Abstract: An embodiment includes analyzing a first digital image using a first trained neural network that classifies the first image as having a first context based on a plurality of characteristics of the first image. The embodiment generates a data structure that associates first and second elements depicted in the first image based on an affinity detected between the first and second elements in the first context. The embodiment executes a querying process that searches for information requested by a user, and detects that a search result from the querying process conveys a second context that is different from the first context. The embodiment identifies a third element in the data structure having an affinity with the first element in the second context. The embodiment renders a machine-generated image that is generated using a second trained neural network and depicts the first element and the third element in the second context.

Abstract: A processor may receive data regarding a context for a first dialog turn. The processor may monitor a voice input from a user for the first dialog turn. The processor may detect a first pause in the voice input, the first pause having a duration that satisfies a time threshold. The processor may receive, based on the first pause, first voice input data. The processor may analyze the first voice input data. The processor may determine that additional time is recommended for the voice input to be provided by the user.

Abstract: A method, system, and computer program product for contextual generation of an ephemeral network are provided. The method detects an initiating event for network generation associated with a user of a first computing device. The method determines a duration of the initiating event. A set of network members is determined based on the initiating event and the duration. The method establishes an ephemeral network, connecting at least a portion of computing devices associated with the set of network members. The ephemeral network is terminated in response to detecting a completion event. In response to terminating the ephemeral network, member information for the set of network members is removed from the portion of the computing devices.

Abstract: An embodiment includes receiving, at database connectivity (DBC) layer, a request to access data of a data source, wherein the data source is registered with a data catalog that includes data governance artifacts, and wherein the request is made via a connection that bypasses the data catalog. The embodiment also includes comparing, by a governance manager at the DBC layer, an access privilege level for a credential associated with the request to access requirements of requested data included in data protection rules of the governance artifacts. The embodiment also includes masking, by the governance manager, a portion of the data provided in response to the request, wherein the portion of the data has an access requirement that is not met by the access privilege level for the credential associated with the request.

Abstract: In an approach to verifying and flagging negative feedback, one or more computer processors monitor one or more websites for product feedback associated with a failed component of a product. One or more computer processors determine the product feedback is detected. One or more computer processors determine the product feedback is negative. One or more computer processors determine whether the failed component is present in a corresponding blockchain ledger. In response to determining the failed component is not present in a corresponding blockchain ledger, one or more computer processors refute the product feedback.

Abstract: A computer-implemented method, system and computer program product for embedding contextual information in an image or video frames. A generative adversarial network (GAN) is trained to provide contextual information to be embedded in an image or video frames, where the contextual information includes text, sound and/or video frames that provides context to the image or video frames. After training the GAN, an image or video frames are received to be embedded with contextual information if necessary. Features are then extracted from the received image/video frames. An image(s) or video frame(s) are identified in a database using the GAN associated with features with a similarity to the extracted features of the received image/video frames that exceeds a threshold value. Such identified images and/or video frames are associated with “references” containing contextual information which are extracted. The received image/video frames are then augmented with the extracted references to provide context.

Abstract: A system and method for managing secure shared office space is provided. In embodiments, a method includes: receiving, by a computing device, a workspace request from a user, the workspace request including scheduling requirements for an activity; determining, by the computing device, security requirements associated with the workspace request utilizing a trained convoluted neural network (CNN) based on participant data including information regarding security requirements of the user and shared workspace information for a pool of shared workspaces; determining, by the computing device, that one or more of the shared workspaces in the pool of shared workspaces meets the security requirements associated with the workspace request; determining, by the computing device, that the one or more of the shared workspaces meets the scheduling requirements of the request; and automatically generating and sending, by the computing device, a notification to the user including the one or more of the shared workspaces.

Abstract: By analyzing a natural language content concurrently with a presentation of the natural language content, a first language of the natural language content is detected. By analyzing the natural language content concurrently with the presentation of the natural language content, it is detected that a subset of the natural language content is expressed in a second language, wherein the second language is different from the first language, wherein a set of known languages comprises the first language, wherein the set of known languages excludes the second language. From the subset of the natural language content, a modified subset expressed in the first language is generated. The modified subset is inserted into the natural language content.

Abstract: According to one embodiment, a method, computer system, and computer program product for three-dimensional printing is provided. The embodiment may include analyzing data of a user. The data is collected while the user is performing an activity. The embodiment may include deriving a user behavior model (UBM) of the user based on the analysis of the data. The embodiment may include calculating a relative comfort coefficient (RCC) of the user for the activity based on attributes of the UBM. The embodiment may include predicting adjustments to the attributes of the UBM which result in the RCC exceeding a threshold value. The predicted adjustments are derived using a convolutional neural network classifier. The embodiment may include defining one or more parameters of a tangible component of an object utilized by the user when performing the activity based on the predicted adjustments.

Abstract: From a set of natural language text documents, a concept tree is constructed. For a node in the concept tree a polarity of the subset represented by the node is scored. A second set of natural language text documents is added to the subset, the adding resulting in a modified subset of natural language text documents having a polarity score within a predefined neutral polarity score range. From the modified subset, a bin of sentences is selected according to a sentence selection parameter, a sentence in the bin of sentences being extracted from a selected document in the modified subset. A sentence having a factuality score below a threshold factuality score is removed from the bin of sentences. From the filtered bin of sentences a new natural language text document corresponding to the filtered bin of sentences is generated using a transformer deep learning narration generation model.

