Abstract: A method and a system for using machine learning technologies to predict the value and timing of operational parameters. These predictions are then used to identify the risk of certain well incidents to occur, and if so notify responsible personnel thereof as to allow preventive actions to be taken.

Abstract: A forced discharge test apparatus includes a heating circuit; a discharge circuit; a temperature sensor; and a controller. When the controller receives a test command indicating a test resistance and a test temperature, the controller outputs a first control signal to the heating circuit to increase the temperature of a battery cell. The controller outputs a second control signal to the discharge circuit to discharge the battery cell when the temperature of the battery cell reaches the set test temperature. The controller determines that the test temperature is valid with respect to the test resistance when the temperature of the battery cell is equal to or lower than the upper temperature limit at a time point at which a predetermined heating time has passed from a time point when the first control signal is outputted.

Abstract: Methods, systems and devices for providing improved calibration accuracy of continuous and/or in vivo analyte monitoring systems based at least in part on insulin delivery information are provided. Many of the embodiments disclosed herein can determine appropriate conditions for performing a calibration of the analyte sensor in view of the scheduled delivery of insulin or administered insulin amount. One or more other parameters or conditions can also be incorporated to improve calibration accuracy including, for example, the physiological model associated with a patient, meal information, exercise information, activity information, disease information, historical physiological condition information, as well as other types of information. Furthermore, according to some embodiments, calibration of the analyte sensor can be delayed or not performed at all, if appropriate conditions are not met.

Abstract: Disclosed herein is a method of detecting stalled state of a dynamic pool equipment unit, comprising receiving a plurality of movement features relating to a dynamic pool equipment unit deployed in a water pool which are captured during a predefined sampling window and comprise (1) motion features of the pool equipment unit, and (2) operational features of electric motor(s) of the pool equipment unit, determining a movement pattern of the pool equipment unit using one or more statistical models applied to the plurality of movement features which are trained to estimate a stalled state of the pool equipment unit in which the pool equipment unit is pitched up and unable to advance on a slopped obstacle in the water pool, and causing the pool equipment unit to stop attempted advance in a current direction responsive to determining that the pool equipment unit is in the stalled state.

Abstract: A system is configured to track and store system and event data for various computing devices. The system is configured to associate the various computing devices with profiles based at least in part on characteristics of the computing devices. The system is further configured to compare performance data and/or performance metrics for particular computing devices having a particular profile against all other devices that share the particular profile. The system then displays this comparison to a user of the particular computing device, substantially automatically diagnoses an issue with the particular computing device based on the performance and system event data, and/or enables the user to diagnose the problem based on the performance and system event data.

Abstract: The present disclosure generally pertains to methods of identifying and quantitating host cell proteins (HCPs) in therapeutic protein development. In particular, the present invention generally pertains to methods of liquid chromatography-tandem mass spectrometry (LC-MS/MS) for unbiased identification and sensitive quantitation of HCPs in therapeutic protein development.

Abstract: A controller for a power converter includes an output terminal operative to output a modulation signal for controlling a phase current of the power converter. A modulator is operative to generate the modulation signal such that an output voltage of the power converter follows a first portion of a load-line when load current is above a first threshold, the first portion of the load-line having a first slope that determines a rate of change of the output voltage as a function of the load current. An interface is operative to receive a temperature signal. Circuitry is operative to change the first threshold in response to receipt of the temperature signal.

Abstract: A method of polishing a substrate includes polishing a conductive layer on the substrate at a polishing station, monitoring the layer with an in-situ eddy current monitoring system to generate a plurality of measured signals values for a plurality of different locations on the layer, generating thickness measurements the locations, and detecting a polishing endpoint or modifying a polishing parameter based on the thickness measurements. The conductive layer is formed of a first material having a first conductivity. Generating includes calculating initial thickness values based on the plurality of measured signals values and processing the initial thickness values through a neural network that was trained using training data acquired by measuring calibration substrates having a conductive layer formed of a second material having a second conductivity that is lower than the first conductivity to generated adjusted thickness values.

Abstract: A system and method are provided for extracting information regarding a drill site including forming one or more documents having one or more raw comments regarding a well site. Raw data may be extracted from the one or more documents to produce extracted raw data. The extracted raw date may be pre-processed by removing ambiguity, artifacts, and/or formatting errors from the one or more raw comments to produce pre-processed data. Topics data may be extracted from the pre-processed data using a natural language processing (NLP) algorithm to produce extracted topics data. Measurement data may also be extracted from the pre-processed data using the NLP algorithm to produce extracted measurement data. The extracted topics data and the extracted measurement data may be aggregated to form a set of discrete data points, such as calibration points, per comment to produce aggregated data and one more calibration points may be identified from the aggregated data.

Abstract: A method of determining ego-motion information of a vehicle comprising a radar sensor having a plurality of antenna elements, comprising: acquiring motion spectrum comprising a plurality of data elements, each calculated for a respective one of a plurality of Doppler bin indices and for a respective one of a plurality of spatial bin indices, each spatial bin index indicating a respective angle-of-arrival of a radar return signal at the radar sensor; and determining the ego-motion information by solving a motion equation system comprising equations of motion generated using the motion spectrum data and each relating a respective value indicating a radial velocity, a respective value indicating an angular displacement, and a variable indicating a velocity of the vehicle.

