International Business Machines Corporation

Wuhan Tianma Micro-electronics Co., Ltd

Wuhan Tianma Microelectronics Co., Ltd. Shanghai Branch

Boe Technology Group Co., Ltd.

Dsm IP Assets B.v.

Cornell Research Foundation Inc.

Hefei Xinsheng Optoelectronics Technology Co., Ltd.

Nuance Communications, Inc.

Hefei Boe Optoelectronics Technology Co., Ltd.

Beijing Baidu Netcom Science and Technology Co., Ltd.

Beijing Drainage Group Co., Ltd

Beijing Drainage Technology Co., Ltd

Shanghai Zhigen Pharmaceutical & Technology Co., Ltd.

Jing Chang Huang

Jian Ding

Peng Ji

Guo Qiang Hu

Jun Chi Yan

Ning Duan

Zhi Hu Wang

Mengmeng Zhang

Chun Ma

Peng Gao

Wei Sun

Yue Ping Li

Yuan Yuan Ding

Sheng Nan Zhu

Yuantao Wu

Ren Jie Yao

Renjie Yao

Hao Zhang

Shao Chun Li

Vaibhava Goel

Junchi Yan

Peder Andreas Olsen

Liang Lu

Steven John Rennie

Reinhard Karge

Meng Guo

Guotao Zhao

Wei-Jing Zhu

Shengnan Wang

Jing F Fan

Shuping Jing

Ralf Proplesch

Mandar Mitra

Shanmugasundaram Ravi Kumar

Deng Ke Zhao

Lei Zhang

Wei Zhang

Xingyao Zhou

Yu Chen Zhou

Jun Xu

Xiao Lin Zhang

Daniel Martin

Dong Sheng Li

Yu Zheng

Jian He

Yi Ge

Qing Zhang

Xiao Bi Liang

Franck Barillaud

Fan Li

Wenjin Fan

Guoqiang Hu

Yong Jiang

Mukund Padmanabhan

Stephen Mingyu Chu

Bisheng Li

Jian Kuang

Baoran Li

Wen Xiong

Peihuan Ning

Liping Liu

Jiawei Wang

Shujun Zhang

Richard Martin Scott

Guangchao Wei

Yilang Chen

Yue Li

Weipeng Zhang

Boliang Chen

Xiaoyu Han

Liantao Wang

Rentan Chen

Frank Eisele

Chenglong Pan

Tao Xue

Joe Wesley Sutton, Jr

Chang Chun Liu

Xiao Wei Zhang

Wenke Wang

Dan Zhao

Gangxin Chen

Zhao Tai Pan

Zhang Xiaowei

Guanglin Chen

Jiewei Zhang

Richard P Christianson

Kai Yang

A display panel and a display apparatus are provided. The display panel includes a substrate and an array layer at a side of the substrate. The array layer includes pixel circuits and at least one first via. The pixel circuit includes transistors. Each transistor includes an active layer. The active layer includes a channel. The transistor includes a driving transistor and a first switching transistor. In a direction perpendicular to the substrate, a distance between one of the at least one first via and the channel of the driving transistor closest to the first via is greater than a preset distance. A distance between an edge of the one of the at least one first via and an edge of the channel of the first switching transistor closest to the one of the at least one first via is smaller than the preset distance.

Display panel and display apparatus

The present invention relates to an aromatic compound and a preparation method therefor and the use thereof. Specifically, disclosed are a compound as shown in the following general formula (I), or a tautomer, an enantiomer, a diastereomer or a racemate thereof or a mixture thereof, or a pharmaceutically acceptable salt thereof. Also disclosed are a method for preparing the above compound and the use of same in the treatment of nervous system diseases.

