Abstract: An exemplary methodology, procedure, system, method and computer-accessible medium can be provided for receiving physiological data for the subject, extracting one or more patterns of features from the physiological data, and classifying the at least one state of the subject using a spatial structure and a temporal structure of the one or more patterns of features, wherein at least one of the at least one state is an ictal state.

Abstract: A method involves providing a parent schema, generating a plurality of distinct and domain-specific instantiations of the parent schema, user-validating at least two of the instantiations of the parent schema, and creating a symmetric schema by combining the user-validated instantiations of the parent schema. The parent schema and the instantiations of the parent schema may be user-provided or iteratively generated. The parent schema contains more than one tractable search spaces. Prior to user-validating the instantiations of the parent schema, they may be optimized using domain-specific knowledge. Additionally, one or more existing Boolean features in one or more cases of a case-based reasoning system may be replaced with the instantiations of the parent schema and non-zero weights for the cases may evolve that include the instantiations of the parent schema. The method may also include generating instantiations of the created symmetric schema.

Abstract: A system for controlling applications of a wireless mobile device includes a server for receiving data related to an adaptive user profile and for controlling operations of applications within the wireless mobile device. An adaptive neural/fuzzy logic control application implemented within the network server generates the adaptive user profile responsive to the received data. The adaptive user profile controls operations of the applications within the wireless mobile device and changes in real time responsive to the received data.

Abstract: In order to improve the prediction accuracy of a service level agreement breach, an agreement breach prediction system includes: a probability distribution calculation unit that calculates a probability distribution of a measured value for each event; a probability calculation unit that calculates, for each event, a probability that applies to an SLA breach and a probability that does not applies to an SLA breach; an SLA distribution calculation unit that calculates a probability density of a measured value corresponding to the SLA breach; and a breach occurrence probability calculation unit that, when the event occurs, calculates a probability that the SLA breach occurs within the predefined time after the occurrence of the event, by using the respective probabilities corresponding to the event, and the respective probability densities corresponding to the measured values at the time of event occurrence.

Abstract: A system, method, and computer-readable instructions for a distributed machine learning system are provided. A plurality of distributed learning environments are in communication over a network, wherein each environment has a computing device having a memory and a processor coupled to the memory, the processor adapted implement a learning environment via one or more agents in a rules-based system, wherein the agents learn to perform tasks in their respective learning environment; and a persistent storage in which knowledge comprising a plurality of rules developed by the agents for performing the tasks are stored, wherein the knowledge is tagged and shared with other agents throughout the plurality of distributed learning environments.

Abstract: Techniques are described for determining what node of a classification and regression tree (CART) should be used by a predictive analysis application. A first approach is to use a standard deviation of the data at a given the level of the CART to determine whether data in the next, lower node is more consistent than the data in the current node. A second approach is to measure a correlation between data points in a given node and the time at which each point was sampled (or other correlation metric) to identify a preferred node.

Abstract: Methods and systems for determining the selection criteria that in its embodiments can distinguish compounds that successfully meet an objective from those that do not, determine the importance of selection criterion in selecting test compounds that have a high probability of achieving an objective and automatically apply the selection criteria to select test compounds with a high chance of meeting an objective.

Abstract: A method of semantic searching. The method may include receiving a first search query, obtaining a disambiguation term for semantically disambiguating the first search query, and creating, with a processor, a second search query based at least in part on the first search query and the disambiguation term. The method may also include at least one of outputting search results obtained from a search conducted based at least in part on the second search query and sending the second search query to a search service for outputting search results.

Abstract: A system and method include comparing a context to cases stored in a case base, where the cases include Boolean and non-Boolean independent weight variables and a domain-specific dependency variable. The case and context independent weight variables are normalized and a normalized weight vector is determined for the case base. A match between the received context and each case of the case base is determined using the normalized context and case variables and the normalized weight vector. A skew value is determined for each category of domain specific dependency variables and the category of domain specific dependency variables having the minimal skew value is selected. The dependency variable associated with the selected category is then displayed to a user.

Abstract: A method includes comparing a user-specified context having natural language contextual antecedents to cases stored in a case base. Each stored case includes case antecedents and case consequents. A matching case exists and is selected if the case antecedents exactly match the contextual antecedents. If no match exists, a best-matching case is determined and selected. The best-matching case may be determined by generalizing the situational part of a rule and comparing the user-specified context to the stored (generalized) cases. The best-matching case is the case having the highest ratio of matching generalized case antecedents to contextual antecedents and having a matching error ratio that does not exceed an error ratio threshold. The case consequents of the selected matching case or best matching case are then displayed to a user, with case base adjustment performed based upon feedback provided by the user in response to the displayed case consequents.

