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20010044766

09746411

1. A method for grouping assets using a classification and regression tree based model of asset portfolios, said method comprising the steps of: defining relevant portfolio segmentations; assessing performance of the classification and regression tree based model against a simple model; and ranking all portfolio segments based upon performance of the models.

8868473

13279447

1. A non-transitory computer-readable medium storing computer-executable instructions that when executed by a computer cause the computer to perform a method, the method comprising: determining a Boolean function that recursively defines split conditions in each node of a binary classification tree as a disjunction of i) a first conjunction of split conditions for the node and one of the node's child nodes and ii) a second conjunction of split conditions for the node and the other of the node's child nodes; representing the binary classification tree as a Rvachev classification tree function by replacing each disjunction in the Boolean function as an Rvachev disjunction and each conjunction in the Boolean function as a Rvachev conjunction; deriving a split parameter update rule for a tree function based, at least in part, on a derivative of the Rvachev classification tree function; applying the split parameter update rule to a plurality of training data samples to determine split parameters for a tree function, where the tree function comprises a sum of products of respective attributes and respective split parameters associated with the respective attributes; and receiving an input data sample for classification as belonging to one of two possible classes, wherein the input data sample includes a set of attribute values; evaluating the set of attribute values with the tree function; and classifying the input data sample as belonging to one of the two classes based, at least in part, on an output of the tree function.

7574359

10957383

1. A computer-implemented method of transforming and combining a plurality of models representing training speakers into a model for a test speaker, comprising: receiving adaptation data from the test speaker; utilizing a computer processor that is a functional component of the computer to select a set of cohort speakers from the training speakers; transforming a plurality of models representing the cohort speakers; and combining the plurality of transformed models to form the model for the test speaker; wherein selecting a set of cohort speakers comprises: generating a Gaussian Mixture Model (GMM) for each of the training speakers in the plurality of training speakers, wherein generating the GMM for each of the training speakers comprises calculating a probability mixture component for each GMM, wherein the Gaussian Mixture Models are calculated according to the following equation: b ⁢ ⁢ ( O ) = ∑ k = 1 M ⁢ ⁢ c k ⁢ G ⁢ ⁢ ( O , μ k , U k ) ; where b(O) is an output probability of observation sequence O, c k is a weight for k-th mixture component, G is a Gaussian function with mean vector μ k and convariance matrix U k , and wherein the probability mixture component is calculated according to the following equation: p ⁢ ⁢ ( k | o ⁢ ⁢ ( t ) , Λ n ) = c k ⁢ G ⁢ ⁢ ( o ⁢ ⁢ ( t ) , μ k , σ k 2 ) ∑ i = 1 M ⁢ ⁢ c i ⁢ G ⁢ ⁢ ( o ⁢ ⁢ ( t ) , μ i , σ i 2 ) ; where p(k|O(t),Λ n ) is a posterior probability for mixture component k and weight vector Λ n , c k is a weight for k-th mixture component, and G is a Gaussian function with observation vector O(t) at time t, mean vector μ k and diagonal covariance matrix σ 2 i ; determining a similarity between the models for the training speakers and the adaptation data from the test speaker based at least in part on the Gaussian Mixture Models and the probability mixture components; and selecting as a set of cohort speakers, training speakers that have models having a desired similarity to the adaptation data from the test speaker; wherein transforming the plurality of models representing the cohort speakers comprises: receiving model data for each of the models representing the cohort speakers; and adapting the model data for each of the models representing the cohort speakers based on the adaptation data from the test speaker, wherein the model data for each of the models representing the cohort speakers is adapted independently from one another; and wherein combining the plurality of transformed models comprises: determining a weight vector for each of the transformed models, the weight vector for each of the transformed models being based at least partially on the adaptation data from the test speaker; and combining the plurality of transformed models based on the weight vectors to form the model for the test speaker.

9923911

14878171

1. A method, comprising: maintaining, by a device in a network, information regarding anomaly detection models used in the network and applications associated with traffic analyzed by the anomaly detection models wherein the device acts as a supervisory and control agent (SCA) device; receiving, at the device, an indication of a planned application deployment in the network; and adjusting, by the device, an anomaly detection strategy of a particular anomaly detector of a distributed learning agent (DLA) device in the network prior to deployment of the planned application, wherein the information regarding anomaly detection models used in the network and the applications associated with the traffic analyzed by the anomaly detection models is used by the device to adjust the anomaly detection strategy.

20100332430

12793138

1. A method of mining a data set that comprises at least one feature created from at least one plant-based molecular genetic marker, to find at least one association rule, and utilizing one or more features created from these association rules for classification or prediction for one or more target features.

20160291788

14391411

1. A device comprising: a display, wherein the display is configured to operate in at least one of a touch mode or a touchless mode; a predictive input system communicatively coupled to the display, wherein the predictive input system comprises: a memory, wherein the memory stores instructions; and a processor, wherein the processor executes the instructions to: store zone data indicating zones of the display, wherein each zone constitutes a portion of a display area of the display; store predictive parameter data, wherein each zone of the zone data is assigned a subset of the predictive parameter data, wherein each subset of the predictive parameter data indicates at least one of a look-ahead prediction value that indicates a time period corresponding to how far in the future a predictive user input pertains, an indication of a particular prediction algorithm, or at least one value used by the particular prediction algorithm, and wherein at least two zones of the display have different values for the subsets of predictive parameter data; receive, via the display, input data stemming from a user's input; determine the zone in which the input data is received; generate prediction data based on the input data, the zone data associated with the determined zone, and the subset of predictive parameter data associated with the determined zone; and output the prediction data.

9626426

14163555

1. A computer-implemented method of clustering a set of query vectors into K clusters using locality-sensitive hashing (LSH), wherein the LSH is parameterized by a number of projections m, a quantization factor w, and a number of repetitions L and hashes a vector to a collection of buckets, comprising: grouping the set of query vectors into K clusters; and iterating the following steps until a termination condition is reached: computing centroids of the K clusters; and assigning each query vector of the set of query vectors to one of the K clusters with a nearest centroid using the LSH over the query vector and the K centroids, wherein the assigning comprises: hashing each of the K centroids using the LSH into the collection of buckets; and for each of the query vectors: hashing the query vector using the LSH into the collection of buckets; identifying the nearest centroid in the collection of the buckets to which the query vector is hashed; and assigning the query vector to the cluster with the nearest centroid.

10068024

14974871

1. A method for generating data to provide situational awareness or decision-making assistance to a user in relation to a physical environment, the method comprising, with a computer system: processing input data comprising at least data associated with the physical environment; and when a need for situational awareness or decision-making assistance is detected based on the input data, generating response data, the response data derived from multimodal data from a plurality of electronic data streams comprising audio, visual and textual information, the data streams received from a plurality of data sources, wherein generating the response data comprises: determining a characteristic of the need for situational awareness or decision-making assistance; extracting semantic information from the audio, visual and textual information; correlating the extracted semantic information in accordance with the characteristic; selecting a subset of the audio, visual and textual information based on the correlation of the extracted semantic information with the characteristic; and outputting at least a portion of the selected subset as the response data.

8671099

13338689

1. A method of clustering devices in an Internet of Things (‘IoT’), the method comprising: receiving, by a device clustering module, a characteristic set for a device, wherein the characteristic set specifies one or more device attributes and an attribute value for each device attribute; clustering, by the device clustering module, the device into an attribute level cluster based on the one or more device attributes specified in the characteristic set for the device; and clustering, by the device clustering module, the device into a value level cluster based on the attribute value for each device attribute, wherein the value level cluster is a subset of the attribute level cluster.

10152318

15420332

1. A non-transitory computer-readable medium storing computer-executable instructions that when executed by a processor of a computer causes the processor to: execute an application as an executing application to process data of attributes stored within a data structure maintained according to a data model; receive a new data structure definition of a new data structure to define for the data model, wherein the new data structure definition defines at least one attribute for the new data structure not stored within the data structure; perform impact analysis to determine whether the executing application is capable of processing data of the new data structure; and in response to determining that the executing application is capable of processing the data of the new data structure: update the data model to include the new data structure definition to create an updated data model; generate control instructions to instruct the executing application to utilize data from the new data structure according to the updated data model, wherein the executing application is controlled to execute the control instructions; and during execution of the executing application, execute the control instructions to reconfigure the executing application to access data of attributes stored within the new data structure and bypass processing data from the data structure.

9336338

13760420

1. A computer-implemented method for optimizing a cost of electric power generation in a smart site energy management model, the method implemented by a computer comprising the steps of: providing, to a computer system, a cost function ζ that models a smart building-grid energy system of a plurality of buildings on a site interconnected with electric power grid energy resources and constraints due to a building model, an electric grid model, and a building-grid interface model, wherein decision variables for each of the building model, the electric grid model, and the building-grid interface model are box-constrained; and minimizing, by the computer system, said cost function subject to the building model constraints, the electric grid model constraints, and building-grid interface model constraints, wherein the building model includes a plurality of buildings, one or more gas turbines and generators as on-site sources for electricity power, electric chillers, pumps and thermal energy storage tanks, wherein waste heat in exhaust gas from the gas turbines is used to generate steam in one or more heat recovery steam generator (HRSG) units, steam from the HRSG units drives one or more absorption chillers to generate cooling, one or more steam turbines to drive additional electricity generators, or provides heating needs for the plurality of buildings, the electric grid includes one or more loads and is modeled as an undirected graph G=(N, E), where N and E denote sets of electric nodes and branches, respectively, wherein each branch has an origin terminal and a destination terminal, each terminal is connected to an electric node, a voltage at node n 1 is a complex number defined by its magnitude and angle, and a power flow at terminal t 1 is a complex number defined by its real and imaginary parts, and the building-grid interface model constrains a building cooling load to be satisfied by chiller operations at all times, and an electricity load to be satisfied by on-site generation and the electric grid.

