Developing creativity and innovation in management education : an artful event for transformative learning

This paper argues that management education needs to consider a trend in learning design which advances more creative learning through an alliance with art-based pedagogical processes. A shift is required from skills training to facilitating transformational learning through experiences that expand human potential, facilitated by artistic processes. In this paper the authors discuss the necessity for creativity and innovation in the workplace and the need to develop better leaders and managers. The inclusion of arts-based processes enhances artful behaviour, aesthetics and creativity within management and organisational behaviour, generating important implications for business innovation. This creative learning focus stems from an analysis of an arts-based intervention for management development. Entitled Management Jazz the program was conducted over three years at a large Australian University. The paper reviews some of the salient literature in the field. It considers four stages of the learning process: capacity, artful event, increased capability, and application/action to produce product. One illustrative example of an arts-based learning process is provided from the Management Jazz program. Research findings indicate that artful learning opportunities enhance capacity for awareness of creativity in one’s self and in others. This capacity correlates positively with a perception that engaging in artful learning enhances the capability of managers in changing collaborative relationships and habitat constraint. The authors conclude that it is through engagement and creative alliance with the arts that management education can explore and discover artful approaches to building creativity and innovation. The illustration presented in this paper will be delivered as a brief workshop at the Fourth Art of Management Conference. The process of bricolage and articles at hand will be used to explore creative constraints and prototypes while generating group collaboration. The mini-workshop will conclude with discussion of the arts-based process and capability enhancement outcomes.

An event-based traffic flow model for traffic control at railway junctions

This paper introduces an event-based traffic model for railway systems adopting fixed-block signalling schemes. In this model, the events of trains' arrival at and departure from signalling blocks constitute the states of the traffic flow. A state transition is equivalent to the progress of the trains by one signalling block and it is realised by referring to past and present states, as well as a number of pre-calculated look-up tables of run-times in the signalling block under various signalling conditions. Simulation results are compared with those from a time-based multi-train simulator to study the improvement of processing time and accuracy.

Influence of historic land use change on the biosphere-atmosphere-exchange of C and N trace gases in the humid, subtropical region of Queensland

Increases in atmospheric concentrations of the greenhouse gases (GHGs) carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) due to human activities have been linked to climate change. GHG emissions from land use change and agriculture have been identified as significant contributors to both Australia’s and the global GHG budget. This is expected to increase over the coming decades as rates of agriculture intensification and land use change accelerate to support population growth and food production. Limited data exists on CO2, CH4 and N2O trace gas fluxes from subtropical or tropical soils and land uses. To develop effective mitigation strategies a full global warming potential (GWP) accounting methodology is required that includes emissions of the three primary greenhouse gases. Mitigation strategies that focus on one gas only can inadvertently increase emissions of another. For this reason, detailed inventories of GHGs from soils and vegetation under individual land uses are urgently required for subtropical Australia. This study aimed to quantify GHG emissions over two consecutive years from three major land uses; a well-established, unfertilized subtropical grass-legume pasture, a 30 year (lychee) orchard and a remnant subtropical Gallery rainforest, all located near Mooloolah, Queensland. GHG fluxes were measured using a combination of high resolution automated sampling, coarser spatial manual sampling and laboratory incubations. Comparison between the land uses revealed that land use change can have a substantial impact on the GWP on a landscape long after the deforestation event. The conversion of rainforest to agricultural land resulted in as much as a 17 fold increase in GWP, from 251 kg CO2 eq. ha-1 yr-1 in the rainforest to 889 kg CO2 eq. ha-1 yr-1 in the pasture to 2538 kg CO2 eq. ha-1 yr-1 in the lychee plantation. This increase resulted from altered N cycling and a reduction in the aerobic capacity of the soil in the pasture and lychee systems, enhancing denitrification and nitrification events, and reducing atmospheric CH4 uptake in the soil. High infiltration, drainage and subsequent soil aeration under the rainforest limited N2O loss, as well as promoting CH4 uptake of 11.2 g CH4-C ha-1 day-1. This was among the highest reported for rainforest systems, indicating that aerated subtropical rainforests can act as substantial sink of CH4. Interannual climatic variation resulted in significantly higher N2O emission from the pasture during 2008 (5.7 g N2O-N ha day) compared to 2007 (3.9 g N2O-N ha day), despite receiving nearly 500 mm less rainfall. Nitrous oxide emissions from the pasture were highest during the summer months and were highly episodic, related more to the magnitude and distribution of rain events rather than soil moisture alone. Mean N2O emissions from the lychee plantation increased from an average of 4.0 g N2O-N ha-1 day-1, to 19.8 g N2O-N ha-1 day-1 following a split application of N fertilizer (560 kg N ha-1, equivalent to 1 kg N tree-1). The timing of the split application was found to be critical to N2O emissions, with over twice as much lost following an application in spring (emission factor (EF): 1.79%) compared to autumn (EF: 0.91%). This was attributed to the hot and moist climatic conditions and a reduction in plant N uptake during the spring creating conditions conducive to N2O loss. These findings demonstrate that land use change in subtropical Australia can be a significant source of GHGs. Moreover, the study shows that modifying the timing of fertilizer application can be an efficient way of reducing GHG emissions from subtropical horticulture.

