Abstract: Disclosed herein are methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for modeling agents in multi-agent systems as reinforcement learning (RL) agents and training control policies that cause the agents to cooperate towards a common goal. A method can include generating, for each of a group of simulated local agents in an agent network in which the simulated local agents share resources, information, or both, experience tuples having a state for the simulated local agent, an action taken by the simulated local agent, and a local result for the action taken, updating each local policy of each simulated local agent according to the respective local result, providing, to each of the simulated local agents, information representing a global state of the agent network, and updating each local policy of each simulated local agent according to the global state of the agent network.

Abstract: A root portion of a root-analog dental implant may include a core positioned in an approximate center of the root portion of the dental implant. The core may provide mechanical strength and/or support for the dental implant and may include one or more struts. The root-analog dental implant may further include a porous surface positioned on a portion of a vertically oriented exterior surface of the core. The struts may be configured and arranged to provide mechanical strength and/or support for the root-analog dental implant.

Abstract: A hanger assembly includes: a main body; a lock ring coupled to the main body and configured to expand radially outward into a profile on an inner diameter of the wellhead; and an actuator, wherein the actuator is capable of transferring an axial force from the actuator into outward radial expansion of the lock ring toward the profile on the inner diameter of the wellhead. An interface between the actuator and the lock ring is shaped such that: axially downward movement of the actuator from a starting position to an intermediate position actuates the lock ring into the profile; and axially downward movement of the actuator from the intermediate position to a pre-load position applies a pre-load to the hanger assembly.

Abstract: Methods and apparatus consistent with the invention provide the ability to organize, index, search, and present time series data based on searches. Time series data are sequences of time stamped records occurring in one or more usually continuous streams, representing some type of activity. In one embodiment, time series data is stored as discrete events time stamps. A search is received and relevant event information is retrieved based in whole or in part on the time stamp, a keyword indexing mechanism, or statistical indices calculated at the time of the search.

Abstract: Methods, apparatus, systems, and articles of manufacture to perform computer-based monitoring of audiences of network-based media using information theory to estimate intermediate level unions are disclosed. An example apparatus to determine a deduplicated, census-based audience metric of media includes panel union calculator circuitry to calculate a threshold statistic corresponding to an intermediate union of a panel hierarchy, and census union calculator circuitry to calculate a deduplicated audience value corresponding to the intermediate union of the census hierarchy based on the threshold statistic.

Abstract: A device to assemble a skin and a frame of an aircraft fuselage. The device includes first and second brace members that extend along opposing sides of a gap. Arches are spaced apart and fixedly connected to the first and second brace members and that extend across the gap. A strongback is attached to and movable along the first and second brace members with the strongback having a curved shape that matches the plurality of arches. The strongback includes clamps configured to engage with the frame. First and second tension devices apply tension to the skin at the strongback.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to estimate population reach from marginals. Example apparatus disclosed herein are to determine an audience relationship value based on first audience exposure values for a recorded audience of a media and a first de-duplicated audience value for the recorded audience of the media, determine bounds of a pseudo universe estimate of a population audience of the media based on the audience relationship value and second audience exposure values for the population audience of the media, and iteratively determine the pseudo universe estimate of the population audience and a second de-duplicated audience value for the population audience of the media based on the audience relationship value and the second audience exposure values, the pseudo universe estimate of the population audience to be within the bounds.

Abstract: Systems, methods, and corresponding computer-readable media for multi-modal hierarchical semantic search of electronic documents. Systems in accordance with the disclosure comprise search engine controllers, any desired numbers of search engine interface controllers, and persistent data stores accessible by the search engine controllers. The controllers are configured to parse searchable document data sets to extract document object data sets. Each document object data set can represent textual and/or image feature of the document. For each document object data sets the controller generates at least one enriched document object data set, and forms at least one of a document graph or index. In response to search requests, the search controller compares document graphs or indexes to identify the most similar documents.

Abstract: Techniques are described herein for evaluating user activities on a website for detecting and alerting anomalies with the website. For example, an alerting system may determine a set of time-windows for each of a set of attribute value(s) and use a set of performance metrics and/or web session events for the time-windows from historical web sessions to detect an anomaly in a current time-window. The alerting system may determine an evaluation range based on weighted performance ranges, and alert a client indicating a performance anomaly if a performance metric at the time of evaluation are out of the evaluation range. Attribute value(s) related to a website issue can be identified based on a correlated to anomalous web session events or to an anomalous time-window.

