Abstract: A memory of an electronic control unit stores a neural network into which travel state quantities of a vehicle are input and from which an internal temperature of a turbocharger is output. An arithmetic processing circuit of the electronic control unit executes an internal temperature estimation process of calculating, as an estimated value of the internal temperature, an output of the neural network using measured values of the travel state quantities as an input, and a deposit amount estimation process of calculating an amount of increase in an amount of oil coke deposits based on the estimated value of the internal temperature and calculating an estimated value of the amount of oil coke deposits as a value integrating the amount of increase.

Abstract: There is disclosed a meteorological observation device for observing weather in an Atmospheric Boundary Layer or a Planetary Boundary Layer, comprising: a basic observation unit and one or more additional observation units which are connected directly or indirectly to the basic observation unit; a storage box whose inner space is compartmentalized to form a plurality of grids, wherein the grids include 1-st type cells, each of which holds the basic observation unit and each of the one or more additional observation units and 2-nd type cells, each of which forms 1-st sub space for holding a basic wire and 2-nd sub space for holding each of additional wires, wherein a size of each of the 2-nd type cells is determined as a size of each of the 1-st type cells.

Abstract: A method is provided for identifying or authenticating an object. The method includes vibrating the object at a plurality of frequencies. The vibrations from the object are sensed at each of the plurality of frequencies using an accelerometer. A vibration profile of the object is generated using the sensed vibrations. The generated vibration profile is then compared to a stored vibration profile. It is determined if the generated vibration profile matches the stored vibration profile. A match indicates that the object has been identified or authenticated. In another embodiment, an object capable of implementing the method is provided. In another embodiment, the object may include a replaceable accessary. In this case, the initial and generated vibration profiles may be created with the replacement accessary attached to the object. A match of the generated and initial vibration profiles indicates that the replaceable accessary is authentic.

Abstract: System and method for estimating how an atmospheric gas is distributed. A server receives prior data related to historical and/or theoretical global patterns of the gas, as well as measurements of the concentration and/or emission of the gas. The server passes the data and measurements to a database for storage and/or to at least one processor, which applies statistical inference methods to estimate a probability distribution of gas concentration and emission within the region. In one embodiment, the entire atmosphere is divided into numerous regions, and gas distributions are evaluated in each region, to thereby produce an estimated distribution covering the atmosphere. In some embodiments, the regions are divisions of an equirectangular projection of the Earth's surface and have a length and width of 0.025°.

Abstract: An information processing device includes processing circuitry configured to classify a plurality of partial waveform patterns that characterize a plurality of time series data into a plurality of classes based on the plurality of time series data classified into the plurality of classes, update shapes of the partial waveform patterns by fitting the partial waveform patterns to the time series data of the corresponding class, and reclassify the plurality of time series data into the plurality of classes based on the updated partial waveform patterns and difficulty levels that represent degrees of difficulty of classification and interpretation of the time series data.

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: For estimating motor torque and velocity, a method estimates a velocity profile for a motor based on line-to-line voltages and phase currents for the motor. The velocity profile is estimated without a position input and a velocity input. The method further estimates a torque profile for the motor based on the line-to-line voltages, the phase currents, and a time interval of the velocity profile of motor velocities greater than a velocity threshold, and wherein the motor is operating over the time interval.

Abstract: An information handling system may include a chassis configured to house components of the information handling system and an air mover assembly comprising an enclosure, an air mover within the enclosure configured to drive airflow to cool one or more components of the information handling system, and a sensor within a path of the airflow and configured to detect a presence of matter harmful to one or more components of the information handling system.

Abstract: Disclosed is a magnetotelluric inversion method based on a fully convolutional neural network.

Abstract: A forecasting system includes a processor and memory. The memory stores a time-series data store and instructions. The instructions include, in response to receiving a forecasting request from a user device for an entity including input data, determining a measure of uncertainty associated with the input data. The input data includes a proposed action and a forecast period. The instructions include obtaining a set of historical data from the time-series data store associated with the proposed action and generating a forecast model using the set of historical data, the input data, and the measure of uncertainty to predict outcomes incrementally during the forecast period. The instructions include determining a predicted outcome using the forecast model for the entity at an end of the forecast period and, in response to the predicted outcome exceeding a threshold, generating a communication indicating the proposed action and transmitting the communication to the user device.

Abstract: A predicting device, including a processor configured to: acquire displacement data that expresses a time series of displacements at respective points in time that are input to a vibration proofing member, and velocity data that expresses a time series of velocities at respective points in time that are input to the vibration proofing member; generate first load data of the vibration proofing member by inputting the acquired displacement data and velocity data into a model that is for inferring, from the displacement data and the velocity data, load data; generate second load data of the vibration proofing member by inputting the acquired displacement data and velocity data into a regression trained model that is for inferring, from the displacement data and the velocity data, load data; and infer load data relating to the vibration proofing member by adding together the generated first load data and the generated second load data.

