Abstract: A biometric information processing device (1) includes a brain wave detecting unit (10), a control unit (20), and a movement assisting unit (30). The brain wave detecting unit (10) detects biometric information in at least one brain region from among a plurality of brain regions that are selectable in accordance with a body part that is a target of function recovery or function improvement. The control unit (20) determines, based on the detected biometric information, at least one activity state in the brain including the location of the brain region(s) that is (are) activated in a subject while attempting to move the body part, and an activation level of such activated brain region(s). When the control unit (20) determines that the at least one activated state of the brain satisfies a predetermined condition, the movement assisting unit (30) executes a predetermined motion to assist movement of the body part.

Abstract: Provided are a computer program product, system, and method for configuring and controlling an automated vehicle to perform user specified operations. User vehicle control programs are loaded in an unmanned vehicle to control the unmanned vehicle to perform a user specified operation. The loading the user vehicle control programs replaces base vehicle control programs in the unmanned vehicle. There is communication with the unmanned vehicle to execute the user vehicle control programs to control the unmanned vehicle to perform the user specified operation. The base vehicle control programs are loaded into the unmanned vehicle to replace the user vehicle control programs to return control of the unmanned vehicle to a vehicle provider after performing the user specified operation.

Abstract: An ability of a power transmission device to transfer electric charge in a power-transmission area at a particular point in time is identified. The ability comprises a threshold number of vehicles to which the power-transmission device can transfer electric charge with at least a threshold efficiency. A predicted number of electric vehicles that are likely to be requesting electric charge within the power-transmission area at the particular point in time is calculated. The number of electric vehicles that are likely to be requesting electric charge within the power-transmission area at the particular point in time is adjusted based on a determination that the predicted number of vehicles is not bound by the threshold number of vehicles.

Abstract: In an approach for generating the most optimal support execution method, a processor receives a shopping support request from a user requesting at least one product be purchased and delivered to the user while the user travels along a scheduled travel route via a public or private transportation method. A processor identifies a plurality of delivery places and a plurality of delivery times. A processor determines at least one shopper candidate who can purchase and deliver the at least one product. A processor presents, to the at least one shopper candidate, a list comprised of optimal support execution methods. Responsive to receiving an acceptance of the shopping support request, a processor sends a support task to at least one shopper. A processor enables the at least one shopper to execute the shopping support request. A processor dynamically updates one or more details of the support task.

Abstract: Aspects of the invention include receiving an identity of a primary web-based material from a user, wherein the primary web-based material describes a topic. Subparts of the primary web-based material are indexed. Supplemental web-based materials accessed by a plurality of reference users are retrieved, wherein the supplemental web-based materials relate to the subparts. A sequence of supplemental web-based materials is generated for the user to follow to gain an understanding of the topic.

Abstract: A laminated iron core includes a plurality of blanked iron core pieces laminated together, a continuity of side parts of the iron core pieces configuring a side surface of the laminated iron core. The side part of each iron core piece includes a specific light reflection area having a prescribed width along a circumferential direction, where the specific light reflection area has different light reflection characteristics from the other area of the side part of the iron core piece, and a striped pattern, configured by the specific light reflection areas, exists on the side surface of the laminated iron core.

Abstract: Provided are techniques for a Generative Adversarial Networks (GANs) based identification of an edge server. At a first edge server, a global discriminator that has been trained with common data is received. It is determined that area data is imbalanced using the global discriminator. A local discriminator is trained with the area data to generate a first result. An exchanged local discriminator from a second edge server is trained with the area data to generate a second result. The first result and the second result indicate that the first edge server and the second edge server are proximate. The first edge server and the second edge server are added to an edge server group list. At least one of an application model and a configuration of an application is updated from one of the first edge server and the second edge server, and the application is executed.

Abstract: Provided are a computer program product, system, and method for configuring and controlling an automated vehicle to perform user specified operations. User vehicle control programs are loaded in an unmanned vehicle to control the unmanned vehicle to perform a user specified operation. The loading the user vehicle control programs replaces base vehicle control programs in the unmanned vehicle. There is communication with the unmanned vehicle to execute the user vehicle control programs to control the unmanned vehicle to perform the user specified operation. The base vehicle control programs are loaded into the unmanned vehicle to replace the user vehicle control programs to return control of the unmanned vehicle to a vehicle provider after performing the user specified operation.

Abstract: A computer system trains a federated learning model. A federated learning model is distributed to a plurality of computing nodes, each having a set of local training data comprising labeled data samples. Statistical data is received from each computing node that indicates the node's count of data samples for each label, and is analyzed to identify one or more computing nodes having local training data in which a label category is underrepresented beyond a threshold value with respect to data samples. Additional data samples labeled with the underrepresented labels are provided, and the computing nodes perform training. Results of training are received and are processed to generate a trained global model. Embodiments of the present invention further include a method and program product for training a federated learning model in substantially the same manner described above.

Abstract: A processor may generate, based on a predicted route of a user, a timeslot for presenting information to the user. The predicted route may be associated with a route segment, and the timeslot may be associated with the route segment. The processor may match one or more proposals to the timeslot associated with the route segment. The one or more proposals may be matched, at least in part, based on proposal criteria set by a proposal criteria user associated with the proposal. The processor may predict an acceptance potentiality of the user. The processor may select a subset of the one or more proposals. The processor may provide the selected subset of the one or more proposals. The selected subset may be provided, at least in part, based on the acceptance potentiality.

