6,055 research outputs found

    Controlling the Gaze of Conversational Agents

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    We report on a pilot experiment that investigated the effects of different eye gaze behaviours of a cartoon-like talking face on the quality of human-agent dialogues. We compared a version of the talking face that roughly implements some patterns of human-like behaviour with\ud two other versions. In one of the other versions the shifts in gaze were kept minimal and in the other version the shifts would occur randomly. The talking face has a number of restrictions. There is no speech recognition, so questions and replies have to be typed in by the users\ud of the systems. Despite this restriction we found that participants that conversed with the agent that behaved according to the human-like patterns appreciated the agent better than participants that conversed with the other agents. Conversations with the optimal version also\ud proceeded more efficiently. Participants needed less time to complete their task

    Experimenting with the Gaze of a Conversational Agent

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    We have carried out a pilot experiment to investigate the effects of different eye gaze behaviors of a cartoon-like talking face on the quality of human-agent dialogues. We compared a version of the talking face that roughly implements some patterns of humanlike behavior with two other versions. We called this the optimal version. In one of the other versions the shifts in gaze were kept minimal and in the other version the shifts would occur randomly. The talking face has a number of restrictions. There is no speech recognition, so questions and replies have to\ud be typed in by the users of the systems. Despite this restriction we found that participants that conversed with the optimal agent appreciated the agent more than participants that conversed with the other agents. Conversations with the optimal version proceeded more efficiently. Participants needed less time to complete their task

    New Interactions with Workflow Systems

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    This paper describes the evaluation of our early design ideas of an ad-hoc of workflow system. Using the teach-back technique, we have performed a hermeneutic analysis of the mockup implementation named NIWS to get corrective and creative feedback at the functional, dialogue and representation level of the new workflow system

    Sticks, balls or a ribbon? Results of a formative user study with bioinformaticians

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    User interfaces in modern bioinformatics tools are designed for experts. They are too complicated for\ud novice users such as bench biologists. This report presents the full results of a formative user study as part of a\ud domain and requirements analysis to enhance user interfaces and collaborative environments for\ud multidisciplinary teamwork. Contextual field observations, questionnaires and interviews with bioinformatics\ud researchers of different levels of expertise and various backgrounds were performed in order to gain insight into\ud their needs and working practices. The analysed results are presented as a user profile description and user\ud requirements for designing user interfaces that support the collaboration of multidisciplinary research teams in\ud scientific collaborative environments. Although the number of participants limits the generalisability of the\ud findings, the combination of recurrent observations with other user analysis techniques in real-life settings\ud makes the contribution of this user study novel

    Climate and terrain factors explaining streamflow response and recession in Australian catchments

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    Daily streamflow data were analysed to assess which climate and terrain factors best explain streamflow response in 183 Australian catchments. Assessed descriptors of catchment response included the parameters of fitted baseflow models, and baseflow index (BFI), average quick flow and average baseflow derived by baseflow separation. The variation in response between catchments was compared with indicators of catchment climate, morphology, geology, soils and land use. Spatial coherence in the residual unexplained variation was investigated using semi-variogram techniques. A linear reservoir model (one parameter; recession coefficient) produced baseflow estimates as good as those obtained using a non-linear reservoir (two parameters) and for practical purposes was therefore considered an appropriate balance between simplicity and explanatory performance. About a third (27–34%) of the spatial variation in recession coefficients and BFI was explained by catchment climate indicators, with another 53% of variation being spatially correlated over distances of 100–150 km, probably indicative of substrate characteristics not captured by the available soil and geology data. The shortest recession half-times occurred in the driest catchments and were attributed to intermittent occurrence of fast-draining (possibly perched) groundwater. Most (70–84%) of the variation in average baseflow and quick flow was explained by rainfall and climate characteristics; another 20% of variation was spatially correlated over distances of 300–700 km, possibly reflecting a combination of terrain and climate factors. It is concluded that catchment streamflow response can be predicted quite well on the basis of catchment climate alone. The prediction of baseflow recession response should be improved further if relevant substrate properties were identified and measured

