Using what we know: consequences of intentionally retrieving gist versus item-specific information

The effect of a prior gist-based versus item-specific retrieval orientation on recognition of objects and words was examined. Prior item-specific retrieval increased item-specific recognition of episodically related but not previously tested objects relative to both conceptual- and perceptual-gist retrieval. An item-specific retrieval advantage also was found when the stimuli were words (synonyms) rather than objects but not when participants overtly named objects during gist-based recognition testing, which suggests that they did not always label objects under general gist-retrieval instructions. Unlike verbal overshadowing, labeling objects during recognition attenuated (but did not eliminate) test- and interference-related forgetting. A full understanding of how retrieval affects subsequent memory, even for events or facts that are not themselves retrieved, must take into account the specificity with which that retrieval occurs.

Transmission of social anxiety from mother to infant: an experimental study using a social referencing paradigm

In this experiment we investigated the impact of indirect expressions of maternal social anxiety on infant interactions with a stranger. A social referencing paradigm was used in which infants first observed their mothers interacting with a stranger and then interacted with the stranger themselves. Mothers made no direct communicative gestures to the infant concerning the stranger throughout the procedure. There were two experimental conditions experienced by all mother-infant pairs (N = 24; 12 boys)-non-anxious and socially anxious-and there were two male strangers. Infants were between 12 and 14 months (M = 12.8, SD =.76). Order of condition and stranger presentation were counterbalanced. Before testing, mothers, none of whom were significantly socially anxious, were trained to behave in a non-anxious and a socially anxious manner on the basis of clinical and empirical descriptions of social phobia. The results showed that, compared to their responses following their mothers interacting normally with a stranger, following a socially anxious mother-stranger interaction, infants were significantly more fearful and avoidant with the stranger. Infant-stranger avoidance was further modified by infant temperament; high fear infants were more avoidant in the socially anxious condition than low-fear infants. We discuss these findings in light of the possible mechanisms underpinning infant affective and behavioral responsiveness. (c) 2005 Elsevier Ltd. All rights reserved

Variable step LMS algorithm using the accumulated instantaneous error concept

The convergence speed of the standard Least Mean Square adaptive array may be degraded in mobile communication environments. Different conventional variable step size LMS algorithms were proposed to enhance the convergence speed while maintaining low steady state error. In this paper, a new variable step LMS algorithm, using the accumulated instantaneous error concept is proposed. In the proposed algorithm, the accumulated instantaneous error is used to update the step size parameter of standard LMS is varied. Simulation results show that the proposed algorithm is simpler and yields better performance than conventional variable step LMS.

Semi-automatic annotation and retrieval of visual content using the topic map technology

There are still major challenges in the area of automatic indexing and retrieval of multimedia content data for very large multimedia content corpora. Current indexing and retrieval applications still use keywords to index multimedia content and those keywords usually do not provide any knowledge about the semantic content of the data. With the increasing amount of multimedia content, it is inefficient to continue with this approach. In this paper, we describe the project DREAM, which addresses such challenges by proposing a new framework for semi-automatic annotation and retrieval of multimedia based on the semantic content. The framework uses the Topic Map Technology, as a tool to model the knowledge automatically extracted from the multimedia content using an Automatic Labelling Engine. We describe how we acquire knowledge from the content and represent this knowledge using the support of NLP to automatically generate Topic Maps. The framework is described in the context of film post-production.

The DREAM Framework: using a network of scalable ontologies for intelligent indexing and retrieval of visual content

There are still major challenges in the area of automatic indexing and retrieval of digital data. The main problem arises from the ever increasing mass of digital media and the lack of efficient methods for indexing and retrieval of such data based on the semantic content rather than keywords. To enable intelligent web interactions or even web filtering, we need to be capable of interpreting the information base in an intelligent manner. Research has been ongoing for a few years in the field of ontological engineering with the aim of using ontologies to add knowledge to information. In this paper we describe the architecture of a system designed to automatically and intelligently index huge repositories of special effects video clips, based on their semantic content, using a network of scalable ontologies to enable intelligent retrieval.

Dynamic virtual environments using really simple syndication

This paper investigates the use of really simple syndication (RSS) to dynamically change virtual environments. The case study presented here uses meteorological data downloaded from the Internet in the form of an RSS feed, this data is used to simulate current weather patterns in a virtual environment. The downloaded data is aggregated and interpreted in conjunction with a configuration file, used to associate relevant weather information to the rendering engine. The engine is able to animate a wide range of basic weather patterns. Virtual reality is a way of immersing a user into a different environment, the amount of immersion the user experiences is important. Collaborative virtual reality will benefit from this work by gaining a simple way to incorporate up-to-date RSS feed data into any environment scenario. Instead of simulating weather conditions in training scenarios, actual weather conditions can be incorporated, improving the scenario and immersion.

Pulse shaping using state space algorithms

We discuss the use of pulse shaping for optimal excitation of samples in time-domain THz spectroscopy. Pulse shaping can be performed in a 4f optical system to specifications from state space models of the system's dynamics. Subspace algorithms may be used for the identification of the state space models.

A sparse kernel density estimation algorithm using forward constrained regression

Using the classical Parzen window (PW) estimate as the target function, the sparse kernel density estimator is constructed in a forward constrained regression manner. The leave-one-out (LOO) test score is used for kernel selection. The jackknife parameter estimator subject to positivity constraint check is used for the parameter estimation of a single parameter at each forward step. As such the proposed approach is simple to implement and the associated computational cost is very low. An illustrative example is employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with comparable accuracy to that of the classical Parzen window estimate.

Suboptimal system recovery from communication loss in a multi-robot localization scenario using EKF algorithms

This paper describes a multi-robot localization scenario where, for a period of time, the robot team loses communication with one of the robots due to system error. In this novel approach, extended Kalman filter (EKF) algorithms utilize relative measurements to localize the robots in space. These measurements are used to reliably compensate "dead-com" periods were no information can be exchanged between the members of the robot group.