Abstract: A system for managing a battery of a vehicle includes a battery, a main relay connected to the battery to transfer or block power of the battery to components in the vehicle, and a controller. The controller is configured to control the components in the vehicle to be in a power-off (IG OFF) state and turning off the main relay when receiving a vehicle power-off input, and to determine whether or not the battery is abnormal by calculating a parameter for determining a state of the battery and comparing the calculated parameter with a plurality of reference values that are preset.

Abstract: A method of diagnosing an electrical energy storage apparatus includes exciting at least one energy storage system in the electrical energy storage apparatus; sampling data associated with an electrical characteristic of the at least one energy storage system in response to the excitation of the at least one energy storage system; and estimating at least one electrical parameter and/or at least one operational condition attribute of the at least one energy storage system.

Abstract: Systems, methods, and apparatuses for enrolling a user with a product of a financial institution. A mobile device includes a processor; and a non-transitory computer readable medium storing instructions, which when executed by the processor, cause the processor to: establish a short-range communication channel with a financial institution computing device based on a tap exchange; retrieve personal information associated with an enrollment of the user with a product of a financial institution associated with the financial institution computing device; provide a graphical user interface indicating each piece of personal information scheduled for transmission to the financial institution computing device prior to transmission of each indicated piece of personal information to the financial institution computing device; and selectively transmit one or more pieces of indicated personal information to the financial institution computing device to enroll the user with the product.

Abstract: An estimation method executed by a computer, the estimation method includes estimating a fouling degree of a target ship based on an accumulation period since a most recent maintenance on the target ship; selecting, as training data, one piece of data that has a fouling degree that resembles the estimated fouling degree, from among a plurality of pieces of data, when generating a machine learning model for estimating an amount of fuel consumption due to navigation; and generating the machine learning model based on the selected training data.

Abstract: A system includes a processor that executes computer executable components. The computer executable components include a battery monitoring component that monitors a power level of a power unit of a sensor device that removably attaches to an absorbent article configured to absorb and contain bodily exudates; and a notification component that generates a replacement notification based on a determination that the power level is below a threshold power level.

Abstract: Example implementations described herein are directed to systems and methods for extracting signal in presence of strong noise for industrial Internet of Things (IoT) system especially for monitoring systems of consumable items such as lathe machines, coolers and so on. Example implementations can utilize a sawtooth mother Wavelet instead of usual wavelet analysis to cleanse the incoming sensor data, thereby allowing for the converting sensor data to feature values despite having heavy noise interference.

Abstract: A mass spectrometric data processing program that processes mass spectrometric data causes a data processor including a computer to execute a data conversion process in which representative value data, which is representative value data including a data set of a representative value of mass-to-charge ratio information and an ion intensity with respect to the representative value, is converted into profile data, which is ion intensity data with respect to the mass-to-charge ratio information.

Abstract: A method for estimating the harmonization values of a magnetometer installed in a mobile machine, said magnetometer being associated with its reference coordinate system XM, YM, ZM, said method, implemented by an electronic device, comprising acquiring magnetic field values measured by the magnetometer and determining the horizontal harmonization (hx, hy) by: estimating a first angle equal to the angle between XM and the large axis of an ellipse, defined in the plane comprising the two axes XM, ZM, by said acquired field values; determining hy as being equal to said first estimated angle, estimating a second angle equal to the angle between YM and the large axis of an ellipse defined, in the plane comprising the two axes YM, ZM, by said acquired field vector values; and determining—hx as being equal to said second estimated angle.

Abstract: A method includes performing by a processor: receiving a plurality of synchrophasor measurements of a power system signal associated with a time interval from a plurality of phasor measurement units (PMUs), respectively, each of the plurality of synchrophasor measurements including a phase angle, frequency value, and a timestamp associated with the synchrophasor measurement; determining, for each of the plurality of PMUs, a dominant mode frequency of a forced oscillation signal component of the power system signal based on the frequency value and the phase angle; determining, for each of the plurality of PMUs, a mode angle of the forced oscillation signal component at the dominant mode frequency; and determining a geographic forced oscillation source location for a source of the forced oscillation signal component based on the plurality of mode angles associated with each of the plurality of PMUs, respectively, and geographic locations of the plurality of PMUs.

Abstract: A method for charging a battery may include: obtaining a state of health of the battery and a magnitude of an initial charging current preset for the battery; converting the magnitude of the initial charging current on the basis of the state of health of the battery, thereby generating a charging current command; and providing the charging current command to a charger, and supplying a charging current corresponding to the charging current command to the battery by the charger.

Abstract: A spatial autocorrelation machine learning-based downscaling method of satellite precipitation data includes obtaining the TRMM precipitation data and the land surface parameters; preprocessing the land surface parameters to obtain DEM, day land surface temperature, night surface land temperature, day-and-night land surface temperature difference and NDVI with spatial resolutions of 1 km and 25 km; performing a spatial autocorrelation analysis of the TRMM precipitation data to obtain an estimated spatial autocorrelation value of the precipitation data with a spatial resolution of 25 km; downscaling the spatial resolution of the spatial autocorrelation value of the precipitation data from 25 km to 1 km; establishing a nonlinear regression model; obtaining a precipitation downscaling data with a spatial resolution of 1 km based on the nonlinear regression model. A system and a terminal are also provided.

Abstract: A topography apparatus may be coupled to an e-vaping device, within an interior defined by a housing of the e-vaping device, such that the topography apparatus may be coupled to an e-vaping device that may generate vapor independently of the topography apparatus. The topography apparatus may generate and communicate vapor topography data associated with vapor generation by the e-vaping device without altering an external appearance or vapor-generation performance of the e-vaping device. The topography apparatus may be detachably coupled to the interior of the e-vaping device. The topography apparatus includes an interface assembly configured to couple with a power supply, control circuitry, and/or sensor of the e-vaping device. Such coupling may include coupling with internal power or communication conduits of the e-vaping device, such that the topography apparatus taps into power and/or communication lines of the e-vaping device without requiring modification of the circuitry of the e-vaping device.

Abstract: A method is described for assessing subsurface structure uncertainty based on at least one subsurface horizon. The method calculates seismic continuity attributes to determine a mappability of the subsurface horizon(s); determines horizontal uncertainty for each fault in vertical uncertainty for each horizon; generates probabilistic scenarios for a subsurface geometry for at least one conceptual model; and generates a map of geological model uncertainty based on the probabilistic scenarios. In some embodiments, the probabilistic scenarios are stochastic simulations. In some embodiments, generating a map of geological model uncertainty is based on information entropy. The method may be executed by a computer system.

Abstract: A yield model generates a yield map for an agricultural field. A measurement system generates measured indicators that are a measurement or quantification of crop yield in the agricultural field. An observation system generates observed indicators that are spatial agricultural datasets describing observed characteristics of the agricultural field. To generate the yield map, the yield model generates a field array representing the agricultural field. The yield model generates an input array and a yield array by mapping the observed indicators and measured indicators to cells of the field array, respectively. The yield model determines a yield value for each cell of the yield array not including a mapped indicator using information included in the corresponding cells of the input array. The yield model generates a yield map using the determined yield values and the yield values in the yield array.

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: Included are embodiments for remotely determining a battery characteristic. Some embodiments include searching for a first wireless signal that identifies the energy storage device and, in response to receiving the first wireless signal, determining a current charge level of the energy storage device. Some embodiments include receiving a second wireless signal from the energy storage device, determining from the second wireless signal, whether the current charge level of the energy storage device reaches a predetermined threshold, and in response to determining that the current charge level of the energy storage device reaches the predetermined threshold, facilitating replacement of the battery.

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.