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—BitTorrent is the most successful open Internet application for content distribution. Despite its importance, both in terms of its footprint in the Internet and the influence it has on emerging P2P applications, the BitTorrent Ecosystem is only partially understood. We seek to provide a nearly complete picture of the entire public BitTorrent Ecosystem. To(More)
Over the last few years, with the immense popularity of the Kinect, there has been renewed interest in developing methods for human gesture and action recognition from 3D skeletal data. A number of approaches have been proposed to extract representative features from 3D skeletal data, most commonly hard wired geometric or bio-inspired shape context(More)
—This paper proposes an operating framework for ag-gregators of plug-in electric vehicles (PEVs). First, a minimum-cost load scheduling algorithm is designed, which determines the purchase of energy in the day-ahead market based on the forecast electricity price and PEV power demands. The same algorithm is applicable for negotiating bilateral contracts.(More)
—In current multi-channel live P2P video systems, there are several fundamental performance problems including exceedingly-large channel switching delays, long playback lags, and poor performance for less popular channels. These performance problems primarily stem from two intrinsic characteristics of multi-channel P2P video systems: channel churn and(More)
—Measurement of available bandwidth in a network has always been a topic of great interest. This knowledge can be applied to a wide variety of applications and can be instrumental in providing Quality of Service to end users. Several probe-based tools have been proposed to measure available bandwidth in wired networks. However, the performance of these(More)
We present <i>femto-photography</i>, a novel imaging technique to capture and visualize the propagation of light. With an effective exposure time of 1.85 picoseconds (ps) per frame, we reconstruct movies of ultrafast events at an equivalent resolution of about one half trillion frames per second. Because cameras with this shutter speed do not exist, we(More)
Building intelligent systems that are capable of extracting high-level representations from high-dimensional sensory data lies at the core of solving many computer vision-related tasks. We propose the multispectral neural networks (MSNN) to learn features from multicolumn deep neural networks and embed the penultimate hierarchical discriminative manifolds(More)
Verification of reachability properties for probabilistic systems is usually based on variants of Markov processes. Current methods assume an exact model of the dynamic behavior and are not suitable for realistic systems that operate in the presence of uncertainty and variability. This research note extends existing methods for Bounded-parameter Markov(More)