International Business Machines Corporation

Lucas Correia Villa Real

Priscilla Barreira Avegliano

Marco Aurelio Stelmar Netto

Carlos Henrique Cardonha

Renato Luiz De Freitas Cunha

Ying Liu

Thomas Henry Osiecki

Hans-Jurgen Eickelman

Vagner Figueredo De Santana

Kiran Mantripragada

Renan Francisco Santos Souza

Atsushi Abe

Renato Fontoura De Gusmao Cerqueira

Marcio Ferreira Moreno

David Allan Pease

Ulisses Mello

Rodrigo Laiola Guimaraes

Victor Fernandes Cavalcante

Ricardo Guimaraes Herrmann

Diego Sanchez Gallo

Marcelo Nery Dos Santos

Cleidson Ronald Botelho De Souza

Tohru Hasegawa

Tsuyoshi Miyamura

Hiroshi Itagaki

Noriko Yamamoto

Shinsuke Mitsuma

Ana Paula Appel

Bruno Silva

Andrea Britto Mattos Lima

Paulo Rodrigo Cavalin

Eduardo Rocha Rodrigues

Bianca Zadrozny

Rafael Rossi De Mello Brandao

Sergio Borger

Alan Braz

Emilio Ashton Vital Brazil

Nicole Barbosa Sultanum

Daniel Salles Chevitarese

Daniel Salles Civitarese

Vitor Henrique Leal Mesquita

Juliana De Melo Batista Dos Santos

Matheus Palhares Viana

Breno William Santos Rezende De Carvalho

Henrique Von Atzingen Do Amaral

Helon Vicente Hultmann Ayala

Rafael Horschutz Nemoto

Alexandre Pfeifer

Raphael Guedes Amorim

Claudio Bandeira Dutra

Rogerio Cesar Barbosa Dos Santos Da Silva Silva

Daniela De Mattos Szwarcman

A plurality of datasets may be received. Multiple instances of a machine learning algorithm may be run to create corresponding multiple machine learning models trained for a specific task in a given domain. Each of the multiple instances may use a different subset of the plurality of datasets in training the corresponding machine learning model. The multiple machine learning models may be run with input data. The multiple machine learning models produce corresponding multiple outcomes. A candidate machine learning model may be determined based on comparing each of the multiple outcomes with ground-truth output. A value associated with the different subset of the plurality of datasets may be determined based on comparing of each of the multiple outcomes with ground-truth output. A smart contract may be created which may include the value and the different subset of the plurality of datasets. The smart contract may be recorded in a blockchain.

Data platform to protect security of data

A method of data transformation for acceleration of context migration includes monitoring user actions in a source code development environment using fragment-based source code documents are monitored. A content of each fragment of the source code document is determined. A sequence of execution of the fragments is determined. A status of a project captured by the source code development environment is determined. A fidelity of the data to be transformed to a new execution environment is determined. Upon determining that a new execution environment is warranted based on the determined fidelity, the new execution environment is determined. The one or more fragments are then executed in the new execution environment.

Data transformation for acceleration of context migration in interactive computing notebooks

A computer implemented method includes receiving a list of areas on a subject tape to be read, wherein each area of the list of areas is indicated by a first record number and a last record number corresponding to the area, identifying parameters of a tape drive configured to read the subject tape, wherein the identified parameters of the tape drive contribute to a speed with which the tape drive can read the list of areas, creating a directed graph of the areas on the subject tape based on the identified parameters, wherein the directed graph indicates how long the tape drive will take to read the areas on the subject tape, and determining a fastest reading order of the areas on the subject tape, based, at least in part, on the directed graph and the identified parameters. A computer program product and computer system are also disclosed.

Read order determination on a tape

An ore content prediction system is provided. The system receives structured geological data that is derived based on spatial geological information that is associated with an input region. The received structured geological data includes a plurality of multidimensional tensors that are derived from spatial geological information of a plurality of sub-regions of the input region. The spatial geological information includes one or more types of data. The system trains a prediction model to produce a prediction output based on an average grade of an ore of a target mineral type at a target region by using the received structured geological data. The system identifies a relationship of the structured geological data to the prediction output and determines a revised input region based on the identified relationship.

Estimate ore content based on spatial geological data through 3D convolutional neural networks

According to one embodiment, a method, computer system, and computer program product for adaptive surrogate modeling is provided. The embodiment may include capturing a plurality of system information for a smart Internet of Things (IoT) device. The embodiment may also include calculating a lifespan value of the smart IoT device based on the plurality of captured system information. The embodiment may further include, in response to the calculated lifespan value being below a threshold and a surrogate model fitting one or more parameters of the smart IoT device not existing, creating the surrogate model for the smart IoT device. The embodiment may also include deploying the created surrogate model to the smart IoT device through an update transmission.