Abstract: Techniques are described herein for evaluating user activities on a website for detecting and alerting anomalies with the website. For example, an alerting system may determine a set of time-windows for each of a set of attribute value(s) and use a set of performance metrics and/or web session events for the time-windows from historical web sessions to detect an anomaly in a current time-window. The alerting system may determine an evaluation range based on weighted performance ranges, and alert a client indicating a performance anomaly if a performance metric at the time of evaluation are out of the evaluation range. Attribute value(s) related to a website issue can be identified based on a correlated to anomalous web session events or to an anomalous time-window.

Abstract: An example robot performs a scan to obtain image data of a given region. The robot performs image analysis on the image data to detect a set of undesirable objects, and generates a reference map that excludes the set of undesirable objects, where the reference map is associated with the location of the robot at the time of the scan.

Abstract: Examples of neural networks trained for multiple tasks are described herein. In some examples, a method may include determining a feature vector using a first portion of a neural network. In some examples, the neural network is trained for multiple tasks. Some examples of the method may include transmitting the feature vector to a remote device. In some examples, the remote device is to perform one of the multiple tasks using a second portion of the neural network.

Abstract: An example control system includes a memory and at least one processor to obtain image data from a given region and perform image analysis on the image data to detect a set of objects in the given region. For each object of the set, the example control system may classify each object as being one of multiple predefined classifications of object permanency, including (i) a fixed classification, (ii) a static and fixed classification, and/or (iii) a dynamic classification. The control system may generate at least a first layer of a occupancy map for the given region that depicts each detected object that is of the static and fixed classification and excluding each detected object that is either of the static and unfixed classification or of the dynamic classification.

Abstract: A method includes receiving, with a computing device, a configuration file and a client request to apply a machine learning model to a set of data from a sensor. The method includes performing, with the computing device, preprocessing on the set of data from the sensor based on the configuration file to generate preprocessed data. The method includes sending, with the computing device, a call to a model server to apply the machine learning model to the preprocessed data.

Abstract: The rack mounted weather shield is an awning. The rack mounted weather shield is configured for use with an automobile. The rack mounted weather shield attaches to a cargo rack. The rack mounted weather shield creates a weather protected space along a side of the automobile. The rack mounted weather shield is used for entering and exiting the automobile in inclement weather. The rack mounted weather shield extends and retracts. The rack mounted weather shield comprises a plurality of fans, a plurality of control circuits, and a remote control. Each of the plurality of fans creates the weather protected space on a side of the automobile. Each of the plurality of control circuits extends and retracts an individual fan selected from the plurality of fans. The remote control is a radio frequency device that controls the operation of the plurality of control circuits.

Abstract: Techniques are described herein for evaluating user activities on a website for detecting and alerting anomalies with the website. For example, an alerting system may determine a set of time-windows for each of a set of attribute value(s) and use a set of performance metrics and/or web session events for the time-windows from historical web sessions to detect an anomaly in a current time-window. The alerting system may determine an evaluation range based on weighted performance ranges, and alert a client indicating a performance anomaly if a performance metric at the time of evaluation are out of the evaluation range. Attribute value(s) related to a website issue can be identified based on a correlated to anomalous web session events or to an anomalous time-window.

Abstract: The invention generally relates to methods and systems for adding chemicals to a body of water through a skimmer basket in a strainer well associated with the body of water.

Abstract: A method includes receiving, with a computing device, a first client request from a first client that identifies a machine learning model and a sensor. The method includes sending, with the computing device, a call to a server to apply the identified machine learning model to a set of data from the identified sensor, in response to the first client request. The method includes receiving, with the computing device, a second client request from a second client that identifies a same machine learning model and sensor as the first client request. The method includes sending, with the computing device, response data from the identified machine learning model to both the first client and the second client without sending an additional call to the server in response to the second client request.

Abstract: A method includes receiving, with a computing device, a configuration file and a client request to apply a machine learning model to a set of data from a sensor. The method includes performing, with the computing device, preprocessing on the set of data from the sensor based on the configuration file to generate preprocessed data. The method includes sending, with the computing device, a call to a model server to apply the machine learning model to the preprocessed data.