Abstract: A processor-implemented method for a neural architecture search (NAS) starts by generating an over-parameterized super network having multiple layers. The super network has multiple operator types. Each of the layers includes a largest super kernel corresponding to a search space. The method also includes performing gradient descent to evolve a largest super kernel to a small kernel corresponding to the search space in order to generate a range of kernel encodings. The method further includes identifying a subset of kernel encodings from the range of kernel encodings, for each layer of the super network, based on the gradient descent. The method determines a set of candidate architectures based on the subset of kernel encodings, each of the candidate architectures having a different model size. The method selects a target model, from the set of architectures, based on meeting hardware specifications, and then applies the target model.

Abstract: A method for transmitting paging message, applied to a base station, where the method includes: determining one paging occasion, where the one paging occasion corresponds to one terminal group; determining a plurality of terminal subgroups comprised in the one terminal group; transmitting a paging message according to the one paging occasion and the plurality of terminal subgroups; where paging messages of terminals in a same terminal subgroup are transmitted in a same search space.

Abstract: The present disclosure discloses a method for encrypting a visually secure image based on adaptive block compressed sensing and non-negative matrix decomposition. Firstly, the Tetrolet transform is performed on the plain image, then the sparsity degree is optimized on the sparsity matrix and the matrix scrambling is performed, such that the sparsity degree in each block region of the image matrix is equalized. Then according to the image information, the sampling number of the block region is calculated, the measurement matrix is constructed and optimized, and the image is compressed by using the optimized measurement matrix. The compressed image is then scrambled and diffused to complete the encryption process. Finally, the image information is embedded into the carrier image through non-negative matrix decomposition to obtain a visually safe ciphertext image. The decryption process is the inverse of the encryption process.

Abstract: A method for constructing an artificial intelligence (AI) integrated model is provided, including: obtaining a training dataset, an initial graph network model, and a plurality of base models; then iteratively training the initial graph network model by using training data in the training dataset and the plurality of base models, to obtain a graph network model; and then constructing the AI integrated model based on the graph network model and the plurality of base models, where an input of the graph network model is a graph structure consisting of outputs of the plurality of base models. Since the graph network model considers neighboring nodes of each node in the graph structure when processing the graph structure, the graph network model fully considers differences and correlations between the base models when fusing the outputs of the plurality of base models.

Abstract: The present disclosure relates to a wide-range perpendicular sensitive magnetic sensor and the method for manufacturing the same, the magnetic sensor includes a substrate, a plurality of magnetic tunnel junctions, a plurality of magnetic flux regulators, a first output port and a second output port.

Abstract: The present disclosure relates to a wide-range perpendicular sensitive magnetic sensor and the method for manufacturing the same, the magnetic sensor includes a substrate, a plurality of magnetic tunnel junctions, a plurality of magnetic flux regulators, a first output port and a second output port.

Abstract: An antenna structure, an electronic device, and a wireless network system are provided, and relate to the field of antenna technologies. A patch antenna array includes four patch antennas. The four patch antennas are arranged in two rows and two columns. One of the feeding structures is included between two of the patch antennas in each row. One of the feeding structures is included between two of the patch antennas in each column. The feeding structure located between the two patch antennas in each column is connected to the first feeding port, so that the four patch antennas all generate polarization in a first direction. The feeding structure located between the two patch antennas in each row is connected to the second feeding port, so that the four patch antennas all generate polarization in a second direction.

Abstract: The present disclosure relates to an AC/DC closed-loop current sensor, including a magnetism gathering iron core, a TMR chip, a signal processing circuit, a signal generator, and a feedback coil. The TMR chip is arranged at an air gap of the magnetism gathering iron core and connected to the signal processing circuit. The signal processing circuit is connected to the signal generator. The feedback coil is wound around the magnetism gathering iron core and connected to the signal generator. The signal processing circuit is configured to select from the induced signal of the TMR chip and make an amplification to obtain a current signal component and send the current signal component to the signal generator. The signal generator is configured to adjust a current output to the feedback coil based on the current signal component, and output a measurement result of the selected current signal component.

Abstract: Provided are a method and device for receiving a measurement reference signal. The method includes: receiving control signaling; where the control signaling includes configuration information of a measurement reference signal, and the configuration information satisfies the following feature: configuring the measurement reference signal to occupy a frequency domain resource in a time domain symbol of a first set of time domain symbols in which a downlink control channel is located; and receiving the measurement reference signal according to the control signaling; wherein the first set of time domain symbols comprise M symbols, where M is a natural number; where the first set of time domain symbols in which the downlink control channel are determined by semi-static signaling; where a beam for the measurement reference signal and a beam for the downlink control is located channel are same in the time domain symbol.

Abstract: A method for preparing Portland cement includes: respectively weighing iron slag, copper slag, vanadium slag, and nickel slag and grinding, to yield prefabricated iron slag, prefabricated copper slag, prefabricated vanadium slag, and prefabricated nickel slag; weighing mica and kaolinite, mixing, and grinding to obtain aluminous raw materials; evenly mixing the prefabricated iron slag and the aluminous raw materials, and calcining, to yield an iron-aluminum eutectic mineral; weighing the marble, fluorite, dolomite, and quartz, evenly mixing the marble, fluorite, dolomite, and quartz with the prefabricated copper slag, prefabricated vanadium slag, and prefabricated nickel slag to yield a first mixture; grinding the iron-aluminum eutectic mineral to yield powders, and calcining a second mixture of the first mixture and the powders, to yield the cement clinker; and cooling the cement clinker, and grinding a third mixture of the cooled cement clinker and the gypsum, to yield the Portland cement.

