Abstract: A method for converting state space representation (SSR) information to observation space representation (OSR) information includes: obtaining the SSR information, obtaining the OSR information, obtaining information of a virtual observation distance, and obtaining delay information of a troposphere and delay information of an ionosphere. A device for converting SSR information to OSR information includes: a satellite antenna, a global navigation satellite system (GNSS) board, a radio antenna, a mobile network module and antenna, a Bluetooth module and antenna, a Wi-Fi module and antenna, a status indicator light, a plurality of output interfaces, and a power supply unit. A conversion algorithm is realized for converting SSR information to OSR information, and the converted OSR information follows the international standard protocols and can be received by most GNSS receivers. A conversion device is developed based on the aforementioned method.

Abstract: In a method for determining a resource of an asynchronous physical uplink shared channel PUSCH, user equipment (UE) receives time domain resource configuration information and frequency domain resource configuration information from a network device. The UE sets, based on the time domain resource configuration information, a time domain position of a first hop of a first PUSCH and a time domain position of a second hop of the first PUSCH to be inconsecutive in the time domain. The UE then determines a frequency domain position of the first hop of the first PUSCH and a frequency domain position of the second hop of the first PUSCH based on the frequency domain resource configuration information.

Abstract: The application provides a data sending method and a communication apparatus to avoid signaling overheads caused by scheduling by a network device, and a terminal device can flexibly select a quantity of repeated transmissions based on an actual situation, so that data transmission performance is improved. The network device sends configuration information of a receive power to the terminal device. After receiving the configuration information of the receive power, the terminal device determines a quantity of repeated transmissions of target data based on the configuration information of the receive power. After determining the quantity of repeated transmissions of the target data, the terminal device sends the target data to the network device based on the quantity of repeated transmissions of the target data.

Abstract: An uplink control information transmission method and apparatus. The method includes: determining, by a terminal device, a preamble that needs to be sent; determining, by the terminal device based on the preamble, a first resource set that is in a physical uplink shared channel resource and that is used to send uplink control information, where the PUSCH resource includes a plurality of resource sets; and sending, by the terminal device, the uplink control information and uplink data on the PUSCH resource, where the uplink control information is mapped to the first resource set, the uplink data is mapped to a resource that is other than the plurality of resource sets and that is in the PUSCH resource, and no information or uplink data is mapped to a resource set that is other than the first resource set and that is in the plurality of resource sets.

Abstract: Provided herein is a bi-phase composition comprising: (A) a continuous aqueous phase; (B) an oil phase comprising an unstable active agent, and (C) hydrophobic particles adhered on the surface of the oil phase.

Abstract: The purpose of the present invention is to enable learning of a neural network for extracting features of images having high robustness from an undiscriminating image region while minimizing the number of parameters of a pooling layer. A parameter learning unit 130 learns parameters of each layer in a convolutional neural network configured by including a fully convolutional layer for performing convolution of an input image to output a feature tensor of the input image, a weighting matrix estimation layer for estimating a weighting matrix indicating a weighting of each element of the feature tensor, and a pooling layer for extracting a feature vector of the input image based on the feature tensor and the weighting matrix.

Abstract: A system is provided for determining when supplemental content unresponsive to a user input is to be presented during a user interaction. The system determines an action, performance of which, may trigger output of supplemental content. The system may determine when, during a user interaction corresponding to performance of the action, supplemental content may be presented. The system may use constraint data indicating a device type via which the content may be presented, and a time duration during which the supplemental content may be presented. If the constraint data is satisfied, the system may determine to present the supplemental content.

Abstract: An image adjustment device includes: an illumination component derivation unit that derives an illumination component of a grayscale image; a reflectance component derivation unit that derives a reflectance component image that is a resulting image in which the illumination component is removed from the grayscale image; a contrast component derivation unit that derives a contrast component based on a contrast value between a pixel of the reflectance component image and a peripheral area of the pixel; a histogram derivation unit that derives a luminance histogram of the grayscale image weighted according to the contrast value for each pixel of the contrast component; a conversion function derivation unit that derives a luminance conversion function for converting a luminance such that a luminance histogram of a converted grayscale image in which the grayscale image is converted by the luminance conversion function and a predetermined histogram are matched with or similar to each other; and a luminance conversi

