Huawei Technologies Co., Limited

Future Wei Technologies, Inc.

Avary Holding (Shenzhen) Co., Limited.

Hongqisheng Precision Electronics (Qinhuangdao) Co., Ltd.

Zte Corporation

Alibaba Group Holding Limited

Advanced New Technologies Co., Ltd.

Zhejiang University

Xi'an Zhongxing New Software Co., Ltd.

Huawei Digital Power Technologies Co., Ltd.

The Hong Kong Polytechnic University

Byd Company Limited

Lei Zhou

Frank J Effenberger

Xiang Liu

Bo Gao

Dawei Wang

Shengping Li

Huafeng Lin

Rui-Wu Liu

Ming-Jaan Ho

Yali Wang

Huaiyu Zeng

Ning Cheng

Xiaofeng Zhang

Xuming Wu

Mian Huang

Yuqun Fan

Xiaofei Zeng

Jianzhuang Liu

Lin Huang

Shiwei Nie

Man-Zhi Peng

Liming Fang

Kangmin Huang

Qiang Guo

Zhenxing Liao

Yong He

Shanfu Li

Chao Lv

Weihua Qiao

Guo Zhao

Guo Ji Wei

Shan Chen

Min Zhou

Dawei Huo

Shaohua Wang

Zhenping Wang

Shuchang Yao

Yitao Song

Guikai Peng

Meng Sui

Yu Qiao

Lihui Jiang

Xianbo Dai

Shengming Ma

Qiong Zhou

Yunpeng Xie

Xueli Kong

Minghui Tao

Xiaojian Cao

Jing Ge

Xiangyong Hao

Xiaoqiu Li

Yongjian Zhan

Botao Liu

Xin Wang

Zhengjun Qiu

Kuo Zhang

Borui Li

Nan Zhao

Guo Wei

Embodiments of this application provide a method and an apparatus for obtaining a transmitter test parameter, and a storage medium. The method includes: performing waveform sampling on an optical signal sent by a transmitter, to obtain a sampled electrical signal, obtaining a first noise amount associated with the sampled electrical signal based on a preset initial noise ratio parameter and a level amplitude of the sampled electrical signal, and obtaining a second noise amount associated with an ideal electrical signal based on the initial noise ratio parameter and a level amplitude of the ideal electrical signal. According to the application, a noise amount associated with a level amplitude of a sampled electrical signal is obtained without limiting a type of a receiver that performs a consistency test on a transmitter by using a transmitter test parameter.

Method and apparatus for obtaining transmitter test parameter, and storage medium

Embodiments of this application disclose a board, an optical module, a media access control (MAC) chip, a digital signal processor (DSP), and an information processing method. The board in the embodiments of this application includes a MAC chip, a DSP, and an equalizer. The MAC chip is configured to send first information to the DSP at an optical network unit (ONU) online stage, where the first information includes a first ONU identifier. The DSP is configured to receive the first information, and determine a first reference equalization parameter, where the first reference equalization parameter is related to the first ONU identifier. The DSP is further configured to set an equalization parameter of the equalizer to the first reference equalization parameter.

Board, optical module, OLT, and information processing method

A data transmission method includes receiving, by an optical line terminal (OLT) from an optical network unit (ONU), uplink burst data that includes a synchronization data block and a payload, where the synchronization data block includes first synchronization data, wherein the first synchronization data includes a first preamble and an ONU identifier, and a first bandwidth occupied by the first frequency distribution of the first synchronization data is narrower than a second bandwidth occupied by the second frequency distribution of the payload, and obtaining, by the OLT from the first synchronization data, the ONU identifier.

Data transmission method, related apparatus, and system

A plug status detection circuit, a controller, and a vehicle are provided, to detect a plug status in different standards by using one detection circuit. The plug status detection circuit includes a wake-up circuit and a sampling circuit. The wake-up circuit is configured to immediately output or delay outputting a wake-up signal based on a resistance value of a connected resistor of the plug status detection circuit when a plug is connected to a socket, where the wake-up signal is used to trigger a CPU to drive the sampling circuit. The sampling circuit is configured to inject a startup voltage under the drive of the CPU, and after the startup voltage is injected, a level of a detection point of the sampling circuit is used to indicate a plug status.

