A method for analyzing time-series data is provided. The method includes: identifying, from within a first set of time-series data, data sequences that correspond to patterns, each data sequence being representative of a predetermined time interval; converting the data sequences into respective pattern images; receiving a second set of time-series data; converting the second set of time-series data into an additional image; comparing each of the pattern images with a portion of the additional image that corresponds to a most recent time interval; and determining whether the portion of the additional image that corresponds to the most recent time interval corresponds to any of the patterns based on a result of the comparison.

An image object recognition method, apparatus, and computer device are provided. The image object recognition method includes: performing feature extraction in the direction of a horizontal angle of view and in the direction of a vertical angle of view of an image respectively, to extract a lateral feature sequence and a longitudinal feature sequence of the image; fusing the lateral feature sequence and the longitudinal feature sequence to obtain a fused feature; activating the fused feature by using a preset activation function to obtain an image feature; and recognizing an object in the image by decoding the image feature. This solution can improve the efficiency of the object recognition.

Described herein are examples of a system that processes information describing movement of a vehicle at a time related to a potential collision to reliably determine whether a collision occurred and/or one or more characteristics of the collision. In response to obtaining information regarding a potential collision, data describing movement of the vehicle before and/or after a time associated with the potential collision is analyzed to determine whether the collision occurred and/or to determine one or more collision characteristic(s). The analysis may be carried out at least in part using a trained classifier that classifies the vehicle movement data into one or more classes, where at least some the classes are associated with whether a collision occurred and/or one or more characteristics of a collision. If a collision is determined to be likely, one or more actions may be triggered based on the characteristic(s) of the collision.

Methods and systems for a data marketplace in a fluid conveyance device includes a self-organizing data marketplace. The self-organizing data marketplace includes at least one data collector and at least one corresponding fluid conveyance device in an industrial environment, wherein the at least one data collector is structured to collect detection values from the fluid conveyance device; a data storage structured to store a data pool comprising at least a portion of the detection values; a data marketplace structured to self-organize the data pool; and a transaction system structured to interpret a user data request, and to selectively provide a portion of the self-organized data pool to a user in response to the user data request.

A method for processing a neural measurement obtained in the presence of artifact, in order to detect whether a neural response is present in the neural measurement. A neural measurement is obtained from one or more sense electrodes. The neural measurement is correlated against a filter template, the filter template comprising at least three half cycles of an alternating waveform, amplitude modulated by a window. From an output of the correlating, it is determined whether a neural response is present in the neural measurement.

A bio-sensor device, integrated with a display portion, includes a surface for touching by a body part, such as a finger. A light source, such as an array of LEDs, emit light through the surface so as to be reflected and partially absorbed by the body part An array of photodetectors detects light reflected back by the body part and generates signals corresponding to an image of the light reflection, which corresponds to the light absorption pattern in the body part. The light absorption pattern may correlate to a fingerprint, a blood vessel pattern, blood movement within the blood vessels, combinations thereof, or other biometric feature. A processor receives the signals from the photodetectors and analyzes the signals to determine a characteristic of the body part. The characteristic may be used to authenticate the user of the bio-sensor device by comparing the detected characteristic to a stored characteristic.

A system and method for real-time machine learning include an interface device and a processing device to responsive to receiving a document, identify tokens in a document object model (DOM) tree associated with the document, present, on a user interface of the interface device, the document including the identified tokens, label, based on user actions on the user interface, one or more of the tokens in the DOM tree as one of a strong positive, a strong negative, or one of a weak positive or a weak negative token, and provide the DOM tree including the labeled tokens to train a machine learning model.

A method for automatic selection of typhoon center using vectors calculated from radar image data by an optical flow technique includes calculating a valid vector field from the radar image data using the optical flow technique, generating a dense vector field by interpolating an empty spot of the valid vector field using linear interpolation, extracting a rotating component anomaly vector field including typhoon rotating component anomaly vectors by removing a relative vector in the interpolated valid vector field, generating a normal vector intersection point of the vectors of the extracted rotating component anomaly vector field, and finally selecting the typhoon center by calculating a maximum density normal vector intersection point based on a Gaussian kernel density estimation technique. Accordingly, it is possible to detect the moving path of the typhoon rapidly and objectively.

A digital microscope system comprises an imaging device configured to generate digital image data representing a target region of an object, the target region being determined by a changeable setting of the imaging device; and a controller configured to generate monitor image data corresponding to the digital image data generated in accordance with the setting, the monitor image data being configured to be displayed as a monitor image; wherein the controller is further configured to change the setting in response to a user input; and wherein the controller is further configured to compensate for a delay in updating the monitor image data in accordance with the changed setting by storing the digital image data generated in accordance with the unchanged setting in response to the user input and generating simulation monitor image data by performing digital image processing on the stored digital image data taking into account the changed setting, the simulation monitor image data being configured to be displayed as a simulation monitor image during the delay.

A method, system, and computer-readable media for identifying false positive data within a set of blast exposure data. After debiasing and filtering the blast exposure data, an algorithm identifies predetermined features within the data that may be indicative of false positive data. The predetermined features are used to calculate a false positive score and if the false positive score exceeds a predetermined score threshold, the data is flagged with a false positive flag and may be removed from the set of blast exposure data.