How Novices Model Business Processes

In this paper, we examine the design of business process diagrams in contexts where novice analysts only have basic design tools such as paper and pencils available, and little to no understanding of formalized modeling approaches. Based on a quasi-experimental study with 89 BPM students, we identify five distinct process design archetypes ranging from textual to hybrid, and graphical representation forms. We also examine the quality of the designs and identify which representation formats enable an analyst to articulate business rules, states, events, activities, temporal and geospatial information in a process model. We found that the quality of the process designs decreases with the increased use of graphics and that hybrid designs featuring appropriate text labels and abstract graphical forms are well-suited to describe business processes. Our research has implications for practical process design work in industry as well as for academic curricula on process design.

Darjeeling, a Java compatible virtual machine for microcontrollers

The Java programming language enjoys widespread popularity on platforms ranging from servers to mobile phones. While efforts have been made to run Java on microcontroller platforms, there is currently no feature-rich, open source virtual machine available. In this paper we present Darjeeling, a system comprising offline tools and a memory efficient runtime. The offline post-compiler tool analyzes, links and consolidates Java class files into loadable modules. The runtime implements a modified Java VM that supports multithreading and is designed specifically to operate in constrained execution environments such as wireless sensor network nodes. Darjeeling improves upon existing work by supporting inheritance, threads, garbage collection, and loadable modules while keeping memory usage to a minimum. We have demonstrated Java running on AVR128 and MSP430 micro-controllers at speeds of up to 70,000 JVM instructions per second.

Experiments with underwater robot localization and tracking

This paper describes a novel experiment in which two very different methods of underwater robot localization are compared. The first method is based on a geometric approach in which a mobile node moves within a field of static nodes, and all nodes are capable of estimating the range to their neighbours acoustically. The second method uses visual odometry, from stereo cameras, by integrating scaled optical flow. The fundamental algorithmic principles of each localization technique is described. We also present experimental results comparing acoustic localization with GPS for surface operation, and a comparison of acoustic and visual methods for underwater operation.

Virtual fencing applications : Implementing and testing an automated cattle control system

Managing livestock movement in extensive systems has environmental and production benefits. Currently permanent wire fencing is used to control cattle; this is both expensive and inflexible. Cattle are known to respond to auditory and visual cues and we investigated whether these can be used to manipulate their behaviour. Twenty-five Belmont Red steers with a mean live weight of 270kg were each randomly assigned to one of five treatments. Treatments consisted of a combination of cues (audio, tactile and visual stimuli) and consequence (electrical stimulation). The treatments were electrical stimulation alone, audio plus electrical stimulation, vibration plus electrical stimulation, light plus electrical stimulation and electrified electric fence (6kV) plus electrical stimulation. Cue stimuli were administered for 3s followed immediately by electrical stimulation (consequence) of 1kV for 1s. The experiment tested the operational efficacy of an on-animal control or virtual fencing system. A collar-halter device was designed to carry the electronics, batteries and equipment providing the stimuli, including audio, vibration, light and electrical of a prototype virtual fencing device. Cattle were allowed to travel along a 40m alley to a group of peers and feed while their rate of travel and response to the stimuli were recorded. The prototype virtual fencing system was successful in modifying the behaviour of the cattle. The rate of travel of cattle along the alley demonstrated the large variability in behavioural response associated with tactile, visual and audible cues. The experiment demonstrated virtual fencing has potential for controlling cattle in extensive grazing systems. However, larger numbers of cattle need to be tested to derive a better understanding of the behavioural variance. Further controlled experimental work is also necessary to quantify the interaction between cues, consequences and cattle learning.

Animal Control - What constitutes a reliable cue to stop animal movement ?

Controlling free-ranging livestock requires low-stress cues to alter animal behaviour. Recently modulated sound and electric shock were demonstrated to be effective in controlling free-ranging cattle. In this study the behaviour of 60, 300 kg Belmont Red heifers were observed for behavioural changes when presented cues designed to impede their movement through an alley. The heifers were given an overnight drylot shrink off feed but not drinking water prior to being tested. Individual cattle were allowed to move down a 6.5 m wide alley towards a pen of peers and feed located 71 m from their point of release. Each animal was allowed to move through the alley unimpeded five times to establish a basal behavioural pattern. Animals were then randomly assigned to treatments consisting of sound plus shock, vibration plus shock, a visual cue plus shock, shock by itself and a control. The time each animal required to reach the pen of peers and feed was recorded. If the animal was prevented from reaching the pen of peers and feed by not penetrating through the cue barrier at set points along the alley for at least 60 sec the test was stopped and the animal was returned to peers located behind the release pen. Cues and shock were manually applied from a laptop while animals were observed from a 3.5 m tower located outside the alley. Electric shock, sound, vibration and Global Position System (GPS) hardware were housed in a neck collar. Results and implications will be discussed.