Abstract: A method for transporting common control information includes: transmitting, by a transmitting end, to the common control information on M time-domain resources through M transmission beams, where each of the M time-domain resources includes N time-domain symbols. One time-domain resource of the M time-domain resources where the common control information of each of the M transmission beams is located is respectively determined according to a beam index of a transmission beam, wherein M and N are positive integers. One of M time-domain resources for a synchronization signal corresponds to one time-domain resource of the M time-domain resources of the common control information, a one-to-one correspondence exists between the M transmission beams and the M time-domain resources for the synchronization signal; and a one-to-one correspondence exists between the M transmission beams and M time-domain resources of a broadcast channel.

Abstract: The present invention belongs to the technical field of preparing isocyanate derivatives, and particularly relates to a storage-stable polyisocyanate composition and a preparation method therefor. The method comprises: in the presence of a catalyst system, subjecting an isocyanate monomer to a polymerization reaction; terminating the reaction after a suitable conversion rate is reached, so as to obtain a polyisocyanate reaction solution; and then performing heat treatment on the obtained polyisocyanate reaction solution to obtain a heat-treated polyisocyanate mixture, wherein the heat treatment temperature is 10-30° C. higher than the heat-sensitive temperature of the obtained polyisocyanate product, and the heat treatment time is 5-30 min; and then performing separation treatment on the heat-treated polyisocyanate mixture. When the polyisocyanate composition of the present invention is stored at 50° C.

Abstract: This application relates to the field of image annotation and recognition in the field of artificial intelligence technologies, and in particular, to a data annotation method. The method includes: using at least two different classification models; pretraining one of the classification models as an initial classification model, and annotating a label for data in a to-be-annotated source dataset as initial data by using the pretrained classification model; and controlling the classification models to perform alternating training and data annotation a quantity of times. Operations of current training and current data annotation include: obtaining data that is re-annotated with a label by a previously trained classification model, selecting a first part of the data to train a current classification model, and re-annotating, by the trained current classification model, a label for a second part of data that is not selected.

Abstract: A model training method and a related apparatus are provided, which may be used in computer vision to perform image detection. The method includes: extracting feature information in a target image; further separately extracting features of a target object from the feature information by using a Gaussian mask to obtain a first local feature and a second local feature; determining a feature loss by using the first local feature and the second local feature; performing prediction by using the first network and the second network based on a same region proposal set to obtain a first classification predicted value and a second classification predicted value, and obtaining a classification loss based on the first classification predicted value and the second classification predicted value; and training the second network based on the classification loss and the feature loss to obtain a target network.

Abstract: This application relates to the field of artificial intelligence, and specifically, to the field of computer vision. The method includes: performing feature extraction on an image to obtain a basic feature map of the image; determining a proposal of a region possibly including a pedestrian in the image; processing the basic feature map of the image to obtain an object visibility map in which a response to a pedestrian visible part is greater than a response to a pedestrian blocked part and a background part; performing weighted summation processing on the object visibility map and the basic feature map to obtain an enhanced feature map of the image; and determining, based on the proposal of the image and the enhanced feature map of the image, a bounding box including a pedestrian in the image and a confidence level of the bounding box including the pedestrian in the image.

Abstract: Example neural architecture search methods and image processing methods and apparatuses in the field of computer vision in the field of artificial intelligence are provided. The example neural architecture search method includes determining search space and a plurality of construction units, superimposing the plurality of construction units to obtain a search network, adjusting, in the search space, network architectures of the construction units in the search network, to obtain optimized construction units, and establishing a target neural network based on the optimized construction units. In each construction unit, some channels of an output feature map of each node are processed by using a to-be-selected operation to obtain a processed feature map, and the processed feature map and a remaining feature map are stitched and then input to a next node.

Abstract: In an approach for debugging and simulating application runtime execution, a processor loads source code and logs into a debug tool. A processor generates log debug information including a log map, a log variable cross reference table, and a method call stack tree. A processor determines a plurality of log blocks based on log context in the logs and the method call stack tree. A processor maps the source code to the logs for each log block. A processor suggests a starting point and a breakpoint based on the log variable cross reference table and the log blocks. A processor compares a source code variable value to a log variable value and a source code execution path to a log execution path based on the mapping set between the source code and the logs. A processor simulates the source code variable value with the log variable value.

Abstract: A keyword extraction method is provided. In the method, a candidate keyword set in a target text is obtained by processing circuitry of a server. An extraction degree of the candidate keyword is determined by the processing circuitry based on subject similarity and a text conversion frequency of a candidate keyword in the candidate keyword set. The subject similarity is between the candidate keyword and the target text. The extraction degree indicates a probability at which the candidate keyword used as a keyword matching the target text is extracted. The keyword is extracted by the processing circuitry from the candidate keyword set according to the extraction degree.

Abstract: Sensing of scene-based occurrences is disclosed. In one example, a vision sensor system comprises (1) dedicated computer vision (CV) computation hardware configured to receive sensor data from at least one sensor array and capable of computing CV features using readings from multiple neighboring sensor pixels and (2) a first processing unit communicatively coupled with the dedicated CV computation hardware. The vision sensor system is configured to, in response to processing of the one or more computed CV features indicating a presence of one or more irises in a scene captured by the at least one sensor array, generate data in support of iris-related operations to be performed by a second processing unit and send the generated data to the second processing unit.

Abstract: Use of pupillary response to visible light for iris authentication is disclosed. One example involves (a) capturing an initial image of an eye including an inner circular boundary between a pupil region and an iris region and an outer circular boundary between the iris region and a sclera region, (b) determining a first size measurement indicative of the inner circular boundary, (c) responsive to at least the first size measurement, modulating one or more visible light sources to output visible light toward the eye of the user, (d) capturing a subsequent image of the eye of the user during a period of pupillary response, (e) obtaining an iris data record of the user, and (f) comparing the iris data record of the user to one or more registered iris data records to authenticate the user.