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AIPD_evo_claim_one

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8185389

12335558

1. In a computing environment, a method comprising, employing at least one processor to perform steps comprising, receiving first data corresponding to a frame of audible input, receiving second data corresponding to a noise level, and determining a gain value for use in noise reduction based upon the noise level, including determining a high gain value to accomplish little or no noise suppression when the noise level is below a threshold low noise level.

8150183

12374415

1. A method for compression of an image on a computing system, comprising: performing a first minimum mean squared error (MMSE) predictive-transform (PT) operation on the image based on a first isotropic image correlation model and a first average value of a plurality of adjacent pixels within a first pixel block in the image to generate a subband estimate vector; wherein performing the first MMSE PT operation comprises: generating a transform matrix and a prediction matrix based on the first isotropic image correlation model; averaging a value for every pixel in the image to generate an average value; multiplying the transform matrix and the first average value of the plurality of adjacent pixels in the image within the first pixel block to generate a coefficient vector, wherein a size of the first pixel block is smaller than a size of the image; multiplying the prediction matrix and a prediction vector to generate a prediction coefficient vector, wherein the prediction vector is based on the average value; taking a difference between the coefficient vector and the prediction coefficient vector to generate a coefficient error vector; quantizing the coefficient error vector to generate a quantization coefficient error vector; adding the prediction coefficient vector to the quantization coefficient error vector to generate a coefficient estimated vector; and multiplying the coefficient estimated vector by the transform matrix to generate the subband estimate vector; performing a second MMSE PT operation on the image based on the subband estimate vector, a second isotropic image correlation model, and a second average value of a plurality of adjacent pixels within a second pixel block in the image to generate a compressed version of the image; and providing the compressed version of the image.

7979842

11935140

1. A method to model the structure of an item with meta-annotations, comprising: defining the structure of an item with a meta-model employing meta-data annotations, the meta-model at least including one meta-relationship and at least one meta-class, the at least one meta-relationship describing one or more relationships between meta-classes, the at least one meta-class being a class encapsulating data employed to represent another class, and the at least one meta-class is identified via a globally unique identifier; and reading the meta-data annotations from computer readable media to determine the structure of an item.

7860702

10666209

1. A method for simulating an electric power network having a plurality of transmission-level buses and connected electrical elements and a plurality of distribution-level buses and connected electrical elements, the method comprising: determining a model of the transmission-level buses and connected electrical elements, the model of the transmission-level buses including a plurality of transmission lines and a plurality of transmission electrical elements; determining a model of the distribution-level buses and connected electrical elements, the model of the distribution-level buses including a plurality of distribution lines and a plurality of distribution electrical elements; generating a single mathematical model by integrating the model of the transmission-level buses with the model of the distribution-level buses, wherein the single mathematical model further models the interdependency of the plurality of transmission lines and the plurality of transmission electrical elements included in the model of the transmission level buses and the plurality of distribution lines and the plurality of distribution electrical elements included in the model of the distribution-level buses; simulating an operation of the electric power network with the single mathematical model; and outputting data describing the simulated electric power network.

20040039622

10336541

1. A computerized method for facilitating scheduling of operation of a facility for at least a first time interval of a period of time, the method comprising: generating a decision tree based model accounting for a combined effect, on the scheduling of the operation of the facility, of: at least one specified forward price path, over the period of time, including at least one price of at least one commodity associated with operation of the facility; at least one specified level of uncertainty with regard to the at least one specified forward price path; and, at least one specified constraint associated with at least a first state of at least one state of at least one operating parameter associated with the operation of the facility; applying a dynamic optimization algorithm to the decision tree based model to determine an optimal scheduling option for at least the first interval of time; and, storing in a memory optimal scheduling option information associated with the optimal scheduling option.

20080091512

11850650

1. A method of determining a measure of engagement of an audience for a presentation providing a sensory stimulus comprising: exposing the audience to the presentation over a period of time, wherein said period of time is divided into two or more time slots; for each member of said sample population, measuring a plurality of biologically based responses to said presentation; for each time slot, determining at least one intensity value as a function of at least one of the measured biologically based responses, for each time slot, determining at least one synchrony value as a function of a rate of change of at least one of the measured biologically based responses; and for each time slot, determining at least one engagement value as a function of at least one of said intensity values and at least one synchrony value.

5467291

07802993

1. A modeling method for an active semiconductor device, comprising the steps of: providing dynamic equations which define a model of an active semiconductor device for a nonlinear circuit simulator, in terms of functions to be calculated from measured response data and a frequency parameter .omega..sub.t to be specified during simulation; providing branch equations for voltage re-referencing to the dynamic equations which define a large-signal model of the active semiconductor device for the nonlinear circuit simulator, defined in terms of functions to be measured; providing a measurement system for generating stimuli and measuring responses to applied stimuli; measuring series port resistances of the measurement system; connecting terminals of the active semiconductor device to the measurement system; measuring S-parameters versus frequency at the terminals of the active semiconductor device with the measurement system; calculating parasitic device resistances and parasitic device inductances for the active semiconductor device; measuring S-parameters versus applied, measured controlling bias voltages at at least one frequency and d.c. terminal transfer curves versus applied biases over a predetermined operating range of biases of the active semiconductor device with the measurement system; calculating an intrinsic Y-matrix of the active semiconductor device by linear de-embedding of the parasitic device resistances and inductances previously calculated; calculating state functions for the large-signal model, referenced to an applied, measured voltage space defined by the applied, measured controlling bias voltages; and writing a model file, containing tabulated state function values, measurement series port resistances, and calculated parasitic values.

20020042770

09971492

1. Liquid insurance contracts, comprising: a security which is traded or tradable, wherein said security has cash flows to the issuer based upon a liability whose exact value is unknown at the time of issuance.

20100318540

12484256

1. In a computing environment, a method comprising, obtaining lambda gradient scores for sample data items, using the lambda gradient scores to compute re-judgment scores for the sample data items, and selecting sample items for re-judging based upon the re-judgment score associated with each sample item.

20020144212

09818946

1. A system for integrated circuit design, comprising: (a) an application database that stores information about a plurality of users and a plurality of reference designs for integrated circuits; (b) a plurality of servers, each connected to said application database; (c) a gateway, connected to said plurality of servers, that services connections from a plurality of user machines over a communications network; and (d) means for allowing said plurality of user machines to perform at least the following six phases of integrated circuit design via a graphical user interface by communicating with one of said plurality of servers and said application database, via said gateway: (i) system architecture exploration; (ii) software development; (iii) design; (iv) verification; (v) synthesis, layout and static timing analysis; and (vi) auto test pattern generation; wherein each of said plurality of users may remotely perform at least said six phases of integrated circuit design, said gateway is a Web server and said communications network is at least a portion of the Internet.

8865410

13760909

1. A method for detecting errors occurring in the preparation and/or sequencing of a DNA sequencing library, the method comprising: (a) incorporating at least one first nucleic acid adaptor molecule into at least one member of a target library comprising a plurality of nucleic acid molecules, wherein the first adaptor molecule comprises a first defined sequence; (b) amplifying the plurality of nucleic acid molecules to produce an input library comprising a first plurality of amplified DNA molecules, wherein the amplified molecules comprise a sequence identical to or complementary to at least a portion of the first adaptor molecule and sequence identical to or complementary to at least a portion of the at least one member of the target library; (c) sequencing at least a portion of the plurality of amplified DNA molecules to produce a plurality of sequencing reads corresponding to the at least one member of the target library; (d) grouping the plurality of sequencing reads that correspond to the at least one member of the target library; and (e) detecting whether an error exists at a nucleotide position, wherein an error exists when variation of nucleotide identity exists among the grouped sequencing reads at a position corresponding to a nucleotide in the at least one member of the target library.

20170279828

15176652

1. A method comprising: maintaining, at a device in a network, a plurality of anomaly detection models for different sets of aggregated traffic data regarding traffic in the network; determining, by the device, a measure of confidence in a particular one of the anomaly detection models that evaluates a particular set of aggregated traffic data; dynamically replacing, by the device, the particular anomaly detection model with a second anomaly detection model configured to evaluate the particular set of aggregated traffic data and has a different model capacity than that of the particular anomaly detection model; and providing, by the device, an anomaly event notification to a supervisory controller based on a combined output of the second anomaly detection model and of one or more of the anomaly detection models in the plurality of anomaly detection models.

20160063147

14474950

1. A method for posterior estimation of variables in water distribution networks, the method comprising: receiving, by one or more processors, a set of data inputs based on information received from a water distribution system; determining, by the one or more processors, a first model of the water distribution network based on the set of data inputs and uncertainty information; and determining, by the one or more processors, a second model of the water distribution network based on the set of data inputs, and the first model.

9355361

14598146

1. A computer-implemented method comprising: receiving a request from a particular user to view one or more online reviews; in response to receiving the request, accessing a plurality of reviews generated by a plurality of review authors; determining, using one or more hardware processors, a similarity of one or more of the review authors to the particular user, based on at least one of a user preference profile of the particular user and a connection of the particular user on an online social network; sorting the reviews, based on the determined similarity of the one or more of the review authors to the particular user; and providing the sorted reviews to the particular user.

20140181798

13721490

1. A method for performing static analysis of one or more query expressions embedded in programming language source code, the method comprising: extracting the one or more query expressions from the programming language source code; performing the static analysis on the extracted one or more query expressions; and reporting results of performing the static analysis on the one or more query expressions, wherein the results relate errors and warning generated by performing the static analysis to the source code from which the one or more query expressions are extracted.

20050141560

10750008

1. For use in a wireless telecommunication system comprising a base station and a plurality of mobile stations, a method for selecting a best fit transport format combination (TFC) from a transport format combination set that is assigned to at least one mobile station by said base station, said method comprising the steps of: identifying TFC candidates in said transport format combination set that are not best fit candidates; deleting from said transport format combination set said TFC candidates that are not best fit candidates until a sole TFC candidate remains; and identifying said sole remaining TFC candidate as a best fit TFC candidate.

9130997

14296435

1. A computer-implemented method comprising: maintaining, in an online system, a set of feature loops, wherein a feature loop comprises an expression capable of being processed by a computer processor to map a set of input values to an output value, the expression evaluating to a value describing one or more entities in the online system, wherein evaluating the feature loop comprises aggregating values of the expression across a plurality of user actions; receiving information describing a modification to the set of feature loops, wherein the modification to the set of feature loops is performed while the online system is executing; responsive to the set of feature loops being modified, evaluating feature loops of the set of modified feature loops for a subsequent user action; and responding to the subsequent user action based on the values of feature loops from the set of modified feature loops.

9501630

14292266

1. A method for generating a human likeness score based on a Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA), the method comprising: selecting a visual advertising asset; generating the CAPTCHA comprising a graphical interface, the visual advertising asset and a graphical object depicted within the graphical interface; assigning an instruction for completing the CAPTCHA; from a user, receiving an input within the graphical interface, the input comprising a solution to the CAPTCHA from the user, the solution comprising a selection of the graphical object within the graphical interface; extracting a motion pattern from the input; comparing the motion pattern to a motion model based on input patterns of previous users; and calculating the human likeness score of the user based on the comparison of the motion pattern to the motion model, the human likeness score lying within a continuum of discrete human likeness scores, wherein calculating the human likeness score comprises: generating a first confidence group according to an accuracy of the solution in fulfilling the instruction; generating a second confidence group based on the comparison of the motion pattern to the motion model; generating a third confidence group based on user data pertaining to at least one of a CAPTCHA previously attempted by the user, an Internet Protocol address of the user, and a cookie associated with the user; determining a reliability of the first confidence group, the second confidence group, and the third confidence group; compiling the first confidence group, the second confidence group, and the third confidence group, based on the determined reliability thereof, to generate the human likeness score; and selecting a number value, from the continuum of human likeness scores comprising a continuum of number values, that correlates with a calculated confidence that the user is human.

20040060771

10254844

1. A sound diffusor comprising an aperiodic array of diffusor modules including a first module having an asymmetrical surface pattern oriented in a first orientation and at least a second module having the same surface pattern as that of the first module but oriented in a second orientation.

9098215

13732723

1. A method comprising: obtaining an indication of a model element of a first model element type which is to be migrated to a model element of a second model element type, wherein a diagrammatic representation of the model element of the first model element type is present in a diagram of a modeling environment, and wherein the diagrammatic representation of the model element of the first model element type comprises one or more properties; and automatically migrating, by a processor, the model element of the first model element type to the model element of the second model element type, wherein the automatically migrating migrates a relationship between the model element of the first model element type and a related model element to a relationship between the model element of the second model element type and the related model element, in which a replacement relationship type is applied to the relationship between the model element of the second model element type and the related model element, and wherein the automatically migrating comprises: identifying a relationship type of the relationship between the model element of the first model element type and the related model element; determining whether the identified relationship type between the model element of the first model element type and the related model element is a valid type of relationship that may exist as between the second model element type and a model element type of the related model element, wherein the determining comprises checking a model element type relationship table indicating valid relationship types that may exist as between model element types, wherein the identified relationship type is determined to be invalid as between the second model element type and the model element type of the related model element based on the model element type relationship table lacking a valid relationship type as between the second model element type and the model element type of the related model element; based on determining that the identified relationship type is invalid as between the second model element type and the model element type of the related model element, identifying the replacement relationship type which is a valid type of relationship that may exist as between the second model element type and the model element type of the related model element; obtaining the identified replacement relationship type; instantiating a new model element with the second model element type and creating a relationship between the new model element and the related model element, wherein the new model element is the model element of the second model element type, and the creating the relationship between the new model element and the related model element uses the identified replacement relationship type to automatically create, with the identified replacement relationship type, the relationship between the new model element and the related model element; and preserving the one or more properties of the diagrammatic representation of the model element of the first model element type in a diagrammatic representation of the new model element, the preserving the one or more properties of the diagrammatic representation of the model element of the first model element type comprising: obtaining the one or more properties; applying the obtained one or more properties to the diagrammatic representation of the new model element; and replacing the diagrammatic representation of the model element of the first model element type with the diagrammatic representation of the new model element in the diagram.

