Abstract: A method for determining phase locking of critical arc light includes: step 1: monitoring and collecting light radiation intensity of an arc inside a switch cabinet in real time, and converting the collected light radiation intensity into an electrical signal; step 2: extracting a power-frequency fundamental wave of the electrical signal, comparing an amplitude of the power-frequency fundamental wave of the electrical signal with a first threshold, and generating a pre-warning signal based on a comparison result of the first threshold; step 3: comparing the amplitude of the power-frequency fundamental wave of the electrical signal with a second threshold voltage, and generating a control signal based on a comparison result of the second threshold voltage and a protection time threshold; and step 4: protecting the switch cabinet under the critical arc light environment based on the pre-warning signal and the control signal.

Abstract: Introduced here is at least one technique to better estimate interference at a receiver. The technique includes receiving a plurality of reference signals, which each have information indicative of noise. Thus, the technique further includes, for each reference signal, determining a noise estimation and determining a distance metric and log-likelihood ratio (LLR) of the noise estimation. Once the distance metric and LLR of each reference signal is determined, the receiver can determine a final LLR based on the distance metric and LLR of each reference signal. In this manner, a final LLR is determined. This technique can be applied by any device operating on MIMO technology.

Abstract: According to one aspect of the present disclosure, a baseband chip may be configured to receive a data stream associated with a channel. The baseband chip may be configured to select a first anchor point from the first constellation points of the first transmission layer. The baseband chip may be configured to select a first subset of constellation points from the first constellation points and the second constellation points. The baseband chip may be configured to perform a first iteration of a recursive tree search. The baseband chip may be configured to determine a first path metric based at least in part on the first iteration of the recursive tree search operation. The baseband chip may be configured to select a second anchor point from the second constellation points of the second transmission layer. The second anchor point may be associated with a second iteration of the recursive tree search.

Abstract: The present disclosure provides a control method for a display panel, a control device thereof, and a display device. This control method includes: obtaining spatial position coordinates of a pupil of a user; determining coordinates of a gaze point in a display area of a display panel viewed by the user according to the spatial position coordinates of the pupil; determining an area range that the pupil of the user is gazing in the display area according to the spatial position coordinates of the pupil, the coordinates of the gaze point and a preset visual angle; determining a gaze area and a non-gaze area in the display area according to the area range, wherein the gaze area is adjacent to the non-gaze area; and adjusting a first gate driving signal input to the gaze area and a second gate driving signal input to the non-gaze area.

Abstract: Embodiments of this application disclose a data processing method, an apparatus, and a device. The data processing method may be performed by a first communication device, and the first communication device is a transmit end of encoded data. During each time of transmission, the first communication device places information bits into code blocks according to a specified order.

Abstract: A laparoscopic image smoke removal method based on a generative adversarial network, and belongs to the technical field of computer vision. The method includes: processing a laparoscopic image sample to be processed using a smoke mask segmentation network to acquire a smoke mask image; inputting the laparoscopic image sample to be processed and the smoke mask image into a smoke removal network, and extracting features of the laparoscopic image sample to be processed using a multi-level smoke feature extractor to acquire a light smoke feature vector and a heavy smoke feature vector; and acquiring, according to the light smoke feature vector, the heavy smoke feature vector and the smoke mask image, a smoke-free laparoscopic image by filtering out smoke information and maintaining a laparoscopic image by using a mask shielding effect. The method has the technical effects of robustness and ability of being embedded into a laparoscopic device for use.

Abstract: There is provide a method for manufacturing analytical semiconductor samples by using an apparatus for manufacturing analytical semiconductor samples, which minimizes a feedback time by manufacturing a viewing surface that is environment-friendly and has a large area. The method comprising mounting the analytical semiconductor samples to a holder; discharging deionized (DI) water to an upper surface of a polishing plate through a DI water nozzle; grinding the analytical semiconductor samples with the upper surface of the polishing plat; determining whether a desired viewing surface of the analytical semiconductor samples has been acquired after the grinding of the analytical semiconductor samples; and transferring the analytical semiconductor samples to analyze the viewing surface of the ground analytical semiconductor samples based on a determination that the desired viewing surface of the analytical semiconductor samples has been acquired.

Abstract: A moving state reporting method includes communicating, by a terminal, with a network device using a beam to carry a signal reporting, by the terminal, moving state information of the terminal to the network device, where the moving state information includes a speed flag, and the speed flag indicates that a speed of the terminal exceeds a speed threshold, and receiving, by the terminal, beam management information from the network device.

Abstract: Disclosed are a consistency evaluation method for a vehicle battery cell, a device, an equipment, and a storage medium. The method includes: acquiring vehicle operation data, and selecting effective cell data in the vehicle operation data according to a preset effective data standard; processing the effective cell data according to a preset cell consistency index processing method to obtain cell consistency index data; determining a total index deviation value of all battery cells in the current vehicle according to the cell consistency index data; and if the total index deviation value exceeds a preset deviation threshold, determining a consistency risk of the current vehicle.

