Abstract: A method and system for conducting semantically weighted searches in a governed corpus of terms is provided. A search expression having a plurality of terms for performing a search in the governed corpus of terms is received. The governed corpus of terms comprises a plurality of corpus expressions each comprising a plurality of terms, each term within the governed corpus of terms being associated precisely with a single concept within a lexical database. At least one concept of the lexical database is assigned to each term in the search expression based on a syntactical analysis. A semantic similarity is calculated between pairs of concepts of the search expression and one of the corpus expressions. A total semantic similarity is calculated between the search expression and the one of the corpus expressions by aggregating the semantic similarities of the pairs of concepts based on an order of significance of the terms.

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: A behavior control system of a robot for learning a phoneme sequence includes a sound inputting device inputting a phoneme sequence, a sound signal learning unit operable to convert the phoneme sequence into a sound synthesis parameter and to learn or evaluate a relationship between a sound synthesis parameter of a phoneme sequence that is generated by the robot and a sound synthesis parameter used for sound imitation, and a sound synthesizer operable to generate a phoneme sequence based on the sound synthesis parameter obtained by the sound signal learning unit.

Abstract: This is directed to processing stored data to automatically generate metadata for the stored data. In particular, this is directed to identifying metadata associated with stored data, and identifying other data that relates to the stored data from one or more sources. A processing module can identify other data sharing some of the identified metadata, and can extract additional metadata associated with the identified other data. The extracted metadata can then be associated with the user's stored data. The processing module can extract additional metadata from any suitable source, including for example local application data, social networks or blogging sources, and other remote sources. In some embodiments, an electronic device can retrieve data from other users for a particular event based on metadata associated with the user's data for the event to form a master collection of data.

Abstract: In certain example embodiments of this invention, there is provided systems and/or methods for processing BAM-related data to predict when events of interest are about to happen and/or to identify the root causes of, or at least data correlated with, such events of interest. In certain example embodiments, key performance indicators (KPIs) are gathered and gardened. The gardening process may identify KPI values of interest (e.g., based on a Z-factor analysis thereof across one or more collection intervals). The gardened KPIs may be processed using a time-series transform (e.g., a Fast Fourier Transform), matched to one of a plurality of predefined waveforms, and fed into a dynamic Naïve Bayesian Network (NBN) for prediction. The gardened data also may be used to determine the relevance of the KPI for root causes of problems (e.g., based on a chi-square analysis).

Abstract: One or more systems and methods for knowledge pattern search from networked agents are disclosed in various embodiments of the invention. A system and a related method can utilizes a knowledge pattern discovery process, which involves analyzing historical data, contextualizing, conceptualizing, clustering, and modeling of data to pattern and discover information of interest. This process may involve constructing a pattern-identifying model using a computer system by applying a context-concept-cluster (CCC) data analysis method, and visualizing that information using a computer system interface. In one embodiment of the invention, once the pattern-identifying model is constructed, the real-time data can be gathered using multiple learning agent devices, and then analyzed by the pattern-identifying model to identify various patterns for gains analysis and derivation of an anomalousness score.

Abstract: A system and a method are disclosed for implementing managing relationships between data on a mobile computing based on user creation and definition of the relationships. A mobile computing device user generates asymmetric relationships between stored entities, events, tasks and communications. These asymmetric relationships are custom-generated by the user to reflect the user's classification and evaluation of the relationships. The user also assigns a score to each relationship and stored entity, event, task and communication to represent the user's classification of the relationship, entity, event, task or communication. Hence, the user assigns a value to the relationships between data as well as the stored data to indicate which relationship or stored data is most valuable to the user. The user-defined relationships between data can be automatically displayed when the mobile communication device is used to interact with a stored entity.

Abstract: In one embodiment, the present invention includes a method for identifying a deformable object of a scene of a computer game that is visible by an artificial intelligence (AI) character of the game, requesting a speculative physics simulation associated with the deformable object to determine a result of an action to the deformable object by the AI character, and selecting an action to be performed by the AI character, where the selection is based at least in part on the speculative physics simulation. Other embodiments are described and claimed.

