Abstract: A method and system for performing fuzzy logic based de-interlacing on film source fields that might be mixed with video on film. An embodiment of the invention comprises an adaptive de-interlacer by weighing between merge operation and interpolation operation in the case of occurring video on film motion object. A weighing factor is generated from video on film pattern based on fuzzy logic inference rules. This weighing factor specifies the weighting between merging and interpolating in assigning the pixel values of the progressive display output.

Abstract: A system and method for controlling information output based on user feedback about the information that includes a plurality of information sources. At least one neural network module selects one or more of a plurality of objects to receive information from the plurality of information sources based on a plurality of inputs and a plurality of weight values during that epoch. At least one server, associated with the neural network module, provides one or more of the objects to a plurality of recipients. The recipients provide feedback during an epoch. At the conclusion of an epoch, the neural network takes the feedback that has been provided from the recipients and generates a rating value for each of the objects. Based on the rating value and selections made, the neural network redetermines the weight values. The neural network then selects the objects to receive information during a subsequent epoch.

Abstract: This invention provides a data processing apparatus which can store and recall more complicated time-series data than those processed in related art technologies. In the data processing apparatus, a recurrent neural network (RNN) of higher layer generates long-period parameter and supplies it to an input layer of RNN of lower layer via a computing block. The RNN uses this input as a parameter and computes short-period input.

Abstract: A learning machine is used to extract useful information from vast quantities of biological data. The method includes pre-processing of training data and test data to add dimensionality or to identify missing or erroneous data points. The training data is used to train the learning machine after which the success of the training is tested using the test data. The test output is pre-processed to determine whether the knowledge discovered from the pre-processed test data set is desirable. After the training has been confirmed, live biological data can be pre-processed then input into the trained learning machine for extraction of useful information. In the preferred embodiment, the learning machine is one or more support vector machines.

Abstract: A method of forming a schedule of crude oil shipments being received at a refinery facility using a genetic algorithm has been developed. A period of time, T, within which the crude oil shipment schedule is to be formed is determined. A first generation of chromosomes is generated and a fitness function value calculated for each chromosome. A succeeding generation of chromosomes is created using a genetic algorithm and the fitness function value for each chromosome is determined. The steps of producing a succeeding generation of chromosomes using a genetic algorithm and determining a fitness function value for each chromosome are repeated for time T. The chromosome having the highest fitness function value within time T is identified to generate the schedule.

Abstract: A method and system of generating molecular mechanics force fields for computer simulation of molecular systems, including a graphic user interface 101, extensible database 108 containing parameterized force fields, data and molecular models, interfaces to quantum mechanics 102 and molecular mechanics 107 calculations, and a computational engine 105. A force field attributes assigner 205 assigns force field type, functional forms and atom types. A parameter estimator 206 makes initial force field parameters based on the database and a set of mathematical formulas. A fit engine 207 fits complex potential energy surfaces efficiently.

Abstract: A method for learning signatures of a target class using a sequential covering phased rule-induction. The method balances recall and precision for the target class. A first phase aims for high recall by inducing rules with high support and a reasonable level of accuracy. A second phase improves the precision by learning rules to remove false positives in the collection of the records covered by the first phase rules, while keeping the overall recall at a desirable level. The method constructs a mechanism to assign prediction probability scores to each classification decision. The model includes a set of positive rules that predict presence of the target class, a set of negative rules that predict absence of the target class, and a set of prediction score values corresponding to each pair-wise combination of positive and negative rules. The two-phase method is extensible to a multiphase approach.

Abstract: A system and methods for enforcing uniform branching of node-to-node inheritance links within semantic networks, to control data flows to and from such networks in conversational applications. Enforced uniform branching criteria converge the population of directly connected nodes of each node toward a small system-wide constant, and converge each sibling inheritance node to a similar level of abstractness, and are also used to select the best candidate tree from a set of competing representation trees within the semantic network. Uniform branching criteria are applied to competing trees for speech recognition, for object recognition in vision systems, for concept recognition in text scanning systems, and for algorithm definition. For speech recognition, phonemes are identified and matched to dictionary nodes in the semantic network. For visual object recognition, object features are identified and matched. For text scanning, words are identified and matched.

Abstract: An approach for providing notification services using rules-based technology is disclosed. A business rule manager module maps the business rules to business triggers, in which any pre-defined action can be performed based on the rule execution. Business rule triggers map a set of object life cycle states or business processes to set(s) of business rules; these business rules are mapped to trigger conditions. Notifications are then mapped to the business triggers such that the appropriate information can be sent to the recipients according to the business conditions or business rule actions.

Abstract: Systems and methods are provided for monitoring an application processor, such as an application processor for processing applications submitted by consumers. In accordance with an embodiment of the invention, a system is provided that, for example, includes a configuration tool for configuring an audit used to verify whether the application processor correctly invoked a processing rule. The application processor invokes such a processing rule to determine what action to take with respect to a particular application. An audit engine then searches a set of application data generated by the application processor to identify, based on the configured audit, application data where the application processor correctly invoked the processing rule. An output report generator then generates report data reflecting whether the application data correctly invoked the processing rule.

