Abstract: Embodiments of the present application relate to the field of cooking devices. Disclosed are a lid body assembly and a cooking apparatus. The lid body assembly comprises a pot lid, an air blowing apparatus, and a check valve. The pot lid is used for covering a pot body having a cooking cavity to open and close the cooking cavity. The air blowing apparatus is arranged in the pot lid to blow air into the cooking cavity. The check valve is used for allowing airflow to flow from the air blowing apparatus to the cooking cavity in one direction.

Abstract: Disclosed is an unmanned aerial vehicle (UAV)-aided over-the-air computing system based on full-duplex relay and a trajectory and power optimization method thereof. The UAV-aided over-the-air computing system adopts the UAV as a full-duplex relay for data fusing and forwarding. The method of the application aims at minimizing an average mean square error of over-the-air computing, and solves an optimization problem under constraints of sensor transmitting power, information transmission rate, UAV trajectory and denoising factor. For an overall joint optimization problem, each optimization variable is determined one by one by an alternative optimization method according to the high coupling of optimization variables.

Abstract: System and method for aspect-level sentiment classification. The system includes a computing device, the computing device has a processer and a storage device storing computer executable code. The computer executable code is configured to: receive a sentence having a labeled aspect term and context; convert the sentence into a dependency tree graph; calculate an attention matrix of the dependency tree graph based on one-hop attention between any two nodes of the graph; calculate multi-head attention diffusion for any two nodes from the attention matrix; obtain updated embedding of the graph using the multi-head diffusion attention; classify the aspect term based on the updated embedding of the graph to obtain predicted classification of the aspect term; calculate loss function based on the predicted classification and the ground truth label of the aspect term; and adjust parameters of models in the computer executable code based on the loss function.

Abstract: The present disclosure provides a self-service settlement method, apparatus and storage medium, and relates to the technical field of self-service shopping, wherein the method includes: obtaining a monitoring image acquired by an image capture device and corresponding to commodities to be settled which are placed on a settlement counter; obtaining information of the commodities to be settled through image recognition; obtaining a first weight acquired by a weight detection device, obtaining a second weight based on the information of the commodities to be settled, judging whether the information of the commodities to be settled is matched with commodities to be confirmed according to a weight comparison result; and obtaining purchased commodity settlement information under the condition that the information of the commodities to be settled is matched with the commodities to be confirmed, and performing checkout processing.

Abstract: A method and an electronic device for pedestrian re-identification are provided. The method may include: collecting a target image set including at least two target images, where each target image includes at least one person; extracting a global feature and a head-shoulder feature of each person in each target image in the target image set, where the global feature is an overall appearance feature, and the head-shoulder feature is a feature of a head part and a shoulder part determining a representation feature of each person in each target image based on the global feature and the head-shoulder feature of each person in each target image; and determining a given person in different target images based on the representation feature of each person in each target image.

Abstract: A method for intelligent fault detection and location of a power distribution network is provided, which includes: constructing a network topology of the power distribution network, updating the network topology in real time to obtain an updated network topology, performing a fault identification based on the updated network topology, performing a fault locating based on the updated network topology to determine a fault node, and identifying a fault type based on a fault recorded signal of the fault node. With this method, fault locations and fault types of the power distribution network can be accurately detected in real time.

Abstract: System and method for aspect-level sentiment classification. The system includes a computing device, the computing device has a processer and a storage device storing computer executable code. The computer executable code is configured to: receive an aspect term-sentence pair; embed the aspect term-sentence pair; parse the sentence using multiple parsers to obtain dependency trees, and perform edge union to obtain a merged graph; combine the embedding and the merged graph to obtain a relation graph; perform a relation graph neural network on the relation graph; extract hidden representation of the aspect term from updated relation neural network; and classify the aspect term based on the extracted representation to obtain a predicted classification label of the aspect term. During training, the computer executable code is further configured to calculate a loss function based on the predicted label and the ground truth label, and adjust parameters of models.

Abstract: The present disclosure relates to an information sending method, apparatus, system and a computer readable storage medium, and pertains to the technical field of computers. The method in the present disclosure includes: analyzing video data of an offline user to determine an attribute of the offline user; searching for historical access information of at least one online user matching the attribute of the offline user; and determining at least one object recommended to the offline user according to the historical access information of each of the at least one online user, and sending information of the at least one object to the offline user.

Abstract: The present disclosure relates to a sequenced data processing method and device, and a text processing method and device, and relates to the field of data processing.

Abstract: In one aspect of the present application, a computer-implemented method for setting a local coordinate system of a tooth 3D digital model is provided, the method comprises: obtaining a first 3D digital model representing a first tooth, wherein the first 3D digital model is based on a world coordinate system; and setting a local coordinate system for the first 3D digital model using a first artificial neural network based on the first 3D digital model, where the first artificial neural network is a trained deep learning artificial neural network.

