Effective Monte Carlo simulation on System-V massively parallel associative string processing architecture

We show that the latest version of massively parallel processing associative string processing architecture (System-V) is applicable for fast Monte Carlo simulation if an effective on-processor random number generator is implemented. Our lagged Fibonacci generator can produce $10^8$ random numbers on a processor string of 12K PE-s. The time dependent Monte Carlo algorithm of the one-dimensional non-equilibrium kinetic Ising model performs 80 faster than the corresponding serial algorithm on a 300 MHz UltraSparc.Comment: 8 pages, 9 color ps figures embedde

SOURCES OF ERROR WHEN MEASURING ACHILLES TENDON MECHANICS DURING RUNNING ACTIVITIES

Accurate measurements of tendon mechanics are necessary for biomechanists when trying to identify injury risk factors, optimise athletic performance and develop musculoskeletal models. Measuring Achilles tendon (AT) mechanics dynamically is now possible by combining motion capture and ultrasound (US). The aim of this study was to quantify sources of error when measuring AT length using motion capture and US, and establish their effect on calculated strain values. Errors in AT insertion tracking and data synchronisation caused differences in AT length and moment arm of 5.3 ± 1.1 mm and 11.2 ± 0.9 mm, respectively; this decreased calculated AT peak strain from 11.6 ± 3.5% to 5.4 ± 2.5%. These differences could significantly impact a researcher‘s interpretation of the effects of footwear, technique, and specific kinematics on AT loading

Identification of structured nonlinear state–space models for hysteretic systems using neural network hysteresis operators

Hysteretic system behavior is ubiquitous in science and engineering fields including measurement systems and applications. In this paper, we put forth a nonlinear state–space system identification method that combines the state–space equations to capture the system dynamics with a compact and exact artificial neural network (ANN) representation of the classical Prandtl–Ishlinskii (PI) hysteresis. These ANN representations called PI hysteresis operator neurons employ recurrent ANNs with classical activation functions, and thus can be trained with classical neural network learning algorithms. The structured nonlinear state–space model class proposed in this paper, for the first time, offers a flexible interconnection of PI hysteresis operators with a linear state–space model through a linear fractional representation. This results in a comprehensive and flexible model structure. The performance is validated both on numerical simulation and on measurement data.</p

Variability of Massive Stars with Known Spectral Types in the Small Magellanic Cloud Using 8 Years of OGLE-III Data

We present a variability study of 4646 massive stars in the Small Magellanic Cloud (SMC) with known spectral types from the catalog of Bonanos et al. (2010) using the light curves from the OGLE-III database. The goal is to exploit the time domain information available through OGLE-III to gain insight into the processes that govern the evolution of massive stars. This variability survey of massive stars with known spectral types is larger than any previous survey by a factor of 7. We find that 60% of our sample (2766 stars) show no significant variability and 40% (1880 stars) exhibit variability distributed as follows: 807 stars display low-amplitude stochastic variability with fluctuations in I-band of up to 0.05 mag, 443 stars present irregular variability of higher amplitude (76% of these are reported as variables for the first time), 205 are eclipsing binaries (including 101 newly discovered systems), 50 are candidate rotating variables, 126 are classical Cepheids, 188 stars exhibit short-term sinusoidal periodicity (P < 3 days) making them candidate "slowly pulsating B stars" and non-radial Be pulsators, and 61 periodic stars exhibit longer periods. We demonstrate the wealth of information provided in the time domain, by doubling the number of known massive eclipsing binary systems and identifying 189 new candidate early-type Be and 20 Oe stars in the SMC. In addition, we find that ~80% of Be stars are photometrically variable in the OGLE-III time domain and provide evidence that short-term pulsating stars with additional photometric variability are rotating close to their break-up velocity.Comment: 46 pages, 18 figures, 11 tables. A&A in press. See http://media.wix.com/ugd/d2ba94_1596d7db762b496c89f21d03891f46c3.pdf for a version with full resolution figure