Abstract: A computer readable, non-transitory medium has stored therein a trouble pattern creating program. The program causes a computer to execute: (a) extracting, from a plurality of log messages that are output from an information system having a plurality of configuration items and that are output in a predetermined period of time, configuration items that output the log messages; (b) calculating a degree of relationship between the configuration items extracted in the (a) extracting; (c) executing learning of the rate of the number of occurrences of troubles in the information system in the number of times the log messages are output, the learning is executed by a number of times corresponding to the degree of relationship calculated in the (b) calculating; and (d) creating, in accordance with a result of the learning in the (c) executing, a trouble pattern message that is output when a trouble occurs.

Abstract: A device receives instructions for extracting, transforming, and loading data; identifies a plurality of data processing activities based on the instructions; and determines a processing sequence for performing the plurality of data processing activities. The device further creates a plurality of processing objects corresponding to the plurality of data processing activities. Each one of the plurality of processing objects including a discrete data structure that is produced by performing a corresponding one of the plurality of data processing activities. The device performs the plurality of data processing activities in accordance with the processing sequence and by using the plurality of processing objects.

Abstract: A computer-implemented system and method for facilitating evergreen discovery of digital information is provided. A hierarchy of topics for topically-limited subject areas is defined. Seed words characteristic of each topic are selected. Training material from the digital information that corresponds to the respective subject area of each of the topics is designated. Candidate topic models are formed from the seed words. Each candidate topic model includes a pattern evaluable against the digital information. An ability of each of the candidate topic models to identify such digital information matching the candidate topic model's topic is tested by matching the pattern in the candidate topic model to the training material. The candidate topic model for each topic that includes the highest abilities with respect to the topic in performance, simplicity and bias is chosen. An evergreen index is formed by pairing the chosen candidate topic model to each topic in the hierarchy.

Abstract: Systems and methods of anomaly detection in data centers. An example method may include analyzing time series data for the data center by testing statistical hypotheses. The method may also include constructing upper and lower bounds based on the statistical hypotheses. The method may also include flagging anomalies in the time series data falling outside of the upper and lower bounds.

Abstract: A distributed sequential method and system for detecting and identifying radioactive contraband from highly uncertain (noisy) low-count, radionuclide measurements, i.e. an event mode sequence (EMS), using a statistical approach based on Bayesian inference and physics-model-based signal processing based on the representation of a radionuclide as a monoenergetic decomposition of monoenergetic sources. For a given photon event of the EMS, the appropriate monoenergy processing channel is determined using a confidence interval condition-based discriminator for the energy amplitude and interarrival time and parameter estimates are used to update a measured probability density function estimate for a target radionuclide.

Abstract: The location of a sound within a given spatial volume may be used in applications such as augmented reality environments. An artificial neural network processes time-difference-of-arrival data (TDOA) from a known microphone array to determine a spatial location of the sound. The neural network may be located locally or available as a cloud service. The artificial neural network is trained with perturbed and non-perturbed TDOA data.

Abstract: A method and system is provided for validating claim submissions against a claim policy that can perform a comparative analysis by comparing structured or unstructured claim submissions to semantically structured policies to direct and optimize processing of the claim submission. A method and system is also provided for enabling semantic interoperability across different proprietary electronic transaction records. Semantic queries and semantic analysis can be performed on a collection of electronic transaction records originating from different proprietary systems.

Abstract: The method and system of the present invention include, responsive to a receipt of a customer input, customizing an agent interface menu. The customizing includes selecting a plurality of action items for the agent interface menu, and ordering the plurality or more action items in the agent interface menu. The customizing is performed using the customer input and an item of stored customer information. The method further includes presenting an item of the customer input in an agent interface. The agent interface includes the agent interface menu, a communication window, and a customer attributes display. Responsive to a selection of one of the plurality of action items, wherein the plurality of action items is presented by the agent interface menu, an input field in a form provided in support of an action selected from the agent interface menu is populated with the customer input received from the customer interface.

