Abstract: A memory configuration for use in a computer system includes a plurality of address decoders each of which is allocated an identifier having a predetermined number of bits, each bit having first and second selectable states. A data memory having a plurality of word lines of predetermined length, is also included in each of the address decoders and is activatable to select one of the plurality of word lines. The address decoders receive an input address having a predetermined number of bits and compare the identifier of an address decoder with the input address wherein the memory further activates an address decoder if at least a predetermined minimum number of bits set to the first selectable state in the input address correspond to bits set to the first selectable state in the decoder identifier.

Abstract: A learning system uses the concept of template automaton. “Various expected examples of learners” consisting of “correct” answers and “incorrect” answers are collected and a representative NLP technique such as HCS (heaviest common character string) or LCS (longest common character string) algorithm is used as an effective error diagnosis engine in the language learning system. These examples embedded in the template are used for diagnostic analysis of the answers of the learners. This diagnosis is performed by selecting a path of the highest similarity with the input sentence of the learner among a plenty of candidate paths. Thus, it is possible to automatize and simplify the time-requiring authoring task used in the language-oriented intelligent learning system.

Abstract: A signal processing device for learning operations made by a user, and for generating signal optimal to the user based on the learning results. A learning unit monitors supplied operating signals generated based on user operations, and judges whether to learn the operating signals. When the operating signals are to be learned, the learning unit learns a correction norm for correcting input signals, based on the learning operating signals and outputs the correction norm to a correcting unit. The correcting unit corrects input signals based on the correction norm and outputs the corrected signals as output signals. The present invention can be applied to an NR (Noise Reduction) circuit which removes noise.

Abstract: A system, method and computer program for developing artificial intelligence through the generational evolution of one or more genomes. Each genome includes a set of functions. The method includes creating one or more cortices, operating the one or more cortices to perform one or more specified tasks, calculating a fitness score for each cortex based on its ability to perform the specified tasks, and selecting one or more of the cortices based on the respective fitness scores. Each cortex includes a plurality of cortical units. Each cortical unit includes a set of functions. Each cortical unit is created from the one or more genomes.

Abstract: When an alarm condition relating to a performance goal of a storage system is detected, a storage management system invokes an N-step lookahead engine for simulating operation of the storage system when there are multiple actions that could be taken by the storage system for eliminating the alarm condition. The N-step lookahead engine generates N possible system states based on a current state of the storage system. The N possible states are based on a cost model of each of the multiple actions. Each cost model is based on an action, a behavior implication of the action, a resource implication of the action and a transient cost of the action. An action is selected that generates a system state that optimizes the stability, a prerequisite and a transient cost of invoking the selected action.

Abstract: A method of encoding knowledge is disclosed, which can be used to automatically detect problems in software application deployments. The method includes accessing a source of knowledge describing a problem known to occur in deployments of a particular software application, and which identifies a plurality of conditions associated with the problem. An encoded representation of the knowledge source is generated according to a predefined knowledge encoding methodology. The encoded representation is adapted to be applied automatically by a computer to analyze data representing a current state of a monitored deployment of the software application to detect whether the conditions and the problem exist therein.

Abstract: A computer-implemented method for determining a boundary for binary classification includes providing a data set, initializing a value for noise in the data set, and determining a hyperplane dividing the data set and a slack variable given a current value for noise. The method further includes updating the value for noise and the slack variable given the hyperplane, and determining the hyperplane to be the boundary for binary classification of the data set upon determining a termination criterion to be met, wherein elements of the data set are classified according to the boundary.

Abstract: Systems and techniques for classification of incoming text messages into categories. An initial set of categories is created and populated with a set of initial messages in each category. Incoming messages are assigned to a category based on text analysis of the incoming message and analysis of dissimilarities and differences between the message and messages already in the category. A set of unclassified messages is also maintained for incoming messages that do not fit an established category. Periodically, unclassified messages are reassigned to one of the established categories or to new categories created based on analysis of the unclassified messages.

Abstract: Provided is a system 10 which supports a user's behavior by generating a behavioral decision function indicating behavior to be adopted to a certain target. The system 10 includes: a data acquiring section 110 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 120 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: Described herein are systems and methods for normalizing data without the use of external controls. Also described herein are systems and methods for analyzing cluster data, such as genotyping data, using an artificial neural network.