9665909

12906460

1. A method, executed by a processor, for generating a transaction classification rule, comprising: storing a transaction as unclassified in the absence of a classification rule for the transaction until a processing module of a transaction classification system is populated with the classification rule; receiving an identification, from a user and with a user interface (UI) of the transaction classification system, of the existing unclassified transaction upon which the classification rule will be based; generating an identification rule to identify subsequent unclassified transactions as similar to the existing unclassified transaction; using the identification rule to identify the subsequent unclassified transactions; receiving an indication, from the user and with the UI, of a specific web application technology indicated by the user; generating the classification rule using the identified transaction, wherein the classification rule is associated with the user-specified web application technology; and storing the classification rule for application to the subsequent unclassified transactions, wherein application of the generated classification rule to the subsequent unclassified transactions produces transactions classified according to the classification rule.

7949618

11729498

1. A method of training a machine learning system to determine photoresist parameters of a wafer application to fabricate a structure on a wafer using optical metrology, the method comprising: a) obtaining a set of different values of one or more photoresist parameters, wherein the one or more photoresist parameters characterize behavior of photoresist when the photoresist undergoes processing steps in the wafer application; b) obtaining a set of diffraction signals using the set of different values of the one or more photoresist parameters; and c) training a machine learning system using the set of diffraction signals as inputs to the machine learning system and the set of different values of the one or more photoresist parameters as expected outputs of the machine learning system, wherein the one or more photoresist parameters comprise change of inhibitor concentration, surface inhibition, diffusion during the photoresist baking process, development rate parameters, labile absorptivity, non-labile absorptivity, and/or intrinsic sensitivity of the photoresist.

20120136194

13212164

1. A method of forming a treatment plan for treating a patient with radiation therapy, the method comprising: receiving information corresponding to a tumor position in the patient determined using an imaging device; selecting a plurality of beam angles for a respective plurality of beams based on the tumor position; receiving information corresponding to a plurality of constrained and unconstrained objective function parameters related to at least one of a minimum and maximum radiation dosage to a specific region of interest; selecting an intensity for each beam based, in part, on the objective function parameters; selecting new unconstrained objective function parameters based, in part, on the previous unconstrained objective function parameters; and selecting new beam intensities based, in part, on the new unconstrained objective function parameters.

20130262356

13825711

1. A method for classifying biometric data ( 1 ) belonging to a first continuous and limited area of representation corresponding to at least one determined type biometric sensor, comprising: a step of acquiring by said at least one sensor of determined type biometric data in the form of a set of multidimensional vectors of parameters, a step of defining a second area of representation wherein each biometric data ( 1 ) is represented by a first distribution ( 2 ) such that the biometric data are represented thereto by a first set of first distributions, the first distributions responding to a same probability distribution function of at least one first parameter, such that the first set of first distributions is defined by a first set of first parameters determined based on biometric data, a first step of constructing a first statistical model ( 3 ) in automatic classification of a universal collection ( 11 ) of biometric data in the second area of representation, the first statistical model being defined by at least one second finite set of second distributions ( 31 ), the second distributions responding to a same probability distribution function of at least one second parameter and being distributed in the second area of representation according to at least one second set of second parameters, such that each second distribution defines a sub-space of the second area of representation comprising a plurality of first distributions representative of a part of said universal collection ( 11 ) of biometric data, the second set of second parameters being optimized by a first implementation ( 7 ) of a likelihood maximization algorithm, such that the second finite set of second distributions represents with the maximum likelihood the first set of first distributions ( 2 ) corresponding to said universal collection of biometric data, the first statistical model ( 3 ) thus being able to match any biometric data ( 1 ) with a determined sub-space, each sub-space being associated with a plurality of biometric data, and a second step of constructing a second statistical model ( 4 ) comprising a plurality of statistical sub-models ( 41 ) in automatic classification of a set of first individual collections ( 12 ) of biometric data, each sub-model being defined in a corresponding sub-space of the second area of representation, the second construction step comprising, for each distribution representative of each biometric data of each individual collection ( 12 ), the determination of a sub-space corresponding thereto according to the first statistical model ( 3 ), and in this sub-space, its classification ( 8 ) in the corresponding sub-model, such that each sub-model ( 41 ) is defined by a third set of first distributions ( 2 ), the second construction step further comprising, for each sub-space, a step of selecting ( 9 ) first distributions amongst said third set of first distributions by implementing a coverage maximization and redundancy minimization iterative algorithm, for determining a fourth minimum set ( 21 ) of first distributions ( 2 ) maximizing the coverage of the sub-space, such that each sub-model ( 41 ) is defined by the fourth minimum set ( 21 ) of first distributions corresponding thereto, such that the plurality of statistical sub-models ( 41 ) of the second statistical model ( 4 ) is defined by a plurality of fourth minimum sets of first distributions, the second statistical model ( 4 ) being thus able to make it possible for any biometric data of a determined sub-space according to the first statistical model ( 3 ), to determine the first distribution with which its likelihood is maximum from amongst the first distributions of the fourth minimum set ( 21 ) of first corresponding distributions, a step of saving to a memorization medium first and second statistical models, such as to make their future use in automatic classification of biometric data possible.

4630242

06363721

1. A method for estimating the reflection sequence of the earth from a seismic reflection trace generated by a swept frequency vibrator, including the steps of: forming an initial estimate of the reflection sequence from a model of the earth; forming an estimated seismic reflection trace from the initial estimate of the reflection sequence from the model of the earth by convolving the initial estimate of the reflection sequence of the earth with a pilot signal of the swept frequency vibrator; generating an error signal representative of the difference between an uncorrelated seismic reflection trace and the initial estimated seismic reflection trace; and revising the estimate of the reflection sequence of the earth by minimizing the error signal.

20030237062

10178193

1. A process of testing an IC design described in HDL code in conjunction with a hardware simulator and a coverification tool on a workstation, wherein the coverification tool provides both firmware control of the IC design via a modeled processor bus, and test stimuli of the IC design via a modeled system interface that is either an industry standard or a proprietary interface, the process comprising steps of: a) operating the co-verification tool in the workstation to execute IC firmware associated with the IC design; b) operating the IC design through the modeled processor bus using the executed IC firmware; and c) operating the co-verification tool in the workstation to supply test stimuli through the modeled system interface to the IC design, the test stimuli being compatible to the industry standard or proprietary interface and IC design being responsive to the test stimuli to provide responses to the workstation.

8488886

12848246

1. A method, comprising: receiving, by at least one computing device, a glyph; reducing, by the at least one computing device, the received glyph to a predefined format; normalizing, by the at least one computing device, the reduced glyph; comparing, by the at least one computing device, the normalized glyph to a plurality of image prototypes; and outputting, by the at least one computing device, at least one of the plurality of image prototypes based on the comparison of the normalized glyph to the plurality of image prototypes, wherein comparing the normalized glyph to the plurality of image prototypes includes: determining a number of rows in the normalized glyph and a number of rows in a selected one of the plurality of image prototypes; for the lesser of the number of rows in the normalized glyph and the number of rows in the selected one of the plurality of image prototypes, exclusive-or'ing (xor'ing) pixels of the normalized glyph with corresponding pixels of the selected one of the plurality of image prototypes; accumulating a result of the xor'ing of the pixels of the normalized glyph with the corresponding pixels of the selected one of the plurality of image prototypes; for each row of the normalized glyph and the selected one of the plurality of image prototypes that was not xor'ed, adding to the result a number corresponding to the number of pixels ‘on’ in the normalized glyph or the selected one of the plurality of image prototypes; and saving the added result.

20140161346

13521439

1. A feature point selecting system comprising: a recognition task executing unit that executes a recognition task using an importance of each of a plurality of feature point candidates on a three-dimensional shape model for a plurality of evaluation images which are generated from the three-dimensional shape model and which are used to evaluate a recognition error in the recognition task; a recognition error evaluating unit that evaluates a recognition error related to all evaluation images from a difference between a recognition result of the recognition task executing unit and correct data of the recognition task for each evaluation image; a feature point importance determining unit that determines the importance of each feature point candidate by setting a cost function which is a function for the importance of each feature point candidate and which is represented as a function obtained by adding a restriction condition that an importance of an unimportant feature point candidate becomes close to zero, to the recognition error related to the all evaluation images, and calculating the importance of each feature point candidate which minimizes a value of the cost function; and a feature point selecting unit that selects a feature point which needs to be used in the recognition task from the feature point candidates on the three-dimensional shape model based on the importance of each feature point candidate, wherein, with the recognition task executing unit, the recognition error evaluating unit and the feature point importance determining unit, until the value of the cost function which is set based on the importance of each feature point candidate determined by the feature point importance determining unit converges, repeatedly, the recognition task executing unit executes the recognition task, the recognition error evaluating unit evaluates the recognition error related to the all evaluation images and the feature point importance determining unit determines the importance of the feature point candidates.

8645393

13088113

1. A computer-implemented method comprising: accessing clusters, with two or more clusters corresponding to different name contexts, and with a cluster comprising resources that are determined to be relevant to a name context of the cluster; receiving, for a resource in the cluster, a search score for the resource, the search score being indicative of a relevance of the resource to a search query that includes the name context of the cluster; receiving, for the resource in the cluster, a resource ranking score for the resource in the cluster, the resource ranking score being (i) at least partly based on a cluster relation score, and (ii) indicative of a ranking of the resource in the cluster relative to rankings of other resources in the cluster; wherein the cluster relation score is indicative of an authority of the resource relative to authorities of the other resources in the cluster; generating a cluster rank score for the cluster, the cluster rank score at least partly based on the search scores for the resources and the resource ranking scores for the resources; and ranking the clusters according to their cluster rank score.

20120054139

12870703

1. A method for determining an optimal conditional operational schedule for a set of power generators, comprising the steps of: constructing states and transitions of a factored Markov decision process (fMDP) from a target electrical demand and generator variables; constructing a cost function for the fMDP based on the electrical demand, the generator variables, and a risk coefficient; and solving the fMDP to obtain the optimal conditional operational schedule, wherein the steps are performed in a processor.

10113153

15591816

1. A recombinant polynucleotide sequence encoding a recombinant cytochrome P450-BM3 variant, wherein said sequence comprises SEQ ID NO: 3, and further wherein said recombinant cytochromie P450-BM3 variant oxidizes at least three organic substrates.

