Beijing Boe Optoelectronics Technology Co., Ltd.

Mediatek Singapore Pte. Ltd.

Boe Technology Group Co., Ltd.

Beijing Boe Technology Development Co., Ltd.

National Institute of Metrology, China

Chinese Research Academy of Environmental Sciences

Shenzhen Qianhai Qiming Technology Co., Ltd.

Beijing Institute of Nanoenergy and Nanosystems

Wei Tang

Qiang Wang

Lei Guo

Yan Wu

Pengju Zhang

Zhengxin Zhang

Jiali Zhang

Jian Gao

Xin Zhou

Yang Li

Jun Xu

Zhen Song

Yang Yu

Chi Zhang

Ye Wy Wang

Limin Zhang

Hanqing Liu

Shijie Liu

Chao Fu

Tong Wu

Zhonglin Wang

Junrui Cui

Long Liu

Quanping Wang

Yao Yao

Lixia Wang

Qingfei Shen

Zhongzhi Zhang

Xuezhi Dai

Dazhi Wu

Yunlang Wang

Ye Wang

Zhipeng Di

Xiaohui Du

Xinhua Pang

Anxiang Li

Miaomiao Cheng

A standard for near end crosstalk of a category 6A cable, including a registered jack 45 (RJ45), a clamp connected to the RJ45, a first attenuator and a second attenuator. The RJ45 includes a first signal twisted pair to transmit a first source signal and a second source signal, and a second signal twisted pair to transmit a third source signal and a fourth source signal. The clamp includes a first signal pair connector electrically connected to the first signal twisted pair, a second signal pair connector electrically connected to the second signal twisted pair, a first differential amplification circuit and a second differential amplification circuit. The first attenuator is electrically connected to the first signal pair connector. The second attenuator is electrically connected to the second signal pair connector. The second attenuator and the first attenuator are configured to detect the near end crosstalk.

Standard for near end crosstalk of category 6A cable (CAT 6A)

The present disclosure provides a gate driving circuit, a display panel, a driving method and a display device. The gate driving circuit includes an input module, a pull-up node, an output module, a first pull-down node, a first pull-down node control module and a first suppression module. The first pull-down node control module controls to connect the first connection node and the first pull-down node under the control of the pull-up node, and inputs the signal provided by the second signal terminal to the first pull-down node under the control of the potential of the first pull-down node; the first suppression module inputs the signal provided by the first level signal terminal to the first connection node under the control of the pull-up node.

Gate driving circuit having first suppression module, display panel, driving method and display device

A transmission power allocation method is provided. The transmission power allocation method is applied in user equipment (UE). The transmission power allocation method includes the following steps. The UE calculates the target power. The UE calculates the path loss of each antenna of the UE. The UE adjusts the transmission power of each antenna, except for a first antenna which corresponds to the maximum path loss, based on the maximum path loss.

Transmission power allocation method and user equipment thereof

The present disclosure provides an inversion method for determining a pollution source list based on artificial intelligence and big data, an inversion system for determining the pollution source list based on artificial intelligence and big data, and applications thereof, which provides basic data support for government sectors to formulate relevant environmental protection measures. The specific technical solution employed in the present disclosure is as follows: finding out an emission source that makes the highest contribution to the pollutant concentration of any cell with an advanced 3D CNN artificial intelligence algorithm based on artificial intelligence and big data, establishing a model of the relationship between pollutant concentration and emission, and finding out the relationship between pollutant concentration and emission with machine learning technology, i.e., estimating an emission from a given pollutant concentration, and estimating a pollutant concentration from a given emission.

Emission inversion simulator-based artificial intelligence system using deep learning technology

Provided in embodiments of the disclosure are a driving method for a display panel, and a display apparatus. A display frame includes a data refresh phase and a blanking time phase. The driving method for the display panel includes: in the data refresh phase, loading a clock signal including an active level and an inactive level to a gate driving circuit in a display panel to cause a gate line to load a gate-on signal, loading display data to a source driving circuit in the display panel to cause a data line to load a data voltage, and determining a current operating state of the display panel; and in the blanking time phase, loading a clock signal including an inactive level to the gate driving circuit in the display panel to cause the gate line to load a gate-off signal, and sending the current operating state of the display panel.

Driving method for display panel, and display apparatus

A User Equipment (UE) is provided. The UE includes a wireless transceiver and a controller. The wireless transceiver is configured to perform wireless transmission and reception to and from a mobile communication network. The controller is configured to accumulate Transport Block Size (TBS) assigned by the mobile communication network to obtain an estimated TBS during each first period, and obtain an estimated bitrate of a plurality of voice frames to be transmitted to the mobile communication network according to the estimated TBS. When the estimated bitrate of voice frames is different from current bitrate of the voice frames during a second period, the controller is configured to adjust the current bitrate according to the estimated bitrate.

Apparatuses and methods for adjusting bitrate for voice frames

Growing community of inventors

Beijing, China

Wei Tang