Abstract: The present invention relates generally to the field of identification and determination of bioactive amino acid sequences. In particular, the present invention provides method(s) for determining the influence of variation in host genes on selection of microorganisms with particular amino acid variants for the purpose of therapeutic drug or vaccine design or individualisation of such treatment. The invention also provides methods for identifying HLA allele-specific microorganism sequence polymorphisms that result from HLA restriction of antigen-specific cellular immune responses. It also provides diagnostic and therapeutic methodologies that may be used to measure or treat infection by a microorganism or to prevent infection by the microorganism.

Abstract: A method for prognosing a rheumatoid arthritis phenotype using the outcomes of selected single nucleotide polymorphisms (SNPs) and clinical variables. A method for genotyping multiple rheumatoid arthritis associated genetic variations comprising use of a DNA microrarray. A microarray for use in the described methods.

Abstract: A real time detector system for monitoring ram alignment in a can bodymaker measures ram (10) position immediately before and during impact with the dome forming station (1). Displacement measurements of the ram enable the user to adjust dome (1) position or otherwise correct ram (10) alignment and avoid multiple can failures.

Abstract: A system for determining a worst condition, wherein, in a model for which one or more parameters included in a model function that simulates a circuit performance index are random variable(s) to simulate the circuit performance index and fluctuations thereof, the parameter(s) for which the circuit performance index assumes a maximum or minimum value that is to be assumed from the viewpoint of designing is determined as the worst condition; the system comprises a worst condition search unit that searches for a point, having a maximum or minimum value of the circuit performance index, on an equi-probability surface corresponding to a preset good product ration within a space defined by the parameter(s); the point thus searched being determined as the worst condition.

Abstract: Disclosed are method and apparatus for registering multiple sensors collecting data from multiple objects. Sensor registration is decomposed into a two-step procedure. The first step corrects systematic errors. The second step assigns objects measured by one sensor to objects measured by a second sensor. Systematic errors are corrected by generating the global minimum of a systematic error function. One embodiment for generating the global minimum uses a Continuous Greedy Randomized Adaptive Search Procedure.

Abstract: A method for detecting blast induced pressure changes includes exposing a material, a contained solution, a membrane-bound solution, or a photonic crystal material, having a first optical property, to a pressure wave having a blast level. A change in the first optical property to a second optical property of the exposed material, contained solution, membrane-bound solution, or photonic crystal material is determined, and the extent of change corresponds to the blast level.

Abstract: A method, apparatus and computer program product are provided for determining a future time associated with a component, where the future time can be indicative that some action can be taken with respect to the component. In some embodiments, the future time can be indicative of a component's remaining useful life or time until maintenance is required. The future time can be determined as a function of a health indicator and a material constant. In some embodiments, the functional relationship between the future time, the health indicator and the material constant can be based on the functional relationship of Paris' law for fatigue crack growth.

Abstract: A method and system for of fusing the outputs of multiple sensors. The output of each sensor including a sensor class probability vector based on each sensor's classification database is input to a fusion engine which estimates a base class probability vector based on the sensor class probabilities output by the sensors and a preconfigured base database including base classes.

Abstract: A method for prognosing osteoporosis phenotypes or estimating osteoporosis quantitative traits comprising determining outcomes for selected SNP variables and clinical variables. Products and methods for genotyping multiple osteoporosis associated genetic variations.

Abstract: The invention generally provides methods for analyzing and constructing nucleic acid sequences and more specifically for assembling a collection of short read nucleic acid sequences to construct longer nucleic acid sequences.

Abstract: Assuming frame F having specific short length L2 on a transcript, a structure in a small-section is sequentially analyzed while shifting the frame F finely in a step-like manner by constant value t, and first probability for a specific secondary structure in a specific position in each small-section is determined. Then, at least one specific position proved in each small-section is arranged in corresponding position on the original transcript, and the magnitude of degree of overlapping between the specific positions is determined as second probability. By focusing on these two probabilities, it is possible to predict whether an intended secondary structure is actually present in RNA such as mRNA with higher reliability.

