Abstract: A system for transforming time series data into data that is accessible by a data warehouse identifies a data table comprising the time series data. The system creates a virtual view of the data table where the time series data is represented as at least one standard relational table in the virtual view, where the virtual view is presented as a virtual table. The system partitions the virtual table into a plurality of virtual partitions according to a time interval. The virtual table is partitioned across a data time range, where the data time range comprises at least one time interval, and where each of the plurality of virtual partitions has a respective partition time range that spans the time interval. The virtual partitions are created to optimize loading of the data into the data warehouse by incrementally refreshing the data according to the respective partition time range.

Abstract: Systems, methods, and media for outputting a dataset based upon anomaly detection are provided. In some embodiments, methods for outputting a dataset based upon anomaly detection: receive a training dataset having a plurality of n-grams, which plurality includes a first plurality of distinct training n-grams each being a first size; compute a first plurality of appearance frequencies, each for a corresponding one of the first plurality of distinct training n-grams; receive an input dataset including first input n-grams each being the first size; define a first window in the input dataset; identify as being first matching n-grams the first input n-grams in the first window that correspond to the first plurality of distinct training n-grams; compute a first anomaly detection score for the input dataset using the first matching n-grams and the first plurality of appearance frequencies; and output the input dataset based on the first anomaly detection score.

Abstract: A supplemental rescue resources system can receive an emergency alert message from a mobile device and use data from the message and other sources to determine and select appropriate supplemental rescue resources, which may include may include any person that has volunteered or is otherwise a participant in the system that is not an on-duty emergency responder. The supplemental rescue resources system may select a supplemental rescue resources based on the location of such resources relative to the location of an incident, and/or the qualifications and/or preferences of such resources. The supplemental rescue resources system may direct resources to the incident and notify emergency services providers of the supplemental resources.

Abstract: The inventive subject matter is generally directed to a cross channel optimization system, methods, and related software which provide for the conducting of experiments and/or optimization of digital content across a plurality of external content systems to user of the external content systems.

Abstract: A switch unit has one frame buffer pool for storing received frames and another frame buffer pool for storing large frames. The frame size in the large frame buffer pool may be optimized to the largest amount of data the switch unit that an FCoE switching is running on can support (i.e., a limitation of zone entries). Should free space be unavailable in the large frame buffer pool, or if a sequence grows bigger than can be supported, the switch unit may still continue to send response frames back to the sender. While the switch unit may store header information of the frame, the switch unit does not store the data of subsequent frames any longer. Once the sequence has been received completely, a rejection message is sent back with an appropriate error or reason code. The rejection message enables the sender to attempt a retransmission or cancel the current request altogether.

Abstract: Providing a reminder of a task to be performed at a task location includes receiving location information identifying a location of a user via a mobile communication device associated with the user, receiving information that identifies a task, receiving information that identifies a task location, and providing a reminder for the task based on a current location of the user and on a comparison of an estimated probability of the user traveling in a trajectory leading toward the task location and an estimated probability of the user traveling in a trajectory leading away from the task location.

Abstract: A computer system is monitored for conditions bearing on the effective age of various hardware components of the system. Upon detecting an age adjustment condition, the affected hardware components are identified. An age adjustment is determined for each of the affected hardware components. The adjusted age is stored for reference when taking actions based on the adjusted age, such a component replacement and/or workload placement.

Abstract: Performance of a manufacturing tool is optimized. Optimization relies on recipe drifting and generation of knowledge that capture relationships among product output metrics and input material measurement(s) and recipe parameters. Optimized recipe parameters are extracted from a basis of learned functions that predict output metrics for a current state of the manufacturing tool and measurements of input material(s). Drifting and learning are related and lead to dynamic optimization of tool performance, which enables optimized output from the manufacturing tool as the operation conditions of the tool changes. Features of recipe drifting and associated learning can be autonomously or externally configured through suitable user interfaces, which also can be drifted to optimize end-user interaction.

Abstract: Provided is a system for testing mobile handover which makes it possible to test a handover operation on a mobile side by providing an actual base station with a radio wave environment for causing mobile devices to move. The system is intended to test whether or not a handover operation of a mobile present in the service areas of at least three base stations is performed without interrupting service while the mobile moves from the service area of a currently connected base station to another spot.

