12583 results about "Time series" patented technology

A framework is provided for describing multimedia content and a system in which a plurality of multimedia storage devices employing the content description methods of the present invention can interoperate. In accordance with one form of the present invention, the content description framework is a description scheme (DS) for describing streams or aggregations of multimedia objects, which may comprise audio, images, video, text, time series, and various other modalities. This description scheme can accommodate an essentially limitless number of descriptors in terms of features, semantics or metadata, and facilitate content-based search, index, and retrieval, among other capabilities, for both streamed or aggregated multimedia objects.

A system and method for monitoring and controlling the administration of at least one drug having anesthetic properties are provided. In certain embodiments, the method includes assembling physiological data, obtained from a plurality of sensors placed on a subject, into sets of time-series data, separating, from the sets of time-series data, a plurality of low frequency signals, and determining, from the plurality of low frequency signals, at least one of coherence information and synchrony information. The method can also include identifying, using the at least one of the coherence information and the synchrony information, spatiotemporal signatures indicative of at least one of a current state and a predicted future state of the patient consistent with the administration of at least one drug having anesthetic properties and generating a report indicating at least one of the current state and the predicted future state of the patient induced by the drug.

Systems and methods are provided for monitoring a subject, and particularly, for inferring an underlying brain state present in absence of current conditions. In some aspects, a method for monitoring the subject is provided including steps of receiving physiological feedback from at least one sensor configured to acquire physiological information from locations associated with a subject's brain, assembling a set of time-series data using the received physiological feedback, and identifying portions of the set of time-series data that indicate a burst suppression state. The method also includes identifying a burst characteristic profile associated with a burst pattern determined from the identified portions, and comparing the burst characteristic against a reference set of burst profiles. The method further includes determining, based on the comparison, a likelihood of a brain state of the subject underlying the burst suppression state, and generating a report indicative of the likelihood of the determined brain state.

A sensor network collects time-series data from a process tool and supplies the data to an analysis system where pattern analysis techniques are used to identify structures and to monitor subsequent data based on analysis instructions or a composite model. Time-series data from multiple process runs are used to form a composite model of a data structure including variation. Comparison with the composite model gives an indication of tool health. A sensor network may have distributed memory for easy configuration.

A system and method for monitoring and controlling the administration of at least one drug having anesthetic properties are provided. The method includes arranging a plurality of sensors configured to acquire physiological data from a patient and reviewing the physiological data from the plurality of sensors and an indication from a user interface. The method also includes assembling the physiological data into sets of time-series data and analyzing the sets of time-series data to determine signature profiles consistent with the administration of at least one drug. The method further includes identifying, using signature profiles, at least one of a current state and a predicted future state of the patient, controlling the administration of the least one drug to attain the predicted future state, and then generating a report including information regarding at least one of the current state and the predicted future state of the patient induced by the drug.

Methods and apparatus consistent with the invention provide the ability to organize, index, search, and present time series data based on searches. Time series data are sequences of time stamped records occurring in one or more usually continuous streams, representing some type of activity. In one embodiment, time series data is organized into discrete events with normalized time stamps and the events are indexed by time and keyword. A search is received and relevant event information is retrieved based in whole or in part on the time indexing mechanism, keyword indexing mechanism, or statistical indices calculated at the time of the search.

For user authentication, finger touch information from a user is accepted via a touch sensitive element, the finger touch information including at least a time series of finger touch samples that define a trace of the user's signature, and each of the finger touch samples including centroid coordinates and non-centroid information, the non-centroid information including at least one of (A) a shape of the finger touch sample, (B) a size of the finger touch sample, (C) an orientation of the finger touch sample, and (D) characteristics of a multi-touch finger touch sample. A similarity of such finger touch samples with previously entered and stored finger touch samples is determined and compared with a threshold for purposes of user authentication.

