123 resultados para QUESTION MARK EARS
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Question: How parallel is adaptive evolution when it occurs from different genetic backgrounds? Background: Divergent evolutionary lineages of several post-glacial fish species including the threespine stickleback are found together in Ireland. Goals: To investigate the morphological diversity of stickleback populations in Ireland and assess whether morphology evolved in parallel between evolutionary lineages. Methods: We sampled stickleback from lake, river, and coastal habitats across Ireland. Microsatellite and mitochondrial DNA data revealed evolutionary history. Geometric morphometrics and linear trait measurements characterized morphology. We used a multivariate approach to quantify parallel and non-parallel divergence within and between lineages. Results: Repeated evolution of similar morphologies in similar habitats occurred across Ireland, concordant with patterns observed elsewhere in the stickleback distribution. A strong pattern of habitat-specific morphology existed even among divergent lineages. Furthermore, a strong signal of shared morphological divergence occurred along a marine-freshwater axis. Evidently, deterministic natural selection played a more important role in driving freshwater adaptation than independent evolutionary history. © 2013 Mark Ravinet.
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Older adults face important risky decisions about their health, their financial future, and their social environment. We examine age differences in risk-taking behaviors in multiple risk domains across the adult life span.
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There has long been substantial interest in understanding consumer food choices, where a key complexity in this context is the potentially large amount of heterogeneity in tastes across individual consumers, as well as the role of underlying attitudes towards food and cooking. The present paper underlines that both tastes and attitudes are unobserved, and makes the case for a latent variable treatment of these components. Using empirical data collected in Northern Ireland as part of a wider study to elicit intra-household trade-offs between home-cooked meal options, we show how these latent sensitivities and attitudes drive both the choice behaviour as well as the answers to supplementary questions. We find significant heterogeneity across respondents in these underlying factors and show how incorporating them in our models leads to important insights into preferences.
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Ear recognition, as a biometric, has several advantages. In particular, ears can be measured remotely and are also relatively static in size and structure for each individual. Unfortunately, at present, good recognition rates require controlled conditions. For commercial use, these systems need to be much more robust. In particular, ears have to be recognized from different angles ( poses), under different lighting conditions, and with different cameras. It must also be possible to distinguish ears from background clutter and identify them when partly occluded by hair, hats, or other objects. The purpose of this paper is to suggest how progress toward such robustness might be achieved through a technique that improves ear registration. The approach focuses on 2-D images, treating the ear as a planar surface that is registered to a gallery using a homography transform calculated from scale-invariant feature-transform feature matches. The feature matches reduce the gallery size and enable a precise ranking using a simple 2-D distance algorithm. Analysis on a range of data sets demonstrates the technique to be robust to background clutter, viewing angles up to +/- 13 degrees, and up to 18% occlusion. In addition, recognition remains accurate with masked ear images as small as 20 x 35 pixels.
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Recent work suggests that the human ear varies significantly between different subjects and can be used for identification. In principle, therefore, using ears in addition to the face within a recognition system could improve accuracy and robustness, particularly for non-frontal views. The paper describes work that investigates this hypothesis using an approach based on the construction of a 3D morphable model of the head and ear. One issue with creating a model that includes the ear is that existing training datasets contain noise and partial occlusion. Rather than exclude these regions manually, a classifier has been developed which automates this process. When combined with a robust registration algorithm the resulting system enables full head morphable models to be constructed efficiently using less constrained datasets. The algorithm has been evaluated using registration consistency, model coverage and minimalism metrics, which together demonstrate the accuracy of the approach. To make it easier to build on this work, the source code has been made available online.
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Significant recent progress has shown ear recognition to be a viable biometric. Good recognition rates have been demonstrated under controlled conditions, using manual registration or with specialised equipment. This paper describes a new technique which improves the robustness of ear registration and recognition, addressing issues of pose variation, background clutter and occlusion. By treating the ear as a planar surface and creating a homography transform using SIFT feature matches, ears can be registered accurately. The feature matches reduce the gallery size and enable a precise ranking using a simple 2D distance algorithm. When applied to the XM2VTS database it gives results comparable to PCA with manual registration. Further analysis on more challenging datasets demonstrates the technique to be robust to background clutter, viewing angles up to +/- 13 degrees and with over 20% occlusion.
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This text critically reflects on the higher education public engagement training program, entitled ‘Big Ears – sonic art for public ears’. The authors detail the objectives and aims as well as the benefits of this initiative for the enhancement of the student learning experience. We consider Schmidt’s (Schmidt, 2012) notion of mis-listening and Christopher Small’s concept of ‘musicking’ (Small, 1998), and develop a critical argument on how public engagement has changed researchers’ views and attitudes about their own research. The text explores how the creative interaction with a young audience has had great impact on the students’ learning experience as well as on their employability/transferable skills, because Big Ears stresses the importance of pulling practice as research away from the academic argument of why artists should be supported inside an institution, and into the realm of the real – what to do when making art, how to make it relevant and applicable to audiences.
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This paper explores the production and post-production techniques and tensions in designing sound for film. Considering the films of Lucrecia Martel and Sofia Coppola, amongst others, Greene and Yang will discuss how the soundtrack takes on a primary role in these films and becomes a medium for symbolism, reflection, characterisation, as well as storytelling. There will be a close examination of the processes involved in creating character-orientated soundscapes. These processes are sensitive to the effects sound has on an audience. Exploring how these filmmakers (with their sound teams) utilise the listening experience, including attention to point of audition and sound perception, this paper will critically unpick how such creative decisions are arrived at during various stages of the production process. Outlining the use of diegetic and non-diegetic sound and the potential musicality of sound effect design, issues of reverberation, noise and intent are discussed to highlight the sonic framing of these creative teams. Greene will approach these soundtracks from a production/post-production perspective, while Yang will explore the composer’s/designer’s ear.
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