Intel Corporation

Samsung Electronics Co., Ltd.

China University of Mining and Technology

Microsoft Technology Licensing, LLC

Nokia Technologies Oy

Chinese Academy of Sciences

Rosemount Inc.

Inria Institut National De Recherche En Informatique Et En Automatique

Hangzhou Jitai Pharmaceutical Technology Co., Ltd.

Beijing Jitai Pharmaceutical Technology Co., Ltd.

Center for Hydrogeology and Environmental Geology Survey, Cgs

Liu Yang

Anbang Yao

Qiang Li

Lin Xu

Bin Wang

Jinfeng Zhou

Zhichong Chen

Jianbin He

Yurong Chen

Ping Hu

Shandong Wang

Yiwen Guo

Libin Wang

Dongqi Cai

Wenhua Cheng

Xianchao Xu

Yuqing Hou

Zhuo Li

Zhou Su

Yuguang Li

Weike Chen

Huiguang Yang

Zhehan Yu

Yuan Zhu

Sang Joon Kim

Haipeng Lei

Dong Li

Zhi Zhang

Bo Huang

Shuo Wang

Qi Wang

Ji-Rong Wen

Lei Zhang

Honggang Li

He H Liu

Lin Zhang

Jing He

Chisung Bae

Manchao He

Zaiqing Nie

Zongliang Huo

Yixue Lei

Tianchun Ye

Paul Ryan Fadell

Jian Zhao

Zhang Chao

Bing Niu

Yinglai Xi

Jumei Li

Chuangqi Tang

Jianhua Qin

Qianhui Li

Yiyang Jiang

Bruno Levy

Andong Liu

Fei Gong

Jiawei Cai

Fawang Zhang

Guangtao Dong

Liu Haixiao

Yingwei Wang

Long Tan

Shulin Zhang

Jiguang Xue

Xiongzhan Linghu

Manjun Yan

Caida Lai

Wenshou Wang

Xiaolei Yu

Benchao Xu

Chengyu Miu

The provided is an experimental apparatus and method for shale supercritical synergistic penetration and imbibition based on damping vibration, including a reaction autoclave; a damping vibration measurement device, used for measuring the weight of a rock sample; a temperature control device, used for heating and cooling the internal environment of the reaction autoclave; a pressure control device, disposed on the reaction autoclave lid; a water level control device, disposed on the upper inner wall of the reaction autoclave body; a conductivity testing device, disposed on the inner bottom of the reaction autoclave body; and a data processing device, disposed on the reaction autoclave body, used for receiving and processing signals transmitted from the damping vibration measurement device, temperature control device, pressure control device, water level control device, and conductivity testing device.

Experimental apparatus and method for shale supercritical synergistic penetration and imbibition based on damping vibration

A method and apparatus for classifying water-rich weak surrounding rock based on in-situ scribing are provided. The method includes placing a scribing device on tunnel cross-sections of varying lengths; performing in-situ scribing on the tunnel cross-sections to obtain the mechanical parameters of the surrounding rock and determining the surrounding rock strength at different locations; while performing in-situ scribing, employing near-infrared spectroscopy to simultaneously measure the in-situ spectrum of the tunnel surrounding rock, thereby determining the surface water content at different locations; based on the scribing mechanical parameters of the tunnel surrounding rock, establishing a scribing depth curve, and calculating a joint development degree of the tunnel surrounding rock at different locations from the scribing depth curve; and based on the surrounding rock strength, surface water content, and joint development degree of the tunnel surrounding rock at different locations, classifying the surrounding rock grades of the tunnel cross-section.

Method and apparatus for classifying water-rich weak surrounding rock based on in-situ scribing

Methods and systems are disclosed using an execution pipeline on a multi-processor platform for deep learning network execution. In one example, a network workload analyzer receives a workload, analyzes a computation distribution of the workload, and groups the network nodes into groups. A network executor assigns each group to a processing core of the multi-core platform so that the respective processing core handle computation tasks of the received workload for the respective group.

Methods and apparatus for deep learning network execution pipeline on multi-processor platform

A data recovery method for a flash memory includes: reading data from the flash memory by using preset read voltage; calculating a check node error rate corresponding to the data; calculating a read voltage adjustment step size according to the check node error rate; adjusting the preset read voltage according to the read voltage adjustment step size and reading data from the flash memory by using the adjusted preset read voltage, and repeating the operation of calculating a check node error rate corresponding to the data to operation of adjusting the preset read voltage according to the read voltage adjustment step size and reading data from the flash memory by using the adjusted preset read voltage, until the check node error rate is minimum; and selecting a read voltage corresponding to the minimum check node error rate to read data from the flash memory, so as to perform data recovery.

