内隐序列学习的表征机制及年龄效应研究

该研究从年龄效应这一独特视角探讨了内隐序列学习的表征机制。结果表明:(1)内隐序列学习存在具体联结和抽象层级编码双重表征机制,且在该研究中以抽象编码为主;(2)老、青、幼三组被试的内隐序列学习无显著差异,间接支持了具体联结机制不起主要作用的结论。该研究的推论是:(1)内隐序列学习的表征是一个遵循“最优级编码”的动态过程;(2)该过程不涉及注意机制和短时记忆。     

Adaptive criterion setting in perceptual decision making

Pigeons responded in a perceptual categorization task with six different stimuli (shades of gray), three of which were to be classified as "light" or "dark", respectively. Reinforcement probability for correct responses was varied from 0.2 to 0.6 across blocks of sessions and was unequal for correct light and dark responses. Introduction of a new reinforcement contingency resulted in a biphasic process of adjustment: First, choices were strongly biased towards the favored alternative, which was followed by a shift of preference back towards unbiased choice allocation. The data are well described by a signal detection model in which adjustment to a change in reinforcement contingency is modeled as the change of a criterion along a decision axis with fixed stimulus distributions. Moreover, the model shows that pigeons, after an initial overadjustment, distribute their responses almost optimally, although the overall benefit from doing so is extremely small. The strong and swift effect of minute changes in overall reinforcement probability precludes a choice strategy directly maximizing expected value, contrary to the assumption of signal detection theory. Instead, the rapid adjustments observed can be explained by a model in which reinforcement probabilities for each action, contingent on perceived stimulus intensity, determine choice allocation.     

Multicriteria Optimization Technique for Optimal Design of Orthotropic Bridges

The design improvement of large‐scale structures such as cable stayed and suspension bridges with large spans is one of the major engineering optimization problems faced by design engineers. In many real‐life engineering design problems, it is necessary to carry out large‐scale experimental physical models for only one prototype to construct the feasible solution set that is too expensive and not practical. For these reasons, an experimental search for optimal solutions is often not carried out at all. This paper presents a technique for multicriteria analysis, which involve the finite element analysis of the prototype in the optimization process. The improvement of the Suez Canal Bridge in Egypt is introduced as a real‐life large‐scale case study. The parameter space investigation method, the visual basic for application programming language, and Femap as finite element analysis software provide an implementation tools to construct the feasible and Pareto solution sets for the studied bridge. An efficient combination between the parameter space investigation method and the finite element programme was successfully investigated to obtain the Pareto solution set. This study shows possibility to apply the multicriteria optimization method for more applications on different large‐scale structural systems in the future. Copyright © 2013 John Wiley & Sons, Ltd.     

The effects of prompting and feedback on drivers' stopping at stop signs

Complete stops at a high-traffic intersection on the campus of a public university were increased with a prompting and consequence intervention. Data were collected at two opposing stop signs (Stop A and Stop B); however, the intervention was implemented only at Stop A. During the intervention, a volunteer stood next to Stop A holding a poster that read, "Please Stop--I Care," with "Thank You For Stopping" on the reverse side. The poster was held by the volunteer so that drivers approaching Stop A could read the sign. Drivers approaching Stop B could see the volunteer but could not read the sign. When vehicles approaching Stop A made a complete stop, the volunteer flashed the "thank you" side of the poster to the driver. The strategy was evaluated using a multielement design. The intervention increased stops completed at Stop A from a baseline average of 13% to an intervention average of 52%. Stop B also showed improved stopping, from a baseline average of 6% to an intervention average of 28%. Data showed no relation between complete stops made and the drivers' use of turn signals and safety belts.     

