794 results about "State switching" patented technology

The invention provides a method for identifying a power grid frequency signal assessment standard, and the method comprises the steps: constructing a system architecture composed of a master station, a substation and a communication network, and achieving the initialization of equipment through a finite-state machine; the method comprises the following steps: collecting power grid frequency, power generation side frequency difference and communication state multi-dimensional data, processing signals by applying median filtering, a sliding window and an EWMA algorithm, introducing fuzzy logic to evaluate a system state, and dynamically adjusting a response strategy; an improved PID algorithm is adopted to track frequency change, feed-forward compensation and PSO parameter optimization are combined, a hidden Markov model is utilized to predict a communication fault, and local mode switching is triggered in advance; main station, mixing and local three-state switching is carried out according to communication states and load changes, and a frequency modulation dead zone is automatically adjusted according to power grid loads through a dynamic threshold value self-adaptive algorithm; the control effect is verified by using a digital twinning technology; and the safety and reliability of the system are guaranteed by optional quantum encryption and active-active redundancy design. The whole scheme effectively reduces the power loss of power generation enterprises, and maintains the safe and stable operation of a power grid.

The invention provides an edge server dynamic activation method and system based on deep reinforcement learning, and the method comprises the following steps: S1, building system models, including building a network model, an energy consumption model, a communication and service delay model and a state switching cost model, the network model including RES and MES; s2, optimizing a network model by calculating the sum of the cost of the energy consumption model, the communication and service delay model and the state switching cost model; s3, constructing a Markov decision process model, and improving RES stability; s4, predicting a traffic load; s5, calculating a baseline value; s6, training the network model through a centralized intelligent scheduling algorithm CDDS to obtain a trained strategy network model; s7, dividing the trained strategy network model through a federated distributed intelligent scheduling algorithm FDDS, and training the model based on federated learning to obtain a DDPG model; and S8, the DDPG model is deployed to each RES.

The invention discloses a multifunctional broadband metamaterial structure with a polarization independent characteristic and a control method. The structure has a switchable tri-state function and a complete polarization operation capability irrelevant to polarization. By introducing the guide circuit design, three different electromagnetic energy regulation and control modes of second-order filtering, broadband absorption and multi-reflection shielding are efficiently integrated in the same structure, the real broadband performance in the band is realized, and meanwhile, the higher reflection efficiency outside the band is kept. Different from a traditional method which depends on a broadband lossless reflecting layer to expand the transmission bandwidth of an absorption structure, the three arrays are considered as an integral operating system, support three-state switching operation and have real broadband and efficient behaviors.

The invention relates to the technical field of electrochemical energy storage application, and discloses a load power prediction-based user side energy storage operation regulation method, which comprises the following steps of: acquiring load power and energy storage power in a sampling period, calculating a load prediction value at the end of a next period according to the initial load power and the end load power in the period, establishing a historical load extreme value database, and executing an asymmetric condition updating rule, namely, performing online correction on the database according to different comparison conditions in a charging mode and a discharging mode; an adjusting instruction is generated according to the capacity constraint of the transformer in the charging mode, and an adjusting instruction is generated according to the anti-countercurrent threshold constraint in the discharging mode. Preventive measures for two different operation risks of charging overload and discharging countercurrent are unified in a continuous control process with online self-learning capability according to system operation state switching adjustment reference and boundary conditions, and the economical efficiency and the safety of operation are both considered.

Circuits defined by n-state switching tables with n>2 are transformed by at least one n-state inverter which may be a Finite Lab-transform (FLT) into a Finite Lab-transformed (FLTed) n-state switching devices. Computer operations defined by transformed or modified n-state switching tables are applied in cryptographic operations, including one or more message digests or hashing methods or computer one-way functions. A keyword is generated from a public keyword by at least one modified known hashing method. A known hashing method may be selected from the group consisting of SHA-1, SHA-2, SHA-3, MD5, MD6, Blake2, Blake3 and CubeHash. Internal states of known hashing methods are modified to generate unpredictable hash values.