Monitoring and analysis of internet traffic targeting unused address spaces

Today’s evolving networks are experiencing a large number of different attacks ranging from system break-ins, infection from automatic attack tools such as worms, viruses, trojan horses and denial of service (DoS). One important aspect of such attacks is that they are often indiscriminate and target Internet addresses without regard to whether they are bona fide allocated or not. Due to the absence of any advertised host services the traffic observed on unused IP addresses is by definition unsolicited and likely to be either opportunistic or malicious. The analysis of large repositories of such traffic can be used to extract useful information about both ongoing and new attack patterns and unearth unusual attack behaviors. However, such an analysis is difficult due to the size and nature of the collected traffic on unused address spaces. In this dissertation, we present a network traffic analysis technique which uses traffic collected from unused address spaces and relies on the statistical properties of the collected traffic, in order to accurately and quickly detect new and ongoing network anomalies. Detection of network anomalies is based on the concept that an anomalous activity usually transforms the network parameters in such a way that their statistical properties no longer remain constant, resulting in abrupt changes. In this dissertation, we use sequential analysis techniques to identify changes in the behavior of network traffic targeting unused address spaces to unveil both ongoing and new attack patterns. Specifically, we have developed a dynamic sliding window based non-parametric cumulative sum change detection techniques for identification of changes in network traffic. Furthermore we have introduced dynamic thresholds to detect changes in network traffic behavior and also detect when a particular change has ended. Experimental results are presented that demonstrate the operational effectiveness and efficiency of the proposed approach, using both synthetically generated datasets and real network traces collected from a dedicated block of unused IP addresses.

Numerical simulation of axially loaded concrete columns under transverse impact and vulnerability assessment

With a view to assessing the vulnerability of columns to low elevation vehicular impacts, a non-linear explicit numerical model has been developed and validated using existing experimental results. The numerical model accounts for the effects of strain rate and confinement of the reinforced concrete, which are fundamental to the successful prediction of the impact response. The sensitivity of the material model parameters used for the validation is also scrutinised and numerical tests are performed to examine their suitability to simulate the shear failure conditions. Conflicting views on the strain gradient effects are discussed and the validation process is extended to investigate the ability of the equations developed under concentric loading conditions to simulate flexural failure events. Experimental data on impact force–time histories, mid span and residual deflections and support reactions have been verified against corresponding numerical results. A universal technique which can be applied to determine the vulnerability of the impacted columns against collisions with new generation vehicles under the most common impact modes is proposed. Additionally, the observed failure characteristics of the impacted columns are explained using extended outcomes. Based on the overall results, an analytical method is suggested to quantify the vulnerability of the columns.

Is length of experience an appropriate criterion to identify level of expertise?

Clinical experience plays an important role in the development of expertise, particularly when coupled with reflection on practice. There is debate, however, regarding the amount of clinical experience that is required to become an expert. Various lengths of practice have been suggested as suitable for determining expertise, ranging from five years to 15 years. This study aimed to investigate the association between length of experience and therapists’ level of expertise in the field of cerebral palsy with upper limb hypertonicity using an empirical procedure named Cochrane–Weiss–Shanteau (CWS). The methodology involved re-analysis of quantitative data collected in two previous studies. In Study 1, 18 experienced occupational therapists made hypothetical clinical decisions related to 110 case vignettes, while in Study 2, 29 therapists considered 60 case vignettes drawn randomly from those used in Study 1. A CWS index was calculated for each participant's case decisions. Then, in each study, Spearman's rho was calculated to identify the correlations between the duration of experience and level of expertise. There was no significant association between these two variables in both studies. These analyses corroborated previous findings of no association between length of experience and judgemental performance. Therefore, length of experience may not be an appropriate criterion for determining level of expertise in relation to cerebral palsy practice.

A quasi-stationary approach to drying kinetics of different shaped food particulates in a heat pump assisted by fluid bed dryer

Experiments were undertaken to study drying kinetics of different shaped moist food particulates during heat pump assisted fluidised bed drying. Three particular geometrical shapes of parallelepiped, cylindrical and spheres were selected from potatoes (aspect ratio = 1:1, 2:1, 3:1), cut beans (length: diameter = 1:1, 2:1, 3:1) and peas respectively. A batch fluidised bed dryer connected to a heat pump system was used for the experimentation. A Heat pump and fluid bed combination was used to increase overall energy efficiency and achieve higher drying rates. Drying kinetics, were evaluated with non-dimensional moisture at three different drying temperatures of 30, 40 and 50o C. Due to complex hydrodynamics of the fluidised beds, drying kinetics are dryer or material specific. Numerous mathematical models can be used to calculate drying kinetics ranging from analytical models with simplified assumptions to empirical models built by regression using experimental data. Empirical models are commonly used for various food materials due to their simpler approach. However problems in accuracy, limits the applications of empirical models. Some limitations of empirical models could be reduced by using semi-empirical models based on heat and mass transfer of the drying operation. One such method is the quasi-stationary approach. In this study, a modified quasi-stationary approach was used to model drying kinetics of the cylindrical food particles at three drying temperatures.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