Abstract: A method is provided for implementing regular expression matching using ternary content-addressable memory devices. The method includes: receiving a set of regular expressions (REs) that specify data elements to be extracted from data packets; constructing a deterministic finite automaton (DFA) from the set of regular expressions; building a state transition table for each node of the deterministic finite automaton; combining the state transition tables into a single lookup table; and instantiating the lookup table in a ternary content-addressable memory device. Additional techniques are provided to reduce the TCAM space and improve RE matching speed.

Abstract: A string matching device extracts a string by shifting a start position from an input data stream, compares the extracted string with a sub-string included in a target string, and when a prefix of a target string is detected from the string extracted from the input data stream, it selects one of the strings output in the next stage based on the start position of the corresponding string and uses it to detect the sub-string. Also, the device can consecutively detect at least one target string from the input data stream by using a state transition process.

Abstract: A method, computer program product, and system for de-centralized stream processing is provided. The method may include providing a plurality of processing nodes each of said processing nodes configured to transmit and receive a stream of data. The method may also include providing a genome including a hierarchical set of tasks that represent a hierarchical functional decomposition of one or more problem scenarios. The method may further include identifying, at each of the processing nodes, one or more tasks for a first genome level. The method may additionally include differentiating, at one or more of the plurality of processing nodes, into one or more tasks, based upon, at least in part, the first genome level. The method may further include grouping a plurality of the processing nodes together to achieve a power level. The method may also include activating a second genome level once the power level has been reached.

Abstract: An apparatus includes an analytic network process (ANP) storage memory that stores an ANP weighted supermatrix representing an ANP model; and a processor in communication with the ANP storage memory. The processor is configured to facilitate measuring an instantaneous rate of change of alternative scores with respect to a fixed node of the ANP model, to determine a marginal influence of the fixed node. Also, the processor is configured to facilitate maintaining a same proportionality in the stored ANP weighted supermatrix as an importance of the fixed node is changed to measure the instantaneous rate of change.

Abstract: A computer-implemented expertise discovery method and system generates recommendations of people in accordance with inferences of levels of expertise from behavioral information. The generation of the recommendations may be in accordance with comparisons of two or more expertise vectors and associated correlations between the vectors. The inferences of expertise may be with respect to specified topical neighborhoods. Explanations as to why recommendations were made are delivered to the recommendation recipients, and may include references to the inferred levels of expertise, the behavioral bases for the inferences, and/or the confidence in the inferences.

Abstract: In a method for manipulating environmental conditions in an infrastructure containing one or more adaptive vent tiles, correlations between opening levels of the one or more adaptive vent tiles and an environmental condition at one or more heat dissipating devices are identified. In addition, one or more environmental conditions at locations proximate to or within the one or more heat dissipating devices are received and errors between the received one or more environmental conditions and one or more reference environmental conditions are identified. Moreover, opening levels for the one or more adaptive vent tiles are determined based upon the identified correlations and errors.

Abstract: A method, apparatus, and article, illustratively as a method of using an apparatus to computer-process digital data to produce, store, and disseminate output related to medical or health information.

Abstract: A method for changing qubit encoding for implementation of a quantum computational gate is disclosed. Such a method may include providing first and second qubits encoded in a plurality of non-abelian anyons according to a first encoding scheme. The first encoding scheme may not be suitable for implementing a certain topologically protected quantum computational gate, such as an entangling gate, for example. Successive topological charge measurements may be performed on at least a subset of the anyons until the qubits are encoded according to a second encoding scheme. The second encoding scheme may be different from the first encoding scheme, and may be suitable for implementing the gate.

Abstract: A computer-implemented method of scanning a plurality of files stored in a memory of a computer for malware. The computer includes a processor. The method includes, for each respective file of said plurality of files in said memory determining, using said processor, whether a relationship between the respective file and stored data satisfies a predetermined criterion. The stored data indicates one or more files determined not to contain malware and for which data associated with each of said one or more files has a predetermined characteristic. If the relationship satisfies the predetermined criterion, the respective file is processed according to said first processing method and if said relationship does not satisfy said predetermined criterion, the respective file is processed according to said second processing method.

