MAXI J1659-152: The shortest orbital period black-hole transient in outburst

MAXI J1659-152 is a bright X-ray transient black-hole candidate binary system discovered in September 2010. We report here on MAXI, RXTE, Swift, and XMM-Newton observations during its 2010/2011 outburst. We find that during the first one and a half week of the outburst the X-ray light curves display drops in intensity at regular intervals, which we interpret as absorption dips. About three weeks into the outbursts, again drops in intensity are seen. These dips have, however, a spectral behaviour opposite to that of the absorption dips, and are related to fast spectral state changes (hence referred to as transition dips). The absorption dips recur with a period of 2.414+/-0.005 hrs, which we interpret as the orbital period of the system. This implies that MAXI J1659-152 is the shortest period black-hole candidate binary known to date. The inclination of the accretion disk with respect to the line of sight is estimated to be 65-80 degrees. We propose the companion to the black-hole candidate to be close to an M5 dwarf star, with a mass and radius of about 0.15-0.25 M_sun and 0.2-0.25 R_sun, respectively. We derive that the companion had an initial mass of about 1.5 M_sun, which evolved to its current mass in about 5-6 billion years. The system is rather compact (orbital separation of larger than ~1.33 R_sun), and is located at a distance of 8.6+/-3.7 kpc, with a height above the Galactic plane of 2.4+/-1.0 kpc. The characteristics of short orbital period and high Galactic scale height are shared with two other transient black-hole candidate X-ray binaries, i.e., XTE J1118+480 and Swift J1735.5-0127. We suggest that all three are kicked out of the Galactic plane into the halo, rather than being formed in a globular cluster.Comment: 20 pages, 14 figures, accepted for publication in A&

Study of arc-jet propulsion devices Final report, 20 Nov. 1964 - 19 Dec. 1965

Energy transfer mechanisms in radiation, water, and regeneratively cooled, and MPD arc jet propulsion device

Spatial, Spectral, and Perceptual Nonlinear Noise Reduction for Hands-free Microphones in a Car

Speech enhancement in an automobile is a challenging problem because interference can come from engine noise, fans, music, wind, road noise, reverberation, echo, and passengers engaging in other conversations. Hands-free microphones make the situation worse because the strength of the desired speech signal reduces with increased distance between the microphone and talker. Automobile safety is improved when the driver can use a hands-free interface to phones and other devices instead of taking his eyes off the road. The demand for high quality hands-free communication in the automobile requires the introduction of more powerful algorithms. This thesis shows that a unique combination of five algorithms can achieve superior speech enhancement for a hands-free system when compared to beamforming or spectral subtraction alone. Several different designs were analyzed and tested before converging on the configuration that achieved the best results. Beamforming, voice activity detection, spectral subtraction, perceptual nonlinear weighting, and talker isolation via pitch tracking all work together in a complementary iterative manner to create a speech enhancement system capable of significantly enhancing real world speech signals. The following conclusions are supported by the simulation results using data recorded in a car and are in strong agreement with theory. Adaptive beamforming, like the Generalized Side-lobe Canceller (GSC), can be effectively used if the filters only adapt during silent data frames because too much of the desired speech is cancelled otherwise. Spectral subtraction removes stationary noise while perceptual weighting prevents the introduction of offensive audible noise artifacts. Talker isolation via pitch tracking can perform better when used after beamforming and spectral subtraction because of the higher accuracy obtained after initial noise removal. Iterating the algorithm once increases the accuracy of the Voice Activity Detection (VAD), which improves the overall performance of the algorithm. Placing the microphone(s) on the ceiling above the head and slightly forward of the desired talker appears to be the best location in an automobile based on the experiments performed in this thesis. Objective speech quality measures show that the algorithm removes a majority of the stationary noise in a hands-free environment of an automobile with relatively minimal speech distortion