10051808

15402392

1. A plant, a plant part, or a seed of soybean variety CL1361005, wherein a representative sample of seed of said soybean variety CL1361005 has been deposited under ATCC Accession Number PTA-123641.

9057174

13502896

1. A system for diagnosing a state of a construction machine in accordance with at least parameter data acquired by sensors, the system comprising: a diagnosis device for diagnosing the construction machine; a diagnostic knowledge storage device for storage of diagnostic knowledge including a diagnosing technique used for the diagnosis; and a diagnostic data storage device for storage of diagnostic data including the sensor-acquired parameter data, the diagnostic data being used for the diagnosis; wherein the diagnosis device includes: an input and output section for data input and output with respect to outside; a diagnostic data acquisition section for acquiring, on the basis of the data input to the input and output section, diagnostic data including appropriate parameter data, from the diagnostic data storage device; a data characteristics acquisition section for acquiring data characteristics of the diagnostic data acquired by the diagnostic data acquisition section, from the acquired diagnostic data, the data characteristics being inclusive of at least parameter characteristics which denote characteristics of the parameter data; a diagnostic knowledge acquisition section for acquiring, from the diagnostic knowledge storage device, any diagnosing techniques fitting the data characteristics acquired by the data characteristics acquisition section; and a diagnosing section for conducting the diagnosis using both of the diagnostic data including appropriate parameter data acquired by the diagnostic data acquisition section, and the diagnosing techniques acquired by the diagnostic knowledge acquisition section; wherein the diagnosis device further includes an effective rate calculation section for calculating an effective rate of each diagnosing technique acquired by the diagnostic knowledge acquisition section; before conducting the diagnosis, the diagnosing section selects, of the diagnosing techniques acquired by the diagnostic knowledge acquisition section, an optimal diagnosing technique according to particular results of the calculation of the degrees of effectiveness of the acquired diagnosing techniques by the effective rate calculation section; the diagnostic knowledge further includes the number of application cases that denotes the number of application cases in which a combination of the data characteristics and one of the diagnosing techniques is effective; the diagnostic knowledge acquisition section acquires the number of application cases in addition to the diagnosing technique; and the effective rate calculation section calculates the effective rate from a product of two values, wherein one of the two values is a ratio between the number of elements in data characteristics input to the diagnostic knowledge storage device in order to acquire from the device a diagnosing technique fitting the data characteristics previously acquired by the data characteristics acquisition section, and the number of elements in the data characteristics contained in the diagnostic knowledge matching the input data characteristics, and the other value is the number of application cases that is contained in the diagnostic knowledge.

8579632

12369680

1. A computer-implemented athletic performance analysis method, comprising: obtaining, at a computer system, first motion data reflecting motion of a sporting device during one or more drills performed by an athlete; creating and storing action data by identifying a plurality of portions of the first motion data, where each of the portions correspond to one or more actions by the athlete; comparing the action data for the athlete, with the computer system, to one or more groupings of action data, wherein each grouping of action data comprises combined action data for a plurality of other athletes that have been determined to belong in a same athlete skill level classification from among a plurality of athlete skill level classifications; and generating data for a report that reflects a relative athlete skill level classification of the athlete, wherein comparing the action data for the athlete to the one or more groupings of action data comprises identifying the relative athlete skill level classification, from among the plurality of athlete skill level classifications, that has action data that matches the action data for the athlete.

8826907

12479230

1. A method for respiratory support, the method comprising: measuring a pressure and providing a measured pressure; measuring an inlet flow and an outlet flow, and providing a measured net flow; using a relationship between a first value related to the measured pressure, a second value related to the measured net flow, and a third value related to patient effort to provide a prediction of patient effort; and updating an interim value based at least in part on the prediction of the patient effort, wherein the interim value is a composite parameter that does not directly correspond to any identifiable respiratory parameter.

20040186814

10390709

1. A method for determining an efficient frontier, which comprises a collection of security allocations in a portfolio, with multiple, conflicting objectives in a multi-factor portfolio problem, the method comprising: providing a mathematical model of a relaxation of a problem; generating a sequence of additional constraints; and sequentially applying respective nonlinear risk functions to generate respective adjusted maximum return solutions to obtain an efficient frontier.

9158755

13663563

1. A processor-implemented method of lemmatizing a phrase for a specific category, the processor-implemented method comprising: receiving, by a processor, a string of binary data that represents an initial phrase, wherein the initial phrase is an initial version of the phrase, wherein the phrase comprises multiple words, and wherein the phrase is associated with a specific category; removing one or more letters from an end of a word in the initial phrase to form an initial truncated version of the phrase; running, by the processor, a term frequency-inverse document frequency (TF-IDF) algorithm on the initial truncated version of the phrase; the processor lemmatizing subsequent truncated versions of the initial phrase by recursively removing a remaining said one or more letters from the end of the word in a subsequent truncated version of the initial truncated version of the initial phrase; the processor running the TF-IDF algorithm on subsequent truncated versions of the initial truncated version of the initial phrase until a highest TF-IDF value is identified for a specific truncated version of the initial phrase when compared to TF-IDF values of other truncated versions of the initial phrase; assigning the specific truncated version of the initial phrase that is associated with the highest TF-IDF value to the specific category; in response to receiving a request for the phrase within the specific category, returning the specific truncated version of the initial phrase that is associated with the highest TF-IDF value for said specific category; and using the specific truncated version of the initial phrase that is associated with the highest TF-IDF value for said specific category to search a database that is dedicated to the specific category.

7644192

11509971

1. A method of analyzing the behaviour of a storage system when running an input/output (I/O) workload, the method comprising: (a) creating an isochronous thread formed by a sequence of operations to be carried out by the storage system when running the thread, the thread being created by: (i) defining a plurality of factors, each factor corresponding to an aspect of the thread when running the I/O workload, the plurality of factors enabling absolute control over iterative access location, transfer size and access type of the operations of said sequence of operations; (ii) defining one or more timing factors corresponding to a frequency characteristic and a timing pattern for each of the operations of said sequence of operations; (b) causing the storage system to run the I/O workload by: (i) interpreting the one or more timing factors of each operation of said sequence of operations to determine a scheduled time for the corresponding operation; (ii) for each operation in said sequence of operations interpreting the factors of each operation to determine respective operation characteristics for the corresponding operation of said sequence of operations; (iii) for each operation in said sequence of operations, converting the operation characteristics to at least one command for the storage system; (iv) for each operation of said sequence of operations, sending the at least one command to the storage system at a sending time, the sending time being either said scheduled time or the earliest subsequent time the storage system is ready to accept the at least one command of the respective operation of the sequence of operations, whichever is later; (v) for each operation of said sequence of operations, detecting the time of completion of each command of the corresponding operation by the storage system; (vi) deriving, from the time of completion of each command of each operation of said sequence of operations, a time of completion of the corresponding operation of said sequence of operations; (vii) storing the time difference between said sending time and said time of completion of each operation of said sequence of operations; (viii) storing any operation start time latency, said operation start time latency being the difference, if any, in time between said scheduled time and said sending time for each operation of said sequence of operations; (c) analyzing said time differences and said operation start latencies of said sequence of operations, thereby to analyze the behaviour of the storage system.

20020107599

09769866

1. A method for dispatching available lots to unallocated machines, comprising: receiving metrics data providing performance measurements for a plurality of machines; determining a state for each of the machines based on the metrics data; receiving one or more lots to be dispatched, each lot having a lot type and each lot type associated with one of a plurality of models; selecting a preferred lot type for each of the plurality of models associated with each of the machines based on the state of the machine; selecting a preferred model based on a time since a last run of the model, a cost of switching to a new model and lot type, and the state of the machine; resolving conflicts between selected preferred lot type/preferred model combinations when insufficient lots are available to fill the selections; and assigning each lot to one of the machines according to the preferred model and preferred lot type selections.

8977575

12839929

1. A method comprising: training a computer implemented Bayesian based diagnostic system, wherein training includes providing the diagnostic system with historical input data and a corresponding diagnosis to be derived from the historical input data and providing new input data having a predetermined diagnosis, wherein the diagnostic system generates a conditional probability table of a new diagnosis using the new input data; generating a confidence indicator corresponding to the new diagnosis, wherein the confidence indicator is generated on a per-diagnosis basis; comparing the confidence indicator to a predetermined threshold; using the diagnostic system to obtain another diagnosis using other input data in response to determining the confidence indicator of the new diagnosis is greater than a predetermined threshold, the another diagnosis including a corresponding accuracy measure; and generating a cumulative confidence indicator for multiple per-diagnosis confidence intervals, the cumulative confidence indicator including the determined confidence indicator.

8458720

11840556

1. A method for choosing non-continual jobs to run in a stream-based distributed computer system, comprising: determining a total amount of processing resources to be consumed by non-continual jobs, based on priorities of both continual and non-continual work; determining a priority threshold by incrementally increasing the priority threshold; accepting non-continual jobs to be executed based on the priority threshold, wherein non-continual jobs having a priority higher than the priority threshold will be accepted, and non-continual jobs having a priority lower than the priority threshold will be rejected; associating a penalty function with each process element of the accepted non-continual jobs, wherein the penalty function is a non-decreasing objective function with respect to a completion time of the associated process element of the accepted non-continual jobs; creating one or more execution templates for each accepted non-continual job, each of the one or more execution templates having different relative start times and resource allocations for the one or more processing elements of each accepted non-continual job; forming a system execution template by selecting an execution template and a start time for each of the accepted non-continual jobs, wherein the selected execution template and the start time for each of the accepted non-continual job are selected such that the system execution template minimizes the overall penalties based on estimated completion times of the process elements of the accepted non-continual jobs by minimizing a sum of penalty functions across the processing elements of the accepted non-continual jobs; and applying system constraints to the accepted non-continual jobs so that the accepted non-continual jobs meet set criteria such that the accepted non-continual jobs are scheduled to meet the set criteria and minimize overall penalties using the total amount of resources.

9843540

14137957

1. For an electronic device that comprises a physical network interface card (PNIC) with a plurality of queues for temporarily storing data traffic through the PNIC, a method of managing the queues of the PNIC, the method comprising: specifying a first pool and assigning at least a first queue of the queues of the PNIC to the first pool; initializing a first virtual machine (VM) as an addressable node executing on the electronic device, wherein the first VM includes a first virtual network interface card (VNIC) which is coupled through a network stack to the PNIC; assigning a subset of data traffic through the PNIC to the first pool to be supported by queues which are assigned to the first pool including at least the first queue, wherein the subset of data traffic relates to the first VM; initializing a second virtual machine (VM) as an addressable node executing on the electronic device, wherein the second VM includes a second VNIC which is coupled through a network stack to the PNIC; determining that the second VM has a particular traffic requirement relevant to a specific hardware functionality that is supported by the PNIC; specifying a hardware-feature pool and assigning at least a second queue of the queues of the PNIC to the hardware-feature pool, the specifying of the hardware-feature pool and the assigning of at least the second queue comprises determining that none of the queues of the PNIC are free queues and, in response, preempting the second queue which is currently assigned to another pool and assigning the second queue to the hardware-feature pool, wherein the second queue has the specific hardware functionality to match the particular traffic requirement of the VM, and, by way of the preempting, is a free queue of the PNIC prior to assigning the second queue to the hardware-feature pool; and based on the determining, assigning data traffic of the second VM to the hardware-feature pool to be supported by queues which are assigned to the hardware-feature pool including at least the second queue.

20160093115

14498686

1. A method comprising the following steps: assigning a failure class label to each data point, from a set of multiple data points derived from measurements associated with a vehicular component across a fleet of multiple vehicles, that (a) is associated with (i) a scheduled vehicular component replacement or (ii) a failure-caused vehicular component replacement, and (b) is within a pre-specified number of runtime hours of (i) the scheduled vehicular component replacement or (ii) the failure-caused vehicular component replacement; assigning a non-failure class label to each data point, from the set of the multiple data points, that (a) is associated with (i) a scheduled vehicular component replacement or (ii) a failure-caused vehicular component replacement, and (b) is not within the pre-specified number of runtime hours of (i) the scheduled vehicular component replacement or (ii) the failure-caused vehicular component replacement; assigning a non-failure class label to each data point, from the set of the multiple data points, that is associated with an actively running instance of the vehicular component as yet to be replaced; estimating a failure probability for the vehicular component at each of the multiple data points over a pre-specified future runtime of the vehicular component based on the class label assigned to each of the multiple data points; determining a cumulative hazard function for the vehicular component based on the failure probability, wherein said cumulative hazard function assesses the amount of accumulated risk that the vehicular component faced from a given start time until the present time; and generating a cumulative wear-based indicator for the vehicular component by executing a regression function at a given time based on (i) the cumulative hazard function, (ii) one or more selected parameters, and (iii) a determination as to whether the vehicular component (a) was previously replaced due to a failure, (b) was previously replaced due to a non-failure scheduled replacement, or (c) is actively running as yet to be replaced; wherein at least one of the steps is carried out by a computing device.