Aromatic compound and preparation method therefor and use thereof

Present disclosure provide a pixel circuit and a driving method, a display panel, and a display apparatus. The pixel circuit includes: a driving transistor, a gate connected to a first node, a first electrode connected to a second node, a second electrode connected to a third node; a control module, connected to the first node and including a first unit and a second unit that are connected in series, an intermediate node arranged between first unit and second unit; a voltage regulation module, wherein a driving cycle of the pixel circuit includes a writing frame and holding frame, the writing frame includes a first non-light-emission period, the holding frame includes a second non-light-emission period, and the voltage regulation module is configured to adjust, in the second non-light-emission periods in holding frame, a voltage of intermediate node electrically connected thereto to a first voltage.

Pixel circuit and driving method for same, display panel, and display apparatus

A driving circuit and a display panel are provided. The driving circuit includes a pixel circuit and a demultiplexing circuit. The pixel circuit includes a driving transistor, a light-emitting device, and a data writing module. The driving transistor is connected between a first power signal terminal and the light-emitting device in series, to generate a driving current. The data writing module is connected between the driving transistor and the demultiplexing circuit in series, to provide a data signal to the driving transistor. An output terminal of the demultiplexing circuit is connected to an input terminal of the data writing module through a data line. The demultiplexing circuit is configured to write the data signal to the data line when the driving transistor is performing threshold compensation.

Driving circuit, driving method, and display panel

A display panel, a driving method of a display panel, and a display device are provided. The display panel includes pixel circuits and a gate driving circuit including cascaded first shift register units. A trigger signal input terminal of the first stage first shift register unit is connected to a trigger signal terminal through a first switch element. A signal output terminal of the i-th stage first shift register unit is connected to a trigger signal input terminal of the (i+1)-th stage first shift register unit through a second switch element. A trigger signal input terminal of the N-th stage first shift register unit is connected to the trigger signal terminal through a third switch element. A signal output terminal of the j-th stage first shift register unit is connected to a trigger signal input terminal of the (j&#x2212;1)-th stage first shift register unit through a fourth switch element.

Display panel, driving method, and display device with real time switch of forward and reverse scanning

The present invention provides a computer-implemented method, computer system and computer program product for data compression. According to the computer-implemented method, one or more data blocks on a data source to be replicated to a data target may be detected. Then, compression performance of a first compression dictionary may be evaluated. The first compression dictionary may be previously used to compress existing data on the data target. If the compression performance is lower than a preset performance threshold, a second compression dictionary may be generated based on the existing data on the data target. The data target may be updated based on the existing data and the one or more data blocks using the second compression dictionary.

Compression improvement in data replication

Embodiments of the present invention facilitate product defect detection. A computer-implemented method comprises: receiving, by a device operatively coupled to one or more processors, a template image of a normal product; generating, by the device, one or more geometric training parameters for transforming the template image; and transforming, by the device, the template image using the one or more geometric training parameters to generate a transformed image for training a data model, wherein the trained data model being used for aligning the template image and an image under inspection of a product.

Product defect detection

The present disclosure provides a display panel, a driving method, and a display apparatus. The display panel includes pixel circuits, the pixel circuits include: a drive transistor, with a gate electrically connected to a first node, a first electrode electrically connected to a second node; a voltage writing module, electrically connected to a first scanning signal line, a data line, and second node; a threshold compensation module, wherein a driving cycle of the pixel circuit includes a writing phase and a holding phase, writing phase includes a first non-light-emission period, and holding phase includes a second non-light-emission period; voltage writing module writes a display voltage into second node in first non-light-emission period in response to an enable level of first scanning signal, writes a node reset voltage into the second node in the second non-light-emission period in response to the enable level of the first scanning signal.

Display panel, driving method for same, and display apparatus

A driving circuit includes at least two shift registers in cascade. In each shift register, a first output control module is configured to transmit a voltage of a first voltage terminal to an output terminal in response to a turn-on level of a first node. A second output control module is configured to transmit a voltage of a second voltage terminal to an output terminal in response to a turn-on level of a second node. A first node control module is configured to transmit a voltage of the input terminal to the first node in response to a turn-on level of a first clock signal terminal and transmit a voltage of the second voltage terminal to the first node in response to turn-on levels of the second clock signal terminal and the third node or in response to the turn-on level of the second node.

