Abstract: A driver's orientation within a first vehicle is monitored. A change in the driver's orientation is detected. A change to a rear blind spot dimensional area of the first vehicle is calculated based upon the detected change. The rear blind spot dimensional area includes coordinates and dimensions of an area behind a peripheral view area of the driver and outside of rear viewable areas of viewable mirrors of the vehicle. The calculated change is applied to a statistical model of dangerous vehicle situations that includes a probabilistic function of at least one of a Gaussian distribution and a uniform distribution of at least one of the dangerous blind spot coordinates, dangerous information about the first vehicle, and dangerous characteristics of a vehicular environment surrounding the first vehicle. A dangerous situation associated with the first vehicle is predicted based upon a result of the calculated change applied to the statistical model.

Abstract: A driver's orientation within a vehicle is monitored. A change in the driver's orientation is detected. A change to a blind spot of the vehicle is calculated based upon the detected change in the driver's orientation. This abstract is not to be considered limiting, since other embodiments may deviate from the features described in this abstract.

Abstract: A method for providing an evaluation/verification of the correctness of an ontology is described. The method includes loading a first ontology associated with a first rule set. an extended ontology and an extended rule set are generated based at least in part on the first ontology and the first rule set. The extended rule set is applied to the extended ontology. The method also includes determining (e.g., by a data processor) a correctness of the extended ontology. Results are generated which include the correctness. Apparatus and computer readable media are also described.

Abstract: Vehicle performance capability information and spatial relationship information within a vehicular environment is obtained for each of a group of vehicles. Traffic light signaling information is obtained. At least one synchronized control action is determined for each of the group of vehicles by utilizing the vehicle performance capability information in conjunction with the spatial relationship information and the traffic light signaling information.

Abstract: A method, information processing system, and computer readable article of manufacture model data. A first dataset is received that includes a first set of physical world data. At least one data model associated with the first dataset is generated based on the receiving. A second dataset is received that includes a second set of physical world data. The second dataset is compared to the at least one data model. A probability that the second dataset is modeled by the at least one data model is determined. A determination is made that the probability is above a given threshold. A decision associated with the second dataset based on the at least one data model is generated in response to the probability being above the given threshold. The probability and the decision are stored in memory. The probability and the decision are provided to user via a user interface.

Abstract: Spatial relationship information and performance information are determined for vehicles within a vehicular environment. Traffic signaling information is received from a traffic regulation system associated with the vehicular environment. At least one synchronized control action is calculated for each of the vehicles to synchronize the vehicles with the traffic regulation system based upon the traffic signaling information, the determined spatial relationship information, and the determined performance information for each of the vehicles. The associated at least one synchronized control action is communicated to each of the vehicles. This abstract is not to be considered limiting, since other embodiments may deviate from the features described in this abstract.

Abstract: Methods for predicting states of a subject are presented. For example, a method for predicting states of a subject includes obtaining training data comprising a plurality of variables, obtaining training states associated with the training data, and forming a predictive model according to the training data and the training states, the predictive model predictive of the training states. The forming of the predictive model includes extracting one or more hidden components from the training data. The extracting of the one or more hidden components includes regression analysis including determining one or more relationships between the one or more hidden components and the plurality of variables, and determining one or more relationships between the one or more hidden components and the training states. A number of the one or more hidden components is less than a number of the plurality of variables and greater than a number of the training states.

Abstract: A method and system for generating problem resolution flowcharts, whereby users do not author flowcharts directly but instead author a dependency matrix of questions and answers related by state or underlying problem cause. After creation of a matrix of questions and answers, a corresponding flowchart is then calculated based on the information in the dependency matrix, and also based on the likelihood of the various problems and their causes. The probabilities of problems and their causes may be estimated or may be calculated from historical data accumulated by use of the flow chart, or some combination of the two. These probabilities are incorporated into the answer cells of the dependency matrix. The resulting flowchart is tested and evaluated, and the results of testing and evaluation are used to make modifications in the matrix of questions and answers.

Abstract: A method, information processing system, and computer readable article of manufacture model data. A first dataset is received that includes a first set of physical world data. At least one data model associated with the first dataset is generated based on the receiving. A second dataset is received that includes a second set of physical world data. The second dataset is compared to the at least one data model. A probability that the second dataset is modeled by the at least one data model is determined. A determination is made that the probability is above a given threshold. A decision associated with the second dataset based on the at least one data model is generated in response to the probability being above the given threshold. The probability and the decision are stored in memory. The probability and the decision are provided to user via a user interface.

Abstract: Methods for predicting states of a subject are presented. For example, a method for predicting states of a subject includes obtaining training data comprising a plurality of variables, obtaining training states associated with the training data, and forming a predictive model according to the training data and the training states, the predictive model predictive of the training states. The forming of the predictive model includes extracting one or more hidden components from the training data. The extracting of the one or more hidden components includes regression analysis including determining one or more relationships between the one or more hidden components and the plurality of variables, and determining one or more relationships between the one or more hidden components and the training states. A number of the one or more hidden components is less than a number of the plurality of variables and greater than a number of the training states.

Abstract: A method, computer readable storage medium, computer program product and a service. A profile of a computer user is obtained that contains meta tags descriptive of the participants of a first social networking website. A second social networking website having meta tags is selected. A profile from the second social networking website is selected. The meta tags of the first and second social networking websites are compared to determine if there is a match of at least one meta tag. Then, a search is made for related websites having at least one meta tag that matches the at least one meta tag. A list of the related websites is then presented to the computer user.