Abstract: Embodiments are directed towards using a community of weighted results from local and global message classifiers to determine whether a message is spam. Each local classifier may receive a message that is to be evaluated to determine whether it is spam. A local classifier receives the message and performs a classification of the message. The local classifier may receive predictions of whether the message is spam from at least one global classifier. The local and global predictions are combined using, in one embodiment, a regression analysis to generate a single local message classification. Combining the local and global predictions is directed towards enabling a community of predictions to be used to classify messages. The user may then re-classify this output, which in turn is used as feedback to modify weights to the local and received global predictions for a next message.

Abstract: A controller of a distributed computing system assigns feature vectors, and assigns data processors and a model updater to first computers. The data processors have charge of iteration calculation of machine learning algorithms, acquire the feature vectors over a network when starting learning, and store the feature vectors in a local storage. In iteration of second and subsequent learning processes, the data processors load the feature vectors from the local storage, and conduct the learning process. The feature vectors are retained in the local storage till completion of learning. The data processors send only the learning results to the model updater, and waits for a next input from the model updater. The model updater conducts the initialization, integration, and convergence check of the model parameters, completes the processing if the model parameters are converged, and transmits new model parameters to the data processor if the model parameters are not converged.

Abstract: In one embodiment, the present invention includes a method for identifying a deformable object of a scene of a computer game that is visible by an artificial intelligence (AI) character of the game, requesting a speculative physics simulation associated with the deformable object to determine a result of an action to the deformable object by the AI character, and selecting an action to be performed by the AI character, where the selection is based at least in part on the speculative physics simulation. Other embodiments are described and claimed.

Abstract: System(s) and method(s) facilitate a distributed simulation of an industrial control system. A model of the industrial control system is generated and computing resources are scheduled for simulating portions of a simulation according to the model. Computing resources are scheduled to mitigate computational bottlenecks in the simulation and synchronize portions of the simulation deployed in disparate computing resources. Sub-processes of a control process can be simulated in dedicated computing resources as a part of a distributed simulation of the control process. Execution time of one or more portions of a distributed simulation can be increased or slowed down to synchronize said portions.

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: In an embodiment, instructions in a computer language are translated into instructions in a register machine language. The instructions in the register machine language are translated into active element machine instructions. The use of the register machine language is optional. In an embodiment, the first translator may translate the instructions into another machine language. In an embodiment, an active element machine may be programmed using instructions for a register machine with elemental register machine instructions, such as push, pop, copy, and jump, and/or using a higher language, such as C, may be emulated with active element instructions executing on an active element machine.

Abstract: Described is a distributed network optimization system implementing distributed particle swarm optimization, which allows multiple nodes to cooperate in searching efficiently for a set of parameter values that optimizes overall network performance. The system comprises a multi-dimensional network parameter space with software agents configured to operate as a cooperative swarm to locate an objective function optima. The software agents are individually distributed across multiple nodes in the network, and each node processes a portion of each software agent to obtain information regarding the local performance of the software agent. A global measure of network performance is then computed based on sharing of local performance information between nodes, which each node uses to adjust its parameters accordingly. In this manner, the global utility of the network can be optimized using local processing only. Also described is a method of utilizing the system.

Abstract: Implementations and techniques for distributed-type Markov chain Monte Carlo are generally disclosed.

Abstract: Analog processors for solving various computational problems are provided. Such analog processors comprise a plurality of quantum devices, arranged in a lattice, together with a plurality of coupling devices. The analog processors further comprise bias control systems each configured to apply a local effective bias on a corresponding quantum device. A set of coupling devices in the plurality of coupling devices is configured to couple nearest-neighbor quantum devices in the lattice. Another set of coupling devices is configured to couple next-nearest neighbor quantum devices. The analog processors further comprise a plurality of coupling control systems each configured to tune the coupling value of a corresponding coupling device in the plurality of coupling devices to a coupling. Such quantum processors further comprise a set of readout devices each configured to measure the information from a corresponding quantum device in the plurality of quantum devices.