Survey of Spring Oats for Barley Yellow Dwarf Viruses in Illinois

During the spring of 1987, 1,215 samples of spring oats (Avena sativa L.) were collected in Madison, Champaign, Woodford, Warren, and DeKalb counties, Illinois. At each site on each of three sampling dates, 45 samples were collected (regardless of symptoms) in a W pattern in I ha and tested for the PAY, MAV, RPV, and RMV serotypes of barley yellow dwarf virus (BYDV) by direct doubleantibody sandwich enzyme-linked immunosorbent assay (ELISA). RMV was not detected at any location. PAY and RPV were detected at all locations, as early as 17 April in Champaign County. The incidences of P A V and RPV from all plants sampled ranged from 2 to 64% and from 2 to 88%, respectively. Highest incidences of both strains were in May samples [rom Woodford County. MAV was detected in lower incidences (2-16%) only in samples from the central region of the state (Champaign, Woodford, and Warren counties). The presence of MA V serotypes was confirmed in triple-antibody sandwich ELISA with the MA V -specific MAFF2 monoclonal antibody from L. Torrance. In the last previous survey for BYDV in Illinois during 1967-1968 (1), about 75% of the isolates were PAY and about 20% were RPV; single isolates of RMV and MAV were found. Twenty years later, 55% were PAY, 39% were RPV, and 6% were MAV.

Procuring Sydney’s Olympic Stadium : a world class event?

This paper describes and analyses the procurement processes employed in delivering the Sydney Olympic Stadium – arguably the most significant stadia project in the region today. This current high profile project is discussed in terms of a case study into the procurement processes used. Interviews, personal site visits and questionnaires were used to obtain information on the procurement processes used and comments on their application to the project. The alternative procurement process used on this project—Design and Construction within a Build, Own, Operate and Transfer (BOOT) project—is likely to impact on the construction industry as a whole. Already other projects and sectors are following this lead. Based on a series of on-site interviews and questionnaires, a series of benefits and drawbacks to this procurement strategy are provided.The Olympic Stadium project has also been further analysed during construction through a Degree of Interaction framework to determine anticipated project success. This analysis investigates project interaction and user satisfaction to provide a comparable rating. A series of questionnaires were used to collect data to calculate the Degree of Interaction and User Satisfaction ratings.

Parametric differences between a real-world distributed denial-of-service attack and a flash event

Distributed Denial-of-Service (DDoS) attacks continue to be one of the most pernicious threats to the delivery of services over the Internet. Not only are DDoS attacks present in many guises, they are also continuously evolving as new vulnerabilities are exploited. Hence accurate detection of these attacks still remains a challenging problem and a necessity for ensuring high-end network security. An intrinsic challenge in addressing this problem is to effectively distinguish these Denial-of-Service attacks from similar looking Flash Events (FEs) created by legitimate clients. A considerable overlap between the general characteristics of FEs and DDoS attacks makes it difficult to precisely separate these two classes of Internet activity. In this paper we propose parameters which can be used to explicitly distinguish FEs from DDoS attacks and analyse two real-world publicly available datasets to validate our proposal. Our analysis shows that even though FEs appear very similar to DDoS attacks, there are several subtle dissimilarities which can be exploited to separate these two classes of events.

