Abstract: A processor(s) receives a profile of a user and ranks physical activities in a relational data structure based on the user profile to create a customized relational data structure of ranked physical activities for the user. The relational data structure maps physical activities to one or more associated attributes. An activity adviser model is produced specific to the user via machine learning by obtaining data related to physical activities performed by the user from one or more sensors, and receiving user wellness-related feedback related to the user-performed physical activities. The user wellness-related feedback includes a user ranking of one or more aspects of the user-performed physical activities. The activity adviser model specific to the user is built by using the customized relational data structure, the data and the user wellness-related feedback. The processor(s) uses the activity adviser model to provide an activity-related recommendation to the user.

Abstract: A method, system and computer program product related to delivery of packages to online shopping customers. In an embodiment, the invention provides a method comprising identifying a pool of candidate delivery drivers; analyzing driving patterns of the candidate drivers in a geographic area; analyzing activities of specified online shoppers in the geographic area; and sending a message to contact one of the candidate drivers to deliver a package or packages to an online shopper based on a defined matching of the analyzed driving patterns of the candidate drivers with the analyzed activities of the online shoppers. In an embodiment, each of the candidate drivers has an associated mobile communications device; and the analyzing driving patterns of the candidate drivers includes using specified changes in locations of the mobile communication devices associated with the candidate delivery drivers to identify the driving patterns of the candidate drivers.

Abstract: An IoT apparatus in use by a user, which is communicatively linked to a mobile device used by the user, is identified. A determination can be made as to whether documentation for the IoT apparatus is located on the IoT apparatus or on a mobile device. Responsive to determining that the documentation is located on the IoT apparatus or on the mobile device, a determination can be made as to whether the documentation located on the IoT apparatus or on the mobile device is a latest version of the documentation. Responsive to determining that the documentation located on the IoT apparatus or on the mobile device is not the latest version of the documentation, the latest version of the documentation can be automatically accessed from a resource external to the IoT apparatus and the mobile device. Presentation of the latest version of the documentation on a display can be initiated.

Abstract: Solved diagnosis case data is stored by utilizing a redundant discrimination net as a dynamic memory. The stored diagnosis case data is incorporated to form scientific descriptions within a medical knowledge base and heuristics within an empirical knowledge base. Diagnosis hypotheses are generated using an initial symptom description, the dynamic memory, and the medical knowledge base. The initial symptom description is received from an end user. A subset of the diagnosis hypotheses is created to form one or more solution cases. The one or more solution cases are presented to a subject matter expert. A diagnosis success or a diagnosis failure identifying, based on a response received from the subject matter expert, to form an assessed solution case. An assessed solution case is converted into experiences. The experiences are inputted into the dynamic memory. Data containing the assessed solution case is transmitted to a medical artificial intelligence analytics application.

Abstract: A cognitive engine is coupled to at least one requirements management tool and at least one quality management tool. The cognitive engine is configured to: transform the test cases and the initial software requirements into test case objects and requirement objects, respectively; link test case objects to corresponding requirements objects based on like attributes; provide a graphical representation showing test case objects linked to corresponding requirements objects; automatically update the graphical representation in response to updated software requirements or new software requirements; and automatically disseminate the graphical representation or the updated graphical representation if the test case effectiveness exceeds a predetermined confidence threshold.

Abstract: A selection of a three-dimensional model by a user is received, and an interlocking block framework corresponding to the selected three-dimensional model is determined. The interlocking block framework includes one or more physical construction blocks configured to interlock with one another. A three-dimensional gap model is generated based upon the selected three-dimensional model and the interlocking block framework. The three-dimensional gap model is generated by removing a representation of the determined interlocking block framework from the selected three-dimensional model.

Abstract: A selection of a three-dimensional model by a user is received, and an interlocking block framework corresponding to the selected three-dimensional model is determined. The interlocking block framework includes one or more physical construction blocks configured to interlock with one another. A three-dimensional gap model is generated based upon the selected three-dimensional model and the interlocking block framework. The three-dimensional gap model is generated by removing a representation of the determined interlocking block framework from the selected three-dimensional model.

