4239 results about "Observation data" patented technology

Disclosed is a technique for providing, accessing, and using bookmark data to supplement information in a search engine database. The bookmark data indicates saved user selected network addresses, e.g., URLs, that are capable of being selected to access observable data, e.g., a page of text, images, sound file, movie file, etc., at the selected network address. A user computer receives user modifications to bookmark data and transmits the modifications to the bookmark data to a server over a network. A server gathers bookmark data indicating saved user selected network addresses that the user is capable of selecting to access observable data at the selected network address. A search engine server receives bookmark data gathered from multiple Internet users and determines an importance rating for at least one network address from the received bookmark data. The determined importance rating is included in the search engine index. Further, when executing a search query against the index to determine at least one search result, the search engine server presents the search results ordered according to their importance rating.

An automated system for experimentation includes an experiment engine which can define an experiment relating to various treatments for a set of content elements. The experiment engine conducts the experiment over a data network. An observation module collects observation data relating to user behavior for each treatment. A scripting / scheduling engine coordinates the operation of the experiment engine and the observation module.

Vehicles (1-1) or ships (1-2) each carry a magnetic force line sensor (11), a GPS position detector (12), and a data transmitter (13) and travel within an observation area transmitting magnetic field data and position data of each point to an earthquake prediction center (4). A telluric current induction field estimation unit (43) of the earthquake prediction center (4) estimates telluric current induction fields based on the observation data that it receives and collects. A telluric current estimation unit (44) estimates telluric currents based on the results of estimating the telluric current induction fields. A telluric current induction field intensity change pattern generation unit (45) generates patterns that indicate the change over time of the intensity of telluric current induction fields. An earthquake prediction unit (46) analyzes the state of distribution of the telluric currents and the patterns of change in the intensities of the telluric current induction fields and estimates a seismofocal zone, seismic intensity, and time of occurrence of a seismic event.

A server arrangement for managing observation data of wireless devices, including data input logic for obtaining observation data from wireless devices, the obtained data including behavioral and contextual raw data relative to the wireless devices, data mining logic for establishing a number of derived data elements, on the basis of processing and analyzing the obtained observation and optional supplementary data, the processing and analyzing incorporating aggregation procedures. At least one derived data element includes usage metrics with contextual dimension relative to applications or other features of wireless devices and users, data storage for storing the obtained data and the number of derived information elements, and a data distribution logic providing derived data. The distribution logic may serve a data query constructed by an external entity through provision of derived information from derived data elements according to the query parameters. A corresponding method for execution by the server arrangement is presented.

A method of estimating the navigational state of a system entails acquiring observation data produced by noisy measurement sensors and providing a probabilistic inference system to combine the observation data with prediction values of the system state space model to estimate the navigational state of the system. The probabilistic inference system is implemented to include a realization of a Gaussian approximate random variable propagation technique performing deterministic sampling without analytic derivative calculations. This technique achieves for the navigational state of the system an estimation accuracy that is greater than that achievable with an extended Kalman filter-based probabilistic inference system.

An incontinence management system for monitoring wetness in one or more absorbent articles, includes input for receiving one or more sensor signals indicative of a presence of wetness in an absorbent article, processor for processing the one or more sensor signals and for performing an analysis of the signals to characterise wetness events occurring in an absorbent article and user interface for communicating with a user of the system. A mathematical model is used to characterise wetness events, receiving as inputs variables derived from sensor signals and optionally, patient and demographic data. The mathematical model can be configured and / or re-configured utilising observation data obtained while monitoring a patient for wetness. A diaper for use with such as system is also disclosed.

An automated system for experimentation includes an experiment engine which can define an experiment relating to various treatments for a set of content elements. The experiment engine conducts the experiment over a data network. An observation module collects observation data relating to user behavior for each treatment. A scripting / scheduling engine coordinates the operation of the experiment engine and the observation module.

A method and / or system for making determinations regarding samples from biologic sources including statistical methods for making meaning grouping of observed data and / or for determining an overall quality measure of an assay.

A method and system for documenting and managing patient information in real time for accurate medical examination and treatment of a patient is provided. An information carrier device that stores patient information is provided to the patient. A data extraction unit extracts the stored patient information from the information carrier device and transmits the extracted patient information to a patient information processing system. A recording unit records observational data comprising medical examination information and information on treatment prescribed for the patient. The patient information processing system processes and analyzes the patient information received from the information carrier device and / or the data extraction unit and the observational data extracted from the recording unit, generates a medical examination report in one or more of multiple formats, and transmits the medical examination report in one or more formats to the information carrier device for updating the patient information in the information carrier device.