Abstract: A current detector and a voltage detector respectively detect a current value and a voltage value outputted from an engine generator. An operating block determines a weight constant on the basis of the current value and the voltage value, weights the operating time of an engine by using the weight constant, and integrates the weighted operating time to calculate an integral time. A judging block compares the integral time and a reference time, and gives a notification to an indicator when it judges that the integral time exceeds the reference time. Receiving the notification, the indicator makes an external indication. The current detector and the voltage detector can be made of electric circuitry, so that the life of the engine can be predicted at low costs and with high reliability.

Abstract: Several embodiments of systems and methods for adaptive smart environment automation are described herein. In one embodiment, a computer implemented method includes determining a plurality of sequence patterns of data points in a set of input data corresponding to a plurality of sensors in a space. The input data include a plurality of data points corresponding to each of the sensors, and the sequence patterns are at least partially discontinuous. The method also includes generating a plurality of statistical models based on the plurality of sequence patterns, and the individual statistical models corresponding to an activity of a user. The method further includes recognizing the activity of the user based on the statistical models and additional input data from the sensors.

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: Apparatus and method for improving the detection of signals obscured by noise using stochastic resonance noise. The method determines the stochastic resonance noise probability density function in non-linear processing applications that is added to the observed data for optimal detection with no increase in probability of false alarm. The present invention has radar, sonar, signal processing (audio, image and video), communications, geophysical, environmental, and biomedical applications.

Abstract: Methods, software, and systems are provided for determining the probability of an overlap set of entities having an overlap size, where the overlap set is independently selected from two sets of non-identical entities. Applications of the invention to microarrays are provided. Probability distributions are provided for determining the probability that the size of an overlap gene set from two different microarrays occurs by chance. Microarray analysis for determining the size of a statistically significant overlap gene set given two different microarrays is described. Overlap set size probability determinations that account for the total number of genes in two different microarrays and not just the common genes are described.

Abstract: A method of analysis including an intrinsically valid class of statistical methods for dealing with multivariate ordinal data. A decision support system that can (1) provide automated decision support in a transparent fashion (2) optionally be controlled by a decision maker, (3) provide for an evidence acquisition concept, including automatically increasing the content of an underlying database, and (4) provide a computationally efficient interactive distributed environment. The method is exemplified in the context of assisted diagnostic support.

Abstract: Route planning methods for use by a package delivery service provider are disclosed that satisfy a stochastic daily demand while taking advantage of drivers' route familiarity over time. A model for estimating the value of driver familiarity is disclosed along with both an empirical and a mathematical model for estimating the value of route consistency, along with a Core Area Route Design which involves the concepts of combinatorial optimization, meta-heuristic algorithms, tabu search heuristics, network formulation modeling, and multi-stage graph modeling. In one embodiment, a service territory is divided into unassigned cells associated with a grid segment involving prior driver delivery stops, and a driver from a pool of unassigned drivers is assigned to a route based on examining each driver's grid segment visiting frequency limit with respect to a minimum limit so as to optimize driver selection based on of each driver's familiarity with the route.

Abstract: A method for determining whether a first group of a product, a component or a system in reliability life testing has longer lifetime than a second group. This method is non-parametric and free from a pre-assumption of statistical distributions and can be applied to all kinds of data and distributions. Errors from goodness-of-fit of distribution fitting and parameter estimations are thus eliminated. After pre-check on bimodal, early failures, and the failure mechanisms, the method employs numerical solutions with good accuracy by the nonparametric approach. The data under consideration can be censored, interval or bimodal, and not limited to simple cases of complete type. The method can be used to determine multiplicities of reliability tests for all product types and at all levels. Based on a comparability index derived from integrating the weighted difference between the reliability functions of the two groups under comparison. Several indices are proposed for effectiveness of reliability comparability.

Abstract: A system and method for performing a research and analysis in the bioinformatics field which associates data from a variety of experimental platforms with preclinical and/or clinical samples and subjects. The system and method allows for the analysis of data stored therein received from a variety of experimental platforms, as well as association with preclinical and clinical sources. A fully integrated medical informatics/molecular bioinformatics database/analysis package is provided herein suitable for accelerated target discovery, diagnosis, and treatments for molecular-based diseases. An identified relationship is used with a computational distribution for scoring nodes in a network built from a set of experimentally-derived condition-specific genomic or proteomic profiles for the development of new treatments, diagnoses, biomarker identification, or target identification.

