Abstract: A computerized system for measuring and/or detecting responses or conditions in human beings based on data from wearable sensors worn in a natural free-living context. Based upon the measurements and/or detection, various actions can be taken.

Abstract: A method for systematically configuring and deploying an empirical model used for fault detection and equipment health monitoring. The method is driven by a set of data preprocessing and model performance metrics subsystems that when applied to a raw data set, produce an optimal empirical model.

Abstract: A system for empirically diagnosing a condition of a monitored system. Estimates of monitored parameters from a model of the system provide residual values that can be analyzed for failure mode signature recognition. Residual values can also be tested for alert (non-zero) conditions, and patterns of alerts thus generated are analyzed for failure mode signature patterns. The system employs a similarity operator for signature recognition and also for parameter estimation. Failure modes are empirically determined, and precursor data is automatically analyzed to determine differentiable signatures for failure modes.

Abstract: A system, method and program product for monitoring a complex signal for ultrasensitive detection of state changes, or for signature recognition and classification is provided. A complex signal is decomposed periodically for empirical modeling. Wavelet analysis, frequency band filtering or other methods may be used to decompose the complex signal into components. A library of signature data may be referenced for selection of a recognized signature in the decomposed complex signal. The recognized signature may indicate data being carried in the complex signal. Estimated signal data may be generated for determination of an operational state of a monitored process or machine using a statistical hypothesis test with reference to the decomposed input signal.

Abstract: Reference data observations for given system are used to develop a reference set of such observations. Subsequent observations (comprising, in one embodiment, current observations) are then used to facilitate selection of portions of this reference set to yield a resultant set of observations that serves as a model. This model can then be used in comparison to actual system performance to detect, for example, a trend towards a faulty condition. Pursuant to a preferred approach, the model is recomputed from time to time and, pursuant to a particular embodiment, is recomputed with each new set of current observations.

Abstract: A system for monitoring in real-time the health of equipment or the performance of a process utilizing a universal modeling technique that generates estimates of parameters for gauging early indications of anomalies. A kernel regression model such as the Nadaraya-Watson may be used, and may be in autoassociative form. Kernel optimization is automatically provided. A support vector regression can be substituted for the kernel regression.

Abstract: A method and system for monitoring at least one of a system, a process and a data source. A method and system have been developed for carrying out surveillance, testing and modification of an ongoing process or other source of data, such as a spectroscopic examination. A signal from the system under surveillance is collected and compared with a reference signal, a frequency domain transformation carried out for the system signal and reference signal, a frequency domain difference function established. The process is then repeated until a full range of data is accumulated over the time domain and a Sequential Probability Ratio Test methodology applied to determine a three-dimensional surface plot characteristic of the operating state of the system under surveillance.

Abstract: A method and system for monitoring at least one of a system, a process and a data source. A method and system have been developed for carrying out surveillance, testing and modification of an ongoing process or other source of data, such as a spectroscopic examination. A signal from the system under surveillance is collected and compared with a reference signal, a frequency domain transformation carried out for the system signal and reference signal, a frequency domain difference function established. The process is then repeated until a full range of data is accumulated over the time domain and a SPRT methodology applied to determine a three-dimensional surface plot characteristic of the operating state of the system under surveillance.

Abstract: A method and system for providing nuclear fuel rods with a configuration of isotopic gas tags. The method includes selecting a true location of a first gas tag node, selecting initial locations for the remaining n-1 nodes using target gas tag compositions, generating a set of random gene pools with L nodes, applying a Hopfield network for computing on energy, or cost, for each of the L gene pools and using selected constraints to establish minimum energy states to identify optimal gas tag nodes with each energy compared to a convergence threshold and then upon identifying the gas tag node continuing this procedure until establishing the next gas tag node until all remaining n nodes have been established.