Abstract: Systems, methods and apparatus for a scalable quantum processor architecture. A quantum processor is locally programmable by providing a memory register with a signal embodying device control parameter(s), converting the signal to an analog signal; and administering the analog signal to one or more programmable devices.

Abstract: The present invention relates to a fault trees method of early warning indication for critical infrastructure protection, which can provide a proper quantization result to be used for identifying a specific early warning indication for a critical infrastructure based upon the severity of risk assessed according to the quantification result.

Abstract: Described is a behavior recognition system for detecting the behavior of objects in a scene. The system comprises a semantic object stream module for receiving a video stream having at least two frames and detecting objects in the video stream. Also included is a group organization module for utilizing the detected objects from the video stream to detect a behavior of the detected objects. The group organization module further comprises an object group stream module for spatially organizing the detected objects to have relative spatial relationships. The group organization module also comprises a group action stream module for modeling a temporal structure of the detected objects. The temporal structure is an action of the detected objects between the two frames, whereby through detecting, organizing and modeling actions of objects, a user can detect the behavior of the objects.

Abstract: Disclosed herein are efficient geometries for dynamical topology changing (DTC), together with protocols to incorporate DTC into quantum computation. Given an Ising system, twisted depletion to implement a logical gate T, anyonic state teleportation into and out of the topology altering structure, and certain geometries of the (1,?2)-bands, a classical computer can be enabled to implement a quantum algorithm.

Abstract: Although recording of usage data is common in scholarly information services, its exploitation for the creation of value-added services remains limited due to concerns regarding, among others, user privacy, data validity, and the lack of accepted standards for the representation, sharing and aggregation of usage data. A technical, standards-based architecture for sharing usage information is presented. In this architecture, OpenURL-compliant linking servers aggregate usage information of a specific user community as it navigates the distributed information environment that it has access to. This usage information is made OAI-PMH harvestable so that usage information exposed by many linking servers can be aggregated to facilitate the creation of value-added services with a reach beyond that of a single community or a single information service.

Abstract: A method and apparatus for identifying individual trees in LiDAR data based on the view of a LiDAR data point. In one embodiment, those LiDAR data points that do not have neighboring LiDAR data points that block the local view at a defined angle are considered to be in a central part of a tree canopy. In one embodiment, those LiDAR data points that are in a central part of a tree canopy are added to an output file that stores clusters of data points for each tree canopy detected. The central part of the tree canopy area can be analyzed to predict one or more characteristics of the tree.

Abstract: A non transitory computer readable medium and a method of detecting excavation of an underground tunnel, the method includes: propagating a light pulse through an underground optic fiber; generating detection signals responsive to Brillion scattered light resulting from the propagating of the light pulse through the underground optic fiber; wherein the detection signals represent tension values at multiple locations along the underground optic fiber; and processing the detection signals to detect excavation of the underground tunnel.

Abstract: A categorization data structure is described that relates to two groups of individuals. For each of two or more categories, the data structure contains (1) information identifying individuals of the first group assigned to the category, and (2) information identifying individuals of the second group assigned to the category. For each category, the information can be used to adjust the individuals of the first group assigned to the category based upon comparing the proportion of all of the individuals of the second group that are assigned to the category to the proportion of all of the individuals of the first group that are assigned to the category.

Abstract: A compositional recommender framework using modular recommendation functions is described. Each modular recommendation function can use a discrete technology, such as using clustering, a database lookup, or other means. A first recommendation function can recommend to a user items, such as books to check out, automobiles to purchase, people to date, etc. Another modular recommendation function can be daisy chained with the first to recommend items that are similar or related to the first recommended items, such as users who have also checked out the same recommended book, trailers that can be towed by the recommended automobiles, or vacations booked by people that were recommended as people to date. The modular recommendation functions can be used to build customized recommendation engines for different industries.

