Abstract: The following relates generally to computer system efficiency improvements. Broadly, systems and methods are disclosed that improve efficiency in a cluster of nodes by efficient processing of tasks among nodes in a cluster of nodes. Initially, tasks may be scheduled on the nodes in the cluster of nodes. Following that, state information may be received, and a determination may be made as to if tasks should be rescheduled.

Abstract: A system and method schedules jobs in a cluster of compute nodes. A job with an unknown resource requirement profile is received. The job includes a plurality of tasks. Execution of some of the plurality of tasks is scheduled on compute nodes of the cluster with differing capability profiles. Timing information regarding execution time of the scheduled tasks is received. A resource requirement profile for the job is inferred based on the received timing information and the differing capability profiles. Execution of remaining tasks of the job is scheduled on the compute nodes of the cluster using the resource requirement profile.

Abstract: One embodiment of the present invention provides a system for providing assistance to a user of a product in diagnosing faults in the product. During operation, the system receives, at a help server, data associated with current and/or past operation of the product; performs an optimization to determine a sequence of diagnostic actions that is expected to maximize a net benefit to the user. The sequence of diagnostic actions includes one or more actions that require the user to perform at least one task, and performing the optimization involves accounting for costs to the user for performing the at least one task and savings to the user for correcting the faults. The system then interacts with the user, which involves presenting the sequence of diagnostic actions to the user.

Abstract: The following relates generally to computer system efficiency improvements. Broadly, systems and methods are disclosed that improve efficiency in a cluster of nodes by efficient processing of tasks among nodes in the cluster of nodes. Assignment of tasks to compute nodes may be based on learned CPU capabilities and I/O bandwidth capabilities of the compute nodes in the cluster.

Abstract: The following relates generally to computer system efficiency improvements. Broadly, systems and methods are disclosed that improve efficiency in a cluster of nodes by efficient processing of tasks among nodes in a cluster of nodes. Initially, tasks may be scheduled on the nodes in the cluster of nodes. Following that, state information may be received, and a determination may be made as to if tasks should be rescheduled.

Abstract: The following relates generally to computer system efficiency improvements. Broadly, systems and methods are disclosed that improve efficiency in a cluster of nodes by efficient processing of tasks among nodes in the cluster of nodes. Assignment of tasks to compute nodes may be based on learned CPU capabilities and I/O bandwidth capabilities of the compute nodes in the cluster.

Abstract: This NGDE algorithm incorporates a minimum cardinality candidate diagnosis generator which exploits conflict set reduction rules to dramatically reduce the search space and thus reduce the computational resources required to find minimum cardinality diagnoses.

Abstract: The following relates generally to computer system efficiency improvements. Broadly, systems and methods are disclosed that improve efficiency in a cluster of nodes by efficient processing of tasks among nodes in the cluster of nodes. Assignment of tasks to compute nodes may be based on learned CPU capabilities and I/O bandwidth capabilities of the compute nodes in the cluster.

Abstract: A model-based control system for controlling a production system is disclosed. The production system provides jobs and objectives to the model-based control system. The model-based control system includes, a planner operative to provide the production system with a plan, the planner generating the plan using a depth-first target value search. The depth-first target value search being configured to generate the plan with a failure probability most closely approximating a target value. Also provided is a system model operative to model the behavior of the production system. Another aspect of the model-based control system is a diagnosis engine operative to estimate failure probabilities for plans and provide diagnostic guidance to the planner. The model-based control system including the planner, the system model and diagnosis engine are implemented via a digital processing device.

Abstract: One embodiment of the present invention provides a system for providing assistance to a user of a product in diagnosing faults in the product. During operation, the system receives, at a help server, data associated with current and/or past operation of the product; performs an optimization to determine a sequence of diagnostic actions that is expected to maximize a net benefit to the user. The sequence of diagnostic actions includes one or more actions that require the user to perform at least one task, and performing the optimization involves accounting for costs to the user for performing the at least one task and savings to the user for correcting the faults. The system then interacts with the user, which involves presenting the sequence of diagnostic actions to the user.

Abstract: A system and method for determining vehicle component conditions are provided. A function that maps features to door conditions is stored. Motor current measurements are obtained for a door over a predetermined time period. The features of the motor current measurements are determined based on the stored function. The features are then analyzed by mapping the features to one or more door conditions via a predetermined function. At least one condition of the door is determined based on the analyzed features.

