Abstract: Selective display of available objects based on eye-gaze characteristics with respect to currently displayed objects and certain attributes of the currently displayed objects. Similarity-driven selective display compares attributes of a displayed object receiving a fixed gaze to attributes of available objects and displays similar objects in addition to the displayed object receiving the fixed gaze.

Abstract: A field-of-view of a scene is scanned by an augmented reality device. The scene includes one or more objects including a first computing device. A portion of an electronic document is detected based on the scanned field-of-view. The portion of the electronic document is rendered on a display of the first computing device. A content element of the electronic document that is rendered on the display is captured. A second computing device determines an incomplete portion of the content element. A suggestion to complete the incomplete portion is provided by the augmented reality device.

Abstract: Techniques for augmenting technical instruction sets with additional solutions from solution providers are described. A user query for technical instruction comprising a technical problem to solve is received and a current user state from data representing user knowledge and available physical resources is determined from the user. Additionally, a technical instruction set is identified and an augmented technical instruction set comprising additional technical instructions from a winner of a knowledge augmentation auction is generated and returned.

Abstract: Selective display of available objects based on eye-gaze characteristics with respect to currently displayed objects and certain attributes of the currently displayed objects. Similarity-driven selective display compares attributes of a displayed object receiving a fixed gaze to attributes of available objects and displays similar objects in addition to the displayed object receiving the fixed gaze.

Abstract: The augmented reality system described herein calculates a personalized escape plan from a location for a user. A participant is registered to an emergency direction system that employs an augmented reality system to provide instructions to the participant to exit a data center. The emergency direction system receives a floor plan. The emergency direction system may also detect a hazard, and determine a hazard growth score. The emergency direction system can also compute a dynamic escape plan using hazard growth score and the hazard location. In some embodiments, the emergency direction system can also recalculate the dynamic escape plan to account for the person to carry an asset during exiting the structure corresponding to the floor plan in response to the hazard. Instructions for the person to exit the data center in response to the hazard carrying the asset are forwarded to the participant.

Abstract: Autonomous vehicle communications are managed by assigning vehicle clusters to process collected data as a unified cluster, whether transmitting the data to a remote server or processing the data by an assigned vehicle within the cluster. Efficient travel guidance is produced in a timely manner by reducing the network bandwidth usage and volume of data transferred by autonomous vehicles traveling on a roadway with other autonomous vehicles.

Abstract: Managing hybrid cloud resources by grouping at least a portion of the elements of a data set according to attribute sensitivity into a cluster of elements, computing a resource allocation impact of the cluster of elements, computing an information gain associated with the set of elements, and allocating cloud resources according to the resource allocation impact and information gain.

Abstract: Method and apparatus for improving ease of use, customizability, and functionality of computing devices via chatbots may be realized by processing a natural language query, by a first chatbot, to identify a monitored device in a computing environment that relates to the natural language query; transmitting the query to a second chatbot provided by the monitored device; receiving a response from the second chatbot identifying an anomaly observed on the monitored device; and outputting an user interface for display, the user interface comprising a natural language summary of the response.

Abstract: A method, a system and a computer program product for automated ASCII-based object-oriented database schema (OODBS) generation. A parser runs through text sentences of a textual document from a requirements gathering team that includes object-oriented application requirements, and identifies nouns corresponding to an object, and each noun's attributes. An Object-oriented dictionary based ASCII interpreter analyzes the ASCII of the captured requirements. For each identified noun, the system creates first key-value structures mapping each identified object to one or more associated attributes. There is further identified, from the created first key-value structures, any attributes that reference to an identified object, and for each of these identified objects, the system creates second key-value structures mapping, for each attribute identified as a reference, associating a corresponding key where the reference is found as an attribute.

Abstract: Systems, methods, and computer program products that automate the removal of user data, device data and learning data stored by intelligent devices operating as part of an internet-of-things network or managed by IoT platforms. The solutions reverse engineer locally stored data and communication logs maintained in the intelligent device to identify one or more intelligent devices or platforms previously placed in communication with the intelligent device being flushed. The systems, methods and computer program products automatically connect to devices and platforms previously placed in communication with the intelligent device and flush the data associated with the intelligent device or disassociate the device from a user's profile. Verification programs or simulations are run to confirm the removal of the user data, device data and learning data. Confirmation of the removal is provided to the user indicating that the intelligent device can be safely transferred to a new user or third party.

Abstract: Assessing data center impact post disaster is provided. A data center is divided into hazard segments post disaster based on a combination of hazard type, hazard level, and hazard location identified in time series information from sensors and cameras. A financial value of each identifiable asset in the data center is calculated based on determined operational viability status, estimated soft value, and determined criticality of each identifiable asset. A time cost and an operational cost of impact assessment devices used to assess an impact on the data center and recover assets is calculated. A disaster assessed map is generated by overlaying the time series information, calculated financial values, and calculated time and operational costs on a digital floorplan of the data center. One or more types of impact assessment devices are assigned to each hazard segment at different time periods to rescue and recover financially valuable and operationally viable assets.