Abstract: In a machine condition monitoring technique, a sensor reading is filtered using a switching Kalman filter. Kalman filters are created to describe separate modes of the signal, including a steady mode and a non-steady mode. For each new observation of the signal, a new mode is estimated based on the previous mode and state, and a new state is then estimated based on the new mode and the previous mode and state. In the steady mode, evolution covariances of both the observed signal and the rate of change of that signal are low. In the non-steady mode, the evolution covariance of the observed signal is set to a higher value, permitting the observed signal to vary widely, while the evolution covariance of the rate of change of the signal is maintained at a low level.

Abstract: A vehicle having a dynamics control system, the vehicle comprising: a first set comprising multiple adjustable sub-systems that affect the performance of the vehicle's powertrain; a second set comprising multiple adjustable sub-systems that affect the vehicle's handling; a dynamics user interface including a first input device and a second input device; and a dynamics controller coupled to the user interface and configured to adjust the operation of the sub-systems of the first set in dependence on the first input device and to adjust the operation of the sub-systems of the second set in dependence on the second input device.

Abstract: A method and apparatus for identifying individual trees in LiDAR data based on the view of a LiDAR data point. In one embodiment, the number of trees represented by a LiDAR data point cluster is estimated based on a calculated value related to the exposure to the sky of a LiDAR data point in the LiDAR data point cluster.

Abstract: Systems and methods that quantify document relevance for a document relative to a training corpus and select a best match or best matches are provided herein. Methods may include generating an example-based explanation for relevancy of a document to a training corpus by executing a support vector machine classifier, the support vector machine classifier performing a centroid classification of a relevant document in a term frequency-inverse document frequency features space relative to training examples in a training corpus, and generating an example-based explanation by selecting a best match for the relevant document from the training examples based upon the centroid classification. Determining the training example having the closest cosine distance to the relevant document includes ranking the training examples by stretching the internal best match scores for the training examples linearly to cover a complete unit interval.

Abstract: Methods for product data management and corresponding systems and computer-readable mediums. A method includes maintaining a hierarchical data structure for a complex item. The data structure includes a root node representing the complex item, at least one assembly node associated with a the partition node, and a plurality of part nodes each associated with the assembly node. The method includes defining at least two occurrences associated with the root node and corresponding to at least the root node and assembly node. The method includes defining at least one partition node representing a partition of the complex item, the partition node representing an organizational division of the occurrences of the associated with the root node that can be referenced in queries and navigation. The method includes associating at least two of the plurality of occurrences with the at least one partition node.

Abstract: A method of predicting the occurrence of a wind gust at a wind turbine is described. The values of at least one parameter measured for the wind turbine as input data are obtained on a predetermined frequency. A group of input data of predetermined size that was most recently obtained is selected. The probability of the occurrence of a wind gust is calculated based on the selected group of input data. The calculated probability that a wind gust will occur is verified to be above a predetermined probability level. And the occurrence of the wind gust is predicted.

Abstract: Moving information of an object is input, and first sound information around the object is input. A motion status of the object is recognized based on the moving information. Second sound information is selectively extracted from the first sound information, based on the motion status. A first feature quantity is extracted from the second sound information. A plurality of models is stored in a memory. Each model has a second feature quantity and a corresponding specified context. The second feature quantity is previously extracted by the second extraction unit before the first feature quantity is extracted. A present context of the object is decided based on the specified context corresponding to the second feature quantity most similar to the first feature quantity. The present context of the object is output.

Abstract: Intrusion features of a landing page associated with sponsored content are identified. A feature score for the landing page based on the identified intrusion features is generated, and if the feature score for the landing page exceeds a feature threshold, the landing page is classified as a candidate landing page. A sponsor account associated with the candidate landing page can be suspended, or sponsored content associated with the candidate landing page can be suspended.

Abstract: A language-processing system has an input for language in text or audio, as a message, an extractor operating to separate words and phrases from the input, to consult a knowledge base, and to assign a concept to individual ones of the words or phrases, and a connector operating to link the concepts to form a statement. In some cases there is a situation model updated as language is processed. The system may be used for controlling technical systems, such as robotic systems.

