Abstract: A computer receives determines a mobile device requires a recharge, where the mobile device have a solar cell and an imaging device. The computer identifies an object with a low diffusion rate. The computer recharges the mobile device, based on determining that the mobile device receiving the solar energy from the identified object.

Abstract: A method for proximal distance and usage pattern access management includes identifying a first trigger event based on a financial device profile indicating a first proximal distance threshold is exceeded for a first device relative to a second device, where the first device is capable of executing financial transactions. The method further includes querying one or more network devices in the vicinity of the first device to validate the first trigger event. The method further includes responsive to receiving a first validation of the first trigger event from at least one network device from the one or more network devices, applying a first temporal lock on the first device preventing future executions of financial transactions. The method further includes responsive to validating a user associated with the second device, updating the financial device profile based on at least on the first trigger event and a location for the trigger event.

Abstract: Disclosed are methods, computer program products, and systems for maximizing renewals of purchase orders. One embodiment of the method may comprise utilizing a classifier machine learning model to identify metrics that are most relevant to whether customers will renew purchase orders, predicting respective risks of non-renewal for the purchase orders using the identified metrics, applying a tone analyzer natural language processing (NLP) model to determine current sentiments for respective customers, and recommending which of the respective customers to pursue with additional resources based the respectively determined sentiments and risks of non-renewal.

Abstract: Methods, computer program products, and systems are presented for warranty tracking and transactions based on usage metrics by use of blockchain. The methods include, for instance: obtaining a usage report of an IoT device in a predefined format. The usage report is recorded in a blockchain network, and a warranty balance, also recorded in the blockchain network, is updated in the amount corresponding to the usage report on the IoT device. A warranty claim is resolved based on records of the usage report and the warranty balance for the IoT device as recorded in the blockchain network.

Abstract: The present invention may include a computing device receives a location data from a client device, wherein the client device comprises one or more location sensors to generate the location data. The computing device determines an altitude of the client device above a floor from the location data. The computing device determines an age and a height of a user using a trained neural network from the client device and the location data and assigns a wireless network channel to the client device based on the age and the height of the user.

Abstract: Embodiments for managing personal device security by one or more processors are described. Information associated with activity of a personal device is received. The information is detected utilizing a sensor coupled to the personal device. A signal representative of the received information is generated. An operational state of the personal device is caused to be changed after the generating of the signal.

Abstract: A price for use of a digital asset in a set of digital assets is determined. The set of digital assets stored in a digital asset repository. A time slot during which the digital asset is available for use is determined. The digital asset is leased out at the price and during the time slot, the leasing allowing use of the digital asset during the time slot in return for payment of the price. the leased digital asset is integrated with a set of base characteristics of a virtualized user. The integrated leased digital asset is presented in a virtual environment during the time slot.

Abstract: A method of generating a classical model to simulate a quantum computational model includes 1) inputting into a quantum computational model a dataset, the quantum computational model being implemented on a quantum computer, 2) computing output results with the quantum computational model using the quantum computer, 3) introducing a variation to at least a portion of the dataset into the quantum computer, 4) computing updated output results of the quantum computational model based on the variation of the at least the portion of the dataset using the quantum computer, and 5) generating a classical twin model of the quantum computational model based on a relationship of the output results and updated output results to the dataset from the quantum computational model.

Abstract: A system includes: a platform; a payload extending from a platform; an adjustable tether connecting the payload to the platform; and a sail extending from the payload. The system further includes a computer program that is executable to relocate the platform to the area of interest based on a threshold based decision which may include providing a tether and sail configuration.

Abstract: An asset stored on a storage device of a computer system is detected to be omitted from an asset-specific access policy. Using a utilization history of the asset, a criticality of the asset is scored, generating a first criticality score for the asset. Using the first criticality score, the asset is classified into a policy category. A selected access policy selected from a set of access policies assigned to a set of assets in the policy category is applied to the asset, the selected access policy specifying an access restriction of the asset.

Abstract: Approaches presented herein enable dynamically determining a validity of a return. More specifically, a system obtains a return request from a customer, a transaction history of the customer, and a set of return policy rules. A generative adversarial network (GAN) trained to detect non-genuine returns is applied to the return request. The GAN uses, among other this, the transaction history of the customer and the set of return policy rules as parameters of the GAN. Based on an output of the GAN, at least one return processing action is recommended and implemented.