Abstract: A computer-implemented method, a computer program product, and a computer system for parallel cross validation in collaborative machine learning. A server groups local models into groups. In each group, each local device uses its local data to validate accuracies of the local models and sends a validation result to a group leader or the server. The group leader or the server selects groups whose variances of the accuracies are not below a predetermined variance threshold. In each selected group, the group leader or the server compares an accuracy of each local model with an average value of the accuracies and randomly selects one or more local models whose accuracies do not exceed a predetermined accuracy threshold. The server obtains weight parameters of selected local models and updates the global model based on the weight parameters.

Abstract: Utilizing a trained generative adversarial network (GAN) model to cause a computer to output multivariate forecasted time-series data by providing a trained GAN model, the GAN model comprising dilated convolutional layers for receiving time-series multivariate data, receiving time-series multivariable biometric data, generating, using the GAN model, successive time series multivariate biometric data according to the time-series multivariate biometric data, determining an outcome according to the successive time-series multivariate biometric data, and providing an output associated with the outcome.

Abstract: A method for calculating traffic flow changes includes detecting a traffic event. The method further includes determining an affected area of the traffic event and determining an investigation area based on the affected area. The method further includes selecting at least one vehicle located within the investigation area and calculating a change in traffic flow due to the traffic event based on a comparison of a predicted traffic flow with a current traffic flow, wherein the current traffic flow is based on information received from the at least one vehicle. The method further includes updating the affected area based on the change in traffic flow and calculating an updated change in traffic flow based on the updated affected area when the updated affected area is larger than a predetermined threshold area.

Abstract: A method, computer system, and a computer program product for preemptive collision mitigation is provided. The present invention may include calculating a future position of a first vehicle based on carprobe data from a first vehicle, wherein the carprobe data contains neural data of an operator of the first vehicle. The present invention may also include calculating a distance between the future position of the first vehicle and a future position of a second vehicle. The present invention may then include determining the calculated distance between the future position of the first vehicle and the future position of the second vehicle is below a threshold distance.

Abstract: A processor may generate, based on a predicted route of a user, a timeslot for presenting information to the user. The predicted route may be associated with a route segment, and the timeslot may be associated with the route segment. The processor may match one or more proposals to the timeslot associated with the route segment. The one or more proposals may be matched, at least in part, based on proposal criteria set by a proposal criteria user associated with the proposal. The processor may predict an acceptance potentiality of the user. The processor may select a subset of the one or more proposals. The processor may provide the selected subset of the one or more proposals. The selected subset may be provided, at least in part, based on the acceptance potentiality.

Abstract: Utilizing a trained generative adversarial network (GAN) model to cause a computer to output multivariate forecasted time-series data by providing a trained GAN model, the GAN model comprising dilated convolutional layers for receiving time-series multivariate data, receiving time-series multivariable biometric data, generating, using the GAN model, successive time series multivariate biometric data according to the time-series multivariate biometric data, determining an outcome according to the successive time-series multivariate biometric data, and providing an output associated with the outcome.

Abstract: Described are techniques for acquiring geospatial data according to an information value. The techniques including determining a context for geospatial data to be used in an application, where the context is based on one or more external factors that influence variation of the geospatial data. The techniques further include calculating an information value of the geospatial data in the context for each of a plurality of information acquisition methods, where the plurality of information acquisition methods include respective data acquisition frequencies and respective spatial resolutions, and where the information value is based on an information loss function, an information amount, and a cost. The techniques further include selecting a first information acquisition method with a highest information value and acquiring the geospatial data using the first information acquisition method.

Abstract: Described are techniques for acquiring geospatial data according to an information value. The techniques including determining a context for geospatial data to be used in an application, where the context is based on one or more external factors that influence variation of the geospatial data. The techniques further include calculating an information value of the geospatial data in the context for each of a plurality of information acquisition methods, where the plurality of information acquisition methods include respective data acquisition frequencies and respective spatial resolutions, and where the information value is based on an information loss function, an information amount, and a cost. The techniques further include selecting a first information acquisition method with a highest information value and acquiring the geospatial data using the first information acquisition method.

Abstract: In aggregating application functions on multi-access edge computing (MEC) hosts across multiple carriers, a system associated with a particular application receives performance data from a first and second MEC hosts. The first MEC host is deployed on a first network carrier and coupled to first user terminals. The second MEC host is deployed on a second network carrier and coupled to second user terminals. The particular application is installed on the first and second MEC hosts. The system determines whether the performance data from the second MEC host exceeds a threshold value. If so, the system sends instructions to the second MEC host to aggregate function(s) of the particular application to the first MEC host. As a result, each of the first and second user terminals connect to the first MEC host to receive content for the particular application.

Abstract: Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises in response to receiving a data packet from a computing device, classifying the data packet as a task having one or more portions; allocating the classified task to a processing location within a data region based on a location of the computing device; in response to a change associated with the task, dynamically calculating alternate processing locations within a radius of the data region to process one or more portions of the task based on scoring values associated with the change; and redistributing at least one portion of the classified task according to an alternate processing location of dynamically calculated alternate processing locations.