Abstract: An apparatus and method for building a map of probability distribution are provided. The apparatus for building the map of probability distribution includes: a sensor information collector configured to collect sensor information from a plurality of sensors; as object recognizer configured to recognize an object by integrating and inferring the sensor information, and to acquire object information; and a probability distribution creator configured to determine whether to apply an object property model including at least one of kinematic properties, shape properties, and probabilistic properties in correspondence to the object information, to acquire object properties corresponding to the object information, and to create a probability distribution based on foe object properties. Accordingly, it is possible to build a map with high reliability.

Abstract: Methods and systems of forecasting consumption of a consumable for a machine are disclosed. A computing device receives consumption time series data for a consumable for a plurality of machines. The consumption time series data for each machine includes an amount of the consumable consumed by the machine during each of multiple time periods. For at least one of the plurality of machines, the computing device determines a model consumption forecast for the machine for each of multiple dynamic linear models based on the consumption time series data for the consumable for the machine and the dynamic linear model. The computing device further determines, for at least one of the machines, a final consumption forecast based on the model consumption forecasts. An amount of the consumable is provided for the at least one machine based on the final consumption forecast.

Abstract: Methods and apparatus are directed to geofencing applications that utilize machine learning. A computing device can receive a plurality of geofence-status indications, where a geofence-status indication includes training data associated with a geofence at a first location. The geofence is associated with a geographical area. The computing device trains a geofence-status classifier to determine a geofence status by providing the training data as input to the geofence-status classifier. The training data includes data for a plurality of training features. After the geofence-status classifier is trained, the computing device receives query data associated with a second location. The query data includes data for a plurality of query features. The query features include a query feature that corresponds to a training feature. The query data is input to the geofence-status classifier. After providing the query data, the trained geofence-status classifier indicates the geofence status.

Abstract: A system that utilizes a plurality of time series of metric data to more accurately detect anomalies and model and predict metric values. Streams of time series metric data are processed to generate a set of independent metrics. In some instances, the present system may automatically analyze thousands of real-time streams. Advanced machine learning and statistical techniques are used to automatically find anomalies and outliers from the independent metrics by learning latent and hidden patterns in the metrics. The trends of each metric may also be analyzed and the trends for each characteristic may be learned. The system can automatically detect latent and hidden patterns of metrics including weekly, daily, holiday and other application specific patterns. Anomaly detection is important to maintaining system health and predicted values are important for customers to monitor and make planning and decisions in a principled and quantitative way.

Abstract: Methods and systems for providing and processing data are disclosed. An example method can comprise determining a first weighted probability based on a probability of occurrence of a noise signal and a first likelihood ratio. The first likelihood ratio is based on a frequency distribution of the noise signal. An example method can comprise determining a second weighted probability based on a probability of non-occurrence of the noise signal and a second likelihood ratio. An example method can comprise determining a combination of the first weighted probability and the second weighted probability, and providing the combination to a decoder configured to decode a value based on the combination.

Abstract: Apparatus, computer readable medium, program code, and methods for performing a parameter recalibration on parameters for an electrical submersible pump application model, are provided. An example of a method can include generating a data set containing a plurality of winning data sets or rows containing ESP application model input parameters and associated theoretical output parameters for an ESP application model substantially matching a corresponding set of measured ESP output parameters, through application of a self-organizing map analysis on a substantial number of training data sets. An averaging analysis is performed on the plurality of winning data sets or rows to obtain a set of ESP application model input parameters that can be used to recalibrate the ESP application model.

Abstract: Various technologies described herein pertain to generating a video loop. An input video can be received, where the input video includes values at pixels over a time range. An optimization can be performed to determine a respective input time interval within the time range of the input video for each pixel from the pixels in the input video. The respective input time interval for a particular pixel can include a per-pixel loop period and a per-pixel start time of a loop at the particular pixel within the time range from the input video. Moreover, an output video can be created based upon the values at the pixels over the respective input time intervals for the pixels in the input video.

Abstract: Systems and methods for determining an appropriate parameter order for a building energy use model are provided. A described method includes receiving an energy use model for a building site, obtaining a plurality of data points, calculating a first regression statistic indicating a fit of the energy use model to the plurality of data points under a null hypothesis and a second regression statistic indicating a fit of the energy use model to the plurality of data points under an alternative hypothesis, and comparing a test statistic to a threshold value. The test statistic is a function of the first regression statistic and the second regression statistic. The method further includes determining an appropriate parameter order for the energy use model based on a result of the comparison.