Abstract: Techniques described herein may be used to solve a stochastic problem by dividing the stochastic problem into multiple fragments. In some cases, each fragment may be related to a random variable that forms a part of the problem, such that each fragment may produce samples from a probability distribution for that variable. Each fragment of the stochastic problem may then be assigned to a configurable circuit to solve the stochastic fragment. Configurable circuits may be implemented using any suitable combination of hardware and/or software, including using stochastic circuitry. In some embodiments, stochastic circuitry may include a stochastic tile and/or a stochastic memory.

Abstract: An intelligent distributed computing fabric system may comprise a cognitive element, a computing element, a security element, and a network element. The cognitive element may receive inputs from the computing element, the security element, and the network element, and may further receive external information from a sensor interface. The cognitive element may process the inputs from the computing element, the security element, and the network element, and may additionally process the external information from the sensor interface. The cognitive element may make decisions based on the inputs from the computing element, the security element, and the network element, and based on the external information from the sensor interface, to adapt for dynamically varying situations in a fabric infrastructure.

Abstract: An intelligent decision supporting system and a method for making an intelligent decision are provided.

Abstract: A system for composing Web services may include a goal determiner unit and a composer unit. The goal determiner unit may be configured to access a primary goal of final states of Web service representations. The composer unit may be configured to compute a set of transitions from initial states of the Web service representations to the primary goal, compute intermediate states of one or more Web service representations, and generate a copy rule of the set of transitions, the copy rule having a condition part that specifies the intermediate states and a portion of the final states of the primary goal and an activity part that includes assignments of input variables consumed by transitions from the intermediate states.

Abstract: A real time kernel for deploying health monitoring functions in Condition Base Maintenance (CBM) and Real Time Monitoring (RTM) systems is disclosed in this invention. The Optimized Neuro Genetic Fast Estimator (ONGFE) allows embedding failure detection, identification, and prognostics (FDI&P) capability by using Intelligent Software Element (ISE) based upon Artificial Neural Network (ANN). ONGFE enables embedded fast and on-line training for designing ANNs, which perform very high performance FDI&P functions. An advantage is the optimization block based on pseudogenetic algorithms, which compensate for effects due to initial weight values and local minimums without the computational burden of genetic algorithms. It provides a synchronization block for communication with secondary diagnostic modules. Also a scheme for conducting sensor data validation is embedded in Smart Sensors (SS). The algorithms are designed for a distributed, scalar, and modular deployment.

Abstract: A method of assessing a signal to identify particular signal characteristics comprises application of machine learning to multi-dimensional histograms derived from multi-tap sampling of the signal. The signal is sampled from at least two tap points to retrieve a sample set, and the at least two tap points are adapted to retrieve distinct samples from the signal, such as time spaced samples or spectrally distinct samples. Multiple sample sets are retrieved from the signal over time. The at least two dimensional histogram is built from the joint probability distribution of the plurality of sample sets. A machine learning algorithm then processes the multi-dimensional histogram, and is trained to predict a value of at least one characteristic of the signal.

Abstract: Systems and methods for processing medical image data with increased sensitivity to facilitate comparisons among groups of subjects are disclosed herein. In one embodiment, a method comprises receiving a first three-dimensional image comprising a plurality of voxels, reducing a regional trend within the three-dimensional image, computing a semivariogram for a region of interest, defining at least one block of spatially correlated voxels, calculating voxel weights for each voxel within the at least one block, and determining a block average count and variance for the at least one block.

Abstract: A method and system for responding to an alert pertaining to an event. A unique processor of a first micro grid apparatus of at least one micro grid apparatus detects an alert data packet that includes the alert. Each micro grid apparatus includes at least two processors that contain a unique processor. Each processor of each micro grid apparatus has its own operating system. The unique processor of each micro grid apparatus has a unique operating system. Each unique processor selects at least one processor from each micro grid apparatus. Each selected processor is designated as a macro grid processor of a respective macro grid by altering the operating system of each selected processor. An artificial intelligence is generated for each macro grid. The event is responded to and quenched by implementing the artificial intelligence of each macro grid, after which each macro grid is extinguished.

