Abstract: An approach is provided for stop classification and journey extraction from vehicle location trace data. The approach involves, for example, processing vehicle location trace data to determine a sequence of vehicle stop locations. The sequence of vehicle stop locations comprises a first stop location, a second stop location, and a third stop location in chronological order. The approach also involves determining a first route cost (e.g., a first route length) from the first stop location to the third stop location via the second stop location and a second route cost (e.g., a second route length) from the first stop location directly to the third stop location. The approach further involves determining a classification of the second stop location as either a task stop or a rest stop based, at least in part, on a comparison of the first route length and the second route length.

Abstract: A method includes analyzing, via a first capturing agent, packets processed in a first environment associated with a first host to yield first data. The method includes analyzing, via a second capturing agent, packets processed by a second environment associated with a second host to yield second data, collecting the first data and the second data at a collector to yield aggregated data, transmitting the aggregated data to an analysis engine which analyzes the aggregated data to yield an analysis. Based on the analysis, the method includes identifying first packet loss at the first environment and second packet loss at the second environment.

Abstract: A method may include receiving training data comprising a time series of gaps between an ego vehicle and one or more lead vehicles at a plurality of time steps, embedding the training data into a fixed-length sequence, inputting the fixed-length sequence into a Transformer-RNN model comprising a Transformer component and an RNN component, wherein the transformer component applies attention to each data point of the fixed-length sequence based on a fixed number of previous inputs, and training the Transformer-RNN model, using the training data, to output a predicted gap at a future time step based on an input sequence of gaps.

Abstract: A method may include learning reward functions for a plurality of first vehicles based on first vehicle data associated with the plurality of first vehicles using inverse reinforcement learning, associating each vehicle of the plurality of first vehicles with one cluster among a plurality of clusters based on the reward functions, determining a centroid reward function for each of the clusters based on the reward functions associated with each cluster, performing a comparison between second vehicle data associated with a second vehicle and the first vehicle data, determining a vehicle among the plurality of first vehicles having associated first vehicle data that is most similar to the second vehicle data based on the comparison, associating the second vehicle with the cluster associated with the determined vehicle, and controlling operation of the second vehicle based on the centroid reward function of the cluster associated with the second vehicle.

Abstract: Systems and methods for cloud security monitoring and threat intelligence in accordance with embodiments of the invention are disclosed. In one embodiment, a process for monitoring and remediation of security threats includes generating a threat model using a first portion of activity data, identifying, based upon the threat model, a threat using a second portion of activity data, selecting a security policy to implement in response to the identified threat, identifying cloud security controls in a remotely hosted cloud application server system to modify in accordance with the selected security policy, establishing a secure connection to the remotely hosted cloud application server system using login credentials associated with a tenant account with the cloud application, and sending instructions to the remotely hosted cloud application server system to set the identified cloud security controls with respect to the tenant account in accordance with the selected security policy.

Abstract: Methods and server systems for computing fraud risk scores for various merchants associated with an acquirer described herein. The method performed by a server system includes accessing merchant-related transaction data including merchant-related transaction indicators associated with a merchant from a transaction database. Method includes generating a merchant-related transaction features based on the merchant-related indicators. Method includes generating via risk prediction models, for a payment transaction with the merchant, merchant health and compliance risk scores, merchant terminal risk scores, merchant chargeback risk scores, and merchant activity risk scores based on the merchant-related transaction features. Method includes facilitating transmission of a notification message to an acquirer server associated with the merchant.

Abstract: Systems and methods are provided herein to dynamically update content restrictions for multiple users by detecting a first user in the proximity of a media device playing a first content item and detecting a second user entering the proximity of the media device. In response to detecting a second user entering the proximity of the media device and receiving a command from the first user that controls playing the first content, the system modifies a stored relationship between the first user and the second user to track the relationship between the first user and the second user. Thereafter, when the system detects the first user and the second user in the proximity of a media device playing a second content, in response, the system automatically performs an action that controls the playing of the second content (e.g., without user having to issue those commands).

Abstract: An example operation includes one or more of receiving an opt-in request to display information on a display of a vehicle configured to be viewed from outside of the vehicle, authenticating the request to allow displaying information on the display, determining information associated with the vehicle to be displayed on the display, determining misuse of the information displayed on the display based on a notification from another vehicle, and flagging the misuse.

Abstract: An approach is provided for machine learning-based prediction of an estimated time of arrival (ETA) or any other trip characteristic. The approach involves, for example, receiving a request for an ETA (or any other trip characteristic). The request specifies an origin, a destination, and a time of departure. The approach also involves discretizing the origin to an origin ETA homogenous zone and the destination to a destination ETA homogenous zone. The approach further involves determining one or more features of one or more pre-computed k-shortest paths for an origin-destination (O-D) zone pair comprising the origin ETA homogenous zone and the destination ETA homogenous zone. The approach further involves providing the one or more features as an input to a trained machine learning to predict the ETA of the trip (or any other trip characteristic).