Abstract: A method, computer system, and a computer program product for problem solving using selected datasets from an internet-of-things system are provided. A trigger device in an internet-of-things system may be designated. The internet-of-things system may include the trigger device and internet-of-things devices. A trigger message may be received from the trigger device. A problem may be determined based on the trigger message. Data transmissions may be requested from the internet-of-things devices. Data may be received via the data transmission. The data transmission may be ended. A problem contributor may be identified by inputting the received data and the determined problem into a machine learning model. A problem response for responding to the problem may be generated. The generating may include inputting the problem contributor to the machine learning model. The problem response may be performed.

Abstract: An approach for adjusting driving parameters of an AV (autonomous vehicle) based on the driving style of the passenger is disclosed. The approach utilizes existing driving patterns of the passenger and perform a dynamic comparison and correlation with safe driving patterns of the passengers themselves. Based on that evaluation, the approach would suggest the parameters for adjusting the AV driving style in order to ensure AV riding experience meets the expected level of safe and stress-less riding. Furthermore, the approach can dynamically adjust the driving style during the trip based on the reaction and feedback from the passenger.

Abstract: Access authentication in an artificial intelligence system includes perceiving electronically with a first user's artificial intelligence voice response system (AIVRS) a physical presence of a second user. A voice request is generated by the first user's AIVRS and conveyed to a second user requesting access to a knowledge corpus stored by an AIVRS of the second user. Based on a voice response of the second user, the first user's AIVRS instantiates an electronic communications session with the second user's AIVRS. The session is initiated via an electronic communications connection with a portable device of the second user. Selected portions of the knowledge corpus are retrieved by the first user's AIVRS from the second user's AIVRS, the portions selected based on the voice response. An action by one or more IoT devices is initiated in response to a voice prompt interpreted by the first user's AIVRS based on the selected portions.

Abstract: From a set of natural language text documents, a concept tree is constructed. For a node in the concept tree a polarity of the subset represented by the node is scored. A second set of natural language text documents is added to the subset, the adding resulting in a modified subset of natural language text documents having a polarity score within a predefined neutral polarity score range. From the modified subset, a bin of sentences is selected according to a sentence selection parameter, a sentence in the bin of sentences being extracted from a selected document in the modified subset. A sentence having a factuality score below a threshold factuality score is removed from the bin of sentences. From the filtered bin of sentences a new natural language text document corresponding to the filtered bin of sentences is generated using a transformer deep learning narration generation model.

Abstract: Debris signature-based robotic cleaning device navigation includes operating the robotic cleaning device in a first mode as part of a vacuum cycle, the device including suction ports configurable for different suction power levels and each port having a suction path along which debris entering through the suction port is collected by the device. In the first operating mode the suction ports are operated at a first suction power level. The navigation also includes changing operation of the device to a second mode and in which the suction ports are operated at a greater suction power, measuring a respective amount of debris collected through each suction port, and selecting a direction in which to navigate the robotic cleaning device based on the debris measurements.

Abstract: Using machine logic (for example artificial intelligence (AI) software) to assemble emergency equipment during an emergency, with the help of UAVs for transport. Also, using machine logic to design purpose built emergency equipment during an emergency.

Abstract: Systems and techniques that facilitate quantum circuit valuation are provided. In various embodiments, a system can comprise an input component that can access a first quantum circuit. In various embodiments, the system can further comprise a valuation component that can appraise the first quantum circuit based on one or more factors (e.g., frequency factor, complexity factor, resource factor, similarity factor), thereby yielding a value score that characterizes the first quantum circuit. In various instances, the system can further comprise an execution component that can recommend deployment of the first quantum circuit based on determining that the value score exceeds a threshold.

Abstract: A method, computer program product and computer system to determine suspicious activity by users via in-game transactions is provided. A processor identifies a transaction involving a player character operated by a user within a game. A processor retrieves player data associated with the player character and item data associated with the items offered during the transaction involving the player character. A processor determines an optimal choice for the player character based on a comparison between the player data and the item data during the transaction. A processor, in response to the user selecting a suboptimal choice different from the optimal choice, adjusts at least one behavioral score of a profile associated with the user. A processor, in response to the at least one behavioral score being outside an expected range of the at least one behavioral score, restricts at least one aspect of an account associated with the player character.

Abstract: Electric vehicle charging reservation timeslot reallocation includes determining, in connection with an electric vehicle (EV) traveling to a destination, arrival parameters of the EV to arrive at the destination and a charging requirement of the EV to reach the destination within the arrival parameters, identifying reserved charging reservation timeslot(s) at EV charging station(s) along a route to the destination that satisfy the arrival parameters and charging requirement of the EV, determining, using an AI model configured to determine reallocations of charging reservations at electric vehicle charging stations, a proposed reallocation of a reserved charging reservation timeslot of the reserved charging reservation timeslot(s), the reserved charging reservation timeslot owned by an entity, and the proposed reallocation comprising a proposal for the entity to give up at least a portion of the reserved charging reservation timeslot to charge the EV, and electronically offering the proposed reallocation to th

Abstract: A computer-implemented method includes: presenting, by a computing device, a virtual event user interface to an attendee of a virtual event; obtaining, by the computing device, data about actions performed by the attendee within the virtual event; creating, by the computing device, a tensile sphere kernel that is specific to the attendee using the obtained data; creating, by the computing device, a mixed tensile sphere kernel using the tensile sphere kernel that is specific to the attendee and another tensile sphere kernel of another attendee; determining, by the computing device, an event recommendation of the virtual event using the mixed tensile sphere kernel; and presenting, by the computing device, the event recommendation to the attendee by changing the virtual event user interface to show the event recommendation.