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141.发明申请公开(公告)号：US20220318626A1
公开(公告)日：2022-10-06
申请号：US17711408
申请日：2022-04-01
Applicant: NEC Laboratories America, Inc. , NEC Corporation
Inventor： Jingchao Ni , Wei Cheng , Haifeng Chen , Takayoshi Asakura
IPC: G06N3/08
Abstract: A method for performing dialysis event prediction by employing a meta-training strategy for model personalization includes, in a meta-training stage, generating segments from temporal records of patient dialysis data, generating, from the segments, a support set and a query set for each patient of a plurality of patients, formulating tasks for each patient in a pre-training set defined as a meta-training framework (M-DCCN), where each task includes the support set and the query set, and sending the tasks to a two-level meta-training algorithm supported training coordinator. The method further includes, in a finetuning stage, sending the M-DCCN to local machines where a finetuning dataset is collected for new patients, the finetuning dataset including a limited amount of data pertaining the new patients, fine-tuning the M-DCCN for personalization, and using the fine-tuned M-DCCN for future predictive dialysis analysis of future new patients by generating prognostic predictive scores.
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公开(公告)号：US20220107878A1
公开(公告)日：2022-04-07
申请号：US17491632
申请日：2021-10-01
Applicant: NEC Laboratories America, Inc.
Inventor： Yuncong Chen , Zhengzhang Chen , Cristian Lumezanu , Masanao Natsumeda , Xiao Yu , Wei Cheng , Takehiko Mizoguchi , Haifeng Chen
Abstract: A method for system metric prediction and influential events identification by concurrently employing metric logs and event logs is presented. The method includes concurrently modeling multivariate metric series and individual events in event series by a multi-stream recurrent neural network (RNN) to improve prediction of future metrics, where the multi-stream RNN includes a series of RNNs, one RNN for each metric and one RNN for each event sequence and modeling causality relations between the multivariate metric series and the individual events in the event series by employing an attention mechanism to identify target events most responsible for fluctuations of one or more target metrics.
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公开(公告)号：US11281990B2
公开(公告)日：2022-03-22
申请号：US15635995
申请日：2017-06-28
Applicant: NEC Laboratories America, Inc.
Inventor： Wei Cheng , Haifeng Chen , Guofei Jiang , Kai Zhang
Abstract: A computer-implemented method for simultaneous metric learning and variable selection in non-linear regression is presented. The computer-implemented method includes introducing a dataset and a target variable, creating a univariate neighborhood probability map for each reference point of the dataset, and determining a pairwise distance between each reference point and other points within the dataset. The computer-implemented method further includes computing a Hessian matrix of a quadratic programming (QP) problem, performing optimization of the QP problem, re-weighing data derived from the optimization of the QP problem, and performing non-linear regression on the re-weighed data.
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公开(公告)号：US11280816B2
公开(公告)日：2022-03-22
申请号：US16380378
申请日：2019-04-10
Applicant: NEC Laboratories America, Inc.
Inventor： Masanao Natsumeda , Wei Cheng , Haifeng Chen
IPC: G01R21/133
Abstract: Systems and methods for detecting anomalies in a plurality of showcases are provided. A system can obtain a corresponding table between each of the plurality of showcases and at least one corresponding sensor. The system obtains information for showcase clustering. The system can include a processor device that can determine at least one cluster of showcases based on the information for showcase clustering and the corresponding table between each of the plurality of showcases and the at least one corresponding sensor. The system can build at least one model for each of the at least one cluster of showcases and detect at least one anomaly based on data from the at least one cluster of showcases and the at least one model.
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公开(公告)号：US20220084335A1
公开(公告)日：2022-03-17
申请号：US17464056
申请日：2021-09-01
Applicant: NEC Laboratories America, Inc. , NEC Corporation
Inventor： LuAn Tang , Wei Cheng , Haifeng Chen , Yuji Kobayashi , Zhengzhang Chen
Abstract: A method for early warning is provided. The method clusters normal historical data of normal cars into groups based on the car subsystem to which they belong. The method extracts (i) features based on group membership and (ii) feature correlations based on correlation graphs formed from the groups. The method trains an Auto-Encoder and Auto Decoder (AE&AD) model based on the features and the feature correlations to reconstruct the normal historical data with minimum reconstruction errors. The method reconstructs, using the trained AE&AD model, historical data of specific car fault types with reconstruction errors, normalizes the reconstruction errors, and selects features of the car faults with a top k large errors as fault signatures. The method reconstructs streaming data of monitored cars using the trained AE&AD model to determine streaming reconstruction errors, comparing the streaming reconstruction errors with the fault signatures to predict and provide alerts for impending known faults.
