Abstract: A wireless enabled digital media frame that can communicate over a wireless wide area network (WWAN) is provided. The wireless enabled digital media frame comprises an internal or external WWAN modem (e.g. GPRS/EDGE/UMTS/HSPA/LTE) such that the one or more media is transferred to the media frame using a wireless connection (e.g. 2G/3G/3.5G/4G). The wireless enabled digital media frame displays the received media files on a display screen. Further, broadcast alerts received over the WWAN and/or calculated current signal strength is also displayed on the display screen. Furthermore, setting information is received by the WWAN modem and accordingly applied to modify or update media frame functions.

Abstract: Methods, computer-readable media, and apparatuses for determining the status of a clinical database in order to characterize the quality of the database. The status may be based on the proportion of outstanding items in relation to relative milestones. A database rating index for a database is determined from risk factors, where the database rating index is indicative of a status of the clinical database and may be determined from risk factors, where each risk factor includes an issue parameter and a subject parameter, the issue parameter equals the number of occurrences for the corresponding issue, and the subject parameter corresponds to the number of patients associated with the issue parameter. The database rating index may be determined from one of a set of functions that depend on an issue health score and a subject health score.

Abstract: A system and method for representing call content in a searchable database includes transcribing call content to text. The call content is projected to vector space, by creating a vector by indexing the call based on the content and determining a similarity of the call to an atomic-class dictionary. The call is classified in a relational database in accordance with the vector.

Abstract: A method for computing power consumption includes querying a software database for a key node and a gate comprising an input port, connected to the key node, and an output port. The software database is created from a net list associated with a design. The method includes calculating a probability of activity level at the output port based on a predetermined activity level at the key node, and querying the software database for next gate comprising a next input port, connected to the previous output port, and a next output port. The method includes calculating a probability of activity level at the next output port based on the probability of activity level at the previous output port. The method includes computing a sub-circuit gate power by sum of power of all the gates based on the probability of activity level at output ports of the gates.

Abstract: A method of identifying radioactive components in a source comprising (a) obtaining a gamma-ray spectrum from the source; (b) identifying peaks in the gamma-ray spectrum; (c) determining an array of peak energies and peak intensities from the identified peaks; (d) identifying an initial source component based on a comparison of the peak energies with a database of spectral data for radioactive isotopes of interest; (e) estimating a contribution of the initial source component to the peak intensities; (f) modifying the array of peak energies and peak intensities by subtracting the estimated contribution of the initial source component; and (g) identifying a further source component based on a comparison of the modified array of peak energies with the database of spectral data. Thus a method for identifying radioactive components in a source is provided which does not rely on comparing template spectra with an observed spectrum.

Abstract: In a pen-based computing system, use of paradigms similar to those used with physical paper to organize user generated content captured by a smart pen is disclosed. Data, such as handwriting gestures, is captured by the smart pen and transferred to a digital domain, such as by being transferred to a computing system. Once in the digital domain, the captured content is organized as virtual pages or virtual notebooks. Hence, content captured from various sources, such as different notebooks or different physical pieces of paper, is assembled into a virtual page or virtual notebook. User input or automatic application of rules can be used to assemble the captured content into a virtual page or virtual notebook.

Abstract: A method (and structure) of quantum computing. Two independent magnitudes of a three-state physical (quantum) system are set to simultaneously store two real, independent numbers as a qubit. The three-state physical (quantum) system has a first energy level, a second energy level, and a third energy level capable of being degenerate with respect to one another, thereby forming basis states for the qubit.

Abstract: A method, a system, and a computer-readable medium are provided for generating a complex alert. Values of a plurality of physiological characteristics of a patient are received. The received values are compared to a complex alert rule associated with a medical condition. The complex alert rule includes a plurality of alert rules, wherein each alert rule includes an indicator of a physiological characteristic of a patient associated with the alert rule and a condition priority associated with an urgency of the alert rule. The complex alert rule also includes a trigger rule. The trigger rule includes a plurality of rules wherein each rule includes a number of satisfied alert rules for each value of the condition priority. A number of alert rules of the plurality of alert rules that are satisfied is determined for each condition priority of the complex alert rule based on the comparison.

