Abstract: According to one aspect of the present disclosure, a system for providing immersive training experiences can include a training room and a control room. The training room can include one or more physical effects units configured to apply physical effects to the training room; one or more spatial audio units configured to apply spatial audio to the training room; one or more audio capture units; one or more video recording units; and a workstation accessible by a first user to complete a training task. The control room can include an effects interface configured to allow a second user to control the one or more physical effects units and the one or more spatial audio units; an evaluation interface configured to receive and display data feeds from the one or more audio capture units and the one or more video recording units.

Abstract: A balanced piston pump (300) for use in subsea vehicles, for example in a variably buoyancy engine, includes an inlet (321), an outlet (325) and at least one fluid path between the inlet and the outlet. A piston arrangement in the fluid path includes a stepped piston (330) having a large end (333) and a small end (331). The step (336) of the piston cooperates with the body (310) of the pump to form a piston chamber (320). The ends (332, 334) of the piston are each exposed to ambient pressure. The force required to drive the pump is dependent on the difference in cross sectional areas of the ends of the pistons.

Abstract: The face down pool float is the only product of its kind that allows users to float face down while resting on a pool float. This unprecedented product is uniquely designed with a plastic wrap inflatable pillow that can be conveniently replaced and reattached when laying in the face up position, offering flexibility of use, and it is carefully crafted with durable materials to ensure long-term sustainability and functionality.

Abstract: A system includes a first acousto-optic deflector (AOD) for diffracting an incident beam of laser energy to produce and output therefrom a first beam of laser energy and a second beam of laser light, a second AOD arranged to receive the first beam of laser energy and for diffracting the received first beam of laser energy to thereby produce and output therefrom a third beam of laser energy and a fourth beam of laser energy, at least one first beam trap arranged and configured to absorb the second beam of laser energy output from the first AOD, at least one second beam trap arranged and configured to absorb the fourth beam of laser energy output from the second AOD and a controller communicatively coupled to the first AOD and to the second AOD, wherein the controller is configured to operate of the first AOD while not operating the second AOD.

Abstract: The subject matter described herein provides systems and techniques for a network planning and optimization tool that may allow for network capacity planning using key network failures for an arbitrary pair of network topology and demands. Performing network capacity planning with key network failures, instead of using other techniques, may avoid over-building the topology of a network. In particular, key network failures may be generated from the probabilistic failures, and the impact of these failures on a network may be computed. Expected flow availability SLO or a function thereof may be computed, using this information, and used by the tool to design a robust network. With an embedded flow availability calculation and updated risk framework, the capacitated cross-layer network topologies output by the tool may meet network demands/flows with their respective SLO type at the lowest cost.

Abstract: A three-gear hose clamp apparatus designed to securely fasten around hoses. The apparatus includes a clamping band having openings disposed at distal end and forms a loop around hose, when its distal end and proximal end overlap. The constriction and expansion of clamping band is facilitated by a clamp assembly, which employs a drive helical gear with a head section and threaded shaft. The drive helical gear interfaces with a driven spur gear set at a perpendicular axis, which is in direct contact with an elongated driven helical gear that rotates co-axially, its threads mating with the openings of the clamping band. The mechanism is housed in two distinct housings: one that covers the driven helical gear and another envelops both the drive helical gear and driven spur gear.

Abstract: The face down pool float is the only product of its kind that allows users to float face down while resting on a pool float. This unprecedented product is uniquely designed with a plastic wrap inflatable pillow that can be conveniently replaced and reattached when laying in the face up position, offering flexibility of use, and it is carefully crafted with durable materials to ensure long-term sustainability and functionality.

Abstract: A balanced piston pump (300) for use in subsea vehicles, for example in a variably buoyancy engine, includes an inlet (321), an outlet (325) and at least one fluid path between the inlet and the outlet. A piston arrangement in the fluid path includes a stepped piston (330) having a large end (333) and a small end (331). The step (336) of the piston cooperates with the body (310) of the pump to form a piston chamber (320). The ends (332, 334) of the piston are each exposed to ambient pressure. The force required to drive the pump is dependent on the difference in cross sectional areas of the ends of the pistons.

Abstract: Methods, systems, and apparatus, including computer-readable storage media, optimizing interior gateway protocol (IGP) metrics using reinforcement learning (RL) for a network domain. The system can receive a topology (G) of a network domain, a set of flows (F), and an objective function. The system can optimize, using reinforcement learning, the objective function based on the received topology and the one or more flows F. The system can determine updated IGP metrics based on the optimization of the objective function. The IGP metrics for the metric domain may be updated with the updated IGP metrics.

Abstract: Aspects provide for dynamic pathloss mitigation via a cross layer tool chain by simulating a three-dimensional model of a physical environment including an access point, an endpoint running an application, and a passive object; emulating network traffic for the application transmitted between the access point and the endpoint; simulating, in the model, pathways for signals to carry the traffic in a plurality of regions for the physical environment; emulating signal degradation along the pathways in the plurality of regions based on respective locations for the access point, the endpoint, and the passive object in the physical environment; and in response to the signal degradation satisfying a pathloss threshold, outputting a command to the application to affect operations of the endpoint. Additionally, the cross layer tool chain outputs a Graphical User Interface showing a signal degradation map based on the simulated network traffic overlaid on the model.