Abstract: Methods, systems, and computer program products for generating capacity planning schedules while protecting the privacy of stakeholder preferences of a set of metrics are provided herein. A computer-implemented method includes identifying stakeholders associated with capacity planning for a project; determining metrics to be used in the capacity planning; obtaining, from each of the stakeholders, an initial preferred order of emphasis of the metrics; calculating similarity scores between the initial preferred orders of emphasis; outputting, to each of the stakeholders, the similarity scores, wherein the identity of the stakeholders has been masked; obtaining, from each of the stakeholders, at least a second iteration of a preferred order of emphasis of the metrics; generating a final order of emphasis of the multiple metrics upon a determination that the stakeholders provided at least a predetermined number of identical preferred orders of emphasis; and outputting the final order of emphasis of the metrics.

Abstract: On-demand auctioning of cloud services amongst cloud computing service providers includes publishing, by a client, on a publish-subscribe platform, cloud computing resource requirement(s); subscribing to the publish-subscribe platform by at least two providers of cloud computing service(s); bidding, by each of the at least two providers, on one or more the at cloud computing resource requirement(s) via a bidding platform; selecting, by the client, and publishing on the publish-subscribe platform, at least one of the at least two providers for the cloud computing resource requirement(s); and, in one example, prior to the selecting, cognitively recommending to the client, by a data processing system, one or more of the at least two providers.

Abstract: One example of a computer-implemented method comprises receiving recorded data of activity of a first user wearing an augmented reality (AR) device; analyzing the recorded data to identify a current task being performed by the first user; and comparing the identified current task to a plurality of prior tasks performed by the first user. Each prior task is stored in a database with corresponding user data collected during performance of the prior task by the first user. The method further comprises, in response to identifying a prior task corresponding to the identified current task based on the comparison, generating personalized content related to the identified current task based on the user data collected during performance of the corresponding identified prior task by the first user; and outputting, for display on the AR device, the generated personalized content.

Abstract: Systems, methods, and computer program products that automate the removal of user data, device data and learning data stored by intelligent devices operating as part of an internet-of-things network or managed by IoT platforms. The solutions reverse engineer locally stored data and communication logs maintained in the intelligent device to identify one or more intelligent devices or platforms previously placed in communication with the intelligent device being flushed. The systems, methods and computer program products automatically connect to devices and platforms previously placed in communication with the intelligent device and flush the data associated with the intelligent device or disassociate the device from a user's profile. Verification programs or simulations are run to confirm the removal of the user data, device data and learning data. Confirmation of the removal is provided to the user indicating that the intelligent device can be safely transferred to a new user or third party.

Abstract: A cognitive display interface operatively couples to a display device and provides augmentation data for display to a user within a restricted access space based on user input. The interface receives user input and context-related data, with the user providing the user input within the space, and one or more sensors providing the context-related data. The interface analyzes the context-related sensor data to determine a location and an orientation of the user within the space at the time of providing the user input, resolves context of the user input based, at least in part, on the determined location and orientation of the user within the space, and determines a search query from the input and the resolved context. A response to the search query is generated based, at least in part, on searching a database(s), and the interface provides a response as augmentation data for rendering on the display device.

Abstract: A method and system for tracking an IT infrastructure is provided. The method includes modeling an IT infrastructure as a collection of hardware components, software components, and networking components. An observer agent is deployed on each of the components. The observer agent performs a measurement process with respect to each of the components and a mapping process is performed with respect to the measurement process. An aggregation module is deployed and an aggregation process is performed with respect to results of the mapping process. In response, a two dimensional moving graph indicating results of the aggregation process is generated and displayed.

Abstract: A cognitive display interface operatively couples to a display device and provides augmentation data for display to a user within a restricted access space based on user input. The interface receives user input and context-related data, with the user providing the user input within the space, and one or more sensors providing the context-related data. The interface analyzes the context-related sensor data to determine a location and an orientation of the user within the space at the time of providing the user input, resolves context of the user input based, at least in part, on the determined location and orientation of the user within the space, and determines a search query from the input and the resolved context. A response to the search query is generated based, at least in part, on searching a database(s), and the interface provides a response as augmentation data for rendering on the display device.

Abstract: On-demand auctioning of cloud services amongst cloud computing service providers includes publishing, by a client, on a publish-subscribe platform, cloud computing resource requirement(s); subscribing to the publish-subscribe platform by at least two providers of cloud computing service(s); bidding, by each of the at least two providers, on one or more the at cloud computing resource requirement(s) via a bidding platform; selecting, by the client, and publishing on the publish-subscribe platform, at least one of the at least two providers for the cloud computing resource requirement(s); and, in one example, prior to the selecting, cognitively recommending to the client, by a data processing system, one or more of the at least two providers.

Abstract: Techniques for augmenting technical instruction sets with additional solutions from solution providers are described. A user query for technical instruction comprising a technical problem to solve is received and a current user state from data representing user knowledge and available physical resources is determined from the user. Additionally, a technical instruction set is identified and an augmented technical instruction set comprising additional technical instructions from a winner of a knowledge augmentation auction is generated and returned.