Abstract: A predictive maintenance server receives data from sensors of equipment. The server uses one or more machine learning models to assign an anomaly score. Responsive to the anomaly score exceeding a threshold value, the server may issue an alert. The machine learning model may be supervised or unsupervised. In one embodiment, the machine learning model use several sensor channels to predict the values of one or more vitals of the equipment and compare the predicted values to the actual measured values of the vitals. The server may assign an anomaly score based on the differences between the predicted values and the measured values. In one embodiment, the machine learning model may be an autoencoder that generates a distribution of the measurement values to determine the likelihood of observing the actual measured values in a normal operation. In one embodiment, the server may use a histogram approach to predict anomaly.

Abstract: A system and method for obtaining frequency-domain admittance/impedance using a few sets of time-series data. Utilizing an Eigensystem Realization Algorithm (ERA) or a dynamic mode decomposition (DMD), the input/output frequency-domain model reflecting voltage/current relationship is identified, and admittance/impedance identification is demonstrated for a grid-connected inverter-based resource (IBR) system. The proposed approach provides a powerful tool to replace the state-of-the-art harmonic injection methodology.

Abstract: A battery value setting apparatus including an electronic control unit including a microprocessor and a memory connected to the microprocessor. The microprocessor is configured to perform, acquiring a battery information including an information on a usage record of a battery mounted on a predetermined object, determining whether there is an abnormal usage record of the battery based on the battery information, and setting a trade-in value of the battery when it is determined that there is the abnormal usage record lower than the trade-in value when it is determined that there is not the abnormal usage record.

Abstract: An anomaly detection device includes: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to: cluster a plurality of power storage systems into a plurality of clusters; generate a detection model for detecting an anomaly in the power storage systems for each of the clusters; and detect an anomaly in the power storage system for each of the clusters by using the detection model associated with the cluster.

Abstract: A multi-stage inversion method for deblending seismic data includes: a) acquiring blended seismic data from a plurality of seismic sources; b) constructing an optimization model that includes the acquired blended seismic data and unblended seismic data; c) performing sparse inversion, via a computer processor, on the optimization model; d) estimating high-amplitude coherent energy from result of the performing sparse inversion in c); e) re-blending the estimated high-amplitude coherent energy; and f) computing blended data with an attenuated direct arrival energy.

Abstract: An innovative apparatus and computer implemented methods to obtain values for a set of scalars corresponding to each force and displacement, which may be obtained from acoustical signals captured by sensors of a drill bit while drilling, in a material of known mechanical properties, such as a cement from casing the well, such that the application and use of the scalars in relation to measurements of the mechanics while drilling, such as the acceleration of the bit and motion of the bit captured by sensors such as accelerometers, allow for absolute values of mechanical rock properties to be obtained in rock formations, being drilled through, with otherwise unknown mechanical properties prior to drilling.

Abstract: Provided is a battery estimation system comprising a processor and a storage device coupled to the processor. The storage device stores accelerated test data obtained by measuring change in degree of deterioration of a rechargeable battery cell at a predetermined temperature. The processor calculates a relationship between the temperature and the magnitude of an activation energy of the rechargeable battery cell on the basis of the accelerated test data, calculates a temperature as a maximum temperature on the basis of the relationship between the temperature and the magnitude of the activation energy of the rechargeable battery cell, the calculated temperature being a temperature at which the magnitude of the activation energy changes from decreasing to increasing in response to increase in the temperature, and determines a temperature equal to or less than the maximum temperature as a temperature to be used in an accelerated test.

Abstract: A developing cartridge includes a casing, a developer-carrying member, a supply member, a developing electrode, a supply electrode, and an insulating member. The casing is configured to accommodate therein developer. The developer-carrying member is configured to rotate about a rotational axis and carry the developer thereon. The supply member is configured to supply the developer to the developer-carrying member. The developing electrode is configured to be electrically connected to the developer-carrying member. The supply electrode is configured to be electrically connected to the supply member. The insulating member insulates the developing electrode and the supply electrode with each other. The developing electrode, the insulating member, and the supply electrode are overlapped in this order in an axial direction of the rotational axis.

Abstract: Disclosed in the present invention is a method for predicting a weather-related dangerous situation at a specific point on the path of a user by referencing separate observation data observed from multiple observation points, comprising the steps of: a weather-related dangerous situation prediction server obtaining observation data from each of the observation points; and (b) the server predicting the weather status of the specific point by analyzing geographical distribution information of the observation data and/or temporal change information of the observation data by referencing a machine learning database.

Abstract: A method for estimating a capacity of an electrical energy storage device with higher accuracy than what is provided in the prior art. The uncertainties in measured electrical current or voltage used in the estimation of the capacity of the electrical energy storage device are at least partly compensated for by using a bias compensated capacity estimator instead of the often-used prior art capacity estimator. The accuracy of the voltage and/or electric current sensor becomes of less importance which leads to that less complicated and less costly sensors may be used and to improve accuracy of the estimated energy storage capacity. The above advantages are obtained by providing a bias compensated capacity estimator that includes at least one bias term which is related to a deviation of an expected value of an original capacity estimator from a true capacity value.

