International Business Machines Corporation

Catherine Helen Crawford

John A Gunnels

Ramya Raghavendra

Grzegorz Michal Swirszcz

Rhonda L Childress

David B Kumhyr

Neil Raymond Pennell

Nirmit V Desai

Aisha Walcott

Shahrokh Daijavad

Inseok Hwang

Tomasz J Nowicki

Mark Richard Nutter

Lior Horesh

Supriyo Chakraborty

Piotr Padkowski

Kevin J Gildea

Scott Douglas Lekuch

Andrea Reale

Konstantinos Katrinis

Tal Kachman

Paolo Franco Magnone

Sarbajit Kumar Rakshit

Zhen Liu

Mudhakar Srivatsa

Raghu Kiran Ganti

Laura Wynter

Heather D Achilles

Henry C Will, Iv

Steven Edward Millman

Pranita Sharad Dewan

Wendy Chong

Reginald Bryant

Eleni Pratsini

Carmelo I Uria

Peter F Mycue

Adam E Grant

Randy M Fussell

Christopher P Huff

Jimi Xenidis

David Bruce Kumhyr

Physical assistance for identification of an input location on a touchscreen may include detecting that a user has contacted a touchscreen at an initial touch point with a pointing device, predicting an input location from one or more input locations for receiving input on the touchscreen, determining a path from the initial touch point to the predicted input location, and generating a physical cursor on the touchscreen at a location proximate to the pointing device, wherein the physical cursor is a raised portion of the touchscreen.

Physical cursor control in microfluidic display devices

In an embodiment, a method of sketching using a hybrid quantum-classical system includes creating a set of clustered data sets from a first data set. In an embodiment, the method includes evaluating, using a quantum processor and quantum memory, the set of clustered data sets. In an embodiment, the method includes evaluating, using the quantum processor and quantum memory, a set of quality metrics for the set of clustered data sets. In an embodiment, the method includes reclustering, responsive to at least one of the set of quality metrics failing to meet a quality criterion, the first data set.

Sketching using a hybrid quantum-classical system

Techniques for providing a reusable filled bottle are provided. A stations receives a bottle request from a user and uses information from the request to select and associate a sanitized bottle to the user. The user is charged for a bottle rental and provided with a filled reusable bottle. The user may also return the bottle to the station to have the bottle refilled or return the bottle such that the bottle rental is completed and the bottle no longer associated with the user.

Liquid bottle processing and refilling

A notification message is received by a communication device The notification message includes a message identifier and a digital signature generated by an original sender of the notification message. That an integrity of message content in the notification message and an original sender of the notification message is verified is determined using the digital signature. Responsive to determining that the notification message is verified, the notification message is forwarded by the communication device using a peer-to-peer communication channel over a mesh network.

Delivering messages to offline devices using peer-to-peer communication

Hybrid classical-quantum decision maker training includes receiving a training data set, and selecting, by a first processor, a sampling of objects from the training set, each object represented by at least one vector. A quantum processor applies a quantum feature map to the selected objects to produce one or more output vectors. The first processor determines one or more distance measures between pairs of the output vectors, and determines at least one portion of the quantum feature map to modify the classical feature map. The first processor adds an implementation of the at least one portion of the quantum feature map to the classical feature map to generate an updated classical feature map.

Quantum space distance estimation for classifier training using hybrid classical-quantum computing system

A method, computer system, and computer program product for a cognitive, real-time feedback speaking coach are provided. The embodiment may include capturing a plurality of text from a prepared document. The embodiment may also include capturing a plurality of user voice data and a plurality of user movement data. The embodiment may further include calculating a speaker rating based on the plurality of received user voice data, the plurality of received user movement data, and the plurality of captured text. The embodiment may also include identifying one or more points of improvement based on the calculated speaker rating. The embodiment may further include alerting a user of the one or more identified points of improvement.

