公开(公告)号：US20240129195A1

公开(公告)日：2024-04-18

申请号：US18481988

申请日：2023-10-05

Applicant: NEC Laboratories America, Inc.

Inventor： Philip JI ,  Ting WANG ,  Zilong YE

IPC: H04L41/0896 ,  H04L41/122

CPC classification number: H04L41/0896 ,  H04L41/122

Abstract: Described is a novel framework, we call intent-based computing jobs assignment framework, for efficiently accommodating a clients' computing job requests in a mobile edge computing infrastructure. We define the intent-based computing job assignment problem, which jointly optimizes the virtual topology design and virtual topology mapping with the objective of minimizing the total bandwidth consumption. We use the Integer Linear Programming (ILP) technique to formulate this problem, and to facilitate the optimal solution. In addition, we employ a novel and efficient heuristic algorithm, called modified Steiner tree-based (MST-based) heuristic, which coordinately determines the virtual topology design and the virtual topology mapping. Comprehensive simulations to evaluate the performance of our solutions show that the MST-based heuristic can achieve an efficient performance that is close to the optimal performance obtained by the ILP solution.

公开(公告)号：US20240125962A1

公开(公告)日：2024-04-18

申请号：US18485247

申请日：2023-10-11

Applicant: NEC Laboratories America, Inc.

Inventor： Yifan WU ,  Ming-Fang HUANG ,  Shaobo HAN ,  Jian FANG ,  Yuheng CHEN ,  Yaowen LI ,  Mohammad KHOJASTEPOUR

IPC: G01V1/37 ,  G01H9/00 ,  G01V1/30 ,  G01V8/24

CPC classification number: G01V1/375 ,  G01H9/004 ,  G01V1/305 ,  G01V1/307 ,  G01V8/24 ,  G01V2210/21 ,  G01V2210/48 ,  G01V2210/65 ,  G01V2210/667 ,  G01V2210/67 ,  G01V2210/72 ,  G01V2210/74

Abstract: Method for source localization for cable cut prevention using distributed fiber optic sensing (DFOS)/distributed acoustic sensing (DAS) is described that is robust/immune to underground propagation speed uncertainty. The method estimates the location of a vibration source while considering any uncertainty of vibration propagation speed and formulates the localization as an optimization problem, and both location of the sources and the propagation speed are treated as unknown. This advantageously enables our method to adapt to variances of the velocity and produce a better generalized performance with respect to environmental changes experienced in the field. Our method operates using a DFOS system and AI techniques as an integrated solution for vibration source localization along an entire optical sensor fiber cable route and process real-time DFOS data and extract features that are related to a location of a source of vibrations that may threaten optical fiber facilities.

公开(公告)号：US20240104344A1

公开(公告)日：2024-03-28

申请号：US18467069

申请日：2023-09-14

Applicant: NEC Laboratories America, Inc. ,  NEC Corporation

Inventor： LuAn Tang ,  Peng Yuan ,  Yuncong Chen ,  Haifeng Chen ,  Yuji Kobayashi ,  Jiafan He

IPC: G06N3/0442

CPC classification number: G06N3/0442

Abstract: Methods and systems for training a model include distinguishing hidden states of a monitored system based on condition information. An encoder and decoder are generated for each respective hidden state using forward and backward autoencoder losses. A hybrid hidden state is determined for an input sequence based on the hidden states. The input sequence is reconstructed using the encoders and decoders and the hybrid hidden state. Parameters of the encoders and decoders are updated based on a reconstruction loss.

公开(公告)号：US20240103215A1

公开(公告)日：2024-03-28

申请号：US18369041

申请日：2023-09-15

Applicant: NEC Laboratories America, Inc.

Inventor： Fatih YAMAN ,  Shaobo HAN ,  Eduardo Fabian MATEO RODRIGUEZ ,  Yang LI ,  Yoshihisa INADA ,  Takanori INOUE

IPC: G02B6/024 ,  G02B6/44

CPC classification number: G02B6/024 ,  G02B6/4427

Abstract: An advance in the art is made according to aspects of the present disclosure directed to methods for earthquake sensing that employ a supervisory system of undersea fiber optic cables. Earthquakes and other environmental disturbances are detected by monitoring the polarization of interrogation light instead of its phase. More specifically, our methods monitor the transfer matrix rather than just polarization and isolate disturbance location by monitoring eigenvalues of the polarization transfer matrix. From results obtained we have demonstrated experimentally that we can monitor disturbances that affect signal polarization on a span-by-span basis using High Loss Loop Back (HLLB) paths. It is shown that by measuring the polarization rotation matrix and determining the polarization rotation angle we can identify the span where the disturbance occurred with 35 dB extinction with no limitation on the magnitude of the disturbance and the number of affected spans.

公开(公告)号：US20240089592A1

公开(公告)日：2024-03-14

申请号：US18466296

申请日：2023-09-13

Applicant: NEC Laboratories America, Inc.

