task defines the criticality of the ready task; traversing the ready task list to generate a set of actionable actions for each ready task in the list; selecting candidate tasks based on the set of actionable actions; and selecting an execution position from the set of actionable actions of the candidate tasks and initiating execution. This solution not only ensures that critical tasks are executed first, reducing the risk of critical tasks being blocked by non-critical tasks, but also eliminates rollback and reselection due to infeasible decisions, significantly improving the stability and reliability of task scheduling in industrial scenarios and reducing end-to-end task processing latency.

According to an aspect, there is provided a computer- implemented method comprising the following Initially, number of terminal devices per cell for one or more cells is monitored. In response to detecting that the number of terminal devices within a cell is larger than a pre-defined threshold for a pre-defined amount of time, the following is performed. One or more neighboring cells of the cell are detected. One or more first terminal devices operating in any non-mission-critical operating mode in the cell or its neighboring cells are determined. A first set of values for radio transmission power control parameters for the one or more first terminal devices is determined. The first set of values is associated with lower terminal device transmit power compared to current default values. Configuration of the one or more first terminal devices to use the first set of values is caused.