General Electric Company

Lockheed Martin Corporation

Utc Fire & Security Americas Corporation, Inc.

Transportation IP Holdings, LLC

Ge Aviation Systems Limited

Nbcuniversal Media, LLC

Morpho Detection, Inc.

Smiths Detection Inc.

Utc Fire and Security Corporation

Ge Security, Inc.

Lockheed Martin Company

Peter Henry Tu

Xiaoming Liu

Ting Yu

Jens Rittscher

Frederick Wilson Wheeler

Thomas Baby Sebastian

Yi Yao

GianFranco Doretto

Dashan Gao

Jilin Tu

Nils Oliver Krahnstoever

Ming-Ching Chang

Christopher Donald Johnson

James Vradenburg Miller

Glen William Brooksby

Li Guan

Kunter Seref Akbay

Kedar Anil Patwardhan

Timothy Patrick Kelliher

Naresh Sundaram Iyer

Andrew Day

Arpit Jain

Eric Michael Gros

Yan Tong

Xiaogang Wang

Junli Ping

Piero Patrone Bonissone

James D Brooks

John Michael Lizzi

Ya Xue

Matthew William Turek

Corey Nicholas Bufi

Paulo Ricardo Mendonca

Donald Wagner Hamilton

Viswanath Avasarala

Tao Gao

Jixu Chen

Weizhong Yan

Stefan Alexander Schwindt

Ser Nam Lim

Robert August Kaucic

Derek Kevin Woo

Joseph Leagrand Mundy

Daniel Joseph Rush

Jeffrey Richardson Terry

Adam Franco

Alexander S Chen

Guangliang Zhao

Weina Ge

Yelin Kim

Siwei Lyu

Lalit Keshav Mestha

Kenneth Brakeley Welles

Jeffrey Michael Ashe

Xiaoye Wu

Glen Peter Koste

Douglas Henry Marman

Richard I Hartley

Kai Erik Thomenius

Alberto Santamaria-Pang

David Toledano

Paulo Ricardo Dos Santos Mendonca

Sachin Narahari Dekate

Jimmie Autrey Beacham

Varish Vyankatesh Mulwad

Onur Ilkin Dulgeroglu

Kirk Lars Bruns

Geoffrey Cross

Victor Nzomigni

John Charles Hill, Jr

Tao Jia

Wesley David Turner

Kevin Chean

Tony Chishao Pan

Harold Woodruff Tomlinson

James Chapman Ross

Christopher John Olivier

Marco Guerriero

Ambalangoda Gurunnanselage Amitha Perera

Kenneth R Turner

Perera Ambalangoda

Rebecca Erin Biewer Brown

Michael Alan Taister

Kevin William Peter Miller

Amitha Perera

Zhiguang Wang

Tony Chi-shao Pan

Raghu Kokku

Yang Yu

Alexander S-Ban Chen

Piali Das

Marcia Peterson

Seref Akbay Kunter

John Michael Jr Lizzi

An asset identification and tracking system includes one or more monitoring units configured to monitor at least one designated area. Each of the monitoring units includes an imaging device and one or more processors. The imaging device is configured to generate image data depicting one or more mobile assets that move through the at least one designated area. The one or more processors are operably coupled to the imaging device and configured to analyze the image data to detect and decipher one or more identifiers that are displayed on a particular mobile asset of the one or more mobile assets that move through the at least one designated area. The one or more processors are further configured to generate a detection message that includes the one or more identifiers for communication to an asset control system.

Asset identification and tracking system

A method of assessing an operator emotional state and sending an alert based on the emotional state. The method includes tracking during a time period, using at least one sensor, one of an image sensor data, voice data or a biometric parameter of an operator. Determining, using a controller that is operatively connected to at least one sensor, a probability of a likely emotional state from a list of emotional states of an operator based on one of the image sensor data, voice data or the biometric parameter. Comparing, using a processor, the probability of one of the likely emotional states of the operator with a baseline emotional state of the operator. Sending, using the controller, an alert if most likely emotional state deviates from the baseline emotional state by a predetermined threshold.

Method of assessing a pilot emotional state

Briefly, embodiments are directed to a system, method, and article for acquiring a symbol comprising a representation of input data. The symbol may be converted into an emergent language expression in an emergent language via processing of a first neural network. Transmission of the emergent language expression may be initiated over a communications network, where the emergent language comprises a language based on and specific to the input data. The emergent language expression may be translated back into the representation of the input data via processing of a second neural network.