Abstract: A method for intelligent fault detection and location of a power distribution network is provided, which includes: constructing a network topology of the power distribution network, updating the network topology in real time to obtain an updated network topology, performing a fault identification based on the updated network topology, performing a fault locating based on the updated network topology to determine a fault node, and identifying a fault type based on a fault recorded signal of the fault node. With this method, fault locations and fault types of the power distribution network can be accurately detected in real time.

Abstract: Mechanisms are provided for implementing a Question Answering (QA) system utilizing a trained generator of a generative adversarial network (GAN) that generates a bag-of-ngrams (BoN) output representing unlabeled data for performing a natural language processing operation. The QA system obtains a plurality of candidate answers to a natural language question, where each candidate answer comprises one or more ngrams. For each candidate answer, a confidence score is generated based on a comparison of the one or more ngrams in the candidate answer to ngrams in the BoN output of the generator neural network of the GAN. A final answer to the input natural language question is selected from the plurality of candidate answers based on the confidence scores associated with the candidate answers, and is output.

Abstract: Software that generates an answer to an input question using a source document by performing the following operations: (i) receiving a question; (ii) generating a plurality of vectors including a first vector representation of a term in the question and a second vector representation of a term in a source document; (iii) providing each dimension of each of the first vector representation and the second vector representation into a respective input node of an artificial neural network; (iv) determining whether the source document is relevant to answering the question based, at least in part, on an output generated by the artificial neural network; and (v) in response to determining that the source document is relevant, generating an answer to the question utilizing the source document.

Abstract: System and method for aspect-level sentiment classification. The system includes a computing device, the computing device has a processer and a storage device storing computer executable code. The computer executable code is configured to: receive a sentence having a labeled aspect term and context; convert the sentence into a dependency tree graph; calculate an attention matrix of the dependency tree graph based on one-hop attention between any two nodes of the graph; calculate multi-head attention diffusion for any two nodes from the attention matrix; obtain updated embedding of the graph using the multi-head diffusion attention; classify the aspect term based on the updated embedding of the graph to obtain predicted classification of the aspect term; calculate loss function based on the predicted classification and the ground truth label of the aspect term; and adjust parameters of models in the computer executable code based on the loss function.

Abstract: Mechanisms are provided to implement a generative adversarial network (GAN) for natural language processing. With these mechanisms, a generator neural network of the GAN is configured to generate a bag-of-ngrams (BoN) output based on a noise vector input and a discriminator neural network of the GAN is configured to receive a BoN input, where the BoN input is either the BoN output from the generator neural network or a BoN input associated with an actual portion of natural language text. The mechanisms further configure the discriminator neural network of the GAN to output an indication of a probability as to whether the input BoN is from the actual portion of natural language text or is the BoN output of the generator neural network.

Abstract: The present disclosure provides a self-service settlement method, apparatus and storage medium, and relates to the technical field of self-service shopping, wherein the method includes: obtaining a monitoring image acquired by an image capture device and corresponding to commodities to be settled which are placed on a settlement counter; obtaining information of the commodities to be settled through image recognition; obtaining a first weight acquired by a weight detection device, obtaining a second weight based on the information of the commodities to be settled, judging whether the information of the commodities to be settled is matched with commodities to be confirmed according to a weight comparison result; and obtaining purchased commodity settlement information under the condition that the information of the commodities to be settled is matched with the commodities to be confirmed, and performing checkout processing.

Abstract: A commodity recommendation method, apparatus and system, and a computer readable storage medium. The method includes: analyzing an image of a specific offline customer currently entering a store to obtain an attribute of the specific offline customer; determining an online user matching the specific offline customer according to the attribute of the specific offline customer; constructing a collection of popular commodities of the store according to commodities corresponding to stay positions of offline customers who have entered the store before; and recommending a commodity to the specific offline customer according to a historical shopping information of the online user and the collection of popular commodities.

Abstract: In one aspect of the present application, a computer-implemented method for setting a local coordinate system of a tooth 3D digital model is provided, the method comprises: obtaining a first 3D digital model representing a first tooth, wherein the first 3D digital model is based on a world coordinate system; and setting a local coordinate system for the first 3D digital model using a first artificial neural network based on the first 3D digital model, where the first artificial neural network is a trained deep learning artificial neural network.

Abstract: The present disclosure relates to an information sending method, apparatus, system and a computer readable storage medium, and pertains to the technical field of computers. The method in the present disclosure includes: analyzing video data of an offline user to determine an attribute of the offline user; searching for historical access information of at least one online user matching the attribute of the offline user; and determining at least one object recommended to the offline user according to the historical access information of each of the at least one online user, and sending information of the at least one object to the offline user.

Abstract: A method for segmenting 3D digital model of jaw is provided. The method includes: obtaining a first 3D digital model of jaw; and segmenting the first 3D digital model of jaw using a trained deep artificial neural networks.