Interpreting the Good Life: Growth Memories in the Lives of Mature, Happy People.

In 2 studies, the authors examined autobiographical memories for the presence of 2 growth orientations that were expected to correspond differentially to maturity and well-being, which are considered to be key facets of "the good life" by L. A. King (2001). Mature participants emphasized integrative memories (conceptual integration and learning), whereas happy participants emphasized intrinsic memories (humanistic concerns). Both kinds of growth memories correlated more strongly with eudaimonic than with hedonic measures of well-being. Growth memories were largely independent of Big Five traits in relation to maturity and well-being. Finally, older participants were more likely than younger participants to have greater maturity (marginally) and well-being, but this was in part explained by older participants' greater tendency to have growth memories. The discussion considers the role of growth memories in the intentional cultivation of the good life. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Robust H∞ stabilization via parametrized Lyapunovbounds

The parametrized Lyapunov bounding technique of Haddad and Bernstein (1991, 1993, 1995) is extended to include an H_∞ -disturbance attenuation constraint. The results presented in this paper provide a framework for designing fixed-order (i.e., full- and reduced-order) controllers that guarantee robust H₂ and H_∞ performance in the presence of structured constant real parameter variations in the state space model     

Robust controller synthesis via shifted parameter-dependentquadratic cost bounds

Parameterized Lyapunov bounds and shifted quadratic guaranteed cost bounds are merged to develop shifted parameter-dependent quadratic cost bounds for robust stability and robust performance. Robust fixed-order (i.e., full- and reduced-order) controllers are developed based on new shifted parameter-dependent bounding functions. A numerical example is presented to demonstrate the effectiveness of the proposed approach     

String-matching with OBDDs

Ordered binary decision diagrams (OBDDs) are a very popular graph representation for Boolean functions. They can be viewed as finite automata recognizing sets of strings of a fixed length, where the letters of the input strings are read at most once in a predefined ordering. The string matching problem with string w as pattern, consists of determining, given an input string, whether or not it contains w as substring. We show that for a fraction of orderings tending to 1 when n increases arbitrarily, the minimal size of an OBDD solving the string matching problem for strings of length n has a growth which is an exponential in n.     

Uncertainties in Small-Angle Measurement Systems Used to Calibrate Angle Artifacts

We have studied a number of effects that can give rise to errors in small-angle measurement systems when they are used to calibrate artifacts such as optical polygons. Of these sources of uncertainty, the most difficult to quantify are errors associated with the measurement of imperfect, non-flat faces of the artifact, causing the instrument to misinterpret the average orientation of the surface. In an attempt to shed some light on these errors, we have compared autocollimator measurements to angle measurements made with a Fizeau phase-shifting interferometer. These two instruments have very different operating principles and implement different definitions of the orientation of a surface, but (surprisingly) we have not yet seen any clear differences between results obtained with the autocollimator and with the interferometer. The interferometer is in some respects an attractive alternative to an autocollimator for small-angle measurement; it implements an unambiguous and robust definition of surface orientation in terms of the tilt of a best-fit plane, and it is easier to quantify likely errors of the interferometer measurements than to evaluate autocollimator uncertainty.     

Overconfidence in Interval Estimates.

Judges were asked to make numerical estimates (e.g., "In what year was the first flight of a hot air balloon?"). Judges provided high and low estimates such that they were X% sure that the correct answer lay between them. They exhibited substantial overconfidence: The correct answer fell inside their intervals much less than X% of the time. This contrasts with choices between 2 possible answers to a question, which showed much less overconfidence. The authors show that overconfidence in interval estimates can result from variability in setting interval widths. However, the main cause is that subjective intervals are systematically too narrow given the accuracy of one's information-sometimes only 40% as large as necessary to be well calibrated. The degree of overconfidence varies greatly depending on how intervals are elicited. There are also substantial differences among domains and between male and female judges. The authors discuss the possible psychological mechanisms underlying this pattern of findings. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Using Ordinal Optimization Approach to Improve Efficiency of Selection Procedures

Indifference-zone selection procedures have been widely studied and applied to determine the sample sizes for selecting a good design among k alternative designs. However, efficiency is still a key concern for using simulation to solve ranking and selection problems. Ordinal optimization has emerged as an effective technique to improve efficiency of simulation and optimization. In this paper, we incorporate the concept of ordinal optimization with ranking-and-selection methodology and propose using a normal approximation to estimate the probability of correct selection. The proposed procedure takes into account not only the sample variances but also the difference of sample means when determining the sample sizes. Furthermore, the procedure is valid with the variance reduction technique of common random numbers. An experimental performance evaluation demonstrates the efficiency of the new procedure.     

Optimization of the polymer concrete used for manufacturing bases for precision tool machines

Due to its superior damping ratio, high adhesion and fast curing, polymer concrete is used in manufacturing bases for a wide range of precision machines. The coefficient of thermal expansion for polymer concrete is one of the main parameters that can affect the level of accuracy in precision tool machines. Flexural strength is a fundamental strength of the base. In this study six aggregates (basalt, spodumene, fly ash, river gravel, sand and chalk) were investigated. Polymer concrete samples were prepared with different compositions of aggregates containing the same resin volume fraction (aggregates 83% and risen 17%). A four points flexural test was employed to measure the flexural strength of the polymer concrete samples. The coefficient of thermal expansion for polymer concrete was measured using a custom built device. The preliminary optimum composition, with the highest flexural strength and lowest thermal expansion coefficient, was found to be basalt, spodumene and fly ash. Basalt, sand and fly ash composition was the second in the rank. The second composition was nominated for further optimization in terms of resin volume fraction in consideration of its ability to adapt a smaller amount of resin. Different samples of polymer concrete were prepared with a variety of resin volume fractions as follows; 17%, 15% and 13%. The resin volume fraction has been demonstrated to have a significant effect on the coefficient of thermal expansion and flexural strength for polymer concrete. The final optimized composition was basalt, sand and fly ash (filler 87% and resin 13%). ANSYS 13 software was employed in visualizing the influence of polymer concrete compositions on the thermal expansion of the base and how it affected the level of precision of the tool machine.