Abstract: The present invention provides a system, method and apparatus for allocating resources with a linear programming model comprising an objective function and a set of constraints describing feasible allocations of the resources. The method ranks constraints based on a numerical measure derived from criteria selected from at least a first and second group and selects one or more of the top-ranked constraints. A new problem is determined from the model's objective function, the previously selected constraints, and the newly selected constraints, and a tentative resource allocation is determined based on the new problem. Whenever the tentative resource allocation violates a model constraint not in the current problem, one or more of the top-ranked such violated constraints are selected, and the new problem determination and tentative resource allocation steps are repeated. The resources are allocated according to the tentative resource allocation when it does not violate any model constraints.

Abstract: A system for identifying keywords in search results includes a plurality of neurons connected as a neural network, the neurons being associated with words and documents. An activity regulator regulates a minimum and/or maximum number of neurons of the neural network that are excited at any given time. Means for displaying the neurons to a user and identifying the neurons that correspond to keywords can be provided. Means for changing positions of the neurons relative to each other based on input from the user can be provided. The change in position of one neuron changes the keywords. The input from the user can be dragging a neuron on a display device, or changing a relevance of two neurons relative to each other. The neural network can be excited by a query that comprises words selected by a user. The neural network can be a bidirectional network. The user can inhibit neurons of the neural network by indicating irrelevance of a document.

Abstract: Various neural-network based surrogate model construction methods are disclosed herein, along with various applications of such models. Designed for use when only a sparse amount of data is available (a “sparse data condition”), some embodiments of the disclosed systems and methods: create a pool of neural networks trained on a first portion of a sparse data set; generate for each of various multi-objective functions a set of neural network ensembles that minimize the multi-objective function; select a local ensemble from each set of ensembles based on data not included in said first portion of said sparse data set; and combine a subset of the local ensembles to form a global ensemble. This approach enables usage of larger candidate pools, multi-stage validation, and a comprehensive performance measure that provides more robust predictions in the voids of parameter space.

Abstract: A function optimization method includes the operations of: constructing an upper bound using a double majorization bounding process to a sum-of-exponentials function including a summation of exponentials of the form ? k = 1 K ? ? ? k T ? x ; optimizing the constructed upper bound respective to parameters ? to generate optimized parameters ?; and outputting the optimized sum-of-exponentials function represented at least by the optimized parameters ?. An inference process includes the operations of: invoking the function optimization method respective to a softmax function constrained by discrete observations y defining categorization observation conditioned by continuous variables x representing at least one input object; and applying the optimized softmax function output by the invocation of the softmax function optimization method to the continuous variables x representing at least one input object to generate classification probabilities.

Abstract: The present invention relates to methods and systems for applying evolutionary algorithms to generate robust search strategies for problems including decision variables. In one aspect, the invention encodes genomes of at least one triplet comprising a variable, assignment priority, and assigned value. The genome may later be decoded to determine a partial or complete assignment of values to variables. If a partial assignment is reached, a search strategy may be applied to generate a complete or more complete assignment. The genomes may also be evolved to produce offspring genomes. One type of evolutionary operator, called the Lamarckian operator is introduced, wherein the similarities, differences, and unbound variables resulting from the decoding of two or more parent genomes are collected. These collections are then used to encode an offspring genome, building upon the strengths of the parents.

Abstract: The present invention relates to a method for optimizing the design of a shape morphing structure using a genetic algorithm. The method includes defining design parameters of a surface having variable properties into a chromosome. The variable properties of the chromosome are the actual properties of the chromosome. The chromosome has a total of Nmax genes, where each gene corresponds to a variable property element in the surface. Additionally, each gene has n design parameters, wherein the design parameters are incremental changes to the actual properties of the chromosome. A genetic algorithm is employed to optimize the genes until a fitness level for at least one chromosome has been exceeded. When the fitness value for any chromosome in the population is above a predetermined threshold, then the design process is terminated and the final design solution[s] are the design parameters of the chromosome[s] that exceed the predetermined threshold value.

Abstract: Disclosed are methods, systems, and computer-readable media for determining stability of a neural system. The method includes tracking a function world line of an N element neural system within at least one behavioral space, determining whether the tracking function world line is approaching a psychological stability surface, and implementing a quantitative solution that corrects instability if the tracked function world line is approaching the psychological stability surface.

