Abstract: A thermal management system enables fluid coupling of the cooling circuits for the battery and the propeller arrangements. More than one propeller arrangement can be serviced by the same cooling circuit, but distribution of the coolant may be finessed. Optional pathways are provided to use heated coolant for heating (e.g., de-icing, cabin heating, etc.) before cooling the coolant. Fluid coupling of conduits between and/or within the cooling circuits provide redundancy to accommodate various faults and equipment malfunctions.

Abstract: A thermal management system includes a refrigeration circuit that cools at least a first coolant that circulates around a battery cooling loop. Refrigerant of the refrigeration circuit is cooled at a liquid-cooled condenser and at an air-cooled condenser. In certain examples, the liquid-cooled condenser is cooled by coolant circulating along a propeller arrangement cooling loop. In certain examples, the coolant from the propeller arrangement cooling loop may be combined with coolant from the battery cooling loop.

Abstract: This disclosure relates generally to method and system for providing data privacy in service operations. Identifying risk arising from processing of user request in service operations is time consuming and monitoring insider threats is a difficult task. The method includes receiving a user request for a service comprising a plurality of sensitive attributes and further a vulnerability rating is assigned to each sensitive attribute. To mitigate the risk, the method estimates a disclosure proportion for the plurality of sensitive attributes and a masking operation is performed. Further, a sensitivity score is computed to allocate the user request to an agent associated with an agent registry with enabled data privacy and minimal data exposure. The agent is monitored by computing an agent mis-usability score to assess an insider threat risk. Additionally, a feedback alert is notified to autotune the plurality of privacy settings.

Abstract: Example systems and methods provide input suggestions to a user to improve user experience on user devices. The input suggestions can be fill information from another app on device to the present app being used by user, information for performing a search (without the user having to copy-paste data or entering the data manually), responses to a message/notification received by the user, information/content/data to be shared between apps (without switching between apps), and emojis/GIFs that can be used by the user. The method includes analyzing one or more content of one or more screen displayed on device, generating at least one of a logical tree structure and a data mashup model of the one or more analyzed content for each screen, and providing a recommendation to a user. The recommendation can be a connected action or an input suggestion.

Abstract: The embodiments of present disclosure herein address the need of minimizing web services relocation and user centers reallocation to comply with data residency regulations and change in latency threshold for web services based on user demands. The method and system provide a framework that assists enterprises in migrating web services and user center allocation to different data centers with lower additional operational cost from its current configurations and minimal changes (migrations). In case of change in data regulations and invocation frequency from users demand, non-compliant users are allocated to compliant data centers with minimal changes in the original configuration. Though the key decision is to serve the customers effectively, web services need to be deployed across a finite number of servers, there are multiple sub-problems such as minimizing latency and reduction in operational cost that needs to be addressed.

Abstract: Example systems and methods provide input suggestions to a user to improve user experience on user devices. The input suggestions can be fill information from another app on device to the present app being used by user, information for performing a search (without the user having to copy-paste data or entering the data manually), responses to a message/notification received by the user, information/content/data to be shared between apps (without switching between apps), and emojis/GIFs that can be used by the user. The method includes analyzing one or more content of one or more screen displayed on device, generating at least one of a logical tree structure and a data mashup model of the one or more analyzed content for each screen, and providing a recommendation to a user. The recommendation can be a connected action or an input suggestion.

Abstract: An example system includes a vehicle having a prime mover motively coupled to a drive line; a motor/generator selectively coupled to the drive line, and configured to selectively modulate power transfer between an electrical load and the drive line; a battery pack; a DC/DC converter electrically interposed between the motor/generator and the electrical load, and between the battery pack and the electrical load, the DC/DC converter comprising a DC/DC converter housing; and a covering tray positioned over a plurality of batteries of the battery pack, the covering tray comprising a connectivity layer configured to provide electrical connectivity to terminals of the plurality of batteries.

Abstract: Disclosed herein are embodiments for automated intelligent price guidance of listings for a for sale object (FSO) being offered by a seller. Some embodiments may operate by: receiving information relating to the FSO, including specifications for selling the FSO, wherein the specifications include an original offer price and a time window for selling the FSO; determining a category of the FSO; generating an optimal offer price for the FSO based on one or more of: (a) past listings of previously sold FSOs that have a same or similar category of the FSO; (b) the specifications, including the time window; (c) a category decay curve applicable to the category; and (d) seller flexibility curve of the seller; and through the use of a machine learning neural networking analysis suggesting the optimal offer price to the seller as an offer price for a listing corresponding to the FSO, wherein this price is evaluated over time and suggestions are made accordingly.

Abstract: Disclosed herein are embodiments for intelligent listing creation for a for sale object (FSO). Some embodiments operate by determining a numerical identifier corresponding to a category of the FSO. A binarization of the numerical identifier using hot encoding is performed and using a neural network regression model, an optimal offer price is generated based on a category of the FSO. Information about the FSO is provided to the neural network regression model that tokenizes the textual input, and a unique binary vector representing the category is provided instead of the numerical identifier to the neural network regression model. An optimal price, generated by the neural network regression model, based on the unique binary vector representing the category.

