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10012407

14596059

1. A heating, ventilating, and air conditioning (HVAC) control system comprising: a processing system in operative communication with a heating system, the processing system being configured and programmed to control the heating system to: acquire historical temperature information regarding heating of an enclosure during at least one historical period in which the enclosure was heated by the heating system under the control of said HVAC control system; determine a lag value that represents at least in part an amount of system inertia for the enclosure; determine a plurality of candidate heating control strategies based on said historical temperature information; determine an optimal heating control strategy from said plurality of candidate heating control strategies by computing a plurality of predicted temperature responses corresponding respectively to the plurality of candidate heating control strategies; and control the heating system according to the determined optimal heating control strategy.

7574478

10748009

1. A method of sending an electronic mail message to members of a mass audience each connected to a network, said method comprising the steps of: creating a plurality of test messages each having a message content identical in each test message and a plurality of characteristics, each test message varying from all other test messages in at least one of said characteristics; storing said message content and retrieving said message content from storage for inclusion in each test message; sending each test message on said network to different members of said mass audience with all of the test messages together being sent to a minority of the members of said audience; evaluating feedback as to the effectiveness of each test message; creating a final message based on the evaluation of the feedback; sending said final message on the network to all members of said audience that were not sent one of the test messages, wherein said final message is an electronic mail message; and evaluating feedback as to the effectiveness of the final message.

20060212512

11358304

1. A method for optimizing monitoring and discovery services for a grid computing environment, comprising: generating a stability and updateability (SUP) ratio for the grid computing environment; estimating a size of a set of scale free graphs for the grid computing environment; generating the set of scale free graphs based on at least one predetermined parameter; generating a set of perturbed scale free graphs based on the set of scale free graphs; and repeating the above steps for each of the monitoring and discovery services to generate a set of monitoring and discovery service (MDS) topology graphs for the grid computing environment.

8239342

11867890

1. A method for semantic modeling ontology extension, comprising the computer implemented steps of: using a computer, providing a semantic modeling type working process having one or more models modeling meaning of information including situations, said providing including providing an ontology defining a hierarchy of concept classes and relationships that may exist on instances of the classes in the models, wherein the models are any of a graphical representation and text representation; using the computer, supporting a creation event in the working process, said supporting including defining ontology specification for a newly created item in the creation event, the defining being done as a part of the working process during modeling and thus in a manner free of substantial interruption to the working process; and incorporating by the computer the defined ontology specification into the provided ontology resulting in an extended ontology on-demand and as needed during modeling.

8971517

12879868

1. A computer implemented method for modeling business processes, comprising: receiving interaction data describing states and transitions between states within interaction sessions, wherein the interaction data is generated from a work force manager (WFM), which is divided among multiple applications running on a workstation; identifying business processes based on the interaction data; identifying instances of the business processes; storing the instances; generating a model from the instances; providing information about scheduled activities actual activities and exceptions to an adherence application; providing based on the model, a graphical scheduled timeline, a graphical actual timeline, a graphical adherence exception timeline, and a graphical interaction timeline; and displaying the timelines for viewing by a call center supervisor using four separate, substantially parallel lines approximately aligned with a reference timeline axis, wherein the graphical timelines comprise sequential graphical blocks each indicating a period of time starting at a respective start time and ending at a respective end time, and wherein the blocks of the graphical interaction timeline are selectable by a user and upon selection initiate the playback of a recorded interaction corresponding to the respective period of time of a corresponding block of the graphical adherence exception timeline.

20110051999

12078300

1. A target detection device for detecting predetermined targets that are captured within an image, the device including: a target region identification device that is configured to identify a region of interest in the captured image, the region of interest including a target having geometries consistent with the predetermined targets; and a classification device that is configured to determine whether the region of interest includes the predetermined targets by analyzing the region of interest with a strong classifier descriptor that describes at least one of shape attributes and appearance attributes that are characteristic of the predetermined targets, wherein the strong classifier descriptor is based on a subset of weak classifier descriptors that is selected from a plurality of weak classifier descriptors that each describe at least one of shape attributes and appearance attributes that are characteristic of parts of the predetermined targets, and wherein the subset of weak classifier descriptors includes at least one user-defined weak classifier descriptor that is defined by a user based on database images including the predetermined targets.

20030177128

10063061

1. A work object manager for performing operations on work objects, comprising: a user interface for receiving user inputs, the user interface allowing a user to construct queries defining a set of work objects on which simultaneous operations are to be performed and to specify an operation to be performed on the set of work objects; and a plurality of operational modules, one or more of the operational modules being operative to perform the specified operation on the defined set of work objects, one of the operational modules being a batch unlock manager operative to receive a query specifying a range of locations to be searched for work objects, the query further specifying characteristics relating to locking of work objects, the batch unlock manager being operative to return work objects in the specified range of locations and having the specified lock characteristics, the batch object manager being further operative to simultaneously unlock the returned work objects upon a selection by the user.

20130173223

13342162

1. A computer-implemented system for developing a structure design, comprising: a design engine which receives various inputs, and produces a first structure design state; an attributes engine, configured to: receive a plurality of structure design states including said first structure design state, each said design state comprised of a plurality of cells, each cell configured to permit it to interconnect with another cell such that a structure design state comprised of cells represents a valid structure design state; quantify a plurality of measures of various attributes of each said structure design state; from said quantified plurality of measures of various attributes of each said structure design state, determine a structure fitness function value corresponding to said first structure design state; an optimization engine, communicatively connected to said design engine and said attributes engine, configured to: receive, from said design engine, said first structure design state; receive, from a change operation selection mechanism, a first change operation; apply said first change operation to said first structure design state to thereby obtain a second structure design state; provide said second structure design state to said attributes engine to thereby obtain a structure fitness function value corresponding to said second structure design state; and receive and compare said structure fitness function values corresponding to said first and second structure design states and designating as a selected design state that design state having a greater fitness function value and designating as a non-selected design state that design state having a lesser fitness function value.

20090180538

12268307

1. A method of encoding intra-predictions of a current block of a current frame of a video sequence, comprising: identifying and sorting into an ordered list a select number (N) of spatially best matches to a matching template for the current block within previously coded and reconstructed blocks which neighbor the current block of video; encoding a selector which identifies which of the templates in the ordered list provides the actual least predictive error for the current block; and communicating the selector for receipt by a decoder configured for performing the same identifying and sorting step and then selecting for use the best match in response to said selector communicated from the encoder to completing the current block prediction.

7604541

11396339

1. A method for detecting collusion in online poker involving a plurality of players, comprising the steps of: collecting data on every action in every game for every player and sending the data to an online poker database; storing hidden game information data on every action in every game for every player in the online poker database; storing game action data on every action in every game for every player in the online poker database; performing a player action analysis of correlated actions between a pair of online poker players and building a user action database with data obtained in the player action analysis; creating two or more Bayesian Network graphical models including at least one collusional model to represent forms of collusional behavior and at least one non-collusional model to represent forms of non-collusional behavior; employing the created Bayesian Network graphical models to determine a likelihood of conditional behavior between the pair of online poker players; after determining the likelihood of conditional behavior, computing individual scores for the Bayesian Network graphical models using a Bayesian statistical technique; comparing the computed score of a collusional model with that of a non-collusional model; after comparing the computed scores, performing a collusion threshold analysis using a thresholding scheme to determine whether the collusional model indicates collusion for the pair of online poker players; and notifying an appropriate party of unfair collusional play if it is determined that the collusional model is appropriate for the pair of online poker players.

7672919

11498024

1. A method for determining a connectivity-metric for a graph representative of a network of interest, the method comprising: Accessing a graph that represents a network of interest, the graph comprising a plurality of nodes representing points in the network of interest and a plurality of edges corresponding to the plurality of nodes; generating a plurality of bit-vectors respectively corresponding to at least one of the plurality of nodes or the plurality of edges, wherein individual bits in the bit vectors respectively provide a logical indication of connectedness to each other node or edge; determining the connectivity-metric by applying, for each bit-vector, a bit-wise OR with each other bit-vector of the plurality of bit-vectors that has a positive indication of connectedness to the first bit-vector to create a plurality of updated bit-vectors; iteratively applying, for each updated bit-vector, the bit-wise OR with each other updated bit-vector of the plurality of updated bit-vectors until there is no additional change in the plurality of updated bit vectors; determining the connectivity metric by using the updated bit vectors; wherein the accessing, generating, and determining steps are performed on at least one particular machine, said at least one particular machine comprising at least one physical computing device.

7567949

10238175

1. A method that samples with replacement a plurality of records in a database system in a single sequential pass of the records, comprising: identifying the plurality of records; determining a sum of weights to be assigned to all records in the plurality of records; when a record is selected to be included in the sample, tabulating a remaining weight that subtracts all weights associated with records included in the sample from the sum of weights; for each of the plurality of records: inputting the record to a sampling operator that determines a number of times the record is included in the sample by generating a random value from a binomial distribution using the remaining weight and a weight of the current record as parameters; and selectively outputting and storing the record for inclusion in the sample the determined number of times, wherein the record may be included more than one time in the sample.

20090118970

12245242

1. A method for controlling operations of a power system having at least one power unit, the method comprising: (a) identifying a plurality of discrete potential dynamic events; (b) for each potential dynamic event, computing an optimization profile which describes power settings for the power system to follow in order to optimize at least one operating parameter of the at least one power unit; (c) selecting one of the optimization profiles based on the potential dynamic event with the highest current probability; and (d) operating the system in accordance with the selected optimization profile.

