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491.
公开(公告)号:US20230304189A1
公开(公告)日:2023-09-28
申请号:US18174799
申请日:2023-02-27
Applicant: NEC Laboratories America, Inc.
Inventor: Renqiang Min , Hans Peter Graf
IPC: C40B30/04 , G06N3/092 , G06N3/0442 , C40B20/04 , G16B40/00
CPC classification number: C40B30/04 , G06N3/092 , G06N3/0442 , C40B20/04 , G16B40/00
Abstract: A method for implementing deep reinforcement learning with T-cell receptor (TCR) mutation policies to generate binding TCRs for immunotherapy includes extracting peptides to identify a virus or tumor cells, collecting a library of TCRs from patients, predicting interaction scores between the extracted peptides and the TCRs from the patients, developing a deep reinforcement learning framework with TCR mutation policies to generate TCRs with maximum binding scores, defining reward functions, outputting mutated TCRs, ranking the outputted TCRs to utilize top-ranked TCR candidates to target the virus or the tumor cells, and for each top-ranked TCR candidate, repeatedly identifying a set of self-peptides that the top-ranked TCR candidate binds to and further optimizing it greedily by maximizing a sum of its interaction scores with a given set of peptide antigens while minimizing a sum of its interaction scores with the set of self-peptides until stopping criteria of efficacy and safety are met.
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公开(公告)号:US11756349B2
公开(公告)日:2023-09-12
申请号:US17015239
申请日:2020-09-09
Applicant: NEC Laboratories America, Inc.
Inventor: Jianwu Xu , Haifeng Chen
IPC: G07C5/08 , B60W50/02 , G01R31/317 , G06N3/082 , B60W50/06 , B60W60/00 , B60R16/023 , G06N3/088 , G06V20/20 , G06V20/56 , G06F18/214 , G06N3/044 , G06N3/045 , G06V10/764 , G06V10/82 , G05D1/00
CPC classification number: G07C5/0808 , B60R16/0231 , B60W50/0205 , B60W50/06 , B60W60/001 , B60W60/0027 , G01R31/3172 , G01R31/31707 , G06F18/2148 , G06N3/044 , G06N3/045 , G06N3/082 , G06N3/088 , G06V10/764 , G06V10/82 , G06V20/20 , G06V20/56 , G06V20/588 , G05D1/0088 , G05D2201/0213
Abstract: A computer-implemented method for implementing electronic control unit (ECU) testing optimization includes capturing, within a neural network model, input-output relationships of a plurality of ECUs operatively coupled to a controller area network (CAN) bus within a CAN bus framework, including generating the neural network model by pruning a fully-connected neural network model based on comparisons of maximum values of neuron weights to a threshold, reducing signal connections of a plurality of collected input signals and a plurality of collected output signals based on connection weight importance, ranking importance of the plurality of collected input signals based on the neural network model, generating, based on the ranking, a test case execution sequence for testing a system including the plurality of ECUs to identify flaws in the system, and initiating the test case execution sequence for testing the system.
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公开(公告)号:US20230281999A1
公开(公告)日:2023-09-07
申请号:US18188701
申请日:2023-03-23
Applicant: NEC Laboratories America, Inc.
Inventor: Samuel Schulter , Sparsh Garg
CPC classification number: G06V20/54 , G06V20/70 , G06V10/774 , G06V10/26 , G06V10/761 , G06V10/86 , G08G1/16 , G08G1/09 , G06V10/82
Abstract: Methods and systems identifying road hazards include capturing an image of a road scene using a camera. The image is embedded using a segmentation model that includes an image branch having an image embedding layer that embeds images into a joint latent space and a text branch having a text embedding layer that embeds text into the joint latent space. A mask is generated for an object within the image using the segmentation model. A probability is determined that the object matches a road hazard using the segmentation mode. A signal is generated responsive to the probability to ameliorate a danger posed by the road hazard.
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公开(公告)号:US20230280739A1
公开(公告)日:2023-09-07
申请号:US18173452
申请日:2023-02-23
Applicant: NEC Laboratories America, Inc.
Inventor: Peng Yuan , LuAn Tang , Haifeng Chen , Motoyuki Sato
IPC: G05B23/02
CPC classification number: G05B23/0283
Abstract: Methods and systems for anomaly detection include training an anomaly detection histogram model using historical categorical value data. Training the anomaly detection histogram model includes generating a histogram template based on historical categorical data, converting the historical categorical data to a histogram using the histogram template, and determining a normal range and anomaly threshold for the categorical data using the histogram.
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公开(公告)号:US11741712B2
公开(公告)日:2023-08-29
申请号:US17463757
申请日:2021-09-01
Applicant: NEC Laboratories America, Inc.
Inventor: Asim Kadav , Farley Lai , Hans Peter Graf , Alexandru Niculescu-Mizil , Renqiang Min , Honglu Zhou
IPC: G06V20/40 , G06T7/73 , G06T7/246 , G06F18/213 , G06N3/045
CPC classification number: G06V20/41 , G06F18/213 , G06N3/045 , G06T7/246 , G06T7/73 , G06V20/46 , G06T2207/10016 , G06T2207/20081 , G06T2207/20084 , G06V2201/07
Abstract: A method for using a multi-hop reasoning framework to perform multi-step compositional long-term reasoning is presented. The method includes extracting feature maps and frame-level representations from a video stream by using a convolutional neural network (CNN), performing object representation learning and detection, linking objects through time via tracking to generate object tracks and image feature tracks, feeding the object tracks and the image feature tracks to a multi-hop transformer that hops over frames in the video stream while concurrently attending to one or more of the objects in the video stream until the multi-hop transformer arrives at a correct answer, and employing video representation learning and recognition from the objects and image context to locate a target object within the video stream.
