Surveillance, Security and Sporting Mega Events: Toward a Research Agenda on the Organisation of Security Networks

Surveillance and security at sports mega events have been the subject of considerable scholarly attention. Events such as the Olympic Games and Fédération Internationale de Football Association (FIFA) World Cups have become occasions of almost unparalleled economic, political and social significance. In the lead up to the London 2012 Olympic Games, scholars have examined issues such as the ‘security legacies’ of sports mega events, the infrastructures and technologies used in an attempt to secure these events, and the planning mentalities underpinning the staggering ‘security spectacle’ of these globally televised events. This paper deals with the subject of how surveillance and security practices at sports mega events are organised. It uses the emerging paradigm of ‘security networks’ to call attention to some important issues involving the entire ‘security assemblage’ that accompanies these mega events. The paper presents five levels of analysis—structural, cultural, policy, technological and relational—to examine these practices and documents several key areas for further research on sports mega events.

Quantitatively evaluating the effects of price promotions using data mining

Price promotions (also called discount promotions), i.e. short-term temporary price reductions for selected items (Hermann 1989), are frequently used in sales promotions. The main objective of price promotions is to boost sales and increase profits. Quantitative evaluation of the effects of price promotions (QEEPP) is essential and important for sales managers to analyse historical price promotions and informative for devising more effective promotional strategies in the future. However, most previous studies only provide insights into the effects of discount promotions from some specific prospectives, and no approaches have been proposed for comprehensive evaluation of the effects of discount promotions. For example, Hinkle [1965] discovered that price promotions in the off-season are more favourable, and the effects of price promotions are stronger for new products. Peckham [1973] found that price promotions have no impact on long-term trend. Blattberg et al. [1978] identified that different segments respond to price promotions in different ways. Rockney [1991] discovered three basic types of effects: effects on discounted items, effects on substitutes and effects on complementary items.

Auditor industry specialisation, service bundling and partner effects in a mining-dominated city

This study examines auditor industry specialisation effects in Perth, a remote mining town in Australia characterised by a large number of small, homogeneous firms. We consider the impact of leadership by the non-Big 4 auditor BDO Kendalls (BDO) for a sample of 371 mining development stage entities (MDSE's). After controlling for factors known to determine audit fees, we find no evidence of auditor industry leadership fee premiums accruing to (BDO), a result robust to a range of sensitivity tests including the broadening of tests Australia-wide. However, when the dependent variable is redefined to the total 'bundle' of services provided by the audit firm (including audit and non-audit fees), the industry leader is shown to earn a fee premium suggesting BDO uses audits as a conduit to supply higher margin non-audit services. Our findings suggest that strategic pricing by industry leaders may not be confined to Big 4 firms.

A data mining framework for electricity consumption analysis from meter data

This paper presents a novel data mining framework for the exploration and extraction of actionable knowledge from data generated by electricity meters. Although a rich source of information for energy consumption analysis, electricity meters produce a voluminous, fast-paced, transient stream of data that conventional approaches are unable to address entirely. In order to overcome these issues, it is important for a data mining framework to incorporate functionality for interim summarization and incremental analysis using intelligent techniques. The proposed Incremental Summarization and Pattern Characterization (ISPC) framework demonstrates this capability. Stream data is structured in a data warehouse based on key dimensions enabling rapid interim summarization. Independently, the IPCL algorithm incrementally characterizes patterns in stream data and correlates these across time. Eventually, characterized patterns are consolidated with interim summarization to facilitate an overall analysis and prediction of energy consumption trends. Results of experiments conducted using the actual data from electricity meters confirm applicability of the ISPC framework.

A data mining approach for detection of self-propagating worms

In this paper we demonstrate our signature based detector for self-propagating worms. We use a set of worm and benign traffic traces of several endpoints to build benign and worm profiles. These profiles were arranged into separate n-ary trees. We also demonstrate our anomaly detector that was used to deal with tied matches between worm and benign trees. We analyzed the performance of each detector and also with their integration. Results show that our signature based detector can detect very high true positive. Meanwhile, the anomaly detector did not achieve high true positive. Both detectors, when used independently, suffer high false positive. However, when both detectors were integrated they maintained a high detection rate of true positive and minimized the false positive

What do indigenous communities think of the CSR practices of mining companies?

This paper examines how one indigenous community in the Western Province of Papua New Guinea (PNG) views the social responsibility initiatives of OK Tedi Mining Ltd (OTML). This mining operation has been controversial since its inception, and various operators of the mine have sought to engage the community and to undertake a number of CSR-related projects. Insights gained from four focus groups amongst the Ok Tedi River indigenous communities show that while some members of the community are satisfied with the company’s efforts at the macro level, many have reservations about the effectiveness of the programs at the micro level on the village and family unit. The implementation of CSR activities are slow and in many instances do not effectively address stakeholder concerns.

