Abstract: Provided in the present disclosure are an image collection method and apparatus, a terminal, and a storage medium. Provided in some embodiments of the present disclosure is an image collection method, which is used in an image collection apparatus and comprises: acquiring voice information; determining whether the voice information satisfies a first preset condition; if the voice information satisfies the first preset condition, determining the location of a target object; and according to the location of the target object, performing image capture on the target object so as to obtain an image of the target object. In the method of the present disclosure, when a target object needs to be shown to another person, the user does not need to manually operate the image collection apparatus for the other person to conveniently view the target object, thereby freeing both hands and improving convenience.

Abstract: An encoder determines, based on a width and a height of a block, whether or not to disable a prediction mode in which the block is split along a partitioning line defined by a distance and an angle and then prediction is performed; and encodes the block with the prediction mode disabled or not disabled according to a result of the determination on whether or not to disable the prediction mode. Here, the distance is the shortest distance between the center of the block and the partitioning line, and the angle is an angle representing a direction from the center of the block toward the partitioning line in the shortest distance. The encoder determines to disable the prediction mode when (i) a width-to-height ratio is at least 8 or (ii) a height-to-width ratio is at least 8.

Abstract: A method for ecological disturbance risk identification and assessment based on automatic parameter adjusting optimization model is disclosed. The method includes: establishing a three-layer ecological disturbance risk assessment index system based on an ecological disturbance risk identification and assessment function, performing normalization preprocessing on the assessment indexes, screening the assessment indexes meeting a multicollinearity judgement interval based on variance inflation factor method, establishing an ecological disturbance risk assessment model, optimizing weight parameters of the ecological disturbance risk assessment model based on particle swarm optimization algorithm to obtain an optimal solution of the model weight, and outputting a result of the risk index of ecological disturbance.

Abstract: Embodiments are provided for facilitating multimodal extraction across multiple granularities. In one implementation, a set of features of a document for a plurality of granularities of the document is obtained. Via a machine learning model, the set of features of the document are modified to generate a set of modified features using a set of self-attention values to determine relationships within a first type of feature and a set of cross-attention values to determine relationships between the first type of feature and a second type of feature. Thereafter, the set of modified features are provided to a second machine learning model to perform a classification task.

Abstract: The present disclosure discloses a catalyst composition for polymerization of an ?-olefin and preparation and use thereof. The catalyst composition comprises boron trifluoride and at least one protic cocatalyst; the protic cocatalyst has a structural formula of X—(CH2)n—OH, where n is an integer selected from 1 to 10; X is selected from nitro, halogen, cyano, sulfonic acid group, aldehyde group, acyl, carboxyl and amino. The catalyst can be used in production of a poly(?-olefin) synthetic base oil, and is particularly suitable for a low viscosity poly(?-olefin) synthetic base oil with high selectivity of the target product.

Abstract: Systems and methods for machine learning based multipage scanning are provided. In one embodiment, one or more processing devices perform operations that include receiving a video stream that includes image frames that capture a plurality of pages of a document. The operations further include detection, via a machine learning model that is trained to infer events from the video stream detects, a new page event. Detection of the new page event indicates that a page of the plurality of pages available for scanning has changed from a first page to a second page. Based on the detection of the new page event, the one or more processing devices capture an image frame of the page from the video stream. In some embodiments, the machine learning model detects events based on a weighted use of video data, inertial data, audio samples, image depth information, image statistics and/or other information.

Abstract: A decoder includes memory and a processor coupled to the memory and configured to: generate a first coefficient value by applying a CCALF (cross component adaptive loop filtering) process to a first reconstructed image sample of a luma component; clip the first coefficient value such that the clipped first coefficient value is within a first range from ?27 to 27?1; generate a second coefficient value by applying an ALF (adaptive loop filtering) process to a second reconstructed image sample of a chroma component; clip the second coefficient value such that the clipped second coefficient value is within a second range different from the first range; generate a third coefficient value by adding the clipped first coefficient value to the clipped second coefficient value; and generate a third reconstructed image sample of the chroma component using the third coefficient value.

Abstract: The technology described herein is directed to an adaptive sparse attention pattern that is learned during fine-tuning and deployed in a machine-learning model. In aspects, a row or a column in an attention matrix with an importance score for a task that is above a threshold importance score is identified. The important row or the column is included in an adaptive attention pattern used with a machine-learning model having a self-attention operation. In response to an input, a task-specific inference is generated for the input using the machine-learning model with the adaptive attention pattern.

Abstract: Systems, methods, and non-transitory computer-readable media can generate a natural language model that provides user-entity differential privacy. For example, in one or more embodiments, a system samples sensitive data points from a natural language dataset. Using the sampled sensitive data points, the system determines gradient values corresponding to the natural language model. Further, the system generates noise for the natural language model. The system generates parameters for the natural language model using the gradient values and the noise, facilitating simultaneous protection of the users and sensitive entities associated with the natural language dataset. In some implementations, the system generates the natural language model through an iterative process (e.g., by iteratively modifying the parameters).

Abstract: Embodiments of the disclosed technologies receive a first-party trained model and a first-party data set from a first-party system into a protected environment, receive a first third-party data set into the protected environment, and, in a data clean room, joining the first-party data set and the first third-party data set to create a joint data set for the particular segment, tuning a first-party trained model with the joint data set to create a third-party tuned model, sending model parameter data learned in the data clean room as a result of the tuning to an aggregator node, receiving a globally tuned version of the first-party trained model from the aggregator node, applying the globally tuned version of the first-party trained model to a second third-party data set to produce a scored third-party data set, and providing the scored third-party data set to a content distribution service of the first-party system.