Abstract: A feed combine is provided which receives a feed including content from at least one data source. One of a plurality of scoring methods is selected for scoring the content in the feed based on a velocity of the feed. A determination is made as to which content in the feed is appropriate for display by producing a score using the selected scoring method. The scoring method uses a plurality of weighted scoring factors which alter the score based on whether the content includes objectionable material determined in accordance with user-defined criteria. A determination is made as to whether content is to be rendered on at least one rendering device based on a score assigned to the content.

Abstract: A software tool for creating, training and testing a knowledge base of a computerized customer relationship management system is disclosed. The software tool includes corpus editing processes for displaying and editing text-based corpus items, and assigning selected categories to individual corpus items. Knowledge base construction processes construct a knowledge base by analyzing a first subset of the corpus items, and testing processes test the knowledge base on a second subset of the corpus items. Reporting processes generate reports containing indicia representative of the testing results, which may be utilized to edit the corpus items and retrain the knowledge base so as to improve performance.

Abstract: According to an example embodiment, a technique may be provided for managing a label data base of which each entry comprises a data field for insertion into a respective packet in a multicast transmission and a validity field. The technique may include, for example, (a) establishing a fixed size for a cluster of labels, (b) associating with each cluster a pointer to another cluster, (c) establishing a sentinel cluster of which all entries are indicated to be invalid and of which the cluster pointer points to this sentinel cluster, (d) establishing a root table which defines the number of replications of the packet in a multicast group and identifies a first label cluster associated with the multicast group and (e) establishing a chain of clusters of which each cluster which is full of valid entries points to the next cluster in the chain and the last cluster which contains valid entries points to the sentinel cluster.

Abstract: One automatically accesses (101) a hierarchical task model as corresponds to a particular task to be executed by a given end user to thereby identify one or more presently un-executed agenda elements. One also automatically accesses (102) characterizing information for that given end user. (By one approach, for example, this characterizing information can comprise information regarding the given end user's knowledge.) This information regarding the un-executed agenda elements and the characterizing information are then used (103) to identify a highest hierarchical level within the hierarchical task model as corresponds to the given end user's wherewithal to successfully execute without also needing lower hierarchical level content within the hierarchical task model. The identified highest hierarchical level within the hierarchical task model is then used (104) to generate a presentation to present to the given end user to thereby facilitate execution of the particular task by the given end user.

Abstract: Generally, decisions are based on information. To be useful, information must be reliable. Basically, the concept of a Z-number relates to the issue of reliability of information. A Z-number, Z, has two components, Z=(A,B). The first component, A, is a restriction (constraint) on the values which a real-valued uncertain variable, X, is allowed to take. The second component, B, is a measure of reliability (certainty) of the first component. Typically, A and B are described in a natural language, for example: (about 45 minutes, very sure). Z-number has many applications, especially in the realms of economics, decision analysis, risk assessment, prediction, anticipation, rule-based characterization of imprecise functions and relations, and biomedicine. Different methods, applications, and systems are discussed. Other Fuzzy concepts are also discussed.

Abstract: A machine learning model is trained by instructing a user to perform proscribed gestures, sampling signals from EMG sensors arranged arbitrarily on the user's forearm with respect to locations of muscles in the forearm, extracting feature samples from the sampled signals, labeling the feature samples according to the corresponding gestures instructed to be performed, and training the machine learning model with the labeled feature samples. Subsequently, gestures may be recognized using the trained machine learning model by sampling signals from the EMG sensors, extracting from the signals unlabeled feature samples of a same type as those extracted during the training, passing the unlabeled feature samples to the machine learning model, and outputting from the machine learning model indicia of a gesture classified by the machine learning model.