20080234947

12099745

1. A scientist-centric interface system for conducting research using a laboratory instrument with an informatics search tool that utilizes a search algorithm to identify biomolecules, the search algorithm having a set of predefined algorithm control parameters used to control how the search algorithm operates, comprising: a user interface that prompts a user to supply scientist-centric information expressed utilizing terminology of a scientific domain selected from the domains of biology, analytical chemistry or any combination thereof; a translation system receptive of said scientist-centric information and operative to generate control parameters selected from said set of predefined algorithm control parameters and said translation system having a search algorithm interface whereby said generated control parameters are supplied to said search algorithm to control how the algorithm operates; wherein said translation system includes: a translation file that includes a set of hierarchically organized rules that map onto userselectable choices expressed in the terminology of the scientific domain for mediating user selection; a parameters template file that includes a set of rules that map onto the algorithm control parameters; and a workflow engine that extracts user selection information mediated by said translation file and populates the parameters template file based on the user selection information extracted.

8135608

11970776

1. A computer-implemented method for conducting a marketing campaign comprises: receiving by one or more computers scores associated with sending offers to proposed contacts belonging to a pool of customers; randomly assigning customers in the pool of customers into predetermined groups of customers; and optimizing by the one or more computers an overall campaign score corresponding to a sum of the received scores, with optimizing generating optimal assignments of offers to customers that satisfy for-each-customer (FEC) constraints and cross-customer (CC) constraints, the FEC constraints controlling communication to an individual customer and the CC constraints representing resources shared among the pool of customers, the optimal assignments of offers for inclusion in the marketing campaign; by: determining a first assignment of offers for a first group of customers that maximizes a sum of scores for the first group and complies with the FEC constraints and the CC constraints; and determining by the one or more computers subsequent assignments of offers for the remaining groups using information associated with determining the first assignment, the subsequent assignments maximizing the sums of scores for the remaining groups and complying with the FEC constraints and the cross-customer constraints, the optimal assignments including the first assignments and the subsequent assignments.

20090030829

11880980

1. A method of communications-network shopping by buyers of products and services for purchasing such from sellers, wherein buyers request an automatic reverse auctioneer or auction controller (RAC) to initiate a reverse auction in real time amongst willing sellers and to solicit from automated seller engines (SAEJ) of the sellers their automatic real-time iterative bidding price quotations for such products and services to be returned automatically over the network back to the controller without any manual intervention and under the iterative processing guidance of the controller to assure a best bid price quotation for the buyer; the method comprising, providing a choice of a plurality of options for automated seller engine architecture implementations depending upon the particular application involved, and selected from the group consisting of a parallel processing architecture, a pipeline architecture, a hub and spoke architecture and a hybrid combination of all the above; implementing price managing that is responsible for receiving requests from the controller (RAC) for one or more items that the buyer expresses interest in buying; in the light of received market data and historical prices, configuring the seller engine itself to enter the business objectives of that seller in specific terms of targets or goals that the seller enters; and, based on the type and the values of these goals, automatically optimizing the price at the seller engine for realizing the business objectives of the seller.

20110241930

12753955

1. A method for using image grids in detection of discrete objects, comprising: using a sensor to identify detections in a search grid, wherein one or more of the detections are false alarms and one or more of the detections are objects of interest; creating an image grid of the detections; and analyzing the image grid to identify a pattern of detections.

20130332085

13778416

1. A method of calculating a single, fused sensor glucose value based on respective glucose measurement signals of a plurality of redundant sensing electrodes, comprising: performing respective electrochemical impedance spectroscopy (EIS) procedures for each of the plurality of redundant sensing electrodes to obtain values of at least one impedance-based parameter for each said sensing electrode; measuring the electrode current (Isig) for each of the plurality of redundant sensing electrodes; independently calibrating each of the measured Isigs to obtain respective calibrated sensor glucose values; performing a bound check and a noise check on said measured Isig and said values of the at least one impedance-based parameter and assigning a bound-check reliability index and a noise-check reliability index to each said sensing electrode; performing signal-dip analysis based on one or more of said at least one impedance-based parameter and assigning a dip reliability index to each said sensing electrode; performing sensitivity-loss analysis based on one or more of said at least one impedance-based parameter and assigning a sensitivity-loss index to each said sensing electrode; for each of the plurality of electrodes, calculating a total reliability index based on said electrode's bound-check reliability index, noise-check reliability index, dip reliability index, and sensitivity-loss reliability index; for each of the plurality of electrodes, calculating a weight based on said electrode's total reliability index; and calculating said single, fused sensor glucose value based on the respective weights and calibrated sensor glucose values of each of the plurality of redundant sensing electrodes.

8645119

12056083

1. A computer-implemented method comprising: determining, with a data processing apparatus having one or more processors, model parameters for a plurality of feature functions for a linear machine learning model; ranking, with the data processing apparatus, the plurality of feature functions according to a quality criterion; selecting, with the data processing apparatus, a group of feature functions from the plurality of feature functions based on the ranking, where selecting the group of feature functions further comprises: for each source sentence in a plurality of source sentences, calculating a source sentence error surface as a function of number of updates for ranked feature functions, merging all source sentence error surfaces into an aggregate error surface, and identifying an optimal number of updates for ranked feature functions that minimizes the aggregate error surface; and updating, with the data processing apparatus, the model parameters for the feature functions in the selected group.

5559902

08251676

1. A method of generating an enhanced image based on a scanned image, the scanned image comprising image pixel signals having been generated with use of an image scanner, an image pixel signal having a binary value, the method comprising the automated steps of: filtering one or more image pixel signals of the scanned image to form a filter signal, the filter signal corresponding to a given image pixel signal; comparing a value of the filter signal with a value of the given image pixel signal; determining whether complementing the value of the given image pixel signal reduces the sharpness of a wedge-like shape in the image; and complementing the binary value of the given image pixel signal when (i) doing so does not reduce the sharpness of the wedge-like shape in the image and (ii) said filter signal value and given image pixel signal value are not equal, to generate an image pixel signal of the enhanced image.

20140229410

14342205

1. A method for configuring a detection device for detecting a situation from a set of situations wherein a physical system observed by at least one sensor is liable to be, comprising the following steps: reception of a sequence of observation data for the physical system, referred to as a learning sequence, supplied by the sensor and corresponding to a given situation of the physical system, determination, from the learning sequence, of parameters of a hidden-state Markov statistical model recorded in storage means of the detection device and relating to the given situation, by prior initialisation of these parameters, and then updating of these initialised parameters, wherein the prior initialisation comprises the following steps: the statistical model in question comprising a given number of hidden states, determination of a plurality of probability distributions from the learning sequence, by dividing the sequence into sub-sequences and allocating to each sub-sequence a probability distribution that models it statistically, the number of given probability distributions being greater than the number of hidden states of the statistical model in question, distribution of the probability distributions determined between the various hidden states of the statistical model in question, determination, for each hidden state of the statistical model in question and from the probability distributions allocated to this hidden state, of a single probability distribution representing this hidden state, and initialisation of the parameters of the statistical model in question from the determined representative probability distributions, characterised in that, the statistical model in question further comprising impossible transition constraints between certain hidden states, the distribution of the probability distributions determined between the various hidden states of the statistical model in question is done by global optimisation of a function of adaptation of these probability distributions to the various hidden states and to the impossible transition constraints, and the method further comprises a step of configuring the detection device so that the statistical model in question includes the parameters determined by said prior initialisation and then said updating.

20080114472

11810493

1. An autotuning method using an integral of a relay feedback response, the method comprising the steps of: integrating a process data; and removing any effects of harmonics after integrating the process data and computing an ultimate gain.

20130110590

13282572

1. Apparatus for ranking employees, the apparatus comprising: a receiver configured to receive information relating to the performance, by an employee, of a plurality of tasks, wherein each of the plurality of tasks was completed during a predetermined time period; a processor configured to: compute, based at least in part on the received data: a median cycle time score, said median cycle time score being based on a number of times that the employee met a median cycle time assigned to one or more of the plurality of tasks; an accuracy score, said accuracy score being based on a number of times that an error was recorded for one or more of the plurality of tasks; an escalation percentage score, said escalation score being based on a number of times that a complaint was recorded for one or more of the plurality of tasks; a volume score, said volume score being based on a sum of the plurality of tasks; and a client target date score, said client target date score being based on a number of tasks included in the plurality of tasks that met a client target date assigned to each of the number of tasks; wherein each of the medium cycle time score, accuracy score, escalation percentage score, volume score and client target date score is normalized to reduce bias attributable to the difficulty level for one or more of the plurality of tasks; and rank, using percentile ranking, each of the median cycle time score, accuracy score, escalation percentage score, volume score and client target date score against a plurality of median cycle time scores, accuracy scores, escalation percentage scores, volume scores and client target date scores, respectively, that were computed for a group of employees using data generated during the predetermined time period; wherein: the employee and each of the employees included in the group of employees are employed in the same line of business; and the employee and each of the employees included in the group of employees began employment within a predetermined time span.

9646264

14631065

1. A method for forecasting based on time-series decomposition, the method comprising: decomposing, using a processor and a memory, an input time-series into a set of constituent frequencies; selecting, for each constituent frequency in a subset of the set of constituent frequencies, a corresponding forecasting model in a subset from a set of forecasting models; selecting, from a set of component forecasts produced by the subset of forecasting models, a subset of component forecasts, wherein a component forecast in the subset of component forecasts is selected according to a component forecast selection condition; and outputting the subset of component forecasts to revise the forecast selection condition, wherein a revised forecast selection condition increases a relevance of a future subset of component forecasts.

