Abstract: A system and method are provided for generative atomistic design of materials. The disclosure herein includes a machine learning system for generating a new material, using multiple predictive machine learning models for atomic level properties to create training data, and/or then using the same predictive machine learning models to refine the output of a generative machine learning system. In use, one or more datasets are received at at least one computing device corresponding to a desired material. Additionally, using at least two machine learning models associated with the at least one computing device, a new dataset is created for the desired material. Further, the at least two machine learning models are trained, using at least semi-supervised learning, based on the one or more datasets, to model properties of the desired material. Still yet, using the at least one computing device, a prediction is outputted comprising the desired material.

Abstract: A system and method are provided for a machine-learning drive framework for predicting ionic conductivity of solid-state electrolytes. In use, the method and/or system may include receiving, at a machine learning system, two or more molecular structures from at least one structural dataset, where the two or more molecular structures relate to ionic mobility. Additionally, atomic weights are calculated for the two or more molecular structures, and the machine learning system is trained based on the two or more molecular structures, where the training relies on at least one intrinsic atomic feature and the calculated atomic weights for the two or more molecular structures. Further, a bias-correction is applied for the two or more molecular structures to improve the training of the machine learning system. Further, one or more molecular dynamics (MD) simulations are outputted, using the machine learning system, for the two or more molecular structures.

Abstract: A vehicle lock includes a locking mechanism with a rotary latch and a pawl for latching the rotary latch when the vehicle lock is in a closed state, a receiver for receiving a reference code, a code transfer interface for obtaining an access code and a control unit which is configured such that the vehicle lock assumes an unlocked state when the obtained access code matches the reference code. The locking mechanism is used in a method for access-controlled loading and/or unloading of a vehicle. A high degree of automation of an access-controlled process for loading and/or unloading a vehicle can thus be achieved substantially with the aid of the vehicle lock.

Abstract: Values of a variable affecting the determination of the driver of a shared ride may be calculated. Each value may be associated with a respective potential driver. An optimal value from the calculated values may be selected. A potential driver associated with the selected optimal value may be assigned as the driver of the shared ride. The variable may be carbon emission, electricity consumption, passenger to driver role ratio, driving distance, driving time, vehicle size, fuel efficiency, electricity to gasoline usage ratio, accident occurrence, vehicle safety, vehicle comfort, or vehicle speed. The optimal value may be the lowest value or the highest value from the calculated values. Each value may be calculated based on parameters specified by the respective potential driver.

Abstract: Embodiments of the present invention may provide a various techniques for raising user satisfaction with an automated ride sharing system. In one embodiment, the system may disqualify potential passengers that will force the driver to return to a previously departed area. In another embodiment, the system may consolidate multiple stop locations to reduce the number and frequency of stops in a scheduled ride. In another embodiment, the system may select a best possible ride from a plurality of calculated rides based on user satisfaction factors.

Abstract: Values of a variable affecting the determination of the driver of a shared ride may be calculated. Each value may be associated with a respective potential driver. An optimal value from the calculated values may be selected. A potential driver associated with the selected optimal value may be assigned as the driver of the shared ride. The variable may be carbon emission, electricity consumption, passenger to driver role ratio, driving distance, driving time, vehicle size, fuel efficiency, electricity to gasoline usage ratio, accident occurrence, vehicle safety, vehicle comfort, or vehicle speed. The optimal value may be the lowest value or the highest value from the calculated values. Each value may be calculated based on parameters specified by the respective potential driver.

Abstract: A time difference between a segment belonging to a multi-segment ride and a ride intent may be calculated. The time difference may be compared to a threshold. If the time difference is less than or equal to the threshold, the ride intent may be marked as a new segment of the multi-segment ride. The parameters of the segment belonging to the multi-segment ride and the ride intent may be specified through electronic calendar entries. The segment belonging to the multi-segment ride may be the first temporal segment of the multi-segment ride.

Abstract: A backend carpooling system including a memory device, a processing device, a communication device, a calculating arrangement, coupled to the memory and processing devices, that includes one or more algorithms for calculating distances, travel times, routes, and performing optimizations to select a distance, travel time, or route satisfying predetermined optimization criteria, the calculating arrangement generating a plurality of ridesharing opportunities, and a notification arrangement, coupled to the communication device, that transmits the plurality of ridesharing opportunities to a user, wherein the plurality of ridesharing opportunities are periodically transmitted to the user.

Abstract: The invention relates to a method for integrating services in a calendar application via the meeting request functionality of calendar programs comprising: initiating one or multiple services, wherein the initiation may involve the transmission of calendar event information from the calendar application to the service, the service requests being sent as meeting request e-mails to one or more service e-mail addresses, each service e-mail address representing a service, receiving the update requests generated by the one or multiple services, the update requests being meeting request response e-mails or one or multiple second meeting request e-mails processing the received update requests, and updating the calendar application.

