Abstract: A device and algorithm for controlling an autonomic function in an individual. A controller device that utilizes physiological measurements (such as blood pressure) to regulate spinal cord electrical stimulation to stabilize blood pressure. A control interface and algorithm for controlling an autonomic function in a subject. For instance, an algorithm that utilizes physiological measurements (such as blood pressure) to regulate spinal cord electrical stimulation to stabilize blood pressure.

Abstract: Provided is a process, including: receiving, via the network interface, from a remote user device, a command to change a state of the fluid-handling device to a target state; translating the received command into a translated command operative to cause a local controller of the fluid-handling device to drive the fluid-handling equipment to the target state, the local controller being responsive to the command and feedback from the fluid-handling device indicative of whether the fluid-handling device is in the target state; and sending the translated command to the local controller.

Abstract: Provided is a process, including: receiving, via the network interface, from a remote user device, a command to change a state of the fluid-handling device to a target state; translating the received command into a translated command operative to cause a local controller of the fluid-handling device to drive the fluid-handling equipment to the target state, the local controller being responsive to the command and feedback from the fluid-handling device indicative of whether the fluid-handling device is in the target state; and sending the translated command to the local controller

Abstract: A device and algorithm for controlling an autonomic function in an individual. In particular, a controller device that utilizes physiological measurements (such as blood pressure) to regulate spinal cord electrical stimulation to stabilize blood pressure. A control interface and algorithm for controlling an autonomic function in a subject. In particular, an algorithm that utilizes physiological measurements (such as blood pressure) to regulate spinal cord electrical stimulation to stabilize blood pressure.

Abstract: Provided is a surveillance system, including: a trailer having wheels, a mast, and a trailer towing coupler; a camera coupled to the mast; a cellular modem communicatively coupled to the camera and operative to transmit video captured by the camera; a command center server operative to remotely receive and store data describing operation of a fluid-handling device and to receive the transmitted video and send the video to a user in response to a request from a web browser of the user; a power storage device; and a solar panel coupled to the power storage device such that the solar panel charges the power storage device.

Abstract: Provided is a process, including: receiving, via the network interface, from a remote user device, a command to change a state of the fluid-handling device to a target state; translating the received command into a translated command operative to cause a local controller of the fluid-handling device to drive the fluid-handling equipment to the target state, the local controller being responsive to the command and feedback from the fluid-handling device indicative of whether the fluid-handling device is in the target state; and sending the translated command to the local controller.

Abstract: Provided is a surveillance system, including: a trailer having wheels, a mast, and a trailer towing coupler; a camera coupled to the mast; a cellular modem communicatively coupled to the camera and operative to transmit video captured by the camera; a command center server operative to remotely receive and store data describing operation of a fluid-handling device and to receive the transmitted video and send the video to a user in response to a request from a web browser of the user; a power storage device; and a solar panel coupled to the power storage device such that the solar panel charges the power storage device.

Abstract: A target image is projected into a latent space of generative model by determining a latent vector by applying a gradient-free technique and a class vector by applying a gradient-based technique. An image is generated from the latent and class vectors, and a loss function is used to determine a loss between the target image and the generated image. This determining of the latent vector and the class vector, generating an image, and using the loss function is repeated until a loss condition is satisfied. In response to the loss condition being satisfied, the latent and class vectors that resulted in the loss condition being satisfied are identified as the final latent and class vectors, respectively. The final latent and class vectors are provided to the generative model and multiple weights of the generative model are adjusted to fine-tune the generative model.

Abstract: A generative neural network control system controls a generative neural network by modifying the intermediate latent space in the generative neural network. The generative neural network includes multiple layers each generating a set of activation values. An initial layer (and optionally additional layers) receives an input latent vector, and a final layer outputs an image generated based on the input latent vector. The data that is input to each layer (other than the initial layer) is referred to as data in an intermediate latent space. The data in the intermediate latent space includes activation values (e.g., generated by the previous layer or modified using various techniques) and optionally a latent vector. The generative neural network control system modifies the intermediate latent space to achieve various different effects when generating a new image.

Abstract: An online system provides content based on context of host content. The online system allows content providers to define specific context for providing their content for display to users, including specifying categories, format, popularity, and visual appearance of host content eligible for hosting their content. To determine which content a specific content item is eligible for hosting, the online system categories host content items according to specific criteria defined by different content providers for hosting various content. Each content is indexed by classification groups into which the host content items are classified. If a particular content item includes an opportunity for presenting content, the online system identifies content which the particular content item is eligible for hosting. The online system selects one or more identified content for presentation via the opportunity.

Abstract: Virtual reality parallax correction techniques and systems are described that are configured to correct parallax for VR digital content captured from a single point of origin. In one example, a parallax correction module is employed to correct artifacts caused in a change from a point of origin that corresponds to the VR digital content to a new viewpoint with respect to an output of the VR digital content. A variety of techniques may be employed by the parallax correction module to correct parallax. Examples of these techniques include depth filtering, boundary identification, smear detection, mesh cutting, confidence estimation, blurring, and error diffusion as further described in the following sections.