Abstract: A method for determining a probability of damage by an object to be evaluated, including propagating a kinematic state of the object to be evaluated; determining a plurality of probabilities of damage; determining whether each probability of damage is feasible and creating a set of probabilities of feasible damage for each probability of damage; and determining the mean and variance of probability of feasible damage based on the set of probabilities of feasible damage. A system and apparatus for performing the method is also disclosed.

Abstract: A system for determining a probability of interception by an interceptor of an object to be intercepted is disclosed herein. The system includes means for propagating a kinematic state of the object to be intercepted; means for determining a plurality of probabilities of intercept; means for determining whether an intercept is feasible and creating a set of probabilities of successful intercept for each probability of intercept; and means for determining the mean and variance of probability of successful intercept based on the set of probabilities of successful intercept.

Abstract: A method and a processing device are provided for forecasting whether a record of data for an individual is associated with an outcome. Whether an n-gram associated with one of a group of predictors matches an n-gram included in the record of data is determined. When the n-gram included with the one of the group of predictors matches the n-gram in the record of data, a prediction is made as to whether the record of data is associated with the outcome based on a value assigned to the one of the group of predictors.

Abstract: A method and system for detecting and monitoring discrete interactions within a physical social network is provided. The system and method detects attributes associated with human communication activities and distinguishes them from other concurrently detected activities in order to identify discrete interactions that are in turn transmitted across a network having a limited data rate. Generally, in its simplest form a plurality of wireless sensors are deployed across a cross-section of people of interest. Once deployed, the wireless sensors establish an ad-hoc network that transmits a small amount of data relating to the each of the discrete individuals bearing a sensor. The collected data is analyzed through the application of rules set forth in a Bayesian belief network to make a determination regarding the probability that an actual interaction between two individuals bearing sensors in fact occurred.

Abstract: Provided herein are methods, systems, and devices for genetic screening. The genetic screening of two or more individuals can be utilized to predict the phenotype of a child from the group of individuals. Also disclosed is prediction of a phenotype of a child from a subset of biological relatives, such as a potential mother and father, before conception. In many instances, the methods, systems and devices herein are utilized to predict the probability of a child developing a rare genetic disease.

Abstract: The present invention provides a method of analyzing multidimensional data using a computer as well as methods of displaying multidimensional data to a user for further analysis. The present invention provides for a method and system for state model Fitting. The system components include a detector and a computer operably connected to the detector. The computer accesses one or more logic instructions for receiving and analyzing raw data from the detector and generating a state model of the raw data based on probability weights.

Abstract: A device and method for providing a load calculating device is presented. In one embodiment, a load calculating device can include a variable acquiring unit configured to acquire monitoring variables. The monitoring variables can include in 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. The device can also 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. An arithmetic processor can then be used to calculate the intermediate variable from the monitoring variables according to the first statistical model and calculate the physical quantity from calculated intermediate variable according to the second statistical model.

Abstract: An improved resource allocation system comprising a reliability decision engine (323), which allocates the portfolio's assets as required for the desired reliability portfolio. The reliability decision engine including two reliability decision engines, a basic reliability decision engine (325) and a robust reliability decision engine (327). The use of robust optimization makes it possible to determine the sensitivity of the optimized portfolio. Scenarios can be specified directly by the user or automatically generated by the system in response to a selection by the user. Inputs (329, 331) are applied to basic the basic reliability decision engine (325) and inputs (311) are applied to robust reliability decision engine (327).

Abstract: Disclosed are method and apparatus for registering multiple sensors collecting data from multiple objects. Sensor registration is decomposed into a two-step procedure. The first step corrects systematic errors. The second step assigns objects measured by one sensor to objects measured by a second sensor. Systematic errors are corrected by generating the global minimum of a systematic error function. One embodiment for generating the global minimum uses a Continuous Greedy Randomized Adaptive Search Procedure.

Abstract: A method for evaluating measured electromagnetic (EM) data relating to a subsurface region, comprising the steps of: (a) specifying alternative models of the region in terms of input parameters with uncertainty; (b) receiving the measured EM data and an estimated error; and (c) carrying out a Bayesian inversion on the measured data using each of the alternative models to attribute a probability to each model on the basis of the measured data and estimated error. The method allows physical measurements with error to be translated into fundamental parameters which can be used to assess business risk and uncertainty for making decisions, and also provides for parameters and models which can typically be directly estimated by a geoscientist on a coarse spatial grid to be used as an input, and validated using the measured data with error.

