Abstract: In various examples, physical sensor data may be generated by a vehicle in a real-world environment. The physical sensor data may be used to train deep neural networks (DNNs). The DNNs may then be tested in a simulated environment—in some examples using hardware configured for installation in a vehicle to execute an autonomous driving software stack—to control a virtual vehicle in the simulated environment or to otherwise test, verify, or validate the outputs of the DNNs. Prior to use by the DNNs, virtual sensor data generated by virtual sensors within the simulated environment may be encoded to a format consistent with the format of the physical sensor data generated by the vehicle.

Abstract: A compute server receives a request that triggers execution of a code piece out of multiple code pieces. A single process at the compute server executes the code piece, which is run in an isolated execution environment. Each other code piece runs in other isolated execution environments respectively and executed by the single process. The code piece, when executed, modifies a response to the request. The response is generated based at least in part on the executed code piece. The generated response is transmitted.

Abstract: Methods and systems are provided for allocating memory. An example method includes: allocating, for an application logic, a region of external primary memory included in a memory appliance; selecting, by a client device in response to a first request to reclaim a first portion of local primary memory in the client device, a portion of external primary memory from the region of external primary memory; copying data from the first portion of local primary memory to the portion of external primary memory; and converting a portion of a first virtual address space at the client device by remapping at least one virtual address in the first virtual address space at the client device from the first portion of local primary memory to the portion of external primary memory.

Abstract: An apparatus includes a plurality of solar panels, a horizontal scissor configured to support the plurality of solar panels, and an electronic drive motor that is configured to cause the horizontal scissor to extend or retract. The horizontal scissor includes a plurality of beams. The apparatus also includes a drive shaft and drive screw which are configured to extend or retract the horizontal scissor in response to movement of the electronic drive motor. The horizontal scissor and the electronic drive motor are coupled to a standard size unit shipping container. A first beam of the plurality of beams is made of a first material, and a second beam of the plurality of beams is made of a second material. The horizontal scissor is configured so that when fully retracted it fits into one half of the volume available inside the standard size shipping container.

Abstract: The present disclosure provides compositions, methods, systems, and devices for polynucleotide processing and analyte characterization. Such polynucleotide processing may be useful for a variety of applications, including analyte characterization by polynucleotide sequencing. The compositions, methods, systems, and devices disclosed herein generally describe barcoded oligonucleotides, which can be bound to a bead, such as a gel bead, useful for characterizing one or more analytes including, for example, protein (e.g., cell surface or intracellular proteins), genomic DNA, and RNA (e.g., mRNA or CRISPR guide RNAs). Also described herein, are barcoded labelling agents and oligonucleotide molecules useful for “tagging” analytes for characterization.

Abstract: An electrical distribution enclosure includes an electrically insulated panel defining an access portion of the enclosure and a load portion of the enclosure; at least one electrically insulated compartment panel positioned within the access portion; and two or more compartments within the access portion, each compartment separated from an adjacent compartment by an electrically insulated compartment panel, each of the two or more compartments having a front-accessible neutral connection, at least one front-accessible phase connection and a at least rear phase connection.

Abstract: In various examples, physical sensor data may be generated by a vehicle in a real-world environment. The physical sensor data may be used to train deep neural networks (DNNs). The DNNs may then be tested in a simulated environment—in some examples using hardware configured for installation in a vehicle to execute an autonomous driving software stack—to control a virtual vehicle in the simulated environment or to otherwise test, verify, or validate the outputs of the DNNs. Prior to use by the DNNs, virtual sensor data generated by virtual sensors within the simulated environment may be encoded to a format consistent with the format of the physical sensor data generated by the vehicle.

Abstract: A packaging system for fragile items comprising an outer box, a tray insert and a plurality of inner boxes. The system protects items during distribution, and easily convert into a display system for the items at the point of retail sale. Each item is contained in its own inner box, which includes one or more viewing windows to allow a purchaser easily to view the items. The inner boxes fit removably within paired holes in the tray insert, which provides multiple points of contact to hold the boxes in place, yet allows flexibility to protect the items from impact forces and to allow easy access by a purchaser. The tray insert fits within the outer box, which provides impact and debris protection during transit, and converts to a display mode. Both the outer box and each inner box may be marked with a code to allow inventory tracking.

Abstract: Methods, systems, and computer-readable media for multi-domain, multi-modal data segmentation, and automatically generating and refining hypotheses. The method receives data from a plurality of data sources; synthesizing the receive data; identifying trigger event data based on the synthesized data; generating an episode based on a segmentation of the synthesized data and trigger event data; and identifying at least one set of observational features associated with the episode based on the synthesized data and a relevancy metric. The method also includes iteratively generating a hypothesis based on the observational features using machine learning, predicting an outcome based on the hypothesis using machine learning, generating an outcome measure, and validating the hypothesis based on the outcome measure.

Abstract: Various embodiments of the present disclosure relate generally to providing services to users via communication channels. More specifically, various embodiments of the present disclosure relate to systems and methods for modifying, updating, and/or changing communication channel interactions based on the tracking or listening for events within other communication channels.

