Abstract: A method of automatically selecting an item (e.g. s3) from a set (S) of items involves using item properties to determine weighing factors. The weighing factors are then used to produce a preference distribution having sections, the relative sizes of which correspond with the respective weighing factor. A random number may be used to point to a section of the preference distribution and thus select the associated item. The method may be used to select multimedia items, such as songs, stored in a mass storage device.

Abstract: In one embodiment, a method of deriving probability of a medical condition is provided. The method comprises obtaining a first medical data corresponding to a first medical subject from at least one medical information system, obtaining a second medical data corresponding to the first medical subject from an electronic data system, selecting at least one second medical subject with a second medical data substantially same as the second medical data of the first medical subject, obtaining medical condition data for the second medical subject, wherein the medical condition data comprises data corresponding to a medical condition, correlating the first medical data with the medical condition data and deriving probability of the medical condition in the first medical subject based upon the first medical data and the medical condition data.

Abstract: A technique is disclosed for evaluating and monitoring performance of a heat exchanger system. Operating parameters of the system are monitored and fouling factors for heat transfer surfaces of the exchanger are determined. Trending of fouling may be performed over time based upon the fouling factors, and a model of fouling may be selected from known sets of models, or a model may be developed or refined. Fluid treatment, such as water treatment regimes may be taken into account in evaluation of fouling. An automated knowledge based analysis algorithm may diagnose possible caused of fouling based upon sensed and observed parameters and conditions. Corrective actions may be suggested and the system controlled to reduce, avoid or correct for detected fouling.

Abstract: The present invention systems and methods facilitate automated efficient and effective electronic component and system failure prediction and reliability determination. A present invention electronic component reliability determination system and method includes adjustments for actual operating and environmental conditions and stress impacts on failure analysis. A reference failure rate is adjusted based upon monitored operational and environmental conditions to compensate for impacts associated with the monitored conditions. The conditions are monitored at predetermined intervals and an adjusted determination of an “instantaneous” failure rate is made. The instantaneous failure rate is utilized to ascertain a reliability index value. An electronic component reliability determination system and method can also account for infant mortality and aging effects in the determination of the reliability index value.

Abstract: A metrology method of displaying results to a user includes graphically representing a target calibration amount and a tolerance associated with the target calibration on a graph, obtaining a reported reading of an instrument to be tested, and graphically representing the reported reading on the graph with an uncertainty associated with the reported reading. The method also includes display a probability of compliance of the reported reading to the target calibration amount and associated tolerance.

Abstract: A method and system for reliability similarity of semiconductor devices. The method includes providing a first plurality of semiconductor devices, providing a second plurality of semiconductor devices, and determining a first reliability associated with the first plurality of semiconductor devices. The first reliability is represented by at least a first probability density function. Additionally, the method includes determining a second reliability associated with the second plurality of semiconductor devices. The second reliability is represented by at least a second probability density function. Moreover, the method includes processing information associated with the first probability density function and the second probability density function, and determining a numerical number based on at least information associated with the first probability density function and the second probability density function.

Abstract: Information of an action of fact confirmation performed between nodes that are objects relating to fact confirmation in an application procedure is read from a predetermined storage unit that previously stores whether an action of fact confirmation is an action of operating information or an action of confirming information, and based on the read information of the action, when a fraud is committed in an action of operating information, reliability of the application procedure is calculated based on a probability of a detection of a fraud in an action of confirming information performed in a node connected to the action of operating information.

Abstract: Embodiments of the present invention use the results of a plurality of defect detecting tests and adjust the result of each test in a manner that reflects the accuracy of the test that produced it. A manufactured unit can then be evaluated using a mathematical combination of the adjusted results.

Abstract: Predicting the probability of detection of major and minor defects in a structure includes simulating a plurality of N defects at random locations in a region specified by an array of transducers. Defect size is incremented until it intersects one path between two transducers. The defect size is again incremented until it intersects two or more adjacent paths between pairs of transducers. The number of major defects up to a selected size is determined by the total number of single path intersections by defects up to the selected size. The number of minor defects up to a selected size is determined on the basis of the total number of defects intersecting two or more paths up to the selected size. The probability of detection up to a selected size is the cumulative number of major or minor defects up to the selected size normalizing by N.

