Anthony D. Wagner: Award for Distinguished Scientific Early Career Contributions to Psychology.

Presents the citation for Anthony D. Wagner, who received the Award for Distinguished Scientific Early Career Contributions to Psychology (cognition and human learning) "for outstanding and innovative research on the neural basis of memory and executive control." A brief profile and a selected bibliography accompany the citation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A distant-learning training module on the environmental design of urban buildings

The present paper aims to present a distant-learning training module that concerns the environmental design of urban buildings. The whole approach attempts to integrate topics that concern the design of urban buildings from various points of views, e.g. active and passive systems, automation systems, indoor air quality, economic aspects, energy and resources management. The package offers both printed and electronic material that gives the possibility to the students to study the various topics by using different educational methods. Additionally, the present package contains software tools that permit the students to examine real or hypothetical situations and to study further the influence of various parameters that concern the environmental building design.     

Enhancing cognitive radio systems with robust reasoning

Cognitive radio systems dynamically reconfigure the algorithms and parameters they use, in order to adapt to the changing environment conditions. However, reaching proper reconfiguration decisions presupposes a way of knowing, with high enough assurance, the capabilities of the alternate configurations, especially in terms of achievable transmission capacity and coverage. The present paper addresses this problem, firstly, by specifying a complete process for extracting estimations of the capabilities of candidate configurations, in terms of transmission capacity and coverage, and, secondly, by enhancing these estimations with the employment of a machine learning technique. The technique is based on the use of Bayesian Networks, in conjunction with an effective learning and adaptation strategy, and aims at extracting and exploiting knowledge and experience, in order to reach robust (i.e. stable and reliable) estimations of the configurations' capabilities. Comprehensive results of the proposed method are presented, in order to validate its functionality. Copyright © 2007 John Wiley & Sons, Ltd.     

The impact of the Hebbian learning rule on research in behavioural neuroscience.

Hebb's principal theoretical propositions, the cell assembly and the nature of synaptic change, were generated at a time when the focus of work in behavioural neuroscience was directed at understanding issues such as the principles governing the behaviour of animals in neuropsychological studies of learning and memory and the role of drives in the control of behaviours like sex and feeding and drinking. It was not until attention shifted to understanding the neural underpinnings of learning and memory that Hebb's propositions had an impact on behavioural neuroscience as they provided a simple, and testable, mechanism for synaptic plasticity observed both in learning and in other forms of experience-dependent neural change. But much of the field remains interested in other issues such as sensation and perception, motivation, attention, and so on, and to date, Hebb's propositions have had little impact. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Frames of Reference in Mobile Augmented Reality Displays.

In 3 experiments, the authors investigated spatial updating in augmented reality environments. Participants learned locations of virtual objects on the physical floor. They were turned to appropriate facing directions while blindfolded before making pointing judgments (e.g., "Imagine you are facing X. Point to Y"). Experiments manipulated the angular difference between the learning heading and the imagined heading and between the actual heading and the imagined heading. The effect of actual-imagined on pointing latency was observed for naive users but not for users with brief training or instructions concerning the fact that objects can move with body movements. The results indicated that naive users used an environment-stabilized reference frame to access information arrays, but with experience and instruction the nature of the representation changed from an environment stabilized to a body stabilized reference frame. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Peer-assisted learning interventions with elementary school students: A meta-analytic review.

A meta-analytic review of group comparison design studies evaluating peer-assisted learning (PAL) interventions with elementary school students produced positive effect sizes (ESs) indicating increases in achievement (unweighted mean ES = 0.59, SD = 0.90; weighted ES, d = 0.33, p     

Distinctive Features of Minimization of a Risk Functional in Mass Data Sets

A statistical learning model is considered within the framework of the theory of uniform convergence of frequencies of errors in the case where the convergence is violated as a result of increasing the informativeness of training examples. Drawbacks of nonconstructive refinements of Vapnik-Chervonenkis estimates based on an assumption on the distribution law of violations are shown. A new approach to obtaining constructive estimates for mass data sets is proposed.     

Faculty and Student Attitudes Toward Community Service: A Comparative Analysis

The Humanitarian Engineering initiative, sponsored by the William and Flora Hewlett Foundation, at the Colorado School of Mines, is creating a program that will support engineering students in understanding their responsibility for solving community development problems that exist throughout the world. As part of this effort, data has been collected on faculty and student attitudes using the ‘Community Service Attitudes Scale,” developed and validated by Shiarella, McCarthy, and Tucker. During the fall 2004, 78 students and 34 faculty members responded to this instrument. Statistically significant differences were found between the attitudes of students and faculty, males and females, and among different age groupings with respect to service activities. A general finding was that faculty displayed better attitudes toward community service than the students.     

Semi-supervised model adaptation for statistical machine translation

Statistical machine translation systems are usually trained on large amounts of bilingual text (used to learn a translation model), and also large amounts of monolingual text in the target language (used to train a language model). In this article we explore the use of semi-supervised model adaptation methods for the effective use of monolingual data from the source language in order to improve translation quality. We propose several algorithms with this aim, and present the strengths and weaknesses of each one. We present detailed experimental evaluations on the French–English EuroParl data set and on data from the NIST Chinese–English large-data track. We show a significant improvement in translation quality on both tasks.