Abstract: Techniques for implementing a last known good (LKG) client-side cache for DNS resiliency are disclosed. A first DNS request is submitted to a DNS server. A first DNS resolution that resolves an IP address for a domain name is received. A service stores the first DNS resolution in an LKG cache residing on the local host. A second DNS request is sent, where the second DNS request again requests to resolve the same domain name. In response to determining that a second DNS resolution for the second DNS request has not been received, the service obtains the IP address for the domain name from the LKG cache.

Abstract: In one embodiment of the invention, a training model for students is provided that models how to present training items to students in a computer based adaptive trainer. The training model receives student performance data and uses the training model to infer underlying student skill levels throughout the training sequence. Some embodiments of the training model also comprise machine learning techniques that allow the training model to adapt to changes in students skills as the student performs on training items presented by the training model. Furthermore, the training model may also be used to inform a training optimization model, or a learning model, in the form of a Partially Observable Markov Decision Process (POMDP).

Abstract: In one embodiment of the invention, a training model for students is provided that models how to present training items to students in a computer based adaptive trainer. The training model receives student performance data and uses the training model to infer underlying student skill levels throughout the training sequence. Some embodiments of the training model also comprise machine learning techniques that allow the training model to adapt to changes in students skills as the student performs on training items presented by the training model. Furthermore, the training model may also be used to inform a training optimization model, or a learning model, in the form of a Partially Observable Markov Decision Process (POMDP).

Abstract: Systems and methods to provide a training solution for a trainee are disclosed. In some embodiments the method comprises receiving a training requirement comprising a training outcome and a training configuration wherein the training configuration defines a trainee state, determining a training environment based on a relevancy function of the training environment to the training outcome, determining a training content based on a relationship function of the training content to the trainee state and determining a training solution comprising the training environment and the training content. In some embodiments, the relationship function comprises a POMDP model and the relevancy function comprises a best fit curve.

Abstract: Systems and methods to provide a training solution for a trainee are disclosed. In some embodiments the method comprises receiving a training requirement comprising a training outcome and a training configuration wherein the training configuration defines a trainee state, determining a training environment based on a relevancy function of the training environment to the training outcome, determining a training content based on a relationship function of the training content to the trainee state and determining a training solution comprising the training environment and the training content. In some embodiments, the relationship function comprises a POMDP model and the relevancy function comprises a best fit curve.

Abstract: A computer implemented systems and methods for determining an action for a user within a learning domain are disclosed, some embodiments of the methods comprise defining an initial learning model of a learning domain, determining an initial user state of the user, determining an initial user action from at least one learning domain action with the initial learning model, receiving a user observation of the user after the user executes the initial user action, determining an updated user state with the initial learning model given the updated user observation and determining a subsequent user action from the at least one learning domain action. Some embodiments utilize a Partially Observable Markov Model (POMDP) as the learning model.

Abstract: Managing cluster resources for a cluster. The method includes identifying a plurality of quiescence policies. Each of the quiescence policies define one or more conditions for cluster entities which when met, identify that cluster resources should be reclaimed from cluster entities by quiescing cluster entities. The method further includes, for each quiescence policy, identifying an amount of reclaimed capacity defining the amount of cluster resources that will be reclaimed by implementing the quiescence policy. The method further includes, for each quiescence policy, identifying an amount of reserve capacity defining the amount of cluster resources that should be reserved for resuming quiesced cluster entities. The method further includes; selecting a quiescence policy based on comparing the reclaimed capacities and reserve capacities for the quiescence policies. The method further includes, booking cluster resources for cluster entities on the cluster according to the selected quiescence policy.

Abstract: Managing cluster resources for a cluster. The method includes identifying a plurality of quiescence policies. Each of the quiescence policies define one or more conditions for cluster entities which when met, identify that cluster resources should be reclaimed from cluster entities by quiescing cluster entities. The method further includes, for each quiescence policy, identifying an amount of reclaimed capacity defining the amount of cluster resources that will be reclaimed by implementing the quiescence policy. The method further includes, for each quiescence policy, identifying an amount of reserve capacity defining the amount of cluster resources that should be reserved for resuming quiesced cluster entities. The method further includes; selecting a quiescence policy based on comparing the reclaimed capacities and reserve capacities for the quiescence policies.

Abstract: Computer implemented systems and methods of communicating a system reaction to environmental input comprising receiving environmental input, determining a hazard state and a user state from the environmental input, determining a system reaction from the hazard state and the user state and communicating the system reaction to a user interface. In some embodiments, the system reaction comprises a system reaction level and in some embodiments the system reaction level corresponds to a stage of automation. In some embodiments, the user interface is a multimodal interface and in some embodiments the user interface is a haptic interface.