Abstract: A method, computer program product, and system are disclosed for dynamically provisioning clusters of middleware appliances. In one embodiment, the method includes referencing a resource measurement from a plurality of middleware appliances. The middleware appliances process one or more service domains and the resource measurement includes processing resources consumed by each middleware appliance for each of the one or more service domains. The method may also include determining an implementation plan based on a performance goal and one or more resource calculations. The implementation plan specifies service domain instances to activate and service domain instances to deactivate on the plurality of middleware appliances. The method may also include dynamically enabling and disabling the service domain instances on the plurality of middleware appliances based on the implementation plan.

Abstract: A method and apparatus for producing a verification of digital circuits is provided. In an exemplary embodiment, a set of Boolean and Integer constraints are derived, and a set of Boolean and Integer stimuli are generated that meet the constraints. These stimuli are then used to verify a digital design, and a verification report is generated. In other example embodiments, a computing apparatus and computer software product are provided. The computer software product containing a set of executable instructions that, when executed, configure the computing apparatus to produce a verification report by the provided methods.

Abstract: A system for use in a distributed environment comprising a first data processing system having a first entity (e.g. an object) and a second data processing system having a second entity. The first entity sends a request for an operation associated with the second entity. The request comprises an operation identifier in a first format (e.g. a first national language) and the operation comprises an operation identifier in a second format (e.g. a second national language). The environment also comprises a data structure comprising an association between the operation identifier in the first format and the operation identifier in the second format. The system comprises an intercept component for intercepting the request, a search component for searching the data structure for the operation identifier in the first format and a map component for mapping the operation identifier in the first format to the operation identifier in the second format.

Abstract: A method for wafer analysis with artificial neural network and the system thereof are disclosed. The method of the system of the present invention has several steps, including: first of all, providing a test unit for wafer test and generating a plurality of test data; next, transmitting the test data to a processing unit for transferring to output data; then, comparing the output data with predictive value and modifying bias and making the output data close to the predictive value, and repeating the steps mentioned above to train this system; finally, analyzing wafers by the trained system. Using this system to analyze wafers not only saves time, but also reduces manpower and the risk resulting from artificial analysis.

Abstract: A networked computer system, architecture, and method are provided for optimizing human and intellectual capital in the digital workplace environment.

Abstract: An optimum design management apparatus that analyzes response variable values from groups of predictor variable values, and performs optimization using the analysis result, which includes a predictor variable transmission unit that transmits groups of predictor variable values to be used for the analysis to the calculation node, and a response variable reception unit that receives response variable values of the analysis result from the calculation node. The optimum design management apparatus includes a response surface calculation unit that calculates at least one response surface from groups of predictor variable values and response variable values, an optimization calculation unit that updates groups of predictor variable values coming close to a predetermined optimization condition in the response surface to new groups of predictor variable values, and a control unit that repeats the processing continuing from the predictor variable transmission unit until a predetermined end condition is fulfilled.

Abstract: The method for the identifying of multiple input, multiple output (MIMO) Hammerstein models that includes modeling of the linear dynamic part of a Hammerstein model with a state-space model, and modeling the nonlinear part of the Hammerstein model with a radial basis function neural network (RBFNN).

Abstract: The identification of Hammerstein models relates to a computerized method for identifying Hammerstein models in which the linear dynamic part is modeled by a space-state model and the static nonlinear part is modeled using a radial basis function neural network (RBFNN), and in which a particle swarm optimization (PSO) algorithm is used to estimate the neural network parameters and a numerical algorithm for subspace state-space system identification (N4SID) is used for estimation of parameters of the linear part.

Abstract: System and method for managing a biofuel production process. An integrated dynamic multivariate predictive model is provided that includes a continuous process model representing a continuous process of the biofuel production process, a batch process model representing a batch process of the biofuel production process, and a continuous simulation framework. The batch process model interacts with the continuous process model as a nonlinear continuous process via the framework using bridging equations. An objective is received, as is constraint information specifying constraints for the biofuel production process, where the constraints are in terms of the framework, and process information related to the batch and continuous processes.

