Abstract: An automatic visual analyzer having a viewing body, a drive line being a tether, a control and communication system, and power input connected by the tether to the viewing body. The viewing body has a barrel section with a plurality of cameras mounted thereon in fixed related directions to allow a defined directional scan of the confined pathway. At a lower end of the barrel is a bell skirt which extends outwardly with a greater diameter than the barrel and the plurality of cameras so as to be the most outer part of the viewing body and provide protection from side engagements with the wall of the confined pathway.

Abstract: The invention provides physical targets for training, including targets (101) for projectiles fired by non-ballistic ammunition such as paint marker rounds. The targets can be used for detecting the impact of a projectile, with the target including a body (103) and plurality of sensors mounted on the body for detecting an impact of a projectile on the body. Each sensor provides an output representing a detected impact. A processor receives the sensor outputs and determines, from the sensor outputs, a location at which the projectile impacts the body. The target may also include one or more domain actuators (202) controlling actions of the target based on a current behavioural state of the target.

Abstract: Implementations are directed to remote data aggregation, data management, and data visualization of field data from remote field site locations. Actions can include generating, by one or more sensors, the field data, each sensor of the one or more sensors being responsive to field site activity, transmitting, through a regional network, the field data to a back-end system, processing, by the back-end system, the field data to provide visualization data, transmitting the visualization data to one or more mobile computing devices, and providing a computer-executable application for execution on a mobile computing device, the computer-executable application processing the visualization data to provide data visualizations.

Abstract: Tokenized rows of a training portion of a database are selected, each of the selected tokenized rows having a first token value stored in a first column of the database. Training row vectors are grouped into clusters. From the clusters, prototypes are generated, each prototype comprising a numerical representation of a cluster. From input tokens, an input row vector is generated, the input row vector comprising a numerical representation of input tokens representing data in an input row of the database, the input row excluded from the training portion, each input token comprising a textual representation of data in a cell of the input row. Based on similarity with the input row vector, a prototype is selected. Data derived from the selected prototype is inserted into the first column of the input row.

Abstract: Implementations are directed to remote data aggregation, data management, and data visualization of field data from remote field site locations. Actions can include generating, by one or more sensors, the field data, each sensor of the one or more sensors being responsive to field site activity, transmitting, through a regional network, the field data to a back-end system, processing, by the back-end system, the field data to provide visualization data, transmitting the visualization data to one or more mobile computing devices, and providing a computer-executable application for execution on a mobile computing device, the computer-executable application processing the visualization data to provide data visualizations.

Abstract: Examples disclosed herein relate to an autonomous driving system in a vehicle having a radar system with a Non-Line-of-Sight (“NLOS”) correction module to correct for NLOS reflections prior to the radar system identifying targets in a path and a surrounding environment of the vehicle, and a sensor fusion module to receive information from the radar system on the identified targets and compare the information received from the radar system to information received from at least one sensor in the vehicle.

Abstract: Examples disclosed herein relate to a radar system in an autonomous vehicle. The radar system has a radar module including at least one beam steering antenna and an antenna controller. The radar system also includes a perception module having an object detection module to detect objects in a path and surrounding environment of the autonomous vehicle, and a decision network to determine a control action for the antenna controller to perform based on the detected objects and a control policy.

Abstract: An underwater camera system comprising a remote station such as a boat a diver connection module located at the back of diver's helmet including a splitter box. High voltage transmission power and a fiber optics tether come into the box from the boat on the surface through the fiber optics which can be integral with, attached to or coextending with the umbilical cord. The voltage is dropped, the fiber optic signal is converted to USB, and the two are fed out to the camera module which is adjustably mounted on the side of the diver's helmet, to allow change of focus in the same line of sight as the diver's vision and allowing full handsfree use.

Abstract: An inline shower device includes a housing, a hydraulic chamber, a first actuator, and a fluid-driven piston. The housing includes an outlet port. The hydraulic chamber is disposed within the housing. The first actuator is configured to connect a capsule to the housing and to fluidly connect the capsule to the hydraulic chamber. The fluid-driven piston is disposed within the hydraulic chamber and is configured to dispense a fluid from the capsule into the outlet port.

Abstract: Implementations are directed to remote data aggregation, data management, and data visualization of field data from remote field site locations. Actions can include generating, by one or more sensors, the field data, each sensor of the one or more sensors being responsive to field site activity, transmitting, through a regional network, the field data to a back-end system, processing, by the back-end system, the field data to provide visualization data, transmitting the visualization data to one or more mobile computing devices, and providing a computer-executable application for execution on a mobile computing device, the computer-executable application processing the visualization data to provide data visualizations.