Abstract: A method using for performing a scatter-type data distribution among a cluster of computational devices. A number of nodes (equal to a value Cg, the number of tree generator channels) are initially generated, each connected to an initial generator, to create respective initial root nodes of an initial tree structure. Data is transmitted from the initial generator to each of the initial root nodes. Cg root nodes, each connected to a respective new generator, are generated to create respective roots of Cg newly generated tree structures. Each of the tree structures is expanded by generating Ct (the number of communication channels per node in each tree structure) new nodes connected to each node generated in each previous step. Data is then transmitted to each of the new nodes from an immediately preceding one of the nodes, and from each new generator to an associated root node.

Abstract: A system and method for authenticating a subscriber of a first network to access application services through a second network, wherein the second network is a packet data network.

Abstract: In an automated method system for coordinating navigations within two or more knowledge bases that would otherwise be functionally independent, context-continuity is maintained when an automated transfer is executed from a first knowledge base to a second knowledge base. The transfer is triggered by detection that the second knowledge base has a greater relevance to the user. As a result of the context-continuity, information acquired prior to the transfer is used to achieve a partial navigation within the second knowledge base. For embodiments involving Virtual Agents, the content-continuity includes simulating a continuation of dialog despite the transfer.

Abstract: Methods and systems for parallel computation of an algorithm using a plurality of nodes configured as a Howard Cascade. A home node of a Howard Cascade receives a request from a host system to compute an algorithm identified in the request. The request is distributed to processing nodes of the Howard Cascade in a time sequence order in a manner to minimize the time to so expand the Howard Cascade. The participating nodes then perform the designated portion of the algorithm in parallel. Partial results from each node are agglomerated upstream to higher nodes of the structure and then returned to the host system. The nodes each include a library of stored algorithms accompanied by data template information defining partitioning of the data used in the algorithm among the number of participating nodes.

Abstract: Network graphs are determined using data about the vertices. Vertices are clustered into community of vertices based on maximizing the density of linkages within each community. Vertex properties describing the extent to which each vertex's community has exhibited a particular behavior are determined. Vertex properties describing whether the most important vertex in each community has exhibited a particular behavior are determined. Functions describing the relationship between these two categories of vertex properties and other relevant vertex properties, and a particular behavior are determined. These functions are used to predict the likelihood of each vertex exhibiting the particular behavior.

Abstract: A modular representation of a physical system is generated using modules and variables, each module representing a portion of the physical system, each variable representing a parameter of the physical system. Code is generated according to the modular representation such that the code is suitable to be compiled into a machine code that can be executed on hardware to simulate the physical system. The code contains instructions to cause the hardware to solve a system of differential algebraic equations that represent relationships among the variables.

Abstract: Various embodiments enable an agent that utilizes a first, as-needed canonical rule set in a first execution environment to be moved to a second execution environment where the agent utilizes a second, as-needed canonical rule set.

Abstract: Discrete optimization problem are solved using an analog optimization device such as a quantum processor. Problems are solved using an objective function and at least one constraint corresponding to the discrete optimization problems. The objective function is converted into a first set of inputs and the at least one constraint is converted into a second set of inputs for the analog optimization device. A third set of inputs is generated which are indicative of at least one penalty coefficient. A final state of the analog optimization device corresponds to at least a portion of the solution to the discrete optimization problem.

Abstract: The invention relates to a method for modifying the operating mode of a technical communications group platform (TCGPL) of a telecommunications network (TC network) for at least one driving object 1 which is controlled by a subscriber object (SUBC), by modifying by means of at least one modifying object 2 the operating mode of at least one object 3 which is to be modified or has been modified, and a telecommunications group platform (TCGPL) for producing technical communications group processes (TCGPs). The invention further relates to a method for managing technical communications group processes (TCGPs) with the steps: provision of a driving object which defines at least one further object to be provided; making available of at least one modifying object for the provision of the further object defined by the driving object; generation of an algorithm from the modifying object; and provision of the further object by execution of the algorithm.

