L'Impatto delle Condizioni Interne ed Esterne sul Ruolo del Cda : un'Analisi Empirica sulle Grandi Imprese Italiane [The impact of internal and external contingencies on board tasks performance : an empirical investigation of Italian companies]

Il Consiglio di Amministrazione (CdA) è il principale organo di governo delle aziende. La letteratura gli attribuisce tre ruoli: controllo, indirizzo strategico e collegamento con l’ambiente (networking). Precedenti studi empirici hanno analizzato se un Consiglio di Amministrazione è attivo o meno in tutti e tre i ruoli in un dato momento. Nel presente lavoro, invece, si propone un approccio «contingente» e si analizzano i ruoli svolti dal CdA al variare delle condizioni interne (aziende in crisi o di successo) ed esterne (aziende in settori competitivi o regolamentati).. L’indagine empirica è stata condotta su un campione di 301 imprese italiane di grandi dimensioni. I risultati supportano la tesi iniziale secondo cui le condizioni interne ed esterne incidono sul ruolo svolto dal CdA. In particolare i risultati evidenziano che il CdA non svolge sempre tutti e tre i ruoli nello stesso momento, ma esso si concentra sul ruolo o sui ruoli che assumono grande importanza nella situazione in cui si trova l’azienda. Con riferimento alle condizioni interne, nelle imprese in crisi il CdA è attivo in tutti e tre i ruoli, mentre in quelle di successo prevale un orientamento verso la funzione strategica. Nelle aziende che operano in settori competitivi il ruolo di controllo è più pressante mentre nei settori regolamentati prevale una funzione di networking.

Forecasting negative effects of monotony and sensation seeking on performance during a vigilance task

The driving task requires sustained attention during prolonged periods, and can be performed in highly predictable or repetitive environments. Such conditions could create hypovigilance and impair performance towards critical events. Identifying such impairment in monotonous conditions has been a major subject of research, but no research to date has attempted to predict it in real-time. This pilot study aims to show that performance decrements due to monotonous tasks can be predicted through mathematical modelling taking into account sensation seeking levels. A short vigilance task sensitive to short periods of lapses of vigilance called Sustained Attention to Response Task is used to assess participants‟ performance. The framework for prediction developed on this task could be extended to a monotonous driving task. A Hidden Markov Model (HMM) is proposed to predict participants‟ lapses in alertness. Driver‟s vigilance evolution is modelled as a hidden state and is correlated to a surrogate measure: the participant‟s reactions time. This experiment shows that the monotony of the task can lead to an important decline in performance in less than five minutes. This impairment can be predicted four minutes in advance with an 86% accuracy using HMMs. This experiment showed that mathematical models such as HMM can efficiently predict hypovigilance through surrogate measures. The presented model could result in the development of an in-vehicle device that detects driver hypovigilance in advance and warn the driver accordingly, thus offering the potential to enhance road safety and prevent road crashes.

Public-private partnerships in the promotion of sport and well-being : a governance model

This research focuses on exploring the links between sport, Indigenous self determination and deeper engagement within mainstream Australia especially with regard to the issue of promoting healthy lifestyles and the role of governance, through sport governance. Against all social, economic and health criteria Indigenous Australians are disadvantaged – despite government attention and financial input. It is well understood that education is a basis to better health, employment and lifestyle (Furneaux and Brown, 2008). However, many of the issues confronting Indigenous people have not responded to conventional government approaches based on program development and policy initiatives from single organisations (Ryan et al 2006). As a consequence, new approaches that both tap into the specific interests of Indigenous people and better engage them in the process of governance are required. The case material of the research focuses on the Australian Football League (AFL) Kickstart program.

Use of lifts and refuge floors for fire evacuation in high rise apartment buildings

If current population and accommodation trends continue, Australian cities will, in the future, have noticeable numbers of apartment buildings over 60 storeys high. With an aging population it follows that a significant proportion of those occupying these buildings will be senior citizens, many of whom will have some form of disability. For these occupants a fire emergency in a high rise building presents a serious problem. Currently lifts cannot be used for evacuation and going down 60 storeys in a fire isolated staircase would be physically impossible for many. Therefore, for many, the temptation to remain in one’s unit will be very strong. With an awareness of this behaviour trend in older residents, many researchers have, in recent years, explored the possible wider use of lifts in a fire emergency. So far the use of lifts for evacuation has been approved for a small number of buildings but wide acceptance of this solution is still to be achieved. This paper concludes that even in high-rise apartment buildings where lifts are approved for evacuation, architects should design the building with alternative evacuation routes and provide suitable safe refuge areas for those who cannot use the stairs when the lifts are unavailable.

