Abstract: Embodiments of the present disclosure provide systems, methods, and devices for utilizing an application to alert a user to detected changes to inventory data. Example embodiments relate to a predictive model and development of a predictive model using machine learning techniques. Example embodiments of systems and methods may utilize web-based applications and plug-ins, extensions, or add-ons thereof for facilitating communication and presenting dynamic information to a user.

Abstract: Systems and methods herein describe privacy preserving multi-touch attribution. The described systems access a plurality of impression events and a plurality of conversion events, and for each impression event and each conversion event, wherein each impression event and each conversion event are associated with user identifiers, the described systems generates a hashed user identifier based on the associated user identifier, initiates a key agreement protocol comprising a key, generates an encrypted identifier by encrypting the hashed user identifier with the key, and stores the encrypted identifier.

Abstract: A method, computer program product, and computer system are provided for container cross-cluster capacity scaling. The method includes broadcasting local capacity information of capacity availability or capacity requirement for the local cluster and receiving broadcasts from each of one or more other clusters providing capacity information including capacity availability or capacity requirements. The method may map the received capacity information with the local capacity information and may determine a suitable cross-cluster capacity sharing when a capacity requirement of the local cluster maps to a capacity availability of another cluster or when a capacity availability of the local cluster maps to a capacity requirement of another cluster. The method may coordinate the deallocation of a node from the cluster having the capacity availability and reallocation of the node to the cluster having the capacity requirement.

Abstract: Systems and methods herein describe privacy preserving multi-touch attribution. The described systems access a plurality of impression events and a plurality of conversion events, and for each impression event and each conversion event, wherein each impression event and each conversion event are associated with user identifiers, the described systems generates a hashed user identifier based on the associated user identifier, initiates a key agreement protocol comprising a key, generates an encrypted identifier by encrypting the hashed user identifier with the key, and stores the encrypted identifier.

Abstract: Embodiments disclosed herein generally relate to a method and system for generating a container image. A computing system receives a request from a remote computer to provision a container comprising a machine learning model. The computing system generates a first API accessible by the remote computer. The computing system receives one or more parameters for the container via the API. The one or more parameters include a machine learning model type. The computing system retrieves from a library of a plurality of machine learning models a machine learning model corresponding to a type of model specified in the one or more parameters. The computing system generates a container image that includes the machine learning model. The computing system provisions a container based on the container image.

Abstract: Systems and methods for providing improved recommendations are disclosed. In some embodiments, the systems and methods may be used for vehicle recommendations. The system may include a server system configured to receive user historical vehicle preferences, user vehicle preferences, generate weighted feature data sets, and apply a similarity model to the generated weighted feature data set in order to determine a vehicle recommendation data set. A visual representation of the vehicle recommendation data set may then be provided to an interface associated with a user.

Abstract: A device may determine that a user has a threshold level of interest in a type of product. The device may receive an image of a face of the user, may perform a facial recognition analysis of the image, and may determine identification information of the user based on the facial recognition analysis. The device may identify account information associated with the user based on the identification information and may identify a product in an inventory that is associated with the type of product. The device may perform a preauthorization process associated with a transaction involving the product and the user based on the account information, and may perform an action associated with the transaction based on the preauthorization process.

Abstract: Road vector definitions and incident data associated with a traffic incident are obtained from a traffic data source. A determination is made, based on the road vector definitions and the incident data, that the traffic incident affects travel on a particular road. A road classification of the road affected by the traffic incident is determined based on the road vector definitions. An updated version of a previous Transport Protocol Experts Group (TPEG) traffic is generated. Generating the updated version of the previous TPEG traffic frame includes conditionally inserting changed traffic data associated with the particular road into the previous TPEG traffic frame. The changed traffic data associated with the particular road includes at least a portion of the incident data. The updated version of the previous TPEG traffic frame is transmitted to a station importer for broadcast.

Abstract: A device may determine that a user has a threshold level of interest in a type of product. The device may receive an image of a face of the user, may perform a facial recognition analysis of the image, and may determine identification information of the user based on the facial recognition analysis. The device may identify account information associated with the user based on the identification information and may identify a product in an inventory that is associated with the type of product. The device may perform a preauthorization process associated with a transaction involving the product and the user based on the account information, and may perform an action associated with the transaction based on the preauthorization process.