The invention discloses a data path switching method of a Retimer controller and a Retimer chip, and belongs to the field of communication. In order to reduce the risk of timeout of RC and EP in a balance stage, the method for switching the data path of the Retimer controller comprises the following steps: when the Retimer controller simultaneously meets the condition that any channel of an uplink pseudo port and a downlink pseudo port respectively detects eight continuous TS2 sequences with speed fields of 1, the public maximum rate is PCIe Gen6 and is greater than the current rate, and the Retimer controller is in an FLIT mode and a stateful state, setting the start field to 1. And after the negotiation is completed, the RC controller, the EP controller and the Regimer controller enter a recovery. Speed state to switch the speed, and the switching from PCIe Gen5 to Gen6 is completed. And after switching, the Retimer and the EP are switched to a recovery. Phase0 state, the RC is switched to a recovery. Phase1 state, and when the Retimer controller is in the recovery. Phase0 state, a code stream generation module generates a TS0 sequence and sends the TS0 sequence to the RC and the EP. The method is applied to the PCIe field, and the robustness of RC and EP in the balancing process is improved.

The invention discloses a pet behavior data management system and method based on big data, and relates to the technical field of pet behavior intelligent monitoring. Performing time synchronization and time sequence reconstruction; carrying out preprocessing, and carrying out key frame extraction and target detection on the video frame to obtain a pet posture track; on the basis of a state switching point of a hidden Markov model, dividing the data subjected to time sequence reconstruction into a plurality of behavior events, and combining adjacent related behavior events to form behavior blocks; extracting statistical characteristics, behavior frequency and context characteristics of each behavior block, and training an individual behavior baseline model by adopting a multi-scale sliding window and a weight attenuation strategy based on historical behavior data; and comparing the real-time behavior block with the individual behavior baseline, and carrying out anomaly monitoring and warning through an integrated classifier. According to the invention, cross-device pet behavior management and abnormal early warning can be realized, and the reliability and the intelligent level of pet health monitoring and behavior analysis are remarkably improved.

The invention provides a communication module state switching method and system based on event triggering, and relates to the technical field of communication.The method comprises the steps that firstly, multi-source event source information in operation of a communication module is collected, and event influence hierarchy division is conducted; a target association network is generated by combining a current operation state and a historical state switching database of the communication module; generating a dynamic path including a hardware parameter adjustment sequence and the like based on the target association network and the historical stability record; pre-judging the stability of the dynamic path; generating a state switching execution instruction according to the pre-judgment result and generating switching process data; and finally, updating the historical state switching database and the target association network based on the switching process data to form closed-loop optimization, thereby realizing dynamic optimization of communication module state switching, and improving adaptability and stability of switching.

Systems and methods include an Information Handling System (IHS) that is adapted to address power state transition failures by an IHS. An Embedded Controller (EC) of the IHS detects a request for the IHS to transition to a low-power operating state, such as a modern standby power state. The EC monitors for progress of the IHS in transitioning to the low-power operating state. Based on the monitoring, the EC determines the SoC is preventing the transition by the IHS to the low-power operating state. The EC identifies and releases hardware resources of the IHS that are referenced by the SoC and that are preventing the transition of the IHS to the low-power operating state.

The invention relates to the technical field of electric power simulation, and discloses an electric power system data parallel simulation processing method based on distributed modeling. The method comprises the following steps: acquiring voltage, frequency and power parameters of a new energy inverter and an energy storage converter, and generating a state switching feature vector through a fuzzy C-means algorithm; determining and calculating a load abrupt change subsystem according to the load index overrun, and calculating the electrical coupling strength with an adjacent subsystem; allocating reserved computing resources for the mutation subsystem through a particle swarm optimization algorithm to form a dynamic resource allocation table; and adjusting the data synchronization period of the mutation subsystem to an extended time window, and continuing parallel simulation after the adjacent subsystems wait for boundary data. According to the method, the problems that in an existing power system data parallel simulation processing method based on distributed modeling, the calculation load abrupt change and the data synchronization failure caused by strong nonlinear component state switching cannot be processed are solved.

