International Business Machines Corporation

Globalfoundries Inc.

The University of Melbourne

The Florey Institute of Neuroscience and Mental Health

Stefan Harrer

Laurence J Plant

Stephen Mark Rossnagel

Gustavo Alejandro Stolovitzky

Hongbo Peng

Binquan Luan

Ali Afzali-Ardakani

Stanislav Polonsky

Philip S Waggoner

Michael Sean Brown

Sean Rory Costello

Glenn John Martyna

Jianbin Tang

Ajay K Royyuru

James David Cleaver

Julia S Baldauf

Christine Schieber

Subhrajit Roy

Benjamin Scott Mashford

Umar Asif

Filiz Isabell Kiral-Kornek

Natalie J Gunn

Dario Leonardo Goldfarb

George Frederick Walker

John Michael Wagner

Stefan Von Cavallar

Priscilla Racquel Rogers

Steven J Holmes

Hariklia Deligianni

Matthew Earl Colburn

John Albrecht Ott

Dennis Merton Newns

Mark B Ketchen

Jeffrey L Rogers

Xiaoyan Shao

Deqiang Wang

Shafaat Ahmed

Christopher J Pavlovski

Matthew Downton

Erhan Bilal

Mahtab Mirmomeni

Stefan Renard Maetschke

Tian Hao

Deval Samirbhai Mehta

Ross Bathgate

Daniel Scott

Stan Skafidas

Daniel Sanders

Pushkara Rao Varanasi

John Christopher Arnold

Ho-Cheol Kim

Joy Cheng

Kuang-Jung Chen

Young Hoon Kwark

William Dinan Hinsberg

Arun Vishwanath

Saket Sathe

Antonio Jose Jimeno Yepes

Jose Miguel Lobez Comeras

Sung Cheol Kim

Josef Reisinger

Susmita Saha

Michael S Brown

Sue Ann Chen

Sridhar Kannam

Tania Ezra

Matthew Downtown

Ali Afzali-Azdakani

A method, a structure, and a computer system for privacy-preserving motion analysis. Embodiments may include identifying one or more joints of a user based on collected data and generating one or more 3D representations of the one or more joints of the user. Embodiments may further include anonymizing the one or more 3D representations, classifying one or more actions of the user based on the one or more 3D representations, wherein the classifying outputs an action score, and exporting at least one of the one or more actions and the action score.

Privacy-preserving motion analysis

A method, a computer program product, and a computer system determine abnormal motion from a patient. The method includes receiving sensory data of the patient and a location in which the patient is present. The sensory data includes video data over a period of time the patient is being monitored. The method includes generating contextual information based on the sensory data. The contextual information is indicative of surroundings of the patient and characteristics of the location. The method includes generating motion information based on the sensory data. The motion information is indicative of movement of the patient in the location. The method includes generating contextual motion data by incorporating the contextual information with the motion information. The method includes determining the abnormal motion based on the contextual motion data.

Seizure detection using contextual motion

A method, a structure, and a computer system for privacy-preserving motion analysis. Embodiments may include collecting data corresponding to a user with one or more sensors and identifying one or more joints of the user based on the data. Embodiments may additionally include generating one or more 3D representations of the one or more joints of the user and anonymizing the one or more 3D representations by applying thereto a joint-centering and a random shuffling. Embodiments may further include classifying one or more actions of the user based on analysing the one or more 3D representations, and exporting at least one of the data and the one or more actions.

Aspects described herein include a method of generating three-dimensional (3D) spikes. The method comprises receiving a signal comprising time-series data and generating a first two-dimensional (2D) grid. Generating the first 2D grid comprises mapping segments of the time-series data to respective positions of the first 2D grid, and generating, for each position, a spike train corresponding to the respective mapped segment. The method further comprises generating a second 2D grid including performing, for each position, a mathematical operation on the spike train of the corresponding position of the first 2D grid. The method further comprises generating a third 2D grid including performing spatial filtering on the positions of the second 2D grid. The method further comprises generating a 3D grid based on a combination of the first 2D grid, the second 2D grid, and the third 2D grid. The 3D grid comprises one or more 3D spikes.

Generating three-dimensional spikes using low-power computing hardware

Methods, computer program products, and systems are presented. The methods include, for instance: obtaining a style feed including a plurality of original works by an author. An author-style model for the author is built based on the style feed by use of a selected neural network, and a publication is generated in the style of the author based on the author-style model.

Cognitive natural language generation with style model

One or both of epilepsy seizure detection and prediction at least by performing the following: running multiple input signals from sensors for epilepsy seizure detection through multiple classification models, and applying weights to outputs of each of the classification models to create a final classification output. The weights are adjusted to tune relative output contribution from each classifier model in order that accuracy of the final classification output is improved, while power consumption of all the classification models is reduced. One or both of epilepsy seizure detection and prediction are performed with the adjusted weights. Another method uses streams from sensors for epilepsy seizure detection to train and create the classification models, with fixed weights once trained. Information defining the classification models with fixed weights is communicated to wearable computer platforms for epilepsy seizure detection and prediction. The streams may be from multiple people and applied to an individual person.