Abstract: A method and system for creating and using knowledge patterns. One or more patterns derived from one or more pharmaceutical data sources are acquired. A knowledge map is created using the one or more patterns. The knowledge map, such as a self-organizing knowledge map, includes a selected representation of a pattern space. A set of selected regions from the knowledge map are annotated. Others patterns are classified with annotated regions of the knowledge map, thereby adding additional knowledge to the knowledge map. The knowledge map is used for recognizing previously unseen or unknown patterns from large amounts of pharmaceutical data obtained by automated screening systems. The knowledge map includes knowledge for a new real or virtual drug compounds or drug therapies. The knowledge patterns may be used to select new known pharmaceutical compounds, or model new virtual pharmaceutical compounds.

Abstract: A training/managing system and method of basic ability which enables objective and efficient management for improving the basic ability of persons by training toward some kind of target. The training/managing system of basic ability 1 is provided with training terminals 3-1 to 3-n for measuring/training ability to read characters of an employee to be trained, and a management device 4 which are connected to an information communicating network 2. The management device 4 is equipped with a data management server 5 for storing measured data in time-series; performing a predetermined arithmetical operation; and deriving management data, and a management terminal 7 for presenting the management data for a business administrator.

Abstract: A method and apparatus for computing an overall or aggregate decision based on intermediate decisions as to which of a set of alternatives best characterize an object. The alternatives are partitioned into at least two series of preferences corresponding to at least two intermediate rankings. Various embodiments may base the intermediate rankings on: a machine learning technique; a decision tree; a belief network; a neural network; a static model; a program; or an evolutionary training method. Based on the preferences, a weak alternative is selected and removed from the series. The selection of the weak alternative may include identifying which alternatives lose pairwise to the other alternatives, are excluded from the first preferences, are included in the last preferences, or have a lowest average preference ranking. The selecting and removing continue until the remaining alternatives are the aggregate decision.

Abstract: A useful object-oriented knowledge base system is provided, which comprises an ‘object-oriented knowledge base’, an inference mechanism, and an ideal dictionary, etc. Sentences used as a ‘rule’ and/or as a ‘fact’ in the ‘object-oriented knowledge base’ are described according to a simple English grammar. Hierarchical structure of nouns-system in an ‘ideal thesaurus’ is constructed, on the basis of special kind of ‘object-oriented-lexical-definition of nouns’ recorded in the ideal dictionary. Lexical meaning of a verb whose meaning is specific are derived from that of a verb whose meaning is general and universal, by using ‘dichotomy’ on the basis of C-language-like way of description of English sentences in the lexicon. The hierarchical structure of verbs-system in an ‘ideal classification table’ is constructed on the basis of them.

Abstract: Multiple support vector machines are used to extract useful information from vast quantities of biological data. The method includes pre-processing of training data and test data to add dimensionality or to identify missing or erroneous data points. The training data is used to train the learning machine after which the success of the training is tested using the test data. The test output is pre-processed to determine whether the knowledge discovered from the pre-processed test data set is desirable and to identify which of the multiple support vector machines provides the optimal solution. After the training has been confirmed, live biological data can be pre-processed then input into the identified support vector machine that provides the optimal solution for extraction of useful information.

Abstract: An information processing system which understands the input information as a situation, infers the requirements that situation merits and the preferred responses to those requirements using a knowledge base which has knowledge about the situations, requirements and their responses and the relations among them, and by generating these inferences further understands the input and the situation, which enables it to perform efficiently and effectively, given small amount of input information. If input information is in natural language, the linguistic knowledge base is used to analyze the input natural language information. Further, a knowledge of the user, the operations performed by the user and knowledge of the relationship between the operations of the user and the attribute of the user may also be used by the system to appropriately operate for each user.

Abstract: A fuzzy data record pointer is utilized for identification of both a target file and a target data record within the target file. A target data record is accessed from a target file, selected from a set of N related files, utilizing a fuzzy data record pointer (“fuzzy”, as used herein, means that the data record pointer need not be coincident with the actual data record address). A modulus for the data record pointer divided by N is computed. This modulus is used to select the target file. A data record address is computed for the target data record utilizing the data record pointer and modulus. In this manner a fuzzy data record pointer is utilized to determine both the target file from a set of N related files and the target data record to be accessed within the target file.

Abstract: A system and method is provided for monitoring the operating condition of a pump by evaluating fault data encoded in the instantaneous current of the motor driving the pump. The data is converted to a frequency spectrum which is analyzed to create a fault signature having fault attributes relating to various fault conditions associated with the pump. The fault signature is then input to a neural network that operates in conjunction with a preprocessing and post processing module to perform decisions and output those decisions to a user interface. A stand alone module is also provided that includes an adaptive preprocessing module, a one-shot unsupervised neural network and a fuzzy based expert system to provide a decision making module that operates with limited human supervision.

Abstract: The present invention discloses low noise, optically coupled optoelectronic and all-optical artificial neuron devices that can be configured in an array to simulate the function of biological neural networks, and methods for making the artificial neurons. In a first optoelectronic embodiment, the device employs the regenerative pulsation property of astable multivibrators as optical pulse generators. A photosensitive detector, disposed in a circuit to control the state of an astable or bistable multivibrator, converts the intensity of the input light into a train of light pulses having a frequency that is a function of the intensity of the input signal. In an all-optical embodiment of an artificial neuron, an input signal is first integrated and the integrated signal transmitted to an optical pulse generator comprised of a nonlinear material disposed within the cavity of a Fabry-Perot etalon.

Abstract: An adaptive architecture method with feedback control for an intelligent agent provides for adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. An adaptive architecture method with feedback control for multiple intelligent agents provides for coordinating and adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. Re-programming of the adaptive architecture is through a nexus which coordinates reflexive and deliberator components.