公开(公告)号：US20180165147A1

公开(公告)日：2018-06-14

申请号：US15830579

申请日：2017-12-04

Applicant: NEC Laboratories America, Inc.

Inventor： Biplob Debnath ,  Hui Zhang ,  Guofei Jiang

IPC: G06F11/07 ,  G06F17/30 ,  G06F17/27 ,  G06F11/34 ,  G06F11/30

Abstract: A computer-implemented method, computer program product, and computer processing system are provided. The method includes preprocessing, by a processor, a set of heterogeneous logs by splitting each of the logs into tokens to obtain preprocessed logs. Each of the logs in the set is associated with a timestamp and textual content in one or more fields. The method further includes generating, by the processor, a set of regular expressions from the preprocessed logs. The method also includes performing, by the processor, an unsupervised parsing operation by applying the regular expressions to the preprocessed logs to obtain a set of parsed logs and a set of unparsed logs, if any. The method additionally includes storing, by the processor, the set of parsed logs in a log analytics database and the set of unparsed logs in a debugging database.

公开(公告)号：US09984337B2

公开(公告)日：2018-05-29

申请号：US14872521

申请日：2015-10-01

Applicant: NEC Laboratories America, Inc.

Inventor： Asim Kadav ,  Erik Kruus ,  Hao Li

IPC: G06F17/30 ,  G06N99/00 ,  G06F9/46

CPC classification number: G06N99/005 ,  G06F9/46 ,  G06F17/30174 ,  G06F17/30209 ,  G06F17/30578

Abstract: Systems and methods are disclosed for providing distributed learning over a plurality of parallel machine network nodes by allocating a per-sender receive queue at every machine network node and performing distributed in-memory training; and training each unit replica and maintaining multiple copies of the unit replica being trained, wherein all unit replicas train, receive unit updates and merge in parallel in a peer-to-peer fashion, wherein each receiving machine network node merges updates at later point in time without interruption and wherein the propagating and synchronizing unit replica updates are lockless and asynchronous.

公开(公告)号：US20180137365A1

公开(公告)日：2018-05-17

申请号：US15711373

申请日：2017-09-21

Applicant: NEC Laboratories America, Inc.

Inventor： Samuel Schulter ,  Wongun Choi ,  Bharat Singh ,  Manmohan Chandraker

IPC: G06K9/00 ,  G06T9/00 ,  G06K9/32

CPC classification number: G06T7/74 ,  B60W30/09 ,  B60W30/0956 ,  G06F3/0482 ,  G06K9/00744 ,  G06K9/00771 ,  G06K9/00785 ,  G06K9/00791 ,  G06K9/00805 ,  G06K9/3241 ,  G06N3/02 ,  G06T7/20 ,  G06T7/246 ,  G06T7/292 ,  G06T9/002 ,  G06T2200/28 ,  G06T2207/10016 ,  G06T2207/20084 ,  G06T2207/30232 ,  G06T2210/12 ,  G08B21/02

Abstract: An action recognition system and method are provided. The system includes an image capture device configured to capture a video sequence formed from image frames and depicting a set of objects. The system includes a processor configured to detect the objects to form object detections. The processor is configured to track the object detections over the frames to form tracked detections. The processor is configured to generate for a current frame, responsive to conditions, sparse object proposals for a current location of an object based on: (i) the tracked detections of the object from an immediately previous frame; and (ii) detection proposals for the object derived from the current frame. The processor is configured to control a hardware device to perform a response action in response to an identification of an action type of an action performed by the object, the identification being based on the sparse object proposals.

公开(公告)号：US20180137001A1

公开(公告)日：2018-05-17

申请号：US15810960

申请日：2017-11-13

Applicant: NEC Laboratories America, Inc.

