5703 results about "Current time" patented technology

An example operation may include one or more of storing transaction content from transactions executed via one or more fiat payment accounts and one or more crypto accounts of a digital wallet of a user, and determining, via execution of a machine learning model on the stored transaction content, a recurring expense value of the user and a next point in time in which the recurring expense value, dividing the recurring expense value into a plurality of sub-values; generating a plurality of transactions which transfer the plurality of sub-values from a fiat payment account to a crypto account from among the one or more crypto accounts and store the plurality of transactions within a queue, initiating a plurality of time-to-live jobs for the plurality of transactions, respectively, wherein the plurality of time-to-live jobs comprise a plurality of different respective expiration times that are staggered such that the plurality of time-to live jobs expire in incremental intervals from a current time to the next point in time in which the recurring expense value is due and executing the plurality of transactions at the plurality of different expiration times to incrementally transfer the plurality of sub-values from the fiat account to a crypt account via an application programming interface (API).

The present disclosure generally describes user interfaces related to time. In accordance with embodiments, user interfaces for displaying and enabling an adjustment of a displayed time zone are described. In accordance with embodiments, user interfaces for initiating a measurement of time are described. In accordance with embodiments, user interfaces for enabling and displaying a user interface using a character are described. In accordance with embodiments, user interfaces for enabling and displaying a user interface that includes an indication of a current time are described. In accordance with embodiments, user interfaces for enabling configuration of a background for a user interface are described. In accordance with embodiments, user interfaces for enabling configuration of displayed applications on a user interface are described.

This application provides a service widget display method, an electronic device, and a storage medium. The method includes: receiving a first operation of a user in a first state; displaying a first service widget in response to the first operation, where the first service widget includes a first target service; receiving a second operation of the user in a second state; and displaying a second service widget in response to the second operation, where the second service widget includes a second target service; and the first target service is different from the second target service, and one or more of the following information of the electronic device in the first state and the second state are different: a current location and current time of the electronic device.

The invention discloses a bus duct trend analysis early warning method and system and a storage medium, and relates to the technical field of data processing. The method comprises the following steps: determining N bus duct key positions, and arranging sensor groups on the N bus duct key positions respectively to obtain a sensor monitoring network; acquiring N pieces of temperature time sequence data and N pieces of current time sequence data; performing temperature difference calculation and current change rate calculation on the N pieces of temperature time sequence data to obtain N key position temperature change rates and N key position current change rates; carrying out integration trend analysis, and determining a bus duct abnormal operation trend result; and constructing an alarm mechanism, triggering the alarm mechanism based on a bus duct abnormal operation trend result to carry out classification matching, determining operation early warning parameters, and carrying out operation early warning control on the target bus duct. The technical problems of inaccurate monitoring of the running state of the bus duct and untimely early warning in the prior art are solved, and the technical effect of improving the accuracy and timeliness of running monitoring of the bus duct is achieved.

The invention discloses an index alarm method, system and device based on a dynamic baseline and a medium, and the method comprises the steps: collecting software and hardware operation index data, and carrying out the periodic statistics at a preset time interval; wherein the index data comprises real-time data and historical data; preprocessing the historical data; dynamically generating a baseline range based on the preprocessed historical data, and adaptively adjusting along with the periodic fluctuation of the historical data to reflect the index change trend of different time periods; the index data monitored in real time are compared with the dynamic baseline range of the current time period, the alarm boundary is calculated in combination with a preset tolerance threshold value, and the tolerance threshold value is the percentage offset of the baseline value; when the real-time data exceed the alarm boundary, triggering an alarm and generating notification information, and sending the notification information to the operation and maintenance terminal through a preset communication mode; and continuously optimizing the dynamic baseline according to newly added historical data, updating baseline parameters through a machine learning algorithm, and realizing self-adaptive iterative adjustment of an alarm threshold.

