International Business Machines Corporation

Alexandra Urman

Barry Michael Graham

Aaron K Baughman

Christopher J Dawson

Paul R Bastide

Fang Lu

Todd Weston Arnold

Adrian Papacica

Shenbaga Shankar

Methods and systems for cohort selection for agile processes are disclosed. A method includes: assigning, by a computing device, each of a plurality of entities to one of a plurality of groups; and for each of the plurality of groups: for each of the entities in the group, determining, by the computing device, information about the entity and encoding the determined information about the entity using a genetic algorithm; determining a ranking, by the computing device, of each of the entities in the group based on the encoded information about each of entity in the group; crossing over, by the computing device, portions of the encoded information of pairs of entities occupying adjacent positions in the ranking; and measuring, by the computing device, fitness of each of the entities in the group.

Cohort selection for agile processes

A microservices-management system intercepts a request for a cloud-based microservice sent by a microservices-architecture application. The system selects an optimal cloud-service provider from a group of candidate providers capable of delivering the microservice and then forwards the request to the optimal provider. The optimal provider is selected by drawing cognitive inferences from stored blockchain records that each describe a characteristic of a previous delivery of the requested service. Each record is generated by one of the candidate providers when delivering an instance of the microservice, regardless of whether the provider is in a trusted relationship with the application owner. The providers are barred by blockchain's intrinsic security features from altering or deleting previously stored blockchain records. Upon delivery of the service, the system compares the actual quality or cost of the delivery with predicted values in order to learn how to more effectively select optimal providers.

QoS-optimized selection of a cloud microservices provider

In providing visual cues in a document, a server captures search term(s) input by a user and detects a user selection of a document returned based on the search term(s). The server determines a dataset describing the user, where the dataset includes the search term(s), the document, and a set of demographic data of the user. The server maps the dataset to a user group, where the user group is associated with an expertise level for a domain associated with the document. The server assigns the expertise level associated with the user group to the user and maps the expertise level of a risk model for the domain. The risk model is applied to the document to identify the content segments that may pose a risk of harm to a reader with the user's expertise level. The document with the visual cues can then be displayed to the user.

Risk-based comprehension intervention for important documents

A product may be stored in a protective container that is surrounded with a fluid. A heat-sensitivity rating for the product may be obtained, and a product energy for the product may be calculated. The calculating may include adjusting the longest dimension of the product based on the heat-sensitivity rating and defining a sphere of enthalpy around the product. The sphere's radius may be equal to the adjusted product dimension and the sphere may be centered at the product center. The calculating may also comprise multiplying the volume of the sphere by the air pressure inside the protective container. An environmental condition within the sphere during a first time period may be forecasted. It may be determined that the product is likely to deteriorate during the first time period based on the product energy and heat-sensitivity rating. The altitude of the protective container may be altered to mitigate this deterioration.

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New York, NY, United States of America

Alexandra Urman