7937569

10839471

1. A system, comprising: a scheduler configured to store a speculative source tag and a non-speculative source tag for an operand of an operation; and an execution core configured to execute operations issued by the scheduler and to output result tags identifying operands generated by executing the operations; wherein the scheduler comprises circuitry with a first input port and a second input port configured to receive the speculative source tag and the non-speculative source tag, respectively, and an output port coupled to a third input port of a comparator, the output port configured to convey an output value corresponding to either the first or the second input port at any given time, wherein a fourth input port of the comparator is configured to receive result tags output by the execution core, wherein the scheduler is configured to: determine whether the operation is ready to issue by: comparing the speculative source tag, but not the non-speculative source tag, to the result tags output by the execution core unless an incorrect speculation has been detected; and comparing the non-speculative source tag, but not the speculative source tag, to the result tags output by the execution core if the incorrect speculation has been detected; and wherein the scheduler is further configured to issue the operation to the execution core subsequent to determining the operation is ready to issue.

7970550

10662345

1. A method of performing interactive clinical trials for testing a new drug for cancer related studies, resulting in clinical trial designs, the method comprising: a) performing a pre-clinical phase in which a computer model for pharmacodynamics of a drug is determined; b) obtaining data to determine the computer model for the pharmacodynamics of the drug of (a) from in vitro studies of the effect of the drug in animal cells, and optionally, in vivo studies in animals, and obtaining data for the pharmacokinetics of the drug of (a) from in vivo studies in animals; c) performing a phase I clinical trial in which a clinical trial on at least a single dose of the drug of (a) is administered to at least one human, and the phase I clinical trial is performed in parallel by performing computer simulations using the computer model constructed in step (a); d) adjusting the computer model based on comparison of the results of the clinical trial and computer simulations using the computer model, wherein the at least a single dose of step (c) is incrementally increased in at least one dose escalation step; e) calculating the dose escalation step by the computer simulations performed using the computer model in step (d) to obtain a maximal tolerated dose, minimum effective dose, and a recommended dose; f) checking the patient for cumulative drug effects after administration and providing this information to the computer model; g) performing multiple simulations using the computer model with different doses and dosing intervals for different indications and patient populations; h) determining, based on step (g) simulations results, an optimal regimen for the most responsive patient populations and clinical indications for a phase II clinical trial; i) performing at least one phase II clinical trial where a number of small scale clinical trials are performed in parallel in order to test the optimal treatment regimen from step (h) for different pairs of clinical indications and patient populations; j) performing at least one phase III clinical trial for a clinical indication chosen in step (h) using a regimen that was chosen in step (i); and k) performing at least one phase IV clinical trial, based on, at least, one previous clinical trial, for post-marketing subpopulation analysis that may identify differences in efficacy and toxicity between the subpopulations, and long term product safety assessment.

9295061

14339654

1. A method of selecting a transmission parameter by a dynamic spectrum allocation apparatus, the method comprising: collecting, by the dynamic spectrum allocation apparatus, frequency band information comprising a frequency bandwidth and communication environment information comprising a power density of noise; constituting, by the dynamic spectrum allocation apparatus, a plurality of single-objective fitness functions comprising a bandwidth fitness function based on data transmission using two frequency bands, using the frequency band information and the communication environment information; constituting, by the dynamic spectrum allocation apparatus, a multi-objective fitness function obtained by assigning a weight value to each of the plurality of single-objective fitness functions; and selecting, by the dynamic spectrum allocation apparatus, the transmission parameter by applying a genetic algorithm to the multi-objective fitness function.

6108725

09110929

1. For use in a system for controlling data-accessing of a common bus, an improved DRAM architecture comprising a multi-port internally cached DRAM (AMPIC DRAM) comprising a plurality of independent serial data interfaces each connected between a separate external I/O resources and internal DRAM memory through corresponding buffers competing for access to a common internal bus; a switching module interposed between the serial interfaces and the buffers; and a switching module logic control for the connecting of any of the I/O resources through serial interfaces with any of the buffers under a dynamic configuration of switching allocation as appropriate for the desired data routability among the interfaces wherein the number of the serial interfaces is independent of the number of buffers and the number of serial interfaces varies under the dynamic configuration.

8386396

12467413

1. A computer implemented method for bidirectional matching between a plurality of parties belonging to a first group and a plurality of parties belonging to a second group, the method comprising: (a) operating a processor thereby to collect, from each party belonging to the first group, data indicative of first group criterion responses for a plurality of criterions, wherein each criterion has a pre-assigned baseline rating score; (b) operating the processor thereby to determine, in respect of at least a selection of the first group criterion responses, first group preferential rating scores; (c) operating the processor thereby to collect, from each party belonging to the second group, data indicative of second group criterion responses for the plurality of criterions; (d) operating the processor thereby to determine, in respect of at least a selection of the second group criterion responses, second group preferential rating scores; (e) on the basis of a criterion match determination protocol, operating the processor thereby to process the data indicative of criterion responses, thereby to identify criterion matches between parties belonging to the first group and parties belonging to the second group; (f) operating the processor thereby to determine, for each criterion match between a party belonging to the first group and a party belonging to the second group, a criterion match rating based on a function of the baseline rating score and, where determined, the first group preferential rating score, the second group preferential rating score, or the first group preferential rating score and the second group preferential rating score in combination; and (g) operating the processor thereby to calculate, in respect of a match between a given party belonging to the first group and a given party belonging to the second group, a total match rating, wherein the total match rating is calculated based on criterion match ratings determined for criterion matches between the given party belonging to the first group and the given party belonging to the second group, including at least one criterion match rating based on a first group preferential rating score and at least one criterion match rating based on a second group preferential rating score.

20170192397

14984786

1. A system, comprising: one or more sensors providing data representing a current state of each of a plurality of process units within a continuous process, said process units meeting one or more demands of the continuous process; and a control system receiving the current state data and generating an operating state of the continuous process based thereon, the control system comprising a processor executing computer-executable components, the components comprising: a plurality of model components implementing at least one first-principle equation, wherein the first-principle equation represents at least one of the process units, and wherein one or more of the plurality of model components comprise a group; a plurality of switch components each comprising a corresponding one of the plurality of model components and each implementing a mixed integer nonlinear programming (MINLP) behavior of the corresponding model component; a MINLP solver component configured to specify a switching state from a plurality of switching states, the switching states each corresponding to an operational status of the plurality of model components; and an oracle component configured to provide an infeasibility indication to the MINLP solver component as a function of the demands for indicating whether the specified switching state is infeasible.

8494559

11322751

1. A method comprising: receiving, by a computer comprising a processor, location-based information associated with a mobile device; identifying, by the computer, a first wireless access point, comprising a wireless local area network router having a first coverage area encompassing the mobile device, and a first gateway element associated with the first wireless access point, yielding a first access point/gateway pair; identifying, by the computer, a second wireless access point, comprising a cellular base station having a second coverage area encompassing the mobile device, and a second gateway element associated with the second wireless access point, yielding a second access point/gateway pair; determining, by the computer, using the location-based information, which one of the first wireless access point and the second wireless access point to use to connect the mobile device to a communication network, including determining which one of the first access point/gateway pair and the second access point/gateway pair to use to connect the mobile device to the communication network, yielding a determined network access point; and transmitting, by the computer, to the mobile device, an instruction indicating the determined network access point for the mobile device to use to connect to the communication network.

9536328

14590061

1. A computer program product for generating a map based on data and weighted factors to minimize corresponding projection distortions, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a computer to cause the computer to perform a method, comprising: determining visualization goals from analyzing a set of datasets for a map using a computer; calculating a set of visualization characteristics for each dataset based on the visualization goals using the computer, wherein the calculating of a set of visualization characteristics includes determining elements contained within a geographical extent; analyzing the visualization characteristics to weight factors for each of the datasets; adjusting each of the weighted factors based on relevance of each of the datasets for visualization of the map; calculating an aggregate vector of weighted factors based on all of the datasets; generating the map for visualization based on the aggregate vector of weighted factors; building a list of shape files for each of the elements, each shape file being constructed based on a map projection, wherein the weighted factors consider the shape files of each of the elements; ranking the shape files by: comparing an area of the shape file to a geographical area of the element associated with the shape file; comparing a great circle distance between the center of the shape area and the geographical center of the shape file's associated element; and comparing azimuth errors for a set of contained points in a shape associated with each of the shape files; and selecting a map projection that minimizes the differences in area and in distance between a plurality of projections and geographical measures, and minimizes aggregated azimuth errors.

20080056682

11512583

1. A method for receiving, storing, and presenting video programming without indexing the programming prior to storage, the method comprising: a) receiving into an input buffer a Moving Pictures Experts Group (MPEG) stream from an input section, wherein the received MPEG stream comprises video packets from a video programming event; b) storing the received MPEG stream from the input buffer onto a storage device without, prior to storage, analyzing data in the video packets to generate indexing information from the received MPEG stream; c) receiving a seek input; d) determining a data read size and a starting read position in the stored MPEG stream based on the seek input; e) loading a portion of the stored MPEG stream from the storage device, wherein: i) the size of the loaded portion is based on the data read size; and ii) the position of the loaded portion is based on the starting read position; f) analyzing the loaded portion to determine if the loaded portion includes a complete MPEG intra-coded frame; and g) if the loaded portion includes a complete MPEG intra-coded frame, decoding the MPEG intra-coded frame to provide a video frame for presentation on a display device.

7809721

11941696

1. A system for ranking data, comprising: at least one processor; at least one computer-readable storage medium connected to the processor; a data store on the medium; entries stored on the data store; a series of instructions on the medium and executable by the processor, including; a reception component that receives a query; a first calculation component that calculates a qualitative semantic similarity score of a semantic part of the query by associating the semantic part with text from data entries in a data store; a second calculation component that calculates a general quantitative score of by at least calculating a distance score for the data entries based on a geographic location part of the query; a third calculation component that adds the general qualitative semantic similarity score and the general quantitative score to obtain a vector score for the at least one data entry, the general qualitative semantic similarity score and the quantitative score each having a range with a minimum value of the general qualitative score being more than a maximum value of the general quantitative semantic similarity score such that the general quantitative score is never overruled by the general qualitative similarity semantic score; and a ranking component that ranks the at least one data entry among other data entries using the vector score.

20140032558

13558814

1. A computer implemented categorization method comprising: receiving a sequence of pages to be categorized; for each of a plurality of pages in the sequence as a current page: computing a page category score for each of a set of categories for the current page; computing a first bipage category score for each of the set of categories for a first bipage comprising a preceding page and the current page; computing a second bipage category score for each of the set of categories for a second bipage comprising a subsequent page and the current page; computing a first boundary probability that there is a document boundary between the preceding page and the current page; and computing a second boundary probability that there is a document boundary between the subsequent page and the current page; for at least one iteration, for each of the plurality of pages, computing a refined page category score for each of the set of categories for the current page as a function of: the first bipage category scores weighted by a first weighting factor, the first weighting factor being based on the first boundary probability; the second bipage category scores weighted by a second weighting factor, the second weighting factor being based on the second boundary probability; and the page category scores of the current page; and outputting information based on the refined page category scores for each of the plurality of pages.

20110251874

12816448

1. A method for building an integrated customer analytics solution for an enterprise comprising one or more data sources, the method comprising: retrieving and processing data from the one or more data sources, wherein the data represents customer data; generating one or more statistical techniques using the processed data to facilitate analyzing one or more attributes related to the customer; deriving one or more statistical model outputs using the one or more generated statistical techniques, wherein the statistical model outputs represent one or more metrics corresponding to the analyzed attributes; generating one or more statistical models corresponding to the one or more statistical model outputs, wherein the one or more statistical models are associated with one or more scores that facilitates to predict likelihood of customer behavior towards products, services and other customer related aspects associated with the enterprise; generating one or more reports based on at least one of: the processed data and the one or more statistical model outputs; and building one or more analytical modules comprising the one or more reports and the one or more statistical models, wherein the one or more analytical modules constitute the integrated customer analytics solution.

