Initializing Wiener–Hammerstein models based on partitioning of the best linear approximation

This paper describes a new algorithm for initializing and estimating Wiener–Hammerstein models which consist of two linear parts with a static nonlinearity in between. The algorithm makes use of the best linear model of the system, which is a consistent estimate of the systems dynamics for Gaussian excitations. The linear model is split in all possible ways into two sub-models. For all possible splits, a Wiener–Hammerstein model is initialized which means that a nonlinearity is introduced in between the two sub-models. The linear parameters of this nonlinearity can be estimated using least-squares. All initialized models can then be ranked depending on the fit. Typically, one is only interested in the best one, for which all parameters are fitted using prediction error minimization.The paper explains the algorithm in detail and consistency of the initialization is proven. Computational aspects are investigated, showing that in most realistic cases, the number of splits of the initial linear model remains low enough to make the algorithm useful. The algorithm is illustrated on an example where it is shown that the initialization is a tool to avoid many local minima.     

Tuberculosis in BCG-vaccinated and unvaccinated young Swedish Men. A comparative study

Tuberculosis causing exemption from military service was studied in 47,791 tuberculin-tested military recruits between 1941 and 1946. A total of 46.6% were tuberculin negative, and two-thirds were BCG vaccinated. An analysis was made of 304 cases of tuberculosis discovered from 6 months after the test up to the end of 1960. It has been calculated that 69% of "expected cases" of tuberculosis were in the BCG-vaccinated men during the 5-year period after the test, and 20% during the following period; 46% of "expected cases" of post-primary pulmonary tuberculosis and 83% of "expected" deaths were prevented. The differences on which these percentages are based were statistically significant. The efficacy of BCG vaccination was lower in areas with widespread cattle tuberculosis than in areas where cattle tuberculosis is less frequent; this is explained by the influence of previously acquired immunity.     

Physical attractiveness and health: Comment on Weeden and Sabini (2005).

Evolutionary behavioral biology suggests that certain characteristics of the human face and body are important for mate preferences and are therefore subject to sexual selection. J. Weeden and J. Sabini (see record 2005-11504-001) identify a number of weaknesses in the association between traits' attractiveness and health. In contrast, the authors argue that (a) studies on preferences for physical characteristics that rely on 1 trait permit only limited interpretation, (b) limitations placed on J. Weeden and J. Sabini's review exclude important associations, (c) there are misconceptions in their treatment of some traits, and (d) their selected literature provides an inaccurate picture regarding effect size. The authors suggest that future research in this field should seek conceptual and methodological constancy in trait selection and in the evaluation of attractiveness- and health-related traits. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Concrete Beams Exposed to Live Loading during Carbon Fiber Reinforced Polymer Strengthening

The need for structural rehabilitation of concrete structures all over the world is well known. Extensive amounts of research have been carried out and are ongoing in this field. Most of the laboratory research has been undertaken on structural elements without live load during the strengthening process. Normally owners of structures want to continue their activity or service during strengthening. Full-scale applications have shown that this is possible, but there is a lack of understanding as to how cyclic loads are distributed during strengthening; for example, traffic loads affect the final strengthening result. This paper presents laboratory tests on concrete beams strengthened with carbon fiber-reinforced polymer laminates and near-surface mounted reinforcement. The beams were subjected to a cyclic load during setting of the adhesive, and after additional hardening were then loaded by deformation control up to failure.     

1H-spectroscopic imaging with read gradient during acquisition in inhomogeneous fields: analysis, measurement strategy, and data processing

The proton magnetic resonance spectroscopic imaging techniques that use read gradient during acquisition produce proton spectra with high spatial and moderately high spectroscopic resolution in a reasonable time forin vivo applications. These techniques suffer mainly from the spatial and pectral distortions caused by the convolution of spectral/spatial information (chemical-shift artifacts) and from the spectral shifts caused by static magnetic field inhomogeneities. The investigators analyze the chemical-shift artifacts in the presence of nonnegligible static magnetic field inhomogeneities and propose a postdetection processing scheme to correct for such effects. Spectral artifacts caused by chemical shifts, spectral line overlapping, streak broadening, and magnetic field inhomogeneities are discussed. The postdetection data processing scheme is demonstrated on measurements of a phantom as well as a human leg. Supported by the Swedish Medical Research Council, project B-96-17x-006676-14A, and by Uppsala University are gratefully acknowledged. One of us (J.W.) is indebted to the Institute of Measurement Science, Slovak Academy of Sciences, for continuous support, VEGA Grant No. 95/5305/585,468 & 2/1207/96     