Abstract: A method for calculating the probable damage size in a structure includes defining a configuration of an array of transducers mounted on the structure. Any pair of the transducers includes an actuator and a sensor, and each pair defines a propagation path in the structure. All propagation paths that are affected by being touched by a damage of the structure, and all adjacent paths that are untouched and thereby unaffected by the damage, are identified. A range of sizes of the damage is determined, and a probability density of the damage versus damage size is calculated on the basis of the transducer array configuration and the affected and unaffected propagation paths identified. On the basis of the probability density, a most probable damage size is determined, and the probability of the damage being greater or less than the most probable damage size is also determined.

Abstract: A structure formed on a semiconductor wafer can be examined using a support vector machine. A profile model of the structure is obtained. The profile model is defined by profile parameters that characterize the geometric shape of the structure. A set of values for the profile parameters is obtained. A set of simulated diffraction signals is generated using the set of values for the profile parameters, each simulated diffraction signal characterizing the behavior of light diffracted from the structure. The support vector machine is trained using the set of simulated diffraction signals as inputs to the support vector machine and the set of values for the profile parameters as expected outputs of the support vector machine. A measured diffraction signal off the structure is obtained. The measured diffraction signal is inputted into the trained support vector machine. Values of profile parameters of the structure are obtained as an output from the trained support vector machine.

Abstract: In one embodiment, the disclosure relates to a method for predicting a steady state performance of a switched circuit having a first state and a second state, the method includes: identifying a plurality of circuit components, each circuit component having at least one component parameter; determining a transition matrix for the first state [A1] and a transition matrix [A2] for the second state; defining a first state sourcing matrix [B1] and a second state sourcing matrix [B2], the first state transition matrix defining the switched circuit's response to input condition at a start of the first state and the second state transition matrix [A2] defining the switched circuit's response to input condition at a start of the second state; defining a first energy input matrix [E1] and a second energy input matrix [E2], the first energy input matrix [E1] defining energy input to the switched system during state 1 and the second energy input matrix [E2] the defining energy input to the switched system during state 2;

Abstract: A method for automatically creating a probability of detection (POD) curve of an entire network of transducers monitoring and detecting damage in a structure is based on the POD of each of the individual actuator-sensor paths. These individual path PODs may be generated in different ways, such as by experimentation or simulation. This technique makes it possible to create the POD curve of a structural health monitoring (SHM) system for the detection of damages in structures.

Abstract: A case base (54) is generated from historical data containing inflow data (31) that indicates a sewage inflow measured at a sewage treatment plant (10) and meteorological data (33) corresponding to the inflow data (31). A similar case search section (56) and output estimation section (57) predict a sewage inflow corresponding to an input prediction condition (40) after a predetermined prediction time in real time using the case base (54) and output inflow prediction data (20).

Abstract: There is provided with a load calculating device including: a variable acquiring unit configured to acquire, as monitoring variables, a detected value by a sensor monitoring a state of a circuit board and a performance characteristic obtained by a tool monitoring performance of the circuit board; a first storage configured to store a first statistical model that is one of a regression model, an occurrence frequency distribution and a probability distribution; a second storage configured to store a second statistical model that is one of a regression model, an occurrence frequency distribution and a probability distribution; and an arithmetic processor configured to calculate the intermediate variable from the monitoring variables acquired by the variable acquiring unit according to the first statistical model and calculate the physical quantity from calculated intermediate variable according to the second statistical model.