10025860

14798240

1. A system, comprising: at least one processor; a memory coupled to the processor through a bus; and a process executed from the memory by the processor causes the at least one processor to retrieve a plurality of citations composed by a plurality of subjects citing a plurality of objects that fit one or more search criteria, determine an influence of each of the subjects and the objects using a citation graph, wherein the citation graph including includes the plurality of citations each describing an opinion of an object by a subject, the citation graph further including nodes or entities that are subjects that have an opinion or make citations and objects cited by citations relative to subjects that have opinions or make citations, determine an expertise of a subject as a measure of the subjects expertise in a topic relative to a larger population of multiple subjects and allow for determination of expertise on any query term in real-time, rank the cited objects of the plurality of citations using the influence and relative expertise of the subjects, and select objects as a search result for a user based on the matching of the objects with the search criteria as well as the relative expertise of the citing subjects.

9704020

14741015

1. A system, comprising a hardware processor and a memory device, the memory device configured to store computer-executable instructions that when executed by the hardware processor cause the hardware processor to implement one or more computer-executable components, comprising: an access component configured to access information related to at least one of an event or people participating in the event, the people and event captured in a video, the information accessed as part of presenting the video, the access component further configured to access the information according to a predetermined time window, the time window determined based on at least one of kind of the event or duration of the event; a collection component configured to collect training data from the information for identification of at least one or more persons in the video; a training component configured to train a model using the training data, the training data collected and model trained as part of presenting the video; a recognition component configured to perform facial recognition processing of the people in the video to identify the one or more persons, the facial recognition processing performed using the model; and a content component configured to obtain content relevant to the one or more persons identified, the content for presentation with the video and while the video is being viewed.

7788252

11729096

1. A method for determining a local intent of a query comprising: receiving a query; identifying a presence of a location term in the query; separating the query into a root term and the location term when the location term is present; analyzing historical searches that record which location terms are most often associated with the root term; and computing a local intent probability (LIP) for the root term with a probability model using the historical searches wherein computing the LIP comprises a probability model using the historical searches, wherein the probability model is an exponential function between the LIP and a local intent value (LIV).

10147315

15221112

1. A navigation system comprising: a communication interface configured to receive multimedia data including one or more images from a camera representative of traffic conditions along a road segment upstream of a junction; and at least one processor configured to: identify a multi-modality condition along the road segment upstream of the junction based upon an analysis of the multimedia data including the one or more images; evaluate a plurality of probe points representative of travel along the road segment upstream of the junction in accordance with a detection algorithm to separately determine whether the multi-modality condition exists along the road segment upstream of the junction; and determine whether to modify one or more tuning parameters of the detection algorithm based upon the multi-modality condition identified based upon the analysis of the multimedia data including the one or more images, wherein the communication interface is also configured to cause an alert message to be provided based upon the multi-modality condition identified based upon the analysis of the multimedia data including the one or more images.

9892163

14450114

1. A computer program product comprising a non-transitory machine-readable storage medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising: generating, for a multi-operation database process to be performed in a distributed database management system comprising a plurality of computing nodes comprising respective data processors and having respective node locations, a plurality of sub-plans, each of the plurality of sub-plans comprising a different distribution of node locations of a plurality of operators among the plurality of computing nodes, the plurality of operators being those necessary to complete the multi-operation database process; calculating a total minimum global cost for each sub-plan of the plurality of sub-plans; and selecting an optimal plan from the plurality of sub-plans, the optimal plan having a lowest total minimum global cost, the selecting including pruning at least one sub-plan from the plurality of sub-plans by at least eliminating at least one sub-plan having a cost greater than a best sub-tree cost for a location of a node location; wherein the plurality of computing nodes includes a first node and a second node, and a first sub-plan of the plurality of sub-plans includes a first join operation and a second join operation, wherein: the first join operation comprises transferring a first number of rows of a first table from the second node to the first node, and joining the first number of rows with a second number of rows of a second table at the first node, the first number of rows being greater than the second number of rows, and the second join operation comprises joining a result of the first join operation with a third number of rows of a third table at the first node, the third number of rows greater than the first number of rows.

20150317427

14799762

1. A system for designing an integrated circuit, the system comprising: at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the system to: receive a proposed device array layout from a device array design module, the device array design module being configured to generate the proposed device array layout free from a set of system design rule constraints; revise a schematic of the integrated circuit including the proposed device array layout; and determine whether the revised schematic violates one or more system design rule constraints.

20140033223

13561383

1. A computer implemented method for load balancing using progressive sampling to achieve a load balancing quality target over a plurality of worker tasks at a target confidence level, the method comprising: computing a maximum workload variance target based on the load balancing quality target and the target confidence level; sampling, by a computer, a first set of sampled input records to be assigned to at least two of the worker tasks; forming a prospective load balancing assignment by assigning the first set of sampled input records to the plurality of worker tasks based on a workload estimate for the worker tasks; determining whether an additional number of input records are required be sampled to achieve the load balancing target; and sampling the additional number of input records.

9927286

14964533

1. A method for geophysical exploration, comprising: deploying an optical fiber in a borehole formed in a formation; exciting seismic waves into the formation; using an optical interrogation system to obtain data at a plurality of predetermined sampling locations along the optical fiber; processing the data to determine features in the formation; and selecting updated sampling locations along the optical fiber based on the locations of the features.

9501829

14923325

1. A system for associating anatomical information with image data that forms a three-dimensional space, the system comprising: a computer processor configured to: output a graphical user interface (GUI) in which a first two-dimensional image slice of the image data and a second two-dimensional image slice of the image data are simultaneously displayed, wherein the first and second two-dimensional image slices are orthogonal to each other; obtain, via user interaction with the GUI, selection of three points within the three-dimensional space, two of the three points being selected in different respective ones of the first and second two-dimensional image slices, wherein a first point of the three points corresponds to an anterior commissure (AC) and a second point of the three points corresponds to a posterior commissure (PC); record the three points in association with the image data; selecting an alignment point along a line connecting the AC to the PC; aligning the image data with an anatomical atlas by anisotropically scaling the image data using a first scaling factor in an anterior/posterior direction relative to the alignment point and a second scaling factor in a superior/inferior direction relative to the alignment point, wherein the first and second scaling factors are different.

20090248568

12058306

1. An account default prediction method comprising: obtaining a first consumer default risk factor associated with a first consumer; acquiring first mortgage data associated with a first consumer, wherein said first mortgage data is associated with a first lender; obtaining a second consumer default risk factor associated with a second consumer; acquiring second mortgage data associated with a second consumer, wherein said second mortgage data is associated with a first lender; calculating a first lender default risk factor based upon said first consumer default risk factor and said second consumer default risk factor; obtaining a third consumer default risk factor associated with a third consumer; acquiring third mortgage data associated with a third consumer, wherein said third mortgage data is associated with a second lender; obtaining a fourth consumer default risk factor associated with a fourth consumer; acquiring fourth mortgage data associated with a fourth consumer, wherein said fourth mortgage data is associated with said second lender; calculating a second lender default risk factor based upon said third consumer default risk factor and said fourth consumer default risk factor; and ranking said first lender and said second lender based on said first lender default risk factor and said second lender default risk factor to create a default risk factor ranking.

8732097

13402751

1. A computer-implemented method, comprising: computing, by a computing device, a first set of activity probabilities based on contextual information for a first set of historical activities and an activity-prediction model for a target activity, wherein an activity probability indicates a likelihood that the target activity has occurred; comparing a first set of probability thresholds with the first set of activity probabilities to determine a prediction success rate for each probability threshold; computing a utility score for each probability threshold based on the prediction success rates and a utility function, wherein the utility function has the form: U ( P th )= U 1 (TP)+ U 2 (FP)+ U 3 (FN)+ U 4 (TN); wherein P th is the threshold value used to determine whether a historical activity matches the target activity, wherein U 1 (TP) and U 4 (TN) compute a benefit of making a recommendation based on predicting a true positive and a true negative, respectively, and wherein U 2 (FP) and U 3 (FN) compute a cost of making a recommendation based on predicting a false positive and a false negative, respectively; selecting a first probability threshold whose utility score is greater than or equal to a baseline utility score and other utility scores of the first set of thresholds; and assigning the first probability threshold to the activity-prediction model.

20170082530

14860050

1. A system for analyzing particles in a fluid, the system comprising: a flow chamber for receiving a sample of fluid to be analyzed; one or more detectors positioned to detect two different ranges of fluorescence produced by particles in the fluid in said flow chamber, said detectors generating a trigger signal whenever fluorescence is detected; a classifier training set containing organism type and feature values; and a support vector machine classifier training set including related to particle images, wherein feature values of captured images are calculated and the support vector machine classifier training set is applied to captured images to classify the particle associated with each image.

20070021951

10564895

1. A method for prestack time migration, including velocity calibration and trend fitting (“iDEPTHing”) before curved-my prestack time migration, comprising: a. editing seismic velocities, including at least one of honoring geologic trends existing in a survey area, using envelopes of vertical trends based on rock properties and using computed envelopes; b. computing lateral trends of RMS velocities derived from seismic data by geostatistical variogram modeling; c. preparing scale factors from well (hard) data and seismic (soft) data wherein the well (hard) data include at least one of checkshot data and up-scaled and bulk-shifted sonic logs; d. calibrating RMS velocities, including applying interpolated scale factors to RMS velocities wherein the interpolation is a function of the lateral trends; and e. curved-ray prestack time migration using interpolated calibrated RMS velocities, wherein the interpolation is a function of the lateral trends.

