Abstract: The present disclosure provides methods and systems for autonomous data collection and system control of a material recovery facility (MRF). A control system receives data from set of sensors that reflect a status of the MRF. The control system determines an operating status of various MRF components (e.g., material handling units (MHUs), sensors, and/or other elements) and/or a composition of a waste stream being processed by the MRF. The control system controls MHU(s) based on the data to optimize the recovery and/or purity of recoverable materials from the waste stream. The control system may rearranging MHUs within the MRF and/or re-tasking individual MHUs to perform different handling functions. Machine learning (ML) and/or artificial intelligence (AI) mechanisms can be used to optimize the operation of the MRF in an autonomous fashion. Other aspects are also disclosed.

Abstract: The present disclosure provides methods and systems for autonomous data collection and system control of a material recovery facility (MRF). A control system receives data from set of sensors that reflect a status of the MRF. The control system determines an operating status of various MRF components (e.g., material handling units (MHUs), sensors, and/or other elements) and/or a composition of a waste stream being processed by the MRF. The control system controls MHU(s) based on the data to optimize the recovery and/or purity of recoverable materials from the waste stream. The control system may rearranging MHUs within the MRF and/or re-tasking individual MHUs to perform different handling functions. Machine learning (ML) and/or artificial intelligence (AI) mechanisms can be used to optimize the operation of the MRF in an autonomous fashion. Other aspects are also disclosed.

Abstract: The present disclosure provides methods and systems for autonomous data collection and system control of a material recovery facility (MRF). A control system receives data from set of sensors that reflect a status of the MRF. The control system determines an operating status of various MRF components (e.g., material handling units (MHUs), sensors, and/or other elements) and/or a composition of a waste stream being processed by the MRF. The control system controls MHU(s) based on the data to optimize the recovery and/or purity of recoverable materials from the waste stream. The control system may rearranging MHUs within the MRF and/or re-tasking individual MHUs to perform different handling functions. Machine learning (ML) and/or artificial intelligence (AI) mechanisms can be used to optimize the operation of the MRF in an autonomous fashion. Other aspects are also disclosed.

Abstract: Disclosed embodiments include methods and systems for autonomous data collection and system control of a material recovery or recycling facility. In some embodiments, a central control system receives inputs in the form of at least one data stream from each of one or more environmental sensors that reflect the status of a material recovery facility (MRF). The inputs are used to determine the operating status of one or more components of the MRF, and/or composition of a waste stream being processed by the MRF. At least one material handling unit is controlled in response to the inputs to optimize the recovery and/or purity of recyclable or recoverable materials from the waste stream. A service unit or mechanism may also be controlled in response to the inputs indicating that a component of the MRF requires servicing.

Abstract: Disclosed embodiments include methods and systems for autonomous data collection and system control of a material recovery or recycling facility. In some embodiments, a central control system receives inputs in the form of at least one data stream from each of one or more environmental sensors that reflect the status of a material recovery facility (MRF). The inputs are used to determine the operating status of one or more components of the MRF, and/or composition of a waste stream being processed by the MRF. At least one material handling unit is controlled in response to the inputs to optimize the recovery and/or purity of recyclable or recoverable materials from the waste stream. A service unit or mechanism may also be controlled in response to the inputs indicating that a component of the MRF requires servicing.

Abstract: Disclosed embodiments include methods and systems for autonomous data collection and system control of a material recovery or recycling facility. In some embodiments, a central control system receives inputs in the form of at least one data stream from each of one or more environmental sensors that reflect the status of a material recovery facility (MRF). The inputs are used to determine the operating status of one or more components of the MRF, and/or composition of a waste stream being processed by the MRF. At least one material handling unit is controlled in response to the inputs to optimize the recovery and/or purity of recyclable or recoverable materials from the waste stream. A service unit or mechanism may also be controlled in response to the inputs indicating that a component of the MRF requires servicing.

Abstract: System and methods for managing operations of one or more machines are disclosed. One method includes receiving first information relating to an operation of a dump body of a hauling machine operating in at least a partially autonomous manner, determining a failure condition of the operation based at least on the received first information, transmitting a notification relating to the failure condition, and causing a boost pressure to be applied to the dump body of the hauling machine.

Abstract: An automated computing device for providing a planning and analytics tool is disclosed. In some embodiments, the automated computing device may include a reports module configured to receive a data request for activity data associated with a plurality of entities, locate and retrieve data corresponding to the request, and provide the data corresponding to the request to a client device. In some embodiments, the automated computing device may also include a planning module configured to receive the activity data, identify at least one task for a user to complete based on the activity data, and provide the identified at least one task to the client device.

Abstract: System and methods for managing operations of one or more machines are disclosed. One method includes receiving first information relating to an operation of a dump body of a hauling machine operating in at least a partially autonomous manner, determining a failure condition of the operation based at least on the received first information, transmitting a notification relating to the failure condition, and causing a boost pressure to be applied to the dump body of the hauling machine.