Abstract: A method for analyzing an electrical power system using fuzzy logic includes: (a) acquiring data representing a signal of interest of the power system; (b) analyzing the signal using at least one fuzzy logic rule, wherein the fuzzy logic rules include: (1) phase level rules which are based on features extracted from a particular phase on the electric power system; (2) segment level rules which are evaluated using information from different phases; and (3) capture level rules which combine truth values obtained from one or more segments; and (c) based on the analysis, detecting and classifying at least one power system event within the power system.

Abstract: The present invention relates to a music selecting system and method, and more particularly, to a technology that suitably determines an emotional quotient of user by preferably using a heart rate and biorhythm of user, and automatically selecting music of specific genre according to the determined emotional quotient, a current time and an age.

Abstract: A system and method for precaching information on a mobile device. A precaching strategy is built for a mobile device The strategy defines a forecast of data types a user is predicted to request after the occurrence of one or more data refresh conditions. The precaching strategy is built by recognizing data usage patterns in data requested by the user or a group of users over a time period. The data usage pattern comprises data types and events that are correlated to the usage of the data. The events are used to define at least one refresh condition within the precaching strategy. The precaching strategy is executed. When the occurrence of the data refresh condition is detected, data is then retrieved from a data source, wherein the data is retrieved according to the precaching strategy. The retrieved data is transmitted to a user device cache.

Abstract: The system contains a plurality of sensors outputting sensor data. A processor is in communication with the sensors to receive the sensor data. A logic system is in communication with the processor. The logic system evaluates a likelihood of a plurality of hypotheses, generates a representation of the likelihood of the plurality of hypotheses in a coordinate system, and connects trajectories between a plurality of discrete hypothesis aspects of the plurality of hypotheses. An output of the processor provides at least one likely outcome and a confidence level for each of the likely outcomes. At least one likely outcome is selected based on contours of the representation of the likelihood to of the plurality of hypotheses in the coordinate system.

Abstract: A method and apparatus for the creation, selection, ordering, shipping and constructing of personalized living environments with customized configurations through the use of an architectural process, unitized assemblies, and assembly joineries. The architectural process allows for the initial creation, design and selection of the unitized assembly collections based upon human factors behavioral based criteria. The unitized assemblies are fixed and/or flexible, trade-integrated modules in unitized, shippable configurations designed and incorporated with high touch finished crafts, allowing for dimensional flexibility. The unitized assembly and human factors behavioral analysis combine for an experience blueprint of a homeowner's lifestyle portrait. The assembly joineries, based upon the desired collections selection, provide finishing touches to the unitized assembly, efficient strength to weight ratios, and expressed, stylized configurations in hybrid materials.

Abstract: A configuration mapping system and method increase the effectiveness of mapping of information from an established product line to a new product offering. In at least one embodiment, the configuration mapping system herein uses configuration mapping rules to map individual product features and entire configurations from established products to a new product offering. The configuration mapping system also provides a way to appropriately map, for example, demand and sales information for the purpose of demand estimation and sales prediction. Conventionally, mapping can be ineffective because the configuration mapping rules usually focus on one part of the product at a time, and, if applied in isolation, the impact on other parts is missed. The systems and method herein provide a way to integrate configuration mapping rules across feature parts, time periods, and product lines into a unified, holistic view, allowing for new insights.

Abstract: A method for training a system to specifically react on a specific input. The method can include defining a set of binary data structures, each representing a real-world component, item, or virtual object; storing each data structure as a binary pattern; creating uniquely identifiable copies of the data structures to represent individual instances of the components, items, or virtual objects; creating a virtual state space of the components, items, or virtual objects by grouping them as relevant for a specific situation; receiving an input to change a status or an attribute value of at least one of the components, items, or virtual objects; storing the received changes in a new version of the applicable data structure instance; analyzing similarities of the stored binary patterns related to a particular action performed; and if a matched binary pattern is identified, proposing at least one possible action related to the matched binary pattern.

