Abstract: The present invention sets forth a technique for performing workflow orchestration in disparate computer systems and software applications using a universal state manager. This technique includes generating a unique job identifier for a requested automation workflow. The technique also includes retrieving a workflow template specifying phases and tasks associated with the requested automation workflow. The technique further includes associating one or more reference IDs generated by one or more system components to the unique job identifier, wherein each of the one or more system components performs at least a subset of tasks specified in the one or more phases. The technique further includes aggregating status reports generated by the one or more system components, correlating each status report with a corresponding reference ID associated with the system component that generated the status report, and generating a status of the requested automation workflow based on the status reports.

Abstract: A platform and components for an automated consumer retail utility marketplace are provided, including components for machine learning, components for gamification, and components for supporting a related consumer mobile application that enables improved visibility and control by a consumer over its interaction with energy markets.

Abstract: The present disclosure provides a system and method using a charge collection antenna in a wearable device to collect charge variation based on a user's jawbone and muscle motion. The collected charge variation may be used to determine an on-body status of the wearable device. For example, in wireless earbuds, information acquired from a charge collection antenna may be used to determine whether the earbud is worn in-ear by the user. The collected charge variation may also be used to detect jaw motion by the user.

Abstract: A platform and components for an automated consumer retail utility marketplace are provided, including components for machine learning, components for gamification, and components for supporting a related consumer mobile application that enables improved visibility and control by a consumer over its interaction with energy markets.

Abstract: This disclosure describes apparatuses, methods, and techniques for supporting a parallel decode instruction set computer architecture with variable-length instructions. In various aspects, a processor receives an instruction for execution. A decoder identifies multiple fixed-length prefixes in the instruction and identifies multiple variable-length suffixes in the instruction. Each of the multiple fixed-length prefixes is associated with one of the variable-length suffixes. The instruction is then executed based on the plurality of variable-length suffixes. By so doing, the described systems and methods may be implemented in a manner that reduces program size and reduces the required area on the silicon chip.

Abstract: A low torque rotary valve for a vehicle cooling system is provided. The rotary valve includes a tapered valve body that can be lifted during rotation and thereafter seated after being rotated the desired amount. An axial surface of the tapered valve body is in sliding contact with an axial surface of a valve housing or a rotatable disk. As the tapered valve body rotates, one or more ramped projections cause the tapered valve body to displace axially within the valve housing. The sealing members are uncompressed during rotation of the tapered valve body, and a lower torque demand is required, thereby allowing for a smaller and less costly motor actuator.

Abstract: A server provides image data including detailed geometry and shading information for one of more objects in a scene from a last known camera orientation and placement (a “first camera view”) and a height map indicating a distance from the first camera view to each pixel of the image. The image data and the height map are collectively referred to as a “parallax pixel map”. A client device receives the parallax pixel map from the server and updates the parallax pixel map based on a current camera orientation and placement (a “first camera view”). The client device projects the updated parallax pixel map onto the image of the scene based on the current camera view to generate a current display frame. The client device then provides the current display frame for display.

Abstract: A system and method that utilizes machine learning, volume prediction, input staffing and acuity data, and simulation data to align staffing coverage with forecasted coverage needs of an institution, such as a healthcare facility. The system can better match staffing coverage with staffing needs and patient demand resulting in cost savings and reducing the risk of overworking existing staff.

Abstract: A computer-implemented method may be used to manage access to data over a network. The method may include automatically reading a first dataset to infer one or more data types of data within the first dataset and making a data product available over the network. The data product may include at least part of the first dataset. The method may further include receiving a first search query from a user specifying one or more attributes of data desired by the user. The attributes may be based on the data types. The method may further include, responsive to the first search query, identifying a first subset of the first dataset that possesses the attributes. Yet further, the method may include displaying results of the first search query for the user.

Abstract: A platform and components for an automated consumer retail utility marketplace are provided, including components for machine learning, components for gamification, and components for supporting a related consumer mobile application that enables improved visibility and control by a consumer over its interaction with energy markets.

Abstract: According to an aspect, a system includes a battery configured to be charged by a power source, a charging circuit coupled to the battery, and a battery charging manager configured to communicate with the charging circuit to control a charging of the battery by the power source. The battery charging manager obtains a charge pattern including an end charge time corresponding to a time when the battery is estimated to be disconnected from the power source. The battery charging manager controls the charging circuit to charge, over a first charging period, the battery to a temporary charge level, maintain, over a relaxation period, a battery charge level between the temporary charge level and a maintenance charge level, and charge, over a second charging period after the relaxation period, the battery to a maximum battery charge level before the end charge time.

