Interview 1 on a big backyard

Interview with host Nick Renwick about the Boston Bombing and how Stony Brook Journalism School, New York, taught the media coverage in its aftermath.

Interview 2 on a big backyard

Interview about  the role of social media and 'trial by media' in current high profile cases involving child molestation charges against celebrities.

From little things, big things grow: trends and fads in 110 years of Australian ornithology

Publishing histories can reveal changes in ornithological effort, focus or direction through time. This study presents a bibliometric content analysis of Emu (1901–2011) which revealed 115 trends (long-term changes in publication over time) and 18 fads (temporary increases in publication activity) from the classification of 9,039 articles using 128 codes organised into eight categories (author gender, author affiliation, article type, subject, main focus, main method, geographical scale and geographical location). Across 110 years, private authorship declined, while publications involving universities and multiple institutions increased; from 1960, female authorship increased. Over time, question-driven studies and incidental observations increased and decreased in frequency, respectively. Single species and ‘taxonomic group’ subjects increased while studies of birds at specific places decreased. The focus of articles shifted from species distribution and activities of the host organisation to breeding, foraging and other biological/ecological topics. Site- and Australian-continental-scales slightly decreased over time; non-Australian studies increased from the 1970s. A wide variety of fads occurred (e.g. articles on bird distribution, 1942–1951, and using museum specimens, 1906–1913) though the occurrence of fads decreased over time. Changes over time are correlated with technological, theoretical, social and institutional changes, and suggest ornithological priorities, like those of other scientific disciplines, are temporally labile

A little movement orientated to the geomagnetic field makes a big difference in strong flows

Whilst a range of animals have been shown to respond behaviourally to components of the Earth’s magnetic field, evidence of the value of this sensory perception for small animals advected by strong flows (wind/ocean currents) is equivocal. We added geomagnetic directional swimming behaviour for North Atlantic loggerhead turtle hatchlings (Caretta caretta) into a high-resolution (1/4°) global general circulation ocean model to simulate 2,925-year-long hatchling trajectories comprising 355,875 locations. A little directional swimming (1–3 h per day) had a major impact on trajectories; simulated hatchlings travelled further south into warmer water. As a result, thermal elevation of hatchling metabolic rates was estimated to be between 63.3 and 114.5% after 220 days. We show that even small animals in strong flows can benefit from geomagnetic orientation and thus the potential implications of directional swimming for other taxa may be broad.

Desire, dryness and decadence: living big in Australia's suburbs

There are (at least!) two remarkable things about Australia: one is that it is the driest inhabited continent on the planet and the second that it has the largest houses in the world. The relationship between these two facts serves as one way of understanding its settlement patterns and the character of its suburbs, foregrounding the desires that underpin their cultural economies.

Mates and majors: how the big fish survived

In October this year, the Queensland Government slashed funding to small-to-medium sized arts organisations. In part two of a three-part investigation, Ben Eltham asks why the smaller players were targeted, while the major institutions were protected.

Classifying network traffic in the big data era

With the arrival of Big Data Era, properly utilizing the power of big data is becoming increasingly essential for the strength and competitiveness of businesses and organizations. We are facing grand challenges from big data from different perspectives, such as processing, communication, security, and privacy. In this talk, we discuss the big data challenges in network traffic classification and our solutions to the challenges. The significance of the research lies in the fact that each year the network traffic increase exponentially on the current Internet. Traffic classification has wide applications in network management, from security monitoring to quality of service measurements. Recent research tends to apply machine-learning techniques to flow statistical feature based classification methods. In this talk, we propose a series of novel approaches for traffic classification, which can improve the classification performance effectively by incorporating correlated information into the classification process. We analyze the new classification approaches and their performance benefit from both theoretical and empirical perspectives. A large number of experiments are carried out on two real-world traffic datasets to validate the proposed approach. The results show the traffic classification performance can be improved significantly even under the extreme difficult circumstance of very few training samples. Our work has significant impact on security applications.