Abstract: A processor(s) receives a profile of a user and ranks physical activities in a relational data structure based on the user profile to create a customized relational data structure of ranked physical activities for the user. The relational data structure maps physical activities to one or more associated attributes. An activity adviser model is produced specific to the user via machine learning by obtaining data related to physical activities performed by the user from one or more sensors, and receiving user wellness-related feedback related to the user-performed physical activities. The user wellness-related feedback includes a user ranking of one or more aspects of the user-performed physical activities. The activity adviser model specific to the user is built by using the customized relational data structure, the data and the user wellness-related feedback. The processor(s) uses the activity adviser model to provide an activity-related recommendation to the user.

Abstract: A method, system and computer program product related to delivery of packages to online shopping customers. In an embodiment, the invention provides a method comprising identifying a pool of candidate delivery drivers; analyzing driving patterns of the candidate drivers in a geographic area; analyzing activities of specified online shoppers in the geographic area; and sending a message to contact one of the candidate drivers to deliver a package or packages to an online shopper based on a defined matching of the analyzed driving patterns of the candidate drivers with the analyzed activities of the online shoppers. In an embodiment, each of the candidate drivers has an associated mobile communications device; and the analyzing driving patterns of the candidate drivers includes using specified changes in locations of the mobile communication devices associated with the candidate delivery drivers to identify the driving patterns of the candidate drivers.

Abstract: A system and method that includes identifying a change in condition of a working environment. Educational content relevant to an educational category of the change in condition is retrieved. A skill gap of a team member associated with the working environment is calculated by comparing an existing educational training received by the team member relevant to the educational category with the educational content retrieved in response to identifying the change in condition. A custom education plan is built to resolve the skill gap of the team member.

Abstract: An IoT apparatus in use by a user, which is communicatively linked to a mobile device used by the user, is identified. A determination can be made as to whether documentation for the IoT apparatus is located on the IoT apparatus or on a mobile device. Responsive to determining that the documentation is located on the IoT apparatus or on the mobile device, a determination can be made as to whether the documentation located on the IoT apparatus or on the mobile device is a latest version of the documentation. Responsive to determining that the documentation located on the IoT apparatus or on the mobile device is not the latest version of the documentation, the latest version of the documentation can be automatically accessed from a resource external to the IoT apparatus and the mobile device. Presentation of the latest version of the documentation on a display can be initiated.

Abstract: Managing misuse of machinery by an operator is disclosed. A system learns a set of safety conditions which are associated with tasks completed by an operator using machinery. Inappropriate usage of the machinery can be identified and the machinery can be remotely shut down and reports of the inappropriate usage of the machinery can be sent to a responsible party.

Abstract: A method for identifying and initiating actions of a meeting. The method includes a computer processor monitoring a meeting where monitoring the meeting includes receiving input from at least a first computing device. The method further includes identifying a plurality of metadata triggers associated with the received input of meeting. The method further includes identifying an occurrence of a first metadata trigger of the plurality of metadata triggers associated with the received input of the meeting. The method further includes analyzing a first portion of the received input of the meeting that includes an occurrence of the first metadata trigger and identifying a first action associated with the first metadata trigger. The method further includes determining a response criterion of the first metadata trigger. The method further includes responding to a determination that the first metadata trigger includes a response criterion indicating immediate action by initiating the first action.

Abstract: A method for identifying and initiating actions of a meeting. The method includes a computer processor monitoring a meeting where monitoring the meeting includes receiving input from at least a first computing device. The method further includes identifying a plurality of metadata triggers associated with the received input of meeting. The method further includes identifying an occurrence of a first metadata trigger of the plurality of metadata triggers associated with the received input of the meeting. The method further includes analyzing a first portion of the received input of the meeting that includes an occurrence of the first metadata trigger and identifying a first action associated with the first metadata trigger. The method further includes determining a response criterion of the first metadata trigger. The method further includes responding to a determination that the first metadata trigger includes a response criterion indicating immediate action by initiating the first action.