A computer implemented sales transaction tool and associated method of use is disclosed. This includes at least one processor configured to receive sales transaction information and programmed to provide the following functionality: a series of control functions that can be selectively activated by input to the processor for creating at least one subset of the sales transaction information, a plurality of graphical representations that are generated based on the selected subset of sales transaction information, and displaying at least one graphical representation of the plurality of graphical representations on an electronic display associated with the processor. Graphical representations of sales transaction information may include a slope and scatter diagram of sales transaction information, a waterfall chart, waterfall transactional analysis, a time series chart, a price sensor, a margin sensor, a break-even analysis graph and a bubble chart. There are graphical representations to evaluate opportunity of moving low margin products to average margins of comparable products and determining value for products having a single customer.

A state machine gesture recognition algorithm for interpreting streams of coordinates received from a touch sensor. The gesture recognition code can be written in a high level language such as C and then compiled and embedded in a microcontroller chip, or CPU chip as desired. The gesture recognition code can be loaded into the same chip that interprets the touch signals from the touch sensor and generates the time series data, e.g. a microcontroller, or other programmable logic device such as a field programmable gate array.

The present invention is an improved computational method and system of empirical induction that can be used to arrive at generalized conclusions and make predictions involving longitudinal associations between and among variables and events. Empirical induction is used to gain scientific knowledge, to develop and evaluate treatments and other interventions, and to help make predictions and decisions. The invention, which is distinct from and often complementary to the statistical method, is applied to repeated measures and multiple time-series data and can be used to quantify, discover, analyze, and describe longitudinal associations for individual real and conceptual entities. Major improvements include provisions to define Boolean independent events and Boolean dependent events and to apply analysis parameters such as episode length and episode criterion for both independent and dependent variables, persistence after independent events, and delay and persistence after Boolean independent events. These improvements are in addition to levels of independent and dependent variables, delay after independent events, and provision to quantify benefit and harm across two or more dependent variables. Additional improvements include provisions to quantify longitudinal associations as functions of period or time and to compute values of predictive indices when there are two or more independent variables. Major applications and uses of the invention include data mining, the conduct of clinical trials of treatments for the management or control of chronic disorders, health-effect monitoring, the quantification and analysis internal control in adaptive systems, analyses of serial functional images, analyses of behavior and behavior modification, and use to create computerized devices and systems whose behavior can be modified by experience. The present invention is best implemented on the Internet.

A motion image processing method and device for authenticating a user using a specific device, using motion information of an object. Time series monochrome images, obtained by photographing an object, using a camera, are input. An object is detected from an initial frame of the input time series images, using a basic shape characteristic, and a plurality of reference points to be tracked are automatically determined in the object. Then, corresponding points of the respective reference points are detected in an image frame other than the initial frame among the input time series images. Subsequently, motion information of a finger is calculated, based on the result of tracking the respective reference points and an assumption of limited motion in a 3D plane. Based on the calculated motion parameter, a solid object is subjected to coordinate conversion, and displayed if necessary. As a result of the tracking, a reference point in each frame is updated. Tracking, motion parameter calculation, and displaying are repeated with respect to subsequent frames.

The invention includes a method, apparatus, and computer program to selectively suppress wind noise while preserving narrow-band signals in acoustic data. Sound from one or several microphones is digitized into binary data. A time-frequency transform is applied to the data to produce a series of spectra. The spectra are analyzed to detect the presence of wind noise and narrow band signals. Wind noise is selectively suppressed while preserving the narrow band signals. The narrow band signal is interpolated through the times and frequencies when it is masked by the wind noise. A time series is then synthesized from the signal spectral estimate that can be listened to. This invention overcomes prior art limitations that require more than one microphone and an independent measurement of wind speed. Its application results in good-quality speech from data severely degraded by wind noise.

Methods and apparatus are described for collecting and storing large volumes of time series data. For example, such data may comprise metrics gathered from one or more large-scale computing clusters over time. Data are gathered from resources which define aspects of interest in the clusters, such as nodes serving web traffic. The time series data are aggregated into sampling intervals, which measure data points from a resource at successive periods of time. These data points are organized in a database according to the resource and sampling interval. Profiles may also be used to further organize data by the types of metrics gathered. Data are kept in the database during a retention period, after which they may be purged. Each sampling interval may define a different retention period, allowing operating records to stretch far back in time while respecting storage constraints.