9704130

12605635

1. A method for recommending points of integration between an enterprise industry model and a legacy model, the method comprising: receiving a user entered first search term for the enterprise industry model; electronically searching a first domain of instance data of the enterprise industry model for first nodes matching the first search term; generating and displaying a first graphical map that shows one or more first nodes that match the first search term and edges which interconnect the one or more first nodes with other nodes in accordance with relationships defined in the first domain; receiving a user entered second search term for the legacy model; electronically searching a second domain of instance data of the legacy model for second nodes matching the second search term; generating and displaying a second graphical map that shows one or more of the second nodes that match the second search term and edges which interconnect the one or more second nodes with other nodes in accordance with relationships defined in the second domain; calculating a probability score representing a probability that a first one of the matching second nodes is capable of implementing the function of a first one of the matching first nodes; and graphically indicating a connection between and the probability score for the first one of the matching first nodes and the first one of the matching second nodes.

9323070

14124002

1. Method of manufacturing a master grating for diffracting light of a particular wavelength impinging the master grating with a particular angle of incidence, the master grating comprising an array of grooves running in parallel along a planar face of the master grating, the grooves distanced by a grating period; the grooves comprising a triangular profile with flat interfaces, wherein one of the interfaces forms a blaze angle with respect to the planar face; wherein the method comprises providing a wafer comprising a substantially mono-crystalline material, the material having first, second, and third crystal planes, wherein the first and second crystal planes intersect each other at an intersection angle; the wafer being cut along a wafer surface having a cut angle equal to the blaze angle with respect to the first crystal plane; applying an etching resistant material to parts of the wafer surface in a pattern of parallel strips, the centers of the strips distanced by the grating period, wherein exposed parts of the wafer surface are formed between the strips; applying an anisotropic etching process to the wafer surface that etches faster in a direction normal to the third crystal plane than in a direction normal to the first and second crystals planes to form the grooves at the exposed parts wherein the flat interfaces of the grooves are formed along the first and second crystal planes; wherein the method further comprises calculating a corrugation amplitude of the grooves with respect to the wafer surface as a function of a desired diffraction efficiency of the light for the given grating period and blaze angle; and in the applying of the etching resistant material, controlling a line width of the strips such that the grooves are formed with the flat interfaces extending from exposed edges of neighboring strips into the wafer surface and intersecting each other with the intersection angle at a depth equal to the calculated corrugation amplitude.

7497688

10245715

1. A method for creating a training program that is to be administered to a team of employees before the team of employees performs a service for a customer at the customer's workplace and that is intended to provide the team of employees with training that is useful for preparing the team of employees to perform the service for, the customer at the customer's workplace, the method comprising: determining high-level goals specifically for the training program, the specific high-level goals representing goals to be accomplished by the team of employees during the training program in order to acquire experience to perform the service for the customer in a compressed time period that is shorter than a time period in which the experience is acquired without using the training program; determining roles for the team of employees specifically for the training program, wherein: each role is to be performed by a member of the team of employees during the training program in order to accomplish one or more of the high-level goals for the training program, and each role corresponds to a position to be filled while performing the service for the customer; for each role, determining performance objectives specifically for the training program to be completed by the role during the training program in order to accomplish one or more corresponding high-level goals; based on the high-level goals determined specifically for the training program and the roles for the team of employees determined specifically for the training program, creating a learning environment specifically for the training program and within which at least a portion of the training program will be conducted, the learning environment modeling the workplace of the customer where the team of employees will perform the service for the customer and providing a realistic environment within which to acquire the experience to perform the service for the customer by completing the performance objectives specifically determined for the training program, including: assembling and connecting a collection of computer systems, including one or more servers and one or more workstations, in a manner that resembles computer systems of the customer that the team of employees is likely to encounter while performing the service for the customer at the customer's workplace and such that performance and operation of the assembled and connected collection of computer systems can be monitored, and arranging a layout of a physical office space in a manner that resembles physical working conditions that the team of employees is likely to encounter at the customer's workplace while performing the service for the customer; based on the roles for the team of employees specifically determined for the training program, developing an instructional curriculum for the training program by: creating a new performance objective matrix specifically for the training program, the performance objective matrix identifying the specifically determined roles for the team of employees during the training program, the specifically determined performance objectives for each role during the training program, and a time frame for accomplishing the specifically determined performance objectives during the training program, and using the performance objective matrix to create a learning event schedule that specifies one or more instructional activities to be performed in the learning environment specifically created for the training program by each role in order to complete the specifically determined performance objectives during the training program; and creating an evaluation plan specifically for the training program to gauge the progress of the roles towards completing the instructional activities during the training program, wherein the evaluation plan provides a measure that the roles have completed the instructional activities during the training program and have acquired the experience to perform the service for the customer in the compressed time period as a result of participating in the training program.

9122987

13743996

1. A method for predicting future travel times of a target vehicle traveling on a route from a starting point to a destination, comprising the steps of: acquiring real-time probe data by probe vehicles traveling on a set of one or more alternative links, which are substantially parallel to the route traveled by the target vehicle, from the starting point to the destination; estimating a current travel time for each alternative link using the real-time probe data; and predicting the future travel time of the target vehicle traveling on the route based on the current travel times for the set of one or more alternative links using a set of regression functions, wherein each regression function is f L ⁢ ⁢ 1 ⁢ L ⁢ ⁢ 2 ⁡ ( t , τ L ⁢ ⁢ 2 , Δ ⁢ ⁢ t ) = ∑ i = 1 N ⁢ w i ⁢ G ⁡ ( t , τ L ⁢ ⁢ 2 , Δ ⁢ ⁢ t ; θ i ) where a L1 is a current link traveled by the target vehicle at a current time t, τ L2 is a current travel time estimate of a particular alternative link L2, Δt is a future time for the prediction, with respect to the current time, w i is a weight, G is a real valued function with corresponding parameters θ i , wherein the steps are performed in a processor.

8942251

13473956

1. A wireless communication system, comprising: a first network device having a cellular identification, cell ID, the first network device forwarding a first uplink data stream having first uplink data associated with a user device; and a base station in communication with the first network device, the base station having the same cell ID as the cell ID of the first network device, the base station including: at least one receiver, the at least one receiver receiving the first uplink data stream from the first network device; and a processor, the processor configured to: determine channel performance data based at least in part on a portion of first uplink data stream; determine whether the channel performance data meets a predetermined performance level; discard the portion of the first uplink data stream when the channel performance data does not meet the predetermined performance level; and tag the portion of the first uplink data stream for additional processing when the channel performance data meets the predetermined performance level.

20060095883

10977386

1. A method comprising steps of: (a) performing a physical design validation of an integrated circuit design to verify compliance with a set of design rules; (b) generating a results database of design rule violations detected by the physical design validation; (c) identifying locations in the integrated circuit design from the results database for making design corrections according to a post-processing rule deck so that the locations of the design corrections comply with the set of design rules; and (d) implementing the design corrections in the integrated circuit design.

9471712

11927458

1. A method of identifying strings in an e-mail message, the method comprising: receiving an e-mail message; and executing instructions stored in memory, wherein execution of the instructions by a processor: identifies a text string in the e-mail message; determines that the identified text string in the e-mail message is not a safe string, wherein safe strings are predetermined strings stored in a database of acceptable terms and identified as legitimately present in e-mail messages; associates the text string with a guarded term from a database of guarded terms stored in memory, the guarded term being a string of special interest to a user; evaluates a cost of the association of the identified text string that dictates a probability that the identified text string is a mutation of the associated guarded term, wherein the evaluation compares similarities and differences between the identified text string and the guarded term, and wherein the evaluation assigns different penalties for the cost based on whether the mutation includes regular characters or special characters; matches the identified text string with the guarded term when the cost of association of the identified text string meets a predetermined threshold; and characterizes the e-mail message based on the matching between the identified text string and the guarded term.

20100235011

12404019

1. A computer readable storage medium on which is embedded one or more computer programs, said one or more computer programs implementing a method of determining optimal settings for a plurality of resource actuators configured to vary an environment condition at a location of at least one entity, said one or more computer programs comprising a set of instructions for: developing a first model that relates first dependant variables with second dependent variables; developing a second model that relates the first dependant variables with third dependent variables; formulating a constraint optimization problem having an objective function and at least one constraint using the first model and the second model, wherein the objective function computes at least a proportional quantity of a total power consumption level of the plurality of resource actuators and wherein the at least one constraint comprises a setpoint environmental condition at a location of the at least entity; and solving the constraint optimization problem, wherein the solution provides optimal values for the plurality of resource actuator settings.

8706298

12725740

1. A temporal robot controller, comprising: a sensor module for receiving data corresponding to a location of at least one object in a robot environment, the robot environment corresponding to an occupancy grid with which the location of the at least one object is associated; a storage module operatively coupled to said sensor module, said storage module configured to store at least one of data processed from data received by the sensor module or a priori data; a temporal control module operatively coupled to said storage module, the temporal control module configured to temporally estimate a plurality of alternative future locations in the occupancy grid of the at least one object based on data retrieved from the storage module; and a temporal simulation module operatively coupled to said storage module and said temporal control module, the temporal simulation module configured to use the data stored by the storage module and the temporally estimated alternative future locations in the occupancy grid to temporally simulate multiple robot control hypotheses for future robot state planning, wherein iterating of the temporal simulation of the multiple robot control hypotheses by the temporal simulation module is performed asynchronously with respect to iterating of the temporal estimation of alternative future locations in the occupancy grid of the at least one object by the temporal control module and wherein the temporal simulation module is configured to predict actions of the at least one object based on predicted reactions of the at least one obiect to the state of the robot.

20020166105

10040948

1. A method of routing a net within a particular region of an integrated circuit (“IC”) layout, the net having a set of pins, the method comprising: a) partitioning the particular IC region into a plurality of sub-regions, wherein the sub-regions have the same shape; and b) identifying a route that connects a set of sub-regions containing the pins of the net, wherein the route has a route edge that is at least partially diagonal.

4070243

05718807

1. A method for detecting, identifying and enumerating a subpopulation of leukocytes in a mixture of morphologically indistinguishable leukocytes having different membrane characteristics, which method comprises bringing said mixture into close contact with a previously selected strain of bacteria having an affinity for binding only to the cells of said subpopulation by a mechanism not involving the binding sites of any immunoglobulins on the surface of said leukocytes, and observing the presence of said bacteria bound to said subpopulation as a morphologically distinct marker for identification and enumeration of said subpopulation.

