Abstract: A computer-implemented method, system and computer program product for accurately identifying an execution time of a performance test. Network latency data is grouped into clustered groups of network latency data. Furthermore, the performance test execution times for the same group of performance tests run in the local and remote cluster environments are obtained. The test execution times impacted by network latency (compensation times) are then determined based on such obtained performance test execution times in the local and remote cluster environments. Such compensation times are then grouped into clustered groups of compensation times. A regression model is built to predict a performance test execution time impacted by network latency (compensation time) using the clustered groups of network latency data and compensation times.

Abstract: Embodiments of the present invention provide an information transmission method and an apparatus One example method includes: sending a first signal on a first time-frequency resource through a first antenna port, where the first signal is used for synchronization; sending a first message on a second time-frequency resource, where the first message includes time domain resource information and/or cyclic prefix length information of the second time-frequency resource; and sending a second message on a third time-frequency resource.

Abstract: A method of performing synchronous replication from a primary storage system apparatus (PSSA) to a secondary storage system apparatus (SSSA) is provided. The method includes (a) in response to write requests received by the PSSA, (i) calculating metadata changes by the PSSA for accommodating the write requests, (ii) generating, by the PSSA, metadata journal log entries that describe the metadata changes, and (iii) mirroring the metadata journal log entries from the PSSA to the SSSA; (b) regenerating the metadata changes by the SSSA based on the metadata journal log entries mirrored from the PSSA to the SSSA; and (c) writing the regenerated metadata changes to persistent storage of the SSSA. A method performed by the SSSA is also provided. An apparatus, system, and computer program product for performing similar methods are also provided.

Abstract: A computer-implemented method includes: obtaining, by a computing device, data from sensors that collect the data in a system during a time, wherein the data is multi-dimensional time series data; creating, by the computing device, matrices based on the data; determining, by the computing device using a first computer-based numerical modeling method, patterns based on the matrices; creating, by the computing device using a second computer-based numerical modeling method, a single time series model based on the patterns; and predicting, by the computing device, a future condition of the system using the time series model with current data of the system.

Abstract: Identifying node importance in a machine learning pipeline is provided. Changes in accuracy of the machine learning pipeline are recorded for each respective node setting change in a randomly generated group of node settings inputted into each corresponding node included in the machine learning pipeline. A regression model is generated to determine a relationship between each respective node setting change in the randomly generated group of node settings inputted into each corresponding node and the changes in the accuracy of the machine learning pipeline. A node of importance is identified in the machine learning pipeline using the regression model based on the relationship between each respective node setting change in the randomly generated group of node settings inputted into each corresponding node and the changes in the accuracy of the machine learning pipeline.

Abstract: A communication method includes jointly sending first data to a first communication device in n first time domain resources, where the n first time domain resources respectively belong to n first time units, where relative positions of the n first time domain resources in the n first time units are the same, where n is an integer greater than or equal to 2, where the n first time domain resources are included in a second time domain resource, and where the second time domain resource is a first periodic resource.

Abstract: This application discloses a communications method, apparatus, and system, and is applicable to wireless communication fields such as the internet of vehicles, intelligent driving, assisted driving, and intelligent connected vehicles. The communications method may include: encoding first data according to a first coding scheme; sending the encoded first data; encoding second data according to a second coding scheme, where the first data is different from the second data, and the second coding scheme is different from the first coding scheme; and sending the encoded second data.

Abstract: A communication method includes receiving, by a first time domain resource, a first signal for synchronization and receiving, by at least one second time domain resource, a first message comprising one or both of cyclic prefix length information and resource configuration information for uplink transmission and downlink transmission, wherein a length of a time interval between the first time domain resource and each of the at least one second time domain resource is a positive-integer number of time domain resource units.

Abstract: An embodiment includes parsing conversation data to extract a message dataset and a user dataset. The embodiment classifies the message dataset into a category using machine learning processing and identifies the category as a top category based at least in part on an amount of the conversation data associated with the category. The embodiment generates impact data associated with the user dataset based on actions in the conversation data by the user. The embodiment generates role data associated with the user by applying a rule to the conversation data for the user. The embodiment generates key index data associated with the message dataset by identifying interactions with a message represented by the message dataset. The embodiment generates output data arranged according to a specified data format that is compatible with a user interface.

Abstract: A data transmission method includes: A slave node transmits first data to a master node on a first time domain resource in a first time domain resource unit by using a first frequency domain resource. The slave node transmits second data in the target service to the master node on a third time domain resource in a second time domain resource unit using a second frequency domain resource. The first time domain resource unit is adjacent to the second time domain resource unit in a time domain. The first time domain resource unit sequentially includes, in the time domain, the first time domain resource, a first guard period, a second time domain resource, and a second guard period. The second time domain resource unit sequentially includes, in the time domain, the third time domain resource, a third guard period, a fourth time domain resource, and a fourth guard period.