A lane-changing support system includes a processing unit sets an assumed traffic-merging end, predicts a driving behavior of each peripheral vehicle, and generates at least one host vehicle's manipulated-variable time series to be executed until the host vehicle reaches the assumed traffic-merging end. The processing unit determines whether the host vehicle's lane change is appropriately achievable when executing the manipulated-variable time series, and additionally determines which of gaps defined between the peripheral-vehicles traveling on a traffic lane of destination of lane-changing should be suited for an entry of the host vehicle in case of a decision result that the appropriate lane change is achievable by execution of the manipulated-variable time series. The processing unit transmits information regarding a correspondence between a current host vehicle's manipulated variable on the manipulated-variable time series and at least one lane-changing enabling gap to the driver.

Capacitive touch screens are subject to a "handshadow' error associated with the undesired proximity detection of a portion of a relatively large object (such as a hand) comprising or associated with a smaller pointing portion or object (such as finger tip), where the smaller pointing portion is closer to a touch sensing surface than is the rest of the object. A history profile of data derived from the screen both just prior to, and just after the touch is detected can be processed to compensate for the handshadow effect and to determine a corrected touch position value based on regression techniques or other forms of predictive mathematics. In addition to accurately determining positions where a screen is touched, these approaches can also determine a screen location corresponding to a position of closest approach of a pointing object. A system for providing the handshadow-compensated measurements may comprise a memory for storing a temporal sequence of touch screen records and a computer for executing several algorithms.

An intrusion detection system (IDS) that uses application monitors for detecting application-based attacks against computer systems. The IDS implements application monitors in the form of a software program to learn and monitor the behavior of system programs in order to detect attacks against computer hosts. The application monitors implement machine learning algorithms to provide a mechanism for learning from previously observed behavior in order to recognize future attacks that it has not seen before. The application monitors include temporal locality algorithms to increased the accuracy of the IDS. The IDS of the present invention may comprise a string-matching program, a neural network, or a time series prediction algorithm for learning normal application behavior and for detecting anomalies.

A still image generation apparatus of the invention includes an image acquisition module that obtains multiple first image data arrayed in a time series among multiple lower-resolution image data, an image storage module that stores the multiple first image data obtained by the image acquisition module, and a correction rate estimation module that estimates correction rates for eliminating positional shifts between images of the respective first image data, based on the multiple first image data stored in the image storage module. The still image generation apparatus further includes an image composition module that corrects the multiple first image data with the estimated correction rates to eliminate the positional shifts between the images of the respective first image data, and combines the multiple corrected first image data to generate higher-resolution second image data as resulting still image data. This arrangement of the invention desirably shortens the total processing time in the process of combining multiple image data.

A predictive modeling method may include determining a time interval of time-series data; identifying one or more variables of the data as targets; determining a forecast range and a skip range associated with a prediction problem represented by the data; generating training data and testing data from the time-series data; fitting a predictive model to the training data; and testing the fitted model on the testing data. The forecast range may indicate a duration of a period for which values of the targets are to be predicted. The skip range may indicate a temporal lag between the time period corresponding to the data used to make predictions and the time period corresponding to the predictions. The skip range may separate input data subsets representing model inputs from subsets representing model outputs, and separate test data subsets representing model inputs from subsets representing validation data.

