Abstract: A method for motion correction in a magnetic resonance imaging system includes receiving data collected from imaging an object by the magnetic resonance imaging system, or image data reconstructed from the collected data. The method further includes generating motion-related information with respect to a motion of the object while the collected data is being collected. The motion-related information includes a certainty level of the collected data being corrupted by the motion of the object. The method also includes generating, based on the generated motion-related information and the received data or reconstructed image data, motion-corrected image data.

Abstract: Phantoms for use in magnetic resonance imaging (“MRI”) and, in particular, for use in quantifying fat concentration, iron concentration, or both, are provided. The phantoms are constructed to accurately reflect in vivo magnetic resonance signal behavior in the presence of both fat and iron. The phantoms described here can thus be used for phantom-based validation of MRI techniques for the joint quantification of fat and iron concentration, for phantom-based validation of MRI techniques for quantifying fat concentration in the presence of iron overload, and for phantom-based validation of MRI techniques for quantifying iron concentration given the confounding presence of fat.

Abstract: Phantoms for use in magnetic resonance imaging (“MRI”) and, in particular, for use in quantifying fat concentration, iron concentration, or both, are provided. The phantoms are constructed to accurately reflect in vivo magnetic resonance signal behavior in the presence of both fat and iron. The phantoms described here can thus be used for phantom-based validation of MRI techniques for the joint quantification of fat and iron concentration, for phantom-based validation of MRI techniques for quantifying fat concentration in the presence of iron overload, and for phantom-based validation of MRI techniques for quantifying iron concentration given the confounding presence of fat.

Abstract: Equipment failures are diagnosed using an integrated approach of case-based reasoning (CBR) and statistical reliability analysis. The method outputs a single list of suggested failed components, ranked by an overall probability of failure, and their associated past solutions from the case base. The overall probability of failure is calculated using the combined logic of case based reasoning and statistical reliability analysis. The method is typically used in a real-time decision support system to aid equipment diagnosis by a maintenance technician working in the field.

Abstract: A stochastic integer programming based constrained optimization technique enables optimal allocation of classrooms and instructors to requested classes associated with cancellation probabilities. An analytical tool allows optimization of overall operational revenue/profit under different planning scenarios involving chaining of various classes, prerequisite relationships, and inter-class spacing requirements. This system allows the description and input of a list of classes, their cancellation probabilities and the input of available classrooms and instructors for determining the most revenue-generating/profitable class schedule. The revenue/profit optimization model corresponds to a two-stage mixed integer program.

Abstract: Equipment failures are diagnosed using an integrated approach of case-based reasoning (CBR) and statistical reliability analysis. The method outputs a single list of suggested failed components, ranked by an overall probability of failure, and their associated past solutions from the case base. The overall probability of failure is calculated using the combined logic of case based reasoning and statistical reliability analysis. The method is typically used in a real-time decision support system to aid equipment diagnosis by a maintenance technician working in the field.

Abstract: Equipment failures are diagnosed using an integrated approach of case-based reasoning (CBR) and statistical reliability analysis. The method outputs a single list of suggested failed components, ranked by an overall probability of failure, and their associated past solutions from the case base. The overall probability of failure is calculated using the combined logic of case based reasoning and statistical reliability analysis. The method is typically used in a real-time decision support system to aid equipment diagnosis by a maintenance technician working in the field.

Abstract: A stochastic integer programming based constrained optimization technique enables optimal allocation of classrooms and instructors to requested classes associated with cancellation probabilities. An analytical tool allows optimization of overall operational revenue/profit under different planning scenarios involving chaining of various classes, prerequisite relationships, and inter-class spacing requirements. This system allows the description and input of a list of classes, their cancellation probabilities and the input of available classrooms and instructors for determining the most revenue-generating/profitable class schedule. The revenue/profit optimization model corresponds to a two-stage mixed integer program.

Abstract: Equipment failures are diagnosed using an integrated approach of case-based reasoning (CBR) and statistical reliability analysis. The method outputs a single list of suggested failed components, ranked by an overall probability of failure, and their associated past solutions from the case base. The overall probability of failure is calculated using the combined logic of case based reasoning and statistical reliability analysis. The method is typically used in a real-time decision support system to aid equipment diagnosis by a maintenance technician working in the field.