Abstract: Sound discrimination techniques are disclosed that can be employed, for example, in the task of discriminating speech and non-speech in a noisy environment and other noise classification applications. In one particular embodiment, a classifier system is provided that includes a linear Regularized Least Squares classifier used directly on a high-dimensional cortical representation of the target sound. The regularization constant lambda (?) can be selected automatically, yielding a parameter-free learning system. In addition, the high-dimensional hyperplane can be viewed directly in the cortical space, leading to greater interpretability of the classifier results.

Abstract: A method for controlling a decisional process when pursuing an aim in a specific application domain, such as economic, technical, and organizational fields. In the process, a system of agents is created, including creator cognitive agents of portable knowledge objects and constructor agents of knowledge objects by adding supplementary knowledge elements to the knowledge objects created. The system launches the decisional process by tracking the observation of an abnormality in the actual data of the application domain by the creation of an initial knowledge object representative of an alarm index and causes several decisional paths to be established linked to this object, under different points of view of different agents, each in its domain, and the decision is made following merging of decisional paths.

Abstract: A behavioral analysis technique is provided that utilizes a system selected based on a level of data. In use, a level associated with data is identified. In addition, a behavioral analysis is performed on the data utilizing one of a plurality of systems that is selected based on the identified level.

Abstract: A server computer and a multitude of client computers form a network computing system that is scalable and adapted to continue to evaluate the performance characteristics of a number of genes generated using a software application running on the client computers. Each client computer continues to periodically receive data associated with the genes stored in its memory. Using this data, the client computers evaluate the performance characteristic of their genes by comparing a solution provided by the gene with the periodically received data associated with that gene. Accordingly, the performance characteristic of each gene may be updated and varied with each periodically received data. The performance characteristic of a gene defines its fitness. The genes may be virtual asset traders that recommend trading options, and the data associated with the genes may be historical trading data.

Abstract: An approaching human threat or vehicle, such as a suicide bomber nearing a secured zone such as a military base, may be detected and classified. A vibration recognition system may detect a systematic vibration event. The entity might be a medium, human, animal, or a passenger vehicle. The system may discriminate between such an event and a background or other vibration event, such as a falling tree limb. A seismic sensor may be employed to detect vibrations generated by footsteps and a vehicle. Seismic waves may be processed locally where the sensor is located. The system may wirelessly communicate with a remote command center. Temporal features of the vibration signals may be modeled by a Dynamic Synapse Neural Network (DSNN) with good false recognition rates. The models may reject quadrupedal animal footsteps.

Abstract: A predictor of medical treatment outcome is developed and applied. A prognosis model is developed from literature. The model is determined by reverse engineering the literature reported quantities. A relationship of a given variable to a treatment outcome is derived from the literature. A processor may then use individual patient values for one or more variables to predict outcome. The accuracy may be increased by including a data driven model in combination with the literature driven model.

Abstract: Various embodiments enable an agent that utilizes a first, as-needed canonical rule set in a first execution environment to be moved to a second execution environment where the agent utilizes a second, as-needed canonical rule set.

Abstract: A method for performing a calculation that includes determining solutions for a plurality of problem modules. The problem modules are of differing complexities, and their solutions are combined to determine a solution to the calculation. The method may include directing each of the problem modules to at least one master server, estimating a complexity for each of the problem modules, determining a threshold complexity level, sending problem modules having a complexity exceeding the threshold complexity level to at least one slave server and obtaining solutions for the problem modules therefrom, determining solutions for problem modules having a complexity not exceeding the threshold complexity level in the master server(s), and combining the solutions for the problem modules to determine the solution for the calculation.

Abstract: A computerized system configured to provide a data cell graph for a distributed data set comprised of different data formats. The system comprises a plurality of data repositories, each data repository configured to retain a portion of the distributed data set translated into a uniform semantic language and a plurality of processing cells, each processing cell configured to translate a portion of the distributed data set into the uniform semantic language, wherein the processing cells are further configured to perform at least one of applying rules to classify data against semantic knowledge models and/or adding inferred facts to and/or transforming the structure of the data found in the translated data in the data repository. The processing cells are configured in a computerized data cell graph so as to progressively create a unified semantic knowledge model for the distributed data set.

