International Business Machines Corporation

China Academy of Telecommunications Technology

Datang Mobile Communications Equipment Co., Ltd.

Beijing Baidu Netcom Science and Technology Co., Ltd.

Nokia Technologies Oy

Beijing Baidu Netcom Science Technology Co., Ltd

Yuan Feng

Jiayi Fang

Norbert George Vogl

Robert Alan Flavin

Geoffrey Hale Purdy

Li Li Zhao

Edward Payson Clarke, Jr

Rui Zhao

Yi Zhao

Lin Lin

Haijun Zhou

Bin Zhang

Pengcheng Yuan

Ling Zhuo

Jiye Tang

Ying Xin

Shumin Han

Xiaodi Wang

Feng Li

Shufei Lin

Tao Li

Lin Xu

Jing James Xu

Errui Ding

Shilei Wen

Fangchen Cheng

Yue Yang

Jun Wang

Hongwu Zhang

Zhao Cao

Lanjun Wang

Xiang Long

Jingwei Liu

Pei Pei Liang

Yan Yan Han

Yingbo Xu

Yan Peng

Ying Liu

Ke Wei Wei

Xue Ying Zhang

Haiyang Quan

Teng Ge Ma

Yi Dai

Huanglingzi Liu

Guang Ming Zhang

Jinling Hu

Shuang Ys Yu

Chenxin Li

Jianfeng Zhu

Yongguang Guo

Shilei Zheng

Zhuang Jia

Wenli Zhou

Mingyuan Mao

Honghui Zheng

Su Li Hou

Tian Jiao Zhang

Edward Clarke

Xuanyu Guo

Qi Min

Yan Hao Zhang

Li Zhao

Computer-implemented methods for a database schema relationship analysis system are disclosed herein. Aspects include receiving a table name associated with a modified table entity in a database of an application. Aspects further include generating an application documentation table association tree using data from application documentation of the application. Aspects also include generating a source code table association tree using a set of data from source code of the application. Aspects further include determining a similarity level by comparing the application documentation table association tree and the source code table association tree. Aspects include generating a message that includes a suggestion to modify a table entity associated with the modified table entity using data from the application documentation table association tree and the source code table association tree in response to determining that the similarity level is within a threshold value.

Database schema relationship analysis system

A computer-implemented method, system and computer program product for recommending join operations of relational data among different tables. Relationships between one or more pairs of columns of relational data for one or more pairs of tables are identified by determining the semantic similarity between each pair of columns of relational data. The data content join converge for each of the identified relationships in connection with joining the tables involved in such identified relationships is determined. Furthermore, a join strength (indication of the degree that the relational data in the paired columns match) is calculated for each of the identified relationships based on the semantic similarity and the data content join coverage for such identified relationships. Based on the calculated join strength as well as other factors, a combination optimization algorithm identifies the best join combinations of relational data of the tables among a set of tables.

Recommending join operations of relational data among tables based on optimization model

An embodiment generates an initial set of training data from monitoring data. The initial set of training data is generated by combining outputs from a plurality of pretrained classifiers. The embodiment trains a new classification model using the initial set of training data to identify anomalies in monitoring data. The embodiment performs a multiple-level clustering of the data samples resulting in a plurality of clusters of sub-clusters of data samples, and generates a review list of data samples by selecting a representative data sample from each of the clusters. The embodiment receives an updated data sample from the expert review that includes a revised target classification for at least one of the data samples of the expert review list. The embodiment then trains another replacement classification model using a revised set of training data that includes the updated data sample and associated revised target classification.

Intelligent expansion of reviewer feedback on training data

Provided are a method and apparatus for evaluating image relative definition, a device and a medium, relating to technologies such as computer vision, deep learning and intelligent medical. A specific implementation solution is: extracting a multi-scale feature of each image in an image set, where the multi-scale feature is used for representing definition features of objects having different sizes in an image; and scoring relative definition of each image in the image set according to the multi-scale feature by using a relative definition scoring model pre-trained, where the purpose for training the relative definition scoring model is to learn a feature related to image definition in the multi-scale feature.

Method and apparatus for evaluating image relative definition, device and medium

The present disclosure provides a transmission feedback method and a UE. The transmission feedback method includes: transmitting a time-frequency transmission resource for transmitting feedback information for unicasting or multicasting transmission to at least one target UE which has established a connection with a source UE; acquiring the feedback information transmitted on the time-frequency transmission resource from the target UE; and determining a unicasting or multicasting transmission state in accordance with the feedback information.

Transmission feedback method and user equipment

A method for detecting a surface defect, a method for training model, an apparatus, a device, and a medium, are provided. The method includes: inputting a surface image of the article for detection into a defect detection model to perform a defect detection, and acquiring a defect detection result output by the defect detection model; inputting a surface image of a defective article determined to be defective into an image discrimination model based on the defect detection result to determine whether the surface image of the defective article is defective, wherein the image discrimination model is a trained generative adversarial networks model, and the generative adversarial networks model is obtained by training using a surface image of a defect-free good article; and adjusting the defect detection result of the surface image of the defective article according to a determination result of the image discrimination model.