Abstract: The invention relates to a method for determining a probability distribution with local three-dimensional resolution for a substance in a vascular system. An acquisition time is assigned to a group of x-ray images showing a presence distribution with local 2D resolution for a substance in the vascular system at the acquisition time. A first preliminary presence probability distribution is determined using the x-ray images assigned to the acquisition time and a volume data set of the vascular system. A second preliminary presence probability distribution is determined using the presence probability distribution for the preceding acquisition time and a migration probability distribution with the substance migrating from first vascular locations to second vascular locations. A high individual probability to vascular locations is assigned if both preliminary presence probability distributions have a high probability value for the respective vascular location.

Abstract: Methods and apparatuses for providing service availability information to a waiting customer using the customer's wireless device are generally introduced herein.

Abstract: The method provides for the fitting of a different distribution to the tail of a distribution of continuous data, than that distribution fitting to the rest of the distribution. By fitting a distribution to this set of occurrences only, better distributions shapes are obtained for that part of a distribution which might otherwise be overly sensitive to individual or small numbers of occurrences. Over sensitivity can make such distributions unreliable in situations where their value is compared with the value of another distribution. A distribution which does not decline quickly to zero is preferred for the tail, for instance a heavy tailed distribution.

Abstract: Aspects of the various embodiments of the invention relate generally to computing relative base value probabilities using discrete experimental base values to calculate distributions of relative base probabilities. This information can be used with associated experimental measurements to increase the accuracy of the data analysis.

Abstract: An external index detection unit (105) receives an image sensed by a camera (100), and detects an external index set in a real scene. A tachometer (110) measures the rotational velocities of two rear wheels of a vehicle. A vehicle measurement unit (120) measures the position and azimuth of the vehicle on the basis of the image coordinate position of the external index and the rotational velocities of the two rear wheels of the vehicle. A head index detection unit (135) receives an image sensed by a camera (130), and detects a head index set on the head of a passenger (132). A head measurement unit (140) measures the position of the head on the basis of the image coordinate position of the head index.

Abstract: A statistics system stores inputted statistical target information into storage. When each unit time period defined in a statistical calculation rule expires, the statistics system reads all pieces of statistical target information whose occurrence times are contained in the unit time period from storage, executes statistical calculation, and registers the statistical result to the statistical information in storage. When statistical target information is inputted, the statistics system sets a re-calculation flag to a unit time period including the occurrence time shown by the statistical target information among the respective unit time periods whose statistical results are registered in the statistical information.

Abstract: A method and an apparatus are provided for applying a self-adaptive filter to a drifting process. The method includes processing a workpiece, measuring an output characteristic of the processed workpiece and modifying a previous estimated process state based at least on the measured output characteristic. The method further includes estimating a next process state based at least on the modified previous estimated process state.

Abstract: Disclosed are various embodiments for outage detection. In one embodiment, an outage detection system includes a signal sampler configured to sample a signal on a communications link and to determine a noise level and a signal level of the sample. An outage detection system also includes a comparator configured to compare a critical value with a sum of signal and noise of the sample. An outage detection system further includes a binomial probability analyzer configured to calculate a binomial probability of false outage of the sample and the previous N samples.

Abstract: A system, method and program product for monitoring a complex signal for ultrasensitive detection of state changes, or for signature recognition and classification is provided. A complex signal is decomposed periodically for empirical modeling. Wavelet analysis, frequency band filtering or other methods may be used to decompose the complex signal into components. A library of signature data may be referenced for selection of a recognized signature in the decomposed complex signal. The recognized signature may indicate data being carried in the complex signal. Estimated signal data may be generated for determination of an operational state of a monitored process or machine using a statistical hypothesis test with reference to the decomposed input signal.

Abstract: By performing a contingency-based correlation test of measurement data, such as defect data, with respect to electrical test data after progressively filtering the measurement data, an enhanced analysis of process flow characteristics may be accomplished. Consequently, an efficient yield loss estimation may be performed.