Inventor： Bo Zong ,  LuAn Tang ,  Qi Song ,  Biplob Debnath ,  Hui Zhang ,  Guofei Jiang

IPC: G06F11/07 ,  G06F11/34 ,  G06N5/04 ,  G06N3/08 ,  G06F15/18 ,  G06F17/30

CPC classification number: G06F11/079 ,  G06F11/0793 ,  G06F11/3476 ,  G06N3/084 ,  G06N5/022 ,  G06N5/04

Abstract: A method is provided that includes transforming training data into a neural network based learning model using a set of temporal graphs derived from the training data. The method includes performing model learning on the learning model by automatically adjusting learning model parameters based on the set of the temporal graphs to minimize differences between a predetermined ground-truth ranking list and a learning model output ranking list. The method includes transforming testing data into a neural network based inference model using another set of temporal graphs derived from the testing data. The method includes performing model inference by applying the inference and learning models to test data to extract context features for alerts in the test data and calculate a ranking list for the alerts based on the extracted context features. Top-ranked alerts are identified as critical alerts. Each alert represents an anomaly in the test data.

公开(公告)号：US20180130216A1

公开(公告)日：2018-05-10

申请号：US15695625

申请日：2017-09-05

Applicant: NEC Laboratories America, Inc.

Inventor： Samuel Schulter ,  Wongun Choi ,  Paul Vernaza ,  Manmohan Chandraker

IPC: G06T7/20 ,  G06T7/70 ,  H04N7/18

CPC classification number: G06T7/20 ,  G06K9/00771 ,  G06K9/6274 ,  G06T7/70 ,  G06T7/77 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30232 ,  G06T2207/30241 ,  H04N7/18 ,  H04N7/188

Abstract: A surveillance system and method are provided. The surveillance system includes at least one camera configured to capture a set of images of a given target area that includes a set of objects to be tracked. The surveillance system includes a memory storing a learning model configured to perform multi-object tracking by jointly learning arbitrarily parameterized and differentiable cost functions for all variables in a linear program that associates object detections with bounding boxes to form trajectories. The surveillance system includes a processor configured to perform surveillance of the target area to (i) detect the objects and track locations of the objects by applying the learning model to the images in a surveillance task that uses the multi-object tracking, and (ii), provide a listing of the objects and their locations for surveillance task. A bi-level optimization is used to minimize a loss defined on a solution of the linear program.

公开(公告)号：US20180129910A1

公开(公告)日：2018-05-10

申请号：US15709748

申请日：2017-09-20

Applicant: NEC Laboratories America, Inc.

Inventor： Muhammad Zeeshan Zia ,  Quoc-Huy Tran ,  Xiang Yu ,  Manmohan Chandraker ,  Chi Li

IPC: G06K9/62 ,  G06T15/40 ,  G06K9/00 ,  G06N3/02 ,  G06F17/50

CPC classification number: G06K9/6256 ,  B60T2201/022 ,  B60W30/00 ,  G05D1/0221 ,  G06F17/5009 ,  G06K9/00201 ,  G06K9/00208 ,  G06K9/00624 ,  G06K9/00771 ,  G06K9/00805 ,  G06K9/4628 ,  G06K9/6255 ,  G06N3/02 ,  G06N3/084 ,  G06T7/55 ,  G06T7/74 ,  G06T11/60 ,  G06T15/10 ,  G06T15/40 ,  G06T2207/20101 ,  G06T2207/30261 ,  G06T2210/22 ,  G08G1/0962 ,  G08G1/166 ,  H04N7/00

Abstract: A system and method are provided. The system includes an image capture device configured to capture an actual image depicting an object. The system also includes a processor. The processor is configured to render, based on a set of 3D Computer Aided Design (CAD) models, a set of synthetic images with corresponding intermediate shape concept labels. The processor is also configured to form a multi-layer Convolutional Neural Network (CNN) which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is further configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN to the actual image to output an image pair including a 2D geometric structure and a 3D geometric structure of the object depicted in the actual image.

公开(公告)号：US20180129579A1

公开(公告)日：2018-05-10

申请号：US15784393

申请日：2017-10-16

Applicant: NEC Laboratories America, Inc.