The effects of pore architecture in silk fibroin scaffolds on the growth and differentiation of mesenchymal stem cells expressing BMP7

The pore architecture of scaffolds is known to play a critical role in tissue engineering as it provides the vital framework for seeded cells to organize into a functioning tissue. In this report we have investigated the effects of different concentrations of silk fibroin protein on three-dimensional (3D) scaffold pore microstructure. Four pore size ranges of silk fibroin scaffolds were made by the freeze drying technique, with the pore sizes ranging from 50 to 300 lm. The pore sizes of the scaffolds decreased as the concentration of fibroin protein increased. Human bone marrow mesenchymal stromal cells (BMSC) transfected with the BMP7 gene were cultured in these scaffolds. A cell viability colorimetric assay, alkaline phosphatase assay and reverse transcription-polymerase chain reaction were performed to analyze the effect of pore size on cell growth, the secretion of extracellular matrix (ECM) and osteogenic differentiation. Cell migration in 3D scaffolds was confirmed by confocal microscopy. Calvarial defects in SCID mice were used to determine the bone forming ability of the silk fibroin scaffolds incorporating BMSC expressing BMP7. The results showed that BMSC expressing BMP7 preferred a pore size between 100 and 300 lm in silk fibroin protein fabricated scaffolds, with better cell proliferation and ECM production. Furthermore, in vivo transplantation of the silk fibroin scaffolds combined with BMSC expressing BMP7 induced new bone formation. This study has shown that an optimized pore architecture of silk fibroin scaffolds can modulate the bioactivity of BMP7-transfected BMSC in bone formation.

Heavy vehicle suspensions : testing and analysis

Transport regulators consider that, with respect to pavement damage, heavy vehicles (HVs) are the riskiest vehicles on the road network. That HV suspension design contributes to road and bridge damage has been recognised for some decades. This thesis deals with some aspects of HV suspension characteristics, particularly (but not exclusively) air suspensions. This is in the areas of developing low-cost in-service heavy vehicle (HV) suspension testing, the effects of larger-than-industry-standard longitudinal air lines and the characteristics of on-board mass (OBM) systems for HVs. All these areas, whilst seemingly disparate, seek to inform the management of HVs, reduce of their impact on the network asset and/or provide a measurement mechanism for worn HV suspensions. A number of project management groups at the State and National level in Australia have been, and will be, presented with the results of the project that resulted in this thesis. This should serve to inform their activities applicable to this research. A number of HVs were tested for various characteristics. These tests were used to form a number of conclusions about HV suspension behaviours. Wheel forces from road test data were analysed. A “novel roughness” measure was developed and applied to the road test data to determine dynamic load sharing, amongst other research outcomes. Further, it was proposed that this approach could inform future development of pavement models incorporating roughness and peak wheel forces. Left/right variations in wheel forces and wheel force variations for different speeds were also presented. This led on to some conclusions regarding suspension and wheel force frequencies, their transmission to the pavement and repetitive wheel loads in the spatial domain. An improved method of determining dynamic load sharing was developed and presented. It used the correlation coefficient between two elements of a HV to determine dynamic load sharing. This was validated against a mature dynamic loadsharing metric, the dynamic load sharing coefficient (de Pont, 1997). This was the first time that the technique of measuring correlation between elements on a HV has been used for a test case vs. a control case for two different sized air lines. That dynamic load sharing was improved at the air springs was shown for the test case of the large longitudinal air lines. The statistically significant improvement in dynamic load sharing at the air springs from larger longitudinal air lines varied from approximately 30 percent to 80 percent. Dynamic load sharing at the wheels was improved only for low air line flow events for the test case of larger longitudinal air lines. Statistically significant improvements to some suspension metrics across the range of test speeds and “novel roughness” values were evident from the use of larger longitudinal air lines, but these were not uniform. Of note were improvements to suspension metrics involving peak dynamic forces ranging from below the error margin to approximately 24 percent. Abstract models of HV suspensions were developed from the results of some of the tests. Those models were used to propose further development of, and future directions of research into, further gains in HV dynamic load sharing. This was from alterations to currently available damping characteristics combined with implementation of large longitudinal air lines. In-service testing of HV suspensions was found to be possible within a documented range from below the error margin to an error of approximately 16 percent. These results were in comparison with either the manufacturer’s certified data or test results replicating the Australian standard for “road-friendly” HV suspensions, Vehicle Standards Bulletin 11. OBM accuracy testing and development of tamper evidence from OBM data were detailed for over 2000 individual data points across twelve test and control OBM systems from eight suppliers installed on eleven HVs. The results indicated that 95 percent of contemporary OBM systems available in Australia are accurate to +/- 500 kg. The total variation in OBM linearity, after three outliers in the data were removed, was 0.5 percent. A tamper indicator and other OBM metrics that could be used by jurisdictions to determine tamper events were developed and documented. That OBM systems could be used as one vector for in-service testing of HV suspensions was one of a number of synergies between the seemingly disparate streams of this project.