The invention provides a DPU-based remote direct memory access queue pair state machine implementation method and device, and the method comprises the steps: creating a flag bit, and setting the value of the flag bit according to each state of a queue pair state machine, so as to achieve state switching; creating a queue pair, and entering a reset state; configuring attributes of a queue pair, and switching to an initialization state; setting parameters of a receiving end, and switching to a ready receiving state; establishing communication connection, setting parameters of a sending end, switching to a ready-to-send state, and executing remote direct memory access operation so as to perform data transmission; if all the data in the sending queue is sent, switching to a sending completion state; if the sending queue has an error, switching from a sending preparation state or a sending completion state to a sending error state; if the queue pair has an error, switching from the current state to the queue pair error; and switching to a reset state after processing an error. According to the method, the flexibility and expansibility of the system are improved, and the processing efficiency of error and abnormal conditions is improved.

An EMLSR-active non-AP MLD desires to initiate a frame exchange with the AP MLD over one of the EMLSR links. A first link is chosen and the corresponding “first” affiliated STA invokes and starts an EDCA backoff procedure that decrements one or more backoff counters, to access the first link. Alternatively, each EMLSR co-affiliated STA may invoke an EDCA backoff procedure to access their respective link. In embodiments, the first affiliated STA is switched from a listening operation state to an enabled frame exchange state, before invoking the EDCA backoff procedure. In other embodiments, the first affiliated STA first invokes the EDCA backoff procedure, and is switched to the enabled frame exchange state when the backoff counter expires. A corresponding state switching procedure may be invoked so that it ends with the expiry of the backoff counter, or responsive to an expiry of the backoff counter.

The invention provides a backhaul difference compensation system, method and device, a head-up display device and a storage medium, and belongs to the technical field of HUD display control, and the backhaul difference compensation system comprises a stepping motor which is configured to drive a movable assembly of an HUD to move; the measuring unit is configured to perform state switching under the pushing of the movable assembly; the controller is configured to count the actual movement step number of the stepping motor in the process that the movable assembly pushes the measuring unit to be switched from the first state to the second state, and signals corresponding to the first state and the second state are opposite; and based on the actual motion step number and the theoretical motion step number, the return stroke difference of the stepping motor is determined, and the theoretical motion step number is the theoretical demand step number of the stepping motor when the measuring unit is switched from the first state to the second state. According to the embodiment of the invention, the backhaul difference can be dynamically calibrated in each power-on or specific period of the HUD, and the positioning precision is improved.

The invention provides a data transmission method and device, a request end, a response end and a storage medium, and the method comprises the steps: transmitting an RDMA connection request to the response end, and creating a main QP and a standby QP; establishing an RDMA connection with the response end based on the main QP, and synchronizing information of the main QP to the standby QP; in response to the fact that the main QP is detected to be abnormal, performing state switching on the main QP and the standby QP; generating a switching notification message based on the configuration information of the standby QP, and sending the switching notification message to a response end; and receiving confirmation information sent by the response end, and performing data transmission with the response end based on the standby QP. According to the embodiment of the invention, when the RDMA connection is established, the main QP and the standby QP are created at the same time, and when the main QP is abnormal, the standby QP is seamlessly switched to carry out data transmission, so that the connection fault recovery time is shortened, and the reliability of the RDMA connection is enhanced.

The invention relates to the technical field of computer data processing and network security, in particular to an illegal character automatic cleaning system, which comprises a rule compiling module for monitoring rule change, performing semantic fusion and topological mapping on a rule set, constructing a deterministic finite automaton and mapping the deterministic finite automaton into a state transition table; the state switching module is used for constructing a double-buffer context and operating lock-free switching through an atomic pointer to realize hot updating; the speculation execution module is used for carrying out vectorization pre-scanning based on a state transition table by utilizing single-instruction multi-data stream parallel loading, identifying a walk path, falling into a safe state for releasing and falling into a trap state for triggering external verification; the self-adaptive feedback module is used for counting trap state triggering frequency, generating a rule allergy report and dynamically adjusting the size of a read fragment; according to the method, the contradiction between rule flexibility and execution efficiency is solved, and high-performance cleaning based on speculative execution is realized.

