Abstract: A comparison unit (22) compares a measurement value, which is one of changes over time in a voltage value of a bus line (11), distance transition of the voltage value, changes over time in an impedance value of the bus line (11), and distance transition of the impedance value that have been measured, with a normal value, which is one of changes over time in a voltage value of the bus line (11), distance transition of the voltage value, changes over time in an impedance value of the bus line (11), and distance transition of the impedance value in a normal state, and extracts a difference between the measurement value and the normal value. An unauthorized connection determination unit (24) evaluates the difference between the measurement value and the normal value extracted by the comparison unit (22), so as to determine whether an unauthorized device is connected to the bus line (11).

Abstract: A system that can automatically measure, track, and/or report train emissions for complying with geographic environmental restrictions. An emissions module determines the amount of emissions emitted by a train over time. A location module tracks the location of the locomotive of the train relative geographic locations having emission regulations. A compliance module records the amount of emissions emitted by the train in the geographic location.

Abstract: A battery diagnosis apparatus and a battery diagnosis method for accurately diagnosing a secondary battery are proposed. A pulse current generator, a voltage measuring instrument that measures a voltage response to application of a current pulse, a first data processing device that obtains a chronopotentiogram (CP) indicating a change in the voltage response over time and normalizes the CP, a database that saves normalized data, and a second data processing device that uses a correlation between the saved data and a battery state expressing factor prepared in advance to make a battery diagnosis are used. Desirably, the current pulse is a current in the same direction at the time of data obtainment and at the time of a diagnosis. Further, a noise filter for an input signal of the CP and resampling means for reducing the number of pieces of data input to the first data processing device are provided.

Abstract: The disclosed embodiments relate to a system that facilitates development of machine-learning techniques to perform prognostic-surveillance operations on time-series data from a monitored system, such as a power plant and associated power-distribution system. During operation, the system receives original time-series signals comprising sequences of observations obtained from sensors in the monitored system. Next, the system decomposes the original time-series signals into deterministic and stochastic components. The system then uses the deterministic and stochastic components to produce synthetic time-series signals, which are statistically indistinguishable from the original time-series signals. Finally, the system enables a developer to use the synthetic time-series signals to develop machine-learning (ML) techniques to perform prognostic-surveillance operations on subsequently received time-series signals from the monitored system.

Abstract: Systems and method for data collection in an industrial environment can include interpreting a plurality of sensor data values, each sensor operatively coupled to at least one of a plurality of components in the industrial environmental. In response to at least a portion of the plurality of sensor data values, determining a recognized pattern value and providing a system characterization value for the industrial system in response to the recognized pattern value.

Abstract: Provided is an aerosol generating device having a function of estimating battery life, the aerosol generating device including a heater configured to generate an aerosol by heating an aerosol generating substance; a battery configured to supply power to the heater; a counter configured to count the number of usage times the aerosol generating device is used by a user; and a controller configured to control power supplied to the heater, wherein the controller estimates a remaining life of the battery based on at least two from among an initial output voltage of the battery, an output voltage of the battery dropped as the aerosol generating device is used for a counted number of usage times, and the counted number of usage times.

Abstract: System and methods for data collection, processing, and utilization of signals in an industrial environment are disclosed. A data acquisition circuit structured to interpret a plurality of detection values from a plurality of input sensors communicatively coupled to the data acquisition circuit, a peak detection circuit to determine at least one peak value in response to the plurality of detection values, a peak response circuit to select at least one detection value in response to the at least one peak value, a communication circuit to communicate the at least one selected detection value to a remote server, and a monitoring application on the remote server to receive the at least one selected detection value, jointly analyze received detection values and recommend an action in response are disclosed herein.

Abstract: A vehicle test device is to test performance of a vehicle or a part of the vehicle by rotating a wheel placed on a rotating body in order to reproduce an actually running state of the vehicle by controlling rotational speed of the wheel so as to make the rotational speed equal to a target value accurately, and a rotation related value that indicates rotational speed of the wheel or torque applied to the wheel is obtained, and the rotational speed of the rotating body or the torque applied to the rotating body is controlled so as to make the rotation related value equal to a predetermined target value.

Abstract: A method, apparatus, system for batter material screening is disclosed. First, microstructure generation parameters for a plurality of microstructures are received, where the microstructure generation parameters include microstructure characteristics. Microstructure statistics are generated using a first artificial intelligence (“AI”) model, where the received microstructure generation parameters are inputs for the first AI model. Microstructure properties are predicted using a second AI model for the microstructures based on the generated microstructure statistics, the received microstructure generation parameters, and battery cell characteristics. It is determined whether at least one of the microstructures is within a predefined energy profile range based on the predicted microstructure properties.

Abstract: Provided is a method for determining convergence in full wavefield inversion (FWI) of 4D seismic (time-lapse seismic: 3D seismic surveys acquired at different times with the first survey termed as the baseline and subsequent surveys termed as monitors). FWI applied to field seismic data includes iteratively solving for subsurface property models and model difference between monitor and baseline. Iteration occurs until the model difference is sufficiently converged. Rather than determining convergence by examining an entire subsurface region of the models and/or the model difference, subparts of the subsurface region models and/or the model difference are examined in order to determine convergence. For example, different regions behave differently, include the target reservoir region (where hydrocarbon is present) and the background region that is outside the target reservoir region.