Abstract: A method of determining the performance of a chip of an integrated-circuit design comprises instantiating a plurality of HPM in the integrated-circuit design to generate the performance of the chip according to a performance function defined by a polynomial comprising a plurality of terms, wherein each term of the polynomial comprises an exponent of a value generated by a corresponding one of the plurality of HPM(s) and a corresponding coefficient, wherein the coefficients are determined through a regression process with sample chips of the integrated-circuit design having known performance, so that the performance of each chip other than the sample chips can be determined by the performance function and the values of the plurality of HPM(s) of the chip.

Abstract: An apparatus comprising a housing, a gearing system disposed within the housing and comprising a plurality of targets, a plurality of sensors incorporated within the housing, a processor in electrical signal communication with the sensors, and a user interface in signal communication with the processor. A method comprising providing a drive system comprising a drive system power measuring and diagnostic system, wherein the drive system is configured to rotate one or more components comprising a plurality of targets, sense the targets with a sensor pair, thereby producing a data signal, process the data signal from the one or more sensor pairs, thereby producing a processed data signal, and output the processed data signal to a user.

Abstract: A wafer acceptance test (WAT) system and method that, in one embodiment, includes: (1) a saturation current WAT subsystem operable to generate a weighted standard deviation based on target NMOS and PMOS saturation currents and saturation current WAT results, (2) a wafer IC speed WAT subsystem operable to generate a speed performance probability distribution of wafer ICs based on the weighted standard deviation and speed WAT results, (3) a wafer IC power WAT subsystem operable to employ the speed WAT results and power WAT results to generate a power performance model of wafer ICs, and (4) a yield calculator operable to generate a power performance variance probability distribution of wafer ICs based on the power performance model and the power WAT results, and to employ the speed performance probability distribution and the power performance variance probability distribution to generate the yield forecast with respect to a target performance profile.

Abstract: A system and a method, implemented on a computer, for calculating property distribution uncertainty of spatially correlated petrophysical data. The method includes inputting, into the computer, a sample petrophysical data comprising correlated data; applying, using the computer, a variogram to the sample petrophysical data to select a plurality of subsets of data, the subsets of data being substantially less correlated than the sample petrophysical data; and applying, using the computer, a bootstrap process on each of the plurality of subsets of data to obtain a plurality of bootstrap data sets from each of the plurality of subsets of data. The method further includes calculating data distributions for each of the obtained plurality of bootstrap data sets; ranking the data distributions by using a selected statistical parameter to obtain ranked data distributions; and characterizing the uncertainty based on the ranked data distributions.

Abstract: Visualizing content change of a data collection over time. A topic may be split into multiple linear, non-overlapping sub-topics along a timeline by satisfying a diverse set of semantic, temporal, and visualization constraints simultaneously. For each derived sub-topic, a set of representative keywords may be automatically selected to summarize the main content of the sub-topic.

Abstract: A computer-implemented system and method for capability zone-based manufacturing quality control are provided. A specification for manufacturing a part feature is obtained, the specification including a nominal and a tolerance. A plurality of measurements for the feature are obtained. A difference is determined between the nominal and each of the measurements. The difference for each of the measurements is compared to the tolerance. Each of the measurements is assigned into one of a plurality of capability zones of measurements based on the comparison. Visual representations of the capability zones into which the measurements were assigned are displayed.

Abstract: In one aspect, a method for displaying measurement information from at least one sensor of a machine is provided. In another aspect, a computing device for displaying measurement information from at least one sensor of a machine is provided. In another aspect, a system for displaying measurement information from at least one sensor of a machine is provided.

Abstract: A method for detecting a fall by a user includes a method of detecting a fall by a user. The method includes processing measurements obtained from one or more sensors to extract a respective value for a plurality of features associated with a fall. A respective log likelihood ratio for each of the values is determined. Whether the user has fallen is determined based on the determined log likelihood ratios.

Abstract: A method, implemented on a computer, for calculating vertical trend curve uncertainty of spatially correlated reservoir data. The method includes inputting, into the computer, a sample reservoir data comprising correlated data; applying, using the computer, a variogram to the sample reservoir data to select a plurality of subsets of data, the subsets of data being substantially less correlated than the sample reservoir data; and applying, using the computer, a bootstrap process on each of the plurality of subsets of data to obtain a plurality of bootstrap data sets from each of the plurality of subsets of data. The method further includes calculating vertical trend curves for each of the obtained plurality of bootstrap data sets, ranking the vertical trend curves by using a selected statistical parameter to obtain ranked vertical trend curves, and characterizing the uncertainty based on the ranked vertical trend curves.