8060458

12490904

1. A method of an engineering design, comprising the steps of: (a) constructing a plurality of knowledge components, wherein each knowledge component comprises one or more universal modules, each universal module comprising at least operations, procedures, rules and flows of a corresponding engineering design process, wherein each knowledge component is constructed to have: (i) a data interface having data input and output ports; (ii) a control interface having input and output ports, for defining a logical control relation between the knowledge component and its upstream and downstream knowledge components thereof; (iii) a human-computer interactive interface having input ports, for managing data input and data output through the data input and output ports of the data interface; (iv) a message interface having input ports, for receiving external messages and information; and (v) a third party tool interface having input ports, for accessing third party tools, wherein the logical control relation is automatically established in accordance with the sequences that a user uses the knowledge components to complete the engineering design process; (b) defining a data relation and an execution relation of the plurality of knowledge components so as to correlate the plurality of the knowledge components to each other to form a design process model dynamically and concurrently with the design process without programming, wherein when defining the data relation of the plurality of knowledge components, a data mapping relation between the input and output ports of the plurality of knowledge components is automatically established, wherein the execution relation of the plurality of knowledge components comprises logical relations, data driving relations, time characteristics, message triggering mechanisms and any combination thereof, and wherein data of the design process model is automatically modifiable by a computer that is operatively associated with the plurality of knowledge components, in accordance with the rules adapted for defining the design process model; (c) integrating a variety of software platforms via an uniform environment so as to call the plurality of knowledge components of the design process model to perform an engineering design; and (d) packing two or more knowledge components and the data relation and the execution relation thereof into a parent knowledge component without programming, such that the output ports of the data interface and the control interface of any one but the last knowledge component are respectively connected to the input ports of the data interface and the control interface of the immediate next knowledge component, wherein the parent knowledge component comprises: (I) a parent data interface having input ports connected the input ports of the data interface of the first knowledge component, and output ports connected the output ports of the data interface of the last knowledge component; (II) a parent control interface for defining a logical control relation between the parent knowledge component and the upstream and downstream parent knowledge components thereof, having input ports connected the input ports of the control interface of the first knowledge component, and output ports connected the output ports of the control interface of the last knowledge component; (III) a parent human-computer interactive interface having input ports, for managing data input and data output through the data input and output ports of the parent data interface; (IV) a parent message interface having input ports, for receiving external messages and information; (V) a parent third party tool interface having input ports, for accessing third party tools; (VI) a message registration center configured to establish and manage a variety of messages relating to the parent knowledge component, and send the messages to corresponding internal knowledge components to trigger desired activities thereof, wherein the message registration center is connected between the parent message interface and the message input ports of each internal knowledge component; (VII) a customizable human-computer interactive interface having a variety of types of human-computer interactive controls including a data control for modifying data of the parent knowledge component and a message control for binding desired messages in the message registration center for calling the corresponding internal knowledge components, wherein the customizable human-computer interactive interface is connected to the parent human-computer interactive interface, the message registration center and the first knowledge component; (VIII) a knowledge information index coupled to a knowledge information database and configured to record the index relations of a number of activities of the parent knowledge component and usage specifications, design instructions, experiences and knowledge stored in the knowledge information database, and automatically extract the relevant information from the knowledge information database when the parent knowledge component carries out a certain activity; (IX) a timer configured to send a time message to the message registration center on the basis of the time point set by the parent knowledge component; and (X) a tool registration center configured to record information of the third party tool connected into the parent knowledge component, wherein the information includes access interfaces, data interfaces, starting mechanisms of the third party tool, wherein in operation, modifying the data of the design process model triggers the design process model to be partially or fully executed dynamically and concurrently with the design process, whereby both the definition and execution of the design process model occurs concurrently.

20090019408

12216795

1. A production method for a semiconductor integrated circuit comprising: creating a model parameter of an element constituting a cell, wherein said model parameter is defined by a design value and a distribution function of variability from said design value; performing a circuit simulation using said model parameter to create a response function that expresses response of characteristic of said cell to said model parameter; creating a statistical cell library by using said response function, wherein said statistical cell library gives an expected value and statistical variation of said characteristic of cell, wherein said statistical variation is expressed by a product of said distribution function and sensitivity, wherein said sensitivity is calculated based on said response function; updating said statistical cell library when said model parameter is updated, wherein said statistical cell library is updated by using said model parameter after update and said response function without performing a circuit simulation; designing and verifying a semiconductor integrated circuit by using said statistical cell library; and manufacturing said designed semiconductor integrated circuit.

7801748

10425722

1. A process performed by a computing device for preparing an insurance application for underwriting based on a plurality of previous insurance application underwriting decisions, the process comprising: receiving, by the computing device, a request to underwrite the insurance application; assigning, by the computing device, a risk classification to the insurance application; defining, by the computing device, a set comprising at least one of the plurality of previous insurance application underwriting decisions; comparing, by the computing device, the insurance application to the set; and designating, by the computing device, the insurance application based at least in part on the comparison between the insurance application and the set and the risk classification assigned to the insurance application, where the designating includes: designating the insurance application as an outlier insurance application; and where the at least one insurance application in the set includes a classification assignment; and where designating the insurance application as an outlier insurance application is based on determining an occurrence that a dominance relationship between the insurance application and one of the at least one insurance application in the set is inconsistent with a relationship of classification assignments between the insurance application and the one of the at least one insurance application in the set; and the designating the insurance application as an outlier insurance application comprising determining the dominance relationship, the determining the dominance relationship including: defining, by the computing device, a first set comprising at least one of the plurality of previous insurance application underwriting decisions that is not dominated by any other of the plurality of previous insurance application underwriting decisions, such that the first set constitutes a Pareto-best subset; defining, by the computing device, a second set comprising at least one of the plurality of previous insurance application underwriting decisions that does not dominate any of the other of the plurality of previous insurance application underwriting decisions, such that the second set constitutes a Pareto-worst subset, the first set and the second set being constituted by different previous insurance application underwriting decisions; the first set and the second set associated with respective prior applications; and comparing, by the computing device, the insurance application to the first set and the second set; and wherein the insurance application comprises a plurality of features; and where the comparing the insurance application to the first set and the second set further comprises: comparing the at least one feature to a corresponding feature in the at least one of the plurality of previous insurance application underwriting decisions in the first set; and comparing the at least one feature to a corresponding feature in the at least one of the plurality of previous insurance application underwriting decisions in the second set; and where: comparing the at least one feature to a corresponding feature in the first set further comprises determining if the at least one feature in the insurance application is dominated by the corresponding feature in the first set to generate a first dominated determination; and comparing the at least one feature to a corresponding feature in the second set further comprises determining if the at least one feature in the insurance application is dominated by the corresponding feature in the second set to generate a second dominated determination; each of the comparings including determining whether each of said feature in the insurance application represents greater or less risk than the corresponding feature in the first set or second set, respectively; the process further including, based on the first and second dominated determinations, assessing, by the computing device, whether all the features of the application are dominated by all the corresponding features of the first set, and including assessing whether all the features of the application are dominated by all the corresponding features of the second set.

8166552

12355584

1. An automated configuration management system (ACMS) for a virtualized ecosystem, comprising an electronic computing device and one or more computer-executable modules stored on one or more non-transitory computer-readable storage media accessible to said electronic computing device, said modules, when executed by said electronic computing device, configured to cause said electronic computing device to: monitor and record results of compliance-related operations across resources of the virtualized ecosystem, measure dynamic utilization of the resources of the virtualized ecosystem frequently enough to construct informative profiles of the resources, and capture configuration change information associated with the resources of the virtualized ecosystem, analyze data recorded during monitoring of the compliance-related operations, measurement of the dynamic resource utilization and capture of the configuration change information concerning security and compliance criteria of the resources of the virtualized ecosystem, recommend, according to a desired risk profile and results of said analysis, utilization and configuration changes for the resources of the virtualized ecosystem, wherein the configuration changes include security control changes to achieve compliance goals, and said change recommendations are presented along with risk values associated with a risk of performing a recommended change and a risk reduction value of said recommended change, develop a series of best practices for compliance-related operations and dynamic resource utilization within the virtualized ecosystem through said monitoring and analysis, and share information regarding said best practices with other ACMS installations.

8943484

13794938

1. A computer-readable, non-transitory storage medium storing a computer program for generating, from a first code, a specific instruction for performing a same type of operation on different data in parallel by combining two or more instructions included in the first code, and generating a second code including the specific instruction, the computer program causing a computer to perform a procedure comprising: generating first and second operation trees representing a dependency relationship among instructions included in the first code, computing a first operation sequence by arranging operations specified by instructions of the first operation tree in an order that matches a structure of the first operation tree, and computing a second operation sequence by arranging operations specified by instructions of the second operation tree in an order that matches a structure of the second operation tree; computing one or more longest operation subsequences of operation subsequences common to the first and second operation sequences; and evaluating, for each of two or more longest operation subsequences, when computed, utilization of computing resources used for executing combinations of instructions of the first and second operation trees corresponding to operations included in said each longest operation subsequence, and selecting a combination pattern of instructions indicated by one of the two or more longest operation subsequences based on results of the evaluating.

20140330542

13875680

1. A computer-implemented method of managing data for at least one user comprising: sensing actual real-time processing plant operation status data for at least one asset from a set of assets of a processing plant through at least one sensor; recording, to a computer server, the actual real-time processing plant operation status data sensed from the at least one sensor; performing a simulation, through at least one simulation model from a set of simulation models of a planned process design specification, through a computer-implemented simulation engine; recording process design specification data from the simulation, through the computer-implemented simulation engine; correlating the actual real-time processing plant operation status data and the process design specification data through a computer-implemented correlation engine, into a set of correlated data; displaying the set of correlated data, to the at least one user through a computer display, such that the actual real-time processing plant operation status data and the process design specification data are streaming, and visually presented, concurrently, to the at least one user at the same time; and displaying at least one set of further details of the set of correlated data, based upon interaction from the at least one user through a user interface.

7890198

10869163

1. In an electronic device, a method of manipulating a control system representation having a plurality of distributed single input single output (SISO) compensators, the method comprising: providing a graphical user interface (GUI) associated with a simulation environment for simulating the control system representation, the GUI incorporating a plurality of configurable views related to the control system representation; receiving an input through the GUI to modify a parameter of a first SISO compensator of the plurality of distributed SISO compensators; modifying the parameter of the first SISO compensator with a first modification in accordance with the received input, the parameter having a value representative of a substantially constant characteristic of the control system representation; operating the first SISO compensator to generate a resulting output; automatically updating one or more parameters of a remainder of the plurality of SISO compensators with a second modification based on the first modification and the resulting output of the first SISO compensator, the updating occurring contemporaneous with and resulting from modifying the parameter and operating the first SISO compensator; operating the remainder of the plurality of the SISO compensators to generate one or more outputs, the remainder of the plurality of the SISO compensators including a second SISO compensator and a third SISO compensator; and simultaneously displaying the plurality of configurable views related to the control system representation with one or more updated parameters of the remainder of the plurality of SISO compensators, the plurality of configurable views related to the control system representation including a first plot of one or more outputs of the second SISO compensator and a second plot of one or more outputs of the third SISO compensator, the displaying occurring simultaneously with the modifying the parameter of the first SISO compensator.

9349093

12870334

1. A method comprising: receiving a first set of factors and a data set associated with the first set of factors a factor from the first set of factors measuring an aspect of the data set; calculating, based on the data set, an importance value of each factor in the first set of factors, the calculating of an importance value of each factor in the first set of factors comprising: generating a function that approximates results associated with the data set, determining that variation of a first factor from the first set of factors results in greater variation in the results associated with the data set as compared to variation of a second factor from the first set of factors, and assigning a higher importance value to the first factor from as compared to an importance value for the second factor from the first set of factors; ranking the first set of factors based on the importance value of each factor in the first set of factors; selecting, based on the ranking, factors to be included in a reduced set of factors, the reduced set of factors having fewer factors than the first set of factors; and generating, using a genetic algorithm, a prediction function based on the data set and the reduced set of factors, the reduced set of factors derived from the first set of factors.

20110160980

12987654

1. A method of estimating health parameters p(k) representing symptoms of a slowly degrading system that includes at least a turbomachine or an internal combustion engines at a discrete time k, the method begin executed in a processing system having a specific discrete-time Kalman filter having a dynamic evolution model and an extended system model, the method comprising a) providing, in the Kalman filter, a prediction Ppred(k) of the health parameters p(k), b) calculating, in the Kalman filter, a prediction Ypred(k) of output variables y of a model of the system, based on the prediction Ppred(k) of the health parameters and measurements u(k) of input variables u of the model measured at time k, c) establishing, in the Kalman filter, a difference e(k) between the prediction Ypred(k) of the output variables y and measurements y(k) of the output variables y measured at time k, d) calculating, in the Kalman filter, an estimate Pest(k) of the health parameters p(k) based on the prediction Ppred(k) of health parameters p(k) and the difference e(k), wherein step a) comprises providing the prediction Ppred(k) of health parameters p(k) based on an estimate Pest(k−1) of the health parameters p(k−1) at a previous time k−1, wherein an interval D between the time k and the previous time k−1 is smaller than a characteristic degradation time τ of the degrading system, and e) storing or displaying the calculated estimate Pest(k).

20080253672

12046328

1. A method for predicting an offset factor for a target block of a multi-layer image, wherein said multi-layer image comprises a low-dynamic-range layer and a high-dynamic-range layer and said offset factor is used to predict said high-dynamic-range layer from said low-dynamic-range layer, said method comprising: a) determining a first scaling parameter and a first offset parameter for a first adjacent block, said first adjacent block being adjacent to said target block; b) determining a second scaling parameter and a second offset parameter for a second adjacent block, said second adjacent block being adjacent to said target block; c) fitting a mathematical model to said first scaling parameter, said second scaling parameter, said first offset parameter and said second offset parameter; d) determining a target scaling parameter for said target block; and e) determining a target offset parameter for said target block using said target scaling parameter and said mathematical model.

20090040225

12219311

1. A three-dimensional model retrieval apparatus comprising. a model normalizing means for rotating and/or translating a three-dimensional model so that main axis directions of the three-dimensional model are consistent with coordinate axes of a three-dimensional space, and barycenter of the three-dimensional model is consistent with origin of a system coordinate system; a two-dimensional image generating means for projecting said three-dimensional model respectively in a positive direction and a negative direction of each coordinate axis of said system coordinate system to generate a plurality of two-dimensional images; a model describing means for generating a model descriptor of the three-dimensional model from said two-dimensional images; and a retrieving means for retrieving, based on said model descriptor, a three-dimensional model which most matches an input query from a model database.

