International Business Machines Corporation

Globalfoundries Inc.

Sambit Sahu

Milind R Naphade

Anees Abdul Shaikh

Debanjan Saha

Prashant Pradhan

Yaoping Ruan

Ming Li

Zhen Liu

Hai Huang

Douglas Morgan Freimuth

Erich Miles Nahum

Hidayatullah Habeebullah Shaikh

Jing Dai

Dinesh C Verma

Ronald Mraz

John Michael Tracey

Anca Sailer

Ajay Mohindra

Younghun Kim

Elbert C Hu

Ashish Kundu

Dinakaran B Joseph

Lap Thiet Huynh

Raymond Byars Jennings, Iii

Salman Abdul Baset

Michael E Baskey

George V Popescu

Jeremy Silber

Michael D Williams

Hongliang Fei

Stephen Eric Levy

Tian-Jy Chao

Chun-Shi Chang

Kunwadee Sripanidkulchai

Michael R Haley

Mahesh Viswanathan

Andrzej P Kochut

Alexei A Karve

Gerd Breiter

Lawrence David Bergman

Kirk Alan Beaty

Einar Lueck

Chitra Dorai

Charles Otto Schulz

Milton H Hernandez

Jie Zheng

Michael John Fork

Robert Alan Flavin

Kumar Bhaskaran

Upendra Sharma

Ramendra K Sahoo

Pavankumar Murali

Marcel-Catalin Rosu

Sivaram Gottimukkala

Mandis S Beigi

Winnie W Cheng

John Reumann

Ravi B Konuru

Patrick B Heywood

Manpreet Singh

Sanghwan Lee

John Hutchinson

Sanjay K Mamidipalli

Ashish Jagmohan

Michele M Franceschini

Murthy V Devarakonda

Kang-Won Lee

Anton Viktorovich Riabov

Parijat Dube

Suresh N Chari

Donna N Dillenberger

Renu Tewari

Ajay Ashok Deshpande

Hani Talal Jamjoom

Sai Zeng

Jason D LaVoie

Feng Chen

Pau-Chen Cheng

David Alson George

Flavio Du Pin Calmon

Feng Cheng

Augustin Chaintreau

Francois Baccelli

Chang-Hao Tsai

Debanjan Saba

Xiangdong Ding

Yaoping Roan

Roland Mraz

Raymond B Jennings

Kin H Lei

Theophilus Benson

Dehanjan Saba

Kai-Yuan Hou

Elbert V Hu

An example operation may include one or more of partitioning a data set from a data provider into a training data set and a test data set, exposing the training data set to a learning service provider while preventing the learning service provider from being able to access the test data set, wherein the preventing comprises encrypting the test data set and storing the encrypted test data set in an immutable ledger, receiving a learning model that is generated by the learning service provider based on the exposed training data set, executing the received learning model using the test data set as input to verify whether the learning model satisfies a predefined performance threshold, and in response to verifying the learning model satisfies the predefined performance threshold, outputting information about the verification to a computing node.

Learning service blockchain

Providing an end-to-end citizen engagement, in one aspect, may comprise obtaining data of multiple disintegrated sources from one or more of communication and social computing channels via one or more adapters. Data refactoring and management, integration and process orchestration of the data according to a data model as data attributes of the data model may be provided. One or more analytics may be performed based on the data attributes stored according to the data model and input specified to the one or more analytics. One or more results computed by performing the one or more analytics may be provided. One or more application logics supporting one or more front-end applications may be produced. One or more front-end applications for automated sensing of user activities and sensor-based individual assistant capability may be provided.

End-to-end effective citizen engagement via advanced analytics and sensor-based personal assistant capability (EECEASPA)

Access is obtained to a plurality of intermediately transformed electronic documents (with a plurality of sections and subsections) which have been transformed, by topical analysis and text summarization techniques, from a plurality of original electronic documents comprising at least some unstructured electronic documents. Audit and retrieval agent code is appended to the sections and subsections to create a plurality of finally transformed electronic documents. Users are allowed to access the finally transformed electronic documents. The users are provided with accountability reminders contemporaneous with the access. The access of the users to the sections and subsections of the finally transformed electronic documents is logged. An audit report is provided based on the logging. Also provided is a cloud service for enterprise-level sensitive data protection with variable data granularity, using one or more one guest virtual machine images.