Driving circuit, driving method, and display panel with improved control of voltage output by shift register

A mechanism is provided for controlling the internal air-quality of a vehicle, including configuring a control policy that controls an internal air-quality of a vehicle and performing an action dictated by the control policy according to a window status of the vehicle.

Intelligent in-vehicle air-quality control

Provided are an anaerobic ammoxidation synergistic nitrogen removal process device of municipal sewage main and side streams and an application method thereof, comprising a municipal sewage raw water tank (), a biological reaction pool (), a secondary sedimentation pool (), a sludge digestion solution raw water tank () and a sludge digestion solution AOB strengthening pool (); wherein, the municipal sewage raw water tank () is connected with a water inlet valve () of the biological reaction pool () through a water inlet pump () of the biological reaction pool (); the biological reaction pool () is connected with the secondary sedimentation pool () through a secondary sedimentation pool connection pipe (); the sludge digestion solution raw water tank () is connected with a water outlet valve () of the sludge digestion solution raw water tank () through a water inlet pump () of the sludge digestion solution raw water tank (); the sludge digestion solution AOB strengthening pool () is connected with an anaerobic ammoxidation region compartment of the biological reaction pool through a sludge-water mixture reflux pipe () and a sludge-water mixture reflux pump (). It has the advantages of reasonability in structure design, convenience in operation, low running and maintenance cost, relatively low energy consumption, no need of an additional carbon source and the like, it can realize that short distance nitrification of municipal sewage is more stable, and it is high in low-temperature, water quantity and water quality shock resistance and can further increase volumetric load at the same time.

Anaerobic ammoxidation synergistic nitrogen removal process device of municipal sewage main and side streams and application method thereof

The present disclosure relates to training a machine learning model to classify images. An example method generally includes receiving a training data set including images in a first category and images in a second category. A convolutional neural network (CNN) is trained using the training data set, and a feature map is generated from layers of the CNN based on features of images in the training data set. A first area in the feature map including images in the first category and a second area in the feature map where images in the first category overlap with images in the second category are identified. The first category is split into a first subcategory corresponding to the first area and a second subcategory corresponding to the second area. The CNN is retrained based on the images in the first subcategory, images in the second subcategory, and images in the second category.

Classifying images in overlapping groups of images using convolutional neural networks

Partial reloading of source data in data synchronization. Determining whether a source partition of source data in a source database is to be reloaded into target data in a target database, the source partition corresponding to a target partition of the target data. In accordance with a determination that the source partition is to be reloaded, one or more processors determine to load the source partition from the source database into the target database as a reference partition, the reference partition being separated from the target data in the target database and being assigned with a reference partition identity. In accordance with a determination that the loading of the source partition is completed, one or more processors determine to attach the reference partition to the target data.

Partial reloading in data synchronization

Embodiments of the present disclosure relate to object defect detection. In an embodiment, a computer-implemented method is disclosed. According to the method, for a test image of at least one part of a target object, a reference image is generated by repeating a periodic pattern detected in the test image, the target object consisting of elements. A differential image is determined by comparing the test image and the reference image. The differential image is superimposed on a predefined grid image to obtain a superimposed image. The grid image comprises grids corresponding to elements of a reference object associated with the target object. The number of defective elements is determined in the at least one part of the target object based on the superimposed image. In other embodiments, a system and a computer program product are disclosed.

Object defect detection

Embodiments of the present invention may be directed toward a method, a system, and a computer program product of adaptive calibration of sensors through cognitive learning. In an exemplary embodiment, the method, the system, and the computer program product include (1) in response to receiving a data from at least one calibration sensor and data from an itinerant sensor, comparing the data from the at least one calibration sensor and the data from the itinerant sensor, (2) in response to the comparing, determining, by one or more processors, the accuracy of the itinerant sensor, (3) generating, by the one or more processors, one or more calibration parameters based on the determining and based on a machine learning associated with preexisting sensor information, and (4) executing, by the one or more processors, the one or more calibration parameters.

Adaptive calibration of sensors through cognitive learning

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Shanghai, China

Jing Chang Huang