Abstract: Provided are a photoelectric sensor and an electronic device. The photoelectric sensor includes a substrate, a plurality of photoelectric sensing elements, and a wall structure between two adjacent photoelectric sensing elements. The wall structure includes a first layer and a second layer stacked with the first layer. The first layer is arranged at a side of the second layer away from the substrate and includes a light-blocking material. At least one of the first layer or the second layer of the wall structure is arranged in a same layer as at least one layer of the photoelectric sensing element.

Abstract: Provided are a driver board, a display panel, and a display apparatus. The driver board includes a driver circuit. The driver circuit includes N pixel electrodes, N pixel switches, a data switch, and a storage capacitor, N is a positive integer, and N?2. The storage capacitor includes a reference electrode and a counter electrode. A control terminal of the pixel switch receives a gating signal, a first terminal of the pixel switch is connected to the counter electrode, and a second terminal of the pixel switch is connected to the pixel electrode. The driver board further includes data lines, and each data line is connected to the counter electrode via the data switch.

Abstract: Provided are a method for generating a fishing track, a mobile terminal, and a storage medium. The method includes the steps described below. A first position of a user and a second position of at least one fishing area are acquired. A target fishing area in which the user is located is determined from the at least one fishing area according to the first position and the second position. A fishing track is generated according to the first position and a third position of the target fishing area.

Abstract: For one embodiment of the present invention, a method of object detection and part segmentation is described. The method includes generating a three-dimensional (3D) point cloud including a plurality of points in a volume of a space of the point cloud based on receiving point cloud dat. The method further includes obtaining, with a global transformer, a set of global feature tokens and local feature points of the 3D point cloud, enforcing with an attention mechanism information flow across the set of global feature tokens and local feature point, and generating, with the global transformer, a set of new global feature tokens and new local feature points with modeled global context information.

Abstract: Disclosed is an air-drying device for processing of cured meat products, including an air-drying treatment mechanism; the air-drying treatment mechanism includes a first box body, a top wall of the first box body is provided with a blower; a plurality of air-drying components are rotatably connected in the first box body; each air-drying component includes a first cylinder, a side wall of the first cylinder is circumferentially provided with a plurality of openable and closable air inlet channels; a top of each first cylinder is detachably connected with a cover plate, and a bottom of each first cylinder is provided with a bearing plate, and outer side walls of each first cylinder and each bearing plate are circumferentially provided with a plurality of slide rails.

Abstract: For one embodiment of the present invention, a method of object instance edge detection and segmentation is described. The method includes obtaining an input image with a shape and extracting, with a feature extractor of a point supervised transformer model, a hierarchical combination of features from the input image including a set of feature maps having different levels. The method further includes receiving, with a transformer decoder, an output including a feature map from the feature extractor, and object queries each with d dimensions, training the point supervised transformer model with a sparse set of keypoint annotations along a boundary of each object instance, and generating a box prediction, a classification prediction, and a coefficient prediction for each object instance based on an output from the transformer decoder.

Abstract: For one embodiment of the present invention, a method of object detection and part segmentation is described. The method includes generating a three-dimensional (3D) point cloud including a plurality of points in a volume of a space of the point cloud based on receiving point cloud dat. The method further includes obtaining, with a global transformer, a set of global feature tokens and local feature points of the 3D point cloud, enforcing with an attention mechanism information flow across the set of global feature tokens and local feature point, and generating, with the global transformer, a set of new global feature tokens and new local feature points with modeled global context information.

Abstract: Disclosed are an animal fat grading device using superheated steam and a method. The device comprises a bracket, a material container, a steam heating assembly, an oil leakage assembly, a pressing part, an oil pumping assembly, a switch structure and a controller, where an upper part of the bracket is fixedly connected with the material container, a top side wall and a bottom side wall of the material container are provided with the steam heating assembly; an inside is slidably connected with the oil leakage assembly; a top of the oil leakage assembly is fixedly connected with the pressing part; a top surface of the oil leakage assembly is fixedly connected with the oil pumping assembly, a bottom of the material container is communicated with an oil discharging pipe, the switch structure is arranged on the oil discharging pipe, and a temperature sensor is arranged in the material container.

Abstract: A power grid reactive voltage control model training method. The method comprises: establishing a power grid simulation model; establishing a reactive voltage optimization model, according to a power grid reactive voltage control target; building interactive training environment based on Adversarial Markov Decision Process, in combination with the power grid simulation model and the reactive voltage optimization model; training the power grid reactive voltage control model through a joint adversarial training algorithm; and transferring the trained power grid reactive voltage control model to an online system. The power grid reactive voltage control model trained by using the method according to the present disclosure has transferability as compared with the traditional method, and may be directly used for online power grid reactive voltage control.

Abstract: Disclosed is an enzymatic hydrolysis device for livestock and poultry slaughter by-products, including a feeding barrel, and a crushing box is fixed and communicated with a bottom end of the feeding barrel; two symmetrically arranged rolling plates are arranged in the feeding barrel, and a rolling space is arranged between the two rolling plates, and a bottom of the rolling space is provided with a bearing plate; an air pump is fixed at a bottom of the crushing box; and a mixing disturbance mechanism, including a bottom plate, a slide rail fixed on a top surface of the bottom plate, a tank body slidably connected to the slide rail, and baffles fixed at both ends of the bottom plate; the tank body is internally provided with a plurality of circumferentially distributed curved panels; and there are a plurality of circumferentially distributed disturbance components in the disturbance space.