Abstract: A method is used in analyzing device similarity. Data describing a device is received and a model is applied to the data. Based on the modeling, a measure of similarity between the device and a previously known device is determined.

Abstract: An event-driven neural network includes a plurality of interconnected core circuits is provided. Each core circuit includes an electronic synapse array has multiple digital synapses interconnecting a plurality of digital electronic neurons. A synapse interconnects an axon of a pre-synaptic neuron with a dendrite of a post-synaptic neuron. A neuron integrates input spikes and generates a spike event in response to the integrated input spikes exceeding a threshold. Each core circuit also has a scheduler that receives a spike event and delivers the spike event to a selected axon in the synapse array based on a schedule for deterministic event delivery.

Abstract: Methods and systems for predicting user input on a keyboard. Methods include enabling user input on a display comprising at least three fields. The first field displays an input string that is based on input selections such as keyboard entries. The second field displays a candidate prediction generated based on other input selections, consisting at least in part of a proposed completion to the input selection, and partially based on the input string in the first field. The third field displays another candidate prediction generated based on the input string in the first field as well as the candidate prediction in the second field.

Abstract: A platform for managing recommendation models is described. The platform processes and/or facilitates a processing of at least one user identification characteristic associated with at least one device to determine a user identity. The platform further determines at least one communication account active at the at least one device. The platform also causes, at least in part, an association of one or more recommendations models with the user identity, the at least one communication account, the at least one device, or a combination thereof.

Abstract: The present invention provides devices, methods, and systems for coupling a rational agent to a quantum process. In particular, the present invention provides rational agents configured to influence a quantum process, or to derive information from a quantum process, and methods and uses thereof.

Abstract: A browser-based personalized recommendation system and method for lifestyle items comprising style dimension mapping, inputs, outputs, and a computer-algorithm is described. The system gathers information about a user's unique lifestyle preferences, which is then correlated to clothing and lifestyle items. The recommendation system uniquely and directly matches users to discrete items without the need for historic user data.

Abstract: Embodiments of the disclosed systems and methods comprise systems and methods for recognizing actions of an object and matching those actions with expected patterns of actions. In some embodiments, the methods recognize actions using statistical classifiers and aggregate data about locomotions, actions, and interactions of the object to infer patterns of that object using a pattern recognition algorithm. In some embodiments, the systems and methods are further able to select responses to recognized patterns and learn patterns over time.

Abstract: An automated method for calibrating in real time a diagnostic analyzer includes the steps of receiving diagnostic results of patient samples calculated by the analyzer using pre-set parameters of the analyzer, and calculating the centroid of the analyzer's diagnostic results. The centroid of the analyzer's diagnostic results is subtracted from a centroid of diagnostic results of a field population of comparable analyzers to obtain a bias in the centroid of the analyzer's diagnostic results. The bias is compared to predetermined limits. Should the bias fall outside the predetermined limits, an optimization factor is derived and applied to the analyzer's diagnostic results to obtain optimized results from the analyzer without changing the pre-set parameters of the analyzer.

Abstract: A method for classification of a newly arrived multidimensional data point (MDP) in a dynamic data uses multi-scale extension (MSE). The multi-scale out-of-sample extension (OOSE) uses a coarse-to-fine hierarchy of the multi-scale decomposition of a Gaussian kernel that established the distances between MDPs in a training set to find the coordinates of newly arrived MDPs in an embedded space. A well-conditioned basis is first generated in a source matrix of MDPs. A single-scale out-of-sample extension (OOSE) is applied to the newly arrived MDP on the well-conditioned basis to provide coordinates of an approximate location of the newly arrived MDP in an embedded space. A multi-scale OOSE is then applied to the newly arrived MDP to provide improved coordinates of the newly arrived MDP location in the embedded space.

Abstract: A plurality of pruning measures (PM) are calculated from a feature amount (CV) of test data (TD) which is input, a plurality of isopycnic surfaces (EC) are plotted and set on a threshold space (SS), a threshold curved surface (SC) in which a decrease in at least one of a plurality of pruning measures (PM) causes an increase in at least one thereof is generated using a portion of one isopycnic surface (EC) as a part, a hypothesis curved surface (HC) of subject data (CD) is generated on the threshold space (SS) to set a position intersecting the threshold curved surface (SC) to a pruning threshold (PS), and a plurality of hypotheses of the subject data (CD) are pruned. Thereby, there is provided a data processing device of which at least one of the recognition speed and the recognition accuracy is higher than in the related art.