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公开(公告)号:US11736867B2
公开(公告)日:2023-08-22
申请号:US17579516
申请日:2022-01-19
Applicant: NEC Laboratories America, Inc.
Inventor: Junqiang Hu , Ting Wang
CPC classification number: H04R23/008 , G01H9/004 , H03G3/3005 , H04R1/08 , H04R3/00 , H03G2201/103 , H04R2430/01
Abstract: Aspects of the present disclosure describe DFOS/DAS systems, methods, and structures that employ active microphones to enhance DAS operational capabilities by using an active circuit to amplify acoustic signals including voice(s). The circuit includes a microphone to collect acoustic signal(s) resulting from voice signals in the environment, and a speaker or a vibration device driven by an amplifier. The circuit can be clipped onto the fiber, with direct contact through the speaker or vibration device. A microcontroller may advantageously be employed to control the circuit for reduced power consumption, by detecting activities locally and only enabling the speaker when needed. The microcontroller may also send other information such as battery status to the DFOS interrogator through vibration codes.
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497.
公开(公告)号:US20230253068A1
公开(公告)日:2023-08-10
申请号:US18151686
申请日:2023-01-09
Applicant: NEC Laboratories America, Inc.
Inventor: Renqiang Min , Hans Peter Graf , Ziqi Chen
Abstract: A method for implementing deep reinforcement learning with T-cell receptor (TCR) mutation policies to generate binding TCRs recognizing target peptides for immunotherapy is presented. The method includes extracting peptides to identify a virus or tumor cells, collecting a library of TCRs from target patients, predicting, by a deep neural network, interaction scores between the extracted peptides and the TCRs from the target patients, developing a deep reinforcement learning (DRL) framework with TCR mutation policies to generate TCRs with maximum binding scores, defining reward functions based on a reconstruction-based score and a density estimation-based score, randomly sampling batches of TCRs and following a policy network to mutate the TCRs, outputting mutated TCRs, and ranking the outputted TCRs to utilize top-ranked TCR candidates to target the virus or the tumor cells for immunotherapy.
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公开(公告)号:US20230252139A1
公开(公告)日:2023-08-10
申请号:US18157180
申请日:2023-01-20
Applicant: NEC Laboratories America, Inc.
Inventor: Yanchi Liu , Xuchao Zhang , Haifeng Chen , Wei Cheng , Shengming Zhang
IPC: G06F21/55
CPC classification number: G06F21/554
Abstract: A method for implementing a self-attentive encoder-decoder transformer framework for anomaly detection in event sequences is presented. The method includes feeding event content information into a content-awareness layer to generate event representations, inputting, into an encoder, event sequences of two hierarchies to capture long-term and short-term patterns and to generate feature maps, adding, in the decoder, a special sequence token at a beginning of an input sequence under detection, during a training stage, applying a one-class objective to bound the decoded special sequence token with a reconstruction loss for sequence forecasting using the generated feature maps from the encoder, and during a testing stage, labeling any event representation whose decoded special sequence token lies outside a hypersphere as an anomaly.
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公开(公告)号:US11692867B2
公开(公告)日:2023-07-04
申请号:US17506471
申请日:2021-10-20
Applicant: NEC Laboratories America, Inc.
Inventor: Junqiang Hu , Yue-Kai Huang , Ezra Ip
CPC classification number: G01H9/004 , G02B6/4212
Abstract: A distributed optical fiber sensing (DOFS)/distributed acoustic sensing (DAS) method employing polarization diversity combining and spatial diversity combining for a DOFS/DAS system wherein the polarization diversity combining determines a temporal average product for each beating product, determines one having a max average power, rotates that one having max average power for its phase shift to produce a reference, determines a phase difference for each beating product as compared to the reference, compensates any phase difference such that all beating products exhibit a well-aligned phase; and combining the beating products; and wherein the spatial diversity combining uses the combined beating products for each location, determines a temporal average power, determines a location having a greatest average power; and combines the results and provides an indicia of the combined result(s).
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500.
公开(公告)号:US11680849B2
公开(公告)日:2023-06-20
申请号:US17227313
申请日:2021-04-10
Applicant: NEC Laboratories America, Inc.
Inventor: Yangmin Ding , Yue Tian , Sarper Ozharar , Ting Wang
CPC classification number: G01H9/004 , G08B21/182 , G06N20/00
Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously enable and/or facilitate the continuous monitoring and identification of damaged utility poles by employing a DFOS distributed acoustic sensing (DAS) methodology in conjunction with a finite element analysis and operational modal analysis. Of particular advantage and in further contrast to the prior art, systems, methods, and structures according to aspects of the present disclosure utilize existing optical fiber supported/suspended by the utility poles as a sensing medium for the DFOS/DAS operation.
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