Abstract: A method and an apparatus for controlling a distributed automation system, wherein the method comprises determining global constraint rules according to the cooperative relationships between function blocks in the distributed automation system, and establishing a mathematical model based on Membrane Calculus, performing the instantiation of the established mathematical model based on Membrane Calculus according to an executor corresponding to each of the function blocks in the distributed automation system, so as to produce control logics for output to the distributed automation system. If disturbance information is received from the distributed automation system, altering the parameters of the instantiation of the mathematical model based on Membrane Calculus are altered using the disturbance information, so as to produce control logics for outputting to said distributed automation system.

Abstract: Avatars, methods, apparatuses, computer program products, devices and systems are described that carry out presenting to at least one member of a population a plurality of avatars associated with at least one instance of media content; measuring at least one physiologic activity of the at least one member of the population, the at least one physiologic activity proximate to at least one presented avatar among the plurality of avatars associated with at least one instance of media content; associating the at least one physiologic activity with at least one mental state; and identifying at least one preferred instance of media content based on the at least one mental state.

Abstract: Events may be identified by storing information in response to activating an event stamp function. As a result of activating the event function, the information collected may immediately be compared to event information in a database. Alternatively, the information collected may later be compared to event information in a database. One or more candidates for the event of interest may be automatically or manually retrieved, and the user may decide whether a candidate event of the one or more candidates correspond to the event of interest. Alternatively, a purchase of an item related to the event may be automatically made in response to activating the event stamp.

Abstract: The identification of Hammerstein models relates to a computerized method for identifying Hammerstein models in which the linear dynamic part is modeled by a space-state model and the static nonlinear part is modeled using a radial basis function neural network (RBFNN), and in which a particle swarm optimization (PSO) algorithm is used to estimate the neural network parameters and a numerical algorithm for subspace state-space system identification (N4SID) is used for estimation of parameters of the linear part.

Abstract: A method and a system for recognizing power consumption behaviors of electric appliances in a loop are provided. When a variation value of a power consumption information of the loop exceeds a threshold, a current value of the power consumption information is served as a main loop factor value of the loop, and a similar combinative factor value close to the main loop factor value is looked up in a behavior-factor mapping table. If the similar combinative factor value is not found, the main loop factor value corresponding to a new power consumption behavior is obtained according to the variation value of the power consumption information to reconstruct the behavior-factor mapping table. After obtaining the similar combinative factor value from the behavior-factor mapping table, a current electric appliance power consumption behavior of the loop is determined according to a power consumption behavior combination corresponding to the similar combinative factor value.

Abstract: The method for Hammerstein modeling of a steam generator plant includes modeling of the linear dynamic part of a Hammerstein model with a state-space model, and modeling the nonlinear part of the Hammerstein model with a radial basis function neural network (RBFNN). Particle swarm optimization (PSO), typically known for its heuristic search capabilities, is used for estimating the parameters of the RBFNN. Parameters of the linear part are estimated using a numerical algorithm for subspace state-space system identification (N4SID).

Abstract: The method for the identifying of multiple input, multiple output (MIMO) Hammerstein models that includes modeling of the linear dynamic part of a Hammerstein model with a state-space model, and modeling the nonlinear part of the Hammerstein model with a radial basis function neural network (RBFNN).

Abstract: A computerized method for detecting related events in a water monitoring system. The method includes receiving event data from a plurality of sensors in a water network. The method also includes identifying at least two candidate events from the event data as being candidate events which are likely to constitute part of a common anomaly event, the candidate events each being substantially anomalous. An event combination rule is selected. One or more event characteristics are compared between the at least two candidate events based on the event combination rule. The at least two candidate events are determined whether they are related and associated with a common event causing the at least two candidate events on the basis of the comparison. The determination of the at least two candidate events are related and associated with a common event is reported to a user via a user interface.