A method of analyzing electrocardiogram (EKG) data for use in the diagnosis of heart disease, prognosis of cardiac conditions, and the monitoring of heart disease therapies is disclosed. The method utilizes a wavelet-based multifractal analysis with one or more of (1) a discrete wavelet smoothing step to remove the effects of abnormal beats; (2) “Levy flight” analysis to detect the frequency of abnormal beats known to adversely affect the multifractal (MF) analysis; and (3) MF alpha analysis, a multifractal extension of monofractal short term (ST) alpha analysis. The invention further comprises an EKG test battery comprising Levy flight anomalous beat / beat cluster screening, followed by (ST) MF alpha analysis and MF Holder analysis (when validated by the Levy flight analysis). The wavelet smoothing step can also be used to classify human EKGs by observing the effect of sequential smoothing on the MF Holder coefficient. Alternative choices to the wavelet smoothing approach to removal of abnormal beat effects include probability distribution function analysis to determine the MF Holder coefficient directly, abnormal beat ridge skeleton removal to remove the offending beats based on a direct multifractal spectrum calculation, and the calculation of various types of entropy coefficients for the EKG time series.

A computer implemented method, apparatus, and computer program product code for temporal, event-based video fingerprinting. In one embodiment, events in video content are detected. The video content comprises a plurality of video frames. An event represents discrete points of interest in the video content. A set of temporal, event-based segments are generated using the events. Each temporal, event-based segment is a segment of the video content covering a set of events. A time series signal is derived from each temporal, event-based segment using temporal tracking of content-based features of a set of frames associated with the each temporal, event-based segment. A temporal segment based fingerprint is extracted based on the time series signal for the each temporal, event-based segment to form a set of temporal segment based fingerprints associated with the video content.

A technique for communicating multimedia data between nodes over coaxial cable, wherein the nodes are connected via a coaxial cable network, is disclosed. In an embodiment, the technique involves establishing a primary channel for communicating between first and second nodes of the coaxial cable network, establishing a secondary channel for communicating between the first and second nodes of the coaxial cable network, wherein the primary and secondary channels are in different frequency bands and wherein the primary channel is used for communicating media access control frames, and communicating a time series of data frames between the first and second nodes using both the primary channel and the secondary channel.

A method for providing location-based nowcast, comprises the steps of: a) initiation of a request, by an end-user, for a time evolution of user-selected nowcast weather parameters, the transmission of the request being made over a public communication network to a nowcast request processor; b) the determination of the end-user's actual location by the nowcast request processor; c) the nowcast request processor gathering raw weather data from data sources; d) processing the raw data into a time-series of nowcast parameter maps; e) extracting the time evolution of the user requested nowcast parameters from the time-series of nowcast parameter maps by positioning the end-user's location on said time series; and f) distributing the requested information to end-user regarding the user-selected nowcast parameters within the extracted time evolution.

System comprised of a portable medical device and method for non-contact registering at least one of electrocardiographic (ECG), magnetocardiographic (MCG), physical activity, body position, respiration, temperature, blood pressure, vasomotor activity, blood flow, neural activity, and other physiological, and health data, extracting and representing the most significant parameters from time series (trends) of said data. The system achieves the necessary sensitivity (signal-to-noise ratio) in order to miniaturize the device by collecting data of at least one fiducial point in a cardiac complex over a period of at least one, and preferably, several seconds, and extracting the underlying typical patterns from these data. Due to the miniaturization (pocket-size), the system can be implemented in a shape of a pen (or another miniature shape) that can be worn in a pocket.

A highly miniaturized electronic data acquisition system includes MEMS sensors that can be embedded onto moving device without affecting the static / dynamic motion characteristics of the device. The basic inertial magnetic motion capture (IMMCAP) module consists of a 3D printed circuit board having MEMS sensors configured to provide a tri-axial accelerometer; a tri-axial gyroscope, and a tri-axial magnetometer all in communication with analog to digital converters to convert the analog motion data to digital data for determining classic inertial measurement and change in spatial orientation (rho, theta, phi) and linear translation (x, y, z) relative to a fixed external coordinate system as well as the initial spatial orientation relative to the know relationship of the earth magnetic and gravitational fields. The data stream from the IMMCAP modules will allow the reconstruction of the time series of the 6 degrees of freedom for each rigid axis associated with each independent IMMCAP module.