The performance of a sequential procedure for the estimation of the median survival time with specified accuracy

A bound on the order of convergence of the remainder term in the coverage probability of a fixed quantile of the survival distribution is obtained as the prescribed tolerance on the width of the interval shrinks to zero.     

Sequential fixed width confidence intervals for regression parameters from censored data with a discrete covariate

Sequential fixed width interval estimation procedure is considered in a simple linear regression model where the independent variable (covariate) assumes only a finite number of values and the dependent variable (response) is randomly right censored. The censoring distribution may depend on the covariate values. The sequential procedure is shown to be consistent and efficient as the width of the confidence interval decreases to zero. The asymptotic distribution of the underlying stopping rale is obtained     

The implications of Big Five standing for the distribution of trait manifestation in behavior: Fifteen experience-sampling studies and a meta-analysis.

One of the fundamental questions in personality psychology is whether and how strongly trait standing relates to the traits that people actually manifest in their behavior when faced with real pressures and real consequences of their actions. One reason this question is fundamental is the common belief that traits do not predict how individuals behave, which leads to the reasonable conclusion that traits are not important to study. However, this conclusion is surprising given that there is almost no data on the ability of traits to predict distributions of naturally occurring, representative behaviors of individuals (and that there are many studies showing that traits do indeed predict specific behaviors). The authors describe a meta-analysis of 15 experience-sampling studies, conducted over the course of 8 years, amassing over 20,000 reports of trait manifestation in behavior. Participants reported traits on typical self-report questionnaires, then described their current behavior multiple times per day for several days as the behavior was occurring. Results show that traits, contrary to expectations, were strongly predictive of individual differences in trait manifestation in behavior, predicting average levels with correlations between .42 and .56 (approaching .60 for stringently restricted studies). Several other ways of summarizing trait manifestation in behavior were also predicted from traits. These studies provide evidence that traits are powerful predictors of actual manifestation of traits in behavior. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Thermodynamic consistency of the multi-scale Gibbs–Helmholtz constrained equation of state

The multi-scale Gibbs–Helmholtz constrained (GHC) equation is a new predictive cubic equation of state that constrains the energy parameter in the SRK equation to satisfy the Gibbs–Helmholtz equation. It makes use of internal energies of departure calculated from NTP Monte Carlo simulations at the molecular length scale and a novel up-scaling expression to determine the energy parameter at the bulk phase length scale.     

Consumption behavior and the aspiration for conformity and consistency.

The (socio-)psychological concepts of individual aspiration for conformity and consistency are integrated into the rational choice framework. By using this integrative approach, it is shown that, after a shock, the aspiration for conformity results in a steady state that deviates from the homo oeconomicus's behavior toward the consumption of the peer group, whereas the aspiration for consistency leads to the result that the steady-state consumption is not reached at once. With the combination of these effects, a new consumption path is derived. After a shock, the individual consumption converges step by step to the new steady-state consumption. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A selection of material using a novel type decision-making method: Preference selection index method

The aim of the current study is to implement a novel tool to help the decision-maker for selection of a proper material that will meet all the requirements of the design engineers. Preference selection index (PSI) method is a novel tool to select best alternative from given alternatives without deciding relative importance between attributes. In the present study, three different types of material selection problems are examined. A validation and consistency test of preference selection index method is performed in present work by comparing results of PSI method with published results of graph theory and matrix approach (GTMA), and technique for order preference by similarity to ideal solution (TOPSIS) method, respectively. The research has concluded that the PSI method is logical and more appropriate for the material selection problems.     

An investigation on yarn engineering using artificial neural networks

Abstract

Engineering of spun yarns having specific tensile, evenness and hairiness characteristics is a long-cherished dream of spinning technologists. Selection of suitable raw materials at minimum cost and optimisation of process parameters are the two major tasks to be achieved to manufacture engineered yarn. Advent of high-speed fibre-testing machines and development of powerful modelling tools such as artificial neural network (ANN) have provided a great impetus in the yarn engineering research. This article demonstrates the feasibility of yarn engineering by developing a yarn-to-fibre ‘reverse’ model, using ANN. This approach is entirely different from the prevailing forward models, which predict the properties of final yarn using the fibre properties as inputs. The cost minimisation of cotton fibre mix was ensured by using the classical linear programming approach in combination with ANN. The engineered yarns demonstrated good agreement with the target yarn properties.     

Comparing the relative fit of categorical and dimensional latent variable models using consistency tests.

A number of recent studies have used Meehl’s (1995) taxometric method to determine empirically whether one should model assessment-related constructs as categories or dimensions. The taxometric method includes multiple data-analytic procedures designed to check the consistency of results. The goal is to differentiate between strong evidence of categorical structure, strong evidence of dimensional structure, and ambiguous evidence that suggests withholding judgment. Many taxometric consistency tests have been proposed, but their use has not been operationalized and studied rigorously. What tests should be performed, how should results be combined, and what thresholds should be applied? We present an approach to consistency testing that builds on prior work demonstrating that parallel analyses of categorical and dimensional comparison data provide an accurate index of the relative fit of competing structural models. Using a large simulation study spanning a wide range of data conditions, we examine many critical elements of this approach. The results provide empirical support for what marks the first rigorous operationalization of consistency testing. We discuss and empirically illustrate guidelines for implementing this approach and suggest avenues for future research to extend the practice of consistency testing to other techniques for modeling latent variables in the realm of psychological assessment. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Parameter identifiability with Kullback–Leibler information divergence criterion

We study the problem of parameter identifiability with Kullback–Leibler information divergence (KLID) criterion. The KLID‐identifiability is defined, which can be related to many other concepts of identifiability, such as the identifiability with Fisher's information matrix criterion, identifiability with least‐squares criterion, and identifiability with spectral density criterion. We also establish a simple check criterion for the Gaussian process and derive an upper bound for the minimal identifiable horizon of Markov process. Furthermore, we define the asymptotic KLID‐identifiability and prove that, under certain constraints, the KLID‐identifiability will be a sufficient or necessary condition for the asymptotic KLID‐identifiability. The consistency problems of several parameter estimation methods are also discussed. Copyright © 2008 John Wiley & Sons, Ltd.     

钻孔灌注桩施工质量控制若干问题的探讨

桥梁钻孔灌注桩桩身质量存在的问题是相当严重的，一旦桩身发生严重缺陷就很难采取补救措施。本文提出以预防为主的思想，加强质量管理，改进施工操作工艺，提高钻孔灌注桩的质量。