Abstract: A system includes a compressor outlet temperature module, a refrigerant quality module, and a correction factor module. The compressor outlet temperature module is configured to estimate a temperature at an outlet of a compressor in a thermal system of an electric vehicle. The refrigerant quality module is configured to estimate a quality of refrigerant at an inlet of the compressor based on an enthalpy at the compressor inlet and an inlet enthalpy correction factor. The refrigerant quality is a ratio of vapor refrigerant mass to total refrigerant mass. The correction factor module is configured to determine the inlet enthalpy correction factor based on the estimated compressor outlet temperature and a temperature measured at the compressor outlet.

Abstract: A method includes, in response to receiving a forecasting request from a user device via a web portal, determining a measure of uncertainty associated with an input vector specified by the forecasting request. The measure of uncertainty includes a compact representation of uncertainty associated with future time intervals specified by the forecasting request. The method includes obtaining a set of historical data from a time-series data store. The method includes generating a forecast model using the set of historical data, the input vector, and the measure of uncertainty to predict outcomes incrementally for the future time intervals. The method includes determining a predicted outcome using the forecast model at an end of the future time intervals. The method includes, in response to the predicted outcome exceeding a threshold, generating a graphical user interface. The graphical user interface illustrates the mean vector and a magnitude of the predicted uncertainty measure.

Abstract: An aero-engine fault diagnosis method based on 5G edge computing and deep learning is provided. The method includes following steps: performing data acquisition, preprocessing, and storage based on a new 5th Generation Mobile Communication Technology (5G) cloud-edge-terminal network architecture; constructing a machine learning module in an edge cloud, where historical data stored in the aero-engine fault database management system is used as training samples of the machine learning module; and performing intelligent self-management of the aero-engine gear fault simulation platform and the aero-engine fault database management system.

Abstract: The method may comprise receiving historical data (e.g., mineralogy data, irrigation data, raffinate data, heat data, lift height data, geographic data on ore placement and/or blower data); training a predictive model using the historical data to create a trained predictive model; adding future assumption data to the trained predictive model; running the forecast engine for a plurality of parameters to obtain forecast data for a mining production target; comparing the forecast data for the mining production target to the actual data for the mining production target; determining deviations between the forecast data and the actual data, based on the comparing; and changing each of the plurality of parameters from the forecast data to the actual data to determine a contribution to the deviations for each of the plurality of parameters.

Abstract: A fully self-contained portable location tracking device autonomously compares a current location with a latitude-longitude map stored in memory. The latitude-longitude map stores guidance zone values indicative of a predetermined safe zone, progressive alert zones, and a predetermined reference point. The guidance zone values represent actions to be taken based upon current location. When initiated by some combination of current location or zone value, location history, and time, or when otherwise queried, the tracking device transmits the offset from reference location, rather than actual current location data, to at least one wireless communications monitoring apparatus. The monitoring apparatus also stores a copy of the latitude-longitude map and reference point. Using the received offset, the monitoring apparatus knows both the location of the location tracking device and the actions to be taken based upon current location.

Abstract: Hitherto, preprocessing for separating impurities and calculation processing, for example, a peak splitting method, are required in order to acquire information on test substances from spectral information. An information processing apparatus according to the present invention includes information acquisition means for acquiring quantitative information on a test substance estimated by inputting spectral information on a sample containing the test substance and impurities into a learning model.

Abstract: Methods may comprise: identifying a fault indicator associated with a physical system; collecting first data related to a state of the physical system; applying a surrogate model to the first data to produce a plurality of potential fault modes; applying an optimization algorithm to the plurality of potential fault modes using a similarity metric to produce an input and a plurality of outputs, wherein each of the plurality of outputs corresponds to one of the plurality of potential fault modes, wherein the input provides differentiation between each of the plurality of outputs; applying the input to the physical system; collecting second data from physical system in response to applying the input; identifying a true mode of the physical system based on a comparison of the second data and the plurality of outputs; and diagnosing a fault of the physical system based on the true mode.

Abstract: A system for providing a visual summary of a condition of a patient when traumatic brain injury (TBI) is suspected or diagnosed includes at least one patient condition sensor configured to sense data representative of a patient condition parameter of interest for a TBI patient; at least one airflow sensor configured to sense data representative of ventilations provided to the patient; at least one visual display for providing the visual summary to a user; and at least one controller. The at least one controller is configured to cause the visual display to provide the visual summary. The visual summary can include at least one visual representation of at least one patient condition parameter for each time interval of a plurality of time intervals, at least one visual representation of ventilation information, and a visual indication of when at least one patient condition parameter is outside of a target range.

Abstract: A diagnostic device for a sensor for measuring the position of a motor-vehicle drive shaft. The sensor includes a first wired communication link and a second wired communication link, via which wired communication links the sensor sends the signal, and being characterized by an average reference voltage. The diagnostic device for a sensor being intended to be electrically connected between the first wired communication link and the second wired communication link and being configured to: a) receive a first voltage value corresponding to the average voltage in the first wired communication link and a second voltage value corresponding to the average voltage in the second wired communication link; b) detect a short circuit on the first wired communication link; or c) detect a short circuit on the second wired communication link.

Abstract: A computational method for training a neural network force field (NNFF) configured to simulate molecular and/or atomic motion within a material system. The method includes the step of receiving molecular structure data of a molecule in the material system. The method also includes optimizing a geometry of the molecule using the molecular structure data and a density functional theory (DFT) simulation to obtain DFT optimized geometry data. The method further includes optimizing the geometry of the molecule using the molecular structure data and a classical force field (FF) simulation to obtain FF optimized geometry data. The method also includes outputting NNFF training data comprised of the DFT optimized geometry data and the FF optimized geometry data. The NNFF training data is configured to train an NNFF for simulating molecular and/or atomic molecular and/or atomic motion within the material system.