Abstract: A system is disclosed for obtaining and aggregating opinions generated by multiple sources with respect to one or more objects. The disclosed system uses observed variables associated with an opinion and a probabilistic model to estimate latent properties of that opinion. With those latent properties, the disclosed system may enable publishers to reliably and comprehensively present object information to interested users.

Abstract: Techniques for detecting, analyzing, and/or reporting code clone are described herein. In one or more implementations, clone-code detection is performed on one or more source code bases to find true and near clones of a subject code snippet that a user (e.g., a software developer) expressly or implicitly selected. In one or more other implementations, code clone is analyzed to estimate the code-improvement-potential (such as bug-potential and code-refactoring-potential) properties of clones. One or more other implementations present the results of code clone analysis with indications (e.g., rankings) of the estimated properties of the respective the clones.

Abstract: The disclosure includes a system and method for generating a probability model used to estimate most likely routes for users. The system includes one or more processors configured to retrieve route data describing historical routes traveled by a group of users and map date describing a map, match the historical routes to the map, identify one or more intersections associated with the historical routes on the map, determine a maneuver ratio for one of the intersections based on the route data, and generate a probability model including one or more maneuver ratios for the one or more intersections. A maneuver ratio describes a ratio of a maneuver that the group of users has taken at the one of the intersections.

Abstract: Connectivity fault notification is provided by generating an alarm indication signal at a device that is logically adjacent to the fault, and forwarding the alarm indication signal upward through various levels to at least one client level entity. The alarm indication signal may be suppressed at any level for a service instance if service is restored at that level, or if a protection path prevents disruption of the service instance at that level, or auto-suppressed at an originating node based on number of times transmitted or elapsed time. The alarm indication signal may include a point of failure indicator such as the MAC address of the device that generates the alarm indication signal, or a failed resource identity such as an IEEE 802.1AB LLDP MAC Service Access Point (“MSAP”). Further, the alarm indication signal may be employed to trigger use of the protection path.

Abstract: Operational parameters of a single-photon detector are determined with a continuous wave laser source. At a fixed trigger, a dark count probability and a series of count probabilities at different optical powers are determined. A particular optical power is selected by using a wide-range variable attenuator to attenuate the optical power of the continuous wave laser. The dark count probability and the count probabilities are determined for different trigger rates. The operational parameters include efficiency, afterpulsing constant, and detrap time. The operational parameters are computed by fitting the computed dark count probabilities and count probabilities to a user-defined relationship.

Abstract: Methods and devices to detect analyte in body fluid are provided. Embodiments include receiving one or more analyte sensor data, receiving a reference measurement value associated with an analyte level, determining a sensitivity parameter based on the received one or more analyte sensor data and the reference measurement value, performing a probability analysis based on prior analyte sensor data to determine presence of signal attenuation, and generating an output value based on the probability analysis.

Abstract: The present disclosure relates to classification of a material type of an object. A first phase applies an object classifier and a material classifier to obtain first object and material probabilities of the object. A second phase applies an interdependent object/material classifier to the first object and material probabilities to obtain further object and material class probabilities. The interdependent object/material classifier performs multiple iterations of calculating the further object and material class probabilities, and utilizes feedback in which an immediately preceding calculated prior further object class probability is included in a next iteration of calculating a further material class probability, and an immediately preceding calculated prior further material class probability is included in a next iteration of calculating a further object class probability.

Abstract: A method for monitoring a condition of a system or process includes acquiring sensor data from a plurality of sensors disposed within the system (S41 and S44). The acquired sensor data is streamed in real-time to a computer system (S42 and S44). A discriminative framework is applied to the streaming sensor data using the computer system (S43 and S45). The discriminative framework provides a probability value representing a probability that the sensor data is indicative of an anomaly within the system. The discriminative framework is an integration of a Kalman filter with a logistical function (S41).

Abstract: A product inspection device that includes a measuring section, a deemed standard deviation calculation unit, a measurement value standard deviation calculation unit, a determination unit, and a risk calculation unit. The measuring section measures characteristic values of products, the deemed standard deviation calculation unit calculates a deemed standard deviation, and the risk calculation unit calculates a consumer risk and a producer risk based on at least one of an average value of the measured characteristic values of some of the products contained in a measured product lot, the deemed standard deviation, or the measurement value standard deviation. The determination unit changes a inspection standard based on at least one of the calculated consumer risk or the calculated producer risk, and determines whether or not all the products contained in the product lot are non-defective articles with the changed inspection standard as a reference.