20140095513

13632506

1. A system for managing survey data, comprising: at least one processor; a non-transitory computer-readable storage medium including instructions executable by the at least one processor, the instructions configured to implement, a survey metadata handler configured to receive survey metadata for a survey type, the survey metadata including description information for a plurality of questions, and question weights corresponding to the plurality of questions; a survey result handler configured to receive one or more completed or partially completed surveys corresponding to the survey type, each completed or partially completed survey including survey results providing one or more answers to the plurality of questions; a calculating unit configured to calculate one or more weighted answers based on the question weights and the one or more answers, and a satisfaction score for each completed or partially completed survey based on the one or more weighted answers; a category determining unit configured to determine a satisfaction category for the survey type based on the satisfaction scores and satisfaction category information mapping satisfaction categories to satisfaction scores for the survey type; and a database configured to store the survey metadata, the survey results, and the satisfaction category information, as a layered data model.

5517425

08305802

1. A method of producing a hydrogen absorbing alloy having desired equilibrium characteristics of a plateau region of the hydrogen absorbing alloy between a hydrogen solid solution region (.alpha. phase region) thereof and a metal hydride region (.beta. phase region) thereof, comprising the steps of: (a) producing a hydrogen absorbing alloy; (b) measuring the equilibrium hydrogen pressure and hydrogen content of the plateau region of the alloy; (c) expressing the plateau region by a cumulative distribution function wherein the hydrogen content is taken as frequency and the equilibrium hydrogen pressure or a function thereof is taken as a random variable and determining a plurality of parameters defining the cumulative distribution function by numerical analysis of measured data as to the equilibrium hydrogen pressure and the hydrogen content; (d) outputting the determined parameters; (e) producing another alloy based on the determined parameters; and (f) repeating steps (a)-(d) until a hydrogen absorbing alloy having the desired equilibrium characteristics of the plateau region is obtained.

20050187748

10785925

1. A method of modeling at least one physical property of a mixture of at least two chemical species, the method comprising the computer implemented steps of: a) determining at least one conceptual segment for each of the chemical species, including defining an identity and an equivalent number of each conceptual segment; b) using the determined conceptual segments, computing at least one physical property of the mixture; and c) providing an analysis of the computed physical property, wherein the analysis forms a model of the at least one physical property of the mixture.

20020013776

09873510

1. A method for controlling performance of a machine controlled by at least one control module having an input-output relationship regulated by control parameters, said method comprising the steps of: (a) configuring a first generation of chromosomes coding for the control parameters by preselecting genes constituting the first generation of chromosomes from a selection space used as a gene pool, and activating the machine using the first generation of chromosomes, said genes being defined by coordinates in the selection space; (b) selecting and scoring adapted chromosome(s) by evaluating each chromosome based on signals indicative of performance of the machine; (c) setting a search area in the selection space in accordance with the score(s) under predetermined rules; (d) selecting genes for a subsequent generation of chromosomes within the search area, and operating the machine using the subsequent generation of chromosomes; and (e) repeating steps (b) through (d) while operating the machine until desired performance of the machine is demonstrated.

20050256684

11033767

1. A method for optimization, comprising the steps of: (a) providing an initial population or a data set with a plurality of members respectively represented by parameter sets; (b) applying one or a plurality of fitness functions to evaluate the quality of the members of the population; (c) generating offspring of the population by means of a stochastic model using information from all members of the population; (d) applying one or a plurality of fitness functions to evaluate the quality of the offspring with respect to the underlying problem of the optimization; (e) selecting offspring, and (f) repeating steps (c) through (e) until the quality reaches a threshold value.

6092065

09023758

1. A program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform method steps for grouping of character sequences, said method steps comprising: identifying a sequence of characters; identifying a set of internal repeats in said sequence of characters by: identifying a set of proper templates; identifying a first set of patterns based on said set of proper templates and said sequence of characters, wherein each pattern within said first set of patterns is contained within said sequence of characters; and combining patterns within said first set of patterns to form a second set of patterns, wherein each pattern within said second set of patterns is contained within said sequence of characters; for at least one internal repeat belonging to said set of internal repeats, determining if said at least one internal repeat corresponds to a group of character sequences; upon determining that said at least one internal repeat corresponds to a group of character sequences, storing in persistent storage first data that identifies said sequence of characters and second data that associates said sequence of characters with said group of character sequences.

8140515

12607584

1. A computer-implemented method for building a user profile of a user, the method comprising: labeling and storing user registration information in a database as a set of demographic nouns; analyzing, with a computing device, author-generated classification information regarding at least one document of a set of documents and assigning a set of first taxonomic nouns to characterize the user based upon the author-generated classification information; examining, with a computing device, a user-generated tag from a client computer and characterizing the user of at least one document of the set of documents and assigning a set of second taxonomic nouns to characterize the user based upon the user-generated tag characterization; identifying, with a computing device, a method by which the user accessed at least one document of the set of documents from a content provider and assigning a set of third taxonomic nouns to characterize the user based upon the method of access; evaluating, with a computing device, attributes that are related to the method of access and assigning a set of fourth taxonomic nouns to characterize the user based upon the attributes related to the method of access; processing, with a computing device, at least one document of the set of documents to extract a set of fifth taxonomic nouns to characterize the user; aggregating, with a computing device, the set of first taxonomic nouns, the set of second taxonomic nouns, the set of third taxonomic nouns, the set of fourth taxonomic nouns, and the set of fifth taxonomic nouns into a composite set of taxonomic nouns; building, with a computing device, a user profile based upon the composite set of taxonomic nouns, the author-generated classification information, and at least one of the demographic nouns; comparing, with a computing device, the composite set of taxonomic nouns with taxonomic nouns associated with a plurality of other user profiles corresponding to a plurality of other users; and modifying, with a computing device, the user profile based on the comparison.

20170200447

15469312

1. A method for generating a plurality of language models, the method comprising acts of: (A) obtaining language data comprising training data and associated values for one or more metadata attributes, the language data comprising a plurality of instances of language data, an instance of language data comprising an instance of training data and one or more metadata attribute values associated with the instance of training data; (B) identifying, by processing the language data using at least one processor, a set of one or more of the metadata attributes to use for clustering the instances of training data into a plurality of clusters; (C) clustering the training data instances based on their respective values for the identified set of metadata attributes into the plurality of clusters; and (D) generating a language model for each of the plurality of clusters.

20030212584

10140585

1. In an enterprise strategy management system, a strategy alignment framework comprising: a first set of strategic elements having a first type; a second set of strategic elements having a second type; and an alignment matrix having a plurality of intersecting rows and columns, each row having a corresponding strategic element of the first type and each column having a corresponding strategic element of the second type, wherein a box is formed at the intersection of each row and column, each box providing a graphical representation of a relationship between the corresponding strategic element of the first type and the corresponding strategic element of the second type.

20150243026

14433765

1. An image data processor, comprising: a structural image data processor that employs a multi-structure atlas to segment a region of interest from structural image data which includes tissue of interest and that segments the tissue of interests from the region of interest, wherein the structure is rib cage and the tissue of interest is lung lobe, and the multi-structure atlas is a rib cage/lung lobe atlas that includes a mapping that maps one or more ribs to a location of a boundary of a lung lobe, and the mapping includes a lung lobe region of interest, in a form of a least one of a point cloud on a surface of the lung or a 3D sheet across lung, through the rib case/lung lobe atlas; and a functional image data processor that identifies the tissue of interest in functional image data based on the segmented tissue of interest.

9442698

14681153

1. A method comprising: obtaining an indication of a first Unified Modeling Language (UML) model element of a first model element type which is to be migrated to a second UML model element of a second model element type; and automatically migrating the first UML model element of the first model element type to the second UML model element of the second model element type, wherein the automatically migrating migrates a relationship between the first UML model element of the first model element type and a related UML model element, of a third model element type, to a relationship between the second UML model element of the second model element type and the related UML model element, and wherein the automatically migrating comprises: obtaining indications of relationship types that are deemed valid or invalid as between model element types, including as between the second model element type and the third model element type, the relationship types being for relationships between UML model elements, the relationships having at least one directional property associated therewith; checking the relationship between the first UML model element and the related UML model element to identify a relationship type of the relationship between the first UML model element and the related UML model element; checking the obtained indications to determine whether the identified relationship type of the relationship between the first UML model element and the related UML model element is indicated to be a valid relationship type that may exist as between the second UML model element of the second model element type and the related UML model element of the third model element type, wherein the checking the obtained indications checks one or more data structures comprising the indications and determines that the identified relationship type is an invalid type of relationship as between the second model element type and the third model element type; based on determining that the identified relationship type is an invalid type of relationship as between the second model element type and the third model element type, identifying a replacement relationship type that is indicated to be a valid type of relationship that may exist as between the second model element type and the third model element type; obtaining the identified replacement relationship type; and automatically creating, with the identified replacement relationship type, the relationship between the second UML model element of the second model element type and the related UML model element to apply the identified replacement relationship type to the relationship between the second UML model element of the second model element type and the related UML model element.

9026529

12765848

1. A method for frame-based search, performed by computing hardware and programmable memory, comprising the following steps: receiving a first rule, for producing an instance in accordance with a first frame, wherein the first frame comprises a first input role and a first output role; receiving a second rule, for producing an instance in accordance with a second frame, wherein the second frame comprises a second input role and a second output role; receiving a first source corpus; identifying first and second units of natural language from, respectively, first and second snippets of the first source corpus; producing a first instance, from the first unit, by application of the first rule, wherein the first instance has a first input value assigned to its first input role and a first output value assigned to its first output role; producing a second instance, from the second unit, by application of the second rule, wherein the second instance has a second input value assigned to its second input role and a second output value assigned to its second output role; determining the first and second instances represent a same third frame; determining a same third value as representative of the first and second input values; determining a same fourth value as representative of the first and second output values; producing, as a result of computing hardware and programmable memory, a first result that contains a first result-value and a first result-base, wherein the first result-value is the fourth value and the first result-base contains the first and second snippets; determining, as a result of computing hardware and programmable memory, a member-level demographic characteristic for each member of the first result-base; determining, as a result of computing hardware and programmable memory, a first demographic characteristic, for the first result, by combining the member- level demographic characteristics; and displaying, to a user as part of a search result, the first demographic characteristic as a demographic determined for the first result-value.

8719742

13400521

1. A method for generating an abstract model of a circuit, the method comprising: determining a series of transactions of a protocol associated with low-level simulation data from a simulation of the circuit; determining transaction-level circuit simulation data based at least in part on the series of transactions of the protocol; using one or more computers or processors, performing causality analysis on the transaction-level circuit simulation data to determine an association between input signals and output signals, the causality analysis comprising defining a set of causality characters based on the association between the input and output signals, wherein a causality character represents an association between an event and an associated output, and statistically reducing the set of causality characters; using the one or more computers or processors, producing a causality output based on the causality analysis; and using the one or more computers or processors, learning the circuit behavior using the causality output in order to produce the abstract model including a system of equations that approximate the circuit behavior.

8701002

13090148

1. A method for generating and displaying video data representing a workflow history of an electronic document, the method comprising: capturing a plurality of frames of video data, wherein each frame of the video data corresponds to a different screenshot of an application window associated with an application that is configured to modify the document; accessing a plurality of data objects stored in a memory, wherein each data object stores information relating to a different event generated by the application; associating each data object in the plurality of data objects with at least one frame of the video data, wherein, for each data object, the at least one frame of video data was captured at substantially the same time as when the event associated with the data object was generated by the application; dividing the document into n×m cells, wherein each cell represents two or more pixels of the document; adding to a slot in an n×m array a first pointer to a first data object included in the plurality of data objects, wherein the first pointer in the n×m array associates the first data object with at least a first cell that was changed in the document as a result of a first event generated by the application; and causing the plurality of frames to be displayed in a video playback window.

20100246442

12744422

1. A method comprising: determining ( 110 ) one or more quiet-period parameters of a device, broadcasting ( 125 ) the quiet-period parameters, receiving ( 130 ) one or more other quiet-period parameters from an other device, setting ( 155 , 160 ) at least one of the quiet-period parameters of the device equal to at least one of the other quiet-period parameters, if ( 150 , 160 ) a sensing demand of the other device is greater than a sensing rate of the device, repeating the broadcasting ( 125 ), receiving ( 130 ), and setting ( 155 , 160 ), and avoiding ( 180 ) transmission from the device during a quiet-period corresponding to the quiet-period parameters of the device, wherein the sensing demand of the other device is based on one or more of the quiet-period parameters of the other device, and the sensing rate of the device is based on one or more of the quiet-period parameters of the device.