Abstract: An approach is provided in which the approach loads a machine learning model and a set of test case statistical data into a user system. The set of test case statistical data is based on a set of test cases corresponding to the machine learning model and includes a plurality of input parameter sets and a corresponding set of output quality measurements. The approach compares user data on the user system against the set of test case statistical data and identifies one of the plurality of input parameter sets to optimize the machine learning model based on the set of output quality measurements. The approach generates an optimized machine learning model using the machine learning model and the identified input parameter set at the user system.

Abstract: This application relates to a scheduling method, an apparatus, and a system. A first communications apparatus sends first signaling on a first resource, where the first signaling is used to indicate N communications apparatuses. The first communications apparatus sends second signaling on a second resource, where the second signaling is used to schedule the N communications apparatuses to send or receive first data, and the first resource has an association relationship with the second resource. In addition, the first resource has the association relationship with the second resource. In this case, a receive end of the first signaling and the second signaling may determine the second resource after determining the first resource, so that the second signaling is only detected on the second resource, and blind detection does not need to be performed on too many resources.

Abstract: The fuel cell control system includes: a reactor; an air compressor, wherein the air compressor has a compressing cavity, the compressing cavity has a gas inlet and a gas outlet, a rotatable pressure wheel is disposed inside the compressing cavity, and the gas outlet is in communication with the reactor; a control flow channel, wherein a first end of the control flow channel is in communication with the gas-intake side of the pressure wheel, a second end of the control flow channel is in communication with the wheel-back side of the pressure wheel, and the control flow channel is provided with a return valve for regulating the flow rate of the control flow channel; and a central control unit, wherein the central control unit is communicatively connected to the return valve to control the opening degree of the return valve.

Abstract: A method for controlling radar frequency hopping includes determining start frequencies of a plurality of frequency modulated continuous wave (FMCWs) based on a first function, and controlling a radar to sequentially transmit the plurality of FMCWs by performing frequency hopping based on the determined start frequencies.

Abstract: The air compressor includes: a housing assembly, wherein the housing assembly has a first installation cavity, a second installation cavity and a rotation-shaft cooperating cavity, and the first installation cavity has a gas inlet and a gas outlet; a rotor shaft, wherein the rotor shaft is rotatably fitted inside the rotation-shaft cooperating cavity, and extends into the first installation cavity and the second installation cavity; a pressure wheel, wherein the pressure wheel is nested to the rotor shaft and is located inside the first installation cavity, and the housing assembly is provided with a controlling flow channel for communicating the gas-intake side and the wheel-back side of the pressure wheel; and a driving assembly, wherein the driving assembly is nested to the rotor shaft and is located inside the second installation cavity.

Abstract: A driver assistance method and a driver assistance apparatus are provided, which may be applied to the field of autonomous driving or intelligent driving. The driver assistance method includes: determining that a driver is in an abnormal state; determining that a first operation performed by the driver on a first terminal is an abnormal operation; and performing first processing, where the first processing includes outputting indication information and/or control information, and the indication information or the control information indicates a second operation performed on the first terminal, or the first processing includes controlling the first terminal to perform the second operation.

Abstract: An approach is provided in which the approach constructs a 3-dimensional (3D) matrix based on a plurality of historical transactions performed by a user. The 3D matrix includes a set of features, a set of rows, and a set of channels. The approach trains a convolutional neural network using the 3D matrix, and then uses the trained convolutional neural network to predict a risk level of a new transaction initiated by the user. The approach transmits an alert message based on the predicted risk level.

Abstract: Systems and methods are provided to recommend software patches based on task operation mapping. In embodiments, a method includes abstracting test cases for a software patch into a sequence of task operations and parameters associated with each task operation; encoding the task operations and the parameters associated with each task operation based on predetermined rules, thereby generating encoded task operations with unique identifiers assigned thereto and associated encoded parameters with numeric values assigned thereto; generating, using machine learning, a list of frequent operation items, based on the encoded task operations and the associated encoded parameters; generating, using clustering, clusters of parameters for each frequent operation item in the list of frequent operation items; and sending a software patch package including the list of frequent operation items, the clusters of parameters and the software patch to a remote server for distribution to one or more user devices.

Abstract: A computer-implemented method, system and computer program product for accurately identifying an execution time of a performance test. Network latency data is grouped into clustered groups of network latency data. Furthermore, the performance test execution times for the same group of performance tests run in the local and remote cluster environments are obtained. The test execution times impacted by network latency (compensation times) are then determined based on such obtained performance test execution times in the local and remote cluster environments. Such compensation times are then grouped into clustered groups of compensation times. A regression model is built to predict a performance test execution time impacted by network latency (compensation time) using the clustered groups of network latency data and compensation times.

Abstract: A pixel driving circuit and a display panel are provided. The pixel driving circuit includes a control unit to output a control signal by detecting a voltage difference between two opposite ends of a sampling resistor, and to turn on a fourth switch by the control signal. When the fourth switch is turned on, a second positive voltage received by the pixel driving circuit charges a second node to further speed up a voltage pulling up of the second node to improve a detecting speed of the pixel driving circuit.