Abstract: A facility is described for enabling workflow applications. The facility receives a request to identify an optimized resource list that identifies resources capable of performing a workflow process task. The workflow process task can be associated with a document type relating to a document associated with a workflow envelope. The workflow envelope can store multiple documents of at different document types. The facility includes a workflow engine and a simulation engine. The workflow engine performs workflow process tasks based on the tasks identified in the workflow envelope. The simulation engine can employ modeling and historical data from a workflow metrics data source to generate the optimized resource list and identify identifying resources matching the workflow process tasks identified in the workflow envelope. The simulation engine can be used to model the workflow process to adapt, modify or otherwise control the workflow.

Abstract: A facility is described for enabling workflow applications. The facility receives a request to identify an optimized resource list that identifies resources capable of performing a workflow process task. The workflow process task can be associated with a document type relating to a document associated with a workflow envelope. The workflow envelope can store multiple documents of at different document types. The facility includes a workflow engine and a simulation engine. The workflow engine performs workflow process tasks based on the tasks identified in the workflow envelope. The simulation engine can employ modeling and historical data from a workflow metrics data source to generate the optimized resource list and identify identifying resources matching the workflow process tasks identified in the workflow envelope.

Abstract: A facility is described for enabling workflow applications. The facility receives a request to identify an optimized resource list that identifies resources capable of performing a workflow process task. The workflow process task can be associated with a document type relating to a document associated with a workflow envelope. The workflow envelope can store multiple documents of at different document types. The facility includes a workflow engine and a simulation engine. The workflow engine performs workflow process tasks based on the tasks identified in the workflow envelope. The simulation engine can employ modeling and historical data from a workflow metrics data source to generate the optimized resource list and identify identifying resources matching the workflow process tasks identified in the workflow envelope.

Abstract: A facility is described for enabling workflow applications. The facility receives a request to identify an optimized resource list that identifies resources capable of performing a workflow process task. The workflow process task can be associated with a document type relating to a document associated with a workflow envelope. The workflow envelope can store multiple documents of at different document types. The facility includes a workflow engine and a simulation engine. The workflow engine performs workflow process tasks based on the tasks identified in the workflow envelope. The simulation engine can employ modeling and historical data from a workflow metrics data source to generate the optimized resource list and identify identifying resources matching the workflow process tasks identified in the workflow envelope.

Abstract: A reduction in noise radiating from a side of a deployed aircraft flap is achieved by locating a slot adjacent the side of the flap, and then forcing air out through the slot with a suitable mechanism. One, two or even three or more slots are possible, where the slot is located at one or more locations selected from a group of locations comprising a top surface of the flap, a bottom surface of the flap, an intersection of the top and side surface of the flap, an intersection of the bottom and side surfaces of the flap, and a side surface of the flap. In at least one embodiment the slot is substantially rectangular. A device for adjusting a rate of the air forced out through the slot can also be provided.

Abstract: A method and system for mapping acoustic sources determined from a phased microphone array. A plurality of microphones are arranged in an optimized grid pattern including a plurality of grid locations thereof. A linear configuration of N equations and N unknowns can be formed by accounting for a reciprocal influence of one or more beamforming characteristics thereof at varying grid locations among the plurality of grid locations. A full-rank equation derived from the linear configuration of N equations and N unknowns can then be iteratively determined. A full-rank can be attained by the solution requirement of the positivity constraint equivalent to the physical assumption of statically independent noise sources at each N location.

Abstract: Two different and separate audio data streams are processed through a personal computer (PC) system or other computing device so that the separate and distinct audio data streams are heard through separate sound transducers. In a preferred embodiment, chat messages received over a network during execution of a multiplayer game are processed separately from sounds produced by the multiplayer game, enabling a user to hear the game sounds from speakers, separate and distinct from verbal chat messages, which are heard through earphone(s). The earphone(s) are included in a headset, as well as a microphone that enables the user to produce verbal data that are conveyed to a hardware control unit that is connected to the PC system through a universal serial bus (USB) port. The chat audio data are converted into an analog audio signal that is heard by the user in the headphone(s) and is spatially separate and distinct from the game audio data heard through the speakers.

Abstract: A method for creating a multimedia presentation, which presentation comprises an audio or video recording of a session wherein a presenter presents an audiovisual presentation, said method comprising said presenter presenting said audiovisual presentation, making an audio or video recording of said presentation, wherein timing data comprising data for start, end and transition events within said audiovisual presentation are automatically, and without manual processing, incorporated into said audio or video recording, so as to allow said events to be used on playback to coordinate the audio or video portion of said multimedia presentation with the audiovisual portion thereof.

Abstract: An interface module includes a high density analog interface (HAI) for electrical interconnection between a programmable logic controller (PLC) and an analog to digital converter (ADC) or a digital to analog converter (DAC). The HAI includes a single application specific integrated circuit having a data scaling function block, a diagnostics function block configured to verify functionality of said scaling function block, a self-calibration function block configured to compensate for drift in said ADC, and a shared interface function block configured to electronically connect said module with a programmable logic controller (PLC).