University of New South Wales

About: University of New South Wales is a education organization based out in Sydney, New South Wales, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 51197 authors who have published 153634 publications receiving 4880608 citations. The organization is also known as: UNSW & UNSW Australia.

Increasing aridity reduces soil microbial diversity and abundance in global drylands

Abstract: Soil bacteria and fungi play key roles in the functioning of terrestrial ecosystems, yet our understanding of their responses to climate change lags significantly behind that of other organisms. This gap in our understanding is particularly true for drylands, which occupy ∼41% of Earth´s surface, because no global, systematic assessments of the joint diversity of soil bacteria and fungi have been conducted in these environments to date. Here we present results from a study conducted across 80 dryland sites from all continents, except Antarctica, to assess how changes in aridity affect the composition, abundance, and diversity of soil bacteria and fungi. The diversity and abundance of soil bacteria and fungi was reduced as aridity increased. These results were largely driven by the negative impacts of aridity on soil organic carbon content, which positively affected the abundance and diversity of both bacteria and fungi. Aridity promoted shifts in the composition of soil bacteria, with increases in the relative abundance of Chloroflexi and α-Proteobacteria and decreases in Acidobacteria and Verrucomicrobia. Contrary to what has been reported by previous continental and global-scale studies, soil pH was not a major driver of bacterial diversity, and fungal communities were dominated by Ascomycota. Our results fill a critical gap in our understanding of soil microbial communities in terrestrial ecosystems. They suggest that changes in aridity, such as those predicted by climate-change models, may reduce microbial abundance and diversity, a response that will likely impact the provision of key ecosystem services by global drylands.

A measurement of the cosmological mass density from clustering in the 2dF Galaxy Redshift Survey

Abstract: The large-scale structure in the distribution of galaxies is thought to arise from the gravitational instability of small fluctuations in the initial density field of the Universe. A key test of this hypothesis is that forming superclusters of galaxies should generate a systematic infall of other galaxies. This would be evident in the pattern of recessional velocities, causing an anisotropy in the inferred spatial clustering of galaxies. Here we report a precise measurement of this clustering, using the redshifts of more than 141,000 galaxies from the two-degree-field (2dF) galaxy redshift survey. We determine the parameter β = Ω ^(0.6)/b = 0.43 ± 0.07, where Ω is the total mass-density parameter of the Universe and b is a measure of the 'bias' of the luminous galaxies in the survey. (Bias is the difference between the clustering of visible galaxies and of the total mass, most of which is dark.) Combined with the anisotropy of the cosmic microwave background, our results favour a low-density Universe with Ω ≈ 0.3.

The evaluation of Network Anomaly Detection Systems: Statistical analysis of the UNSW-NB15 data set and the comparison with the KDD99 data set

Abstract: Over the last three decades, Network Intrusion Detection Systems NIDSs, particularly, Anomaly Detection Systems ADSs, have become more significant in detecting novel attacks than Signature Detection Systems SDSs. Evaluating NIDSs using the existing benchmark data sets of KDD99 and NSLKDD does not reflect satisfactory results, due to three major issues: 1 their lack of modern low footprint attack styles, 2 their lack of modern normal traffic scenarios, and 3 a different distribution of training and testing sets. To address these issues, the UNSW-NB15 data set has recently been generated. This data set has nine types of the modern attacks fashions and new patterns of normal traffic, and it contains 49 attributes that comprise the flow based between hosts and the network packets inspection to discriminate between the observations, either normal or abnormal. In this paper, we demonstrate the complexity of the UNSW-NB15 data set in three aspects. First, the statistical analysis of the observations and the attributes are explained. Second, the examination of feature correlations is provided. Third, five existing classifiers are used to evaluate the complexity in terms of accuracy and false alarm rates FARs and then, the results are compared with the KDD99 data set. The experimental results show that UNSW-NB15 is more complex than KDD99 and is considered as a new benchmark data set for evaluating NIDSs.

An Underwater Color Image Quality Evaluation Metric

Abstract: Quality evaluation of underwater images is a key goal of underwater video image retrieval and intelligent processing. To date, no metric has been proposed for underwater color image quality evaluation (UCIQE). The special absorption and scattering characteristics of the water medium do not allow direct application of natural color image quality metrics especially to different underwater environments. In this paper, subjective testing for underwater image quality has been organized. The statistical distribution of the underwater image pixels in the CIELab color space related to subjective evaluation indicates the sharpness and colorful factors correlate well with subjective image quality perception. Based on these, a new UCIQE metric, which is a linear combination of chroma, saturation, and contrast, is proposed to quantify the non-uniform color cast, blurring, and low-contrast that characterize underwater engineering and monitoring images. Experiments are conducted to illustrate the performance of the proposed UCIQE metric and its capability to measure the underwater image enhancement results. They show that the proposed metric has comparable performance to the leading natural color image quality metrics and the underwater grayscale image quality metrics available in the literature, and can predict with higher accuracy the relative amount of degradation with similar image content in underwater environments. Importantly, UCIQE is a simple and fast solution for real-time underwater video processing. The effectiveness of the presented measure is also demonstrated by subjective evaluation. The results show better correlation between the UCIQE and the subjective mean opinion score.