Abstract: Mechanisms are provided for customizing an avatar in a virtual environment. A user that is interacting with the virtual environment, and to whom the avatar is to be rendered in the virtual environment, is identified and classified with regard to a plurality of affinity groups specifying levels of affinity between the first user and an operator of the avatar. A user security and privacy policy (USPP) data structure, associated with the operator, is retrieved that specifying security and privacy policies for each affinity group in the plurality of affinity groups. Based on the user classification and the security and privacy policy, an anonymization operation is applied to static and/or dynamic characteristics data for the operator which are used to render the avatar, to thereby generate anonymized characteristic data. The anonymized characteristic data is output for rendering the avatar in the virtual environment.

Abstract: A method, computer system, and a computer program product for supply chain optimization is provided. The present invention may include receiving augmented reality data from a plurality of users. The present invention may include categorizing the augmented reality data into one or more cohort groups according to attributes of the plurality of users. The present invention may include utilizing the one or more cohort groups to define a plurality of new products. The present invention may include presenting one or more of the plurality of new products to a user based on at least one of the one or more cohort groups to which the user belongs.

Abstract: Computer-implemented methods for providing personalized, interactive, and dynamic manuals for technical assistance are provided. Aspects include obtaining data representative of one or more actions of a user and instruction data, where the data and the instruction data are associated with performing a task. Aspects also include generating a latent space representation based on the data and the instruction data, the latent space representation including a first set of vectors corresponding to the one or more actions and a second set of vectors corresponding to the instruction data. Aspects also include managing the instruction data based on a result of comparing the first set of vectors and the second set of vectors.

Abstract: A method, system, and computer program product are configured to: receive a list of attributes of a virtual world rendering of an object, the list of attributes having been created by a first user; receive a digital rendering of a physical object provided to a second user based on the virtual world rendering of the object; determine attributes of the physical object from the digital rendering; make a determination that the physical object matches or does not match the virtual world rendering of the object based on comparing the list of attributes to the determined attributes of the physical object; and notify the first user and the second user of the determination that the physical object matches or does not match the virtual world rendering of the object.

Abstract: Personalization with on-device privacy preservation is provided by receiving, at a user device, a generalized recommendation from a remote provider backend, which include a plurality of candidate items responsive to a request from an application running on the user device; generating a plurality of candidate vectors corresponding to the plurality of candidate items representing a corresponding candidate item in a binary format across a plurality of metrics associated with the plurality of candidate items; generating a user vector based on personal data stored on the user device, the user vector representing a user in a binary format across one or more metrics associated with the personal data; determining interaction propensities based on the user vector and the plurality of candidate vectors according to a global model run on the user device; and displaying, on the user device, the plurality of candidate items according to the interaction propensities.

Abstract: Embodiments are disclosed for a method for a wearable secure data device. The method includes setting an operational mode for the wearable secure data device that stores a plurality of secure data items. The method also includes receiving a request for at least one of the secure data items from a client device that is communicating with a third-party device. Additionally, the method includes determining if the operational mode is associated with allowing access to the secure data items. Further, the method includes providing a response based on the determination.

Abstract: A set of network traffic among a plurality of legacy applications is monitored. From the set of network traffic, a communication graph is generated for the plurality. From the communication graph, a set of migratable applications within the plurality is identified. The set of migratable applications is migrated to a cloud edge layer, and a user is notified of the migration.

Abstract: A set of network traffic among a plurality of legacy applications is monitored. From the set of network traffic, a communication graph is generated for the plurality. From the communication graph, a set of migratable applications within the plurality is identified. The set of migratable applications is migrated to a cloud edge layer, and a user is notified of the migration.

Abstract: A notification message is received by a communication device The notification message includes a message identifier and a digital signature generated by an original sender of the notification message. That an integrity of message content in the notification message and an original sender of the notification message is verified is determined using the digital signature. Responsive to determining that the notification message is verified, the notification message is forwarded by the communication device using a peer-to-peer communication channel over a mesh network.

Abstract: A trained base model is distributed to a set of nodes. From a first node in the set of nodes, a first set of meta-metrics resulting from a transfer learning operation on the trained base model at the first node is collected. The transfer learning at the first node uses first local data available at the first node. The first node is clustered in a cluster with a second node from the set of nodes, in response to a meta-metric in the first set of meta-metrics being within a tolerance value of a corresponding meta-metric in a second set of meta-metrics collected from the second node. A normalized set of model parameters is constructed after an iteration of transfer learning or local learning at the first and second nodes. The normalized set of model parameters is distributed to the first node and the second node in the cluster.

Abstract: According to an embodiment, a method for registering a component is provided. The method includes receiving a request for registration of the component. The method also includes acquiring registration information of the component in response to the request by communicating directly with the component and exacting the registration information and modifying a registration entry associated with the component in a registration database according to the registration information.