Abstract: The present disclosure relates to an asymmetric font pairing system that efficiently pairs digital fonts. For example, in one or more embodiments, the asymmetric font pairing system automatically identifies and provides users with visually aesthetic font pairs for use in different sections of an electronic document. In particular, the asymmetric font pairing system learns visually aesthetic font pairs using joint symmetric and asymmetric compatibility metric learning. In addition, the asymmetric font pairing system provides compact compatibility spaces (e.g., a symmetric compatibility space and an asymmetric compatibility space) to computing devices (e.g., client devices and server devices), which enable the computing devices to quickly and efficiently provide font pairs to users.

Abstract: Digital image layout training is described using wireframe rendering within a generative adversarial network (GAN) system. A GAN system is employed to train the generator module to refine digital image layouts. To do so, a wireframe rendering discriminator module rasterizes a refined digital training digital image layout received from a generator module into a wireframe digital image layout. The wireframe digital image layout is then compared with at least one ground truth digital image layout using a loss function as part of machine learning by the wireframe discriminator module. The generator module is then trained by backpropagating a result of the comparison.

Abstract: Provided is a process including: receiving a tank-nearly-full message indicating that a tank at an oil or gas related facility is or will be ready for a truck to unload and transport fluid accumulating in the tank; in response to the tank-nearly-full message, creating a tank-run record; sending a description of the tank-run to a mobile device of a driver of an oilfield truck; receiving, from the mobile device of the driver of the oilfield truck, a tank-run claimed message indicating that the driver will drive to the oil or gas related facility and transport at least some of the fluid accumulating in the tank; and after the tank-run claimed message, performing steps including: confirming that the tank-run has not yet been claimed; after the confirmation, designating the tank-run as claimed by the driver; and sending confirmation to the mobile device of the driver.

Abstract: Provided is process of operating a wireless device configured to act as a node in an ad hoc multi-hop mobile network, the process including: snooping, with a wireless device, a packet transmitted from a sending node to a receiving node in a multi-hop wireless connection, the sending node and the receiving node being in a different location; extracting from the snooped packet an identifier of the sending node and an identifier of the receiving node; determining based on the identifier of the sending node, the identifier of the receiving node, and a record in memory of the wireless device that the wireless device is part of a multi-hop wireless connection including the sending node and the receiving node; determining that a signal strength of a signal conveying the snooped packet exceeds a threshold; and transmitting a kill packet to the sending node and the receiving node that reconfigures the multi-hop wireless connection to bypass the receiving node.

Abstract: Provided is a process that includes obtaining a directed acyclic graph describing a plurality wireless connections between a plurality of downstream nodes forming a multi-path route to an Internet connected wireless transceiver; determining an encoding kernel specifying transformations to be performed by the plurality of downstream nodes on data received from upstream nodes; transmitting at least part of the encoding kernel to at least some of the downstream nodes; and transmitting data from a data source to a downstream node in the directed acyclic graph specified by the encoding kernel such that the data is conveyed through the multi-hop, multi-path route to the Internet connected wireless transceiver.

Abstract: Provided is a process including: receiving a tank-nearly-full message indicating that a tank at an oil or gas related facility is or will be ready for a truck to unload and transport fluid accumulating in the tank; in response to the tank-nearly-full message, creating a tank-run record; sending a description of the tank-run to a mobile device of a driver of an oilfield truck; receiving, from the mobile device of the driver of the oilfield truck, a tank-run claimed message indicating that the driver will drive to the oil or gas related facility and transport at least some of the fluid accumulating in the tank; and after the tank-run claimed message, performing steps including: confirming that the tank-run has not yet been claimed; after the confirmation, designating the tank-run as claimed by the driver; and sending confirmation to the mobile device of the driver.

Abstract: Provided is process of operating a wireless device configured to act as a node in an ad hoc multi-hop mobile network, the process including: snooping, with a wireless device, a packet transmitted from a sending node to a receiving node in a multi-hop wireless connection, the sending node and the receiving node being in a different location; extracting from the snooped packet an identifier of the sending node and an identifier of the receiving node; determining based on the identifier of the sending node, the identifier of the receiving node, and a record in memory of the wireless device that the wireless device is part of a multi-hop wireless connection including the sending node and the receiving node; determining that a signal strength of a signal conveying the snooped packet exceeds a threshold; and transmitting a kill packet to the sending node and the receiving node that reconfigures the multi-hop wireless connection to bypass the receiving node.

Abstract: Techniques and systems to support collaborative interaction as part of virtual reality video are described. In one example, a viewport is generated such that a reviewing user of a reviewing user device may view VR video viewed by a source user of a source user device. The viewport, for instance, may be configured as a border at least partially surrounding a portion of the VR video output by the reviewing VR device. In another instance, the viewport is configured to support output of thumbnails within an output of VR video by the reviewing VR device. Techniques and systems are also described to support communication of annotations between the source and reviewing VR devices. Techniques and systems are also described to support efficient distribution of VR video within a context of a content editing application.

Abstract: Virtual reality parallax correction techniques and systems are described that are configured to correct parallax for VR digital content captured from a single point of origin. In one example, a parallax correction module is employed to correct artifacts caused in a change from a point of origin that corresponds to the VR digital content to a new viewpoint with respect to an output of the VR digital content. A variety of techniques may be employed by the parallax correction module to correct parallax. Examples of these techniques include depth filtering, boundary identification, smear detection, mesh cutting, confidence estimation, blurring, and error diffusion as further described in the following sections.