Abstract: A new method and system for generating probabilities of objective values of hazards as a fine granularity grid in four dimensions (three spatial dimensions plus time) to be used by decision support and visualization tools. Utilizing the proposed system, proxies for hazard data received at different times and in different formats may be used as input data to a grid of intelligent software agents which generate a four dimensional matrix of probabilities of objective values of hazards. The method allows for proxies and/or subjective information on hazards that may arrive asynchronously and with coarse temporal and spatial accuracy to be converted into a standard fine granularity four dimensional hazard probability grid. The grid is created automatically, without the need for expert human interpretation, can provide visualization of the four dimensional hazard volumes and may be used directly by decision support tools without the need for expert human interpretation.

Abstract: The present disclosure is concerned with the identification of fault origins of slowly degrading systems such as industrial gas turbines. Following the initial input of some parameter values, exemplary procedure comprises a number of steps which are repeated periodically during the operation of the gas turbine. First, for each potential fault such as e.g. a contamination of compressor blades, erosion of turbine blades or corrosion of machine parts, a pre-symptom fault probability, characteristic of the specific gas turbine considered, and a symptom-conditional fault probability are calculated. In a second step, on-line data from the monitoring devices are loaded in order to update information about symptoms such as e.g. reductions in polytropic efficiency and in flow capacity, changes in vibration spectrum, or other machine condition indicators, and a post-symptom fault probability is calculated.

Abstract: System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Abstract: A computer-implemented method for decompression in data compression systems with decpder side-information including a plurality of signals each of which is correlated to a source, includes determining a conditional probability function of the source conditioned upon a subset of decoder side-information signals, wherein the decoder side-information signals include pre-stored and received statistical information, estimating an a-posteriori probability function based on the conditional probability function and extrinsic information, evaluating a stopping criterion for decompresiion, generating the extrinsic information based on the a-posteriori probability function, and determining a likelihood threshold for determining a most probable value of a quantized source signal based on the a-posteriori probability function and outputting the quantized source upon determining to stop decompression.

Abstract: There is provided a probability density function separating apparatus that separates a predetermined component in a given probability density function. The probability density function separating apparatus includes a domain transforming section that is supplied with the probability density function and transforms the probability density function into a spectrum in a frequency domain, and a deterministic component computing section that multiplies a multiplier coefficient according to a type of distribution of a deterministic component included in the given probability density function by a first null frequency of the spectrum in the frequency domain and computes a peak to peak value of the probability density function with the deterministic component.

Abstract: A probability distribution for a reference summary of a document is determined. The probability distribution for the reference summary is then used to generate a score for a machine-generated summary of the document.

Abstract: A method and system is disclosed for scaling performance indicators of control applications in an environmental control system. The method and system include receiving more than one performance indicator from a first control application, wherein the first control application includes a modulating control output and receiving more than one performance indicator from a second control application, wherein the second control application includes a staged-control output. The method and system further include identifying a probability distribution, wherein the probability distribution is characteristic of a fault-free environmental control system and calculating probability distributions associated with the performance indicators of the first and second control applications. The method and system also include displaying the probability distributions of the first and second control applications on a common scale.

Abstract: The present invention is an online methodology for end point detection for use in a chemical mechanical planarization process which is both robust and inexpensive while overcoming some of the drawbacks of the existing end point detection approaches currently known in the art. The present invention provides a system and method for identifying a significant event in a chemical mechanical planarization process including the steps of decomposing coefficient of friction data acquired from a chemical mechanical planarization process using wavelet-based multiresolution analysis, and applying a sequential probability ratio test for variance on the decomposed data to identify a significant event in the chemical mechanical planarization process.

Abstract: A spectroscopy instrument that uses spectra produced from random binary sequence modulated data. Statistical estimation techniques are used to achieve resolution enhancement, while properly accounting for the Poisson noise distribution and other artifacts introduced by a modulator or “chopper” or other system components. A resolution similar to that of modern spectrometers can be achieved. Both static and dynamic behaviors are theoretically or measured experimentally accounted for in the model as determined. In one embodiment, the finite penetration of the field beyond the plane of the chopper leads to non-ideal chopper response, which is characterized in terms of an “energy corruption” effect and a lead or lag in the time at which the beam responds to the chopper potential.