20100128041

12596786

1. A method for generating a constrained Delaunay triangulation for a planar domain with boundaries and internal features, comprising: approximating the boundaries and internal features of the domain with polylines; constructing unconstrained Delaunay triangulation for the domain; modifying the unconstrained Delaunay triangulation to conform triangle sides to the polylines; correcting the modified constrained triangulation to make it a constrained Delaunay triangulation.

20030118121

10339554

1. A method for measuring imperfections in a digital quadrature modulator operation in which an input signal of the modulator comprises quadrature-phase I and Q channels, whereby during a normal operation of the modulator a local oscillator carrier wave leak, an imbalance in I and Q channel amplitudes, a quadrature error between the I and Q channels and an amplitude error are determined from an output signal of the modulator, characterized in that the method comprises the steps in which from an amplitude of the output signal are taken, at a rate based on a symbol clock of the modulator, numerous momentary samples; a direction angle of a transmission signal corresponding to the samples is divided, on the basis of data bits to be transmitted or modulator input signals, into different direction angle sectors; and from amplitude sample deviations between the different direction angle sectors or from a nominal value are calculated the magnitudes of the distortions in the modulator operation.

20130179453

13346730

1. A graphical user interface comprising: a means of visually representing the weighting of database search criteria, a means of user manipulation of search criteria weighting, and a means of creating data searches across multiple data bases.

7752100

10644422

1. A method of performing financial processing in one or more computers, comprising: (a) selecting, in the one or more computers, accounts, forecast amounts, and attrition and propensity rates from a database through parallel processing of a selector function, wherein the selector function uses selection criteria specified by rules to select the accounts, forecast amounts, and attrition and propensity rates from the database, the selector function dynamically generates Structured Query Language (SQL) statements using the selection criteria, the selection criteria are grouped in order to combine them in the dynamically generated SQL statements, and the grouped selection criteria are processed independently and in parallel to yield output tables comprising the accounts, forecast amounts, and attrition and propensity rates selected from the database; (b) performing, in the one or more computers, one or more Net Present Value (NPV) and Future Value (FV) calculations on the selected accounts using the selected forecast amounts and attrition and propensity rates, wherein results from the NPV and FV calculations are integrated to provide a Life-Time Value (LTV) of one or more customers for presentation to a user; and (c) providing, by the one or more computers, the LTV to the user.

20060079979

11083825

1. A method of analyzing a manufacturing system, the system including a plurality of manufacturing resources, a set of orders being currently appointed for processing by the manufacturing system, each order of the set of orders requiring performance of at least one task, each task to be performed by at least a respective one of the manufacturing resources, the method comprising: determining stochastic parameters for each task of said plurality of tasks; and calculating a stochastic waiting time for at least one selected task of said plurality of tasks, said calculating based at least in part on said stochastic parameters of said tasks.

20110130886

13023392

1. A computer system for use with a building management system in a building, comprising: a processing circuit configured to use historical data received from the building management system to automatically select a set of variables estimated to be significant to energy usage in the building; wherein the processing circuit is further configured to apply a regression analysis to the selected set of variables to generate a baseline model for predicting energy usage in the building.

20090210364

12033896

1. A method of creating an input event feature vector for use as input to a standard learning algorithm, said method comprising the steps of: defining the characteristics of said input event feature vector; gathering a plurality of input events; populating individual vector elements of said input event feature vector based on a subset of said plurality of input events; and constructing said input event feature vector from said individual vector elements.

8832013

13294369

1. An apparatus comprising: an analytic network process (ANP) storage memory that stores an ANP weighted supermatrix representing an ANP model populated with data, the ANP model having feedback connections in place among nodes within the ANP model; and a processor in communication with the ANP storage memory, the processor being configured to facilitate selecting one or more metrics to use to determine influence of criteria within the ANP model; determining a combined influence score using the selected one or more metrics, the combined influence score being a single score for each of the criteria throughout the entire ANP weighted supermatrix representing the ANP model that has feedback connections; and determining, based on the combined influence score for each of the criteria, which of the criteria in the ANP model is most influential among the criteria in the ANP model, for the one or more metric which is selected to use to determine the influence of the nodes in the ANP model.

20120323518

13161262

1. A method for ranking tests of interest, the method comprising: determining a set of failure modes of interest; determining a set of tests of interest; computing a differentiation factor for each of the tests of interest; and ranking each of the tests of interest based on respective differentiation factors.

8831329

14059151

1. A computer-implemented method for extracting card information, comprising: receiving, by one or more computing devices, an image of a card; identifying, by the one or more computing devices, a first area of the image, the first area being selected as a potential location of one or more digits on the image; performing, by the one or more computing devices, a classification algorithm on data encompassed by the first area; identifying, by the one or more computing devices, one or more lines of potential digits on the image based on the results of the application of the classification; determining, by the one or more computing devices, one or more card models associated with a user, each of the one or more card models comprising digit distribution patterns of data displayed on an image associated with the particular card model; comparing, by the one or more computing devices, the image to the one or more card models associated with the user to identify a particular one of the card models corresponding to the image; performing, by the one or more computing devices, an optical character recognition algorithm on areas of the card that are anticipated by the one or more computing devices as comprising digits based on the identified particular one of the card models and the identified lines; determining, by the one or more computing devices, a confidence level of one or more results of the applications of the optical character recognition algorithm to the image; and verifying, by the one or more computing devices, a particular result based at least in part on a determination that the confidence level is the highest of the determined confidence levels.

5467407

08216752

1. A method for recognizing cursive handwritten words from stroke data, said method comprising the steps of: accepting digital information representing a sequence of points including a beginning point and an end point; selecting as a candidate word the sequence of points bounded by said beginning point and said ending point; replacing said candidate word sequence with a first plurality of metastrokes, said first plurality of metastrokes representing said candidate word sequence; compiling a list of possible matching word metastrokes using a dictionary of whole word metastrokes and said first plurality of metastrokes; comparing a first possible matching word metastrokes from said list of possible matching word metastrokes with said first plurality of metastrokes; computing a first word metric based on said comparison; and outputting a first possible matching word if said first word metric exceeds a predetermined threshold, said first possible matching word representing said first matching word metastrokes.

8402148

11965141

1. A system to facilitate communications between parties comprising at least one of a contactor and a contactee, the system comprising: a user interface that receives input specifying N parameters, the N parameters comprising a cost to the contactee of deferring a communication between the parties until a predetermined time, the cost is specified for at least one contactor based on identity of the at least one contactor and a comparison of a current state of the contactee and a future state of the contactee at the predetermined time, the current state comprising at least one first communication modality currently available to the contactee and the future state comprising at least one second communication modality projected to be available to the contactee at the predetermined time; a data store that receives the N parameters from the user interface, wherein: N is an integer, the N parameters relate to at least one of a communications preference, context, or policy, the N parameters are employed to guide decisions that facilitate communications between the parties, and at least one of the N parameters relates to the cost to the contactee of deferring the communication; and at least one computer processor that facilitates communications between the parties based upon a negotiation of the N parameters, wherein the negotiation comprises assessing the cost to the contactee of deferring the communication and a cost to the contactor of deferring the communication until the predetermined time.

10037758

15120539

1. An intent understanding device, comprising: a voice recognizer that recognizes one speech spoken in a natural language by a user, to thereby generate plural voice recognition results of highly ranked recognition scores; a morphological analyzer that converts the respective voice recognition results into morpheme strings; an intent understanding processor that estimates an intent about the speech by the user on the basis of each of the morpheme strings, to thereby output from each one of the morpheme strings, one or more candidates of intent understanding result and scores indicative of degrees of likelihood of the candidates and generate the candidates of intent understanding result in descending order of likelihoods of the plural voice recognition results; a weight calculator that calculates respective weights for the candidates of intent understanding result using setting information previously set by a user of a control target apparatus that operates based on the intent understanding result selected by the intent understanding corrector; and an intent understanding corrector that corrects the scores of the candidates of intent understanding result, using the weights, to thereby calculate their final scores, and then selects the candidate of intent understanding result with the final score that satisfies a preset condition first, as the intent understanding result, wherein the weight calculator has a table in which constrained conditions and the weights to be used when the respective constrained conditions are satisfied, are defined, and determines whether or not the constrained condition is satisfied, based on the setting information previously set by the user of the control target apparatus, to thereby select each of the weights.

8682617

13187638

1. An apparatus, comprising: at least one processor; and memory storing computer-readable instructions that, when executed by the at least one processor, cause the apparatus to: forecast one or more input values corresponding to one or more input variables of a modeling function; calculate one or more results of the modeling function using the one or more forecasted input values; receive actual performance data corresponding to the modeling function; calculate one or more holdout values for the modeling function using the actual performance data; and plot a graph that includes a plot of the one or more results of the modeling function, a plot of the actual performance data, and a plot of the one or more holdout values for the modeling function.

20180276556

15466342

1. A method for solving an optimization task using a system including multiple computing resources, the method comprising: receiving input data comprising (i) data specifying system parameters of the optimization task to be solved, and (ii) data specifying task objectives for solving the optimization task, comprising one or more local task objectives and one or more global task objectives; processing, by a local optimization engine, the received input data to obtain one or more initial solutions to the optimization task based on the local task objectives, comprising: transmitting, using a router, from the local optimization engine and to a first quantum computing resource, (i) the received data specifying the optimization task to be solved, and (ii) data representing one or more of the local task objectives, the router determining which computations to outsource to the first quantum computing resource; and receiving, from the first quantum computing resource and at the local optimization engine, data representing an initial solution to the optimization task; and processing, by a global optimization engine, the generated one or more initial solutions using a second quantum computing resource to generate a global solution to the optimization task based on the global task objectives, comprising: transmitting, from the global optimization engine and to the second quantum computing resource, (i) data representing the one or more obtained initial solutions to the optimization task, and (ii) the received data specifying the optimization task to be solved, and (iii) data representing the one or more global task objectives; and receiving, from the second quantum computing resource and at the global optimization engine, data representing the global solution to the optimization task; comparing, using a comparison module, the data representing the global solution to the one or more global task objectives to determine whether the global solution satisfies the one or more global task objectives; and adjusting values of the system parameters using the generated global solution to the optimization task.