The present invention relates to the technical field of computers, and provides a log processing method and system, a log management platform, and an electronic device. The method comprises: acquiring real-time log data of each service system, and storing the log data in a message queue; according to a preset time window, writing the log data in the message queue into a target file of a specified storage directory; and in response to completion of data writing of a current time window, on the basis of the storage directory of the target file, calling a log analysis interface of a log analysis service to perform log analysis on the target file. The log processing method in the present invention reduces the risk incident rate of service systems, and improves the localization accuracy of an anomaly condition of a service log.

The invention provides an electronic book file secondary encryption method based on MD5 encryption and an asynchronous request, and relates to the field of data processing. Comprising the following steps: firstly, acquiring a current timestamp, a network state, a user request attribute and a system load state through a data acquisition module, and then performing MD5 preliminary encryption on an electronic book file to generate a first layer of ciphertext; segmenting the first-layer ciphertext and transmitting the segmented first-layer ciphertext to an encryption module through an asynchronous request; a self-adaptive distributed load balancing mechanism is adopted to monitor the system state through an encryption module, resources are dynamically allocated, and tasks are scheduled; in combination with intelligent priority scheduling, determining the priority according to the attributes of the data segments; generating a dynamic key based on a timestamp, a network state and the like to encrypt the data segment in real time; and finally, sorting, checking and combining the encrypted data segments into a complete ciphertext file.

A computing device can identify an anomaly based on metadata associated with network traffic messages corresponding to a particular account. After identifying the anomaly, the computing device can determine a failure score for the network traffic messages representing a failure rate for the message traffic. The computing device can determine a fluctuation score by comparing the network traffic messages in a current time period to a previous time period. The computing device can determine a sparsity score by analyzing the message traffic in a previous period of time. The computing device can generate an anomaly impact score based on the failure score, the fluctuation score, and the sparsity score and assign the anomaly to a severity bin based on the anomaly impact score.

The invention relates to the technical field of Internet of Things security, and provides a security authentication method and system for an Internet of Things device, a medium and a device, and the method comprises the steps: responding to an authentication request of the Internet of Things device, the authentication request comprising a unique identifier, a current timestamp and a comprehensive feature vector of the Internet of Things device; after the current timestamp and the comprehensive feature vector are connected, generating a random challenge value through a random function and sending the random challenge value to obtain a returned Internet of Things equipment response value; after the authentication key, the comprehensive feature vector and the random challenge value are connected, an expected response value is generated through a secure hash function, and whether the Internet of Things equipment is successfully authenticated or not is judged through comparison; and if the authentication is successful, generating a session key, connecting the authentication key with the session key, and updating the authentication key through a secure hash function. The common security threats such as replay attack and man-in-the-middle attack are effectively prevented, and the uniqueness and security of each authentication are ensured.

The invention discloses a virtualized container environment monitoring device and method based on eBPF, and aims to solve the problems of poor isolation, insufficient security and platform adaptation deficiency in a virtualized container environment. According to the method, time sequence data of monitored events in a virtualized container environment are collected in real time through an eBPF technology, the time sequence data are transmitted to a data analysis module through eBPF mapping and message queues, data are analyzed through a long-short-term memory network, the deviation degree of the current time sequence data and historical data is calculated, abnormal behaviors are judged, and an alarm is given. According to the method, the user-defined program is operated under the condition that kernel codes do not need to be modified, intelligent analysis and abnormal behavior recognition are conducted on the collected data, comprehensive monitoring and dynamic detection of complex threats are achieved, the safety, stability and compatibility of the system are improved, and the method is suitable for virtual environments under cloud computing and big data scenes.

The present disclosure generally relates to real-time communication user interfaces. A computer system displays a user interface corresponding to a real-time communication application that includes concurrently displaying a first user interface object corresponding to a first real-time communication session between a user of the computer system, where the first real-time communication session occurred prior to a current time, and a second user and a second user interface object corresponding to a second real-time communication session between the user of the computer system and a third user, where the second real-time communication session is scheduled to occur at a time after the current time. In response to receiving user input corresponding to a respective user interface object of the user interface, the computer system initiates a real-time communication session.

