Abstract: A system includes at least one article of personal protective equipment, one or more industrial devices, an industrial controller device configured to output industrial controller data indicative of one or more attributes of the one or more industrial devices, and a computing device. The computing devices is configured to determine a set of one or more safety rules corresponding to a work environment at the first time and determine a change in an attribute of the one or more attributes of the one or more industrial devices. The computing device is further configured to identify an updated set of one or more worker safety rules corresponding to the work environment at the second time and determine whether the status of at least one article of personal protective equipment satisfies the updated set of one or more worker safety rules.

Abstract: A modular display unit, comprising a housing having a front wall, a rear wall, a roof and a floor. The roof slopes downwardly from said rear wall towards said front wall when the display unit is mounted to a vertical wall. A plurality of containers is disposed in a row between the front and rear walls. Each of the containers has a bottom support portion and an open top portion. The open top portion is configured for coupling with a tubular extension for increasing the length of each of the containers. A plurality of pegboard hangers is provided on the rear wall.

Abstract: A computer program product for detecting anomalies from multidimensional data comprises: a) receiving multidimensional data; b) estimating background parameters of a normal compositional model from the multidimensional data; c) estimating abundance values of the normal compositional model from the background parameters and the multidimensional data; d) determining an anomaly detection statistic from the multidimensional data, the background parameters, and abundance values; and e) classifying an observation from the multidimensional data as either a background reference or an anomaly from the anomaly detection statistic.

Abstract: A method for detecting targets comprises: a) receiving spectral data; b) using a normal compositional model for estimating background parameters from the spectral data and target components; c) estimating abundance values of classes of the normal compositional model from the background parameters and the spectral data; d) estimating target class covariance values from the spectral data, the background parameters, and the target components; e) estimating target-plus-background abundance values from the target class covariance values, the background parameters, the spectral data, and the target components; f) employing a normal compositional model for determining a likelihood ratio detection statistic from the target class covariance values, target-plus-background abundance values, spectral data, target components, background parameters, and background abundance values; and g) generating a determination output signal that represents whether an observation includes a target from the likelihood ratio detection st