Abstract: Improved problem diagnosis techniques for use in accordance with computing systems, e.g., distributed computing systems, are disclosed. In one aspect of the invention, a technique for diagnosing a problem associated with a computing system comprises the following steps/operations. One or more probes are executed in accordance with at least a portion of a previously selected probe schedule. When a result of one or more of the probes of the previously selected probe schedule indicates, at least, a potential problem associated with the computing system, one or more probes which optimize at least one criterion are selected in real-time. The one or more selected probes are executed so as to diagnose the potential problem.

Abstract: Improved problem diagnosis techniques for use in accordance with computing systems, e.g., distributed computing systems, are disclosed. In one aspect of the invention, a technique for diagnosing a problem associated with a computing system comprises the following steps/operations. One or more probes are executed in accordance with at least a portion of a previously selected probe schedule. When a result of one or more of the probes of the previously selected probe schedule indicates, at least, a potential problem associated with the computing system, one or more probes which optimize at least one criterion are selected in real-time. The one or more selected probes are executed so as to diagnose the potential problem.

Abstract: Systems, methods and computer program products for supervised dimensionality reduction. Exemplary embodiments include a method including receiving an input in the form of a data matrix X of size N×D, wherein N is a number of samples, D is a dimensionality, a vector Y of size N×1, hidden variables U of a number K, a data type of the matrix X and the vector Y, and a trade-off constant alpha; selecting loss functions in the form of Lx(X,UV) and Ly(Y,UW) appropriate for the type of data in the matrix X and the vector Y, where U, V and W are matrices, selecting corresponding sets of update rules RU, RV and RW for updating the matrices U,V and W, learning U, V and W that provide a minimum total loss L(U,V,W)=Lx(X,UV)+alpha*Ly(Y,UW), and returning matrices U, V and W.

Abstract: A method for providing an evaluation/verification of the correctness of an ontology is described. The method includes loading a first ontology associated with a first rule set. an extended ontology and an extended rule set are generated based at least in part on the first ontology and the first rule set. The extended rule set is applied to the extended ontology. The method also includes determining (e.g., by a data processor) a correctness of the extended ontology. Results are generated which include the correctness. Apparatus and computer readable media are also described.

Abstract: Methods for predicting states of a subject are presented. For example, a method for predicting states of a subject includes obtaining training data comprising a plurality of variables, obtaining training states associated with the training data, and forming a predictive model according to the training data and the training states, the predictive model predictive of the training states. The forming of the predictive model includes extracting one or more hidden components from the training data. The extracting of the one or more hidden components includes regression analysis including determining one or more relationships between the one or more hidden components and the plurality of variables, and determining one or more relationships between the one or more hidden components and the training states. A number of the one or more hidden components is less than a number of the plurality of variables and greater than a number of the training states.

Abstract: Methods and apparatus for language translation in a computing environment associated with a virtual application are presented. For example, a method for providing language translation includes determining languages of a user and a correspondent; determining one or more sequences of translators; determining a selected sequence of selected translators from the one or more sequences of the translators; requesting a change in virtual locations, within the computing environment associated with the virtual application, of one or more selected translator virtual representations of the selected translators to a virtual meeting location within the computing environment associated with the virtual application; and changing virtual locations of the one or more selected translator virtual representations to the virtual meeting location.

Abstract: A method, information processing system, and computer readable article of manufacture model data. A first dataset is received that includes a first set of physical world data. At least one data model associated with the first dataset is generated based on the receiving. A second dataset is received that includes a second set of physical world data. The second dataset is compared to the at least one data model. A probability that the second dataset is modeled by the at least one data model is determined. A determination is made that the probability is above a given threshold. A decision associated with the second dataset based on the at least one data model is generated in response to the probability being above the given threshold. The probability and the decision are stored in memory. The probability and the decision are provided to user via a user interface.

Abstract: A method, information processing system, and computer readable article of manufacture reinforce behavior in an individual. A behavior associated with an individual is monitored. A determination is made, based on the monitoring, that the behavior substantially matches a behavior in a set of behaviors. A set of interactive actions associated with the behavior are identified. At least one of the interactive actions in the set of interactive actions is selected. The at least one of the interactive actions that has been selected is performed. A response from the individual is monitored in response to the least one of the interactive actions being performed. An indicator is associated with the at least one of the interactive actions based on the reaction from the individual. The indicator indicates a relative degree of success in obtaining a desired response from the individual.

Abstract: A method for performance bottleneck diagnosis and dependency discovery in distributed systems and computer networks includes receiving a real-valued end-to-end measurement matrix, a number of end-to-end measurements, a number of time points, a number of network components, a loss function, and a plurality of constraints on output matrices. The method further includes learning basic output matrices by best approximation of a transpose of the real-valued end-to-end measurement matrix, selecting a first threshold based on a real-valued mixing-weights matrix and a second threshold based on a real-valued delay matrix, converting the real-valued mixing-weights matrix and the real-valued delay matrix into respective binary matrices using the first threshold and the second threshold, and returning the real-valued mixing-weights matrix, the real-valued delay matrix, and the respective binary matrices to represent bottlenecks dependencies of the distributed system or computer network.