Abstract: An inline shower device includes a housing, a hydraulic chamber, a first actuator, and a fluid-driven piston. The housing includes an outlet port. The hydraulic chamber is disposed within the housing. The first actuator is configured to connect a capsule to the housing and to fluidly connect the capsule to the hydraulic chamber. The fluid-driven piston is disposed within the hydraulic chamber and is configured to dispense a fluid from the capsule into the outlet port.

Abstract: In at least one aspect, a method comprises: receiving information associated with a plurality of scheduled actions, each of the plurality of scheduled actions defining a device to be controlled, an action to be carried out with respect to the device to be controlled, a scheduled day on which to carry out the scheduled action and a scheduled time of day to carry out the scheduled action on the scheduled day; determining a chronological ordering that indicates a chronological order in which at least a subset of the plurality of scheduled actions are scheduled to be carried out; generating a view based at least in part on the chronological ordering; and displaying the generated view. Such methods may be performed or implemented by various devices, apparatuses and/or systems.

Abstract: A method, a computer program product, and a computer system for classifying bacteria. The method comprises extracting a morphology signature corresponding to one or more bacteria and extracting a motility signature corresponding to the one or more bacteria. The method further comprises merging the morphology signature and the motility signature into a merged vector signature and classifying the one or more bacteria based on the merged vector signature.

Abstract: Examples disclosed herein relate to an autonomous driving system in a vehicle having a radar system with a Non-Line-of-Sight (“NLOS”) correction module to correct for NLOS reflections prior to the radar system identifying targets in a path and a surrounding environment of the vehicle, and a sensor fusion module to receive information from the radar system on the identified targets and compare the information received from the radar system to information received from at least one sensor in the vehicle.

Abstract: A set of partial words is received. At least one partial word in the set of partial words is completed. The set of partial words with the at least one completed partial word is run through a trained deep neural network, the trained deep neural network inferring a word embedding associated with an unfinished word in the set of partial words. An inferred word is determined based on the inferred word embedding associated with the unfinished word. A sentence may be output, which includes at least the completed partial word and the inferred word.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for communicating between an operational asset and a backend network that include the actions of receiving first data from an operational asset through a first communication interface that is configured to communicate with an operational asset, and where the first data is formatted according to a first data format that is specific to the operational asset. Processing the first data according to an asset template to generate second data, where the second data includes the first data and being formatted according to a second data format that is specific to the backend network. Causing the second data to be transmitted to the backend network by a second communication interface that is configured to communicate with a backend network.

Abstract: Examples disclosed herein relate to an autonomous driving system in a vehicle having a radar system with a Non-Line-of-Sight (“NLOS”) correction module to correct for NLOS reflections prior to the radar system identifying targets in a path and a surrounding environment of the vehicle, and a sensor fusion module to receive information from the radar system on the identified targets and compare the information received from the radar system to information received from at least one sensor in the vehicle.

Abstract: A hierarchy is a multi-level linked structure of nodes, wherein the hierarchy represents data relating to a set of one or more items to be processed. Where there are multiple input hierarchies, it may improve the efficiency of the processing of the items to merge the input hierarchies to form a merged hierarchy. The hierarchies are merged by identifying two or more sub-hierarchies within the input hierarchies which are to be merged, and determining one or more nodes of the merged hierarchy which reference nodes of the identified sub-hierarchies. The determined nodes of the merged hierarchy are stored and indications of the references between the determined nodes of the merged hierarchy and the referenced nodes of the identified sub-hierarchies are also stored. In this way, the merged hierarchy is formed for use in processing the items.

Abstract: A method includes clustering a plurality of weights of a neural network model into a first plurality of clusters and clustering differences between (i) the plurality of weights assigned to a first cluster of the first plurality of clusters and (ii) a centroid value of the first cluster into a second plurality of clusters. The method also includes storing, in a first table, an identifier and a centroid value for each cluster of the second plurality of clusters and for each of the plurality of weights assigned to the first cluster, storing, in a second table, an identifier of a respective cluster of the second plurality of clusters corresponding to that weight.

Abstract: A method, computer-program product, and system is provided. Separate computing devices can be controlled with one or more user input devices linked to the separate computing devices by an application. An image of a display from one of the linked computing devices can be captured with a smart headset and can be compared to display outputs retrieved from linked computing devices and the user input device can be activated one the corresponding linked computing device.