Certain nonlinear partially observable stochastic optimal controlproblems with explicit control laws equivalent to LEQG/LQG problems

This paper is concerned with partially observed stochastic optimal control problems when nonlinearities enter the dynamics of the unobservable state and the observations as gradients of potential functions. Explicit representations for the information state are derived in terms of a finite number of sufficient statistics. Consequently, the partially observed problem is recast as one of complete information with a new state generated by a modified version of the Kalman filter. When the terminal cost is quadratic in the unobservable state and includes the integral of the nonlinearities, the optimal control laws are explicitly computed, similar to linear-exponential-quadratic-Gaussian (LEQG) and linear-quadratic-Gaussian (LQG) tracking problems. The results are applicable to filtering and control of Hamiltonian systems     

Use of weibull statistics to quantify property variability in TiAl alloys

Tensile experiments have been performed on specimens of four different investment-cast TiAl-based alloys with variations in casting conditions. The average ductilities obtained in these experiments vary between approximately 0.8 to 2.0 pct plastic strain to failure in tension. By using the three-parameter form of the Weibull relation, with the 0.2 pct offset yield strength as the minimum failure strength, the resulting variability in the data can be quantified and is found to be similar for those alloys with similar microstructural scale (grain size). Large variations in lamellar volume fraction, segregation, and phase distribution have a minor influence on property variability, compared to changes in the scale of the grain structure caused by either variations in cooling rate during casting or the addition of grain refiners.     

Limitations on the uses of multimedia exposure measurements for multipathway exposure assessment--Part II: Effects of missing data and imprecision.

Multimedia data from two probability-based exposure studies were investigated in terms of how missing data and measurement-error imprecision affected estimation of population parameters and associations. Missing data resulted mainly from individuals'refusing to participate in certain measurement activities, rather than from field or laboratory problems; it suggests that future studies should focus on methods for maximizing participation rates. Measurement error variances computed from duplicate-sample data were small relative to the inherent variation in the populations; consequently, adjustments in nonparametric percentile estimates to account for measurement imprecision were small. Methods of adjustment based on lognormality assumptions, however, appeared to perform poorly.     

The Lambda Library: unnamed functions in C++

The Lambda Library (LL) adds a form of lambda functions to C++, which are common in functional programming languages. The LL is implemented as a template library using standard C++; thus no language extensions or preprocessing is required. The LL consists of a rich set of tools for defining unnamed functions. In particular these unnamed functions work seamlessly with the generic algorithms in the C++ Standard Library. The LL offers significant improvements, in terms of generality and ease of use, compared to the current tools in the C++ Standard Library. Copyright © 2003 John Wiley & Sons, Ltd.