Abstract: A method for generating a manufacturing process map comprises obtaining sets of N-dimensional expert data from at least three sources, defining a membership function for each set of expert data, applying fuzzy logic operations to said membership functions to generate new membership functions, the new membership functions defining N-dimensional regions within an N-dimensional design space and using one of said N-dimensional regions to generate the manufacturing process map.

Abstract: An information processor, a state judging unit, a diagnostic unit, an information processing method, a state judging method and a diagnosing method aim at precisely recognizing each operation carried out by an object that functions in a number of operation modes. For this purpose, a number of combinations of n parameter values, concerning each of the operation modes, that vary with operation are detected by sensors (1a-1d) during the operation of the object, and a Self-Organizing Map creating means (2) creates Self-Organizing Maps, which corresponds one to each of the operation modes and which serve as individual separation models, regarding detection data based on the detected combination of parameter values as learning data.

Abstract: An approach that enables reducing the number of computations while modeling data sets using a neural network. To model a first system characterized by a data set, a determination is made as to whether the data elements of the data set follow a similar pattern as data elements of another data set. If such an another data set exists, the weights determined with a system associated with the another data set, are used as initial weights while modeling the first system. Due to such a feature, number of computations in a neural network can be reduced while modeling several data sets.

Abstract: Systems and methods are disclosed that facilitate producing probabilistic outputs also referred to as posterior probabilities. The probabilistic outputs include an estimate of classification strength. The present invention intercepts non-probabilistic classifier output and applies a set of kernel models based on a softmax function to derive the desired probabilistic outputs. Such probabilistic outputs can be employed with handwriting recognition where the probability of a handwriting sample classification is combined with language models to make better classification decisions.

Abstract: Systems, methods and computer program products for assisting a user who is designing a project in selecting a technical architecture suitable for the project. A catalog of architectures and architecture components and various criteria to be met by project architectures, including such as technical standards, organization policies and guidelines, and legal or regulatory ones, are stored. The catalog may be web-based. Questions are posed to the user about the nature of the project, and a rules engine guides the user through relevant portions of the catalog based on the user's answers to the questions, and a set of one or more architectures that would be suitable for the project is proposed to the user. Once the user selects an architecture, the rules engine leads the user through a review of the stored criteria applicable to the project, to identify any that are not met by the selected architecture.

Abstract: A system for inferring geological classes from oilfield well input data is described using a neural network for inferring class probabilities and class sequencing knowledge and optimising the class probabilities according to the sequencing knowledge.

Abstract: Method and system for designing experiments by selecting at least a first experiment from an experimental space using a data-driven optimizer, receiving experimentally determined data, evaluating the experimentally determined data at a mata layer module, processing the experimentally determined data at the optimizer; the processing at the optimizer being influenced by the evaluation data.

Abstract: Techniques are described for determining the quality of software using fuzzy logic. The techniques include using linguistic variables to translate a numeric value of a quality attribute into a linguistic value of a quality attribute. The linguistic values of multiple quality attributes are aggregated into a quality rating of the software. The quality rating then is used to predict a performance attribute for the software. Techniques are described that may help improve the accuracy of the prediction, including refining software quality parameters based on a comparison of the parameters with software quality of the developed software. The techniques also include the ability to modify the quality attributes used based on the computing environment, the organizational environment or other characteristics.

Abstract: A method for discriminating between explosive events having their origins in High Explosive or Chemical/Biological detonation employing multiresolution analysis provided by a discrete wavelet transform. Original signatures of explosive events are broken down into subband components thereby removing higher frequency noise features and creating two sets of coefficients at varying levels of decomposition. These coefficients are obtained each time the signal is passed through a lowpass and highpass filter bank whose impulse response is derived from Daubechies db5 wavelet. Distinct features are obtained through the process of isolating the details of the high oscillatory components of the signature. The ratio of energy contained within the details at varying levels of decomposition is sufficient to discriminate between explosive events such as High Explosive and Chemical/Biological.

Abstract: The present invention comprises a method and software for recognizing and flagging a data item used by one or more application program as falling within the scope of a rule but anomalous when compared with other data items falling within the scope of the rule. The method of the present invention comprises determining a collection to which the data item belongs as defined by the rule. The collection that the data item belongs to is analyzed to calculate statistics regarding the other data items that are part of the collection. Based on the statistical calculations, it is determined whether the data item is an anomalous data item. If the data item is identified as an anomalous data item, it is flagged.