The internet and the changing global media environment

This chapter describes current trends in the global media environment, with a focus on their implications for the management of public agendas and political processes. It assesses the extent to which trends such as the growth of the blogosphere, "citizen journalism," and other forms if user-generated content, have complicated and problematized news and agenda management as engaged in by both media and political elites. It argues that, in large part due to the rise of the internet and the proliferation if online producers of information and commentary, alongside 24-hour news channels such as CNN and Al Jazeera, political and social actors today face a much more complex, chaotic communication environment than ever bifore, an environment characterized as one of cultural chaos. Having outlined the roots of this trend in the emergence of an expanded, globalized public sphere, the chapter goes on to ask if elite control over the political agenda has been eroded, and if it has, what the consequences for governmmt and the exercise if power might be. Can authoritarian regimes in China, the Middle East, and elsewhere survive the onset if internet-fueled global journalism, for example? In a political environment where public opinion is driven and buffeted by news coverage if unprecedented speed and volume, can democratic governments retain sufficient control over decision- and policy-making processes to enable competent social administration al'ld political management? Can the citizens of contemporary democracies use the emerging media environment to enhance elite accountability and strengthen the democratic process? The chapter concludes that the changing global media environment has the potmtial to strengthen democratic processes, though there is no sil'lgle template for the impact of the internet and other new media on specific countries.

Introduction to special issue on what criminology can say about the war on terror

On 20 September 2001, the former US President, George W. Bush, declared what is now widely, and arguably infamously, known as a ‘war on terror’. In response to the fatal 9/11 attacks in New York and Washington, DC, President Bush identified the US military response as having far-reaching and long-lasting consequences. It was, he argued, ‘our war on terror’ that began ‘with al Qaeda, but … it will not end until every terrorist group of global reach has been found, stopped and defeated’ (CNN 2001). This was to be a war that would, in the words of former British Prime Minister, Tony Blair, seek to eliminate a threat that was ‘aimed at the whole democratic world’ (Blair 2001). Blair claimed that this threat is of such magnitude that unprecedented measures would need to be taken to uphold freedom and security. Blair would later admit that it was a war that ‘divided the country’ and was based on evidence ‘about Saddam having actual biological and chemical weapons, as opposed to the capability to develop them, has turned out to be wrong’ (Blair 2004). The failures of intelligence ushered in new political rhetoric in the form of ‘trust me’ because ‘instinct is no science’ (Blair 2004). The war on terror has been one of the most significant international events in the past three decades, alongside the collapse of the former Soviet Union, the end of apartheid in South Africa, the unification of Europe and the marketization of the People's Republic of China. Yet, unlike the other events, it will not be remembered for advancing democracy or sovereignty, but for the conviction politics of particular politicians who chose to dispense with international law and custom in pursuit of personal instincts that proved fatal. Since the invasions of Afghanistan in October 2001 and …

Construction of interstellar cumulenes and heterocumulenes : Mass spectrometric studies

The last few years have brought an increasing interest in the chemistry of rite interstellar and circumstellar environs. Many of the molecular species discovered in remote galactic regions have been dubbed 'non-terrestrial' because of their unique structures (Thaddeus et al, 1993). These findings have provided a challenge to chemists in many differing fields to attempt to generate these unusual species in the laboratory of particular recent interest have been the unsaturated hydrocarbon families, CnH and CnH2, which have been pursued by a number of diverse methodologies. A wine range of heterocumulenes, including CnO, HCnO, CnN, HCnN, CnS, HCnS, CnSi and HCnSi have also provided intriguing targets for laboratory experiments. Strictly the term cumulene refers to a class of compounds that possess a series of adjacent double bonds, with allene representing the simplest example (H2C=C=CH2). However for many of the non-terrestrial molecules presented here, the carbon chain cannot be described in terms of a single simple valence structure, and so we use the terms cumulene and heterocumulene in a more general sense: to describe molecular species that contain an unsaturated polycarbon chain. Mass spectrometry has proved an invaluable tool in the quest for interstellar cumulenes and heterocumulenes in the laboratory it has the ability in its many forms, to (i) generate charged analogs of these species in the gas phase, (ii) probe their connectivity, ion chemistry, and thermochemistry, and (iii) in some cases, elucidate the neutrals themselves. Here, we will discuss the progress of these studies to this time. (C) 1999 John Wiley & Sons, Inc.