Device lifetime-aware creation of customizable surrogate-based models

A collection of code fragments loaded in an interactive development platform for running on a first processor can be received. A candidate fragment in the collection of code fragments can be determined for migration to a second processor based on characterizing the collection of code fragments. Based on a location of the candidate fragment in the collection of code fragments, a spot can be identified in the collection of code fragments to inject a code for saving program context. The code for saving program context can be injected in the identified spot. Responsive to the code for saving program context having run on the first processor and based on a criterion, the program context can be migrated to the second processor.

Program context migration

A system for initiating web containers and isolating network traffic to web containers is described. The system initiates and uses web containers for associated web-based resources, such as domain addresses owned by a single entity. When a web container for a domain address has not been initiated, the system determines an owner of the domain address and any domain addresses associated with the owner and initiates a web container for the domain address and the associated domains. When a user navigates to the domain addresses associated with the determined owner, the system isolates the network activity to the initiated web container.

Internet activity compartmentalization

Embodiments relate to keeping databases compliant with data protection regulations by sensing the presence of sensitive data and transferring the data to compliant geographies. A request including information is received, the request being intended for processing on a local database. A model is used to process the information of the request. Responsive to the model determining that information relates to sensitive data, the request is transferred to a remote database associated with a geography meeting a requirement for the sensitive data in order to execute the request.

Keeping databases compliant with data protection regulations by sensing the presence of sensitive data and transferring the data to compliant geographies

A method, computer system, and a computer program product for dynamic role assignment is provided. The present invention may include identifying a crisis event based on data collected by one or more internet-connected sensors. The present invention may then include selecting an incident plan based on the identified crisis event. The present invention may then include communicating an incident role to a registered device of a crowd member.

Dynamic assignment of tasks to internet connected devices

A hybrid knowledge representation is searched for a machine learning component corresponding to a search query. The hybrid knowledge representation may be structured as nodes representing machine learning workflow components and edges (e.g., links) connecting the nodes based on relationships between the nodes. Responsive to finding the machine learning component in the hybrid knowledge representation, the machine learning component is returned. Responsive to not finding the machine learning component in the hybrid knowledge representation, the hybrid knowledge representation is searched for machine learning model fragments associated with building the machine learning component, generating a new machine learning component by combining the machine learning model fragments and returning the new machine learning component.

Machine learning engineering through hybrid knowledge representation

Approaches presented herein enable asset identification for collaborative projects in software development. More specifically, a plurality of assets is identified. Content provided by at least one asset of the plurality of assets is determined. A project that is associated with the content provided by the at least one asset is determined. A repository associated with the project to include the at least one asset is updated.

Asset identification for collaborative projects in software development

Techniques for automatically recreating data removed from storage are disclosed. A request to access data at a first storage location is received. It is determined, based on a catalog and using a computer processor, that the data has been removed from the first storage location. In response the data at the first storage location is automatically recreated using the computer processor. The recreating includes identifying a second storage location for the data, based on the catalog, retrieving the data from the second storage location, and storing the data at the first storage location. The catalog is updated to reflect recreating the data at the first storage location.

Continuous storage of data in a system with limited storage capacity

A technique relates to tracking a foodstuff. A device images human consumable code formed on the foodstuff, the human consumable code being part of the foodstuff, the foodstuff being unpackaged. A coding associated with the human consumable code is determined. Product information of the foodstuff is retrieved from a computer system by using the coding. The product information of the foodstuff is provided on the device.

Image-based encoding

A method for transporting data from a source location to a destination location includes receiving the data from at least one sender at the source location, the sender specifying at least one recipient at the destination location; splitting the data into a plurality of portions; and finding one or more couriers who will travel from the source location to the destination location. The method also includes: while at least a given courier is at the source location, sending at least one of the plurality of portions to a mobile device of at least the given courier; once the given courier travels to the destination location, receiving the at least one of the portions from the mobile device of the given courier; and once the plurality of portions of the data have been received at the destination location, sending the data set to the at least one recipient.

Crowdsourcing big data transfer

A method for coordinating activities includes monitoring physiologic signals and movement signals from a plurality of individuals, and learning at least one baseline for each of the plurality of individuals from the physiologic stress signals and the movement signals. The method further includes comparing the individual's physiologic signals to their baseline, determining a current activity for each individual, and learning correlations between current activities and sequences of activities and estimated divergences of the physiologic signals from baseline. The method also includes determining prospective activities for each individual, identifying at least one prospective shared activity among two or more individuals, estimating prospective divergences of the physiologic signals associated with the prospective shared activity, and mitigating the prospective divergences of the physiologic signals by controlling the scheduling component to adjust a schedule of the at least one prospective shared activity.

Coordinating activities responsive to physiologic signals

Growing community of inventors

Sao Paulo, Brazil

Lucas Correia Villa Real