The invention relates to the technical field of intelligent control, and discloses a state switching-oriented reinforcement learning discrete-continuous hierarchical decision-making architecture and method, and the method comprises the steps: constructing a hierarchical discrete-continuous decision-making architecture, obtaining a state value function and a discrete action value function through a Critic network, separating a continuous action decision-making evaluation system from a discrete action decision-making evaluation system, and carrying out the state switching-oriented reinforcement learning discrete-continuous hierarchical decision-making evaluation system. The coupling between the two is reduced; then discrete actions serve as enabling conditions of continuous parameters, it is ensured that relevant continuous control channels are thoroughly blocked when discrete decisions are not activated, and therefore action instruction conflicts are avoided; a variable gating matrix is constructed based on the discrete decision quantity, gradient propagation paths of corresponding neurons are directly cut off through the gating matrix, specific shielding parameters of discrete actions during switching of two modes are distinguished, and then continuous control quantity decision of mode switching is executed. Therefore, the problems of coupling conflict and efficiency bottleneck in mixed action space processing are effectively solved.

A power consumption prediction and management method and system based on a solid state disk, a medium and a product relate to the field of solid state disks. The method comprises the following steps: predicting the workload intensity of a host in a first preset time window based on an I / O (Input / Output) instruction stream to obtain an expected host workload curve, and determining an expected host idle time period; calculating an expected host power consumption value in the expected host idle time period; extracting internal state parameters of the solid state disk according to the historical operation log data; establishing a background task triggering probability model, and calculating the triggering probability of starting the high-power-consumption background task by the solid state disk in a first preset time window; performing power consumption conflict judgment according to the expected host power consumption value and the triggering probability, and generating a comprehensive predicted power consumption value; and based on the comprehensive predicted power consumption value, determining an optimal target power consumption state, and instructing the solid state disk to be switched to the optimal target power consumption state. By implementing the technical scheme provided by the invention, the stability of state switching of the solid state disk is improved.

The invention provides a communication method, terminal equipment and network equipment. The method comprises: a terminal device receiving first information sent by a network device, the first information being used for triggering receiving or sending of a target signal, the target signal comprising one or more of the following: an uplink reference signal; a downlink reference signal; a CSI; wherein the first information is sent by the network equipment in an uplink random access process; or the first information is sent by the network equipment in the process that the auxiliary cell is activated or quits the dormant state. The first information used for triggering the uplink reference signal, the downlink reference signal or the CSI is transmitted in advance to an uplink random access process, an auxiliary cell activation process or an auxiliary cell quit a dormant state, so that the signals are transmitted as early as possible, the transmission delay of the signals is reduced, and the transmission efficiency is improved. And the time delay from the state switching of the terminal equipment to the channel detection is shortened, so that the network decision is facilitated.

The invention discloses an equipment energy consumption simulation prediction method and system based on a discrete manufacturing system and a storage medium, and the method comprises the following steps: S1, collecting the average power data of all process equipment in the discrete manufacturing system under each state and during the conversion of different states, and constructing an equipment power database; s2, collecting process and logistics information of a workshop; s3, integrating the equipment power database into the simulation model, and calling corresponding power data in the equipment power database according to the process equipment operation state determined by simulation; s4, inputting production parameters, operating the simulation model, and calculating an energy consumption prediction result; according to the method, the state switching energy consumption can be quantified, and accurate calculation of multi-process equipment energy consumption under various production scenes is supported.

A method of quality of experience (QoE) measurement and reporting, includes: receiving, by a user equipment (UE), a first radio resource control (RRC) message comprising first configuration parameters of a first QoE configuration and second configuration parameters of a second QoE configuration; receiving, by the UE, an RRC release message indicating transitioning of the UE from an RRC connected state to an RRC inactive state, wherein the UE is in a connected state when the RRC release message is received; receiving, by the UE, from a second BS, an RRC resume message indicating transitioning of the UE from the RRC inactive state to the RRC connected state, wherein the UE is in an inactive state when the RRC resume message is received; and in response to receiving the RRC resume message, releasing the first QoE configuration and resuming the second QoE configuration.