Abstract: Methods and systems of determining a failure copula for a consumable are disclosed. Multiple consumable levels for a consumable and multiple timestamps are received from a device. Each timestamp is associated with one of the consumable levels. The consumable levels are ordered into a time-ordered sequence based on the associated timestamps. For at least one consumable level in the time-ordered sequence, a computing device determines a value associated with the consumable level based on at least one earlier and at least one later consumable level in the time-ordered sequence. The computing device identifies historical consumable replacement(s) based on the values associated with the consumable levels in the time-ordered sequence and determines one or more consumable lifetimes and one or more consumable yields based on the historical consumable replacement(s). The computing device determines a failure copula based on the one or more consumable lifetimes and consumable yields.

Abstract: Apparatus and method for improving the performance of a threshold-based detector or classifier, or a generic detector or classifier and increasing the probability of detecting at least one object in an image using novel algorithms and stochastic resonance noise is provided, where a suitable dose of noise is introduced to the image data such that the performance of the above-referenced detectors or classifiers is improved without altering the detector's or classifier's parameters. Several stochastic resonance (SR) noise-based detection and classification enhancement schemes are presented. The SR noise-enhanced detection and classification schemes can improve any algorithms and systems. To implement these schemes, the only knowledge that is needed is the original input data (no matter 1D, 2D, 3D or others) and the output (detection results) of the existing algorithms and systems.

Abstract: Techniques are presented for producing demographics, in an automated fashion, from a search result of computer-accessible content. While the demographics can be determined for a research product that has been produced by any technique, they are particularly useful when applied to an automated frame-based search approach. Frame-based search engines are presented for technology profiling, healthcare-related search and brand research. Determination of a demographic proceeds at two levels: member and population. At the member level, a demographic characteristic can be determined applicable with either total or partial certainty. Each value assigned by a demographic, to a population member, has a confidence level associated with it and the assignments can be represented by a Confidence Distribution. Summarization of a demographic, at the population level, depends upon whether the certainty assignments, at the member level, are total or partial. Declarant Demographics are presented.

Abstract: In analyzing an elaborate computer system which requires large-scale or numerous event propagation models, a law-of-causality matrix gains size, so that significant amount of storage resources has been used in a management computer. To solve such a problem, the management computer to manage the computer system stores topologies, event propagation models, and causality information including one or more causal relations in the storage resources, determines, when the management computer analyzes or detects an event, whether a causal relation has already been created for the event to be analyzed, and creates the causal relation based on a topology and event propagation models, if not yet.

Abstract: A method for locating the position of the wheels of a vehicle, each wheel being equipped with a sensor capable of emitting a location signal and the vehicle being equipped with a receiver capable of receiving the location signals emitted by the sensors. The method includes the step of determining a signature of the location signal emitted by the sensor of each wheel as a function of the position of the wheel on the vehicle, and the step of storing in the receiver the signature and the corresponding position of each of the wheels. The receiver is equipped with at two least two antennas, called first and second antennas, the signature of the location signal emitted by the sensor of each wheel being determined from the strength difference between the strength of the signal received by the first antenna and the strength of the signal received by the second antenna.

Abstract: A system for improved reliability operations of a system with a heat recovery steam generator (HRSG) are presented. The system includes a processor configured to execute a model library to model a safety system. The model library includes a plurality of subsystem models each configured to derive a reliability measure. The system also includes the HRSG and an HRSG advisory system. The HRSG advisory system may be executed by the processor and is configured to receive one or more condition monitoring algorithm results, receive one or more measurements; and determine a probability of failure for the HRSG based at least in part on the one or more condition monitoring algorithm results, the one or more measurements, the model library, or a combination thereof. Moreover, determining the probability of failure includes determining a most likely state of a plurality of states of the HRSG.

Abstract: A feature extraction method and apparatus for use in causal effect analysis, pertaining to data analysis, which includes: determining a feature time point for use in causal effect analysis on a resultant event; acquiring a predetermined number of time intervals according to the determined feature time point, where the predetermined number of time intervals are prior to the determined feature time point, and the interval length from the time interval to the determined feature time point is in positive correlation to the span of the time interval; and extracting features for use in causal effect analysis on the resultant event according to event information of potential causal events occurred in each of the time intervals. According to the present disclosure, considering the short-period and long-period potential causal event, the number of extracted features is controlled, thereby reducing the calculation workload, preventing overfitting, and improving the accuracy in causal effect analysis.

