Abstract: A control system for an industrial vehicle includes a badge communicator and an information linking device. The badge communicator has a transceiver for short range communication with electronic badges that are within in a fixed short range of the badge communicator, defining a first zone. The information linking device is programmed to execute program code. The program code extracts a current state of an operating parameter read from an industrial vehicle network bus, generates a second zone within the first zone that is defined based upon the extracted industrial vehicle operating parameter, detects a presence of an electronic badge within the first zone, determines whether the electronic badge is within the second zone, performs a first action if the detected electronic badge is not within the second zone, and performs a second action if the electronic badge is within the second zone.

Abstract: A system for adjusting control of an industrial vehicle comprises a badge communicator that communicates with electronic badges that are in short range proximity of the industrial vehicle; and a controller coupled to memory, wherein the controller executes program code stored in the memory to adjust control of operating parameters of the industrial vehicle. The controller executes the program code to receive a badge identifier wirelessly transmitted by a detected electronic badge and identify a role associated with the badge identifier. Based on the role associated with the badge identifier, the controller modifies a set point of the industrial vehicle from a first set point to a second set point by communicating information concerning the set point to a vehicle control module of the electronic vehicle.

Abstract: Operating a materials handling vehicle includes monitoring, by a controller, a first vehicle drive parameter during a first manual operation of the vehicle by an operator; monitoring, by the controller, the first vehicle drive parameter during a second manual operation of the vehicle by the operator; receiving, by the controller after the first manual operation of the vehicle and the second manual operation of the vehicle, a request to implement a semi-automated driving operation; calculating, by the controller, a first weighted average based on the monitored first vehicle drive parameter during the first manual operation of the vehicle and the monitored first vehicle parameter during the second manual operation of the vehicle; and based at least in part on the calculated first weighted average, controlling, by the controller, implementation of the semi-automated driving operation.

Abstract: A method for operating a materials handling vehicle is provided and comprises: monitoring, by a controller, a first vehicle drive parameter during a manual operation of the vehicle by an operator; storing, by the controller, data related to the monitored first vehicle drive parameter. The controller is configured to use the stored data for implementing a semi-automated driving operation of the vehicle subsequent to the manual operation of the vehicle. The method further comprises: detecting, by the controller, operation of the vehicle indicative of a start of a pick operation occurring during the manual operation of the vehicle; and based on detecting the start of the pick operation, resetting, by the controller, the stored data related to the monitored first vehicle drive parameter.

Abstract: A method for processing a transparent workpiece includes directing a pulsed laser beam into the transparent workpiece such that a portion of the pulsed laser beam directed into the transparent workpiece generates an induced absorption within the transparent workpiece, thereby forming a damage line within the transparent workpiece, and the portion of the pulsed laser beam directed into the transparent workpiece includes a wavelength ?, a spot size wo, and a Rayleigh range ZR that is greater than F D ? ? ? w 0 , 2 ? , where FD is a dimensionless divergence factor comprising a value of 10 or greater. Further, the method for processing the transparent workpiece includes etching the transparent workpiece with an etching vapor to remove at least a portion of the transparent workpiece along the damage line, thereby forming an aperture extending through the at least a portion of the thickness of the transparent workpiece.

Abstract: A system, method and computer product for training a neural network system. The method comprises inputting an audio signal to the system to generate plural outputs f(X, ?). The audio signal includes one or more of vocal content and/or musical instrument content, and each output f(X, ?) corresponds to a respective one of the different content types. The method also comprises comparing individual outputs f(X, ?) of the neural network system to corresponding target signals. For each compared output f(X, ?), at least one parameter of the system is adjusted to reduce a result of the comparing performed for the output f(X, ?), to train the system to estimate the different content types. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate various different types of vocal and/or instrument components of an audio signal, depending on which type of component(s) the system is trained to estimate.

Abstract: A method is provided for controlling a light source device associated with a materials handling vehicle, wherein the materials handling vehicle includes one or more sensing devices, comprising: sensing via the one or more sensing devices a first distance from a left side of the vehicle to a first boundary object and a second distance from a right side of the vehicle to a second boundary object; controlling the light source device to designate a first area to the left side of the vehicle as either a limited operation area or a non-limited operation area and to designate a second area to the right side of the vehicle as either a limited operation area or a non-limited operation area.

Abstract: A materials handling vehicle includes a power unit, a load handling assembly and a positioning assistance system that provides assistance to an operator that is driving the vehicle. The assistance provided by the positioning assistance system includes at least one of an audible, tactile, or visual cue to indicate at least one of: a distance from the vehicle to a boundary object; or a heading of the vehicle with respect to the boundary object.

Abstract: A materials handling vehicle includes: a power unit including: a steered wheel, and a steering device for generating a steer control signal; a load handling assembly coupled to the power unit; a controller located on the power unit for receiving the steer control signal; and a sensing device on the power unit and coupled to the controller. The sensing device monitoring areas in front of and next to the vehicle. Based on sensing device data, the controller may modify at least one of the following vehicle parameters: a maximum allowable turning angle or a steered-wheel-to-steering-device ratio.

Abstract: A system, method and computer product for training a neural network system. The method comprises applying an audio signal to the neural network system, the audio signal including a vocal component and a non-vocal component. The method also comprises comparing an output of the neural network system to a target signal, and adjusting at least one parameter of the neural network system to reduce a result of the comparing, for training the neural network system to estimate one of the vocal component and the non-vocal component. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate vocal or instrumental components of an audio signal, depending on which type of component the system is trained to estimate.