Abstract: A dynamic constraint solver for solving a constraint satisfaction problem network that includes a plurality of nodes and a plurality of constraints determines a cardinality for a set of sub-problems. The cardinality is a numeric domain that represents the minimum number of instances in a port. The solver determines if a number of identifiable instances of sub-problems is less than the minimum number of instances. The solver then causes a user interface to display the identifiable instances and a placeholder for each instance that is below the minimum number of instances and is not identifiable.

Abstract: Provided is a system which supports a user's behavior by generating a behavioral decision function indicating behavior to be adopted to a certain target. The system includes: a data acquiring section which acquires a cost caused as a result of adopting each of a plurality of behaviors to a target as training data for generating the behavioral decision function, the plurality of behaviors having already been adopted to the target; and a function generator which generates, based on the training data, the behavioral decision function to minimize the expected shortfall of a cost to be obtained as a result of adopting the behavior to the target.

Abstract: The Thought Dynamo Decision (TDD) Mapping Model includes three overlapping 3-D grids that represent decisions from the perspectives of intellect, emotions and imagined outcomes. The continuums of the logic of intellect are power-powerless, good-evil and accuracy-intuitive. The logic of emotion has three continuums: trust-fear, honor-shame, freedom-bonding. And the imagined outcomes continuums are thriving-surviving, desired identity-undesired identity, and meaningful-meaningless. The intersection of each grid forms a central tendency: creative harmony of jealous space. A five step process is used for mapping thoughts and decisions: plot, associate, adjust, solidify and employ. The dynamics of thought and decision are mapped by assigning weights to inputs, strength to associations, dynamically accounting for adjustments and solidifications over time and projecting rules of thumb in decision making onto (3) 3-D axes.

Abstract: A system for generating optimized values for variable inputs to an animal production system. The system includes a simulator engine configured to receive a plurality of animal information inputs and generate a performance projection. At least one of the animal information inputs is designated as a variable input. The system further includes an enterprise supervisor engine configured to generate first and second optimized values for the at least one variable input. The first optimized value is generated based on an optimization criteria and the second optimized value is generated based on empirical feedback after application of the first variable input.

Abstract: It is difficult to select parameter values for constraint programming problem solvers which will yield good performance. Automated tuning of such problem solvers on a per problem instance basis may be used and this involves learning a function for predicting the runtime of a problem solver depending on parameter values of the problem solver and features of the problem instance being solved. However, it takes time for such prediction functions to be learnt, either during operation of a problem solver or offline, using specified examples. To address this, information about such a prediction function is shared between two or more problem solvers to improve performance. A sharing system may be used to receive prediction function information and send this to problem solvers.

Abstract: Provided is a problem solving system. More specifically, the problem solving system provides an interface operable to receive user supplied input data, the input data having at least one user defined characteristic. The system provides an algorithm pool having a plurality of pre-defined algorithms, each algorithm having at least one associated algorithm characteristic. The system also provides a data source pool having at least one data source, each data source having at least one data characteristic. An algorithm selector is in communication with the interface, algorithm pool and data source pool.

Abstract: The present invention provides a system and method for resolving a test generation problem involving constraint resolution problems where a verification environment includes constraints that are suitable for resolution using one type of solver for a first domain and other constraints that are suitable for resolution using a different solver in a second domain. The invention further comprises variables and, in instances where at least one variable is in each of the first and second domains, using these solvers to restrict the set of permissible values of variables to be consistent in multiple domains, preferably in all relevant domains. A constraint resolution problem is divided into clusters of constraints connected within a domain, and connected clusters of clusters that are connected through shared variables that are subject to constraints in more than one cluster.

Abstract: Methods, systems, and computer program products are provided for the online convex optimization problem, in which the decision maker has knowledge of the all past states and resulting cost functions for his previous choices and attempts to make a new choice that results in minimum regret. The method does not rely upon the structure of the cost function or the characterization of the states and takes advantage of the similarity between successive states to enable the method to converge to a reasonably optimal result.

