Semiconductor Manufacturing International (shanghai) Corporation

International Business Machines Corporation

Semiconductor Manufacturing International (beijing) Corporation

Savant Technologies LLC

Boe Technology Group Co., Ltd.

Lenovo (beijing) Limited

Hefei Boe Optoelectronics Technology Co., Ltd.

Peking University

Shanghai Jiaotong University

Semiconductor Manufacturing International Corp.

Lixil (china) Investment Co., Ltd

Savant Technoloiges LLC

Li Jiang

Mingqi Li

Jing Bo Jiang

Li Ni Zhang

Li Long Chen

Lan Luo

Wen Rui Zhao

Yu Xin Zhao

Jing Chen

Pulei Zhu

Kun Xiao

Hai Huang

Jie Gao

Zhe Wang

Rui Lin

Qin Zhao

Jiachen Yang

Hao Meng Wang

Yang Liu

Xue Ying Zhang

Yu Zhao

Li Li Gu

Xiantao Li

Shuisheng Yu

Liang Liang Dai

Jun Xu

Jun Yang

Fei Chen

Bin Li

Tongmin Liu

Heng Zhang

Ying Shao

Litong Han

Hongyan Li

Liang Shan

Qun Shao

Xiaolong He

Yude Li

Siyang Liang

Super Liao

Meng Wu

Qingling Wang

Jong Woo Kim

Zhongde Fan

Aoxiang Li

Zhenghong Chen

Hong Xiu Peng

Libbert Peng

Guangbo Meng

Auter Wu

Yongze Liu

Tiantao Li

Chun Qing W Wu

Chaoqun Chu

Yongyue Sun

A method for processing time series data comprises: dividing time series data into a plurality of data fragments according to an objective function, the plurality of data fragments having a greatest similarity; in response to determining that at least one data fragment does not satisfy an iteration termination condition, performing following iteration operations on the at least one data fragment; and constructing a time series base pattern library by using a plurality of time series base patterns. The iteration operations includes: using the at least one data fragment as at least one update time series fragment; dividing each update time series fragment into a plurality of update data fragments; using each update data fragment that does not satisfy the iteration termination condition as a new update time series fragment; and using each update data fragment that satisfies the iteration termination condition as a time series base pattern.

Method, apparatus and electronic device for processing time series data

The present disclosure relates to a pruning method based on a crossbar architecture and a system thereof, wherein the method comprises the steps of: carrying out structured pruning on a weight matrix to be processed at the current layer of a neural network without considering architecture factors to obtain a first weight matrix, wherein the weight matrix is the weight matrix of the neural network; determining the pruning scheme according to the size of the first weight matrix and the size of the crossbar, wherein the pruning scheme comprises: block-based structured pruning, crossbar row pruning and crossbar column pruning; and pruning the first weight matrix according to the pruning scheme to obtain a second weight matrix, wherein the second weight matrix is mapped to the crossbar array in an accelerator, and the neural network is accelerated by the accelerator.

Pruning method based on crossbar architecture and system thereof

Managing security access in real-time to a computer system using control lists includes detecting a security event at a computer system. The security event is analyzed including an analysis of a historical corpus having historical data of security events. An access control list is generated based on the security event. A determination is made when the security event includes abnormal behavior based on the analysis of the security event and the historical corpus. The security event is published to a monitoring system for controlling access to the computer system, in response to the security event.

Data access control management computer system for event driven dynamic security

Wireless docking station

Projection lamp

Techniques are described for linked blockchains that allow computing devices to access information from an acceptance blockchain about acceptance reports stored in an enterprise delivery blockchain that are also linked to a product blockchain that stores information of the products of the acceptance reports. An acceptance report is indicative of operability of a product in a service provided by a service provider. A processor is configured to access the block in the enterprise delivery blockchain, retrieve the acceptance report from the block in the enterprise delivery blockchain, determine an identifier, identified in the block in the enterprise delivery blockchain, to a block in an acceptance blockchain, access the block in the acceptance blockchain via the determined identifier, retrieve from the block in the acceptance blockchain contextual information of the acceptance report, and output the acceptance report and contextual information of the acceptance report.

Linked blockchain structures for accelerated multi-chain verification

Lamp housing

The present utility model relates to the field of manufacture of sanitary wares, and provides a toilet. The toilet includes a seat body with a sewage accommodating bowl, and a cistern. The inside of the cistern is provided with a fill valve, a first ring flushing pipeline, a first water inlet end of the first ring flushing pipeline is selectively in fluid communication with the fill valve, a first water outlet end of the first ring flushing pipeline is in fluid communication with a ring flushing port opening, and the first ring flushing pipeline includes a first jet flow increasing structure; a second bottom flushing pipeline, a second water inlet end of the second bottom flushing pipeline is selectively in fluid communication with the fill valve, and the second bottom flushing pipeline includes a second jet flow increasing structure; and a pipeline switching mechanism, being able to automatically switch the fluid communication between the first ring flushing pipeline and the fill valve or between the second bottom flushing pipeline and the fill valve in response to a water level in the cistern. By using such toilet, the sewage accommodating bowl can be more cleanly and thoroughly flushed with the same water consumption, or a low-profile cistern design can be realized under the same water pressure requirement.

Toilet bowl flush device

Managing network interactions by engaging a networked information broadcast service, receiving information from the networked information broadcast service, filtering the information according to a profile, and sending information according to the filtered information using another network communications connection.

Smart edge network management

A computer-implemented method, computer system, and computer program product for blockchain enabled service reservation and delegation. The present invention may include receiving one or more first or second trigger conditions defined by a user, detecting an occurrence of the one or more first trigger conditions, deploying a smart contract based on the received one or more first trigger condition, detecting an occurrence of the one or more second trigger conditions, and deactivating the smart contract based on the received one or more second trigger conditions. The present invention may include receiving a subject registration, the subject is the user, a service, or a device. The one or more first trigger conditions may be a condition that upon its occurrence may initiate the deployment of the smart contract. The one or more second trigger conditions may be a condition that upon its occurrence may initiate the deactivation of the smart contract.

Blockchain based service reservation and delegation

Methods and systems for selecting a tool for a project is described. In an example, a processor can run a machine learning model to generate a set of requirements to implement a project. The processor can identify a keyword from the set of requirements. The processor can search for the keyword on a search engine. The processor can receive a search result from the search engine corresponding to the keyword. The processor can identify, based on the search result, a tool that can be used to implement the project, where the tool can be in compliance with the set of requirements.

Machine learning for technical tool selection

In an approach to blockchain management of cloud service provisioning failures, one or more computer processors capture one or more application programming interface (API) calls associated with a service provision. One or more computer processors submit the captured one or more API calls to a blockchain ledger. One or more computer processors detect a system failure during the service provision. One or more computer processors extract the submitted one or more API calls from the blockchain ledger. Based on the extracted one or more API calls, one or more computer processors identify a problematic system associated with the system failure.

Blockchain management of provisioning failures

Growing community of inventors

Shanghai, China

Li Jiang