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Patent Agency Ranking
146.发明授权公开(公告)号：US11087226B2
公开(公告)日：2021-08-10
申请号：US15888472
申请日：2018-02-05
Applicant: NEC Laboratories America, Inc.
Inventor： Wei Cheng , Haifeng Chen
Abstract: A system identifies multiple causal anomalies in a power plant having multiple system components. The system includes a processor. The processor constructs an invariant network model having (i) nodes, each representing a respective system component and (ii) invariant links, each representing a stable component interaction. The processor constructs a broken network model having (i) the invariant network model nodes and (ii) broken links, each representing an unstable component interaction. The processor ranks causal anomalies in node clusters in the invariant network model to obtain anomaly score results. The processor generates, using a joint optimization clustering process applied to the models, (i) a model clustering structure and (ii) broken cluster scores. The processor performs weighted fusion ranking on the anomaly score results and broken cluster scores, based on the clustering structure and implicated degrees of severity of any abnormal system components, to identify the multiple causal anomalies in the power plant.
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公开(公告)号：US20210232918A1
公开(公告)日：2021-07-29
申请号：US17158092
申请日：2021-01-26
Applicant: NEC Laboratories America, Inc.
Inventor： Wei Cheng , Haifeng Chen , Wenchao Yu
Abstract: Methods and systems for training a graph neural network (GNN) include training a denoising network in a GNN model, which generates a subgraph of an input graph by removing at least one edge of the input graph. At least one GNN layer in the GNN model, which performs a GNN task on the subgraph, is jointly trained with the denoising network.
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公开(公告)号：US20210089992A1
公开(公告)日：2021-03-25
申请号：US17016709
申请日：2020-09-10
Applicant: NEC Laboratories America, Inc.
Inventor： Jianwu Xu , Ding Li , Wei Cheng , Haifeng Chen
Abstract: A method for automatically recommending a reviewer for submitted codes is presented. The method includes employing, in a learning phase, an artificial intelligence agent for learning an underlying and contextual structure of code regions, mapping the code regions into a distributed representation to define code region representations, employing, in a recommendation phase, the artificial intelligence agent to produce a ranked list of recommended reviewers for any given submitted code review request, and outputting the ranked list of recommended reviewers to a visualization device.
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公开(公告)号：US20200380295A1
公开(公告)日：2020-12-03
申请号：US16816752
申请日：2020-03-12
Applicant: NEC Laboratories America, Inc.
Inventor： Masanao Natsumeda , Wei Cheng , Haifeng Chen , Yuncong Chen
Abstract: Methods and systems for predicting failure in a cyber-physical system include determining a prediction index based on a comparison of input time series, from respective sensors in a cyber-physical system, to failure precursors. A failure precursor is detected in the input time series, responsive to a comparison of the prediction index to a threshold. A subset of the sensors associated with the failure precursor is determined, based on a gradient of the prediction index. A corrective action is performed responsive to the determined subset of sensors.
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公开(公告)号：US20200090025A1
公开(公告)日：2020-03-19
申请号：US16553465
申请日：2019-08-28
Applicant: NEC Laboratories America, Inc.
Inventor： Wei Cheng , LuAn Tang , Dongjin Song , Bo Zong , Haifeng Chen , Jingchao Ni , Wenchao Yu
Abstract: Systems and methods for predicting system device failure are provided. The method includes representing device failure related data associated with the devices from a predetermined domain by temporal graphs for each of the devices. The method also includes extracting vector representations based on temporal graph features from the temporal graphs that capture both temporal and structural correlation in the device failure related data. The method further includes predicting, based on the vector representations and device failure related metrics in the predetermined domain, one or more of the devices that is expected to fail within a predetermined time.
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