Abstract: In general, the invention is directed to a technique for selection of parameter configurations for a neurostimulator using neural networks. The technique may be employed by a programming device to allow a clinician to select parameter configurations, and then program an implantable neurostimulator to deliver therapy using the selected parameter configurations. The parameter configurations may include one or more of a variety of parameters, such as electrode configurations defining electrode combinations and polarities for an electrode set implanted in a patient. The electrode set may be carried by one or more implanted leads that are electrically coupled to the neurostimulator. In operation, the programming device executes a parameter configuration search algorithm to guide the clinician in the selection of parameter configurations. The search algorithm relies on a neural network that identifies potential optimum parameter configurations.

Abstract: A method and system is provided for analyzing a package having components. The package may include electrical or computer components. The method and system uses a computer program to receive inputted data and extract data from files. The computer program also selects the best sub-program to analyze the data to compute the parameters for packaging the components and designing the package, and displays the results of the analysis.

Abstract: A real-time operating optimized method of multi-input and multi-output continuous manufacture procedure includes steps as follows: first, using plurality of pivotal operation conditions in the manufacture procedure as optimized variables, and using the technical target associating with the pivotal operation conditions as the objective function, then, calculating on line the grades vector between pivotal operation conditions and the technical target at current time according to historical data of pivotal operation conditions and the technical target, using correlation integral method or other methods, at last, using this grades vector to define the adjustment direction of the operation conditions. When the grades vector is positive or negative, the pivotal operation conditions should be adjusted in order to change the grades vector to zero.

Abstract: A computer-implemented land planning system is designed to generate at least one conceptual fit solution to a user-defined land development problem. The system electronically creates at least one candidate solution to the land development problem. The candidate solution incorporates a number of engineering measurements applicable in development of an undeveloped land site. A fitness function quantitatively evaluates the candidate solution based on its fitness. A heuristic problem-solving strategy manipulates the engineering measurements of the candidate solution to achieve a more quantitatively fit solution to the land development problem. A computer output device outputs to a user documentation illustrating the fit solution to the land development problem.

Abstract: A navigation system and method uses loops as opposed to existing search techniques to more expeditiously find routes on a map from a starting point to a destination. Roads on a map are traced to form one or more continuous loops. Information regarding the loops is stored for future reference. A starting point and at least one destination are specified, and loops that connect the loops containing the starting point and destination are determined. A route is then formulated from the starting point to the destination using road segments or intersections where the identified loops are mutually contiguous. A list is generated including the loops and the road segments associated therewith. The road segments of an initial loop are examined and, if a road segment or intersection common to a next loop is identified, the road segments of that loop are examined, and so on, until a route from the starting point to the destination is found.

Abstract: A system for generating an animal feed formulation based on environmental nutrient inputs. The system comprises a simulator engine configured to generate a set of animal requirements in view of environmental nutrients received by an animal based on characteristics of the animal and a formulator engine configured to receive the set of animal requirements and generate an optimized animal feed formulation based on the animal requirements.

Abstract: Systems and methods for managing floating point variables are described in the present disclosure. According to one example, an embodiment of a method is described. The method comprises providing a floating point variable having a domain that includes a flag representing whether a specific value is included in or excluded from the domain of the floating point variable. The method also includes analyzing a constraint on the floating point variable to determine if the constraint excludes the specific value from the domain of the floating point variable. A value of the flag is manipulated to indicate that the specific value is excluded from the domain of the floating point variable if it is determined that the constraint excludes the specific value. In some cases, the specific value can be the value zero, for example.

Abstract: Approaches for performing simulation optimization for solving a constrained optimization problem are generally disclosed. One embodiment according to the present disclosure is to formulate a Lagrange equation having incorporated a Lagrange parameter, a first long run average function for an objective associated with the constrained optimization problem, and a second long run average function for a constraint associated with the constrained optimization problem. Then, to identify a parameter value that may lead to an extreme value for the Lagrange equation, in an iterative manner, averages of the first long run average function and the second long run average function are calculated, a gradient of the Lagrange equation is estimated, and the Lagrange parameter is updated.

Abstract: A dynamic constraint solver system for solving a constraint satisfaction problem model includes a plurality of ports. The system defines a hierarchical union that includes all problems in a lower port that is in a problem under another port in the model. The system generates a constraint that computes a cardinality of the hierarchical union and determines an included set and an excluded set for the hierarchical union. The system then propagates the included set and excluded set to participating ports of the hierarchical union.