Abstract: Transport Protocol Experts Group (TPEG) traffic messages, which include traffic information associated with road vector definitions, are generated. Bounding area definitions associating the road vector definitions with bounding areas are obtained, and automatically adjusted based on a time associated with broadcast of the TPEG traffic messages. TPEG traffic messages to be included in a TPEG frame associated with a particular bounding area are selected based on the bounding area definitions. The TPEG frame is generated, and transmitted for broadcast in the particular bounding area.

Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include compiling cost data for at least one node and revenue data for at least one pod. The operations may include calculating a resource value of a node of the at least one node with the cost data and quantifying a priority value of a pod of the at least one pod with the revenue data. The operations may include pairing the priority value of the pod with the resource value of the node and assigning the pod to the node.

Abstract: A boundary specifying a bounded geographic area for which travel information is to be reported is generated. Flow section information associated with flow sections located within the boundary is obtained. The flow sections represent portions of one or more roadways assigned relevant functional road classes (FRCs). The flow section information includes information about traffic flow associated with the flow sections. FRC current traffic messages, which include non-predictive traffic information associated with roadway portions that are in the bounded geographic area and are assigned relevant FRCs, are combined with the flow section information to generate a first data group. The first data group is streamed to a first traffic message service.

Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include monitoring a container. The operations may further include identifying a usage variance of the container based on consumption information for the container. The operations may also include managing an uptime of the container based on the usage variance.

Abstract: A device receives, from a user device, a request to prune a primary database, and receives primary database information associated with the primary database and secondary database information associated with a secondary database that is different than the primary database. The device processes the primary database information and the secondary database information, with a machine learning model, to generate suggested pruning parameters, and provides the suggested pruning parameters to the user device. The device receives selected pruning parameters from the user device, where the selected pruning parameters are selected from the suggested pruning parameters or are input via the user device. The device removes pruned information from the primary database based on the selected pruning parameters, and provides the pruned information to the secondary database based on the selected pruning parameters.

Abstract: Travel-related-information messages (TRIMS) are received from one or more information sources, and information included in the messages is separated into a first (e.g. TPEG™) or second (e.g. TPEG+) group. A broadcast area to which the information included in the TRIMs is to be broadcast is determined. A further determination indicates that a subset of information assigned to the first group is to be reassigned to the second group. The subset of information is reassigned from the first group to the second group based on parameters associated with the broadcast area. The information included in the first group and the second group is delivered to one or more processing modules that generate a first TRIM reporting message using information included in the first group and a second TRIM reporting message using information included in the second group.

Abstract: Methods of treating cancer with particular doses of anti-ICOS antibodies are provided.

Abstract: Embodiments of the present disclosure provide systems, methods, and devices for utilizing an application to alert a user to detected changes to inventory data. Example embodiments relate to a predictive model and development of a predictive model using machine learning techniques. Example embodiments of systems and methods may utilize web-based applications and plug-ins, extensions, or add-ons thereof for facilitating communication and presenting dynamic information to a user.

Abstract: Embodiments of the present disclosure provide systems, methods, and devices for utilizing an application to alert a user to detected changes to inventory data. Example embodiments relate to a predictive model and development of a predictive model using machine learning techniques. Example embodiments of systems and methods may utilize web-based applications and plug-ins, extensions, or add-ons thereof for facilitating communication and presenting dynamic information to a user.

Abstract: A method provides personalized recommendations to a mobile device associated with a user. The method includes obtaining an event log from the one or more sensors embedded in the mobile device associated with the user. The event log is analyzed by a processor of the present invention to identify one or more attributes associated with the surroundings of the mobile device. A method selects one or more recommendations to be sent to the mobile device associated with the user. In additional embodiments, methods record the response received to the recommendations and using the recorded responses to further select more personalized recommendations.

Abstract: According to a method disclosed herein, Transport Protocol Experts Group (TPEG) traffic messages, which include traffic information associated with road vector definitions, are generated. bounding area definitions associating the road vector definitions with bounding areas are obtained, and automatically adjusted based on a time associated with broadcast of the TPEG traffic messages. TPEG traffic messages to be included in a TPEG frame associated with a particular bounding area are selected based on the bounding area definitions. The TPEG frame is generated, and transmitted for broadcast in the particular bounding area.