Abstract: A refuse vehicle includes a chassis, a body, and a hydraulic system. The body is coupled with the chassis and includes a first frame rail and a second frame rail. The hydraulic system includes a pump, a hydraulic cylinder, and a hydraulic line. The pump is configured to pressurize a fluid. The hydraulic cylinder is configured to receive the fluid and extend or retract. The hydraulic line is configured to fluidly couple with an outlet of the pump and an inlet of the hydraulic cylinder. The hydraulic line is configured to extend laterally through the first frame rail by fluidly coupling with a connector that extends through an opening in the first frame rail. A portion of the hydraulic line extends in a longitudinal direction between the first frame rail and the second frame rail from the connector to the hydraulic cylinder.

Abstract: A refuse vehicle includes a chassis and a body supported by the chassis. The body defines a collection chamber that is configured to store refuse therein. The body includes a bottom wall and a sub-frame assembly. The sub-frame assembly includes a pair of frame rails and a plurality of cross-members. The pair of frame rails is coupled to the bottom wall and extending in a longitudinal direction along the bottom wall. The plurality of cross-members is engaged with the bottom wall and extend in a lateral direction that is substantially perpendicular to the longitudinal direction. Each of the plurality of cross-members extends through the pair of frame rails. The plurality of cross-members each has a uniform cross-sectional shape along their entire length.

Abstract: Disclosed are systems and methods for extracting content based on image analysis. A method may include receiving content including at least an image depicting a coupon; converting the received content into a larger image including the image depicting the coupon; determining, utilizing one or more neural networks, the image depicting the coupon within the larger image, wherein determining the image depicting the coupon comprises: segmenting a foreground bounding box including the image depicting the coupon from background image portions of the image; cropping the larger image based on the bounding box, wherein the cropped image consists of the image depicting the coupon; determining text included in the cropped image; and extracting information included in the coupon based on the determined text.

Abstract: Methods, systems, and technologies for preconditioning an interior/cabin of a vehicle using a control system and an HVAC system. The preconditioning can include heating or cooling the interior/cabin to a desired temperature or temperature range, and/or maintaining the interior/cabin at the desired temperature or temperature range once reached, e.g., prior to departure/operation of an associated vehicle. The preconditioning can be initiated and/or controlled based on an estimated or selected departure time, and/or can be performed in multiple phases that use different operation of the HVAC system to manage heat transfer and power use. The preconditioning can also be adjusted based on a rate of battery charging to facilitate a desired battery charge prior to departure.

Abstract: Disclosed are systems and methods for extracting content based on image analysis. A method may include receiving content including at least an image depicting a coupon; converting the received content into a larger image including the image depicting the coupon; determining, utilizing one or more neural networks, the image depicting the coupon within the larger image, wherein determining the image depicting the coupon comprises: segmenting a foreground bounding box including the image depicting the coupon from background image portions of the image; cropping the larger image based on the bounding box, wherein the cropped image consists of the image depicting the coupon; determining text included in the cropped image; and extracting information included in the coupon based on the determined text.

Abstract: Aspects herein relate to an elongated structural member for use on a front box structure of a vehicle, and a front box structure incorporating the elongated structural member. In some aspects the elongated structural member comprises an elongated rigid frame surrounding an internal space, with a first fluid channel and a second fluid channel within the internal space. The elongated structural has a length, and, in some aspects, the first fluid channel and the second fluid channel extend the length of the structural member and have an open end at each end. In some aspects, the first fluid channel and the second fluid channel are integrally formed with the rigid frame, such as by an extrusion.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework that automatically labels and classifies incoming emails. The disclosed framework embodies a novel computerized taxonomy configured as a multi-tier, multi-label classification system. The first tier involves an offline grid classifier that has higher accuracy, and the second tier is an online classifier that classifies emails in real-time. Thus, the framework provides a novel approach to classifying messages based on a multi-tiered analysis, which is utilized for generating user profiles, delivering the messages, and the like.

Abstract: Disclosed are systems and methods for extracting content based on image analysis. A method may include receiving content including at least an image depicting a coupon; converting the received content into a larger image including the image depicting the coupon; determining, utilizing one or more neural networks, the image depicting the coupon within the larger image, wherein determining the image depicting the coupon comprises: segmenting a foreground bounding box including the image depicting the coupon from background image portions of the image; cropping the larger image based on the bounding box, wherein the cropped image consists of the image depicting the coupon; determining text included in the cropped image; and extracting information included in the coupon based on the determined text.

