Bimodal biometric verification based on face and lips

In this paper, we present a novel approach to person verification by fusing face and lip features. Specifically, the face is modeled by the discriminative common vector and the discrete wavelet transform. Our lip features are simple geometric features based on a lip contour, which can be interpreted as multiple spatial widths and heights from a center of mass. In order to combine these features, we consider two simple fusion strategies: data fusion before training and score fusion after training, working with two different face databases. Fusing them together boosts the performance to achieve an equal error rate as low as 0.4% and 0.28%, respectively, confirming that our approach of fusing lips and face is effective and promising.

Does the freshwater pearl mussel, Margaritifera margaritifera L., face extinction in Northern Ireland?

1. Until recently the status of Margaritifera margaritifera L. in Northern Ireland was not well documented. This paper presents the results of field surveys conducted in 1990/'91 and in 1996 at over 200 sites covering all major river systems in Northern Ireland. 2.Margaritifera populations in Northern Ireland were recorded at just 20 sites mainly located in the west of the province. Formerly many rivers supported vast numbers of mussels but anecdotal evidence points to periods of major declines in mussel populations since the turn of the century. 3. The absence of mussels smaller than 30 mm in length at most sites suggests very little or no recruitment during the past decade. During the surveys, deteriorating water quality, habitat disturbance and pearl fishing were recorded and are the major causes of the decline of the freshwater pearl mussel in Northern Ireland. 4. Unless the above problems are alleviated in the very near future, M.margaritifera will probably become extinct in Northern Ireland. © 1998 John Wiley & Sons, Ltd.

Predicting community responses to perturbations in the face of imperfect knowledge and network complexity

How best to predict the effects of perturbations to ecological communities has been a long-standing goal for both applied and basic ecology. This quest has recently been revived by new empirical data, new analysis methods, and increased computing speed, with the promise that ecologically important insights may be obtainable from a limited knowledge of community interactions. We use empirically based and simulated networks of varying size and connectance to assess two limitations to predicting perturbation responses in multispecies communities: (1) the inaccuracy by which species interaction strengths are empirically quantified and (2) the indeterminacy of species responses due to indirect effects associated with network size and structure. We find that even modest levels of species richness and connectance (similar to 25 pairwise interactions) impose high requirements for interaction strength estimates because system indeterminacy rapidly overwhelms predictive insights. Nevertheless, even poorly estimated interaction strengths provide greater average predictive certainty than an approach that uses only the sign of each interaction. Our simulations provide guidance in dealing with the trade-offs involved in maximizing the utility of network approaches for predicting dynamics in multispecies communities.