Method and system for mixing static scene and live annotations for efficient labeled image dataset collection

    公开(公告)号:US12223595B2

    公开(公告)日:2025-02-11

    申请号:US17879480

    申请日:2022-08-02

    Abstract: A system is provided which mixes static scene and live annotations for labeled dataset collection. A first recording device obtains a 3D mesh of a scene with physical objects. The first recording device marks, while in a first mode, first annotations for a physical object displayed in the 3D mesh. The system switches to a second mode. The system displays, on the first recording device while in the second mode, the 3D mesh including a first projection indicating a 2D bounding area corresponding to the marked first annotations. The first recording device marks, while in the second mode, second annotations for the physical object or another physical object displayed in the 3D mesh. The system switches to the first mode. The first recording device displays, while in the first mode, the 3D mesh including a second projection indicating a 2D bounding area corresponding to the marked second annotations.

    Non-invasive transcranial stimulation system and method using pre-recorded neurostimulation data

    公开(公告)号:US12207930B2

    公开(公告)日:2025-01-28

    申请号:US17128740

    申请日:2020-12-21

    Abstract: An electronic memory is configured to store pre-recorded neurostimulation data comprising patterns of stimulation of a specified region of a subject's brain developed to recreate a response by one or more of a sensing organ or sensing organs, a vestibular system, and a memory of the subject. A focused ultrasound transducer arrangement is operably coupled to the electronic memory and comprises an array of ultrasound transducers. The focused ultrasound transducer arrangement is configured to deliver transcranial stimulation to the specified region of a person's brain using the pre-recorded neurostimulation data to recreate the response by one or more of the sensing organ or sensing organs, the vestibular system, and the memory of the subject. A support structure is configured for placement on or about a person's head. The support structure is configured to support at least the focused ultrasound transducer arrangement.

    DESIGN OF INTELLIGENT RESILIENT STRUCTURES VIA AUTOMATIC PLACEMENT OF SENSOR AND SMART ACTUATORS

    公开(公告)号:US20240273245A1

    公开(公告)日:2024-08-15

    申请号:US18168011

    申请日:2023-02-13

    CPC classification number: G06F30/10 G06F2119/02

    Abstract: An innovative method to automatically place sensors and stimuli-sensitive active actuators to neutralize the effects of structural faults and design a smart fault-resilient system is described. To the best of our knowledge, the proposed framework is the first systematic integration of thermally activated shape memory polymer actuators with a sensor distribution framework targeted to bring a damaged structural system to its native state. The framework does not explicitly model the material constitutive model and hence can be applied to linear and nonlinear material behaviors. The approach enables the design of resilient smart structures that can be additively manufactured. The framework computes a matrix of relative importance for different sensor positions and uses that to optimally place actuators to reconfigure the system in presence of faults.

    PREDICTION OF REMAINING USEFUL LIFE OF AN ASSET USING CONFORMAL MATHEMATICAL FILTERING

    公开(公告)号:US20240264590A1

    公开(公告)日:2024-08-08

    申请号:US18105317

    申请日:2023-02-03

    CPC classification number: G05B23/0283 G05B23/0254

    Abstract: A system determines that an asset of an engineering system has transitioned from a quasi-steady degradation stage to an accelerated degradation phase based on sensor measurements received from an asset. During the accelerated degradation phase, features are extracted from the sensor measurements that are indicative of wear of the asset. A conformal mathematical filter is applied to the features that causes the features to conform to a wear curve formulation associated with the asset. An output of the filter is resampled to form a noise-reduced signal. The noise-reduced signal is input into a sequence machine learning model. A loss function of the sequence machine learning model uses an increased penalty to overprediction and a relaxed penalty for underprediction. An output of the sequence machine learning model is used to predict a remaining useful life (RUL) of the asset.

    MODELING OF LIQUID-GAS MENISCUS DYNAMICS FOR ARBITRARY NOZZLE GEOMETRIES

    公开(公告)号:US20240211655A1

    公开(公告)日:2024-06-27

    申请号:US18086348

    申请日:2022-12-21

    CPC classification number: G06F30/23 G06F2113/10

    Abstract: Techniques for determining a damping rate of unforced oscillations of a meniscus are disclosed. An example method includes receiving input describing a shape of a container, physical parameters of a liquid inside the container, and an equilibrium shape of the meniscus. The method also includes generating a mesh conforming to the shape of the container and generating a discrete version of a continuous eigenvalue problem based on this mesh. The method also includes computing, at appropriate mesh nodes, values for pressure, velocity components, and meniscus surface deformation corresponding to a suitable number of least-damped late-time oscillation modes of the liquid and computing an angular frequency and damping rate of these least-damped late-time oscillation modes from the discrete version of the continuous eigenvalue problem. The method also includes identifying the mode that has the lowest damping rate and computing a liquid relaxation time by inverting the damping rate of the identified mode.

    REMAINING USEFUL LIFE ESTIMATION USING HYBRID PHYSICS-MACHINE LEARNING REASONING

    公开(公告)号:US20240210934A1

    公开(公告)日:2024-06-27

    申请号:US18086325

    申请日:2022-12-21

    CPC classification number: G05B23/0283 G06N3/0985

    Abstract: Condition-monitoring data of an engineering system is received at a computing system. The condition-monitoring data is input to a hybrid model that includes a machine learning model empowered with physics-informed transfer functions on the computing system. The machine learning model outputting a prediction of health variables of the engineering system as intermediate variables. These variables are transformed via mathematically parametrized transfer functions on the computing system. A remaining useful life of the engineering system is estimated based on the transformation outputs. The remaining useful life is used to perform a remedial action on the engineering system.

    METHOD AND SYSTEM FOR AUTOMATICALLY CREATING A PLAN FOR HYBRID MANUFACTURING

    公开(公告)号:US20240201665A1

    公开(公告)日:2024-06-20

    申请号:US18081086

    申请日:2022-12-14

    CPC classification number: G05B19/41835 G05B2219/23012

    Abstract: An approach to automating hybrid manufacturing is provided. This approach first splits an item of manufacture into irreducible pieces called atoms, then extracts constraints between the atoms, and then uses a planner to find the best way to assemble the atoms into the item of manufacture given the constraints. The approach splits the item into atoms based on various properties such as the presence or absence of support, the need for scaffolding, tool reachability constraints, and the presence of cycles of dependencies which prevent the item from being manufactured.

    SYSTEM AND METHOD FOR ESTIMATING ERRORS IN A SENSOR NETWORK IMPLEMENTING HIGH FREQUENCY (HF) COMMUNICATION CHANNELS

    公开(公告)号:US20240195524A1

    公开(公告)日:2024-06-13

    申请号:US18077108

    申请日:2022-12-07

    CPC classification number: H04L1/0036

    Abstract: One embodiment can provide a method and system for estimating a remote quantity of interest (QoI). During operation, the system can receive, over a communication channel, a radio frequency (RF) signal carrying an estimate of the QoI measured by a sensor. The system can estimate probability distributions of a set of random channel parameters associated with the HF communication channel. The system can further reconstruct the estimate based on the probability distributions of the channel parameters and the received RF signal, determine a level of uncertainty associated with the reconstructed estimate, and combine reconstructed estimates from multiple sensors based on the determined level of uncertainty associated with each reconstructed estimate to output a combined estimate of the QoI.

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