The disclosed embodiments provide a system that detects sensor anomalies in a univariate time-series signal. During a surveillance mode, the system receives the univariate time-series signal from a sensor in a monitored system. Next, the system performs a staggered-sampling operation on the univariate time-series signal to produce N sub-sampled time-series signals, wherein the staggered-sampling operation allocates consecutive samples from the univariate time-series signal to the N sub-sampled time-series signals in a round-robin ordering. The system then uses a trained inferential model to generate estimated values for the N sub-sampled time-series signals based on cross-correlations with other sub-sampled time-series signals. Next, the system performs an anomaly detection operation to detect incipient sensor anomalies in the univariate time-series signal based on differences between actual values and the estimated values for the N sub-sampled time-series signals. Whenever an incipient sensor anomaly is detected, the system generates a notification.

A method for determining the quality of running of a test subject includes: measuring at least two orthogonal acceleration values a.sub.c and a.sub.c of the test subject each at a plurality of times t.sub.i, wherein a.sub.c and a.sub.c are each one differently selected from the group of: acceleration a.sub.z of the test subject in the down-up direction, acceleration a.sub.y of the test subject in the right-left direction, and the acceleration a.sub.x of the test subject in the backward-forward direction; wherein the down-up direction, the left-right direction and the backward-forward direction form a Cartesian coordinate system for the test subject; determining the area A.sub.i defined by the origin (0,0) and the points (a.sub.c(t.sub.i),a.sub.c(t.sub.i)) and (a.sub.c(t.sub.i1), a.sub.c(t.sub.i1)); and calculating the accumulated area A (t.sub.N)=.sub.i=1.sup.N A.sub.i by adding the areas A.sub.i until a point in time t.sub.N.

A user-wearable device includes a housing and a band that straps the housing to a portion of a user's body (e.g., wrist). One or more skin contact sensors in and/or on the housing can sense biometric information of a user wearing the device. An authentication module performs or receives results of an authentication determination that compares the sensed biometric information to baseline biometric information to determine whether they match. An on-body detector uses one or more of the sensors to determine whether the device is being worn by a user. After a user is authenticated based on a match between the sensed and baseline biometric information, the authentication module continually concludes that the user is authenticated for at least a period of time, without an additional comparison between sensed and baseline biometric information, if the on-body detector detects that the user-wearable device is still being worn by the user.

The present invention discloses a method for authentication of animal species origin of leather products, which includes the following steps: Step 1: Model establishment: (1) Collect leather samples from different animal species origins, set mass spectrometric parameters, cut the surface of leather samples using a preheated electric soldering iron, and detect the resulting sample ions using the mass spectrometer; (2) Create a multivariate statistical model based on principal component analysis and linear discriminant analysis of rapid evaporative ionization mass spectrometric data and evaluate the model with cross-validation tests; Step 2: Analysis of real leather samples: detect and authenticate the identity of real leather samples based on the multivariate statistical model. The authentication method disclosed in present invention is a rapid analytical method that requires no sample pretreatment and can identify the animal species origin of leather products rapidly and accurately.

According to one embodiment, a data processing device includes an acquisition part, and a processor. The acquisition part is configured to acquire first data including time-series image data. The processor is configured to derive first feature information based on a multidimensional array of n dimensions based on the first data acquired by the acquisition part. n is an integer not less than 3. A first axis of the multidimensional array is related to time.

Disclosed herein are methods and systems for detection and discrimination of optical signals from a densely packed substrate. These have broad applications for biomolecule detection near or below the diffraction limit of optical systems, including in improving the efficiency and accuracy of polynucleotide sequencing applications.