20170193333

14984542

1. A computer implemented method of analyzing image data, the method comprising: receiving, using a processor system, image data of one or more images that have been posted to internet websites; analyzing, using the processor system, the image data to extract image feature data for each one of the one or more images; analyzing, using the processor system, the image data to extract metadata of the one or more images; creating multiple image files; wherein each one of the multiple image files comprises individual ones of the one or more images linked together based on overlaps between the image feature data of the individual ones of the one or more images; wherein each one of the multiple image files further comprises individual ones of the one or more images linked together based on overlaps between the metadata of the individual ones of the one or more images; indexing the multiple image files to form multiple indexed image files; wherein the indexing is based on the image feature data of the individual ones of the one or more images in an individual indexed image file; wherein the indexing is further based on the metadata of the individual ones of the one or more images in the individual indexed image file; and storing the multiple indexed image files in a memory of the processor system having a searchable indexed data storage structure.

8515752

12047108

1. A method comprising: receiving, by one or more processors in one or more computer devices, a voice search query; determining, by the one or more processors and from the voice search query, recognition hypotheses for the voice search query, the recognition hypotheses being associated with statistical weights, each of the statistical weights reflecting a respective likelihood that a corresponding recognition hypothesis, of the recognition hypotheses, is accurate for the voice search query; selecting, by the one or more processors and based on the statistical weights, a plurality of the recognition hypotheses as selected recognition hypotheses, where the selected recognition hypotheses are associated with, respectively, corresponding-statistical weights of the statistical weights, and where a quantity of the selected recognition hypotheses is determined based on a quantity of terms included in one of the selected recognition hypotheses and a maximum quantity of terms to be included in a weighted boolean query; constructing, by the one or more processors, the weighted boolean query, the weighted boolean query including the selected recognition hypotheses weighted by the corresponding statistical weights; obtaining, by the one or more processors, results associated with the weighted boolean query; and providing, by the one or more processors, the results for display.

20080134069

11965222

1. A user interface to facilitate communications between parties, comprising: a display providing one or more display objects associated with configuring a data store, the data store adapted to receive N parameters, N being an integer, the N parameters relating to at least one of a communications preference, context and policy, the N parameters employed to guide decisions that facilitate optimal communications between the parties; and one or more inputs associated with the display objects to facilitate configuration of the user interface according to the at least one of the communications preference, context and policy associated with the parties.

20070003137

11397040

1. A method of segmenting an object in a set of image data using one or more prior instances of the object, comprising: determining a nonparametric estimate of a property from the one or more prior instances of the object in a subspace spanned by the one or more prior instances of the object; imposing the nonparametric estimate of the one or more priors in a Bayesian expression conditioned on the set of image data; and selecting a segmentation of the object in the set of image data by executing a level set method which optimizes the Bayesian expression.

20120115116

13293478

1. In connection with a psychological test wherein an examinee enters into a computer information pertaining to the examinee's chronological age and subjectively expected lifespan and responds to cues by entering into the computer subjective point values for significant events occurring in predetermined time segments in said expected lifespan, and wherein the computer calculates from the point values and the expected lifespan the psychological age of the examinee, a method for providing a visible indication on a screen of the computer of the examinee's chronological age and the psychological age, said method comprising the steps of: (a) establishing on the computer screen a lifespan time scale representing the examinee's entered expected lifespan; (b) providing a first indicator representing the examinee's chronological age at a first location on the lifespan time scale corresponding to said chronological age; and (c) providing a second indicator representing the examinee's calculated psychological age at a second location on the lifespan time scale corresponding to said psychological age; wherein spacing on said lifespan time scale between said first and second indicators represents the difference between the examinee's chronological age and calculated psychological age.

7870550

11316202

1. A meta-application system for managing a deployment of a software application, comprising: a computer system comprising one or more computers, said computer system programmed to implement at least: a non-transitory machine-readable repository of encoded knowledge comprising: a collection of deployment-independent rules describing problems associated with the software application, at least some of the rules comprising logical combinations of conditions individually satisfied by features of the deployment; and deployment-independent remedies for countering the problems; wherein the rules collectively comprise predicates, logical operators, mathematical operators, free variables, and constant terms, the logical operators including AND and OR operators; a monitoring component that collects data values of state metrics from the deployment, wherein the meta-application system is configured to derive at least one of the features from one or more of the collected state metric data values; and a problem detector that detects instances of the problems within the deployment, at least by programmatically using the features of the deployment to satisfy the logical combinations of conditions of the rules, the problem detector configured to satisfy at least some of the conditions by conducting pattern-matching between features represented as closed atomic formulae with constant term arguments and no free variables, and conditions represented as open atomic formulae with free variables.

7716622

11767385

1. A method of re-implementing a memory module, or a part of a memory module, that has been implemented on an FPGA device, the method being executable on a computer, comprising: performing a physical timing analysis on an initial implementation of the memory module or the part of a memory module, the memory module being at least partially implemented in a dedicated memory logic block on the FPGA device; re-implementing the memory module or the part of a memory module, the re-implementation of the memory module or the part of a memory module comprising two or more logic blocks; identifying a critical pin in the dedicated memory logic block, the critical pin being one that is susceptible to faults due to a propagation delay identified in the physical timing analysis; separating the dedicated memory logic block by removing the critical pin and assigning the critical pin to at least one of the two or more logic blocks; placing the two or more logic blocks on the FPGA device; and re-connecting the two or more logic blocks, based at least in part on the physical timing analysis, so as to reduce circuit delay.

8457656

13244257

1. A method for determining a real-time location of an object within a facility, the method comprising: transmitting a wireless signal from a communication device associated with an object; receiving the wireless signal at least one of a plurality of sensors positioned within a facility, the plurality of sensors forming a mesh network; forwarding the wireless signal from the mesh network to each of the plurality of location engines; and determining a real-time location of the object in the facility at each of the plurality of location engines, each of the plurality of location engines using an algorithm comprising a plurality of location sub-algorithms with a signal characteristic for the wireless signal received at the at least one of a plurality of sensors, wherein the signal characteristic is a power value, an angle, or an ultrasound phase, wherein the plurality of location sub-algorithms comprise at least one of a voting algorithm, an averaging algorithm and a confidence algorithm.

20180018517

15209628

1. A computing device comprising: a memory; one or more processors communicatively coupled to the memory; one or more instructions stored in the memory, executed by the one or more processors, and configured to cause the one or more processors to perform: obtaining a first pixel map for a predicted agronomic yield of a particular field wherein each pixel of the first pixel map represents an agronomic yield of a crop at a physical location within the particular field; obtaining a second pixel map for a measured agronomic yield of the particular field wherein each pixel of the second pixel map represents an agronomic yield of a crop at a physical location within the particular field; generating, from the first pixel map, a first vector of values; generating, from the second pixel map, a second vector of values; generating a matrix of metric coefficients wherein each row of the matrix of metric coefficients corresponds to a first pixel location of the first pixel map, each column of the matrix of metric coefficients corresponds to a second pixel location of the first pixel map, and each value in the matrix of metric coefficients is computed using a spatial distance between the first pixel location and the second pixel location for the value; computing a particular difference metric that specifies a difference between the first pixel map and the second pixel map based on the first vector of values, the second vector of values, and the matrix of metric coefficients; computing, from the particular difference metric, a particular normalized difference metric comprising a quotient of the difference metric with a sum of the metric coefficients in the matrix of metric coefficients; generating and sending, to a field manager computing device, one or more field management recommendations based, at least in part, on the particular normalized difference metric.

8255516

11413349

1. A method for server consolidation, comprising: accessing, by a consolidation analysis module in a computer, performance data of a plurality of source servers in a desired environment that are selected for server consolidation; receiving multiple consolidation parameters for a desired target server platform including target servers; receiving selected configurations for a new target server that is potentially included in the desired target server platform; computing, by the consolidation analysis module in the computer, a minimum number of the target servers required to consolidate the plurality of source servers based at least on the performance data, the selected configurations for the desired target server platform, and the multiple consolidation parameters; marking each of the plurality of source servers with one of a first status, second status, and third status, wherein the first status indicates the marked source server is to be replaced in the server consolidation, the second status indicates the marked source server is to be reused in the server consolidation, and the third status indicates the marked source server is to be replaced or reused as necessary; deriving, by the consolidation analysis module in the computer, a bin-packing solution to the server consolidation based at least on the performance data, the selected configurations for the new target server, and the minimum number of the target servers, wherein the bin-packing solution includes assigning each of the source servers to one of the target servers; and reporting the bin-packing solution, including reporting the computed minimum number of the target servers and a consolidation assignment specifying the target servers that each of the source servers is assigned to.

5495419

08229826

1. A physical design automation system for producing an optimized cell placement for an integrated circuit chip, comprising: a decomposer for decomposing a placement optimization methodology into a plurality of cell placement optimization processes; a plurality of parallel processors for performing said optimization processes simultaneously on input data representing said chip; a recomposer for recomposing results of said optimization processes and producing an optimized cell placement corresponding thereto; and a controller for analyzing a fitness of said optimized cell placement and controlling the parallel processors to selectively repeat performing said optimization processes for further optimizing said optimized cell placement if said fitness does not satisfy a predetermined criterion; in which the controller identifies low fitness areas of said optimized placement and selectively assigns the processors to repeat performing said optimization processes on said low fitness areas respectively.