8606815

12331271

1. A computer-implemented method for systematically analyzing an electronic text, comprising: receiving by a computer the electronic text from a plurality of sources; determining an at least one term of interest to be identified in the electronic text; determining an at least one term of interest to be identified in the electronic text; identifying by the computer a plurality of locations within the electronic text including the at least one term of interest; for each location within a plurality of locations, creating by the computer a snippet from a text segment around the at least one term of interest at the location within the electronic text; creating by the computer multiple taxonomies for the at least one term of interest from the snippets, wherein the taxonomies include an at least one category, the at least one category including a sentiment based taxonomy; and determining by the computer associations between categories of a different taxonomies of the multiple taxonomies by determining: co-occurrences between the multiple taxonomies; and significance of co-occurrences between the multiple taxonomies, wherein the determining the co-occurrences further comprises: determining co-occurrences between a category of a single taxonomy and the at least one term of interest to determine significance of the at least one term of interest; and sorting the at least one term of interest by significance; and wherein at least one of the taxonomies is a time based taxonomy that is based on the creation date of the electronic text, the time based taxonomy generated by: crawling sources of electronic text to extract the creation dates; attaching an extracted creation date to a respective snippet to generate a dated snippet; and organizing the dated snippets into chronologically contiguous categories, wherein the sentiment based taxonomy is determined by: creating a list of positive, negative and neutral terms indicative of different sentiments, respectively; determining the level of sentiment corresponding to the at least one term generated from a respective snippet based on an assigned value; normalizing the values to generate at least one term having a sentiment score corresponding thereto, the sentiment score including at least one of a positive sentiment score and a negative sentiment score; and sorting snippets of the electronic text based on a calculated sentiment score differential between the at least one positive sentiment score and the at least one negative sentiment score.

20040249612

10453610

1. An apparatus for monitoring high impedance failures in system interconnects, comprising: monitoring circuitry located on a chip, comprising: a resistance continuity monitoring circuit (RCMC), wherein the RCMC measures the resistance of a connection of a representative set of pins on the chip with a circuit board, outputting an analog measured resistance data; a signal path connecting the representative set of pins to the RCMC; and a system interface for connecting the RCMC with other system components; wherein the monitoring circuitry converts the analog measured resistance data to digital resistance data and displays the digital resistance data on an output device.

20030059106

10183821

1. A method for classifying an object in image data, comprising the steps of: detecting an object in said image data; and classifying said object using a hierarchical object classification scheme.

20140025188

14039164

1. A method for customizing a performance device, comprising: providing a baseline model defining modifications to a base device necessary to obtain a master device, including at least one modification calculated to improve performance of the master device over the base device; receiving at least one change to a parameter of the baseline model from a customer; responsive to the at least one changed parameter, modifying a plurality of other parameters in the baseline model to obtain a customized device having the improved performance of the master device; and generating manufacturing instructions, the instructions when executed by an automated production machine, causes the production machine to manufacture the customized device.

8260603

12241948

1. A method for scaling a prediction model of resource usage of an application in a virtual environment, comprising: providing a predetermined set of benchmarks, wherein the predetermined set of benchmarks includes at least one of: a computation-intensive workload, a network-intensive workload, and a disk-intensive workload; executing the predetermined set of benchmarks in a first native hardware system in which the application natively resides; executing the predetermined set of benchmarks in the virtual environment; generating at least one first prediction model that predicts a resource usage of the application running in the virtual environment based on the executions of the predetermined set of benchmarks in the first native hardware system and the virtual environment; determining a resource usage of the application running in a second native hardware system in which the application also natively resides; generating at least one second prediction model based on a scaling of a portion of the at least one first prediction model by a predetermined constant, while the remaining portion of the at least one first prediction model remains the same; and predicting a resource usage of the application running in the virtual environment based on the resource usage of the application running in the second native hardware system and the at least one second prediction model.

9367654

14846975

1. A method for back-end-of-line variation modeling, comprising: defining a bounding box for a device within a design layout of a semiconductor arrangement, wherein a size of the bounding box is a function of patterns surrounding the device; determining a back-end-of-line variation parameter for the bounding box; applying, using a computing device, the back-end-of-line variation parameter as a back-end-of-line constraint for simulation of the design layout; and modifying a physical feature of the design layout based upon a result of the simulation, wherein the design layout is implemented in fabrication of the device.

20170209101

15481347

1. A method for processing data from a continuous glucose sensor, the method comprising: monitoring a data stream generated by a working electrode of a continuous glucose sensor, the data stream comprising a glucose sensor data point; monitoring an output of a counter electrode of the continuous glucose sensor; detecting a signal artifact associated with the glucose sensor data point; classifying the signal artifact based on the monitoring of the output of the counter electrode; selectively applying one or more of a plurality of signal estimation algorithms based on the classification to generate an estimated sensor data point; and replacing the sensor data point with the estimated sensor data point.

10093897

14072025

1. A method for differentiating mammalian induced pluripotent stem (iPS) cells into neural progenitors of dorsal forebrain identity comprising the steps of: a) plating undifferentiated mammalian iPS cells onto a substrate which allows adherence of cells thereto; and b) culturing the mammalian iPS cells of a) which have adhered to said substrate in a medium permissive to differentiation of the mammalian iPS cells comprising exposing the cells to an antagonist of the sonic hedgehog (SHH) signaling pathway during at least part of the culturing step, whereby neural progenitors of dorsal forebrain activity are obtained.

20030195877

10404992

1. A method of assisting users in locating items that are arranged within a database system by category, the method comprising: monitoring user actions performed with respect to specific items in the database system to generate item usage data; calculating item scores for specific items in the database system, wherein an item score for an item is dependent upon the item usage data associated with that item; receiving a search query specified by a user; identifying, within each of multiple categories of the database system, items that are responsive to the search query (“responsive items”); for each of the multiple categories, calculating a respective category score based at least in-part on the item scores of responsive items in that category; and determining an order in which to present the multiple categories to the user such that the order is dependent upon the category scores.

20030003873

09896241

1. In a communication system having a first communication station for communicating a communication signal to a second communication station, the communication signal weighted at the first communication station with a first antenna weight for communication to the second communication station by way of a first channel path and weighted at the first communication station with a second antenna weight for communication to the second communication station by way of a second channel path, an improvement of apparatus for verifying closed-loop values indicative of the first antenna weight and the second antenna weight, said apparatus comprising: a sequence estimator coupled to receive indications of the communication signal, once received at the second communication station, said sequence estimator for estimating estimated values of the first antenna weight and of the second antenna weight by which to weight the communication signal, the estimated values formed by said sequence estimator selected responsive to both a memory component and a current component, the estimated values verifying the closed-loop values indicative of the first antenna weight and the second antenna weight.

7565585

10707797

1. An integrated redundancy architecture for providing BIST redundancy allocation to an embedded memory system, the integrated redundancy architecture comprising: a BIST for identifying and transmitting row and column addresses of failed memory cells of embedded memory; a first memory element for storing, as to-be-repaired row addresses, ones of the row addresses assigned by said BIST for repair by row redundancy; a second memory element for storing, as to-be-repaired column addresses, ones of the column addresses assigned by said BIST for repair by column redundancy; a third memory element for accumulating ones of the row and column addresses of the failed memory cells not already contained in said first and second memory elements and for assigning each of the row and column addresses accumulated in said third memory element a particular weight value based on the number of the row and column addresses already accumulated in said third memory element and the relative locations within the memory system of the row and column addresses accumulated in said third memory element; and a means for: determining whether the row address of a failed memory cell matches any of the to-be-repaired row addresses stored in the first memory element; determining whether the column address of the failed memory cell matches any of the to-be-repaired column addresses stored in the second memory element; if the row address of the failed memory cell does not match any of the to-be-repaired row addresses stored in the first memory element and the column address of the failed memory cell does not match any of the to-be-repaired column addresses stored in the second memory element, storing the row and column addresses of the failed memory cell in the third memory element; if either the row address of the failed memory cell matches one of the to-be-repaired row addresses stored in the first memory element or the column address of the failed memory cell matches one of the to-be-repaired column addresses stored in the second memory element, or both, then: determining whether the row address of another failed memory cell matches any of the to-be-repaired row addresses stored in the first memory element; and determining whether the column address of the another failed memory cell matches any of the to-be-repaired column addresses stored in the second memory element.

9058748

13215462

1. A training apparatus comprising: a training sample storage unit that stores therein a plurality of training samples that are classified into C (C≧3) categories, wherein categories of the plurality of categories are different from each other; a selecting unit that performs, N (N≧2) times, a selection process of selecting a plurality of groups each including one or more training samples from the training sample storage unit, the one or more training samples included in each of the plurality of groups being selected at random; and a training unit that trains, each time the selection process is performed, a classifier Fi(x) for classifying the plurality of groups selected in the selection process, where 1≦i≦N, and generates an evaluation metric, wherein the evaluation metric is an array of classifiers F1(x), F2(x), through FN(x), the evaluation metric outputs a feature value v(X) for an input data, the feature value v(X) is an array of elements of an evaluation si, the evaluation value si is an output of the classifier F i (x) for the input data, the evaluation si is a vector, and the feature value v(X) indicates to which category the input data belongs among the C categories and one or more non-C categories.

20090125463

12270721

1. A system for generating a plurality of models for classifying input data into a plurality of classes on the basis of training data in which elements are previously classified into the plurality of classes, the system comprising: a sampling unit for sampling, from the training data, a plurality of datasets each including a predetermined number of elements classified into a minority class and a corresponding number of elements classified into a majority class, the corresponding number being determined in accordance with the predetermined number; and a learning unit for learning each of the plurality of models for classifying the input data into the plurality of classes, by using a machine learning technique on the basis of the plurality of sampled datasets.

20050136944

10999191

1. A method for estimating a target device's location, the method comprising: maintaining a probabilistic model for a plurality of sample points, each sample point comprising a sample location and an expected distribution of signal values at that sample point; making a sequence of observations o n , n=1. .. N, of signal values wherein each observation corresponds to a respective location q n along the target device's path, wherein the sequence of observations and the respective location constitute a hidden Markov model; estimating the target device's location q t based on the probabilistic model and the sequence of observations, wherein the sequence of observations comprises one or more future observations o t+m for which m is a positive integer, such that t+m<N.

10097000

14823531

1. A method of analyzing the stability of a networked power system, comprising: storing a reduced state model of the power system in memory of a computer and integrating over the model to derive a fault-on trajectory; storing in memory of the computer a numerical energy function for a post-fault condition of the power system; using the computer to compute an exit point at which a projected fault-on trajectory reaches a first local maximum of potential energy; using the exit point as an initial point and then using the computer to solve a post-fault reduced-state model; using the computer to determine a controlling unstable equilibrium point (CUEP) with respect to the projected fault-on trajectory of the networked power system by applying a homotopy algorithm that uses the exit point as an initial condition; solving the numerical energy function at the CUEP to determine a critical energy value; calculating a value of the numerical energy function at a time of fault clearance using an initial condition of the post-fault trajectory; and using the computer to test if the value of the numerical energy function is less than the critical energy value: (a) if so, reporting that the initial condition lies within a stability boundary; and (b) if not, reporting that the initial condition may be unstable.

20040153180

10402948

1. A method of predicting a number of defective electrode array panels that will result during a manufacturing run in a liquid crystal display (LCD) manufacturing setup, wherein a plurality of electrode array panels are manufactured on a common substrate during the manufacturing run, comprising: determining a number of defects on the common substrate; and predicting a number of defective electrode panels based on the number of defects on the common substrate and a quantity of electrode array panels manufactured on the common substrate.

20120137267

12955360

1. A computer program product comprising a machine-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising: generating a runtime model of a business object, the runtime model comprising a plurality of structural entities and a plurality of functional entities; instantiating a simulation runtime model of the business object, the simulation runtime model comprising a plurality of pseudo-structural entities and a plurality of pseudo-functional entities; selecting, during the simulation runtime model, a predetermined business object service of the business object and determining at least one parameter of the predetermined business object service; replacing, during the simulation runtime model, the plurality of functional entities of the runtime model with the plurality of pseudo-functional entities of the simulation runtime model; and executing, by the at least one processor, during the simulation runtime model, the simulation runtime model using the plurality of pseudo-functional entities.

20120300991

13560609

1. A method performed by a software process executing on a computer system, the method comprising: accessing a digital image comprising a plurality of pixels; determining, by a hardware processor, whether one or more pixels bounding a first rectangular sub-region of a predetermined size within the digital image satisfy a specified criterion; if a predetermined percentage of only the bounding pixels satisfy the specified criterion, assuming that all pixels within the first rectangular sub-region also satisfy the specified criterion; and selectively performing, by the hardware processor, an image analysis algorithm on the digital image using the assumption that all pixels within the first rectangular sub-region also satisfy the specified criterion.

7493602

11119553

1. A method of analyzing multi-language software programs, said method comprising the step of: using a computer processor coupled to memory to execute the step of: inputting a program containing elements written in a plurality of languages; inputting a rule set specifying allowable behaviors of a correct program; transforming the input program, wherein said transforming comprises preserving sufficient data and control flow information relating to the input program in a predetermined amount and to a predetermined degree of precision; and wherein the transforming includes translating the program to a target language as an output program; detecting in the input program any violation relating to the rule set, wherein said detecting comprises employing the target language in detecting a violation relating to the rule set; ensuring that the input program avoids any violation relating to the rule set; mapping back to an original source code any violation relating to the rule set; wherein at least a portion of the input program is written in C programming language, and the portion is translated into Java programming language, and further wherein the translating step comprises: implementing function pointers using virtual method and anonymous inner classes in the output program, said pointers being mapped to arrays of length one in Java programming language, said implementing function pointers comprises: mapping each function pointer type to an F n class, the F n class being constructed with a virtual method named idr C all overloaded multiple times, wherein for each signature of different length used at an indirect call site anywhere in the software program idr C all is overloaded one more time; extending an F n class anonymously whenever an address of a function is being taken; overriding a virtual member method with matching arguments to now branch to a destination function, and relinking indirect call sites to transit via a virtual function; and implementing goto translation in a way that does not modify control and data flow of the input program; wherein Basic types in C programming language are mapped directly to the same types in Java programming language, Structures and unions are mapped to classes with the corresponding fields set to public, and Functions become public methods of a global class representing an entire file being translated; and employing the target language to verify that said rules are not violated.

