A method and system are provided for identifying a matching signal from a signal bank, that includes a plurality of signals, to a first signal, the method includes steps of; receiving, by a processor, the first signal; performing, by the processor, a spectral analysis of the first signal and the plurality of signals, the spectral analysis further includes; computing a chromatogram comprising a plurality of frames; splitting each of the plurality of frames into a plurality of pitch classes; analyzing each of the plurality of pitch classes; determining dominant pitch class from the plurality of pitch classes, wherein the dominant pitch class has highest frequency magnitude; and matching, by the processor, dominant pitch class of the first signal with dominant pitch class of at least one of the plurality of signals.

A power generator system with anomaly detection and methods for detecting anomalies include a power generator that includes one or more physical components configured to provide electrical power. Sensors are configured to make measurements of a state of respective physical components, outputting respective time series of said measurements. A monitoring system includes a fitting module configured to determine a predictive model for each pair of a set of time series, an anomaly detection module configured to compare new values of each pair of time series to values predicted by the respective predictive model to determine if the respective predictive model is broken and to determine a number of broken predictive model, and an alert module configured to generate an anomaly alert if the number of broken predictive models exceeds a threshold.

The present disclosure provides a system comprising a communication interface and computer for assigning a label to the biomolecule fingerprint, wherein the label corresponds to a biological state. The present disclosure also provides a sensor arrays for detecting biomolecules and methods of use. In some embodiments, the sensor arrays are capable of determining a disease state in a subject.

A confidence interval determination system includes a processor and memory. The memory stores a historical data store and instructions. The instructions include, in response to receiving a prediction request, determining a size of each element of the prediction request and obtaining a previous prediction request. The instructions include, in response to the prediction request being different from the previous prediction request, for each element of the prediction request, generating a classifier based on the training data and, for each bin of a set of bins of the element, determining a set of predicted likelihoods using the classifier. The instructions include generating a mean vector prediction and a covariance matrix using the sets of bins generated, determining a predicted outcome and a confidence interval using the mean vector prediction and the covariance matrix, and, in response to the confidence interval exceeding a threshold, outputting the predicted outcome and the confidence interval.

System monitors and methods of monitoring a system are disclosed. In one arrangement a system monitor predicts a future state of a system. A data receiving unit receives system data representing a set of one or more measurements performed on the system. A first statistical model is fitted to the system data. The first statistical model is compared to each of a plurality of dictionary entries in a database. Each dictionary entry comprises a second statistical model. The second statistical model is of the same general class as the first statistical model and obtained by fitting the second statistical model to data representing a set of one or more previous measurements performed on a system of the same type as the system being monitored and having a known subsequent state. A prediction of a future state of the system being monitored is output based on the comparison. The first statistical model and the second statistical model are each a stochastic process or approximation to a stochastic process.

Generally discussed herein are devices, systems, and methods for generating a phrase that is confusing to a language classifier. A method can include determining, by the LC, a first classification score (CS) of a prompt indicating whether the prompt is a first class or a second class, predicting, based on the prompt and by a pre-trained language model (PLM), likely next words and a corresponding probability for each of the likely next words, determining, by the LC, a second CS for each of the likely next words, determining, by an adversarial classifier, respective scores for each of the likely next words, the respective scores determined based on the first CS of the prompt, the second CS of the likely next words, and the probabilities of the likely next words, and selecting, by an adversarial classifier, a next word of the likely next words based on the respective scores.

There is provided a method of determining the orientation of an accelerometer that is being carried or worn by a user, the method comprising measuring acceleration using the accelerometer as the user moves; processing the measured acceleration to determine a step frequency of the movements by the user; and processing the measured acceleration to identify a lateral component of acceleration as a component of acceleration having a high response at a frequency corresponding to half the step frequency.

The present disclosure provides a system comprising a communication interface and computer for assigning a label to the biomolecule fingerprint, wherein the label corresponds to a biological state. The present disclosure also provides a sensor arrays for detecting biomolecules and methods of use. In some embodiments, the sensor arrays are capable of determining a disease state in a subject.

The present disclosure provides a system comprising a communication interface and computer for assigning a label to the biomolecule fingerprint, wherein the label corresponds to a biological state. The present disclosure also provides a sensor arrays for detecting biomolecules and methods of use. In some embodiments, the sensor arrays are capable of determining a disease state in a subject.

Generally discussed herein are devices, systems, and methods for generating a phrase that is confusing to a language classifier. A method can include determining, by the LC, a first classification score (CS) of a prompt indicating whether the prompt is a first class or a second class, predicting, based on the prompt and by a pre-trained language model (PLM), likely next words and a corresponding probability for each of the likely next words, determining, by the LC, a second CS for each of the likely next words, determining, by an adversarial classifier, respective scores for each of the likely next words, the respective scores determined based on the first CS of the prompt, the second CS of the likely next words, and the probabilities of the likely next words, and selecting, by an adversarial classifier, a next word of the likely next words based on the respective scores.