Inventor： Biplob Debnath ,  Nipun Arora ,  Hui Zhang ,  Guofei Jiang ,  Mohiuddin Solaimani ,  Muhammad Ali Gulzar

IPC: G06F11/34 ,  G06F11/07 ,  G06F11/30 ,  G06F15/18

CPC classification number: G06F11/3476 ,  G06F11/0706 ,  G06F11/0775 ,  G06F11/0787 ,  G06F11/3065 ,  G06N20/00

Abstract: Systems and methods are disclosed for processing a stream of logged data by: creating one or more models from a set of training logs during a training phase; receiving testing data in real-time and generating anomalies using the models created during the training phase; updating the one or more models during real-time processing of a live stream of logs; and detecting a log anomaly from the live stream of logs.

公开(公告)号：US09964572B2

公开(公告)日：2018-05-08

申请号：US15019610

申请日：2016-02-09

Applicant: NEC Laboratories America, Inc.

Inventor： Di Shi ,  Ratnesh Sharma ,  Feng Guo

IPC: H02J3/32 ,  G01R21/133 ,  G01R23/00 ,  H02J13/00

CPC classification number: G01R21/133 ,  G01R23/00 ,  H02J3/32 ,  H02J13/0013 ,  Y02E60/722 ,  Y02E60/7807 ,  Y04S10/14 ,  Y04S40/12

Abstract: A method and system are provided. The method includes collecting, from a plurality of phasor measurement units, a plurality of synchronized phasor measurements from different portions of a power system. The method further includes estimating, by a controller, oscillation modes of the plurality of synchronized phasor measurements. Each estimated oscillation mode specifies, for each of the plurality of synchronized phasor measurements, two or more of an amplitude, a phase, a frequency, and damping coefficients. The method also includes performing, by the controller, a modal analysis of the oscillation modes of the plurality of synchronized phasor measurements to identify critical modes based on critical mode identifying criteria. The method additionally includes constructing, by the controller based on the critical modes, a power system oscillation dampening control signal for controlling a grid-scale storage portion of the power system to dampen one or more oscillations of the power system at any given time.

公开(公告)号：US20180107529A1

公开(公告)日：2018-04-19

申请号：US15783372

申请日：2017-10-13

Applicant: NEC Laboratories America, Inc.

Inventor： Pranay ANCHURI ,  Fei WU

IPC: G06F9/54 ,  G06F17/30

CPC classification number: G06F9/542 ,  G06F11/3065 ,  G06F11/3476 ,  G06F16/2465 ,  G06F2201/86 ,  G06F2216/03

Abstract: Aspects of the present disclosure describe structural event detection from system log messages. More particularly disclosed are computer-implemented methods to mine structural events as directed workflow graphs where nodes of the graphs represent log patterns and edges represent relations among patterns. Advantageously, the structural events are inclusive and correspond to interpretable episodes in the system and methods according to the present disclosure directly model the overall quality of structural events. Through both qualitative and quantitative experiments on real-world datasets, the effectiveness of the disclosed methods are demonstrated.

公开(公告)号：US20180102851A1

公开(公告)日：2018-04-12

申请号：US15729021

申请日：2017-10-10

Applicant: NEC Laboratories America, Inc. ,  NEC Corporation

Inventor： Shaoliang Zhang ,  Fatih Yaman ,  Eduardo Mateo Rodriquez ,  Yoshihisa Inada

IPC: H04B10/516 ,  H04B10/079 ,  H04Q11/00

CPC classification number: H04B10/5161 ,  H04B10/07953 ,  H04B10/532 ,  H04B10/541 ,  H04Q11/0066 ,  H04Q2011/0049 ,  H04Q2011/0083

Abstract: Systems and methods for data transport in an optical communications system, including generating a pairwise optimized (PO) multi-dimensional signal constellation in a single stage. The PO multi-dimensional signal constellation is generated by selecting a pair of symbols from a received constellation with M symbols, defining and minimizing an objective function with one or more constraints to optimize the selected pair of symbols, and iteratively selecting and optimizing one or more different pairs of symbols from the received constellation until a threshold condition is reached. Neighbor symbols from the generated PO multi-dimensional signal constellation in each polarization are clustered to formulate a clustered PO multi-dimensional signal constellation, and data is modulated and transmitted in accordance with the clustered PO multi-dimensional signal constellation.