The invention discloses an air conditioner control method and system, electronic equipment and a storage medium, and relates to the field of air conditioner control. The method comprises the following steps: determining an energy-saving award coefficient and a comfort award coefficient according to a current time period and a current season; constructing an energy-saving award function according to the energy-saving award coefficient, constructing a comfort award function according to the comfort award coefficient, and constructing an instant award function according to the energy-saving award function, the comfort award function and a punishment mechanism; state data and action data of operation of the air conditioner are obtained, the state data comprise the indoor temperature, the outdoor temperature and the temperature, the mode and the air speed set by a user, and the action data comprise air speed adjustment, mode adjustment and temperature adjustment; and the optimal action of the next state is determined according to the state data, the action data and the instant reward function, and the operation parameters of the air conditioner are adjusted according to the optimal action. By implementing the technical scheme provided by the invention, a more efficient and environment-friendly air conditioner control method is provided.

The invention provides a charging facility anomaly detection method and device, equipment and a storage medium, and relates to the technical field of electric vehicle charging, and the method comprises the steps: obtaining first charging power data when a target charging pile charges a target vehicle within a preset duration before a current moment, and obtaining a charging facility anomaly detection result according to the first charging power data; calculating a first stability index of the target charging pile; environment parameters of the target charging pile at the current moment are obtained, the first stability index is adjusted according to the environment parameters, and a second stability index is generated: second charging power data of related charging piles sharing the same power supply loop with the target charging pile within the preset duration are obtained, and a load influence index is generated according to the second charging power data; adjusting the second stability index according to the load influence index to generate a target stability index; and when the target stability index exceeds a preset index, determining that the target charging pile is abnormal at the current moment. The technical effect of the invention is that the accuracy of anomaly detection is improved.

The invention relates to an electric power internet of things operation and maintenance management method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining sensor data, carrying out the cleaning and time alignment of the sensor data, and obtaining standard operation data; based on a historical data window corresponding to the standard operation data, calculating a mean value and a standard deviation of the historical data, and further generating a dynamic detection threshold value; comparing the standard operation data of the current time node with a dynamic detection threshold value, and screening out potential abnormal data; calculating an abnormal trend factor corresponding to the potential abnormal data, and determining an abnormal development trend of the potential abnormal data according to the abnormal trend factor; and determining a corresponding causal influence weight based on a preset causal relationship network, and calculating a fault score according to the causal influence weight and the abnormal trend factor, so as to generate an early warning report according to the fault score. The method has the effect of improving the management efficiency of the power equipment.

The invention relates to the technical field of data processing, in particular to a distributed automobile liquid cooling over-charging control method and system, and the method comprises the steps: merging the operation information of an over-charging network and the real-time charging parameter information in a current time period, and obtaining the merged information; performing internal weight focusing distribution on the merged information to obtain temporary vector representation, and performing multi-target decision prediction according to the temporary vector representation to obtain target charging scheduling strategy information of one or more layers; and according to the target charging parameter information determined by adopting the target charging scheduling strategy information, starting to perform charging scheduling decision on the overcharge charging demand in a time period after the overcharge management of the charging pile. The priority judgment is carried out on different types of charging parameter information and over-charging network operation information based on the internal weight focusing strategy, so that the effect of advanced features is expanded, and the scheduling effect can be improved when the output target charging scheduling strategy information is used for the charging scheduling decision in the next time period.

The invention discloses a UKEY-based network submission method and system and a storage medium, and relates to the technical field of information security, and the method comprises the steps: receiving a login authentication request sent by a mechanism end; after verification, generating authentication information containing an organization number and a current timestamp; generating a session identifier, and integrating the session identifier, the organization number and the current timestamp to generate secret key negotiation reference data; encrypting the key negotiation reference data to obtain first encrypted data; receiving second encrypted data, and generating a symmetric encryption key according to the first encrypted data and the second encrypted data; receiving the encrypted data packet encrypted by the mechanism end by using the symmetric encryption key, and decrypting the encrypted data packet by using the symmetric encryption key to obtain submitted data; and after the validity of the submitted data is confirmed according to the session identifier, storing the submitted data into a preset database, and returning storage confirmation information to the mechanism end. By implementing the application, the security of network submission can be improved.

