Abstract: In a noise removing apparatus, a data acquisition unit acquires sets of odor data measured using a sensor with respect to a plurality of objects, each set of odor data representing features of an odor of an object by respective rates of a plurality of odor molecules. A noise component extraction unit extract a noise component using a set of odor data. A noise removing unit removes the noise component from each set of odor data to be processed.

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 method and a device for testing an electrode sheet, the method may comprise: acquiring M pieces of test data of a tab, wherein the tab protrudes from the end face of the electrode sheet along the first direction, the M pieces of test data are the test data of the tab at M consecutive positions along the second direction, the M pieces of test data are the test data of the height of the tab in the first direction, the second direction is perpendicular to the first direction, and M is a positive integer greater than 1; and determining whether the shape of the tab is normal based on the M pieces of test data.

Abstract: Techniques and apparatus for diagnostic processes for analytical instruments are described. In one embodiment, for example, an apparatus may include at least one memory, and logic coupled to the at least one memory. The logic may be configured to receive diagnostic information associated with at least one analytical instrument, and process the diagnostic information using a computational model to generate at least one diagnostic model for at least one diagnostic. Other embodiments are described.

Abstract: The prevent invention relates a method and apparatus based on neural network for pre-diagnosing defect and fire in battery cell. A method based on neural network for pre-diagnosing defect and fire in battery cell in an apparatus for pre-diagnosing defect and fire in battery cell is proposed, the method including collecting, by the battery cell defect and fire pre-diagnosis apparatus, data including at least one of chemical composition, current, voltage, and temperature data measured for each predetermined time interval within each charge and discharge cycle while charging and discharging a plurality of batteries; training, by the battery to cell defect and fire pre-diagnosis apparatus, the neural network by inputting the collected data to the neural network; and predicting, by the battery cell defect and fire pre-diagnosis apparatus, a battery deviated from a main cluster of the neural network as defective.

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 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: 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: 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: 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: 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: 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.