    Selection of an appropriately simple storm runoff model

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    An appropriately simple event runoff model for catchment hydrological studies was derived. The model was selected from several variants as having the optimum balance between simplicity and the ability to explain daily observations of streamflow from 260 Australian catchments (23–1902 km<sup>2</sup>). Event rainfall and runoff were estimated from the observations through a combination of baseflow separation and storm flow recession analysis, producing a storm flow recession coefficient (<i>k</i><sub>QF</sub>). Various model structures with up to six free parameters were investigated, covering most of the equations applied in existing lumped catchment models. The performance of alternative structures and free parameters were expressed in Aikake's Final Prediction Error Criterion (FPEC) and corresponding Nash-Sutcliffe model efficiencies (NSME) for event runoff totals. For each model variant, the number of free parameters was reduced in steps based on calculated parameter sensitivity. The resulting optimal model structure had two or three free parameters; the first describing the non-linear relationship between event rainfall and runoff (<i>S</i><sub>max</sub>), the second relating runoff to antecedent groundwater storage (<i>C</i><sub>Sg</sub>), and a third that described initial rainfall losses (<i>L</i><sub>i</sub>), but which could be set at 8 mm without affecting model performance too much. The best three parameter model produced a median NSME of 0.64 and outperformed, for example, the Soil Conservation Service Curve Number technique (median NSME 0.30–0.41). Parameter estimation in ungauged catchments is likely to be challenging: 64% of the variance in <i>k</i><sub>QF</sub> among stations could be explained by catchment climate indicators and spatial correlation, but corresponding numbers were a modest 45% for <i>C</i><sub>Sg</sub>, 21% for <i>S</i><sub>max</sub> and none for <i>L</i><sub>i</sub>, respectively. In gauged catchments, better estimates of event rainfall depth and intensity are likely prerequisites to further improve model performance

    Communication of anger versus disappointment in bargaining and the moderating role of power

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    Emotional expressions can have a pervasive impact on bargaining behavior and outcomes. This widely documented phenomenon implies that in their communications, bargainers may adjust their apparent emotions. In the current paper, we developed a paradigm to study the communication of anger and disappointment, two of the most commonly experienced emotions in bargaining. The results of three experiments show that bargainers often adjust the intensity of their emotions in their communicated emotions. The findings show a differentiated pattern, revealing that bargainers rather exaggerate their disappointment than their anger, especially when the target of their communication is in a high power position. The results are discussed and related to the social functional approach of emotions

    Measurement-induced focusing and the magnitude of loss aversion:The difference between comparing gains to losses and losses to gains

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    Research has identified loss aversion as a strong and robust phenomenon, but has also revealed some moderators affecting the magnitude of its effect on decision making. In the current article, we draw attention to the fact that even the measurement of loss aversion itself may affect its magnitude by inducing a focus on either losses or gains. In three studies, we provide empirical evidence for such a measurement-induced focus. In all studies we used coin-toss gambles---in which there is a 50/50 chance to win or to lose---to assess gain/loss ratios as a measure of loss aversion. Participants either filled out the loss side or the gain side of this gain/loss ratio. The studies consistently showed that---using within- and between-subject designs and anticipated and real coin-toss gambles---the strength of loss aversion depended on the measurement format (fill-in-the-loss versus fill-in-the-gain); filling in the loss side increased loss aversion. Moreover, loss aversion was more affected by the stakes of the gamble in the fill-in-the-loss format than in the fill-in-the-gain format

    Sample size, lag order and critical values of seasonal unit root tests

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    This paper presents a response surface analysis for the distributions of the popular tests for seasonal unit roots in quarterly observed time series variables developed by Hylleberg et al. (1990). Approximate asymptotic distributions are obtained, and response surface coefficients for 1%-, 5%- and 10%-level critical values are reported, permitting simple computation of accurate critical values for any sample size and lag order. Five test statistics are considered, along with five different specifications of the deterministic component in the test regression; allowance is also made for the lag order to be determined endogenously, using commonly applied selection methods. Dependence of the critical values and the probability density functions on the sample size and lag order is also investigated
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