Convolutional Neural Network-based place recognition

Recently Convolutional Neural Networks (CNNs) have been shown to achieve state-of-the-art performance on various classification tasks. In this paper, we present for the first time a place recognition technique based on CNN models, by combining the powerful features learnt by CNNs with a spatial and sequential filter. Applying the system to a 70 km benchmark place recognition dataset we achieve a 75% increase in recall at 100% precision, significantly outperforming all previous state of the art techniques. We also conduct a comprehensive performance comparison of the utility of features from all 21 layers for place recognition, both for the benchmark dataset and for a second dataset with more significant viewpoint changes.

Improving Near-Miss Event Detection Rate at Railway Level Crossings

Even though crashes between trains and road users are rare events at railway level crossings, they are one of the major safety concerns for the Australian railway industry. Nearmiss events at level crossings occur more frequently, and can provide more information about factors leading to level crossing incidents. In this paper we introduce a video analytic approach for automatically detecting and localizing vehicles from cameras mounted on trains for detecting near-miss events. To detect and localize vehicles at level crossings we extract patches from an image and classify each patch for detecting vehicles. We developed a region proposals algorithm for generating patches, and we use a Convolutional Neural Network (CNN) for classifying each patch. To localize vehicles in images we combine the patches that are classified as vehicles according to their CNN scores and positions. We compared our system with the Deformable Part Models (DPM) and Regions with CNN features (R-CNN) object detectors. Experimental results on a railway dataset show that the recall rate of our proposed system is 29% higher than what can be achieved with DPM or R-CNN detectors.

African Gamer: Whose Story Is It Anyway?

New Video Gamer: Africa Needs More Technology (CNN 12/12/2011) In December 2011 CNN news service online edition (Sutter, 2011) posted a short item about Cwi Nqane, a Khoisan man who entered Samsung’s Namibian World Cyber Games (WCG) heats held at the 2011 the annual Windhoek Show. Cwi Nqane won a place on the Namibian WCG team playing a smartphone game called Asphalt 6: Adrena-line (Gameloft, 2011). Cwi was presented with a ‘top of the line’ Samsung Galaxy tablet and subsequently sent to compete in Korea. Later, other news and game news websites re-reported the incident, which inspired a variety of enthusiastic comment about tech-nology and ‘new knowledge’. Then Kotaku news service picked up the item (Narcisse, 2011) and took a very different slant. Kotaku proposed that Samsung was exploiting Cwi and had assumed the role of a Techno-Tarzan: “striding into Nqane’s homeland and swinging him off into the wonders of the modern world where they can trot him out as a curiosity”. These two perspectives on the story of Cwi’s WCG entry expose two dominant views on Indigenous knowledges and technologies: ICTs as progress for in-digenous peoples and ICTs as disruptive and exploitative. Neither position, however, allows for the claiming of digital technology by indigenous communities, indeed both views position indigenous cultures as being outsiders.

Enhancing human action recognition with region proposals

Deep convolutional network models have dominated recent work in human action recognition as well as image classification. However, these methods are often unduly influenced by the image background, learning and exploiting the presence of cues in typical computer vision datasets. For unbiased robotics applications, the degree of variation and novelty in action backgrounds is far greater than in computer vision datasets. To address this challenge, we propose an “action region proposal” method that, informed by optical flow, extracts image regions likely to contain actions for input into the network both during training and testing. In a range of experiments, we demonstrate that manually segmenting the background is not enough; but through active action region proposals during training and testing, state-of-the-art or better performance can be achieved on individual spatial and temporal video components. Finally, we show by focusing attention through action region proposals, we can further improve upon the existing state-of-the-art in spatio-temporally fused action recognition performance.