Abstract: A self-aware machine platform is implemented through analyzing operational data of machining tools to achieve machine tool damage assessment, prediction and planning in manufacturing shop floor. Machining processes are first identified by matching similar processes through an ICP algorithm. Machining processes are further clustered by Hotelling's T-squared statistics. Degradation of the machining tool is detected through a trend of the operational data within a cluster of machining processes by a monotonicity test, and the remaining useful life of the machining tool is predicted through a particle filter by extrapolating the trend under a first-order Markov process. In addition, process anomalies across machines are detected through a combination of outlier detection methods including SOMs, multivariate regression, and robust Mahalanobis distance. Warnings and recommendations are flexibly provided to manufacturing shop floor based on policy choice.

Abstract: A method is provided for automatically generating an augmented model of a cyber-physical component. Cyber-physical components are built from or depend upon the synergy computational and physical components. The method includes: reading an input model (22) into a processor (10), the input model describing a nominal mode of operation for a physical component modeled by the input model; parsing with the processor the input model to generate a parse thereof; analyzing with the processor the parse of the input model; and automatically writing with the processor an augmented model (42) for the physical component from the input model based on the analysis, the augmented model describing the nominal mode of operation for the modeled physical component and at least one alternate mode of operation for the modeled physical component which is different from the nominal mode of operation.

Abstract: A system and method schedules jobs in a cluster of compute nodes. A job with an unknown resource requirement profile is received. The job includes a plurality of tasks. Execution of some of the plurality of tasks is scheduled on compute nodes of the cluster with differing capability profiles. Timing information regarding execution time of the scheduled tasks is received. A resource requirement profile for the job is inferred based on the received timing information and the differing capability profiles. Execution of remaining tasks of the job is scheduled on the compute nodes of the cluster using the resource requirement profile.

Abstract: A computer based method and system for tiered inference multiple fault diagnosis is provided. The method includes using a computer processor to dissect a hypothesis space representing a production system having a plurality of production modules into tiers. Production modules in the current tier are partitioned into a group or a set of sub-groups. A fault diagnosis algorithm is applied to the group of each sub-group to identify an acceptable fault diagnosis. When no acceptable fault diagnosis is found, the process moves to the next tier to perform further investigations. The process continues to move to higher tiers until an acceptable fault diagnosis is obtained or the system instructs the process to end.

Abstract: A system and method provides decision support for planning in an environment where a competition for use of resources exist and events affecting the planning are occurring dynamically. A system model of an actual system is provided. Then in a dynamic factored manner, an envisionment related to at least some aspects of the system model is built. From this envisionment output is generated related to at least some aspects of the system model. Finally, changes are made to the actual system, based on the generated output thereby changing a configuration and/or operation of the actual system.

Abstract: The disclosure describes a method and apparatus for maintaining groupings and relationships of propositions associated with a knowledge base. In one embodiment, the method includes providing multiple microtheories to form a knowledge base. Each microtheory includes multiple propositions. An mt label is provided for each microtheory. A proposition label is provided for each proposition. The proposition label for a specific proposition is compared with the microtheory labels in response to a transaction request. Microtheory labels that have a common element with the proposition label are determined. In another embodiment, the method includes providing multiple microtheories, providing an mt label for each microtheory, and initializing tags for first and second microtheories to a clean value. In one embodiment, the apparatus may include one or more storage devices and a tag processing logic.

Abstract: Methods and systems for solving a target value search problem using a multi-interval heuristic are presented. The methods and system identity a path, or paths, in a graph, whereby a connection graph is created and range sets are generated for each vertex in the connection graph. Range sets include one or more intervals. Thereafter, a best search is performed to identify a path, or paths, from a starting vertex to a goal vertex having a path value closest to a target value.

Abstract: A method for determining a target path for a model-based control system. The model-based control system includes a directed acyclic graph, where the directed acyclic graph includes a plurality of vertices interconnected by a plurality of edges. The method includes the steps of performing a depth-first search of the directed acyclic graph for the target path. The depth-first search is operative to return an explicit solution or an implicit solution, wherein the implicit solution is determined using a heuristic. The method further includes determining if the depth-first search returned an explicit solution or an implicit solution, and if the depth-first search returned an implicit solution, constructing the target path from the implicit solution. The method may further include constructing a pattern database.

Abstract: Diagnostic systems and methods are presented for determining the current condition of a production plant and the resources thereof, in which successively more complex diagnostic abstractions are used to determine the plant condition, with a more complex abstraction being selected when the most recently selected diagnostic abstraction is logically inconsistent with the current fault status indications.