Abstract: A computerized travel itinerary recommendation tool includes a traveler monitor, a contextual information parser, and a recommendation engine. The traveler monitor obtains traveler preference information associated with a traveler. The traveler preference information indicates one or more travel criteria for a trip. Travel criteria comprises one or more parameters of travel products available for the trip. The contextual information parser infers one or more travel criteria from contextual information obtained for the trip. The contextual information is information that does not include any travel criterion. The recommendation engine determines a recommended travel itinerary for the trip to the traveler based on the travel preference information and the contextual information. The recommendation engine further causes a display of the recommended travel itinerary to the traveler.

Abstract: A system and method for improving payload delivery utilizing environmental factors is disclosed. The method includes receiving a request for delivery of a payload, the request including a destination location; determining an optimal height for a release of the payload at the destination location, wherein the payload is delivered by a UAV configured to hover at the destination location; generating a navigation plan including a flight path having an origin point and the destination location; and configuring the UAV to execute the navigation plan and release the payload at the destination location from the determined optimal height.

Abstract: Provided are a method and an apparatus for predicting cancellations of reservation services based on fusion of multi-scale time series features, relating to the field of predicting cancellations of reservation services. The method includes: obtaining reservation feature data of a reservation service order to be predicted, where the reservation feature data includes service provider feature information, user reservation feature information, statistical time series data, and statistical non-time series data; performing multi-scale time series feature fusion on various time series in the statistical time series data, and inputting fused data, together with other reservation feature data, into a multi-task learning prediction network for cancellation prediction. The multi-task learning prediction network includes a main cancellation prediction model and an auxiliary rejection prediction model. This application can accurately predict whether a reservation service order to be predicted is canceled during service.

Abstract: The present application describes a payload management system that routes a payload item associated with an individual from an origin to a destination. In some examples, the payload item is routed from the origin to the destination separate from a travel itinerary associated with the individual. For example, the payload item can be routed via a vehicle other than a VTOL aircraft that is assigned to the individual for a multi-modal transportation service.

Abstract: A federated learning framework including household agents configured to continuously learn model parameters for managing charging periods and discharging periods of household batteries, and microgrid agents to maximize use of local energy based on a pricing policy, including accessing power from other microgrids when there is insufficient local energy to cover local demand. and selling surplus energy to the other microgrids when power generation by the microgrid surpasses the local demand. Each household machine learning agent is configured to control household energy demand from and supply to a microgrid which they are connected in order to minimize household energy cost while adapting to changes in the energy price that is determined based on the pricing policy of the microgrid agent that encourages reduction of carbon emission. A federated learning engine combines the model parameters from the household machine learning agents to update a global household machine learning agent.

Abstract: A data input device including a keypad. The data input device includes at least one proximity sensor positioned within a housing formed in an element of the device forming a projection in the vicinity of the keypad, the proximity sensor being oriented toward the keypad, the proximity sensor delivering measurements; and a program for analysing the measurements, delivering information representative of the presumed presence of a spy device on the keypad when the measurements are higher than a predetermined threshold for a predetermined time period.

Abstract: Artificial intelligence (AI) based systems and methods are described for analyzing order data to generate a driver logistics prediction value. Processors of a logistics server receive order data from order data sources corresponding to an order. A dispatch learning model then analyzes the order data to generate a driver logistics prediction value corresponding to the order data. The dispatch learning model is trained or provided with logistics data regarding order data of respective orders, and the dispatch learning model is configured to output one or more driver logistics prediction values corresponding to the order data of the respective orders. The processors generate a driver determination that identifies a driver to fulfill the order based on the driver logistics prediction value, and push the driver determination to a dispatch application. Responsive to receiving the driver determination, the dispatch app displays a graphical user interface (GUI) depicting the driver determination.

Abstract: Systems and methods perform operations that include receiving information regarding an item; obtaining one or more digital images of the item; generating an image dataset, which may be unique, for the item based on the one or more digital images; storing information linking the image data set to the information regarding the item; receiving, from an item disposition system, a request to identify the item, wherein the request includes the image dataset for the item; identifying the item based on receiving the request and the image dataset; and providing, to the item disposition system, the information regarding the item to cause the item disposition system to disposition the item based on the information regarding the item.

Abstract: Techniques for transportation speed prediction and transit time estimation are provided. In an example, a computer system generates a first input to a first machine learning model based on temporal information, road segment information, and attribute information for road segments in a geographic region. The computer system receives a first output of the first machine learning model. The first output indicates a predicted speed value associated with a road segment for a transportation resource. The computer system generates a second input to a second machine learning model based on the first input, the predicted speed value, and properties associated with a transportation load. The computer system receives a second output of the second machine learning model. The second output indicates a distribution of a time length for transporting the transportation load using the transportation resource. The second output is usable in deploying the transportation resource for transporting the transportation load.

Abstract: Systems and methods are provided for facilitating the discovery and presentations of skills and data processed by the skills within blocks of a canvas displayed to a user within a user interface. The systems also identify schemas and data output formats of the relevant skills, and a desired presentation schema based on the user contexts and the application contexts. The systems further identify modules for normalizing the schemas of the relevant skills to the desired presentation schema, and uses the identified modules to normalize data obtained from the relevant skills into the desired presentation schema for presentation within the blocks of the canvas.