Plug status detection circuit, controller, and vehicle

The present application discloses a data transmission method and apparatus. Multiple first data blocks of one service are received by a network interface card and the card allocates the received multiple first data blocks to a same data queue. When a tuner generates scheduling information for the service, the multiple first data blocks is sent to a virtual machine by using a resource in a resource pool of a NUMA node designated in the scheduling information; or when a tuner does not generate scheduling information, determining, according to a correspondence between the data queue and a resource pool of a NUMA node, a resource pool corresponding to the data queue in which the multiple first data blocks are located, and sending the multiple first data blocks to a virtual machine.

Data transmission method and apparatus using resources in a resource pool of a same NUMA node

An action recognition method and apparatus related to artificial intelligence and include extracting a spatial feature of a to-be-processed picture, determining a virtual optical flow feature of the to-be-processed picture based on the spatial feature and X spatial features and X optical flow features in a preset feature library, where the X spatial features and the X optical flow features include a one-to-one correspondence, determining a first type of confidence of the to-be-processed picture in different action categories based on similarities between the virtual optical flow feature and Y optical flow features, where each of the Y optical flow features in the preset feature library corresponds to one action category, X and Y are both integers greater than 1, and determining an action category of the to-be-processed picture based on the first type of confidence.

Action recognition method and apparatus

Embodiments of this application disclose a board, an optical module, a MAC chip, a DSP, and an information processing method. The board in the embodiments of this application includes a media access control (MAC) chip, a digital signal processor (DSP), and an equalizer. The MAC chip is configured to send first information to the DSP at an optical network unit (ONU) online stage, where the first information includes a first ONU identifier. The DSP is configured to receive the first information, and determine a first reference equalization parameter, where the first reference equalization parameter is related to the first ONU identifier. The DSP is further configured to set an equalization parameter of the equalizer to the first reference equalization parameter.

A method for manufacturing a printed circuit board (PCB) with high component density includes at least two reinforcing plates, at least two connecting plates, a first circuit board unit, and a second circuit board unit. The reinforcing plate includes a supporting portion, a first connecting portion, and a second connecting portion. The first connecting portion and the second connecting portion connect to ends of the supporting portion. The connecting plates are bendable circuit boards. Each connecting plate is attached to the supporting portion, the first connecting portion, and the second connecting portion of a reinforcing plate. The first circuit board unit is fixed and electrically connected to a connecting plate away from first connecting portion. The second circuit board unit is fixed and electrically connected to a connecting plate away from the second connecting portion.

Printed circuit board and method for manufacturing the same

The present invention discloses a method and an apparatus for measuring leaf nitrogen content (LNC), and belongs to the spectral analysis and artificial intelligence (AI) field. The method includes the following steps: (1) obtaining a single-band image of a target leaf illuminated by a light source in a single feature band; (2) repeating step (1), to collect image information in four feature bands; (3) combining the collected images in the four feature bands into a four-channel spectral image; (4) training a deep learning model by using the spectral image and a corresponding nitrogen content label, to obtain a nitrogen content prediction model; (5) transplanting the trained nitrogen content prediction model into an AI control system; (6) collecting information about a to-be-predicted leaf sample, predicting nitrogen content by using an AI sensor equipped with the AI control system, and outputting the predicted nitrogen content.

Method and apparatus for measuring leaf nitrogen content

This disclosure relates to identification preprocessing. In one aspect, a method includes receiving at an identification server, and from a mobile computing device that has entered a predetermined area surrounding a biometric feature collection device, a group identifier of a user group to which a user of the mobile computing device belongs. The group identifier is transmitted by the mobile computing device in response to the mobile computing device receiving a radio signal broadcast to the predetermined area. The user group is one of multiple user groups. Based on the group identifier, the identification server selects, from a stored registration biometric feature set, a registration biometric feature associated with each user in the user group. The identification server adds the registration biometric feature to a screening feature set established for the biometric feature collection device. Biometric feature-based identification is performed on the user using the screening feature set.

Identification preprocessing

Data transmission method and apparatus using resources in a resource pool of a same NUMA mode

A radio channel control method includes: collecting a real-time user experience index for access to a media service by a user terminal, and collecting a media service transmission parameter of the media service provided by a server; determining whether the real-time user experience index is less than a user experience index defined in a user experience level of an ordered traffic package of the user terminal, and if the real-time user experience index is less than the user experience index defined in the user experience level of the ordered traffic package of the user terminal, calculating, by using the real-time user experience index and the media service transmission parameter, a radio channel parameter that is required by the user experience index; and transmitting the radio channel parameter to a core network device.

Radio channel control method, traffic package trading and recommending methods, and related device

Growing community of inventors

Shenzhen, China

Lei Zhou