Abstract: Various technologies and techniques are disclosed that improve handwriting recognition operations. Handwritten input is received in training mode and run through several base recognizers to generate several alternate lists. The alternate lists are unioned together into a combined alternate list. If the correct result is in the combined list, each correct/incorrect alternate pair is used to generate training patterns. The weights associated with the alternate pairs are stored. At runtime, the combined alternate list is generated just as training time. The trained comparator-net can be used to compare any two alternates in the combined list. A template matching base recognizer is used with one or more neural network base recognizers to improve recognition operations. The system provides comparator-net and reorder-net processes trained on print and cursive data, and ones that have been trained on cursive-only data. The respective comparator-net and reorder-net processes are used accordingly.

Abstract: A method for scheduling and usage of satellite bandwidth wherein data is transmitted to an artificial intelligence model for analysis and assigned a ranking. An event resource allocation model analyzes the ranking and determines how to compress the associated video. The event resource allocation model also determines when to compress the remotely stored video and transmit via satellite to a central data center where the video may be reviewed.

Abstract: A system and method is disclosed which integrates a machine learning solution into a large scale, distributed transaction processing system using a supporting architecture comprising a combination of computer hardware and software. Methods of using a system comprising such supporting architecture provide application designers access to the functionality included in a machine learning solution, but might also provide additional functionality not supported by the machine learning solution itself.

Abstract: The invention is directed to a method for training at least one learning-capable system comprising the steps of providing a predetermined training data set corresponding to a predetermined number of subjects comprising a predetermined input data set and a predetermined outcome data set, augmenting the input data set and/or the outcome data set, and training each learning-capable system using the augmented input data set and/or the augmented outcome data set.

Abstract: A graphics system includes a transposer. A read scheduler utilizes a minimum cost analysis to schedule a read transfer order for the transposer to minimize the total number of passes required to process a set of input vectors.

Abstract: Components of a distributed computing system are monitored, the components including hardware components and software components that operate on the hardware components. At least one of the software components is a service that includes a service level agreement. Performance characteristics of the components are determined based on the monitoring. The performance characteristics of the service are compared to the service level agreement to determine whether the service level agreement has been violated. At least one of the service or an additional service collocated with the service is migrated based on the performance characteristics of the components if the service level agreement has been violated.

Abstract: A method and apparatus for automated document layout creation is disclosed. In one embodiment, the method comprises receiving a first layout of document image objects and creating a second layout of document image objects subject to placement constraints corresponding to placement of document image objects, at least one of the placement constraints being based on object content in one or more of the document image objects.

Abstract: An expert system having a data storage device and a processor. The data storage device stores models having attributes, objectives having rules for evaluating the models, and strategies having rules for modifying the attributes. The processor evaluates a selected model in accordance with a selected objective and having the variable attribute set in accordance with a selected strategy to determine a characteristic value associated with the selected model and the variable attribute setting. The processor also stores information associated with improved results in the data storage device.

Abstract: A system and method for determining unknown values of certain motor parameters includes a motor input device connectable to an electric motor having associated therewith values for known motor parameters and an unknown value of at least one motor parameter. The motor input device includes a processing unit that receives a first input from the electric motor comprising values for the known motor parameters for the electric motor and receive a second input comprising motor data on a plurality of reference motors, including values for motor parameters corresponding to the known motor parameters of the electric motor and values for motor parameters corresponding to the at least one unknown motor parameter value of the electric motor. The processor determines the unknown value of the at least one motor parameter from the first input and the second input and determines a motor management strategy for the electric motor based thereon.

Abstract: A method and computer-readable medium are provided for fitting text to shapes within a graphic. According to the method, initial constraints are defined that comprise initial values describing how a shape and text within the shape should be laid out. Constraint rules are also defined for use in modifying the initial constraints when application of the initial constraints to the text in a shape results in the text overflowing the boundaries of the shape. A change may be detected to the graphic that would affect the size or position of one or more of the shapes or the text within one of the shapes. If such a change causes text to overflow when laid out using the initial constraints, the constraint rules are applied sequentially to modify the constraints. The modified constraints are then reapplied to the shapes to create a new layout for the graphic.