The embodiment of the invention provides an auxiliary card searching module and method and near field communication equipment. Wherein the auxiliary card searching module comprises a pulse detection unit, a control unit and a modulation unit; the control unit is respectively connected with the pulse detection unit and the modulation unit; the pulse detection unit is used for generating a trigger signal within a preset duration based on a response signal of an equipment antenna of the slave equipment; the response signal is generated by the device antenna of the slave device in response to a radio frequency signal sent by the master device; the preset time length is smaller than the pulse time length of a radio frequency signal sent by the main equipment; and the control unit is used for controlling the modulation unit to perform state switching according to the trigger signal so as to promote the main equipment to enter a polling mode.

The invention relates to the technical field of resource scheduling, in particular to an AI-assisted multi-factory collaborative production scheduling system which comprises a path filing module, a task sorting module, a strategy switching module, a node evaluation module and a task mapping module. According to the invention, the device sharing node is identified through the transverse connection of the device and the path node, the resource cross interference degree is effectively mastered, the task priority is accurately adjusted, the coordination of resource allocation and task execution is optimized, and the flexible adjustment capability in the task execution process is improved; node resource state switching and fluctuation changes are dynamically monitored, abnormal node load and processing time features are accurately extracted, a path replacement strategy is finely judged in combination with equipment shutdown time sequence analysis and resource residual feature classification, and the flexibility and adaptability in multi-factory collaborative production scheduling are enhanced. Equipment faults and state fluctuation are pre-judged, and a path strategy is adjusted, so that the risk of task delay caused by production rhythm fluctuation and resource interference is effectively reduced.

Wireless communications may use one or more devices for transmission and / or reception that may lead to potentially harmful exposure. One or more safety measures may be used for wireless communication devices, such as maximum power exposure (MPE) reporting and / or related operations. An MPE report may be sent based on MPE detection and one or more messages, such as for cell activation, bandwidth part (BWP) or other wireless resource activation and / or switching, and / or a discontinuous reception (DRX) or other state transition.

The invention relates to the technical field of robot intelligent control, and discloses an inspection robot task scheduling and state switching method for quantifying a state machine, which comprises the following steps: acquiring state machine operation configuration data; performing health degree evaluation on the sensor, navigation, communication and battery systems in an initial state; in the idle state, a segmented charging strategy is adopted, and task priorities are calculated through a neural network; a breakpoint resume and event-driven architecture is adopted to execute tasks in the inspection state; in a warehouse returning state, a deep neural network is adopted to predict return flight energy consumption, and a path is re-planned through multi-objective optimization when the electric quantity is insufficient; processing a control instruction by adopting speed limitation in a manual or mapping state, and starting an SLAM module in the mapping state; and in an abnormal state, a fuzzy logic reasoning system is adopted to calculate an abnormal grade, and recovery waiting, degradation protection or alarm is executed according to the grade. According to the invention, autonomous operation and intelligent decision making of the inspection robot in a complex dynamic environment can be realized.

This disclosure provides a state switching method, apparatus, and electronic device. The state switching method includes: generating and maintaining a state switching signal when a preset state switching condition is met; switching the state of a target object using the state switching signal; calculating the time interval between the current time and the end time of a synchronization alignment signal; the synchronization alignment signal is a signal applied to the target object earlier than the state switching signal; and ending the state switching signal when the time interval meets a preset condition, thus completing the state switching of the target object; the preset condition includes the time interval being an even multiple of a first clock cycle. This embodiment ensures that the output signal of the target object after state switching is synchronized with the synchronization alignment signal, solving the problem of timing disorder and improving circuit performance.

The invention relates to the technical field of tea processing, and discloses a tea processing auxiliary method and system based on intelligent decision making. The method comprises the following steps: acquiring a multi-source sensor data stream of tea processing equipment in real time, and identifying a critical time point of processing state switching; intercepting time window data by taking a critical point as a center, performing empirical mode decomposition on channel data of each sensor, extracting an intrinsic mode function component, calculating a sample entropy value, and constructing a multi-channel entropy value characteristic matrix; inputting the matrix into a graph attention network, learning a spatial dependency relationship between sensor channels, and outputting a graph embedding representation of a processing state; calculating an abnormal score and generating a processing quality deviation index; analyzing the influence of processing parameter adjustment on a quality index by adopting a gradient lifting decision tree model, and determining the contribution weight of a key sensor channel; high-weight sensor data are integrated, dynamic segmentation is carried out, timing sequence characteristics are fused by applying a gating circulation unit network, and an accurate processing control decision is output.