7765178

11245601

1. In a computerized search system in which queries are submitted by users who receive, in response, a list of documents selected from a corpus of documents wherein the list comprises documents deemed responsive to a user's query, a method of determining relevance of the documents comprising: obtaining, at a server computer comprising a processor, the query from a user; determining initial probabilities that at least one leaf category of a taxonomy contains documents relevant to the query, at least one of the initial probabilities being non-zero, wherein the at least one leaf category contains indexed documents predetermined to be related to one another and the initial probabilities are numeric values between zero and one; determining a relevance of the documents matching the query in each leaf category having non-zero initial probability; and determining a relevance of documents to the query based on the initial probabilities of the at least one leaf category and the relevance of the documents matching the query, wherein determining the relevance of documents to the query comprises: for each particular leaf category containing a particular document, determining a weighted relevance value by multiplying a determined relevance of the particular document matching the query by the initial probability that the particular leaf category includes relevant documents; generating updated probabilities that the nodes of the taxonomy contain relevant documents by weighting each of the relevance of documents to the query, wherein weights used to generate the updated probabilities decay monotonically with the probability that a document matching the query resides in the particular node; determining an updated relevance of documents to the query based on the updated probabilities and the probability that a document matching the query resides in the particular node; and summing the weighted relevance values to determine the relevance of the particular document to the query.

9898024

14733540

1. A controller for an energy consumption modeling system, comprising: a memory; and a processor configured to execute executable instructions stored in the memory to: assign energy consumption data to an on state and an off state of a device; generate a model configured to predict a future state of the device and a duration of the future state of the device by: generating a probability distribution for a duration of a current state of the device as a function of a duration of a previous state of the device and operating conditions of the device that include a temperature setpoint of the device and a geographic location of the device; and predicting a transition between the current state of the device and the future state of the device using the probability distribution and an amount of time already spent by the device in the current state; predict a future energy consumption of the device using the assigned energy consumption data and the generated model, wherein the predicted future energy consumption of the device is used by a utility to perform a demand response event; and detect a fault of the device using the assigned energy consumption data and the generated model.

20140137086

14160271

1. An apparatus for executing object-oriented code, said apparatus comprising: a computer with a runtime that interprets producer dependency declarations in the object-oriented code for methods in the object-oriented code, said producer dependency declarations identify at run time a set of zero or more producers, where a producer is a runtime instantiated construct, wherein each producer is instantiated from a respective combination of a particular instance of a class and a particular method of that class and identifies said particular instance and said particular method, wherein execution of a producer results in the method identified by that producer being executed on the instance identified by that producer, the runtime including, an automated producer graph generation module to receive a designation of a producer of interest, to add the producer of interest as part of a producer graph, and to automatically generate a remainder of the producer graph through linking, and instantiation as necessary, of other producers based on the producer dependency declarations of the methods identified by the producers already in the producer graph, and a producer graph execution module to execute the producers in the producer graph in the order indicated by the producer graph.

9106922

13836174

1. A method of motion estimation for video coding, comprising: creating a transformed reference image for encoding a frame by sequentially transforming original luma pixels, and storing the transformed image in a frame image buffer; performing rough motion estimation in transformed image space, and storing resulted motion vectors MV for a coding unit CU 16×16 into a MV buffer; generating a merge mode list of MV candidates and an AMVP mode list of MV candidates; removing repetitive vectors from the lists and storing unique merge mode MV according to MV identifiers; storing fractional parts of MV according to an index number of a prediction unit PU inside a coding tree unit CTU; loading reference blocks from a reference buffer into a merge motion estimator; defining SAD for 5 partitions (1×(16×16), 2×(8×16), 2×(16×8)), which are calculated using a current CU and its prediction from a reference picture; comparing a weighted SAD of a current MV candidate to a weighted SAD of a previous MV candidate for each of the 5 partitions and storing the best merge mode MV candidates with SAD; repeating steps of loading reference blocks, defining SADs and comparing weighted SADs until all MM candidates are considered, or until the end of predetermined calculation time; loading resulting MV of rough estimation from MV buffer into AMVP list of candidates; loading a search window from the reference buffer according to the MV candidates from the AMVP list; performing a full search of best MV candidates inside the loaded window; comparing the weighted SAD of the current MV candidate with the weighted SAD of the previous MV candidate for each 5 CU partitions, and storing the best AMVP candidates with SAD; repeating steps of loading search window to storing the best AMVP candidates until all of the AMVP candidates are considered, or until the end of predetermined calculation time; comparing estimation results of the Merge Mode and the AMVP Mode and selecting best decisions for each of the 5 CU partitions; repeating motion estimation for all 16×16 CU in the Coding Tree Unit (CTU); and merging neighboring partitions according to MV identifiers using entire list of best MV candidates.

20120195165

13018122

1. A computer-implemented method for constructing an earth model using multi-offset-multi-attribute image volumes and identified geobodies associated with a geologic volume of interest, the method comprising: obtaining an updated earth model and/or velocity model, wherein one or more rock properties of geobodies represented in the updated earth model and/or velocity model have been constrained based on assigned geobody types of identified geobodies represented in the updated earth model and/or velocity model; obtaining synthetic seismic data corresponding to the updated earth model and/or velocity model; obtaining a plurality of multi-offset-multi-attribute image volumes from the synthetic seismic data, wherein a given one of the multi-offset-multi-attribute image volumes (1) corresponds to one of an offset stack, an angle stack, or an azimuth stack of the synthetic seismic data, (2) is associated with a seismic attribute, and (3) includes geobody representations of geobodies previously unidentified in the updated earth model and/or velocity model; performing a constrained seismic inversion to determine rock properties of the identified geobodies, and to identify other geobodies with associated rock properties in order to reduce differences between observed seismic data and the synthetic data, wherein the constrained seismic inversion is stabilized by the constrained rock properties of the identified geobodies; and obtaining a three-dimensional earth model and/or velocity model based on the constrained seismic inversion.

20030023612

10167533

1. A method of processing data associated with a domain-specific event, the method comprising the steps of: obtaining data associated with the domain-specific event, the data at least comprising sensor data captured in accordance with the event and analyzed; and automatically determining results associated with the domain-specific event in accordance with at least a portion of the analyzed sensor data, and based on at least one user-specified criterion.

20110161264

12648959

1. A method comprising: determining that a criterion for inserting seed candidate solutions for an optimization problem has been met while an evolutionary algorithm based computer simulation is running and after a first selected generation of candidate solutions has been determined by the computer simulation; inserting, into a current generation of candidate solutions generated by the computer simulation, at least a first dataset that represents a first seed candidate solution in response to determining that the criterion for inserting seed candidate solutions has been met; and generating a solution for the optimization problem from the computer simulation based, at least in part, on a successive generation of candidate solutions produced after said inserting, into the current generation of candidate solutions generated by the computer simulation, at least the first dataset that represents the first candidate solution.

8139630

12335493

1. A multi-channel equalizer comprising: a feedforward equalizer (FFE) coupled to receive an interleaved signal from a plurality of different channels, the feedforward equalizer capable of applying different equalization coefficients to data bits received from the different channels; a Viterbi decoder coupled to an output of the feedforward equalizer, the Viterbi decoder determining detected symbols based on a channel model of at least one of the different channels; and a channel estimator coupled to receive the output of the feedforward equalizer and the output of the Viterbi decoder and produce an error feedback signal to adaptively update the equalization coefficients of the feedforward equalizer based on the error feedback signal, the channel estimator modeling a response of the at least one channel based on a Volterra series model of the at least one channel and providing an input to the Viterbi decoder indicative of the channel model.

9200270

12380703

1. A method of preparing a yeast library by electroporation of yeast cells comprising the steps of: incubating the yeast cells in a solution comprising 0.01 to 1.0 M lithium acetate (LiAc) and 1 to 100 mM dithiothreitol (DTT), providing a suspension comprising vector DNA, insert DNA, the incubated yeast cells, 0.1 to 10 M sorbitol, and 0.1 to 10 mM CaCl 2 or MgCl 2 , and electroporating the suspension at 5 kV/cm to 12.5 kV/cm with a capacitance of about 10 to about 50 μF; wherein the yeast cells are transformed with a transformation efficiency greater than 1×10 8 transformed yeast cells per μg of nucleic acid vector, thereby to obtain a library size of at least 1×10 9 .

7552005

10802151

1. A method of analyzing a turbine engine to determine a normal engine condition or a faulty engine condition, said method comprising the steps of: acquiring at least one engine operating parameter; calculating at least one engine residual value from said at least one engine operating parameter; normalizing said at least one engine residual value to yield at least one normalized engine residual; mapping, via a clustering technique, said at least one normalized engine residual as at least one input vector into an engine condition space having a plurality of clusters, each of said plurality of clusters representing either a normal vector engine condition or a faulty vector engine condition; identifying a closest cluster within said engine condition space, said closest cluster being closer to said at least one input vector than any other of said plurality of clusters; and determining a normal engine condition for the engine undergoing analysis if said closest cluster represents a normal vector engine condition, and determining a faulty engine condition for the engine undergoing analysis if said closest cluster represents a faulty vector engine condition.

20160313897

15201650

1. A commodity recognition apparatus, comprising: a memory configured to store computer executable instructions; and a processor configured to execute the computer executable instruction to perform operations, the operations comprising: photographing an image capturing area including a commodity to capture an image thereof; displaying the image on a display screen; receiving a selection input on any position on the image; counting a number of frames displayed on the image; displaying a frame for surrounding the commodity on the image in response to the selection input when a count value obtained by the counting is zero; determining a position on which an instruction input is received in response to the selection input when the count value is one or more; displaying a frame for surrounding the commodity on the image if the position on which the instruction input is received is outside the frame; recognizing a candidate of the commodity imaged in the frame according to the feature amount of the image in the area surrounded by the frame; outputting information of a best candidate commodity among the candidates of the commodity recognized; receiving a change instruction for the best candidate commodity if the position on which the instruction input is received is inside the frame; and outputting information of the commodity other than the best candidate selected from the candidates if the change instruction for the candidate of the commodity is received.

