Abstract: Systems and methods for initiating an action based on electronic activities of a user. Generally, a computing device receives a policy for enabling cryptographically secure tracking of electronic activities of a user and a particular electronic computing device. The policy can include definitions for a multiple actions to be taken with respect to certain electronic activities resulting from interaction by the user with the at least one computing device. The computing device can identify a particular electronic activity resulting from user interaction with the at least one computing device. The computing device can determine a particular action to take by applying the policy to the particular electronic activity. The computing device can initiate the particular action with respect to the particular electronic activity.

Abstract: Methods of embedding a heating circuit in an article fabricated by additive manufacturing. The methods describe techniques such as co-extruding a wire, capable of being heated, along with print material in additive manufacturing of the article, and placing a pre-shaped wire capable of being heated between adjacent layers of the article. A third method includes dispensing a wire, capable of being heated, during the additive manufacturing of the article, and compacting the wire into the printed material. An apparatus for embedding a heating circuit in an article fabricated by additive manufacturing. The apparatus contains a wire dispenser, a cutter to control the length of the wire dispensed, and a compactor capable of embedding the wire capable of being heated into the printed material. An article made by additive manufacturing is disclosed. The article contains at least one heating element embedded in the article during the additive manufacturing process.

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.

Abstract: Systems and techniques are disclosed for enabling structured data to be associated with visual content in a manner that preserves the ability to edit the visual content using a content application such as a notebook application. Techniques and systems enable semantic notation to be introduced into selected regions of the visual content that indicate the visual content's structured data, allowing the content to be searched and accessed more easily by common search technologies and search engines. The semantic notation is assigned to the visual content so that the introduction of the semantic notation does not hinder the user's viewing or editing of the visual content with a content application. The inclusion of the semantic notation does not cause existing visual editing tools that do not understand the semantic notation to cease to function properly.

Abstract: Embodiments are directed to monitoring network traffic using network computers. Monitoring triggers associated with one or more conditions and one or more actions may be provided. A monitoring engine may monitor information that is associated with network traffic associated with networks based on an inspection detail level. The monitoring engine may compare the monitored information to the conditions associated with the monitoring triggers. The monitoring engine may activate one or more monitoring triggers based on a result of the comparison. The monitoring engine may modify the inspection detail level based on the actions associated with the activated monitoring triggers to increase the amount of the information monitored by the monitoring engine. An analysis engine may provide analysis of the network traffic based on the monitored information.

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 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: A system and method for dynamically cancelling haptic feedback in certain areas of a touchpad, and/or to dynamically isolating haptic feedback in certain areas of the touchpad, may enhance flexibility, utility and functionality of the touchpad. A first haptic engine may generate and transmit haptic feedback in response to an input detected in an input area of the touchpad. A second haptic engine may generate haptic cancellation feedback, and transmit the cancellation feedback after a time delay, to cancel out the effect of the haptic feedback in a cancellation area of the touchpad. This may allow a user to experience the haptic feedback in response to an input in the input area, and to rest hand(s) on other portions of the touchpad display without feeling haptic feedback in the other portions of the touchpad.