Griffith University

About: Griffith University is a education organization based out in Brisbane, Queensland, Australia. It is known for research contribution in the topics: Population & Context (language use). The organization has 13830 authors who have published 49318 publications receiving 1420865 citations.

Fiji's Tourism Demand: The ARDL Approach to Cointegration

Abstract: This paper examines the short-run and long-run relationships between visitor arrivals in Fiji, real disposable incomes and relative hotel and substitute prices for the period 1970–2000, using coint...

Call dimensions : options and issues in computer-assisted language learning

Abstract: Preface. Introduction. Design. Evaluation. Computer-Mediated Communication. Theory. Research. Practice. Technology. Integration. Emergent and Established CALL. Appendices.

General Retinal Vessel Segmentation Using Regularization-Based Multiconcavity Modeling

Abstract: Detecting blood vessels in retinal images with the presence of bright and dark lesions is a challenging unsolved problem. In this paper, a novel multiconcavity modeling approach is proposed to handle both healthy and unhealthy retinas simultaneously. The differentiable concavity measure is proposed to handle bright lesions in a perceptive space. The line-shape concavity measure is proposed to remove dark lesions which have an intensity structure different from the line-shaped vessels in a retina. The locally normalized concavity measure is designed to deal with unevenly distributed noise due to the spherical intensity variation in a retinal image. These concavity measures are combined together according to their statistical distributions to detect vessels in general retinal images. Very encouraging experimental results demonstrate that the proposed method consistently yields the best performance over existing state-of-the-art methods on the abnormal retinas and its accuracy outperforms the human observer, which has not been achieved by any of the state-of-the-art benchmark methods. Most importantly, unlike existing methods, the proposed method shows very attractive performances not only on healthy retinas but also on a mixture of healthy and pathological retinas.

Precipitation drives global variation in natural selection.

Abstract: Climate change has the potential to affect the ecology and evolution of every species on Earth. Although the ecological consequences of climate change are increasingly well documented, the effects of climate on the key evolutionary process driving adaptation—natural selection—are largely unknown. We report that aspects of precipitation and potential evapotranspiration, along with the North Atlantic Oscillation, predicted variation in selection across plant and animal populations throughout many terrestrial biomes, whereas temperature explained little variation. By showing that selection was influenced by climate variation, our results indicate that climate change may cause widespread alterations in selection regimes, potentially shifting evolutionary trajectories at a global scale.