Abstract: A digital media item, such as an electronic book (eBook), may include testing content. The testing content may include questions about the content of the digital media item. When is user is viewing the digital media item on an electronic device, such as an eBook reader, the user may be allowed to select whether the testing content is displayed. The user may also be allowed to select a particular mode of testing, such as automatic testing, selective testing, etc. If the user chooses to display the testing content, the user may also be allowed to provide answers to the testing questions.

Abstract: Managing a portfolio of experts is described where the experts may be for example, automated experts or human experts. In an embodiment a selection engine selects an expert from a portfolio of experts and assigns the expert to a specified task. For example, the selection engine has a Bayesian machine learning system which is iteratively updated each time an experts performance on a task is observed. For example, sparsely active binary task and expert feature vectors are input to the selection engine which maps those feature vectors to a multi-dimensional trait space using a mapping learnt by the machine learning system. In examples, an inner product of the mapped vectors gives an estimate of a probability distribution over expert performance. In an embodiment the experts are automated problem solvers and the task is a hard combinatorial problem such as a constraint satisfaction problem or combinatorial auction.

Abstract: Optional components are delivered to a software platform as a database load. A component is deployed to an application server of a first system. The component comprises at least a portion of the software to be delivered as a database load to a second system that implements the software platform. A component export tool in the first system identifies database table structures and database table entries created by the deployment of the component. The component export tool generates a load delivery package based on the identified database table structures and database table entries and then exports the load delivery package to the second system. A component load tool in the second system generates application tables based on the identified database table structures in the shipment package. The database table entries are then imported into the generated application packages in the load delivery package so that the component can be loaded into the software platform.

Abstract: A system and method for determining the health of a component includes retrieving measured health signatures from the component, retrieving component usage variables, estimating component health signatures using an aging model, determining an aging derivative using the aging model and calculating an aging error based on the estimated component health signatures, the aging derivative and the measured health signatures.

Abstract: Aspects relate to a cognitive agent that performs functions associated with a desired result. The functions performed by cognitive agent supplement other activities performed at a same time. In such a manner, the cognitive agent can function as a surrogate for a user. A performed activity can trigger implementation of another activity that is an extension of the performed activity. Cognitive agent can perform functions that can be represented as an avatar. Further, cognitive agent can be associated with a diagnostics component that evaluates an operating condition. Based on the operating condition cognitive agent can implement automatic actions associated with mitigating failures and/or prolonging the life of machinery.

Abstract: Systems and methods for determining muscle force are presented. Proportional, integral, and derivative control is used to simulate muscle forces for multiple muscles contributing to a kinematic profile. The simulated muscle forces arc modified by dynamic gains that are calculated in order to achieve a muscle recruitment objective such as minimizing collective muscle effort while still achieving the kinematic motion.

Abstract: A method of and apparatus and software for validating a computer model of a complex system comprising eliciting information regarding the complex system from one or more human experts, determining from the elicited information a set of variables and a set of constraints on those variables regarding the complex system, automatically by computer examining output of the computer model to locate violations of determined constraints, and generating output establishing any located violations.

Abstract: A computer system for visualizing recombination events in a group of individuals is provided. According to one aspect of the invention, high-density SNP genotype data is obtained from related individuals in a family. A pedigree is created, haplotypes are reconstructed and likely recombination breakpoints are identified with the use of publicly available computer programs. A software tool is then used facilitate the visualization of the recombination events in the family.

Abstract: A probabilistic database can including a set of geospatially referenced records and a probability engine. The geospatially referenced records corresponding to a real-world volumetric space indexed against voxels. Each voxel can have a unique identifier in the probabilistic database. Each voxel can corresponds to a volumetric unit of the real-world volumetric space. Geospatial information referenced against voxels can be internally inconsistent, which results in a naturally probabilistic storage format. The probability engine can be operable to dynamically determine a certainty value for an object of the probabilistic database. The certainty value can be a value from zero to one hundred percent, which is based upon a statistical analysis of the internally inconsistent geospatial information referenced against the voxels. The internally inconsistent geospatial information can correspond to a volumetric unit of the real-world volumetric space in which the object has a probability of residing within.