Method for detecting surface defect, method for training model, apparatus, device, and media

An approach is provided in which the approach captures a first user activity log of a first user accessing multiple systems and captures a set of second user activity logs of a set of second users accessing the multiple systems. The approach determines a set of system monitoring preferences based the first user activity log and the set of second user activity logs, and scores the multiple systems based on the set of system monitoring preferences. The approach generates a recommended system monitoring list based on the scored multiple systems, and transmits the recommended system monitoring list to the first user.

Recommend target systems for operator to attention in monitor tool

An object area measurement method and an apparatus are provided, relating to the computer vision and deep learning technology. The method includes acquiring an original image with a spatial resolution, the original image including a target object; acquiring an object identification model including at least two sets of classification models; generating one or more original image blocks based on the original image; performing operations on each original image block: scaling each original image block at at least two scaling levels to obtain scaled image blocks with at least two sizes, the scaled image blocks respectively corresponding to the at least two sets of classification models, and inputting the scaled image blocks into the object identification model to obtain an identification result of the target object; and determining an area of the target object based on the respective identification results of the one or more original image blocks and the spatial resolution.

Object area measurement method, electronic device and storage medium

The present application discloses a method and an apparatus for detecting wearing of a safety helmet, a device and a storage medium. The method for detecting wearing of a safety helmet includes: acquiring a first image collected by a camera device, where the first image includes at least one human body image; determining the at least one human body image and at least one head image in the first image; determining a human body image corresponding to each head image in the at least one human body image according to an area where the at least one human body image is located and an area where the at least one head image is located; and processing the human body image corresponding to the at least one head image according to a type of the at least one head image.

Method and apparatus for detecting wearing of safety helmet, device and storage medium

A method and a device for indicating transmission resources, and a storage medium are provided. The method includes: selecting N transmissions according to a target indication rule, and determining N transmission resources of data information of a data packet corresponding to the N transmissions as selected; and transmitting in control information the N transmission resources as determined.

Method and device for indicating transmission resources and storage medium

Disclosed are a resource selection method and apparatus under multiple carriers, a computer device and a storage medium. The resource selection method comprises: determining at least one candidate carrier according to a resource occupancy exclusion result on each carrier; setting a resource on the candidate carrier to be available, performing exclusion according to a sensing result and obtaining a set of available resources; selecting a transmission resource from the set of available resources, and setting a semi-persistent scheduling counter for resource scheduling. The present application provides a resource selection solution reducing half-duplex influence as far as possible, and reducing the impact due to loss of receiving opportunities and the number of skip subframes, and also avoids the problem of too severe power allocation caused by simultaneous transmission with multiple service packets.

Resource selection method and apparatus under multiple carriers, computer device, and storage medium

The present disclosure provides a sidelink communication method, a terminal and network equipment. The method includes: receiving, by a first terminal, resource configuration information sent by first network equipment; entering a distributed resource scheduling mode to perform sidelink communication with a second terminal if the resource configuration information sent by the first network equipment includes first preset information, otherwise, establishing connection with second network equipment, and receiving resource configuration information sent by the second network equipment; entering the distributed resource scheduling mode to perform sidelink communication with the second terminal if the resource configuration information sent by the second network equipment includes second preset information; entering a centralized resource scheduling mode to perform sidelink communication with the second terminal if the resource configuration information sent by the second network equipment includes third preset information.

Sidelink communication method, terminal and network equipment

A method and device for resource reservation are provided. The resource reservation method includes: receiving scheduling assignment information transmitted by first UE, where the scheduling assignment information includes information about time-frequency resource that the first UE needs to reserve; determining the quantity of reservations for the time-frequency resource by the first UE according to the scheduling assignment information; if new scheduling assignment information about the time-frequency resource transmitted by the first UE has been received before the quantity of reservations becomes invalid, re-determining reservation information for the time-frequency resource according to the new scheduling assignment information; and if no new scheduling assignment information about the time-frequency resource transmitted by the first UE has been received before the quantity of reservations becomes invalid, taking the time-frequency resource as an idle resource.

Method and device for resource reservation

Disclosed are a method and device for allocating cell resources of a device to device (D2D) system, which are used for improving the communication reliability of nodes located in different cell edge areas in an edge area ad hoc network manner. Provided is a method for allocating cell resources of a device to device (D2D) system, comprising: determining an edge area for D2D resource coordination of a cell; and allocating a resource pool to a node in the edge area, wherein the node in the edge area selects a resource from the resource pool in an ad hoc manner for communication, the resource being a time slot or time frequency block.

Method and device for allocating cell resources of a device to device system

The present disclosure provides a method and a device for scheduling resources in an internet of vehicles system, to centrally allocate timeslot resources in the internet of vehicles system at a network side. The method includes: receiving, by a scheduling device, information of a geographical area reported by a first node and corresponding to the first node; and determining, by the scheduling device, timeslot resources capable of being scheduled within the geographical area reported by the first node, and allocating a timeslot resource from the determined timeslot resources for the first node. Each cell is divided into geographical areas, and an identical timeslot resource can be shared by non-adjacent geographical areas in an identical cell, and/or non-adjacent geographical areas in different cells. By centralized scheduling of timeslot resources, it is able to ensure communication between nodes within a predetermined range, thereby preventing impact of timeslot resources used by the nodes.

Method and device for scheduling resources in internet of vehicles system

Growing community of inventors

Beijing, China

Yuan Feng