The use of ZIP and CART to model cryptosporidiosis in relation to climatic variables

This research assesses the potential impact of weekly weather variability on the incidence of cryptosporidiosis disease using time series zero-inflated Poisson (ZIP) and classification and regression tree (CART) models. Data on weather variables, notified cryptosporidiosis cases and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Both time series ZIP and CART models show a clear association between weather variables (maximum temperature, relative humidity, rainfall and wind speed) and cryptosporidiosis disease. The time series CART models indicated that, when weekly maximum temperature exceeded 31°C and relative humidity was less than 63%, the relative risk of cryptosporidiosis rose by 13.64 (expected morbidity: 39.4; 95% confidence interval: 30.9–47.9). These findings may have applications as a decision support tool in planning disease control and risk management programs for cryptosporidiosis disease.

The impacts of traffic and rainfall characteristics on heavy metals build-up and wash-off from urban roads

An investigation into the effects of changes in urban traffic characteristics due to rapid urbanisation and the predicted changes in rainfall characteristics due to climate change on the build-up and wash-off of heavy metals was carried out in Gold Coast, Australia. The study sites encompassed three different urban land uses. Nine heavy metals commonly associated with traffic emissions were selected. The results were interpreted using multivariate data analysis and decision making tools, such as principal component analysis (PCA), fuzzy clustering (FC), PROMETHEE and GAIA. Initial analyses established high, low and moderate traffic scenarios as well as low, low to moderate, moderate, high and extreme rainfall scenarios for build-up and wash-off investigations. GAIA analyses established that moderate to high traffic scenarios could affect the build-up while moderate to high rainfall scenarios could affect the wash-off of heavy metals under changed conditions. However, in wash-off, metal concentrations in 1-75µm fraction were found to be independent of the changes to rainfall characteristics. In build-up, high traffic activities in commercial and industrial areas influenced the accumulation of heavy metal concentrations in particulate size range from 75 - >300 µm, whereas metal concentrations in finer size range of <1-75 µm were not affected. As practical implications, solids <1 µm and organic matter from 1 - >300 µm can be targeted for removal of Ni, Cu, Pb, Cd, Cr and Zn from build-up whilst organic matter from <1 - >300 µm can be targeted for removal of Cd, Cr, Pb and Ni from wash-off. Cu and Zn need to be removed as free ions from most fractions in wash-off.

The role of bricolage and resource constraints in high potential sustainability ventures

Sustainability decisions and their impacts may be among the greatest challenges facing the world in the 21st century (Davos 2000). Apart from adaptation on the part of established organizations these challenges are arguably going to require solutions developed by new actors However, young ventures have only recently begun generating research interest within sustainability literature (Shepherd et al. 2009). In particular, little is known about resource behaviours of these ventures and how they adapt to substantial resource constraints. One promising theory that has been identified as a way that some entrepreneurs manage constraints is bricolage: a construct defined as “making do by applying combinations of the resources at hand to new problems and opportunities” (Baker and Nelson 2005: 333). Bricolage may be critical as the means of continued venture success as these ventures are frequently developed in severe resource constraint, owing to higher levels of technical sophistication (Rothaermel and Deeds 2006). Further, they are often developed by entrepreneurs committed to personal and social goals of resourcefulness, including values that focus on conservation rather than consumption of resources (Shepherd et al. 2009). In this paper, using seven novel cases of high potential sustainability firms from CAUSEE we consider how constraints impact resource behaviours and further illustrate and extend bricolage domains previously developed by Baker and Nelson (2005) with recommendations for theory and practice provided.

When sparks fly : developing formal mentoring programs for the career development of young and emerging artists