Inventor： Kunal Rao ,  Sibendu Paul ,  Giuseppe Coviello ,  Murugan Sankaradas ,  Oliver Po ,  Srimat Chakradhar

IPC: H04N23/60 ,  H04N23/61

CPC classification number: H04N23/64 ,  H04N23/61

Abstract: Systems and methods are provided for dynamically tuning camera parameters in a video analytics system to optimize analytics accuracy. A camera captures a current scene, and optimal camera parameter settings are learned and identified for the current scene using a Reinforcement Learning (RL) engine. The learning includes defining a state within the RL engine as a tuple of two vectors: a first representing current camera parameter values and a second representing measured values of frames of the current scene. Quality of frames is estimated using a quality estimator, and camera parameters are adjusted based on the quality estimator and the RL engine for optimization. Effectiveness of tuning is determined using perceptual Image Quality Assessment (IQA) to quantify a quality measure. Camera parameters are adaptively tuned in real-time based on learned optimal camera parameter settings, state, quality measure, and set of actions, to optimize the analytics accuracy for video analytics tasks.

公开(公告)号：US20240078430A1

公开(公告)日：2024-03-07

申请号：US18449748

申请日：2023-08-15

Applicant: NEC Laboratories America, Inc.

Inventor： Renqiang Min ,  Hans Peter Graf ,  Tianxiao Li

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: A computer-implemented method for learning disentangled representations for T-cell receptors to improve immunotherapy is provided. The method includes optionally introducing a minimal number of mutations to a T-cell receptor (TCR) sequence to enable the TCR sequence to bind to a peptide, using a disentangled Wasserstein autoencoder to separate an embedding space of the TCR sequence into functional embeddings and structural embeddings, feeding the functional embeddings and the structural embeddings to a long short-term memory (LSTM) or transformer decoder, using an auxiliary classifier to predict a probability of a positive binding label from the functional embeddings and the peptide, and generating new TCR sequences with enhanced binding affinity for immunotherapy to target a particular virus or tumor.

公开(公告)号：US20240071571A1

公开(公告)日：2024-02-29

申请号：US18471641

申请日：2023-09-21

Applicant: NEC Laboratories America, Inc.

Inventor： Renqiang Min ,  Hans Peter Graf ,  Ziqi Chen

IPC: G16B40/00 ,  G06N3/08 ,  G16B15/30

CPC classification number: G16B40/00 ,  G06N3/08 ,  G16B15/30

Abstract: A system for binding peptide search for immunotherapy is presented. The system includes employing a deep neural network to predict a peptide presentation given Major Histocompatibility Complex allele sequences and peptide sequences, training a Variational Autoencoder (VAE) to reconstruct peptides by converting the peptide sequences into continuous embedding vectors, running a Monte Carlo Tree Search to generate a first set of positive peptide vaccine candidates, running a Bayesian Optimization search with the trained VAE and a Backpropagation search with the trained VAE to generate a second set of positive peptide vaccine candidates, using a sampling from a Position Weight Matrix (sPWM) to generate a third set of positive peptide vaccine candidates, screening and merging the first, second, and third sets of positive peptide vaccine candidates, and outputting qualified peptides for immunotherapy from the screened and merged sets of positive peptide vaccine candidates.

公开(公告)号：US20240070232A1

公开(公告)日：2024-02-29

申请号：US18452664

申请日：2023-08-21

Applicant: NEC Laboratories America, Inc.

Inventor： Wei Cheng ,  Jingchao Ni ,  Liang Tong ,  Haifeng Chen ,  Yizhou Zhang

IPC: G06F18/2413 ,  G06F18/2415 ,  H04B10/69

CPC classification number: G06F18/24133 ,  G06F18/2415 ,  H04B10/697

Abstract: Methods and systems for training a model include determining class prototypes of time series samples from a training dataset. A task corresponding to the time series samples is encoded using the class prototypes and a task-level configuration. A likelihood value is determined based on outputs of a time series density model, a task-class distance from a task embedding model, and a task density model. Parameters of the time series density model, the task embedding model, and the task density model are adjusted responsive to the likelihood value.

公开(公告)号：US20240064161A1

公开(公告)日：2024-02-22

申请号：US18359179

申请日：2023-07-26

Applicant: NEC Laboratories America, Inc.

Inventor： Yanchi Liu ,  Haifeng Chen ,  Yufei Li

IPC: H04L9/40 ,  H04L41/16

CPC classification number: H04L63/1425 ,  H04L41/16

Abstract: A computer-implemented method for employing a graph-based log anomaly detection framework to detect relational anomalies in system logs is provided. The method includes collecting log events from systems or applications or sensors or instruments, constructing dynamic graphs to describe relationships among the log events and log fields by using a sliding window with a fixed time interval to snapshot a batch of the log events, capturing sequential patterns by employing temporal-attentive transformers to learn temporal dependencies within the sequential patterns, and detecting anomalous patterns in the log events based on relationships between the log events and temporal context determined from the temporal-attentive transformers.

公开(公告)号：US20240062043A1

公开(公告)日：2024-02-22

申请号：US18364746

申请日：2023-08-03

Applicant: NEC Laboratories America, Inc.

Inventor： Liang Tong ,  Zhengzhang Chen ,  Wei Cheng ,  Haifeng Chen ,  Zhuohang Li

IPC: G06N3/0455 ,  G06N3/08

CPC classification number: G06N3/0455 ,  G06N3/08

Abstract: A computer-implemented method for employing a graph-based adaptive domain generation framework is provided. The method includes, in a training phase, performing domain prototypical network training on source domains, constructing an autoencoding domain relation graph by applying a graph autoencoder to produce domain node embeddings, and performing, via a domain-adaptive classifier, domain-adaptive classifier training to make an informed decision. The method further includes, in a testing phase, given testing samples from a new source domain, computing a prototype by using a pretrained domain prototypical network, inferring node embedding, and making a prediction by the domain-adaptive classifier based on the domain node embeddings.