20070239643

11378095

1. A computer-readable medium having computer-executable instructions for performing steps comprising: (a) representing a dataset as a higher-order tensor at a symbol level, the higher-order tensor having an order of at least three; (b) reducing a dimension of the higher-order tensor to obtain an extracted reduced tensor; and (c) determining an associated categorization of the dataset from the extracted reduced tensor.

20140068053

13603167

1. A computer implemented method for recommending alternative computing architectures for a selected application using automated workload instrumentation, the method comprising: selecting a plurality of pre-determined performance parameters; instrumenting the selected application to provide at least one measurement instrument corresponding to at least one of the pre-determined performance parameters; measuring, on the first computing architecture, a first performance of the selected application using at least one of the measurement instruments; measuring, on a second computing architecture, a second performance of the selected application using at least one of the measurement instruments; and comparing, by a computer, the first performance of the selected application to the second performance of the selected application to produce a comparison.

20150138205

14543651

1. A physiological parameter presentation system for a measured physiological parameter, comprising: a processor; an electronic input receiver configured to receive an electronic value corresponding to a measured physiological parameter of a patient; a data store configured to store a plurality of historical values of the measured physiological parameter; a display module in communication with the processor configured to generate a graphical display that includes: a range of possible values for the physiological parameter including a minimum value and a maximum value; a visual representation of at least one threshold value between the minimum value and the maximum value; a numerical display of the current value of the measured physiological parameter; and a historical comparator based on one or more of the historical values of the measured physiological parameter; and an electronic display output configured to output the generated graphical display to an electronic display.

9645654

14560923

1. A computer implemented method for initializing a model, comprising: receiving at least one image of a control object observed in a 3D imaging space; calculating span lengths between opposing sides of the control object; determining a number of span modes of the control object applicable to a frequency distribution of the span lengths; for each span mode, calculating one or more span width parameters from at least part of the distribution of the span lengths; using the span width parameters to initialize at least a portion of a model of the control object; and generating predictive information from an initialized model.

9418316

14500208

1. A computing device comprising: at least one processor; and a memory including instructions operable to be executed by the at least one processor, to configure the at least one processor to: binarize a first image frame to generate a second binarized image frame; output the second binarized image frame; receive a first indication indicating that the second binarized image frame contains at least one of: no text, text that is not recognizable, text that is partially recognizable, or text that is recognizable; determine a first feature metric characterizing image sharpness; generate, using the first feature metric, a first feature value associated with the first image frame; train an image classifier to select an input image frame for optical character recognition using at least the first feature metric and the first indication; output a first pair of image frames including a third image frame and a fourth image frame; receive, for the first pair of image frames, a second indication indicating which image frame of the first pair of image frames is sharper; generate, using the first feature metric, a second feature value associated with the third image frame; generate, using the first feature metric, a third feature value associated with the fourth image frame; receive a first score for the third image frame, the first score being output by the image classifier and based on the second feature value; receive a second score for the fourth image frame, the second score output by the image classifier and based on the third feature value; generate first results indicating which of the first score and the second score is higher; compare the second indication with the first results; determine a first accuracy of the first feature metric based on a first consistency of the second indication with the first results; determine that the first accuracy of the first feature metric satisfies a selection criteria; and select the first feature metric for use in image frame selection.

20120079341

13322454

1. A method, comprising: accepting modulated symbols, which carry bits of a code word of a Low Density Parity Check (LDPC) code; computing respective soft input metrics for the bits; and decoding the code word using an iterative LDPC decoding process comprising: selecting, based on a predefined criterion, a number of internal iterations to be performed by an LDPC decoder in the process; performing the selected number of the internal iterations using the LDPC decoder, so as to estimate decoded bits and soft output metrics indicative of the input bits based on the soft input metrics; performing an external iteration that updates one or more of the soft input metrics based on one or more of the soft output metrics produced by the LDPC decoder; and repeating at least one of the internal iterations using the updated soft input metrics.

10083013

14160271

1. An apparatus for executing object-oriented code, said apparatus comprising: a computer with: a runtime, executed by a processor, including: an automated producer graph generation module to receive a designation of a producer of interest, to instantiate the producer of interest if not yet instantiated, to add the producer of interest as part of a producer graph, and to automatically generate a remainder of the producer graph through iteratively parsing producer dependency declarations for the added producers to identify other producers that need to be added, instantiating any of the other producers that are not already instantiated, and adding them to the producer graph, wherein each of the producers is a runtime construct that identifies a respective combination of a particular instance of a class and one particular method of that class, wherein there is one of the producer dependency declarations for each of the methods identified by the producers to identify at run time execution relationships between the producers, and a producer graph execution module to execute the producers in the producer graph in an order indicated by the producer graph, wherein execution of each of the producers in the producer graph results in the one particular method identified by that respective producer being executed on the particular instance identified by that producer.

8355945

12463621

1. One or more non-transitory computer-readable media having computer-executable instructions embodied thereon that, when executed, enable a computing device to perform a method of identifying one or more high-ranking sectors that require additional communications resources in a wireless network that includes a plurality sectors serving multiple wireless-service subscribers, the method comprising: identifying a set of churners that are wireless-service subscribers that have churned during a given period of time; for each of the plurality of sectors, capturing by the computing device customer profile data, usage data, and terrain data related to the set of churners for a pre-churn time period that is a first period that precedes said given time period; ranking by the computing device the plurality of sectors based on a probability of each sector to produce churners, wherein the probability of each sector to produce churners is based on the customer profile data, the usage data, and the terrain data for that sector, wherein ranking the plurality of sectors includes ranking the plurality of sectors based on the probability that each of the plurality of sectors is one of the top five percentile churning sectors; determining one or more reasons for each of the plurality of sectors being ranked and including the one or more reasons with each ranking, wherein the one or more reasons include high ratio of blocked calls and a high ratio of failed connection attempts; and identifying by the computing device one or more high-ranking sectors that require additional communications resources based on the ranking.

9215712

13758526

1. A baseband processor for processing communication signals in a wireless communication device, comprising: a mixing frequency generator configured to select a plurality of frequency offsets for an iteration of multiple frequency hypothesis (MFH) testing; a plurality of MFH branches, coupled to the mixing frequency generator, configured to receive respective frequency offsets in the plurality of frequency offsets; and an MFH branch selector, coupled to the plurality of MFH branches, wherein, for each iteration of the MFH testing, the MFH branch selector is configured to: determine, based on respective primary synchronization sequence (PSS) correlation peak magnitudes of the plurality of MFH branches, a selected MFH branch in the plurality of MFH branches, and check a consistency of cell identification (ID) information between a first portion of a radio frame for the selected MFH branch and a second portion of the radio frame for the selected MFH branch.

9582495

14307248

1. A computer-implemented method comprising: providing an engine in communication with a database configured to store a data type; causing the engine to receive a heterogeneous input data stream comprising an element; causing the engine to reference a mapping schema of a knowledge model created by a domain expert, to produce a mapping of the element with a class of the mapping schema; causing the engine to output a resource model comprising the mapping and a relationship between the element and the data type; causing the engine to apply a first pattern recognition to partition the data stream into a segment including a data interval; causing the engine to apply a second pattern recognition to determine a data value change in the segment; causing the engine to apply an attribute schema of the resource model to the segment to identify an event; causing the engine to apply a segment schema of the resource model to the data stream to generate a pattern-driven annotation stream comprising a triple in a form of (b,t 1 ,t 2 ), where b comprises a behavior and t 1 and t 2 indicate the data interval; and maintaining the event and the behavior in an entity pool.

7860878

12036970

1. A computer-implemented method for prioritizing a plurality of media assets, the method comprising identifying text associated with each media asset, the text representing subject matter to which the associated media asset relates; determining data relating to current interest topics, the current interest topics data having been generated from a dynamic data set, wherein the dynamic data set changes over time and represents actions by a population of users involving user interactions with one or more of a search engine, a web page or a computer application, and wherein the current interest topics data represents a plurality of current topics of interest associated with the population of users and changes in the topics of interest over time as the dynamic data set changes over time; ranking the media assets based at least in part on a comparison of the current interest topics data with the text associated with each media asset; and selecting a subset of the media assets based on the ranking of the media assets.

8433556

11592450

1. A method for aligning words in parallel segments, the method comprising: calculating a first probability distribution, utilizing a processor and a memory, according to a model estimate of word alignments within a first corpus comprising word-level unaligned parallel segments, the model estimate comprising an N-best list of one or more sub-models; modifying the model estimate according to the first probability distribution; discriminatively re-ranking one or more sub-models associated with the modified model estimate according to word-level annotated parallel segments; and calculating a second probability distribution of the word alignments within the first corpus according to the re-ranked sub-models associated with the modified model estimate; wherein discriminatively re-ranking one or more sub-models within the modified model estimate according to manual alignments further comprises: adding manual alignments to hypothesized alignments within the first corpus; comparing the manual alignments to the hypothesized alignments; and weighting the one or more sub-models according to the comparison; and wherein the comparing of the manual alignments to the hypothesized alignments comprises: comparing an updated weighting factor for each sub-model derived using the first corpus to randomly generated weighting factors; and selecting one of the updated weighting factor and the randomly generated weighting factor that generates a least amount of error.