Abstract: The subject matter described herein provides systems and techniques for a network planning and optimization tool that may allow for network capacity planning using key network failures for an arbitrary pair of network topology and demands. Performing network capacity planning with key network failures, instead of using other techniques, may avoid over-building the topology of a network. In particular, key network failures may be generated from the probabilistic failures, and the impact of these failures on a network may be computed. Expected flow availability SLO or a function thereof may be computed, using this information, and used by the tool to design a robust network. With an embedded flow availability calculation and updated risk framework, the capacitated cross-layer network topologies output by the tool may meet network demands/flows with their respective SLO type at the lowest cost.

Abstract: The subject matter described herein provides systems and techniques for a network planning and optimization tool that may allow for network capacity planning using key network failures for an arbitrary pair of network topology and demands. Performing network capacity planning with key network failures, instead of using other techniques, may avoid over-building the topology of a network. In particular, key network failures may be generated from the probabilistic failures, and the impact of these failures on a network may be computed. Expected flow availability SLO or a function thereof may be computed, using this information, and used by the tool to design a robust network. With an embedded flow availability calculation and updated risk framework, the capacitated cross-layer network topologies output by the tool may meet network demands/flows with their respective SLO type at the lowest cost.

Abstract: Methods, systems, and apparatus, including computer-readable storage media, optimizing interior gateway protocol (IGP) metrics using reinforcement learning (RL) for a network domain. The system can receive a topology (G) of a network domain, a set of flows (F), and an objective function. The system can optimize, using reinforcement learning, the objective function based on the received topology and the one or more flows F. The system can determine updated IGP metrics based on the optimization of the objective function. The IGP metrics for the metric domain may be updated with the updated IGP metrics.

Abstract: The subject matter described herein provides systems and techniques for a network planning and optimization tool that may allow for network capacity planning using key network failures for an arbitrary pair of network topology and demands. Performing network capacity planning with key network failures, instead of using other techniques, may avoid over-building the topology of a network. In particular, key network failures may be generated from the probabilistic failures, and the impact of these failures on a network may be computed. Expected flow availability SLO or a function thereof may be computed, using this information, and used by the tool to design a robust network. With an embedded flow availability calculation and updated risk framework, the capacitated cross-layer network topologies output by the tool may meet network demands/flows with their respective SLO type at the lowest cost.

Abstract: Methods, systems, and apparatus, including computer-readable storage media, optimizing interior gateway protocol (IGP) metrics using reinforcement learning (RL) for a network domain. The system can receive a topology (G) of a network domain, a set of flows (F), and an objective function. The system can optimize, using reinforcement learning, the objective function based on the received topology and the one or more flows F. The system can determine updated IGP metrics based on the optimization of the objective function. The IGP metrics for the metric domain may be updated with the updated IGP metrics.

Abstract: A multisensory system provides both temporal and spatial coverage capacities for auto-detection of bird collision events. The system includes an apparatus having a first circuitry to capture and store a series of images or video of a blade of a wind turbine; and a memory to store the images from the first circuitry. The apparatus also has one or more sensors to continuously sense vibration of the blade or for acoustic recordings; and a second circuitry to analyze the sensor data stream and/or the series of images or video to identify a cause of the vibration and to trigger the camera(s). A communication interface transmits data from the second circuitry to another device, wherein the second circuitry applies artificial intelligence or machine learning to control sensitivity of the one or more sensors.

Abstract: Methods, systems, and apparatus, including computer-readable storage media, optimizing interior gateway protocol (IGP) metrics using reinforcement learning (RL) for a network domain. The system can receive a topology (G) of a network domain, a set of flows (F), and an objective function. The system can optimize, using reinforcement learning, the objective function based on the received topology and the one or more flows F. The system can determine updated IGP metrics based on the optimization of the objective function. The IGP metrics for the metric domain may be updated with the updated IGP metrics.

Abstract: The integrated circuit (IC) described herein lowers the start-up voltage to, for example, 50 mV, compatible for starting a DC-DC converter from a thermoelectric generator (TEG), even with a small temperature gradient. The IC further improves end-to-end efficiency of the energy harvester by improving power efficiency of the DC-DC converter while ensuring maximum power transfer from the TEG at low voltages. The IC uses a low voltage integrated charge pump that can boost sub-100 mV input voltage. A startup clock is generated by a ring-oscillator that begins operation with low supply (e.g., 50 mV or less), and which allows for one inductor to be used for DC-DC converter and for startup of the converter. The IC can be configured between the TEG and any downstream sensor or communication circuits to provide an acceptable (e.g., greater than 1 V) voltage for powering the downstream circuits from a low-voltage (e.g., less than 200 mV) TEG energy source.

Abstract: Determining an upgrade path from a starting topology to a target topology of a network is computationally intense and does not guarantee a steadily increasing usable capacity of the network at each stage within the upgrade path. The disclosed technology allows for a sequence of stages related to network upgrades to be generated. The technology ensures that networks can be upgraded in a sequential manner, where each step in the sequence does not violate service level objectives related to the network, ensures operational continuity of the network by users of the network, and ensures that the available network resources increase as the sequential upgrades are rolled out. The pathway determined is determined in a computationally efficient manner.

Abstract: A battery-less heartbeat monitoring system that operates continuously using energy harvested from a low-grade heat source or small thermal gradient, such as human body heat and the gradient that exists between skin and the ambient environment in most circumstances.