Abstract: A computer implemented method and system for assessing the risk of an anthropogenic event are disclosed. An anthropogenic event is defined and recursively decomposed into causal conditions with ascertainable probabilities. The causal conditions and probabilities are transformed into a comprehensive probability of the event. The risk related to the occurrence of the event, such as a monetary loss, is computed based on its derived probability.

Abstract: A system that determines the performance of an integrated circuit (IC). During operation, the system receives probability distributions for parameters for the IC. Next, the system generates samples of the IC, wherein generating a given sample involves using the probability distribution to assign values to the parameters for components within the IC. The system then calculates output performance metrics for the samples based on the assigned values of the parameters, and uses the calculated output performance metrics to generate a distribution of output performance metrics for the samples.

Abstract: The present invention relates to a method for visually detecting and tracking an object through a space. The method chooses modules for a restricting a search function within the space to regions with a high probability of significant change, the search function operating on images supplied by a camera. The method also derives statistical models for errors, including quantifying an indexing step performed by an indexing module, and tuning system parameters. Further the method applies a likelihood model for candidate hypothesis evaluation and object parameters estimation for locating the object.

Abstract: The present invention provides a method and apparatus for determining the probability that sampled data, associated with a source and obtained from a plurality of data input sources, are from a known source, given prior observed data obtained by the plurality of data input sources for one or more known sources. In one embodiment the data input sources are sensors for detecting molecules conveyed though the air and the method comprises identifying a source of the molecules. The present invention also provides a method of determining information about the position of at least one sensor relative to a previously known type of source.

Abstract: A payoff matrix based collaborative monitoring model presents a formal framework for defining policies to assign different payoffs for different subjects corresponding to their reporting behavior against different policy violations. An embodiment such as a formal model can be used by security administrators to get better estimates on various factors affecting the required parameters controlling the payoff values, e.g., reporting behavior of users, group dynamics, characteristics of the violations, and likelihood of detection. The proposed model effectively complements the payoff matrix-based approach for enabling the collaborative monitoring of policy violations.

Abstract: A computer classification method and apparatus employs statistical analysis of known objects in the class of interest. For each known object in the class, a respective vector of q bits is formed. Each bit indicates presence or absence of an activity or physical property in the object. The probability that a bit is equal to 1 in the class is then applied to vector representations of test objects and determines probability of the test object belonging to the class.

Abstract: A system that facilitates determination of a sampling rate to utilize in connection with sampling data in an industrial environment comprises a receiver component that receives data from an I/O port of a controller. An analysis component automatically and dynamically determines a rate at which data associated with the I/O port is to be sampled based at least in part upon the received data. The system can further comprise a sampling component that samples data at the rate determined by the analysis component.

Abstract: A fault detection and classification (FDC) method for wafer acceptance test (WAT) parameters includes the following steps. A plurality of fault detection and classification parameters is collected. A plurality of wafer acceptance test parameters that are corresponded by the fault detection and classification parameters is collected. The fault detection and classification parameters are grouped. A contingency table of the wafer acceptance test parameters corresponding to the fault detection and classification parameters is built. A probability model of the contingency table is built. Finally, a safety range of the probability model is determined.

Abstract: A simulation that integrates historical data and real-time data as a test or simulation tool can capture an entry that relates to a desired output as function points. A determination can intellectually be made as to which activities can achieve the desired output. The activities can be process steps that can represent a workflow that can be automatically implemented by an MES Appliance or other enterprise components. If a simulation reveals that the desired output might not be achieved, a change to one or more function points can be analyzed in an attempt to achieve the desired result. This change can be input into a simulation tool through a feedback loop, for example. Another simulation can performed on the modified data until a determination is made that the desired output can be achieved.

Abstract: There is provided a probability density function separating apparatus that separates a predetermined component in a given probability density function, including: 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 standard deviation computing section that computes standard deviation of a random component included in the probability density function based on the spectrum.

Abstract: Arrangements are provided for performing structural clustering between different time series. Time series data relating to a plurality of time series is accepted, structural features relating to the time series data are ascertained, and at least one distance between different time series via employing the structural features is determined. The different time series may be partitioned into clusters based on the at least one distance, and/or the k closest matches to a given time series query based on the at least one distance may be returned.

