International Business Machines Corporation

Boe Technology Group Co., Ltd.

Microsoft Technology Licensing, LLC

Beijing Boe Optoelectronics Technology Co., Ltd.

Nokia Technologies Oy

Beijing Boe Display Technology Co., Ltd.

State Grid Corporation of China

Beijing Friendship Hospital, Capital Medical University

Chengdu Boe Optoelectronics Technology Co., Ltd.

Beijing Boe Technology Development Co., Ltd.

Beijing Baidu Netcom Science and Technology Co., Ltd.

Hefei Boe Display Technology Co., Ltd.

China Electric Power Research Institute

Beijing Kedong Power Control System Co., Ltd

Nari Group Corporation

Dong Hui Liu

Jia Yu

Yong Yin

Peng Hui Jiang

Jia Tian Zhong

Jing Lu

Xiao Yan Tang

Xing Xing Shen

Feng Wu

Jun Su

Chao Yu

Shipeng Li

Yanming Wang

Xiaoyan Sun

Jiaqiang Wang

Bao Zhang

Naijie Li

Jian Wang

Jing Li

Hao Yang

Rui Liu

Dawei Wang

Wei Zheng

Zhan Peng Huo

Yanchao Zhang

Pengfei Zhao

Zhengxuan Lv

Leo Y Liu

Tingting Zhang

Yawen Liu

Zhenchang Wang

Han Lv

Yi Gong

Lei Wang

Wei Wang

Li Ni Zhang

Tao Wang

Jun Zhu

Qi Cheng Li

Xibin Shao

Bo Yang

Jiantao Liu

Ying Liu

Xin Zhou

Qian Zhang

Hong-Jiang Zhang

Xiao Ling Chen

Cheng Fang Wang

Yanping Liao

Fan Li

Xian-Sheng Hua

Wei Lu

Tao Yang

Meng Wang

Jie Liu

Jilei Tian

Thomas Y Woo

Guo Tong Xie

Yan Zhao

Dongchuan Chen

Yingmeng Miao

Lin Zhang

Qing Bo Wang

Li Cao

Gang Hu

Gang Liu

Jiang Yi Liu

Yue Pan

Yingying Qu

Linjun Yang

Jian Ren

Ning Yang

Jilei Gao

Lin Cheng

Xiaolong Zhu

Zhong Tian

Xian Wei Zhang

Cheng Chang

Chun Ying

Li Tao

Junjie Xu

Jianye Tang

Hong Cai

Gaowei Chen

Zhao Ming Qiu

Bo Qin

Zhiyuan He

Fuan Zhu

Chunyan Wang

Zheng Ni

Xiuqin Yang

Fangzhe Chang

Zongli Gao

Xiao Xuan Fu

Siying Lu

Xin Chang

Haining Wang

Wenwei Xue

Xiang Zu

Haiqi Liang

Pre-initialization environments are generated on at least one hardware processor for running incoming applications. Resource usage of resources configured for the pre-initialization environments in running the incoming applications is monitored. Automatic tuning of a pre-initialization environment among the pre-initialization environments is deactivated, responsive to determining based on the resource usage of resources configured for the pre-initialization environment, that the pre-initialization environment is maintaining a threshold level of efficiency. Automatic tuning of the pre-initialization environment among the pre-initialization environments is activated, responsive to determining based on the resource usage of resources configured for the pre-initialization environment, that the pre-initialization environment is overloaded. Automatic tuning of the pre-initialization environment among the pre-initialization environments is activated, responsive to determining, based on the resource usage of resources configured for the pre-initialization environment, that the pre-initialization environment is idle.

Activating and deactivating a pre-initialization environment tuning

A method, including: monitoring resource utilization of an operating system (OS) with applications utilizing larger pages; determining the monitored resource utilization is greater than a threshold resource utilization; in response to the determining the monitored resource utilization is greater than a threshold resource utilization, determining a respective larger pages index value for each of the applications utilizing larger pages; and turning off larger pages utilization of a subset of the applications utilizing larger pages, wherein the subset comprises a predefined number of the applications utilizing larger pages that have highest determined larger pages index values.

Dynamic management of larger pages during runtime

A computer-implemented method, system and computer program product for improving accuracy and efficiency of auditing databases. A table, list or index of a database is analyzed to identify metadata, which includes time series data, user data, an Internet Protocol address and operation data. The identified metadata is associated with the corresponding record or row of the table, list or index from which the metadata was extracted. A determination is then made as to whether to record a raw data image associated with the record or row of the analyzed table, list or index based on the corresponding data operation. The identified metadata as well as the recorded data images, if any, are stored in a structured audit log. Auditing information is then obtained from a structured audit log based on matching the record or row identifier (RID) associated with the query with the RID associated with the structured audit log.

Utilizing a structured audit log for improving accuracy and efficiency of database auditing

A display substrate, including: a base substrate; a plurality of data lines on the base substrate; a first insulating layer on a side of the plurality of data lines away from the base substrate; a plurality of gate lines on a side of the first insulating layer away from the plurality of data lines, where extension directions of the gate and data lines are intersected; a second insulating layer on a side of the plurality of gate lines away from the first insulating layer; and a first electrode on a side of the second insulating layer away from the plurality of gate lines, where at least a portion of an orthographic projection of the first electrode on the base substrate is within an region surrounded by orthographic projections of two adjacent data lines on the base substrate and orthographic projections of two adjacent gate lines on the base substrate.