Abstract: An encoder includes circuitry and memory coupled to the circuitry. The circuitry, in response to a first reconstructed image sample being located outside a virtual boundary, duplicates a reconstructed sample located inside and adjacent to the virtual boundary to generate the first reconstructed image sample. The circuitry generates a first coefficient value by applying a CCALF (cross component adaptive loop filtering) process to the first reconstructed image sample of a luma component. The circuitry generates a second coefficient value by applying an ALF (adaptive loop filtering) process to a second reconstructed image sample of a chroma component. The circuitry generates a third coefficient value by adding the first coefficient value to the second coefficient value, and encodes a third reconstructed image sample of the chroma component using the third coefficient value.

Abstract: An encoder includes circuitry and memory coupled to the circuitry. In operation, the circuitry: encodes information for deriving a parameter into a header of a bitstream; filters reconstructed samples in a first image using a filtering process, to generate a second image; determines whether the parameter has a predefined value; encodes a third image using the second image when the parameter has the predefined value; and encodes the third image using the first image when the parameter does not have the predefined value.

Abstract: In the method and the apparatus for thermal management and control, and the vehicle according to the present disclosure, an overtemperature threshold of the vehicle may be adjusted in off-road conditions, and/or an operating temperature of the vehicle may be obtained, and driving parameters of the vehicle may be adjusted according to the operating temperature, so as to enhance the heat dissipation performance of the vehicle in the off-road conditions, and avoid that an over-temperature protection of the engine is easily triggered when the engine is operated at a high speed and a high torque in the off-road conditions, resulting in driving experience being affected by limited torque of the engine and turn-off of an air conditioning occurring in the vehicle, and driving safety also being affected, with no high-power fan and large-size radiator being additionally installed, and thus reducing weight and manufacturing cost of the vehicles.

Abstract: An encoder determines, based on a width and a height of a block, whether or not to disable a prediction mode in which the block is split along a partitioning line defined by a distance and an angle and then prediction is performed; and encodes the block with the prediction mode disabled or not disabled according to a result of the determination on whether or not to disable the prediction mode. Here, the distance is the shortest distance between the center of the block and the partitioning line, and the angle is an angle representing a direction from the center of the block toward the partitioning line in the shortest distance. The encoder determines to disable the prediction mode when (i) a width-to-height ratio is at least 8 or (ii) a height-to-width ratio is at least 8.

Abstract: The present disclosure belongs to the technical field of sewage treatment, and discloses a method and system for enhanced culture of aerobic granular sludge. The system includes a reaction tank, a water inlet and outlet unit, an aeration unit, and a sludge discharge unit. The water inlet and outlet unit includes a water inlet pump, a water inlet electric valve, a liquid flowmeter, a sewage uniform distribution treatment device, buffers, a water drainage pipe, and a water drainage electric valve. The aeration unit includes a blower, microporous aerators, and a gas flowmeter. The sludge discharge unit includes sludge discharge pumps, a sludge discharge pipe, a sludge discharge electric valve, and a sludge concentration meter. In the present disclosure, a multi-point uniform water distribution method is used.

Abstract: Reaction products of amines and polymers containing saturated heterocyclic moieties may be used as levelers in metal electroplating baths. The reaction products may plate metal with good surface properties and good physical reliability.

Abstract: An encoder determines, based on a width and a height of a block, whether or not to disable a prediction mode in which the block is split along a partitioning line defined by a distance and an angle and then prediction is performed; and encodes the block with the prediction mode disabled or not disabled according to a result of the determination on whether or not to disable the prediction mode. Here, the distance is the shortest distance between the center of the block and the partitioning line, and the angle is an angle representing a direction from the center of the block toward the partitioning line in the shortest distance. The encoder determines to disable the prediction mode when (i) a width-to-height ratio is at least 8 or (ii) a height-to-width ratio is at least 8.

Abstract: An encoder includes circuitry and memory coupled to the circuitry. In operation, the circuitry: encodes information for deriving a parameter into a header of a bitstream; filters reconstructed samples in a first image using a filtering process, to generate a second image; determines whether the parameter has a predefined value; encodes a third image using the second image when the parameter has the predefined value; and encodes the third image using the first image when the parameter does not have the predefined value.

Abstract: There is provided a semiconductor device 100, comprising: at least one semiconductor chip 5, and a structure 2 thermally coupled to the at least one semiconductor chip 5, wherein the structure 2 comprises a surface located within an interior of the semiconductor device, and the surface comprises a groove 12; and a sensor 16 comprising an optical fibre 13 passing through the groove 12, wherein the sensor 16 is configured to sense a temperature of the at least one semiconductor chip 5.

Abstract: Techniques and systems are provided for predicting answers in response to one or more input queries. For instance, text from a corpus of text can be processed by a reader to generate one or multiple question and answer spaces. A question and answer space can include answerable questions and the answers associated with the questions (referred to as “question and answer pairs”). A query defining a question can be received (e.g., from a user input device) and processed by a retriever portion of the system. The retriever portion of the system can retrieve an answer to the question from the one or more pre-constructed question and answer spaces, and/or can determine an answer by comparing one or more answers retrieved from the one or more pre-constructed question and answer spaces to an answer generated by a retriever-reader system.