The invention discloses a large model adaptive security detection method and system based on four-order linkage, and the method achieves the security detection of the output content of a large model through four-stage collaborative linkage: in the context consistency reasoning stage, calculating the semantic consistency score of a generated text, a multi-round dialogue history, a user prompt word and an external knowledge base; marking a potential risk; in the causal chain risk detection stage, modeling multiple rounds of dialogues into a causal graph, calculating a risk path probability, matching an attack pattern library, and marking high risks; in the dynamic game optimization stage, a game space of a detector and an attacker is constructed, an optimal detection threshold value is solved, and parameters of each stage are linked and updated; in the cycle state switching stage, switching is carried out between a low-power-consumption monitoring state and a dynamic updating state according to system performance and a risk situation, and a risk level is output by integrating results of the four stages. According to the method, the problems of low hidden attack detection rate, high false alarm, risk non-traceability and resource waste in the prior art are solved, and self-adaption, low false alarm, traceability, high efficiency and energy conservation are realized.

The invention relates to a real-time eye identification and visual detection process control method, which comprises the following steps of: applying bitamporal edge disturbance stimulation in a visual field, inducing spontaneous dominant reaction of a dominant eye of a user, collecting perceptual response difference of a non-gazing area to the disturbance stimulation, and judging the current dominant state of the dominant eye; on the basis of micro-differential pressure distribution of different quadrant areas of eye sockets, speculating a visual attention gravity center in real time, and executing spatial geometric deformation on an ROI (Region of Interest) in a visual detection process, so that a detection area dynamically adapts to a gaze offset trend of a user; the method comprises the following steps: respectively constructing two physically independent visual detection links of a feature target strong discrimination process driven by a main visual eye and an environment contour weak confirmation process driven by an auxiliary visual eye, introducing a logic thermal impedance adjustment mechanism, and setting a buffer time window to absorb processing fluctuation caused by state switching; and dynamically matching a visual detection flow path by constructing a mapping relationship between the eye dominant frequency and the user intention type on the basis of statistical information of the dominant eye identification frequency.

The invention relates to a trigger unit. The trigger unit comprises a first comparison feedback circuit, a first clock gating circuit, a master latch and a slave latch assembly, the first comparison feedback circuit is used for detecting a signal hopping state of an external input signal according to a first output signal output by the output end of the main latch, and generating a corresponding first state feedback signal, so that the first clock gating circuit generates a corresponding first gating clock signal according to the first state feedback signal and a reference clock signal, and sends the first gating clock signal to the second clock gating circuit; under the condition that the first gating clock signal is valid, the main latch is controlled to update the first output signal according to the external input signal; the state switching opportunity of the main latch can be accurately controlled, and unnecessary clock flipping in the trigger and transistor switching activity caused by the unnecessary clock flipping are effectively reduced, so that dynamic power consumption related to a clock network and dynamic power consumption generated by flipping of nodes in a data path are effectively reduced.

Described herein is a A User Equipment, UE, comprising: at least one processor, and at least one memory storing instructions that, when executed by the at least one processor, cause the UE at least to: receive, before or when entering a Radio Resource Control, RRC, inactive state, from a network node, configuration information associated with a plurality of candidate cells for the UE to perform a Random Access Channel less, RACH-less access, the configuration information being further associated with a state transition of the UE from the RRC inactive state to an RRC connected state, wherein the plurality of candidate cells comprises a last serving cell of the UE before the state transition and / or one or more neighboring cells of the last serving cell, wherein the configuration information comprises Timing Advance related, TA-related configurations for determining a Timing Advance, TA, value at least for a target cell from the plurality of candidate cells, wherein the target cell is the last serving cell or one of the neighboring cells, wherein the UE is further configured to, while in the RRC inactive state: determine to transition from the RRC inactive state to the RRC connected state in response to an indication relating to data associated with the target cell; determine, for the target cell, the TA value based on the TA-related configurations; and perform the RACH-less access to the target cell based on the determined TA value for the target cell.