Abstract: Method, system and computer program product for providing real time detection of analyte sensor sensitivity decline is continuous glucose monitoring systems are provided.

Abstract: Transactions involving assets that share a common characteristic are represented as respective data points associated with values of the assets. The data points include transaction value information. The data points belong to sets associated with respective geographical areas. Data points of at least two of the sets are aggregated into a superset representing transactions of a larger geographical region. A hypothetical probability density function is represented by a parametrization that describes the data points of the superset. An index is formed of values associated with the assets using at least one of the determined parameters.

Abstract: In a method, arrangement and computer program for analysis of neuronal activities in neuronal areas, signals are recorded, with each signal describing the neuronal activity in one of the neuronal areas. A matchable coupling forms the basis of all signals, described by the use of matchable coupling parameters that describe the statistical relationship between the signals. Probabilities for an occurrence of the signals are determined, whereby a statistical distribution is the basis of the signals. The matchable coupling parameters are determined by optimization of the probabilities, hence matched and analyzed.

Abstract: A method, system, and computer program product related to the maintenance of optimal control of diabetes, and is directed to predicting patterns of hypoglycemia, hyperglycemia, increased glucose variability, and insufficient or excessive testing for the upcoming period of time, based on blood glucose readings collected by a self-monitoring blood glucose device. The method, system, and computer program product pertain directly to the enhancement of existing home blood glucose monitoring devices, by introducing an intelligent data interpretation component capable of predicting and alerting the user to periods of increased risk for hyperglycemia, hypoglycemia, increased glucose variability, and ineffective testing, and to the enhancement of emerging self-monitoring blood glucose devices by the same features. With these predictions the diabetic can take steps to prevent the adverse consequences associated with hyperglycemia, hypoglycemia, and increased glucose variability.

Abstract: Disclosed is a method for determining the confidence index of the estimated position for a target device in a wireless system. In the online location determining phase, after knowing the observations of the radio signal for a target device, the target device's probability distribution of location and its motion model are combined to calculate the position uncertainty, thereby giving the confidence index of this location estimate. The invention determines the location probability distribution, and calculates the uncertainty of the location probability distribution and the possible maximum uncertainty under the current situation. Based on these uncertainties, this invention determines the confidence index of the radio signal. The confidence may be regarded as a quantity that the location uncertainty can be excluded in the location prediction. The larger the quantity is, the more confident the estimated location is.

Abstract: A method of incrementally maintaining a stable, bounded, uniform random sample S from a dataset R, in the presence of arbitrary insertions and deletions to the dataset R, and without accesses to the dataset R, comprises a random pairing method in which deletions are uncompensated until compensated by a subsequent insertion (randomly paired to the deletion) by including the insertion's item into S if and only if the uncompensated deletion's item was removed from S (i.e., was in S so that it could be removed). A method for resizing a sample to a new uniform sample of increased size while maintaining a bound on the sample size and balancing cost between dataset accesses and transactions to the dataset is also disclosed. A method for maintaining uniform, bounded samples for a dataset in the presence of growth in size of the dataset is additionally disclosed.

Abstract: Methods and apparatuses for updating a forecast model quantifying the marketing of to the demand for a product and/or service are described. An original forecast model created at a reference M is used. An error of the forecast model is determined based on data including an original data and an additional data. At least one parameter is identified to be changed in value in, added to, or removed from the original forecast model. The forecast model is then modified to reduce the error of the forecast model by changing the value of the identified parameter in the forecast model, adding the identified parameter to the original forecast model, and/or removing the identified parameter from the original forecast model.

Abstract: A method of determining that protected software is running in a virtualized environment includes obtaining a set of baseline measurements of system call timings in native operating system environments. Statistical thresholds are established based on the baseline measurements such that there is a predetermined probability that protected software running in a native environment will experience system call durations that exceed the thresholds. The protected software is analyzed and instructions are incorporated within the software such that particular system calls, demonstrated to be differentiating using the set of baseline measurements and the threshold analysis, are executed during the normal running of the protected software. The incorporated instructions are used to estimate the parameter values that are to be compared with the established statistical thresholds.