20120041734

13264990

1. A method for collaborative building a shared self-refining surrogate model for engineering simulations in a computer network, comprising: running a reduced order engineering simulation model on a complex system to simulate one or more simulation items in the complex system by a user on a client device connected to the computer network; querying the same shared self-refining surrogate model via the computer network upon receiving a request for a higher order simulation for a reduced order simulated item; estimating a required higher order simulation result having a desired confidence interval for the reduced order simulated item using the shared self-refining surrogate model; determining whether the required higher order simulation result having the desired confidence interval for the reduced order simulated item is in the shared self-refining surrogate model; and if not, performing the higher order simulation to obtain the required higher order simulation result having the desired confidence interval for the reduced order simulated item, enriching the shared self-refining surrogate model with the obtained higher order simulation result, and sending the obtained higher order simulation result to the reduced order engineering simulation model.

8751209

11686170

1. A method for determining optimum positions in a region for a plurality of sensors, wherein the sensors are capable of detecting occurrence of a hazard in the region, comprising: a. simulating occurrence and movement over time of the hazard in the region to produce data representative thereof; b. simulating a reaction of sensors at a set of all possible candidate sensor locations in the region and for each of a plurality of sensor types responsive to the simulated occurrence and movement of the hazard over time; c. storing in a simulation cache data resulting from the simulated reaction of the sensors at the set of all possible candidate sensor locations in the region for each of the plurality of sensor types responsive to the simulated occurrence and movement of the hazard over time; d. selecting one of a plurality of candidate sensor solutions, wherein each candidate sensor solution comprises one or more sensors of one or more sensor types at corresponding selected ones of the candidate sensor locations within the set of all possible candidate sensor locations; e. retrieving from the simulation cache data for the selected candidate sensor solution from the stored data; f. evaluating the data retrieved from the simulation cache from said (e) retrieving with respect to performance criteria for the selected one of the candidate sensor solutions; and g. selecting another one of the plurality of candidate sensor solutions and repeating (e) and (f), the another one of the plurality of candidate sensor solutions differing from the one of the plurality of candidate sensor solutions in at least one candidate sensor location or at least one sensor type.

20140297241

14091353

1. A method for calculating disease progression against multiple populations utilizing existing studies, risk models and hypotheses; Wherein, multiple disease simulation results are queried against multiple populations with multiple outcomes. Wherein, either summary data, or detailed individual data, or both can be used.

20170328948

15666790

1. A method implemented in a computer infrastructure having computer executable code tangibly embodied on a computer readable storage medium having programming instructions operable to: separate random variation in a logarithm of a leakage current into a correlated random component and an uncorrelated random component; determine a first standard deviation of the correlated random component for an ensemble device; determine a second standard deviation of the uncorrelated random component for the ensemble device; generate a statistical model for electrical features of the ensemble device, based on a number m of individual devices within the ensemble device, a sub-threshold slope, an uplift factor, the first standard deviation, the second standard deviation, and statistical random variables for use in fabrication of integrated chips for semiconductor manufacturing.

20050073519

10901213

1. An analytical shell model forming apparatus for forming an analytical shell model for numerical analysis from a solid model to be analyzed, comprising: medial surface forming means for forming a plurality of medial surfaces for a same potion of the solid model; extracting means for extracting a difference portion by comparing the plurality of formed medial surfaces for a same surface of the solid model; medial surface candidate model forming means for forming a plurality of medial surface candidate models by using the extracted difference portion; and selecting means for selecting a medial surface model to be used for analysis from the plurality of formed medial surface candidate models.

20030236691

10176505

1. A method of improving business process executions, comprising: accessing process execution data generated by one or more components of a business process platform during execution of one or more instances of a business process involving a set of one or more activities each defined by a respective service and performed by a respective set of one or more resources; classifying business process instances in accordance with a quality taxonomy; and building a predictive model comprising a set of rules for scoring business process outcomes at different stages of the business process based upon the classified business process instances.

9930845

15397872

1. A plant, a plant part, or a seed of soybean variety CL1463057, wherein a representative sample of seed of said soybean variety CL1463057 has been deposited under ATCC Accession Number PTA-123638.

20030068844

09964472

1. A process for making an integrated circuit, comprising: a) providing a substrate or epitaxial layer of p-type material; and b) applying a sequence of mask steps as follows: (1) applying a first mask and forming at least one N-well in said p-type material therethrough; (2) applying a second mask and forming an active region therethrough; (3) applying a third mask and forming a p-type field region therethrough; (4) applying a fourth mask and forming a gate oxide therethrough; (5) applying a fifth mask and carrying out a p-type implantation therethrough; (6) applying a sixth mask and forming polysilicon gate regions therethrough; (7) applying a seventh mask and forming a p-base region therethrough; (8) applying an eighth mask and forming a N-extended region therethrough; (9) applying a ninth mask and forming a p-top region therethrough; (10) applying a tenth mask and carrying out an N+ implant therethrough; (11) applying an eleventh mask and carrying out a P+ implant therethrough; (12) applying a twelfth mask and forming contacts therethrough; (13) applying a thirteenth mask and depositing a metal layer therethrough; (14) applying a fourteenth mask and forming vias therethrough; (15) applying a fifteenth mask and depositing a metal layer therethrough; and (16) applying a sixteenth mask and forming a passivation layer therethrough; and wherein up to any three of mask steps 4, 7, 8, and 9 may be omitted depending on the type of integrated circuit.

4800763

07147780

1. A method of sampling a fluid stream with reference to one or more criteria by drawing samples and analysis, characterized by drawing successively from the fluid stream a number of samples that is at least one more than the number of analysis criteria, each sampling step including analyzing a portion of the fluid stream and preserving another portion, and then, at intervals, on the ground of a selection criterion, removing one of the samples preserved and drawing a fresh sample, thereby again analyzing a portion of the fluid stream and preserving another portion, the arrangement being such that, at all times, one sample is preserved that corresponds with an extreme value of each of the criteria of analysis.

20160308900

15098263

1. A method for identifying and preventing malicious application programming interface (API) attacks in a client-server architecture, performed on a computer having a processor, a memory, and one or more code sets stored in the memory and executed by the processor, the method comprising: during a learning stage: monitoring, by the processor, all requests sent to a server API and all responses sent from the server API; identifying, by the processor, one or more first characteristic data points of each request and response sent during the learning stage; and determining, by the processor, based at least in part on the identified one or more first characteristic data points, one or more characteristic data models, wherein a characteristic data model represents at least one of an expected input to the API and an expected output of the API; and during a protection stage: monitoring, by the processor, all requests sent to the server API and all responses sent from the server API; identifying, by the processor, one or more second characteristic data points of each request and response sent during the protection stage; and one of validating and invalidating, by the processor, the identified one or more second characteristic data points against the one or more characteristic data models.

20100232722

12554390

1. A method of encoding an image, the method comprising: determining a context model to be used to entropy encode a residual value of a current pixel with reference to at least one pixel value that is encoded before the current pixel; determining a residual value group to which the residual value belongs, based on the determined context model; selecting a code table based on the determined context model and the determined residual value group; and entropy encoding the residual value according to the selected code table.

7509243

11148086

1. A method of determining and building a high-speed VLSI reduced-order interconnect, comprising: a) accessing an interconnect in VLSI to be analyzed and creating a mathematical model based on electrical parameters including resistance, capacitance, inductance, coupling capacitance, and mutual inductance of the interconnect; b) feeding an expand frequency point based on a predetermined operating frequency; c) performing a non-symmetric Lanczos Algorithm; d) determining an order of reduced model for model reduction based on iteration termination conditions; e) performing a projection algorithm; f) creating a reduced system; g) inputting the reduced system into a signal analyzer for a high-speed and very-large IC interconnect; and h) analyzing the reduced system and building an interconnect using the reduced system, wherein the model reduction method has a transfer function of the perturbed system equal to the transfer function H(s) of original system, and a transfer function H Δ (s) of modified nodal analysis expressed as follows: ( A - Δ ) ⁢ ⅆ x Δ ⁡ ( t ) ⅆ t = x Δ ⁡ ( t ) - ru ⁡ ( t ) , ⁢ y Δ ⁡ ( t ) = c T ⁢ x Δ ⁡ ( t ) where, Δ=v q+1 δ q+1 w q ′+v q β q=1 w q=1 ′, q is the order of reduced model employed the non-symmetric Lanczos Algorithm comprising: 1) inputting a state equation of a target system; 2) selecting an expand frequency point of a reduced system; 3) determining an order of the reduced system; 4) performing the non-symmetric Lanczos Algorithm to create a projection matrix; 5) performing a double projection on state variables by means of the projection matrix to obtain a state equation of the reduced system; and 6) simulating by applying the state equation of the reduced system, while δ q+1 and β q+1 are obtained from computational process of reduced system; and the transfer function H Δ (s) of perturbed system is equal to transfer function Ĥ(s) of reduced system.

20130257594

13573396

1. A system that tracks assets as they move from one location to another location in order to detect anomalies in the movement and/or handling of an asset comprising in combination: a tag attached to each of said assets that stores a code that uniquely identifies each of said assets; a database in which is stored data for each of said assets to which data said code points: a computer processor coupled to said data base; an expert system program coupled to said processor; said processor accessing said expert system program and said data base to classify said assets into classes with common proprieties; a tag reader input device that reads said tag attached to an asset as said asset is moved from one location as it is received at another location, said input device reading the time and location of said one location and said another location. said tag reader input device coupled to said database and storing in said database data parameters including location and time of each location of said assets in accordance with classification to which an asset has been assigned; said processor accessing said expert system program and said data base to build a predictive model for a class from the stored data parameters for assets of that class; said processor accessing said expert system program and said predictive model for a class and comparing said data parameters for an asset movement with said predictive model and generating a flag message when said data parameters do not match said predictive model within predetermined range.

