Tencent Technology (Shenzhen) Company Limited

Aac Technologies Pte. Ltd.

Huawei Technologies Co., Limited

Zte Corporation

Huawei Device Co., Ltd.

Shenzhen Idata Technology Company Ltd.

Other

Byd Company Limited

Honor Device Co., Ltd.

Shenzhen Kiwi Instruments Corporation

Tencent Technology Company Limited

Jing Zhao

Hua Li

Lei Liu

Chao Wang

Xiaoyue Xia

Zhimin Zhu

Wei Li

Zhishan Zhuang

Xuanliang Pan

Yabing Feng

Xiaoxiao Chen

Bin Hu

Bo Hu

Lichun Liu

Zhengdong Yong

Haixia Chai

Junbin Lai

Yu Liao

Chao He

Dongsheng Wang

Shian Shen

Qingyu Cui

Xiuming Yuan

Hao Tang

Wei Zhao

Chong Zhu

Dajiang Wang

Chao Ding

Chundong Li

Bo Liu

Meng Deng

Hailin Lei

Zhenchao Lin

Ronggen Li

Munyong Choi

Xiufeng Yu

Fengyong Qian

Jinbo Li

Honghui Wu

Lijun Dong

Shun Xu

Mingqian Shao

Yongsong Liu

Dongzhi Zhao

Lanying Wei

Shoudong Lu

A method is applied to an electronic device, and includes: obtaining content copied by a user on a first page, and determining a category to which the content belongs; obtaining a category of a second page; matching the category of the content against the category of the second page; and if a matching result is not empty, displaying at least one operation option on the second page, where the at least one operation option has a function of performing an operation for the content on the second page, so that the electronic device directly performs the function after the user selects the operation option.

Method and apparatus for displaying text content copied from a first application in a second application

The present disclosure provides a RFID terminal and a method of using the same. The RFID terminal includes: a directional antenna module configured to directionally receive a signal transmitted by an electronic tag on an item in a region to be read; a camera configured to collect an image of the region to be read; and a control unit configured to screen information of a target item according to the image of the region to be read captured by the camera.

RFID terminal and method of using the same

A control circuit for controlling power switch in switching power supply circuit. The optimization circuit comprises an adaptive amplitude jitter generating circuit, a comparison circuit and a trigger circuit. The adaptive amplitude jitter generating circuit is used to generate a periodic amplitude jitter signal according to the feedback voltage signal indicative of the output of the switching power supply circuit. The comparison circuit is used to compare the sampled voltage signal with periodic amplitude jitter signal, and generate an output signal with periodic fluctuations. The trigger circuit is used for outputting the control signal for driving the power switch according to the output signal with periodic fluctuations and the clock signal.

Control circuit for controlling a power switch in a switching power supply circuit for improved EMI performance

A data processing method and device are provided. The method includes: extracting a plurality of data sets from unlabeled data; and for each data set, creating a plurality of sample sets by assigning labels to data samples in the data set, respectively training, for each sample set created from the data set, a classifier by using the sample set and labeled data, obtaining a sample set that corresponds to a trained classifier with the highest performance, and adding the obtained sample set to a candidate training set. Each sample set includes the first preset number of data samples with respective labels, the labels of the data samples in each sample set constitutes a label combination, and label combinations corresponding to different sample sets are different from each other. The method also includes adding a second preset number of sample sets in the candidate training set to the labeled data.

Data processing method and device, classifier training method and system, and storage medium

A machine learning model training method includes: training a machine learning model using features of samples in a training set, where a sample in the training set corresponds to an initial first weight and an initial second weight. In one iteration, the method includes: determining a first sample set comprising one or more samples whose corresponding target variables are incorrectly predicted; determining an overall predicted loss of the first sample set based on the predicted losses and corresponding first weights of samples in the first sample set; updating the first weights and second weights of the samples in the first sample set based on the overall predicted loss of the first sample set; and inputting the second weights, the features, and the target variables of the samples in the training set to the machine learning model, and initiating a next iteration of training the machine learning model.

Machine learning model training method and apparatus, server, and storage medium

A screen display control method may be implemented by an electronic device configured with a foldable touchscreen. The touchscreen includes a first area and a second area. A first interface is displayed in a first area and a first operation is detected in a first interface. A second interface is displayed in a second area in response to the first operation and the second interface is associated with content displayed in the first interface.

Screen display control method and electronic device

The present disclosure discloses a method, a related apparatus and storage medium for distributed transaction processing. The method includes: obtaining, by a distributed transaction processing device, a distributed transaction processing request; writing, by the distributed transaction processing device, a commit log corresponding to the distributed transaction processing request to a second object database set in the target database cluster, the commit log comprising a commit indication result; obtaining, by the distributed transaction processing device after the distributed transaction processing device resumes distributed transaction processing, the commit log from the second object database set; and performing, by the distributed transaction processing device when the commit indication result in the commit log instructs to commit the processing operation on the account data in the N accounts, the processing operation on the account data in the N accounts. The present disclosure resolves a technical problem that the accuracy of distributed transaction processing cannot be ensured when established steps of a distributed transaction are interrupted.

Distributed transaction processing method and related apparatus

Embodiments of the present invention disclose a method and an apparatus for managing a notification bar message. The method according to the present invention includes: searching for a resident notification message; after the resident notification message is found, displaying, in a notification bar, prompt information prompting whether to delete the resident notification message; and if a user chooses to delete the resident notification message, deleting the resident notification message according to a system permission.

Method and apparatus for managing notification bar message

This application provides example circuit modules and example electronic devices comprising the circuit module. One example circuit module includes a power input terminal, a power output terminal, a first switching transistor, a second switching transistor, a comparison unit, a boost unit, an energy storage unit, and a direct current conversion unit, where the first switching transistor is turned on and the second switching transistor is cut off when a source voltage input by the power input terminal to the comparison unit is greater than the preset threshold, or the first switching transistor is cut off and the second switching transistor is turned on when a source voltage input by the power input terminal to the comparison unit is less than or equal to the preset threshold.

Circuit module and electronic device

Night light

A machine learning model training method includes: training a machine learning model using features of each sample in a training set based on an initial first weight and an initial second weight. In one iteration, the method includes determining a first sample set in which a target variable is incorrectly predicted, and a second sample set in which a target variable is correctly predicted, based on a predicted loss of each sample; and determining overall predicted loss of the first sample set based on a predicted loss and a first weight of each sample in the first sample set. The method also includes updating the first weight and a second weight of each sample in the first sample set based on the overall predicted loss; and inputting the updated second weight, the features, and the target variable of each sample to the machine learning model, and initiating a next iteration.

Embodiments of the present invention disclose a method and an apparatus for managing a notification bar message. The method includes: searching for a resident notification message; after the resident notification message is found, displaying, in a notification bar, prompt information prompting whether to delete the resident notification message; and if a user chooses to delete the resident notification message, deleting the resident notification message according to a system permission.

An antenna module and a mobile terminal are provided. The antenna module is applied to a mobile terminal, and the mobile terminal includes a 3D glass back cover. The antenna module includes a patch antenna provided inside of the 3D glass back cover and spaced apart from the 3D glass back cover by a predetermined distance. The patch antenna is fed with power through a probe and operates in millimeter wave bands. The antenna module and the mobile terminal provided effectively improve the impedance bandwidth by changing a position of a feeding point.

Antenna module and mobile terminal

Growing community of inventors

Shenzhen, China

Jing Zhao