Abstract: Embodiments are directed to monitoring network traffic. A monitoring engine may monitor network traffic associated with a plurality of entities in networks to provide metrics. And provide a device relation model based on the plurality of entities, the network traffic, and the metrics. An inference engine may associate each entity in the plurality of entities with an importance score based on the device relation model and the metrics such that each importance score is associated with a significance of an entity to operations of the networks. An alert engine may generate a plurality of alerts associated with the plurality of entities based on the metrics. And provide one or more alerts from the plurality of alerts to one or more users based on one or more ranked importance scores associated with one or more entities.

Abstract: A platform and components for an automated consumer retail utility marketplace are provided, including components for machine learning, components for gamification, and components for supporting a related consumer mobile application that enables improved visibility and control by a consumer over its interaction with energy markets.

Abstract: According to an aspect, a system includes a battery configured to be charged by a power source, a charging circuit coupled to the battery, and a battery charging manager configured to communicate with the charging circuit to control a charging of the battery by the power source. The battery charging manager obtains a charge pattern including an end charge time corresponding to a time when the battery is estimated to be disconnected from the power source. The battery charging manager controls the charging circuit to charge, over a first charging period, the battery to a temporary charge level, maintain, over a relaxation period, a battery charge level between the temporary charge level and a maintenance charge level, and charge, over a second charging period after the relaxation period, the battery to a maximum battery charge level before the end charge time.

Abstract: Embodiments are directed to monitoring network traffic associated with networks to provide metrics. A monitoring engine may determine an anomaly based on the metrics exceeding threshold values. An inference engine may be instantiated to provide an anomaly profile based on portions of the network traffic that are associated with the anomaly. The inference engine may provide an investigation profile based on the anomaly profile such that the investigation profile includes information associated with investigation activities associated with an investigation of the anomaly. The inference engine may monitor the investigation of the anomaly based on other portions of the network traffic such that the other portions of the network traffic are associated with monitoring an occurrence of the investigation activities. The inference engine may modify a performance score associated with the investigation profile based on the occurrence of the investigation activities and a completion status of the investigation.

Abstract: Embodiments are directed to monitoring network traffic. A monitoring engine may monitor network traffic associated with a plurality of entities in networks to provide metrics. And provide a device relation model based on the plurality of entities, the network traffic, and the metrics. An inference engine may associate each entity in the plurality of entities with an importance score based on the device relation model and the metrics such that each importance score is associated with a significance of an entity to operations of the networks. An alert engine may generate a plurality of alerts associated with the plurality of entities based on the metrics. And provide one or more alerts from the plurality of alerts to one or more users based on one or more ranked importance scores associated with one or more entities.

Abstract: According to an aspect, a system includes a battery configured to be charged by a power source, a charging circuit coupled to the battery, and a battery charging manager configured to communicate with the charging circuit to control a charging of the battery by the power source. The battery charging manager obtains a charge pattern including an end charge time corresponding to a time when the battery is estimated to be disconnected from the power source. The battery charging manager controls the charging circuit to charge, over a first charging period, the battery to a temporary charge level, maintain, over a relaxation period, a battery charge level between the temporary charge level and a maintenance charge level, and charge, over a second charging period after the relaxation period, the battery to a maximum battery charge level before the end charge time.

Abstract: Embodiments are directed to monitoring network traffic. A monitoring engine may monitor network traffic associated with a plurality of entities in networks to provide metrics. And provide a device relation model based on the plurality of entities, the network traffic, and the metrics. An inference engine may associate each entity in the plurality of entities with an importance score based on the device relation model and the metrics such that each importance score is associated with a significance of an entity to operations of the networks. An alert engine may generate a plurality of alerts associated with the plurality of entities based on the metrics. And provide one or more alerts from the plurality of alerts to one or more users based on one or more ranked importance scores associated with one or more entities.

Abstract: Embodiments are directed to monitoring network traffic associated with networks to provide metrics. A monitoring engine may determine an anomaly based on the metrics exceeding threshold values. An inference engine may be instantiated to provide an anomaly profile based on portions of the network traffic that are associated with the anomaly. The inference engine may provide an investigation profile based on the anomaly profile such that the investigation profile includes information associated with investigation activities associated with an investigation of the anomaly. The inference engine may monitor the investigation of the anomaly based on other portions of the network traffic such that the other portions of the network traffic are associated with monitoring an occurrence of the investigation activities. The inference engine may modify a performance score associated with the investigation profile based on the occurrence of the investigation activities and a completion status of the investigation.

Abstract: Embodiments are directed to monitoring network traffic using network computers. A monitoring engine may monitor network traffic associated with a plurality of entities in a network to provide metrics. A device relation model may be provided based on the plurality of entities, the network traffic, and the metrics. Interest information for a user may be provided based on one or more properties associated with the user. An inference engine may associate each entity in the plurality of entities with an interest score based on the interest information, the device relation model, and the metrics. An alert engine may generate a plurality of alerts associated with the plurality of entities based on the metrics. Some of the alerts may be provided to the user based on ranked interest scores associated with the entities.