Abstract: Methods, systems, and computer-readable media for generating a statistically covaried machine learning model for performance measurement of service providers. The method receives a configuration file that includes one or more parameters associated with a plurality of individuals and parses it to generate and executing the database query on input data to generate sets of tabulated data of individuals of the plurality of individuals. The method next determines one or more measures of service providers listed in the configuration file using two or more tabulated data of individuals from the sets of tabulated data of individuals. The method finally generates a covaried machine learning model by training a machine learning model by statistically covarying measures and using them as training data.

Abstract: Methods, systems, and computer-readable media for multi-domain, multi-modal data segmentation, and automatically generating and refining hypotheses. The method receives data from a plurality of data sources; synthesizing the receive data; identifying trigger event data based on the synthesized data; generating an episode based on a segmentation of the synthesized data and trigger event data; and identifying at least one set of observational features associated with the episode based on the synthesized data and a relevancy metric. The method also includes iteratively generating a hypothesis based on the observational features using machine learning, predicting an outcome based on the hypothesis using machine learning, generating an outcome measure, and validating the hypothesis based on the outcome measure.

Abstract: Methods, systems, and computer-readable media for generating a statistically covaried machine learning model for performance measurement of service providers. The method receives a configuration file that includes one or more parameters associated with a plurality of individuals and parses it to generate and executing the database query on input data to generate sets of tabulated data of individuals of the plurality of individuals. The method next determines one or more measures of service providers listed in the configuration file using two or more tabulated data of individuals from the sets of tabulated data of individuals. The method finally generates a covaried machine learning model by training a machine learning model by statistically covarying measures and using them as training data.

Abstract: Methods, systems, and computer-readable media for generating a personalized action recommendation are provided. The method acquires a request for a service that is associated with a user and the user's condition. The method then identifies one or more features of the user based on stored user information. The method next assigns the user to a segment based on the identified one or more features, generates a set of one or more recommended actions for the user based on the segment, and determines an expected value of each of the one or more recommended actions. The method determines a rank of the one or more recommended actions based on the expected value of each of the one or more recommended actions, and outputs a recommended action with a highest expected value for the user in response to the request for the service.

Abstract: A method and apparatus for perforating a wellbore by firing one or more projectiles into a casing and formation using a single source of energy.

Abstract: Methods, systems, and computer-readable media for multi-domain, multi-modal data segmentation, and automatically generating and refining hypotheses. The method receives data from a plurality of data sources; synthesizing the receive data; identifying trigger event data based on the synthesized data; generating an episode based on a segmentation of the synthesized data and trigger event data; and identifying at least one set of observational features associated with the episode based on the synthesized data and a relevancy metric. The method also includes iteratively generating a hypothesis based on the observational features using machine learning, predicting an outcome based on the hypothesis using machine learning, generating an outcome measure, and validating the hypothesis based on the outcome measure.

Abstract: Methods, systems, and computer-readable media for generating a personalized action recommendation are provided. The method acquires a request for a service that is associated with a user and the user's condition. The method then identifies one or more features of the user based on stored user information. The method next assigns the user to a segment based on the identified one or more features, generates a set of one or more recommended actions for the user based on the segment, and determines an expected value of each of the one or more recommended actions. The method determines a rank of the one or more recommended actions based on the expected value of each of the one or more recommended actions, and outputs a recommended action with a highest expected value for the user in response to the request for the service.

Abstract: A packaging system for fragile items comprising an outer box, a tray insert and a plurality of inner boxes. The system protects items during distribution, and easily convert into a display system for the items at the point of retail sale. Each item is contained in its own inner box, which includes one or more viewing windows to allow a purchaser easily to view the items. The inner boxes fit removably within paired holes in the tray insert, which provides multiple points of contact to hold the boxes in place, yet allows flexibility to protect the items from impact forces and to allow easy access by a purchaser. The tray insert fits within the outer box, which provides impact and debris protection during transit, and converts to a display mode. Both the outer box and each inner box may be marked with a code to allow inventory tracking.

Abstract: A customer logs into a desired retailer through a Virtual Reality (VR)/Augmented Reality (AR) cross-retailer application (app). Preferences and/or a profile are obtained from the retailer via an Application Programming Interface (API). A customized VR/AR setting is rendered within the app based on the preferences and/or profile and a VR/AR session is initiated with the app. Consumable items and ingredients of each item are rendered as VR/AR selectable objects during the session for interaction by the customer and a custom item is made with selected ingredients. The customer purchases the item within the session and an order is placed with the retailer through the API. In an embodiment, an avatar of the customer and avatars of other customer placing orders with the retailer are rendered on a virtual floor or superimposed on an actual floor of the customer's physical environment within the app for social interaction and social network features.

Abstract: A touch field is created around a touchscreen display, the field is in front of a touch surface of the display and the field maps to locations on the display. An operator of a terminal during a transaction is presented with transaction interface screens that are visually rendered on the display. The operator makes interface options selections, performs screen navigation, and provides date entry field inputs by placing the operator's hand within the field without touching the touch surface of the display and making hand poses, hand movements, and/or hand gestures. The poses, movements, and/or gestures are translated into touch actions and touch inputs recognized by the transaction interface and processed as operator-provided input during the transaction.