Abstract: Disclosed are systems and methods for extracting content based on image analysis. A method may include receiving content including at least an image depicting a coupon; converting the received content into a larger image including the image depicting the coupon; determining, utilizing one or more neural networks, the image depicting the coupon within the larger image, wherein determining the image depicting the coupon comprises: segmenting a foreground bounding box including the image depicting the coupon from background image portions of the image; cropping the larger image based on the bounding box, wherein the cropped image consists of the image depicting the coupon; determining text included in the cropped image; and extracting information included in the coupon based on the determined text.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework for partitioning HTML content in electronic messages based on the relative positions of the content's links within the DOM hierarchy of the messages, and basing the propagation (e.g., display or communication) of such content therefrom. The disclosed message partitioning and extraction framework can be applied online, in real-time, at scale, without any pre-processing or pre-learning/training.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework for partitioning HTML content in electronic messages based on the relative positions of the content's links within the DOM hierarchy of the messages, and basing the propagation (e.g., display or communication) of such content therefrom. The disclosed message partitioning and extraction framework can be applied online, in real-time, at scale, without any pre-processing or pre-learning/training.

Abstract: A device may include a first module to capture information relating to network traffic passing through a first interface in a network device. A second module may capture information relating to network traffic passing through a second interface in the network device. A control module may be configured to transmit control commands to the first module and the second module, the control commands instructing the first module and the second module to capture information relating to network traffic passing through the first interface and the second interface, respectively. The control module may be further configured to receive the captured information from the first module and the second module, correlate the received information from the first module and the second module; and provide the correlated information to a user.

Abstract: A system for monitoring, troubleshooting, controlling, calibrating and/or configuring a digital television is provided. The system includes a functionality module configured to perform one or more functions of a digital television. The system includes a testing module associated with the digital television, communicatively coupled to the functionality module and being configured to receive from the functionality module, data indicative of the one or more functions of the digital television. The testing module is configured to perform processing using the received data to determine whether to alter one or more parameters associated with the one or more functions of the digital television.

Abstract: A system and method in accordance with exemplary embodiments may include receiving, from a video source device, a standard definition video signal, fragmenting the standard definition video signal into at least one of a red representation of the standard definition video signal, a green representation of the standard definition video signal, and a blue representation of the standard definition video signal using one or more 3D converter devices, reconstructing at least one of the red representation of the standard definition video signal, the green representation of the standard definition video signal, and the blue representation of the standard definition video signal using one or more video reconstruction devices, capturing at least one of a reconstructed red representation of the standard definition video signal, a reconstructed green representation of the standard definition video signal, and a reconstructed blue representation of the standard definition video signal using one or more video image capture

Abstract: A device may include a first module to capture information relating to network traffic passing through a first interface in a network device. A second module may capture information relating to network traffic passing through a second interface in the network device. A control module may be configured to transmit control commands to the first module and the second module, the control commands instructing the first module and the second module to capture information relating to network traffic passing through the first interface and the second interface, respectively. The control module may be further configured to receive the captured information from the first module and the second module, correlate the received information from the first module and the second module; and provide the correlated information to a user.

Abstract: A device may include a first network module to capture network data at a first location in a network and a second network module to capture network data at a second location in the network different from the first location in the network. The device may include a control module to receive control commands relating to the first network module and the second network module. The control module may forwarded the control commands to the first network module and the second network module. The control module may receive the captured network data from the first network module and the second network module.

Abstract: A system and method in accordance with exemplary embodiments may include receiving, from a video source device, a standard definition video signal, fragmenting the standard definition video signal into at least one of a red representation of the standard definition video signal, a green representation of the standard definition video signal, and a blue representation of the standard definition video signal using one or more 3D converter devices, reconstructing at least one of the red representation of the standard definition video signal, the green representation of the standard definition video signal, and the blue representation of the standard definition video signal using one or more video reconstruction devices, capturing at least one of a reconstructed red representation of the standard definition video signal, a reconstructed green representation of the standard definition video signal, and a reconstructed blue representation of the standard definition video signal using one or more video image capture

Abstract: A system for monitoring, troubleshooting, controlling, calibrating and/or configuring a digital television is provided. The system includes a functionality module configured to perform one or more functions of a digital television. The system includes a testing module associated with the digital television, communicatively coupled to the functionality module and being configured to receive from the functionality module, data indicative of the one or more functions of the digital television. The testing module is configured to perform processing using the received data to determine whether to alter one or more parameters associated with the one or more functions of the digital television.

Abstract: A device may include a first network module to capture network data at a first location in a network and a second network module to capture network data at a second location in the network different from the first location in the network. The device may include a control module to receive control commands relating to the first network module and the second network module. The control module may forwarded the control commands to the first network module and the second network module. The control module may receive the captured network data from the first network module and the second network module.