Human risky choice under temporal constraints: tests of an energy-budget model

Risk-sensitive foraging models predict that choice between fixed and variable food delays should be influenced by an organism's energy budget. To investigate whether the predictions of these models could be extended to choice in humans, risk sensitivity in 4 adults was investigated under laboratory conditions designed to model positive and negative energy budgets. Subjects chose between fixed and variable trial durations with the same mean value. An energy requirement was modeled by requiring that five trials be completed within a limited time period for points delivered at the end of the period (block of trials) to be exchanged later for money. Manipulating the duration of this time period generated positive and negative earnings budgets (or, alternatively, "time budgets"). Choices were consistent with the predictions of energy-budget models: The fixed-delay option was strongly preferred under positive earnings-budget conditions and the variable-delay option was strongly preferred under negative earnings-budget conditions. Within-block (or trial-by-trial) choices were also frequently consistent with the predictions of a dynamic optimization model, indicating that choice was simultaneously sensitive to the temporal requirements, delays associated with fixed and variable choices on the upcoming trial, cumulative delays within the block of trials, and trial position within a block.     

How Can Contextual Variables Influence Creative Thinking? Contributions from the Optimal-Level of Arousal Model

More and more research is showing how different environments can lead to greater or lower creative skills. The purpose of this concept paper is to introduce a novel application of the optimal-level of arousal model that could address inconsistencies present in the literature. After introducing possible definitions of creativity, I discuss the optimal-level of arousal theory and how considering the “arousal” and “mood changing” potentials of contexts could enlighten findings related to inter-individual differences, domain-specificities, developmental aspects, and gender differences. Among other things, this model will clarify the factors influencing motivation to display creative skills which could improve the external validity of creativity studies. Examples of the kinds of hypotheses that can be tested by applying this model in future creative studies will also be proposed.     

Homogeneity analysis withk sets of variables: An alternating least squares method with optimal scaling features

Homogeneity analysis, or multiple correspondence analysis, is usually applied tok separate variables. In this paper we apply it to sets of variables by using sums within sets. The resulting technique is called OVERALS. It uses the notion of optimal scaling, with transformations that can be multiple or single. The single transformations consist of three types: nominal, ordinal, and numerical. The corresponding OVERALS computer program minimizes a least squares loss function by using an alternating least squares algorithm. Many existing linear and nonlinear multivariate analysis techniques are shown to be special cases of OVERALS. An application to data from an epidemiological survey is presented.This research was partly supported by SWOV (Institute for Road Safety Research) in Leidschendam, The Netherlands.     

An examination of procedures for determining the number of clusters in a data set

A Monte Carlo evaluation of 30 procedures for determining the number of clusters was conducted on artificial data sets which contained either 2, 3, 4, or 5 distinct nonoverlapping clusters. To provide a variety of clustering solutions, the data sets were analyzed by four hierarchical clustering methods. External criterion measures indicated excellent recovery of the true cluster structure by the methods at the correct hierarchy level. Thus, the clustering present in the data was quite strong. The simulation results for the stopping rules revealed a wide range in their ability to determine the correct number of clusters in the data. Several procedures worked fairly well, whereas others performed rather poorly. Thus, the latter group of rules would appear to have little validity, particularly for data sets containing distinct clusters. Applied researchers are urged to select one or more of the better criteria. However, users are cautioned that the performance of some of the criteria may be data dependent.The authors would like to express their appreciation to a number of individuals who provided assistance during the conduct of this research. Those who deserve recognition include Roger Blashfield, John Crawford, John Gower, James Lingoes, Wansoo Rhee, F. James Rohlf, Warren Sarle, and Tom Soon.     

A distance-based variety of nonlinear multivariate data analysis, including weights for objects and variables

In the distance approach to nonlinear multivariate data analysis the focus is on the optimal representation of the relationships between the objects in the analysis. In this paper two methods are presented for including weights in distance-based nonlinear multivariate data analysis. In the first method, weights are assigned to the objects while the second method is concerned with differential weighting of groups of variables. When each analysis variable defines a group the latter method becomes a variable weighting method. For objects the weights are assumed to be given; for groups of variables they may be given, or estimated. These weighting schemes can also be combined and have several important applications. For example, they make it possible to perform efficient analyses of large data sets, to use the distance-based variety of nonlinear multivariate data analysis as an addition to loglinear analysis of multiway contingency tables, and to do stability studies of the solutions by applying the bootstrap on the objects or the variables in the analysis. These and other applications are discussed, and an efficient algorithm is proposed to minimize the corresponding loss function.This study is funded by The Netherlands Organization for Scientific Research (NWO) by grant nr. 030-56403 for the PIONEER project Subject Oriented Multivariate Analysis to the third author.