Abstract: Estimating the overall efficacy of a mathematical model of system behavior involves providing a template representing factors that affect the overall efficacy of the mathematical model. A Bayesian Belief Network (BBN) having nodes based on the factors of the template is created and the BBN is used to obtain an estimate of the overall efficacy of the mathematical model of system behavior.

Abstract: A method is described for structurally individualized simulation of the introduction of a wall support element into a section of a tubular structure. To this end, image data of the interior of the section of the tubular structure are provided. A start point and an end point of the section of the tubular structure are then determined, and a lumen and a profile line of the tubular structure are determined between the start point and the end point. Furthermore, an individual elastic structure model for the section of the tubular structure is identified by adapting a tubular elastic initial model to the section of the tubular structure on the basis of the identified lumen and the profile line, and a tubular elastic wall support element model which is positioned inside the individual structure model is provided.

Abstract: A rules system for creating rules to an expert system is provided, the rules system providing a user-friendly, guided process for creating such rules.

Abstract: An automotive air conditioner includes a storage unit which stores a plurality of pieces of state information as respective learned data; a learning unit which constructs a probabilistic model; a control information correcting unit which corrects setting information, etc., related to a vehicle occupant's setting operation in accordance with a calculated probability so as to achieve a specific setting operation; and an air-conditioning control unit which controls an air-conditioning unit in accordance with the corrected setting information, etc.

Abstract: A hardware-implemented method for proofreading updates of connections in a hardware artificial neural network (hANN) includes computing a draft weight change independently at a connection between neuroids and at a corresponding dedicated special purpose nousoid, determining whether the draft weight changes agree, and executing a weight change at the connection equal to the draft weight change upon determining that the draft weight changes agree.

Abstract: A method and system for creating healthy operating envelope from only data samples obtained during normal operation/behavior of dynamic systems is provided. This method determines healthy operating envelope by clustering a stream of discrete event code sequences from the underlying system under normal operation condition only. The method is unsupervised, that is, requiring no prior knowledge of event code patterns corresponding to different operation conditions. Such created envelope can be used for fault detection and health monitoring of dynamic systems.

Abstract: A method (and structure) for using reasoning heuristics in a network-based information system based on an entity/relation paradigm and characterized as being a self-similar hypergraph. The method includes packaging domain-independent reasoning heuristics so that they can be attached to data in a self-similar-hypergraph information system, thereby allowing self-describing knowledge capsules to be created from the data.

Abstract: A system is disclosed for the graphical entry of knowledge information in Task-Method-Knowledge (TMK) notation into a computer system. The system comprises methods for entering the TMK hierarchy, defining new tasks 510, methods 512, procedures 522, and subtasks 518. Defined elements may be reviewed, modified, or deleted. Inputs to the tasks may be defined and the outputs of methods and procedures may be assigned. The hierarchy may be processed towards a solution. The entered hierarchy is displayed with visual clues as to the state and progress of the solution process.

Abstract: A method of identifying and localizing objects belonging to one of three or more classes, includes deriving vectors, each being mapped to one of the objects, where each of the vectors is an element of an N-dimensional space. The method includes training an ensemble of binary classifiers with a CISS technique, using an ECOC technique. For each object corresponding to a class, the method includes calculating a probability that the associated vector belongs to a particular class, using an ECOC probability estimation technique. In another embodiment, increased detection accuracy is achieved by using images obtained with different contrast methods. A nonlinear dimensional reduction technique, Kernel PCA, was employed to extract features from the multi-contrast composite image. The Kernel PCA preprocessing shows improvements over traditional linear PCA preprocessing possibly due to its ability to capture high-order, nonlinear correlations in the high dimensional image space.

Abstract: System and method for developing cognitive skills in a student, utilizing a computing device to present stimuli and to record responses. A stimulus may be graphically presented to the student via the computing device, and the student may be required to respond to the stimulus. A determination may then be made as to the correctness of the student's response. The graphically presenting, requiring, and determining may be performed for each of a plurality of stimuli. Additionally, the graphically presenting, requiring, determining, and performing may be performed in an iterative manner to improve the cognitive skills of the student. Various exercises directed to different cognitive skills and learning approaches may utilize this basic framework, and may be performed in an iterative manner to build cognitive skills in the student.

