Accenture Global Solutions Limited

Skylark Wl Holdings, LLC

Narendra Anand

Teresa Sheausan Tung

Colin Anil Puri

Carl Matthew Dukatz

Srinivas Yelisetty

Anuraag Chintalapally

Sarah Crabb

Michael Giba

Lin Zhong

Edward Knightly

Clayton Wells Shepard

Ryan E Guerra

Arnob Bhuyan

Aparna Pranavi Kakarlapudi

Gabriel Ernesto Gutierrez Anez

Arijit Bhuyan

Alfredo Arvide

Raquel Andrea Werner

Sai Gattu

Michael Thomas Giba

In some implementations, a target object identification system may train a machine learning model to identify a target object in a volume of solid waste. The target object identification system may receive, from at least one imaging device positioned in a waste processing facility, imaging data associated with a portion of a volume of solid waste. The target object identification system may identify, using the trained machine learning model and based at least in part on the imaging data, the target object, wherein the target object is disposed within the volume of solid waste. The target object identification system may provide, to a separator control assembly that controls a separator, an output associated with the target object, wherein the output is to facilitate removal of the target object from the volume of solid waste.

Target object identification for waste processing

In some implementations, a system may receive, from a differential pressure sensor, a differential pressure measurement associated with a differential pressure across an air filter within an airway of a manual ventilator. The system may determine, based on the differential pressure measurement, an air flow rate through the airway. The system may determine timing of a compression cycle of the manual ventilator. The system may determine, based on the timing, a flow threshold associated with a desired breathing cycle. The system may determine a difference between the flow threshold and the air flow rate. The system may provide, via a display associated with the manual ventilator, a representation associated with the difference to indicate whether a compression parameter of the compression cycle is to be adjusted.

System, device, and arrangement for a manual ventilation assistant

Base stations for MIMO wireless systems embodying efficient channel estimation techniques. One illustrative embodiment includes: an array of multiple antennas to exchange uplink and downlink signals with spatially-distributed user terminals; multiple transmit chains, each coupled to one of the multiple antennas by a respective transceiver that also couples that antenna to a respective one of multiple receive chains; and a controller. Each of the receive chains opportunistically derives estimated uplink channel response coefficients from packet headers in the wireless uplink signals, and the controller determines a steering transform based at least in part on the estimated channel response coefficients. The transmit chains apply the steering transform to spatially-distinct downlink signals to produce antenna-specific downlink signals for each antenna in the array. Another illustrative embodiment determines, based at least in part on the estimated channel response coefficients, a mobility indicator for each user terminal, and, based on the mobility indicators, schedules at least one action.

Efficient channel estimation for implicit MU-MIMO

A method for provisioning a computer includes providing a graph that defines relationships between one or more hardware components of a plurality of computers and component characteristics of the one or more hardware components, and relationships between one or more applications and requirements of the one or more applications. The method further includes receiving a selection of an application and determining, via the graph, whether at least one computer with hardware components capable of meeting the requirements of the application exists. If a computer exits, the method also includes communicating the application to the computer; triggering the computer to execute the application; and communicating, from the computer, data processed by the application to an external system.

Edge computing platform

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Sunnyvale, CA, United States of America

Narendra Anand