The invention belongs to the satellite navigation and positioning technical field and discloses a low earth orbit satellite-based satellite-earth differential real-time precise positioning method. A low earth orbit satellite is utilized to broadcast the observation data and real-time orbit data of the satellite-borne GNSS (Global Navigation Satellite System) receiver of the low earth orbit satellite to the ground; and after receiving the differential information broadcasted by the low earth orbit satellite, a ground receiver generates a double-difference observation value consisting of the differential information and a local GNSS observation value and performs pseudorange-based moving base station DGNSS (Differential Navigation Satellite System) positioning and carrier phase-based moving base station RTK (Rea-time kinematic) positioning. According to the positioning method of the invention, the global mobile low earth orbit satellite platform is adopted as a reference station, so that real-time precision differential positioning service in the whole world can be realized, and the method does not depend on the distribution of ground reference stations; and a user can realize differential real-time precise positioning just through using a single receiver, and therefore, the method is free of operating range restrictions, and data communication links are not required to be considered.

A method of estimating the navigational state of a system entails acquiring observation data produced by noisy measurement sensors and providing a probabilistic inference system to combine the observation data with prediction values of the system state space model to estimate the navigational state of the system. The probabilistic inference system is implemented to include a realization of a Gaussian approximate random variable propagation technique performing deterministic sampling without analytic derivative calculations. This technique achieves for the navigational state of the system an estimation accuracy that is greater than that achievable with an extended Kalman filter-based probabilistic inference system.

A mobile terminal for providing life observations including: a processing entity, memory, a wireless transceiver for wirelessly transmitting and receiving data relative to external entities, an observation logic conducting active and passive observations detectable relative the mobile terminal in response to active and passive triggers, respectively, each active trigger being associated with a triggering rule for conducting a related observation, each passive trigger being associated with a change in the observation environment, the occurrence of which in the mobile terminal triggers conducting the observation linked to the passive trigger, and a data handling logic for storing, analyzing, and aggregating observation data points of the gathered observation data to timed observation data transmissions via the wireless transceiver towards an external entity. A server arrangement for analyzing context and behavior modelling using observations from plural mobile terminals and guiding the mobile terminals for future observations is also presented, with corresponding methods.

In a sensor network system comprising a sensor terminal and a management server, the sensor terminal transmits observation data acquired using the sensor, the management server has a latest data storage manager which manages the latest observation data among observation data received from the sensor terminal, a history data storage manager which manages the history of the observation data from any time when data was received from the sensor terminal to the latest observation data, and a missing data manager which manages missing history data, and compensates the missing history data based on a predetermined rule, and when a request for such observation data is received, at least one of the latest observation data managed by the latest data storage manager, and history data wherein the missing data has been compensated and managed by the history data storage manager, is output according to the type of request.

Robust forecasting techniques are relatively immune from anomalies or outliers in observed data, such as a stream of data values reflective of the operation or use of a computer system. One robust technique provides a relatively accurate forecast of seasonal behavior even in the presence of an anomaly in corresponding historical data. Another robust forecasting technique provides a relatively accurate forecast even in the presence of an anomaly that spans multiple recent observations. In one embodiment, both techniques are used in combination to automatically detect anomalies in the operation and / or use of a multi-user computer system.

An automated system for experimentation includes an experiment engine which can define an experiment relating to various treatments for a set of content elements. The experiment engine conducts the experiment over a data network. An observation module collects observation data relating to user behavior for each treatment. A scripting / scheduling engine coordinates the operation of the experiment engine and the observation module.

The invention discloses an estimation method of a co-prime array DOA (Direction Of Arrival) angle based on sparse reconstruction, and mainly solves the problems that a prior art is higher in operand, less in identification information source amount and large in passive location evaluated error, and needs more priori knowledge. The method comprises the realizing steps of forming a co-prime array by an antenna receiver; obtaining observation data to spatial signal sampling; receiving data vectors by a virtual array element obtained by observation data; dividing spatial grids to form over-complete bases; receiving a spare relationship between the data vectors and the over-complete bases by the virtual array element to build a spare restraint equation; resolving the spare restraint equation by adopting a convex optimization method to obtain sparest resolution; drawing a magnitude spectrogram by a relative relationship between the sparest resolution and the spatial angle to obtain a DOA angle value. According to the method provided by the invention, the passive direction-finding precision and operating speed can be improved under a condition of low priori knowledge, the number of the recognized information source can be improved, and the estimation precision of a signal direction angle can be improved in a low signal to noise ratio, therefore the estimation method can be used for target reconnaissance and passive location.