Data recovery method for flash memory

Provided herein is a class of ionizable lipid compounds represented by formula (IV), or pharmaceutically acceptable salts, isotopic variants, tautomers or stereoisomers thereof. Also provided is a nanoparticle pharmaceutical composition comprising said compound, and the application of said compound and its composition in the delivery of nucleic acids.

Ionizable lipid compounds

A device and a method for evaluating damage of high-temperature and high-humidity gas to a surrounding rock porous structure are provided. The device includes a rock sample clamper, a temperature control device, a pressurizing device, a gas mixing injection device, a CT scanning device and a low-temperature nitrogen adsorption device. By simulating the gas rock reaction under the conditions of in-situ temp., pressure and gas, using CT scanning device to visually monitor and analyze the reaction condition of gas and tunnel surrounding rock and the change condition of porous structure, and using low-temperature nitrogen adsorption test to obtain porous structure parameters change condition before and after reaction of gas and tunnel surrounding rock, and the damage evaluation index of the porous structure is established.

Device and method for evaluating damage to surrounding rock porous structure due to high-temperature and high-humidity gas

Skin smoothing is applied to images using a bilateral filter and aided by a skin map. In one example a method includes receiving an image having pixels at an original resolution. The image is buffered. The image is downscaled from the original resolution to a lower resolution. A bilateral filter is applied to pixels of the downscaled image. The filtered pixels of the downscaled image are blended with pixels of the image having the original resolution, and the blended image is produced.

Skin map-aided skin smoothing of images using a bilateral filter

Methods, apparatus, systems and articles of manufacture are disclosed to improve deep learning resource efficiency. An example apparatus includes a graph monitor to select a candidate operation node in response to receiving an operation graph, the operation graph including one or more other operation nodes, a node rule evaluator to evaluate the candidate operation node based on an operating principle, the operating principle to determine an output storage destination of the candidate operation node based on a topology of the operation graph, and a tag engine to tag the candidate operation node with a memory tag value based on the determined output storage destination.

Methods, systems and apparatus to improve deep learning resource efficiency

Methods and systems are disclosed using camera devices for deep channel and Convolutional Neural Network (CNN) images and formats. In one example, image values are captured by a color sensor array in an image capturing device or camera. The image values provide color channel data. The captured image values by the color sensor array are input to a CNN having at least one CNN layer. The CNN provides CNN channel data for each layer. The color channel data and CNN channel data is to form a deep channel image that stored in a memory. In another example, image values are captured by sensor array. The captured image values by the sensor array are input a CNN having a first CNN layer. An output is generated at the first CNN layer using the captured image values by the color sensor array. The output of the first CNN layer is stored as a feature map of the captured image.

Methods and systems using camera devices for deep channel and convolutional neural network images and formats

A pose estimation method includes obtains an event stream from an event-based vision sensor configured to capture a target object to which light-emitting devices flickering at a predetermined first frequency are attached, obtains a polarity change period of at least one pixel based on the event stream, generates an image frame sequence using at least one target pixel having a polarity change period corresponding to the first frequency, among the at least one pixel, extracts a feature sequence including feature vectors corresponding to the at least one target pixel, from the image frame sequence, and estimates a pose sequence of the target object by applying the feature sequence to a deep neural network (DNN) model.

Pose estimation method, pose estimation apparatus, and training method for pose estimation

A method and apparatus for processing sparse points. The method includes determining spatial hierarchical point data based on a key point set and a local point set of a sparse point set, determining relationship feature data by encoding a spatial hierarchical relationship between points of the spatial hierarchical point data, generating a global feature and a local feature of the sparse point set through a conversion operation associated with the relationship feature data, and generating a processing result for the sparse point set based on the global feature and the local feature.

Method and apparatus for processing sparse points

Methods and systems for advanced and augmented training of deep neural networks (DNNs) using synthetic data and innovative generative networks. A method includes training a DNN using synthetic data, training a plurality of DNNs using context data, associating features of the DNNs trained using context data with features of the DNN trained with synthetic data, and generating an augmented DNN using the associated features.

Methods and systems for advanced and augmented training of deep neural networks using synthetic data and innovative generative networks

Described herein are advanced artificial intelligence agents for modeling physical interactions. An apparatus to provide an active artificial intelligence (AI) agent includes at least one database to store physical interaction data and compute cluster coupled to the at least one database. The compute cluster automatically obtains physical interaction data from a data collection module without manual interaction, stores the physical interaction data in the at least one database, and automatically trains diverse sets of machine learning program units to simulate physical interactions with each individual program unit having a different model based on the applied physical interaction data.

Advanced artificial intelligence agent for modeling physical interactions

Growing community of inventors

Beijing, China

Liu Yang