Abstract: Various embodiments of the teachings herein include a dynamic prediction control method for a precision air conditioner. An example method includes: generating a three-dimensional simulation model on the basis of a simulation template according to static information of a hardware configuration and layout of an application scene where the precision air conditioner is located, wherein the three-dimensional simulation model and a static model of the hardware configuration and layout of the application scene correspond to each other; running a simulation on the basis of a dynamic parameter of the precision air conditioner corresponding to the three-dimensional simulation model and establishing a correspondence relationship between the dynamic parameter and a simulation result using machine learning, so as to generate a proxy model; and predicting a temperature distribution and change of the application scene on the basis of the proxy model and real-time dynamic data of the precision air conditioner.

Abstract: The present invention relates to a method and apparatus for controlling a wind turbine. The method includes: dividing a plurality of wind turbines into at least one group based on a similarity in status information of the plurality of wind turbines; in response to having detected a fault in a first wind turbine of the plurality of wind turbines, searching a group to which the first wind turbine belongs for a second wind turbine matching status information of the first wind turbine; and controlling the first wind turbine based on parameters from the second wind turbine.

Abstract: A computing device includes computing modules, each of which comprises a plurality of neuron populations. The computing module is configured to project the input spike train which is weighted by a first weight matrix to a first neuron population through a multi-synapse projection. The multi-synapse projection has at least two different and positive synaptic time constants, or at least two different synaptic transmission delays. In order to realize time-domain convolution in a spiking neural network with low hardware resource consumption, a multi-synaptic projection technology means with different synaptic time constants is proposed. On this basis, a waveform-aware spike neural network for time-domain signal processing characterized by residual connections and skip connections is further proposed. Through these technical means, the performance gap between SNN and ANN is bridged, and SNN with performance reaching or close to ANN is obtained.

Abstract: A frame image conversion spike system is disclosed. In order to solve the technical problem of high power consumption when converting a frame image into a spike event, a frame rate or difference frame frequency is adaptively adjusted according to the amount of effective pixel change between frame images, so as to reduce system power consumption and adaptively respond to scene application needs. In order to solve the issue of low inference accuracy after converting frame images into spike events and directly applying them to an SNN processor, a global randomization scheme is proposed considering the randomization process of images as a whole. It has opened up all the links of applying a frame image sensor to the SNN processor and provided an alternative to an event camera. This is suitable for a brain-inspired chip and AIoT field.

Abstract: A method, a device and a computer program product for abnormal air pollution emission prediction are proposed. In the method, a first set of features characterizing air condition in a zone is obtained. Whether the zone is subject to abnormal air pollution emission in a future first time period is determined based on the first set of features and using a first prediction classifier. In response to determining that the zone is subject to abnormal air pollution emission in the first time period, a second set of features characterizing air condition in the zone is obtained. A future second time period in which the zone is subject to abnormal air pollution emission is determined based on the second set of features and using a second prediction classifier. The second time period is included in the first time period. In this way, the abnormal air pollution emission in the zone can be accurately and efficiently predicted.

Abstract: The present invention relates to a method and apparatus for controlling a wind turbine. The method includes: dividing a plurality of wind turbines into at least one group based on a similarity in status information of the plurality of wind turbines; in response to having detected a fault in a first wind turbine of the plurality of wind turbines, searching a group to which the first wind turbine belongs for a second wind turbine matching status information of the first wind turbine; and controlling the first wind turbine based on parameters from the second wind turbine.

Abstract: A terminal device obtains a first group of parameters corresponding to a first mode. A network device obtains a second group of parameters corresponding to the first mode, where the first group of parameters correspond to the second group of parameters. When a compatibility problem exists between the terminal device and the network device, the terminal device initiates initial access to the network device based on the first group of parameters, and the network device accepts, based on the second group of parameters, the initial access initiated by the terminal device.

Abstract: This application provides an image prediction method, an electronic device, and a storage medium. The prediction method includes: obtaining a drawing instruction stream of a first image frame, wherein the first image frame contains one or more first objects; calculating a first motion vector between the one or more first objects and the one or more third objects, wherein the one or more third objects match the one or more first objects; obtaining a second motion vector, wherein the second motion vector is a motion vector between the one or more third objects and one or more fourth objects in a third image frame; calculating a third motion vector based on a first motion vector and a second motion vector; obtaining a first prediction image frame based on the first motion vector, the third motion vector, and the one or more first objects.

Abstract: Various embodiments of the teachings herein include an edge computing method. The method may include: installing a daemon on a first edge device connected to a control server, wherein the daemon sends information to the server when an accelerator is connected to the edge device indicating the first edge device is connected to an accelerator; receiving the connection information from the daemon and configuring an accelerator enabled flag for the first edge device indicating the first edge device is connected to an accelerator; receiving a sharing request from either edge device, wherein the sharing request requesting an accelerator execute a target application; labeling an edge device with the accelerator enabled flag as a second edge device according to the sharing request; and loading the target application onto the second edge device so the accelerator connected to the second edge device executes the target application.