Abstract: Embodiments are disclosed for a method for a wearable secure data device. The method includes setting an operational mode for the wearable secure data device that stores a plurality of secure data items. The method also includes receiving a request for at least one of the secure data items from a client device that is communicating with a third-party device. Additionally, the method includes determining if the operational mode is associated with allowing access to the secure data items. Further, the method includes providing a response based on the determination.

Abstract: Personalization with on-device privacy preservation is provided by receiving, at a user device, a generalized recommendation from a remote provider backend, which include a plurality of candidate items responsive to a request from an application running on the user device; generating a plurality of candidate vectors corresponding to the plurality of candidate items representing a corresponding candidate item in a binary format across a plurality of metrics associated with the plurality of candidate items; generating a user vector based on personal data stored on the user device, the user vector representing a user in a binary format across one or more metrics associated with the personal data; determining interaction propensities based on the user vector and the plurality of candidate vectors according to a global model run on the user device; and displaying, on the user device, the plurality of candidate items according to the interaction propensities.

Abstract: A portable computing system includes a portable computing device consisting essentially of a logical processor, a memory in communication with the logical processor with operating system software, a high speed, secure wireless communication module in communication with the logical processor, an integrated power source suitable to provide all power needs of the portable computing device and an integrated electric power generation mechanism in communication with the integrated power source to recharge the integrated power source. In addition a visual display is provided that has a power supply separate from the integrated power source of the portable computing device and a complementary wireless communication module, the portable visual display in communication with the high speed, secure wireless communication module through the complementary wireless communication module. The portable computing device and the visual display do not share a physical connection.

Abstract: A trained base model is distributed to a set of nodes. From a first node in the set of nodes, a first set of meta-metrics resulting from a transfer learning operation on the trained base model at the first node is collected. The transfer learning at the first node uses first local data available at the first node. The first node is clustered in a cluster with a second node from the set of nodes, in response to a meta-metric in the first set of meta-metrics being within a tolerance value of a corresponding meta-metric in a second set of meta-metrics collected from the second node. A normalized set of model parameters is constructed after an iteration of transfer learning or local learning at the first and second nodes. The normalized set of model parameters is distributed to the first node and the second node in the cluster.

Abstract: Technical solutions are described for selecting components from multiple vendors for a system. An example computer-implemented method includes receiving, by a processor, an environment map that identifies a first component placeholder of the system. The computer-implemented method further includes identifying, by the processor, that the first component placeholder interfaces with a second component placeholder of the system. The computer-implemented method further includes determining, by the processor, a role assigned to the first component placeholder, where the role indicates a type of data that a first component at the first component placeholder communicates with a second component at the second component placeholder. The computer-implemented method further includes determining, by the processor, a list of components for selecting the first component, where each component from the list of components matches the role assigned to the first component placeholder.

Abstract: A notification message is received by a communication device The notification message includes a message identifier and a digital signature generated by an original sender of the notification message. That an integrity of message content in the notification message and an original sender of the notification message is verified is determined using the digital signature. Responsive to determining that the notification message is verified, the notification message is forwarded by the communication device using a peer-to-peer communication channel over a mesh network.

Abstract: An application configured to provide a service using a particular type of sensor data can be executed by a first mobile device. The application attempting to access the particular type of sensor data from the first mobile device can be detected. Responsive to detecting the application attempting to access the particular type of sensor data from the first mobile device, the first mobile device can receive first sensor data from at least a second mobile device via at least a first low energy communication link, wherein the first sensor data received from the second mobile device is the particular type of sensor data the application is attempting to access, and the first mobile device can execute program code configured to provide the particular type of sensor data, and providing the first sensor data received from the second mobile device to the application.

Abstract: Techniques for reconfiguring mobile networks based on network state information are provided. In one aspect, a method for managing a mobile network is provided. The method includes the steps of: gathering network state information from an edge of the mobile network, wherein the edge of the mobile network includes a radio network and a cellular network through which user equipment communicate with an internet protocol (IP) network which is at a core of the mobile network; analyzing the network state information based on policy controls to determine actions for optimizing the mobile network; and reconfiguring the mobile network using the actions for optimizing the mobile network. A system for managing a mobile network is also provided.

Abstract: An application configured to provide a service using a particular type of sensor data can be executed by a first mobile device. The application attempting to access the particular type of sensor data from the first mobile device can be detected. Responsive to detecting the application attempting to access the particular type of sensor data from the first mobile device, the first mobile device can receive first sensor data from at least a second mobile device via at least a first low energy communication link, wherein the first sensor data received from the second mobile device is the particular type of sensor data the application is attempting to access, and the first mobile device can execute program code configured to provide the particular type of sensor data, and providing the first sensor data received from the second mobile device to the application.