Abstract: A method for converting state space representation (SSR) information to observation space representation (OSR) information includes: obtaining the SSR information, obtaining the OSR information, obtaining information of a virtual observation distance, and obtaining delay information of a troposphere and delay information of an ionosphere. A device for converting SSR information to OSR information includes: a satellite antenna, a global navigation satellite system (GNSS) board, a radio antenna, a mobile network module and antenna, a Bluetooth module and antenna, a Wi-Fi module and antenna, a status indicator light, a plurality of output interfaces, and a power supply unit. A conversion algorithm is realized for converting SSR information to OSR information, and the converted OSR information follows the international standard protocols and can be received by most GNSS receivers. A conversion device is developed based on the aforementioned method.

Abstract: Techniques for performing tests by a speech processing system are described. A speech processing system may apply a hash function to a group of user identifiers, a content provider identifier, and time data to segment the group of user identifiers into non-holdout, holdout control, and holdout treatment groups. A non-holdout group represents users not subject to a test for a duration of time. A holdout control group represents users subject to a test for the duration of time, but which do not receive unresponsive content during the duration of time. A holdout treatment group represents users subject to a test and which receive unresponsive content over the duration of time. User activity of the holdout control and holdout treatment groups may be compared to measure an effectiveness of the unresponsive content. The measured effectiveness may be used to determine a ranking of the content provider at runtime.

Abstract: A search apparatus for searching media data for a target region that matches query data includes a first feature extraction unit configured to extract a first feature vector from the query data using a first trained neural network; a second feature extraction unit configured to obtain a first region from the media data and extract a second feature vector from the first region using a second trained neural network; a localization unit configured to determine a candidate for the target region using a third trained neural network, based on the first feature vector, the second feature vector, and the first region or a location of the first region; and a control unit configured to repeat the operations of the second feature extraction unit and the localization unit until a predetermined condition is satisfied, by using the determined candidate for the target region as the first region to be used by the second feature extraction unit.

Abstract: The present invention provides a two-component foamable silicone composition comprising: a component A comprising (a) at least one polyorganosiloxane having at least one vinyl group, (b) at least one chemical blowing agent, and (c) at least one catalyst; and a component B comprising (d) at least one polyorganosiloxane having at least one vinyl group, and (e) at least one polyorganosiloxane having at least one —SiH group, and at least one expandable graphite in an amount of less than 10% by weight, based on the total weight of the component B, which exhibits excellent flame retardancy, good sealing performance, high compression rate, low gasket density, good dispensing continuity and good cell structure. The present invention also provides a preparing method and use thereof.

Abstract: The purpose of the present invention is to enable learning of a neural network for extracting features of images having high robustness from an undiscriminating image region while minimizing the number of parameters of a pooling layer. A parameter learning unit 130 learns parameters of each layer in a convolutional neural network configured by including a fully convolutional layer for performing convolution of an input image to output a feature tensor of the input image, a weighting matrix estimation layer for estimating a weighting matrix indicating a weighting of each element of the feature tensor, and a pooling layer for extracting a feature vector of the input image based on the feature tensor and the weighting matrix.

Abstract: An image collation device includes: a tentative matching point extraction unit configured to extract a plurality of tentative matching points that are pairs of corresponding feature points between a pair of input images; and a spatial verification unit configured to evaluate a degree of similarity between the pair of input images on the basis of all of a limiting conditions regarding consistency of a scale factor, a limiting conditions regarding consistency of a rotational angle, and a limiting conditions regarding consistency of a relative positional relationship according to a comparison of or a difference between geometric transformation parameters of the tentative matching points for each of the pairs of tentative matching points that is a combination of the tentative matching points extracted by the tentative matching point extraction unit.

Abstract: An image collation device includes: a tentative matching point extraction unit configured to extract a plurality of tentative matching points that are pairs of corresponding feature points between a pair of input images; and a spatial verification unit configured to evaluate a degree of similarity between the pair of input images on the basis of all of a limiting conditions regarding consistency of a scale factor, a limiting conditions regarding consistency of a rotational angle, and a limiting conditions regarding consistency of a relative positional relationship according to a comparison of or a difference between geometric transformation parameters of the tentative matching points for each of the pairs of tentative matching points that is a combination of the tentative matching points extracted by the tentative matching point extraction unit.