20120114262

13091137

1. An image correction method, for outputting a corrected image according to an image to be corrected, the corrected image comprising a plurality of corrected pixel blocks, the image correction method performing a plurality of pixel value computations, each pixel value computation being utilized for generating a pixel value of each corrected pixel within a corrected pixel block, and comprising: establishing a coordinate transformation relation between the image to be corrected and the corrected image, such that a first coordinate value of each corrected pixel within the corrected pixel block corresponds to a second coordinate value within the image to be corrected; according to the coordinate transformation relation, determining a pixel block to be corrected corresponding to the corrected pixel block, and selecting a pixel block to be processed which comprises at least the pixel block to be corrected from the image to be corrected, wherein the pixel block to be processed has a plurality of rows of pixels to be processed; temporarily storing a pixel value of each pixel to be processed into a memory device having a plurality of memory banks, wherein pixel values of pixels to be processed that are located at different rows are temporarily stored into different memory banks of the memory device, respectively; and utilizing the second coordinate value corresponding to the corrected pixel for determining a plurality of specific pixels to be processed that correspond to the corrected pixel, reading a plurality of pixels values of the specific pixels to be processed from the memory device, and generating a pixel value of the corrected pixel by performing an interpolation computation upon the pixels values of the specific pixels; wherein the pixel values of the specific pixels to be processed are temporarily stored in different memory banks.

8600908

12926384

1. A carrier selection method for a logistics network, the logistics network comprising a plurality of nodes and a plurality of minimal paths, wherein the nodes include a start and a terminal, and the minimal paths extend from the start to the terminal of respective said nodes, each of the minimal paths being formed by a plurality of routes without a loop, and each of the routes extending between two of the nodes, said method comprising the steps of: utilizing a computer to execute carrier selection software having a virtual network that simulates a logistics network, the computer including an input unit, an operating unit and an output unit; providing a plurality of carriers in the logistics network; choosing one of the carriers for each routes in the logistics network to form one carrier set, so as to generate a plurality of carrier sets; the input unit receiving a demand for transport from the start to the terminal in the logistics network by a user input to the carrier selection software; defining the demand distributed among and transmitted through the minimal paths; defining each of the carriers as having a plurality of cargo capacities and a maximal capacity; defining a flow vector having a flow of each of minimal paths so that each of the routes has a traveled flow, wherein the sum of the flows of the minimal paths is equal to the demand; the operating unit selecting the flow vector for satisfying a first constraint, wherein the first constraint is defined that the flow of each of minimal paths is smaller than or equal to the maximal capacity; the operating unit transforming each of the flow vectors satisfying the first constraint into a corresponding capacity vector, wherein the corresponding capacity vector has a needed capacity of each of the routes; the operating unit selecting the capacity vector for satisfying a second constraint, wherein the second constraint is defined that the needed capacity is equal to a minimal cargo capacity among the cargo capacities of the carriers, wherein the cargo capacities of the carriers are more than or equal to the traveled flow for each of the routes, so that the capacity vector satisfying the second constraint is defined as a lower vector; the operating unit calculating a probability that each of the capacity vectors is larger than or equal to the lower vector, and defining the probability as the network reliability; the operating unit executing a genetic algorithm with the carrier sets as chromosomes in the genetic algorithm to search for an optimal carrier set among the carrier sets, wherein the optimal carrier set has a maximal network reliability; and displaying the optimal carrier set on the output unit.

8096811

10998384

1. A computer implemented process for evaluating user interactions with a dynamic simulation of a system portraying at least one system state and responsive to user queries and interventions comprising the steps of: a) assigning a simulation to at least one user; b) using a computer to generate a simulated system comprising a system age and at least one system state affecting said system; c) using a computer to dynamically generate at least one criterion, said criterion associated with at least one of said system state, a query, a query result, and an intervention, when a change occurs in said at least one system state affecting said system by: i) identifying an inference program; ii) providing at least one input datum relating to said change in said at least one system state affecting said system, said at least one input datum defining the state of an input node in said inference program; iii) generating at least one criterion as an inference from said at least one input datum; said criterion comprising: a) a selected user activity to monitor, said activity comprising starting an intervention to improve the present or future state of the simulated system; b) a system age range in which to monitor said user activity, said age range comprising a start age and a stop age, wherein said start age is calculated by adding said system age to a relative start time, and said stop age is calculated by adding said system age to a relative stop time; c) a classification of said user activity as desirable or not desirable; and d) a weight value selected from a weight value set having at least one weight value; d) accepting at least one user action comprised of said selected user activity and an age of the simulated system when the selected user activity occurs; e) evaluating said at least one accepted user action to determine if at least one of said accepted user action and its consequences require generation of additional criterion and repeating steps c and d if additional criterion require generation; f) determining a status of said at least one criterion dynamically generated in step c; and, g) generating at least one performance description based on at least one of: desirable actions performed; undesirable actions avoided; desirable actions omitted, and undesirable actions committed.

8908942

13279195

1. A method for reconstructing an image, said method comprising: receiving raw image data acquired from an image acquisition system; shaping a filtered backprojection filter to emulate a specified iteration result of an iterative algorithm reconstruction method; filtering said received image data utilizing said shaped filtered backprojection filter; backprojecting said received image data; and generating a reconstructed image using the filtered and backprojected image data.

20130046797

13660940

1. A method comprising: parsing patent data to generate a set of nodes; selecting at least one node of the set of nodes; determining initial links from meta data associated with the patent data for the at least one node; creating links among the set of nodes based on the metadata; identifying a set of seed nodes; determining a community structure for the set of seed nodes, the community structure including a plurality of communities; and assigning concepts to the plurality of communities.