Abstract: A method that occurs at a calibration system includes generating a first digital record based on a calibration of the calibration system using a calibration source; providing a copy of the first digital record to a first device under test (DUT); and providing a calibration test signal associated with a calibration of the first DUT, wherein the first DUT uses the first digital record in generating a second digital record based on the calibration of the first DUT.

Abstract: A method for predicting time-to-failure and remaining-life of an electrical power system asset includes analyzing characteristics of the power system asset over a specified time interval; based on the analysis, associating the power system asset with a pool of similar power system assets having similar historical performance characteristics; and based on the association, calculating time-to-failure and remaining-life probability factors for the power system asset. A computer program product is also provided for carrying out the method, and the method may further include a mechanism whereby the computer program learns ways to modify and enhance the analysis of the performance characteristics to provide for higher confidence levels in time-to-failure and remaining-life probability calculations.

Abstract: Implementations are described herein for predicting a future climate condition in an agricultural area. In various implementations, a teleconnection model may be applied to a dataset of remote climate conditions such as water surface temperatures to identify one or more of the most influential remote climate conditions on the future climate condition in the agricultural area. A trained machine learning model may be applied to the one or more most influential remote climate conditions and to historical climate data for the agricultural area to generate data indicative of the predicted future climate condition. Based on the data indicative of the predicted future climate condition, one or more output components may be caused to render output that conveys the predicted future climate condition.

Abstract: An estimation device include: an acquisition unit that acquires information relating to a part of a third characteristic that is an energy storage amount-voltage charge characteristic and/or a fourth characteristic that is an energy storage amount-voltage discharge characteristic, of an energy storage device; a storage unit that stores a plurality of energy storage amount characteristics that are at least any of first characteristics, second characteristics, third characteristics that are energy storage amount-voltage charge characteristics, fourth characteristics that are energy storage amount-voltage discharge characteristics, and pieces of V?dQ/dV in correspondence with a change in a feature value, which is changed by repeated charge-discharge, or stores as a function of the feature value; and a first estimation unit that estimates an internal state of the energy storage device on the basis of the information and the energy storage amount characteristics.

Abstract: In one embodiment, a sensor device includes a sensor configured to obtain sensor data and a communication interface configured to communicate with a set of secondary sensor devices. The set of secondary sensor devices comprise a set of secondary sensors and a set of secondary processing devices. The set of secondary sensors obtain additional sensor data. The set of secondary processing devices process the additional sensor data based on a set of secondary machine learning models, and generate activation data based on the additional sensor data. The sensor device also includes a processing device. The processing device is also configured to receive the activation data from the set of secondary sensor devices and cause the sensor to obtain first sensor data based on the activation data. The processing device is further configured to generate one or more inferences based on the first sensor data and a machine learning model.

Abstract: Technologies are provided for feature-based continuous integration. A feature manifest can be created that identifies versions of program/hardware definition assets (such as source code files and register-transfer-level (RTL) definition files) that are stored in separate source control repositories but are related to a particular application or hardware feature. The identified versions of the assets can be retrieved from the separate repositories and, optionally, built, deployed, and/or tested. For example, a hardware feature manifest can be defined that identifies a version of an RTL definition for a hardware component stored in a first repository and a version of a verification program stored in a second repository. The hardware feature manifest can be used to retrieve the identified RTL definition from the first repository and to deploy it. The identified version of the verification program can be retrieved from the second repository and used to test the deployed RTL definition.

Abstract: Apparatus and methods for obtaining initial settings of station-specific parameters descriptive of wellbore/formation properties specific to downhole pressure test stations, and obtaining initial settings of station-shared parameters descriptive of petrophysical properties of petrophysically unique formation zones. A pressure transient model of the zones is obtained by regression utilizing the pressure data of each station and the initial settings of the station-specific and station-shared parameters. The regression analytically determines a model value of at least one of the station-specific parameters and the station-shared parameters.

Abstract: Disclosed in present invention are a method for supporting aviation safety and a server for same, the method comprising the steps of: (a) the server for supporting aviation safety obtaining observation data measured from each of a plurality of weather observation apparatuses located in a specific zone; and (b) the server for supporting aviation safety predicting the weather state in the specific zone at a certain time after the current time by analyzing a generated map by referencing a machine learning database.

Abstract: A developing cartridge includes a casing, a developer-carrying member, a supply member, a developing electrode, a supply electrode, and an insulating member. The casing is configured to accommodate therein developer. The developer-carrying member is configured to rotate about a rotational axis and carry the developer thereon. The supply member is configured to supply the developer to the developer-carrying member. The developing electrode is configured to be electrically connected to the developer-carrying member. The supply electrode is configured to be electrically connected to the supply member. The insulating member insulates the developing electrode and the supply electrode with each other. The developing electrode, the insulating member, and the supply electrode are overlapped in this order in an axial direction of the rotational axis.

Abstract: A system for recycling a mobile device. A system configured in accordance with one embodiment of the present technology includes an electrical connector and testing electronics. The electrical connector is configured to be electrically connected to a mobile device, and the testing electronics are configured to produce an electrical measurement by measuring an electrical attribute associated with a hardware component of the mobile device over the electrical connector. The system is further configured to valuate, identify, and/or authenticate the mobile device based at least in part on the electrical measurement.