9467918

14833791

1. A method comprising: calculating predicted load changes for a target radio access point for one or more potential user equipment (UE) handovers from each of a plurality of source radio access points for a radio access network based, at least in part, on application of current measurement data to a trained statistical model representing load changes for the radio access network; determining a set of one or more source radio access points that can be powered off to maximize energy savings or minimize energy consumption for the radio access network; initiating handover to the target radio access point for one or more UE connected to the one or more source radio access points belonging to the set; and powering off the one or more source radio access points belonging to the set.

5446826

08165875

1. A tuning apparatus which tunes a membership function to perform a fuzzy inference using a singleton as the conclusion-membership function, said tuning apparatus comprising: a) an error calculation means for receiving an output result of fuzzy inference and an output expectation value, and for redetermining an error between the output result of fuzzy inference and the output expectation value with respect to an input value of fuzzy inference; b) a distance calculation means for receiving a height signal, and for calculating: 1) a total sum of heights of conclusion membership functions in a defuzzy calculation in said fuzzy inference, 2) a ratio of a height of each conclusion-membership function to said total sum, and 3) a distance in proportion to said ratio; c) an updating means, connected to said error calculation means to receive the error and to said distance calculation means to receive the distance, for tuning and updating the conclusion-membership function by shifting a position of said conclusion-membership function according to said distance calculated by said distance calculation means and the error determined by said error calculation means; and d) a control means to which said error calculation means, said distance calculation means and said updating means are connected, for controlling said error calculation means, said distance calculation means and said updating means.

9754021

14638264

1. A method, in an information handling system comprising a processor and a memory, of identifying cluster relationships for searching across a plurality of corpora, the method comprising: identifying, by the system, a plurality of different cluster classifications for a corresponding plurality of corpora; classifying, by the system, entity information from documents stored in the plurality of corpora into the plurality of different cluster classifications by extracting named entities, terms, contexts, and concepts from the documents, and assigning the named entities, terms, contexts, and concepts to at least one of the plurality of different cluster classifications; applying semantic analysis, by the system, to identify entity relationships between entity information classified in the plurality of different cluster classifications by applying shallow and deep semantic analysis methods to identify entity relationships between the plurality of different cluster classifications; determining, by the system, one or more scores for each identified entity relationship; identifying, by the system, a cluster relationship between at least two cluster classifications based on the one or more scores for each identified entity relationship; and searching, by the information handling system, at least first and second corpora corresponding to the at least two cluster classifications having the identified cluster relationship.

9356849

13985110

1. A method comprising: providing a candidate category hierarchy, including candidate categories, and a mapping between reference pages and the candidate categories, including mapped reference pages; obtaining population usage data of each of the mapped reference pages; using the population usage data to determine a population traffic metric for each of the candidate categories; generating population categories from the candidate categories by using the population traffic metric of each of the candidate categories; and producing a population category hierarchy including the population categories.

20030156623

10348532

1. A scanning heat flow probe, comprising: an electric current conductor in a cantilever structure connecting a probe tip at one end and to a probe body at an opposite end; first and second voltage sense leads coupled to the electric conductor at first and second sense points; and two thermocouple junctions in the cantilever structure and operatively positioned proximate the first and second sense points.

8024681

12314615

1. A Hardware Description Language (HDL) processing method, to be implemented in a computer, for processing a HDL file which is written in HDL having a hierarchical structure including three or more hierarchical levels in a Computer-Aided Design (CAD) which supports hardware design, comprising: analyzing the hierarchical structure of the HDL and obtaining an analysis result; and processing the HDL one at a time for each hierarchical level based on the analysis result said processing including compiling a logic synthesis or a logic simulation with respect to the HDL, and wherein said analyzing analyzes the hierarchical structure of the HDL based on an entity table which stores position information of the HDL file for each entity, a high-level entity list table which stores a number allocated to the high-level entity list and a list of links to the entity table indicating a list of numbers allocated to the entity table, and an execution preparation list which is input with entities for which a number of low-level entities is 0 from the entity table.

7660735

10216510

1. A computerized method of identifying segments of consumers having similar behavior, the method comprising the steps of: (a) storing on a computer readable medium a plurality of micro-segments of consumer behavior; (b) retrieving said micro-segments by a computing device which decomposes said micro-segments under program control into age based components defining a segment maturation curve and time based components defining a segment exogenous curve and scaling parameters for each micro-segment; (c) said computing device calculating under program control a distance matrix between the micro-segments based on at least one of the generated decomposed curves; and (d) said computing device identifying micro-segments with similar consumer behavior under program control by clustering the micro-segments based on the distance between matrix calculations defining segment clusters in order to identify segments with similar consumer behavior and storing said segment clusters on computer readable medium.

9043253

13671535

1. An article of manufacture including a non-transitory computer readable storage medium to store instructions, which when executed by a computer, cause the computer to: receive a selection of a plurality of objects associated with a dataset, a key object and a specified number of nearest objects corresponding to the selected key object; sort the plurality of objects in a structured format, wherein the sorted plurality of objects is adjacent to the key object; define one or more windows including a subset of the sorted plurality of objects, wherein a cardinality of the subset corresponds to the specified number of nearest objects; and determine distances between the key object and the sorted plurality of objects based on the defined one or more windows to identify one or more nearest objects for data analysis, wherein identifying the one or more nearest objects to the key object, comprises: determining a first distance between the key object and a first object adjacent to the key object, and a second distance between the key object and a second object adjacent to the key object; based on the determined first distance and the determined second distance, identifying one of the first object and the second object adjacent to the key object as a first nearest object; determining a distance between the key object and a third object adjacent to the first nearest object; and based on the determined distance between the key object and the third object, identify one of the third object and remaining of the first object and the second object adjacent to the key object as a second nearest object.

8327299

12644789

1. A computer implemented method for merging a plurality of two-dimensional (2D) image-based design rules (IBDRs) stored in a design rule database into a subset of 2D IBDRs, comprising: using at least one computer system including at least one processor to perform a process, the process comprising: characterizing one or more desired rule geometries; sorting the plurality of two-dimensional image-based design rules into one or more groups according to the one or more desired rule geometries, wherein a group of the one or more groups comprises multiple two-dimensional image-based design rules, each of which includes one or more similar geometric features; and merging one or more groups, which includes the group, of the groups of two-dimensional image-based design rules into a single representative search pattern.

20090076791

11901780

1. A method for converting a computer game into a real-life simulation environment, the method comprising: receiving metadata produced by a computer application useable in conjunction with the computer game, the metadata generated in response to an input defining virtual features and a virtual layout of the computer game; matching the virtual features to simulation features of the real-life simulation environment; mapping the virtual layout onto the real-life simulation environment; and compiling the simulation features and the real-life simulation environment to produce data corresponding to a real-life simulation of the computer game.

20030004777

09814308

1. A controller for controlling a system, capable of presentation of a plurality of candidate propositions resulting in a response performance, in order to optimise an objective function of the system, the controller comprising: means for storing, according to candidate proposition, a representation of the response performance in actual use of respective propositions; means for assessing which candidate proposition is likely to result in the lowest expected regret after the next presentation on the basis of an understanding of the probability distribution of the response performance of all of the plurality of candidate propositions; where regret is a term used for the shortfall in response performance between always presenting a true best candidate proposition and using the candidate proposition actually presented.

20140172399

13883304

1. A method for non-destructively analyzing a weld in a sample comprising: (1) activating a pulsed, concentrated energy source to create ultrasonic waves in the sample; (2) receiving the ultrasound waves with an ultrasound receiver; (3) storing the signal generated by the ultrasound receiver on a computer readable medium; (4) moving the sample a first predetermined distance; repeating steps 1-4 until the sample has moved a second predetermined distance and a plurality of signals generated by the ultrasound receiver have been stored on the computer readable medium; and creating a model correlating the plurality of signals generated by the ultrasound receiver with empirical data for the sample.

8006236

11361597

1. A non-transitory computer readable medium storing a compiler, comprising: a transformer configured to: receive a high level primitive program for a programmable graphics pipeline, wherein the high level primitive program is expressed in a shader language and configured to receive a stream of vertices; and produce, by operation of one or more computer processors, another form of the high level primitive program that has been transformed for optimized execution by a target platform; and a micro-code generator configured to: convert the transformed high level primitive program into primitive program micro-code that will process the stream of vertices to produce an ordered stream of primitives when executed by the target platform; and determine, based on the target platform application programming interface (API), whether at least one per-vertex attribute needed to produce a primitive included in the ordered stream of primitives is to be provided by a first vertex of the primitive or a last vertex of the primitive, wherein, when the target platform API comprises a first target platform API, the first vertex provides the at least one per-vertex attribute, and, when the target platform API comprises a second target platform API, the last vertex provides the at least one per-vertex attribute, and wherein the transformed high level primitive program specifies which one of the first vertex or the last vertex is to provide the at least one per-vertex attribute needed to produce the primitive.

20050027492

10480445

1. A method of building a statistical shape model by automatically establishing correspondence between a set of two dimensional shapes or three dimensional shapes, the method comprising: a. determining a parameterisation of each shape, building a statistical shape model using the parameterisation, using an objective function to provide an output which indicates the quality of the statistical shape model, b. performing step a repeatedly for different parameterisations and comparing the quality of the resulting statistical shape models using output of the objective function to determine which parameterisation provides the statistical shape model having the best quality, wherein the output of the objective function is a measure of the quantity of information required to code the set of shapes using the statistical shape model.

20160147585

14687848

1. A method implemented by one or more processing devices, the method comprising: receiving a diagnostic level selection from a user; obtaining a data set for one or more data centers; identifying performance anomalies in the data set that have anomaly scores within the diagnostic level selection; determining predicates for the performance anomalies; generating a ranked list of the predicates based on the anomaly scores; and causing at least one of the predicates of the ranked list to be presented.

