Abstract: The present invention relates to methods, devices and systems for associating consumable data with an assay consumable used in a biological assay. Provided are assay systems and associated consumables, wherein the assay system adjusts one or more steps of an assay protocol based on consumable data specific for that consumable. Various types of consumable data are described, as well as methods of using such data in the conduct of an assay by an assay system. The present invention also relates to consumables (e.g., kits and reagent containers), software, data deployable bundles, computer-readable media, loading carts, instruments, systems, and methods, for performing automated biological assays.

Abstract: A method detects anomalies in time series data, wherein the time series data is multivariate, by partitioning time series training data into partitions. A representation for each partition in each time window is determined to form a model of the time series training data, wherein the model includes representations of distributions of the time series training data. The representations obtained from partitions of time series test data are compared to the model to obtain anomaly scores.

Abstract: A method detects anomalies in time series data, wherein the time series data is multivariate, by partitioning time series training data into partitions. A representation for each partition in each time window is determined to form a model of the time series training data, wherein the model includes representations of distributions of the time series training data. The representations obtained from partitions of time series test data are compared to the model to obtain anomaly scores.

Abstract: A method identifies an unknown face in an input image using reference images of known faces. A Haar-like feature vector is extracted from each image. The vectors are compressed. An L1 norm is determined between the compressed feature vector of the input image and each compressed feature vector from the set of reference images to determine a most similar reference image. The identity of the face associated with the most similar reference image is assigned as the identity of the unknown face in the input image.

Abstract: A method identifies an unknown face in an input image using reference images of known faces. A Haar-like feature vector is extracted from each image. The vectors are compressed. An L1 norm is determined between the compressed feature vector of the input image and each compressed feature vector from the set of reference images to determine a most similar reference image. The identity of the face associated with the most similar reference image is assigned as the identity of the unknown face in the input image.

Abstract: A method for determining attributes of a face in an image compares each patch in the set of patches of the image of the face with a set of prototypical patches. The result of comparison is a set of matching prototypical patches. The attributes of the image of the face are determined based on the attributes of the set of matching prototypical patches.