Abstract: Systems and methods provide for preprocessing non-metric response categories in order to efficiently cluster or partition predictors have similar responses. The non-metric response categories are transformed into distance vectors by calculating a frequency count for the response, transforming the frequency count to a proportional value, and calculating a distance vector using the vector of proportional values.

Abstract: An improved security system for and method of detecting and responding to cyber attacks on a network or network element. The system comprises: (a) an intelligent agent-based information retrieval subsystem configured so as to automatically search for and retrieve relevant data from distributed sources; (b) a rule-based inferencing mechanism configured so as to interpret retrieved data within the situational context to support event and alert generation for cyber threat assessment and prediction; and (c) a threat assessment and prediction mechanism configured so as to capture relating to the interrelationship between cyber sensor outputs and cyber attacks.

Abstract: Systems, methods and apparatus are provided through which in some embodiments an autonomic entity manages a system by generating one or more stay alive signals based on the functioning status and operating state of the system. In some embodiments, an evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy. The evolvable neural interface receives and generates heartbeat monitor signals and pulse monitor signals that are used to generate a stay alive signal that is used to manage the operations of the synthetic neural system. In another embodiment an asynchronous Alice signal (Autonomic license) requiring valid credentials of an anonymous autonomous agent is initiated. An unsatisfactory Alice exchange may lead to self-destruction of the anonymous autonomous agent for self-protection.

Abstract: Complex nested if-then statement on data objects in a digital computer are organized as a plurality of logical case statements; for each case statement, a set of binary condition arrays is provided and for each data object a condition set. Case statements are executed on the data objects for which a condition array from the set of binary condition arrays matches the condition set for the data object.

Abstract: An optimization processing method comprises forming a plurality of islands each having a plurality of individuals and repeating crossover, mutation, evaluation and selection on the individuals until the desired condition has been satisfied by applying a genetic algorithm to each of the plurality of islands thereby obtaining an optimized solution, in which the optimized solution is obtained by migrating individuals to other islands.

Abstract: A special purpose processor (SPP) can use a Field Programmable Gate Array (FPGA) to model a large number of neural elements. The FPGAs or similar programmable device can have multiple cores doing presynaptic, postsynaptic, and plasticity calculations in parallel. Each core can implement multiple neural elements of the neural model.

Abstract: A method for optimizing fracture treatments includes interpreting a nominal pump schedule corresponding to a nominal value for each fracture control parameter. The method further includes interpreting environmental variables, and interpreting probability distributions for each of the environmental variables that is uncertain. The method further includes defining an objective function such as a net present value of each fracture treatment over a 365 day period following the fracture treatment. The method includes determining an optimal value for each fracture control parameter according to the objective function by determining the fracture control parameter values that yield the best mean net present value given the variability in the environmental variables as described by their probability distributions.

Abstract: A computer implemented method, apparatus, and computer usable program product for generating an expected behavior model. The process parses event data derived from video data to identify behavioral patterns, wherein the event data comprises metadata describing events occurring in a selected environment. The process analyzes the behavioral patterns to identify a set of expected behavioral patterns occurring in the environment, and generates the expected behavioral model using the expected behavioral patterns.

Abstract: Methods and apparatus, including computer program products, for scalable ontology reasoning. A method of generating a summarized ontology includes loading an ontology from a store, eliminating relationships in the ontology, the eliminating relationships including an insertion of new relationships that simplify the ontology, eliminating individuals in the ontology, the eliminating individuals including insertion of new individuals to simplify the ontology, eliminating concepts in the ontology including insertion of new concepts to simplify the ontology, and generating the summarized ontology from the eliminating relationships, eliminating individuals and eliminating concepts.

Abstract: A system and method are disclosed for generating a robust model of a system that selects a modeling function. The modeling function has a set of weights and the modeling function has a complexity that is determined by a complexity parameter. For each of a plurality of values of the complexity parameter an associated set of weights of the modeling function is determined such that a training error is minimized for a training data set. An error for a cross validation data set is determined for each set of weights associated with one of the plurality of values of the complexity parameter and the set of weights associated with the value of the complexity parameter is selected that best satisfies a cross validation criteria. Thus, the selected set of weights used with the modeling function provides the robust model.