Abstract: Methods and systems for determining a probabilistic assessment of a person developing cancer are disclosed. The probabilistic assessment may include receiving a digital breast image of a person, selecting a region of interest within the received breast image, and analyzing this selected region of interest with respect to texture analysis. A probabilistic assessment may then be determined through the use of a logistic regression model based on the texture analysis within the region of interest and personal risk factors. A probabilistic assessment may also be determined through the use of a linear regression model based on the texture analysis within the region of interest and a known cancer indicator or risk factor.

Abstract: One embodiment of the present invention includes a method for traitor tracing that selects a probability distribution for the assignment of file-segment variations in a digital file. This probability distribution is selected to improve traceability for a particular size of a coalition of attackers. At least one symbol for each file-segment variation is then distributed based on the selected probability distribution.

Abstract: A method for implementing a point estimation method (PEM) that predicts variability of a system output response based on variabilities of inputs includes building a customized designed experiment such that each input variable x for the designed experiment is assigned a number of variable values n based on the respective input variable's contribution p to overall response variability.

Abstract: There is provided a method for generating a probability distribution for a desired variable. A hyper parameter density function is provided, from which values are randomly selected. The selected hyper parameter value is used to compute an input variable value. A value is randomly selected from each input variable probability density function. These values are input into a physics model to compute an output value. This process is repeated to generate numerous output values, which are then used to construct an output value probability density function. After the output value probability density function is constructed, output value sensor data is obtained. The output density function is updated using the sensor data and a probabilistic evaluation of the hyper parameters. Improved predictions are iteratively made with the updated output distribution.

Abstract: Sampling sufficiency determinations are performed using probability calculations and statistical analysis during a testing process of a population of items. For example, an auditing or reviewing process may involve testing a predetermined sample set of items from the population in order to draw statistical conclusions about the passing or failing rate of the population as a whole. During an ongoing testing process, probability calculations and statistical analyses may be performed regarding the likelihood of the population to pass or fail according to an acceptable failure rate, based on the test results of a subset of the sample set. The sampling sufficiency analyses may potentially allow determinations that the testing process may be stopped before the complete testing of the sample set, and that the population may be declared a passing or failing population within a desired level of confidence.

Abstract: A state estimating apparatus permits efficient, highly accurate estimation of the state of an object. A particle in a state variable space defined by a second state variable preferentially remains or increases as the likelihood thereof relative to a current measured value of a first state variable is higher, while a particle is preferentially extinguished as the likelihood thereof is lower. A particle which transitions in the state variable space according to a state transition model with a high probability of being followed by an object (a high-likelihood model) as a next model tends to increase. On the other hand, although in a small quantity, there are particles having models (low-likelihood models) which are different from the high-likelihood model as their unique models.

Abstract: A method for advanced condition monitoring of an asset system includes sensing actual values of an operating condition for an operating regime of the asset system using at least one sensor; estimating sensed values of the operating condition by using an auto-associative neural network; determining a residual vector between the estimated sensed values and the actual values; and performing a fault diagnostic on the residual vector. In another method, an operating space of the asset system is segmented into operating regimes; the auto-associative neural network determines estimates of actual measured values; a residual vector is determined from the auto-associative neural network; a fault diagnostic is performed on the residual vector; and a change of the operation of the asset system is determined by analysis of the residual vector. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

Abstract: A damage probability calculating apparatus for calculating a damage probability of a specific estimation target includes: a storage unit 1 that stores a damage rate function representing a relationship between a damage rate and time; a damage rate function correcting unit 3 that corrects the damage rate function on the basis of examination data acquired at the time of general examination of the estimation target; and a damage probability calculating unit 4 that calculates the damage probability on the basis of the damage rate function corrected by the damage rate function correcting unit 3.

Abstract: A method for containing a fraction of values of a measurable characteristic of interest, occurring in process outcomes provided from a corresponding formation process, within tolerance limits based on samples thereof, the tolerance limits being based on a different formation process by which similar process outcomes are known to have been previously through selecting a probability representation over a representational variable to represent the distribution of values of the measurable characteristic of interest in the formation processes outcomes and using a selected Monte Carlo method with the probability representation to provide a plurality of sample values sets for the measurable characteristic of interest each containing a common selected number of sample values. A statistic is formed to test selected tolerance limits to find a value for tan incremental variable to assure those tolerance limits will be met with a selected confidence.