Abstract: A system, method and computer product for training a neural network system. The method comprises applying an audio signal to the neural network system, the audio signal including a vocal component and a non-vocal component. The method also comprises comparing an output of the neural network system to a target signal, and adjusting at least one parameter of the neural network system to reduce a result of the comparing, for training the neural network system to estimate one of the vocal component and the non-vocal component. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate vocal or instrumental components of an audio signal, depending on which type of component the system is trained to estimate.

Abstract: A process for automating control of an industrial vehicle based on location comprises scanning an environment in a travel direction of the industrial vehicle, by using an optical scanner affixed to the industrial vehicle. A marker defined by a series of tags is identified by recursively receiving a reflection of the optical scanner; determining if the reflection is indicative of an optical tag; and concatenating the indication of an optical tag to the marker. Once the marker is identified, the marker is transformed into an environmental condition and a status of the vehicle is determined, where the status correlates to the environmental condition. Further, an automated control is applied on the industrial vehicle based on the environmental condition and the status of the industrial vehicle.

Abstract: A method for processing a transparent workpiece includes directing a pulsed laser beam into the transparent workpiece such that a portion of the pulsed laser beam directed into the transparent workpiece generates an induced absorption within the transparent workpiece, thereby forming a damage line within the transparent workpiece, and the portion of the pulsed laser beam directed into the transparent workpiece includes a wavelength ?, a spot size w0, and a Rayleigh range ZR that is greater than F D ? ? ? w 0 2 ? , where FD is a dimensionless divergence factor comprising a value of 10 or greater. Further, the method for processing the transparent workpiece includes etching the transparent workpiece with an etching vapor to remove at least a portion of the transparent workpiece along the damage line, thereby forming an aperture extending through the at least a portion of the thickness of the transparent workpiece.

Abstract: Systems and methods for automated hospitality services in a lodging facility. A hospitality services processing system comprises a kiosk and a hospitality services management system. The hospitality management system interacts with an automated kiosk terminal in a hotel via a network to allow a user to complete a variety of hospitality services such as a check in or out process without the need for assistance by hotel staff. The kiosk captures biometric or identification credential information to confirm an existing reservation from a hotel reservation database. The system is configured to accept and process payment and provide hotel room key cards. A method of using the system and kiosk is also provided.

Abstract: A system, method and computer product for estimating a component of a provided audio signal. The method comprises converting the provided audio signal to an image, processing the image with a neural network trained to estimate one of vocal content and instrumental content, and storing a spectral mask output from the neural network as a result of the image being processed by the neural network. The neural network is a U-Net. The method also comprises providing the spectral mask to a client media playback device, which applies the spectral mask to a spectrogram of the provided audio signal, to provide a masked spectrogram. The media playback device also transforms the masked spectrogram to an audio signal, and plays back that audio signal via an output user interface.

Abstract: A system, method and computer product for training a neural network system. The method comprises inputting an audio signal to the system to generate plural outputs f(X, ?). The audio signal includes one or more of vocal content and/or musical instrument content, and each output f(X, ?) corresponds to a respective one of the different content types. The method also comprises comparing individual outputs f(X, ?) of the neural network system to corresponding target signals. For each compared output f(X, ?), at least one parameter of the system is adjusted to reduce a result of the comparing performed for the output f(X, ?), to train the system to estimate the different content types. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate various different types of vocal and/or instrument components of an audio signal, depending on which type of component(s) the system is trained to estimate.

Abstract: A method for operating a materials handling vehicle is provided comprising: monitoring, by a controller, a first vehicle drive parameter corresponding to a first direction of travel of the vehicle during a first manual operation of the vehicle by an operator and concurrently monitoring, by the controller, a second vehicle drive parameter corresponding to a second direction different from the first direction of travel during the first manual operation of the vehicle by an operator. The controller receives, after the first manual operation of the vehicle, a request to implement a first semi-automated driving operation. Based on the first and second monitored vehicle drive parameters during the first manual operation, the controller controls implementation of the first semi-automated driving operation.

Abstract: A system, method and computer product for training a neural network system. The method comprises applying an audio signal to the neural network system, the audio signal including a vocal component and a non-vocal component. The method also comprises comparing an output of the neural network system to a target signal, and adjusting at least one parameter of the neural network system to reduce a result of the comparing, for training the neural network system to estimate one of the vocal component and the non-vocal component. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate vocal or instrumental components of an audio signal, depending on which type of component the system is trained to estimate.

Abstract: A system, method and computer product for training a neural network system. The method comprises applying an audio signal to the neural network system, the audio signal including a vocal component and a non-vocal component. The method also comprises comparing an output of the neural network system to a target signal, and adjusting at least one parameter of the neural network system to reduce a result of the comparing, for training the neural network system to estimate one of the vocal component and the non-vocal component. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate vocal or instrumental components of an audio signal, depending on which type of component the system is trained to estimate.

Abstract: A method of separating a transparent mother sheet includes contacting a first surface of the transparent mother sheet with an open ended pressure assembly including a pressure vessel shell, thereby forming a shell cavity defined by the first surface of the transparent mother sheet and the pressure vessel shell, where the transparent mother sheet comprises a damage path. The method also includes removing gas from the shell cavity through a fluid removal outlet extending through the pressure vessel shell to reduce a cavity pressure in the shell cavity, thereby applying stress to the damage path to separate a portion of the transparent mother sheet along the damage path.