Abstract: A method and system for allocating users as trip accompanies provides for: creating a first trip prediction algorithm, collecting input parameters, predicting by the first trip prediction algorithm using the collected input parameters as input, at least one first trip, executing a matching method, the matching method comparing attributes of the predicted at least one first trip with attributes of at least one second trip, and allocating the first and the second user to each other as trip accompanies in dependence of the matching score of the first and second potential trip data object.

Abstract: A system and method described herein provide for the generation of self-optimization algorithms from user survey results for a complex system, such as a matching algorithm for a trip sharing service. User feedback surveys are generated and transmitted to users of the complex system to obtain feedback on a user's experience using the complex system. Survey results from completed surveys are compiled to demonstrate statistical evidence of alternations that can be made to adjust the settings of the complex system. The system and method may use the generated alternations by the complex system to modify the settings of the complex system.

Abstract: Embodiments of the present invention may provide a various techniques for raising user satisfaction with an automated ride sharing system. In one embodiment, the system may disqualify potential passengers that will force the driver to return to a previously departed area. In another embodiment, the system may consolidate multiple stop locations to reduce the number and frequency of stops in a scheduled ride. In another embodiment, the system may select a best possible ride from a plurality of calculated rides based on user satisfaction factors.

Abstract: The invention relates to a method for integrating services in a calendar application via the meeting request functionality of calendar programs comprising: initiating one or multiple services, wherein the initiation may involve the transmission of calendar event information from the calendar application to the service, the service requests being sent as meeting request e-mails to one or more service e-mail addresses, each service e-mail address representing a service, receiving the update requests generated by the one or multiple services, the update requests being meeting request response e-mails or one or multiple second meeting request e-mails processing the received update requests, and updating the calendar application.

Abstract: A navigation device and computer implemented method for predicting the destination of a trip, the method being executed by a navigation device, the method comprising the steps of: determining starting parameters, the starting parameters comprising at least the starting point, starting time and date of the trip, executing a destination prediction algorithm, the destination prediction algorithm taking the starting parameters as input and predicting a destination, wherein the destination prediction algorithm is generated by using information of a trip history; determining, upon arrival at the predicted or another destination, the actual destination.

Abstract: The invention relates to a method for integrating services in a calendar application via the meeting request functionality of calendar programs comprising: initiating one or multiple services, wherein the initiation may involve the transmission of calendar event information from the calendar application to the service, the service requests being sent as meeting request e-mails to one or more service e-mail addresses, each service e-mail address representing a service, receiving the update requests generated by the one or multiple services, the update requests being meeting request response e-mails or one or multiple second meeting request e-mails processing the received update requests, and updating the calendar application.

Abstract: A system and method to integrate a service in a calendar application. A service integration module and a calendar application may be installed on a client computing device. The service integration module may have read and write access to the calendar application of the client computing device and may submit a service request to a remote service. The service request may be a call of a first web service interface of the service and may initiate the execution of the service which may generate a result. The service integration module may receive the result. The service integration module may process the result, which may include extracting data required for specifying an event in an electronic calendar of the calendar application. The service integration module may create, delete, or modify an event in the electronic calendar of the calendar application.

Abstract: This disclosure provides various embodiments of systems, software, and computerized methods for reducing the number of server requests sent to a web server. In one aspect, the software generates a file reference uniquely identifying a version of a file capable of being cached by a requester. The file reference can comprise a network-addressable location of the version of the cacheable file and a parameter uniquely identifying the version of the cacheable file, where the parameter is separated from the network-addressable location of the version of the cacheable file. The software can further embed the file reference into a web page file, and send the web page file in response to a request for the web page. The parameter may include a plurality of data elements, such as a second instance of the file name, a timestamp, or a version number of the cacheable file.

Abstract: Techniques for allocating drivers and passengers sharing a trip. The techniques may include a trip sharing service comprising receiving a first service request; specifying a first potential trip data object by the trip sharing service and executing a matching method. Matching may include checking a first potential trip data object against at least a second potential trip data object. Matching may further include comparing the specifications of the first potential trip data object with the specifications of the at least one second potential trip data object, determining the degree of congruency of the specifications of the compared potential trip data objects, assigning one role to a first and a second user, and adding the second potential trip data object to a result list in case the determined degree of congruency between the first and the second potential trip data object exceeds a predefined threshold.

Abstract: A method and system for allocating users as trip accompanies provides for: creating a first trip prediction algorithm, collecting input parameters, predicting by the first trip prediction algorithm using the collected input parameters as input, at least one first trip, executing a matching method, the matching method comparing attributes of the predicted at least one first trip with attributes of at least one second trip, and allocating the first and the second user to each other as trip accompanies in dependence of the matching score of the first and second potential trip data object.

Abstract: A navigation device and computer implemented method for predicting the destination of a trip, the method being executed by a navigation device, the method comprising the steps of: determining starting parameters, the starting parameters comprising at least the starting point, starting time and date of the trip, executing a destination prediction algorithm, the destination prediction algorithm taking the starting parameters as input and predicting a destination, wherein the destination prediction algorithm is generated by using information of a trip history; determining, upon arrival at the predicted or another destination, the actual destination.