Disclosed is a telemetering system that comprises a wireless base station and a number of wireless sensor nodes. Each wireless sensor node includes a solar cell, a sensor for producing observation data indicating a quantity being measured, a wireless interface for receiving the observation data from the sensor when the node is activated, and a time-schedule memory for storing time-schedule data. Control circuitry briefly activates its own node by supplying power from the solar cell to the wireless interface at periodic intervals according to the time-schedule data of the memory and briefly establishes a wireless link to the base station. During the time the wireless link is briefly established, the control circuitry of each node transmits the observation data to the base station and updates its time-schedule memory if it receives time-schedule data from the base station.

The invention provides a method for assimilating remote sensing data of soil humidity in a watershed scale. The method comprises the following steps of: improving a watershed runoff producing calculation module and developing a distributed hydrological model which is suitable for assimilating remote sensing soil humidity information and describes a soil hydrodynamic process; introducing a particle filtering sequence data assimilation method of information science, and continuously merging and assimilating new remote sensing observation data in a dynamic operation process of distributed hydrological process numerical simulation so as to acquire updated watershed soil humidity assimilated data during sequential assimilation; feeding the updated watershed soil humidity assimilated data back to a distributed hydrological model platform; and gradually estimating the time and space distribution pattern of watershed soil moisture content. Practices prove that by the method, not only high-precision and physically consistent watershed soil humidity data can be provided for research on hydrology, zoology, environment and agriculture, but also the foundation is laid for performing four-dimensional data assimilation processing on soil humidity data of an upper soil layer acquired by using remote sensing retrieval, and improving the precision of the model.

A method, system and program storage device for history matching and forecasting of subterranean reservoirs is provided. Reservoir parameters and probability models associated with a reservoir model are defined. A likelihood function associated with observed data is also defined. A usable likelihood proxy for the likelihood function is constructed. Reservoir model parameters are sampled utilizing the usable proxy for the likelihood function and utilizing the probability models to determine a set of retained models. Forecasts are estimated for the retained models using a forecast proxy. Finally, computations are made on the parameters and forecasts associated with the retained models to obtain at least one of probability density functions, cumulative density functions and histograms for the reservoir model parameters and forecasts. The system carries out the above method and the program storage device carries instructions for carrying out the method.

The invention relates to a Kalman filter prediction-based robot obstacle avoidance method. In a complex environment, the robot travelling environment changes dynamically; and when an environment of a preplanned mission is determined to have a significant change, the target objective is modified, the target is planned in real time, and the path is modified. In the obstacle avoidance method, a path scheduler sorts a target set according to a digital map, the target set and the state of the robot acquired by a sensor system so as to generate a robot travelling point sequence; the robot travelling point sequence is executed by a servo system; when the sensor system detects a new obstacle, a Kalman filter model is established according to observation data; and parameters are identified and modified by using the observation data and an expectation maximization model identification algorithm of a classical linear dynamic system; and the digital map is updated for the next turn of local re-planning of the path scheduler. The method can realize obstacle avoidance path planning of the robot generated locally and dynamically in an undetermined environment, and has the advantages of simple implementation and good real-time performance.

Robust forecasting techniques are relatively immune from anomalies or outliers in observed data, such as a stream of data values reflective of the operation or use of a computer system. One robust technique provides a relatively accurate forecast of seasonal behavior even in the presence of an anomaly in corresponding historical data. Another robust forecasting technique provides a relatively accurate forecast even in the presence of an anomaly that spans multiple recent observations. In one embodiment, both techniques are used in combination to automatically detect anomalies in the operation and / or use of a multi-user computer system.

Signals are separated by introducing a function having a monotonously increasing characteristic like an exponential type function as a cost function, and applying an adaptive algorithm that minimizes that cost function in terms of a signal separation matrix. That is, there is provided a signal processing apparatus that separates and outputs an original signal from the observed signal x(t), in which multiple multidimensional signals are mixed, wherein the nonlinear function 21 is operated on an input observed signal x(t) and an estimated separation matrix W(t−1) estimated at a previous cycle. Then, an error signal e(t) is calculated 22 based on y(t) formed by this nonlinear function 21, the estimated separation matrix W(t−1) estimated at the previous cycle, and the observed signal x(t) at that time. Then, based on the calculated error signal e(t), the update of the separation matrix W(t) at that time is performed 23 such that consideration weight is increased when estimation errors are large using the cost function having a monotonously increasing characteristic.

