Abstract: A computer-implemented method for detecting anomalous behavior of one or more computers in a large group of computers comprises (1) receiving log files including a plurality of entries of data regarding connections between a plurality of computers belonging to an organization and a plurality of websites outside the organization, each entry being associated with the actions of one computer, (2) applying a first plurality of algorithms to determine features of the data which may contribute to anomalous behavior of the computers, and (3) applying a second plurality of algorithms to determine which computers are behaving anomalously based upon the features.

Abstract: A system and method for monitoring a vehicle are presented. The system includes a first imaging subsystem for acquiring a plurality of load-carrying-portion images. A cargo-detection subsystem is configured for analyzing each of the plurality of load-carrying-portion images to determine whether cargo is positioned on the load-carrying portion of the vehicle. A power-detection subsystem is configured for determining when the vehicle is running. A motion-detection subsystem is configured for determining when the vehicle is in motion. An analytics subsystem is configured for calculating at least one of (i) the amount of time that the vehicle is running, (ii) the amount of time that the vehicle is running while cargo is positioned on the load-carrying portion, (iii) the amount of time the vehicle is in motion, and (iv) the amount of time the vehicle is in motion while cargo is positioned on the load-carrying portion.

Abstract: A system and method for monitoring an industrial vehicle are presented. The system includes a first imaging subsystem for acquiring a plurality of load-carrying-portion images. A cargo-detection subsystem is configured for analyzing each of the plurality of load-carrying-portion images to determine whether cargo is positioned on the load-carrying portion. A power-detection subsystem is configured for determining when the industrial vehicle is running. A motion-detection subsystem is configured for determining when the industrial vehicle is in motion. An analytics subsystem is configured for calculating the amount of time that the industrial vehicle is running, the amount of time that the industrial vehicle is running while cargo is positioned on the load-carrying portion, the amount of time the industrial vehicle is in motion, and the amount of time the industrial vehicle is in motion while cargo is positioned on the load-carrying portion.

Abstract: A computer-implemented method for determining features of a dataset that are indicative of anomalous behavior of one or more computers in a large group of computers comprises (1) receiving log files including a plurality of entries of data regarding connections between a plurality of computers belonging to an organization and a plurality of websites outside the organization, each entry being associated with the actions of one computer, (2) executing a time series decomposition algorithm on a portion of the features of the data to generate a first list of features, (3) implementing a plurality of traffic dispersion graphs to generate a second list of features, and (4) implementing an autoencoder and a random forest regressor to generate a third list of features.

Abstract: A method and apparatus for identifying a cause for a fuel inefficiency of a vehicle are disclosed. For example, the method categorizes a plurality of vehicles into a plurality of peer groups, determines for each peer group a baseline of a vehicle operation efficiency, determines for each peer group a baseline of driving behavior, identifies at least one vehicle with a vehicle operation efficiency in one peer group of the plurality of peer groups that is an outlier as compared to the baseline of the vehicle operation efficiency associated with the one peer group, determines whether a driving behavior of a driver driving the at least one vehicle is an outlier as compared to the baseline of the driving behavior associated with the one peer group, and identifies a cause for the vehicle operation efficiency being an outlier.

Abstract: A reconfigurable sled for a mobile device with camera is provided. The reconfigurable sled may be moved into different configurations in order to facilitate either normal or specialized use. For example, in a first configuration, the mobile device's camera is unobstructed and imaging may proceed normally. In a second configuration, on the other hand, the camera's imaging direction may be repositioned by a reflective element in the camera's optical path. The reflective element provides feedback to the mobile device via visible markings that may be imaged by the camera and detected by the mobile device. If the mobile device determines that the mirror is in the optical path, then the mobile device may respond to accommodate the mirror and enable a function, like reading an indicium.

Abstract: An encoded information reading terminal can comprise a microprocessor, a memory communicatively coupled to the microprocessor, a communication interface, and an RFID reading device configured to output raw message data comprising an encoded message and/or output decoded message data corresponding to an encoded message. The EIR terminal can be configured, responsive to receiving one or more target item identifiers, to attempt to locate at least one RFID tag transmitting an encoded representation of a binary string, at least part of which is equal to at least part one of the specified one or more target item identifiers. The EIR terminal can be further configured, responsive to successfully locating at least one RFID tag, to notify a user via a visual message and/or an audible message.