Abstract: For each cell in a plurality of cells from a same manufacturing run, a first and a second cell characteristic are received in order to obtain a plurality of cell characteristics. For each cell, a batch compatibility number that is associated with a number of compatible cells that that cell is compatible with is determined based at least in part on the plurality of cell characteristics. The plurality of cells is sorted according to the batch compatibility numbers to obtain a sorted list of cells. A plurality of compatible cells to include in a battery is selected from the plurality of cells, including by evaluating the plurality of cells according to the order of the sorted list of cells and beginning with the lowest batch compatibility number.

Abstract: A prediction method of part surface roughness and tool wear based on multi-task learning belong to the file of machining technology. Firstly, the vibration signals in the machining process are collected; next, the part surface roughness and tool wear are measured, and the measured results are corresponding to the vibration signals respectively; secondly, the samples are expanded, the features are extracted and normalized; then, a multi-task prediction model based on deep belief networks (DBN) is constructed, and the part surface roughness and tool wear are taken as the output of the model, and the features are extracted as the input to establish the multi-task DBN prediction model; finally, the vibration signals are input into the multi-task prediction model to predict the surface roughness and tool wear.

Abstract: A farming machine is configured to identify and treat plants in a field. The farming machine includes one or more light sensors for measuring a characteristic of light. The one or more light sensors are coupled to the farming machine and are directed a substantially upwards orientation away from the plants. A control system adjusts settings of an image acquisition system based on a characteristic of light measured by the one or more light sensors. The image acquisition system captures an image of a plant using one or more image sensors coupled to the farming machine, the one or more image sensors directed in a substantially downwards orientation towards the plants. The control system identifies a plant in the image and actuates a treatment mechanism to treat the identified plant.

Abstract: A system and methods for OCD metrology are provided including receiving multiple first sets of scatterometric data, dividing each set into k sub-vectors, and training, in a self-supervised manner, k2 auto-encoder neural networks that map each of the k sub-vectors to each other. Subsequently multiple respective sets of reference parameters and multiple corresponding second sets of scatterometric data are received and a transfer neural network (NN) is trained. Initial layers include a parallel arrangement of the k2 encoder neural networks. Target output of the transfer NN training is set to the multiple sets of reference parameters and feature input is set to the multiple corresponding second sets of scatterometric data, such that the transfer NN is trained to estimate new wafer pattern parameters from subsequently measured sets of scatterometric data.

Abstract: Disclosed are a gas detection intelligence training system and an operating method thereof. The gas detection intelligence training system includes a mixing gas measuring device that collects an environmental gas from a surrounding environment, generates a mixing gas based on the collected environmental gas and a target gas, senses the mixing gas by using a first sensor array and a second sensor array under a first sensing condition and a second sensing condition, respectively, and generates measurement data based on the sensed results of the first sensor array and the second sensor array, and a detection intelligence training device including a processor that generates an ensemble prediction model based on the measurement data.

Abstract: A sensor measures an environmental factor in an ambient environment immediately surrounding an information handling system. A processor determines that the information handling system is in a first location, provides a first sampling frequency of the sensor based upon the first location, determines that the information handling system is in a second location, and provides a second sampling frequency of the sensor based upon the second location. The first sampling frequency is different from the second sampling frequency.

Abstract: A method for agricultural land parcel valuation includes: accessing data for parcels within a prescribed region, the data comprising management practices, historical weather conditions, locations and topography, remote sense images, soil types, and crop types; assessing and ranking the management practices for each of the parcels; generating simulation inputs for the each of the parcels, where the simulation inputs comprise highest ranked management practices, the historical weather conditions, the locations and topography, the soil types, and the crop types; simulating crop growth for the each of the parcels over a prescribed number of previous years, where the simulating employs the simulation inputs provided by the generating; and employing selected outputs from the simulating to calculate agricultural metrics and a valuation corresponding to the each of the parcels, where the agricultural metrics and the valuation for the each of the parcels are expressed relative to all of the parcels within the prescrib

Abstract: A method for agricultural land parcel valuation includes: accessing data for parcels within a prescribed region, the data comprising management practices, historical weather conditions, locations and topography, remote sense images, soil types, and crop types; assessing and ranking the management practices for each of the parcels; generating simulation inputs for the each of the parcels, where the simulation inputs comprise highest ranked management practices, the historical weather conditions, the locations and topography, the soil types, and the crop types; simulating crop growth for the each of the parcels over a prescribed number of previous years, where the simulating employs the simulation inputs provided by the generating; and employing selected outputs from the simulating to calculate agricultural metrics and a valuation corresponding to the each of the parcels, where the agricultural metrics include a sustainability metric.

Abstract: A method may include obtaining, by a computer processor, seismic data regarding a geological region of interest. The method may further include obtaining, by the computer processor, well log data from a wellbore within the geological region of interest. The method may further include determining, by the computer processor, a formation top depth using the seismic data, the well log data, a stratigraphic column, and a machine-learning model. The stratigraphic column may describe an order of various formations within the geological region of interest. The machine-learning model may assign a feature among the seismic data and the well log data to a formation among the formations in the stratigraphic column to determine the formation top depth.