Abstract: Systems, methods and apparatus are provided through which in some embodiments self health/urgency data and environment health/urgency data may be transmitted externally from an autonomic element. Other embodiments may include transmitting the self health/urgency data and environment health/urgency data together on a regular basis similar to the lub-dub of a heartbeat. Yet other embodiments may include a method for managing a system based on the functioning state and operating status of the system, wherein the method may include processing received signals from the system indicative of the functioning state and the operating status to obtain an analysis of the condition of the system, generating one or more stay alive signals based on the functioning status and the operating state of the system, transmitting the stay-alive signal, transmitting self health/urgency data, and transmitting environment health/urgency data.

Abstract: The present invention relates to a system and method for problem solving using intelligent agents. The intelligent agents may be embodied as processor-readable software code stored on a processor-readable medium. The intelligent agents may include a brain agent to parse the input and direct the parsed input query to other intelligent agents within the system. The apparatus and method may use, for example, a personality agent, a language agent, a knowledge agent, a mood agent, a visual agent, sound agent, a tactile agent, and a smell/taste agent and various connectors to external data sources or other intelligent systems to interpret questions and provide responses back to the user. The apparatus and method may further parse questions in a conceptual manner. The apparatus and method may further optimize its system performance by evolving with and reacting to specific user interactions. Thus, the present invention may be configured to receive a human question and to output a human answer.

Abstract: Method and agent network architecture for processing a subject message, where each agent has a view of its own domain of responsibility. An initiator agent which receives a user-input request and does not itself have a relevant interpretation policy, queries its downchain agents whether the queried agent considers such message to be in its domain of responsibility. Each queried agent recursively determines whether it has an interpretation policy of its own that applies to the request, and if not, further queries its own further downchain neighboring agents. The further agents eventually respond to such further queries, thereby allowing the first-queried agents to respond to the initiator agent. The recursive invocation of this procedure ultimately determines one or more paths through the network from the initiator agent to one more more leaf agents.

Abstract: An information register stores information represented by the states of endohedral fullerenes in a nanotube. Possible states are spin-states or morphological states, such as endohedral species having intrinsic or induced electric dipole moment or characteristic electric polarizility. The states of successive endohedral fullerenes along the nanotube are coupled by interaction mediated by electrons in the nanotube. The register can be used as part of a quantum computer or a classical computer.

Abstract: The context engine of a context aware platform may comprise a provider manager coupled to context providers and the provider manager may communicate with the context providers using application programming interfaces (API). To optimize the use of system resources, the provider manager may load/unload the context providers based on value of a load field of a hint signal or on prediction values. The context providers is to activate a first set of sensors of the plurality of sensors if the preferred activity level for the first set of sensors is set to activate state in the hint signal. The context providers is to deactivate a second set of sensors of the plurality of sensors if the preferred activity level for the first set of sensors is set to deactivate state in the hint signal.

Abstract: A system that incorporates teachings of the present disclosure may include, for example, a synthesis engine having a controller, and a storage medium for storing instructions to be executed by the controller. The instructions, when executed by the controller, can cause the controller to retrieve collected information associated with a behavior of an individual, synthesize from the information a measure of a mood of the individual to interact with others, and transmit the measure to a system associated with the individual to manage requests between the individual and the entity. The measure of the mood of the individual can indicate an availability of the individual and a receptiveness of the individual to accept a request to interact with an entity. The measure can be described by a plurality of dimensions. Other embodiments are disclosed.

Abstract: Methods and systems for parallel computation of an algorithm using a plurality of nodes configured as a Howard Cascade. A home node of a Howard Cascade receives a request from a host system to compute an algorithm identified in the request. The request is distributed to processing nodes of the Howard Cascade in a time sequence order in a manner to minimize the time to so expand the Howard Cascade. The participating nodes then perform the designated portion of the algorithm in parallel. Partial results from each node are agglomerated upstream to higher nodes of the structure and then returned to the host system. The nodes each include a library of stored algorithms accompanied by data template information defining partitioning of the data used in the algorithm among the number of participating nodes.