20130226879

13434647

1. A computer-implemented method for detecting a set of inconsistent data records in a database including multiple records, comprising: selecting a data quality rule representing a functional dependency for the database; transforming the data quality rule into at least one rule vector with hashed components; selecting a set of attributes of the database; transforming at least one record of the database selected on the basis of the selected attributes into a record vector with hashed components; computing a dot product of the rule and record vectors to generate a measure representing violation of the data quality rule by the record.

20130097414

13274911

1. A system for reconfiguring a node of a complex system health monitoring system without recompiling and relinking executable code, comprising: a software module containing previously compiled instructions to perform one of a plurality of different standardized functions; a computing node comprising a processor and plurality of software objects, the processor inoperable communication with the software module and configured to execute the previously compiled instructions, the plurality of software objects including utility functions and internal algorithms that facilitate the execution of the previously compiled instructions; and a configuration file configured to provide static and dynamic data to the software module, the configuration file comprising a dynamic data store (DDS), a static data store (SDS) and an binary code database (BCD), the BCD comprising a library of externally compiled executable algorithms that are callable and executable by the software module, the BCD being configured with database identification and retrieval data structures associated with library of externally compiled executable algorithms.

20090239473

12382363

1. A method for transmitting channel information in a multi-antenna system, the method comprising: calculating channel quality information (CQI) with respect to each mode; comparing the CQI with respect to each mode to a threshold value with respect to each mode; and transmitting CQI with respect to a mode having higher CQI than the threshold value as channel information.

20150255061

14201704

1. A method of adapting and personalizing a deep neural network (DNN) model for automatic speech recognition (ASR), comprising: receiving, by a computing device, at least one utterance comprising a plurality of speech features for one or more speakers from one or more ASR tasks; applying, by the computing device, a decomposition approach to an original matrix in the DNN model; in response to applying the decomposition approach, converting the original matrix into a plurality of new matrices, each of the plurality of new matrices being smaller than the original matrix; adding, by the computing device, another matrix to the plurality of new matrices; and adapting, by the computing device, the DNN model by updating the added matrix, the adapted DNN model comprising a reduction in a number of parameters in the DNN model.

10055843

15562088

1. A system for polyp detection using optical images acquired during a colonoscopy, the system comprising: an input configured to receive a set of optical images acquired from a patient during a colonoscopy; a processor configured to process the series of optical images with steps comprising: i. receiving the set of optical images from the input; ii. generating polyp candidates by analyzing the received set of optical images; iii. generating a plurality of image patches around locations associated with the generated polyp candidates; iv. applying a set of convolutional neural networks to the corresponding image patches; v. computing probabilities indicative of a maximum response for each convolutional neural network; vi. identifying polyps using the computed probabilities, wherein the processor is further configured to compute a confidence score for each polyp candidate using the computed probabilities; vii. generating a report indicating identified polyps; and an output for displaying the report.

8178775

12247049

1. A method for controlling orientation of a photovoltaic collection system to track apparent movement of the sun using a photovoltaic-collection-system-derived tracking algorithm, the method comprising: determining an initial orientation of a photovoltaic collection system; automatically deriving, using output from the photovoltaic collection system as it tracks apparent movement of the sun across the sky caused by the spinning of the earth on its axis and its orbit around the sun, a tracking algorithm for controlling orientation of the photovoltaic collection system to track the apparent movement of the sun, wherein automatically deriving the tracking algorithm includes estimating a trajectory of the sun during a first day; and controlling orientation of the photovoltaic collection system to track the apparent movement of the sun using the photovoltaic-collection-system-derived tracking algorithm, wherein controlling the orientation of the photovoltaic collection system includes using the estimated trajectory to drive the photovoltaic collection system during a second day after the first day.

20130028511

13199303

1. A method of determining a saliency map for an image, said method comprising using a processing device for executing the steps of determining to which of at least two predetermined scene categories a scene depicted in the image belongs wherein each of the at least two predetermined scene categories is associated with a different predetermined set of weights, each predetermined set of weights comprising weights for colour dependent subbands, selecting the weight set associated with the determined scene category, splitting the image into colour dependent frequency subbands and orientation subbands by splitting the image into colour components and applying wavelet transformation to each colour component, determining early feature maps for the subbands by extracting visual features from the wavelet transforms by a center-surround mechanism based on a Difference of Gaussian, using the selected weight set for weighting the early feature maps and fusing the weighted feature maps.

8834367

13658156

1. A method of assessing blood glucose levels, comprising providing a patient with a blood glucose and lifestyle factors tracking apparatus, the blood glucose and lifestyle factors tracking apparatus comprises: a foldable substrate having a front side including a plurality of regions for tracking blood glucose values; a second side including a portion having a plurality of instructions for using the plurality of regions for tracking blood glucose values; and a foldable portion, wherein the plurality of instructions for using the plurality of regions for tracking blood glucose values are printed on the second side of the foldable substrate in a manner that folding the foldable portion causes the plurality of instructions on the second side to overlap the plurality of regions for tracking blood glucose values of the front side in a manner to instruct the patient to input blood glucose and lifestyle factors into the plurality of regions for tracking blood glucose values on the front side.

8577775

13601386

1. A computer-implemented method of evaluating a relationship between a first investment and a second investment, the method comprising: generating, using a computer, a first deal code record comprising identifications of a first position as a primary position for a first investment and a second position as a hedge position for the first investment; storing, using a computer, the first deal code record in a database; generating, using a computer, a second deal code record comprising identifications of a primary position for a second investment and a hedge position for the second investment; storing, using a computer, the second deal code record in the database; querying, using a computer, for performance data over historical periods regarding the positions in the first and second deal code records; determining, using a computer, whether combined performance data regarding the first deal code record during each historical period exceeds a profit and loss threshold value; determining, using a computer, whether combined performance data regarding the second deal code record during each historical period exceeds the threshold value; determining, using a computer, a qualifying number of historical periods in which both the first and second deal code records demonstrate combined performance data that exceeds the threshold value; determining, using a computer, a relationship between the first deal code record and the second deal code record based at least on the number of qualifying historical periods, wherein a relation value based on an extent of the relationship is calculated, using a computer, by subtracting a first value from a second value to obtain a third value, and dividing the third value by the total number of qualifying historical periods, the first value is a number of qualifying historical periods that combined performance data regarding the first deal code record indicates a change in the same direction as combined performance data regarding the second deal code record, and the second value is a number of qualifying historical periods that combined performance data regarding the first deal code record indicates a change in an opposite direction from combined performance data regarding the second deal code record; and displaying, using a computer, an indication that represents the relationship.

8355997

12618159

1. A computer-implemented method of developing a classifier, comprising: receiving input for a case, the case comprising a plurality of instances and an example, the example comprising a plurality of data fields each corresponding to one of the plurality of instances, wherein the input indicates which one, if any, of the plurality of instances includes a data field belonging to a target class; and training the classifier based, at least in part, on the input from the trainer.

20110071855

12565080

1. A computer-implemented method for performing analysis of financial data, comprising the steps of: storing, in a computer readable memory, financial data related to a population of financial data records and segmented into a number (x) of classes, wherein the class segments are mutually exclusive and collectively exhaustive of the financial data, and scenario data for a set of scenarios, wherein each of the scenarios is defined at least in part by a set of variables, and wherein the scenario data for each of the scenarios comprise at least some parameter values for the set of variables; providing a computer processor associated with the computer readable memory with a model of a system defined at least in part by the set of variables; and processing, with the computer processor, the financial data and the scenario data using the model to obtain an estimated model outcome distribution comprising a distribution of estimated model outcomes relating to the system and based on the set of scenarios, the processing further comprising: selecting a first subset of the financial data as a first sample, the first subset drawn without replacement from each of the class segments of the population and having a sample size (z); performing, with the model and the first subset, a first test of the set of scenarios to obtain a first set of sample outcomes for each of the scenarios; and repeating the selecting and performing steps using additional subsets of the financial data to perform additional tests of the set of scenarios and to obtain additional sets of sample outcomes for each of the scenarios; wherein the additional subsets are drawn without replacement from each of the class segments; wherein the first sample outcomes and the additional sample outcomes are combined to create a cumulative estimated model outcome distribution; wherein the selecting and performing steps are repeated until the cumulative model outcome distribution is within a pre-determined acceptable tolerance limit from a distribution of fully assessed model outcomes for the set of scenarios obtainable by performing, with the model, a single test of the set of scenarios using all of the data; and wherein the cumulative model outcome distribution is identified as the estimated model outcome distribution; wherein the number (x) of classes, the sample size (z), and a number (y) of tests comprising a count of the number of times that the performing step is conducted ensure that the cumulative model outcome distribution is within the pre-determined acceptable tolerance limit from the distribution of fully assessed model outcomes.

20180074412

15262452

1. A method comprising: accessing an indication of an output of an optical source of a photolithography system, the optical source being associated with a range of input values and a corresponding range of output values, the correspondence between the range of input values and the corresponding range of output values being based on an initial gain relationship; accessing an indication of an input provided to the optical source of the photolithography system, the provided input being associated with the accessed indication of the output of the optical source; determining an output error from an expected amount of output and the accessed indication of the output of the optical source; estimating a local gain associated with the accessed indication of the input provided to the optical source; determining a gain error from the estimated local gain and an expected local gain; estimating a current value of one or more operating metrics of the optical source based on the output error and/or the gain error; and updating the initial gain relationship for the optical source based on the estimated current value of the one or more operating metrics to determine an updated gain relationship for the optical source, the updated gain relationship relating the range of input values to a corresponding range of expected output values.