Abstract: A method and apparatus that detects a multiplicity of normal data sets, each of which includes values of n parameters, for each of the operation modes of an object having a plurality of operation modes. Self-organizing maps are provided for each operation mode using the normal data sets. Abnormal data sets representing virtual abnormal states are created by modifying the values of the n parameters of each of the multiple normal data sets so that as many abnormal data sets as the number of deviation vectors are created for each of the multiple normal data sets. Abnormal operation mode proportion vectors are then created by selecting a self-organizing map from the above noted self-organizing maps which has the highest similarity degree to each of the abnormal data sets.

Abstract: The present invention provides systems and methods for dynamic detection and prevention of electronic fraud and network intrusion using an integrated set of intelligent technologies. The intelligent technologies include neural networks, multi-agents, data mining, case-based reasoning, rule-based reasoning, fuzzy logic, constraint programming, and genetic algorithms. The systems and methods of the present invention involve a fraud detection and prevention model that successfully detects and prevents electronic fraud and network intrusion in real-time. The model is not sensitive to known or unknown different types of fraud or network intrusion attacks, and can be used to detect and prevent fraud and network intrusion across multiple networks and industries.

Abstract: A sensor network routing is formulated as a joint optimization problem taking into account routing cost and information aggregation. Information gain is used explicitly to optimize the routing path. The optimization approach involves a shortest path algorithm in a modified network graph. A method is provided that routes queries from an arbitrary entry point to high activity network sensor regions using inputs from sensor nodes along the path to refine the message. The multiple step look-ahead approach provides deadlock avoidance and routing around sensor network holes. For point-to-point query routing, a method based on real-time A* (RTA*) search is provided to find a path which takes detours efficiently to maximize information aggregation. Future information expected to be gained along the path from an arbitrary node to an exit node may be estimated to allow the selection of a successor sensor node.

Abstract: A system for solving a dynamic constraint satisfaction problem comprises a constraint network of variables and constraints. The system creates a first sub-problem model that includes a first model type, one or more first variables and zero or more first constraints. The system propagates the first constraints through the constraint network and determines if a first conflict is detected from propagating the first constraints. If the first conflict is detected, the system restores the constraint network variables to a first previous state before the first constraints were propagated. The system creates a first sub-problem set that includes a second model type and one or more sub-problem models. The system connects the first sub-problem model to the first sub-problem set via a second constraint and propagates the second constraint through the constraint network.

Abstract: The time it takes to recover from a system initialization failure may be reduced by determining whether to enable a recovery process immediately, or defer such a process. Sometimes it is desirable to defer a recovery process until certain interdependencies between system components are satisfied.

Abstract: A function optimization method includes the operations of: constructing an upper bound using a double majorization bounding process to a sum-of-exponentials function including a summation of exponentials of the form ? k = 1 K ? ? ? k T ? x ; optimizing the constructed upper bound respective to parameters ? to generate optimized parameters ?; and outputting the optimized sum-of-exponentials function represented at least by the optimized parameters ?. An inference process includes the operations of: invoking the function optimization method respective to a softmax function constrained by discrete observations y defining categorization observation conditioned by continuous variables x representing at least one input object; and applying the optimized softmax function output by the invocation of the softmax function optimization method to the continuous variables x representing at least one input object to generate classification probabilities.

Abstract: An iterative approach to solving the optimization problem is provided. The invention provides an iteration of four basic operations; determining the segments, balancing the segments, expanding a segment, and solving the segment optimization. The method and apparatus can use any off-the-shelf linear programming (LP) solver, such as Dash Optimization Xpress, by Dash Optimization, during the solve operation. The size of the problem fed into the LP solver remains bounded and relatively small compared to the entire problem size. Thus, the algorithm can solve problems of several orders of magnitude larger. In one embodiment of the invention, the sampling and segmentation techniques are removed to where the problem is solved at the account-level. In the above cases, the solution is produced in a more cost-effective manner and the best possible return is achieved because the doubt of achieving a true global solution is removed.