The invention provides an asynchronous service deployment method and device for an edge cloud network, and the method comprises the steps: checking whether a current time slot meets a layer cache updating condition or not in response to a deployment request for a target micro service received in the current time slot; if not, for any deployable node, scheduling the scheduling information of any required mirror image layer and the data access rate between the nodes from any other node according to the mirror image layer required by the target micro-service, the memory space of the corresponding mirror image layer and the micro-service deployment information under the current time slot; and constructing a total layer loading time function that the target micro-service is deployed on the node and changes along with the time slot, so as to construct a service utility function that corresponds to the node and changes along with the time slot in combination with profit information and starting cost of the node, thereby determining a deployment strategy of the target micro-service, and starting the target micro-service based on a mirror image layer required by the target micro-service. The method effectively balances the service performance and the resource utilization rate.

The invention discloses an inner draught fan control method and device, equipment, a medium and a computer program product, and relates to the technical field of inner draught fans, and the inner draught fan control method comprises the steps that a historical reward value obtained after an inner draught fan executes a first state adjustment action of the last time step is obtained; the first state adjustment action is an action determined based on an empirical value in a previous preset empirical value table; on the basis of the historical reward value and the environment state of the inner fan in the current time step, an empirical value in a previous preset empirical value table is updated; and based on a target empirical value corresponding to the environment state of the current time step in the updated current preset empirical value table, controlling the inner fan to execute a second state adjustment action of the current time step so as to adjust the current state parameter value of the inner fan to a target state parameter value corresponding to the target empirical value. By introducing reinforcement learning, the inner fan can continuously interact with the environment and accumulate experience, so that the optimal control scheme under different working conditions is learned, and the self-adaptive control of the state of the inner fan is realized.

The invention provides a sensitive information detection method and content display method in a question and answer scene, and the method comprises the steps: obtaining the current output information of a large language model, and storing the output information to a preset buffer area; wherein the output form of the output information is streaming output; taking the output information and original information stored in a preset buffer area as a current to-be-processed text; in response to the fact that the data length of the current to-be-processed text exceeds a preset length, taking the current to-be-processed text as a target detection text; wherein the preset length is determined according to a pre-constructed sensitive word library; and performing sensitive word detection on the target detection text to obtain the detection result, thereby improving the detection speed of the sensitive information, reducing the waiting time of the user and improving the user experience.

The invention provides a battery state prediction method and system, computer equipment and a storage medium, and the method comprises the steps: randomly selecting a preset proportion of batteries from a target batch of batteries as a test sample set; performing current switching cycle life test on each battery sample to obtain a plurality of groups of current sudden change data comprising current time sequence data, voltage time sequence data and battery health state corresponding to the preset charge state segment point sequence; obtaining a current abrupt change point battery impedance spectrum according to the current time sequence data and the voltage time sequence data in each group of current abrupt change data, and constructing a battery state prediction model according to all the current abrupt change point battery impedance spectrums and the corresponding battery health states; and obtaining a battery state prediction value according to the obtained current mutation battery impedance spectrum of the to-be-evaluated battery and the battery state prediction model. According to the invention, the high efficiency, accuracy and operation convenience of online monitoring of the health state of the battery can be effectively improved under the low-cost condition of not additionally adding measuring equipment.