Emergent language based data encryption

An analogy generating system includes one or more image databases that include a first set of images depicting a first symbolic class and a second set of images depicting a second symbolic class and an autoencoder that receive images from the first set of images and the second set of images; determines a first characteristic shared between the first symbolic class and the second symbolic class using a first node from multiple nodes on a neural network; determine a second characteristic shared between the first symbolic class and the second symbolic class using a second node from multiple nodes on the neural network; and exchange the first characteristic and the second characteristic between the first node and the second node to establish an analogy between the first symbolic class and the second symbolic class.

Analogy engine for grounding and situational awareness

A methodof assessing an operator emotional stateand sending an alertbased on the emotional state. The methodincludes trackingduring a time period, using at least one sensor, one of an image sensor data, voice data or a biometric parameter of an operator. Determining, using a controllerthat is operatively connected to at least one sensor, a probability of a likely emotional statefrom a list of emotional statesof an operator based on one of the image sensor data, voice data or the biometric parameter. Comparing, using a processor, the probability of one of the likely emotional statesof the operator with a baseline emotional stateof the operator. Sending, using the controller, an alert if most likely emotional state deviates from the baseline emotional state by a predetermined threshold.

The present approach relates to an automatic and efficient motion plan for a drone to collect and save a qualified dataset that may be used to improve reconstruction of 3D models using the acquired data. The present architecture provides an automatic image processing context, eliminating low quality images and providing improved image data for point cloud generation and texture mapping.

Image and video capture architecture for three-dimensional reconstruction

The present approach relates to the use of a point cloud of an object to initialize or seed a space carving technique used to generate a 3D model of the object. In one implementation, feature matching is performed on 2D images, with matched features constituting the points of a point cloud model. The point cloud generated in this manner, is one input of a foreground/background segmentation algorithm, which generates a set of segmented 2D images used by a space carving routine to generate a 3D model of the object.

Three-dimensional modeling of an object

A control system having one or more controllers configured to determine physical or psychophysiological (3P) changes of an operator of a vehicle. First and second imaging devices take real-time images of an operator of a vehicle. Then, based on the physical, physiological and/or psychological features extracted from the imaging device data, and a 3P model from historical data the one or more processors also configured to, responsive to the physical, physiological and/or psychological changes of the operator of the vehicle, alert the operator and control the operation of the vehicle.

Control system and method

A method for analyzing time series data to identify an event of interest is provided. The method includes receiving, at a computing device, time series data that includes the event of interest, identifying, using the computing device, a start time of the event of interest and an end time of the event of interest by modeling at least one transitional pattern in the time series data, and categorizing, using the computing device, the event of interest based on the at least one transitional pattern.

Systems and methods for analyzing time series data based on event transitions

The present disclosure relates to the reduction of pressure ulcers and falls with respect to patients with physical or cognitive impairments who are in bed. A control system assures that the bed and ancillary apparatus are physically set and that patient behaviors are responded to by care providers. Motion is monitored with a non-mutually exclusive portfolio of sensors, and this information is used by one or more reasoning engines. An integrated clinical workflow is informed by the patterns of movement and then the physical environment, patient interaction, and care provider workflow are controlled to reduce the incidence of falls and pressure ulcers in bed ridden patients.

Sensing device for controlling the delivery of care to immobile patients

An example method includes: classifying lung function risk based on patient attributes and a clinical protocol; generating alarms and incentives for compliance with the clinical protocol based on patient attributes, clinical protocol, and patient lung function risk; determining an orientation and position of a clinical device based on tagged feature(s) of the clinical device compared to identified patient feature(s); monitoring patient interaction with the clinical device; identifying a deviation from the clinical protocol based on the monitored patient interaction, a patient biometric indicator, and a desired setpoint state in the protocol; when a deviation is identified, providing feedback proportional to the deviation, the feedback including an adjustment with respect to the clinical protocol and/or the clinical device; and triggering at least one alarm and/or incentive based on deviation and feedback, wherein the alarm/incentives differs based on whether and to what extent deviation is identified and feedback.

Systems and methods to improve lung function protocols

An authentication system includes a processor, a non-transitory computer readable medium, and one or more programs stored on the computer readable medium, where the processor, under control of the programs implements at least one neural network trained to produce first feature vectors from facial features extracted from a population of first facial images and, after training, configured to produce a second feature vector from facial features extracted from a second facial image, a discriminative classifier trained to identify closely matching ones of the first feature vectors and configured to identify whether at least one first feature vector and the second feature vector meet a correlation threshold. The authentication system may also include an access interface configured to allow access if the correlation threshold is met.

Automatic authentification for MES system using facial recognition

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Niskayuna, NY, United States of America

Peter Henry Tu