Deng Li

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We report on an ongoing effort to build a Dynamic Data Driven Application System (DDDAS) for short-range forecast of weather and wildfire behavior from real-time weather data, images, and sensor streams. The system changes the forecast as new data is received. We encapsulate the model code and apply an ensemble Kalman filter in time-space with a highly(More)
—In order to guarantee both the efficiency and robustness in the Peer-to-Peer (P2P) network, the paper designs a novel Super-node Overlay Based on Information Exchange called SOBIE. Differing from current structured and unstructured, or meshed and tree-like P2P overlay, the SOBIE is a whole new structure to improve the efficiency of searching in the P2P(More)
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Locating content in an efficient and scalable way without centralized control is one of the challenges within P2P computing. The paper presents an unstructured P2P overlay called Maya pyramid overlay (MPO) where update and backup only take place in two neighboring levels or layers, differing from the recursive method in traditional hierarchical P2P(More)
We explore methods to automatically detect the quality in individual or batches of pharmaceutical products as they are manufactured. The goal is to detect 100% of the defects, not just statistically sample a small percentage of the products and draw conclusions that may not be 100% accurate. Removing all of the defective products, or halting production in(More)
We describe three different dynamic data-driven applications systems (DDDAS): an empty house, a contaminant identification and tracking, and a wildland fire. Each has something in common with all of the rest and can use some common tools. Each DDDAS is quite complicated in comparison to a traditional static input simulation that is run with large numbers of(More)