Abstract: Incidents may be monitored using a camera in response to an activation of a trigger device. Trigger data may be received over a communication network in response to activation of a trigger device disposed within a first area of a vehicle. A camera disposed within a second area of the vehicle may be controlled over the communication network in response to receiving the trigger data, the controlling causing the camera to capture sensor information of a passenger of the vehicle. Passenger information of the passenger of the vehicle may be obtained in response to receiving the trigger data. An alert notification may be generated. The alert notification may comprise at least a portion of the sensor information of the passenger, and the alert notification may be capable of initiating one or more incident actions associated with the passenger.

Abstract: Providing a predictive model for a target language by determining an instance weight for a labeled source language textual unit according to a set of unlabeled target language textual units, scaling, by the one or more computer processors, an error between a predicted label for the source language textual unit and a ground-truth label for the source language textual unit according to the instance weight, updating, by the one or more computer processors, network parameters of a predictive neural network model for the target language according to the error, and providing, by the one or more computer processors, the predictive neural network model for the target language to a user.

Abstract: After determining a trip order has a high risk, verification information unavailable in a passenger information database system can be requested and provided for a passenger of the account. Validity of the verification information can be determined using a verification service and stored in a passenger information database. A decision for the trip order can be determined based on the validity of the verification information stored in the passenger information database.

Abstract: Incidents may be monitored using a camera in response to an activation of a trigger device. Trigger data may be received over a communication network in response to activation of a trigger device disposed within a first area of a vehicle. A camera disposed within a second area of the vehicle may be controlled over the communication network in response to receiving the trigger data, the controlling causing the camera to capture sensor information of a passenger of the vehicle. Passenger information of the passenger of the vehicle may be obtained in response to receiving the trigger data. An alert notification may be generated. The alert notification may comprise at least a portion of the sensor information of the passenger, and the alert notification may be capable of initiating one or more incident actions associated with the passenger.

Abstract: A local activation method and system based on a binary neural network, said method including: during forward propagation, comparing the difference between a center pixel and an adjacent pixel to determine a local activation value; during forward propagation, setting an appropriate number of local activation channels and an activation direction to obtain a local activation feature map having different activation directions; during forward propagation, using weighting coefficients, which can be learned, to perform channel fusion on the output feature map after local activation and direct activation, and obtaining an output feature map containing both texture features and contour features; during backpropagation, using an asymptotic sine function to update the weights of the binary neural network.

Abstract: One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to regularizing semantic similarity relationships relative to a pair of languages. A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise a computation component that generates a transformation comprising a semantic similarity relationship between detected semantic labels of a pair of languages.

Abstract: After determining a trip order has a high risk, verification information unavailable in a passenger information database system can be requested and provided for a passenger of the account. Validity of the verification information can be determined using a verification service and stored in a passenger information database. A decision for the trip order can be determined based on the validity of the verification information stored in the passenger information database.

Abstract: Systems and techniques that facilitate parameterized neighborhood memory adaptation for semantic role labeling are provided. In various embodiments, a system can comprise a receiver component that can access a semantic role labeling model trained on a training dataset. In various aspects, the system can further comprise an execution component that can retrain a labeler of the semantic role labeling model based on a set of neighborhood parameters learned from the training dataset. In various instances, the execution component can execute, after retraining, the semantic role labeling model on an inputted sentence.

Abstract: Dynamic geofence zones may be deployed and updated for a ride sharing service. At least one set of dynamic geofence zones may be created which are associated with a ride sharing service. At least one time period may be set for the at least one set of dynamic geofence zones. The at least one set of dynamic geofence zones may be deployed. The at least one set of dynamic geofence zones may be updated.

Abstract: After determining a trip order has a high risk, verification information unavailable in a passenger information database system can be requested and provided for a passenger of the account. Validity of the verification information can be determined using a verification service and stored in a passenger information database. A decision for the trip order can be determined based on the validity of the verification information stored in the passenger information database.

Abstract: Systems and methods are provided for data security grading. An exemplary method for data security grading, implementable by a computer, may comprise receiving a request to access a query data field, searching for the query data field from a security level table, in response to finding the query data field from the security level table, obtaining from the security level table a security level corresponding to the query data field, and in response to not finding the query data field from the security level table, determining a security level corresponding to the query data field based at least on a lineage tree and the security level table. The lineage tree may trace the query data field to one or more source data fields, and the security data level table may comprise one or more security levels corresponding to the one or more source data fields.