Dynamic texture reconstruction from sparse codes for unusual event detection in crowded scenes

Unusual event detection in crowded scenes remains challenging because of the diversity of events and noise. In this paper, we present a novel approach for unusual event detection via sparse reconstruction of dynamic textures over an overcomplete basis set, with the dynamic texture described by local binary patterns from three orthogonal planes (LBPTOP). The overcomplete basis set is learnt from the training data where only the normal items observed. In the detection process, given a new observation, we compute the sparse coefficients using the Dantzig Selector algorithm which was proposed in the literature of compressed sensing. Then the reconstruction errors are computed, based on which we detect the abnormal items. Our application can be used to detect both local and global abnormal events. We evaluate our algorithm on UCSD Abnormality Datasets for local anomaly detection, which is shown to outperform current state-of-the-art approaches, and we also get promising results for rapid escape detection using the PETS2009 dataset.

Unusual Event Detection in Crowded Scenes Using Bag of LBPs in spatio-temporal patches

Modelling events in densely crowded environments remains challenging, due to the diversity of events and the noise in the scene. We propose a novel approach for anomalous event detection in crowded scenes using dynamic textures described by the Local Binary Patterns from Three Orthogonal Planes (LBP-TOP) descriptor. The scene is divided into spatio-temporal patches where LBP-TOP based dynamic textures are extracted. We apply hierarchical Bayesian models to detect the patches containing unusual events. Our method is an unsupervised approach, and it does not rely on object tracking or background subtraction. We show that our approach outperforms existing state of the art algorithms for anomalous event detection in UCSD dataset.

Planning volunteer responses to low-volume mass gatherings: do event characteristics predict patient workload?

INTRODUCTION: Workforce planning for first aid and medical coverage of mass gatherings is hampered by limited research. In particular, the characteristics and likely presentation patterns of low-volume mass gatherings of between several hundred to several thousand people are poorly described in the existing literature. OBJECTIVES: This study was conducted to: 1. Describe key patient and event characteristics of medical presentations at a series of mass gatherings, including events smaller than those previously described in the literature; 2. Determine whether event type and event size affect the mean number of patients presenting for treatment per event, and specifically, whether the 1:2,000 deployment rule used by St John Ambulance Australia is appropriate; and 3. Identify factors that are predictive of injury at mass gatherings. METHODS: A retrospective, observational, case-series design was used to examine all cases treated by two Divisions of St John Ambulance (Queensland) in the greater metropolitan Brisbane region over a three-year period (01 January 2002-31 December 2004). Data were obtained from routinely collected patient treatment forms completed by St John officers at the time of treatment. Event-related data (e.g., weather, event size) were obtained from event forms designed for this study. Outcome measures include: total and average number of patient presentations for each event; event type; and event size category. Descriptive analyses were conducted using chi-square tests, and mean presentations per event and event type were investigated using Kruskal-Wallis tests. Logistic regression analyses were used to identify variables independently associated with injury presentation (compared with non-injury presentations). RESULTS: Over the three-year study period, St John Ambulance officers treated 705 patients over 156 separate events. The mean number of patients who presented with any medical condition at small events (less than or equal to 2,000 attendees) did not differ significantly from that of large (>2,000 attendees) events (4.44 vs. 4.67, F = 0.72, df = 1, 154, p = 0.79). Logistic regression analyses indicated that presentation with an injury compared with non-injury was independently associated with male gender, winter season, and sporting events, even after adjusting for relevant variables. CONCLUSIONS: In this study of low-volume mass gatherings, a similar number of patients sought medical treatment at small (<2,000 patrons) and large (>2,000 patrons) events. This demonstrates that for low-volume mass gatherings, planning based solely on anticipated event size may be flawed, and could lead to inappropriate levels of first-aid coverage. This study also highlights the importance of considering other factors, such as event type and patient characteristics, when determining appropriate first-aid resourcing for low-volume events. Additionally, identification of factors predictive of injury presentations at mass gatherings has the potential to significantly enhance the ability of event coordinators to plan effective prevention strategies and response capability for these events.