General Electric Company

Nbcuniversal Media, LLC

Angshuman Saha

John Michael Lizzi

Colin Craig McCulloch

Necip Doganaksoy

Rajesh Tyagi

Philippe Giguere

Thomas Paul Repoff

Jayanth Kalle Marasanapalle

Abhishek Srivastava

Abhinanda Sarkar

Vineel Gujjar

Martha Gardner

Andrew Francis Skinner

Shirley Au

Roy Wilson

Malcolm Craig Winslow

Michael Dion

Joseph E Cates

Pameet Singh

Michelle My-Ly Huynh

Early detection of high volume swarms in a peer-to-peer network, including a data feed of peer-to-peer swarm activity, and an analytics engine processing the data feed and identifying the high volume swarms that have parameters that exceed a threshold. The system can include a pre-processing section for conditioning the swarm data for the analytics section. There can also be a verification section that confirms that the peer download file matches the target file. The early detection provides for enhanced anti-piracy efforts, improved allocation of network resources, and better business decision-making.

Early detection of high volume peer-to-peer swarms

The present disclosure relates to an approach by which low-performing turbines may be identified from among a plurality of wind turbines, such as may be present at a wind power plant. In accordance with one embodiment, low-performing turbines are identified from among pairs of turbines and based upon a comparison of the observed and expected performance of the turbines within each pair.

Systems and methods for identifying wind turbine performance inefficiency

A method and system for assessing and optimizing crude selection are provided. A predictive engine uses data from a database to execute at least one predictive performance model and/or at least one risk assessment model designed to optimize or improve refining operations during a refining process. The predictive engine takes as input key crude information corresponding to a particular crude or crude blend, e.g., at least one crude slate, and refinery operating parameters and/or conditions corresponding to a specific refinery and uses desirability metrics to assess the similarity to data in the database. Based on the resulting output, at least one predictive performance and/or at least one risk assessment model uses the output to predict performance or risk measures of refining the particular crude or crude blend using the specific refinery during the refining process, the probability of problems occurring during the refining process, the distribution of the problems throughout the refining process, etc.

Method and system for assessing and optimizing crude selection

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Bengaluru, India

Angshuman Saha