Cognitive real-time feedback speaking coach on a mobile device

A distributed file system (DFS) is provided that is configured to store data in a General Parallel File system (GPFS) and interface with a client configured to interface with a HADOOP Distributed File System (HDFS). The DFS includes a first Node; and a plurality of second Nodes including the GPFS. The first Node is configured to convert an HDFS command from the client into a GPFS command, apply the GPFS command to the GPFS to access a GPFS file, format an HDFS data structure to include identifiers of a set of the second nodes storing the GPFS file, a filename of the GPFS file, and an offset into the GFPS file, and send the HDFS data structure to the client. Each of the second Nodes is configured to access the GPFS using a part of the HDFS data structure received from the client.

Enabling a Hadoop file system with POSIX compliance

A path computing method, system, and computer program product, include extracting unpleasant data from a database to create a multivariate spatia-temporal density function, collecting a tolerance level of a user, and computing a path for the user based on the tolerance level and the density function.

System, method and computer program product for path computing based on unpleasant data

A first feature set for an accident is identified, based on one or more historical accident reports. The accident is geolocated to obtain road data for a location of the accident. Weather data for the accident is obtained, based on the accident location. Hidden data for the accident is obtained, based on the accident location and the time of the accident. The first feature set is combined with the road data, weather data, and hidden data to produce a complete feature set for the accident. A model feature set is generated, based on a combination of the complete feature set and a plurality of other complete feature sets produced based on historical accident reports for a plurality of other accidents.

Generating driving behavior models

A method and system of storing and retrieving data in a computer system are disclosed. In an embodiment, the method comprises storing a data object at a specified location in a first data store, storing in a second data store first information identifying said specified location, retrieving the data object from a defined location in the first data store, obtaining second information identifying the defined location in the first data store, and comparing the second information to the first information to determine if the first information and the second information identify a same location in the first data store. In embodiments of the invention, the method further comprises when the second information and the first information identify different locations in the first data store, generating a fault signal to indicate that the location of the data object in the first data store has changed.

Distributed client based cache for keys using demand fault invalidation

A vehicle weight detection method, system, and non-transitory computer readable medium, include calculating a first difference between a first expected weight of a vehicle and a first current weight of the vehicle based on On-Board Dash (OBD) input data, calculating a second difference between a second expected weight of the vehicle and a second current weight of the vehicle based on a spring-mass-damper mechanical algorithm using vehicle data received from a user device, and a comparing circuit configured to compare each of the first difference and the second difference to a predetermined weight difference threshold value.

Vehicle weight detection

A geolocation data discovery method, system, and non-transitory computer readable medium, include mining a textual alert message of an event from secure source data for a geolocational indicator, a temporal indicator, and a type of alert, embedding a geolocational tag location and a temporal tag time to the event based on the geolocational indicator and the temporal indicator mined from the textual alert message by the secure text mining, mapping the event with an icon related to the type of alert at the geolocational tag location on a navigational map at a time associated with the temporal tag time of the event, learning a false-positive event by comparing a secure sensor with an unsecure sensor as the secure source data, and removing updates to the icon on the map based on the learned false-positive event.

System, method, and recording medium for geolocation data discovery in streaming texts

Dynamic graph adaptation for stream processing over hybrid, physically disparate analytics platforms, by means of a computer-implemented method that includes obtaining a streaming application graph, generating a partitioned graph by partitioning the streaming application graph in response to a topology descriptor and a partitioning algorithm, compiling the partitioned graph into a plurality of subgraphs for deployment to a plurality of respective runtimes that are described by the topology descriptor, and deploying the plurality of subgraphs to the plurality of respective runtimes.

Dynamic graph adaptation for stream processing over hybrid, physically disparate analytics platforms

A geolocation data discovery method, system, and non-transitory computer readable medium, include a secure text mining circuit configured to mine a textual alert message of an event from secure source data for a geolocational indicator, a temporal indicator, and a type of alert, a geolocation and temporal embedding circuit configured to embed a geolocational tag location and a temporal tag time to the event based on the geolocational indicator and the temporal indicator mined from the textual alert message by the secure text mining circuit, and an event mapping circuit configured to map the event with an icon related to the type of alert at the geolocational tag location on a navigational map at a time associated with the temporal tag time of the event.

Growing community of inventors

Carmel, NY, United States of America

Catherine Helen Crawford