Abstract: A system and method of automated driver selection is disclosed. A plurality of driver profiles and a first order are received. Each of the driver profiles includes at least one driver parameter. The first order includes at least one order parameter. A driver score is calculated for each of the plurality of driver profiles for the first order. The driver score is calculated based on the at least one driver parameter and the at least one order parameter. Each driver profile is ranked based on the calculated driver score and a first delivery assignment request is transmitted to a system associated with a first-ranked driver profile. A response is received to the first delivery assignment request.

Abstract: An approach is provided for spatial aggregation for location based services. The approach involves, for example, determining a plurality of partitions for a geographic area. The approach also involves determining a set of destinations that is common to a first partition and a second partition of the plurality of partitions. The set of destinations are associated with a plurality of trips originating from first partition, the second partition, or a combination thereof. The approach further involves determining a statistical property of the plurality of trips between any of the set of destinations and the first partition, the second partition, or a combination thereof. The approach further involves merging the first partition with the second partition into the traffic analysis zone based on the statistical property.

Abstract: A hybrid deterministic override to cloud based probabilistic advanced driver assistance systems. Under default driving conditions, an ego vehicle is controlled by a probabilistic controller in a cloud. An overall gap between the ego vehicle and a leading vehicle is divided into an emergency collision gap and a driver specified gap. The vehicle sensors monitor the overall gap. When the gap between the ego vehicle and the leading vehicle is less than or equal to the emergency collision gap, a deterministic controller of the ego vehicle overrides the cloud based probabilistic controller to control the braking and acceleration of the ego vehicle.

Abstract: Systems and methods for unifying business records data from different database sources into a common format in the same repository are disclosed. In one embodiment, a process includes receiving, by an integration platform system, a first set of business records data from a customer records system, where the business records data includes records in a first format, identifying a first transformation rule corresponding to the first format using the integration platform system, where the first transformation rule includes information for converting data from the first format to a unified format, converting each record in the first set of business records from the first format to the unified format by the integration platform system using the first transformation rule, and storing the first set of converted records in the unified format in a business records database.

Abstract: The present disclosure is generally directed to media systems configured to receive and play live media content. In particular, methods and systems are provided for a multi-screen content playback experience for time shifted live stream content. Systems and methods are provided herein for generating for display a catch-up video (e.g., a segment of a live stream stored as URLs on a local device during the time the live stream was interrupted) in a picture-in-picture (PIP) window, and generating the PIP catch-up window and the live window for simultaneous display.

Abstract: The disclosure generally includes systems and methods of generating a preferred personalized adaptive cruise control (P-ACC) mode of operation. The method includes capturing vehicle data using one or more internal and external vehicle sensors, and adjusting one or more P-ACC mode of operation parameters, based on captured vehicle data, before operation of the P-ACC mode of operation. Vehicle data includes internal vehicle data comprising a type of passenger and number of passengers in the vehicle.

Abstract: A method for managing moving agents is provided. The method comprises identifying goods agents, moving agents, and a plurality of requests within a predetermined area, generating a nodal graph including the moving agents, requests, and goods as vertices and edges defining relations between two vertices, obtaining actions for the moving agents by inputting the nodal graph to a reinforcement-learning based graphical neural network model stored in the moving agents, the reinforcement-learning based graphical neural network outputs the action for the moving agent in response to receiving the nodal graph, and instructing the moving agents to operate based on the actions to satisfy at least one of the plurality of requests.

Abstract: Methods, vehicles, and systems described herein generate alerts based on a generated macro state level indicative of a traffic hazard risk in view of a set of parameters which may lead driver to make various sub-conscious decisions. The set of parameters can include at least one of a vehicle parameter, driver state parameter, or external parameter.

Abstract: Described herein is a release coating comprising a blend of: (a) a first polymer, wherein the first polymer is a silicone-containing (meth)acrylic polymer; and (b) a second polymer, wherein the second polymer comprises the polymerization reaction product of: (i) a first monomer having an alkyl group with 12 to 24 carbon atoms, a linking group containing a nitrogen or ester group, and a free-radically polymerizable (meth)acryl group; and (ii) a second free-radically polymerizable monomer having less than 12 carbon atoms. Such release coatings can be coated onto a substrate and used as a release coating for pressure sensitive adhesives.

Abstract: Systems, methods, and other embodiments described herein relate to generating a notification about a risk of a target vehicle toppling over due to wind. In one embodiment, a method includes determining a wind force of the wind at a location of the target vehicle and determining one or more characteristics of the target vehicle. The method includes determining whether there is a risk of the target vehicle toppling over based on the wind force of the wind and the one or more characteristics of the target vehicle. The method includes generating a notification about the risk.

Abstract: Bid values submitted for various keywords can take into account the recovery propensity between paid search and organic search. When submitting a bid to a search engine provider for a keyword, an entity may get a certain level of performance in return. If not submitting a bid, however, the entity will likely still get some level of performance, although likely less than for paid search. In order to optimize for a parameter such as impressions, purchases, or profit, the recovery propensity can be taken into account in order to adjust the bid price, taking into account the relative performance of paid and organic search and then optimizing for the determined goal. Organic search data in some embodiments can be obtained through testing or modeling, or a combination thereof.