International Business Machines Corporation

Alibaba Group Holding Limited

Huawei Technologies Co., Limited

Xfusion Digital Technologies Co., Ltd.

Ke Jin

Qing Fa Wang

Yubo Li

Jie Zhang

Shi Lei Zhang

Chen Zhu

Hu Wei

Xu Qiang Yue

Jing Feng Luo

Ling Cao

Xin Zhang

Chong Wei Zhang

Kai Zhu

Junsong Wang

Shiwan Zhao

Yonghua Lin

Zhen Cao

Fei Zheng

Dongshu Zhou

Baicheng Fu

A fault diagnosis system is disclosed, including: a control unit, a first management board, a first pull-up unit, a second pull-up unit, a first pull-up switch, a second pull-up switch, and at least one central processing unit, the control unit is configured to receive physical partitioning information sent by the first management board, the first pull-up unit and the second pull-up unit are configured to pull up a fault indication signal of a fault diagnosis path to obtain a target signal, the first management board is configured to detect whether a level of the target signal is lower than a diagnosis threshold, and when the level of the target signal is lower than the diagnosis threshold, determine that a faulty central processing unit exists in the at least one central processing unit.

Fault diagnosis system and server

In some examples, a method includes receiving a test image from a user or client, the test image depicting an anatomical region or structure of a human body, obtaining a reference image corresponding to the anatomical region or structure depicted in the test image, and analyzing the test image and the reference image to obtain a set of differences between the two images. In some examples, the method further includes, based at least in part on the set of differences, detecting a possible abnormality in the test image and outputting a result to the user or client. In some examples, a fast R-CNN is used to detecting the possible abnormality in the test image.

Reference image guided object detection in medical image processing

Technology for performing object tracking of an object in a video image using both object detection algorithm and an object tracking algorithm. Because object detection algorithms are generally slower, but accurate, than object tracking algorithms, only certain sampled video frames are subject to the object detection algorithm. The non-sampled frames locate the object using the object tracking algorithm, using the most recent previous object detected frame as a starting frame. In this way, the object detection algorithm is used to periodically, effectively calibrate the object tracking algorithm by using a lagging detection result to hide latency introduced by the object detection algorithm.

Stream object tracking with delayed object detection

A method, computer system, and computer program product for model selection for training a new dataset is provided. The present invention may include choosing a model from a set of models to be evaluated for training the new dataset, selecting a sample input from a subset of the new dataset, calculating a model activation score for each of the sample inputs in the chosen model, calculating an accumulated model activation score for the chosen model, depending on the model activation score of each of the sample inputs in the chosen model, calculating an accumulated model activation score for each model from the set of models to be evaluated for training the new dataset, and selecting the model for training the new dataset with the highest accumulated model activation score.

Model matching and learning rate selection for fine tuning

An Internet of Things data transmission method includes sending, by a terminal device, a first data request to a server, and continuously receiving, by the terminal device, N data packets from the server. The first data request instructs the server to continuously send a plurality of data packets. The first data request includes a quantity N of data packets, that the terminal device is capable of continuously receiving, and a time interval for sending two consecutive data packets, where N is an integer greater than 1. The N data packets include at least one non-confirmable Constrained Application Protocol (NON) data packet, a sending time interval between two consecutive data packets in the N data packets and the at least one NON data packet indicates that sending a receiving response from the terminal device to the server is unnecessary.

Internet of things data transmission method, device and system

A method includes obtaining a first set of parameters corresponding to a first video, such parameters including a first skip number and a first segment length. The method includes obtaining a first set of image feature values corresponding to the first video and storing the first set of parameters and the first set of image feature values as reference data. The method includes calculating a second set of image feature values corresponding to a second video and comparing the second set of image feature values to the reference data, and determining, based on the comparing, that the second set of image feature values exceeds a threshold. The method includes calculating, in response to the determining, a variance. The method includes generating, based on the variance, a second set of parameters corresponding to the second video, the second set of parameters including a second skip number and a second segment length.

Dynamic sequential image processing

A computer-implemented method includes identifying a source data object of a distributed computing environment. The distributed computing environment includes two or more storage nodes. The source data object exists as two or more slices. At least one of the slices is replicated on at least two storage nodes. The computer-implemented method further includes associating the source data object with a tape. The tape is written by a tape drive controlled from the distributed computing environment. The computer-implemented method further includes copying the source data object to the tape by, for each source slice of the two or more slices, in sequence: selecting a source node of the two or more storage nodes whereon the source slice is replicated, mounting the tape drive to the source node, appending the source slice to the tape, and unmounting the tape drive. A corresponding computer program product and computer system are also disclosed.

Tape backup in large scale distributed systems

A computer-implemented method includes identifying a source data object of a distributed computing environment. The distributed computing environment includes two or more storage nodes. The source data object exists as two or more slices. At least one of the slices is replicated on at least two storage nodes. The computer-implemented method further includes associating the source data object with a tape. The tape is written by a tape drive controlled from the distributed computing environment. The computer-implemented method further includes copying the source data object to the tape by, for each source slice of the two or more slices, in sequence: selecting a source node of the two or more storage nodes whereon the source slice is replicated, mounting the tape drive to the source node, appending the source slice to the tape, and unmounting the tape drive.

Saving database storage space includes receiving, using a processor, one or more properties associated with a newly released commodity input at a front-end server; determining whether the one or more properties of the newly released commodity match a standard property unit (SPU), wherein the SPU includes a plurality of properties common to at least two commodities of which data is stored at a back-end server; and in the event that the one or more properties of the newly released commodity match the SPU, storing data associated with binding the newly released commodity with the matching SPU at the back-end server.

Method and system for processing product properties

Method and system for saving database storage space

Saving database storage space includes extracting a standard property unit from a database of commodity information and including the SPU in a SPU library, generating a sequence document of the standard property unit and sending the sequence document to a front-end device, determining whether a newly released commodity matches the standard property unit of the sequence document of the standard property unit and in the event that the newly released commodity matches the standard property unit of the sequence document, binding the new released commodity and the matched standard property unit.

Growing community of inventors

Beijing, China

Ke Jin