Abstract: The embodiments of the present disclosure provide systems and methods for outbound forecasting, comprising receiving an initial distribution of priority values to each fulfillment center (FC) in each region, running a simulation, using a simulation algorithm, of the initial distribution, calculating an outbound capacity utilization value of each FC, determining a number of FCs comprising an outbound capacity utilization value that exceeds a predetermined threshold, feeding the simulation algorithm with the determined number of FCs to generate one or more additional distributions of priority values, generating a FC priority filter comprising an optimal set of priority values based on the one or more additional distributions of priority values, and modifying an allocation of a plurality of SKUs among a plurality of FCs based on the generated FC priority filter.

Abstract: System and method for prediction using a machine learning model. The system includes a coordinator, an active computing device and a passive computing device in communication with each other. The active computing device has a processor and a storage device storing computer executable code. The computer executable code is configured to: obtain parameters of the machine learning model; retrieve an instance from the local data; sample a random direction of the instance; compute a dot product of the random direction and the instance, and calculate a random feature; compute predicted values of the instance in the active and passive computing devices and summarize them to obtain a final predicted value; determine a model coefficient using the random feature, the final predicted value, and a target value of the instance; update the machine learning model using the model coefficient; and predict a value for a new instance.

Abstract: System and method for training a federated learning model asynchronously. The system includes a coordinator, an active computing device and a passive computing device in communication with each other. The active computing device has a processor and a storage device storing computer executable code. The computer executable code is configured to: train the federated learning model in the active computing device using dimensions of an instance in the active computing device; and instruct the at least one passive computing device to train the federated learning model in the at least one passive computing device using dimensions of the instance in the at least one passive computing device. The training instances in the active and the at least one passive computing devices do not correspond to each other at the same training time.

Abstract: A moving state reporting method includes communicating, by a terminal, with a network device using a beam to carry a signal reporting, by the terminal, moving state information of the terminal to the network device, where the moving state information includes a speed flag, and the speed flag indicates that a speed of the terminal exceeds a speed threshold, and receiving, by the terminal, beam management information from the network device.

Abstract: The invention provides pharmaceutical compositions and methods of use thereof for preventing or ameliorating disorders of the nervous system. More specifically, the invention provides pharmaceutical compositions, including phosphopeptides that when administered disrupt the physical interaction of TrkB with its signaling effector, phospholipase C?1 (PLC?1). The invention further provides method of treatment comprising administering phosphopeptides that uncouple TrkB from PLC?1 in order to prevent and/or ameliorate nervous system disorders such as epilepsy, anxiety, and seizures.

Abstract: System and method for prediction using a machine learning model. The system includes a coordinator, an active computing device and a passive computing device in communication with each other. The active computing device has a processor and a storage device storing computer executable code. The computer executable code is configured to: obtain parameters of the machine learning model; retrieve an instance from the local data; sample a random direction of the instance; compute a dot product of the random direction and the instance, and calculate a random feature; compute predicted values of the instance in the active and passive computing devices and summarize them to obtain a final predicted value; determine a model coefficient using the random feature, the final predicted value, and a target value of the instance; update the machine learning model using the model coefficient; and predict a value for a new instance.

Abstract: System and method for training a federated learning model asynchronously. The system includes a coordinator, an active computing device and a passive computing device in communication with each other. The active computing device has a processor and a storage device storing computer executable code. The computer executable code is configured to: train the federated learning model in the active computing device using dimensions of an instance in the active computing device; and instruct the at least one passive computing device to train the federated learning model in the at least one passive computing device using dimensions of the instance in the at least one passive computing device. The training instances in the active and the at least one passive computing devices do not correspond to each other at the same training time.

Abstract: An electronic device may receive or provide power using bidirectional wired and wireless power converters. A bypass path may be included to bypass the battery charger and to allow direct power transfers from a connector of the electronic device to the wireless power converter or from the wireless power converter to the connector of the electronic device. Current limiting and regulation circuitry may also be included.

Abstract: A method for executing multiple versions of an application within a computing environment. The method includes a computer processor identifying a request to execute an instance of a first version of an application within a computing environment and determining that an instance of a second version of the application is active within the computing environment. The method further includes accessing a data structure including information associated with the application to obtain a first set of data corresponding to the first version of the application. The method further includes copying one or more executable objects associated with the first version of the application based, at least in part, on the first set of data to the computing environment. The method further includes executing the copied one or more executable objects associated with the first version that comprise the requested instance of the first version of the application within the computing environment.

Abstract: A deployment specification for implementing a requested cloud service is received by a server. A resource pool is queried by the server for available resources required by the deployment specifications. The resource pool includes a plurality of pre-configured resources for implementing one or more cloud services. A first resource required by the deployment specification is determined to be available within the resource pool. First resource metadata associated with the first resource is requested from a database. The resource metadata includes a resource identifier and a resource type of the first resource. The resource metadata associated with the first resource is received from the database. The first resource is deployed from the resource pool according to the deployment specification to implement the requested cloud service.

Abstract: The invention provides pharmaceutical compositions and methods of use thereof for preventing or ameliorating disorders of the nervous system. More specifically, the invention provides pharmaceutical compositions, including phosphopeptides that when administered disrupt the physical interaction of TrkB with its signaling effector, phospholipase C?1 (PLC?1). The invention further provides method of treatment comprising administering phosphopeptides that uncouple TrkB from PLC?1 in order to prevent and/or ameliorate nervous system disorders such as epilepsy, anxiety, and seizures.