Abstract: In some example embodiments, a system and method are illustrated as including receive pattern data that includes transaction data relating to transactions between persons. Next, the system and method may include building at least one secondary network based upon the pattern data. Additionally, the system and method may include displaying the at least one secondary network.

Abstract: A location history manager may be configured to determine a location history associated with a user, and a resource usage manager may be configured to determine a computing resource usage history associated with the user. A location monitor may be configured to determine a location of the user. A resource predictor may be configured to generate a prediction of a computing resource, based on the location history, the computing resource usage history, and the location. A resource provider may be configured to provide the computing resource, based on the prediction.

Abstract: A device for designing a sensor arrangement for an automated system, the device comprising a first input unit for receiving a specification of a plurality of sensor measurements to be carried out by the sensor arrangement, a second input unit for receiving a specification of a confidence region together with an associated confidence level for each of the specified sensor measurements, a third input unit for receiving a specification of a target confidence level for the automated system, and a configuration unit for configuring the plurality of sensor measurements and for configuring the combination of the sensor measurements in a manner to guarantee the target confidence level for the automated system.

Abstract: The present invention provides a method for learning a policy used by a computing system to perform a task, such delivery of one or more objects by the computing system. During a first time interval, the computing system determines a first state, a first action and a first reward value. As the computing system determines different states, actions and reward values during subsequent time intervals, a state description identifying the current sate, the current action, the current reward and a predicted action is stored. Responsive to a variance of a stored state description falling below a threshold value, the stored state description is used to modify one or more weights in the policy associated with the first state.

Abstract: A method of determining an appropriate response to an input includes linking a plurality of attributes to a plurality of response templates using a plurality of Boolean expressions. Each attribute is associated with a set of patterns. Each pattern within the set of patterns is equivalent. The method also includes determining an appropriate response template from the plurality of response templates based on the input.

Abstract: A process, machine, manufacture, or composition of matter, and improvements, illustratively as method of using a machine, the method including: storing data of a population in memory; computing, by a computer accessing the data stored in the memory, a probability of at least one future medical treatment needed by at least one individual having data in the data of a population; ascribing, by the computer applying the computed probabilities, each said individual with one of a plurality of risk stratifications for each said future medical treatment; and producing, by the computer communicating to an output device, output including at least one said ascribed individual in association with the one of the risk stratifications. The method can also include forming, by the computer accessing the data stored in the memory, an association of travel by an individual and a health consequence as a result of the travel by the individual; and generating, at the output device, output including the association.

Abstract: A method includes performing quantum state tomography from the statistics of a collection of measurements, each of which has only two possible outcomes and has the feature of being a measurement of a single qubit. By carefully choosing the measurements it becomes possible to infer the state of a quantum system from the statistics. Moreover, the function which computes the state from the measurement statistics can be computed efficiently in the dimension of the underlying system. Reconstructing the quantum state is performed in accordance with the following expression: ? = ( 2 d ? ? i = 1 d 2 - 1 ? ? p i ? P i + ( 1 - p i ) ? ( 1 - P i ) ) - ( d 2 - 2 d ) ? I d , where d is the dimension of the quantum mechanical system, ? is the state of the quantum mechanical system, Id denotes the identity operator, Pi is one of the plurality of measurement projectors, and pi is the probability for the measurement projector Pi.

Abstract: The present invention provides a robot apparatus that can perform appropriate actions in accordance with the ambient conditions, and a method of controlling the behavior of the robot apparatus.

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: 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: Methods, systems, and apparatus, for selecting a trained predictive models. A request is received from a client-subscriber computing system for access to a trained predictive model that can generate a predictive output in response to receiving input data having one or more input types. Information that describes each of the trained predictive models in a predictive model repository can be used to determine that one or more models included in the repository match the request. Determining a match can be based (at least in part) on a comparison of the one or more input types to input types included in the information that describes the trained predictive models. Access is provided to at least one of the models to the client-subscriber computing system. The models that match the request are models that were trained using training data provided by a computing system other than the client-subscriber computing system.