Efficient mining of top-k breaker emerging subgraph patterns from graph datasets

This paper introduces a new type of discriminative subgraph pattern called breaker emerging subgraph pattern by introducing three constraints and two new concepts: base and breaker. A breaker emerging sub-graph pattern consists of three subpatterns: a con-strained emerging subgraph pattern, a set of bases and a set of breakers. An efficient approach is pro-posed for the discovery of top-k breaker emerging sub-graph patterns from graph datasets. Experimental re-sults show that the approach is capable of efficiently discovering top-k breaker emerging subgraph patterns from given datasets, is more efficient than two previ-ous methods for mining discriminative subgraph pat-terns. The discovered top-k breaker emerging sub-graph patterns are more informative, more discrim-inative, more accurate and more compact than the minimal distinguishing subgraph patterns. The top-k breaker emerging patterns are more useful for sub-structure analysis, such as molecular fragment analy-sis. © 2009, Australian Computer Society, Inc.

Mega-events and mega-profits: Unravelling the Vancouver 2010 security–development nexus

Academic and political commentators have commonly sought to understand the Olympics as a cultural dynamic, a "spectacle" that motivates certain actors to project their relative interests in localized spaces and as well on a global scale (Hiller 2006; Boyle and Haggerty 2009b ). Mega-events, as this argument goes, are monumental cultural events (Roche 2000) that rely on the audacity of spectacle to dramatize and condition the cultural, political, legal and economic landscape. Extending these insights into surveillance studies, Boyle and Haggerty (2009b: 259-260) position spectacle and the disciplinary mechanisms of anxieties associated with mega-events to explain the risk management practices of security planners. The dynamic social implications of the spectacle condition dramatic regimes of securitization and surveillance such that sovereign power emanates from the production and consumption of spectacle. In similar fashion Vida Bajc (2007: 1648) writes that security meta-rituals "demonstrate[s] that the process of transformation of [the] public space [of mega-events] from one of routine of daily life into a sterile area [that] has a ritual form [that] .... separates insiders from outsiders and brings about a new socio-political reality." Put another way, the "security-meta ritual" legitimates security and surveillance practices by normalizing the social hierarchies it imposes. Bajc focuses on the over-determination of dividing practices in mega-event security, but the signifying practices associated with capital are absent (perhaps due to her empirical focus on presidential addresses). Klauser (2008: 181) links commercialization and mechanisms of surveillance, but only by foregrounding the significance of "neutralized space" created by granting absolute commercial rights to event sponsors. Neoliberalprivatization and its articulation with security and surveillance, however, cannot be reduced to control over sponsorship rights and consumptive practices in particular urban "zones," nor can it be limited by the methodological temporality of the event itself.

Charismatic marine mega-fauna: some recent discoveries and future challenges

 The last 20 years have been exciting times for scientists working with charismatic marine mega-fauna. Here recent advances are reviewed. There have been advances in both data gathering and data-analysis techniques that have allowed new insights into the physiological and behavioural ecology of free-ranging mega-faunal species; some marine mega-faunal species have now become model organisms for cutting edge approaches to identify the underlying mathematical properties of animal search patterns and hence the underlying behavioural processes (e.g. Levy flight versus Brownian motion); the implications of climate change have started to become more apparent with extended time-series of animal movements, abundance and performance; conservation issues have become integrated into marine planning and have resulted in the advent of extended networks of marine protected areas (MPAs) as well as large MPAs that span many 100,000 km2; and collaborative crossdisciplinary teams have started to reveal the importance of ocean currents in animal dispersal, the ontogeny of migration and population genetic structure. Looking to the future, increased data availability (e.g. through data sharing) will likely allow more holistic across-taxa analyses to become routine.
© 2013 Elsevier B.V. All rights reserved.

Mining streams of short text for analysis of world-wide event evolutions

Streams of short text, such as news titles, enable us to effectively and efficiently learn the real world events that occur anywhere and anytime. Short text messages that are companied by timestamps and generally brief events using only a few words differ from other longer text documents, such as web pages, news stories, blogs, technical papers and books. For example, few words repeat in the same news titles, thus frequency of the term (i.e., TF) is not as important in short text corpus as in longer text corpus. Therefore, analysis of short text faces new challenges. Also, detecting and tracking events through short text analysis need to reliably identify events from constant topic clusters; however, existing methods, such as Latent Dirichlet Allocation (LDA), generates different topic results for a corpus at different executions. In this paper, we provide a Finding Topic Clusters using Co-occurring Terms (FTCCT) algorithm to automatically generate topics from a short text corpus, and develop an Event Evolution Mining (EEM) algorithm to discover hot events and their evolutions (i.e., the popularity degrees of events changing over time). In FTCCT, a term (i.e., a single word or a multiple-words phrase) belongs to only one topic in a corpus. Experiments on news titles of 157 countries within 4 months (from July to October, 2013) demonstrate that our FTCCT-based method (combining FTCCT and EEM) achieves far higher quality of the event's content and description words than LDA-based method (combining LDA and EEM) for analysis of streams of short text. Our method also visualizes the evolutions of the hot events. The discovered world-wide event evolutions have explored some interesting correlations of the world-wide events; for example, successive extreme weather phenomenon occur in different locations - typhoon in Hong Kong and Philippines followed hurricane and storm flood in Mexico in September 2013. © 2014 Springer Science+Business Media New York.