Abstract: A computer-implemented method, system and computer program product for watermarking quantum models. A precision for a parameter of a quantum model on a quantum computer is determined. The parameter is then truncated based on the determined precision. Furthermore, the watermark is appended in one or more positions of truncated portion of the truncated parameter. In this manner, watermarking quantum models, such as quantum machine learning models, is achieved.

Abstract: Embodiments relate to a system, program product, and method for leveraging cognitive systems to facilitate the bilateral contextual alignment of textual material and associated diagrammatic matter. The system, computer program product, and method disclosed herein facilitate leveraging a trained cognitive system to understand textual and diagrammatic patterns established by a user, and to learn to draft and edit such textual material and associated diagrammatic matter based on user behavior and preferences. The cognitive system is trained to bilaterally translate between textual material and diagrammatic matter, where the cognitive system includes natural language processing (NLP) features, diagram analytics features, and one or more user profiles.

Abstract: In an approach for identifying a user's interest in a media object and one or more personalities and presenting the user with a visual of how the media object looks on a particular personality, a processor receives a request to determine suitability of the media object for the user. A processor presents the media object to a multilabel classifier to be matched to a set of profile data of the user and a set of data of one or more personalities. A processor receives an output instruction from the multilabel classifier to combine the media object with a particular personality of the one or more personalities. A processor generates a combined media object of the media object with the particular personality using a generative adversarial neural network. A processor inserts the combined media object into an advertising template to generate an advertisement. A processor presents the advertisement to the user.

Abstract: A computer-implemented method, a computer system and a computer program product manage disruption between activities in a common area environment. The method includes capturing activity data from the common area environment, where the activity data is selected from a group consisting of: video data, audio data and biometric data and text data. The method also includes identifying a plurality of current activities in the activity data. Each current activity is associated with a device and includes a context with respect to other current activities in the plurality of current activities. In addition, the method includes determining a disruption score for each current activity in the plurality of current activities based on the context with respect to the other current activities. Lastly, the method includes transmitting a notification response to the device associated with a current activity when the disruption score for the current activity is above a threshold.

Abstract: Methods, computer program products, and systems are presented. The method, computer program products, and systems can include, for instance: receiving personal inputs regarding a first individual, the first individual previously having given informed consent, automatically generating a work profile for the first individual based on the plurality of personal inputs; based on the work profile of the first individual and a preexisting work profile of a second individual, predicting a work affinity indicator for the first individual and the second individual, the predicting including using an affinity model trained via ensemble learning; and providing the work affinity indicator to a user for optional consideration in making a work-related or employment-related decision.

Abstract: Text is received from a user describing item(s) for migration to a computing environment with cloud feature(s), resulting in item description(s), the text including unstructured text that are processed separately. Text mining is performed on the unstructured text to extract item feature(s). For each listing a portion of the unstructured text is extracted, resulting in an extracted text portion for each listing from which an entity is identified. Each entity or item feature is mapped to cloud feature(s) available from solution(s) with cloud feature(s). Based on the cloud feature(s), recommendation(s) are made to the user regarding cloud feature(s) of the solution(s) for optional consideration by the user. Explanation(s) for the recommended cloud feature(s) from explainability model(s) may be provided to the user.

Abstract: A computer-implemented method, including: analyzing, by a computing device, historical information associated with a business application; determining, by the computing device, a business process based on the analyzed historical information; generating, by the computing device, a virtual reality simulation of the business process; identifying, by the computing device, a business application requirement based on a user interaction with the virtual reality simulation; and generating, by the computing device, the ad-hoc application based on the identified business application requirement.

Abstract: A method for chronologically aggregating media content for a specific topic from media content providers includes receiving multi-type media content relating to the specific topic, where the multi-type media content includes at least a first type of media content and a second type of media content. Identifying a first statement in a first portion of the first type of media content that responds to a second statement in a second portion of the second type of media content. Determining a chronological sequence for the first portion of the first type of media content and the second portion of the second type of media content, where the first portion of the first type of media content occurs after the second portion of the first type of media content. Generating a final media content presentation file for the determined chronological sequence.

Abstract: An approach is provided in which the approach receives a request to upload a file at a server system that includes metadata encoded with a non-invertible key. The metadata includes contact information corresponding to an owner of the file. The approach establishes both a photon channel and a classical channel between the server system and a client system, which are both secured using one or more shared secret keys. The approach interfaces with the client system over the photon channel and the classical channel to decode the contact information at the server system, and sends an upload request from the server system to the owner of the file using the contact information. The approach authorizes the upload request at the server system in response to receiving an upload approval from the owner.