The embodiment of the invention discloses a control method, a training method, a control assembly and a robot, the control method is applied to the robot, and the control method comprises the steps of determining a first interaction pose for a to-be-interacted object based on an image of an environment where the robot is located; generating a splicing feature of the current time step based on an output instruction of the previous time step and the first interaction pose; inputting the splicing feature of the current time step and the splicing feature of at least one historical time step into a trained attribute prediction module to obtain an attribute feature; the attribute features are used for representing attribute data, related to interaction influence, of the to-be-interacted object; and inputting the attribute features and the splicing features of the current time step into a trained reinforcement learning module to obtain an output instruction of the current time step. In this way, the reinforcement learning module can better understand the intrinsic characteristics of the object, and has high generalization ability when processing unseen objects.

The invention discloses a downlink resource scheduling method and device for a 5G differentiated scene and a storage medium. The method comprises the following steps: acquiring information, wherein the information comprises time slot network state information of each time slot; converting the information into historical state track information; the historical state track information serves as input vectors to be input into a DQN neural network and a TD3 neural network respectively, and core parameters are output; respectively training a DQN neural network and a TD3 neural network according to the historical state trajectory information and the core parameters to obtain a trained DQN neural network and a trained TD3 neural network; the time slot network state information of the current time slot serves as a current input vector to be input into the trained DQN neural network and the trained TD3 neural network, and a current core parameter is output; calculating the priority of each user for each resource block based on a priority formula of a heuristic algorithm according to the current core parameter; and performing resource scheduling on the resource blocks based on a greedy strategy according to the priority. According to the method, the defects of a traditional priority-based scheduling algorithm in a complex network environment are overcome.

The invention discloses a dynamic tension control method for a dry-method winding and unwinding system, solves the problems of high overshoot, long coil diameter sudden change adjustment time and large steady-state fluctuation in low-speed operation of the dry-method winding and unwinding system under a high-speed reversing working condition, and belongs to the technical field of composite material equipment development. The method comprises the steps of collecting data of a winding and unwinding system, identifying total rotational inertia and friction torque on line according to the data, obtaining a friction compensation item according to the friction torque, and obtaining a rotational inertia feed-forward item according to the total rotational inertia; the method comprises the following steps of S1, inputting the tension error and the tension error change rate of the winding and unwinding system into a fuzzy PID controller to obtain a PID parameter real-time adjustment amount, updating a PID parameter, and then obtaining a PID feedback control amount at the current moment k by using the PID controller and the tension error, and S3, synthesizing a friction force compensation item, a rotational inertia feed-forward item and the PID feedback control amount into a final control amount of the winding and unwinding system.

The invention relates to the technical field of circuit monitoring, in particular to an intelligent sensing and identifying method for circuit faults of a semiconductor hybrid solid-state circuit breaker. Obtaining a fluctuation abnormal moment according to the amplitude characteristic and the continuous characteristic of the current fluctuation in the current time sequence curve; obtaining a suspected current anomaly moment according to the difference characteristic of the fluctuation anomaly degree of the fluctuation anomaly moment and the same historical moment; clustering is carried out according to the current characteristics and fluctuation characteristics of all suspected current abnormal moments in the current time sequence curve, and different clusters are obtained; obtaining the current anomaly degree of the clustering cluster according to the quantity characteristics of the suspected current anomaly moments in the clustering cluster and the distance characteristics in the clustering space; obtaining a current abnormity moment according to the current abnormity degree; a fault characteristic value is obtained according to the distribution characteristic of the current abnormity moment and the change characteristic of the current abnormity degree in the current time sequence curve, and circuit fault identification is carried out, so that the working stability of the circuit breaker is improved.

The invention discloses a data processing method and device, computer equipment and a storage medium, relates to the technical field of data processing and database optimization, and can solve the problem that in the prior art, a compression strategy cannot be dynamically adjusted according to the characteristics of partitions, so that the data storage speed and the storage space utilization rate are affected. The method comprises the following steps: inputting a target data feature of a target partition in a current time period into a preset prediction model for prediction to obtain a query frequency corresponding to the target partition in a next time period; based on the frequency range to which the query frequency belongs, determining a compression strategy corresponding to the target partition in the next time period; and adjusting the compression ratio of the target partition based on the compression strategy.