Abstract: A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

Abstract: In one embodiment, we describe a method that generates seasonality rules for anomaly detection for a hierarchical/tree based data structure. A new algorithm for processing nodes in hierarchy, as well as business rules for nodes, is described. Variations and examples are given to describe different scopes and embodiments of the invention. Exclusion criteria and children nodes are used as some examples for the implementations, with flow charts to describe the methods of application, as examples.

Abstract: A method for legal knowledge modeling and automated legal evaluation, such as for online, questionnaire-based legal analysis, is provided. Information, such as facts and characteristics of a legal situation or legal scenario, as it relates to a legal conclusion or a legal result, in addition to the probabilities of such conclusions or results, are modeled in a Bayesian Network. The Bayesian Network may comprise instantiable nodes, fault nodes, intermediary nodes, a utility node and decision nodes. The Bayesian network is automatically updated on a periodic basis to reflect new legislation or court decisions. Using Bayesian inference, the conditional probability of a legal conclusion based on a user's answers to a questionnaire may be determined. These conditional probabilities are modified upon the input of evidence, which is typically in the form of answers to a dynamic set of questions designed to identify a legal conclusion or a legal result.

Abstract: A computer system creates and stores a library of LiDAR models for standard trees that have measured characteristics. A point cloud of LiDAR data from an unidentified tree in a forest is compared against a point cloud defined by a LiDAR model of a standard tree in the library to find a match. If a match is found, one or more characteristics of the matching standard tree are associated with the unidentified tree.

Abstract: A dynamic constraint solver for solving a constraint satisfaction problem network that includes a plurality of nodes and a plurality of constraints determines a cardinality for a set of sub-problems. The cardinality is a numeric domain that represents the minimum number of instances in a port. The solver determines if a number of identifiable instances of sub-problems is less than the minimum number of instances. The solver then causes a user interface to display the identifiable instances and a placeholder for each instance that is below the minimum number of instances and is not identifiable.

Abstract: Systems and methods presented herein construct groups and determine the presence for the groups. The groups can be constructed based on business logic. A set of components can model a group from the business logic, can establish a membership for the group, can determine one or more rules that govern presence determination for the membership, and can provide the group model, membership information, and the one or more rules to a rules engine. The rules engine can evaluate presence within the group model based on the membership and the one or more rules. The group presence can then be provided to one or more entities, applications, or workflows that subscribe to the rules engine for the group presence.

Abstract: Methods, systems and computer program products for evaluating performance of generative models are disclosed. One method includes providing a base model and a candidate model having observed variables and first and second conceptually related variables related to the observed variables, respectively, receiving observations assigned to a subset of the observed variables, and for each observation, evaluating the observation by the base model to produce a base assessment of the observation, evaluating the observation by the candidate model to produce a second assessment of the observation, determining a similarity measure of the assessment of the observation based on the base and second assessments, and selecting a subset of observations having low similarity measures for use in evaluating performance of the candidate model.

Abstract: As provided herein objects from a source catalog, such as a provider's catalog, can be added to a target catalog, such as an enterprise master catalog, in a scalable manner utilizing catalog taxonomies. A baseline classifier determines probabilities for source objects to target catalog classes. Source objects can be assigned to those classes with probabilities that meet a desired threshold and meet a desired rate. A classification cost for target classes can be determined for respective unassigned source objects, which can comprise determining an assignment cost and separation cost for the source objects for respective desired target classes. The separation and assignment costs can be combined to determine the classification cost, and the unassigned source objects can be assigned to those classes having a desired classification cost.

Abstract: The present invention provides a diagnostic system that diagnoses a diagnostic object by applying a diagnostic rule to data measured on the diagnostic object wherein an object of the present invention is to allow the diagnostic rule to be updated based on a variety of diagnostic case data. Each of multiple diagnostic devices 101 makes a diagnosis by applying a diagnostic rule to diagnostic object data measured on a diagnostic object 104 and sends diagnostic case data, which includes diagnostic object data and its diagnostic result, to a diagnostic rule generation device 102 via a network 103. The diagnostic rule generation device 102 generates a diagnostic rule based on the diagnostic case data received from the multiple diagnostic devices 101 and sends the generated diagnostic rule to the diagnostic devices 101 via the network 103. The diagnostic devices 101 update a diagnostic rule in their devices with the diagnostic rule received from the diagnostic rule generation device 102.