9094665

14216923

1. A digital watermarking based method for objectively evaluating quality of stereo image, comprising following steps of: {circle around (1)}-1 at a transmitting terminal, denoting an original undistorted stereo image as S org , denoting a left-view image of S org as L org and a right-view image of S org as R org ; dividing L org and R org respectively into M × N 8 × 8 image blocks which are non-overlapped with each other and have a size of 8×8, wherein M is a width of L org or R org , N is a height of L org or R org ; {circle around (1)}-2 processing discrete cosine transform (DCT) on each image block in L org and R org , so as to obtain a DCT coefficient matrix of each image block in L org and R org ; {circle around (1)}-3 processing coefficient reorganization on all DTC coefficients in the DCT coefficient matrix of all of the image blocks in L org and R org , so as to obtain 10 coefficient reorganized matrixes which are different from each other and respectively corresponding to L org and R org , denoting an n′th coefficient reorganized matrix corresponding to L org as S L,org n′ , denoting an n′th coefficient reorganized matrix corresponding to R org as S R,org n′ , wherein DCT coefficients having a same coordinate position in the DCT coefficient matrixes of all the image blocks in L org are located in a same coefficient reorganized matrix, and DCT coefficients having a same coordinate position in the DCT coefficient matrixes of all the image blocks in R org are located in a same coefficient reorganized matrix, wherein 1≦n′≦10; {circle around (1)}-4 calculating an absolute value matrix of a difference value of each coefficient reorganized matrix corresponding to L org and each coefficient reorganized matrix corresponding to R org , denoting an absolute value matrix of a difference value of an n′ th coefficient reorganized matrix S L,org n′ corresponding to L org and an n′ th coefficient reorganized matrix S R,org n′ corresponding to R org as D org n′ , denoting an l th coefficient of D org n′ as D org n′ (l), wherein D org n′ (l)=|S L,org n′ (l)−S R,org n′ (l)|; calculating an average value and a standard deviation of the absolute value matrix of the difference value of each coefficient reorganized matrix corresponding to L org and each coefficient reorganized matrix corresponding to R org , respectively denoting the average value and the standard deviation of D org n′ as μ r n′ and σ r n′ , wherein μ r n ′ = 1 L n ′ ⁢ ∑ l = 1 L n ′ ⁢ ⁢ D org n ′ ⁡ ( l ) , σ r n ′ = 1 L n ′ - 1 ⁢ ∑ l = 1 L n ′ ⁢ ⁢ ( D org n ′ ⁡ ( l ) - μ r n ′ ) 2 ; wherein S L,org n′ (l) represents an l th DCT coefficient in S L,org n′ , S R,org n′ (l) represents an l th DCT coefficient in S R,org n′ , wherein “∥” is an absolute value sign, 1≦l≦L n′ , wherein L n′ represents a total number of DCT coefficients in S L,org n′ or S R,org n′ ; {circle around (1)}-5 respectively processing filtering on all of the DCT coefficients in the DCT coefficient matrix of each image block in L org and R org utilizing Watson sensitivity operator, so as to obtain a filtered DCT coefficient matrix of each image block in L org and R org ; {circle around (1)}-6 respectively processing coefficient reorganization on the DCT coefficients of the filtered DCT coefficient matrix of all the image blocks in L org and R org utilizing the same way of coefficient reorganization as thereof in the step {circle around (1)}-3, so as to obtain 10 filtered coefficient reorganized matrixes which are respectively corresponding to L org and R org , and different from each other, denoting an n′th filtered coefficient reorganized matrix corresponding to L org as S L,org n′ , denoting an n′th filtered coefficient reorganized matrix corresponding to R org as S R,org n′ , wherein filtered DCT coefficients having a same coordinate position in the filtered DCT coefficient matrixes of all the image blocks in L org are located in a same filtered coefficient reorganized matrix, and filtered DCT coefficients having a same coordinate position in the filtered DCT coefficient matrixes of all the image blocks in R org are located in a same filtered coefficient reorganized matrix, wherein 1≦n≦10; {circle around (1)}-7 according to all of the filtered DCT coefficients in the 10 filtered coefficient reorganized matrixes respectively corresponding to L org and R org , calculating a first sensitivity threshold, which is denoted as T1, wherein T ⁢ ⁢ 1 = α × ∑ k = 1 10 ⁢ ⁢ ∑ l = 1 L k ⁢ ⁢  S org _ k ⁡ ( l )  / ∑ k = 1 10 ⁢ ⁢ L k , wherein α is a sensitivity threshold regulatory factor, 1≦k≦10, 1≦l≦L k , wherein L k represents a total number of filtered DCT coefficients of a k th filtered coefficient reorganized matrix in the 10 filtered coefficient reorganized matrixes respectively corresponding to L org or R org , wherein S org k (l) represents an l th filtered DCT coefficient of a k th filtered coefficient reorganized matrix in the 10 filtered coefficient reorganized matrixes, wherein “∥” is an absolute value sign; {circle around (1)}-8 selecting filtered DCT coefficients in each filtered coefficient reorganized matrix respectively corresponding to L org and R org which are greater than the first sensitivity threshold T1 to be determined as visual sensitivity coefficients, calculating proportions of visual sensitivity coefficients in each filtered coefficient reorganized matrix respectively corresponding to L org and R org , denoting a proportion of visual sensitivity coefficients in an n′ th filtered coefficient reorganized matrix S L,org n′ corresponding to L org as P r L (n′), wherein P r L (n′)=R T L (n′)/R L (n′), denoting a proportion of visual sensitivity coefficients in an n′th filtered coefficient reorganized matrix S R,org n′ corresponding to R org as P r R (n′), wherein P r R (n′)=R T R (n′)/R R (n′), wherein R T L (n′) represents a number of visual sensitivity coefficients in the n′ th filtered coefficient reorganized matrix S L,org n′ corresponding to L org , R L (n′) represents a total number of filtered DCT coefficients in the n′ th filtered coefficient reorganized matrix S L,org n′ corresponding to L org , R T R (n′) represents a number of visual sensitivity coefficients in the n′th filtered coefficient reorganized matrix S R,org n′ corresponding to R org , and R R (n′) represents a total number of filtered DCT coefficients in the n′th filtered coefficient reorganized matrix S R,org n′ corresponding to R org ; {circle around (1)}-9 processing quantization coding on the average value and the standard deviation of the absolute value matrix of the difference value of each coefficient reorganized matrix corresponding to L org and each coefficient reorganized matrix corresponding to R org for serving as a first digital watermarking information; processing quantization coding on a proportion of the visual sensitivity coefficients in each filtered coefficient reorganized matrix corresponding to L org for serving as a second digital watermarking information; processing quantization coding on a proportion of the visual sensitivity coefficients in each filtered coefficient reorganized matrix corresponding to R org for serving as a third digital watermarking information; utilizing a dither modulation digital watermarking embedding method, respectively embedding the first digital watermarking information into a fourth coefficient reorganized matrix S L,org 4 corresponding to L org and a fourth coefficient reorganized matrix S R,org 4 corresponding to R org , respectively embedding the second digital watermarking information into a fifth coefficient reorganized matrix S L,org 5 corresponding to L org and a fifth coefficient reorganized matrix S R,org 5 corresponding to R org , respectively embedding the third digital watermarking information into a sixth coefficient reorganized matrix S L,org 6 corresponding to L org and a sixth coefficient reorganized matrix S R,org 6 corresponding to R org , in such a manner that a stereo image with digital watermarking is obtained; {circle around (1)}-10 sending the stereo image with digital watermarking to a receiving terminal by the transmitting terminal; {circle around (2)}-1 at the receiving terminal, denoting a received distorted stereo image with digital watermarking for evaluating as S dis , S dis is a distorted stereo image of S org , denoting a left-view image of S dis as L dis , denoting a right-view image of S dis as R dis ; dividing L dis and R dis respectively into M × N 8 × 8 image blocks which are non-overlapped with each other and have a size of 8×8, wherein M is a width of L dis and R dis , N is a height of L dis and R dis ; {circle around (2)}-2 processing discrete cosine transform (DCT) on each image block in L dis and R dis , so as to obtain a DCT coefficient matrix of each image block in L dis and R dis ; {circle around (2)}-3 processing coefficient reorganization on all DTC coefficients in the DCT coefficient matrix of all of the image blocks in L dis and R dis , so as to obtain 10 coefficient reorganized matrixes which are different from each other and respectively corresponding to L dis and R dis , denoting an n′th coefficient reorganized matrix corresponding to L dis as S L,dis n′ denoting an n′th coefficient reorganized matrix corresponding to R dis as S R,dis n′ , wherein DCT coefficients having a same coordinate position in the DCT coefficient matrixes of all the image blocks in L dis are located in a same coefficient reorganized matrix, and DCT coefficients having a same coordinate position in the DCT coefficient matrixes of all the image blocks in R dis are located in a same coefficient reorganized matrix, wherein 1≦n′≦10; {circle around (2)}-4 calculating an absolute value matrix of a difference value of each coefficient reorganized matrix corresponding to L dis and each coefficient reorganized matrix corresponding to R dis , denoting an absolute value matrix of a difference value of an n′ th coefficient reorganized matrix S L,dis n′ corresponding to L dis and an n′ th coefficient reorganized matrix S R,dis n′ corresponding to R dis as D dis n′ , denoting an lth DCT coefficient of D dis n′ as D dis n′ (l), wherein D dis n′ (l)=|S L,dis n′ (l)−S R,dis n′ (l)|; calculating an average value and a standard deviation of the absolute value matrix of the difference value of each coefficient reorganized matrix corresponding to L dis and each coefficient reorganized matrix corresponding to R dis , respectively denoting the average value and the standard deviation of D dis n′ as μ d n′ and σ d n′ , wherein μ d n ′ = 1 L n ′ ⁢ ∑ l = 1 L n ′ ⁢ ⁢ D dis n ′ ⁡ ( l ) , σ d n ′ = 1 L n ′ - 1 ⁢ ∑ l = 1 L n ′ ⁢ ⁢ ( D dis n ′ ⁡ ( l ) - μ d n ′ ) 2 ; wherein S L,dis n′ (l) represents an lth DCT coefficient in S L,dis n′ , S R,dis n′ (l) represents an l th DCT coefficient in S R,dis n′ , wherein “∥” is an absolute value sign, 1≦l≦L n′ wherein L n′ represents a total number of DCT coefficients in S L,dis n′ or S R,dis n′ ; {circle around (2)}-5 respectively processing filtering on all of the DCT coefficients in the DCT coefficient matrix of each image block in L dis and R dis utilizing Watson sensitivity operator, so as to obtain a filtered DCT coefficient matrix of each image block in L dis and R dis ; {circle around (2)}-6 respectively processing coefficient reorganization on the DCT coefficients of the filtered DCT coefficient matrix of all the image blocks in L dis and R dis utilizing the same way of coefficient reorganization as thereof in the step {circle around (2)}-3, so as to obtain 10 filtered coefficient reorganized matrixes which are respectively corresponding to L dis and R dis , and different from each other, denoting an n′th filtered coefficient reorganized matrix corresponding to L dis as S L,dis n′ , denoting an n′th filtered coefficient reorganized matrix corresponding to R dis as S R,dis n′ , wherein filtered DCT coefficients having a same coordinate position in the filtered DCT coefficient matrixes of all the image blocks in L dis are located in a same filtered coefficient reorganized matrix, and filtered DCT coefficients having a same coordinate position in the filtered DCT coefficient matrixes of all the image blocks in R dis are located in a same filtered coefficient reorganized matrix, wherein 1≦n≦10; {circle around (2)}-7 according to all of the filtered DCT coefficients in the 10 filtered coefficient reorganized matrixes respectively corresponding to L dis and R dis , calculating a second sensitivity threshold, which is denoted as T2, wherein T ⁢ ⁢ 2 = α × ∑ k = 1 10 ⁢ ⁢ ∑ l = 1 L k ⁢ ⁢  S dis _ k ⁡ ( l )  / ∑ k = 1 10 ⁢ ⁢ L k , wherein α is a sensitivity threshold regulatory factor, 1≦k≦10, 1≦l≦L k , wherein L k represents a total number of filtered DCT coefficients of a k th filtered coefficient reorganized matrix in the 10 filtered coefficient reorganized matrixes respectively corresponding to L dis , or R dis , wherein S dis k (l) represents an l th filtered DCT coefficient of a k th filtered coefficient reorganized matrix in the 10 filtered coefficient reorganized matrixes respectively corresponding to L dis or R dis , wherein “∥” is an absolute value sign; {circle around (2)}-8 selecting filtered DCT coefficients in each filtered coefficient reorganized matrix respectively corresponding to L dis and R dis which are greater than the second sensitivity threshold T2 to be determined as visual sensitivity coefficients, calculating proportions of visual sensitivity coefficients in each filtered coefficient reorganized matrix respectively corresponding to L dis and R dis , denoting a proportion of visual sensitivity coefficients in an n′ th filtered coefficient reorganized matrix S L,dis n′ corresponding to L dis as P d L (n′), wherein P d L (n′)=D T L (n′)/D L (n′), denoting a proportion of visual sensitivity coefficients in an n′th filtered coefficient reorganized matrix S R,dis n′ corresponding to R dis as P d R (n′), wherein P d R (n′)=D T R (n′)/D R (n′), wherein D T L (n′) represents a number of visual sensitivity coefficients in the n′th filtered coefficient reorganized matrix S L,dis n′ corresponding to L dis , D L (n′) represents a total number of filtered DCT coefficients in the n′th filtered coefficient reorganized matrix S L,dis n′ corresponding to L dis , D T R (n′) represents a number of visual sensitivity coefficients in the n′ th filtered coefficient reorganized matrix S R,dis n′ corresponding to R dis , and D R (n′) represents a total number of filtered DCT coefficients in the n′ th filtered coefficient reorganized matrix S R,dis n′ corresponding to R dis ; {circle around (2)}-9 detecting a first digital watermarking information embedded in S dis , processing decoding and inverse quantization on the detected first digital watermarking information, so as to obtain an average value and a standard deviation of the absolute value matrix of the difference value of each coefficient reorganized matrix corresponding to L org and each coefficient reorganized matrix corresponding to R org embedded at the transmitting terminal, processing texture similarity measurement on S dis utilizing Canberra distance, so as to obtain a stereo perception value of S dis , which is denoted as Q disp , wherein Q disp = ∑ n ′ = 1 10 ⁢ ⁢ w n ′ (  μ r n ′ - μ d n ′ ⁢  +  ⁢ σ r n ′ - σ d n ′  ) ∑ n ′ = 1 10 ⁢ ⁢ w n ′ ⁡ ( μ r n ′ + μ d n ′ + σ r n ′ + σ d n ′ ) , wherein μ r n′ and σ r n′ respectively represent a average value and a standard deviation of absolute value matrix of the difference value of an n′ th coefficient reorganized matrix S L,org n′ corresponding to L org and an n′ th coefficient reorganized matrix S R,org n′ corresponding to R org embedded at the transmitting terminal, wherein w n′ represents a weight, w n ′ = { 1 , if ⁢ ⁢ n ′ = 1 0.5 if ⁢ ⁢ n ′ = 2 ⁢ ⁢ or ⁢ ⁢ n ′ = 3 ⁢ ⁢ or ⁢ ⁢ n ′ = 4 0.25 , if ⁢ ⁢ n ′ = 5 ⁢ ⁢ or ⁢ ⁢ n ′ = 6 ⁢ ⁢ or ⁢ ⁢ n ′ = 7 0.125 , if ⁢ ⁢ n ′ = 8 ⁢ ⁢ or ⁢ ⁢ n ′ = 9 ⁢ ⁢ or ⁢ ⁢ n ′ = 10 , “∥” is an absolute value sign; detecting a second digital watermarking information embedded in S dis , processing decoding and inverse quantization on the detected second digital watermarking information, so as to obtain a proportion of visual sensitivity coefficients in each filtered coefficient reorganized matrix corresponding to L org embedded at the transmitting terminal, then calculating a left-view quality value, which is denoted as Q view L , wherein Q view L = 1 1 + log 2 ( K L Q 0 + 1 ) , wherein Q 0 is a dynamic adjustor, K L = ∑ n ′ = 1 10 ⁢ ⁢  P r L ⁡ ( n ′ ) - P d L ⁡ ( n ′ )  , wherein P r L (n′) represents a proportion of visual sensitivity coefficients in an n′th filtered coefficient reorganized matrix S L,org n′ corresponding to L org embedded at the transmitting terminal, “∥” is an absolute value sign; detecting a third digital watermarking information embedded in S dis , then processing decoding and inverse quantization on the third digital watermarking information detected, so as to obtain a proportion of visual sensitivity coefficients in each filtered coefficient reorganized matrix corresponding to R org embedded at the transmitting terminal, then calculating a right-view quality value, which is denoted as Q view R , Q view R = 1 1 + log 2 ( K R Q 0 + 1 ) , wherein K R = ∑ n ′ = 1 10 ⁢ ⁢  P r R ⁡ ( n ′ ) - P d R ⁡ ( n ′ )  , P r R ⁡ ( n ′ ) represents a proportion of visual sensitivity coefficients in an n′th filtered coefficient reorganized matrix S R,org n′ corresponding to R org embedded at the transmitting terminal; {circle around (2)}-10 calculating a view quality value of S dis according to Q view L and Q view R , which is denoted as Q view , wherein Q view =(Q view L +Q view R )/2; {circle around (2)}-11 calculating an objective quality score of the distorted stereo image S dis utilizing a support vector regression model with an optimal weight vector W opt and an optimal bias b opt , denoting the objective quality score of the distorted stereo image S dis as Q obj , Q obj =(W opt ) T φ(x)+b opt , wherein x=[Q disp ,Q view ], x represents a vector constituted by the stereo perception value and the view quality value of the distorted stereo image S dis , (W opt ) is a transposed vector of W opt , φ(x) is a linear function of x.

9633017

14074616

1. A method for building a user interest profile, comprising: identifying features of each of a plurality of articles; for a given user, logging views of one or more of the plurality of articles, the one or more of the plurality of articles being provided by a content server over a network to a client device for viewing on the client device; for each view, measuring a corresponding dwell time for the view by the given user, wherein measuring the corresponding dwell time includes processing interaction data received over the network from the client device; for each view, applying a corresponding weight based on the corresponding measured dwell time, wherein applying the corresponding weight to each view uses a logarithm of the corresponding measured dwell time, such that a weighted view is separately determined for each single view of one of the articles; determining user interest scores for features of the one or more of the plurality of articles based on the weighted views; generating a user interest profile for the given user based on the user interest scores; wherein the method is executed by at least one processor.

20060242129

11373020

1. A computer method of processing a search query result, the computer method comprising: identifying a plurality of result pages in response to a search query submitted from a computing device directed to a collection of pages; determining a relevancy ranking of the result pages in accordance with a multiple dimension parameter set that includes metrics relating to the search query itself and also includes metrics unique to a subscriber associated with the search query; providing the result pages in accordance with the determined relevancy ranking.

20140324871

13874299

1. A decision-tree system comprising: a data store having structured data comprising a decision tree; an additional data store having a record to be analyzed according to the decision tree; a distinction module operable to select between multiple paths extending from a node in the decision tree based on a unit of data from the record, the unit of data carrying information relevant to a distinction of the node, the distinction module further comprising a real-value module operable to make a first comparison between the unit of data and a predetermined real value for the distinction of the node, and a set-value module operable to make a second comparison between the unit of data and a predetermined set value for the distinction of the node; and the distinction module further operable to select a path from the multiple paths based on at least one of the first comparison and the second comparison.

8326469

11826486

1. A method for operating a remote vehicle using a diagnostic behavior, the method comprising: inputting and analyzing data received from a plurality of sensors to determine the existence of deviations from normal operation of the remote vehicle; updating parameters, using diagnostic assembly, in reference mobility model comprising a computer model configured to predict vehicle performance for operation in a variety of environments and based on one or more of the parameters, the parameters being updated based on the determined deviations from normal operation; and revising strategies to achieve an operational goal of the remote vehicle to accommodate the determined deviations from normal operation, wherein the data regards the status of the remote vehicle's components.

8069014

12355195

1. A method for normalizing data from a target data set, the method being implemented in a computer and comprising the steps of: sorting data from a reference data set according to measurement value; selecting, from the sorted data, according to a predetermined criterion, reference subsets, the reference subsets having at least one reference measurement value; selecting, utilizing the reference subsets, data elements in the target data set substantially equivalent to one reference subset; sorting the data elements substantially equivalent to the one reference subset by measurement values, the sorted data elements comprising a sorted substantially equivalent subset; and normalizing the target data set, utilizing the at least one reference measurement value and the sorted substantially equivalent subset; wherein the steps of selecting data elements in said target data set, sorting the data elements and normalizing said target data set being performed by means of a non-transitory computer usable medium having computer readable code that causes the computer to perform the steps; wherein the method is utilized for decision making to increase confidence on the use of the data in activities including manufacturing, handling, hybridization, and gene expression.