Abstract: A method for multi-time scale reactive voltage control based on reinforcement learning in a power distribution network is provided, which relates to the field of power system operation and control. The method includes: constituting an optimization model for multi-time scale reactive voltage control in a power distribution network based on a reactive voltage control object of a slow discrete device and a reactive voltage control object of a fast continuous device in the power distribution network; constructing a hierarchical interaction training framework based on a two-layer Markov decision process based on the model; setting a slow agent for the slow discrete device and setting a fast agent for the fast continuous device; and deciding action values of the controlled devices by each agent based on measurement information inputted, so as to realize the multi-time scale reactive voltage control while the slow agent and the fast agent perform continuous online learning.

Abstract: A power grid reactive voltage control method and control system based on two-stage deep reinforcement learning, comprising steps of: building interactive training environment based on Markov decision process, according to a regional power grid simulation model and a reactive voltage optimization model; training a reactive voltage control model offline by using a SAC algorithm, in the interactive training environment based on Markov decision process; deploying the reactive voltage control model to a regional power grid online system; and acquiring operating state information of the regional power grid, updating the reactive voltage control model, and generating an optimal reactive voltage control policy. As compared with the existing power grid optimizing method based on reinforcement learning, the online control training according to the present disclosure has costs and safety hazards greatly reduced, and is more suitable for deployment in an actual power system.

Abstract: The present disclosure discloses a horizontal type combined filter separator, including a barrel-shaped structure. The inside of the shell is sequentially divided into a first cavity, a second cavity and a third cavity from a first end and a second end. A fourth cavity is formed in the first cavity. The horizontal type combined filter separator further includes a communicating pipe with one opened end and one closed end; the closed end of the communicating pipe extends into the first cavity, and the opened end passes through the second cavity and extends into the third cavity. The shell is provided with a gas intake connection pipe communicating with the fourth cavity. A plurality of cyclone separators are provided; a gas inlet of each cyclone separator communicates with the fourth cavity; a dust discharging port communicates with the first cavity; and an exhaust port extends into the communicating pipe.

Abstract: The present disclosure discloses a vertical type combined filter separator, including a shell. The inside of the shell is divided into a first cavity, a second cavity, a third cavity, a fourth cavity and a fifth cavity in sequence from a first end to a second end. A gas intake connection pipe is arranged on the second cavity, and several cyclone separators are arranged in the second cavity. For each cyclone separator, a gas inlet is exposed into the second cavity, a dust discharging port communicates with the first cavity, and an exhaust port communicates with the third cavity. The third cavity passes through the fourth cavity through the communicating pipe and directly communicates with the fifth cavity. The fifth cavity communicates with the fourth cavity through a filter separation assembly. A gas outlet connection pipe for discharging separated purified gas is arranged on the fourth cavity.

Abstract: The present disclosure discloses a vertical type combined filter separator, including a shell. The inside of the shell is divided into a first cavity, a second cavity, a third cavity, a fourth cavity and a fifth cavity in sequence from a first end to a second end. A gas intake connection pipe is arranged on the second cavity, and several cyclone separators are arranged in the second cavity. For each cyclone separator, a gas inlet is exposed into the second cavity, a dust discharging port communicates with the first cavity, and an exhaust port communicates with the third cavity. The third cavity passes through the fourth cavity through the communicating pipe and directly communicates with the fifth cavity. The fifth cavity communicates with the fourth cavity through a filter separation assembly. A gas outlet connection pipe for discharging separated purified gas is arranged on the fourth cavity.

Abstract: The present disclosure discloses a horizontal type combined filter separator, including a barrel-shaped structure. The inside of the shell is sequentially divided into a first cavity, a second cavity and a third cavity from a first end and a second end. A fourth cavity is formed in the first cavity. The horizontal type combined filter separator further includes a communicating pipe with one opened end and one closed end; the closed end of the communicating pipe extends into the first cavity, and the opened end passes through the second cavity and extends into the third cavity. The shell is provided with a gas intake connection pipe communicating with the fourth cavity. A plurality of cyclone separators are provided; a gas inlet of each cyclone separator communicates with the fourth cavity; a dust discharging port communicates with the first cavity; and an exhaust port extends into the communicating pipe.

Abstract: A method for evaluating physical stamina indicators in running exercise includes collecting different exercise condition data, establishing a second and a third model equations, calculating a first and a second standard paces, calculating a first and a second physical stamina levels according to the paces, and finally confirming the physical stamina category. The accuracy of the evaluation results is high for the reference.

Abstract: A power grid reactive voltage control method and control system based on two-stage deep reinforcement learning, comprising steps of: building interactive training environment based on Markov decision process, according to a regional power grid simulation model and a reactive voltage optimization model; training a reactive voltage control model offline by using a SAC algorithm, in the interactive training environment based on Markov decision process; deploying the reactive voltage control model to a regional power grid online system; and acquiring operating state information of the regional power grid, updating the reactive voltage control model, and generating an optimal reactive voltage control policy. As compared with the existing power grid optimizing method based on reinforcement learning, the online control training according to the present disclosure has costs and safety hazards greatly reduced, and is more suitable for deployment in an actual power system.

Abstract: A power grid reactive voltage control model training method. The method comprises: establishing a power grid simulation model; establishing a reactive voltage optimization model, according to a power grid reactive voltage control target; building interactive training environment based on Adversarial Markov Decision Process, in combination with the power grid simulation model and the reactive voltage optimization model; training the power grid reactive voltage control model through a joint adversarial training algorithm; and transferring the trained power grid reactive voltage control model to an online system. The power grid reactive voltage control model trained by using the method according to the present disclosure has transferability as compared with the traditional method, and may be directly used for online power grid reactive voltage control.