Abstract: A system includes a data interface that receives data associated with a plurality of wells; an inference engine that receives and analyzes at least a portion of the data to generate results; and a communication engine that outputs information based at least in part on the results.

Abstract: A computing system, method, and apparatus for determining a state of health indication for a battery are provided. A first supervised deep neural network (“DNN”) is trained using received characteristics for the battery as input and received process parameters as outputs. An unsupervised AI estimator is trained using one or more clustering methods based on extracted features from the first supervised DNN, where the received characteristics are input to the unsupervised AI estimator. A second supervised DNN is trained using identified clusters from the unsupervised AI estimator. The identified clusters are validated with state of health indications. User battery data is inputted to the second supervised DNN to determine the state of health for the battery.

Abstract: Systems and methods for monitoring data collection in an industrial environment are disclosed. A data acquisition circuit structured to interpret a plurality of detection values from a plurality of input sensors communicatively coupled to the data acquisition circuit, each of the plurality of detection values corresponding to at least one of the plurality of input sensors, a peak detection circuit structured to determine at least one peak value in response to the plurality of detection values and a peak response circuit structured to perform at least one operation in response to the at least one peak value are disclosed.

Abstract: A battery deterioration judging system includes a memory, and a processor coupled to the memory. The processor is configured to acquire a state amount of a battery, derive a first deterioration probability of the battery, based on the state amount of the battery and a predetermined first calculation model, derive a reliability degree of a second calculation model, which is different than the first calculation model, based on a number of state amounts, derive a second deterioration probability of the battery, based on the state amount of the battery and the second calculation model, and judge deterioration of the battery based on the reliability degree, and at least one of the first deterioration probability or the second deterioration probability.

Abstract: The disclosed systems and methods are generally directed to interpreting neuromuscular signals. The system includes (A) a plurality of neuromuscular sensors that detect a plurality of neuromuscular signals from a user and (B) at least one multiplexer in communication with the plurality of neuromuscular sensors and that is capable of dynamically adjusting neuromuscular sensor processing based on neuromuscular signal characteristics. A computer processor is programmed to (i) receive a set of neuromuscular signals from the plurality of neuromuscular sensors, (ii) determine, via a real-time system, at least one signal characteristic included in a neuromuscular signal, where the neuromuscular signal is associated with a first neuromuscular sensor included in the plurality of neuromuscular sensors; and (iii) dynamically reconfigure the processing of neuromuscular signals from the plurality of neuromuscular sensors based on an output from the multiplexer.

Abstract: A method can include receiving data acquired via survey equipment disposed in an environment; analyzing at least a portion of the data via an iterative adaptive approach that implements matching pursuit to generate analysis results; and identifying at least one feature in the environment based at least in part on a portion of the analysis results.

Abstract: Physical-device anomalies and degradation can be mitigated by implementing some aspects described herein. For example, a system can determine a first data window and a second data window by applying a window function to streaming data. The system can determine a first principal eigenvector of the first data window and a first principal eigenvector of the second data window. The system can determine an angle change between the first principal eigenvectors of the two data windows. The system can then detect an anomaly based on determining that the angle change exceeds a predefined angle-change threshold. Additionally or alternatively, the system may compare the first principal eigenvector for the second data window to a baseline value to determine an absolute angle associated with the second data window. The system can then detect a degradation based on determining that the absolute angle exceeds a predefined absolute-angle threshold.

Abstract: The invention notably relates to a computer-implemented method for processing a 4D seismic signal relative to a subsoil, the subsoil including a zone subject to extraction and/or injection, the method comprising: providing the 4D seismic signal; identifying a part of the 4D seismic signal corresponding to a zone of the subsoil distinct from the zone subject to extraction and/or injection; determining a noise model of the 4D seismic signal based on the identified part of the 4D seismic signal; and processing the 4D seismic signal based on the noise model. This improves the field of 4D seismic data processing.

Abstract: A plant operating condition setting support system for supporting the setting of a plant operating condition includes: a learning device that learns a regression model for calculating, from values of a plurality of state parameters indicating an operating condition of a plant and values of a plurality of manipulation parameters set to control an operation of the plant, a predicted value of an output indicating a result of operating the plant when the values of the plurality of manipulation parameters are set in the operating condition indicated by the values of the plurality of state parameters; and an operating condition setting support device that calculates the values of the plurality of manipulation parameters that should be set to control the operation of the plant, by using the regression model learned by the learning device.

Abstract: Processing of data relating to energy usage. First data relating to energy usage is loaded for analysis by an energy management platform. Second data relating to energy usage is stream processed by the energy management platform. Third data relating to energy usage is batch parallel processed by the energy management platform. Additional computing resources, owned by a third party separate from an entity that owns the computer system that supports the energy management platform, are provisioned based on increasing computing demand. Existing computing resources owned by the third party are released based on decreasing computing demand.