The invention discloses an electric connector fault prediction method, and the method comprises the steps: synchronously obtaining multiple types of time series data of a contact area of a target electric connector in a preset time window based on a preset data collection device, and the time series data comprise temperature spatial and temporal distribution time series data, contact resistance transient time series data and a surface image sequence; performing feature analysis on the multi-source time sequence data by using a preset time sequence coupling sign extraction mechanism to obtain a multi-source phase change feature vector of the target electric connector in the current time window; inputting the multi-source phase change feature vector into a pre-trained electric connector health state prediction model, and outputting a prediction result of the health state of the target connector at the current moment, including a health state index; and performing differential early warning based on the predicted health state index of the target connector. Therefore, early and quantitative accurate prediction of the state of the electric connector is realized.

The invention discloses a real-time data subscription method and device based on a time sequence database and a medium, belongs to the technical field of databases, and aims to solve the technical problems that the real-time performance is poor, the resource consumption is large and the time sequence data required by the current time sequence database in real time acquisition in mass data storage and processing is poor. According to the technical scheme, the method comprises the steps that a data subscription scheduling task is constructed through a predefined SQL statement, in combination with an efficient data change capture module based on a Raft log mechanism, data subscribed by a user is obtained in real time, and the data subscribed by the user is filtered according to a customization rule; then the screened data is automatically transmitted to a preset target sink component in a specified format, so that the whole data processing flow has the characteristics of real-time performance, accuracy and high availability; the method specifically comprises the following steps: constructing a data subscription scheduling task; executing the data subscription scheduling task; and capturing data change based on the raft log.

Systems and methods for detecting intermittent connections in a battery energy storage system (BESS) subsystem are disclosed. For each battery rack in the BESS subsystem, current time series data is received. A current rolling average is determined for each data point of the time series data by averaging current values of timestamps over a specified time interval. A current delta is determined for each data point, where the current delta is a difference between the current rolling average associated with the battery rack under analysis and a mean of the current rolling averages associated with the other battery racks in the BESS subsystem. A distribution profile of the current deltas is analyzed to detect a current anomaly at the respective battery rack. In response to detecting the current anomaly at the battery rack under analysis, an alert indicative of a faulty connection is displayed on a user interface.

The invention discloses a resource allocation method and electronic equipment, target resources required by each large model during task processing are determined, different large models are used for processing different types of tasks, and the target resources at least comprise computing power resources; predicting the number and the type of tasks to be processed in the (t + n) th time period based on the historical record, t time period being the current time period, t being greater than or equal to 0, and n being greater than 0; determining a resource allocation strategy of the (t + n) th time period based on the number and the type of the tasks to be processed in the (t + n) th time period according to target resources required by each large model during task processing; initial target resources of different large models in the (t + n) th time period are allocated based on a resource allocation strategy, pre-stored resources are allocated, and the pre-stored resources are part of resources reserved from the total target resources and are used for guaranteeing the processing efficiency of tasks processed in the (t + n) th time period.

The invention relates to the technical field of data processing, in particular to an equipment state monitoring method and system based on data analysis. The method comprises the steps that multiple real-time monitoring parameter sequences, corresponding to different monitoring parameters, of the packaging equipment in the current time period are obtained; determining a cross-correlation sequence between a historical monitoring parameter sequence corresponding to the target monitoring parameter and the real-time monitoring parameter sequence so as to determine a volatility parameter value of an extreme point in the cross-correlation sequence; determining a difference degree value corresponding to the real-time monitoring parameter sequence; taking the product of the volatility parameter value corresponding to the target monitoring parameter and the difference degree value as the weight value of the target monitoring parameter; and constructing an isolated forest according to the weight values of the different monitoring parameters, and obtaining an abnormal score value of the current time period by using the isolated forest so as to monitor the equipment state of the packaging equipment. According to the technical scheme, the state of the packaging equipment can be better monitored.