Interactions between energy intake and expenditure in the development and treatment of obesity.

Summary There are four interactions to consider between energy intake (EI) and energy expenditure (EE) in the development and treatment of obesity. (1) Does sedentariness alter levels of EI or subsequent EE? and (2) Do high levels of EI alter physical activity or exercise? (3) Do exercise-induced increases in EE drive EI upwards and undermine dietary approaches to weight management and (4) Do low levels of EI elevate or decrease EE? There is little evidence that sedentariness alters levels of EI. This lack of cross-talk between altered EE and EI appears to promote a positive EB. Lifestyle studies also suggest that a sedentary routine actually offers the opportunity for over-consumption. Substantive changes in non exercise activity thermogenesis are feasible, but not clearly demonstrated. Cross talk between elevated EE and EI is initially too weak and takes too long to activate, to seriously threaten dietary approaches to weight management. It appears that substantial fat loss is possible before intake begins to track a sustained elevation of EE. There is more evidence that low levels of EI does lower physical activity levels, in relatively lean men under conditions of acute or prolonged semi-starvation and in dieting obese subjects. During altered EB there are a number of small but significant changes in the components of EE, including (i) sleeping and basal metabolic rate, (ii) energy cost of weight change alters as weight is gained or lost, (iii) exercise efficiency, (iv) energy cost of weight bearing activities, (v) during substantive overfeeding diet composition (fat versus carbohydrate) will influence the energy cost of nutrient storage by ~ 15%. The responses (i-v) above are all “obligatory” responses. Altered EB can also stimulate facultative behavioural responses, as a consequence of cross-talk between EI and EE. Altered EB will lead to changes in the mode duration and intensity of physical activities. Feeding behaviour can also change. The degree of inter-individual variability in these responses will define the scope within which various mechanisms of EB compensation can operate. The relative importance of “obligatory” versus facultative, behavioural responses -as components of EB control- need to be defined.

On democracy

If one clear argument emerged from my doctoral thesis in political science, it is that there is no agreement as to what democracy is. There are over 40 different varieties of democracy ranging from those in the mainstream with subtle or minute differences to those playing by themselves in the corner. And many of these various types of democracy are very well argued, empirically supported, and highly relevant to certain polities. The irony is that the thing which all of these democratic varieties or the ‘basic democracy’ that all other forms of democracy stem from, is elusive. There is no international agreement in the literature or in political practice as to what ‘basic democracy’ is and that is problematic as many of us use the word ‘democracy’ every day and it is a concept of tremendous importance internationally. I am still uncertain as to why this problem has not been resolved before by far greater minds than my own, and it may have something to do with the recent growth in democratic theory this past decade and the innovative areas of thought my thesis required, but I think I’ve got the answer. By listing each type of democracy and filling the column next to this list with the literature associated with these various styles of democracy, I amassed a large and comprehensive body of textual data. My research intended to find out what these various styles of democracy had in common and to create a taxonomy (like the ‘tree of life’ in biology) of democracy to attempt at showing how various styles of democracy have ‘evolved’ over the past 5000 years.ii I then ran a word frequency analysis program or a piece of software that counts the 100 most commonly used words in the texts. This is where my logic came in as I had to make sense of these words. How did they answer what the most fundamental commonalities are between 40 different styles of democracy? I used a grounded theory analysis which required that I argue my way through these words to form a ‘theory’ or plausible explanation as to why these particular words and not others are the important ones for answering the question. It came down to the argument that all 40 styles of democracy analysed have the following in common 1) A concept of a citizenry. 2) A concept of sovereignty. 3) A concept of equality. 4) A concept of law. 5) A concept of communication. 6) And a concept of selecting officials. Thus, democracy is a defined citizenry with its own concept of sovereignty which it exercises through the institutions which support the citizenry’s understandings of equality, law, communication, and the selection of officials. Once any of these 6 concepts are defined in a particular way it creates a style of democracy. From this, we can also see that there can be more than one style of democracy active in a particular government as a citizenry is composed of many different aggregates with their own understandings of the six concepts.