20100038416

12228585

1. A device for collecting information from a customer concerning a point of interest, the device comprising: a memory configured to store a unique location identifier associated with the point of interest; a processor configured to: receive a unique customer identifier from the customer; store the unique customer identifier in the memory; receive the information concerning the point of interest from the customer; and store the information in the memory.

8855487

13808267

1. A method for obtaining routing information of an electro-optical multi-layer network, comprising: determining ports on which an optical transmitter and an optical receiver are located; and adding electro-optical conversion information to the routing information on a port of an optical layer node side or an electro layer node side on which the optical transmitter and the optical receiver are located.

20080104062

11927458

1. A method of determining whether a guarded term is represented in a message, comprising: associating a portion of the message with the guarded term; and evaluating a cost of the association.

20140051456

13585676

1. A method for determining which of a plurality of data connectivity pipes will be used to transmit data for one or more applications operating on a vehicle, said method comprising: determining a default bandwidth demand and a default delay tolerance for each of the applications; modifying the default bandwidth demand and the default delay tolerance for each of the applications as the applications are active over time; identifying which of the applications are active at a particular point in time; identifying a number of configurations based on the number of applications that are active at the particular point in time and the number of the data pipes that are available to transmit data for the applications; identifying a plurality of performance metrics for each configuration; determining an optimal performance value for each performance metric from all of the configurations; determining an overall utility function for each configuration that is based on its performance value and the optimal performance value; and selecting a data pipe for each application that is active based on a maximum overall utility function from each application's available overall utility function.

20080221954

12050371

1. A computer-implemented ranking-based method for evaluating regression models by obtaining predictions ŷ from one or more models to be evaluated on a test set of customers for which the true value y of the quantity of interest has been observed comprising the steps of: storing the test set resides in an electronic database sorted in increasing order such that “large” corresponds to one of a plurality of customers and/or potential customers with largest perceived spending budget, and “small” corresponds to one of a plurality of customers and/or potential customers with smallest perceived spending budget; applying all models to customer data from the test set to obtain predictions for the spending for each model and customer; converting the predictions into ranks and storing for each model in one or more electronic databases as a model ranking table, a number of ranking order switches relative to ranking of the observed customer spending being calculated for each model and ranking order switches being defined as those changes in ranking position of the prediction relative to the order of the true observations y; calculating a measure of a magnitude of erroneous ranking from a weighted sum of ranking order switches; transforming the number of ranking switches and weighted sum of ranking order switches into a range of [−1, 1] wherein −1 corresponds to making all possible errors (inverse ranking) and 1 corresponds to a perfect model wherein said number of ranking switches has been transformed to represent a difference between a probability that the ranking of two customers and/or potential customers are in the same order versus the probability that two of the customers and/or potential customers are in different orders from the originally obtained rank; normalizing transformed measures of order switches into a range of [0,1] wherein 1 corresponds to perfect ranking and 0 corresponds inverse ranking; calculating a variance of measures of order switches and determining confidence intervals for each ranking measure; updating the model performance table with the ranking measures and their confidence intervals; and outputting the ranking measures and confidence levels as well as graphical representations thereof to a domain expert, who will choose based on this information the best model m* of the one or more models evaluated, and storing the predictions of ŷ=m*(x) in the optimal prediction table.

20060114780

10904759

1. A recording device for selecting a preferred write strategy for an optical disc, the optical disc containing a characteristic value indicating manufacturer information or material information of the optical disc, the recording device comprising: a reading/writing circuit coupled to read the characteristic value of the optical disc; and a controller coupled to the reading/writing circuit for selecting a first set of write strategies according to the characteristic value, and determining the preferred write strategy by evaluating actual writing quality of the write strategies included in the first set of write strategies.

20160155471

15013868

1. A method for selectively designating tracks as guard regions between bands having a variable storage capacity per band, comprising: a) providing a plurality of tracks in an area of a disk surface consistently configured for shingled magnetic recording, the tracks being grouped into bands by means of entire tracks designated as circular guard regions, each guard region having a constant width and an invariable sector count, the entire area being configured without spare sectors, and each band having a variable storage capacity without a minimum storage capacity, b) determining that one or more defective sections are physically located on a single track in a first band, said single track being any track of said first band, c) determining the radial distances on said disk surface between said one or more defective sections and the preceding and succeeding guard regions adjacent to said first band, d) selecting said preceding guard region if said one or more defective sections are essentially located in the upper half of said first band, e) selecting said succeeding guard region if said one or more defective sections are essentially located in the lower half of said first band, f) displacing at least the selected guard region onto the physical location of said one or more defective sections, wherein the entire, circular guard region is displaced in the radial direction of said disk surface such that the radius of the circular guard region is changed, g) decreasing the track count of said first band by the number of tracks, by which said selected guard region is displaced, h) converting the former physical location of said selected guard region into one or more newly constituted tracks and integrating said one or more newly constituted tracks into the regular tracks of a second band that is adjacent to said first band, said one or more newly constituted tracks being entire, circular tracks, i) reassigning payload data by moving allocations from said first band to said second band to such an extent that the decreased track count of said first band is compensated, j) storing payload data at least on said one or more newly constituted tracks, whereby said one or more defective sections are remedied without sector slipping and without spare sectors.

8285531

12105108

1. A method of optimizing a drilling tool assembly comprising: inputting well data into an optimization system, the optimization system including an experience data set and an artificial neural network; comparing the well data to the experience data set; developing an initial drilling tool assembly based on the comparing the well data to the experience data, wherein the drilling tool assembly is developed using the artificial neural network; simulating the initial drilling tool assembly in the optimization system; creating result data in the optimization system based on the simulating; and optimizing the drilling tool assembly based on the result data.

20140096119

13630147

1. A method, comprising: setting a dynamic adjustment value of a vectorization loop; executing the vectorization loop to vectorize a loop of by grouping iterations of the loop into one or more vectors; identifying a dependency between iterations of the loop; and setting the dynamic adjustment value based on the identified dependency.

10127061

14832726

1. A method for controlling priority of dynamic compilation by a computer system, the method comprising: executing compilation tasks and application tasks by using threads pooled in a thread pool; monitoring a metric related to the dynamic compilation; determining whether the metric meets a predetermined criterion; and increasing resources for executing compilation tasks to reach peak throughput without relying on root privilege or losing thread fairness by causing a lowering of priority of the threads executing the application tasks in returning of the threads to the thread pool for next execution by a processor if the metric is determined to meet the predetermined criterion.

9750454

14847179

1. A method for precise, mobile acquisition of training data, the method comprising: determining sensor values in movement patterns via said mobile device that is fixed to a body segment; calculating training data from said sensor values using said mobile device; storing said training data in a first storage unit in said mobile device; selecting a sport exercise X with a set movement pattern and a training utensil Y, from sport exercises and training utensils via of the mobile device; recalling predetermined movement data, comprising the characteristic variables of set movement patterns of one said sport exercise X using one said training utensil Y from a second storage unit in said mobile device; determining raw sensor values using said mobile device in said set movement patterns of said sport exercise X using said training utensil Y, comprising acceleration and angular speed values; calculating reworked measurement values using said mobile device based on said predetermined movement data and said raw sensor values; calculating multiple training data using said mobile device, on the basis of said reworked measurement values.

20130329833

13493434

1. A method of compensating for distortions introduced by an electronic device, comprising: receiving an input signal to a predistorter and an output signal from the electronic device; generating a first set of model coefficients based on a first predistorter model used in an adaptation circuit, the input signal to the predistorter, and the output signal; generating a second set of model coefficients for a second predistorter model by applying a conversion function to the first set of model coefficients, wherein the second predistorter model is used by the predistorter; adapting the predistorter based on the second set of model coefficients; and predistorting input signals to the predistorter based on the second predistorter model.

20030208284

10138859

1. A computer program product encoding a computer program for executing on a computer system a computer process for optimizing a computer system configuration, the computer process comprising: generating a candidate computer system configuration from a skeleton configuration and a set of one or more parameters that parameterize the skeleton configuration; receiving simulation data generated by a performance simulator based on the candidate computer system configuration; computing an objective based on one or more selected variables from the simulation data; and comparing the objective to a previously computed objective based on a previously simulated computer system configuration to yield an optimum configuration.

8832361

13962455

1. A storage device comprising: a semiconductor memory which has memory areas, a part of the memory areas being assigned to a user area which can be accessed from outside, the user area including allocation units (AUs), each management unit including recording units (RUs); a controller instructing to write data to the semiconductor memory in accordance with a request the controller receives; a first register provided in the controller and holding a class value corresponding to a performance class of the storage device; and a second register provided in the controller and holding information of a size of an AU, the size of the AU being memory management information used to manage the user area, wherein a worst average write performance of the storage device, which is an average of measured sequential writes performance, is larger than or equal to performance specified by the class value held in the first register, a write size of each of the sequential writes is a size of one of the RUs, and the first and second registers are accessible from outside.

20130152060

13762934

1. A dual evaluation mode method comprising: determining, for certain functions and expressions within input computer code, whether each function and expression may have any recursive dependencies; generating, using one or more computer processors, eager evaluation mode executable code for one or more elements of the input computer code based on the act of determining; and providing both eager evaluation mode executable code and non-eager evaluation mode executable code to runtime software that supports both eager and non-eager evaluation modes.