Formal mentoring programs are accepted as a valuable strategy for developing young and emerging artists. This thesis presents the results of an evaluation of the SPARK National Young Artists Mentoring Program (SPARK). SPARK was a ten-month formal mentoring program managed by Youth Arts Queensland (YAQ) on behalf of the Australia Council for the Arts from 2003-2009. The program aimed to assist young and emerging Australian artists between the ages of 18-26 to establish a professional career in the arts. It was a highly successful formal arts mentoring program that facilitated 58 mentorships between young and emerging artists and professional artists from across Australia in five program rounds over its seven year lifespan. Interest from other cultural organisations looking to develop their own formal mentoring programs encouraged YAQ to commission this research to determine how the program works to achieve its effects. This study was conducted with young and emerging artists who participated in SPARK from 2003 to 2008. It took a theory-driven evaluation approach to examine SPARK as an example of what makes formal arts mentoring programs effective. It focused on understanding the program’s theory or how the program worked to achieve its desired outcomes. The program activities and assumed responses to program activities were mapped out in a theories of change model. This theoretical framework was then used to plan the points for data collection. Through the process of data collection, actual program developments were compared to the theoretical framework to see what occurred as expected and what did not. The findings were then generalised for knowledge and wider application. The findings demonstrated that SPARK was a successful and effective program and an exemplar model of a formal mentoring program preparing young and emerging artists for professional careers in the arts. They also indicate several ways in which this already strong program could be further improved, including: looking at the way mentoring relationships are set up and how the mentoring process is managed; considering the balance between artistic and professional development; developing career development competencies and networking skills; taking into account the needs of young and emerging artists to develop their professional identity and build confidence; and giving more thought to the desired program outcomes and considering the issue of timeliness and readiness for career transition. From these findings, together with principles outlined in the mentoring and career development literature, a number of necessary conditions have been identified for developing effective mentoring programs in the career development of young and emerging artists.

Impacts and adaptation response of infrastructure and communities to heatwaves : the southern Australian experience of 2009

From 27 January to 8 February during the summer of 2009, southern Australia experienced one of the nation‘s most severe heatwaves. Governments, councils, utilities, hospitals and emergency response organisations and the community were largely underprepared for an extreme event of this magnitude. This case study targets the experience and challenges faced by decision makers and policy makers and focuses on the major metropolitan areas affected by the heatwave — Melbourne and Adelaide. The study examines the 2009 heatwave‘s characteristics; its impacts (on human health, infrastructure and human services); the degree of adaptive capacity (vulnerability and resilience) of various sectors, communities and individuals; and the reactive responses of government and emergency and associated services and their effectiveness. Barriers and challenges to adaptation and increasing resilience are also identified and further areas for research are suggested. This study does not include details of the heatwave‘s effects beyond Victoria and South Australia, or its economic impacts, or of Victoria‘s 'Black Saturday‘ bushfires.

The shaping of midlife women's views of health and health behaviors

The menopausal transition is a marker of aging for women and a time when health professionals urge women to prevent disease. In this research we adopted a constructivist, inductive approach in exploring how and why midlife women think about health in general, about being healthy, and about factors that influence engaging in healthy behaviors. The sample constituted 23 women who had participated in a women’s wellness program intervention trial and subsequent interviews. The women described lives of healthy eating and exercise, yet, their perceptions of health and healthy behavior at midlife contradicted that history. Midlife was associated with risk and guilt at not doing enough to be healthy. Health professionals provided a very limited frame within which to judge what is healthy. Mostly this was left up to individual women. Those who were successful framed health as “being able to do what you want to do when you want to do it.” In this article we present study findings of how meanings attached to health and being healthy were constructed through social expectations, family relationships, and life experiences.

Impact of zooming and enhancing Region of Interests for optimizing user experience on mobile sports video

In mobile videos, small viewing size and bitrate limitation often cause unpleasant viewing experiences, which is particularly important for fast-moving sports videos. For optimizing the overall user experience of viewing sports videos on mobile phones, this paper explores the benefits of emphasizing Region of Interest (ROI) by 1) zooming in and 2) enhancing the quality. The main goal is to measure the effectiveness of these two approaches and determine which one is more effective. To obtain a more comprehensive understanding of the overall user experience, the study considers user’s interest in video content and user’s acceptance of the perceived video quality, and compares the user experience in sports videos with other content types such as talk shows. The results from a user study with 40 subjects demonstrate that zooming and ROI-enhancement are both effective in improving the overall user experience with talk show and mid-shot soccer videos. However, for the full-shot scenes in soccer videos, only zooming is effective while ROI-enhancement has a negative effect. Moreover, user’s interest in video content directly affects not only the user experience and the acceptance of video quality, but also the effect of content type on the user experience. Finally, the overall user experience is closely related to the degree of the acceptance of video quality and the degree of the interest in video content. This study is valuable in exploiting effective approaches to improve user experience, especially in mobile sports video streaming contexts, whereby the available bandwidth is usually low or limited. It also provides further understanding of the influencing factors of user experience.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

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.

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.