Abstract: An electronic device includes an integrated circuit and a smart film layer. Integrated circuit is configured to output a control signal. Smart film layer is coupled to integrated circuit and includes a first substrate, a second substrate, a liquid crystal layer, a transparent glue layer, a cover, and at least one touch electrode layer. Second substrate is located on first substrate. Liquid crystal layer is located between first substrate and second substrate. Transparent glue layer is located on second substrate. Cover is located on transparent glue layer. At least one touch electrode layer is located between two of first substrate, second substrate, liquid crystal layer, transparent glue layer, or cover. At least one touch electrode layer is configured to transmit a touch signal or at least one touch electrode layer is configured to control liquid crystal layer to present in transparent states according to control signal of integrated circuit.

Abstract: A method and apparatus for forecasting output power of wind turbine in a wind farm. The present invention provides a method for forecasting output power of a wind turbine in a wind farm, including: generating a corrected data set based on environmental data collected from at least one sensor in the wind farm; correcting a weather forecasting model by using the corrected data set; obtaining a forecast value of wind information at the wind turbine based on the corrected weather forecasting model; and forecasting the output power of the wind turbine based on the forecast value and a power forecasting model.

Abstract: A method and apparatus for forecasting output power of wind turbine in a wind farm. The present invention provides a method for forecasting output power of a wind turbine in a wind farm, including: generating a corrected data set based on environmental data collected from at least one sensor in the wind farm; correcting a weather forecasting model by using the corrected data set; obtaining a forecast value of wind information at the wind turbine based on the corrected weather forecasting model; and forecasting the output power of the wind turbine based on the forecast value and a power forecasting model.

Abstract: An abnormal area is detected using an initial spatial weights matrix between pairs of air quality sensors in a plurality of air quality sensors distributed across a geographical area and air quality data for each air quality sensor. The spatial weights matrix utilizes a distance between pairs of air quality sensors and wind direction through the geographical area. The initial spatial weights matrix and air quality data are used to calculate a plurality of local moran's indexes, one for each air quality sensor. The plurality of local moran's indexes are used to divide the plurality of air quality sensors into four groups. The groups are classified as proper or improper, and the proper groups are identified as abnormal areas.

Abstract: A method for file storage and a storage device are disclosed. The method includes: receiving, by a file system, a file create request sent by an application, where the file create request includes a file storage characteristic and a file storage path; selecting, by the file system from M domains based on the file storage characteristic, a domain whose domain storage characteristic has a highest degree of conformity with the file storage characteristic as a target domain; creating, by the file system, a file in the target domain; and adding, by the file system, the file to a directory tree based on the file storage path. The method can facilitate file and directory management in a storage device.

Abstract: A virtual disk file format conversion method and an apparatus that relate to the field of virtualization technologies and to resolve a service interruption caused by offline conversion of a virtual machine disk image file format when a virtual machine is migrated between different types of VMMs. The method and apparatus include establishing a mapping table between a virtual address of a virtual machine (VM) disk image file and a physical address of a disk image file that is compatible with a virtual machine monitor (VMM), converting, according to the mapping table, the virtual address used when a user performs reading/writing on the VM disk image file, into the physical address mapped to the virtual address, and performing data reading/writing on the VM disk image file based on the physical address.

Abstract: Correction management techniques are provided. In one embodiment, the techniques involve determining, via a first machine learning model, a first and second data based on a respective first and second raw data obtained from a plurality of sensors, determining, based on a deviation between the first data and the second data, an inaccuracy of the first data, identifying an ambient situation corresponding to the first raw data and the second raw data, selecting, from historical raw data of the plurality of sensors, a group of raw data corresponding to the ambient situation, and correcting, via a second machine learning model, the first data based on the selected group of raw data.

Abstract: A projection system includes a projection device including a projector unit and a camera unit, a signal transmitter unit mounted to a projection screen, and a processing unit. The camera unit captures an image of a projection image projected by the projector unit onto the projection screen, and the processing unit obtains a position of the projection image accordingly. The processing unit obtains a position of the projection screen based on signals wirelessly transmitted by the signal transmitter unit and adjusts setting parameter(s) related to the projector unit based on a comparison between the positions of the projection image and the projection screen to reduce dimensional and/or positional differences between the two.

Abstract: The present invention relates to a method and apparatus for controlling a wind turbine. The method includes: dividing a plurality of wind turbines into at least one group based on a similarity in status information of the plurality of wind turbines; in response to having detected a fault in a first wind turbine of the plurality of wind turbines, searching a group to which the first wind turbine belongs for a second wind turbine matching status information of the first wind turbine; and controlling the first wind turbine based on parameters from the second wind turbine.