20160019108

14867972

1. A method comprising: determining a time range for a first instance of an incident in a computer system; collecting conditions of a plurality of components of the computer system; and deriving a set of alert conditions for the incident from the collected conditions; wherein: existence of the incident inhibits functionality of at least one component of the plurality of components; the collected conditions were present during the time range; and at least the collecting and deriving steps are performed by computer software running on computer hardware.

9589560

14135309

1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain a model for detecting a keyword in an audio sample and a detection threshold corresponding to the model, wherein a detection score greater than the detection threshold indicates that the keyword is present in the audio sample, and wherein the detection score is computed using the audio sample and the model; determine an estimated false rejection rate, wherein the false rejection rate comprises an estimate of a probability that a received audio sample comprises the keyword and that a detection score for the received audio sample is less than the detection threshold; obtain a transmit threshold for determining whether to transmit audio samples, wherein a detection score greater than the transmit threshold indicates that an audio sample for which the detection score is computed is to be transmitted to a server computing device, and wherein the transmit threshold is less than the detection threshold; transmit the model, the detection threshold, and the transmit threshold to a client computing device, wherein the client computing device receives a first audio sample, computes a first detection score using the first audio sample and the model, determines that the first detection score is greater than the transmit threshold, and transmits the first audio sample to the server computing device based at least on the first detection score being greater than the transmit threshold; obtain, from the client computing device, a plurality of audio samples, wherein each of the audio samples is associated with a detection score; determine a false rejection rate using at least a portion of the plurality of audio samples; determine, based at least in part on the determined false rejection rate, at least one of a second model or a second detection threshold; and transmit at least one of the second model or the second detection threshold to the client computing device.

20140373015

13917212

1. An apparatus for converting MLOAD and TPUMP operations, the apparatus comprising: a memory; a processor; and a module stored in memory, executable by the processor, and configured to: receive an input production parameter, wherein the input production parameter is associated with a load utility and defines a library of parameters, wherein the library of parameters defines a first syntax; convert the first syntax of the library of parameters to a second syntax, wherein the second syntax is associated with the load utility; validate the second syntax of the library of parameters; and write an output parameter to a memory location based on positive validation of the second syntax of the library of parameters.

9836572

14946043

1. A computer-implemented method of performing incremental common path pessimism analysis in integrated circuit design, the method comprising: performing, using a processor, common path pessimism removal (CPPR) analysis to provide timing credit for one or more paths that are subject to common path pessimism; identifying one or more post-CPPR critical paths following the CPPR analysis that provides the timing credit to the one or more paths that are subject to common path pessimism; setting flags for critical nodes of the one or more post-CPPR critical paths; performing a design fix to address the one or more post-CPPR critical paths; applying a set of rules based on the design fix and the flags to identify seed points among the critical nodes of the one or more post-CPPR critical paths, wherein the identifying the seed points is by identifying the critical nodes that meet one or more of the following criteria: the critical node is a sink of an edge added as a result of the performing the design fix, the critical node is a source or sink of an edge deleted as a result of the performing the design fix, the critical node is a sink of an edge with a changed arrival time based on the performing the design fix, and the critical node is a source of an edge with a changed required arrival time based on the performing the design fix; and invalidating and re-performing the CPPR analysis only for paths in a fan-out cone from the seed points, wherein the integrated circuit design resulting from the incremental common path pessimism analysis is implemented as a physical implementation of an integrated circuit.

8447423

12950364

1. A method for operating one or more bulk product blending and packaging plants in a manner that moves operations of a given plant, or a given collection of plants, toward an optimum for a performance metric during a designated time horizon comprising one or more time intervals under operating constraints and physical and/or economical limitations, each such plant comprising blending equipment, at least one storage tank, packaging equipment, one or more packaged product storage facilities and unloading and discharging facilities, wherein said method comprises the following steps: (I) a computer implemented step of receiving a data set comprising: (a) data identifying a time horizon comprising one or more time intervals; (b) data identifying blending equipment and one or more operational parameters thereof; (c) data identifying at least one storage tank and one or more operational parameters thereof; (d) data identifying packaging equipment and one or more operational parameters thereof; (e) data identifying packaged product storage facilities and one or more operational parameters thereof; (f) data identifying unloading and discharging facilities and one or more operational parameters thereof; (g) data relating to the interconnections between plant equipment; and (h) data relating to historical demand for each packaged product; (II) a computer implemented step of using the data set to populate model parameters of a mixed-integer non-linear mathematical optimization model constructed to mathematically describe the operations of the blending and packaging plant(s); wherein the model comprises model parameters, decision variables, constraints, and an objective function; wherein the decision variables represent quantitative decisions to be made in each interval regarding plant capacity as a function of one or more of the following: number of production equipment, number of workers, production shift structure, overtime, number of product changeovers and setup time required to complete a product changeover; wherein additional decision variables are quantitative decisions to be made in each interval regarding plant production and inventory; wherein the constraints comprise: (a) one or more terms limiting availability and capacity of the blending equipment; (b) one or more terms limiting availability and capacity of the at least one storage tank; (c) one or more terms limiting availability and capacity of the packaging equipment; (d) one or more terms limiting availability and capacity of the packaged product storage facilities; (e) one or more terms limiting availability and capacity of the unloading and discharging facilities; (f) one or more non-linear terms relating number of batches of each packaged product to product batch size; and (g) one or more non-linear terms relating the size of each batch of packaged products to quantity of safety stock required for the product; wherein the objective function is a performance metric: (III) a computer implemented step of running an algorithmic solver to obtain a solution to the mixed-integer non-linear mathematical optimization model; and (IV) operating the plant(s) substantially according to the solution obtained or according to an operating plan made based on the solution obtained.

7552065

09733299

1. A computer-readable medium having stored thereon computer-executable instructions for instantiating a forecasting tool for predicting future demand for quantifiable items in connection with a plurality of projects, the tool being instantiated on at least one computer in the form of a database having multiple tables, each of the multiple tables having information therein, wherein instantiating the forecasting tool comprises: receiving a query from a user to the tool, accessing the database having multiple tables, receiving a selection of at least one milestone to be employed with one of the projects, the at least one milestone originating from a milestone-type table, wherein the milestone is associated with a change of at least one milestone-related material and the milestone includes an amount of milestone-related material required for the project and a projected milestone start date and a projected milestone end date; determining an actual milestone date from the milestone-type table; calculating a material required date of milestone-related material based on the actual milestone date and the projected milestone start date and the projected milestone end date; determining a supplier for the material from a material table; obtaining a lead-time for supplying the material based on a suppliers table; calculating an order date based on the material required date and the lead-time; populating a requirements table according to the calculated order date, and outputting the requirements table and the order date to a display, and the multiple tables comprising: a project table having project information for each project, the project information including: a reference to at least one item to be employed in connection with the project, and an identification of a project-type of the project; a project-type table having project-type information for each project-type referenced by the project table, the project-type information comprising a list including each item to be employed in connection with the project-type, wherein the list is constructed based on: at least one telecommunications infrastructure requirement for the project-type; at least one previous project of a same project-type, and at least one new material requirement for the project-type based on at least one of the following: a new type of construction method, a new service, or a new regulation; an item table having item information for each item referenced by the project table, the item information including a reference to an algorithm to be employed to determine a quantity of the item for a particular project; an algorithm table having algorithm information for each algorithm referenced by the item table, the requirements table populated by the forecasting tool on a dynamic basis with information obtained from the multiple tables in response to a query for demand for items, the tool populating the requirements table by accepting the query, traversing the multiple tables of the database according to the query to accumulate data necessary to populate the requirements table, and populating the requirements table based on the accumulated data, wherein the requirements table is output to the display by the forecasting tool for viewing by personnel.

8554701

13051309

1. A computer-implemented method of classifying sentences as to sentiment, the method comprising executing instructions in a computer system to perform the operations of: acquiring training data comprising a plurality of sentences labeled as to sentiment; pre-processing the plurality of labeled sentences from the training data; generating a list of terms from the plurality of labeled sentences; determining sentiment scores for the terms in the list of terms utilizing a machine learning technique based on the plurality of labeled sentences; receiving a collection of sentences to be classified; pre-processing the collection of sentences; classifying each sentence from the collection of sentences as having a neutral sentiment or a non-neutral sentiment utilizing a first logistic regression classifier trained on the sentiment scores determined for the terms in the list of terms; and classifying each sentence having a non-neutral sentiment from the collection of sentences as having a positive sentiment or a negative sentiment by applying a second logistic regression classifier trained on the sentiment scores determined for the terms in the list of terms to determine a positive score for the sentence, applying a third logistic regression classifier trained on the sentiment scores determined for the terms in the list of terms to determine a negative score for the sentence, and combining the positive score and the negative score for the sentence.

9412176

14705866

1. A method of generating an edge-based feature descriptor for a digital image at a feature detection device, the method comprising: detecting, by the feature detection device, a plurality of edges within the digital image; selecting, by the feature detection device, an anchor point located along an edge of the plurality of edges; generating, by the feature detection device, an analysis grid associated with the anchor point, the analysis grid including a plurality of cells; calculating, by the feature detection device, an anchor point normal vector comprising a normal vector of the edge at the anchor point; calculating, by the feature detection device, one or more edge pixel normal vectors comprising normal vectors of the edge at one or more locations along the edge within the cells of the analysis grid; generating, by the feature detection device, a histogram of similarity for each of one or more cells of the analysis grid, each histogram of similarity being based on a similarity measure between each of the edge pixel normal vectors within a cell and the anchor point normal vector; and generating, by the feature detection device, a descriptor for the analysis grid based on the histograms of similarity.

20130227233

13408787

1. A system for integrated sub-block interleaving and rate matching, the system comprising: a buffer memory for storing sub-block data that has been encoded according to a channel encoding algorithm; a rate matching module for reading the sub-block data from the buffer memory using a sequence of addresses according to an interleaving algorithm, such that data is transferred from the buffer memory to the rate matching module in an order that emulates the order that the data would be produced by the interleaving algorithm.