Enterprise-level data protection with variable data granularity and data disclosure control with hierarchical summarization, topical structuring, and traversal audit

A GPS-enabled cellular electronic device is operated in an indoor mode. An increase in strength of a cellular signal is detected at the GPS-enabled cellular electronic device. Responsive at least to the increase in cellular signal strength, the GPS-enabled cellular electronic device is transitioned to an outdoor testing mode. Detecting is carried out to determine whether movement of the GPS-enabled cellular electronic device occurs during the outdoor testing mode. If so, the GPS-enabled cellular electronic device is transitioned to an outdoor mode.

Energy efficient location tracking on smart phones

In an illustrative embodiment, a computing system comprises a first computer coupled to one or more additional computers. Each of the one or more additional computers manages a respective set of one or more virtualized computing resources. The first computer manages the one or more additional computers.

Modular cloud computing system

Providing an end-to-end citizen engagement, in one aspect, may comprise obtaining data of multiple disintegrated sources from one or more of communication and social computing channels via one or more adapters. Data refactoring and management, integration and process orchestration of the data according to a data model as data attributes of the data model may be provided. One or more analytics may be performed based on the data attributes stored according to the data model and input specified to the one or more analytics. One or more results computed by performing the one or more analytics may be provided. One or more application logics supporting one or more front-end applications may be produced. One or more front-end applications for automated sensing of user activities and sensor-based personal assistant capability may be provided.

Systems and articles of manufacture for enabling access to user-specified and/or user-chosen content via remote third-party systems include communicating with a content provider via use of one or more user credentials, wherein the content provider maintains a list of user content choices and one or more preferences for content, wherein the content is generated by the user and/or by the content provider and/or by one or more other users, automatically downloading an amount of user-specified and/or user-chosen content from the list of user content choices and one or more preferences to a primary enterprise system and/or a secondary enterprise system in conjunction with an interaction between the user and the primary enterprise system, and providing access to the downloaded user-specified and/or user-chosen content to the user in conjunction with an interaction between the user and the secondary enterprise system, the content provider and/or the primary enterprise system.

Enabling access to user-chosen and/or preferred content via remote trusted third-party systems

Techniques for enabling access to user-specified and/or user-chosen content via remote third-party systems. A method includes communicating with a content provider via use of one or more user credentials, wherein the content provider maintains a list of user content choices and one or more preferences for content, wherein the content is generated by the user and/or by the content provider and/or by one or more other users, automatically downloading an amount of user-specified and/or user-chosen content from the list of user content choices and one or more preferences to a primary enterprise system and/or a secondary enterprise system in conjunction with an interaction between the user and the primary enterprise system, and providing access to the downloaded user-specified and/or user-chosen content to the user in conjunction with an interaction between the user and the secondary enterprise system, the content provider and/or the primary enterprise system.

A method for freight vehicle monitoring includes obtaining historical telecommunications data, performing vehicle location identification using the historical telecommunications data, wherein performing the vehicle location identification comprises using a machine learning based algorithm to determine one or more meaningful vehicle locations, identifying, based on the one or more meaningful vehicle locations, if one or more telecommunications devices are those of a freight vehicle occupant, and tracking a location of the one or more telecommunications devices identified as those of a freight vehicle occupant.

Freight vehicle monitoring using telecommunications data

Enhanced personalized advertisements may be provided through media such as IPTV, for example, by analyzing data such as subscribers' mobility data (calling and movement data), television (TV) watching history, online browsing data (e.g., Internet, web site browsing), and subscribers' historical purchasing transactions. With the analysis, subscribers' contexts, any information that reflects subscribers' interests and activities, and intents, tendency to buy certain products, items, services, and/or travel to some locations may be inferred.

Mobility enhanced advertising on internet protocol television

Detecting appliance in a building, in one aspect, may comprise receiving meter data associated with energy consumption, the meter data comprising at least energy consumption data associated with usage of the appliance, receiving customer data associated with the meter data, extracting features for training a model for detecting the appliance, based on at least the meter data and the customer data, and constructing the model based on the features.

Detecting appliances in a building from coarse grained meter data with partial label

Growing community of inventors

Hopewell Junction, NY, United States of America

Sambit Sahu