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: 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 implantable blood pressure monitor has two or more elements configured to wrap at least part way around a blood vessel. Changes in pressure within the blood vessel may be sensed by detecting movements of the elements or forces applied to the elements. A blood pressure monitor may be implanted without surgery. The blood pressure monitor may transmit real time blood pressure information to a receiver by wireless data transmission.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for normalizing, compressing, and correlating vulnerabilities are disclosed. In one aspect, a method includes the actions of generating a first and second copy of a software target. The actions further include providing the first copy to a first scanning tool and the second copy to a second scanning tool. The actions further include receiving a first scanning tool output that identifies a first issue of the software target. The actions further include receiving a second scanning tool output that identifies a second issue of the software target. The actions further include determining that the first issue and the second issue are a same issue. The actions further include generating a combined issue of the first issue and the second issue. The actions further include outputting a notification that includes the combined issue.

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 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: Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a multi-stroke neural network for modifying a digital image via a plurality of generated stroke parameters in a single pass of the neural network. Specifically, the disclosed system utilizes an encoder neural network to generate an encoding of a digital image. The disclosed system then utilizes a decoder neural network that generates a sequence of stroke parameters for digital drawing strokes from the encoding in a single pass of the encoder neural network and decoder neural network. Additionally, the disclosed system utilizes a renderer neural network to render the digital drawing strokes on a digital canvas according to the sequence of stroke parameters. In additional embodiments, the disclosed system utilizes a balance of loss functions to learn parameters of the multi-stroke neural network to generate stroke parameters according to various rendering styles.

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: 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: 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: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for normalizing, compressing, and correlating vulnerabilities are disclosed. In one aspect, a method includes the actions of generating a first and second copy of a software target. The actions further include providing the first copy to a first scanning tool and the second copy to a second scanning tool. The actions further include receiving a first scanning tool output that identifies a first issue of the software target. The actions further include receiving a second scanning tool output that identifies a second issue of the software target. The actions further include determining that the first issue and the second issue are a same issue. The actions further include generating a combined issue of the first issue and the second issue. The actions further include outputting a notification that includes the combined issue.

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: 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 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: 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: A system for neuromodulation and/or neurostimulation, for the treatment of a mammal, at least comprising: at least one control unit configured and arranged to provide stimulation data; at least one stimulation unit configured and arranged to provide a stimulation pulse; at least one real-time monitoring unit; at least one signal-processing unit; wherein the system is configured and arranged for control of blood pressure, wherein the stimulation unit is constructed to comprise a lead, and wherein the lead is capable and configured to provide stimulation to the spinal cord at level T9-L1.

Abstract: A neuromodulation system, especially a neurostimulation system, for treating a patient, especially for enhancing at least one autonomous function such as blood circulation and/or respiration, wherein the system comprises: at least one signal input module, which is configured to receive at least one or more signals being indicative for blood circulation, especially being indicative for pulse and/or blood pressure, at least one control module, wherein the control module is connected to the signal input module, wherein the control module is configured to adapt the neurostimulation provided by the neuromodulation system on the basis of the signal(s) received by the signal input module.