Epilepsy seizure detection and prediction using techniques such as deep learning methods

A method and system for improving a machine learning technical support applicant selection process is provided. The method includes retrieving and analyzing, in real time, job role data, resume based data, and sensor data associated with a plurality of individuals. A specialized memory repository is generated within a specified portion of a hardware memory device and results of the analysis are stored within the specialized memory repository. Self-learning software code for executing a job applicant selection process is generated and a plurality of current resumes and previously generated time-based resumes are retrieved for current job applicants for a specified position. The current resumes are analyzed with respect to the previously generated time-based resumes and associated inconsistencies are determined. A first job applicant is selected and the self-learning software code is modified.

Machine learning technical support selection

A process for monitoring binding events, a coating compound, and a device for monitoring binding events are disclosed. The process includes providing two reservoirs that contain an electrically conductive fluid, wherein the reservoirs are separated by a membrane having a nanopore. The process also includes selecting a target compound, selecting a ligand based on the selection of the target compound, and preparing a coating that includes the coating compound, wherein the coating compound includes the ligand and a moiety that immobilizes the ligand. Additionally, the process includes applying the coating to the inner surface of the nanopore, adding the target compound to a conductive liquid in the first chamber, establishing a voltage gradient across the membrane, and electrically monitoring translocation of the target molecule. The device includes the reservoirs and the membrane having the coated nanopore.

Nanopore coating for sensing chemical bond formation

A recommendation method, system, and computer program product include monitoring a patient using a plurality of sensors, receiving patient information including a comfort level corresponding to a sensor of the plurality of sensors, determining a relevance of each sensor of the plurality of sensors to at least one health conditions of the patient, and determining at least one sensor of the plurality of sensors to disconnect based on the comfort level and the relevance of each sensor.

Dynamic recommendations of sensors for patient monitoring

A health-monitoring method, system, and computer program product include operating at least one sensor of a health-monitoring device having a plurality of sensors, detecting a health condition event that requires operation of an additional sensor of the plurality of sensors to monitor the health condition event, activating the additional sensor of the health-monitoring device, and deactivating the additional sensor when the health condition event that requires the second sensor is no longer detected by the detecting.

Energy-efficient multisensory system for mobile health-monitoring

Nanofluidic passages such as nanochannels and nanopores are closed or opened in a controlled manner through the use of a feedback system. An oxide layer is grown or removed within a passage in the presence of an electrolyte until the passage reaches selected dimensions or is closed. The change in dimensions of the nanofluidic passage is measured during fabrication. The ionic current level through the passage can be used to determine passage dimensions. Fluid flow through an array of fluidic elements can be controlled by selective oxidation of fluidic passages between elements.

Feedback control of dimensions in nanopore and nanofluidic devices

A cognitive coaching method; detecting one or more real-time specific action occurrences during one or more game phases; generating, with a heat map generator, one or more real-time heat maps with one or more specific action label based on the detected one or more real-time specific action occurrences; training a heat map image classifier with an analytics module; transposing one or more historical heat maps comprised in a historical heat map library onto the one or more generated real-time heat maps, in real time, to generate strategic insight on one or more opposing teams; analyzing, using a predictive module, a future potential outcome based on the one or more transposed heat maps; and signaling, to a user, a recommended corrective action deployment strategy based on the analysis of the future potential outcome.

In-game strategic insight with real-time heat map generation and historical heat maps

Methods, computer program products, and systems are presented. The methods include, for instance: obtaining sample essays, sample annotations corresponding to the sample essays, and a subject content for building a subject domain comprehension model and an essay annotation model, by use of one or more neural network. The nodes of the subject domain comprehension model and the essay annotation model are interconnected based on respective relevancies for automatically annotating student works according to a standard of review corresponding to submitting students.

Cognitive essay annotation

A method and system for predicting system states is provided. The method includes receiving a first reference model associated with a first operational attribute of a system from a first integrated circuit internally comprising a first processing circuit and a first sensor measuring a first parameter of the system. Additionally, a second reference model associated with a second operational attribute of the system is received from a second integrated circuit internally comprising a second processing circuit and a second sensor measuring a second parameter of the system. A combination reference model based on the first reference model and the second reference model is generated and a predicted future state and associated operational attributes for the system are determined based on the combination reference model.

Sensor based system state prediction

Remote access of a service provider to a secure enterprise computing environment through a firewall through the use of tokens.

Secure access to an enterprise computing environment

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Hampton, Australia

Stefan Harrer