Abstract: An example operation may include one or more of connecting, by a disposition node, to a blockchain comprised of a plurality of user nodes connected to a plurality of device nodes that store user data of the plurality of the user nodes, receiving, by the disposition node, a request from a user node of the plurality of the user nodes to dispose of user data (D) on at least one of the device nodes of the plurality of the device nodes, the request contains a disposal policy (P) and a disposal method (M) of the D, executing, by the disposition node, a consensus algorithm to validate the request based on the D, P and M, in response to a validation of the request, accessing, by the disposition node, the D on the at least one of the device nodes of the plurality of the device nodes, generating, by the disposition node, a location sensitive hash of the D (LSH(D)) and a crypto hash of the D (SHA256(D)), storing, by the disposition node, the LSH(D), the SHA256(D), the P and the M on the blockchain, executing, by the dis

Abstract: An example operation may include one or more of connecting, by a disposition node, to a blockchain comprised of a plurality of user nodes connected to a plurality of device nodes that store user data of the plurality of the user nodes, receiving, by the disposition node, a request from a user node of the plurality of the user nodes to dispose of user data (D) on at least one of the device nodes of the plurality of the device nodes, the request contains a disposal policy (P) and a disposal method (M) of the D, executing, by the disposition node, a consensus algorithm to validate the request based on the D, P and M, in response to a validation of the request, accessing, by the disposition node, the D on the at least one of the device nodes of the plurality of the device nodes, generating, by the disposition node, a location sensitive hash of the D (LSH(D)) and a crypto hash of the D (SHA256(D)), storing, by the disposition node, the LSH(D), the SHA256(D), the P and the M on the blockchain, executing, by the dis

Abstract: An approach is provided that receives, from a neurological sensor worn by a user, words as they are silently read the user. The words being read by the user correspond to a set of actual words that are included in a passage that is being read by the user. The approach compares the words as read by the user with the actual words included in the passage to identify one or more reading mistakes. The reading mistakes are analyzed resulting in a set of feedback that is provided to the user.

Abstract: An approach is provided that receives, from a neurological sensor worn by a user, words as they are silently read the user. The words being read by the user correspond to a set of actual words that are included in a passage that is being read by the user. The approach compares the words as read by the user with the actual words included in the passage to identify one or more reading mistakes. The reading mistakes are analyzed resulting in a set of feedback that is provided to the user.

Abstract: A method for predicting a computerized service delivery organization workload including collecting data of a computer implementing service delivery routine including overlapping samples of load values, overlapping samples of performance values, overlapping samples of event outputs, ticket values and ticket volumes, building a first correlation of said load values with said performance values for predicting new performance values based on new data, building a second correlation of said performance values with said event outputs, said ticket values and said ticket volumes, combining said first and second correlations into a third correlation for correlating said load values with a ticket volume and an event volume, and determining at least one projected event volume or projected ticket volume value using said third correlation and at least one projected load value of said computer.

Abstract: Embodiments of the present invention provide an approach to resize (e.g., shrink and/or enlarge) objects in a region of a VU so that additional objects can be accommodated. Specifically, embodiments of the present invention provide a mechanism for a region/room to calculate when it has reached full capacity, and use a configurable multiplier to decrease the size of all objects in the room, including avatars, desks, chairs, tables, etc. This allows for accommodation of a significantly higher quantity of objects within the region. In a typical embodiment, the transition to smaller size would be seamless to the user. Moreover, in one embodiment, if the room is of a certain type (e.g., auditorium), additional objects may be auto-created or deleted based on the number of avatars entering or exiting the room. Still yet, objects can be enlarged as the occupancy falls below the capacity.

Abstract: Embodiments of the present invention provide an approach to resize (e.g., shrink and/or enlarge) objects in a region of a VU so that additional objects can be accommodated. Specifically, embodiments of the present invention provide a mechanism for a region/room to calculate when it has reached full capacity, and use a configurable multiplier to decrease the size of all objects in the room, including avatars, desks, chairs, tables, etc. This allows for accommodation of a significantly higher quantity of objects within the region. In a typical embodiment, the transition to smaller size would be seamless to the user. Moreover, in one embodiment, if the room is of a certain type (e.g., auditorium), additional objects may be auto-created or deleted based on the number of avatars entering or exiting the room. Still yet, objects can be enlarged as the occupancy falls below the capacity.

Abstract: A method for predicting a computerized service delivery organization workload including collecting data of a computer implementing service delivery routine including overlapping samples of load values, overlapping samples of performance values, overlapping samples of event outputs, ticket values and ticket volumes, building a first correlation of said load values with said performance values for predicting new performance values based on new data, building a second correlation of said performance values with said event outputs, said ticket values and said ticket volumes, combining said first and second correlations into a third correlation for correlating said load values with a ticket volume and an event volume, and determining at least one projected event volume or projected ticket volume value using said third correlation and at least one projected load value of said computer.

Abstract: A method for predicting service delivery costs for a changed business requirement including detecting an infrastructure change corresponding to the changed business requirement affecting a computer server, deriving a service delivery workload change of the computer server from the infrastructure change, and determining a service delivery cost of the computer server based on the service delivery workload change.

Abstract: One embodiment of the invention, directed to a computer implemented method in a computer system comprising at least one component, includes the step of responsive to detecting a problem in the system, generating a set of crowdsourcing tasks for analyzing a first possible cause of the detected problem. The method further includes the steps of assigning the set of crowdsourcing tasks to one or more selected crowdsourcing experts, and using information derived at least in part from task results provided by one or more crowdsourcing experts to compute a problem completeness (PC) index. Responsive to determining that the first possible cause is not the root cause of the detected problem, the PC Index is used to determine whether to assign one or more additional crowdsourcing tasks to any crowdsourcing experts.

Abstract: One embodiment of the invention, directed to a computer implemented method in a computer system comprising at least one component, includes the step of responsive to detecting a problem in the system, generating a set of crowdsourcing tasks for analyzing a first possible cause of the detected problem. The method further includes the steps of assigning the set of crowdsourcing tasks to one or more selected crowdsourcing experts, and using information derived at least in part from task results provided by one or more crowdsourcing experts to compute a problem completeness (PC) index. Responsive to determining that the first possible cause is not the root cause of the detected problem, the PC Index is used to determine whether to assign one or more additional crowdsourcing tasks to any crowdsourcing experts.

Abstract: Embodiments of the present invention provide an approach to resize (e.g., shrink and/or enlarge) objects in a region of a VU so that additional objects can be accommodated. Specifically, embodiments of the present invention provide a mechanism for a region/room to calculate when it has reached full capacity, and use a configurable multiplier to decrease the size of all objects in the room, including avatars, desks, chairs, tables, etc. This allows for accommodation of a significantly higher quantity of objects within the region. In a typical embodiment, the transition to smaller size would be seamless to the user. Moreover, in one embodiment, if the room is of a certain type (e.g., auditorium), additional objects may be auto-created or deleted based on the number of avatars entering or exiting the room. Still yet, objects can be enlarged as the occupancy falls below the capacity.

Abstract: A method, data processing system, and computer program product for managing bookmarks. An application program, executed by a processor unit, identifies an external bookmark associated with a function in response to receiving a user input requesting information about the function in an application program executed by a processor unit in a computer, wherein the external bookmark points to a webpage available from another computer. The application program displays the identified bookmark.