Abstract: A computer-implemented method includes identifying a first traveler profile and additional traveler profiles. Each traveler profile is associated with a mobile device. The method further includes, for the first traveler profile, determining a first travel pattern, based on geographically tracking the first traveler mobile device, and determining an additional travel patterns, based on geographically tracking the additional travelers' mobile devices. The method further includes determining a compatible route between the first traveler profile and a compatible traveler profile, based on optimizing the first travel pattern with the additional travel patterns, wherein the first traveler profile includes an optimal driver for the at least one compatible route. The computer-implemented method further includes presenting to the first traveler profile, via its mobile device, a suggestion that the first traveler profile become a driver profile for at least one travel application.

Abstract: A computer-implemented method includes detecting, using a processor, an arrangement of a plurality of blocks that are interconnected, where each block of the plurality of blocks is a physical block representing a corresponding atomic service. It is determined, using the processor, whether each atomic service represented by a block in the plurality of blocks is configured to communicate with each other atomic service represented by an other block with which the block is interconnected in the plurality of blocks. Based at least in part on determining that each atomic service represented by a block in the plurality of blocks is configured to communicate with each other atomic service represented by an other block with which the block is interconnected in the plurality of blocks, a microservice represented by the arrangement of the plurality of blocks is defined. The microservice is deployed.

Abstract: Various embodiments for managing data transmission errors in a computing storage environment, by a processor device, are provided. In one embodiment, data traffic is routed through a data path in the computing storage environment, and in response to detecting errors in routing the data traffic through the data path, the routing of the data traffic is switched to an alternate data path. In response to reaching a predetermined error threshold while routing the data traffic through the alternate data path the computing storage environment, at least certain data traffic is wirelessly transmitted from a source to a switch nearest a destination of the certain data traffic.

Abstract: Solved diagnosis case data is stored by utilizing a redundant discrimination net as a dynamic memory. The stored diagnosis case data is incorporated to form scientific descriptions within a medical knowledge base and heuristics within an empirical knowledge base. Diagnosis hypotheses are generated using an initial symptom description, the dynamic memory, and the medical knowledge base. The initial symptom description is received from an end user. A subset of the diagnosis hypotheses is created to form one or more solution cases. The one or more solution cases are presented to a subject matter expert. A diagnosis success or a diagnosis failure identifying, based on a response received from the subject matter expert, to form an assessed solution case. An assessed solution case is converted into experiences. The experiences are inputted into the dynamic memory. Data containing the assessed solution case is transmitted to a medical artificial intelligence analytics application.

Abstract: An IoT apparatus in use by a user, which is communicatively linked to a mobile device used by the user, is identified. A determination can be made as to whether documentation for the IoT apparatus is located on the IoT apparatus or on a mobile device. Responsive to determining that the documentation is located on the IoT apparatus or on the mobile device, a determination can be made as to whether the documentation located on the IoT apparatus or on the mobile device is a latest version of the documentation. Responsive to determining that the documentation located on the IoT apparatus or on the mobile device is not the latest version of the documentation, the latest version of the documentation can be automatically accessed from a resource external to the IoT apparatus and the mobile device. Presentation of the latest version of the documentation on a display can be initiated.

Abstract: A method, system and computer program product for defining an evolving set of test cases for testing software applications. In an embodiment, the method comprises identifying a set of criteria for the test cases; assigning a weight to each of the criteria; and for each of a multitude of test cases, assigning a value to each of the criteria, and determining a criteria score for the test case based on the values assigned to the criteria for the test case and the weights assigned to the criteria. Each of the test cases is assigned to one of a plurality of groups based on the criteria scores. Each of the groups of test cases is associated with one of a plurality of testing procedures, and one of those procedures is selected to test a software application using the group of test cases associated with that selected testing procedure.