A format for providing messages among GNSS apparatus includes providing a message identification block and a message body. The message identification block includes information specifying a message length and a message type block specifying a message type. Rather than sending all data from one apparatus to another, ambiguous observation data is sent to conserve bandwidth. At the sender a deconstruction of GNSS code and carrier observations using knowledge of the signal structure and constellation geometry, together with simplifications of atmospheric models, allows removal from the observation data of that information which can be implicitly understood or recreated by the recipient. This enables only the necessary information to be packed for transmission to the recipient.

The invention relates to an earth face evapotranspiration remote sensing inversion method and system based on MODIS data. The earth face evapotranspiration remote sensing inversion method comprises the following steps that (1), a research area is confirmed, relative MODIS data porducts in the research area are achieved and pretreated; (2), a scatter diagram of space change information is built by the utilization of the pretreated MODIS data products, a remote sensing inversion of pixel sized surface evaporation ratio EF is conducted; (3), according to the relative MODIS data products, remote sensing inversions of pixel sized surface net radiation Rn and soil heat flux G are conducted; (4), according to the surface evaporation ratio EF, the surface net radiation Rn and the soil heat flux G, a remote sensing inversion of pixel sized earth face evapotranspiration LE is conducted. The earth face evapotranspiration remote sensing inversion method only needs to input the MODIS data, the problem that the current evapotranspiration remote sensing inversion usually needs more ground observation data to assist is solved, and the earth face evapotranspiration remote sensing inversion method can be used for the evapotranspiration remote sensing inversion in the area with no data or with few data.

The invention discloses a multi-system dynamic PPP resolving method based on robust self-adaption Kalman smoothing. The method includes the steps that receiving machine outline coordinates and receiving machine clock bias of all systems are solved through selecting-weight-iteration pseudo-range single-point positioning, and accordingly all positioning error correction values are calculated according to an error correction model in combination with the satellite precise ephemeris and satellite precise clock bias; strict data quality control is conducted on observation data. Due to the fact that dynamic PPP accuracy is easily affected by undetected small cycle slips or the gross error and the like, an observation equation weight matrix is adjusted according to the observation value residual vectors, and the undetected small cycle slips or the gross error and other influence factors are removed; self-adaption factors are determined according to the state predictive information, and thus the influence on parameter estimation of the predictive information is controlled. By means of the method, when multi-system dynamic PPP is conducted through a single receiving machine, the feature that the number of multi-system satellites is increased greatly, on the basis that the stability of the satellite structure is guaranteed, the influence of the gross error is weaken effectively, the dynamic noise abnormity in dynamic positioning is improved, and finally the high-precision and high-stability multi-system dynamic PPP result is achieved.

A system for assessing the health of a mechanism includes a processor for receiving observation data from at least one sensor, the processor including: a detector receptive to the observation data and capable of identifying whether the mechanism is operating in a normal or degraded mode; a diagnoser to identify a type of fault from at least one symptom pattern; and a prognoser capable of calculating a remaining useful life (RUL) of the mechanism, wherein the prognoser includes a population prognoser for calculating the RUL based on a duration of use of the mechanism, a cause prognoser for calculating the RUL based on causal data, and an effect prognoser for calculating the RUL based on effect data generated from the fault. A method and computer program product for assessing the health of a downhole tool is also disclosed.

An approximation of the bandwidth of the narrowest link in a network is determined by watching how fast data gets to the other end and then back again. The rate of data transmission is limited according to this approximation. Dynamic capacity of the link, i.e. the amount of data that can be in-flight at the same time, neglecting any buffers, is also tracked. The technique looks at how much data is in-flight and, if there is more data in flight than the dynamic capacity of the network, the data transmission rate is slowed down.

Disclosed is a rolling bearing remaining life prediction method based on feature fusion and particle filtering. According to an index calculation process, firstly, original features are extracted from bearing vibration signals, the extracted original features are clustered by the adoption of a relevance clustering method, then, one typical feature is selected from each cluster to form optimal feature sets, and finally the feature sets are fused by the adoption of a weight fusion method into a final recession index. According to a life prediction process, firstly, smoothing and resampling are carried out on the recession index, the time interval is adjusted to be an expected value, state-space model initial parameters are calculated by the adoption of least square fitting, then, model parameters are updated in real time according to new observation data, and finally the remaining life of a bearing can be predicted. According to the rolling bearing remaining life prediction method based on feature fusion and particle filtering, the difference between the life prediction result and a true value is small, and the application effect is good.