Abstract: System, method, computer program product embodiments and combinations and sub-combinations thereof for data replication in a database system environment are described. In an aspect, the data replication includes grouping, in-memory, a plurality of transactions to be replicated as a single transaction from a source database system to a target database system. A plurality of net row changes is compiled for the plurality of transactions, and data inconsistency detection and resolution within a command application order are performed. Further included is bulk application of the plurality of net row changes to the target database system.

Abstract: The present invention provides automatic gating methods that are useful to gate populations of interest in multidimensional data, wherein the populations of interest are only a subset of the populations identifiable in the data. The populations are modeled as a finite mixture of multivariate probability distributions, preferably normal or t distributions. The distribution parameters that provide a best fit of the model distribution to the data are estimated using an Expectation Maximization (EM) algorithm that further includes a dynamic neighborhood thresholding that enables gating of a subset of the clusters present in the data.

Abstract: A supplemental rescue resources system can receive an emergency alert message from a mobile device and use data from the message and other sources to determine and select appropriate supplemental rescue resources, which may include may include any person that has volunteered or is otherwise a participant in the system that is not an on-duty emergency responder. The supplemental rescue resources system may select a supplemental rescue resources based on the location of such resources relative to the location of an incident, and/or the qualifications and/or preferences of such resources. The supplemental rescue resources system may direct resources to the incident and notify emergency services providers of the supplemental resources.

Abstract: In one example of a method for remote identifying a non-Lambertian target material, a spectral signature for a target is determined from each of at least two different sets of imagery acquired at different angles, and compared to a predicted signature for a candidate material for each of the at least two different angles. The predicted signatures take into account the known anisotropy of reflectance, and thus also radiance, of the candidate material.

Abstract: A method of analyzing failures of a print device may include receiving failure information associated with a print device in a print shop. The failure information may pertain to a plurality of failures experienced by the print device over a period of time. The method may include generating, by a computing device, failure distribution information by, for each pair of consecutive failures in the failure information, determining a time to failure between the pair of consecutive failures, determining a repair time associated with each failure in the pair of consecutive failures, and setting the determined times to failure and the determined repair times as the failure distribution information. The method may include performing, by the computing device, a simulation of processing of one or more print jobs by the print device using the failure distribution information, and displaying one or more results of the simulation to a user.

Abstract: Determination of digital compensation to compensate for non-linearity of stochastic system configured to sample a phase difference, based on statistical analysis of calibration data generated by the stochastic system in response to a linear phase ramp. The stochastic system may include a set of stochastic sampler circuits to sample a phase difference at periodic events, and calibration data may include a digital value of set of stochastic samples for each of multiple events. The calibration data may include sequences of the digital values in which the digital values increment over a range of the stochastic system (i.e., between saturation states of the stochastic system). Statistical analysis may include histogram analysis to estimate the probability distribution of the calibration data. The stochastic system may be configured as part of a time-to-digital converter, which may be configured within a feedback loop of a digitally controllable phase lock loop.

Abstract: A method of obtaining a consistent evaluation of the state of the system which has been monitored by measurement of multiple parameters of that system. The multiple parameters are used to calculate a single dimensional value based on the distance between the current state and normal states of the system using a Parzen Windows probability function. Consistent single dimensional values regardless of the dimensionality of the original data set can be obtained by finding a relationship between the single dimensional value and the probability of status of the system. Different relationships are obtained for different dimensionalities of data sets. Sensor malfunction can also be detected by testing the probability of the state implied by measuring all of the available parameters against the probability of the state implied by ignoring different individual ones of the parameters. A significant disparity in the two probabilities indicate possible sensor malfunction.

Abstract: A method to automatically quantify dendrite arm spacing in dendritic microstructures. Once a location of interest in a cast material specimen has been identified, the information contained in it is automatically analyzed to quantify dendrite cell size information that is subsequently converted into a quantified dendrite arm spacing through an empirical relationship or a theoretical relationship. In one form, the relationship between DCS and DAS is such that the DAS in dendritic structure of cast aluminum alloys may be automatically determined from the measurement of one or more of dendrite cell size and the actual volume fraction of the eutectic phases in the local casting microstructure. Non-equilibrium conditions may be accounted for in situations where a theoretical volume fraction of a eutectic phase of the alloy in equilibrium condition is appropriately modified.