Abstract: Creating web application using cloud-based friction-free databases without web hosting knowledge. User credentials are received at a web application service for initiating a web application task via client software. The user credentials are analyzed to determine whether to grant the user permission to initiate the requested web application task. The web application task is initiated when the permission is granted. Data associated with the initiated web application task is received at the web application service for analysis of the data to host and render a web application based solely on received data provided without basis of web hosting knowledge.

Abstract: Systems and methods to provide a training solution for a trainee are disclosed. In some embodiments the method comprises receiving a training requirement comprising a training outcome and a training configuration wherein the training configuration defines a trainee state, determining a training environment based on a relevancy function of the training environment to the training outcome, determining a training content based on a relationship function of the training content to the trainee state and determining a training solution comprising the training environment and the training content. In some embodiments, the relationship function comprises a POMDP model and the relevancy function comprises a best fit curve.

Abstract: A device is configured with components to enable debugging of the device's entry into and exit from a low power mode. The device includes: core logic, debug components, and a power management module (PMM). When the device exits a low power mode in which the states of the debug components are lost, the PMM prevents the core logic from resuming processing operations until the debug components have been re-configured to their prior states. The PMM either holds the core logic in reset or alternatively withholds power to the core logic. Reconfiguration of the debug components is initiated by a connected debugger, which can set one or more control and status (CS) register values within the device. The CS register values determine when the PMM prevents the core logic processing from resuming and when the PMM enables core logic processing to resume following the device's return from low power mode.

Abstract: A computer implemented systems and methods for determining an action for a user within a learning domain are disclosed, some embodiments of the methods comprise defining an initial learning model of a learning domain, determining an initial user state of the user, determining an initial user action from at least one learning domain action with the initial learning model, receiving a user observation of the user after the user executes the initial user action, determining an updated user state with the initial learning model given the updated user observation and determining a subsequent user action from the at least one learning domain action. Some embodiments utilize a Partially Observable Markov Model (POMDP) as the learning model.

Abstract: Computer implemented systems and methods of communicating a system reaction to environmental input comprising receiving environmental input, determining a hazard state and a user state from the environmental input, determining a system reaction from the hazard state and the user state and communicating the system reaction to a user interface. In some embodiments, the system reaction comprises a system reaction level and in some embodiments the system reaction level corresponds to a stage of automation. In some embodiments, the user interface is a multimodal interface and in some embodiments the user interface is a haptic interface.

Abstract: Creating web application using cloud-based friction-free databases without web hosting knowledge. User credentials are received at a web application service for initiating a web application task via client software. The user credentials are analyzed to determine whether to grant the user permission to initiate the requested web application task. The web application task is initiated when the permission is granted. Data associated with the initiated web application task is received at the web application service for analysis of the data to host and render a web application based solely on received data provided without basis of web hosting knowledge.

Abstract: Systems and methods that group atomic scalar values recognized by a database such as columns into sets (e.g., column sets). A grouping component associated with the SQL server creates a logical representation for column groupings, which are accessible by a single I/O and can be co-located (e.g., substantially close or compact) in terms of storage location. Interesting column sets (e.g., non-null) can also be selected for a data representation thereof as a single entity to other applications.

Abstract: A device is configured with components to enable debugging of the device's entry into and exit from a low power mode. The device includes: core logic, debug components, and a power management module (PMM). When the device exits a low power mode in which the states of the debug components are lost, the PMM prevents the core logic from resuming processing operations until the debug components have been re-configured to their prior states. The PMM either holds the core logic in reset or alternatively withholds power to the core logic. Reconfiguration of the debug components is initiated by a connected debugger, which can set one or more control and status (CS) register values within the device. The CS register values determine when the PMM prevents the core logic processing from resuming and when the PMM enables core logic processing to resume following the device's return from low power mode.

Abstract: Architecture that maps document data (e.g., XML-extended markup language) into columns of one table, thereby avoiding schema normalization problems through special data storage. Moreover, an algorithm is described that can translate a query (e.g., in XPath (XML path language), a query language for navigating through document elements and attributes of an XML document) into a relational algebra query of the document column representation. Based on the characteristics of the new mapping, query rewriting rules are provided that optimize the relational algebra query by minimizing the number of joins. The mapping of XML documents to the table is based on a summary structure and a hierarchical labeling scheme (e.g., ordpath) to enable a high-fidelity representation. Annotations are employed on the summary structure nodes to assist in mapping XML elements and attributes to the table.

Abstract: Systems and methods that group atomic scalar values recognized by a database such as columns into sets (e.g., column sets). A grouping component associated with the SQL server creates a logical representation for column groupings, which are accessible by a single I/O and can be co-located (e.g., substantially close or compact) in terms of storage location. Interesting column sets (e.g., non-null) can also be selected for a data representation thereof as a single entity to other applications.