Abstract: One embodiment provides a technique for analyzing a target electromagnetic signal radiating from a monitored system. During the technique, the monitored system is positioned at a first locus of an ellipsoidal surface to amplify the target electromagnetic signal received at a second locus of the ellipsoidal surface. Next, the amplified target electromagnetic signal is monitored using an antenna positioned at the second locus of the ellipsoidal surface. Finally, the integrity of the monitored system is assessed by analyzing the amplified target electromagnetic signal monitored by the antenna.

Abstract: A context inference system including a mobile device and at least one information sending unit is provided. The mobile device includes an information receiving unit and a context operation platform. The information receiving unit receives a context information. The context operation platform includes an information collection module for collecting the information used for inferring a context based on a convergent search and an expanded search, a data classification and storage module for storing and classifying a user preference information of a user, and an inference module for inferring a context. The information sending unit transmits the context information to the mobile device. The context operation platform performs a context inference process according to the context information and the user preference information in order to forecast the user's need and provide a recommendation information to the user.

Abstract: There is provided a substrate processing system that can automatically inspect the operation of various kinds of parts of a semiconductor manufacturing apparatus without increasing the load of a main controller in the semiconductor manufacturing apparatus. In the substrate processing system of the present invention, inspection data of the semiconductor manufacturing apparatus 1 under operation are shared and collected online by a main controller 5, a data collection auxiliary computer 2 and a data collecting computer 3 through a network 6, and the operation state is collectively inspected by an inspecting computer 4.

Abstract: The present invention disclosed a method constructing an intelligent system processing uncertain causal relationship information. It can express, monitor and analyze the causal logic relationship among the different variables in complex systems directly, implicitly or in both way of them under the circumstance of unsure, dynamic, having a logic loop, lacking of statistical data, unclear evidence, mixture of discrete and continuous variables, incomplete knowledge, multi-resource of knowledge. It gave effective bases to solve the problems in the domain of production, monitoring, detection, diagnosis, prediction, et al.

Abstract: A self-adaptive resource management method (200) is proposed. The system is based on an authority (105) that publishes multiple rules into a corresponding repository (115). Each rule defines a desired target configuration for a category of subjects (110); each category is specified by one or more attributes that are evaluated by corresponding scanners (233-239). Whenever new rules are published, a dedicated module (120) creates and publishes further rules for selectively installing the scanners that are required for evaluating the attributes included in the categories of the new rules. These further rules are defined according to an algorithm that attempts to minimize the cost involved by the installation of the scanners.

Abstract: A window processing system is disclosed for fabricating window frames. A welding station has welding heads to weld or fuse vinyl frame parts together. The frames are taken to a cleaning station having a number of cleaning heads that are independently actuated to move into a position relative selected portions of the window frame to clean off burrs, weld beads etc from the welded window frame. The cleaning process involves both training of a controller to recognize certain frame profiles and a compensation process for adjusting the cleaning process for individual variations in the frame that occur during fabrication. Real-time cleaning involves coupling a visual sensor to a moving support that also supports a cleaning tool.

Abstract: Methods, systems, and apparatus, including computer programs encoded on one or more computer storage devices, for training and retraining predictive models. A series of training data sets for predictive modeling can be received, e.g., over a network from a client computing system. The training data included in the training data sets is different from initial training data that was used with multiple training functions to train multiple trained predictive models stored in a predictive model repository. The series of training data sets are used with multiple trained updateable predictive models obtained from the predictive model repository and multiple training functions to generate multiple retrained predictive models. An effectiveness score is generated for each of the retrained predictive models. A first trained predictive model is selected from among the trained predictive models included in the predictive model repository and the retrained predictive models based on their respective effectiveness scores.