9870419

13407712

1. A method for in-memory cache data profiling, comprising: executing an Extract Transfer Load (ETL) process in which data is first moved from a source database of a source application to a target database of a target application during which movement the data is extracted from the source database into a persistency comprising a staging area, an alignment area and a preload area, then transformed to a model that is common to both the source and target databases, and finally cleansed and loaded into the target database so as to initially populate a data warehouse; performing baseline data profiling on the extracted data in the persistency during ETL in order to produce baseline data profiling results; and, subsequent to the ETL, receiving in an enterprise service bus (ESB) updates to the source database and placing the updates in a cache memory on the ESB, determining whether multi-record profiling or only single record profiling has been selected for profiling cached updates, on condition that multi-record profiling is selected, performing data profiling on the updates in the cache on the ESB and determining current data profiling results for the cached updates and, comparing the current data profiling results for the cached updates to the baseline data profiling results, but otherwise performing single record profiling on the updates without comparing the current data profiling results for the cached updates to the baseline data profiling results, and triggering an action if a threshold disparity is detected based upon the current data profiling results.

7725408

11633190

1. A method for constructing learning data, comprising the steps of: (a) generating learning models by performing machine learning with respect to learning data; (b) attaching tags to a raw corpus automatically using the generated learning models to thereby generate learning data candidates; (c) calculating confidence scores of the generated learning data candidates, and selecting a learning data candidate by using the calculated confidence scores; and (d) allowing a user to correct an error in the selected learning data candidate through an interface and adding the error-corrected learning data candidate to the learning data, thereby adding new learning models incrementally.

20110264649

12989756

1. A system comprising: a knowledge management component to acquire, classify and disseminate information of a dataset; a human-computer interaction component to visualize multiple perspectives of the dataset and to model user interactions with the multiple perspectives; and an adaptivity component to modify one or more of the multiple perspectives of the dataset based on a user-interaction model.

20120022952

12893939

1. A computer-implemented method for combining probability of click models in an online advertising system, said method comprising: receiving, at a computer, at least one feature set slice; training, in a computer, a plurality of slice predictive models, the slice predictive models corresponding to at least a portion of the features in the at least one feature set slice; weighting, in a computer, at least two of the plurality of slice predictive models by overlaying a weighted distribution model over the plurality of slice predictive models; and calculating, in a computer, a combined predictive model based on the weighted distribution model and the at least two of the plurality of slice predictive models.

20110178972

13121713

1. A method for use with a storage system, comprising: in response to writes, creating snapshots of data using a snapshot algorithm; and selecting the snapshot algorithm from among a plurality of different snapshot algorithms according to one or more criteria.

20100049581

12544124

1. An apparatus for characterization of areas of consultant expertise of consultants, the apparatus comprising: means for obtaining information on how recently a consultant purchased products of a given category, and how often the consultant purchased the products; means for determining whether consultant advice given has been found by shoppers to be relevant and helpful in the past; means for determining a willingness and capability of each consultant to give advice, based on physical proximity, current workload and explicitly stated desire; and means for assigning a score to each consultant based on the information, willingness and capability.

9434919

14950712

1. An isolated, genetically modified Myceliophthora deficient in at least one protease native to said Myceliophthora , wherein said protease is capable of degrading Myceliophthora cellobiohydrolase enzymes, and comprises an amino acid sequence having at least 98% identity with the polypeptide sequence set forth in SEQ ID NO:12.

20020004697

09873969

1. A method for target correlation between target information in an air traffic control system, the method comprising: comparing selected components of a first target report associated with a first target to selected components of a second target report associated with a second target; producing a confidence level for each component comparison; and determining whether to declare the first target of the first report and the second target of the second target report similar based on the confidence level for each component compared.

20110306363

13216697

1. A method for optimizing a tracking area, comprising: obtaining, by an Operation, Administration and Maintenance entity, an optimization threshold; and performing a tracking area optimization according to the optimization threshold.

20110055596

12552279

1. An apparatus comprising: a central processing unit (CPU); and a graphics processing unit (GPU) communicatively coupled to the CPU; wherein a first thermal management system compares a metric representing a combined measure of power used by the CPU and power used by the GPU to a shared power budget, wherein a state of the CPU and a state of the GPU are regulated to maintain the metric within the shared power budget.

20040150407

10445876

1. A method of improving a defect detection efficiency of a test recipe used to evaluate electrode array panels, wherein the test recipe comprises pixel driving signals applied to the electrode array panels that generate pixel voltages, and thresholding parameters applied to the pixel voltages to determine if a pixel is defective, the method comprising: determining if a process abnormality occurred during a manufacturing process for the electrode array panel; and adjusting the thresholding parameters based on the existence of a process abnormality during the manufacturing process.

20060195409

11350048

1. A learning control apparatus for controlling a learning operation of an apparatus sensing a state of an environment and selecting a behavior based on the sensed content, comprising: predicting means for learning the behavior and a change in the state of the environment, and predicting a change in the state of the environment in response to a predetermined behavior; goal state setting means for setting a goal state in the behavior; planning means for planning a behavior sequence from a current state to the goal state set by the goal state setting means based on a prediction of the predicting means; and control means for controlling the behavior in the behavior sequence planned by the planning means and learning an input and output relationship in the behavior, wherein the predicting means calculates first information relating to an prediction accuracy based on learning, and supplies the first information to the goal state setting means, wherein the planning means calculates second information corresponding to an index that indicates whether the behavior based on the behavior sequence controlled by the control means comes close to the goal state, and supplies the second information to the goal state setting means, wherein the control means calculates third information relating to a progress of learning of the input and output relationship, and supplies the third information to the goal state setting means, and wherein the goal state setting means sets the goal state based on the first information, the second information, and the third information.

20060294577

11444017

1. A computer-implementable method comprising: receiving at least two designs for a rule-based system; and computing at least one functional discrepancy between said at least two designs utilizing decision diagrams.

5555201

08196337

1. An interactive system for hierarchical display of control and dataflow information, comprising: an ECAD system including a computer processor, means for storing design-related information, and graphical display means; means for a problem-solving user to enter a high-level design description on said ECAD system and to store said design description on said means for storing; means, on the ECAD system, for analyzing the high-level design description to identify modules of the design and to organize the modules in a hierarchical manner such that: each module at other than a highest level of abstraction is associated with ancestor modules at higher levels of abstraction; each module at other than a lowest level of abstraction is associated with progeny modules at lower levels of abstraction; means, on the ECAD system, for synthesizing one or more detailed electronic designs from the high-level design description; graphical display means, connected to said computer processor, for displaying graphical objects representing selected modules of the design; means for graphically indicating control and data flow between said graphical objects on said graphical display means, said graphical control and data flow indications representing control and data flow between the modules represented by the graphical objects; means for selecting a level of hierarchical abstraction for any displayed graphical object; and means for indicating that a displayed graphical object represents a module which has progeny modules associated therewith at a lower level of abstraction.

8621287

12939016

1. A computer implemented method of computing system monitoring comprising using a computing device with a processor and a memory for storing executable instructions that are executable by the processor to perform: detecting a system problem associated with a computing system; logging the system problem to a database; analyzing the system problem to determine a location of the system problem; integrating the database and a mapping of executable instructions attributable to the system problem; and providing a map of at least a portion of the computing system via a graphical user interface, wherein the map is selected from the group consisting of raster maps and vector maps, and the map indicates the location of the system problem within the computing system.

7653509

11897148

1. A system for generating a probability state model, the system comprising: a detector; and a computer operably connected to the detector, wherein the computer accesses one or more logic instructions for receiving raw data at the computer and generating a probability state model display of one or more parameters associated with the raw data, wherein the probability state model comprises one or more parameter profiles comprising a plurality of distribution points, and wherein each distribution point is mapped to a parameter, an event, an a state index, wherein the computer performs the steps of: a. storing one or more retrievable models in a memory portion in communication with the computer, wherein: i. each of the one or more retrievable models comprises at least two control definition points and two intermediate definition points associated with a measurable parameter and plotted against state index values comprising a progression index, and ii. each definition point further comprises a probability distribution curve; b. receiving raw data for at least one parameter, wherein the raw data comprises a plurality of observed event measurements for the at least one parameter; c. applying each of the plurality of observed event measurements to one of the one or more retrievable models; d. calculating a probability weight for each state based on the probability that each of the plurality of observed event measurements coincides with the probability distribution curve for each of the one or more control definition points and/or intermediate definition points; e. creating a state selection vector for each of the plurality of observed event measurements based on the calculated probability weights for the progression of state index values; f. stochastically selecting a specific state index value from the state selection vector calculated in step d) based on the probability weights wherein the specific state index value selected determines the definition point associated with that state index value for each of the one or more parameters; g. incrementing a frequency counter representing the frequency that each of the control definition points and intermediate definition points are stochastically selected in step f) for each state index in the progression; h. displaying a parameter profile on a graphical user interface at a display terminal in communication with the computer, wherein the parameter profile comprises definition points for one or more events that are plotted against the progression of state index values, such that each state index value in a full progression of state index values is associated with a definition point; i. analyzing the frequencies of the control definition points and intermediate definition points throughout the progression for uniformity; j. moving the control definition points left and right and the intermediate definition points left, right up, and down along the parameter profile to produce uniform frequencies across the progression; and k. displaying said parameter profile on said graphical user interface in communication with the computer, wherein the plurality of observed event measurements for each of the one or more parameters are a function of state index.

7536338

09955264

1. A computer implemented method for determining an optimal bid for an item in a market, said method comprising: a) selecting characteristics of said market; b) selecting user-specific auction evaluation criterion; c) selecting a bidding model, wherein the bidding model specifies bidding behavior as a function of information held by a bidder and the characteristics of the market; d) estimating a structure of said market, wherein unobservable variables are expressed in terms of observable bids by inverting said bidding model; e) determining a bid function, wherein the bid function is determined based on the structure of said market and user inputs regarding item being bid and characteristics of rival bidders; and f) determining by a processor said optimal bid, which is a prediction of an amount a bidder should bid, wherein said optimal bid is calculated based upon the received evaluation criteria and said bid function.