Abstract: The system and method of the present invention automatically extracts the top k recommendations of objects, such as topics, items, products, books, movies, food, drinks, etc., from a local probabilistic recommendation system. Unlike prior systems, the present invention accomplishes the extraction of the top k recommendations of objects without examining a probability for every object that can be recommended. Further, the system and method of the present invention is capable of being implemented using probabilistic recommendation systems based on any conventional type of probabilistic distribution or machine learning technique, including, for example, decision trees and Bayesian networks.

Abstract: Systems and methods for probabilistic determination of real world events in a sensory environment such as a predicting location in a responsive environment are described. A responsive environment system includes a set of sensors for making probabilistic observations of RFID sensor tags. The system also includes a control system employing a set of possible real world events and statistical processing system for predicting a particular real world event state based upon the sensor observations. In one configuration, a Hidden Markov Model is used for the statistical processing system and may be updated based upon the prediction of the model. The responsive environment will then launch a response based upon the predicted real world event state.

Abstract: Under one aspect, a computer-implemented method of generating a predictive model includes accepting search criteria from a user, the search criteria including information identifying a past event, a domain identifier identifying a domain in which the past event occurred, and a time identifier identifying a time period preceding the past event; obtaining a plurality of sets of document-location-time tuples based on the domain identifier and the time identifier; statistically analyzing the sets of document-location-time tuples; comparing results of the statistical analysis of the sets of document-location-time tuples to identify information that precedes and statistically correlates with the past event; and displaying information associated with the identified information on a display device.

Abstract: One embodiment of the present invention provides a system that facilitates computer system monitoring. During operation, the system receives monitored signals from a computer system. The system then computes cross-correlation coefficients between the signals. Next, the system groups the signals into clusters based on the cross-correlation coefficients, wherein signals within a cluster are closely correlated. The system also monitors signals within each cluster, and checks cross correlations between signals within each cluster to identify computer system anomalies.

Abstract: An NSET method and apparatus for modeling and monitoring the status of a system is disclosed. The NSET employs a nonlinear similarity operator in place of linear matrix multiplication, to estimate a set of sensor data based on learned reference data, responsive to receiving a set of actual sensor data. Regularization is used in the generation of the estimate. The estimated data values and the actual sensor data are differenced to produce residuals, which are statistically tested with a SPRT to detect anomalies. Cluster centers may be used to represent learned reference data. The detection of anomalies can be used advantageously for sensor calibration verification.

Abstract: The present invention relates to a method of determining the probability that a statistical model describes the driving style or usage of a vehicle observed. By identifying an appropriate statistical model, the driving style can be detected and vehicle operation can be optimized. The method may be applied to both hybrid and non-hybrid vehicles. The method may also be augmented to determine the most probable statistical model of the usage of the vehicle. This allows detection of driving styles that can be classified as urban, highway, aggressive, etc. For example, the augmented method can be used to distinguish between highway and urban driving with a very high certainty.

Abstract: Maximum conjunction probability calculations are refined by addressing rectangular object shapes, even though their orientation may not be known. Object dimensions and relative miss distance, coupled with the aspect ratio of the projected combined covariance, are used to determine the size and orientation of the covariance as well as the object orientation that produces the maximum probability. In treating the objects as rectangles instead of spheres, the probability calculation becomes more realistic by accounting for object shape. In the absence of object attitude information, a footprint is created that completely defines the region where the two objects might touch. This footprint can then be rotated to determine the orientation that produces the largest probability, making it the most conservative estimate for the given conjunction conditions.

Abstract: One embodiment of the present invention provides a system that determines the complexity of a transaction between a first entity and a second entity. The system starts by determining a first probability of success for a portion of the transaction which is associated with actions of the first entity. The system then determines a second probability of success for a portion of the transaction which is associated with actions of the second entity. The system next calculates a transactional complexity for the transaction based on the first probability of success and the second probability of success.