Display substrate, display panel and display device

In a first aspect of the invention, there is a computer-implemented method including: generating, by one or more processors, dependency version information for a target software application, based on activity of a compiler registered with an event handler; generating, by the one or more processors, one or more dependency sections with a dependency list for the target software application, wherein the dependency list incorporates the dependency version information; and building, by the one or more processors, a software package with the one or more dependency sections with the dependency list for the target software application.

Automatic precision dependencies management

A method, system, and computer program product for dynamic cue generation for language learning are provided. The method identifies one or more listener actions for a listener engaged in listening learning. Based on the one or more listener actions, a language level of the listener is determined. A set of prompt metrics are generated based on the language level and the one or more listener actions. A set of audio stream levels is generated based on the set of prompt metrics. The method selects an audio stream level for a listening prompt, where the audio stream level is selected from the set of audio stream levels based on the language level of the listener.

Dynamic cue generation for language learning

A method, including: identifying static application features of an application; identifying resource access features of the application; labeling a translation lookaside buffer (TLB) miss threshold of a runtime feature of the application; determining utilization of larger pages during the runtime based on the TLB miss threshold; and setting the TLB miss threshold based on the determined utilization of the larger pages.

Dynamic tuning of larger pages during runtime

Embodiments of the present disclosure relate to a method, system, and computer program product for comparison of database data. According to the method, a first tree structure corresponding to first data segments of first database data and a second tree structure corresponding to second data segments of second database data are at least partially obtained. Each node of the first or second tree structure indicating a characteristic value of at least one of the first or second data segments, and nodes of the first or second tree structure are divided into a first or second plurality of branches from a first or second root node based on update frequencies of the first or second data segments. A difference between the first data segments and the second data segments is determined by at least comparing characteristic values indicated by nodes in the obtained parts of the first and second tree structures.

Comparison of database data

Methods, systems, and computer program products for de-duplicating data in executable files in a container image are disclosed. The method may include receiving a request to read a file in a first layer in a container image including a plurality of layers, wherein the file is a delta file which is from an updated executable file based on a base executable file, the base executable file is in a lower layer than the first layer in the container image, and the delta file includes block mappings between the updated executable file and the base executable file and different data between the two files, and blocks included in the two files are based on respective file structure. The method may also include restoring the updated executable file based on the delta file and the base executable file. The method may further include returning data in the updated executable file.

De-duplication of data in executable files in a container image

The present application discloses a cerebral perfusion state classification apparatus and method, a device, and a storage medium. The method includes: acquiring, by a transceiving module, cervical blood flow data from an ultrasound data collecting device; determining, by a processor, cerebral perfusion data corresponding to the cervical blood flow data based on the cervical blood flow data and a mapping relationship between the cervical blood flow data and the cerebral perfusion data, and classifying cerebral perfusion states of a plurality of brain regions based on blood perfusion characteristics of the plurality of brain regions in the cerebral perfusion data.

Cerebral perfusion state classification apparatus and method, device, and storage medium

Mechanisms are provided for scheduling a workload in a cloud computing system. A cloud affinity factor (CAF) computer model is trained, via a machine learning process based on a training dataset comprising static characteristics of a workload binary for a workload, and dynamic characteristics corresponding to historical performance data for the workload, such that the trained CAF computer model predicts a performance classification for a given workload binary. The trained CAF computer model processes a new workload to generate a performance classification for the new workload. Cloud affinity factor(s) are generated based on the performance classification for the new workload. Node affinity and dispatch rule(s) are applied to the cloud affinity factor(s) to select one or more nodes of the cloud computing system to which to dispatch the workload. The workload is then scheduled on the selected one or more nodes.

Cloud affinity based on evaluation of static and dynamic workload characteristics

Embodiments of the invention are directed to updating a dynamic library. Aspects include receiving an indication that the dynamic library has been updated and identifying all program modules that depend on the dynamic library. Aspects also include, for each program module that depends on the dynamic library, reassigning an application program interface (API) address for a current version of the dynamic library to an API address of the updated version of the dynamic library.

Dynamically updating a dynamic library

Software for proximity positioning that performs the following operations: (i) receiving at least one parameter via an advertising channel of a first protocol, wherein the at least one parameter is encoded in an advertising packet of the first protocol, and wherein the first protocol supports a first proximity positioning technology; (ii) extracting the encoded at least one parameter from the advertising packet; and (iii) performing, by a second proximity positioning technology different from the first proximity positioning technology, a measurement of distance based, at least in part, on the at least one parameter.

Proximity positioning

The present disclosure discloses a cerebral perfusion state classification apparatus, method and device, and a model training apparatus. In the apparatus, a transceiver module is used for receiving physiological feature data from different data collection devices; and a processor is used for extracting physiological features from the physiological feature data; inputting the physiological features into a random forest model to cause a plurality of decision-making trees in the random forest model to predict a cerebral perfusion state type corresponding to the physiological features; and classifying a cerebral perfusion state based on the cerebral perfusion state type corresponding to the physiological features.

Cerebral perfusion state classification apparatus, method and device, and model training apparatus

Embodiments of the present invention relate to password authentication. According to an embodiment of the present invention, a password associated with a user identification is received from a user device. The password is authenticated based on a preset relationship between a seed password and a graphical password associated with the user identification. The seed password consists of a string of characters. The graphical password is a directed path traversing all keys of a keypad in an order. Each of the keys represents one of the characters and is associated with an order number according to the order of the keys being traversed. The preset relationship is that the password consists of respective order numbers associated with respective keys representing corresponding characters of the seed password.

Password authentication

Growing community of inventors

Beijing, China

Dong Hui Liu