Abstract: Example systems and methods provide input suggestions to a user to improve user experience on user devices. The input suggestions can be fill information from another app on device to the present app being used by user, information for performing a search (without the user having to copy-paste data or entering the data manually), responses to a message/notification received by the user, information/content/data to be shared between apps (without switching between apps), and emojis/GIFs that can be used by the user. The method includes analyzing one or more content of one or more screen displayed on device, generating at least one of a logical tree structure and a data mashup model of the one or more analyzed content for each screen, and providing a recommendation to a user. The recommendation can be a connected action or an input suggestion.

Abstract: A thermal management system includes a refrigeration circuit that cools at least a first coolant that circulates around a battery cooling loop. Refrigerant of the refrigeration circuit is cooled at a liquid-cooled condenser and at an air-cooled condenser. In certain examples, the liquid-cooled condenser is cooled by coolant circulating along a propeller arrangement cooling loop. In certain examples, the coolant from the propeller arrangement cooling loop may be combined with coolant from the battery cooling loop.

Abstract: A thermal management system enables fluid coupling of the cooling circuits for the battery and the propeller arrangements. More than one propeller arrangement can be serviced by the same cooling circuit, but distribution of the coolant may be finessed. Optional pathways are provided to use heated coolant for heating (e.g., de-icing, cabin heating, etc.) before cooling the coolant. Fluid coupling of conduits between and/or within the cooling circuits provide redundancy to accommodate various faults and equipment malfunctions.

Abstract: A thermal management system proactively provides cooling to powered components and/or the battery of an aircraft based on expected temperature rises of the components. The thermal management system may monitor maneuver commands input by a pilot and/or may monitor a flight plan including maneuver commands and associated trigger events to determine when to take proactive steps. The thermal management system may adjust a coolant flow rate and/or may adjust a refrigerant flow rate to increase or decrease the level of cooling provided to various components.

Abstract: Disclosed herein are embodiments for intelligent listing creation for a for sale object (FSO). Some embodiments operate by determining a numerical identifier corresponding to a category of the FSO. A binarization of the numerical identifier using hot encoding is performed and using a neural network regression model, an optimal offer price is generated based on a category of the FSO. Information about the FSO is provided to the neural network regression model that tokenizes the textual input, and a unique binary vector representing the category is provided instead of the numerical identifier to the neural network regression model. An optimal price, generated by the neural network regression model, based on the unique binary vector representing the category.

Abstract: Disclosed herein are embodiments for automatic, intelligent generation of listings for a for sale object (FSO) being offered by a seller. Some embodiments operate by: receiving information relating to the FSO, including specifications for selling the FSO and an election of an automatic listing option; determining a category of the FSO; generating an optimal offer price based on at least the category; and generating multiple listings for the FSO, wherein the multiple listings have varying titles, descriptions, pictures and offer prices.

Abstract: An operation method for generating content including a user identification (ID), and an apparatus therefor are provided. The operation method of the device includes obtaining mapping information by making one or more pieces of biometric information for each of a plurality of users correspond to a user ID of each of the plurality of users, obtaining first content including a first user by photographing the first user, obtaining first biometric information of the first user, determining a first user ID corresponding to the first biometric information of the first user, based on the mapping information, and associating the first content with the first user ID, and storing the association of the first content with the first user ID.

Abstract: An example system includes a vehicle having a prime mover motively coupled to a drive line; a motor/generator selectively coupled to the drive line, and configured to selectively modulate power transfer between an electrical load and the drive line; a battery pack; a DC/DC converter electrically interposed between the motor/generator and the electrical load, and between the battery pack and the electrical load, the DC/DC converter comprising a DC/DC converter housing; and a covering tray positioned over a plurality of batteries of the battery pack, the covering tray comprising a connectivity layer configured to provide electrical connectivity to terminals of the plurality of batteries.

Abstract: Disclosed herein are system, computer-program product (non-transitory computer-readable medium), and method embodiments for machine-learning prediction or suggestion based on object identification. A system including at least one processor may be configured to cross-reference an identifier of a selected object with a list of known unique identifiers. The selected object may be selected via received selection. The at least one processor may further retrieve a set of values associated with the identifier of the selected object, upon determining that the list of known unique identifiers includes the identifier of the selected object, and perform machine-learning to derive a predicted-value set based at least in part on the set of values associated with the identifier of the selected object and a category applicable to the selected object. The at least one processor may determine that the predicted-value set satisfies a predetermined confidence condition, and output at least part of the predicted-value set.

Abstract: Disclosed herein are embodiments for automatic, intelligent generation of listings for a for sale object (FSO) being offered by a seller. Some embodiments operate by: receiving information relating to the FSO, including specifications for selling the FSO and an election of an automatic listing option; determining a category of the FSO; generating an optimal offer price based on at least the category; and generating multiple listings for the FSO, wherein the multiple listings have varying titles, descriptions, pictures and offer prices.

Abstract: Disclosed herein are embodiments for automated intelligent price guidance of listings for a for sale object (FSO) being offered by a seller. Some embodiments may operate by: receiving information relating to the FSO, including specifications for selling the FSO, wherein the specifications include an original offer price and a time window for selling the FSO; determining a category of the FSO; generating an optimal offer price for the FSO based on one or more of: (a) past listings of previously sold FSOs that have a same or similar category of the FSO; (b) the specifications, including the time window; (c) a category decay curve applicable to the category; and (d) seller flexibility curve of the seller; and through the use of a machine learning neural networking analysis suggesting the optimal offer price to the seller as an offer price for a listing corresponding to the FSO, wherein this price is evaluated over time and suggestions are made accordingly.