Abstract: A computing system is configured to: (i) create a data science model that is configured to (a) receive a value for a metric that provides insight regarding a party's usage of a software tool of a construction management software application on a construction project and (b) based on an evaluation of the received value for the metric, output a prediction of the party's performance on the construction project and, (ii) after creating the data science model, utilize the data science model to produce a prediction of a given party's performance on a given construction project by inputting a given value for the metric into the data science model and thereby causing the data science model to (a) evaluate the given value of the metric, and (b) based on the evaluation, output the prediction of performance on the given construction project.

Abstract: Some embodiments described in this disclosure are directed to a system for determining a deficit or surplus in green energy for use in an industrial process. In some embodiments, the system is configured to predict future available green energy using weather forecasts. In some embodiments, the system is configured to model power demand for an industrial process and determine whether a green energy source such as solar and/or wind will be able to meet the power demand. In some embodiments, the system is configured to suggest alternate energy sources for purchase to make up for a green energy deficit. In some embodiments, the system is configured to suggest a best time to buy or sell energy to optimize a profit or loss.

Abstract: A computer-implemented method, a computer system and a computer program product customize delivery of transactional documents. The method includes receiving a transactional document associated with a user. The method also includes obtaining a preferred document format for the user and a preferred delivery method for the user from a database. The method further includes identifying a current display format of the transactional document. In addition, the method includes modifying the current display format of the transactional document, wherein a modified transactional document has the preferred document format for the user. Lastly, the method includes transmitting the modified transactional document to the user using the preferred delivery method for the user.

Abstract: Systems and methods for reconciling location based on multiple computing device signals. For example, the computing system can obtain location datasets associated with freight carrier services from computing sources. The computing system can determine an expected signal pattern for a location associated with a freight transportation service. The computing system can determine, for each computing source, a confidence score. The confidence score can represent the probability that the respective location dataset is associated with a load being transported for a freight transportation service. The computing system can determine a primary location dataset based on the confidence scores. The computing system can perform actions based on the primary location dataset.

Abstract: Systems and methods are provided to generate an actual number of search results, a total estimated number of search results based on historical search data in the online marketplace, and a conversion estimated number of search results for users who converted, for a given set of query parameters in an online marketplace.

Abstract: A system for providing frictionless transfer of tickets at a venue comprising: a server system comprising at least one server, a processor, and a database; at least one user device; and at least one unique ticket ID corresponding to a particular seat or ticket; wherein the server performs the following method: accessing the system via the user device and identifying a first ticket corresponding to an event, said first ticket having a unique ticket ID; validating ownership of the first ticket through a confirmation process by validating the unique ticket ID and storing the same within the database; identifying a second ticket for exchange; and confirming the exchange of the first ticket and the second ticket.

Abstract: A computing system for interactive prompting for a supply chain includes processing circuitry that constructs a knowledge graph based ontologies from a plurality of data sources, the ontologies being related to a product. In a turn-based dialog session, the processing circuitry receives a prompt for the product, identifies at least one ontology-level node in a first layer of the knowledge graph, and generates one or more sub-questions. The processing circuitry outputs the sub-questions via a large language model, receives responses to the sub-questions, identifies one or more second-level nodes in a second, middle layer of the knowledge graph based on the responses, and performs a multi-hop query to identify one or more instance-level nodes in the third layer of the knowledge graph. The processing circuitry outputs, via the large language model, text data corresponding to the instance-level nodes as an answer to the prompt.

Abstract: The present disclosure relates to a mobile charging service system and method for an electric vehicle. The mobile charging service system according to an embodiment of the present disclosure for providing a mobile charging service whereby, upon request of a service user to a service provider, the service provider charges an electric vehicle of the user, the mobile charging service system includes: a service terminal configured to receive a request for the mobile charging service and receive location information of the electric vehicle; and a charging service vehicle configured to charge a battery of the electric vehicle in response to a shared key being authenticated by the electric vehicle.

Abstract: Systems and methods are provided for evaluating career interests through situational judgment test format. In embodiments, a career assessment is generated, using a first language based machine learning model and a set of criteria. The career assessment is administered to a user. A plurality of test answers for the user are received based on the career assessment. For a particular test answer a score is assigned for the particular test answer and at least one user career interest category based on the score is determined. The totals for the at least one user career interest category based on the determining is tabulated. At least one career suggestion is provided, using a second language based machine learning model, based on the totals for the at least one user career interest category.

Abstract: A zone assignment system includes a schedule obtainer that obtains usage schedules of users each indicating the intended use of a space by a user; an assigner that assigns each user a zone to use, based on the usage schedules obtained; and an outputter that outputs an assignment result indicating the zone assigned. The assigner assigns a first zone out of the zones to the user, among the users, who has a usage schedule indicating a first intended use as the intended use, and the assigner assigns a second zone out of the zones to the user, among the users, who has a usage schedule indicating a second intended use as the intended use, the second zone being a zone not adjacent to the first zone.