Evaluating a realistic agent in an advice-giving task

The aim of this study was to empirically evaluate an embodied conversational agent called GRETA in an effort to answer two main questions: (1) What are the benefits (and costs) of presenting information via an animated agent, with certain characteristics, in a 'persuasion' task, compared to other forms of display? (2) How important is it that emotional expressions are added in a way that is consistent with the content of the message, in animated agents? To address these questions, a positively framed healthy eating message was created which was variously presented via GRETA, a matched human actor, GRETA's voice only (no face) or as text only. Furthermore, versions of GRETA were created which displayed additional emotional facial expressions in a way that was either consistent or inconsistent with the content of the message. Overall, it was found that although GRETA received significantly higher ratings for helpfulness and likability, presenting the message via GRETA led to the poorest memory performance among users. Importantly, however, when GRETA's additional emotional expressions were consistent with the content of the verbal message, the negative effect on memory performance disappeared. Overall, the findings point to the importance of achieving consistency in animated agents. (c) 2005 Elsevier Ltd. All rights reserved.

On the spectra of certain integro-differential-delay problems with applications in neurodynamics

We investigate the spectrum of certain integro-differential-delay equations (IDDEs) which arise naturally within spatially distributed, nonlocal, pattern formation problems. Our approach is based on the reformulation of the relevant dispersion relations with the use of the Lambert function. As a particular application of this approach, we consider the case of the Amari delay neural field equation which describes the local activity of a population of neurons taking into consideration the finite propagation speed of the electric signal. We show that if the kernel appearing in this equation is symmetric around some point a= 0 or consists of a sum of such terms, then the relevant dispersion relation yields spectra with an infinite number of branches, as opposed to finite sets of eigenvalues considered in previous works. Also, in earlier works the focus has been on the most rightward part of the spectrum and the possibility of an instability driven pattern formation. Here, we numerically survey the structure of the entire spectra and argue that a detailed knowledge of this structure is important within neurodynamical applications. Indeed, the Amari IDDE acts as a filter with the ability to recognise and respond whenever it is excited in such a way so as to resonate with one of its rightward modes, thereby amplifying such inputs and dampening others. Finally, we discuss how these results can be generalised to the case of systems of IDDEs.

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy. The accuracy was reduced in urban areas partly because of TerraSAR-X’s restricted visibility of the ground surface due to radar shadow and layover.

A near real-time algorithm for flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management and flood forecasting. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy.

The impact on housing supply in England of planning delay and uncertainty

The time taken to consider development proposals within the English planning system continues to provoke great policy concern despite a decade of inquiry and policy change. The results of an extensive site-based survey and hedonic modelling exercise across 45 local authorities are reported here. The analysis reveals a slow, uncertain system. It identifies planning delay as a serious problem for housing supply and its ability to respond to increases in demand. Only a relatively limited set of factors seem relevant in explaining differences in times and the results suggest that 80% of councils’ performances are statistically indistinguishable from each other. These findings question the policy emphasis put on rankings of local authorities, though some influence from local politics is apparent. Development control is consistently a lengthy and uncertain process due to its complexity. Therefore, success in lowering planning delay is only likely through radical simplification.

Motivational factors impacting the productivity of construction master craftsmen in Kuwait

In today's global economic conditions, improving the productivity of the construction industry is becoming more pressing than ever. Several factors impact the efficiency of construction operatives, but motivation is among the most important. Since low productivity is one of the significant challenges facing the construction industry in the State of Kuwait, the objective of this case study is to identify, explore, and rank the relative importance of the factors perceived to impact the motivational level of master craftsmen involved in primary construction trades. To achieve this objective, a structured questionnaire survey comprising 23 factors, which were shortlisted based on relevant previous research on motivation, the input of local industry experts, and numerous interviews with skilled operatives, was distributed to a large number of master craftsmen. Using the “Relative Importance Index” technique, the following prominent factors are identified: (1) payment delay; (2) rework; (3) lack of a financial incentive scheme; (4) the extent of change orders during execution; (5) incompetent supervisors; (6) delays in responding to Requests For Information (RFI); (7) overcrowding and operatives interface; (8) unrealistic scheduling and performance expectation; (9) shortage of materials on site; and (10) drawings quality level. The findings can be used to provide industry practitioners with guidance for focusing, acting upon, and controlling the critical factors influencing the performance of master craftsmen, hence, assist in achieving an efficient utilization of the workforce, and a reasonable level of competitiveness and cost effective operation.