Control applications of nonlinear convex programming

Since 1984 there has been a concentrated effort to develop efficient interior-point methods for linear programming (LP). In the last few years researchers have begun to appreciate a very important property of these interior-point methods (beyond their efficiency for LP): they extend gracefully to nonlinear convex optimization problems. New interior-point algorithms for problem classes such as semidefinite programming (SDP) or second-order cone programming (SOCP) are now approaching the extreme efficiency of modern linear programming codes. In this paper we discuss three examples of areas of control where our ability to efficiently solve nonlinear convex optimization problems opens up new applications. In the first example we show how SOCP can be used to solve robust open-loop optimal control problems. In the second example, we show how SOCP can be used to simultaneously design the set-point and feedback gains for a controller, and compare this method with the more standard approach. Our final application concerns analysis and synthesis via linear matrix inequalities and SDP.     

Open Embedded Control

Embedded control devices today usually allow parameter changes, and possibly activation of different pre-implemented algorithms. Full reprogramming using the complete source code is not allowed for safety, efficiency, and proprietary reasons. For these reasons, embedded regulators are quite rigid and closed concerning the control structure. In several applications, like industrial robots, there is a need to tailor the low level control to meet specific application demands. In order to meet the efficiency and safety demands, a way of building more generic and open regulators has been developed. The key idea is to use pieces of compiled executable code as functional operators, which in the simplest case may appear as ordinary control parameters. In an object oriented framework, this means that new methods can be added to controller objects after implementation of the basic control, even at run-time. The implementation was carried out in industrially well accepted languages such as C and C++. The dynamic binding at run-time differs from ordinary dynamic linking in that only a subset of the symbols can be used. This subset is defined by the fixed part of the system. The safety demands can therefore still be fulfilled. Encouraged by results from fully implemented test cases, we believe that extensive use of this concept will admit more open, still efficient, embedded systems.     

Local effects in the vicinity of inserts in sandwich panels

The paper considers local bending effects induced in the vicinity of inserts in sandwich panels. Such local bending effects are associated with an increase of bending stresses in the sandwich faces and normal and shear stresses in the sandwich core. An earlier developed analytic model [Proceedings of the Sixth International Conference on Sandwich Structures (ICSS-6) (2002) 551] is adapted for the case of a sandwich panel with circular insert, with elastic properties differing from those of the core. The locally induced stresses in the faces and core due to presence of the insert are expressed via simple analytic relations (and charts) enabling an estimation of these local stresses. Finite element analysis is employed to demonstrate the applicability of the analytic model, and a good correspondence between the numerical and the analytical data is found. A study case related to marine applications, namely a circular insert in a sandwich deck panel used for mounting of a rigging fixture, is considered, and optimization of an existing design is carried out.     

Subjective Probability Intervals: How to Reduce Overconfidence by Interval Evaluation.

Format dependence implies that assessment of the same subjective probability distribution produces different conclusions about over- or underconfidence depending on the assessment format. In 2 experiments, the authors demonstrate that the overconfidence bias that occurs when participants produce intervals for an uncertain quantity is almost abolished when they evaluate the probability that the same intervals include the quantity. The authors successfully apply a method for adaptive adjustment of probability intervals as a debiasing tool and discuss a tentative explanation in terms of a naive sampling model. According to this view, people report their experiences accurately, but they are naive in that they treat both sample proportion and sample dispersion as unbiased estimators, yielding small bias in probability evaluation but strong bias in interval production. (PsycINFO Database Record (c) 2010 APA, all rights reserved)