Abstract: Technology for selecting a correct answer (for example, a correct label for a data set to be used in machine learning algorithms) from among a plurality of candidate answers, where the answers selected relatively infrequently by a plurality of human evaluators are cold from the full plurality of candidate answers to obtain a reduced subset of candidate answers. In this way, further selection of the correct answer (for example, ultimate selection of the correct answer by a human expert) will only need to consider the reduced subset, thereby potentially saving time and effort in the selection of the correct answer.

Abstract: Providing a predictive model for a target language by determining an instance weight for a labeled source language textual unit according to a set of unlabeled target language textual units, scaling, by the one or more computer processors, an error between a predicted label for the source language textual unit and a ground-truth label for the source language textual unit according to the instance weight, updating, by the one or more computer processors, network parameters of a predictive neural network model for the target language according to the error, and providing, by the one or more computer processors, the predictive neural network model for the target language to a user.

Abstract: Safety geofence zones may be created and deployed for a ride sharing service. At least one set of safety geofence zones may be created which are associated with a ride sharing service. A zone type may be set for each set of safety geofence zones in the at least one set of safety geofence zones. At least one trigger condition may be set for the at least one set of safety geofence zones. The at least one set of safety geofence zones may be deployed.

Abstract: Incidents may be monitored using a camera in response to an activation of a trigger device. Trigger data may be received over a communication network in response to activation of a trigger device disposed within a first area of a vehicle. A camera disposed within a second area of the vehicle may be controlled over the communication network in response to receiving the trigger data, the controlling causing the camera to capture sensor information of a passenger of the vehicle. Passenger information of the passenger of the vehicle may be obtained in response to receiving the trigger data. An alert notification may be generated. The alert notification may comprise at least a portion of the sensor information of the passenger, and the alert notification may be capable of initiating one or more incident actions associated with the passenger.

Abstract: A computer-implemented method according to one embodiment includes identifying features of a plurality of data instances within a target domain; assigning weights to the plurality of data instances within the target domain, based on similarities among the features; selecting a subset of the plurality of data instances within the target domain, based on the weights; associating expert annotations with respective ones of data instances within the subset; and training a machine learning algorithm, utilizing the subset of the plurality of data instances and associated expert annotations.

Abstract: Incidents may be monitored using a camera in response to an activation of a trigger device. Trigger data may be received over a communication network in response to activation of a trigger device disposed within a first area of a vehicle. A camera disposed within a second area of the vehicle may be controlled over the communication network in response to receiving the trigger data, the controlling causing the camera to capture sensor information of a passenger of the vehicle. Passenger information of the passenger of the vehicle may be obtained in response to receiving the trigger data. An alert notification may be generated. The alert notification may comprise at least a portion of the sensor information of the passenger, and the alert notification may be capable of initiating one or more incident actions associated with the passenger.

Abstract: Methods, systems, and computer program products for constraint tracking and inference generation are provided herein. A computer-implemented method includes parsing descriptions of one or more user-provided constraints pertaining to data within a target system, parsing truth value assignments to the user-provided constraints, and deriving a truth value for at least one of the user-provided constraints that does not correspond to a known truth value, wherein said deriving comprises performing a logical inference utilizing known truth values of one or more of the user-provided constraints. The computer-implemented method also includes storing, in a database, (i) the user-provided constraints, (ii) the known truth values, and (iii) the at least one derived truth value, and outputting the at least one derived truth value, one or more identified contradictions among the known truth values, and/or an indication that one or more unknown truth values corresponding to the user-provided constraints remain unknown.

Abstract: A computer-implemented method according to one embodiment includes identifying features of a plurality of data instances within a target domain; assigning weights to the plurality of data instances within the target domain, based on similarities among the features; selecting a subset of the plurality of data instances within the target domain, based on the weights; associating expert annotations with respective ones of data instances within the subset; and training a machine learning algorithm, utilizing the subset of the plurality of data instances and associated expert annotations.

Abstract: Incidents may be monitored using a camera in response to an activation of a trigger device. Trigger data may be received over a communication network in response to activation of a trigger device disposed within a first area of a vehicle. A camera disposed within a second area of the vehicle may be controlled over the communication network in response to receiving the trigger data, the controlling causing the camera to capture sensor information of a passenger of the vehicle. Passenger information of the passenger of the vehicle may be obtained in response to receiving the trigger data. An alert notification may be generated. The alert notification may comprise at least a portion of the sensor information of the passenger, and the alert notification may be capable of initiating one or more incident actions associated with the passenger.